IMPACT OF GALVANIC CORROSION ON LEAD …...ii ii IMPACT OF GALVANIC CORROSION ON LEAD RELEASE AFTER PARTIAL LEAD SERVICE LINE REPLACEMENT Emily Mi Zhou Master’s of Applied Science,

IMPACT OF GALVANIC CORROSION

ON LEAD RELEASE AFTER

PARTIAL LEAD SERVICE LINE

REPLACEMENT

by

Emily Mi Zhou

A thesis submitted in conformity with the requirements

for the degree of Master of Applied Science

Graduate Department of Civil Engineering

University of Toronto

© Copyright by Emily Mi Zhou 2013

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IMPACT OF GALVANIC CORROSION ON LEAD RELEASE AFTER PARTIAL

LEAD SERVICE LINE REPLACEMENT

Emily Mi Zhou

Master’s of Applied Science, 2013

Graduate Department of Civil Engineering

University of Toronto

ABSTRACT

The EPA Lead and Copper Rule set action limits for lead and copper concentrations in

drinking water, but accelerated corrosion of lead in distribution systems due to a galvanic

connection to copper. Prior research has demonstrated that the effects of galvanic corrosion

can be controlled by water chemistry. This study not only investigated the main effects of

alkalinity, natural organic matter (NOM), nitrate, disinfectant and inhibitor to galvanic

corrosion, but also the interplay between these factors. A 2-level factorial (2v5-1

) design was

adopted which resulted in 16 testing conditions.

Results of bench-scale experiments using static pipes with lead and copper segments

demonstrated that alkalinity, disinfectant, inhibitor and alkalinity-inhibitor interaction had a

significant impact on galvanic current. The significant factors affecting total lead release

were alkalinity, NOM, disinfectant, alkalinity-inhibitor interaction, NOM-nitrate interaction,

NOM-disinfectant interaction, NOM-inhibitor interaction, nitrate-disinfectant interaction

and disinfectant-inhibitor interaction.

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ACKNOWLEDGEMENTS

Above all, I honor God his abundant love and mercy given to me unconditionally and the

continuous guidance and strength he has provided.

I am exceptionally appreciative to Prof. Robert Andrews and Prof. Ron Hofmann, my

supervisors, who were fundamental in my advancement, and was supportive throughout my

studies. Jim Wang was very helpful when dealing with equipment in the lab. Thanks also to

the rest of the Drinking Water Research Group for their help and support.

I give special thanks to my parents for their love and support.

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TABLE OF CONTENTS

ABSTRACT .................................................................................................................................... ii

ACKNOWLEDGEMENTS ........................................................................................................... iii

TABLE OF CONTENTS ............................................................................................................... iv

LIST OF TABLES ........................................................................................................................ vii

LIST OF FIGURES ......................................................................................................................... x

NOMENCLATURE ..................................................................................................................... xvi

1 Introduction ................................................................................................................................. 1

1.1 Background .......................................................................................................................... 1

1.2 Objectives ............................................................................................................................ 3

2 Literature Review ....................................................................................................................... 4

2.1 The Impact of Water Chemistry on Lead Corrosion ........................................................... 4

2.1.1 Chloride to Sulfate Mass Ratio ................................................................................ 4

2.1.2 Orthophosphate ........................................................................................................ 5

2.1.3 Disinfectant .............................................................................................................. 6

2.1.4 Natural Organic Matter ............................................................................................ 8

2.1.5 Nitrate ...................................................................................................................... 9

2.1.6 Sodium Silicate ...................................................................................................... 10

2.2 Aged Lead Pipes ................................................................................................................ 11

2.3 Relationship between Galvanic Current, Galvanic Corrosion and Lead Release ............. 12

3 Experimental Design ................................................................................................................ 14

3.1 Impact of Alkalinity, Nitrate, NOM, Disinfectant, Inhibitor on Lead Release after

Partial Lead Pipe Replacement .......................................................................................... 15

4 Materials and Methods ............................................................................................................. 19

4.1 Test Water Preparation ...................................................................................................... 19

4.1.1 NOM ...................................................................................................................... 19

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4.1.2 Nitrate .................................................................................................................... 20

4.1.3 Inhibitor ................................................................................................................. 20

4.1.4 CSMR .................................................................................................................... 21

4.1.5 Alkalinity ............................................................................................................... 21

4.1.6 pH .......................................................................................................................... 22

4.1.7 Disinfectant ............................................................................................................ 22

4.2 Analysis Methods .............................................................................................................. 23

4.2.1 Total Organic Carbon (TOC) ................................................................................ 23

4.2.2 pH .......................................................................................................................... 25

4.2.3 Chlorine and Monochloramine Residual ............................................................... 26

4.2.4 Oxidation-Reduction Potential .............................................................................. 26

4.2.5 Galvanic Current ................................................................................................... 26

4.2.6 Analysis of Silica, Phosphorus, Nitrate, Sulfate and Chloride .............................. 27

4.2.7 Lead Analysis ........................................................................................................ 27

4.3 Pipe Rig ............................................................................................................................. 28

5 Results ....................................................................................................................................... 30

5.1 Chlorine and Monochloramine Demand Test ................................................................... 30

5.1.1 Chlorine Demand Tests ........................................................................................ 30

5.1.2 Monochloramine Demand Tests ............................................................................ 36

5.1.3 Impact of Alkalinity and Inhibitor on Chlorine Demand ...................................... 41

5.2 Significant Factors Affecting Galvanic Current after Partial Lead Pipe

Replacement ...................................................................................................................... 45

5.2.1 Factors that Affect the Size of Galvanic Current .................................................. 45

5.2.2 Conductivity of Synthetic Water ........................................................................... 47

5.2.3 Significant Factors Affecting Galvanic Current .................................................... 50

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5.3 Water Quality Factors Affecting Total Lead Release after Partial Lead Pipe

Replacement ...................................................................................................................... 58

5.4 Water Quality Factors Affecting Dissolved Lead Release after Partial Lead Pipe

Replacement ...................................................................................................................... 77

5.5 Galvanic Current and Lead Release Relationship ............................................................. 87

5.6 Conclusions ....................................................................................................................... 91

6 Reference List ........................................................................................................................... 93

7 Appendices ............................................................................................................................. 100

7.1 Sample Calculations ........................................................................................................ 100

7.1.1 Chlorine Dose Required to Give a Specific Residual Concentration at the

Desired Time ....................................................................................................... 100

7.2 Experimental Procedures ................................................................................................. 101

7.2.1 Chlorine/monochloramine Demand Test............................................................. 101

7.2.2 pH Control by the Addition of Carbon Dioxide .................................................. 105

7.2.3 Measure Concentrations of Silica, Phosphorus, Nitrate, Sulfate and

Chloride ............................................................................................................... 107

7.3 Raw Data ......................................................................................................................... 117

7.3.1 Chlorine/monochloramine Demand Test............................................................. 117

7.3.2 Galvanic Current Data ......................................................................................... 124

7.3.3 Total Lead Data ................................................................................................... 125

7.3.4 Dissolved Lead Data ............................................................................................ 127

7.3.5 Test Water Parameters ......................................................................................... 128

7.3.6 Inhibitor Residual and Disinfectant Residual in the Weekly Composite

Water ................................................................................................................... 130

7.4 Preliminary Results ......................................................................................................... 133

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LIST OF TABLES

Table 1-1: Standard electromotive force potentials (reduction potentials) .............................. 2

Table 3-1: Quantities of water condition factors tested in past studies .................................. 15

Table 3-2: 2v5-1

factorial design for water chemistry factors .................................................. 17

Table 4-1: Filtered stock solution preparation outline............................................................ 20

Table 4-2: Total organic carbon reagents ............................................................................... 25

Table 4-3: Total organic carbon instrument conditions ......................................................... 25

Table 4-4: Total organic carbon method outline .................................................................... 25

Table 5-1: Test conditions for the chlorine demand test ........................................................ 30

Table 5-2: Values of parameters k, a, e and f as calculated for Equation 5-3 and 5-4, for

various initial chlorine concentrations in the time interval 4 hr to 11 days............................ 35

Table 5-3: Test conditions for the monochloramine demand test .......................................... 36

Table 5-4: Values of parameters k, a, e and f as calculated for Equations 5-3 and 5-4 for

various initial monochloramine concentrations in the time interval 4 hours to 11 days ........ 40

Table 5-5: Test conditions to examine the influence of alkalinity and inhibitor .................... 41

Table 5-6: The average, standard deviation and variance values for chlorine residual on the

9th

day ..................................................................................................................................... 43

Table 5-7: T-test results .......................................................................................................... 44

Table 5-8: Conductivity approximation based on the major ion species in the water

(equivalent conductivity of ion (λi), data from (Harned and Owen, 1964)) ........................... 48

Table 5-9: Analysis of variance table of total lead ................................................................. 61

Table 5-10: Analysis of variance table of dissolved lead ....................................................... 77

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Table 5-11: Summary table of significant factors .................................................................. 91

Table 5-13: Performance comparison of corrosion inhibitor ................................................. 92

Table 7-1: The amount of salt needed for preparing working solutions containing different

ions ....................................................................................................................................... 102

Table 7-2: The volume of working solution needed to prepare 2 L of test water ................ 103

Table 7-3: Free chlorine residual (mg/L Cl2) measured over 11 days.................................. 117

Table 7-4: pH of chlorine demand test measured over 11 days ........................................... 120

Table 7-5: Monochloramine residual (mg/L Cl2) measured over 11 days ........................... 121

Table 7-6: pH of monochloramine demand test measured over 11 days ............................. 123

Table 7-7: Galvanic current data .......................................................................................... 124

Table 7-8: Measured total lead release in the weekly composite water ............................... 125

Table 7-9: Calculated maximum lead release using Equation 2-5 ....................................... 126

Table 7-10: Measured dissolved lead release in the weekly composite water ..................... 127

Table 7-11: Electric conductivity of test water .................................................................... 128

Table 7-12: OPR of test water .............................................................................................. 129

Table 7-13: Orthophosphate residual in the weekly composite water .................................. 130

Table 7-14: Silicate residual in the weekly composite water ............................................... 131

Table 7-15: Disinfectant residual in the weekly composite water ........................................ 132

Table 7-16: The test concentrations of the test waters ......................................................... 133

Table 7-17: The actual concentrations of the test waters ..................................................... 134

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Table 7-18: Total lead concentrations (µg/L) measured by ICP-MS ................................... 135

Table 7-19: Weekly composite waters ................................................................................. 149

Table 7-20: pH and OPR ...................................................................................................... 150

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LIST OF FIGURES

Figure 1-1: Corrosion of (a) pure lead pipe (b) galvanically connected copper and lead ........ 2

Figure 4-1: Example total organic carbon calibration curve .................................................. 24

Figure 4-2: Total organic carbon quality control chart (3.0 mg/L) (July to December, 2012)

................................................................................................................................................ 24

Figure 4-3: Photo of a pipe rig set-up. .................................................................................... 28

Figure 4-4: The lead portion and copper portion are separated by an insulating spacer and

connected by an external wire ................................................................................................ 29

Figure 5-1: Free chlorine residual versus time (time = 0 to 11 day) for water samples dosed

with DOC at 0 mg/L, chlorine at 3.5 mg/L Cl2. Note: the error bars represent one standard

deviation of n=2. Some error bars were too small to see. ...................................................... 31

Figure 5-2: Free chlorine residual versus time (time = 0 to 11 day) for waters with different

levels of DOC and chlorine. Note: the error bars represent one standard deviation n =2.

Some error bars were too small to see .................................................................................... 32

Figure 5-3: Log-chlorine residual concentration versus time plots (time = 4 hr to 11 day) ... 33

Figure 5-4: Initial free chlorine concentration versus free chlorine residual concentration on

the 9th

day ............................................................................................................................... 35

Figure 5-5: Monochloramine versus time (time = 0 to 11 day) for water samples dosed with

DOC at 0 mg/L, monochloramine at 6 mg/L Cl2. Note: the error bars represent one standard


Figure 5-6: Monochloramine residual versus time (time = 0 to 11 day) for waters with

different levels of DOC and monochloramine. Note: the error bars represent one standard


Figure 5-7: Log-monochloramine residual concentration versus time (time = 4 hr to 11 day)

................................................................................................................................................ 39

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Figure 5-8: Initial monochloramine concentration versus monochloramine residual

concentration on the 9th

day .................................................................................................... 40

Figure 5-9: Chlorine free residual concentration versus time (0 to 11 days) for waters with

different levels of alkalinity and inhibitors. DOC = 1 mg/L, chlorine = 3.5 mg/L. Note: the

error bars represent one standard deviation of n=2. Some error bars were too small to see .. 42

Figure 5-10: Half-normal plot of measured electric conductivity of synthetic waters ........... 49

Figure 5-11: Temporal trend of average galvanic current. Note: the error bars represent one

standard deviation of n= 5. ALK= alkalinity (mg/L CaCO3), DOC= dissolved organic

carbon (mg/L), N= nitrate (mg/L N), OP = orthophosphate (mg/L P), Si = silicate (mg/L

SiO2), C= Chlorine residual (mg/L Cl2), MC = monochloramine residual (mg/L Cl2) .......... 50

Figure 5-13: Predicted and actual galvanic current (µA). The predicted values were

calculated using ANONA model. ........................................................................................... 52

Figure 5-14: The impact of alkalinity on galvanic current. Note: the error bar represents

95% confidence interval. ........................................................................................................ 54

Figure 5-15: The impact of disinfectant on galvanic current. Note: the error bar represents

95% confidence interval ......................................................................................................... 55

Figure 5-16: The impact of inhibitor on galvanic current. Note: the error bar represents 95%

confidence interval ................................................................................................................. 56

Figure 5-17: The impact of alkalinity and inhibitor interaction to galvanic current. Note: the

error bar represents 95% confidence interval ......................................................................... 57

Figure 5-18: Temporal trend of total lead release Note: ALK= alkalinity (mg/L CaCO3),

DOC= dissolved organic carbon (mg/L), N= nitrate (mg/L N), OP = orthophosphate (mg/L

P), C= chlorine residual (mg/L), Si = silicate (mg/L), MC = monochloramine residual

(mg/L) ..................................................................................................................................... 59

Figure 5-19: Half-normal plot of total lead ............................................................................ 60

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Figure 5-20: Predicted and actual total lead release ............................................................... 62

Figure 5-21: The impact of alkalinity on total lead release. Note: the error bar represents


Figure 5-22: The impact of interaction of alkalinity and inhibitor on total lead release. Note:

the error bar represents 95% confidence interval ................................................................... 65

Figure 5-23: The impact of SNOM on total lead release. Note: the error bar represents 95%

confidence interval ................................................................................................................. 67

Figure 5-24: The impact of interaction of SNOM and nitrate on total lead release. Note: the

error bar represents 95% confidence interval ......................................................................... 68

Figure 5-25: The impact of interaction of SNOM and disinfectant on total lead release.

Note: the error bars represent 95% confidence interval ......................................................... 69

Figure 5-26: The impact of interaction of SNOM and inhibitor on total lead release. Note:

the error bars represent 95% confidence interval ................................................................... 70

Figure 5-27: Conceptual scheme of reactions involving Pb(II) and Pb(IV) species in the

presence of free chlorine (adjusted from Boyd et al., 2010) .................................................. 71

Figure 5-28: The impact of disinfectant on total lead release. Note: the error bar represents


Figure 5-29: ORP comparisons between free chlorine and monochloramine ........................ 74

Figure 5-30: The impact of interaction of nitrate and disinfectant on total lead release. Note:

the error bars represent 95% confidence interval ................................................................... 75

Figure 5-31: The impact of interaction of disinfectant and inhibitor on total lead release.

Note: the error bar represents 95% confidence interval ......................................................... 76

Figure 5-32: Temporal trend of dissolved lead release. Note: ALK= alkalinity (mg/L

CaCO3), DOC= dissolved organic carbon (mg/L), N= nitrate (mg/L N), OP =

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orthophosphate (mg/L P), C= chlorine residual (mg/L), Si= silicate (mg/L), MC=

monochloramine residual (mg/L) ........................................................................................... 78

Figure 5-33: Half-normal plot of dissolved lead .................................................................... 79

Figure 5-34: Predicted and actual values of dissolved lead release ....................................... 80

Figure 5-35: The impact of alkalinity on dissolved lead release. Note: the error bar

represents 95% confidence interval ........................................................................................ 81

Figure 5-36: Eh-pH diagram for the Pb-CO3-H2O system at 25° C and 1 atm (adjusted from

Scheetz, 2004) ........................................................................................................................ 82

Figure 5-37: The impact of nitrate on dissolved lead release. Note: the error bar represents


Figure 5-38: The impact of interaction between alkalinity and nitrate on dissolved lead

release. Note: the error bar represents 95% confidence interval ............................................ 83

Figure 5-39: The impact of inhibitor on dissolved lead release. Note: the error bar represents


Figure 5-40: The impact of interaction between alkalinity and inhibitor on dissolved lead

release. Note: the error bar represents 95% confidence interval ............................................ 85

Figure 5-41 : The impact of SNOM on dissolved lead release. Note: the error bars represent


Figure 5-42: Correlation of galvanic current to total lead release during Week 4 to Week 12

................................................................................................................................................ 87

Figure 5-43: Demonstrating galvanic relationship between predicted (calculated using

current values) vs. actual total lead leaching .......................................................................... 88

Figure 5-44: Comparison of total lead release from galvanically connected pipe rigs and

galvancially disconnected pipe rigs. Note: The galvanically connected lead release values

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were average total lead release from Week 4 to Week 12. The error bar represents one

standard deviation of n=8. The galvanically disconnected lead release values were total lead

release in Week 10. ................................................................................................................. 89

Figure 5-45: Comparison of dissolved lead release from galvanically connected pipe rigs and

galvancially disconnected pipe rigs. Note: The galvanically connected lead release values

were the average of dissolved lead release of Week 6, 9 and 12. The error bar represents one

standard deviation of n=3. The galvanically disconnected lead release values were dissolved

lead release in Week 10. ......................................................................................................... 90

Figure 7-1: Total lead release of test condition 1: alkalinity at 15 mg/L CaCO3, DOC at 7

mg/L, nitrate at 1 mg/L N, inhibitor at 1 mg/L P and disinfectant at 1 mg/L free chlorine

(error bars denote 95% confidence intervals) ....................................................................... 136


mg/L, nitrate at 1 mg/L N, inhibitor at 24 mg/L SiO2 and disinfectant at 3 mg/L

monochloramine (error bars denote 95% confidence intervals) ........................................... 137


mg/L, nitrate at 7 mg/L N, inhibitor at 24 mg/L SiO2 and disinfectant at 1 mg/L free chlorine

(error bars denote 95% confidence intervals) ....................................................................... 138


mg/L, nitrate at 7 mg/L N, inhibitor at 24 mg/L SiO2 and disinfectant at 3 mg/L


Figure 7-5: Total lead release of test condition 5: alkalinity at 250mg/L CaCO3, DOC at 7

mg/L, nitrate at 1 mg/L N, inhibitor at 1 mg/L P and disinfectant at 3 mg/L



mg/L, nitrate at 7 mg/L N, inhibitor at 1 mg/L P and disinfectant at chlorine at 1 mg/L (error

bars denote 95% confidence intervals) ................................................................................. 141

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Figure 7-7: Lead release comparison between high and low alkalinity (the data was the lead

release from week 3; error bars denote 95% confidence intervals) ...................................... 142

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NOMENCLATURE

ANOVA Analysis of variance

CSMR Chloride to sulfate mass ratio

DBPs Disinfection byproducts

DOC Dissolved organic carbon

IHSS International Humic Substances Society

LCR Lead and copper rule

MCL Maximum contaminant level

NOM Natural organic matter

ORP Oxidation reduction potential

PACl Polyaluminum chloride

PVC Polyvinyl chloride

PLSLR Partial lead service line replacement

SHE Standard hydrogen electrode

SNOM Suwannee river natural organic matter

TOC Total organic carbon

http://www.humicsubstances.org/

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1 Introduction

1.1 Background

Lead is rarely found in source water, but the leaching of lead to potable water from lead

pipes due to corrosion has often caused the concentration of lead to exceed the American

Lead and Copper Rule (LCR) lead action limit of 15 μg/L (U.S. Environmental Protection

Agency, 1991). Researchers have found that lead affects multiple systems in the human

body including the central and peripheral nervous systems, the gastrointestinal tract, the

kidneys and the haematological system (Hayes et al, 1997). Lead is a cumulative toxin and

there is no threshold below which lead remains without producing physiological damages

(Finkelstein et al., 1998). Therefore, reducing the lead level in potable water is of paramount

importance. Lead service lines were the standard in many U.S. cities in the 1950’s, and

many lead pipelines still exist today (Sandvig et al., 2009). An historical survey has

reported that a typical service line is about 18.3-20.4 m (60-68 ft) with 7.6 m ( ≈40%) being

under the utility’s jurisdiction (Sandvig et al., 2009), and that the length varies depending on

the service location. Replacement with copper is a common practice to reduce lead leaching.

However, replacing a single lead service line can cost from $1,000 to more than $3,000

which makes it very hard for home owners to pay to replace their portion of the lead service

line (AWWA, 2005). The practice of replacing the utility owned portion of lead pipe is

referred to as partial lead service line replacement (PLSLR). Recent studies (Brown et al.,

2011; Frumkin, 2010) have suggested this partial lead service line replacement might be

linked with the increased chance of high blood lead levels (≥10µg/dL) in children. The

increased lead leaching to water could be due to multiple reasons. Lead scale disturbance as

the short-term issue and galvanic corrosion between the old lead pipe and the new copper

pipe as the long-term issue are causes for the increase in lead concentration after PLSLR

(Boyd et al., 2004).

Before the partial replacement, the corrosion is uniform throughout the entire lead pipes

surface. According to Dudi (2004), lead oxidation (anodic) and oxygen reduction (cathodic)

are very close on the lead surface (Figure 1-1: Corrosion of (a) pure lead pipe (b)

galvanically connected copper and lead).

http://journals1.scholarsportal.info.myaccess.library.utoronto.ca/search-advanced.xqy?q=Yoram%20Finkelstein&field=AU

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Anodic Reaction: Pb(s) → Pb+2

(aq) + 2e- 1-1

Cathodic Reaction: O2 + 4e- + 2H2O → 4OH

- 1-2

Figure 1-1: Corrosion of (a) pure lead pipe (b) galvanically connected copper and lead

The production of Pb+2

, a Lewis acid, causes a local pH drop. The basic (OH-) and acidic

species produced through the reactions can neutralize each other in which the pH remains

the same or increase a little on the lead surface (Dudi, 2004). Corrosion of pure lead is

known as dissolution. After copper is connected with lead, due to the potential difference

(Table 1-1) between lead and copper, lead becomes the sacrificial anode and copper is the

protected cathode (Dudi, 2004).

Table 1-1: Standard electromotive force potentials (reduction potentials)

Reaction Standard Potential (Volts vs. SHE)

Cu2+

+2e- = Cu 0.342

Pb2+

+ 2e- = Pb -0.126

Note: SHE is standard hydrogen electrode

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Since the anodic and cathodic reactions are separated with cathodic reactions on the copper

surface (Figure 1-1(b)), pH decreases at the lead surface which further induces lead

corrosion. The combined effect of higher corrosion rate due to galvanic connection and the

production of acidity on the lead surface make lead leaching much worse compared to lead

dissolution alone. Past studies (Dudi, 2004; Edwards and Dudi, 2004; Edwards and

Triantafyllidou, 2007; Triantafyllidou et al., 2010; Nguyen et al., 2010; Arnold, 2011;

Nguyen et al., 2011a; Nguyen et al., 2011b; Clark et al., 2011) have shown lead release due

to galvanic corrosion is highly depended on several factors including the water chemistry,

water flow patterns and age of the pipelines.

1.2 Objectives

The overall objective of the thesis was to examine the effect of galvanic action on lead pipes

after PLSLR to reduce lead release. This thesis was conducted in the following areas:

1. Lead leaching was examined as a function of water chemistry. Water chemistry

strongly influences the scale formation at the lead surface which determines the

solubility of lead. Section 2.1 discusses how water chemistry affects lead leaching

level.

2. The relationship between galvanic current and actual lead release was investigated

experimentally. Galvanic current is a measure of galvanic corrosion only, and does

not take account of lead dissolution or any other forms of corrosion. Therefore

understanding of this subject can help to know whether galvanic corrosion is the

dominant mechanism of lead release after partial lead service line replacement.

Section 0 discusses the relationships in more detail.

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2 Literature Review

2.1 The Impact of Water Chemistry on Lead Corrosion

2.1.1 Chloride to Sulfate Mass Ratio

Historically, both chloride and sulfate are known to protect lead bearing material. When lead

is galvanically connected to copper, chloride tends to attack lead (Oliphant, 1983). Gregory

(1985) further studied the phenomena by defining a concept called chloride to sulfate mass

ratio (CSMR) and demonstrated the important role of CSMR to galvanic corrosion of lead.

