IMPACT OF GALVANIC CORROSION ON LEAD RELEASE AFTER PARTIAL LEAD SERVICE LINE REPLACEMENT

Transcription

1 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

2 ii 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 (2 5-1 v ) 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. ii

3 iii 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. iii

4 iv TABLE OF CONTENTS ABSTRACT... ii ACKNOWLEDGEMENTS... iii TABLE OF CONTENTS... iv LIST OF TABLES... vii LIST OF FIGURES... x NOMENCLATURE... xvi 1 Introduction Background Objectives Literature Review The Impact of Water Chemistry on Lead Corrosion Chloride to Sulfate Mass Ratio Orthophosphate Disinfectant Natural Organic Matter Nitrate Sodium Silicate Aged Lead Pipes Relationship between Galvanic Current, Galvanic Corrosion and Lead Release Experimental Design Impact of Alkalinity, Nitrate, NOM, Disinfectant, Inhibitor on Lead Release after Partial Lead Pipe Replacement Materials and Methods Test Water Preparation NOM iv

5 v Nitrate Inhibitor CSMR Alkalinity ph Disinfectant Analysis Methods Total Organic Carbon (TOC) ph Chlorine and Monochloramine Residual Oxidation-Reduction Potential Galvanic Current Analysis of Silica, Phosphorus, Nitrate, Sulfate and Chloride Lead Analysis Pipe Rig Results Chlorine and Monochloramine Demand Test Chlorine Demand Tests Monochloramine Demand Tests Impact of Alkalinity and Inhibitor on Chlorine Demand Significant Factors Affecting Galvanic Current after Partial Lead Pipe Replacement Factors that Affect the Size of Galvanic Current Conductivity of Synthetic Water Significant Factors Affecting Galvanic Current v

6 vi 5.3 Water Quality Factors Affecting Total Lead Release after Partial Lead Pipe Replacement Water Quality Factors Affecting Dissolved Lead Release after Partial Lead Pipe Replacement Galvanic Current and Lead Release Relationship Conclusions Reference List Appendices Sample Calculations Chlorine Dose Required to Give a Specific Residual Concentration at the Desired Time Experimental Procedures Chlorine/monochloramine Demand Test ph Control by the Addition of Carbon Dioxide Measure Concentrations of Silica, Phosphorus, Nitrate, Sulfate and Chloride Raw Data Chlorine/monochloramine Demand Test Galvanic Current Data Total Lead Data Dissolved Lead Data Test Water Parameters Inhibitor Residual and Disinfectant Residual in the Weekly Composite Water Preliminary Results vi

7 vii 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 Table 3-2: 2 v factorial design for water chemistry factors Table 4-1: Filtered stock solution preparation outline Table 4-2: Total organic carbon reagents Table 4-3: Total organic carbon instrument conditions Table 4-4: Total organic carbon method outline Table 5-1: Test conditions for the chlorine demand test 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 Table 5-3: Test conditions for the monochloramine demand test 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 Table 5-5: Test conditions to examine the influence of alkalinity and inhibitor Table 5-6: The average, standard deviation and variance values for chlorine residual on the 9 th day Table 5-7: T-test results Table 5-8: Conductivity approximation based on the major ion species in the water (equivalent conductivity of ion (λ i ), data from (Harned and Owen, 1964)) Table 5-9: Analysis of variance table of total lead Table 5-10: Analysis of variance table of dissolved lead vii

8 viii Table 5-11: Summary table of significant factors Table 5-13: Performance comparison of corrosion inhibitor Table 7-1: The amount of salt needed for preparing working solutions containing different ions Table 7-2: The volume of working solution needed to prepare 2 L of test water Table 7-3: Free chlorine residual (mg/l Cl 2 ) measured over 11 days Table 7-4: ph of chlorine demand test measured over 11 days Table 7-5: Monochloramine residual (mg/l Cl 2 ) measured over 11 days Table 7-6: ph of monochloramine demand test measured over 11 days Table 7-7: Galvanic current data Table 7-8: Measured total lead release in the weekly composite water Table 7-9: Calculated maximum lead release using Equation Table 7-10: Measured dissolved lead release in the weekly composite water Table 7-11: Electric conductivity of test water Table 7-12: OPR of test water Table 7-13: Orthophosphate residual in the weekly composite water Table 7-14: Silicate residual in the weekly composite water Table 7-15: Disinfectant residual in the weekly composite water Table 7-16: The test concentrations of the test waters Table 7-17: The actual concentrations of the test waters viii

9 ix Table 7-18: Total lead concentrations (µg/l) measured by ICP-MS Table 7-19: Weekly composite waters Table 7-20: ph and OPR ix

10 x 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 Figure 4-2: Total organic carbon quality control chart (3.0 mg/l) (July to December, 2012) Figure 4-3: Photo of a pipe rig set-up Figure 4-4: The lead portion and copper portion are separated by an insulating spacer and connected by an external wire 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 Cl 2. Note: the error bars represent one standard deviation of n=2. Some error bars were too small to see 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 Figure 5-3: Log-chlorine residual concentration versus time plots (time = 4 hr to 11 day) Figure 5-4: Initial free chlorine concentration versus free chlorine residual concentration on the 9 th day 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 Cl 2. Note: the error bars represent one standard deviation of n=2. Some error bars were too small to see 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 Figure 5-7: Log-monochloramine residual concentration versus time (time = 4 hr to 11 day) x

