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Pilot capacity iron electrocoagulation scale-up for natural organic matter removal for drinking water… McBeath, Sean T. 2017

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   PILOT CAPACITY IRON ELECTROCOAGULATION SCALE-UP FOR NATURAL ORGANIC MATTER REMOVAL FOR DRINKING WATER TREATMENT  by  Sean T. McBeath  B.A.Sc., The University of British Columbia, 2013    A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF APPLIED SCIENCE  in  THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES  (Chemical & Biological Engineering)   THE UNIVERSITY OF BRITISH COLUMBIA  (Vancouver)    February 2017     © Sean T. McBeath, 2017  ii Abstract Canadian remote communities are most often those who are affected by poor water quality and boil water advisories. A major issue is the applicability of traditional water treatment technologies to unconventional applications (small-scale and inaccessible communities).  Their inaccessibility presents difficulties for supplying needed chemicals involved in traditional treatment processes such as coagulations and flocculation. Electrocoagulation (EC), an electrochemical process producing coagulant chemicals on-site and on-demand, may be an alternative technology to traditional coagulation suitable for small and remote communities. The following work investigated a continuous iron EC process for natural organic matter (NOM) removal. EC experiments were undertaken in the laboratory at 1.35 and 5 LPM, using synthetic surface water, monitoring the effect of flocculation, metal loading (ML), current density and inter-electrode gap. At both flow rates, flocculation was found to have no effect on the reduction of DOC or UV-abs-254. ML was found to have the greatest effect on both DOC and UV-abs-254 reductions, where the highest ML tested yielded reductions >90% and >60%, respectively. Increases in UV-abs-254 at low ML were found to be due to dissolved residual iron. It was determined that humic acid and chloride functioned as ligands and increased the solubility of iron. Operations were scaled-up to 10 LPM and integrated into a water treatment plant in the community of Van Anda, using raw surface water. Average DOC and UV-abs-254 reductions at the greatest ML were 37.2±4.2% and 54.7±0.9%, respectively. EC was found to have low energy requirements at a pilot-scale, whereby 0.480-0.621 kWh per cubic meter of water treated was required to operate at the conditions that yielded the greatest NOM reductions. Finally, an investigation to determine the current density distribution was undertaken. Current distribution results yielded increased current uniformity with the increase of the inter- iii electrode gap. This increased uniformity can be attributed to the water velocity profiles in the reactor. Through computational fluid dynamic (CFD) models, it was demonstrated that fluid flow uniformity also increased with an increasing inter-electrode gap. Regions of the electrode that were observed to be occupied by high fluid velocity were also areas yielding greater current density.   iv Preface The research outlined in the following thesis has materialized into multiple manuscripts and conference presentations. The electrocoagulation laboratory scale-up work outlined in Chapter 2 was published in a non-referred/proceedings journal:  S.T. McBeath, K.L. Dubrawski, M. Mohseni, D.P. Wilkinson, “Pilot-Scale Iron Electrocoagulation for Natural Organic Matter Removal,” Vatten – Journal of Water Management and Research, vol. 71, pp. 231-238, 2014. Additionally, two manuscripts are currently in progress. The first manuscript includes the research related to and outlined in Chapter 3. The manuscript title is as follows:  S.T. McBeath, M. Mohseni, D.P. Wilkinson, “Pilot Capacity Iron Electrocoagulation Scale-Up for Natural Organic Matter Removal,” 2017. In Progress. The second manuscript currently in progress includes the research described in Chapter 4. The manuscript title is as follows:  S.T. McBeath, M. Mohseni, D.P. Wilkinson, “In-situ Determination of Current Distribution for Pilot-Scale Iron Electrocoagulation,” 2017. In Progress. In addition to the aforementioned journal publications, the research throughout this author’s M.A.Sc. was presented (poster and/or oral) at various conferences. A total of three RES’EAU WaterNet Annual General Meeting conferences were attended, whereby a poster was presented at each: S.T. McBeath, K.L. Dubrawski, M. Mohseni, D.P. Wilkinson,  “Pilot-Scale EC Process Parameters for NOM Removal from Drinking Water,” May 29-30, 2014. S.T. McBeath, M. Mohseni, D.P. Wilkinson, “Pilot-Scale Iron Electrocoagulation for Natural Organic Matter Removal,” May 26-27, 2015. S.T. McBeath, M. Mohseni, D.P. Wilkinson, “Pilot-Scale Electrocoagulation for NOM Removal from VAID’s Surface Water Supply,” April 30-May 1, 2016. Preliminary electrocoagulation scale-up work was presented at the poster competition in  v the British Columbia Electrochemical Society Chapter’s Young Electrochemists Symposium, winning 3rd place: S.T. McBeath, K.L. Dubrawski, M. Mohseni, D.P. Wilkinson,  “Pilot-Scale EC Process Parameters for NOM Removal from Drinking Water,” July 4, 2014. Laboratory scale-up research outlined in Chapter 2 was orally presented in the long presentation format at the Water and Engineering Student Talks (WEST) Conference, where it received the “People’s Choice” award: S.T. McBeath, M. Mohseni, D.P. Wilkinson, “Electrocoagulation for Drinking Water Treatment – The Search for an Alternative Technology Appropriate for Remote BC Communities,” July 8-9, 2015 The M.A.Sc. work was also presented at two major international conferences as a poster presentation and oral presentation. A poster featuring laboratory scale-up research was presented at the International Water Association NOM 6 conference in Malmo, Sweden: S.T. McBeath, K.L. Dubrawski, M. Mohseni, D.P. Wilkinson, “Pilot-Scale Iron Electrocoagulation for Natural Organic Matter Removal,” September 7-10, 2015. A oral presentation featuring pilot-plant electrocoagulation research, outlined in Chapter 3, as well as electrode current density mapping (Chapter 4) was presented at the American Water Works Association ACE 16 conference in Chicago, Illinois:  S.T. McBeath, M. Mohseni, D.P. Wilkinson, “Electrocoagulation – An Emerging Drinking Water Treatment Technology for Small Systems,” July 21-23, 2015         vi      Table of Contents  Abstract ................................................................................................................. ii Preface .................................................................................................................. iv Table of Contents ................................................................................................. vi List of Figures ....................................................................................................... ix List of Tables ...................................................................................................... xiii List of Abbreviations .......................................................................................... xiv List of Symbols .................................................................................................... xv Acknowledgements .............................................................................................. xvi 1   Introduction ..................................................................................................... 1      1.1     Drinking Water Treatment for Surface Water Supplies ................................... 2           1.1.1   Conventional Drinking Water Treatment .................................................. 3           1.1.2   Small and Remote Community Water Challenges ..................................... 6      1.2     Electrocoagulation Background & Literature Review ...................................... 7           1.2.1   Electrocoagulation Principles ..................................................................... 8           1.2.2   Electrocoagulation for Wastewater Treatment ........................................ 14           1.2.3   Electrocoagulation for Drinking Water Treatment .................................. 16           1.2.4   Electrochemical Investigations of Electrocoagulation .............................. 20           1.2.5   Natural Organic Matter and Disinfection By-Products ........................... 22           1.2.6   RES’EAU Community Circle: VAID ....................................................... 23      1.3     Research Scope and Objective ........................................................................ 25           1.3.1     Electrocoagulation Scale-Up .................................................................. 25           1.3.2   Current Distribution Mapping ................................................................. 27  vii           1.3.3   Research Limitations ............................................................................... 29 2   Iron Electrocoagulation Scale-Up ................................................................... 31      2.1   Chapter Introduction ........................................................................................ 31      2.2   Low and Medium Flow Electrocoagulation ...................................................... 31           2.2.1   Materials and Methods ............................................................................ 32           2.2.2   Results and Discussion ............................................................................. 36                2.2.2.1   Flocculation Effects ......................................................................... 36                2.2.2.2   Metal Loading Effects ..................................................................... 37                     2.2.2.2.1   Low Flow Rate ....................................................................... 37                     2.2.2.2.2   Medium Flow Rate ................................................................. 42                2.2.2.3   Electrocoagulation Using Suwannee River NOM ............................ 47                2.2.2.4   Inter-Electrode Gap and Current Density Effects ........................... 53                2.2.2.5   Electrocoagulation Power Requirements ......................................... 59      2.3   Chapter Conclusions ......................................................................................... 62 3   Pilot-Scale Iron Electrocoagulation ................................................................ 65      3.1   Chapter Introduction ........................................................................................ 65      3.2   Pilot-Capacity Electrocoagulation .................................................................... 66           3.2.1   Materials and Methods ............................................................................ 66           3.2.2   Results and Discussion ............................................................................. 69                3.2.2.1   Metal Loading Effects ..................................................................... 70                3.2.2.2   Inter-Electrode Gap and Current Density Effects ........................... 74                3.2.2.3   NOM Removal Characterization ..................................................... 78                3.2.2.4   Pilot Electrocoagulation Energy Requirements ............................... 81      3.3   Chapter Conclusion .......................................................................................... 85 4   Electrode Current Density Mapping .............................................................. 87      4.1   Chapter Introduction ........................................................................................ 87      4.2   Partial Electrode Approach .............................................................................. 88           4.2.1   Material and Methods .............................................................................. 89           4.2.2   Results and Discussion ............................................................................. 92                4.2.2.1   Low Flow Rate Current Distribution .............................................. 92                4.2.2.2   High Flow Rate Current Distribution ........................................... 104      4.3   Chapter Conclusion ........................................................................................ 114 5   Conclusion ..................................................................................................... 116      5.1   Summary of Results ....................................................................................... 116      5.2   Recommended Future Work ........................................................................... 120  viii Bibliography ....................................................................................................... 122 Appendix A – Raw Experimental Data .............................................................. 128      A.1   Low Flow Electrocoagulation Raw Data ....................................................... 128      A.2   Medium Flow Electrocoagulation Raw Data ................................................. 137      A.3   Pilot-Scale, Raw Water Electrocoagulation Raw Data .................................. 143      A.4   Low Flow Polarization Curve Data ............................................................... 145      A.5   High Flow Polarization Curve Data .............................................................. 151 Appendix B – Reactor & Software Design .......................................................... 157      B.1   Electrocoagulation Reactor & Electrode Design ............................................ 157      B.2   LabVIEW Software Design ............................................................................ 160 Appendix C – Synthetic Water Preparation ....................................................... 162      C.1   Humic Acid Stock Solution Preparation ........................................................ 162      C.2   Synthetic Surface Water Preparation ............................................................ 163     ix      List of Figures  Figure 1-1: Common drinking water treatment unit operations from surface supplies ..... 4 Figure 1-2: Electrocoagulation process: (a) half-cell reactions, (b) coagulant and floc formation .......................................................................................................................... 8 Figure 1-3: Iron Pourbaix diagram ................................................................................. 13 Figure 1-4: Possible structures of (a) NOM and, (b) HA ............................................... 23 Figure 1-5: a) Texada Island and VAID location, with respect to BC. (b) Priest Lake ..... ........................................................................................................................................ 24 Figure 1-6: Main experimental and performance variables for factorial design  scale-up 26 Figure 1-7: Horizontal and vertical masked regions of the electrodes, for current distribution determination .............................................................................................. 28 Figure 2-1: Schematic drawing of designed EC reactor; A, B and C indicate the baffled inlet, the electrode area, and the outlet, respectively ..................................................... 32 Figure 2-2: Top view of the EC reactor; (a) single-cell setup, (b) four-cell setup ........... 33 Figure 2-3: Electrocoagulation reactor during EC operation .......................................... 34 Figure 2-4: Experimental EC process flow diagram ........................................................ 36 Figure 2-5: Low flow rate (1.35 LPM) DOC reductions: (a) 2-cell, and (b) 1 mm inter-electrode gap ................................................................................................................... 39 Figure 2-6: Low flow rate (1.35 LPM) experiments operating with a 10 mm inter-electrode gap ................................................................................................................... 40 Figure 2-7: Low flow rate (1.35 LPM) UV-abs-254 reductions: (a) 2-cell, and (b) 1 mm inter-electrode gap .......................................................................................................... 41  x Figure 2-8: Medium flow (5.00 LPM) DOC reductions: (a) 2-cell, (b) 1 mm inter-electrode gap ................................................................................................................... 43 Figure 2-9: Medium flow rate (5.00 LPM) UV-abs-254 reductions: (a) 2-cell, (b) 1 mm inter-electrode gap .......................................................................................................... 