CSMR =][

][2

4

SO

Cl 2-1

Since the CSMR is the ratio of chloride and sulfate, when the mass of chloride is greater to

the mass of sulfate, CSMR would be greater than 0.5 and Gregory (1985) has suggested that

it would promote galvanic corrosion, whereas low CSMR (< 0.5) which represents less mass

of chloride to sulfate would suppress galvanic corrosion. A utility survey study conducted

by Dodrill and Edwards (1995) showed a CSMR of 0.58 as the boundary. Twelve utilities in

the survey met the lead action limit of 15 μg/L when keeping the CSMR below 0.58.

However, as the CSMR went beyond 0.58, seven utilities exceeded the lead action limit

(Dodrill and Edwards, 1995). It has also been demonstrated that as the CSMR increased,

lead leaching also increased (Dudi, 2004). In an experiment, two types of water referred to

as “normal chloride” and “higher chloride” were prepared (Dudi, 2004). The CSMR for the

normal and the higher chloride water were around 0.9 and 22 and lead leaching for yellow

brass device were 10 μg/L and 50 μg/L lead respectively, demonstrating that lead leaching

was promoted by the higher CSMR. The same tendency was observed on lead leaching

under a series of pipe rig experiments simulating PLSLR (Triantafyllidou et al., 2010).

Water with CSMR values of 0.2 and 16.2 were used in the experiments and the results

showed that the lead concentration in the high CSMR water was about 3 to 11 times greater

than in the low CSMR water (Triantafyllidou et al., 2010).

The impact of CSMR on the lead leaching can help to explain sudden lead level fluctuations

after changes to a seemingly innocuous treatment step such as a switch in coagulant type.

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Investigations on the corrosion of lead solder galvanically connected with copper pipe with

either polyaluminum chloride (PACl) or alum coagulation treatment have shown substantial

differences in terms of lead release (Edwards and Triantafyllidou, 2007). The lead leaching

in the PACl water was 1.5 to 3 times greater than observed for alum water with no inhibitor

(Edwards and Triantafyllidou, 2007). This was because CSMR increased after the addition

of PACl since it contains chloride, and decreased with the addition of alum.

The solubility of lead was studied to provide some mechanistic insight into the CSMR

effects on lead leaching. Chloride (0 to 8 mM Cl-) and sulfate (0 to 2.66 mM SO4

2-) were

added to water separately to examine individual effects (Clark, 2008). The concentration of

soluble lead decreased with the addition of sulfate, whereas soluble lead increased with the

addition of chloride (Clark, 2008). Higher chloride concentration increased lead solubility

by the formation of PbCln(2-n)

complexes and sulfate contributed to the formation of

PbSO4(s) which is insoluble even at pH of 3 (Clark, 2008). Hence, CSMR can be viewed as

the relative amount of soluble lead to insoluble lead. The impact of CSMR on galvanic

corrosion of lead has been thoroughly studied (Triantafyllidou et al., 2010; Nguyen et al.,

2011a).

2.1.2 Orthophosphate

Phosphate has long been known for its role in preventing scale buildup in water distribution

systems. In a utility survey conducted by Dodrill and Edwards (1995), the majority of

utilities reported phosphate-based inhibitors did not only prevent iron corrosion, but were

also beneficial for lead corrosion control. The addition of phosphate increases alkalinity

which can buffer pH drops from galvanic corrosion at the lead surface. However, not all

phosphate-based inhibitors have a positive effect on lead corrosion. Orthophosphate tends to

decrease the solubility of lead by forming an insoluble layer on the surface, whereas

polyphosphate is expected to increase lead solubility which causes higher lead leaching

(Edwards and McNeill, 2002). These same researchers demonstrated that orthophosphate

can reduce soluble lead leaching by up to 70% when compared to no inhibitor. In most

cases, lead forms several phosphate solids such as hydroxypyromorphite [Pb5(PO4)3OH] and

tertiary lead orthophosphate [Pb3(PO4)2] which are less soluble than lead carbonate, PbCO3

(Schock, 1989).

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The degree to which orthophosphate can help to suppress lead corrosion depends on water

chemistry. pH and alkalinity can influence the formation of different species which

dominate lead solubility. The addition of orthophosphate as a corrosion inhibitor has

optimum performance at pH 7.5 or higher (Schock, 1989; Tam and Elefsiniotis, 2009).

Another study tested galvanically connected lead and copper pipelines in both low (12 mg/L

CaCO3) and high (250 mg/L CaCO3) alkalinity (Arnold, 2011). The results showed that

higher alkalinity was less corrosive (Arnold, 2011). In high alkalinity water orthophosphate

(0 to 2 mg/L P) reduced lead release from 2500 μg/L to 1000 μg/L, whereas in low alkalinity

water it significantly increased lead release from 6000 μg/L to 17000 μg/L (Arnold, 2011).

In another study by Nguyen et al. (2011b), the adverse effects of orthophosphate increased

when the concentration of sulfate was less than 10mg/L.

Orthophosphate can bring both positive and negative influence to lead release, when and

how it can mitigate or exacerbate galvanic corrosion and lead release still needs more

fundamental research, especially on its interplay with alkalinity and pH.

2.1.3 Disinfectant

Free chlorine is a common disinfectant. However, as utilities face more stringent regulations

on the safety of drinking water, some have adopted chloramines as a secondary disinfectant

in the distribution system to reduce the formation of disinfection byproducts (DBPs) and

increase the stability of the residual in the distribution systems (Farren, 2003). The use of

chloramines may promote lead leaching. In 2001, the lead level in Washington D.C. water

started to exceed the 15 μg/L action limit when chlorine was switched to chloarmines, but

due to improper sampling and monitoring techniques, it was not confirmed until 2004

(Edwards and Dudi, 2004). During the three years (2001 to 2004) the likelihood for the

children under 1.3 years old to have elevated blood lead (blood lead ≥10 μg/dL) were found

to be 4 times higher compared to the year 2000 when lead levels were below the action limit

(Edwards et al., 2009).

There is a long history of research on the impact of disinfectants on lead corrosion and

release. Early studies demonstrated that chloramines can attack brass and cause lead

leaching under certain circumstances (Larson et al., 1956). In a more recent study, copper

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coils with 50/50 pb-Sn solder were examined in both chlorinated and chloraminated water

over 18 months (Portland Bureau of Water Works, 1983). Samples exposed to chlorinated

water leached an average of 10 μg/L lead, whereas samples exposed to chloraminated water

leached an average of 100 μg/L lead under pH at 6-9 (Portland Bureau of Water Works,

1983). In another study, lead, copper/lead-solder, and brass coupon tests were conducted

with both free chlorine and chloramines. For both pure lead and copper/lead-solder coupons

the lead leaching was higher with free chlorine (Lin et al., 1997). Conversely, for brass

coupons, lead leaching with chloramines was two to five times more than free chlorine (Lin

et al., 1997). It can be seen that the effect of chloramines on leaching from pure lead pipe do

not appear to be significant with respect to free chlorine. However, it can impact strongly

when lead (especially in brass) is galvanically connected with copper.

Numerous researchers have attempted to explain the mechanism behind the effect of

disinfectant on lead leaching. Conventional understanding assumes Pb+2

complexes such as

cerussite [PbCO3] and hydrocerussite [Pb (CO3)2(OH) 2] were the dominating species for the

passive layer (Schock, 1989). Researchers started to discover discrepancies between the

conventional model and lead solubility data (Schock and Gardels, 1983). The discrepancy

was first believed to be experimental and theoretical errors, and later proved to be the

presence of Pb+4

species that formed in a highly oxidizing water (Boyd et al., 2008).

The oxidation reduction potential (ORP) of water can be greatly controlled by the change of

disinfectant (Rajasekharan et al., 2007; Switzer et al., 2006). The theoretical redox potential

for the transformation from Pb+2

to Pb+4

is very high. In a drinking water system, free

chlorine and chlorine dioxide are the only candidates to achieve the transformation (Ltyle

and Schock, 2005). Once the transformation requirement is met, plattnerite (β-PbO2) and

scrutinyite (α-PbO2) can be formed as the protective film for the lead bulk (Boyd et al.,

2006). The solubility of Pb+4

complexes are much lower compared to Pb

+2 complexes (Boyd

et al., 2006). Thus, as disinfectant changes from free chlorine to chloramine, there is more

lead in the Pb+2

state which is relatively easier to leach out. This explains the high lead

levels reported in Washington D.C. upon disinfectant change. Since many utilities are

switching to chloramines as their secondary disinfectant, further investigation is needed on

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the impact of chloramines on lead leaching, as well as on how switching disinfectants can

influence lead leaching under galvanic corrosion.

2.1.4 Natural Organic Matter

The composition and properties of NOM are site-specific, but the predominant part of NOM

is humic substances. Prior studies have demonstrated that higher NOM concentrations can

result in increases in lead concentration (Korshin et al., 1999; Korshin et al., 2000). It has

been shown by Korshin et al. (2000) that NOM increased both short-term and long-term lead

leaching. Brass was exposed to water over 12 months with a range of NOM concentration (0

to 10 DOC, mg/L). The lead concentration in water increased with NOM concentration, the

concentration increased very rapidly in the range of 0 to 2 mg/L DOC, beyond 2 mg/L DOC

lead concentration increased slowly and eventually reached a plateau (Korshin et al., 2000).

The lead concentrations also depended on time. Lead reached to 350 μg/L during the first

week with 10 mg/L DOC (Korshin et al., 2000). As time passed, the rate of lead leaching

decreased slowly. After 1 year, only 200 μg/L lead was released at 10 mg/L DOC (Korshin

et al., 2000).

With the absence of NOM, perfect crystals of hydrocerussite [Pb (CO3)2(OH) 2] are usually

formed on the lead surface. However, scanning electron microscope imaging has provided

evidence that an amorphous hydrated surface layer was formed on the surface of lead after

NOM was added to the water (Korshin et al., 2000). It was believed that this new layer

experienced a higher rate of oxidation on the lead surface which resulted in higher lead

release (Korshin et al., 2000). It has been reaffirmed that NOM prevented the formation of

hydrocerussite by Korshin et al. (2005) and the same researchers discovered that the

formation can be less hindered when NOM was altered by chlorination or ozonation. This

was reported based on the observation that zeta-potential which is a measure of the surface

activity was the highest for unaltered NOM, while ozonation and chlorination decreased it

(Korshin et al., 2005).

Some studies were focused on the mixed impact of NOM and disinfectant to lead leaching.

As mentioned above, PbO2 can only be formed upon the addition of strong oxidizing agent

such as free chlorine. NOM, on the other hand, as a common reducing agent, can cause the

http://en.wikipedia.org/wiki/Scanning_electron_microscope

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9

reductive dissolution of PbO2 which can enhance lead leaching (Lin and Valentine, 2009).

The adverse role of NOM in both the DBP formation and the lead release suggests that the

removal of NOM in the water treatment plant is of paramount importance.

The interplay between NOM and other water chemistry parameters was also reported. In one

study, lead release was measured upon addition of NOM (0, 1 and 4 mg/L TOC) with

different configurations of plumbing material (Arnold, 2011). When lead pipe was attached

to copper pipe, no clear trend was observed between NOM and lead release (Arnold, 2011).

When lead solder was attached to copper pipe, it was observed that NOM can influence the

impact of orthophosphate addition. Without the addition of NOM, the lead concentration

was 6800 μg/L with the addition of orthophosphate (2mg/L p) (Arnold, 2011). With 1 mg/L

TOC, the lead concentration decreased to 2200 μg/L with the same level of orthophosphate

(Arnold, 2011). Nyugen et al. (2011 b) also had similar observations on this combined effect

of NOM and orthophosphate which was contradicting what Hayes et al. (2010) reported.

Hayes et al. (2010) reported that orthophosphate dosing was needed for lead release caused

by NOM. As can be seen, when different water parameters are simultaneously present in

water, their combined effect on lead release is very complex and more research is needed

2.1.5 Nitrate

Nitrate (NO3-) is often found in drinking water due to fertilizer run-off and industrial

contamination (Nguyen et al., 2011). The maximum contaminant level (MCL) set by the U.S

Environmental Protection Agency for nitrate is 10 mg/L NO3-N (U.S Environmental

Protection Agency, 1985). In recent years, as more utilities start using chloramines as the

disinfectant, the concentration of nitrate may be increased since chloramines decay to form

ammonia which can be converted to nitrate (refer to Equation 2-2) (Dudi, 2004). Hence, it is

worthwhile to review the effect of nitrogen-containing compounds on lead corrosion. A

study reported by Uchida and Okuwakin (1999) has shown that nitrate can attack lead-

bearing material by destroying its passive layer and causing pitting on the surface. Nitrate’s

reaction with lead can form nitrite and with further reaction with lead may form ammonia

(refer to Equation 2-3 & 2-4) (Uchida and Okuwakin, 1999). Uchida and Okuwaki (1999)

also found that ammonia can disturb the passive layer formation of lead with the aid of

scanning electron microscope imaging. Therefore, in the presence of nitrate, corrosion of

http://en.wikipedia.org/wiki/Scanning_electron_microscope

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lead becomes more vigorous. However, the nitrate concentrations used in the study were 10

times higher than the levels that would be found in drinking waters (Uchida and Okuwakin,

1999).

NH3Cl→ N2 + NH3+ 3Cl- + 3H

+ (Nguyen et al., 2011) 2-2

NO3- + Pb → NO2

- + PbO (Dudi, 2004) 2-3

NO2- + 3Pb + 2H2O → NH3 + 3PbO + OH

(Dudi, 2004) 2-4

More recent studies have demonstrated the impact of nitrate at concentrations found in

drinking water. Dudi (2004) conducted experiments both with and without 10 mg/L NO3-N

on various brass samples. Seven out of eight brass samples with nitrate all showed an

increase in lead concentration (Dudi, 2004). The increase of lead leaching was varied which

confirmed lead leaching from brass devices can be a complex function of the brass type.

Another study was performed on galvanic lead solder using a copper coupon with nitrate

concentrations from 0 to 10 mg/L NO3-N for nine weeks (Nguyen et al., 2011). The lowest

lead leaching was 18 µg/L with 0 mg/L NO3-N, and the highest lead leaching was 4000

µg/L with 10 mg/L NO3-N (Nguyen et al., 2011). For low nitrate concentrations (0 to 1

mg/L NO3-N), lead leaching increased with nitrate concentration but decreased with

exposure time. However, for high nitrate concentrations (2.5 to 10 mg/L NO3-N), lead

leaching increased with both nitrate concentration and exposure time. It can be seen that

nitrate can exert a strong influence on lead leaching and past studies only focused on lead

solder and brass material. Hence, it is necessary to conduct research on the impact of nitrate

after PLSLR.

2.1.6 Sodium Silicate

Sodium silicate (Na2SiO3) is often used as a chemical sequester for iron and manganese

control in drinking water (Robinson et al., 1992). Stericker (1945) suggested that sodium

silicate could also be beneficial for lead and copper control because a silicate coating may

act as a protective diffusion barrier. In addition, sodium silicate can elevate pH since it is

basic which reduce lead and copper solubility (Schock et al., 2005). The exact mechanism of

corrosion inhibition of sodium silicate still remains uncertain. It was documented that 25-30

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mg/L silicate dose elevated the pH from 6.3 to 7.1 and resulted in a 55% lead level reduction

(Schock et al., 2005). The lead leaching reduction did not happen right at the addition of

sodium silicate, instead lead concentrations gradually reduced over a period of several

months (Schock et al., 2005). This could be due to a slow formation of protective films on

pipe surfaces as suggested by LaRosa-Thompson et al. (1997). It can be seen that sodium

silicate may inhibit lead corrosion and reduce lead leaching. However, the impact of sodium

silicate on galvanic corrosion between lead and copper has not been carefully studied, and

the comparison with other inhibitors such as orthophosphate deserves further study. Silicate

products are commonly seen with weight ratios of silica (SiO2) to alkali (Na2O or K2O) of

up to 4.0. The most common commercial liquid sodium silicate is a product having a weight

ratio of silica to alkali (as Na2O) of 3.22, and with 37 to 38% solids (Woszczynski, 2011).

The ratio recommended for water that has a pH greater than 6.0 is 3.22 (Thompson et al.,

1997). A dosage of 24 to 25 mg/L as SiO2 is recommended for the first month or two,

followed by a maintenance dosage of 8 to 10 mg/L as SiO2 (Thompson et al., 1997).

2.2 Aged Lead Pipes

Galvanic corrosion is the one important contributor for lead leaching to water after PLSLR.

Just like water chemistry, the age of the lead bearing material is also important to lead

leaching. The major difference between new and old lead pipes is the scale formed on the

inner surface. Currently, many researchers are still dedicated to the chemistry of the

corrosion products at the inner surface of the lead pipes, as well as their formation processes.

In general, lead passivation occurs over time by the formation of corrosion products such as

cerussite [PbCO3], hydrocerussite [Pb3 (CO3)2(OH) 2], plumbonacrite (Pb10 (CO3)6 (OH)6O),

litharge (PbO), and plattnerite (PbO2) (Kim and Herrera, 2010). The amount and the species

of the corrosion product formed is a complex function of various water quality parameter

and time.

Triantafyllidou et al. (2010) compared the lead release from new and old lead pipes, while

simulating PLSLR. Two types of old lead pipes were employed; one had been used for 4

months and another for up to 1 year. Although similar trends were found as for the new lead

pipes, the absolute lead leaching level varied substantially (Triantafyllidou et al., 2010). For

the 4-month old lead pipes, the highest leaching level was from the 17% replaced lead pipe

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being 13000 μg/L (Triantafyllidou et al., 2010). For the one-year old lead pipes, the highest

leaching level was 21000 μg/L also from the 17% replaced lead pipe (Triantafyllidou et al.,

2010). Since used pipes are more passivated, it was expected to weaken the galvanic effect

and reduce the lead leaching level. There was also a big difference between the two types of

used pipes. Since their previous usage conditions were not mentioned, the exact reason

behind was not clear. The lead release difference may be due to different corrosion products

which have different lead solubility.

Pipe age may also be considered for lead corrosion control upon changes to water

chemistry/treatment. Lead levels above the action limit were found in drinking water in

Washington, D.C.in 2001. This incident is now known to be caused by a change in

disinfectant from free chlorine to chloramines (Edwards and Dudi, 2004). The same

researchers (2004) showed that chloramines sometime make lead leaching much higher than

free chlorine for the old pipes, but do not impact new lead pipes as much. After many years

of using free chlorine as disinfectant, a solid layer of PbO2 had already formed on the old

pipes, and the change in disinfectant lowered the redox potential of the aqueous phase,

causing the destabilization and dissolution of PbO2 (Kim and Herrera, 2010). While for the

new pipes, no corrosion product has formed yet; therefore, corrosion rate is not as rapid.

Recent studies on PLSLR were mostly conducted on the new lead pipes and it can be seen

that new lead pipes cannot accurately represent used pipes behaviors. Hence, the current

study tested used lead pipes since used pipes are the ones used in practice.

2.3 Relationship between Galvanic Current, Galvanic Corrosion and Lead Release

The correlation between galvanic current and lead leaching was studied by Triantafyllidou et

al. (2010) for both new and old pipes. They suggested that for R2 as high as 0.44 for high

CSMR (16.2), galvanic corrosion is likely the dominating source of lead release. As R2

decreases, lead released would be contributed by other sources such as dissolution, particle

detachment and deposition corrosion. Arnold (2011) also measured galvanic current along

with the lead concentration. In low alkalinity (12 mg/L CaCO3) water, the addition of

orthophosphate (2 mg/L P) tripled lead concentration from 6000 µg/L to 17000 µg/L, but the

current only increased from 25 µA to 35 µA (Arnold, 2011). In high alkalinity (250 mg/L

CaCO3) water, as orthophosphate (2 mg/L P) was added, lead concentration decreased from

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2500 µg/L to 1100 µg/L, but current decreased by only 25% from 23 µA to 16 µA (Arnold,

2011). No correlation was observed from the data. Therefore, galvanic corrosion was not the

sole contributor to lead release. By measuring galvanic current, it becomes possible to

observe the contribution of galvanic corrosion to total lead release.

An equation describing the relationship between current and lead release due to galvanic

action was suggested by Dudi (2004) assuming constant current during 8 hours of stagnation

period for a brass hose bib device.

Maximum Lead Leaching (g) =

2-5

where I is current (µA)

t is time (s)

M is molar mass (g/mol)

This relationship can be used to predict lead leaching levels. The predicted lead release was

equal or lower when compared to the actual measurement (Dudi, 2004). Lead leached from

the lead pipe was not only due to galvanic corrosion; therefore the result was not surprising.

It can be seen that it is necessary to measure galvanic current also in the current study and to

investigate the relationship between current and lead release for partially replaced lead pipes.

As mentioned in the previous sections, galvanic corrosion is not the only mechanism

responsible for lead release from partially replaced lead pipes and knowing the relationship

between galvanic current and lead release can help in identifying the contribution of

galvanic corrosion to lead release.

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3 Experimental Design

Most laboratory studies investigating lead release from service lines have been conducted

using lead/copper or lead/brass coupons. The current study adopted static pipe rigs instead of

coupons since they resemble the real service line the most. Each pipe rig consisted of a lead

pipe segment (0.5 m), a copper pipe segment (0.5 m), and incorporated silicone stoppers at

both ends to retain the water. The total length of the pipe rig was 1 meter (Triantafyllidou et

al., 2010). The purchased copper pipes were brand new with inner diameter of 1.27 cm and

lead pipes were excavated from the City of London (Ontario) and had inner diameters of

1.28 cm ± 0.03 cm.

The primary objective (refer to Section 1.2) of this thesis was to investigate the effect of

galvanic action on aged lead pipes by examining lead leaching levels from pipe rigs as a

function of water chemistry. From the literature, five factors were identified when

considering galvanic corrosion between lead and copper: alkalinity, nitrate, natural organic

matter (NOM), disinfectant, and corrosion inhibitor. Most past studies only focused on one

or two of these factors. The current study not only examined their individual effects, but also

interaction effects of several factors on lead leaching. A factorial design was used since

unlike a one-variable-at-a-time approach which tacitly assumes the effect of one variable is

independent of the level of the other variables, it can detect and estimate the interaction

between variables to the response.

The second objective (refer to Section 1.2) was to study the relationship between galvanic

current and the actual lead release. Galvanic current was measured for each pipe rig in the

experiment and was correlated to total lead leaching.

A “dump and fill” protocol was adopted (Triantafyllidou et al., 2010; Anrold, 2011). The

test water was used to fill the pipe rigs three times per week, on Monday, Wednesday, and

Friday, draining the pipes at the same time and collecting the sample. At the end of each

week, the three water samples were combined to form a weekly composite which was

analyzed.

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3.1 Impact of Alkalinity, Nitrate, NOM, Disinfectant, Inhibitor on Lead Release

after Partial Lead Pipe Replacement

Bench-scale laboratory experiments were conducted using pipe rigs to examine the effects of

NOM, nitrate, alkalinity, disinfectant and inhibitors on lead release during stagnant

conditions. The constituent levels in the current study were selected to be within a normal

drinking water range and also similar to previous lead release studies (Table 3-1). The

maximum contaminant level (MCL) set by the U.S Environmental Protection Agency for

nitrate is 10 mg/L NO3-N (U.S Environmental Protection Agency, 1985), so nitrate was

varied between 0 and 10 mg/L NO3-N. NOM was between 0-10 mg/L DOC. DOC was

provided by SNOM (Suwannee River natural organic matter). The levels of alkalinity,

disinfectant and inhibitor were selected within the ranges reported in past studies.

Table 3-1: Quantities of water condition factors tested in past studies

Factor Quantities Reference

Alkalinity (mg/L CaCO3) 12 as “low”, 250 as “high” Arnold, 2011

15 Triantafyllidou et al., 2010

Nitrate (mg/L NO3-N) 0 to 10 Nguyen et al., 2011

NOM (mg/L DOC) 0 to 10 Korshin et al., 2000

Korshin et al., 2005

Disinfectant (mg/L Cl2)

Chlorine: 1

0.1 to 3

Woszczynski,2011

Lytle and Schock, 2005

Chloramines: 4 Triantafyllidou et al., 2010

Inhibitor (mg/L) Orthophosphate: 0-2 Arnold, 2011

Silicate: 18 Woszczynski,2011

Two levels of each of NOM, nitrate, alkalinity and two types of disinfectants and inhibitors

were dosed to Milli-Q®

water respectively. CSMR and pH was adjusted to 2.5 and 8.0

respectively before going to the pipe rigs (Triantafyllidou et al., 2010). Galvanic current was

monitored every day of the week. At the end of each week, water samples were collected for

total lead and dissolved lead analysis.

A 2-level factorial design was used to investigate impacts of five water chemistry factors to

galvanic corrosion. A half factorial (2v5-1

) design was adopted which resulted in 16 testing

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conditions. 2v5-1

design has a resolution R = 5 so that the main effects would be confounded

with four-factor interactions, and two-factor interactions would be confounded with certain

three-factor interactions. Since high order interactions are usually small when compared to

the main effects, a 2v5-1

design is able to capture the major effects between the factors.

Design Expert 8.0.6 software was used to generate the test conditions based on the above-

mentioned requirements (Table 3-2).

The significant factors for lead release were determined by Analysis of Variance (ANOVA).