11 xi Figure 5-8: Initial monochloramine concentration versus monochloramine residual concentration on the 9 th day 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 Figure 5-11: Temporal trend of average galvanic current. Note: the error bars represent one standard deviation of n= 5. ALK= alkalinity (mg/l CaCO 3 ), DOC= dissolved organic carbon (mg/l), N= nitrate (mg/l N), OP = orthophosphate (mg/l P), Si = silicate (mg/l SiO 2 ), C= Chlorine residual (mg/l Cl 2 ), MC = monochloramine residual (mg/l Cl 2 ) Figure 5-13: Predicted and actual galvanic current (µa). The predicted values were calculated using ANONA model Figure 5-14: The impact of alkalinity on galvanic current. Note: the error bar represents 95% confidence interval Figure 5-15: The impact of disinfectant on galvanic current. Note: the error bar represents 95% confidence interval Figure 5-16: The impact of inhibitor on galvanic current. Note: the error bar represents 95% confidence interval Figure 5-17: The impact of alkalinity and inhibitor interaction to galvanic current. Note: the error bar represents 95% confidence interval Figure 5-18: Temporal trend of total lead release Note: ALK= alkalinity (mg/l CaCO 3 ), 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) Figure 5-19: Half-normal plot of total lead xi

12 xii Figure 5-20: Predicted and actual total lead release Figure 5-21: The impact of alkalinity on total lead release. Note: the error bar represents 95% confidence interval Figure 5-22: The impact of interaction of alkalinity and inhibitor on total lead release. Note: the error bar represents 95% confidence interval Figure 5-23: The impact of SNOM on total lead release. Note: the error bar represents 95% confidence interval Figure 5-24: The impact of interaction of SNOM and nitrate on total lead release. Note: the error bar represents 95% confidence interval Figure 5-25: The impact of interaction of SNOM and disinfectant on total lead release. Note: the error bars represent 95% confidence interval Figure 5-26: The impact of interaction of SNOM and inhibitor on total lead release. Note: the error bars represent 95% confidence interval 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) Figure 5-28: The impact of disinfectant on total lead release. Note: the error bar represents 95% confidence interval Figure 5-29: ORP comparisons between free chlorine and monochloramine Figure 5-30: The impact of interaction of nitrate and disinfectant on total lead release. Note: the error bars represent 95% confidence interval Figure 5-31: The impact of interaction of disinfectant and inhibitor on total lead release. Note: the error bar represents 95% confidence interval Figure 5-32: Temporal trend of dissolved lead release. Note: ALK= alkalinity (mg/l CaCO 3 ), DOC= dissolved organic carbon (mg/l), N= nitrate (mg/l N), OP = xii

13 xiii orthophosphate (mg/l P), C= chlorine residual (mg/l), Si= silicate (mg/l), MC= monochloramine residual (mg/l) Figure 5-33: Half-normal plot of dissolved lead Figure 5-34: Predicted and actual values of dissolved lead release Figure 5-35: The impact of alkalinity on dissolved lead release. Note: the error bar represents 95% confidence interval Figure 5-36: Eh-pH diagram for the Pb-CO 3 -H 2 O system at 25 C and 1 atm (adjusted from Scheetz, 2004) Figure 5-37: The impact of nitrate on dissolved lead release. Note: the error bar represents 95% confidence interval Figure 5-38: The impact of interaction between alkalinity and nitrate on dissolved lead release. Note: the error bar represents 95% confidence interval Figure 5-39: The impact of inhibitor on dissolved lead release. Note: the error bar represents 95% confidence interval Figure 5-40: The impact of interaction between alkalinity and inhibitor on dissolved lead release. Note: the error bar represents 95% confidence interval Figure 5-41 : The impact of SNOM on dissolved lead release. Note: the error bars represent 95% confidence interval Figure 5-42: Correlation of galvanic current to total lead release during Week 4 to Week Figure 5-43: Demonstrating galvanic relationship between predicted (calculated using current values) vs. actual total lead leaching 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 xiii

14 xiv 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 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 Figure 7-1: Total lead release of test condition 1: alkalinity at 15 mg/l CaCO 3, 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) Figure 7-2: Total lead release of test condition 2: alkalinity at 250 mg/l CaCO 3, DOC at 1 mg/l, nitrate at 1 mg/l N, inhibitor at 24 mg/l SiO 2 and disinfectant at 3 mg/l monochloramine (error bars denote 95% confidence intervals) Figure 7-3: Total lead release of test condition 3: alkalinity at 250 mg/l CaCO 3, DOC at 1 mg/l, nitrate at 7 mg/l N, inhibitor at 24 mg/l SiO 2 and disinfectant at 1 mg/l free chlorine (error bars denote 95% confidence intervals) Figure 7-4: Total lead release of test condition 4: alkalinity at 250 mg/l CaCO 3, DOC at 7 mg/l, nitrate at 7 mg/l N, inhibitor at 24 mg/l SiO 2 and disinfectant at 3 mg/l monochloramine (error bars denote 95% confidence intervals) Figure 7-5: Total lead release of test condition 5: alkalinity at 250mg/L CaCO 3, 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) Figure 7-6: Total lead release of test condition 6: alkalinity at 250 mg/l CaCO 3, 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) xiv

