Uptake of Lead by Iron Corrosion Scales: Effects of Iron Mineralogy and Orthophosphate

A thesis submitted to the

Graduate School

of the University of Cincinnati

in partial fulfillment of the

requirements for the degree of

Master of Science

in the Department of Geology

of the College of Arts and Sciences

Lauren W. Wasserstrom

B.A. University of Cincinnati

2014

Committee Chair: J. Barry Maynard, Ph.D.

ABSTRACT

Owing to its toxic nature, lead (Pb) in tap water (released from pipes, solder, and brass fittings) poses an important risk to human health. High concentrations of lead have recently been found to accumulate in iron corrosion scales formed in galvanized iron pipes in household plumbing, but the interaction between iron and lead in this situation is not well understood. Therefore, a model system of simulated iron-bearing corrosion scales in household plumbing was devised to isolate the variables that influence lead uptake. Continuous flow experiments were performed to test the interaction of lead with the iron minerals in corrosion scales in household plumbing, and to assess the influence of changing orthophosphate concentration on lead previously accumulated in the analog iron corrosion scales. Serving as laboratory analogs for the capture of lead by iron corrosion products, sediment filters impregnated with various iron oxy-hydroxides that represent actual iron corrosion scale solids were synthesized and tested in a laboratory apparatus. Water quality was monitored and the analog iron corrosion scales were analyzed. A mass balance was performed on lead to evaluate the effectiveness of the iron filter.

Results showed that the presence of iron greatly enhances lead uptake by the sediment filter compared to the control containing no iron. Filter efficiency was evaluated using normalized ratios of lead, phosphorous, and copper uptake to the mass of iron (Fe) in the sediment filter.

This revealed very different behaviors for the iron minerals. Lead uptake by the filter was highest with feroxyhyte (0.02 mg of Pb per mg of Fe), followed closely by lepidocrocite (0.01), and then by goethite (0.003), magnetite (0.002), and ferrihydrite (0.002). Variable uptake of phosphorous and copper was also observed. Phosphorous was most strongly associated with lepidocrocite, followed by ferrihydrite, feroxyhyte, and magnetite, but did not bind to goethite. Copper was taken up more by feroxyhyte and lepidocrocite with some uptake by goethite and magnetite, but

II did not bind to ferrihydrite.

Feroxyhyte and lepidocrocite appear to be the most effective scavengers for lead and copper, whereas phosphorous uptake is highest with lepidocrocite. Although lead uptake was highest for feroxyhyte it has not been reported in drinking water corrosion scales. Based on these findings, lepidocrocite was chosen as the most appropriate model corrosion scale.

Lepidocrocite-impregnated filters were used in the final stage of the study to evaluate the impact of varying orthophosphate concentrations on lead previously accumulated in the iron-bearing filter. Increasing the orthophosphate levels suppressed the release of lead. However, the effect was only noticeable at 3.5 mg/L as PO4 or higher. These findings confirm the suggestion that galvanized pipes in household plumbing have the ability to trap lead from upstream sources, and emphasize the need to consider galvanized pipes as a significant source of lead in tap water.

Furthermore, typical orthophosphate dosing used in the U.S. (< 3.0 mg/L as PO4) will not be sufficient to prevent lead release from galvanized pipes.

III

ACKNOWLEDGEMENTS

Foremost, I would like to express my sincere gratitude to my advisor Dr. Barry Maynard for his continuous guidance, support, and patience through every step of my thesis. To my other committee members, Michael Schock, Philip Hart, and Dr. Warren Huff, thank you for your invaluable advice, expertise, and encouragement. I am honored to have had the opportunity to work with this team of extraordinarily talented, dedicated, and inspiring individuals.

I thank Keith Kelty and Maily Pham for water quality analyses, and Stephan Harmon from the U.S. Environmental Protection Agency for assisting in SEM analysis. To Dawn Webb and Jeff Swertfeger at the Cincinnati Water Works, thank you for lending laboratory equipment and other supplies, as well as your willingness to help in any way possible. I also thank Nicholas

Sylvest with Pegasus Technical Services for helping with laboratory experiments.

I am indebted to the Department of Geology for providing support and equipment, and to the Environmental Protection Agency, Office of Research and Development, for which funding for this research via the UC-USEPA Research Traineeship Program was awarded.

Last, but certainly not least, thank you to my parents (Jon Wasserstrom; Jayne and Rick

Nathans), siblings (Cara and Bryan), and grandparents (Dr. Herbert and Marilyn Bell) for your constant love, support, and encouragement in everything I do.

TABLE OF CONTENTS

ABSTRACT ...... II ACKNOWLEDGEMENTS ...... V LIST OF FIGURES ...... VII LIST OF TABLES ...... VIII LIST OF SYMBOLS ...... IX LIST OF APPENDICES ...... XI

CHAPTER 1: INTRODCUTION ...... 1 Background ...... 1 Importance of Iron ...... 3 Motivation ...... 5 Approach ...... 6

CHAPTER 2: METHODS AND MATERIALS ...... 9 Study Design...... 9 Carbon Block Filters ...... 9 Sediment Filters ...... 12 Water Analyses ...... 16 Water Quality Parameters ...... 16 Metal Analyses ...... 17 General Protocol ...... 18

CHAPTER 3: RESULTS AND DISCUSSION ...... 26 Stage 1 ...... 26 Stage 2 ...... 32 Stage 3 ...... 38

CONCLUSIONS ...... 59

REFERENCES ...... 63

APPENDIX ...... 72

LIST OF FIGURES

Figure 1 Images of sediment filter from field studies ...... 7

Figure 2 Labeled photograph of laboratory apparatus ...... 8

Figure 3 Configuration of laboratory apparatus ...... 20

Figure 4 Sediment filter fabrication process ...... 22

Figure 5 Diagram of the sampling points on the apparatus ...... 23

Figure 6 Comparison of metal concentrations in water from both sides of apparatus ..... 43

Figure 7 Total lead accumulated in the Fe1 sediment filter ...... 44

Figure 8 Correlation of Pb added to the tank and Pb measured in the tank by ICP...... 45

Figure 9 SEM images of sediment filters from Stage 1 ...... 47

Figure 10 Photographs of sediment filters used in Stage 2 ...... 48

Figure 11 X-ray diffractograms of iron minerals used in Stages 2 and 3 ...... 49

Figure 12 Efficiency of iron filters from Stage 2 ...... 50

Figure 13 SEM images of sediment filters from Stage 2 ...... 53

Figure 14 Efficiency of iron filters from Stage 3 ...... 54

Figure 15 SEM images of sediment filters from Stage 3 ...... 58

VII

LIST OF TABLES

Table 1 Iron-impregnated sediment filter preparation ...... 21

Table 2 Experimental conditions for each filter run ...... 24

Table 3 Finished water characteristics for the Miller Plant in Cincinnati, OH ...... 25

Table 4 Mass balance for lead in Stage 1 ...... 46

Table 5 Dominant mineralogy for each iron-impregnated sediment filter ...... 50

Table 6 Water quality characteristics in Stage 2 ...... 51

Table 7 Mass balance for lead in Stage 2 ...... 52

Table 8 Comparison of lead retained in sediment filters after each batch in Stage 3 ...... 55

Table 9 Water quality characteristics in Stage 3 ...... 56

Table 10 Mass balance for lead in Stage 3 ...... 57

VIII

LIST OF SYMBOLS

AES atomic emission spectroscopy Al aluminum Alk total alkalinity Au gold Ca calcium C carbon CF carbon filter Cl chlorine Cu copper DWDS drinking water distribution system EDS energy dispersive spectrometry EPA Environmental Protection Agency FCV flow control valve Fe iron gpm gallons per minute h hour HDPE high-density polyethylene

H2O2 hydrogen peroxide ICP inductively coupled plasma L liter LCR Lead and Copper Rule MDL minimum detection limit Mg magnesium mg milligram mg/L milligram per liter min minute Mn manganese

Na sodium

Na2HPO4 sodium phosphate N nitrogen

NSF/ANSI National Sanitation Foundation/American National Standards Institute O oxygen

ORP oxidation-reduction potential Ortho-P orthophosphate Pb lead

Pb(NO3)2 lead nitrate Pd palladium POE point-of-entry

PO4 phosphate P phosphorous Sec second SEM scanning electron microscopy SF sediment filter Si silicon SL service line S sulfur Temp temperature Turb turbidity WRF Water Research Foundation XRD X-ray diffraction XRF X-ray fluorescence Zn zinc µg/L microgram per liter µm micron

LIST OF APPENDICES

Figure A.1 SEM images of sediment filter from field studies ...... 72

Figure A.2 Labeled photograph of carbon filter components ...... 74

Figure A.3 Process of ashing carbon filters for XRF analysis ...... 75

Figure A.4 Photographs of selected sediment filter sizes ...... 76

Figure A.5 Photographs of synthesizing iron solutions ...... 77

Figure A.6 Photographs of melting sediment filter material for XRF analyses ...... 78

Figure A.7 EDS analysis for iron filter (Fe1) in Stage 1 ...... 79

Figure A.8 EDS analysis for control filter (C1) in Stage 1 ...... 80

Figure A.9 Digital microscope images of blended sediment filters from Stage 2 ...... 81

Figure A.10 EDS analysis for lepidocrocite filter (Fe3) in Stage 2 ...... 82

Figure A.11 EDS analysis for magnetite filter (Fe4) in Stage 2 ...... 83

Figure A.12 EDS analysis for ferrihydrite filter(Fe5) in Stage 2...... 84

Figure A.13 EDS analysis for goethite filter (Fe6) in Stage 2 ...... 85

Figure A.14 EDS analysis for control filter (C6) in Stage 2 ...... 86

Figure A.15 EDS analysis for lepidocrocite filter (Fe7) in Stage 3 ...... 87

Figure A.16 EDS analysis for control filter (C7) in Stage 3 ...... 88

Figure A.17 EDS analysis for lepidocrocite filter (Fe8) in Stage 3 ...... 89

Figure A.18 EDS analysis for control filter (C8) in Stage 3 ...... 90

Figure A.19 EDS analysis for lepidocrocite filter (Fe9) in Stage 3 ...... 91

Figure A.20 EDS analysis for control filter (C9) in Stage 3 ...... 92

Table A.1 Equipment specifications for filter apparatus...... 93

Table A.2 Effectiveness of carbon filter for removing lead ...... 94

Table A.3 NSF/ANSI test results for the carbon filter ...... 95

Table A.4 Metal concentrations in water from each faucet side on the apparatus ...... 96

Table A.5 Equations used to determine the mass balance for lead ...... 97

Table A.6 Mass balance for lead measured in water samples for the right faucet ...... 98

Table A.7 Mass balance for lead measured in water samples for the left faucet ...... 99

Table A.8 Mass balance for lead based on the tank addition for the right faucet ...... 100

Table A.9 Mass balance for lead based on the tank addition for the left faucet ...... 101

Table A.10 Mass balance for lead measured in the carbon filter on the right faucet ..... 102

Table A.11 Mass balance for lead measured in the carbon filter on the left faucet ...... 103

XII

CHAPTER 1: INTRODUCTION

BACKGROUND

Due to its toxic nature, lead (Pb) in tap water remains an important risk to human health.