44 Figure 2-10: Low and medium flow rate DOC and UV-abs-254 comparison (N=2, δ=1 mm) ................................................................................................................................ 45 Figure 2-11: Residual iron concentrations after EC and direct filtration ........................ 46 Figure 2-12: UV-abs-254 (a) and DOC (b) reductions of synthetic water containing chloride and Van Anda representative surface water. Low flow rate (1.35 LPM), N=4, δ=1 mm .......................................................................................................................... 50 Figure 2-13: Effect of HA concentrations on UV-abs-254 at constant chloride concentration of 0.3225 g/L. Low flow rate (1.35 LPM), N=4, δ=1 mm ....................... 51 Figure 2-14: EC effect on UV-abs-254 using Suwannee River NOM. Low flow rate (1.35 LPM), N=4, δ=1 mm ............................................................................................ 52 Figure 2-15: DOC reductions during low flow rate (1.35 LPM) and the effect of current density and inter-electrode gap at: (a) ML=25.5 mg/L, (b) ML=38.3 mg/L, (c) ML=51.1 mg/L, (d) ML=63.8 mg/L .............................................................................. 55 Figure 2-16: Cell potential during low flow rate (1.35 LPM) experiments at: (a) ML=25.5 mg/L, (b) ML=38.3 mg/L, (c) ML=51.1 mg/L, (d) ML=63.8 mg/L ............ 55 Figure 2-17: DOC reductions during medium flow rate (5.00 LPM) and the effect of current density and inter-electrode gap at: (a) ML=13.9 mg/L, (b) ML=38.2 mg/L, (c) ML=51.1 mg/L, (d) ML=66.0 mg/L ........................................................................ 57 Figure 2-18: DOC reduction of EC at i=8.66±0.11 mA/cm2 operating at medium flow rate (5.00 LPM) .............................................................................................................. 58 Figure 2-19: Effect of ML on energy requirements per unit water treated at low flow rate (1.35 LPM) during 4-cell configuration experiments ............................................... 60 Figure 2-20: Energy requirements for low flow rate (1.35 LPM) EC operations at (a) ML=51.1 mg/L, (b) ML=63.8 mg/L .............................................................................. 61 Figure 2-21: Energy requirements for medium flow rate (5.00 LPM) EC operations at (a) ML=51.1 mg/L, (b) ML=63.8 mg/L ........................................................................ 62 Figure 3-1: (a) Van Anda MWTP at Priest Lake, (b) Inside the MWTP ..................... 65  xi Figure 3-2: Experimental apparatus: (a) raw water inlet, (b) 100 L vessel, (c) pump inlet tube, (d) peristaltic pump, (e) EC reactor, (f) DC power supply, (g) reactor outlet and bag filter ........................................................................................................ 67 Figure 3-3: Metal loading effects on the reduction of DOC, (a) 4-cell configuration, (b) 2 mm inter-electrode gap ................................................................................................ 72 Figure 3-4: Metal loading effects on the reduction of UV-abs-254, (a) 4-cell configuration, (b) 2 mm inter-electrode gap ................................................................... 73 Figure 3-5: Cell configuration and inter-electrode gap effects on the reduction of (a) DOC and (b) UV-abs-254 ............................................................................................... 76 Figure 3-6: HPSEC analysis of NOM removal during 4-cell EC (ML=38.2 mg/L); magnified region, whereby shaded areas represent error ................................................. 78 Figure 3-7: HPSEC NOM MW removal distribution (N=4, δ=1 mm) ........................... 80 Figure 3-8: Energy requirements (per unit of water treated) for N=4, 2 and δ=1, 2 mm pilot experiments ............................................................................................................ 82 Figure 4-1: Schematic drawing of the seven electrode configurations tested .................. 91 Figure 4-2: Vertical & horizontal electrode regions for current distribution determination .................................................................................................................. 91 Figure 4-3: Low flow rate (1.35 LPM) horizontal segment polarization curves for 1 mm gap .................................................................................................................................. 93 Figure 4-4: Low flow rate (1.35 LPM) horizontal segment polarization curves for (a) 2 mm and (b) 10 mm gap .................................................................................................. 94 Figure 4-5: Low flow (1.35 LPM) vertical segment polarization curves  for 1  mm  gap 95 Figure 4-6: Low flow (1.35 LPM) horizontal segment polarization curves for (a) 2 mm and (b) 10 mm gap ......................................................................................................... 97 Figure 4-7: CFD generated water velocity profiles for low flow (1.35 LPM) experiments (top) and CFD models with electrode segments overlaid ............................................... 99 Figure 4-8: Low flow (1.35 LPM) current distributions for combined segments (horizontal/vertical average) at 8 V ............................................................................. 100 Figure 4-9: High flow (10 LPM) horizontal segment polarization curves for (a) 1 mm and (b) 2 mm gap ......................................................................................................... 106 Figure 4-10: High flow (10 LPM) horizontal segment polarization curves for 10 mm gap ................................................................................................................................ 107  xii Figure 4-11: High flow (10 LPM) vertical segment polarization curves for (a) 1 mm and (b) 2 mm gap ......................................................................................................... 108 Figure 4-12: High flow (10 LPM) vertical segment polarization curves for 10  mm gap109 Figure 4-13: CFD generated water velocity profiles for high flow (10 LPM) experiments (top) and CFD models with electrode segments overlaid ............................................. 110 Figure 4-14: High flow (10 LPM) current distributions for combined segments (horizontal/vertical average) ........................................................................................ 111 Figure 4-15: CFD generated water velocity profiles for 2 mm inter-electrode gap conditions at: (a) low flow (1.35 LPM) and, (b) high flow (10 LPM) experiments ...... 114      xiii      List of Tables  Table 1-1: Expected EC half-cell reactions and potentials for Al and Fe ....................... 10 Table 1-2: Complete list of iron hydr(oxides) ................................................................. 12 Table 2-1: Solute concentrations for synthetic water representative of Van Anda surface water ............................................................................................................................... 49 Table 2-2: Current densities tested at low and medium flow rate .................................. 53 Table 3-1: Priest Lake raw surface water quality variables ............................................ 66 Table 3-2: Overview of experiments attempted, and those that succeeded and those that exceeded the power supply limits ........................................................................... 70 Table 3-3: Voltage ranges for all applied MLs at 1, 2 and 10 mm inter-electrode gap ... 70 Table 3-4: Current density values for each metal loading and cell configuration at pilot-scale ................................................................................................................................ 75 Table 3-5: Cell and gap effects on the reduction of DOC and UV-abs-254 .................... 77 Table 3-6: Metal loading effect on SUVA (N=4, δ=1 mm) ............................................ 77 Table 3-7: Energy requirements per water treated (corresponding to Figure 3-8) .......... 80 Table 4-1: Voltage ranges investigated for current distribution experiments ................. 82 Table 4-2: Current density ranges at low flow (1.35 LPM) and 8 V constant cell potential .......................................................................................................................... 95 Table 4-3: Sherwood numbers (Sh) for 1, 2 and 10 mm inter-electrode gap conditions at low flow (1.35 LPM), using a parallel-plate, fully developed horizontal laminar flow correlation ..................................................................................................................... 104 Table 4-4: Sherwood numbers (Sh) for 1, 2 and 10 mm inter-electrode gap conditions at high flow (10 LPM), using a parallel-plate, turbulent flow correlation ........................ 112  xiv      List of Abbreviations  •! AA-Spec – Atomic Absorption Spectroscopy  •! CC – Chemical Coagulation •! CDWQG – Canadian Drinking Water Quality Guideline  •! CFD – Computational Fluid Dynamics •! CLR – Charge Loading Rate •! COD – Chemical Oxygen Demand  •! DPB – Disinfection Byproduct •! DO – Dissolved Oxygen •! DOC – Dissolved Organic Carbon •! EC – Electrocoagulation  •! GR – Green Rust •! HA – Humic Acid •! HPSEC – High Performance Size Exclusion Chromatography  •! LPM – Liters per minute •! ML – Metal Loading •! MW – Molecular Weight •! MWTP – Mobile Water Treatment Plant •! NOM – Natural Organic Matter •! TOC – Total Organic Carbon •! RO – Reverse Osmosis •! WHO – World Health Organization  •! UV – Ultraviolet  •! UV-Abs-254 – Ultraviolet Absorption Spectroscopy at 254 nm •! UVT – Ultraviolet Transmittance  •! VAID – Van Anda Improvement District     xv      List of Symbols  Symbol Definition Unit Al Aluminum - cm Centimeter - e- Electron - F Faraday’s Constant C/mol e- Fe Iron - OH- Hydroxide Anion - I Current A or mA i Current Density mA/cm2 m Meter - Mez+ Metal Cation - nm Nanometer - H2 Hydrogen - Q Flow Rate L/min R Resistance Ohm (Ω) V Voltage or Potential Volt (V) ! Current Efficiency - μ Micro - § Section -     xvi Acknowledgements I would first like to thank my supervisors, Dr. David Wilkinson and Dr. Madjid Mohseni, for being exemplary leaders, mentors and supervisors throughout my Master’s degree. Not only were you pillars of support for my research and academics, but understanding and encouraging of my volunteer pursuits and athletic endeavors away from school. I would also like to thank RES’EAU WaterNET for funding my research. The meaningful research dedicated to those who need it most in this country, small and remote communities, gave all of my long hours in the lab and late nights writing meaning and purpose.  I am grateful for those who made coming to school everyday for the last few years enjoyable. Thank you to my lab-mates and friends; Pranav and Adrian, for the constant proofreading, practice presentations, feedback and support. A great deal of gratitude is extended to Saad. You’ve played a pivotal role in my in my life, filling the big shoes of Tyler, and being a true mentor – thank you.  Of course, I owe all of my achievements (academic and non-academic) to my parents. I don’t think I say it enough, but please know that I am forever grateful for all you have given me and the opportunities you have provided me. Carl - you are the best brother, friend and supporter I could ever ask for. You have always been there for me and I will always look up to you. Thank you.  Last, but certainly not least, I would like to thank Alisha. You have truly endured a lifetime of grumpiness, complaining, stress and frustration throughout this degree. You have done it with grace and kindness. Thank you.   xvii           This work is dedicated to my friend and mentor, Tyler Graham Prindle Lewis.  Without having shared his passion with me,  I would have never ventured down this road.   Thank you.  1    Chapter 1  Introduction  British Columbia is a vast province with a seemingly endless array of geographies including semi-arid desserts, coastal islands, mountain ranges and deciduous rainforests. It is also home to one of Canada’s largest metropolises, Vancouver, but contains some of Canada’s smallest communities. It is the inherent geographical mosaic which contributes to the remoteness of some 24,000 people across the province, comprised of over 85 communities [1];  it is most often these small and remote communities that are affected by the boil water advisories.  Although most of the densely populated regions of British Columbia have access to clean drinking water, it also leads the country in boil water advisories. It has nearly double the advisories of Saskatchewan, the province with the second highest advisories at 296 [2]. Latest estimates suggest that British Columbia advisory counts are as high as 544, whereby 35 of these advisories affect indigenous communities [2].  The issues that propagate this inordinate amount of boil water advisories can be distilled into many different aspects, however one such aspect involves the appropriateness and applicability of traditional water treatment technologies to unconventional applications (i.e., small-scale and inaccessible communities) [3]. Aside from the economic implications of implementing traditional multi-unit water treatment  2 processes for communities sometimes comprised of populations less than 100 people, the inaccessibility of the remote communities present difficulties for supplying needed chemicals involved in the treatment process. One such water treatment technology requiring a constant supply of chemicals is coagulation. It is for this reason that alternative processes are needed in order to minimize or eliminate the chemical supply chain necessary for adequate water treatment practices.  The following research investigates a potential technology capable of eliminating the chemical supply chain associated with the traditional chemical coagulation (CC) process, whereby the necessary chemicals are produced in-situ. The following thesis summarizes the research exploring this alternative technology, known as electrocoagulation (EC), in fulfillment of this author’s Masters of Applied Science degree.  1.1   Drinking Water Treatment for Surface Water Supplies Surface waters contain a plethora of organic and inorganic contaminants needing to be removed prior to human consumption. These contaminants can include clays, silts and organic materials, in a dissolved or undissolved form, amongst other more acutely harmful constituents such as bacteria and viruses. For the assurance of adequate water treatment and safe water, the Guidelines for Canadian Drinking Water Quality are suggested to be met, as set forth by the Government of Canada. The province of British Columbia has also set a standard for drinking water treatment, known as the “4-3-2-1-0 Drinking Water Objective”. This objective is merely a provincial standard and is described as follows: o! 4-log inactivation of viruses o! 3-log removal or inactivation of Giardia Lamblia and Cryptosporidium  3 o! 2 treatment processes/barriers for surface water systems (minimum) o! 1 NTU of turbidity or less o! 0 fecal and total coliforms and E. coli   Although the National and Provincial governments have established these drinking water guidelines and standards, it is the responsibility of municipalities and/or regional districts to achieve these standards [4]. A myriad of well understood and established treatment technologies are commercially available that allow water providers to meet the aforementioned guidelines. However, socioeconomic issues can impede the application of these sophisticated technologies and processes. The following sections briefly explore some typically utilized water treatment processes in North America, and the challenges that arise when implementing these technologies in small and remote systems.  1.1.1. Conventional Drinking Water Treatment Process Although the processes employed for drinking water treatment are highly dependent on the water source (surface or ground) and its matrix (ions, organics, bacteria, metals, etc.), there are several highly utilized unit operations: coagulation and flocculation, gravity separation, filtration and disinfection [5]. This section will briefly outline these commonly used technologies for surface water supplies in modern treatment processes.  Typical particulates and contaminants that can be found in surface water supplies may include, but are not limited to, clays, silts, natural organic matter (NOM), bacteria and viruses. In current water treatment practices, the most common process used to remove such colloids and dissolved organic contaminants is by sedimentation and/or filtration after a conditioning process known as coagulation and flocculation [5]. Coagulation is the process by which coagulant chemicals, usually iron or aluminum  4 based salts, are added to water and compress the diffuse layer of the charged dissolved and undissolved contaminants present in the water. The particle-particle electrostatic repulsion is minimized due to the compression of the diffuse layer of the contaminants, whereby Van der Waals forces begin to predominate and promote particle-particle attraction [5][6]. The flocculation process involves the continued aggregation of contaminant particles after the addition of coagulant chemicals, where ‘flocs’ form and grow through increasing particle-particle interactions (usually by gentle mechanical or static hydrodynamic mixing). The process of coagulation and flocculation is often referred to as ‘conditioning steps’, as they are usually precursor unit operations to more involved contaminant removal processes.   