15 xv 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) xv

16 xvi NOMENCLATURE ANOVA CSMR DBPs DOC IHSS LCR MCL NOM ORP PACl PVC PLSLR SHE SNOM TOC Analysis of variance Chloride to sulfate mass ratio Disinfection byproducts Dissolved organic carbon International Humic Substances Society Lead and copper rule Maximum contaminant level Natural organic matter Oxidation reduction potential Polyaluminum chloride Polyvinyl chloride Partial lead service line replacement Standard hydrogen electrode Suwannee river natural organic matter Total organic carbon xvi

17 1 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 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). 1

18 2 Anodic Reaction: Pb (s) Pb +2 (aq) + 2e Cathodic Reaction: O 2 + 4e - + 2H 2 O 4OH 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) Cu 2+ +2e - = Cu Pb e - = Pb Note: SHE is standard hydrogen electrode 2

19 3 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. 3

20 4 2 Literature Review 2.1 The Impact of Water Chemistry on Lead Corrosion 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. [ Cl CSMR = [ SO ] 2 4 ] 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 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. 4

21 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 (2-n) by the formation of PbCl n complexes and sulfate contributed to the formation of PbSO 4 (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) 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 [Pb 5 (PO 4 ) 3 OH] and tertiary lead orthophosphate [Pb 3 (PO 4 ) 2 ] which are less soluble than lead carbonate, PbCO 3 (Schock, 1989). 5

22 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 CaCO 3 ) and high (250 mg/l CaCO 3 ) 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 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 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 6

23 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 [PbCO 3 ] and hydrocerussite [Pb (CO 3 ) 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-pbo 2 ) and scrutinyite (α-pbo 2 ) 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 7

24 8 the impact of chloramines on lead leaching, as well as on how switching disinfectants can influence lead leaching under galvanic corrosion 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 (CO 3 ) 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, PbO 2 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 8

25 9 reductive dissolution of PbO 2 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 Nitrate Nitrate (NO - 3 ) 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 NO 3 -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 leadbearing 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 9

26 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). NH 3 Cl N 2 + NH 3 + 3Cl - + 3H + (Nguyen et al., 2011) 2-2 NO Pb NO PbO (Dudi, 2004) 2-3 NO Pb + 2H 2 O NH 3 + 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 NO 3 -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 NO 3 -N for nine weeks (Nguyen et al., 2011). The lowest lead leaching was 18 µg/l with 0 mg/l NO 3 -N, and the highest lead leaching was 4000 µg/l with 10 mg/l NO 3 -N (Nguyen et al., 2011). For low nitrate concentrations (0 to 1 mg/l NO 3 -N), lead leaching increased with nitrate concentration but decreased with exposure time. However, for high nitrate concentrations (2.5 to 10 mg/l NO 3 -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 Sodium Silicate Sodium silicate (Na 2 SiO 3 ) 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

27 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 (SiO 2 ) to alkali (Na 2 O or K 2 O) of up to 4.0. The most common commercial liquid sodium silicate is a product having a weight ratio of silica to alkali (as Na 2 O) 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 SiO 2 is recommended for the first month or two, followed by a maintenance dosage of 8 to 10 mg/l as SiO 2 (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 [PbCO 3 ], hydrocerussite [Pb 3 (CO 3 ) 2 (OH) 2], plumbonacrite (Pb 10 (CO 3 ) 6 (OH) 6 O), litharge (PbO), and plattnerite (PbO 2 ) (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 11

28 12 being μg/l (Triantafyllidou et al., 2010). For the one-year old lead pipes, the highest leaching level was 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 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 PbO 2 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 PbO 2 (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 R 2 as high as 0.44 for high CSMR (16.2), galvanic corrosion is likely the dominating source of lead release. As R 2 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 CaCO 3 ) water, the addition of orthophosphate (2 mg/l P) tripled lead concentration from 6000 µg/l to µg/l, but the current only increased from 25 µa to 35 µa (Arnold, 2011). In high alkalinity (250 mg/l CaCO 3 ) water, as orthophosphate (2 mg/l P) was added, lead concentration decreased from 12

29 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. 13

30 14 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. 14

31 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 NO 3 -N (U.S Environmental Protection Agency, 1985), so nitrate was varied between 0 and 10 mg/l NO 3 -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 CaCO 3 ) 12 as low, 250 as high Arnold, Triantafyllidou et al., 2010 Nitrate (mg/l NO 3 -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 Cl 2 ) Inhibitor (mg/l) Chlorine: to 3 Woszczynski,2011 Lytle and Schock, 2005 Chloramines: 4 Triantafyllidou et al., 2010 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 (2 5-1 v ) design was adopted which resulted in 16 testing 15