Lead primarily enters drinking water as a result of corrosion or the wearing away of materials that are in the distribution system and in household (premise) plumbing. Lead-bearing plumbing components include Pb pipes, usually as service lines, leaded brass fittings, and Pb-based solder.

The occurrence of Pb in the distribution system poses a serious concern for water utilities because of the adverse impacts of Pb on human health, and especially on the cognitive development of children (Triantafyllidou et al, 2007; Fewtrell et al, 2004; WHO, 1993; Bellinger et al, 1991). The U.S. Environmental Protection Agency’s Lead and Copper Rule (LCR) established a 90th percentile action level of 0.015 mg/L for Pb at the consumer’s tap (USEPA,

1994a; 1992; 1991a; 1991b). Yet, the LCR is not designed to regulate the level of human exposure. It is meant to specify when adjustments to water treatment are needed and emphasizes corrosion control (Schock, 1999). While the LCR has successfully reduced Pb levels in potable water supplies, Pb remains high in parts of some distribution systems [e.g., Del Toral et al.

(2013), Deshommes (2010), HDR (2009), Giani et al. (2005)].

Compliance with the LCR is still a major challenge for many water utilities. Utilities that do not satisfy the regulation for Pb are required to optimize corrosion control treatment. Many water utilities have mitigated Pb corrosion by adjustment of pH and/or alkalinity, but even more have added phosphate-based corrosion inhibitors (Tam & Elefsiniotis, 2009; Lasheenet al, 2008;

McNeill & Edwards, 2001; Droste, 1997). Orthophosphate (ortho-P) is commonly used for corrosion control, with the generally accepted theory of reducing Pb solubility by causing the formation of relatively insoluble Pb-ortho-P compounds that create a passivating film on the pipe

1 wall to inhibit Pb release into the water (Schock & Lytle, 2011; Schock, 1996; Friedman et al,

1994; Schock, 1989; Sheiham & Jackson, 1981; Schock, 1981; Schock, 1980). If tap water Pb levels continue to exceed the action level for Pb after corrosion control is implemented, then the

LCR usually requires utilities to replace Pb service lines (SLs) that it controls in the distribution system (Welter et al, 2013; USEPA, 1992; 1991a; 1991b).

Lead SLs are generally the largest source of Pb in drinking water distribution systems

(DWDSs) (Sandvig et al, 2008), and can contribute 50-75% of the total Pb mass measured at the tap (Cartier et al, 2011; Sandvig et al, 2008). Water utilities are only required to replace the portion of the Pb SL that they own. The remaining portion of the SL is the responsibility of the property owner. Participation rates in partial SL replacements on the private side are reported to range from 1-25%, largely due to the cost of the operation (Welter et al, 2013). Transient elevated Pb levels in tap water have been associated with partial replacements and physical disturbances, such as repairs or replacements to a water meter or an external service shut-off valve (Del Toral et al, 2013; Commons, 2012; USEPA, 2011; Sandvig et al, 2008; Swertfeger et al, 2006; Boyd et al, 2004; Zietz et al, 2001; Schock et al, 1996). However, full SL replacements have been found to release high Pb concentrations even after the entire Pb SL has been removed, suggesting that Pb from upstream SLs had accumulated in the corrosion scale solids in premise plumbing and was dislodged into the water (McFadden et al, 2011; Sandvig et al, 2008; HDR,

2009) likely by disturbances from Pb SL replacement construction. In both cases, the Pb is dominantly released as particulates. A recent study (Schock et al, 2014) has further examined the mechanism of the Pb elevations remaining after full Pb SL replacement in Madison, WI, and found the mechanism appeared to be accumulation of upstream Pb in manganese-rich deposits carried into interior premise plumbing, probably by a sorption mechanism.

Importance of Iron. Iron is not a regulated metal, but has a non-enforceable, secondary maximum contaminant level of 0.30 mg/L, which was set based on color and taste concerns.

Beyond these aesthetic considerations, the ability for Fe to sorb Pb makes it important for public health. The binding of Pb to Fe oxy-hydroxides in natural systems has been recognized for many years (Cornell & Schwertmann, 2003; O’Reilly & Hochella, 2003; Nelson et al, 1995; Benjamin

& Leckie, 1981; McKenzie, R.M., 1980). A large body of literature on surfaces coated with Fe, used for various purposes, also exists. For example, Fe coated sands used for controlling metals in urban runoff (Sansalone, 1996), and Fe coated well-plates for studying biofilms (Pouran et al,

2014). Further, high concentrations of Pb have recently been found to accumulate in galvanized

Fe corrosion scales of household plumbing. Several studies have identified a potential link between Pb mobilization and Fe, and have demonstrated that Pb-rich Fe corrosion scales could form via sorption mechanisms (Camara, 2012; McFadden et al, 2011; Deshommes et al, 2010;

Friedman et al, 2009; HDR, 2009). Since the presence of leaded-iron scales can contribute significantly to Pb levels at the tap, it is important to understand the interaction between Fe scales and Pb in order to minimize Pb in drinking water.

Lead may physically accumulate on the surface of or be occluded within DWDS corrosion scale solids that contain Fe oxy-hydroxides. Accumulated Pb in corrosion scales could eventually be erratically released into the water due to physical and hydraulic disturbances, for example, from SL replacements or changes in flow rates. Changes in water quality, such as pH, use of corrosion inhibitors, and disinfection/disinfection changes, could also result in high Pb levels at the tap. Further, ortho-P corrosion inhibitors that are typically highly favorable for Pb

(Liu et al, 2010; Stone et al, 2009; Cantor et al, 2000; Schock et al, 1996) have been observed to be less beneficial for Fe (Lytle et al, 2005; Sarin et al, 2003; McNeill & Edwards, 2000), while

3 several authors have reported that ortho-P reduced Fe levels (Sarin et al, 2003; Lytle &

Snoeyink, 2002; Benjamin et al, 1996; Vik et al, 1996).

Additionally, numerous studies have examined single Fe minerals, but few studies compare them, and even fewer have examined Pb and phosphorous simultaneously. The majority of studies have considered amorphous Fe oxides or ferrihydrite (Tiberg et al, 2013; Gustafsson et al, 2011; Xu et al, 2006; Swedlund et al, 2003; Trivedi & Sparks, 2003; Scheinost et al, 2001;

Swedlund & Webster, 2001; Aualiitia & Pickering, 1987; Zachara et al, 1987; Benjamin, 1981;

Gadde & Laitinen, 1974); goethite (Xie & Giammar, 2007; Villalobos et al, 2001; Ostergren et al, 2000; Weesner & Bleam, 1998; Bargar et al, 1997; Geelhoed et al, 1997; Benjamin & Leckie,

1981); and goethite and lepidocrocite (Peacock et al, 2004; Parkman, 1999). The enhanced uptake of Pb by Fe is generally associated with higher pH and with Fe phases that possess greater surface areas. In addition, the high affinity of phosphorous for Fe oxy-hydroxides has previously been documented (Gustafsson, 2003; Schwertmann & Cornell, 2000). The adsorption of phosphorous onto the surface of Fe minerals is well established (Yamaguchi et al, 1996; Hsu,

1976; Atkinson et al, 1974), and could be significant in this work. Moreover, the use of phosphate-based inhibitors in DWDSs has been shown to influence the accumulation and release of trace inorganic contaminants from various metal oxide surfaces through competitive sorption effects (Friedman et al, 2009; Lytle et al, 2004). Yet, studies comparing the influence of the various Fe minerals on Pb and phosphorous uptake are limited.

Understanding the impacts of physical and chemical changes in the DWDS on Pb release from Fe-bearing corrosion scales is pertinent to minimizing the Pb release in premise plumbing, and to protect public health. This study is designed to test the interaction of Pb from upstream sources with the Fe minerals in corrosion scales in premise plumbing, and to assess the influence

4 of changing ortho-P concentration on Pb previously accumulated in the Fe. A model system was devised to isolate the target variables and evaluate the impact of Fe mineralogy, and ortho-P levels, on the Pb content in drinking water at the tap.

MOTIVATION

It was found in field studies that point-of-entry (POE) sediment filters that accumulate Fe oxy-hydroxides become effective agents for capturing Pb from water (Cantor et al, 2013), and therefore might serve as laboratory analogs for the capture of Pb by Fe corrosion products. Two neighboring homes were being monitored: one with the Pb SL replaced completely with copper

(Cu), and one with only the city portion replaced with Cu (a partial replacement). At the POE into the home with the partial replacement was a sediment filter (SF), which was installed prior to the SL construction in 2008, and remained in place until monitoring began in 2012. To permit equivalent conditions for water quality sampling between the two homes, aside from SLs, the SF was removed. Initial assessment of the SF showed that it was stained with Fe and had trapped large particles that appeared to be Fe oxides (Figure 1, part A). The elemental composition of the

SF was determined by X-ray fluorescence (XRF) analysis, which revealed high levels of Fe at

0.42 wt. %, and also Pb (0.38 wt. %).

The likely source of the Pb found is the SL, and it is plausible that most was released as particles during the partial replacement. Trapping of these particles may have been simply physical straining by the filter or may have been enhanced by the presence of so much Fe.

Accumulation of the Fe may have been gradual over time or mainly captured following the disturbance from the SL replacement. Also, since the time of replacement, more Pb may have been released into solution from brass fittings or from the lingering effects of the Pb SL and precipitated by reaction with the Fe in the filter. The nature of the particles trapped was

5 investigated using Scanning Electron Microscopy (SEM), and several modes of trapping were evident (Figure 1, parts B and C; and Appendix, Figure A.1).

Approach. In this study, experiments were conducted to replicate this Fe-Pb reaction under controlled conditions. A model system of simulated Fe-bearing corrosion scales in premise plumbing was developed (see Figure 2 for labeled photograph of apparatus). Modified Cincinnati tap water, dosed with either Pb or ortho-P, was pumped from a large water reservoir to two kitchen faucets. Placed ahead of the faucets was a pair of SFs impregnated with Fe oxy- hydroxides, representative of actual Fe corrosion scale solids, which were synthesized and tested in the laboratory apparatus. Seven sets of filter runs were conducted in a continuous flow experiment, where water quality was monitored and a mass balance was performed on Pb to evaluate the effectiveness of the Fe filters.

Filter runs were conducted in a series of 3 stages: 1) reproducing field observations; 2) investigation of different Fe minerals on Pb uptake; and 3) impact of changing ortho-P levels on

Pb accumulated in the Fe. Reproducing field observations was completed first to validate the testing system design. Then, five different Fe-impregnated SFs were prepared and tested to assess the influence of different Fe minerals, in a form similar to water distribution system piping scales, on Pb uptake. The most efficient Fe filter for trapping Pb was selected and implemented in the final stage of the study to determine the effects of increasing ortho-P concentrations on Pb previously accumulated in the Fe mineral material.

Figure 1 Images of sediment filter from field observations

Photograph of (A) sediment filter from field studies appeared to be stained with iron. SEM images showed lead-rich grains coating the surface of fibers (B), while nano-scale lead particles were found crystallizing on filter fibers upon closer inspection (C).