Figure 1-1: Common drinking water treatment unit operations from surface supplies A typical process found after coagulation and flocculation for the removal of the newly formed flocs is the technique of gravity separation. This method of removing suspended materials from water is the oldest and is still one of the most widely used  5 techniques in current treatment processes [5]. Traditionally gravity separation solely utilizes the differences of water and contaminant densities to settle suspended solids to the bottom of a basin, which are then mechanically removed. Although organic materials can be harder to settle and subsequently remove due to their inherently low densities, typically ranging from 1010 to 1100 kg/m3, requiring much longer settling times [5]. More recently, techniques have been developed to overcome low-density contaminant removal by sparging small air bubbles at the bottom of separation basins, promoting transport and floating of contaminant particles to the surface of the water, which can once again be mechanically removed. This process is known as dissolved air flotation [5].  Upon passing through a gravity separation unit, water often undergoes some sort of filtration. In processes that exclude the addition of gravity separation after coagulation and prior to filtration, the process is known as ‘direct filtration’ (a technique employed in the EC experiments outlined in the following chapters). Although there are different mediums of filtration, including granular media filtration, membrane filtration or ceramic filtration, the process is defined as the removal of suspended solid particles via the passage through a porous medium [5].  Usually the final step in an established North American water treatment facility is one or two forms of disinfection. In some cases for many communities without a drinking water treatment process, it is the only form of treatment employed. Disinfection is used to inactivate microbiological contaminants, like viruses and bacteria, prior to entering the distribution system to the end consumer. Two commonly used forms of disinfection are ultraviolet (UV) radiation and chlorine disinfection. Very commonly, UV is used as a primary disinfectant, meaning its effects occur in-situ within the UV reactor, and a residual concentration of chlorine is added to water prior to entering the distribution system for continued disinfection after leaving the treatment  6 plant. The latter is known as secondary disinfection [5]. Another form of disinfection, more often used in European systems, is ozone. More recently, there has been concern of by-products being formed during these commonly used UV/chlorine disinfection processes [7], some of which  are speculated to be chronically harmful to human health [8], which will be expanded upon in §1.2.5. Unwanted disinfection by-products have also been found to occur during ozonation of water sources that contain bromide, with the formation of bromate [9].  1.1.2. Small and Remote Community Water Challenges Although a myriad of technologies is available to treat even the most challenging water, many complexities for implementing these processes arise with small systems. Canada has adopted a decentralized approach at water governance, which creates many challenges for small and remote communities [4]. As more than 80% of Canada’s drinking water systems are considered to be small (serving a population of ≤5000) [10], much attention is being paid to address these problems. The problems that small communities face include the availability of skilled water operators for monitoring, maintenance and daily operations [11], as well as managing sophisticated technology [12], availability of funds to build and/or upgrade current treatment systems [13], and accessibility to replenish needed materials and chemicals (known as the chemical supply chain), requiring stock piling of materials and resources [14],[3].    One potential technology that has the means of addressing all of the aforementioned challenges facing small water systems is electrocoagulation.  EC is an alternative technology to traditional chemical coagulation, and may be suitable to replace it in certain circumstances, such as for small-scale operations. Its appeal as a potential small system process is due to the elimination of the chemical supply chain required for traditional CC, its seemingly easy operation and maintenance, as well as  7 purported low operating costs [15]. In the following sections, the principles of EC will be outlined and a comprehensive literature review is provided.  1.2   Electrocoagulation Background & Literature Review Electrocoagulation is a technology yet to be widely commercialized and adopted in any water treatment application (drinking or waste water, etc.). Although with the continued efforts by researchers dedicated to investigating EC, the technology is gaining momentum and could be potentially utilized by several companies in a variety of niche applications in Canada, United States and abroad.   A local company, Boydel Wastewater Technologies located in Ladysmith, BC, is exploring electrocoagulation for the treatment of raw sewage flows. A company founded in the United States, OilTrap Environment Products, is employing the use of EC for the removal of emulsified oil and grease, total petroleum hydrocarbons, suspended solids and heavy metals in wash-water and wastewater. A United Kingdom based company, Green Park Consultancy Limited, is using EC for the treatment and reuse of wastewater, rainwater and grey water. Although this is merely a short list of companies currently using EC for water treatment, no applications of EC in the drinking water treatment field have been adopted, with the exception of the work being done by Luminous Water Technologies in partnership with the Gadgil Lab from the University of California, Berkeley. This partnership is developing EC technology to treat arsenic-containing groundwater for a West Bengal (India) high school, in a large-scale batch process (10,000 L/day).  The following sections provide a brief summary of some research that has been conducted in the areas of electrocoagulation for wastewater and drinking water  8 treatment. In addition to the fundamental principles of the process, a summary of previously conducted electrochemical research is also provided.   1.2.1. Electrocoagulation Principles EC is an alternative treatment technology to conventional CC, as briefly introduced in §1.1.1. The basis of EC involves the in-situ production of coagulant species, in the form of metal hydroxides, through the electrochemical process of slowly dissolving a metal electrode into water.  Figure 1-2: Electrocoagulation process: (a) half-cell reactions, (b) coagulant and floc formation In accordance with Figure 1-2, one or more electrochemical cells are comprised of sacrificial anodes (typically aluminum and/or iron) and inert cathodes (stainless steel) placed in solution – the water to be treated. By use of an external DC power supply, current is passed through the electrochemical cell initiating the slow dissolution of metal cations (Mez+) into the solution (R.1) at the anode-solution interface. On the cathode side of cell, the electrolysis process reduces water molecules to hydroxide anions (OH-)  9 and hydrogen gas (H2), as represented by reaction R.2 below. These two electrochemical half-cell reactions occur simultaneously. As the process continues, metal cations and hydroxide anions interact in solution and combine to synthesize various metal oxides and metal hydroxides (R.3), collectively referred to as metal hydr(oxides). It is these metal hydr(oxides) that that function as the coagulants in an EC process. In a traditional CC process [see §1.1.1], aluminum or iron derived coagulants such as aluminum sulfate (alum) or ferric sulfate are added to the water. The selection of the appropriate coagulant will be defined by the characteristics of the water and target contaminant, such as concentration and type of contaminant, water temperature, pH and quality [5]. When these iron and aluminum salts are added to water, they dissociate to form bi- and trivalent ions, subsequently undergoing a number of hydrolytic reactions to form aquometal complexes and metal hydr(oxides). As with EC, the final hydrated metal-water complexes formed during conventional CC are the species that interact with contaminant particles to form flocs [5].   Anode: "#(%) ⇌ "#(())*+ + *#- (R.1) Cathode: ./012(3) + *#- ⇌ 4501(6) + *20(())-  (R.2) In Solution: "#(())*+ + *20(())- ⇌ "#(20)*(%) (R.3)  Depending on the metal anode material, Me, used in the EC process, different half-cell potentials for the respective reactions taking place at the metal-solution interface, as well as in solution, will exist. Table 1-1 below summarizes some typical reactions that are expected to take place during EC at the anode and cathode surface, as well as their respective half-cell potentials. Aluminum (Al) and iron (Fe) are outlined, as these are the most typical anode materials used in EC research.   10 Table 1-1: Expected EC half-cell reactions and potentials for Al and Fe [16] ANODE Reaction Potential, V Al3+ + 3e- ⇌ Al -1.662 Fe2+ + 2e- ⇌ Fe  -0.447 Fe3+ + 3e- ⇌ Fe  -0.037 CATHODE Reaction Potential, V 2H2O + 2e- ⇌ H2 + 2OH– -0.8277 As more electrical current is provided to the system, the rate of dissolution of metal cations and reduction of water also increases. Intuitively, this results in the increased formation of metal hydr(oxides). This current controlled rate of metal hydr(oxide) formation can be compared to the dosage of chemical coagulants in a traditional CC process. To more accurately describe this phenomenon, specifically for EC, the term metal loading (ML) is given. The term ML and dosage will henceforth be applied synonymously to describe the concentration of coagulant species being added to water. ML can be determined using Faraday’s Law:   "7 = ! ⋅ : ⋅ ";< ⋅ * ⋅ =  (E.1)  In E.1, the numerator terms !, I and MW respectively represent the current efficiency, operating current and molecular weight of the anode metal. The denominator terms Q, * and F represent the operating flow rate, the number of transferred electrons and Faraday’s constant (96,485 C/mol⋅e-), respectively. The resulting ML is described in units of mass per volume (e.g., mg/L).  The majority of published EC research has been focused around two metal types: aluminum and iron. Although both metal types have been shown to be effective for the  11 removal of a number of contaminants (to be expanded upon in the following sections), some research has suggested that Fe provides the lowest residual metal concentration post-EC and filtration [17]. That is to say, the Fe EC process yields the lowest concentration of dissolved residual metals after coagulation, flocculation and filtration when compared to Al and Zinc (Zn) EC processes being operated at the same ML. Fe has also shown to be superior to Al and Zn by yielding greater removal of dissolved organic contaminants (NOM), while showing no passivation layer accumulation or linear voltage ramp due to increased resistance associated with passivation layer accumulation [18]. Moreover, when compared to Al and other metal types like zinc, Fe is the least costly and most available material. It is for this reason that iron EC is the focus of this research.  In total, there are 16 different iron hydr(oxide) species [19], outlined in Table 1-2. There are several factors that can influence the selectivity of an EC process to predominantly produce one species in greater quantities than others. These factors include anode potential, pH, temperature, dissolved oxygen (DO), [Fe(II)]:[Fe(III)] and co-occurring solute concentration and ratios [20]. Although the speciation mechanism and identification of different iron hydr(oxide) species is beyond the scope of this research project, it should be noted that each species has varying affinity to function as a coagulant chemical [20].      12 Table 1-2: Complete list of iron hydr(oxides) [19] Oxide-hydroxides and hydroxides Oxides Geothite, α-FeOOH Hematite, α-Fe2O3 Lepidocrocite, ϒ-FeOOH Magnetite, Fe3O4 (FeIIFe2IIIO4) Akaganéite, β-FeOOH Maghemite, ϒ-Fe2O3 Schwertmannite, Fe16O16(OH)y(SO4)z⋅nH2O β-Fe2O3 δ-FeOOH ε-Fe2O3 Feroxyhyte, δ’-FeOOH Wüstite, FeO High pressure FeOOH  Ferrihydrite, Fe5HO8⋅4H2O  Bernalite, Fe(OH)3  Fe(OH)2  Green Rust, FexIIIFeyII(OH)3x+2y-z(A-)z; A-= Cl-;½ SO42-   Although EC is a seemingly simple technology, when considering all electrochemical variables, a higher level of complexity is associated with the process. In addition to current, which dictates the ML, the cell resistance (R) will ultimately dictate the electrical potential (V) of the cell. Ohm’s Law can mathematically describe this relationship:   : = >? (E.2)  where R represents the resistivity of the water, I is the applied current, and V is the potential. The resistance of the cell can be affected by the conductivity of the water, the current density (current normalized by the electrode surface area by which it is distributed) and the distance between the electrodes, also known as the inter-electrode gap. Ultimately, all of the aforementioned variables will affect one another and play a role in the contaminant removal efficiency and process energy requirements.  13 Of the aforementioned variables affecting the iron species synthesis selectivity during the EC process (V, pH, temperature, DO, [Fe(II)]:[Fe(III)]), potential has a particularly significant affect. Although not considered in this author’s experiments, it should be noted that the operating potential will dictate the thermodynamic stability for iron hydr(oxide) species. These thermodynamic stabilities can be represented using Pourbaix diagrams [see Figure 1-3], which simply plot the possible stable phases of iron species (or other metal molecules) in an aqueous electrochemical system, with respect to potential and pH.   Figure 1-3: Iron Pourbaix diagram (modified and adapted by [21] and [22]) As opposed to wastewater and brine water treatment processes, which are either highly ionic or can be made to be, drinking water treatment processes cannot increase ion concentrations as they would need to be removed downstream. This gives the EC process an advantage for wastewater practices, as energy requirements can be minimized when compared to drinking water applications.   14 1.2.2. Electrocoagulation for Wastewater Treatment EC research for the removal of dyestuff, substances yielding a dye or used as a dye, investigated the effects of current density, inter-electrode gap and inlet flow rate, amongst other parameters, on decolorization of contaminated water. From this research, it was found that dye removal efficiency increased from 95.1 to 99.5% with flow rate decreasing from 0.15 L/min to 0.05 L/min. When flow rate was increased to 0.20 L/min, however, removal efficiency plummeted to 58.5%, presumably due to the influence of reduced retention time in the reactor. An increase of over 30% in the dye removal ratio was also observed when the inter-electrode gap was decreased from 30 to 5 mm. Finally, a correlation between increased dye removal during current density increase (1-4.5 mA/cm2) was observed [23].   Wastewater treatment targeted at the removal of humic substances was investigated, varying the initial pH of the water and the initial humic concentration. Using aluminum anodes, water was treated with initial humic acid concentrations between 200 mg/L and 500 mg/L. It was found, that removal efficiencies decreased with increasing humic concentration, due to a gel formation on the electrode surface. Koparal et al found that reduced pH maintained a high removal efficiency and minimized the effects of gel formation, with an optimal pH of 5.0 [24]. Additional research investigating EC for the removal of organics in the form of concentrated NOM focused on the effect of the supporting electrolyte concentration, as well as initial pH. This research observed two effects propagated by increasing the electrolyte concentration of the wastewater: a compression of the double-layer of NOM and an increase in conductivity. It was observed that regardless of the initial NOM concentrations (100 and 200 mg/L), the supporting electrolyte (Na2SO4) concentration had no distinguishable effect on the removal efficiency of NOM. In agreement with Koparal et al, removal rates for the  15 batch EC experiments were found to occur at the lower pH test (5), achieving 92.7% removal of an initial NOM concentration of 200 mg/L [25].  