32 conditions. 2 v 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 5-1 the main effects, a 2 v design is able to capture the major effects between the factors. Design Expert software was used to generate the test conditions based on the abovementioned 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. 16

33 17 Table 3-2: 2 v 5-1 factorial design for water chemistry factors Run# Factor A: Alkalinity Factor B: SNOM Factor C: Nitrate Factor D: Disinfectant Factor E: Inhibitor Response a, b, c a, b, c a, b, c a, b, c a, b, c a, b, c a, b, c a, b, c a, b, c a, b, c a, b, c a, b, c a, b, c a, b, c a, b, c a, b, c Note: Factor 1: Alkalinity (mg/l CaCO 3 ) Factor 2: SNOM (mg/l DOC) Factor 3: Nitrate (mg N/L NO 3 )

34 18 Factor 4: Disinfectant Factor 5: Inhibitor None Monochloramine Orthophosphates None (3 mg-cl 2 /L) (1 mg-p /L) Chlorine (1 mg-cl 2 /L) Sodium silicate (24 mg-sio 2 /L) a- total lead (µg/l), b- dissolved lead (µg/l), c- galvanic current (µa) 18

35 19 4 Materials and Methods 4.1 Test Water Preparation The volume of test water to fill one pipe rig (1 meter long) was 150 cm 3 ( 0.15 L) using Equation 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 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 wt % carbon, 4.19 wt % hydrogen, 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 ( mg/l DOC) (Table 4-1: Filtered stock solution preparation outline and dosing an 19

36 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 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 Calculate the volume of stock solution need to be added to make up 1 and 7 mg/l DOC Nitrate The target levels for nitrate in the test water were 1 and 7 mg-n /L NO 3. This was accomplished by adding a previously made nitrate stock solution to Milli-Q water. A 250 ml nitrate stock solution (1400 mg/l NO 3 -N) was prepared by adding 2.13 g of NaNO 3 (Sigma-Aldrich Corporation, Oakville, ON) to Milli-Q water (Nguyen et al., 2011c). Nitrate level were verified as described in Section 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 SiO 2 and Na 2 O with 37.5% solids, was used to make test water containing 24 mg/l SiO 2 (Woszczynski, 2011). For each litre of test water, 0.06 ml of sodium silicate solution was added. Sodium orthophosphate (Na 2 HPO 4 ) (Sigma-Aldrich Corporation, Oakville, ON) was used to make an orthophosphate stock solution of 200 mg/l as P (Arnold, 2011). A 250 ml 20

37 21 orthophosphate stock solution was made by adding g of Na 2 HPO 4 to Milli-Q water. Silica and phosphorous level were verified as described in Section 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 (K 2 SO 4 ) (Sigma-Aldrich Corporation, Oakville, ON) were used to make a stock solution containing 5000 mg/l Cl - 2- and 2000 mg/l SO 4 (Nguyen et al., 2011b). The concentration of chloride and sulfate were verified as described in Section Alkalinity The target alkalinity levels for the test water were 15 mg/l and 250 mg/l as CaCO 3, respectively. The target alkalinity was made up by sodium bicarbonate (NaHCO 3 ) (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, CaCO 3 + H 2 O + CO 2 Ca(HCO 3 ) CaCO 3 has a molecular weight of 100 g/mol. HCO - 3 has a molecular weight of 61 g/mol. Therefore, each mole of Ca (HCO 3 ) 2 corresponds to one mole of CaCO 3 (100 g) and contains (2-61) = 122 g of HCO 3. Hence, 250 mg /L CaCO 3 corresponds to (250 / ) = 305 mg/l - HCO 3. In 305 mg/l HCO - 3, 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 CaCO 3. Sodium bicarbonate (NaHCO 3 ) (Sigma-Aldrich Corporation, Oakville, ON) was used to make a stock solution containing 5000 mg/l TIC by adding 8.75 g NaHCO 3 in 250 ml Milli-Q water. 21

38 ph The ph of each test waters was adjusted to 8.0 ± 0.1. Common strong acid such as nitric acid (HNO 3 ), hydrochloric acid (HCl) and sulfuric acid (H 2 SO 4 ) would introduce undesired anions into the test water. Hence, ph was adjusted by adding 99.9% pure CO 2 gas to the test water prior to filling the pipes (Arnold, 2011; Nguyen et al., 2011c). For detailed procedures please see Section ph of the test waters can be measured as described in Section 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 Monochloramine working solution was prepared using sodium hypochlorite solution and ammonium hydroxide (NH 4 OH) 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

39 Analysis Methods 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 CO 2, 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 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 (H 2 SO 4 ) 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 , 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). 23

40 TOC concentration (mg/l) Area count y = x R 2 = Concentration (mg/l) Figure 4-1: Example total organic carbon calibration curve Upper CL Upper WL Mean Lower WL Lower CL Figure 4-2: Total organic carbon quality control chart (3.0 mg/l) (July to December, 2012) 24