Figure 2 Labeled photograph of the laboratory apparatus

CHAPTER 2: METHODS AND MATERIALS

STUDY DESIGN

A laboratory apparatus designed for the Water Research Foundation (WRF) Project

#4415 (Cantor et al, 2013) was used as a model system to simulate Fe-bearing corrosion scales in premise plumbing. The design of the system allowed isolation of the variables that influence Pb uptake by Fe under controlled conditions. The original design was modified to expose SFs impregnated with Fe oxy-hydroxides to a controlled mass of Pb, and then of ortho-P, under similar water flow and pressure conditions. Seven sets of filter runs were conducted in a continuous flow experiment, where water quality was monitored and a mass balance was performed on Pb to evaluate the effectiveness of the Fe filters.

The design of the testing system consisted of a solution tank, a recirculation pump, and a pair of SFs followed by a pair of carbon filters (Figure 2; Figure 3 diagram of apparatus;

Appendix, Table A.1 for list of equipment). The solution tank was a 150-gallon polyethylene tank with lid. A recirculation pump was used to continuously mix the solution, and to transport the water from the tank through the rest of the apparatus. Cincinnati tap water, dosed with either

Pb or ortho-P, was pumped from the large water reservoir to two kitchen faucets. Placed ahead of the faucets was a pair of SFs, and attached to each faucet was a point-of-use carbon block filter to trap any remaining Pb.

Carbon Block Filters. Lead uptake was monitored by an integrated sampling approach using a carbon filter (CF) device that is about 97% efficient for Pb removal (Cantor et al, 2013)

(Appendix, Table A.2). The CFs consisted of a solid block of activated carbon (C) with a fabric wrap around the outside, plus a center fill of calcium carbonate (see Appendix, Figure A.2 for

9 photos of CF components). Information on filter performance, data sheets, and official certificates listing the results of the National Sanitation Foundation/American National Standards

Institute (NSF/ANSI) Standards 42 and 53 testing, were reported elsewhere (Cantor et al,2013)

(see Appendix, Table A.3).

The use of these filters provided continuous integrated sampling of the water exiting the

SF. That is, they effectively capture the remaining Pb in the water, thereby providing an estimate of how much mass of Pb was retained by the SF. Their efficiency for trapping phosphorous (P) and other regulated metals was also investigated.

After each run, the two CFs were removed from their associated faucet. Filter cartridges were placed in an upright position to allow excess water to drain, and were then sliced open using a chrome-free, cross-cut carpenter’s saw. Both ends of the cartridges were cut off using the saw. Since the C block is glued to the top of the housing, some C was inadvertently lost. The teeth of the saw blade were cleaned between samples by cutting a piece of fresh wood to avoid cross-contamination. Components of the CFs were collected separately, and placed in a 55C oven until dry, which took about 24 h. Approximately half of all components per sample were collectively placed into a crucible. The crucible was then placed in a muffle oven, and the temperature was slowly ramped up from 200C to 600C. Once the temperature reached 600C, it was left in the oven for about 12 h to ash the composite sample. This process provided a method for concentrating the inorganic constituents in the sample and for analyzing all filter components at once (Appendix, Figure A.3 for photos of ashing process).

For each run, a 3-pack of filters with the same lot number was used: 1) attached to the right faucet; 2) attached to the left faucet; and 3) an unreacted filter that was used as a blank.

Ashed materials were ground to a powder, using a ceramic mortar and pestle, and sieved to less than 200 mesh. Approximately 2.0 g of each bulk sample were added to 0.2 g of binder, using

3644 UltraBind from Spex SamplePrep. Both components were mixed thoroughly using polyacrylic balls, from Spex SamplePrep, in plastic vials in a Spex SamplePrep ball mill shaker.

A cellulose backing was first made for each sample, rather than using the standard aluminum cup to house the pellets. This backing made the pressed sample pellet more durable and less prone to breakage in comparison to those that were made in the aluminum cups. About

0.2 g of Spex SamplePrep cellulose binder was added to the stainless steel die set. The cellulose was leveled and the plunger from the die set was inverted, meaning the beveled side facing downward towards the binder. Using a Spex 3624B X-Press hydraulic press machine, the cellulose was pressed at 10 tons for about 5 sec. After pressing, the plunger was removed and any loose binder in the barrel was gently blown out with air. The sample/binder mixture was carefully poured into the die set and the material was leveled. Applying 20 tons of pressure for about 30 sec, using the hydraulic press machine, the sample was pressed into a pellet. The disk was stored in sealed container until analyzed using a Rigaku 3070 X-ray fluorescence (XRF) spectrometer to determine the bulk chemical composition of each CF.

A split of a set of ashed CF samples was sent to a commercial laboratory for elemental analysis by fused-disk XRF. A second split of these samples was then used as a set of secondary standards and combined with a set of certified USGS and NIST standards to build the XRF calibration curves for pressed powders. Elemental intensity data were converted to percent (%) by weight or mg kg-1 using simple and multiple regressions applied to the secondary and certified standards.

Sediment Filters. Two whole-house water filtration units (ACE 49560) in clear holders were purchased at a local hardware store. The SF cartridges for this system consisted of a spool of polypropylene yarn that were about 25 cm long and 6.5 cm in diameter. The cartridges were available in three filtration pore sizes: 1, 5 or 10µm (Appendix, Figure A.4 for photos of selected filter sizes). In stage 1, 10µm filters were used with the notion of producing a uniform Fe coating more easily with the larger filter size. However, this filter material proved more difficult to process in subsequent analysis, compared to the other two filter sizes. In stage 2, it was found that the 1µm filter material was easier to process, but the impregnation process was very challenging due to the small pore size. Fortunately, the 5µm SFs were both easier to uniformly coat with Fe and process for chemical analysis.

Synthetic Fe suspensions were prepared in the laboratory following two recipes from

Schwertmann & Cornell (2000). The Fe-SF in Stage 1 (Fe1) followed the pure goethite formation formula. Submerged in a 2 L cylinder, the SF soaked in a 1 L reagent grade ferrous chloride solution with nitrogen (N2) gas bubbling through for about 3 h. A 1 M NaHCO3 solution was added, then the N2 was replaced with air, and the SF soaked overnight. Hydrogen peroxide

(H2O2) was added to boost the speed of the reaction. When the Fe coating appeared to be both the correct color specified in the method, and uniform, it was removed from the cylinder. The color of the Fe suspension played a crucial role in identifying the particular mineral at the time of synthesis. The entire process took about 30 h to complete compared to the 48 h specified in the published description of the method, which likely resulted from the H2O2 modification.

Remaining Fe-SFs were prepared using the lepidocrocite method from Schwertmann &

Cornell (2000). The process was slightly altered, based on general knowledge of Fe mineral formation, to yield five Fe filters of various mineralogies common in Fe corrosion scale solids.

By using the same method to prepare the Fe SFs used in Stages 2 and 3, it provided a means for directly comparing the filters.

Synthesis of each Fe-impregnated filter involved bubbling N2 gas through distilled water for about 30 min. Reagent grade ferrous chloride crystals were then added, and air was used in place of the N2. Since a uniform coating of Fe on the filters was the desired outcome, multiple batches of the Fe suspension were prepared until an even coating was achieved, which is why the amounts of ferrous chloride used for each filter varied (Table 1 iron filter preparation; Appendix,

Figure A.5 for Fe synthesis photos). A magnetic stirrer and stir plate were used until the Fe crystals completely dissolved, and then either a 1 M NaOH or 1 M NaHCO3 solution was used to adjust the pH of the acidic solution, and initiate Fe precipitation; the pH of the solution was monitored while making adjustments. Filters Fe1 and Fe6 had the same target mineralogy, and used the NaHCO3 solution. All other solutions used different quantities of NaOH, which was based on the color of the Fe suspension for each desired mineral phase. Quick mineral formation was important to decrease the possibility of forming large crystals that interfered with developing a uniform coating throughout the entire filter. Therefore, H2O2 was usually used to boost the speed of the reaction. Since the Fe precipitants for the Fe2 and Fe4 filters were rapid they were the only filters that did not require the H2O2 addition. The amount added of each component differed based on the target mineral (Table 1); the length of the entire process took

10-15 h to complete.

After the Fe suspension was prepared it was slowly dripped from a separatory funnel into a reaction vessel (Figure 4 photographs of SF fabrication process). An unused, discontinued, field sampling cell for water, from YSI, Inc., was used as the reaction vessel. It contained various, secure openings at the top that were originally intended for electrodes, but instead were

13 used to: 1) add small increments of the Fe suspension; 2) add tap water from the solution tank; and 3) connect the reaction vessel to the SF housing unit.

The laboratory apparatus was used to provide a flow of water under pressure to the reaction vessel (Figure 4). By controlling the flow rate of water sent to the reaction vessel from the tank, the influent flow to the vessel forced the Fe suspension out and into the SF housing.

Suspended Fe in the water from the reaction vessel was trapped by the SF, while the remaining water flowed through tubing to the sink drain. As more suspension was added to the reaction vessel, the water flow was minimized to stop any backflow of water from displacing the suspension in the funnel. It was also important for the funnel to be set as high as possible above the reaction vessel to ensure continuous flow of the Fe suspension into the water stream. The direction of the SF was reversed after half of the Fe suspension was used to allow equal exposure on both sides.

X-ray diffraction (XRD) was used to confirm the identity of the Fe minerals for each SF.

Immediately after impregnating the SF with Fe, any material caked onto the surface was gently scraped with a quartz slide. Ethanol was used to make a slurry and evenly coat the slide with the

Fe oxy-hydroxide. After preparing the slide it was analyzed by XRD. Data were collected using a Siemens D-500 automated diffractometer equipped with a Cu Kα X-ray source (40 kV and 30 mA), and were analyzed and matched on the basis of peak position and peak intensities to reference patterns using the American Mineralogist Crystal Structure and the Mineral Database

(2003), and the International Center for Diffraction Data PDF-4+ (2010).

Once laboratory runs were complete, SFs were taken down from their housing unit. The remaining water was decanted and filters were removed. They were placed in a 55C oven and regularly monitored until completely dry by periodically weighing the filter until the weight was

14 constant. Dry filter weights were recorded, and used to evaluate the extent of Pb, P, and other accumulated metals in each filter. Heating did not alter the concentrations of metals of interest.

However, the mineralogy could have been altered by heating, and therefore was not determined after filter runs were completed (Goodman, 1979).

Material from both ends of the dry SF was removed with a stainless steel knife and ripped into smaller pieces by hand using a new pair of laboratory gloves for each sample. Smaller shreds of material were placed into a typical household-style blender that was specifically purchased for this study. Since the SFs were dry, a small amount of ethanol was added to aid in grinding. The blender was pulsed until all shreds were visually ground to the same size to ensure homogenous, representative samples. As a result of the extremely coarse nature of the filter material it could not be sieved. A visual distinction was observed after blending, where the material was either in the form of chunks or shavings. The shavings were considered the ground material, while the chunks were picked out by hand and blended until they were the same size as the shavings. Once the ethanol evaporated, about 1.5 g of the blended material was used to make a melted disk for XRF. Aluminum (Al) cups, originally designed for holding pressed XRF disks, were coated with petroleum jelly. Material was packed into the cup, and then melted in a 250˚C muffle oven for about 7 min. More blended material was packed into the Al-cup and placed back in the oven two more times in order to make a thick enough pellet that could be run in the instrument. After melting, disks were placed in a 55˚C oven for about 30 min, and then cooled to room temperature. Stainless steel pliers were used to carefully remove the Al-cup, and the pellet was placed in a sealed container until analyzed (Appendix, Figure A.6). Duplicate pellets were made to assess variability, while an unused SF was treated in the same way to determine blank values.