A study encompassing the removal of both organic and inorganic contaminants has also been undertaken. To do so, researchers investigated the reduction of chemical oxygen demand (COD) in wastewater by way of iron EC. COD is the measureable amount of oxygen that is used by organic matter, as well as in the chemical oxidation of inorganics (eutrophication). Researchers observed that depending on the organic compounds present in the water, three scenarios could be observed: (1) COD increased, (2) COD remained roughly unchanged, and (3) COD decreased. In general, it was determined that in the presence of acids, COD increased due to reactions with Fe2+ to form soluble products that could remain in solution. COD was found to be unchanged when the wastewater contained sugars and alcohols, such as glucose, lactose, sucrose, isopropyl alcohol and phenol. It is hypothesized that the COD remained relatively unchanged because these soluble and miscible compounds do not react with Fe2+ and Fe3+. COD was found to be partially or highly removed, when wastewaters contained contaminants in the form of suspended solids and liquids such as fecal coliforms, turbidity, fats, oil and grease because they react with Fe(II), Fe(III) or both to from larger agglomerates that can then be more easily removed [21].  Electrocoagulation has more recently been explored for use in the treatment of produced water in a hydraulic fracturing process. Because flowback and produced water from shale oil and gas fracturing can be characterized by high turbidity and hardness, an EC-softening process was evaluated. It was determined that when a softening unit was placed prior to EC for older well waters, EC was found to be most effective at removing turbidity [26].       16 1.2.3. Electrocoagulation for Drinking Water Treatment A higher level of complexity is associated with electrocoagulation when implemented into a drinking water treatment process. Due to the inherently low conductivities found in most drinking water supplies, higher resistivity between electrodes results in higher operating potentials and power consumption. As opposed to wastewater and brine water treatment processes, which are inherently highly ionic or can be made to be by way of salt addition, drinking water treatment processes should not increase ion concentrations as these ions would need to be removed further downstream; a process that tends to be very expensive.  Although EC for drinking water treatment does have its fundamental complications, it carries many advantages as a potential process option. One such advantage is that the process produces coagulant species in-situ. For small and remote communities that are difficult to access, or are very far from major shipping routes, EC would eliminate the needed chemical supply chain necessary for conventional chemical coagulation. EC for drinking water treatment has been an area of interest for some researchers, many of which investigated Al and Fe electrocoagulation processes; the evidence of which can predominantly be found in publications over the last 15 years.  A large body of work has been directed towards Al electrocoagulation research. An empirical scale-up investigation of Al electrocoagulation for the removal of fluorides from Saharan ground water investigated inter-electrode gap, current density and temperature. It was concluded that the maximum defluoridation occurred at a 20 mm inter-electrode gap distance, 7.5 mA/cm2, and a temperature of 20°C [27]. The same researcher then extended the same investigation to a larger pilot-scale system, utilizing aluminum bipolar electrodes with a 1.6 m2 surface area. From this investigation, the researchers concluded that two main operating parameters affected the process’ fluoride removal efficiency: flow rate and current. It was found that as both the flow rate and  17 current reduced from 21 L/min to 15 L/min and 60 A to 25 A, respectively, the absolute removal of fluoride approached World Health Organization (WHO) fluoride concentration requirements. Although preferable results were obtained at lower current, it should be noted that the decrease in flow rate kept ML similar at either condition. The researchers surmised that both of these variables attributed to large variations in dead volumes and hydraulic short-circuiting of the reactor, which ultimately governed the processes effectiveness [28].  Defluoridation was once again investigated by Zhu et al. using Al EC, however the main focus was to understand the importance of pH, charge loading, current density and initial fluoride concentration effects on the process’ performance. It was determined by the researchers that efficient fluoride removal primarily occurred at higher current densities, where removal was associated with absorption on to a passivation layer of the electrode surface, where removal by floc formation was a secondary means of defluoridation [29].  Research comparing conventional chemical coagulation using alum (aluminum sulphate) and aluminum EC for the removal of the turbidity associated with clay pollutants has also been investigated. It was found that alum coagulation provided more effective turbidity reduction under acidic conditions and low coagulant dosing. It was also found that at higher operating currents, pollutant removal occurred more quickly, however more pollutant was removed per unit of Al introduced at lower operating currents [30].  A substantial body of work has also been contributed in the area of Fe electrocoagulation for drinking water treatment. Research undertaken by Gadgil’s team at Berkley focused on the removal of arsenic from synthetic water, mimicking that of arsenic latent Bangladesh groundwater containing phosphate, silicate and bicarbonate solutes. The experiments yielded reductions of arsenic from 550-580 μg/L initial  18 concentrations to below 10 μg/L, the WHO recommended maximum concentration for arsenic. It was found that arsenic removal capacity was highly dependent on current densities, where removal effectiveness decreased with increasing current densities (0.02 mA/cm2 to 100 mA/cm2) [31].  Aluminum based EC has also been investigated for its effectiveness on the removal of NOM. Vik et al. explored the removal of humic substances from raw surface waters, taken from three different locations in Oslo, Norway [32]. Research primarily focused on the effect of current density and aluminum metal loading on the removal of aquatic humus, and its comparative performance to traditional alum CC. It was concluded that no significant difference in removal performance was observed between EC and CC. There was, however, higher residual aluminum concentrations after the EC process, compared to the traditional CC, which the authors attributed to the high pH of the water; a phenomenon that is typical of the EC process [32]. Other researchers found that Al-EC outperformed traditional CC using aluminum sulphate coagulant; achieving 20% greater reductions in dissolved organic carbon (DOC) while using synthetic water samples, while operating in a current density range of 10-20 mA/cm2. It was seen, however, that when natural surface waters were tested, similar contaminant removal performances were achieved with both EC and CC [33].  Thorough research has also been conducted in the area of NOM removal by means of Fe electrocoagulation. Studies investigating reactor design parameters (current density and charge loading rate) for NOM removal in a bench-scale batch reactor found a decrease in current efficiency with an increase in current density, negatively affecting NOM removal, whereby an optimum operating current density of 10 mA/cm2 was suggested. Additionally, the greatest NOM reductions where found to occur at lower charge loading rates (CLR), where CLR is described as the rate of coagulant generation and is represented by equation E.3:  19   @7? = :< (E.3)  It was also observed that a shorter operation time was required for higher CLR conditions, even though longer flocculation or greater ML doses were needed in order to achieve comparable NOM reductions [34]. Research involving the effect of the NOM sources on removal as well as initial NOM concentration has also been conducted. Three NOM sources were investigated: Suwannee River (USA), Nordic Reservoir (Norway) and Lost Lagoon (Canada). The two former sources were NOM isolates produced by reverse osmosis and added to deionized water, while the latter was locally collected raw water. It was found that EC predominantly favored the removal of NOM with higher concentrations of large hydrophobic and high molecular weight fractions. Source waters containing higher NOM fractions of larger hydrophobic structures yielded greater decreases in DOC. It was also observed that the relative reduction in DOC with two different initial NOM concentrations (13.79 and 21.59 mg/L) was not significantly different, performing equally for either treatment at the same EC operating conditions [17].   Other relevant research investigated the iron hydr(oxide) speciation phenomena during an EC process applied to natural waters, where species were identified in-situ using Raman spectrophotometric analysis. In particular, the impact of current density, CLR and DO on speciation was investigated. The three most predominant iron species were identified to be green rust (GR) (FexIIIFeyII(OH)3x+2y-z(A-)z; A-= Cl-;½ SO42-), lepidocrocite (ϒ-FeOOH) and magnetite (Fe3O4). GR speciation occurred in low current density and intermediate CLR conditions, while magnetite was found to predominate during processes at high current density and CLR. All other conditions yielded the formation of lepidocrocite. Further analysis compared the varying effectiveness of the  20 three species functionality as a coagulant chemical. It was suggested that GR was the preferred iron species due to its ability to most effectively reduce NOM concentrations [20]. Further research was dedicated to investigating the formation and persistence of magnetite and GR throughout an iron electrocoagulation process, by the same researcher.   1.2.4. Electrochemical Investigations of Electrocoagulation A variety of electrochemical investigations have also been published. Because EC is a deceivingly complicated process, with many electrochemical variables that can often be overlooked, many have sought to describe the process through models. One such study developed a general potential-current model for EC. Using a segmented electrode EC-setup, the model describing the effect of potential and current under conditions of fully developed laminar flow, was validated. While investigating the contribution of ionic concentrations, temperature, conductivity and cathodic hydrogen flux, current from each electrode segment was used to determine the total electrode current, which was then compared to the model predicted current. It was found that experiments operating between 5-80 mA/cm2 at a low flow rate (0.1-0.3 L/min) and an inter-electrode gap of 2 mm, corresponded well to the generated model. However, greater deviations from the model were seen when the inter-electrode gap increased to 10 mm and Na2SO4 was used as an electrolyte in the synthetic water matrix. It was hypothesized by the authors that this deviation could be due to parasitic H2O oxidation and a varying current efficiency from one electrode segment to another [35].  Chen et al. also developed theoretical models for EC, describing the effect of variables such as solution pH, flow rate, inter-electrode gap, conductivity and current density, on the electrolysis potential. It was determined that although pH and flow rate had minimal effects on voltage, inter-electrode gap, conductivity and current density  21 were the primary variables effecting the magnitude of the EC operating voltage. These phenomena described by the theoretical model were validated experimentally [36]. These results somewhat disagreed with pilot-scale EC experiments conducted by Mameri et al., who saw a great variance in EC efficiency with respect to flow rate. The flow rates investigated were much larger, and it was presumed by the investigators that flow rate greatly affected current densities on the electrode surface, which consequently will effect operating potentials [27].   Research involving the dosing rate, or ML, and subsequent power consumption for EC was conducted for both aluminum and iron electrodes. The effect of current density on ML in a bench EC reactor was compared to values, as predicted by Faraday’s law (E.1). It was found that under the conditions studied, iron ML measured quantities followed those predicted by Faraday’s law, while aluminum anode dosing rates were observed to be as much as 83% greater than Faradaic predicted rates. This increased ML was attributed to the chemical corrosion of both the anode and cathode. In the latter case, small ML contributions of the cathode were attributed to high local pH conditions produced adjacent to metal surface, due to hydroxide formation, promoting the dissolution of Al. Furthermore, the authors developed an equation to determine the faradaic power consumption of EC, as a function of current density, and ultimately the energy consumption as a function of coagulant dose (ML) [15].  Researchers investigated the formation of Fe2+ and Fe3+ during iron EC, for insight into the predominant cation dissolution species. By addition of an organic metal complexing agent, 1,10 phenanthroline, to avoid the measure of Fe3+, the abundance of Fe2+ was quantified using UV absorbance. Total iron concentration was measured using atomic absorption spectroscopy (AA-spec). It was found that Fe2+:Fe3+ measured between 82-91% for the pH and current density ranges investigated. This investigation gave insight into the main EC products at the metal-solution interface [37].    22 1.2.5. Natural Organic Matter and Disinfection By-Products A problem communities using natural surface water as a source for drinking water often face is the presence of NOM, which is the product of degrading plant and animal matter. Although NOM is not an acutely harmful contaminant to human health, it is considered to be a disinfection by-product (DBP) precursor [38].  DPBs such as tri-halomethanes and haloacetic acids are formed during chlorine disinfection, an extremely common unit operation for drinking water treatment facilities, whereby chlorine addition leads to partial oxidation of NOM and formation of chlorinated DBPs [39]. It is these DPBs that are regulated due to having a varying degree of negative consequences on human health [8][40]. Additional reasons for removing NOM from surface waters may include its ability to foul filter membranes and decrease the efficacy of UV disinfection (due to higher absorbance and lowered radiation penetration through the water). Finally, it can also provide unsightly aesthetic characteristics to water.  There is no single chemical composition for NOM; however, it is characterized by a mixture of aromatic structures, carboxylic acid and phenol groups, having an apparent molecular weight between 200-20,000 Da [41]. A proposed structure of NOM is seen in Figure 1-4. Humic substances, composed of humic and fulvic acid, comprise roughly 50-70% of NOM, while small hydrophobic and hydrophilic molecules make up the rest of NOM components [42]. Due to the larger experimental scale of this project, humic acid (HA) will be used as a surrogate species to NOM as it is more readily available at a much lower cost. This is a fair substitution since it is a major component of NOM and similar chemical structures.  23  Figure 1-4: Possible structures of (a) NOM [18] and, (b) HA [43] The amount of NOM present in a solution is characterized by the total organic carbon (TOC) or DOC (NOM structures that are able to pass through a 0.45 μm filter). Typical Canadian natural surface waters range from 2-10 mg/L DOC, however ‘events’ such as spring snowmelts can spike levels up to around 50 mg/L [18]. To complement DOC data, NOM is also quantified using UV-absorbance at 254 nm (UV-abs-254).  UV-abs-254 is a water quality parameter which detects organic matter, as it has a bias absorbance for aromatic structures, like those found in NOM and HA [38].   1.2.6. RES’EAU Community Circle: Van Anda Improvement District RES’EAU-WaterNET is a program, funded by public and private industry partners and organizations, as well as the Natural Sciences and Engineering Research Council (NSERC) of Canada. The program funds crucial research dedicated to engineering, science and social sciences for small water system applications. Additionally, RES’EAU-WaterNET takes a “Community Circle” approach in order to solve some of the water problems that many small and remote Canadian communities encounter, as described in §1.1.3.   24 One of the partnered Community Circles is the Van Anda Improvement District (VAID), located on Texada Island, just off the southern coast of British Columbia (see Figure 1-5). The VAID community is comprised of roughly 550 members, of whom use water from a nearby lake, known as Priest Lake, as their primary drinking water supply.  