41 25 Table 4-2: Total organic carbon reagents Reagent Supplier and Purity Sodium persulphate [Na 2 S 2 O 8 ] (100 g/l) Aldrich, 98+% Potassium hydrogen phthalate [C 8 H 5 KO 4 ] Aldrich, 98+% Sulphuric acid, concentrated [H 2 SO 4 ] 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 Stock solution (1 g/l): Running standard (3 mg/l): Blanks: Table 4-4: Total organic carbon method outline Dissolve g of anhydrous C 8 H 5 KO 4 in about 500 ml Milli-Q water and bring volume to 1 L using volumetric flask with Milli-Q water. 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. Use 40 ml of Milli-Q water 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. 25

42 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 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 Galvanic Current Galvanic current between copper pipe and lead pipe was conducted using a RadioShack multimeter (Model # ) 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. 26

43 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 (SiO 2 ) was measured using HACH silicomolybdate Method (8185) for high range (1 to 100 mg/l SiO 2 ). 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-NO 3 (APHA, 1998). Sulfate was measured using HACH SulfaVer 4 Method Powder Pillows (8051) 2- which was adapted from Standard Methods 4500-SO 4 (APHA, 1998). Experimental procedures are in Section 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. 27

44 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. 28

45 29 Figure 4-4: The lead portion and copper portion are separated by an insulating spacer and connected by an external wire 29

46 30 5 Results 5.1 Chlorine and Monochloramine Demand Test 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 NO 3 N, orthophosphate at 1 mg/l P and alkalinity at 250 mg/l CaCO 3. Experimental procedures are listed in Section and raw data in Section Table 5-1: Test conditions for the chlorine demand test DOC (mg/l) Initial chlorine dosage 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 Cl 2. 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. 30

47 Free chlorine residual concentration (mg/l) DOC = 0 mg/l, Chlorine = 3.5 mg/l Time (day) 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 Cl 2. 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: 31

48 Free chlorine residual concentration (mg/l) 32 If Equation 5.1 is converted to a log form, it becomes: C t = C 0 e -kt 5-1 ln C t = -kt + ln C where C t = chlorine concentration (mg/l) at time t C 0 = initial chlorine concentration (mg/l) t = time (day) k = the first-order decay constant = the slope of the linear function when plotting ln C t 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 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 Time (day) 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

49 In(Ct) 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) 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 2 y = x R 2 = y = x R 2 = y = x R 2 = y = x R 2 = y = x R 2 = y = x R 2 = Time (day) Figure 5-3: Log-chlorine residual concentration versus time plots (time = 4 hr to 11 day) 33

50 34 To find the initial dosage that can provide 1 mg/l chlorine at the 9 th 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 R 2 > 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 9 th 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 C 0 was then plotted against the calculated C t on the 9 th day for each of the initial concentrations (Figure 5-4), and a linear function was fitted to this data, according to the following equation: C 0 = f + e C t 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 Cl 2 ) at the desired time (9 th day), by substituting C t, 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 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. 34

51 Initial chlorine concentration (mg/l) DOC = 1 mg/l DOC = 4 mg/l DOC = 7 mg/l y = x y = x y = x Chlorine residual concentration (mg/l) Figure 5-4: Initial free chlorine concentration versus free chlorine residual concentration on the 9 th 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 C t calculated on the 9th day e f Target c t on 9 th day Estimated initial chlorine conc. to provide 1 mg/l residual (mg/l) Note: k and a are parameters for Equation 5-3, e and f are parameters for Equation

52 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 NO 3 N, orthophosphate of 1 mg/l P and alkalinity of 250 mg/l CaCO 3. Experimental procedures were listed in Section and raw data in Table 5-3: Test conditions for the monochloramine demand test DOC (mg/l) Initial doses of monochloramine (mg/l) 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. 36

53 Monochloramine residual concentration (mg/l) DOC = 0 mg/l, Monochloramine = 6 mg/l Time (day) 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 Cl 2. 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. 37

54 Monochloramine residual concentration (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 Time (day) 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

55 Ln (C t ) y = x R2 = y = x R2 = y = x R2 = y = x R2 = y = x R 2 = y = x R 2 = 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 Time (day) Figure 5-7: Log-monochloramine residual concentration versus time (time = 4 hr to 11 day) 39

56 Initial monochloramine concentration (mg/l) y = x DOC = 1 mg/l DOC = 4 mg/l DOC = 7 mg/l 6 y = x y = x Monochloramine residual concentration (mg/l) Figure 5-8: Initial monochloramine concentration versus monochloramine residual concentration on the 9 th 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 monochloramine (mg/l) k a C t calculated on the 9th day e f Target c t on 9 th day Estimated initial monochloramine conc. (mg/l)

57 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 NO 3 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 (CaCO 3 mg/l) Silica (SiO 2 mg/l) PO 4 3- (PO 4 -P mg/l) As can be seen in Figure 5-9, the three chlorine decay curves showed similar decreasing trends. 41

58 Chlorine residual concentration (mg/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 Time (day) 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 9 th 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. 42