Melted disks were also analyzed for its elemental composition using the XRF spectrometer. Since it was difficult finding a suitable matrix match for the SFs, a split of a set of melted disks was sent to a commercial laboratory for elemental analysis by fused-disk XRF. A second split of these samples was then used as a set of secondary standards and combined with a set of certified USGS and NIST standards that have about the same matrix to build the XRF calibration curves for pressed powders.

Micro-scale images of the blended filter material were taken using a Keyence Digital

Microscope VHX-500F. Scanning electron microscopy-energy dispersive X-ray analysis (SEM-

EDS) was performed, using a FEI XL30 ESEM and an associated X-ray EDX system, on the filter fibers to characterize the Pb-Fe association and to assess the distribution of Pb in the Fe- impregnated filters. Samples were coated before analysis with a gold/palladium (Au/Pd) alloy to improve the image quality, as samples are nonconductive and tend to charge when scanned by the electron beam.

WATER ANALYSES

Water Quality Parameters. Measurements were made on water samples during each filter run to assess water quality changes throughout the testing system, particularly before and after passing through the filters as well as the solution tank (Figure 5). Temperature, pH, and oxidation-reduction potential were measured using meters with sensing probes. A turbidimeter was used to measure turbidity, and colorimetric field test kits were used to measure total chlorine and ortho-P concentrations. Ortho-P was measured following the Hach Method 8048, EPA

Method 365.1, and SM 4500-P-E (Hach, 1996; 2008; APHA, AWWA, & WEF, 2005; USEPA,

1993). Alkalinity and chloride content were determined for the inlet water by titration following

SM 2320-B.4.b for alkalinity, and SM 4500-Cl D for chloride (APHA, AWWA, & WEF, 2005).

Method accuracy, plus analytical and process precision were reported elsewhere (Cantor et al,

2013).

Metal Analyses. All metal analyses on water samples were collected using a Thermo

Electron iCAP 6000 inductively coupled plasma emission spectrometer. Water samples were measured according to the EPA method 200.7 (USEPA, 2001; 1994b). Samples were collected in

125-mL HDPE bottles and preserved at the time of collection using concentrated nitric acid. The pH was checked in the laboratory upon submission (Feldmann et al, 1992).

At the Pb concentrations used in this study, particulates were expected to form in the solution tank, based on previous work by Cantor et al. (2013). Since the intent of this study was to simulate Pb uptake from Fe-bearing corrosion scales in DWDSs, having both dissolved and particulate Pb was of interest. For selected samples, both total and dissolved metals were determined to track the fate of metal particulates by filtering a portion of the sample through a

0.45μm filter. An equipment blank was performed prior to filtering field samples.

Water samples were collected from various outlets on the filter apparatus, including: (S0) the influent water; (S1) solution tank outlet; (S2 & S3) after the SFs on both faucet sides; and (S4

& S5) after the CF that was attached to each faucet (Figure 5 diagram of the sampling points on the apparatus). This enabled determination, at least for one time during the experiment, of the mass balance for Pb and P, at each point in the system. These results were then compared with the time integrated results from the XRF analysis of the CF. All water samples were run in triplicate readings and the results are expressed as the average of those measurements. Numbers are accurate ± 5-10% above the minimum detection limit (MDL) for each given element based on a set of known standards. If sample averages were below the MDL, then values were taken at half the MDL for completion of calculations.

General Protocol. Before each filter run, the laboratory apparatus was disinfected using a shock chlorination process. Liquid household bleach containing 5.7% free chlorine was added to the tank solution at a concentration of 4 mg/L of free chlorine. Bleach was poured directly into the recirculation stream of the solution tank, and the tank was filled with tap water. The solution was mixed for about 30 min, and then disposed of down the drain. The tank was flushed 2-3 times, while also sending water through all parts of the laboratory apparatus, until the chlorine concentration in the tank matched that of the municipal water supply. This cleaning procedure was used in an attempt to isolate the effects of microorganisms during experiments by disinfecting the tank. However, it should be noted that microbiological activity may influence the variables examined in this study in actual DWDSs.

Filters were exposed to known concentrations of Pb or ortho-P in a continuous flow experiment. Solutions were composed of Cincinnati municipal water that had been passed through a 5µm filter to remove particles acquired from the distribution system, dosed with reagent grade Pb nitrate (about 20-40 µg/L as Pb), or dibasic sodium phosphate (about 1.8-11.6 mg/L as PO4) (Table 2 shows the experimental conditions for each run). Filter runs consisted of about 400 L of water per faucet (800 L total), and took about 6 h to complete.

Flow rate measurements and the quantity of flow per filter were determined using a

Totalizing Sensus iPerlTM meter associated with each filter. Adjustment of the flow control valve

(FCV) enabled the proportion of flow that was returned to the tank and the portion sent to the faucets to be regulated. To mix the solution tank water, through the plunge of the return water, the return flow was positioned above the fill level of the tank. Combined use of the FCV with the pump controller allowed similar flow rates (averaging about 0.5 gpm) for each faucet to be maintained.

Since real tap water was used for the study, inherent seasonal and other variations in water quality were expected. Changes in important source water quality parameters, such as alkalinity, chloride, and pH, were closely monitored and compared to experimental trends to ensure that variability of the base water supply was not responsible for the observed effects

(Table 3 shows average water quality for Cincinnati tap water).

Chemicals were stored in a 55˚C oven until used, as drying improved accuracy for accounting of the Pb and P mass captured by the filters. Calculated quantities of the chemicals were acidified in beakers to ensure complete dissolution before adding to the tank, and then they were poured into the recirculation stream of the solution tank. Mixing of the solution in the tank was attained by closing all valves leading to the faucet, and solely using the recirculation pipe loop between the pump and the tank for about 15 min. After mixing, the initial totalizer readings for each faucet were recorded, and the valves leading to the faucets were opened. Flow rates were checked, by recording the totalizer readings over time, to compare the two faucets. If flow rates were different, the pressure valves were adjusted until similar rates were achieved.

Water quality field parameters were run on the inlet water, and on water from the solution tank outlet first. Towards the end of each run (Batch B), water quality parameters were measured before and after the CFs. In addition, 125 mL water samples were taken to be analyzed by ICP-

AES for metal concentrations. In stage 3, where Pb was added in Batch A and ortho-P in Batch

B, water samples were collected for each batch. At the end of the run, the pump on the laboratory apparatus shut off. End totalizer readings associated with each faucet were recorded, and both filter types were taken down for further processing.

Figure 3 Configuration of laboratory apparatus used for filter runs

Note: Numbering is used to represent the flow of water, from the solution tank through the sediment filter followed by the carbon filter, and finally emerges from the carbon filter attached to the faucet; Influent water comes from Cincinnati municipal water. A line was tapped into the existing plumbing, and a 1µm physical filter was installed to prevent any plumbing system metal particulates from entering the solution tank.

Table 1 Iron-impregnated sediment filter preparation

*The objective was to achieve a uniform iron coating on the sediment filter, rather than using a consistent amount of iron. Therefore, the mass of ferrous chloride varied with the desired filter type. †Color of iron solution played crucial role in determining initial mineralogy. ‘―’ means that it was not added during synthesis of solutions; solutions were prepared using methods modified from Schwertmann & Cornell (2000).

Figure 4 Sediment filter fabrication process

Photographs showing A) view of the whole system; B) view of the iron-impregnated sediment filter; and C) close-up of the reaction vessel.

Figure 5 Diagram of the sampling points on the apparatus

All water samples were measured for metal concentrations by ICP-AES. X1 and X2 are used to represent the water from the solution tank before passing through the sediment filters, however, there are no actual sample ports on the apparatus. Therefore, mass balance calculations for lead assume that the tank concentration is the same as what goes to each faucet side (X1 = X2 = S¹); the Fe1 filter in Stage 1 also assumes that the tank concentration is the same as what goes to the right faucet side, which is the control SF side (S¹ = S²); the influent water is collected as well and used as a blank subtraction. Note: SF refers to the sediment filters, and CF denotes the carbon filters.

Table 2 Experimental conditions for each filter run

*All runs consisted of two batches (A and B), where each used about 400 L of Cincinnati tap water dosed with either reagent grade lead nitrate (Pb(NO3)2) or sodium phosphate (Na2HPO4). †Orthophosphate was only added in Stage 3, Batch B. However, sodium hexametaphosphate is added to the Cincinnati municipal water supply at 0.3-0.5 mg/L as PO4. Therefore, some phosphate was present in all filters.

Table 3 Finished water characteristics for the Miller Plant in Cincinnati, OH*

*GCWW Annual Water Quality Report (2010) †Reported as mg/L except where noted

CHAPTER 3: RESULTS AND DISCUSSION

The results are divided into sections corresponding to the three stages of this study: 1) reproducing field observations; 2) investigating Fe mineralogy on Pb uptake; and 3) assessing the influence of changing ortho-P concentration on Pb previously accumulated in the Fe mineral material. All results are discussed in terms of the implication of in-home galvanized plumbing for providing a reservoir for the accumulation and potential release of Pb in tap water.

Stage 1. The calculations used to evaluate the SFs assume that the same mass of Pb, and other constituents present in the solution tank, was sent to each branch of the apparatus. In the

WRF4415 project, this assumption was found to be untrue (Cantor et al, 2013), and the geometry of the apparatus was modified to make the two sides of the testing system hydraulically identical.

Consequently, a symmetry run with water sampling was performed first to investigate the assumption. If the metal concentrations measured in the water by ICP-AES were equivalent for both sides of the apparatus, then the slope of a linear correlation line would equal 1 and the correlation coefficient, r2, would equal 1. There are very close correlations found between the two branches with a slope of 0.99 and the r2 = 1, confirming both sides of the apparatus were balanced (Figure 6 comparison of metal concentrations on each faucet side of the apparatus;

Appendix, Table A.4).

After verifying the symmetry of the apparatus, five experimental filter runs were performed using a Fe-impregnated SF (Fe1) and a control filter with no Fe (C1) placed in-line ahead of the two faucets. Filters were exposed for about 6 h to known concentrations of Pb (20-

40 µg/L as Pb per batch) in a continuous flow experiment using about 400 L of water for each faucet. Water quality was monitored and a mass balance performed on Pb to evaluate the effectiveness of the Fe filter.

Macroscopic inspection of the Fe1 filter revealed an ochreous hue, consistent with the formation of goethite (Schwertmann & Cornell, 2000). However, it proved impossible to recover sufficient material for XRD analysis to confirm the mineralogy. As a result, the fabrication process was refined, and a SF with smaller pore size (5µm rather than 10µm) was used, which permitted excess material to accumulate on the surface of the filter that could be gently removed and used to identify Fe minerals in the subsequent stages of this study.

