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
deviation of n=2. Some error bars were too small to see. ...................................................... 37
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. ...................................................... 38
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
95% confidence interval ......................................................................................................... 64
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
95% confidence interval ......................................................................................................... 73
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
95% confidence interval ......................................................................................................... 82
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
95% confidence interval ......................................................................................................... 84
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
95% confidence interval ......................................................................................................... 86
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
Figure 7-2: Total lead release of test condition 2: alkalinity at 250 mg/L CaCO3, DOC at 1
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
Figure 7-3: Total lead release of test condition 3: alkalinity at 250 mg/L CaCO3, DOC at 1
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
Figure 7-4: Total lead release of test condition 4: alkalinity at 250 mg/L CaCO3, DOC at 7
mg/L, nitrate at 7 mg/L N, inhibitor at 24 mg/L SiO2 and disinfectant at 3 mg/L
monochloramine (error bars denote 95% confidence intervals) ........................................... 139
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 bars denote 95% confidence intervals) ........................................... 140
Figure 7-6: Total lead release of test condition 6: alkalinity at 250 mg/L CaCO3, DOC at 7
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
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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).
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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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5
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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6
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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7
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
8
8
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
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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
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10
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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11
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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12
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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13
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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15
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
16
16
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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17
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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20
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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21
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
with DOC at 0 mg/L, chlorine at 3.5 mg/L Cl2. Note: the error bars represent one standard
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
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.
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 = 1 mg/L, Chlorine = 2.5 mg/L
DOC = 1 mg/L, Chlorine = 3.5 mg/L
DOC = 4 mg/L, Chlorine = 8 mg/L
DOC = 4 mg/L, Chlorine = 10 mg/L
DOC = 7 mg/L, Chlorine = 16 mg/L
DOC = 7 mg/L, Chlorine = 19 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)
DOC = 1 mg/L, Chlorine = 2.5 mg/L
DOC = 1 mg/L, Chlorine = 3.5 mg/L
DOC = 4 mg/L, Chlorine = 8 mg/L
DOC = 4 mg/L, Chlorine = 10 mg/L
DOC = 7 mg/L, Chlorine = 16 mg/L
DOC = 7 mg/L, Chlorine = 19 mg/L
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)
DOC = 1 mg/L, Monochloramine = 4 mg/L
DOC = 1 mg/L, Monochloramine = 6 mg/L
DOC = 4 mg/L, Monochloramine = 6 mg/L
DOC = 4 mg/L, Monochloramine = 9 mg/L
DOC = 7 mg/L, Monochloramine = 9 mg/L
DOC = 7 mg/L, Monochloramine = 12 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)
DOC = 1 mg/L, Monochloramine = 4 mg/L
DOC = 1 mg/L, Monochloramine = 6 mg/L
DOC = 4 mg/L, Monochloramine = 6 mg/L
DOC = 4 mg/L, Monochloramine = 9 mg/L
DOC = 7 mg/L, Monochloramine = 9 mg/L
DOC = 7 mg/L, Monochloramine = 12 mg/L
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
Chlorine residual for
alkalinity = 15 mg/L,
phosphate = 1 mg/L
2.63
2.92
Accept
Ho: u1 = u2
Chlorine residual for
alkalinity = 250 mg/L,
phosphate = 1 mg/L
Chlorine residual for
alkalinity = 250 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
46
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
47
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
49
49
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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51
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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53
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
)
55
55
Figure 5-14: The impact of disinfectant on galvanic current. Note: the error bar represents 95%
confidence interval
Design-Expert?Software
Average current (uA)
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
Design-Expert?Software
Average current (uA)
X1 = E: Inhibitor
Actual Factors
A: Alkalinity = 132.50
B: SNOM = 4.00
C: Nitrate = 4.00
D: Disinfectant = Average
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.