Figure 1-5: (a) Texada Island and VAID location, with respect to BC. (b) Priest Lake Priest Lake water is characterized by high concentrations of DOC, and is currently being treated solely with chlorine disinfection. As previously decribed (§1.1.5.), simply treating NOM using chlorine disinfection could potentially be heightening the risk to the end users’ exposure to harmful DBPs.  RES’EAU-WaterNET has established a partnership with the VAID, incorporating an on-site water treatment pilot-plant at Priest Lake in order to help the community identify and implement a sustainable water treatment process. The ultimate goal from this Community Circle partnership is to investigate multiple water treatment  25 unit operations and in doing so, propose and implement a multi-barrier treatment process that the community can both afford and sustain well into the distant future.  As a part of the pilot-plant technologies being investigated, EC was incorporated into the VAID Community Circle research.   1.3 Research Scope and Objectives In order to determine the efficacy of EC as a potential alternative to chemical coagulation for specialty markets such as small and remote communities, a thorough scale-up investigation is required. These scale-up efforts must include a systematic factorial design approach in order to fully understand the process’ ability to remove the target contaminant, NOM. In doing so, two main research objectives are to be reached: (1)!Pilot capacity scale-up: Scale-up the iron electrocoagulation process to 10 L/min, while understanding the effect of current density, inter-electrode gap and metal loading on NOM removal (2)!Current distribution mapping: Mapping of the EC reactor electrode surface to better understand the current density distribution due to mass transport Both of the aforementioned research objectives are summarized in the following sections and thoroughly explored in the following three chapters.   1.3.1. Electrocoagulation Scale-Up The primary research objective of this project involves scaling up an iron electrocoagulation process from 1.35 to 10 L/min, while gaining a thorough understanding of the NOM removal efficiency, while varying three process parameters: current density, metal loading, and inter-electrode gap. Using a factorial design based methodology, the effects that each operating condition as well as the inter-connected  26 effects, has on the process’ ability to remove NOM will be gained. Moreover, as each parameter is varied, insight into the process power requirements will be attained through the monitoring of electrode potential data for all experiments. Finally, operational conditions effects on the downstream process of flocculation will be investigated, as some conditions may yield more effective floc formation when compared to other operating parameter combinations. Experiments will be repeated in a gradual process, whereby all experiments will first be undertaken at a low flow rate of 1.35 L/min. All experiments associated with the following methodology are performed with the same procedures. Upon the completion of all treatments at the low flow rate, treatments will be repeated at 5 L/min. At these two flow rates, all experiments can be accommodated and performed in the UBC Chemical and Biological Engineering laboratories using synthetic surface water. Upon the completion of the 5 L/min flow experiments, an on-location investigation at 10 L/min will be performed using Priest Lake surface water, located in the Van Anda Improvement District. At all three flowrates, a factorial design methodology will be employed, investigating current density, metal loading and inter-electrode gap [see Figure 1-6].   Figure 1-6: Main experimental and performance variables for factorial design scale-up Current Density electric current per unit area of cross section Inter-Electrode Gap distance between parallel electrodes  Metal Loading coagulant dosing concentration determined by Faraday’s law UV-abs-254 UV-absorption spectroscopy at 254nm DOC dissolved organic carbon Experimental Variables Performance Variables 0.5-33 mA cm-2 1, 2 & 10 mm 25-64 mgFe L-1  27 Stock synthetic surface water of known and constant DOC and UV-absorbance flows through the electrocoagulation reactor, operating with a specific treatment dictated by the factors and respective levels. Samples are collected at the outlet of the electrocoagulation unit after steady state operation has been achieved, and are then placed in a jar-testing unit to allow flocculation to occur. Subsamples are then collected frequently throughout the flocculation process, filtered and analyzed with UV-abs-254 spectroscopy and DOC. All treatments will be performed in duplicates, and when necessary, triplicates. A complete set of data will have been collected from the lower flow rates to determine operating conditions, which yield the desired DOC and UV-absorbance reductions. From this data, ideal-operating conditions can be suggested for the scaled-up flow-through electrocoagulation operation at 10 L/min. This will maximize treatment efficiency and reduce associated operating costs for the larger flow rate system.  1.3.2. Current Distribution Mapping The secondary research objective involves an electrochemical investigation to better understand the current distribution over the electrode surface in the reactor. Understanding the distribution characteristics of the current will help to attain the real current density values during the EC process, as the Part 1 experiments assume uniform current distribution. A clearer insight of the fluid dynamics and it affect on the electrochemistry of the reactor will be better understood. Additionally, insight into the current distribution relation to inter-electrode gap and increasing flow rates will be attained. Electrode ‘dead spots’, or areas of limited dissolution activity, will be determined. From this, electrode and reactor design can be optimized or better understood for future design iterations.  28 In order to determine the current distribution on the electrode surfaces being used in the experimental work outlined in §1.4.1., an in-situ partial electrode method for current distribution determination will be utilized. Using single cell assemblies, potentiostatic electrocoagulation operation will be undertaken at different potentials to generate polarization curves at different inter-electrode gaps and flow rates. Seven segment configurations will be investigate; vertical and horizontal exposure of the electrode (¼, ½, ¾, and full electrode exposure) corresponding to Figure 1-7 below.   Figure 1-7: Horizontal and vertical masked regions of the electrodes, for current distribution determination All treatments will be performed while only horizontal region (1) of the electrode is exposed. The experiment will then be repeated with horizontal regions (1) and (2) exposed. These procedures will continue until the entire electrode is exposed (regions 1-4), and repeated for the vertically masked electrode. By subtracting each successive polarization curve from another, a segmented current distribution can be extracted for each rectangular segment of the electrode. All experiment will be performed in duplicates.   29 1.3.3. Research Limitations Although the project aims to determine the appropriateness of EC for future scale-up efforts and/or implementation into water treatment approaches, some limitations are associated with the proposed research. Due to time constraints of this project, temperature, co-occurring solute effects, floc quality and characteristics analysis and iron speciation effects are not considered in the iron EC removal efficiency of NOM. Additionally, pH effects on the effectiveness of post-EC flocculation are not explored. Although it is known that these effects may have some impact on the EC process, some prior reported research has explored these phenomena. Research involving the removal of NOM using iron EC in a batch reactor at a bench-scale found that NOM removal was not significantly affected by calcium, phosphate or chloride. However, some negative effects were observed when carbonate was present in the water, whereby DOC and UV-abs-254 reductions where roughly half of that when no carbonates were present [18]. Some suggestions for this phenomenon include an increased formation of a passivation layer on the anode, thereby limiting the synthesis of coagulant species due to decreased dissolution of metal into solution [44].  Temperature has also been investigated for the removal of fluoride from groundwater using aluminum EC. Saharan groundwater was used and varied in temperatures between 20-55°C for experiments, exceeding that of typical Canadian natural surface water sources. From this research, an increased EC removal efficiency correlated to a decrease in temperature. The optimal operation was found to be at 20°C, the lowest treatment level investigated [27]. Various species of iron hydr(oxides) have been shown to have a varying affinity to function as a coagulant species. In particular, the removal of NOM with three predominating EC coagulant species, GR, magnetite and lepidocrite, were investigated. It was determined that of the three species, GR most efficiently reduced both DOC and  30 UV-abs-254 at all ML investigated (5-30 mg/L) [20]. The speciation mechanism of GR and magnetite was also investigated for the subsequent removal of arsenic from groundwater. Although researchers successfully mapped the production and transformation mechanisms of Fe2+ and Fe3+ generated during the electrocoagulation process to GR and magnetite, no clear conclusion was made on which species’ had the greater affinity for removal arsenic [45]. Finally, the quality and characteristics of the flocs being formed after the EC process were not analyzed. Floc characteristics such as size and density can provide insight for the design requirements of subsequent downstream unit operations (sedimentation/flotation). For multi-unit processes incorporating EC, floc analysis would be an important aspect to consider, however the following research utilized direct filtration to solely understand the dissolved organic removal efficiency of EC.   Although temperature, co-occurring solutes and iron speciation are not explicitly explored during this Fe EC investigation, they can be considered as a possible factor in deviations from expected results. Both temperature and co-occurring solute variables are controlled and remain constant throughout all the experiments in this work in order to minimize performance effects associated with them. Experiments were controlled to keep certain conditions constant (pH, current density, conductivity), however variables which could not be controlled such as dissolved oxygen (DO) and voltage (because experiments were run galvanostatically) have been shown to have an effect on speciation during EC [20].     31    Chapter 2  Iron Electrocoagulation Scale-Up  2.1 Chapter Introduction This chapter outlines the scale-up experiments undertaken prior to the implementation of the iron-EC process in a drinking water pilot-plant. Experiments were performed in a stepwise process, whereby all experiments were first undertaken at a “low flow rate” of 1.35 LPM. Upon the completion of all treatments at the low flow rate, treatments were once again repeated at a “medium flow rate” of 5 LPM. At these two flow rates [§2.2], all experiments were accommodated and performed in the UBC Chemical and Biological Engineering laboratories using synthetic surface water composed of humic acid and distilled water.   2.2 Low and Medium Flow Rate Electrocoagulation This section outlines the low and medium flow rate experiments performed, evaluating the humic acid removal efficiency of EC. The section will first provide a summary of the materials and methods used when conducting the experiments, followed by a discussion on the various outcomes and results observed.    32 2.2.1. Materials and Methods The electrocoagulation reactor used for all experiments was a collaborative design by this author and a post-doctoral fellow. A schematic drawing produced with SolidWorks is shown in Figure 2-1. The design considered the need to accommodate the range of flow rates (1–10 LPM) utilized in the scale-up process. A second consideration was to maximize the uniform flow distribution over electrodes and throughout multiple cells (when applicable). In order to do so, a baffled inlet was implemented, whereby liquid entering the EC unit must first rise and fall over a baffle spanning the entire width of the reactor (as labelled A in Figure 2-1). A complete engineering drawing can be found in Appendix B.  Figure 2-1: Schematic drawing of designed EC reactor; A, B and C indicate the baffled inlet, the electrode area, and the outlet, respectively  Upon passing over the baffle, water then enters the main volume of the reactor where the electrodes are housed (as labeled B in Figure 2-1). This section accommodates removable electrode holders, which are outfitted with machined slits with varied spacing, corresponding to the inter-electrode gaps required when electrodes are installed A"B"C" 33 into the reactor. Depending on the number of cells being used during experimentation, ‘flow blockers’ can be inserted between the outside of the electrodes and the walls of the reactor, as seen in Figure 2-2 for a single-cell (a), and four-cell (b) setup. Brass ‘bus bars’ are used for configurations implementing two or more cells, in order to have a single electrical connection with the all electrodes [see Figure 2-2(b)]. Water travels upwards through the electrodes and spills over an additional baffle into section C, with respect to Figure 2-1, before exiting the EC reactor.   Figure 2-2: Top view of the EC reactor; (a) single-cell setup, (b) four-cell setup The reactor was fabricated by the workshop personnel in the Department of Chemical and Biological Engineering at the University of British Columbia. The reactor, electrode holder inserts and flow blockers were all constructed entirely of inert acrylic. Figure 2-3 shows the fabricated reactor during EC operation.  For all experiments during scale-up, the same cathode and anode materials were used. Cathode electrodes were austenitic, a face centered cubic crystal stainless steel alloy containing trace amounts of chromium and nickel, while the anode material was A1008 cold-rolled steel iron, containing trace amounts of carbon, manganese,  34 phosphorus and sulfur. Both anode and cathode electrodes were 16-gauge thickness (1.519 mm) and had a single side active surface area of 310.8 cm2.  Figure 2-3: Electrocoagulation reactor during EC operation Due to the large-scale operations being conducted, a surrogate compound to the traditionally utilized reverse osmosis isolated NOM, was sought in order to reduce experimental costs. Suwanee reverse osmosis isolated NOM purchased through the International Humic Substances Society lists at $30 USD per 100 mg, amounting to an estimated single experiment cost of $600 USD (~50 L experiment). By the nature of the scale-up work, hundreds of trials would be needed, making the use of purchased NOM economical unfeasible. The surrogate species implemented in the experiments was humic acid. Both structures are predominantly composed of aromatic carbon rings, sharing some similar carboxylic and phenol functional groups. Technical grade HA can be purchased through Sigma-Aldrich at a price of $203.50 CAD per 50 g, reducing experiment costs to $7.66 CAD for a single trial, once again estimating 50 L experiments. Inlet solutions are prepared to a concentration of 40 mg/L of HA by dilution of a neutral pH stock HA solution of 1000 mg/L in distilled water. A 40 mg/L HA solution was used to obtain a DOC and UV-abs-254 of 10.72 ± 1.64 mg/L and  35 1.1359 ± 0.0977 cm-1, respectively; a challenging representation of natural surface water compositions during non-events (i.e. spring melts, flash floods, etc). Other monitored parameters including pH and conductivity, with average values of 6.61 ± 0.22 and 568 ± 28 μS/cm respectively, were achieved.  The experimental setup consists of a 100 L inlet tank, the electrocoagulation unit, a 100 L outlet tank, and a jar tester unit. A process flow diagram of the experimental setup is illustrated in Figure 2-4. The inlet tank holds the synthetic surface water, whereby a Masterflex L/S Drive and L/S High Performance Head (for 1.35 LPM flow) and a Masterflex I/P Drive and I/P High Performance Head (for 5 LPM flow) peristaltic pump pumped the water into the EC reactor. Stock synthetic surface water then flows through the electrocoagulation reactor, operating at a specific treatment condition.  A BK Precision 1687B (1-36V 10A) and 1688B (1-18V 20A) Switching DC Power Supply was used for the low and medium flow rate experiments, respectively.  After passing through the chamber housing the electrodes, water exits the reactor and flows through an outlet tube into the outlet tank for later disposal. Upon reaching steady-state EC operations, 2 L samples were collected and placed in a Bird and Phipps jar-testing unit to allow flocculation to occur, with a mixing speed of 30 rpm.  