59 43 Table 5-6: The average, standard deviation and variance values for chlorine residual on the 9 th day Chlorine residual (mg/l) on the 9 th day Average Standard Deviation Variance Condition A: Alkalinity = 250 mg/l, phosphate = 1 mg/l Condition B: Alkalinity = 15 mg/l, phosphate = 1 mg/l Condition C: Alkalinity = 250 mg/l, silicate = 24 mg/l To perform the statistical analysis, the null (H o ) and alternative (H A ) hypotheses were first defined as: H o : u 1 = u 2, the mean from population 1 and population 2 are the same H A : u 1 < u 2, the mean from population 1 and population 2 are different Assume both populations are normally distributed. If t 0 > t n1+n2-2, α, (α = 0.05), then H o is rejected in favor of H A which means the two means are different at 95% confidence level. t 0= x S n 1 x 1 S n Where n 1 and n 2 are the sample sizes, x1and x 2 are the sample means, and S 1 and S 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 =

60 44 t 0 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 t 0 t n1+n2-2, α Result Chlorine residual for alkalinity = 250 mg/l, Chlorine residual for alkalinity = 15 mg/l, Accept phosphate = 1 mg/l phosphate = 1 mg/l H o : u 1 = u 2 Chlorine residual for alkalinity = 250 mg/l, Chlorine residual for alkalinity = 250 mg/l, Accept phosphate = 1 mg/l silicate = 24 mg/l H o : u 1 = u 2 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. 44

61 Significant Factors Affecting Galvanic Current after Partial Lead Pipe Replacement 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): E c - E a = I (R e + R m ) 5-6 where R e is the resistance of the electrolytic portion of the galvanic cell R m is the resistance of the metallic portion of the galvanic cell E c is the effective potential of the cathodic member of the couple E a 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 45

62 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 (E c - E a ) was the considered the same for all pipe rigs. For aged pipes, R m, 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, R m should be different for each pipe rig. Electrolyte, which was the synthetic water in this experiment, was different among different pipe rigs, so R e 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 46

63 47 pipe rigs to exclusively electrolyte chemical properties; the metallic resistance would confound the measurements Conductivity of Synthetic Water Since the conductivity of synthetic water is important to R e, they were calculated. κ = Σ α i λ i C i, 5-7 where κ is conductivity of the solution, α i is fraction of the i th constituent present as the free ion λ i is equivalent conductivity of the i th ion, C i, is concentration of the i th species. with α i, 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 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.. 47

64 48 Table 5-8: Conductivity approximation based on the major ion species in the water (equivalent conductivity of ion (λ i ), data from (Harned and Owen, 1964)) Controlled parameter CSMR ph Alkalinity Nitrate Disinfectant Inhibitor SNOM Controlled level mg/l CaCO 3 15 mg/l CaCO 3 7 mg/l N 1mg/L N 1 mg/l Cl 2 free chlorine residual Ions Concentration (mg/l) Milliequivalents per liter (meq/l) Conductivity (µs/cm) K SO Na Cl H OH Na HCO Na HCO Na NO Na NO Na Cl Total (µs/cm) mg/l Cl 2 H monochloramine residual Cl Na mg/l P H PO mg/l SiO 2 Na OH mg/l DOC mg/l DOC

65 Half-Normal % Probability 49 In the experiment, the conductivity of all synthetic water was measured and listed in Table 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. Design-Expert?Software Electric conductivity of syntheic water Half-Normal Plot Shapiro-Wilk test W-value = p-value = A: Alkalinity B: SNOM C: Nitrate D: Disinfectant E: Inhibitor Positive Effects Negative Effects C B BD E A D Standardized Effect Figure 5-10: Half-normal plot of measured electric conductivity of synthetic waters 49

66 Galvanic Current (µa) 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 ALK15DOC7N1OP1C1 ALK250DOC1N1Si24MC3 ALK250DOC1N7Si24C1 ALK250DOC7N7Si24MC3 ALK250DOC7N1OP1MC3 ALK250DOC7N7OP1C1 Alk15DOC7N7OP1MC3 Alk250DOC1N7 OP1MC3 Alk15DOC1N7 Si24MC3 Alk15DOC7N7 Si24C1 Alk15DOC1N1 OP1MC3 Alk15DOC1N1 OP1MC3 Alk15DOC1N7 OP1C1 Alk250DOC7N1 Si24C1 Alk250DOC1N1 OP1C1 Alk15DOC1N1 Si24C Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Week 9 Week 11Week 12 Figure 5-11: Temporal trend of average galvanic current. Note: the error bars represent one standard deviation of n= 5. ALK= alkalinity (mg/l CaCO 3 ), DOC= dissolved organic carbon (mg/l), N= nitrate (mg/l N), OP = orthophosphate (mg/l P), Si = silicate (mg/l SiO 2 ), C= Chlorine residual (mg/l Cl 2 ), MC = monochloramine residual (mg/l Cl 2 ) 50

67 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 The R 2 for the ANOVA was Table 5-9: Analysis of variance table of galvanc current Source Sum of Squares df Mean Square F Value p-value Prob > F Model A-Alkalinity B-SNOM C-Nitrate D-Disinfectant E-Inhibitor AE Residual Cor Total* Note: The Model F-value of implies that the model is significant. Value of "Prob > F" less than indicates that the model term is significant. *= Total corrected for the mean 51