Design-Expert?Software
Average current (uA)
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
D: Disinfectant = Average
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
58
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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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59
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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60
Figure 5-18: Half-normal plot of total lead
Design-Expert?Software
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
|Standardized Effect|
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
Predicted vs. Actual
-2000
1750
5500
9250
13000
-1261.57 2303.82 5869.21 9434.61 13000.00
63
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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64
Figure 5-20: The impact of alkalinity on total lead release. Note: the error bar represents 95%
confidence interval
Design-Expert?Software
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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Figure 5-21: The impact of interaction of alkalinity and inhibitor on total lead release. Note: the
error bar represents 95% confidence interval
Design-Expert?Software
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
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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
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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
Design-Expert?Software
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
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Figure 5-23: The impact of interaction of SNOM and nitrate on total lead release. Note: the
error bar represents 95% confidence interval
Design-Expert?Software
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
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Figure 5-24: The impact of interaction of SNOM and disinfectant on total lead release. Note:
the error bars represent 95% confidence interval
Design-Expert?Software
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
Design-Expert?Software
W4-W12 Total lead
E1 orthophosphate 1 mg/L PE2 silicate 24 mg/L SiO2
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
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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
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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.
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Figure 5-27: The impact of disinfectant on total lead release. Note: the error bar represents
95% confidence interval
Design-Expert?Software
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
free chlorine 1 mg/L monochloramine 3 mg/L
0
1500
3000
4500
6000
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Figure 5-28: ORP comparisons between free chlorine and monochloramine
Design-Expert?Software
ORP (mV) X1 = D: Disinfectant
Actual FactorsA: Alkalinity = 132.50B: SNOM = 4.00C: Nitrate = 4.00E: Inhibitor = Average
D: Disinf ectant
OR
P (
mV
)
free chlorine 1 mg/L monochloramine 3 mg/L
0
182.5
365
547.5
730
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Figure 5-29: The impact of interaction of nitrate and disinfectant on total lead release. Note:
the error bars represent 95% confidence interval
Design-Expert?Software
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
free chlorine 1 mg/L monochloramine 3 mg/L
Interaction
D: Disinf ectant
W4
-W1
2 T
ota
l le
ad
0
1625
3250
4875
6500
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Figure 5-30: The impact of interaction of disinfectant and inhibitor on total lead release. Note:
the error bar represents 95% confidence interval
Design-Expert?Software
W4-W12 Total lead
E1 orthophosphate 1 mg/L PE2 silicate 24 mg/L SiO2
X1 = D: DisinfectantX2 = E: Inhibitor
Actual FactorsA: Alkalinity = 132.50B: SNOM = 4.00C: Nitrate = 4.00
E: Inhibitor
free chlorine 1 mg/L monochloramine 3 mg/L
Interaction
D: Disinf ectant
W4
-W1
2 T
ota
l le
ad
0
1588.47
3176.94
4765.41
6353.88
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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
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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
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Figure 5-32: Half-normal plot of dissolved lead
Design-Expert?Software
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
|Standardized Effect|
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
Predicted vs. Actual
-200.00
175.00
550.00
925.00
1300.00
-165.83 198.12 562.08 926.04 1290.00
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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
95% confidence interval
Design-Expert?Software
W6.W9, W12 Dissolved 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
150
300
450
600
A: Alkalinity
W6
.W9
, W1
2 D
isso
lve
d le
ad
One Factor
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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
Design-Expert?Software
W6.W9, W12 Dissolved lead
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
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Figure 5-37: The impact of interaction between alkalinity and nitrate on dissolved lead release.
Note: the error bar represents 95% confidence interval
Design-Expert?Software
W6.W9, W12 Dissolved lead
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
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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
95% confidence interval
Design-Expert?Software
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
Design-Expert?Software
W6.W9, W12 Dissolved 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
W6
.W9
, W1
2 D
isso
lve
d le
ad
0
150
300
450
600
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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
95% confidence interval
Design-Expert?Software
W6.W9, W12 Dissolved 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
150
300
450
600
B: SNOM
W6
.W9
, W1
2 D
isso
lve
d le
ad
One Factor
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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
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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
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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
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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.
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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
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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–
.