Subsamples of roughly 40 mL were then collected from the 2 L flocculation beaker at 0, 5, 30 and 60 minutes and filtered using a 0.45 μm PVDF syringe filter. These direct filtered samples were then analyzed to quantify DOC and UV-abs-254, using a Shimadzu ASI-V Total Organic Carbon Analyzer and Agilent Technologies Cary 100 UV-Vis Spectrophotometer, respectively.  36  Figure 2-4: Experimental EC process flow diagram For all experiments, it was assumed that all NOM that entered the EC reactor also exited the reactor; for mass balance purposes, all NOM either remained dissolved in solution after EC or became undissolved and removed by filtration prior to DOC and UV-abs-254 analysis (no NOM accumulated in the reactor or inlet/outlet pipes). For medium flow experiments, additional analysis was conducted in order to quantify the residual metal concentration after filtration. Atomic absorption spectroscopy (AA-spec) was utilized for this task [Varian SpectrAA 220 Fast Sequential AAS]. All treatments were performed in duplicate or triplicate, when necessary.  2.2.2. Results and Discussion 2.2.2.1. Flocculation Effects A constant parameter monitored throughout all treatments and levels of experimentation was the effect of flocculation time on the removal of HA. All low and medium flow samples were filtered and analyzed for DOC and UV-abs-254 immediately after EC, as well as after 5, 30 and 60 min of constant flocculation at a agitation speed  37 of 30 rpm. Throughout all levels of the factorial design, no clear trends were observed with respect to flocculation time and the increased or decreased reduction of DOC or UV-abs-254. It was observed that any reductions in DOC and UV-abs-254 at either flow rate, or increases for the latter in some cases, occurred immediately after electrocoagulation and only small fluctuations in either parameter existed throughout the 60 min of flocculation.  It was observed for any specific treatment, only small fluctuations in DOC occur from 0 to 60 min of flocculation, and most of the significant reduction occurs immediately after electrocoagulation. Similarly, in either case of the UV-abs-254 increasing or decreasing, all changes that occurred from the initial water sample to post-EC values occurred immediate after treatment, without any observable trends correlating to flocculation times. Irrespective of current density, inter-electrode gap or metal loading doses, no conclusive evidence was found for flocculation effects ameliorating HA removal post-electrocoagulation. From this, it can be inferred that any dissolved HA contaminants present in the inlet water which are later removed during filtration become undissolved either during the EC process, or while exiting the reactor immediately after passing through the electrodes. Since this was conclusive for all experiments conducted during scale-up, all further discussions will henceforth be focused on results obtained immediately after the EC process for consistency.   2.2.2.2. Metal Loading Effects 2.2.2.2.1. Low Flow Rate The one factor yielding the most obvious trend in HA reductions is the effect of metal loading. At low flow experiments, metal loadings of 25.5, 38.3, 51.1 and 63.8 mg/L were tested. Throughout all the factors and levels of experiments, there was a clear relationship between ML and subsequent DOC and UV-abs-254 reductions. As the ML  38 increased from 25.5 to 63.4 mg/L (corresponding to 2.0 A and 5.0 A of current respectively, for all different cell configurations), clear reductions in DOC were observed. At 25.5 mg/L, the lowest ML tested, roughly 30-50% decreases were observed throughout all current densities (dictated by the number of cells) and inter-electrode gaps. When ML was increased to 38.2 mg/L, corresponding to 3.0 A operation, further average DOC reduction was increased to 70-80% for all factors and treatments investigated, with the exception of some 10 mm inter-electrode gap experiments. When ML was further increased to 51.1 and 63.4 mg/L, applying 4.0 and 5.0 A respectively, DOC reductions were observed to reduce below 1.500 mg/L in nearly all cases, corresponding to a ≥85% reductions from initial conditions. These two highest ML levels provided very close final results, with average reductions of 74.6 and 77.8%, respectively, where no significant differences were observed between them for any set of operating parameters tested, as seen in Figure 2-5.  Contrary to the majority of the results yielded, a phenomenon was observed with DOC reductions for the 10 mm inter-electrode gap experiments. Although typical results, as demonstrated in Figure 2-5, were seen with the two cell experiments, significantly less reduction in DOC was observed for the single- and four-cell configurations [see Figure 2-6]. There were no observable correlations with these poor results and the effect of current density or potential, which will be expanded upon in §2.2.2.4.  39  Figure 2-5: Low flow rate (1.35 LPM) DOC reductions: (a) 2-cell, and (b) 1 mm inter-electrode gap Although clear decreases in DOC were observed in all experiments after electrocoagulation, UV-abs-254 yielded different trends. For all experiments, the lowest two ML levels produced increases in UV-abs-254, suggesting the introduction of dissolved contaminants in the water during the EC process. A qualitative inspection of samples producing higher absorbance generally show a dark orange color compared to the inlet water, a visual characteristic sometimes associated with rust/Fe [19].  0.00.20.40.60.81.00 10 20 30 40 50 60 70DOC/DOC 0Metal+Loading+(mg/L)1+mm2+mm10+mmInitial0.00.20.40.60.81.00 10 20 30 40 50 60 70DOC/DOC 0Metal+Loading+(mg/L)1+Cell2+Cell4+CellInitial(a) (b)  40  Figure 2-6: Low flow rate (1.35 LPM) experiments operating with a 10 mm inter-electrode gap Although spectrophotometry is conducted at a 254 nm wavelength, targeting aromatic-structured organics like NOM and HA, the only explanation for the increase in absorbance is the presence of dissolved iron species performing poorly as a coagulant and passing through the 0.45 μm filter. Ultraviolet-visible absorption bands for several iron hydr(oxide) species are found in lower wavelength ranges near 254 nm, including goethite (250 nm), hematite (270 nm) and maghemite (250 nm) [19]. More notably, lepidocrocite and magnetite have absorption band positions at 239 and 300 nm [19], respectively; iron hydr(oxides) that have been previously identified as predominant species during iron EC for similar operating ranges to those used in this author’s experiments [20].  It is not possible to speculate on the concentration of Fe purely based on the DOC and UV-abs-254 results, therefore it is unknown whether the higher UV-abs-254 at an ML of 25.52 mg/L is associated with a greater concentrations of dissolved Fe passing through the filter after EC when compared to an ML of 38.30 mg/L. Since DOC results outlined above indicate lower HA concentrations at 38.2 mg/L ML, in general, it can be 0.00.20.40.60.81.00 10 20 30 40 50 60 70DOC/DOC 0Metal+Loading+(mg/L)1+Cell2+Cell4+CellInitial 41 assumed that the increased absorbance values are associated with Fe. These assumptions were confirmed during medium flow experiments, by quantifying the Fe concentrations using AA-spec.   Figure 2-7: Low flow rate (1.35 LPM) UV-abs-254 reductions: (a) 2-cell, and (b) 1 mm inter-electrode gap.  In general, when ML parameters were increased above 38.2 mg/L, UV-abs-254 below initial inlet water levels was achieved. When ML was administered at 51.1 mg/L, 0.00.40.81.21.62.00 10 20 30 40 50 60 70UV7Abs7254/UV7Abs7254 0Metal+Loading+(mg/L)1+mm2+mm10+mmInitial0.00.40.81.21.62.00 10 20 30 40 50 60 70UV7Abs7254/UV7Abs7254 0Metal+Loading+(mg/L)1+Cell2+Cell4+CellInitial(a) (b)  42 an average UV-abs-254 reduction of 31.2% was realized. Much larger reductions were observed with the highest tested ML = 63.4 mg/L, yielding an average UV-abs-254 reduction of 57.7%. Despite reducing UV-abs-254 below half of its initial value, further reductions in absorbance would be recommended for effective disinfection process downstream of the EC treatment.   2.2.2.2.2. Medium Flow Rate When experiments were repeated at the medium flow rate (5 LPM), similar trends in DOC and UV-abs-254 were observed, with respect to ML. Although similar conditions were investigated, a lower ML was tested (13.9 mg/L) than that used during low flow experiments (25.5 mg/L) in order to study a larger range of MLs. The MLs tested were 13.9, 38.2, 51.1 and 66.0 mg/L, corresponding to a current of 4.0, 11.0, 14.7 and 19.0 A, respectively. Similar to the low flow experiments, ML was the variable that yielded the most conclusive trends in reductions of both DOC and UV-abs-254. A clear correlation in the reduction in DOC to an increase in ML can be seen for all inter-electrode gaps and current densities investigated, as seen in Figure 2-8. At the lowest ML, 13.9 mg/L, DOC was observed to reduce less than all other MLs tested, yielding an average reduction of 20.9 ± 14.7%, for all inter-electrode gaps and current densities investigated. Specific reductions with respect to inter-electrode gaps and current densities will be discussed further in section §2.2.2.4. When ML was increased to 38.2 mg/L, DOC reductions were observed between 40-89%, with an average reduction of 59.6%. These results correspond well to the low flow experiments, where at the same ML, an average reduction in DOC of 65.8 % was achieved. The two highest ML conditions tested (51.1 and 66.0 mg/L) yielded similar reductions, a phenomenon observed for the low flow experiments as well. Although at the highest ML, the greatest overall reduction in DOC was observed at 97.4%, the average reductions for 51.1 and  43 66.0 mg/L MLs were 85.3±9.41% and 90.1±14.7% respectively, indicating insignificant variances between the two highest levels tested. Results for medium flow rates that were obtained at the highest MLs yielded slightly greater average and overall reductions in DOC than those obtained at low flow experiments. These results suggest that like experiments conducted at a low flow rate, as ML increases, the reductions in DOC also increase.  Figure 2-8: Medium flow (5.00 LPM) DOC reductions: (a) 2-cell, (b) 1 mm inter-electrode gap Similar to the results obtained for low flow rate experiments, both increases and decreases in UV-abs-254 were observed during the medium flow rate experiments. As 0.00.20.40.60.81.00 10 20 30 40 50 60 70DOC/DOC 0Metal+Loading+(mg/L)1+mm2+mm10+mmInitial0.00.20.40.60.81.00 10 20 30 40 50 60 70DOC/DOC 0Metal+Loading+(mg/L)1+Cell2+Cell4+CellInitial(a) (b)  44 with low flow results, reductions in UV-abs-254 were not typically seen until the ML was increased to 51.1 and 66.0 mg/L. In most cases, increases in UV-abs-254 were yielded with the two lowest MLs investigated, as seen in Figure 2-9. At the lowest ML, no combination of variables (inter-electrode gap and current density) yielded reductions in UV-abs-254. Moreover, only under a single circumstance with a 2 mm inter-electrode gap and a 2-cell configuration, was a reduction in absorbance achieved at the second lowest ML of 38.2 mg/L.  Figure 2-9: Medium flow rate (5.00 LPM) UV-abs-254 reductions: (a) 2-cell, (b) 1 mm inter-electrode gap 0.00.40.81.21.62.00 10 20 30 40 50 60 70UV7Abs7254/UV7Abs7254 0Metal+Loading+(mg/L)1+mm2+mm10+mmInitial0.00.40.81.21.62.00 10 20 30 40 50 60 70UV7Abs7254/UV7Abs7254 0Metal+Loading+(mg/L)1+Cell2+Cell4+CellInitial(a) (b)  45 When ML was increased above 38.2 mg/L, reductions in UV-abs-254 were predominantly observed. Average reductions in absorbance at an ML of 51.1 and 66.0 mg/L were 24.1% and 62.9%, respectively, including all variables and experiments investigated. These UV-abs-254 results are very similar to those achieved with low flow experiments: 26.7% and 56.6% for ML of 51.1 and 63.8 mg/L, respectively. Once again, although reductions were achieved at the higher MLs, further reductions in UV-abs-254 would be necessary prior to disinfection as high UV-abs-254 reduce the efficacy of UV or chlorine disinfection. A comparison of DOC and UV-abs-254 reductions at low and medium flow experiments is seen in Figure 2-10.   Figure 2-10: Low and medium flow rate DOC and UV-abs-254 comparison (N=2, δ=1 mm) The increases in UV-abs-254 can once again be attributed to the aforementioned phenomena of dissolved iron species being introduced to treated water samples through HA-Fe complexes. In order to confirm this hypothesis, samples treated at 5 LPM were 0.00.40.81.21.62.00.00.20.40.60.81.00 10 20 30 40 50 60 70UV7abs7254/UV7abs7254 0DOC/DOC 0Metal+Loading+(mg/L)Low+< 2+Cell+(DOC)Med+< 2+Cell+(DOC)Low+< 2+Cell+(UV<abs<254)Med+< 2+Cell+(UV<abs<254) 46 analyzed using AA-spectroscopy during select experiments. A summary of the AA-spec analysis is outlined in Figure 2-11.  Figure 2-11: Residual iron concentrations after EC and direct filtration For multiple cell configurations and inter-electrode gaps, two MLs were investigated: 38.2 and 66.0 mg/L, whereby the former typically yielded increases, while the latter typically yielded reductions in UV-abs-254. From Figure 2-11, it can be seen that all conditions tested which yielded an increase in UV-abs-254, correlated to relatively higher iron concentrations compared to those which produced reductions in absorbance, despite the increased addition of iron (high ML) through electrolysis. In all instances, except for experiments with a 4-cell configuration and 10 mm inter-electrode gap (N=4, δ=10 mm), the higher ML tested yielded decreases in UV-abs-254, and consequently yielded lower iron concentration compared to the lower ML tests, which produced increases in absorbance. During the sole experiment where the lower ML produced lower UV-abs-254 results (N=4, δ=10 mm), iron concentrations remained consistent with all other experiments, in that the lower absorbance was accompanied by a lower iron concentration, and vice versa.  0.00.40.81.21.62.002468101214161838.2+mg/L66.0+mg/L38.2+mg/L66.0+mg/L38.2+mg/L66.0+mg/L38.2+mg/L66.0+mg/L38.2+mg/L66.0+mg/LDOC/DOC 0UV7Abs/UV7Abs 0[Fe],+mg/LMetal+Loading[Fe] UV/UV0 DOC/DOC0! ! ! ! !N=2,+δ=1+mm+ N=2,+δ=2+mm+ N=4,+δ=1+mm+ N=4,+δ=2+mm+ N=4,+δ=10+mm+ 47 It should be noted that iron concentrations reported are all extremely high with respect to the limit set out by the Canadian Drinking Water Quality Guideline (CDWQG), exceeding the minimum iron concentration of 0.3 mg/L [46]. Although it is acknowledged by Health Canada in the CDWQG that no evidence exists which could support the consumption of iron having toxic or having an adverse effect on ones health, the guidelines are set forth due to aesthetic taste and order concerns, as well as staining of laundry and plumbing fixtures. From the high iron concentrations confirmed using AA-spec, as well as increased UV-abs-254 results, it is believed that the HA or water matrix being used in the experiments formed dissolved Fe-HA complexes; this phenomenon will be further explored in the following section [§2.2.2.3].  2.2.2.3. Electrocoagulation Using Suwannee River NOM Iron complexation through anion adsorption with inorganic and organic anions has been widely investigated, whereby organic ligands adsorb on iron hydr(oxides) specifically, involving the replacement of a surface hydroxyl group, or non-specifically [19]. In soil chemistry, this phenomenon has been investigated through the increased retention of humic species in soils relatively rich in iron hydr(oxides) [47]. Researchers have investigated for the formation of Fe-NOM complexes using several aromatic structured acids, including benzoic, phthaltic and pyromellitic acid, as NOM surrogates. Researchers found that absorption of iron on the organic structures increased as the concentration of -COOH groups located on the benzene rings of the acids increased [7],[8]. Specific studies on the adsorption and desorption kinetics of Sigma-Aldrich HA, the same compound used in this author’s research, have also been conducted. It was found that the HA adsorption rate onto hematite was strongly dependent on HA concentration. Using reflectometry, Avena and Koopal (1999) found that as HA solution concentrations increased from 6 to 50 mg/L, adsorption rates sharply increased [50]. The  48 same researchers found that, in general, desorption of iron oxide and Sigma-Aldrich HA is not easily achieved unless an increase in pH occurs after adsorption [51]. In this author’s experiments, a high concentration (40 mg/L) of HA was used and post-electrolysis conditions were characterized by a slowly decreasing pH, suggesting conditions promoting high adsorption rates and slow desorption rates. Additionally, it has been shown that iron oxide adsorption of humic acid can alter the surface hydrophobicity of the organic compound. As humic acid concentrations increased, structural configurations were adopted that limited surface carbon availability, which then further limited hydrophobic organic carbon sorption [52]. This phenomenon could potentially hinder continued floc formation amongst other HA and Fe-HA particles, limiting contaminant removal through the filtration of suspended flocs. In other EC studies [18], as well as CC, it was found that the large hydrophobic fractions of NOM were more predominantly removed than all other fractions of NOM.  