ANOVA is a statistical process for analyzing the amount of variance that is contributed to a

sample by different factors. It is often used to detect significant factors in a multi-factor

model. For this experiment, there were three dependent variables and five independent

variables. The three dependent variables, which were the responses for the experiment, were

galvanic current, total lead and dissolved lead. The five independent variables were

Alkalinity (A), SNOM (B), Nitrate (C), Disinfectant (D) and Inhibitor (E). The most

common approaches of ANOVA are called Type I, II and III sums of squares. Type III was

applied in here since this approach is valid in the presence of significant interactions.

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Table 3-2: 2v5-1

factorial design for water chemistry factors

Note:

Factor 1: Alkalinity (mg/L CaCO3) Factor 2: SNOM (mg/L DOC) Factor 3: Nitrate (mg–N/L NO3)

+1 0 -1 +1 0 -1 +1 0 -1

250 150 15 7 4 1 7 4 1

Run# Factor A: Alkalinity Factor B: SNOM Factor C: Nitrate Factor D: Disinfectant Factor E: Inhibitor Response

1 -1 1 -1 1 1 a, b, c

2 1 -1 -1 -1 -1 a, b, c

3 1 -1 1 1 -1 a, b, c

4 1 1 1 -1 -1 a, b, c

5 1 1 -1 -1 1 a, b, c

6 1 1 1 1 1 a, b, c

7 -1 1 1 -1 1 a, b, c

8 1 -1 1 -1 1 a, b, c

9 -1 -1 1 -1 -1 a, b, c

10 -1 1 1 1 -1 a, b, c

11 -1 1 -1 -1 -1 a, b, c

12 -1 -1 -1 -1 1 a, b, c

13 -1 -1 1 1 1 a, b, c

14 1 1 -1 1 -1 a, b, c

15 1 -1 -1 1 1 a, b, c

16 -1 -1 -1 1 -1 a, b, c

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Factor 4: Disinfectant Factor 5: Inhibitor

+1 0 -1 +1 0 -1

Chlorine

(1 mg-Cl2/L)

None Monochloramine

(3 mg-Cl2/L)

Orthophosphates

(1 mg-P /L)

None Sodium silicate

(24 mg-SiO2/L)

a- total lead (µg/L), b- dissolved lead (µg/L), c- galvanic current (µA)

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4 Materials and Methods

4.1 Test Water Preparation

The volume of test water to fill one pipe rig (1 meter long) was 150 cm3 (≈ 0.15 L) using

Equation 4-1.

4-1

where V= volume (L)

r = radius (m)

H=height (m)

A “dump and fill” protocol was adopted (Triantafyllidou et al., 2010; Anrold, 2011). Each pipe

rig was filled with test water three times per week, on Monday, Wednesday, and Friday. Test

waters were prepared with Milli-Q®

water in the DWRG lab. The purification processes

involved successive steps of filtration and deionization in order to achieve a purity expediently

characterized in terms of resistivity (18.2 MΩ•cm at 25 °C). Target levels of NOM, nitrate,

inhibitors, disinfectants, sulfate and chloride were added to the Mill-Q®

water. pH and alkalinity

in the test water were adjusted accordingly. Disinfectant residual levels were checked and

adjusted right before test water filling the pipe rigs to leave a desired residual level going to the

pipe rigs, as explained later on.

4.1.1 NOM

Reference Suwannee River NOM (catalog #1R101) was procured from the International Humic

Substances Society (IHSS) (St. Paul, Minnesota). The stock NOM sample is in the form of

desalted, freeze-dried solid powders. On the basis of the analytical information provided by the

IHSS, Suwannee River NOM is composed of 52.47 wt % carbon, 4.19 wt % hydrogen, 42.69

wt % oxygen, 1.10 wt % nitrogen, 0.65 wt % sulfur, 0.02 wt % phosphate, and the ash content is

7.0 wt %. NOM was added to the Milli-Q®

water at concentrations of 1 and 7 mg/L as dissolved

organic carbon (DOC). This was achieved by first preparing a filtered stock NOM solution

(155-175 mg/L DOC) (Table 4-1: Filtered stock solution preparation outline and dosing an



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appropriate amount of the stock solution to Milli-Q®

water. DOC is the fraction of total organic

carbon (TOC) in a sample that passes through a filter with a pore size of 0.45 μm. DOC were

verified by analyzing the filtered water using the TOC method described in Section 4.2.1

Table 4-1: Filtered stock solution preparation outline

1. Prepare a 500 mL stock solution of 0.4 g/L SNOM. Add 0.2 g of SNOM and 2 mL 1M

NaOH to 498 mL Milli-Q®

water.

2. Pass the solution through a polyethersulfone membrane filter with a pore size of 0.45 μm

(Gelman Supor, Gelman Sciences, Ann Arbor, MI) (Comerton, 2008).

3. Analyze the TOC of the filtered solution using the TOC method described in Section 4.2.1.

4. Calculate the volume of stock solution need to be added to make up 1 and 7 mg/L DOC

4.1.2 Nitrate

The target levels for nitrate in the test water were 1 and 7 mg-N /L NO3. This was accomplished

by adding a previously made nitrate stock solution to Milli-Q®

water. A 250 mL nitrate stock

solution (1400 mg/L NO3-N) was prepared by adding 2.13 g of NaNO3 (Sigma-Aldrich

Corporation, Oakville, ON) to Milli-Q®

water (Nguyen et al., 2011c). Nitrate level were verified

as described in Section 4.2.6.

4.1.3 Inhibitor

Two types of inhibitors, sodium silicate and orthophosphate, were used in this study. Sodium

silicate solution (National Silicates, Etobicoke, ON) having a weight ratio of 3.22 between SiO2

and Na2O with 37.5% solids, was used to make test water containing 24 mg/L SiO2

(Woszczynski, 2011). For each litre of test water, 0.06 mL of sodium silicate solution was

added.

Sodium orthophosphate (Na2HPO4) (Sigma-Aldrich Corporation, Oakville, ON) was used to

make an orthophosphate stock solution of 200 mg/L as P (Arnold, 2011). A 250 mL

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orthophosphate stock solution was made by adding 0.2292 g of Na2HPO4 to Milli-Q®

water.

Silica and phosphorous level were verified as described in Section 4.2.6.

4.1.4 CSMR

CSMR for the test water was 2.5. Since CSMR is the ratio of chloride and sulfate, the target

concentration of chloride and sulfate were 25 mg/L and 10 mg/L respectively. Sodium chloride

(NaCl) and potassium sulfate (K2SO4) (Sigma-Aldrich Corporation, Oakville, ON) were used to

make a stock solution containing 5000 mg/L Cl- and 2000 mg/L SO4

2- (Nguyen et al., 2011b).

The concentration of chloride and sulfate were verified as described in Section 4.2.6.

4.1.5 Alkalinity

The target alkalinity levels for the test water were 15 mg/L and 250 mg/L as CaCO3,

respectively. The target alkalinity was made up by sodium bicarbonate (NaHCO3) (Sigma-

Aldrich Corporation, Oakville, ON). The level of alkalinity was verified using a Total Inorganic

Carbon Analyzer (O-I Corporation Model 1010 Analytical TOC Analyzer and Model 1051 Vial

Multi-Sampler, College Station, Texas) since the only source of inorganic carbon was sodium

bicarbonate in this study. To convert alkalinity to TIC,

CaCO3 + H2O + CO2 → Ca(HCO3)2

4-2

CaCO3 has a molecular weight of 100 g/mol.

HCO3- has a molecular weight of 61 g/mol.

Therefore, each mole of Ca (HCO3)2 corresponds to one mole of CaCO3 (100 g) and contains (2

× 61) = 122 g of HCO3-. Hence, 250 mg /L CaCO3 corresponds to (250 /100 × 122) = 305 mg/L

HCO3- . In 305 mg/L HCO3

-, there are

(305×12/61) = 60 mg/L carbon. Hence, the expected TIC

level should be 3.6 mg/L and 60 mg/L respectively for 15 mg/L and 250 mg/L CaCO3.

Sodium bicarbonate (NaHCO3) (Sigma-Aldrich Corporation, Oakville, ON) was used to make a

stock solution containing 5000 mg/L TIC by adding 8.75 g NaHCO3 in 250 mL Milli-Q®

water.

22

22

4.1.6 pH

The pH of each test waters was adjusted to 8.0 ± 0.1. Common strong acid such as nitric acid

(HNO3), hydrochloric acid (HCl) and sulfuric acid (H2SO4) would introduce undesired anions

into the test water. Hence, pH was adjusted by adding 99.9% pure CO2 gas to the test water

prior to filling the pipes (Arnold, 2011; Nguyen et al., 2011c). For detailed procedures please

see Section 7.2.2. pH of the test waters can be measured as described in Section 4.2.2

4.1.7 Disinfectant

Two types of disinfectants, chlorine and monochloramine were included in this study. Sodium

hypochlorite (NaClO) solution (12% Cl2, BioShop Canada, Inc., Burlington, ON) was used to

establish the target chlorine residual. Sodium hypochlorite working solutions were prepared by

diluting 5 mL of sodium hypochlorite stock solution to 200 mL using Milli-Q®

water. The

working solution contained about 3000 mg/L free chlorine which can be verified as described in

Section 4.2.3.

Monochloramine working solution was prepared using sodium hypochlorite solution and

ammonium hydroxide (NH4OH) solution. Ammonium working solution was prepared by

diluting 1 mL of the original solution to 100 mL using Mill-Q water. 10 mL of ammonium

hydroxide working solution and 30 mL of sodium hypochlorite working solution was mixed

using a magnetic stirrer for 3 hours. The concentration of monochloramine working solution

was measured as described in Section 4.2.3.

23

23

4.2 Analysis Methods

4.2.1 Total Organic Carbon (TOC)

TOC provides an important role in quantifying the amount of NOM in the water source. Total

carbon is defined as the sum of inorganic carbon (IC) which includes carbonate, bicarbonate,

dissolved CO2, and total organic carbon (TOC). A typical analysis for TOC measures both the

total carbon and IC. TOC can also be measured after removing the IC portion first and then

measuring the leftover carbon. The TOC was analyzed using an O-I Corporation Model 1010

Analytical TOC Analyzer and Model 1051 Vial Multi-Sampler (College Station, Texas). The

method was based on the wet oxidation method described in Standard Method 5310 D (APHA,

1998). The required reagents are listed in Table 4-2, and the instrument conditions are described

in Table 4-3. The method steps are outlined in Table 4-4. 40 mL of sample after passing through

a filter (Gelman Supor, Gelman Sciences, Ann Arbor, MI) with a pore size of 0.45 μm was

collected and acidified to pH < 2 which was verified by a pH meter with concentrated (98+ %)

sulphuric acid (H2SO4) and stored in the dark at 4°C (up to 2 weeks) before analysis (Comerton,

2008). Stock solution of 1 g/L TOC was made from dry potassium hydrogen phthalate (KHP)

(Sigma-Aldrich Corporation, Oakville, ON) in Milli-Q®

water. 0.625, 1.25, 2.5, 5, 10 mg/L

TOC calibration standard solutions were used to generate a calibration curve. The

concentrations of the samples were determined through correlation with calibration standards.

Blanks (Milli-Q®

water), and running standards were run every 10 samples. An example of a

typical TOC calibration curve is presented in Figure 4-1. Quality control charts are presented in

Figure 4-2. The method detection limit for TOC was 0.07_mg/L, determined by multiplying the

standard deviation of 8 low concentration replicates by the Student-t value (3.0).

24

24

y = 6227.1x + 2989.8

R2 = 0.9999

0

10000

20000

30000

40000

50000

60000

70000

0 2 4 6 8 10 12

Concentration (mg/L)

Are

a c

ou

nt

Figure 4-1: Example total organic carbon calibration curve

Figure 4-2: Total organic carbon quality control chart (3.0 mg/L) (July to December, 2012)

2.5

2.6

2.7

2.8

2.9

3

3.1

3.2

3.3

3.4

3.5

TO

C c

on

ce

ntr

atio

n (m

g/L

)

Upper CLUpper WL

Mean

Lower WLLower CL

25

25

Table 4-2: Total organic carbon reagents

Reagent Supplier and Purity

Sodium persulphate [Na2S2O8] (100 g/L) Aldrich, 98+%

Potassium hydrogen phthalate [C8H5KO4] Aldrich, 98+%

Sulphuric acid, concentrated [H2SO4] VWR International, 98+%

Table 4-3: Total organic carbon instrument conditions

Parameter Description

Acid volume 200 μL of 5% phosphoric acid

Oxidant volume 1000 μL of 100 g/L sodium persulphate

Sample volume 15 mL

Rinses per sample 1

Volume per rinse 15 mL

Purge gas Nitrogen

Loop size 5 mL

Table 4-4: Total organic carbon method outline

Stock solution (1 g/L): Dissolve 2.1254 g of anhydrous C8H5KO4 in about 500 mL

Milli-Q® water and bring volume to 1 L using volumetric

flask with Milli-Q® water.

Running standard (3 mg/L): Prepare a 3.0 mg/L check standard by diluting 1.5 mL of

stock solution into 500 mL of Milli-Q® water using a

volumetric flask.

Blanks: Use 40 mL of Milli-Q® water.

4.2.2 pH

The pH of the sample was measured using a laboratory pH meter (Model 8015, VWR Scientific

Inc., Mississauga, ON). Standard buffer solutions of pH at 4, 7 and 10 (Canadawide Scientific,

Ottawa, ON) were used to calibrate the instrument prior to the start of each experiment. All

samples and standards were brought to room temperature before use. The electrode was rinsed

by Milli-Q®

water before contacting the sample solution. 50 mL of the water sample was stirred

moderately without breaking the surface during the measurement. After the meter stabilized, pH

of the sample was taken.

26

26

4.2.3 Chlorine and Monochloramine Residual

Free chlorine and monochloramine residual were determined following the DPD colorimetric

method as described in Standard Method 4500-Cl D (APHA, 1998).The instrument used was

DR 2700 Portable Spectrophotometer (HACH Co., Loveland, Co). The spectrophotometer was

blanked using the sample water. To measure free chlorine residual, the contents of a DPD free

chlorine powder pillows (HACH Co., Loveland, Colorado) was added to 25 mL sample water in

a square glass vial. The vial was capped with a glass top and mixed by shaking rapidly. After 20

seconds reaction period, the vial was inserted into the instrument and analyzed for absorbance at

530 nm. To measure monochloramine residual, the contents of a DPD monochloramine powder

pillows (HACH Co., Loveland, Colorado) was added to 25 mL sample water in a round plastic

vial. The vial was capped with a Teflon®

top and mixed by inverting. After 5 minutes reaction

period, the vial was inserted into the instrument and analyzed for absorbance at 530 nm.

4.2.4 Oxidation-Reduction Potential

As described in Standard Methods Section 2580 (APHA, 1998), oxidation reduction potential

(ORP) is a measure of the capacity of an aqueous solution to either release electrons in chemical

reactions (oxidation) or gain electrons in chemical reactions (reduction). A sensION Portable

Multi-Parameter Meter (HACH Co., Loveland, Colorado) was used to measure ORP for sample

solutions. For accurate sample measurements, ORP electrode performances were checked

against ORP standard solutions (200 mV). The electrode was rinsed with Milli-Q®

after each

sample to prevent contamination.

4.2.5 Galvanic Current

Galvanic current between copper pipe and lead pipe was conducted using a RadioShack multi-

meter (Model # 22-811) with 100 Ω resistance (Nguyen et al., 2011b). The measurements were

taken by connecting the multi-meter in-line for 15 seconds after disconnecting the external wire

between the two metals.

27

27

4.2.6 Analysis of Silica, Phosphorus, Nitrate, Sulfate and Chloride

The concentrations of silica, phosphorus, nitrate, sulfate and chloride in the test water were

measured using DR 2700 Portable Spectrophotometer (HACH Co., Loveland, Co). Silica (SiO2)

was measured using HACH silicomolybdate Method (8185) for high range (1 to 100 mg/L

SiO2). Phosphorus was measured using the HACH PhosVer®

3 Method (8048) which was

adapted from Standard Method 4500-P (APHA, 1998). Nitrate was measured using the HACH

HR Cadmium Reduction Method (8039) which was adapted from Standard Methods 4500-NO3-

(APHA, 1998). Sulfate was measured using HACH SulfaVer 4 Method Powder Pillows (8051)

which was adapted from Standard Methods 4500-SO42-

(APHA, 1998). Experimental

procedures are in Section 7.2.3.

4.2.7 Lead Analysis

Total and dissolved leads were analyzed using ICP-MS in this study. Inductively coupled

plasma mass spectroscopy (ICP-MS) was developed in the late 1980's to combine the easy

sample introduction and accurate and low detection limits (1 to 100 ng/L) of a mass

spectrometer. Dissolved lead samples were prepared by passing sample through a filter with a

pore size of 0.45 µm. 4 mL of nitric acid (HNO3) of 18% concentration was added to the 200

mL of sample for preservation. The sample waters were shipped to Maxxam Analytics for lead

analysis.

28

28

4.3 Pipe Rig

The pipe rigs consisted of a copper pipe portion that was connected to a lead pipe portion. The

lead portion and copper portion were separated by an insulating spacer, but an external wire

connecting the two segments was used to complete the galvanic circuit during normal

experimental conditions. The new copper pipes were rinsed with deionized water for 1 minute in

both directions. The old lead pipes were rinsed with deionized water for 1 minute in the original

water flow direction. .

Figure 4-3: Photo of a pipe rig set-up.

29

29

Figure 4-4: The lead portion and copper portion are separated by an insulating spacer and

connected by an external wire

30

30

5 Results

5.1 Chlorine and Monochloramine Demand Test

5.1.1 Chlorine Demand Tests

The purpose of this experiment was to find the initial chlorine dosages that can provide 1 ± 0.2

mg/L free chlorine residual after 7 to 11 days following the addition of chlorine to waters

containing 1, 4, and 7 mg/L DOC. There were 7 test conditions in total, as illustrated in Table 5-

1. These 7 test conditions, which included one blank condition (zero DOC) and two chlorine

dosages for each other level of DOC, were adjusted to have a CSMR of 2.5, nitrate at 7 mg/L

NO3–N, orthophosphate at 1 mg/L P and alkalinity at 250 mg/L CaCO3. Experimental

procedures are listed in Section 7.2.1 and raw data in Section 7.3.1

Table 5-1: Test conditions for the chlorine demand test

The blank condition had 0 mg/L DOC and 3.5 mg/L chlorine in it. The free chlorine decay curve

(Figure 5-1: Free chlorine residual versus time (time = 0 to 11 day) for water samples dosed


deviation) shows that over the 11 days of the test period, the free chlorine measured was stable

and remained at 3.5 ± 0.15 mg/L which was the amount added to the water. The trend was

expected and proved that the bottles which the samples were in had no chlorine demand.

DOC (mg/L) Initial chlorine dosage

0 3.5

1 2.5

1 3.5

4 8

4 10

7 16

7 19

31

31

0

1

2

3

4

0 2 4 6 8 10 12

Time (day)

Fre

e c

hlo

rin

e r

esid

ual

co

ncen

tra

tio

n (

mg

/L)

DOC = 0 mg/L, Chlorine = 3.5 mg/L

Figure 5-1: Free chlorine residual versus time (time = 0 to 11 day) for water samples dosed


deviation of n=2. Some error bars were too small to see.

When chlorine reacts with natural organic matter (NOM), the rates of the reactions can vary

greatly, depending on the nature of the organic species present (Clark and Sivaganesan 2002;

Gang et al., 2002). The variation in reactivity of chlorine with these organic species leads to

complications in modeling the chlorine decay trend. Many models reported in the literature to

represent chlorine decay in bulk water adopt either first-order or second-order kinetics (Gang et

al., 2002; Vasconcelos et al., 1997; Boccelli et al., 2003). Some models make use of a sequence

of different models to characterize the different reactions occurring over the period of interest

(Sung et al., 2001; Warton et al., 2006). The general first-order kinetic expression for the

decrease in the concentration of chlorine in water is expressed as follows:

32

32

Ct = C0 • e-kt

5-1

If Equation 5.1 is converted to a log form, it becomes:

ln Ct = -kt + ln C0 5-2

where Ct = chlorine concentration (mg/L) at time t

C0 = initial chlorine concentration (mg/L)

t = time (day)

k = the first-order decay constant

= the slope of the linear function when plotting ln Ct against t

In this chlorine demand test, the chlorine decay for the time between time = 0 and time = 4 hr

was very fast (Figure 5-2, the vertical portion of the curve). Therefore, the decay process was

divided into two time intervals: 0 – 4 hr and 4 hr – 11 day.

0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

0 2 4 6 8 10 12

Time (day)

Fre

e c

hlo

rin

e r

es

idu

al

co

nc

en

tra

tio

n (

mg

/L)



DOC = 4 mg/L, Chlorine = 8 mg/L




Figure 5-2: Free chlorine residual versus time (time = 0 to 11 day) for waters with different

levels of DOC and chlorine. Note: the error bars represent one standard deviation n =2. Some

error bars were too small to see

33

33

The chlorine decay during the first time interval (0 to 4 hr) was defined as instantaneous

demand, and a first-order decay model was applied to the chlorine decay during the second time

interval (4 hr to 11 day) (Figure 5-3).

y = -0.072x + 0.4036

R2 = 0.9382

y = -0.1723x + 1.5419

R2 = 0.9676

y = -0.0383x + 0.9028

R2 = 0.9005

y = -0.1283x + 2.1406

R2 = 0.9709

y = -0.0892x + 1.7783

R2 = 0.9608

y = -0.087x + 2.4256

R2 = 0.9582

-0.5

0

0.5

1

1.5

2

2.5

3

0 2 4 6 8 10 12

Time (day)

In(C

t)







Figure 5-3: Log-chlorine residual concentration versus time plots (time = 4 hr to 11 day)

34

34

To find the initial dosage that can provide 1 mg/L chlorine at the 9th

day following addition, a

method introduced by Warton et al. (2006) was applied. First, a first-order decay model was

applied to the chlorine decay for the time period from 4 hr to 11 day (Figure 5-3), according to

the following equation:

y = - k t + a 5-3

The linear functions fitted the data adequately, with correlation coefficients of R2

> 0.90. The

parameters a and k (Eq. 5-3) for each of the initial concentrations were calculated by Excel, and

were listed in Table 5-2. Second, the first-order decay function was used to back-calculate the

chlorine residual concentration on the 9th

day. The value of time t, was substituted into Equation

5-3, together with the appropriate values of k and a for each of the initial chlorine concentrations

used. Third, the initial concentration C0 was then plotted against the calculated Ct on the 9th

day

for each of the initial concentrations (Figure 5-4), and a linear function was fitted to this data,

according to the following equation:

C0 = f + e × Ct 5-4

The parameters e and f (Eq. 5-4) for each of DOC levels were calculated, and were listed in

Table 5-2. Lastly, Equation 5-4 was used to determine the chlorine dose required to give a

specific residual concentration (1 mg/L Cl2) at the desired time (9th

day), by substituting Ct, e

and f into Equation 5-4. The estimated initial chlorine dosages are listed in Table 5-2. They are

2.73 mg/L for DOC at 1 mg/L, 8.01 mg/L for DOC at 4 mg/L and 13.97 mg/L for DOC at 7

mg/L. Hence, 2.8 mg/L, 8.0 mg/L and 14 mg/L were the initial dosages for making the test

water for DOC at 1, 4, and 7 mg/L respectively.

35

35

Figure 5-4: Initial free chlorine concentration versus free chlorine residual concentration on the

9th

day

Table 5-2: Values of parameters k, a, e and f as calculated for Equation 5-3 and 5-4, for various

initial chlorine concentrations in the time interval 4 hr to 11 days

DOC

(mg/L)

Dose of

chlorine

(mg/L)

k a

Ct

calculated

on the 9th

day

e f

Target

ct on

9th

day

Estimated

initial

chlorine conc.

to provide 1

mg/L residual

(mg/L)

1 2.5 0.072 0.4035 0.78

1.0371 1.6879 1 2.73 3.5 0.0383 0.9028 1.75

4 8 0.1723 1.5417 0.99

1.2022 6.8085 1 8.01 10 0.0891 1.7782 2.65

7 16 0.1283 2.1405 2.68

1.2057 12.769 1 13.97 19 0.087 2.4255 5.17

Note: k and a are parameters for Equation 5-3, e and f are parameters for Equation 5-4.

y = 1.0371x + 1.6879

y = 1.2022x + 6.8085

y = 1.2057x + 12.769

0

2

4

6

8

10

12

14

16

18

20

0.00 1.00 2.00 3.00 4.00 5.00 6.00

Init

ial c

hlo

rin

e c

on

ce

ntr

ati

on

(m

g/L

)

Chlorine residual concentration (mg/L)

DOC = 1 mg/L

DOC = 4 mg/L

DOC = 7 mg/L

36

36

5.1.2 Monochloramine Demand Tests

The purpose of this experiment was to find the monochloramine dosages that can provide 3 ±

0.2 mg/L monochloramine residual following 7 to 11 days after the addition of monochloramine

for waters containing 1, 4, and 7 mg/L DOC. There were 7 test conditions, which included one

blank condition (zero DOC) and two dosages for each other level of DOC (Table 5-3). All test

waters were adjusted to have a CSMR of 2.5, nitrate of 7 mg/L NO3–N, orthophosphate of 1

mg/L P and alkalinity of 250 mg/L CaCO3. Experimental procedures were listed in Section 7.2.1

and raw data in 7.3.1.