Iron filter efficiency for trapping Pb was first evaluated, by using XRF data from the CFs after each filter run, for quality control purposes to validate the testing system and how representative it is of the field conditions. The difference in Pb content of the CF on the control faucet (C1), and the CF fed through the Fe-SF (Fe1), should be the amount of Pb held by the Fe- impregnated SF. Values were normalized to account for the 97% efficiency of the CF to trap Pb.

Cumulative Pb added to the Fe filter was then compared with the cumulative Pb sent to the Fe-

SF based on amounts initially added to the tank. The total approximate mass of Pb sent to the

Fe1 filter was determined by taking the concentration of Pb added to the solution tank for the five runs, and multiplying each one by the volume of water that passed through the Fe-SF

(known from totalizer readings). If all of the mass added to the solution tank was measured downstream, the slope of a linear correlation line would equal 1 and the correlation coefficient, r2, would equal 1. There are very close correlations found between the cumulative mass of Pb sent to the Fe1 filter and the cumulative mass of Pb added to Fe1 with r2 = 0.99 and slope of 0.61

(Figure 7). The slope is not exactly equal to 1 because the Fe-impregnated SF is not 100 percent efficient for trapping Pb. Nonetheless, the data show substantial removal of Pb by the Fe-SF.

Furthermore, since the Fe filter continued to trap Pb in a linear fashion for all the filter runs, there is no indication that the Fe-SF approached saturation of the sites available on the goethite

27 surface.

Additionally, it was important to compare the calculated concentration of Pb based on the known addition of Pb to the solution tank with the concentration of Pb measured in the tank by

ICP. Since r2 = 0.94 and the slope is 1.03, a very close correlation was found (Figure 8).

Sometimes mass is lost by precipitation of metal particulates, and sometimes mass is added, possibly by entrainment of metal particulates remaining in the apparatus from a previous run or from the building water itself. The data suggest that particulate Pb was likely accumulating in the solution tank, as there is less correlation as the metal concentration increases and more particulates are involved. The Pb measured in the tank represents one snapshot in time, and how characteristic it was of the possibly non-homogenous solution, due to the particulates, also affected the accuracy of these calculations.

To assess the influence of these factors on the Pb concentrations, the maximum possible uncertainty from the measurement limitations was calculated (Harris, 2010). The absolute uncertainty was ± 13 mg/L as Pb for the ICP measurements, and ± 5 mg/L as Pb for the calculated concentration. The uncertainly associated with the calculated Pb concentration involves error from drying of the chemical prior to adding the Pb to the solution tank. This specific type of error is extremely difficult to account for because it is hard to truly verify if something is dry or not. If the chemical was not dried enough, it is expected to have an overestimation of Pb for the calculated concentration. About half of the values were higher on the calculated Pb compared to the measured Pb. Therefore, it is reasonable to believe that some of the error is linked to the chemical not being dried enough. However, the other half of the measurements are high for the measured values. It is likely that using a more sensitive instrument to measure Pb in the water, such as ICP-MS, would be useful in future studies to eliminate

28 potential error. More observations and replicate measurements are also recommended for a rigorous statistical interpretation. Nonetheless, there is a pretty good agreement overall between the calculated and measured Pb concentrations in the solution tank, which provides quality control for the testing system design.

After each filter run, a three-way check on the mass balance for Pb was performed using:

1) Pb measured in water samples by ICP-AES; 2) Pb measured in the whole CF by XRF; and 3) calculated Pb based on the mass added to the solution tank (see Appendix, Table A.5 for mass balance equations). Since there were not enough observations for a rigorous statistical interpretation these specific calculations were used, which are amenable to comparison statistics such as a t-test. Theoretically, all three calculations should be identical, but overall the match appears to be good except at very low numbers (Table 4; Appendix, Tables A.6-A.11).

The calculated concentration of Pb in the solution tank, which was determined using the known amount of Pb added to the tank divided by the volume of water, was compared to the measured Pb concentration in the water by ICP. The average absolute percent difference between the two was 7%. This compares with the typical uncertainty in ICP measurements of ± 10% and

± 5% for XRF.

The mass of Pb retained in the SF was determined using two techniques: 1) influent and effluent mass of Pb measured in the water by ICP; and 2) Pb measured in the SF by XRF. As a result of the larger pore size of this filter (10µm), the material could not be homogenized and the mass of Pb in the SF using XRF could not be determined. This analytical issue was solved in the subsequent stages of the study by using smaller sized filters (5µm). Therefore, only ICP was used to evaluate the amount of Pb taken up the SFs. The negative values associated with the mass of Pb retained by the control SF may reflect Pb release from the filter, it may be a result of

29 not obtaining a representative water sample or it could simply be the result of small concentrations.

Additionally, the mass of Pb in the water before and after the CFs was determined using

ICP. Mass of Pb measured in the CF was then compared in two ways: 1) calculated mass of Pb using the influent and effluent concentrations measured in the water by ICP (1 snapshot in time); and 2) measured mass of Pb in the CFs by XRF (integrated sample). The average absolute percent difference between the two calculations was 26%. Measurements below 1.0 mg as Pb were not used to assess the variation between the calculations as they were below the detection limit for the analysis. Lastly, the total mass of Pb in the testing system was compared using: 1) the mass of Pb sent to the SF based on the ICP data; and 2) the measured Pb in the SF by combining the influent and effluent Pb in the water by ICP with the Pb measured in the CF by

XRF. The average percent difference between the two methods was 41%.

There were some variations between the calculated mass of Pb compared with that of the measured value. Differences may be a result of a variety of factors including loss of mass possibly by precipitation of metal particulates, addition of mass perhaps from potential entrainment of metal particulates remaining in the apparatus from a previous run, or the analytical procedure itself, for instance, not obtaining representative samples or possibly flaws in matrix matches. In addition, it was found that XRF analysis of CFs were considerably less accurate if the mass of Pb was less than 1.0 mg as Pb, because it is close to the detection limit for the analysis. Further, the concentration of the water in the solution tank is assumed to be the same as that sent to each faucet side. Adding two sample ports, one associated with each faucet, to measure the metal concentrations in the water directly before it enters the SF, rather than relying on the water from the tank, would be ideal in future studies. In general, there is a very

30 close comparison between the various calculations except at low numbers, which is close to the detection limit. Yet, all calculations should be identical. Therefore, they were used in combination for quality control purposes to verify the operation and design of the testing system, the homogeneity of the initial solution, and the laboratory procedure by comparing the snapshot analysis of the water by ICP with the integrated sampling approach of the CFs by XRF.

SEM micrographs, in backscatter electron mode, was used to assess the influence of Fe on

Pb uptake in the Fe1 filter compared to the control (Figure 9). Bright and dark contrast zones indicate the presence of heavier chemical elements (e.g. Pb) within the bright areas, while lighter chemical elements (e.g. C) are depicted by darker areas. Areas of small Pb-rich particles (bright grains) coating the surface of the Fe filter were detected on Fe1. EDS analysis of several of these areas showed correspondingly high Pb (5-6 wt. %), Fe (44-72 wt. %), C, and oxygen (O) content with some capture of P, copper (Cu), calcium (Ca), sulfur (S), silicon (Si), sodium (Na), and zinc

(Zn) likely from the base water supply (Appendix, Figure A.8). Darker areas were high in C, O and occasionally Fe, which was expected based on the major C content from the polypropylene filter material. No bright areas were observed on the control (C1). EDS analysis showed high C and O content with some Si (Appendix, Figure A.9). The EDS data for the SFs was strictly used to compare the filters to one another. The results were used as a semi-quantitative test to evaluate the amount of analytes in the sample relative to others, and not the absolute amount of analytes in the filters.

Results from SEM-EDS analysis clearly demonstrate the occurrence of Pb in Fe1, and the absence of Pb in C1, confirming the presence of Fe enhanced Pb uptake. Additionally, the morphology of the Fe crystals was investigated. Goethite crystals are usually acicular or needle- shaped and vary considerably in size (Kosmulski et al, 2004; Schwertmann & Cornell, 2000).

Secondary electron images show that Fe1 typically lacked morphologically significant features.

Therefore, the presence of goethite in the filter could not be verified based on morphology.

Stage 2. Three sets of filter runs were performed in the same fashion as described in

Stage 1, except placed ahead of the faucets were a pair of 5µm SFs impregnated with five different Fe minerals representative of actual Fe corrosion scale solids (Figure 10 for photographs of sediment filters; Appendix, Figure A.10, for digital microscope images of sediment filters). Also, a Pb nitrate stock solution was added to the solution tank at about 40

µg/L as Pb in two batches, A and B.

XRD analyses revealed the dominant Fe mineral phases found in each SF. These are feroxyhyte (Fe2); lepidocrocite (Fe3); magnetite with minor maghemite (Fe4); ferrihydrite (Fe5); and goethite (Fe6) (Figure 11, part A, for XRD patterns; and Table 5 for list of dominant mineralogy). Excluding feroxyhyte, these minerals have been identified as major Fe corrosion scale solids (Peng et al, 2010; Schock, 2005; Sarin et al, 2004; Lin et al, 2001; Sarin et al, 2001;

Benjamin et al, 1996; Smith et al, 1996; Singley et al, 1985; Tuovinen et al, 1980; Feigenbaum,

1978). Occurrences of broad peaks are likely an effect of quick mineral formation, which was done to encourage smaller-sized particles and to permit uniform Fe coating on SFs. This, in turn, affected the degree of crystallinity. Further, elevated background in XRD patterns are a possible result of insufficient material coating the slide, but may also indicate the presence of some microcrystalline or X-ray amorphous material. Since there is considerable overlap of peaks among Fe minerals the presence of other Fe oxy-hydroxides cannot be totally ruled out. Lastly, the sample preparation could have altered the Fe mineralogy, since it was exposed to the atmosphere and was not analyzed in-situ (Cornell & Schwertmann, 2003). However, the sample

32 was prepared and analyzed immediately after the impregnation process to avoid possible biases in determining the Fe minerals.

Filter efficiency was evaluated using normalized ratios of Pb uptake by the Fe SF to the mass of Fe in the SF. Consistently higher Pb values by XRF data from SFs compared to ICP data from water samples was observed. This systematic difference suggests an issue with possible inhomogeneity of the Fe accumulation on the filter, and as a result a good representation of what is in the SF was not being captured. It is likely that homogenizing the entire SF would enable a more accurate determination, as the XRF on the filter is subject to large errors in weighing and in selecting parts of the filter to analyze. However, it is impractical to melt and homogenize the entire SF and, therefore, ICP data was primarily used to assess the impact of Fe mineralogy on

Pb uptake.

Uptake by the Fe-impregnated SF was monitored by ICP-AES analysis of metal concentrations in water before and after passing through the SF. The difference in Pb content of the water before and after the SF should be the amount of Pb retained by the filter. The mass was calculated according to the following equation:

in out Mass of Pb (mg) added to the SF = (CPb * V) – (CPb * V)

in Where CPb is the measured concentration of Pb in the solution tank (mg/L), V is the total

out volume of solution that passed through the SF known from totalizer readings (L), and CPb is the measured concentration of Pb in the water leaving the SF (mg/L). Because the amounts of Fe in the filters vary, the mass of Pb retained by the Fe filter was normalized to mg of Fe in the SF measured by XRF. To assess uncertainty associated with the normalized ratios, the maximum possible uncertainty from the measurement limitations was calculated since there was not enough observations for a rigorous statistical interpretation (Harris, 2010). The absolute uncertainty was

± 13 mg/L as Pb for the ICP measurements, and ± 3 % for the mass of Fe in the SFs measured by

XRF.