110
110
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.
111
111
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:
Standard Solution Method
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:
Standard Solution Method
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:
Standard Solution Method
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.
117
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
124
124
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
125
125
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
126
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
127
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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
129
129
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)
Condition 3: ALK250DOC1N7S
i24C1 250 1 7
Sodium silicate (24 mg/L SiO2)
Chlorine (1 mg/L Cl2)
Condition 4: ALK250DOC7N7S
i24MC3 250 7 7
Sodium silicate (24 mg/L SiO2)
Monochloramine
(3 mg/L Cl2)-
Condition 5: ALK250DOC7N1O
P1MC3 250 7 1
Orthophosphate (1 mg/L P)
Monochloramine
(3 mg/L Cl2)-
Condition 6: ALK250DOC7N7O
P1C1 250 7 7
Orthophosphate (1mg/L P)
Chlorine (1 mg/L Cl2)
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
Figure 7-2: Total lead release of test condition 2: alkalinity at 250 mg/L CaCO3, DOC at 1 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)
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
Figure 7-3: Total lead release of test condition 3: alkalinity at 250 mg/L CaCO3, DOC at 1 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)
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
)
Condition 4: PS-ALK250DOC7N7Si24MC3
Figure 7-4: Total lead release of test condition 4: alkalinity at 250 mg/L CaCO3, DOC at 7 mg/L,
nitrate at 7 mg/L N, inhibitor at 24 mg/L SiO2 and disinfectant at 3 mg/L monochloramine (error
bars denote 95% confidence intervals)
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
bars denote 95% confidence intervals)
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
)
Condition 6: PS-ALK250DOC7N7OP1C1
Figure 7-6: Total lead release of test condition 6: alkalinity at 250 mg/L CaCO3, DOC at 7 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)
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
)
Condition 1: PS-ALK15DOC7N1OP1C1
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
Experiment Time (days)
Ga
lva
nic
Cu
rre
nt
(uA
)
Condition 2: PS-ALK250DOC1N1Si24MC3
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
Experiment Time (days)
Ga
lva
nic
Cu
rre
nt
(uA
)
Condition 3: PS-ALK250DOC1N7Si24C1
Figure 6-12: Galvanic current with respect to experiment time (error bars denote 95% confidence
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
Experiment Time (days)
Ga
lva
nic
Cu
rre
nt
(uA
)
Condition 4: PS-ALK250DOC7N7Si24MC3
Figure 6-13: 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
0 2 4 6 8 10 12 14 16 18 20
Experiment Time (days)
Ga
lva
nic
Cu
rre
nt
(uA
)
Condition 5: PS-ALK250DOC7N1OP1MC3
Figure 6-14: Galvanic current with respect to experiment time (error bars denote 95% confidence
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
Experiment Time (days)
Ga
lva
nic
Cu
rre
nt
(uA
)
Condition 6: PS-ALK250DOC7N7OP1C1
Figure 6-15: Galvanic current with respect to experiment time (error bars denote 95% confidence
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
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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
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0.00
50.00
100.00
150.00
200.00
250.00
0 5 10 15 20 25
Experiment Time (days)
OP
R(m
V)
Condition 1: PS-ALK15DOC7N1OP1C1
Condition 2: PS-ALK250DOC1N1Si24MC3
Condition 3: PS-ALK250DOC1N7Si24C1
Condition 4: PS-ALK250DOC7N7Si24MC3
Condition 5: PS-ALK250DOC7N1OP1MC3
Condition 6: PS-ALK250DOC7N7OP1C1
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
Experiment Time (days)
pH
Condition 1: PS-ALK15DOC7N1OP1C1
Condition 2: PS-ALK250DOC1N1Si24MC3
Condition 3: PS-ALK250DOC1N7Si24C1
Condition 4: PS-ALK250DOC7N7Si24MC3
Condition 5: PS-ALK250DOC7N1OP1MC3
Condition 6: PS-ALK250DOC7N7OP1C1
Figure 6-17: pH with respect to experiment time
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