Table 5-3: Test conditions for the monochloramine demand test

DOC (mg/L) Initial doses of

monochloramine (mg/L)

0 6

1 4

1 6

4 6

4 9

7 9

7 12

The blank condition had 0 mg/L DOC and 6 mg/L monochloramine. A monochloramine decay

curve (Figure 5-5) has shown that over the 11 days the monochloramine measured was stable.

The trend was expected and proved that the bottles which the samples were in had no

chloramine demand.

37

37

0

1

2

3

4

5

6

7

0 2 4 6 8 10 12

Time (day)

Mo

no

ch

lora

min

e r

es

idu

al

co

nc

en

tra

tio

n (

mg

/L)

DOC = 0 mg/L, Monochloramine = 6 mg/L

Figure 5-5: Monochloramine versus time (time = 0 to 11 day) for water samples dosed with

DOC at 0 mg/L, monochloramine at 6 mg/L Cl2. Note: the error bars represent one standard

deviation of n=2. Some error bars were too small to see.

In the monochloramine demand tests when using waters with DOC, the monochloramine decay

for the time between 0 and 4 hours was typically quite fast (Figure 5-6, the vertical portion of

the curve). Therefore, the decay process was divided into two time intervals: 0 – 4 hr and 4 hr –

11 day. A first-order decay model was applied to the monochloramine decay for the time period

from 4 hr to 11 day (Figure 5-7). The same method described previously for the free chlorine

was applied to monochloramine to determine the initial dosages to yield a 3 mg/L

monochloramine residual after 9 days. The parameters a, k, e and f for Equations 5-3 and 5-4

were found through Figure 5-7 and Figure 5-8. The estimated initial monochloramine dosages

are listed in Table 5-4, and are 3.96 mg/L for DOC at 1 mg/L, 4.86 mg/L for DOC at 4 mg/L

and 6.43 mg/L for DOC at 7 mg/L. Hence, 4.0 mg/L, 5.0 mg/L and 6.5 mg/L monochloramine

were the initial dosages for making the test water with DOC at 1, 4, 7mg/L respectively.

38

38

0

2

4

6

8

10

12

14

0 2 4 6 8 10 12

Time (day)

Mo

no

ch

lora

min

e r

es

idu

al

co

nc

en

tra

tio

n (

mg

/L)







Figure 5-6: Monochloramine residual versus time (time = 0 to 11 day) for waters with different

levels of DOC and monochloramine. Note: the error bars represent one standard deviation of

n=2. Some error bars were too small to see.

39

39

y = -0.0215x + 1.3007

R2 = 0.8722

y = -0.0314x + 1.6439

R2 = 0.9956y = -0.0233x + 1.6454

R2 = 0.8459

y = -0.0525x + 2.0736

R2 = 0.9654 y = -0.0319x + 2.1248

R2 = 0.9688

y = -0.0376x + 2.319

R2 = 0.9463

0

0.5

1

1.5

2

2.5

0 2 4 6 8 10 12

Time (day)

Ln

(C

t)







Figure 5-7: Log-monochloramine residual concentration versus time (time = 4 hr to 11 day)

40

40

Figure 5-8: Initial monochloramine concentration versus monochloramine residual

concentration on the 9th

day

Table 5-4: Values of parameters k, a, e and f as calculated for Equations 5-3 and 5-4 for various

initial monochloramine concentrations in the time interval 4 hours to 11 days

DOC

(mg/L)

Dose of

mono-

chloramine

(mg/L)

k a

Ct

calculated

on the 9th

day

e f

Target

ct on

9th

day

Estimated

initial

mono-

chloramine

conc. (mg/L)

1 4 0.0215 1.3007 3.03

1.7003 1.1448 3 3.96 6 0.0233 1.6453 4.20

4 6 0.0314 1.6439 3.90

1.2601 1.0841 3 4.86 9 0.0319 2.1248 6.28

7 9 0.0525 2.0736 4.96

1.3108 2.5002 3 6.43 12 0.0376 2.3190 7.25

y = 1.7003x - 1.1448

y = 1.2601x + 1.0841

y = 1.3108x + 2.5002

0

2

4

6

8

10

12

14

0 1 2 3 4 5 6 7 8

Init

ial m

on

oc

hlo

ram

ine c

on

cen

tra

tio

n (m

g/L

)

Monochloramine residual concentration (mg/L)

DOC = 1 mg/L

DOC = 4 mg/L

DOC = 7 mg/L

41

41

5.1.3 Impact of Alkalinity and Inhibitor on Chlorine Demand

The purpose of this experiment was to examine the influence of alkalinity and inhibitor on

chlorine demand. There were three test conditions as illustrated in Table 5-5. All test waters

were adjusted to have a CSMR of 2.5, nitrate of 7 mg/L NO3–N, DOC of 1 mg/L and initial

chlorine at 3.5 mg/L.

Table 5-5: Test conditions to examine the influence of alkalinity and inhibitor

Alkalinity

(CaCO3 mg/L)

Silica

(SiO2 mg/L)

PO43-

(PO4-P mg/L)

250 0 1

15 0 1

250 24 0

As can be seen in Figure 5-9, the three chlorine decay curves showed similar decreasing trends.

42

42

0

0.5

1

1.5

2

2.5

3

3.5

4

0 2 4 6 8 10 12

Time (day)

Ch

lori

ne

re

sid

ua

l c

on

ce

ntr

ati

on

(m

g/L

)

Alkalinity at 250 mg/L CaCO3, Phosphate at 1 mg/L P

Alkalinity at 15 mg/L CaCO3, Phosphate at 1 mg/L P

Alkalinity at 250 mg/L CaCO3, Silicate at 24 mg/L

Figure 5-9: Chlorine free residual concentration versus time (0 to 11 days) for waters with

different levels of alkalinity and inhibitors. DOC = 1 mg/L, chlorine = 3.5 mg/L. Note: the error

bars represent one standard deviation of n=2. Some error bars were too small to see

Chlorine residual concentrations on the 9th

day of the three conditions were compared using the

Student’s t-test at a confidence level of 95% to determine whether any of the three conditions

yielded differences in chlorine decay rates that were different from the other two.

43

43

Table 5-6: The average, standard deviation and variance values for chlorine residual on the 9th

day

Chlorine residual (mg/L) on

the 9th

day Average

Standard

Deviation Variance

Condition A: Alkalinity = 250

mg/L, phosphate = 1 mg/L 1.81 0.0495 0.0025

Condition B: Alkalinity = 15

mg/L, phosphate = 1 mg/L 1.91 0.021 0.0008

Condition C: Alkalinity = 250

mg/L, silicate = 24 mg/L 3 1.95 0.0495 0.0025

To perform the statistical analysis, the null (Ho) and alternative (HA) hypotheses were first

defined as:

Ho: u1 = u2, the mean from population 1 and population 2 are the same

HA: u1< u2, the mean from population 1 and population 2 are different

Assume both populations are normally distributed. If t0 > tn1+n2-2, α, (α = 0.05), then Ho is rejected

in favor of HA which means the two means are different at 95% confidence level.

t0=

2

2

2

1

2

1

12

n

S

n

S

xx

5-5

Where n1 and n2 are the sample sizes, 1x and 2x are the sample means, and S12 and S2

2 are the

sample variances.

The sample size for all three conditions is 2. Hence, t n1+ n2-2, α = t 2+2-2, 0.05 = 2.92

44

44

t0 was calculated for each comparison and the results are listed in Table 5-6Table 5-7.

Table 5-7: T-test results

Population 1 Population 2 t0 tn1+n2-2, α Result

Chlorine residual for

alkalinity = 250 mg/L,

phosphate = 1 mg/L



phosphate = 1 mg/L

2.63

2.92

Accept

Ho: u1 = u2



phosphate = 1 mg/L



silicate = 24 mg/L

2.82

2.92

Accept

Ho: u1 = u2

Note: α = 0.05 for 95 % confidence level

Hence, the level of alkalinity and type of inhibitor do not have a significant impact on the

chlorine demand. Since monochloramine was less reactive when compared to free chlorine,

alkalinity and inhibitor should not pose a significant impact on monochloramine demand as

well. Therefore, 2.8 mg/L, 8.0 mg/L and 14 mg/L were determined to be the initial chlorine

dosages and 4.0 mg/L, 5.0 mg/L and 6.5 mg/L were determined to be the initial

monochloramine dosages for making the test water with DOC at 1, 4, and 7 mg/L respectively.

45

45

5.2 Significant Factors Affecting Galvanic Current after Partial Lead Pipe

Replacement

5.2.1 Factors that Affect the Size of Galvanic Current

Galvanic current is a direct measure of galvanic corrosion. In real life, galvanic corrosion is a

very complex phenomenon. The size of the galvanic current and its corrosive effect depends on

many factors. The most important factors are listed below (Jones, 1996; Zhang, 2011):

The difference in potential between anode and cathode

The geometric arrangement of the galvanic couple

The effective ratio of cathodic to anodic surface

The surface condition of the two electrode: passive film, corrosion product

The electrolyte properties: temperature, ionic species, pH, conductivity

The fundamental relationship for galvanic corrosion is described by Kirchhoff’s second law

(Jones, 1996):

Ec - Ea = I (Re + Rm)

5-6

where Re is the resistance of the electrolytic portion of the galvanic cell

Rm is the resistance of the metallic portion of the galvanic cell

Ec is the effective potential of the cathodic member of the couple

Ea is the effective potential of the anodic member of the couple.

I is the galvanic current

All of the above factors affect galvanic current according to this mathematical relationship. In

this experiment, the geometric arrangement of each of the pipe rig, electrolyte pH and

temperature, as well as the surface ratio of cathode and anode were considered the same for each

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46

pipe rig. The effective ratio of cathodic and anodic surface area was the ratio of the areas of the

exposed metal surfaces wetted by the electrolyte. The inner diameter (ID) of the new copper

pipe was 1.27 cm and the length was 50 cm. The average ID of the aged lead pipe was 1.28 ±

0.03 cm and the length was 49 ± 1.97 cm. Hence, the ratio of the inner surface between cathode

and anode is roughly 1:1 for all pipe rigs.

The theoretical potential difference between lead metal and copper metal should be 0.47 V. For

the sixteen pipe rigs used in this experimental, the measured potential difference between lead

and copper varied from 0.45 V to 0.49 V when filled with tap water. Since the potential

differences were quite close to the theoretical value, the potential difference (Ec - Ea) was the

considered the same for all pipe rigs.

For aged pipes, Rm, the resistance of the metallic portion of the galvanic cell can be important to

the galvanic action. The old lead pipes used in this experiment, whose age varied from 70 to 110

years old, were collected from residences in the City of London (Ontario). For pipes this old,

the inner surfaces where the metal and electrolyte meet surely have various forms of corrosion

products accumulated on them. The surface of pipe in contact with electrolyte is not just bare

lead but also various forms of corrosion products. Hence, the resistance of this corrosion scale

material also plays a role in galvanic corrosion in this study. No material characterization was

done for the scale on these pipes, so the compositions of the corrosion scale remained unknown.

However, the corrosion scale should consist of lead (II) oxides, lead (II) carbonates, and lead

(IV) oxides as these have been widely observed as corrosion scale buildup on pipe surfaces

(Schock et al., 2008). Since the spatial distribution and composition of the scales are not

uniform on the pipe surface, Rm should be different for each pipe rig.

Electrolyte, which was the synthetic water in this experiment, was different among different

pipe rigs, so Re should be different for each pipe rig. Therefore, both electrolyte chemical

properties (especially electrical conductivity) and the resistance of the metallic portion of the

galvanic cell could be responsible for the differences in galvanic current between pipe rigs. For

the current study, since resistance of the metallic portion of the galvanic cell could not be

measured, it is impossible to attribute measured differences in galvanic current in the different

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47

pipe rigs to exclusively electrolyte chemical properties; the metallic resistance would confound

the measurements.

5.2.2 Conductivity of Synthetic Water

Since the conductivity of synthetic water is important to Re, they were calculated.

κ = Σ αi λi Ci,

5-7

where κ is conductivity of the solution,

αi is fraction of the ith

constituent present as the free ion

λi is equivalent conductivity of the ith

ion,

Ci, is concentration of the ith

species.

with αi , being unity, implying complete dissociation, the conductivity of the synthetic water

were approximated using Equation 5-7 (Miller et al., 1988). The ion species involved in the

calculation and the total conductivity for each of the controlled parameter are listed in Table 5-8.

For all the waters, CSMR and pH were adjusted to 2.5 and 8.0 respectively. Hence the baseline

conductivity should be 88 µS/cm. For each of the five factors, there were two controlled levels

which resulted in a difference in ions present in water. When comparing the five factors,

alkalinity had the largest difference in conductivity (472 vs. 28 µS/cm) for its two levels. The

conductivity difference between the two levels of nitrate was 51 µS/cm. For the two types of

disinfectants, they would both decay to chloride and their contribution to conductivity (47 and

42 µS/cm) was about the same. Phosphate inhibitor brought a tiny amount of conductivity (21

µS/cm) to the water, whereas silicate inhibitor provided 60 µS/cm conductivity. In a previous

study (Rangsivek and Jekel, 2008), SNOM was found to have 300 µS/cm when pH = 5 and

DOC = 4.3 mg/L. For the two levels of SNOM (1 and 7 mg/L) in this study, conductivities were

assumed to be 200-300 and 300 to 400 µS/cm. Theoretically, the change in alkalinity should

impact on the conductivity the most, following by the change in SNOM, nitrate and inhibitor.

Disinfectant change should not impact the conductivity at all.

.

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48

Table 5-8: Conductivity approximation based on the major ion species in the water (equivalent

conductivity of ion (λi), data from (Harned and Owen, 1964))

Controlled

parameter

Controlled

level Ions

Concentration

(mg/L)

Milliequivalents

per liter

(meq/L)

Conductivity

(µS/cm)

Total

(µS/cm)

CSMR 2.5

K+ 8 0.21 15.43

SO42- 10 0.21 16.79

Na+ 16 0.44 22.03

Cl- 25 0.44 33.60

87.85

pH 8

H+

0.00001 0.0035

OH-

0.001 0.1985

0.20

Alkalinity

250 mg/L

CaCO3

Na+ 115.76 5 250.37

HCO3- 305 5 222.39

472.76

15 mg/L

CaCO3

Na+ 7 0.3 15.02

HCO3- 18.3 0.3 13.34

28.37

Nitrate

7 mg/L N Na+ 10.95 0.49 24.54

NO3- 30.8 0.49 34.97

59.51

1mg/L N Na+ 1.56 0.07 3.51

NO3- 4.4 0.07 5.00

8.50

Disinfectant

1 mg/L Cl2 free

chlorine residual

Na+

0.37 18.53

Cl-

0.37 28.25

46.78

3 mg/L Cl2

monochloramine

residual

H+

0.1 34.96

Cl-

0.1 7.64

42.60

Inhibitor

1 mg/L P

Na+ 2.26 0.065 3.25

H+ 0.032 0.032 11.19

PO43- 4.5 0.095 6.55

20.99

24 mg/L SiO2 Na+ 0.24 12.24

OH- 0.24 47.4

59.64

SNOM 7 mg/L DOC

300-400

1 mg/L DOC

200-300

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In the experiment, the conductivity of all synthetic water was measured and listed in Table 7-11.

With the minimum conductivity at 70 µS/cm and the maximum at 260 µS/cm, the entire

empirical data set were smaller when compared to the calculated values. This is because

complete dissociation was assumed in the calculation. As the half-normal plot of conductivity

(Figure 5-10: Half-normal plot of measured electric conductivity of synthetic waters)

suggested, alkalinity had the largest effect on conductivity, and disinfectant did not have any

effect on conductivity. The measured conductivity matched with theoretical approximation.

Figure 5-10: Half-normal plot of measured electric conductivity of synthetic waters

Design-Expert?SoftwareElectric conductivity of syntheic water

Shapiro-Wilk testW-value = 0.936p-value = 0.540A: AlkalinityB: SNOMC: NitrateD: DisinfectantE: Inhibitor

Positive Effects Negative Effects

Half-Normal Plot

Ha

lf-N

orm

al %

Pro

ba

bili

ty

|Standardized Effect|

0.00 36.17 72.34 108.52 144.69

0

10

20

30

50

70

80

90

95

99

A

B

C

D

E

BD

50

50

5.2.3 Significant Factors Affecting Galvanic Current

The experiment was run for 12 weeks. Preferential corrosion near the junction between

dissimilar metal is a characteristic of galvanic corrosion (Jones, 1996). Triantafylliou’s study

has shown 90-95% of the total galvanic current was dissipated in the small area adjacent to the

lead/copper joint (< 15 cm) (Triantafylliou, 2011). In this experiment, the current was measured

at 10 cm from the joint. In Figure 5-11, the weekly average galvanic current of all pipe rigs was

plotted with respect to time. It is observed that, the average galvanic current was almost constant

over the 12 weeks of the experiment

Figure 5-11: Temporal trend of average galvanic current. Note: the error bars represent one

standard deviation of n= 5. ALK= alkalinity (mg/L CaCO3), DOC= dissolved organic carbon

(mg/L), N= nitrate (mg/L N), OP = orthophosphate (mg/L P), Si = silicate (mg/L SiO2), C=

Chlorine residual (mg/L Cl2), MC = monochloramine residual (mg/L Cl2)

0

10

20

30

40

50

60

Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Week 9 Week 11Week 12

Ga

lva

nic

Cu

rre

nt (µ

A)

ALK15DOC7N1OP1C1 ALK250DOC1N1Si24MC3 ALK250DOC1N7Si24C1

ALK250DOC7N7Si24MC3 ALK250DOC7N1OP1MC3 ALK250DOC7N7OP1C1

Alk15DOC7N7OP1MC3 Alk250DOC1N7 OP1MC3 Alk15DOC1N7 Si24MC3

Alk15DOC7N7 Si24C1 Alk15DOC1N1 OP1MC3 Alk15DOC1N1 OP1MC3

Alk15DOC1N7 OP1C1 Alk250DOC7N1 Si24C1 Alk250DOC1N1 OP1C1

Alk15DOC1N1 Si24C1

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Analysis of variance (ANOVA) was used to determine the effect the water matrix components

on galvanic current. It was observed that alkalinity (A), disinfectant (D), inhibitor (E) and the

alkalinity-inhibitor (AE) interaction had statistically significant impacts. The ANOVA table and

is shown in Table 5-9: Analysis of variance table of galvanc current. The predicted vs. actual

plot is shown in Figure 5-12. The R2 for the ANOVA was 0.8327.

Table 5-9: Analysis of variance table of galvanc current

Source Sum of Squares df Mean Square F Value

p-value

Prob > F

Model 1214.186 8 151.7733 9.29063 0.0041

A-Alkalinity 698.0494 1 698.0494 42.73031 0.0003

B-SNOM 7.125563 1 7.125563 0.436183 0.5301

C-Nitrate 7.738829 1 7.738829 0.473724 0.5134

D-Disinfectant 195.0387 1 195.0387 11.93907 0.0106

E-Inhibitor 99.51309 1 99.51309 6.091582 0.0430

AE 113.7022 1 113.7022 6.960155 0.0335

Residual 114.3532 7 16.33616

Cor Total* 1328.539 15

Note: The Model F-value of 12.71 implies that the model is significant.

Value of "Prob > F" less than 0.0500 indicates that the model term is significant.

*= Total corrected for the mean

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Figure 5-12: Predicted and actual galvanic current (µA). The predicted values were calculated

using ANONA model.

As mentioned in Section 5.2.1, galvanic current depend on both Re and Rm, where Re mostly

depends on electrolyte conductivity. If the impact of Rm on galvanic current was relatively small

when compared to the impact of Re., then electrolyte conductivity would be directly related to

galvanic current. If the assumption is true, then based on the conductivity results in Section

5.2.2, alkalinity would have the largest impact on galvanic current, followed by nitrate, SNOM,

inhibitor, and the changes in disinfectant would not cause a change in galvanic current.

However, as can be observed in the ANOVA results, alkalinity still had the largest impact on

galvanic current, but both SNOM and nitrate had no significant impact on galvanic current.

Design-Expert?SoftwareAverage current

Color points by value ofAverage current :

39.9375

8.9525

Actual

Pre

dic

ted

Predicted vs. Actual

8.00

16.00

24.00

32.00

40.00

8.95 16.70 24.45 32.19 39.94

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Alkalinity is comprised primarily of bicarbonate, carbonate and hydroxide ions. At pH 8,

alkalinity is in the form of bicarbonate, which is a decent ion conductor. Therefore, higher

alkalinity produces higher conductivity. A positive correlation between alkalinity and solution

conductivity has previously been reported (Sechriest, 1960). Since electrolyte conductivity was

a primary driving force for galvanic current, high alkalinity level should give high galvanic

current. Hence, it was expected that when alkalinity changed from 15 mg/L to 250 mg/L CaCO3,

galvanic current should increase, as was observed (Figure 5-13). In a study by Triantafylliou

(2011), the galvanic current increased by up to 20% when alkalinity increased from 15 to 100

mg/L CaCO3. In this study, the current increased by 12 µA for the large increase in alkalinity

(15 to 250 mg/L CaCO3).

SNOM is a complex mixture of organic compounds with varying molecular sizes. Although it

showed an effect on conductivity, it did not affect galvanic current. No significant impact was

also reported by Arnold (2011). Conductivity was also shown to increase with increasing nitrate

(from 1 to 7 mg-N/L), but no impact was observed on galvanic current. Possible reasons for this

could be that the presence of SNOM and nitrate attacked the surface layer of lead pipe in which

various corrosion products formed and resided on the pipe surface. As Rm increased, the impact

on galvanic current due to decreasing Re was offset by increasing Rm. Hence, no significant

impact on galvanic current by SNOM and nitrate was seen in this study.

The disinfectant, regardless of whether it is in free chlorine or monochloramine form, decays to

chloride and forms some other compounds or ions along the way. In this study, since the

amount of conductivity provided by both free chlorine and monochloramine was about the

same, the disinfectant did not impact on conductivity significantly. It was expected that galvanic

current for the two types of disinfectants would be about the same. However, as disinfectant

changed from free chlorine to monochloramine, average galvanic current increased from 16 to

22 µA (Figure 5-14). The choice of disinfectant can change the ORP of the water which leads to

the formation of different lead complexes. Rm changed and affected the galvanic current.

Two types of inhibitor were compared in this study, 1 mg-P /L orthophosphate and 24 mg-

SiO2/L silicate. Their impact on galvanic current matched their impact on conductivity. As

silicate provided a higher conductivity to the water, silicate-treated water also gave a higher

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galvanic current. The average galvanic current in the presence of 24 mg-SiO2/L silicate (22 µA)

was higher than 1 mg/L P orthophosphate (17 µA) (Figure 5-15).

Figure 5-13: The impact of alkalinity on galvanic current. Note: the error bar represents 95%

confidence interval.

Design-Expert?Software

Average current (uA)

X1 = A: Alkalinity

Actual Factors

B: SNOM = 4.00

C: Nitrate = 4.00

D: Disinfectant = Average

E: Inhibitor = Average

15.00 73.75 132.50 191.25 250.00

8

16

24

32

40

A: Alkalinity

Avera

ge c

urr

ent

(uA

)

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55

Figure 5-14: The impact of disinfectant on galvanic current. Note: the error bar represents 95%

confidence interval



X1 = D: Disinfectant

Actual Factors

A: Alkalinity = 132.50

B: SNOM = 4.00

C: Nitrate = 4.00

E: Inhibitor = Average

D: Disinfectant

Avera

ge c

urr

ent

(uA

)

free chlorine 1 mg/L monochloramine 3 mg/L

8

16

24

32

40

56

56

Figure 5-15: The impact of inhibitor on galvanic current. Note: the error bar represents 95%

confidence interval



X1 = E: Inhibitor

Actual Factors

A: Alkalinity = 132.50

B: SNOM = 4.00

C: Nitrate = 4.00


E: Inhibitor

Avera

ge c

urr

ent

(uA

)

orthophosphate 1 mg/L P silicate 24 mg/L SiO2

8

16

24

32

40

57

57

The interaction between alkalinity and inhibitor also significantly affected galvanic current

(Figure 5-16). At the low alkalinity (15 mg/L CaCO3), there was little difference in the galvanic

current in waters treated with silicate or orthophosphate, but at the higher alkalinity (250 mg/L

CaCO3), the silicate-treated water showed a significantly higher galvanic current than the

orthophosphate-treated water.

Figure 5-16: The impact of alkalinity and inhibitor interaction to galvanic current. Note: the

error bar represents 95% confidence interval

In summary, alkalinity (A), disinfectant (D), inhibitor (E) and the alkalinity-inhibitor (AE)

interaction significantly impacted galvanic current. Since galvanic current can lead to galvanic

corrosion, low alkalinity (15 mg/L CaCO3), free chlorine disinfectant and orthophosphate

inhibitor can help to restrain galvanic corrosion.