Based on the normalized ratios, there were very different behaviors for the Fe minerals

(Figure 12). Lead uptake by the filter was highest with feroxyhyte (Fe2) with 0.02 mg of Pb per mg of Fe, followed by lepidocrocite (Fe3) at 0.01, goethite (Fe6) at 0.003, and magnetite (Fe4) and ferrihydrite (Fe5) both at 0.002. Variable uptake of Cu and P was also observed using the same calculation previously mentioned for Pb. Phosphorous showed the highest accumulation in lepidocrocite (0.018 mg of P per mg of Fe), followed by ferrihydrite (0.009), feroxyhyte (0.006), and magnetite (0.004), but did not bind to goethite (-0.001). Copper was taken up more by feroxyhyte (0.0006 mg of Cu per mg of Fe) and lepidocrocite (0.0004) with some uptake by goethite (0.0002) and magnetite (0.0001), but did not bind to ferrihydrite (-0.0001). After passing through the SF for the goethite and ferrihydrite filters the water had high turbidity levels (Table 6 for water quality characteristics). This means that particles are being carried in the water and that they may carry P or Cu, which would explain the negative ratios associated with P uptake in the goethite filter, and Cu accumulation in the ferrihydrite filter. No obvious relationships were found between Fe and the other elements that were tested.

As in Stage 1, three methods were used to assess the mass balance for Pb. Comparison of the calculations shows high correlation, except at very low numbers, which were close to the detection limit for the analysis (Table 7; Appendix, Tables A.6-A.11). The average absolute percent difference between the calculated and measured Pb concentration in the solution tank was 3%.

Measured Pb retained by the SF was evaluated using ICP and XRF data. The average percent difference between the two methods was 51%. This high average is likely a result of

34 inhomogeneity of the Fe accumulation on the filter, which gave a higher mass of Pb when analyzed by XRF compared to that of ICP. As a result, the uptake of Pb by the Fe SF was evaluated using the ICP data rather than the XRF of the SF.

Mass of Pb in the CF was assessed using the ICP and XRF data, and the average percent difference was 7%. Lastly, the total mass of Pb in the testing system was compared using: 1) the mass of Pb sent to the SF based on the ICP data; and 2) the measured Pb in the SF by combining the influent and effluent Pb in the water by ICP with the Pb measured in the CF by XRF. The average percent difference between the two methods was 5%. Theoretically, the calculations should be identical, but overall that match appears to be good except at very low numbers. The values were not close to one another when the numbers were very low, below 1.0 mg as Pb, because it they are very close to the detection limit, so the errors in the calculations for the samples are large.

Under the conditions of the experiment, feroxyhyte and lepidocrocite seem to be the most effective scavengers for Pb, whereas P was most strongly scavenged by lepidocrocite. Although

Pb uptake was highest for feroxyhyte its occurrence in Fe-bearing corrosion scales in drinking water pipes has not been reported. Thus, based on these findings, lepidocrocite seems to be the most appropriate model corrosion scale. Consequently, limited emphasis is placed on feroxyhyte for the remainder of this section.

SEM-EDS analysis was employed to characterize the nature of the Pb-Fe association, and to assess the distribution of Pb in the Fe-impregnated SFs. Bright and dark areas on the surface of the filters were observed (Figure 13). EDS analysis of several of these areas revealed notable trends in Fe filters. In the darker regions, C, O, and Fe were the dominant elements. The C and

Fe content typically ranged between 50-90 wt. % for C, and 10-70 wt. % for Fe. Co-occurrence

35 of high Pb (1-8 wt. %) and Fe were observed in the brighter areas, except in the magnetite- impregnated SF (Fe4). Minor amounts of Si, P, Ca, Cu, Mn, Cl, and Na were also found

(Appendix, Figures A.11-14). No bright areas were seen on the control filter (C6). EDS analysis found no Pb, but showed high amounts of C (usually around 90 wt. %) and O with some Si and P ranging from 1-3 wt. % (Appendix, Figure A.15).

The general morphology of the filters was further examined using SEM. Individual Fe mineral crystals in the lepidocrocite filter were anhedral to subhedral in shape and mostly spherical to sugary with some waxy grains. This observation differs from previous characterization research conducted for lepidocrocite, which were laths-like crystals

(Schwertmann & Cornell, 2000). Examination of the entire sample showed an even distribution of Pb associated with the Fe. Lead was not as prevalent in the magnetite filter, and appeared to be trapped as particles rather than associated with Fe. This was not found in previous Pb adsorption studies using magnetite (Camara, 2012). However, the morphology is consistent in that magnetite contained spheroidal like structures that agglomerated into clusters (Camara,

2012; Giri et al, 2011; Wie & Viadero, 2007). SEM images showed that ferrihydrite exists in a heavily aggregated form with conchoidal fractures indicating its amorphous nature, which is consistent with other studies (Schwertmann & Cornell, 2000; Jambor & Dutrizac, 1998). Lead was not as widespread or homogeneous as was observed with the lepidocrocite filter, but when present it was associated with high Fe content. Iron crystals in the goethite filter were mainly spheroidal-like structures that agglomerated into clusters with some larger crystals that were anhedral to subhedral in shape. However, other studies characterizing goethite observed smooth, needle-like crystals (Kosmulski et al, 2004; Schwertmann & Cornell, 2000).These differences in shape could have some relation to the way the Fe precipitate was formed and then delivered to

36 the filter media, in contrast to the observations from other synthesis experiments. SEM provided no further insights into the mechanisms of Pb uptake by Fe. Perhaps examining samples at a finer scale with high-resolution microscopy, such as transmission electron microscopy, would be useful for future studies.

The results from this stage of the study are consistent with a similar comparative study on goethite and magnetite (Camara, 2013), in that magnetite accumulated more Pb compared to goethite. The enhanced Pb uptake by feroxyhyte or lepidocrocite compared to the other minerals was surprising because this had not been previously reported. In terms of water chemistry, the most likely factors to have a profound effect on the Fe-Pb association are the pH, disinfectant, and, if used, the phosphate inhibitor. Most utilities operate at a pH of 7 or above for compliance with the LCR and/or because of the Langelier Index, which indicates the degree of saturation of calcium carbonate in the water. The results from this study are only applicable for a distribution system operating at a pH above 7.5, which is above the point of zero charge (pzc) for the Fe species examined in this study (Cornell & Schwertmann, 2003). The pH at which the net surface charge is zero is termed the pzc. Pure Fe oxy-hydroxides without accumulated ions have pzc’s ranging from about 7-10. However, adsorption of anions may shift the pzc to lower pH values, while adsorption of cation may shift the pzc to higher pH values. If the pzc is negative the Fe species will attract cations, such as Pb and Cu. Yet, if the pzc is positive the Fe will attract anions, for example carbonate and chloride. An overall positive surface charge is not required for all anion uptake, such as phosphate, which likely explains why P accumulation in the SFs occurred at pH’s above the pzc (Cornell & Schwertmann, 2003). If a water utility is below pH

7.5 then the uptake behavior for the ions examined in this study, specifically Pb and P uptake by

Fe, will change.

The type of disinfectant used in water treatment will also have an influence on the uptake of various ions by Fe because Fe minerals have different stability in chlorine versus chloramine.

Switching from chlorine to chloramine could release Pb from Fe, since chloramine has a lower oxidation potential than chlorine. The chloramine may form more soluble scales that can increase dissolution of metals by breaking down the Fe scales and leaching Fe and Pb into the water

(Boyd et al, 2008).

The most common types of phosphate inhibitors used in water treatment include ortho-P, zinc ortho-P, zinc metaphosphate, bimetallic phosphate (sodium-zinc- or potassium-zinc- phosphate), and hexametaphosphate (polyphosphate) (AWWARF, 1996). Polyphosphates are typically used for Fe and Ca sequestration, while ortho-P is used for Pb and Cu corrosion control.

Since all phosphate inhibitors are not chemically alike, the type of inhibitor used will have an impact on the accumulation and possible release of Pb, P and other metals in the water.

Stage 3. The role of ortho-P on the release of Pb accumulated in the Fe corrosion scale solids was examined because of its wide use as a Pb corrosion control strategy, and, moreover, its possible detrimental effect on Fe release. Based on the results from Stage 2, experiments were repeated using a lepidocrocite-impregnated SF placed in-line ahead of one faucet (Fe7- Fe9), and a control filter (C7-C9) ahead of the other faucet. Filters were first exposed to known concentrations of Pb in Batch A (about 40 µg/L as Pb), and varying concentrations of only ortho-

P in Batch B (1.8, 3.5, and 11.6 mg/L as PO4).

XRD confirmed the presence of lepidocrocite in filters Fe7-Fe9, as shown in Figure 11, part B. Filter efficiency was evaluated using normalized ratios of Pb uptake to the mass of Fe, as described in Stage 2. Different behavior for these lepidocrocite filters was observed based on the normalized ratios (Figure 14). Lead and copper uptake by the filter was highest with Fe8,

38 followed by Fe9, and Fe7. Phosphorous was most scavenged by Fe9, followed by Fe8, and Fe7, which correspond directly to the increasing phosphate concentration. Meaning that the phosphate uptake by the Fe was proportional to the concentration, where the more phosphate added the more that was accumulated in the Fe SF.

Additionally, to assess Pb release from the SFs, the mass of Pb retained in the filter was calculated after each batch to evaluate the impact of changing ortho-P levels on Pb previously accumulated in the Fe; these calculations are described in Stage 2. Based on the calculations, in

Batch A where Pb was added to the tank, it was found that the lepidocrocite filters accumulated

Pb while the control filters did not trap any Pb (Table 8).

In Batch B where ortho-P was added to the tank, some Pb release from the Fe filter was observed using the 1.8 mg/L as PO4. No obvious correlation between Pb and Fe release or Pb and other water chemistry variables was found (Table 9 for water quality characteristics).

Therefore, Pb release may be explained by desorption from the Fe surfaces.

Further, one very obvious trend in the lepidocrocite filter is the higher the concentration of ortho-P the lower the release of Pb accumulated in the Fe. The trend of Pb release from the Fe solids follows the trend observed for Pb leaching with increasing phosphate dosing (Xie &

Giammar, 2011; Cardew, 2009; Hayes et al, 2008; Xie & Giammar, 2007; Edwards & McNeill,

2002; Colling et al, 1992).

The decrease in Pb release in the presence of ortho-P was not expected given the potential for phosphate to release minerals from corrosion scales, as documented by others

(HDR, 2009; Tesfai et al, 2006; McNeill & Edwards, 2000). The study results show that increasing the ortho-P levels suppressed the release of Pb from the model Fe corrosion scales.

However, the effect was only noticeable at 3.5 mg/L as PO4 or higher. If Pb is already

39 accumulated in the Fe scales, then adding phosphate to the water may immobilize some of it.