68 Predicted 52 Design-Expert?Software Average current Predicted vs. Actual Color points by value of Average current : Actual 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 R e and R m, where R e mostly depends on electrolyte conductivity. If the impact of R m on galvanic current was relatively small when compared to the impact of R e., 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. 52

69 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 CaCO 3, 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 CaCO 3. In this study, the current increased by 12 µa for the large increase in alkalinity (15 to 250 mg/l CaCO 3 ). 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 R m increased, the impact on galvanic current due to decreasing R e was offset by increasing R m. 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. R m changed and affected the galvanic current. Two types of inhibitor were compared in this study, 1 mg-p /L orthophosphate and 24 mg- SiO 2 /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 53

70 Average current (ua) 54 galvanic current. The average galvanic current in the presence of 24 mg-sio 2 /L silicate (22 µa) was higher than 1 mg/l P orthophosphate (17 µa) (Figure 5-15). 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 A: Alkalinity Figure 5-13: The impact of alkalinity on galvanic current. Note: the error bar represents 95% confidence interval. 54

71 Average current (ua) 55 Design-Expert?Software Average current (ua) X1 = D: Disinfectant Actual Factors A: Alkalinity = B: SNOM = 4.00 C: Nitrate = 4.00 E: Inhibitor = Average free chlorine 1 mg/l monochloramine 3 mg/l D: Disinfectant Figure 5-14: The impact of disinfectant on galvanic current. Note: the error bar represents 95% confidence interval 55

72 Average current (ua) 56 Design-Expert?Software Average current (ua) X1 = E: Inhibitor Actual Factors A: Alkalinity = B: SNOM = 4.00 C: Nitrate = 4.00 D: Disinfectant = Average orthophosphate 1 mg/l P silicate 24 mg/l SiO2 E: Inhibitor Figure 5-15: The impact of inhibitor on galvanic current. Note: the error bar represents 95% confidence interval 56

73 Average current (ua) 57 The interaction between alkalinity and inhibitor also significantly affected galvanic current (Figure 5-16). At the low alkalinity (15 mg/l CaCO 3 ), there was little difference in the galvanic current in waters treated with silicate or orthophosphate, but at the higher alkalinity (250 mg/l CaCO 3 ), the silicate-treated water showed a significantly higher galvanic current than the orthophosphate-treated water. Design-Expert?Software Average current (ua) E1 orthophosphate 1 mg/l P E2 silicate 24 mg/l SiO2 X1 = A: Alkalinity X2 = E: Inhibitor 40 Interaction E: Inhibitor Actual Factors B: SNOM = 4.00 C: Nitrate = 4.00 D: Disinfectant = Average A: Alkalinity 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 CaCO 3 ), free chlorine disinfectant and orthophosphate inhibitor can help to restrain galvanic corrosion. 57

74 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 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 SNOMnitrate (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 R 2 for the model was

75 Total lead (µg/l ) ALK15DOC7N1OP1C1 ALK250DOC1N1Si24MC 3 ALK250DOC1N7Si24C1 ALK250DOC7N7Si24MC 3 ALK250DOC7N1OP1MC 3 ALK250DOC7N7OP1C Week 4 Week 5 Week 6 Week 7 Week 8 Week 9 Week 11 Week 12 Alk15DOC7N7OP1MC3 Alk250DOC1N7 OP1MC3 Alk15DOC1N7 Si24MC3 Alk15DOC7N7 Si24C1 Alk15DOC7N1 Si24MC3 Alk15DOC1N1 OP1MC3 Alk15DOC1N7 OP1C1 Alk250DOC7N1 Si24C1 Alk250DOC1N1 OP1C1 Alk15DOC1N1 Si24C1 Figure 5-17: Temporal trend of total lead release Note: ALK= alkalinity (mg/l CaCO 3 ), 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

76 Half-Normal % Probability 60 Design-Expert?Software W4-W12 Total lead Error from replicates Half-Normal Plot Shapiro-Wilk test W-value = p-value = A: Alkalinity B: SNOM C: Nitrate D: Disinfectant E: Inhibitor Positive Effects Negative Effects E AE B BC A DE BD CD D C Standardized Effect Figure 5-18: Half-normal plot of total lead 60

77 61 Table 5-10: Analysis of variance table of total lead p-value Source Sum of Squares df Mean Square F Value Prob > F Block Model 6.55E < A-Alkalinity < B-SNOM C-Nitrate D-Disinfectant 1.41E E < E-Inhibitor AE BC BD < BE CD 1.28E E < DE < Residual 3.61E Cor Total* 1.07E Note: The Model F-value of implies the model is significant. Value of "Prob > F" less than indicate model terms are significant. *= Total corrected for the mean 61

78 Predicted 62 Design-Expert?Software W4-W12 Total lead Predicted vs. Actual Color points by value of W4-W12 Total lead: Actual 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 CaCO 3 ) was shown to reduce the average total lead leaching from the pipes, from 4400 to 3083 µg/l, as shown in Figure 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 (PbCO 3 ) and hydrocarnoate hydrocerussite (Pb 3 (CO 3 ) 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 At the low alkalinity (15 mg/l 62