Although the above-discussed mechanisms could contribute to the increase in UV-abs-254 if the Fe-HA complexes remained dissolved, it does not account completely for this phenomenon. Since all experiments yielded decreases in DOC, even in the cases yielding increases in UV-abs-254, it is known that HA was ultimately being removed. In other similar EC research it was discovered that the UV-abs-254 increased in treated synthetic water containing chloride solute. Although NOM concentrations were presumed to decrease because of decreased DOC, the increase in absorbance was accounted for by dissolved Fe2+ oxidizing to a more insoluble Fe3+ form [18]. The solubility of iron and iron hydr(oxide) species can be influenced by the presence of ligands such as phosphate, citrate and chloride, which can form soluble complexes [19].  In order to make highly concentrated HA solutions, NaOH was used during stock HA preparations. To neutralize HA stock solutions, HCl was used, which also consequently enhanced the conductivity of synthetic waters to desired levels for  49 representative surface water [see Appendix C for complete instruction of HA stock preparation]. Consequently, chloride was abundantly present in all synthetic water solutions used during all experiments. To determine if chloride was the attributing factor for the increases in UV-abs-254, a series of experiments were undertaken at various chloride levels. For these experiments, lower HA concentrations were used as the highly concentrated stock solutions used previously could not be used due to their inherently high concentration of chloride.  Using the same operating procedures outlined in §2.2.1 with 1 mm inter-electrode gap and a 4-cell configuration, two initial water matrices were used. In order to understand the UV-abs-254 trend using the new HA concentration of 22.5 mg/L, a control water matrix was used containing the same concentration of chloride used in the previous experiments (322.5 mg/L) and chloride was the sole solute. The second water matrix representing surface water sampled between April 28th-July 28th 2015 in Van Anda (expanded upon in Chapter 3) was made to the following specifications: Table 2-1: Solute concentrations for synthetic water representative of Van Anda surface water HA Chloride Nitrate Sulfate 22.5 mg/L 2.94 mg/L 0.52 mg/L 32.5 mg/L  Initial DOC and UV-abs-254 with the new HA concentration were 2.308±0.08 mg/L and 0.2803±0.007 cm-1, respectively. Operating at a low flow rate (1.35 L/min), the same MLs previously investigated were applied and all experiments were run in duplicates.   Results from the low flow rate (1.35 LPM) experiments are summarized in Figure 2-12a. At the decreased HA concentration, it was observed that no increases in UV-abs-254 were yielded with either water tested. It was however observed that the water  50 representative of Van Anda surface water and low chloride concentration yielded much greater decreases in absorbance initially. Synthetic Van Anda water yielded >95% reductions at the lowest ML, with little to insignificant differences as ML was increased. Synthetic water using only chloride as a solute had <50% reduction in absorbance initially, but as ML was increased, reductions in UV-avs-254 began to reach the values which were achieved with the Van Anda synthetic water.   Figure 2-12: UV-abs-254 (a) and DOC (b) reductions of synthetic water containing chloride and Van Anda representative surface water. Low flow rate (1.35 LPM), N=4, δ=1 mm Differences in reduction of DOC were much less pronounced than UV-abs-254 results [see Figure 2-12b]. From these results, as well as with previous experiments, it can be hypothesized that the poor UV-abs-254 results obtained is likely associated with chloride functioning as a ligand increasing the solubility of iron. Since no increases in absorbance were obtained, the same experiments were repeated at a constant chloride concentration of 0.3225 g/L and an increasing HA concentration. HA concentrations of 22.5, 26.0, 30.0 and 40.0 mg/L were used.  0.000.250.500.751.000 20 40 60 80DOC+/DOC 0Metal+Loading+(mg/L)HA+NaClHA+++Van+Anda0.000.050.100.150.200.250.300 20 40 60 80UV7Abs7254,+cm<1Metal+Loading+(mg/L)HA+NaClHA+Van+Anda(a) (b)  51  Figure 2-13: Effect of HA concentrations on UV-abs-254 at constant chloride concentration of 0.3225 g/L. Low flow rate (1.35 LPM), N=4, δ=1 mm As seen in Figure 2-13, as HA concentrations increased from 22.5 to 40.0 mg/L, UV-abs-254 reductions were negatively affected. Increases in absorbance were observed for all HA concentrations tested, except for 22.5 mg/L. Furthermore, as HA increased, greater ML dosages were required to decrease UV-abs-254 below untreated raw water values. These results could indicate a coupled effect of HA-Fe and Cl-Fe complexes attributing to the observed increase of UV-abs-254 in the presence of water containing high chloride concentrations like those in Figure 2-13.   In order to determine whether the type of HA used during experiments attributed to the poor UV-abs-254 results, experiments were repeated using reverse osmosis isolated Suwannee River NOM. During these experiments, the same concentration of chloride (0.3225 g/L) used in previous experiments was utilized. Experiments with a 1 mm inter-electrode gap and 4-cell configuration were performed at the low flow rate, applying the same MLs as previous experiments. 0.00.30.60.91.21.51.80 10 20 30 40 50 60 70UV7Abs7254/UV7Abs7254 0Metal+Loading+(mg/L)HA+=+22.5+mg/LHA+=+26.0+mg/LHA+=+30.0+mg/LHA+=+40.0+mg/L 52  Figure 2-14: EC effect on UV-abs-254 using Suwannee River NOM. Low flow rate (1.35 LPM), N=4, δ=1 mm Figure 2-14 shows the results of the NOM experiments in comparison to previously conducted HA experiments. Although initial UV-abs-254 is much greater when HA is used, the same initial absorbance increase trend was yielded using Suwannee River NOM. Once again, a characteristic decrease in UV-abs-254 is observed as the ML increases. The initial UV-abs-254 differences can be attributed to the different structures of HA and NOM, as well as the different molecular weight fractions in the composition of each organic species. The experiments from Figure 2-14 were conducted after the on-site pilot experiments outlined in Chapter 3, however it is recommended that future EC research include the addition of chloride into raw surface water to confirm the affect of chloride on UV-abs-254 obtained using synthetic surface water.  Due to the effect of high chloride concentration on the solubility of iron and the subsequent effect on UV-abs-254 post EC, the remaining discussion of Chapter 2 will focus on DOC results and exclude UV-abs-254 results. UV-abs-254 results are excluded 0.000.250.500.751.001.251.501.750 10 20 30 40 50 60 70UV7Abs7254+(cm<1)Metal+Loading+(mg/L)Suwannee+River+NOMSigma<Aldrich+HA 53 in the following sections because, as outlined in §2.2.2.2 and §2.2.2.3, it is not indicative of the HA/NOM removal performance of electrocoagulation.   2.2.2.4. Inter-Electrode Gap and Current Density Effects This section will explore the effect of both inter-electrode gap and current density on the reduction of DOC. Unlike metal loading, the effect on DOC reduction with respect to inter-electrode gap and current density were not as clear. Three inter-electrode gaps (1, 2 and 10 mm) were investigated, as well as three cell configurations (1, 2 and 4-cells). Under constant current conditions, adding or eliminating the amount of cells used will dictate the current density. Current densities with respect to ML for low and medium flow rate experiments, 1.35 and 5 LPM respectively, are outlined in Table 2-2.  Table 2-2: Current densities tested at low and medium flow rate experiments ML (mg/L) Low Flow, 1.35 LPM ML (mg/L) Medium Flow, 5 LPM Current Density, mA/cm2 Current Density, mA/cm2 1 Cell 2 Cell 4 Cell 1 Cell 2 Cell 4 Cell 25.5 6.44 2.15 0.92 13.9 25.74 8.58 3.68 38.3 9.65 3.22 1.38 38.2 35.39 11.80 5.06 51.1 12.87 4.29 1.84 51.1 47.30 15.77 6.76 63.8 16.09 5.36 2.30 65.6 61.13 20.38 8.73 It has been purported in prior EC research, that operations at lower current densities yielded greater organic and inorganic contaminant reductions [18], [31]. Similar results were obtained in low flow experiments. As seen in Figure 2-15, for all MLs tested, a general trend is observed where as the number of cells increase, DOC reductions increase. As ML increases, and consequently DOC reductions also increase, the differences in DOC become statistically insignificant, as the error of each condition  54 overlaps. Once again, certain outliers in this trend exist, specifically for 10 mm inter-electrode gap experiment and a 4-cell configuration, where little reductions in DOC occurred and 2-cell configurations yielded the greatest reductions, a phenomenon previously discussed. Due to the predominantly poor DOC reduction performance of experiments utilizing a 10 mm inter-electrode gap, it can also be observed that a general DOC reduction trend occurs with a decreasing inter-electrode gap. An exception to this observation is low ML experiments (25.5 and 28.3 mg/L) performed in a 2-cell configuration, where a small decrease in DOC was observed with an increase of the inter-electrode gap. It should however be noted that the variations in DOC for this trend were statistically insignificant. Both trends associated with DOC reductions (decreasing current density and inter-electrode gap) are also characterized by a decrease in the operating cell potential. Although the effect of speciation was not considered in this scale-up work, the increased DOC reductions at lower potential operations could potentially be attributed to the synthesis of iron hydr(oxide) species with a greater affinity to function as a coagulant, a phenomenon previously reported in the literature [20]. The operating cell potential during EC can strongly dictate speciation. The variation in potential for all low flow rate experiments is summarized in Figure 2-16.   55  Figure 2-15: DOC reductions during low flow rate (1.35 LPM) and the effect of current density and inter-electrode gap at: (a) ML=25.5 mg/L, (b) ML=38.3 mg/L, (c) ML=51.1 mg/L, (d) ML=63.8 mg/L   Figure 2-16: Cell potential during low flow rate (1.35 LPM) experiments at: (a) ML=25.5 mg/L, (b) ML=38.3 mg/L, (c) ML=51.1 mg/L, (d) ML=63.8 mg/L 10+mm2+mm1+mm0.000.250.500.751.00Initial 1+Cell 2+Cell 4+CellDOC/DOC 0+,+mg/L10+mm2+mm1+mm0.000.250.500.751.00Initial 1+Cell 2+Cell 4+CellDOC/DOC 0,+mg/L10+mm2+mm1+mm0.000.250.500.751.00Initial 1+Cell 2+Cell 4+CellDOC/DOC 0,+mg/L10+mm2+mm1+mm0.000.250.500.751.00Initial 1+Cell 2+Cell 4+CellDOC/DOC 0,+mg/L(a) (c) (b) (d) 10+mm2+mm1+mm0481216201+Cell 2+Cell 4+CellPotential,+V10+mm2+mm1+mm0481216201+Cell 2+Cell 4+CellPotential,+V10+mm2+mm1+mm0481216201+Cell 2+Cell 4+CellPotential,+V10+mm2+mm1+mm0481216201+Cell 2+Cell 4+CellPotential,+V(a) (c) (b) (d)  56 When experiments were scaled up to medium flow rate (5.0 LPM), many of the trends observed at low flow rate changed. DOC data for medium flow experiments are summarized in Figure 2-17. At the lowest ML, single cell experiments reduced DOC significantly less than the 2- and 4-cell experiments. While at low flow a correlation between greater reductions in DOC to increasing the number of cells was observed, at medium flow, 2- and 4-cell configurations performed similarly, without any significant differences. Single cell experiments yielded an average DOC reduction of 2.8% with no statistically significant difference among the different inter-electrode gaps. For 2- and 4-cell configurations, an average reduction of 30.0% was achieved, once again with no significant difference among all inter-electrode gaps, with the sole exception of 2-cell experiments at 10 mm (43.4±2.3% reduction). The reason for this phenomenon is unknown, as experiments performed at similar current densities and potentials in low flow experiments (ML= 38.3 mg/L, 1-cell, 10 mm) showed contradictory results with extremely poor reductions in DOC, as described earlier, but once again this could be the result of speciation differences.   At ML=38.2 mg/L a new trend was observed whereby operation with a 4-cell configuration resulted in the least reductions, while 1- and 2-cell experiments provided the greatest. An average DOC reduction of 47.7±5.7% was achieved for 1, 2 and 10 mm gaps, with no significant deviation amongst all experiments. No significant differences were observed during experiments performed with 1- and 2-cells, yielding an average DOC reduction of 63.4±9.1%. A single outlier in the data arose during the 2-cell, 2 mm experiment, where the greatest DOC reduction was achieved (DOC/DOC0 = 0.111 ± 0.005). This experiment was characterized by i =11.80 mA/cm2 and P =5.20 V. No other experiments operated under the same current densities and potentials; however similar conditions at low flow experiments did not yield these unusual results. A possible explanation for this phenomenon is the production of an iron species with a higher  57 affinity for the removal of HA; however no in-situ speciation analysis was performed and therefore this speculation cannot be confirmed.  Figure 2-17: DOC reductions during medium flow rate (5.00 LPM) and the effect of current density and inter-electrode gap at: (a) ML=13.9 mg/L, (b) ML=38.2 mg/L, (c) ML=51.1 mg/L, (d) ML=66.0 mg/L Experiments at the two highest MLs, regardless of inter-electrode gap or current density, yielded high reductions in DOC. At both 51.1 and 66.0 mg/L ML, single cell experiments with a 10 mm inter-electrode gap could not be performed, as electrical potential requirements exceeded the DC power supply limitations. These experiments have been omitted in from DOC and UV-abs-254 figures. At ML=51.1 mg/L, although no significant difference was yielded for all experiments, except a single outlier (10 mm, 4-cell), a general trend of increased DOC reduction with increasing current density was observed, with an average reduction of 88.5±2.4%. Comparatively low reductions were yielded at 10 mm and 4-cells, a phenomenon that has been discussed earlier. At the highest ML, similar average reductions were yielded, at 91.4±1.4% for all current 10+mm2+mm1+mm0.000.250.500.751.00Initial 1+Cell 2+Cell 4+CellDOC/DOC 010+mm2+mm1+mm0.000.250.500.751.00Initial 1+Cell 2+Cell 4+CellDOC/DOC 010+mm2+mm1+mm0.000.250.500.751.00Initial 1+Cell 2+Cell 4+CellDOC/DOC 010+mm2+mm1+mm0.000.250.500.751.00Initial 1+Cell 2+Cell 4+CellDOC/DOC 0(a) (c) (b) (d)  58 densities and inter-electrode gaps. Outliers from this average included two poor performing conditions (2-cell, 1 mm and 4-cell, 10 mm) and the greatest performing condition (4-cell, 1 mm). At 97.4±0.1% reduction, the conditions with the lowest current density and smallest inter-electrode gap yielded the greatest overall reduction in DOC compared to all other experiments performed in the scale-up project. A trend of low current density and inter-electrode gap yielding better performance was observed frequently at low flow experiments. It should be noted, however, that experiments conducted at the same current density, inter-electrode gap and consequently similar operating potentials, at different MLs, yielded a different trend in DOC reductions [see Figure 2-18].   Figure 2-18: DOC reduction of EC at i=8.66±0.11 mA/cm2 operating at medium flow rate (5.00 LPM) Although intuitively it should be expected that an overall greater reduction in DOC result at high ML, a similar trend with respect to inter-electrode gap and potential would be expected. This may suggest that other variables that were not monitored in this research affect the performance of EC. Variables such as pH and dissolved oxygen (DO) can also dictate the speciation of iron hydroxides in an EC process [20]. Both of 10+mm2+mm1+mm0.000.250.500.751.00Initial25.5+mg/L66.0+mg/LDOC/DOC 0Metal+Loading3.30+V+ 12.30+V+4.20+V+3.60+V+4.40+V+12.60+V+ 59 these variables could differ substantially at either condition, potentially dictating the small variations, trends and outliers in the DOC reductions at both low and medium flow experiments.   In an effort to identify possible wavelength peaks to further identify different species of iron hydr(oxide) in treated samples (because of frequent increases in UV-abs-254) during medium flow experiments, full UV-absorbance spectral analysis (200-800 nm) was employed. The spectral analysis provided no insight into speciation, as no peaks were yielded, but rather an exponentially decreasing curve, with a maximum absorbance at shorter wavelengths, decaying to nearly unidentifiable absorbance at 800 nm. This characteristic graph was present for all samples analyzed, and therefore no further discussion of UV-absorbance will be presented. Conclusive evidence of speciation effects on HA removal could only be confirmed if in-situ monitoring was performed during scale-up experiments, not with ultraviolet spectroscopy of post-EC water samples.  