Yet, a high concentration of phosphate is needed to accomplish that. About 3.5 mg/L as PO4 is a bit higher than what is commonly used in the U.S., but it is a plausible dosage for many water systems, as 10 mg/L as total phosphate ion is the ANSI/NSF Standard 60 limit for use of inorganic phosphate. In actual distribution systems, the amount of Pb release would also vary with the background water quality. The key to health and regulatory compliance issues, based on the LCR’s one liter first-draw water sample, would be whether the concentration of the Pb released from the scales would be close to the 0.015 mg/L as Pb action level, presuming any upstream Pb SL was removed. Additionally, further research is needed to determine the operative phosphate threshold for removing Pb in drinking water at the tap, which is known from this study to be somewhere between 1.8 – 3.5 mg/L as PO4.

The mass balance for Pb was also determined after each filter run, as previously mentioned in the other stages. Comparison of the three calculations showed a reasonable match

(Table 10; Appendix, Tables A.6-A.11). The average absolute percent difference for the calculated and measured Pb concentration in the solution tank was 11%. However, no Pb was added to the tank in Batch B, ortho-P was used instead, which explains why the percent difference observed in Batch B was below detection.

Measured Pb retained in the SF was determined using ICP and XRF. The average absolute percent difference between the two was 117%. As previously mentioned, this variation is likely a result of possible inhomogeneity of the Fe accumulation on the filter, which gave a higher mass of Pb when analyzed by XRF compared that of ICP.

The two techniques used to quantify the mass of Pb in the CF (Pb calculated using ICP and Pb measured by XRF) were also compared. The average percent difference was 24%. Lastly,

40 the total mass of Pb in the testing system was compared using: 1) the mass of Pb sent to the SF based on the ICP data; and 2) the measured Pb in the SF by combining the influent and effluent

Pb in the water by ICP with the Pb measured in the CF by XRF. The average percent difference between the two methods was 24%. As noted in the previous stages, both calculations should be identical, however, there are a variety of reasons why the calculations are not equal. Nonetheless, they overall appear to be a pretty good match except at very low numbers. More observations for a rigorous statistical interpretation are recommended for future studies, as well as the use of more sensitive instrumentation for low concentrations of Pb and other elements of interest in the water and solid samples.

SEM-EDS analysis was used to characterize the nature of the Pb-Fe association, and to evaluate the distribution of Pb in the Fe filters. EDS analysis of several of the contrasting areas on samples revealed similar trends among the lepidocrocite filters. High C, O, and Fe content were observed with some Pb, Si, and Ca, and occasionally Mg, Al, and Zn (Appendix, Figure

A.15, A.17, and A.19). The distribution of Pb did not appear to be homogeneous, but a co- occurrence of Pb and Fe was always observed. No discrete Pb or Pb-P grains were identified

(Figure 15). This may have been an effect of the Au/Pd coating applied to the samples, which overlaps with the P peaks on the EDS spectra. The specific emission lines comprising the overlap are 2.013 keV for the Kα-line for P and 2.120 keV for the Mα-line for Au (USEPA, 2002).

Lepidocrocite filters appeared to be more crystalline in comparison to the lepidocrocite filter in

Stage 2 (Fe3) when no ortho-P was added. Yet, the general morphology was similar; anhedral to subhedral in shape and mostly spherical to sugary grains that agglomerated into clusters.

Adsorbed P may have inhibited the formation of more crystalline Fe phases, presumably by incorporation into the crystal lattice structure. EDS analysis of the control filters showed high C

41 and O content with some Fe, Pb, P, Ca, Mg, and Si that was trapped as particles (Appendix,

Figure A.16, A.18, and A.20). Similar to the lepidocrocite filters, Pb was found in the presence of Fe. Until this stage of the study, no Pb was found in the control filters. It is reasonable to believe that the trapping of Pb and the other elements as particles was due to the presence of ortho-P. Additionally, as the ortho-P concentration increased more particles were observed in the filters. Further, the phosphate appears to be reacting with the constituents in the background water, and the added Pb to form particulates that are trapped by the control filters.

Figure 6 Comparison of metal concentrations in water from each faucet side on the laboratory apparatus

Note: ICP-AES was used to determine the concentrations of metals in water samples

Figure 7 Total lead accumulated by the Fe1 sediment filter

*Cumlative Pb in the Fe1 sediment filter was determined using the XRF data from the carbon filters (CFs). The difference in Pb content of the CF on the control faucet (C1), and the CF fed through the Fe sediment filter (Fe1), should be the amount of Pb held by the Fe1 sediment filter. Note: CF data was normalized to account for the 97% efficiency of the CF.

Figure 8 Comparison of lead added to the solution tank and lead measured in the tank by ICP-AES in Stage 1

Table 4 Mass balance for lead in Stage 1

*No ICP data collected for run 1; Filters could not be processed for XRF analysis in this stage of the study; Negative values associated with the mass of Pb retained by the control sediment filter (SF) may reflect release of Pb from the filter or it may be a result of not obtaining a representative water sample. Note: values that are bold represent data that is close to the detection limit for the analysis.

Figure 9 SEM images of sediment filters used in Stage 1

These backscatter electron micrographs show areas of small lead-rich particles (bright grains) coating the surface of the iron filter (left), while no lead is found on the control (right), confirming the presence of iron enhanced lead uptake.

Figure 10 Photographs of sediment filters used in Stage 2

Images depict the distinct color variations observed in the iron-impregnated filters compared to the control (C6). Colors aided in mineral identification during synthesis (scale bar divisions are cm on the left and inches on the right side, except in C6 where divisions are reversed).

Figure 11 X-ray diffractograms of synthetic iron oxy-hydroxides from representative iron-impregnated sediment filters in A) Stage 2, and B) Stage 3

F=Feroxyhyte, L=Lepidocrocite, M=Magnetite, Mh=Maghemite, Fh=Ferrihydrite, and G=Goethite are the dominate iron mineral phases found in these iron sediment filters.

Table 5 Dominant mineralogy for each iron- impregnated sediment filter

Figure 12 Efficiency of iron-impregnated sediment filters from Stage 2

Normalized ratios of the mass of lead (Pb), phosphorous (P), and copper (Cu) uptake (measured in the water samples by ICP) to the mass of iron (Fe), which was measured in sediment filter by XRF, are used to evaluate the iron sediment filter efficiency.

Table 6 Water quality field parameters collected in Stage 2

Table 7 Mass balance for lead in Stage 2

Note: bold values represent data that is close to the detection limit for the analysis or reflect that no ICP data was collected (ICP data was only collected in the third run); All water samples analyzed by ICP were collected in Batch B, which may reflect the negative values associated with the mass of Pb retained by the sediment filters (SF); Lastly, 'BD' means below detection for the analysis.

Figure 13 SEM micrographs of selected sediment filters from Stage 2

Images depict the morphological differences among iron minerals. Lead content in the iron filters (Fe3-Fe6) varied, but co-occurrence of lead and iron were observed using EDS analysis, except in Fe4 (data not shown). No lead was found in the control filter (C6), which further confirmed that the presence of iron enhanced lead uptake.

Figure 14 Efficiency of iron-impregnated sediment filters from Stage 3

Table 8 Comparison of lead retained in sediment filters after each batch in Stage 3

Table 9 Water quality field parameters collected in Stage 3

Table 10 Mass balance for lead in Stage 3

Note: bold values represent data that is close to the detection limit for the analysis; 'BD' means below detection for the analysis.

Figure 15 SEM micrographs of selected sediment filters from Stage 3

Images show more crystalline nature of particles associated with filters in this stage of the study. Lead content in the iron filters (Fe6-Fe9) varied, but co- occurrence of lead and iron was observed using EDS analysis (data not shown). Lead-iron complexes were found as trapped particles on control filters (C7-C9), and are likely an effect from the orthophosphate addition.

CONCLUSIONS

Several continuous flow experiments were conducted to: 1) investigate the uptake of Pb on different Fe minerals in a form similar to water distribution system piping scales; 2) assess the influence of changing ortho-P levels on Pb previously accumulated in the Fe mineral material; and 3) evaluate the impact of Fe mineralogy and ortho-P concentrations on Pb levels in drinking water at the tap. The novelty of this testing system design is the ability to isolate the variables that influence Pb.

The results from this study show that the presence of Fe greatly enhanced Pb uptake in the filter compared to the control containing no Fe. XRF and ICP data revealed a very different behavior for the five Fe-SFs. Under the conditions of the experiment, feroxyhyte and lepidocrocite seem to be the most effective scavengers for Pb and Cu, while P was most strongly associated with lepidocrocite. Using lepidocrocite-impregnated SFs, it was found that progressively increasing ortho-P residual levels in the water will suppress the release of accumulated Pb from Fe corrosion scales. However, the effect was only noticeable at 3.5 mg/L as PO4 or higher. The mass of Pb in the water after passing through the lepidocrocite filter using

1.8 mg/L as PO4 was about 1.5 mg as Pb. This was similar to the mass of Pb observed for the lepidocrocite filter from Stage 2 where no ortho-P was added, which was also about 1.5 mg as

Pb. Yet, the mass of Pb in the water after passing through the lepidocrocite filter was 0.2 mg as

Pb when both 3.5 and 11.6 mg/L as PO4 was used.

Furthermore, results confirm the suggestion that galvanized pipes in premise plumbing have the ability to trap Pb from upstream sources. The addition of ortho-P from 3.5 to 11.6 mg/L as PO4 was not found to disturb and elevate particulate Pb or Fe release from the impregnated filter material, suggesting that such a treatment would not be detrimental to scales in galvanized

59 steel or unlined Fe pipes. However, other changes in water treatment (e.g. disinfectant changes) or hydraulic disturbances, such as Pb SL replacements or water flow changes, could have a profound effect on Pb and other regulated contaminants accumulated in the Fe corrosion scales.

Therefore, it is important to keep corrosion scales as stable as possible to prevent potential release of Pb and other contaminants in tap water at levels that may exceed the regulations set by the EPA. Additionally, some Pb release was observed with the 1.8 mg/L as PO4, which suggests that typical ortho-P dosing used in the U.S. (usually < 3.0 mg/L as PO4) will not be sufficient to prevent Pb release from galvanized pipes.

Based on these findings, there are a couple recommendations for minimizing Pb exposure in premise plumbing. They are divided into two cases depending on the plumbing materials. The first case is for homes with Pb service lines. A three part filtration system is suggested that uses:

1) a 5μm SF impregnated with Fe followed by; 2) a 1μm SF not impregnated with Fe installed at the entry point into the home; and 3) point-of-use CF that is certified under NSF/ANSI (Standard

53 for both particulate and dissolved Pb) attached to the faucet. The combination of the two SFs would not contribute any Fe to the house, and would provide protection from any Pb released by the SL for the entire home. The CF should only be applied at the point-of-use since they remove any chlorine in the water, which is necessary for controlling microbial activity. Use of the CF would provide an additional measure that removes any remaining Pb in the water that the SFs did not trap.

The second case is for homes with galvanized pipes. Since there is likely remnant Pb in the pipes, presumably from upstream Pb sources (mainly the Pb service line), the SFs at the entry point into the home would not protect against the relic Pb. Instead, it is desirable to replace the

60 galvanized pipes. However, if the immediate cost is too high then the only protection against Pb would be the point-of-use carbon filter attached to the faucet.