79 63 CaCO 3 ), 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 CaCO 3 ), 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 [Pb 5 (PO 4 ) 3 OH] and tertiary lead orthophosphate [Pb 3 (PO 4 ) 2 ] are less soluble than lead carbonate such as PbCO 3 (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. 63

80 W4-W12 Total lead 64 Design-Expert?Software W4-W12 Total lead 6000 One Factor X1 = A: Alkalinity Actual Factors B: SNOM = 4.00 C: Nitrate = 4.00 D: Disinfectant = Average E: Inhibitor = Average A: Alkalinity Figure 5-20: The impact of alkalinity on total lead release. Note: the error bar represents 95% confidence interval 64

81 W4-W12 Total lead 65 Design-Expert?Software W4-W12 Total lead E1 orthophosphate 1 mg/l P E2 silicate 24 mg/l SiO Interaction E: Inhibitor X1 = A: Alkalinity X2 = E: Inhibitor Actual Factors B: SNOM = 4.00 C: Nitrate = 4.00 D: Disinfectant = Average A: Alkalinity Figure 5-21: The impact of interaction of alkalinity and inhibitor on total lead release. Note: the error bar represents 95% confidence interval 65

82 66 It was previously shown that Suwanee River natural organic matter (SNOM) had no impact on galvanic current. In contrast, as SNOM increased from 1 mg/l DOC to 7 mg/l DOC, the average total lead release increased from 3198 µg/l to 4325 µg/l (Figure 5-22). Lead release is a complex phenomenon which involves many mechanisms, and galvanic corrosion is only one of them. While SNOM did not affect galvanic corrosion, it affected lead release signifcantly. It is believed that SNOM can introduce an amorphous hydrated surface layer to pipe walls which leads to a higher rate of oxidation on the lead surface, resulting in higher lead release (Korshin et al., 2000). Lin and valentine (2008) showed that the extent of lead release increased with increasing NOM concentration. The impact of SNOM on lead release also depended on nitrate, disinfectant and inhibitor. At 7 mg-n/l nitrate, when the SNOM concentration increased, there was no significant change for the average lead release, but for 1 mg-n/l nitrate, when the SNOM concentration increased, the average lead release almost doubled (Figure 5-23). Uchida and Okuwakin (1999) have shown that nitrate can attack lead-bearing material by destroying its passive layer. When both SNOM and nitrate are present in the water, it was possible that nitrate attacks the amorphous hydrated surface layer which SNOM tends to form. Thus, when the concentration of nitrate is high, the tendency for SNOM to suppress lead release is lowered. As seen in the half-normal plot (Figure 5-18), the standardized effect of disinfectant was much higher than SNOM and the interaction of SNOM-disinfectant. Hence, the impact of SNOMdisinfectant 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 Cl 2 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 Cl 2 for SNOM at 1 mg/l and mg/l Cl 2 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 66

83 W4-W12 Total lead 67 to be able to reduce PbO 2 (s) to Pb 2+ (Boyd et al., 2010) and the formation and stability of PbO 2 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. Design-Expert?Software W4-W12 Total lead 6000 X1 = B: SNOM Actual Factors A: Alkalinity = C: Nitrate = 4.00 D: Disinfectant = Average E: Inhibitor = Average B: SNOM Figure 5-22: The impact of SNOM on total lead release. Note: the error bar represents 95% confidence interval 67

84 W4-W12 Total lead 68 Design-Expert?Software W4-W12 Total lead C C Interaction C: Nitrate X1 = B: SNOM X2 = C: Nitrate Actual Factors A: Alkalinity = D: Disinfectant = Average E: Inhibitor = Average B: SNOM Figure 5-23: The impact of interaction of SNOM and nitrate on total lead release. Note: the error bar represents 95% confidence interval 68

85 W4-W12 Total lead 69 Design-Expert?Software W4-W12 Total lead D1 free chlorine 1 mg/l D2 monochloramine 3 mg/l 6000 Interaction D: Disinf ectant X1 = B: SNOM X2 = D: Disinfectant Actual Factors A: Alkalinity = C: Nitrate = 4.00 E: Inhibitor = Average B: SNOM Figure 5-24: The impact of interaction of SNOM and disinfectant on total lead release. Note: the error bars represent 95% confidence interval 69

86 W4-W12 Total lead 70 Design-Expert?Software W4-W12 Total lead E1 orthophosphate 1 mg/l P E2 silicate 24 mg/l SiO Interaction E: Inhibitor X1 = B: SNOM X2 = E: Inhibitor Actual Factors A: Alkalinity = C: Nitrate = 4.00 D: Disinfectant = Average B: SNOM Figure 5-25: The impact of interaction of SNOM and inhibitor on total lead release. Note: the error bars represent 95% confidence interval 70

87 71 The choice of disinfectant plays a very important role in lead corrosion, as it had the largest standardized effect on the half-normal plot. The effect of free chlorine versus monochloramine on total lead release is shown in Figure 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 PbO 2 (s) to PbCO 3 (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, NaNO 3 and NH 4 NO 3, demonstrated different mechanisms for the dissolution of lead (Uchida and Okuwakin, 1999). Upon the 71