E1 orthophosphate 1 mg/L P

E2 silicate 24 mg/L SiO2

X1 = A: Alkalinity

X2 = E: Inhibitor

Actual Factors

B: SNOM = 4.00

C: Nitrate = 4.00


E: Inhibitor

15.00 73.75 132.50 191.25 250.00

Interaction

A: Alkalinity

Avera

ge c

urr

ent

(uA

)

8

16

24

32

40

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5.3 Water Quality Factors Affecting Total Lead Release after Partial Lead Pipe

Replacement

The pipe rig apparatus was run for 12 weeks to measure total and dissolved lead release, along

with the galvanic current discussed in the previous section. There was some instability in Weeks

1-3, assumed to be due to conditioning, so the lead data for Weeks 1-3 were not included in the

ANOVA analysis of the impact of water quality factors on measured lead

The total lead release data (including Weeks 1-3) are shown in Figure 5-17. For the ANOVA,

each week’s lead data was treated as a replicate (from Week 4 to Week 12 but excluding Week

10 where the wire connection between the copper and lead pipe segments was disconnected for

quality control testing). The significant factors affecting total lead release were alkalinity (A),

SNOM (B), disinfectant (D), interaction of alkalinity-inhibitor (AE), interaction of SNOM-

nitrate (BC), interaction of SNOM-disinfectant (BD), interaction of SNOM-inhibitor (BE),

interaction of nitrate-disinfectant (CD) and interaction of disinfectant-inhibitor (DE). The

ANOVA table and half-normal plot are shown in Table 5-10 and Figure 5-18: Half-normal plot

of total lead. The model predicted vs. actual measurements plot is shown in Figure 5-19:

Predicted and actual total lead release. The R2 for the model was 0.6448.

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Figure 5-17: Temporal trend of total lead release Note: ALK= alkalinity (mg/L CaCO3), DOC=

dissolved organic carbon (mg/L), N= nitrate (mg/L N), OP = orthophosphate (mg/L P), C=

chlorine residual (mg/L), Si = silicate (mg/L), MC = monochloramine residual (mg/L)

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

Week 4 Week 5 Week 6 Week 7 Week 8 Week 9 Week 11 Week 12

To

tal l

ea

d (µ

g/L

)ALK15DOC7N1OP1C1

ALK250DOC1N1Si24MC3ALK250DOC1N7Si24C1

ALK250DOC7N7Si24MC3 ALK250DOC7N1OP1MC3ALK250DOC7N7OP1C1

Alk15DOC7N7OP1MC3

Alk250DOC1N7 OP1MC3Alk15DOC1N7 Si24MC3

Alk15DOC7N7 Si24C1

Alk15DOC7N1 Si24MC3

Alk15DOC1N1 OP1MC3

Alk15DOC1N7 OP1C1

Alk250DOC7N1 Si24C1

Alk250DOC1N1 OP1C1

Alk15DOC1N1 Si24C1

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Figure 5-18: Half-normal plot of total lead


W4-W12 Total lead

Error from replicates

Shapiro-Wilk test

W-value = 0.913

p-value = 0.487

A: Alkalinity

B: SNOM

C: Nitrate

D: Disinfectant

E: Inhibitor

Positive Effects

Negative Effects

Half-Normal Plot

Half-N

orm

al %

Pro

bability


0.00 524.38 1048.76 1573.14 2097.52

0.0

10.0

20.0

30.0

50.0

70.0

80.0

90.0

95.0

99.0

99.9

A

B

C

D

E

AEBC

BD

CD

DE

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Table 5-10: Analysis of variance table of total lead

Source Sum of Squares df Mean Square F Value

p-value

Prob > F

Block 57448880 7 8206983

Model 6.55E+08 11 59560030 17.99 < 0.0001

A-Alkalinity 58863188 1 58863188 17.78 < 0.0001

B-SNOM 40610969 1 40610969 12.26 0.0007

C-Nitrate 2904480 1 2904480 0.87 0.3510

D-Disinfectant 1.41E+08 1 1.41E+08 42.52 < 0.0001

E-Inhibitor 11197433 1 11197433 3.38 0.0686

AE 35215529 1 35215529 10.63 0.0015

BC 44295897 1 44295897 13.38 0.0004

BD 77405681 1 77405681 23.38 < 0.0001

BE 35110704 1 35110704 10.60 0.0015

CD 1.28E+08 1 1.28E+08 38.52 < 0.0001

DE 81251654 1 81251654 24.54 < 0.0001

Residual 3.61E+08 109 3310356

Cor Total* 1.07E+09 127

Note: The Model F-value of 17.99 implies the model is significant.

Value of "Prob > F" less than 0.0500 indicate model terms are significant.

*= Total corrected for the mean

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62

Figure 5-19: Predicted and actual total lead release

It was previously shown that an increase in alkalinity increased the galvanic current. Logically,

this should result in an increase in lead release. In contrast, however, the increase in alkalinity

(15 to 250 mg/L CaCO3) was shown to reduce the average total lead leaching from the pipes,

from 4400 to 3083 µg/L, as shown in Figure 5-20. It is possible that effect of increase in

alkalinity to increase the galvanic current was offset by the greater alkalinity (and dissolved

inorganic carbon) suppressing lead release through direct chemical means. Arnold (2011) also

reported a reduced lead release with high alkalinity. It is known that water with a high alkaliniy

favors the formation of lead (II) carbonate cerussite (PbCO3) and hydrocarnoate hydrocerussite

(Pb3(CO3)2(OH)2) which are less soluble forms of lead (Kim and Herrera, 2010).

Alkalinity was also observed to have an interaction effect with corrosion inhibitor (Figure 5-21).

Silicate inihbitor and orthophosphate inhibitor had opposite impacts on the effect of alkalinity

on total lead release as the crossing lines suggest in Figure 5-21. At the low alkalinity (15 mg/L

Design-Expert?SoftwareW4-W12 Total lead

Color points by value ofW4-W12 Total lead:

13000

360

Actual

Pre

dic

ted


-2000

1750

5500

9250

13000

-1261.57 2303.82 5869.21 9434.61 13000.00

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63

CaCO3), the average total lead release was 4660 µg/L and 4210 µg/L in the presence of

orthophosphate and silicate respectively. At the high alkalinity (250 mg/L CaCO3), the average

total lead release was 2260 µg/L and 3910 µg/L in the presence of orthophosphate and silicate

respectively. Silicate had about the same amount of total lead release at the two alkalinity levels.

It therefore undermined the beneficial impact of inorganic carbon on total lead release. Possible

reasons could be that the silicate’s protective films on the pipe surfaces were a strong barrier

which blocked the chemical reactions between lead and inorganic carbon. Therefore, the

average total lead leaching was about the same in the presence of silicate inhibitor regardless the

alkalinity level. The addition of orthophosphate showed no impact on lead release at the low

alkalinity, but reduced total lead release at the high alkalinity. Arnold (2011) also observed

silimiar trends in the presence of orthophosphate inhibitors. It is known that orthophosphate lead

solids such as hydroxypyromorphite [Pb5 (PO4)3OH] and tertiary lead orthophosphate [Pb3

(PO4)2] are less soluble than lead carbonate such as PbCO3 (Schock, 1989). It is apparent that

the addition of orthophosphate which leads to the formation of lead phosphate solids scale

should help to reduce total lead release. Therefore, orthophosphate is a better inhibitor for total

lead release than silicate.

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Figure 5-20: The impact of alkalinity on total lead release. Note: the error bar represents 95%

confidence interval


W4-W12 Total lead

X1 = A: Alkalinity

Actual FactorsB: SNOM = 4.00C: Nitrate = 4.00D: Disinfectant = AverageE: Inhibitor = Average

15.00 73.75 132.50 191.25 250.00

0

1500

3000

4500

6000

A: Alkalinity

W4

-W1

2 T

ota

l le

ad

One Factor

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65

Figure 5-21: The impact of interaction of alkalinity and inhibitor on total lead release. Note: the



W4-W12 Total lead

E1 orthophosphate 1 mg/L PE2 silicate 24 mg/L SiO2

X1 = A: AlkalinityX2 = E: Inhibitor

Actual FactorsB: SNOM = 4.00C: Nitrate = 4.00D: Disinfectant = Average

E: Inhibitor

15.00 73.75 132.50 191.25 250.00

Interaction

A: Alkalinity

W4

-W1

2 T

ota

l le

ad

0

1500

3000

4500

6000

66

66

It was previously shown that Suwanee River natural organic matter (SNOM) had no impact on

galvanic current. In contrast, as SNOM increased from 1 mg/L DOC to 7 mg/L DOC, the

average total lead release increased from 3198 µg/L to 4325 µg/L (Figure 5-22). Lead release is

a complex phenomenon which involves many mechanisms, and galvanic corrosion is only one

of them. While SNOM did not affect galvanic corrosion, it affected lead release signifcantly. It

is believed that SNOM can introduce an amorphous hydrated surface layer to pipe walls which

leads to a higher rate of oxidation on the lead surface, resulting in higher lead release (Korshin

et al., 2000). Lin and valentine (2008) showed that the extent of lead release increased with

increasing NOM concentration.

The impact of SNOM on lead release also depended on nitrate, disinfectant and inhibitor. At 7

mg-N/L nitrate, when the SNOM concentration increased, there was no significant change for

the average lead release, but for 1 mg-N/L nitrate, when the SNOM concentration increased, the

average lead release almost doubled (Figure 5-23). Uchida and Okuwakin (1999) have shown

that nitrate can attack lead-bearing material by destroying its passive layer. When both SNOM

and nitrate are present in the water, it was possible that nitrate attacks the amorphous hydrated

surface layer which SNOM tends to form. Thus, when the concentration of nitrate is high, the

tendency for SNOM to suppress lead release is lowered.

As seen in the half-normal plot (Figure 5-18), the standardized effect of disinfectant was much

higher than SNOM and the interaction of SNOM-disinfectant. Hence, the impact of SNOM-

disinfectant interaction on total lead release was dominated by the impact of disinfectant. Hence,

under the impact of disinfectant, the impact of SNOM was not obvious. In Figure 5-24, the

average total lead release was much higher in the presence of monochloramine than the average

total lead release in the presence of free chlorine for all concentrations of SNOM. The average

total lead release was statistically the same for different SNOM concentrations with

monochloramine. In the presence of 1 mg/L Cl2 free chlorine residual, the average total lead

release increased dramatically from 1372 µg/L to 4050 µg/L (Figure 5-24). This was because

for higher level of SNOM, a higher initial chlorine dosage was applied to the water (2.73 mg/L

Cl2 for SNOM at 1 mg/L and 13.97 mg/L Cl2 for SNOM at 7 mg/L) to leave a sufficient residual

in the water. Chlorine eventually was reduced to chloride ion, and it is possible that the greater

concentration of chloride ions caused more pipe deterioration. Furthermore, SNOM was shown

67

67

to be able to reduce PbO2 (s) to Pb2+

(Boyd et al., 2010) and the formation and stability of PbO2

is greatly dependant on the presence of free chlorine. Hence, in the presence of free chlorine,

total lead release should increase as SNOM increases.

The impact of SNOM was observed to be different depending on the corrosion inhibitors present

(Figure 5-25: The impact of interaction of SNOM and inhibitor on total lead release. Note:

the error bars represent 95% confidence interval). Orthophosphate appeared to nullify any

impact of SNOM on total lead release, with lead measurements similar regardless of the amount

of SNOM in the presence of orthophosphate. With silicate present, however, there was more

total lead (approximately 5100 µg/L), at the higher SNOM values. As described earlier, it has

been observed that SNOM, alone, tends to lead to more lead release. This interaction result

suggests that silicate does nothing to modify this phenomenon, whereas orthophosphate acts to

inhibit the detrimental effect of SNOM on total lead release. As such, orthophosphate would be

the superior corrosion inhibitor under these circumstances.

Figure 5-22: The impact of SNOM on total lead release. Note: the error bar represents 95%

confidence interval


W4-W12 Total lead

X1 = B: SNOM

Actual FactorsA: Alkalinity = 132.50C: Nitrate = 4.00D: Disinfectant = AverageE: Inhibitor = Average

1.00 2.50 4.00 5.50 7.00

0

1500

3000

4500

6000

B: SNOM

W4

-W1

2 T

ota

l le

ad

68

68

Figure 5-23: The impact of interaction of SNOM and nitrate on total lead release. Note: the



W4-W12 Total lead

C- 1.000C+ 7.000

X1 = B: SNOMX2 = C: Nitrate

Actual FactorsA: Alkalinity = 132.50D: Disinfectant = AverageE: Inhibitor = Average

C: Nitrate

1.00 2.50 4.00 5.50 7.00

Interaction

B: SNOM

W4

-W1

2 T

ota

l le

ad

0

1500

3000

4500

6000

69

69

Figure 5-24: The impact of interaction of SNOM and disinfectant on total lead release. Note:

the error bars represent 95% confidence interval


W4-W12 Total lead

D1 free chlorine 1 mg/LD2 monochloramine 3 mg/L

X1 = B: SNOMX2 = D: Disinfectant

Actual FactorsA: Alkalinity = 132.50C: Nitrate = 4.00E: Inhibitor = Average

D: Disinf ectant

1.00 2.50 4.00 5.50 7.00

Interaction

B: SNOM

W4

-W1

2 T

ota

l le

ad

0

1500

3000

4500

6000

70

70

Figure 5-25: The impact of interaction of SNOM and inhibitor on total lead release. Note: the

error bars represent 95% confidence interval


W4-W12 Total lead


X1 = B: SNOMX2 = E: Inhibitor

Actual FactorsA: Alkalinity = 132.50C: Nitrate = 4.00D: Disinfectant = Average

E: Inhibitor

1.00 2.50 4.00 5.50 7.00

Interaction

B: SNOM

W4

-W1

2 T

ota

l le

ad

0

1500

3000

4500

6000

71

71

The choice of disinfectant plays a very important role in lead corrosion, as it had the largest

standardized effect on the half-normal plot. The effect of free chlorine versus monochloramine

on total lead release is shown in Figure 5-27. On average, more total lead was observed when

monochloramine was applied than free chlorine (4830 versus 2713 µg/L). Many common

oxidants in water such as dissolved oxygen, chlorine or chloramines can oxidize lead metal to

Pb (II) species (Figure 5-26). These Pb (II) species can then react with inorganic species or

NOM to form various complexes, either as corrosion scale or precipitate in the water (Boyd et

al., 2010). Pb (II) species can be further oxidized to Pb (IV) species under high ORP conditions.

Researches has observed reduction of PbO2(s) to PbCO3(s), showing that the oxidation of Pb (II)

is reversible under low ORP conditions (Lytle and Shock, 2005).

Figure 5-26: Conceptual scheme of reactions involving Pb(II) and Pb(IV) species in the

presence of free chlorine (adjusted from Boyd et al., 2010)

Disinfectants, as oxidants, are closely related to the oxidation-reduction potential (ORP). As

shown in Figure 5-28, the ORP was much higher in the presence of free chlorine than

monochloramine by about 720 versus 470 mV, respectively. It is known that free chlorine is the

only common secondary disinfectant that can provide high enough ORP in the water for Pb (IV)

solids to form. The presence of Pb (IV) can greatly reduce lead release due to the extremely low

solubility of Pb (IV) solids compared to Pb (II) solids.

Total lead release was also affected by the interaction between disinfectants and nitrate. A

previous study showed that in the presence of nitrate, lead corrosion became more pronounced

(Uchida and Okuwakin, 1999). Two types of nitrate, NaNO3 and NH4NO3, demonstrated

different mechanisms for the dissolution of lead (Uchida and Okuwakin, 1999). Upon the

72

72

addition of NaNO3, the lead surface was smooth and no grains were observed. On the other

hand, many cracks were observed on the surface of the lead when NH4NO3 was in the water

(Uchida and Okuwakin, 1999). It is believed that the later morphology of the corroded surface

makes it easier for the nitrate ion to attack the lead matrix. Therefore, the dissolution rate of lead

in NaNO3 water was much slower than that in NH4NO3 water. For the current study, when both

monochloramine and nitrate were present in water, the existence of NH4NO3 was possible since

monochloramine decayed into ammonia and chloride. Therefore, nitrate addition should further

increase the total lead difference between free chlorine and monochloramine. With nitrate at 7

mg-N/L, the total lead release increased dramatically from 1900 to 6000 µg/L as the disinfectant

changed from free chlorine to monochloramine (Figure 5-29). This observation reinforces the

findings of Nguyen et al. (2011c), who discovered that lead release increased by 2 orders of

magnitude as nitrate increased from 1.25 to 5 mg-N/L from solder coupons with

monochloramine. However, at nitrate at 1 mg-N/L, the total lead release was shown to be the

same for both disinfectants, which was unexpected. This phenomenon cannot be explained

based on the current understanding on lead release. More research should be done with various

concentrations of nitrate to collect more observations.

The impact of disinfectant was observed to be different depending on the corrosion inhibitors

present. In the presence of 1 mg-Cl2 /L free chlorine residual, total lead in water with

orthophosphate and silicate inhibitor were 3200 versus 2200 µg/L, respecvtively. In the

presence 3 mg-Cl2 /L monochloramine residual, total lead in the water with orthophosphate and

silicate inhibitor was 3700 and 5910 µg/L, respecvtively. Orthophosphate was a superior choice

in the presence of monochloramine (Figure 5-30). Arnold (2011) also showed that

orthophosphate would reduce galvanic corrosion in waters with monochloramine. The reason

that orthophosphate does not perform well in chlorinated water is because orthophosphate

inhibits the formation of Pb (IV) as per prior experimental results (Lytle et al, 2009). Hence,

silicate inhibitor works better with free chlorine, whereas orthophosphate silicate inhibitor

works better with monochloramine.

73

73

Figure 5-27: The impact of disinfectant on total lead release. Note: the error bar represents

95% confidence interval


W4-W12 Total lead X1 = D: Disinfectant

Actual FactorsA: Alkalinity = 132.50B: SNOM = 4.00C: Nitrate = 4.00E: Inhibitor = Average

D: Disinf ectant

W4

-W1

2 T

ota

l le

ad


0

1500

3000

4500

6000

74

74

Figure 5-28: ORP comparisons between free chlorine and monochloramine


ORP (mV) X1 = D: Disinfectant

Actual FactorsA: Alkalinity = 132.50B: SNOM = 4.00C: Nitrate = 4.00E: Inhibitor = Average

D: Disinf ectant

OR

P (

mV

)


0

182.5

365

547.5

730

75

75

Figure 5-29: The impact of interaction of nitrate and disinfectant on total lead release. Note:

the error bars represent 95% confidence interval


W4-W12 Total lead

C- 1.000C+ 7.000

X1 = D: DisinfectantX2 = C: Nitrate

Actual FactorsA: Alkalinity = 132.50B: SNOM = 4.00E: Inhibitor = Average

C: Nitrate


Interaction

D: Disinf ectant

W4

-W1

2 T

ota

l le

ad

0

1625

3250

4875

6500

76

76

Figure 5-30: The impact of interaction of disinfectant and inhibitor on total lead release. Note:

the error bar represents 95% confidence interval


W4-W12 Total lead


X1 = D: DisinfectantX2 = E: Inhibitor

Actual FactorsA: Alkalinity = 132.50B: SNOM = 4.00C: Nitrate = 4.00

E: Inhibitor


Interaction

D: Disinf ectant

W4

-W1

2 T

ota

l le

ad

0

1588.47

3176.94

4765.41

6353.88

77

77

5.4 Water Quality Factors Affecting Dissolved Lead Release after Partial Lead Pipe

Replacement

The pipe rig apparatus was run for 12 weeks. While total lead was measured every week, as

discussed in the previous section, dissolved lead was measured only on Week 3, 6, 9, and 12.

Soluble lead was operationally defined by filtration through a 0.45 um pore size syringe filter.

Since colloidal species can sometimes pass through this filter (Edward and McNeill, 2002), the

filtration approach represents an upper bound to truly soluble lead. The results are shown in

Figure 5-31. Typically, the dissolved lead concentration was approximately 5-20% of the total

lead, with particulate lead (> 45 µm) forming the majority of the total lead. There was no strong

trend in dissolved lead with time over the 12 weeks. As such, dissolved lead data of Week 6, 9,

and 12 were treated as replicates for the ANOVA. The significant factors affecting dissolved

lead release according to the ANOVA were alkalinity (A), SNOM (B), nitrate (C), inhibitor (E),

interaction of alkalinity-nitrate (AC) and interaction of alkalinity-inhibitor (AE). The ANOVA

table and half-normal plot are shown in Table 5-11 and Figure 5-23, respectively. The predicted

data versus actual data plot is shown in Figure 5-33. The model R2 was 0.8695.

Table 5-11: Analysis of variance table of dissolved lead

Source Sum of Squares

df Mean Square F Value

p-value

Prob > F

Block 6654.16 2 3327.083

Model 3441485 9 382387.3 35.21 < 0.0001

A-Alkalinity 708102.1 1 708102.1 65.21 < 0.0001

B-SNOM 989002.1 1 989002.1 91.08 < 0.0001

C-Nitrate 271502.1 1 271502.1 25 < 0.0001

D-Disinfectant 2002.08 1 2002.083 0.18 0.6702

E-Inhibitor 305602.1 1 305602.1 28.14 < 0.0001

AC 312018.8 1 312018.8 28.73 < 0.0001

AE 618802.1 1 618802.1 56.98 < 0.0001

Residual 390908.3 36 10858.56 Cor Total 3.839E+006 47

78

78

Figure 5-31: Temporal trend of dissolved lead release. Note: ALK= alkalinity (mg/L CaCO3),

DOC= dissolved organic carbon (mg/L), N= nitrate (mg/L N), OP = orthophosphate (mg/L P),

C= chlorine residual (mg/L), Si= silicate (mg/L), MC= monochloramine residual (mg/L)

0

200

400

600

800

1000

1200

1400

Week 3 Week 6 Week 9 Week12

Dis

so

lve

d L

ea

d (µ

g/L

)

ALK15DOC7N1OP1C1 ALK250DOC1N1Si24MC3 ALK250DOC1N7Si24C1

ALK250DOC7N7Si24MC3 ALK250DOC7N1OP1MC3 ALK250DOC7N7OP1C1

Alk15DOC7N7OP1MC3 Alk250DOC1N7 OP1MC3 Alk15DOC1N7 Si24MC3

Alk15DOC7N7 Si24C1 Alk15DOC7N1 Si24MC3 Alk15DOC1N1 OP1MC3

Alk15DOC1N7 OP1C1 Alk250DOC7N1 Si24C1 Alk250DOC1N1 OP1C1

Alk15DOC1N1 Si24C1

79

79

Figure 5-32: Half-normal plot of dissolved lead


W6.W9, W12 Dissolved lead

Error from replicates

Shapiro-Wilk test

W-value = 0.911

p-value = 0.364

A: Alkalinity

B: SNOM

C: Nitrate

D: Disinfectant

E: Inhibitor

Positive Effects

Negative Effects

Half-Normal Plot

Half-N

orm

al %

Pro

bability


0.00 71.77 143.54 215.31 287.08

0

10

20

30

50

70

80

90

95

99

A

B

C

D

EAC

AE

80

80

Figure 5-33: Predicted and actual values of dissolved lead release

The trend of dissolved lead with respect to alkalinity was the same as previously described for

total lead, with the average dissolved lead decreasing (from 339 to 96 µg/L) upon an increase in

alkalinity from 15 to 250 mg/L CaCO3 (Figure 5-34). Alkalinity or inorganic carbon and pH are

closedly relately to the solubility of lead. At pH less than 6, lead can be released in the form of

Pb2+

in water (Figure 5-35: Eh-pH diagram for the Pb-CO3-H2O system at 25° C and 1 atm

(adjusted from Scheetz, 2004)). When alkalinity was high (250 mg/L CaCO3), the pH had less

chance to drop due to the strong buffer presence. Therefore, less soluble lead was leached.

Nitrate was a significant factor affecting dissloved lead, despite not having an observed impact

on galvanic corrosion or total lead release. As nitrate increased from 1 mg/L N to 7 mg/L N, the

average dissloved lead decreased from 292 to 142 µg/L (

Design-Expert?SoftwareW6.W9, W12 Dissolved lead

Color points by value ofW6.W9, W12 Dissolved lead:

1290

0

Actual

Pre

dic

ted


-200.00

175.00

550.00

925.00

1300.00

-165.83 198.12 562.08 926.04 1290.00

81

81

Figure 5-36). Nitrate can oxidize metallic lead to lead oxide, therefore, a higher level of nitrate

resulted in less soluble lead in the water (Woszczynski, 2011)

Pb+ NO3- → NO2

- + PbO

5-8

The decreased dissolved lead release with increasing nitrate was only observed for the low

alkalnity level, however at the higher alkalinity, dissolved lead release was the same for both

nitrate levels (Figure 5-37). Because at high level of alkalinity (250 mg/L CaCO3), lead

carbonates are easier to form than lead oxides, the effect of nitrate to soluble lead release was

presumably weakened.