This research emphasizes the need to consider galvanized pipes as a significant source of

Pb in tap water when there was an upstream source of Pb. Important additional studies are needed to determine how long a Fe-SF would last, to evaluate the effect of other important water quality variables (e.g. pH, use of chloramine for disinfection, alkalinity, etc.), to assess the effect of decreasing ortho-P concentrations on the Pb content in drinking water, and also to determine the point between 1.8 and 3.5 mg/L as PO4 where ortho-P is most effective for reducing Pb levels in drinking water. The use of other types of phosphate inhibitors, such as polyphosphate, should also be evaluated. Finally, studies are needed to identify the existence of, or the potential for, accumulation of other contaminants in galvanized pipes in premise plumbing such as arsenic, aluminum, chromium. In all cases, various improvements to the study design should be made including: 1) employing other analytical methods to evaluate speciation in order to understand the accumulation mechanism; 2) use of more sensitive analytical instrumentation, such as ICP-mass spectrometry, to detect low Pb levels in the water samples; 3) more rigorous statistical interpretations using more observations; and 4) homogenization of the entire SF for more accurate determination of the chemical composition.

It is recommended that the study results should be carefully evaluated before being applied to actual drinking water systems. The experimental approach used in this study is not a complete representation of household plumbing conditions in terms of water flow patterns, and materials used, for instance using Fe-impregnated SFs rather than actual galvanized pipes.

Additionally, the levels of Pb and ortho-P studied are conceivable but are higher than what most utilities in the U.S. use in water treatment. By using the high ortho-P concentration (11.6 mg/L as

PO4) the probability of observing any effects of Fe mineralogy and ortho-P on the Pb content in tap water was believed to be the greatest. Lastly, the effects of Fe surface area for the various minerals examined was outside the scope of this project, but its impact on Pb uptake cannot be totally ruled out. Thus, there is no guarantee that trends noted here would be directly transferable to other DWDSs. Nonetheless, this approach did permit unambiguous evaluation of two isolated variables that influence Pb uptake, and provides some important insights into the significance of

Fe mineralogy and changing ortho-P levels on the Pb content in drinking water at the tap.

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APPENDIX Figure A.1 The nature of the particles trapped in the sediment filter from field studies was investigated using SEM Several modes of trapping were evident:

Small Pb particles (bright grains) covering the Small Pb particles (bright grains) embedded in a surface of a darker Ca mineral, probably CaCO3. darker Ca mineral, probably CaCO3.

Scanning (left) and backscatter image (right) of a Pb-rich grain trapped by the filter. Pb content about 75 wt. %.

Very small Pb grains, revealed in backscatter Closer view. Note the nano-scale Pb-rich grains. mode that may be growing from solution on filter Pb about 40 wt. %; Fe 2 wt. %; and Mn 1 wt. %. fibers.

Figure A.2 Labeled photograph of carbon filter components

Figure A.3 Process of ashing carbon filters for XRF analysis

Photographs showing the filter components before ashing (top), and after ashing (bottom). Note: Scale bar subdivisions are mm (at the top); images were taken under ambient laboratory lighting.

Figure A.4 Photographs of selected sediment filter sizes

Images of two virgin sediment filters with different pore sizes: 5 µm (left), and 10 µm (right) filters. The filter on the left-side is cut in half, vertically, to illustrate the physical differences between the filter sizes. Note: Scale bar subdivisions are mm (left-side); images were taken under ambient laboratory lighting.

Figure A.5 Photographs of synthesizing iron solutions

All iron solutions, except Fe1, were prepared by: 1) bubbling nitrogen gas through distilled water; 2) adding ferrous chloride crystals, and replacing the gas with air; and 3) adding either 1 M NaOH or 1 M NaHCO3 solution. Note: The angle of the tubing in the beaker played an important role in mixing the solution; also, color was a major initial indicator for the particular iron mineral formed during synthesis.

Figure A.6 Photographs of melting sediment filter material for XRF analyses

Method for making XRF pellets involved a three part melting process, using blended filter materials, to achieve the desired thickness. Note: Pellets were made in duplicates to assess potential variance; images were taken under ambient laboratory lighting; scale bar subdivisions are in mm (left-side).

Figure A.7 EDS analysis for the Fe1 sediment filter (Stage 1)

Spectrum Na Si P Cl Ca Fe Cu Pb Spectrum 1 2.3 1.2 3.4 1.9 2.8 36 2.1 6.5 Spectrum 2 2.1 1.4 3.6 1.8 2.3 37 1.8 6.4 Spectrum 3 - 2.1 3.7 0.67 2.0 39 1.5 5.7 Spectrum 4 ------

Spectrum 5 - - - - - 34 - -

Note: All results are expressed in wt. % .C and O are present in all spectrums; however, it is difficult to quantify the exact amount present and, therefore, the data is not shown. The lighter areas in Spectrums 1-3 confirm the presence of Pb in the Fe-impregnated sediment filter. Spectrum 4 is taken on the C-rich SEM stub to verify that only C was present, and Spectrum 5 shows only Fe on the darker regions of the sediment filter fiber. Lastly, this is only one of many EDS analysis that was performed on the sediment filter fibers.

Figure A.8 EDS analysis for C1 (Stage 1)

Spectrum Si Spectrum 1 7.9 Spectrum 2 17 Spectrum 3 - Spectrum 4 -

Note: All results are expressed in wt. %. C and O are present in all spectrums, and are the major constituents found in the control filter; however, it is difficult to quantify the exact amount present and, therefore, the data is not shown. Spectrums 1-3 are taken to verify the chemical composition of the filter, while Spectrum 4 is performed on the C-rich SEM stub to confirm that only C is present. Additionally, this is only one of many EDS analysis that was performed on the sediment filter fibers.

Figure A.9 Digital microscope images of blended sediment filter materials from Stage 2

Note: all micro-images are taken at 50x magnification.

Figure A.10 EDS analysis for lepidocrocite (Fe3) in Stage 2

Element Wt. % C 54 O 15 Pb 1.4 Fe 30

Figure A.11 EDS analysis for magnetite (Fe4) in Stage 2

Element Wt. % C 58 O 25 Si 1.1 Fe 15

Note: It is difficult to quantify the exact amount of C and O present in the sample; they were only obtained to better assess the amount, and the distribution of Pb, as well as other elements, in the sample. No Pb was observed in association with Fe, but some Pb particles were found (data not shown). These were likely trapped as particulates by the filter fibers. Lastly, this is only one of many EDS analysis that was performed on the sediment filter fibers.

Figure A.12 EDS analysis for ferrihydrite (Fe5) in Stage 2

Element Wt. % C 28 O 13 Fe 41 Si 4.5 N 4.2 Cl 3.2 Pb 2.0 Note: It is difficult to quantify the exact amount of C and O present in the sample; they were only obtained to better assess the amount, and the distribution of Pb, as well as other elements, in the sample. Lastly, this is only one of many EDS analysis that was performed on the sediment filter fibers.

Figure A.13 EDS analysis for goethite (Fe6) in Stage 2

Element Wt. % C 38 O 16 Fe 42 Pb 3.4

Figure A.14 EDS analysis for the control filter (C6) in Stage 2

Element Wt. % C 91 O 8.8

Note: It is difficult to quantify the exact amount of C and O present in the sample, but they are the major constituents found in the control filter as well as some Si and P. Additionally, this is only one of many EDS analysis that was performed on the sediment filter fibers.

Figure A.15 EDS analysis for the lepidocrocite filter (Fe7) in Stage 3

Element Wt. % C 66 O 17 Fe 14 Pb 2.0

Note: It is difficult to quantify the exact amount of C and O present in the sample; they were only obtained to better assess the amount, and the distribution of Pb, as well as other elements, in the sample. The sediment filter was high in C, O, and Fe with some Pb, Si, Ca, and occasionally some Mg, Al, and Zn. Distribution of Pb did not appear to be homogenous, but a co-occurrence of Pb and Fe was always observed. Lastly, this is only one of many EDS analysis that was performed on the sediment filter fibers.

Figure A.16 EDS analysis for the control filter (C7) in Stage 3

Element Wt. % C 33

O 25 Fe 32 Pb 1.8 Si 3.6 P 1.6 Ca 1.3 Mg 1.0

Note: It is difficult to quantify the exact amount of C and O present in the sample, but they are the major constituents found in the control filter as well as some Fe, Pb, P, Ca, Mg, and Si that were trapped as particles. Additionally, this is only one of many EDS analysis that was performed on the sediment filter fibers.

Figure A.17 EDS analysis for the lepidocrocite filter (Fe8) in Stage 3

Element Wt. % C 20 O 23 Fe 49 Pb 1.5 Si 1.7 P 1.8 Ca 1.5 Mg 1.6

Note: It is difficult to quantify the exact amount of C and O present in the sample; they were only obtained to better assess the amount, and the distribution of Pb, as well as other elements, in the sample. The sediment filter was high in C, O, and Fe with some Pb, Si, Ca, and occasionally some Mg, Al, and Zn. Distribution of Pb did not appear to be homogenous, but a co-occurrence of Pb and Fe was always observed. Lastly, this is only one of many EDS analysis that was performed on the sediment filter fibers. 89

Figure A.18 EDS analysis for the control filter (C8) in Stage 3

Element Wt. %

C 56 O 11 Fe 29 Pb 1.6 Si 1.9

Figure A.19 EDS analysis for the lepidocrocite filter (Fe8) in Stage 3

Element Wt. % C 54 O 15 Fe 23 Pb 1.9 Si 2.4 P 1.4 Ca 1.1

Note: It is difficult to quantify the exact amount of C and O present in the sample; they were only obtained to better assess the amount, and the distribution of Pb, as well as other elements, in the sample. The sediment filter was high in C, O, and Fe with some Pb, Si, Ca, and occasionally some Mg, Al, and Zn. Distribution of Pb did not appear to be homogenous, but a co-occurrence of Pb and Fe was always observed. Lastly, this is only one of many EDS analysis that was performed on the sediment filter fibers.

Figure A.20 EDS analysis for the control filter (C9) in Stage 3

Element Wt. % C 58

O 18 Mg 4.4

Ca 6.1

Table A.1 Equipment specifications for filter apparatus

Table A.2 Effectiveness of the carbon filter used in filter runs for removing lead in the water

Table A.3 NSF/ANSI Standards 42 and53 certification test results for the carbon filter used in the study

Table A.4 Comparison of metal concentrations in water from each faucet side on the laboratory apparatus

Note: metal concentrations were determined by ICP; the detection limit refers to the minimum detection limit for each element.

Table A.5 Equations used to determine the mass balance for lead .

Table A.6 Mass balance for lead measured in water samples for the right faucet

Table A.7 Mass balance for lead measured in water samples for the left faucet

Table A.8 Mass balance for lead calculated based on the solution tank addition for the right faucet

100

Table A.9 Mass balance for lead calculated based on the solution tank addition for the left faucet

101

Table A.10 Mass balance for lead measured in the carbon block filter associated with the right faucet

102

Table A.11 Mass balance for lead measured in the carbon block filter associated with the left faucet

103