Figure 5-34: The impact of alkalinity on dissolved lead release. Note: the error bar represents




X1 = A: Alkalinity

Actual FactorsB: SNOM = 4.00C: Nitrate = 4.00D: Disinfectant = AverageE: Inhibitor = Average

15.00 73.75 132.50 191.25 250.00

0

150

300

450

600

A: Alkalinity

W6

.W9

, W1

2 D

isso

lve

d le

ad

One Factor

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82

Figure 5-35: Eh-pH diagram for the Pb-CO3-H2O system at 25° C and 1 atm (adjusted from

Scheetz, 2004)

Figure 5-36: The impact of nitrate on dissolved lead release. Note: the error bar represents 95%

confidence interval



X1 = C: Nitrate

Actual FactorsA: Alkalinity = 132.50B: SNOM = 4.00D: Disinfectant = AverageE: Inhibitor = Average

1.00 2.50 4.00 5.50 7.00

0

150

300

450

600

C: Nitrate

W6

.W9

, W1

2 D

isso

lve

d le

ad

One Factor

83

83

Figure 5-37: The impact of interaction between alkalinity and nitrate on dissolved lead release.

Note: the error bar represents 95% confidence interval



C- 1.000C+ 7.000

X1 = A: AlkalinityX2 = C: Nitrate

Actual FactorsB: SNOM = 4.00D: Disinfectant = AverageE: Inhibitor = Average

C: Nitrate

15.00 73.75 132.50 191.25 250.00

Interaction

A: Alkalinity

W6

.W9

, W1

2 D

isso

lve

d le

ad

0

150

300

450

600

84

84

The average dissolved lead release in the presence of 24 mg/L SiO2 silicate was approximately

half that observed in the presence of 1 mg/L P orthophosphate (Figure 5-38). This was

especially true for the low alkalinity conditions (Figure 5-39), where given 15 mg/L CaCO3 of

alkalinity, the average dissolved lead release was 145 µg/L for 24 mg/L SiO2 silicate and was

532 µg/L for 1 mg/L P orthophosphate (Figure 5-39). With 250 mg/L CaCO3 alkalinity, there

was essentially no difference in dissolved lead release between the silicate and the

orthophosphate. Since orthophosphate hinders the formation of Pb (IV) solids which are the

least soluble corrosion by-products (Lytle et al, 2009), more soluble lead is more likely to be in

the water. Many previous studies showed orthophosphate as a superior inhibitor when compared

to sodium silicate for lead corrosion control, but since they only measured total lead, the fact

that orthophosphate might lead to more dissolved lead release in the water was overlooked.

Figure 5-38: The impact of inhibitor on dissolved lead release. Note: the error bar represents



W6.W9, W12 Dissolved lead X1 = E: Inhibitor

Actual FactorsA: Alkalinity = 132.50B: SNOM = 4.00C: Nitrate = 4.00D: Disinfectant = Average

E: Inhibitor

W6

.W9

, W1

2 D

isso

lve

d le

ad

One Factor

orthophosphate 1 mg/L P silicate 24 mg/L SiO2

0

150

300

450

600

85

85

Figure 5-39: The impact of interaction between alkalinity and inhibitor on dissolved lead

release. Note: the error bar represents 95% confidence interval




X1 = A: AlkalinityX2 = E: Inhibitor

Actual FactorsB: SNOM = 4.00C: Nitrate = 4.00D: Disinfectant = Average

E: Inhibitor

15.00 73.75 132.50 191.25 250.00

Interaction

A: Alkalinity

W6

.W9

, W1

2 D

isso

lve

d le

ad

0

150

300

450

600

86

86

SNOM had a detrimental effect on total lead release as mentioned previously. It was also

observed to promote dissloved lead release. When SNOM increased from 1 mg/L DOC to 7

mg/L DOC, average dissovled lead release increased from 74 µg/L to 360 µg/L (Figure 5-40).

This is likely because SNOM was shown to be able to reduce PbO2 (s) to Pb2+

(Boyd et al.,

2010).

Figure 5-40 : The impact of SNOM on dissolved lead release. Note: the error bars represent




X1 = B: SNOM

Actual FactorsA: Alkalinity = 132.50C: Nitrate = 4.00D: Disinfectant = AverageE: Inhibitor = Average

1.00 2.50 4.00 5.50 7.00

0

150

300

450

600

B: SNOM

W6

.W9

, W1

2 D

isso

lve

d le

ad

One Factor

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87

5.5 Galvanic Current and Lead Release Relationship

Figure 5-41: Correlation of galvanic current to total lead release during Week 4 to Week 12

The correlation coefficient (R2) between galvanic current and total lead release in the pipe rigs

was only 0.15 in this experiment, as shown in Figure 5-41. As previously mentioned, lead

release due to galvanic corrosion is theoretically dependent on galvanic current. Lead release is

also affected by the release of lead scale, electrolyte behavior, etc. The lead corrosion

attributable to galvanic current could also form lead rust on the pipe wall instead of being

released to the water. Triantafyllidou (2009) reported a correlation coefficient of 0.12 with low-

CSMR (0.2) water and 0.44 with high-CSMR (16.2) water. Hence, the correlation between

galvanic current and total lead release from aged lead pipe is poor due to the complex nature of

lead release.

R² = 0.1521

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

0 10 20 30 40 50

To

tal l

ea

d (µ

g/L

)

Galvanic Current (µA)

88

88

Figure 5-42: Demonstrating galvanic relationship between predicted (calculated using current

values) vs. actual total lead leaching

In theory, for every pair of electrons removed from lead by galvanic current, one lead molecule

can be corroded and potentially released to water. Current was measured and assumed to stay

constant during the 48 hours stagnation period, allowing lead leached from galvanic action to be

predicted using the Equation 2-5. Maximum lead leaching versus actual lead concentration was

plotted in Figure 5-42. Hypothetically, lead leaching is directly proportional to the current

flowing between the metals. When results were compared across the wide range of experiments

performed regardless water chemistry conditions, actual lead leaching was equal to or greater

than predicted in most cases. This is possible since lead release can be due to reasons (i.e.

particle detachment, dissolution) other than galvanic corrosion.

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

0 2000 4000 6000 8000 10000

Ac

tua

l to

tal le

ad

re

lea

se

(µ

g/L

)

Predicted maxmium total lead release (µg/L)

1:1 line for relationship

89

89

Figure 5-43: Comparison of total lead release from galvanically connected pipe rigs and

galvancially disconnected pipe rigs. Note: The galvanically connected lead release values were

average total lead release from Week 4 to Week 12. The error bar represents one standard

deviation of n=8. The galvanically disconnected lead release values were total lead release in

Week 10.

The entire experiment lasted for 12 weeks. There were external wires connecting lead and

copper pipes at all times except for Week 10. In Week 10, there was no direct galvanic

corrosion due to the removal of the external wires. As shown in Figure 5-43, Figure 5-44, lead

release with galvanic corrosion was mostly higher when compared to the one without galvanic

corrosion. The differences between blue and red bars indicated the amount of lead release due to

galvanic corrosion and the size of the differences depended on the water chemistry.

0

2000

4000

6000

8000

10000

12000T

ota

l le

ad

re

lea

se

(µ

g/L

)Galvanically connected Galvanically disconnected

90

90

Figure 5-44: Comparison of dissolved lead release from galvanically connected pipe rigs and

galvancially disconnected pipe rigs. Note: The galvanically connected lead release values were

the average of dissolved lead release of Week 6, 9 and 12. The error bar represents one standard

deviation of n=3. The galvanically disconnected lead release values were dissolved lead release

in Week 10.

0

200

400

600

800

1000

1200

1400D

iss

olv

ed

lea

d (µ

g/L

)Galvanically connected Galvanically disconnected

91

91

5.6 Conclusions

Galvanic corrosion, as one of the mechanisms of both total and dissolved lead release, depends

on water chemistry. Certain waters may be able to minimize the lead release. The significant

factors observed for total lead release, dissolved lead release and galvanic current are listed in

the table below.

Table 5-12: Summary table of significant factors

Factor Total lead Dissolved lead Galvanic Current

A (Alkalinity)

B (SNOM)

C (Nitrate)

D(Disinfectant)

E (Inhibitor)

AB

AC

AD

AE

BC

BD

BE

CD

CE

DE

Alkalinity and its interaction with corrosion inhibitor were very important for controlling

galvanic corrosion and lead release. Many previous studies showed orthophosphate as a superior

inhibitor when compared to sodium silicate for lead corrosion control. For total lead release, this

study also showed orthophosphate had better performance over sodium silicate. However, the

observation that dosing of orthophosphate inhibitor can actually lead to more dissolved lead

release than sodium silicate should raise concerns.

92

92

Table 5-13: Performance comparison of corrosion inhibitor

Total lead Dissolved lead

High alkalinity same silicate is better

Low alkalinity orthophosphate is better same

The presence of SNOM had an overall detrimental effect on both total and dissolved lead

release. In the presence of free chlorine, total lead release increased as SNOM level increased.

Orthophosphate acted to inhibit the detrimental effect of SNOM on total lead release.

Additional conclusions included:

- Monochloramine led to the release of more total lead than using free chlorine.

- Silicate inhibitor worked better with free chlorine, whereas orthophosphate inhibitor

worked better with monochloramine.

- There was a nitrate-disinfectant interaction on total lead release that could not be fully

explained using previous theory. More research should be done in this area.

93

93

6 Reference List

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and Wastewater, 20th ed. APHA, American WaterWorks Association, and Water Environment

Federation, Washington, DC,1998.

Arnold, B. R. (2011) New Insights into Lead and Copper Corrosion: Impacts of Galvanic

Corrosion, Flow Pattern, Potential Reversal, and Natural Organic Matter. M.S. Thesis,

Department of Civil and Environmental Engineering, Virginia Tech.

AWWA (2005) Strategies to Obtain Customer Acceptance of Complete Lead Service Line

Replacement. AWWA, Denver

Boccelli, D.L., Tryby, M.E., Uber, J.G. and Summers, R.S. (2003) A reactive species model for

chlorine decay and THM formation under rechlorination conditions. Water Research. 37 2654–

2666.

Boyd, G. R., Shetty, P., Sandvig, A., and G. Pierson. (2004) Pb in tap water following simulated

partial lead pipe replacements. Jour. Envir. Engrg., 130(10) 1188-1197.

Boyd, G. R., Dewis, K. M., Sandvig, A.M, Kirmeyer, G.J., (2006) Effects of changing

disinfectants on distribution system lead and copper release Part I: Literature Review. AWWA

Research Foundation Report, Denver

Boyd, G. R., Dewis, K. M., Korshin, G. V., Reiber, S. H., Schock, M. R., Sandvig, A. M. and

Giani, R. (2008) Effects of changing disinfectants on lead and copper release. Journal AWWA,

100(11) 75-87.

Boyd, G. R., McFadden, M. S., Reiber, S. H., Sandvig, A. M. (2010) Effects of changing

disinfectants on distribution system lead and copper release Part II: Research Results. AWWA

Research Foundation Report, Denver

Cardew, P.T. (2006) Development of a convective diffusion model for lead pipe rigs operating

in laminar flow. Water Research, 40 2190-2200

Clark, Brandi N. (2008) Solubility as a Mechanism for CSMR Effects on Lead Leaching.

Proceedings of the World Environmental and Water Resources Congress 2008

Clark, Brandi N., Cartier, C., St. Clair, J., Triantafyllidou,S., Prévost, M. and Edwards, M.

(2010) Lead Contamination of Drinking Water After Partial Lead Service Line Replacements

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7 Appendices

7.1 Sample Calculations

7.1.1 Chlorine Dose Required to Give a Specific Residual Concentration at the

Desired Time

Step 1: Modeling chlorine decay for time 4 hr to 11 day

A first-order decay model was applied. Parameters a and k in Eq.5-3 (y = -kt + a) can be found

on Figure 5-3. For example, for DOC = 1 mg/L, chlorine = 2.5 mg/L, y = 0.072 x + 0.4035,

hence, k = 0.072, a = 0.4035

Step 2: Use Eq 5-3 to calculate Ct at 9th

day

For example, for DOC = 1 mg/L, chlorine = 2.5 mg/L, y = -0.072 t + 0.4035.

Ct = e (-0.072 × 9) + 0.4035

= 0.78 mg/L

Step 3: Find parameter e and f

Parameter e and f in Eq.5-4 (C0 = f + e × Ct) can be found on Figure 5-4.

For example, for DOC = 1 mg/L, chlorine = 2.5 mg/L, y = 1.0371 x + 1.6879, hence, e

=1.0371, f =1.6879

Step 4: Use Eq. 5-4 to determine the initial chlorine dose required

For example, for DOC = 1 mg/L, the target chlorine residual at the 9th

day is 1 mg/L Cl2.

C0 = 1.6879 + 1.0371× Ct

C0 = 1.6879 + 1.0371× 1 = 2.73 mg/L

Hence, the initial chlorine dosage for DOC at 1 mg/L should be at 2.73 mg/L chlorine.

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7.2 Experimental Procedures

7.2.1 Chlorine/monochloramine Demand Test

Step 1: Clean glasswares

The glassware for chlorine and chloramines demand tests and analysis should be chlorine

demand free since even with traces of chlorine-demand present it would alter the analytical

results as the chlorine in the samples would react with the chlorine-demand species. Therefore,

it was necessary to prepare chorine demand free glassware. To prepare a 500 mL glass bottle

with zero chlorine demand:

Add 45 mL NaOCl to a 500mL glass bottle

Fill the rest of the bottle with tap water

Cap the bottle and shake

Store at room temperature for 2 -3 hours

Empty the bottles

Rinse with distilled water (few remaining drops will not interfere with analysis)

Step 2: Prepare working solution

Prepare sulfate, chloride, nitrate, alkalinity, phosphate, silica working solution by adding salt to

Mill-Q water as listed in Table 7-1.

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Table 7-1: The amount of salt needed for preparing working solutions containing different ions

Working solution concentration Salt Need amount (g/L)

SO42-

(mg/L) 2000 K2SO4 3.628

Cl-(mg/L) 5000 NaCl 8.24

NO3-(NO3 -N mg/L) 1400 NaNO3 8.4952

Alkalinity (CaCO3 mg/L) 20833 NaHCO3 34.96

PO43-

(PO4 - P mg/L) 200 Na2HPO4 0.9168

Silica (SiO2 g/ L) 400 Purchased

Note: 2000 mg/L SO42-

stock solution is made by adding 3.628 g of K2SO4 to 1 L Mill-Q water.

500 mL DOC working solution preparation:

Dissolve 0.2 g SNOM and 2 mL of 1 M NaOH in about 400 mL Mill-Q water and bring the

volume to 500 mL using volumetric flask with Mill-Q water. Mix for 1 hour using magnetic stir

with a magnetic bar. Pass the mixed solution through a polyethersulfone membrane filter with a

pore size of 0.45 μm (Gelman Supor, Gelman Sciences, Ann Arbor, MI) (Comerton, 2008). The

DOC working solution was measured to be 188 mg/L TOC.

200 mL chlorine working solution preparation:

Dilute 5 mL of chlorine stock solution (Sigma-Aldrich Corporation, Oakville, ON) to 200 mL in

a 200 mL volumetric flask with Mill-Q water. The chlorine working solution was measured to

be 2850 mg/L cl2.

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40 mL monochloramine working solution preparation:

NH4OH working solution was obtained by diluting 100 times of the NH4OH stock solution

(Sigma-Aldrich Corporation, Oakville, ON). Then 10 mL of the NH4OH working solution was

mixed with 30 mL of the chlorine working solution for 30 minutes using magnetic stir with a

magnetic bar. Monochloramine working solution was measured to be 1920 mg/L cl2.

Step 3: Prepare test water

2 L test waters were prepared by mixing working solutions to Mill-Q water. The amount for

each of the working solutions needed were calculated and listed in the table below.

Table 7-2: The volume of working solution needed to prepare 2 L of test water

Chemical

species

SO42-

(mg/L) Cl

-(mg/L)

NO3-(NO3

-N mg/L) Alkalinity (CaCO3 mg/L)

Silica (SiO2

mg /L)

PO43-

(PO4 -

P mg/L)

10 25 7 250 15 24 1

working

solution

needed

sulfate

working

solution

10 ml

chloride

working

solution

10 ml

nitrate

working

solution

10 ml

bicarbonate

working

solution

24 mL

bicarbonate

working

solution

1.44 mL

Silica

working

solution

0.12 ml

Phosphate

working

solution

10 ml

Step 4: Transfer test water to 125 mL amber glass bottles

These 125 mL amber glass bottle have been pretreated in order to eliminate any chlorine

demand remained on the walls of the bottles. Each test water (2 L) was transferred to twelve 125

mL amber glass bottles.

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Step 5: Measure free chlorine or monochloramine.

Free chlorine or monochloramine residual concentrations were being monitored over the period

of two weeks (measurements taken at time = 0, 10 min, 4hr, 2 days, 4 days, 7days, 9 days and

11 days). For each new day, two new bottles from the set were randomly selected for the

measurement. pH values were also measured for each day

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7.2.2 pH Control by the Addition of Carbon Dioxide

SOP for pH adjustment by adding CO2 gas

PRINCIPLE:

Strong acid such as nitric acid (HNO3), hydrochloric acid (HCl) and sulfuric acid (H2SO4) will

introduce undesired anions into my test water. pH can be adjusted by adding 99.9% pure CO2

gas to the test water. Carbon dioxide is gaining acceptance for pH control. It reduces high pH

levels quickly. Carbon dioxide dissolves in water forming carbonic acid according to the

following reaction:

CO2 + H2O ＝ H2CO3 7-1

Carbonic acid is then ionized into:

H2CO3 ＝ H +

+ HCO3- 7-2

Because carbon dioxide introduces same amount of H +

and HCO3

- , it does not affect the

alkalinity of the water.

SAFETY NOTES AND OPERATIONAL CONCERNS:

This laboratory involves the uses of Carbon dioxide (CO2) (compressed gas). The gas is slightly

acidic and may be felt to have a slight, pungent odor and biting tast. CO2 is a relatively inert

nonreactive gas. It is noncorrosive and nonflammable. As a high-pressure gas (vapor pressure at

20°C: 838 psig (5778 kPa)), it can cause rapid suffocation, increase respiration and heart rate,

may cause nervous system damage, frostbite, dizziness and drowsiness. Self-contained

breathing apparatus may be required by rescue workers. No harm expected from vapor with Eye

or skin Contact.

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REAGENTS:

Reagent [CASRN] Supplier and Purity

Carbon dioxide (CO2) Praxair Technology Inc, 99.99% industrial

grade

METHOD OUTLINE:

1. Connect the regulator to the CO2 cylinder by screwing the regulator input valve firmly onto

the tank's output. Connect the regulator to the glass diffuser.

2. After connecting all part together, verify that leaks are not present by putting soap solution at

the connection area. If air bubble was observed, close the valve and check the connection.

3. Setting the pressure: close the regulator by turning the adjustment screw counter-clockwise

until it turns freely. Open the tank valve. No CO2 should be coming out and the high pressure

gauge should indicate the pressure inside the tank (around 800psi when full). Slowly turn the

regulator's adjustment screw clockwise until the low pressure gauge reads to a desired level (i.e

30 psi).

4. Stick the glass diffuser into a 1 L amber bottle deep enough so that the glass diffuser is

submerged by the test water completely in the bottle. The diffusers may require a little time for

pressure to build up and start diffusing. When bubbles are observed in the water, CO2 is coming

out from the diffuser. Adjust the gas flow rate using the regulator.

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7.2.3 Measure Concentrations of Silica, Phosphorus, Nitrate, Sulfate and Chloride

Silica (SiO2) was measured using HACH silicomolybdate Method (8185) for high range (1 to

100 mg/L SiO2). The 95% Confidence Interval for 49 mg/L is 47 to 71 mg/L.

SOP for Analysis of Silicate (adapted from DR 2800 Spectrophotometer manual)

Principle:

Silica and phosphate in the sample react with molybdate ion under acidic conditions to form

yellow silicomolybdic acid complexes and phosphomolybdic acid complexes. Addition of citric

acid destroys the phosphate complexes. Silica is then determined by measuring the remaining

yellow color. Test results are measured at 452 nm.

Reagents:

Supplier and Purity

[Product Number]

Acid Reagent Powder Pillows for HR Silica HACH [2429600]

Citric Acid Powder Pillows HACH [2429600]

Molybdate Reagent Powder Pillows for HR Silica HACH [2429600]

Mill-Q water N/A

Silica Standard Solution HACH; 50mg/L [111729]

Method Outline:

1. Select the stored program: 656 Silica HR

2. Fill sample cell with 10 mL of sample

3. Add the contents of one Molybdate Reagent Powder Pillow for High Range Silica to the

sample cell

4. Swirl until completely dissolved

5. Add contents of one Acid Reagent Powder Pillow for High Range Silica

6. Swirl to mix (a yellow colour will develop if silica or phosphorus is present)

7. Wait 10 minutes for the reaction to occur

8. Add contents of Citric Acid Powder Pillow to the sample cell

9. Swirl to mix (a yellow colour due to phosphorus is removed in this step)

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10. Wait 2 minutes for the reaction to occur

11. Blank preparation: fill a second sample cell with 10 mL of original sample

12. Wipe the blank and insert it into the cell holder

13. Zero the instrument

14. Wipe the prepared sample and insert it into the cell holder

15. Read/ record the results in mg/L SiO2

Accuracy check:

To check test accuracy, use the 50-mg/L Silica Standard Solution. Use Mill-Q water as the

blank.

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Phosphorus was measured using the HACH PhosVer® 3 Method (8048) which is adapted from

Standard Method 4500-P (APHA, 1998). This method is able to measure phosphorus in the

range of 0.06 to 5.00 mg/L PO43– or 0.02 to 1.60 mg/L P.The 95% Confidence Interval for 2.98

mg/L is 2.92 to 3.04 mg/L.

SOP for Analysis of Phosphorus (adapted from DR 2800 Spectrophotometer manual)

Principle:

Orthophosphate reacts with molybdate in an acid medium to produce a mixed

phosphate/molybdate complex. Ascorbic acid then reduces the complex, giving an intense

molybdenum blue color. Test results are measured at 880 nm.

Reagents:

Supplier and Purity

[Product Number]

Reactive Phosphorus Test ’N Tube™ Reagent Set HACH[27425-45]

Mill-Q water N/A

Phosphate Standard Solution, 1 mg/L as PO43–

HACH[2569-49]

Method Outline:

1. Select the test : 535 P React.PV TNT

2. Use a TenSette® Pipet to add 5.0 mL of sample to a Reactive Phosphorus Test ‘N Tube

Dilution Vial.Cap and mix.

3. Insert the vial into the16-mm round cell holder. Press Zero. The display will show: 0.00

mg/L PO43–

4. Add the contents of one PhosVer 3 Phosphate Powder Pillow to the vial. Immediately

cap the vial tightly and shake for at least 20 seconds. The powder will not dissolve

completely. A two-minute reaction period will begin. Read samples between two and

eight minutes after adding the PhosVer 3 reagent

5. When the timer expires, insert the vial into the 16 mm round cell holder. Press READ.

Results are in mg/L PO43–

.

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Accuracy check:

Standard Solution Method

1. Use a 1.0-mg/L phosphate standard solution in place of the sample. Perform the procedure as

describe above.

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Nitrate was measured using the HACH HR Cadmium Reduction Method (8039) which is

adapted from Standard Methods 4500-NO3- (APHA, 1998). This method is able to measure

nitrate in the range of 0.3–30.0 mg/L NO3-––N. The 95% Confidence Interval for 14.7 mg/L is

14 to 15.4 mg/L.

SOP for Analysis of Nitrate (adapted from DR 2800 Spectrophotometer manual)

Principle:

Cadmium metal reduces nitrates in the sample to nitrite. The nitrite ion reacts in an acidic

medium with sulfanilic acid to form an intermediate diazonium salt. The salt couples with

gentisic acid to form an amber colored solution. Test results are measured at 500 nm.

Reagents:

Supplier and Purity [Product

Number]

NitraVer® 5 Nitrate Reagent Powder Pillows HACH[21061-69]

Mill-Q water N/A

Nitrate Nitrogen Standard Solution, 10-mg/L HACH[307-49]

Method Outline:

1. Select the test : 355 N Nitrate HR

2. Fill a square sample cell with 10 mL of sample.

3. Prepared Sample: Add the contents of one NitraVer 5 Nitrate Reagent Powder Pillow.

Put on stopper

4. Press TIMER>OK. A one-minute reaction will begin. Shake the cell vigorously until

the timer expires. When the timer, press TIMER>OK again. A five-minute reaction

period will begin. An amber color will develop if nitrate is present.

5. Blank Preparation: When the timer expires, fill a second square sample cell with 10 mL

of sample

6. Wipe the blank and insert it into the cell holder with the fill line facing right. Press

ZERO. The display will show: 0.0 mg/L NO3-––N

7. Within one minute after the timer expires, wipe the prepared sample and insert it into the

cell holder with the fill line facing right. Press READ. Results are in mg/L NO3-––N.

112

112

Accuracy check:


1. Use a 10.0-mg/L Nitrate Nitrogen Standard Solution in place of the sample and perform the

procedure as described above.

113

113

Sulfate was measured using HACH SulfaVer 4 Method Powder Pillows (8051) which is adapted

from Standard Methods 4500-SO42-

(APHA, 1998). This method is able to measure sulfate in

the range of 2 to 70 mg/L SO42-

. The 95% Confidence Interval for 40 mg/L is 30 to 50 mg/L.

SOP for Analysis of Sulfate (adapted from DR 2800 Spectrophotometer manual)

Principle:

Sulfate ions in the sample react with barium in the SulfaVer 4 and form a precipitate of barium

sulfate. The amount of turbidity formed is proportional to the sulfate concentration. Test results

are measured at 450 nm.

Reagents:

Supplier and Purity

[Product Number]

SulfaVer® 4 Reagent Powder Pillows HACH[21067-69]

Mill-Q water N/A

Sulfate Standard Solution, 1000-mg/L HACH[21757-49]

Method Outline:

1. Select the test: 680 sulfate

2. Fill a square sample cell with 10 mL of sample.

3. Prepared Sample: Add the contents of one SulfaVer 4 Reagent Powder Pillow to the

sample cell. Swirl vigorously to dissolve powder. White turbidity will form if sulfate is

present.

4. Press TIMER>OK.A five-minute reaction period will begin. Do not disturb the cell

during this time.

5. Fill a second square sample cell with 10 mL of sample.

6. When the timer expires, insert the blank into the cell holder with the fill line facing right.

Press ZERO. The display will show: 0 mg/L SO42–

114

114

7. Within five minutes after the timer expires, insert the prepared sample into the cell

holder with the fill line facing right. Press READ. Results are in mg/L SO42–

. Clean

sample cells with a soap and brush

Accuracy check:


1. Prepare a 10.0-mg/L chloride standard solution as follows: Transfer 1 mL of Sulfate

Standard Solution, 1000-mg/L, into a 100-mL volumetric flask. Dilute to the mark with

Mill-Q water. Prepare this solution daily. Perform the SulfaVer procedure as described

above.

115

115

Chloride will be measured using HACH Mercuric Thiocyanate method (81130). This method is

able to measure chloride in the range of 0.1 to 25 mg/L Cl-. The 95% Confidence Interval for

17.8 mg/L is 15.7 to 19.9 mg/L.

SOP for Analysis of Chloride (adapted from DR 2800 Spectrophotometer manual)

Principle:

Chloride in the sample reacts with mercuric thiocyanate to form mercuric chloride and liberate

thiocyanate ion. Thiocyanate ions react with the ferric ions to form an orange ferric thiocyanate

complex. The amount of this complex is proportional to the chloride concentration. Test results

are measured at 455 nm.

Reagents:

Supplier and Purity

[Product Number]

Ferric Ion Solution HACH[22122-42]

Mercuric Thiocyanate Solution HACH[22121-29]

Chloride Standard Solution, 1000-mg/L Cl– HACH[183-49]

Mill-Q water N/A

Method Outline:

1. Select the test: 70 Chloride

2. Fill a square sample cell with 10 mL of sample

3. Fill another square sample cell with 10 mL of deionized water

4. Pipet 0.8 mL of Mercuric Thiocyanate Solution into each sample cell. Swirl to mix

5. Pipet 0.4 mL of Ferric Ion Solution into each sample cell. Swirl to mix. An orange color

will develop if chloride is present.

6. Press timer OK. A two-minute reaction time will begin

7. Within five minutes after the timer expires, wipe the blank and insert it into the cell

holder with the fill line facing right. Press ZERO. The display will show:0.0 mg/L Cl–

116

116

8. Wipe the prepared sample and insert it into the cell holder with the fill line facing right.

Press READ. Results are in mg/L Cl–.

Accuracy check:


1. Prepare a 20.0-mg/L chloride standard solution as follows: using Class A glassware, pipet

1.00 mL of Chloride Standard Solution, 1000-mg/L, into a 50-mL volumetric flask, dilute to the

mark with Mill-Q water. Perform the chloride procedure as described above.

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117

7.3 Raw Data

7.3.1 Chlorine/monochloramine Demand Test

Table 7-3: Free chlorine residual (mg/L Cl2) measured over 11 days

Alkalinity

(CaCO3 mg/L)

Silica (SiO2 mg/L)

PO43-

(PO4-P mg/L)

DOC (mg/L)

Dose of chlorine(m

g/L)

Time (Days)

0 0.01 0.16 0.92 4 7 9 11

250 0 1 0 3.5

#1 3.64 3.63 3.45 3.4 3.38 3.53 3.5 3.58

#2 3.64 3.65 3.5 3.4 3.35 3.55 3.6 3.58

Average 3.64 3.64 3.48 3.4 3.36 3.54 3.55 3.58

Std 0.00 0.02 0.04 0 0.02 0.02 0.07 0

250 0 1 1 2.5

#1 2.64 2.38 1.63 1.28 1.13 1 0.7 0.7

#2 2.64 2.38 1.55 1.3 1.13 0.95 0.7 0.73

Average 2.64 2.38 1.59 1.29 1.13 0.98 0.7 0.71

Std 0.00 0 0.05 0.02 0 0.04 0 0.02

250 0 1 1 3.5

#1 3.64 3 2.68 2.23 2.08 1.88 1.83 1.68

#2 3.64 3 2.68 2.23 2 1.95 1.78 1.67

Average 3.64 3 2.68 2.23 2.04 1.91 1.80 1.67

Std 0.00 0 0 0 0.05 0.05 0.05 0.01

250 0 1 4 8

#1 8.20 6.85 5.45 3.6 2.08 1.43 0.83 0.83

#2 8.20 6.9 5.45 3.6 2.15 1.43 0.9 0.8

Average 8.20 6.88 5.45 3.6 2.11 1.43 0.86 0.81

Std 0.00 0.04 0 0 0.05 0 0.05 0.02

118

118

Table 6.3: Free chlorine residual (mg/L Cl2) measured over 11 days (cont’d)

250 0 1 4 10

#1 10.23 8.65 6.55 5.15 3.7 3.03 2.68 2.38

#2 10.23 8.65 6.6 5.25 3.88 3.05 2.6 2.38

Average 10.23 8.65 6.58 5.2 3.79 3.04 2.64 2.38

Std 0.00 0 0.04 0.07 0.12 0.02 0.05 0

250 0 1 7 16

#1 16.33 14.7 9.7 6.9 4.6 3.5 2.65 2.2

#2 16.33 14.9 9.75 6.8 4.7 3.45 2.53 2.23

Average 16.33 14.8 9.73 6.85 4.65 3.48 2.59 2.21

Std 0.00 0.14 0.04 0.07 0.07 0.04 0.09 0.02

250 0 1 7 19

#1 19.33 18.1 12.7 9.6 7.15 6.05 5.3 4.4

#2 19.33 18 12.6 9.9 7.4 5.95 5.4 4.5

Average 19.33 18.05 12.65 9.75 7.28 6 5.35 4.45

Std 0.00 0.07 0.07 0.21 0.18 0.07 0.07 0.07

15 0 1 0 3.5

#1 3.64 3.5 3.6 3.67 3.43 3.63 3.63 3.5

#2 3.64 3.47 3.67 3.7 3.45 3.65 3.65 3.48

Average 3.64 3.49 3.64 3.69 3.44 3.64 3.64 3.49

Std 0.00 0.02 0.05 0.02 0.01 0.01 0.01 0.02

15 0 1 1 3.5

#1 3.64 3.25 2.98 2.6 2.25 2.08 1.93 1.7

#2 3.64 3.18 2.98 2.58 2.25 2.1 1.90 1.73

Average 3.64 3.22 2.98 2.59 2.25 2.09 1.91 1.71

Std 0.00 0.05 0 0.02 0 0.01 0.02 0.02

119

119

Table 6.3: Free chlorine residual (mg/L Cl2) measured over 11 days (cont’d)

250 24 0 0 3.5

#1 3.64 3.4 3.68 3.63 3.63 3.65 3.6 3.65

#2 3.64 3.4 3.63 3.68 3.68 3.68 3.63 3.65

Average 3.64 3.4 3.65 3.65 3.65 3.66 3.61 3.65

Std 0.00 0 0.04 0.04 0.04 0.02 0.02 0

250 24 0 1 3.5

#1 3.64 3.28 3.03 2.75 2.35 2.18 1.98 1.83

#2 3.64 3.38 3.03 2.75 2.38 2.2 1.93 1.75

Average 3.64 3.33 3.03 2.75 2.36 2.19 1.96 1.79

Std 0.00 0.07 0 0 0.02 0.02 0.04 0.05

120

120

Table 7-4: pH of chlorine demand test measured over 11 days

Alkalinity (CaCO3 mg/L)

Silica (SiO2 mg/L)

PO43-

(PO4-P mg/L)

DOC (mg/L)

Dose of chlorine (mg/L)

Time

Day 1 Day 2 Day 4 Day 7 Day 9 Day 11

250 0 1 0 3.5 8.41 8.46 8.47 8.54 8.46 8.44

250 0 1 1 2.5 8.43 8.46 8.47 8.48 8.44 8.54

250 0 1 1 3.5 8.42 8.46 8.47 8.45 8.52 8.51

250 0 1 4 8 8.55 8.54 8.54 8.47 8.48 8.49

250 0 1 4 10 8.57 8.58 8.58 8.56 8.5 8.52

250 0 1 7 16 8.64 8.63 8.59 8.52 8.52 8.48

250 0 1 7 19 8.64 8.64 8.58 8.53 8.53 8.51

15 0 1 0 3.5 8.35 8.33 8.19 8.39 8.51 8.45

15 0 1 1 3.5 8.48 8.55 8.3 8.2 8.49 8.4

250 24 0 0 3.5 8.98 8.98 8.97 8.92 8.95 8.97

250 24 0 1 3.5 8.99 9 8.98 9 8.97 9

121

121

Table 7-5: Monochloramine residual (mg/L Cl2) measured over 11 days

Alkalinity (CaCO3 mg/L)

PO43-

(PO4-P mg/L)

DOC (mg/L)

Dose of chlorine (mg/L)

(Days) 0 0.01 0.16 0.92 4 7 9 11

0 0 0 6

#1 6.02 5.53 5.4 5.5 5.3 5.3 5.45 5.25

#2 6.02 5.65 5.3 5.55 5.38 5.4 5 5

AVG 6.02 5.59 5.35 5.53 5.34 5.35 5.23 5.13

Std 0 0.08 0.07 0.04 0.05 0.07 0.32 0.18

250 1 0 6

#1 6.02 5.4 5.75 5.25 5.75 5.25 5.15 5

#2 6.02 5.8 5.8 5.35 5.85 5.15 5.2 5

AVG 6.02 5.6 5.78 5.3 5.8 5.2 5.18 5

Std 0 0.28 0.04 0.07 0.07 0.07 0.04 0

250 1 1 4

#1 4.04 3.35 3.63 3.57 3.38 3.2 2.95 2.98

#2 4.04 3.58 3.88 3.5 3.35 3.2 2.75 3.08

AVG 4.04 3.47 3.75 3.54 3.36 3.2 2.85 3.03

Std 0 0.16 0.18 0.05 0.02 0 0.14 0.07

250 1 1 6

#1 6.02 5.35 5.13 5.13 4.8 4.13 4 4.25

#2 6.02 5.45 5.3 5.05 4.9 4.13 4.13 4.25

AVG 6.02 5.4 5.21 5.09 4.85 4.13 4.06 4.25

Std 0 0.07 0.12 0.06 0.07 0 0.09 0

250 1 4 6

#1 6.02 5.65 5.1 5.1 4.6 4.23 3.93 3.75

#2 6.02 5.9 5.25 5.05 4.35 4.05 3.9 3.63

AVG 6.02 5.78 5.18 5.08 4.48 4.14 3.91 3.69

Std 0 0.18 0.11 0.04 0.18 0.12 0.02 0.09

250 1 4 9

#1 8.99 8.65 8.75 8.08 7.18 6.68 6.4 5.95

#2 8.99 8.95 8.78 7.75 7 6.6 6.35 5.95

AVG 8.99 8.8 8.76 7.91 7.09 6.64 6.38 5.95

Std 0 0.21 0.02 0.23 0.12 0.05 0.04 0

Note: AVG is average, Std is standard deviation

122

122

Table 6.5: Monochloramine residual (mg/L Cl2) measured over 11 days (cont’d)

250 1 7 9

#1 8.99 8.88 8.38 7.05 6.38 5.43 5 4.5

#2 8.99 9.05 8.5 7.25 6.25 5.43 5.2 4.4

AVG 8.99 8.96 8.44 7.15 6.31 5.43 5.1 4.45

Std 0 0.12 0.09 0.14 0.09 0 0.14 0.07

250 1 7 12

#1 11.95 11.75 10.38 9.4 8.75 7.4 7.05 7

#2 11.95 11.95 10.63 9.78 8.73 7.75 7.1 7

AVG 11.95 11.85 10.5 9.59 8.74 7.58 7.08 7

Std 0 0.14 0.18 0.27 0.02 0.25 0.04 0

123

123

Table 7-6: pH of monochloramine demand test measured over 11 days

Alkalinity

(CaCO3

mg/L)

PO43-

(PO4-P

mg/L)

DOC

(mg/L)

Dose of

chlorine

(mg/L)

Time

Day 1 Day 2 Day 4 Day 7 Day 9 Day 11

0 0 0 6 9.74 9.69 9.68 9.87 9.87 9.87

250 1 0 6 8.88 8.85 8.87 8.9 8.88 8.89

250 1 1 4 8.81 8.83 8.83 8.84 8.87 8.88

250 1 1 6 8.88 8.9 8.86 8.86 8.92 8.9

250 1 4 6 8.97 8.97 8.95 8.95 9.01 9

250 1 4 9 9.07 9.04 9.01 9.05 9.06 9.06

250 1 7 9 9.09 9.07 9 9 9.09 9.08

250 1 7 12 9.1 9.1 9.08 9.11 9.14 9.12

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7.3.2 Galvanic Current Data

Table 7-7: Galvanic current data

Average current (µA) Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Week 9 Week

11 Week

12

ALK15DOC7N1OP1C1 11.98 5.3 7.78 7.76 8.72 9.1 10.62 12.86 10.96 11.26 11.02

ALK250DOC1N1Si24MC3 35.36 30.1 33.48 36.26 38.14 33.44 36.5 37.16 30.16 31.58 30.7

ALK250DOC1N7Si24C1 41.28 30.78 25.38 21.62 21.68 20.16 18.62 17.6 15.44 16.34 18.04

ALK250DOC7N7Si24MC3 42.98 40.36 39.6 40.86 41.66 39.26 39.96 40.92 32.84 39.74 44.26

ALK250DOC7N1OP1MC3 40.02 30.84 29.92 25.46 22.4 20.16 18.48 18.02 17.34 14.34 14.96

ALK250DOC7N7OP1C1 32.82 29.54 20.76 21.2 22.28 21.74 19.4 23.58 16.48 16.92 15.4

Alk15DOC7N7OP1MC3 17.36 14.64 14.86 13.8 13.66 15.12 13.08 14.52 14.38 13.94 15.56

Alk250DOC1N7 OP1MC3 38.42 33.58 30.1 33.56 31.68 31.4 28.98 30.86 28.28 28.06 28.1

Alk15DOC1N7 Si24MC3 23.74 19.08 17.82 16.8 16.56 15.08 14.72 16.58 14.46 16.24 15.92

Alk15DOC7N7 Si24C1 19.2 16.98 19.22 12.92 12.86 12.66 10.8 11.3 8.16 7.6 7.48

Alk15DOC7N1 Si24MC3 20.3 19.34 20.32 18.12 18.04 16.2 15.04 17.52 13.5 13.54 13.54

Alk15DOC1N1 OP1MC3 18.68 16.62 16.44 16.74 16.72 15.2 14.82 16.52 14.18 13.64 12.44

Alk15DOC1N7 OP1C1 20.28 16.98 15.58 14.6 12.86 13.36 12.6 14.74 12.84 11.24 9.4

Alk250DOC7N1 Si24C1 34.14 36.52 38.18 38.12 34.44 31.64 27.92 34.32 30.24 31.24 29.74

Alk250DOC1N1 OP1C1 25.88 22.66 19.78 19.42 15.8 15.76 13.26 16.42 12.9 14.14 13.6

Alk15DOC1N1 Si24C1 16.76 13.38 12.18 10.82 8.92 9.12 8.62 10.46 7.9 8.4 7.38

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7.3.3 Total Lead Data

Table 7-8: Measured total lead release in the weekly composite water

Total lead (µg/L) Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Week 9 Week

11 Week

12

ALK15DOC7N1OP1C1 200000 18000 20000 13000 13000 8600 6900 2700 3000 3300 4700

ALK250DOC1N1Si24MC3 41000 2900 5400 4700 2200 2300 5400 1500 1800 1600 1700

ALK250DOC1N7Si24C1 30000 1200 610 500 620 590 490 450 570 520 360

ALK250DOC7N7Si24MC3 260000 9800 2900 11000 6300 7700 8200 7328 9700 3500 4900

ALK250DOC7N1OP1MC3 15000 3000 2000 1400 1500 1300 1100 1100 880 800 1100

ALK250DOC7N7OP1C1 75000 1500 870 1100 2800 2300 2200 2500 2000 1500 1200

Alk15DOC7N7OP1MC3 53000 13000 6500 6100 7300 5100 3800 2700 2000 2700 2600

Alk250DOC1N7 OP1MC3 87000 9600 7000 7700 5900 3500 3300 3400 4500 5900 3500

Alk15DOC1N7 Si24MC3 88000 8500 6000 5500 8000 6100 13000 8800 5800 7200 7700

Alk15DOC7N7 Si24C1 76000 4700 3300 2400 1800 2400 4900 1700 1900 1400 1500

Alk15DOC7N1 Si24MC3 49000 6700 8300 7200 4800 7800 4100 5300 6700 3300 7800

Alk15DOC1N1 OP1MC3 14000 6300 7300 3000 4000 3900 6000 4500 11000 2600 4800

Alk15DOC1N7 OP1C1 37000 4600 3800 3200 4100 1900 2800 3400 3600 1400 1700

Alk250DOC7N1 Si24C1 54000 9000 20000 6500 17000 8200 4300 4400 4100 3800 4700

Alk250DOC1N1 OP1C1 21000 2600 1300 1500 1300 880 910 2800 1000 710 950

Alk15DOC1N1 Si24C1 33000 2300 690 1200 580 580 900 1100 1400 920 980

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126

Table 7-9: Calculated maximum lead release using Equation 2-5

Total lead (µg/L) Week 4 Week 5 Week 6 Week 7 Week 8 Week 9 Week 11 Week 12

ALK15DOC7N1OP1C1 1440.167 1618.332 1688.856 1970.951 2386.669 2034.051 2089.727 2045.186

ALK250DOC1N1Si24MC3 6729.442 7078.348 6206.082 6773.983 6896.472 5597.351 5860.887 5697.569

ALK250DOC1N7Si24C1 4012.425 4023.56 3741.466 3455.659 3266.359 2865.488 3032.517 3348.018

ALK250DOC7N7Si24MC3 7583.149 7731.62 7286.208 7416.12 7594.285 6094.729 7375.29 8214.15

ALK250DOC7N1OP1MC3 4725.085 4157.184 3741.466 3429.677 3344.306 3218.106 2661.34 2776.405

ALK250DOC7N7OP1C1 3934.478 4134.913 4034.696 3600.418 4376.179 3058.5 3140.159 2858.064

Alk15DOC7N7OP1MC3 2561.122 2535.14 2806.099 2427.499 2694.746 2668.764 2587.105 2887.758

Alk250DOC1N7 OP1MC3 6228.353 5879.446 5827.481 5378.357 5727.263 5248.445 5207.615 5215.039

Alk15DOC1N7 Si24MC3 3117.888 3073.347 2798.676 2731.864 3077.059 2683.611 3013.958 2954.57

Alk15DOC7N7 Si24C1 2397.804 2386.669 2349.551 2004.357 2097.151 1514.403 1410.473 1388.203

Alk15DOC7N1 Si24MC3 3362.865 3348.018 3006.535 2791.252 3251.512 2505.446 2512.869 2512.869

Alk15DOC1N1 OP1MC3 3106.753 3103.041 2820.946 2750.423 3065.923 2631.646 2531.428 2308.722

Alk15DOC1N7 OP1C1 2709.593 2386.669 2479.463 2338.416 2735.576 2382.957 2086.016 1744.533

Alk250DOC7N1 Si24C1 7074.637 6391.671 5872.023 5181.633 6369.4 5612.199 5797.787 5519.404

Alk250DOC1N1 OP1C1 3604.13 2932.3 2924.876 2460.905 3047.364 2394.093 2624.222 2524.005

Alk15DOC1N1 Si24C1 2008.068 1655.45 1692.568 1599.774 1941.257 1466.15 1558.944 1369.644

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7.3.4 Dissolved Lead Data

Table 7-10: Measured dissolved lead release in the weekly composite water

Dissolved lead (µg/L) Week 3 Week 6 Week 9 Week 10 Week12

ALK15DOC7N1OP1C1 1100 1290 970 300 990

ALK250DOC1N1Si24MC3 85 60 0 0 0

ALK250DOC1N7Si24C1 11 0 0 0 0

ALK250DOC7N7Si24MC3 330 320 310 310 270

ALK250DOC7N1OP1MC3 170 150 150 160 130

ALK250DOC7N7OP1C1 68 140 100 80 80

Alk15DOC7N7OP1MC3 450 490 470 310 400

Alk250DOC1N7 OP1MC3 66 50 0 0 0

Alk15DOC1N7 Si24MC3 37 70 0 0 0

Alk15DOC7N7 Si24C1 150 170 170 140 130

Alk15DOC7N1 Si24MC3 420 410 490 250 380

Alk15DOC1N1 OP1MC3 240 330 480 190 600

Alk15DOC1N7 OP1C1 110 70 220 80 80

Alk250DOC7N1 Si24C1 130 280 220 270 180

Alk250DOC1N1 OP1C1 29 0 0 0 0

Alk15DOC1N1 Si24C1 16 0 0 0 0

128

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7.3.5 Test Water Parameters

Table 7-11: Electric conductivity of test water

Electric conductivity (µS/cm)

Week 1

Week 2

Week 3

Week 4

Week 5

Week 6

Week 7

week 8

week 9

week 10

week 11

week 12

ALK15DOC7N1OP1C1 90.5 84.2 81 88.7 105.2 81 102.3 110 99.5 90.1 94.1 93.6

ALK250DOC1N1Si24MC3 215 210 212 227 238 236 237 240 229 208 227 201

ALK250DOC1N7Si24C1 222 221 212 235 274 237 249 260 243 219 234 198.9

ALK250DOC7N7Si24MC3 235 232 230 248 265 263 270 265 254 233 264 224

ALK250DOC7N1OP1MC3 213 209 212 224 236 238 234 240 224 209 240 202

ALK250DOC7N7OP1C1 238 239 231 253 275 265 268 282 255 239 252 232

Alk15DOC7N7OP1MC3 94.8 92.5 100.2 99.7 106.3 109.9 105.1 110 99.9 90.7 118.6 95.6

Alk250DOC1N7 OP1MC3 220 219 220 236 244 237 247 276 234 214 237 208

Alk15DOC1N7 Si24MC3 90.3 91.3 88.4 93.7 99.1 97.9 102.2 111 95.9 83.3 94.3 85.1

Alk15DOC7N7 Si24C1 115.3 105.8 140.3 115.7 130.6 128.8 126.4 138 115.7 110.3 113.8 106.6

Alk15DOC7N1 Si24MC3 85.6 79.3 83.3 89.1 93.8 95.2 92.7 111.8 88.5 80.9 91.6 92.2

Alk15DOC1N1 OP1MC3 67.5 67.4 66 69.2 75.3 76.7 75.3 89 74 64.9 72 63.5

Alk15DOC1N7 OP1C1 82.6 74.5 75.7 80.7 87.3 87.7 90.4 120.5 85.6 78 80.3 75.3

Alk250DOC7N1 Si24C1 228 228 219 240 261 256 260 283 252 234 241 219

Alk250DOC1N1 OP1C1 203 196 196.8 206 215 211 223 256 212 193.2 204 193.1

Alk15DOC1N1 Si24C1 73.4 66.3 62.7 74.7 73.4 72.8 74.9 97 70.8 64.3 70.5 67.9

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Table 7-12: OPR of test water

OPR (mV) Week

1 Week

2 Week

3 Week

4 Week

5 Week

6 Week

7 Week

8 Week

9 Week

10 Week

11 Week

12

ALK15DOC7N1OP1C1 719 718 724 709 708 724 716 722 718 683 714 704

ALK250DOC1N1Si24MC3 499 504 511 491 504 500 514 518 478 504 492 508

ALK250DOC1N7Si24C1 706 697 700 706 697 700 694 714 714 694 711 710

ALK250DOC7N7Si24MC3 419 424 389 429 424 388 458 499 428 428 422 446

ALK250DOC7N1OP1MC3 440 417 385 450 417 385 428 433 443 429 441 428

ALK250DOC7N7OP1C1 714 719 710 724 719 713 713 740 714 714 731 712

Alk15DOC7N7OP1MC3 469 456 399 486 456 391 463 457 481 460 460 449

Alk250DOC1N7 OP1MC3 499 493 462 491 493 462 499 494 497 496 480 505

Alk15DOC1N7 Si24MC3 518 494 499 508 494 470 504 456 506 503 495 480

Alk15DOC7N7 Si24C1 713 711 712 723 711 712 715 739 716 709 722 719

Alk15DOC7N1 Si24MC3 452 450 440 462 450 399 475 463 469 463 457 457

Alk15DOC1N1 OP1MC3 517 495 499 507 495 491 521 508 499 519 493 503

Alk15DOC1N7 OP1C1 698 689 706 698 689 706 715 715 715 651 717 629

Alk250DOC7N1 Si24C1 739 717 723 734 717 723 723 737 718 713 743 718

Alk250DOC1N1 OP1C1 726 705 721 725 705 731 725 705 715 717 730 729

Alk15DOC1N1 Si24C1 722 705 693 720 705 693 718 697 709 705 711 730

130

130

7.3.6 Inhibitor Residual and Disinfectant Residual in the Weekly Composite Water

Table 7-13: Orthophosphate residual in the weekly composite water

Sample Orthophosphate (mg/L as P)

Week 1

Week 2

Week 3

Week 4

Week 5

Week 6

Week 7

Week 8

Week 9

Week 10

Week 11

Week 12

ALK15DOC7N1OP1C1 0.09 0.24 0.27 0.30 0.31 0.41 0.44 0.49 0.53 0.34 0.65 0.54

ALK250DOC1N1Si24MC3

ALK250DOC1N7Si24C1

ALK250DOC7N7Si24MC3

ALK250DOC7N1OP1MC3 0.29 0.48 0.51 0.50 0.52 0.57 0.57 0.54 0.46 0.57 0.53 0.49

ALK250DOC7N7OP1C1 0.17 0.43 0.45 0.48 0.53 0.51 0.53 0.50 0.48 0.51 0.52 0.52

Alk15DOC7N7OP1MC3 0.07 0.36 0.37 0.37 0.45 0.41 0.42 0.41 0.46 0.40 0.41 0.41

Alk250DOC1N7 OP1MC3 0.15 0.21 0.40 0.43 0.49 0.48 0.51 0.48 0.42 0.47 0.50 0.46

Alk15DOC1N7 Si24MC3

Alk15DOC7N7 Si24C1

Alk15DOC7N1 Si24MC3

Alk15DOC1N1 OP1MC3 0.15 0.29 0.36 0.31 0.37 0.39 0.15 0.47 0.44 0.38 0.39 0.44

Alk15DOC1N7 OP1C1 0.14 0.33 0.43 0.42 0.44 0.44 0.45 0.41 0.42 0.45 0.46 0.56

Alk250DOC7N1 Si24C1

Alk250DOC1N1 OP1C1 0.32 0.47 0.51 0.47 0.50 0.53 0.56 0.56 0.54 0.57 0.51 0.64

Alk15DOC1N1 Si24C1

131

131

Table 7-14: Silicate residual in the weekly composite water

Sample Silicate (mg/L as SiO2)

Week 1

Week 2

Week 3

Week 4

Week 5

Week 6

Week 7

Week 8

Week 9

Week 10

Week 11

Week 12

ALK15DOC7N1OP1C1

ALK250DOC1N1Si24MC3 10.80 14.90 17.40 17.3 18.5 17.3 21.2 20.5 21.3 22.5 22.1 20.4

ALK250DOC1N7Si24C1 12.00 17.50 21.50 19.5 19.6 19.5 21.9 21.5 22.7 23.4 22.4 22.9

ALK250DOC7N7Si24MC3 7.80 17.80 20.60 20.1 20.1 20.9 20.8 22.2 20 24 21.3 23.5

ALK250DOC7N1OP1MC3

ALK250DOC7N7OP1C1

Alk15DOC7N7OP1MC3

Alk250DOC1N7 OP1MC3

Alk15DOC1N7 Si24MC3 10.10 13.54 20.20 19.6 20 19.7 17.9 18.9 19.3 20.5 22.2 22.6

Alk15DOC7N7 Si24C1 7.60 10.00 21.60 21 21.3 21.3 23.2 22.4 20 24.1 22.6 23.3

Alk15DOC7N1 Si24MC3 7.30 12.00 13.70 14.7 16.5 16.1 18 17.9 15.4 21.5 22.7 20.8

Alk15DOC1N1 OP1MC3

Alk15DOC1N7 OP1C1

Alk250DOC7N1 Si24C1 11.80 15.20 16.2 18.7 20.4 21.1 23.2 23 23 20.8 21.5 24.2

Alk250DOC1N1 OP1C1

Alk15DOC1N1 Si24C1 11.20 16.50 12.1 18.2 19.7 21 21.5 21.6 21.5 19.7 22.7 23

132

132

Table 7-15: Disinfectant residual in the weekly composite water

Sample Disinfectant residual (mg/L)

Week

1 Week

2 Week

3 Week

4 Week

5 Week

6 Week

7 week

8 week

9 week

10 week

11 week

12

ALK15DOC7N1OP1C1 Free 0.36 0.11 0.01 0.01 0.03 0.08 0.08 0.05 0.05 0.07 0.06 0.07

ALK250DOC1N1Si24MC3 Mono 0.04 0.21 0.15 0.06 0.1 0.2 0.05 0.07 0.01 0.03 0.05 0.03

ALK250DOC1N7Si24C1 Free 0.06 0.02 0.02 0.04 0.04 0.07 0.12 0.15 0.03 0.09 0.1 0.06

ALK250DOC7N7Si24MC3 Mono 0.04 0.23 0.05 0.02 0.09 0.09 0.03 0.15 0.04 0.05 0.08 0.03

ALK250DOC7N1OP1MC3 Mono 0.2 0.05 0.19 0.06 0.09 0.05 0.01 0.04 0.04 0.06 0.03 0.03

ALK250DOC7N7OP1C1 Free 0.18 0.04 0.05 0.05 0.11 0.05 0.05 0.11 0.03 0.05 0.1 0.06

Alk15DOC7N7OP1MC3 Mono 0.22 0.19 0.22 0.11 0.26 0.12 0.14 0.23 0.04 0.06 0.04 0.03

Alk250DOC1N7 OP1MC3 Mono 0.38 0.35 0.25 0.13 0.23 0.4 0.23 0.2 0.32 0.07 0.06 0.05

Alk15DOC1N7 Si24MC3 Mono 0.6 0.55 0.87 0.64 0.8 0.65 0.54 0.72 0.67 0.8 1.03 0.69

Alk15DOC7N7 Si24C1 Free 0.4 0.02 0.03 0.02 0.07 0.06 0.06 0.1 0.06 0.03 0.09 0.19

Alk15DOC7N1 Si24MC3 Mono 0.05 0.13 0.18 0.03 0.13 0.05 0.05 0.06 0.05 0.05 0.04 0.07

Alk15DOC1N1 OP1MC3 Mono 0.5 0.58 0.76 0.43 0.73 0.55 0.29 0.5 0.4 0.25 0.76 0.56

Alk15DOC1N7 OP1C1 Free 0.2 0.04 0.03 0.04 0.09 0.06 0.2 0.09 0.06 0.09 0.1 0.1

Alk250DOC7N1 Si24C1 Free 0.38 0.06 0.05 0.06 0.12 0.1 0.1 0.1 0.05 0.09 0.11 0.11

Alk250DOC1N1 OP1C1 Free 0.08 0.04 0.04 0.03 0.08 0.07 0.17 0.09 0.07 0.08 0.09 0.11

Alk15DOC1N1 Si24C1 Free 0.18 0.03 0.01 0.02 0.09 0.09 0.14 0.05 0.05 0.09 0.12 0.07

133

133

7.4 Preliminary Results

The main purpose of the preliminary experiment was to determine the experimental time needed

for lead leaching levels to stabilize, also to evaluate the repeatability of the pipe rig test. The pipe

rigs for this tests consisted of 0.5 m new lead pips (diameter =1.9cm) and 0.5m new copper pipe

(diameter =1.9cm). Six test conditions were included in the preliminary experiment as listed in

Table 7-16.

Table 7-16: The test concentrations of the test waters

Test condition

Alkalinity (CaCO3

mg/L)

DOC

(mg/L)

Nitrate

(mg/L

NO3 –N)

Inhibitor Disinfectants

Condition 1: ALK15DOC7N1O

P1C1 15 7 1

Orthophosphate (1 mg/L P)

Chlorine (1 mg/L Cl2)

Condition 2: ALK250DOC1N1S

i24MC3 250 1 1

Sodium silicate (24 mg/L SiO2)

Monochloramine

(3 mg/L Cl2)


i24C1 250 1 7




i24MC3 250 7 7


Monochloramine

(3 mg/L Cl2)-


P1MC3 250 7 1

Orthophosphate (1 mg/L P)

Monochloramine

(3 mg/L Cl2)-


P1C1 250 7 7

Orthophosphate (1mg/L P)


134

134

The actual measured concentrations of each of the test water were listed in Table 7-17: The

actual concentrations of the test watersPhosphate only achieved 75% of its target

concentration. Chloride was about 1.5 times of its target concentration which increased the

CSMR up to 2.8 to 4.2. The increase in chloride concentration was due to disinfectant decay.

Table 7-17: The actual concentrations of the test waters

Test condition Inhibitor Sulfate (mg/L)

Chloride (mg/L)

CSMR

Condition 1:

ALK15DOC7N1OP1C1 0.78 ( mg/L P) 10.77 44.99 4.18

Condition 2:

ALK250DOC1N1Si24MC3

23.3 (mg/L SiO2)

11.20 33.63 3.00

Condition 3:

ALK250DOC1N7Si24C1

23.9 (mg/L SiO2)

11.32 31.38 2.77

Condition 4: ALK250DOC7N7Si24MC3 24.6 (mg/L

SiO2) 11.16 38.34 3.44

Condition 5: ALK250DOC7N1OP1MC3

0.77

( mg/L P) 11.13 37.84 3.40

Condition 6: ALK250DOC7N7OP1C1

0.72

( mg/L P) 10.69 44.74 4.19

Total lead was measured for the weekly composite samples at each week. The results were

summarized in Table 7-18 and plotted with respect with experimental time in Figure 6.1 to 6.6.

The coefficient of variation between the replicates was about 20-30% for all conditions, which

showed the repeatability was fair. T-tests were performed to evaluate the significance of the

difference between the means of total lead from two consecutive weeks. The results of the T-

tests were listed in Table 6.12. Only for one of the test conditions (#1), the difference of lead

release between week N and week (N-1) was significantly different at 95% confidence level.

135

135

Table 7-18: Total lead concentrations (µg/L) measured by ICP-MS

Repli

cate

1

Repli

cate

2

Repli

cate

3 Average STD

a to t n1+ n2-2, αb Δ

c

Condition 1:

ALK15DOC

7N1OP1C1d

Week 1 2500

0 2200

0 2300

0 23333.33 1527

Week 2 9300 8800 1100

0 9700.00 1153 12.34 2.13 Yes

Week 3 3700 3300 6700 4566.67 1858 4.07 2.13 Yes

Condition 2:

ALK250DO

C1N1Si24M

C3

Week 1 1100 1300 870 1090.00 215.17

Week 2 660 1100 650 803.33 256.97 1.48 2.13 NO

Week 3 670 1200 690 853.33 300.39 0.22 2.13 NO

Condition 3:

ALK250DO

C1N7Si24C1

Week 1 720 950 610 760.00 173.49

Week 2 460 730 830 673.33 191.40 0.58 2.13 NO

Week 3 770 1200 1100 1023.33 225.02 2.05 2.13 NO

Condition 4:

ALK250DO

C7N7Si24M

C3

Week 1 1500 1100 1500 1366.67 230.94

Week 2 2000 1400 1500 1633.33 321.46 1.17 2.13 NO

Week 3 2200 1700 2000 1966.67 251.66 1.41 2.13 NO

Condition 5:

ALK250DO

C7N1OP1M

C3

Week 1 760 1300 1100 1053.33 273.01

Week 2 1100 1100 1100 1100.00 0.00 0.29 2.13 NO

Week 3 1000 1300 1000 1100.00 173.21 0.00 2.13 NO

Condition 6:

ALK250DO

C7N7OP1C1

Week 1 1000 650 1100 916.67 236.29

Week 2 1500 850 1200 1183.33 325.32 1.15 2.13 NO

Week 3 960 1800 1100 1286.67 450.04 0.32 2.13 NO

Note:

a. STD= standard deviation

b. tn1+n2-2, α = t3+3-2, 0.5 = 2.13

c. Δ = significantly different at 95% confidence level between week N and week N-1

d. Note: In “ALK15DOC7N1OP1C1-R1”, ALK= alkalinity (mg/L CaCO3), DOC= dissolved

organic carbon (mg/L), N= Nitrate (mg/L N), OP = Orthophosphate (mg/L P), C= Chlorine

residual (mg/L), R= Replicate, Si= Silicate (mg/L), MC= Monochloramine residual (mg/L)

136

136

0

5000

10000

15000

20000

25000

30000

1 2 3

Time (week)

To

tal

Le

ad

Co

nc

en

tra

tio

n (

µg

/L)

Condition 1: PS-ALK15DOC7N1OP1C1

Figure 7-1: Total lead release of test condition 1: alkalinity at 15 mg/L CaCO3, DOC at 7 mg/L,

nitrate at 1 mg/L N, inhibitor at 1 mg/L P and disinfectant at 1 mg/L free chlorine (error bars

denote 95% confidence intervals)

137

137

0

200

400

600

800

1000

1200

1400

1600

1 2 3

Time (week)

To

tal

Lea

d C

on

ce

ntr

ati

on

(µ

g/L

)

Condition 2: PS-ALK250DOC1N1Si24MC3


nitrate at 1 mg/L N, inhibitor at 24 mg/L SiO2 and disinfectant at 3 mg/L monochloramine (error

bars denote 95% confidence intervals)

138

138

0

200

400

600

800

1000

1200

1400

1600

1 2 3

Time (week)

To

tal

Lea

d C

on

ce

ntr

ati

on

(µ

g/L

)

Condition 3: PS-ALK250DOC1N7Si24C1


nitrate at 7 mg/L N, inhibitor at 24 mg/L SiO2 and disinfectant at 1 mg/L free chlorine (error bars


139

139

0

500

1000

1500

2000

2500

3000

1 2 3

Time (week)

To

tal

Lea

d C

on

ce

ntr

ati

on

(µ

g/L

)



nitrate at 7 mg/L N, inhibitor at 24 mg/L SiO2 and disinfectant at 3 mg/L monochloramine (error


140

140

0

200

400

600

800

1000

1200

1400

1600

1800

1 2 3

Time (week)

To

tal

Lea

d C

on

ce

ntr

ati

on

(µ

g/L

)

Condition 5: PS-ALK250DOC7N1OP1MC3

Figure 7-5: Total lead release of test condition 5: alkalinity at 250mg/L CaCO3, DOC at 7 mg/L,

nitrate at 1 mg/L N, inhibitor at 1 mg/L P and disinfectant at 3 mg/L monochloramine (error


141

141

0.00

500.00

1000.00

1500.00

2000.00

2500.00

1 2 3

Time (week)

To

tal

Lea

d C

on

ce

ntr

ati

on

(µ

g/L

)



nitrate at 7 mg/L N, inhibitor at 1 mg/L P and disinfectant at chlorine at 1 mg/L (error bars


142

142

The Impact of Alkalinity on Lead Release

In Figure 6.7, as can be seen, low alkalinity had high lead release which agreed with Arnold’s

experiment (2011). The impact of galvanic corrosion tended to be higher with lower alkalinity.

The average lead release from Arnold’s experiment (2011) for low alkalinity was 3000 to 15000

µg/L, for high alkalinity was 500-2000 µg/L which also happened to be consistent with the

current study. However, in Triantafylliou’s (2011) study, when increased alkalinity from 15 to

100 mg/L CaCO3, the lead release levels were statistically similar. Triantafylliou’s study used

much higher CSMR (16), and the current study has CSMR of 2.8 to 4.2.

0

1000

2000

3000

4000

5000

6000

7000

8000

0 1 2 3 4 5 6 7

Test Conditions

To

tal L

ea

d (

µg

/L)

High alkalinity

Low alkalinity

Figure 7-7: Lead release comparison between high and low alkalinity (the data was the lead

release from week 3; error bars denote 95% confidence intervals)

143

143

The Impact of NOM and Nitrate on Lead Release

According to Korshin et al. (1999), lead release increased as the level of NOM increased for pure

lead coupon. Arnold (2011) showed NOM had a diminished influence on lead release with high

alkalinity upon the connection with copper which meant NOM’s impact on lead release due to

galvanic corrosion is not as great as to uniform corrosion/deposition corrosion. In the current

study, under high alkalinity, lead releases between high and low NOM levels were compared

(Figure 6.8). Lead levels were statistically similar between high and low level of NOM for low

level of nitrate (red bars), whereas lead level was significantly higher for high NOM when the

nitrate level was high (blue bars). This increase in lead release could be due to the combined

effect of high NOM and high nitrate level. No study was done on the interplay between nitrate

and NOM to lead release due to galvanic corrosion.

0

500

1000

1500

2000

2500

3000

Low NOM High NOM

To

tal

Lea

d (

µg

/L)

7 mg/L as N

1 mg/L as N

Figure 6-8: Impact of NOM and nitrate on lead release under high alkalinity (the data was the

lead release from week 3; error bars denote 95% confidence intervals)

144

144

The Impact of Inhibitors on Lead Release

Woszczynski (2011) studied sodium silicate and phosphate as corrosions inhibitors at a pilot scale.

The results of her pipe loop experiments showed that sodium silicate releases more lead and copper

than when using phosphate as a corrosion inhibitor. Edwards et al (2002) investigated the impact of

corrosion inhibitors to pure lead pipes. The results showed orthophosphate significantly reduced lead

release for aged pipe (about 3 yr), but was detrimental for new pipes (two weeks old) for stagnant

condition. Nguyen et al (2011) found that orthophosphate increased lead release from soldered

copper coupons. Arnold (2011) found that orthophosphate increased lead release in low alkalinity

water, whereas decreased lead release in high alkalinity water with no NOM for pipe rig tests. Arnold

(2011) was the only study on the impact of phosphate inhibitors to galvanic corrosion. For the current

study, the lead release between silicate and orthophosphate were not significant different at 95%

confidence level for the conditions tested which involved high alkalinity, high NOM and high nitrate

level (Figure 6.9).

0

500

1000

1500

2000

2500

3000

24 mg/L as SiO2 1 mg/L as P

To

tal

Lea

d (

µg

/L)

Figure 6-9: Impact of inhibitors under high alkalinity, high NOM and high nitrate level (the data

was the lead release from week 3, error bars denotes 95% confidence intervals)

145

145

Results on Galvanic Current and Anions

Galvanic current was measured by multi-meter in a daily basis during the three week period. The

galvanic current decreased over time (Figure 6.10 to 6.15), and in the third week of the

experiment, it became stable for all conditions. For low alkalinity, the current eventually

reached to 30 µA. For high alkalinity, the average current was between 60-80 µA. The highest

galvanic current measured in Arnold’s experiment was 36 µA. The galvanic current reported by

Triantafylliou’s (2011) was between 40 to 90 µA.

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

0 2 4 6 8 10 12 14 16 18 20

Experiment Time (days)

Ga

lva

nic

Cu

rre

nt

(uA

)


Figure 6-10: Galvanic current with respect to experiment time (error bars denote 95%

confidence intervals)

146

146

0.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

0 2 4 6 8 10 12 14 16 18 20


Ga

lva

nic

Cu

rre

nt

(uA

)


Figure 6-11: Galvanic current with respect to experiment time (error bars denote 95% confidence

intervals)

0.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

160.00

0 2 4 6 8 10 12 14 16 18 20


Ga

lva

nic

Cu

rre

nt

(uA

)



intervals)

147

147

0.00

20.00

40.00

60.00

80.00

100.00

120.00

0 2 4 6 8 10 12 14 16 18 20


Ga

lva

nic

Cu

rre

nt

(uA

)



intervals)

0.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

0 2 4 6 8 10 12 14 16 18 20


Ga

lva

nic

Cu

rre

nt

(uA

)



intervals)

148

148

0.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

160.00

0 2 4 6 8 10 12 14 16 18 20


Ga

lva

nic

Cu

rre

nt

(uA

)



intervals)

Sulfate, chloride, phosphate, nitrate and silicate concentrations were measured by HACH

spectrophotometer for the weekly composite samples (Table 7-19). The sulfate concentrations

were increased after contacting the pipe walls, but from the week 2 results, these concentrations

dropped back to its original concentration (10 mg/L). This extra sulfate came from the pipe wall

since sulphuric acid was used to pre-clean the lead pipes and not all of the sulfate were rinsed

off. The concentrations of chloride, nitrate and silicate were about the same before and after

entering the pipes. The concentration of phosphate decreased dramatically from 0.75 mg/L P to

an average of 0.35 mg/L P.

149

149

Table 7-19: Weekly composite waters

Sulfate

(mg/L) Chloride (mg/L)

Phosphate

(mg/L P)

Silicate (mg/L

SiO2)

Nitrate (mg/L N)

Avga STDb Avg STD CSMR Avg STD Avg STD Avg STD

Condition 1:

ALK15DOC7N1OP1

C1

Week 1 19.00 0.61 39.83 4.43 2.10 0.25 0.01 1.14 0.01

Week 2 14.19 1.67 45.41 6.08 3.20 0.27 0.02 1.03 0.03

Condition 2:

ALK250DOC1N1Si2

4MC3

Week 1 55.91 5.50 34.56 6.32 0.62 23.40 0.20 1.26 0.01

Week 2 13.56 0.47 37.87 5.37 2.79 24.00 0.10 1.14 0.01

Condition 3:

ALK250DOC1N7Si2

4C1

Week 1 36.63 1.56 30.90 5.07 0.84 21.90 0.30 6.79 0.25

Week 2 10.85 0.20 37.84 2.99 3.49 22.50 0.30 6.85 0.16

Condition 4:

ALK250DOC7N7Si2

4MC3

Week 1 17.57 0.68 41.11 5.79 2.34 23.90 0.20 6.95 0.12

Week 2 11.54 0.20 39.14 3.61 3.39 22.50 0.40 6.86 0.12

Condition 5:

ALK250DOC7N1OP

1MC3

Week 1 19.14 0.68 46.97 5.79 2.45 0.39 0.03 1.26 0.02

Week 2 11.66 0.20 45.97 3.61 3.94 0.00 0.00 1.14 0.01

Condition 6:

ALK250DOC7N7OP

1C1

Week 1 19.14 4.16 46.97 6.04 2.45 0.37 0.06 7.16 0.09

Week 2 11.66 0.27 45.97 4.99 3.94 0.00 0.00 6.85 0.12

Note:

a. Average from three replicates of pipe rigs

b. STD= standard deviation

150

150

Results on pH and ORP

The pH and ORP of the weekly composite were listed in Table 7-20. The pH increased 1 to 3

units in average, raised up to 8.8 to 10.8. pH was decreasing with respect with time. OPR was

inversely related to pH. The natural pH of all conditions were between 8.6 to 9.2, then they were

adjusted to 8.0 by bubbling CO2. The reason for the overall increase in pH was not clear. Based

on Arnold’s study, the micro-pH at the surface of the lead pipe dropped rapidly once the water

entered the pipe rig, and the pH would stay low (< 6) over 24 hours.

Table 7-20: pH and OPR

pH ORP (mV)

Average Average

Condition 1: ALK15DOC7N1OP1C1

Week 1 10.78 130.03

Week 2 10.14 140.57

Week 3 10.06 146.73

Condition 2:

ALK250DOC1N1Si24MC3

Week 1 9.35 178.43

Week 2 8.97 204.67

Week 3 8.83 210.00

Condition 3:

ALK250DOC1N7Si24C1

Week 1 9.63 171.73

Week 2 9.05 198.70

Week 3 8.91 209.33

Condition 4:

ALK250DOC7N7Si24MC3

Week 1 9.15 202.33

Week 2 8.78 213.33

Week 3 8.78 216.33

Condition 5:

ALK250DOC7N1OP1MC3

Week 1 9.03 211.33

Week 2 8.71 222.00

Week 3 8.64 223.33

Condition 6:

ALK250DOC7N7OP1C1

Week 1 9.22 202.33

Week 2 8.78 206.30

Week 3 8.75 216.33

Note: Average from three replicates of pipe rigs

151

151

0.00

50.00

100.00

150.00

200.00

250.00

0 5 10 15 20 25


OP

R(m

V)







Figure 6-16: OPR with respect to experiment time

0.00

2.00

4.00

6.00

8.00

10.00

12.00

0 5 10 15 20 25


pH







Figure 6-17: pH with respect to experiment time

152

152

Documents

IMPACT OF GALVANIC CORROSION ON LEAD …...ii ii IMPACT OF GALVANIC CORROSION ON LEAD RELEASE AFTER PARTIAL LEAD SERVICE LINE REPLACEMENT Emily Mi Zhou Master’s of Applied Science,