2.2.2.5. Electrocoagulation Power Requirements This section analyzes the energy requirements for the iron electrocoagulation process utilized during the previous scale-up experiments. Requirements are described by the energy in kilowatt-hour (kWh) used, normalized by the volume of water (cubic meters) treated at each respective flow rate. This energy analysis will solely describes the operating requirements of the process and any cost analysis will omit capital, infrastructure or consumable material costs (i.e. electrodes) associated with the process.  In general, the power and energy of the EC process is dictated by both the electrical current and potential utilized. Consequently, all variables investigated (metal loading, inter-electrode gap and cell configuration/current density) will have an effect on the energy requirements of electrocoagulation. During experiments, ML was controlled  60 through the current applied to the cell. When the current is increased, the ML increases, as well as the cell potential. Therefore, as a higher ML is applied in the EC process, power requirements also increase due to increased current and potential. At constant current, the cell potential will change based on resistance, an aforementioned phenomena described by Ohm’s law in Chapter 1. Resistance will greatly increase as the inter-electrode gap increases, as well as when the electrode surface area decreases. It can therefore be predicted that power requirements of the EC process will decrease as the inter-electrode gap and the current density decrease.  During low flow rate (1.35 LPM) experiments, energy requirements ranged from 0.027-1.165 kWh/m3, depending on the ML, inter-electrode gap and current density. It can be predicted that at the highest ML, with a single cell and 10 mm gap the experiment will have the highest energy requirements, while at the lowest ML, with a 4-cell and 1 mm gap the experiment will have the lowest energy requirements; this clear relationship between variables and their effect on power was confirmed experimentally. The effect of ML on energy use is seen in Figure 2-19 for 4-cell configuration experiments.   Figure 2-19: Effect of ML on energy requirements per unit water treated at low flow rate (1.35 LPM) during 4-cell configuration experiments 10+mm2+mm1+mm0.000.050.100.150.200.2525.5 38.3 51.1 63.80.0490.0960.1600.2310.031 0.0540.0810.1140.027 0.0480.0740.102Energy,+kWh/m3Metal+Loading,+mg/L 61 Only at the two highest MLs for low flow rate experiments were reductions in both DOC and UV-abs-254 predominantly yielded. Energy requirements per unit of water treated for different cell configurations and inter-electrode gaps at given MLs are shown in Figure 2-20. Once again, the predicted trend in energy requirements is confirmed at these conditions. When considering both DOC and UV-abs-254 reductions, it was seen that the smallest current density and inter-electrode gap provided one of the preferred operating conditions at both a 51.1 and 63.8 mg/L ML, correlating to an energy demand of 0.074 and 0.102 kWh/m3, respectively. These requirements are relatively low compared to an incumbent water treatment process like reverse osmosis [see §3.2.2.4] [53], translating into $0.0076/m3 and $0.0105/m3 respectively, based on BC Hydro general business rates for small and medium customers ($0.1030/kWh) [54].    Figure 2-20: Energy requirements for low flow rate (1.35 LPM) EC operations at (a) ML=51.1 mg/L, (b) ML=63.8 mg/L Medium flow rate (5.0 LPM) experiments were characterized by the same trend in energy consumption to that of the low flow experiments. The condition requiring the least energy (ML=13.9 mg/L, N=4, δ=1 mm) operated at 0.061 kWh/m3, while the most energy intensive condition that could be tested (ML=65.6 mg/L, N=1, δ=2 mm) was 1.070 kWh/m3. It should be noted that the same experiment at an inter-electrode gap of 10 mm was unable to be performed because the required potential exceeded the 1+mm2+mm10+mm0.00.20.40.60.81+Cell 2+Cell 4+Cell0.1850.0990.0740.2470.1190.0810.7780.3600.160Energy,+kWh/m31+mm2+mm10+mm0.00.40.81.21+Cell 2+Cell 4+Cell0.3270.1390.1020.3580.1670.1141.1650.5310.231Energy,+kWh/m3(a) (b)  62 power supply limits. Again, at medium flow experiments, consistent reductions in both DOC and UV-abs-254 occurred at the two highest ML tested. Conditions that saw the great overall reduction of both performance variables were N=2, δ=2 mm and N=4, δ=1 mm for 51.1 and 65.6 mg/L ML, respectively. The energy consumption at these two conditions were 0.309 and 0.228 kWh/m3, correlating to BC Hydro rates of $0.0318/m3 and $0.0235/m3, whereby the more effective EC condition required less energy.   Figure 2-21: Energy requirements for medium flow rate (5.00 LPM) EC operations at (a) ML=51.1 mg/L, (b) ML=63.8 mg/L In terms of EC efficiency, at the same operating conditions, low flow rate operations yielded lower energy consumptions per unit of water treated. This is to be expected, as a greater current is required in order to supply the same ML at a higher flow rate. In general, the EC process at both 1.35 and 5 LPM had energy requirements yielding operating costs that are nearly equal to those for an alum chemical coagulation process, described in detail in §3.2.2.4 [55].  2.3 Chapter Conclusion In Chapter 2, the efficacy of iron EC for the removal of HA was investigated at bench-scale low and medium flow rates of 1.35 and 5 LPM. Four variables were monitored: flocculation time, metal loading, current density and inter-electrode gap. For 1+mm2+mm10+mm0.00.20.40.60.81.01+Cell 2+Cell 4+Cell0.4620.2450.1520.7010.3090.1810.9520.505Energy,+kWh/m31+mm2+mm10+mm0.00.40.81.21.61+Cell 2+Cell 4+Cell0.7220.3740.2281.0700.4810.2791.5200.798Energy,+kWh/m3(a) (b)  63 all experiments, no effect was observed for the increased or decreased reduction of DOC or UV-abs-254 with respect to flocculation time. It was therefore concluded that floc formation occurred either during the electrolysis process, immediately after, or a combination of both. Metal loading was found to have the more profound impact on HA removal, with respect to all other variables tested. A clear trend of increased reductions in both DOC and UV-abs-254 were yielded with increased ML. Increases in UV-abs-254 were observed initially at lower MLs, which was confirmed to be due to the presence of high dissolved residual iron concentrations after filtration using AA-spectroscopy.   To understand the mechanisms contributing to the high concentration of dissolved iron after EC at lower MLs, effects of both HA and chloride were investigated. Using Sigma-Aldrich HA, two different water matrices were using: (1) HA and a sole solute of chloride in high concentration (same water used for all scale-up experiments), and (2) HA and three co-occurring solutes (low concentrations of chloride, nitrate and sulfate) mimicking raw surface water from Van Anda. While DOC results closely matched for both water matrices, significantly greater reductions of UV-abs-254 were observed using the water with low concentrations of chloride. As the HA concentration increased under constant chloride concentrations, UV-abs-254 also increased, confirming that high chloride concentration and humic substances function as ligands increasing the solubility of iron.  No clear trends in both DOC and UV-abs-254 were determined with respect to inter-electrode gap and current density. A number of unmonitored factors could be responsible for the results yielded, such as effect of DO, pH and potential on the speciation of iron hydr(oxides). It is known that different iron species synthesized during EC have varying affinities to function as a coagulant, and it is therefore unknown to what extent this effect will have on the removal of HA in this research. It is therefore recommended that further research be conducted in the area of in-situ speciation  64 determination, to understand the outliers that occurred during the above bench-scale experiments.  EC energy analysis was also conducted at both low and medium flow rates. It was found that the process has a low energy footprint, whereby the conditions providing the great reductions in DOC and UV-abs-254 at the highest ML also tended to be the least energy intensive (low current density and inter-electrode gap).    65    Chapter 3  Pilot-Scale Iron Electrocoagulation  3.1 Chapter Introduction The following chapter discusses the pilot experiments undertaken in the community of Van Anda, Taxeda Island, as a part of the RES’EAU Mobile Water Treatment Plant (MWTP) project with various Community Circles in British Columbia. Experiments were designed to complement the scale-up experiments at low and medium flow, investigating the same operating variables as those discussed in Chapter 2.   Figure 3-1: (a) Van Anda MWTP at Priest Lake, (b) Inside the MWTP (b) (a)  66 Experiments were performed in the MWTP with a flow rate of 10 LPM at the Van Anda community’s surface water supply from Priest Lake [see Figure 3-1]. Priest Lake water is characterized by relatively high natural organic matter concentrations for typical surface water supplies and is currently being treated solely with chlorine disinfection, potentially exposing water users to DBPs. Given the water matrix [see Table 3-1], Van Anda provided a suitable water supply for pilot-scale experiments.  Table 3-1: Priest Lake raw surface water quality variables  DOC 6.036 ± 0.2 mg/L UV-Abs-254 0.1330 ± 0.001 cm-1 UVT 74.0 ± 0.4 % pH 7.87 ± 0.09 Conductivity 236 ± 6 μS/cm  3.2 Pilot-Capacity Electrocoagulation Similar to bench-capacity experiments undertaken at the UBC CHBE facilities, pilot-scale experiments investigated the effect of metal loading, current density and inter-electrode gap on the removal of organics using iron electrocoagulation. The target pilot flow rate was 10 LPM, a scale that would be unfeasible in the laboratory using synthetic water. The following section will explore the materials and methods utilized during pilot experiments, as well as the results obtained. All piloting of the iron EC technology in Van Anda took place between October 5-9th, 2015.   3.2.1. Materials and Methods The same EC apparatus, as well as electrode materials and sizes used in experiments from Chapter 2 were used during the pilot experiments. The process utilized during EC piloting was similar to that employed in scale-up experiments with  67 some slight modifications and the omission of jar tests after EC treatment. Priest Lake water was drawn via the community’s drinking water intake, roughly 100 m from the reservoir’s shoreline and the MWTP. A split stream from the community’s intake supplied the pilot-plant with raw water, whereby it was pumped into a 100 L holding vessel. From the holding vessel, a Masterflex I/P Drive and I/P High Performance Head peristaltic pump managed flow from the vessel to the EC reactor, ensuring precise and stable flow throughout all experiments. Upon exiting the EC reactor, water was passed through two bag filters in series (10 and 5 μm, respectively), to remove large iron-NOM flocs prior to disposal [see Figure 3-2]. A Keithley 2260B-30-72 DC Power Supply was used for all experiments.   Figure 3-2: Experimental apparatus: (a) raw water inlet, (b) 100 L vessel, (c) pump inlet tube, (d) peristaltic pump, (e) EC reactor, (f) DC power supply, (g) reactor outlet and bag filter  Once again, EC experiments were performed galvanostactically in order to operate under constant ML conditions. For each operating condition tested, trials were run until a stable potential was reached, whereby roughly 80 mL of treated sample was drawn and filtered using a 0.45 μm PVDF syringe filter. Upon filtration, the UV (a) (b) (c) (d) (e) (f) (g)  68 transmittance (UVT) was measured, as well as the pH. UVT is a measure of the ultraviolet energy at 254 nm that can be transmitted through the water, expressed as a percentage. UTV is a variable often monitored by water treatment operators to evaluate turbidity and relates to UV-abs-254 as follows:   UVT % = 100×10-(UV-abs-254) (E.4)  After UVT and pH analysis, samples were refrigerated and stored for transport back to UBC for further analysis using TOC, UV-spec (complimenting and confirming UVT measurements), AA-spec, and high performance size exclusion chromatography (HPSEC).  Once again, three variables were investigated: (1) ML, (2) current density (by adding or subtracting the amount of electrochemical cells), and (3) inter-electrode gap. To match prior lab experiments, the four MLs investigated were 27.8, 38.2, 51.1 and 66.0 mg/L, achieved by applying constant current at 16.0, 22.0, 29.4 and 35.0 A until a stable voltage was reached, respectively. A range of current densities was investigated, dependent on the applied current and number of cells being used (1, 2 and 4-cell configurations). The same three inter-electrode gaps previously investigated (1, 2 and 10 mm) were also used in the pilot-scale experiments. All experiments were performed in duplicates.  Priest Lake contains challenging water, characterized by high concentrations of NOM and lower conductivities compared to synthetic waters used in scale-up laboratory experiments. An overview of Priest Lake water characteristics is found in Table 3-1. DOC was analyzed using a Shimadzu ASI-V Total Organic Carbon Analyzer, utilizing the non-purgeable organic carbon method. UV-abs-254 was measured using an Agilent Technologies Cary 100 UV-Vis Spectrophotometer at a constant wavelength of 254 nm. The apparent molecular weight (AMW) of NOM from untreated and treated Priest  69 Lake samples was characterized using HPSEC (Water 2695 Separation Module), equipped with a Waters Protein-PakTM, a 125 Å column and a 2998 Photodiode Array Detector. The Waters 2487 dual wavelength absorbance detector was set to 260 nm and a phosphate buffer carrier solution (0.02 M) was used to adjust the pH to 6.8 at a flow rate of 0.7 mL/min. Column retention times were correlated to AMW using a calibration curve derived from using polysulfonate standards (15, 7, 4 and 2 kDa, American Polymer Standards Corporation). Residual iron concentrations were measured using AA-spec (Varian SpectrAA 220 Fast Sequential AAS). All replicates were analyzed with the above techniques.   3.2.2. Results and Discussion A large challenge encountered during pilot-scale experiments was exceeding the power limitations of the DC power supply. Although the power supply was equipped to provide adequate current to achieve the desired MLs, some operating conditions required cell potentials that were unable to be reached. An overview of the experiments that were attempted, as well as those which exceeded power limitations is seen in Table 3-2. Due to the omission of many operating conditions, much of the following discussion will focus on 2 and 4-cell operations, in addition to 1 and 2 mm inter-electrode gaps; conditions that were observed to provide significant HA removal in laboratory scale-up experiments.  Similar to laboratory scale-up experiments discussed in Chapter 2, the effects of speciation were not considered in the pilot-scale experiments of Chapter 3. As previously discussed, speciation can have a effect on the effectiveness of EC in removing NOM, as well as other contaminants, however it was beyond the scope of this author’s research. Since cell potential, amongst other factors, can influence the iron speciation during EC,  70 Table 3-3 below outlines the voltage ranges experienced during EC piloting. The operating voltages will also be relevant when considering EC energy requirements, discussed further in §3.2.2.4. Table 3-2: Overview of experiments attempted, and those that succeeded (✔) and those that exceeded the power supply limits (✗) ML mg/L Cell Configuration 1-Cell 2-Cell 4-Cell Inter-Electrode Gap Inter-Electrode Gap Inter-Electrode Gap 1 mm 2 mm 10 mm 1 mm 2 mm 10 mm 1 mm 2 mm 10mm 27.8 ✔ ✔ ✗ ✔ ✔ ✗ ✔ ✔ ✔ 38.2 ✗ ✗ ✗ ✔ ✔ ✗ ✔ ✔ ✔ 51.1 ✗ ✗ ✗ ✔ ✔ ✗ ✔ ✔ ✗ 66.0 ✗ ✗ ✗ ✔ ✔ ✗ ✔ ✔ ✗ Table 3-3: Voltage ranges for all applied MLs at 1, 2 and 10 mm inter-electrode gap 2-Cell Configuration Inter-Electrode Gap Voltage Range 1 mm 12 – 20 V 2 mm 15 – 25 V 4-Cell Configuration Inter-Electrode Gap Voltage Range 1 mm 7 – 11 V 2 mm 7 – 14 V 10 mm 26 – 30 V  3.2.2.1. Metal Loading Effects Similar to lab-scale experiments [Chapter 2], a clear effect of ML on the reduction of DOC and UV-abs-254 was observed at the pilot-scale. A general trend of reductions in both DOC and UV-abs-254 was yielded with increasing ML. At lower MLs, greater variations in reduction were observed for both DOC and UV-abs-254 with respect to current density and inter-electrode gap. With increased ML and consequently increased reduction of NOM, a smaller standard deviation in reduction between all operating variables arose. DOC was observed to reduce 29.5±4.8%, 33.7±4.8%, 37.1±3.4% and 37.2±4.2%, for MLs of 27.8, 38.2, 51.1 and 66.0 mg/L, respectively. Compared to low  71 and medium flow experiments using synthetic water, much less variations in reduction were observed amongst all treatments tested. However, reductions much greater than 50% were not observed using raw water at 10 LPM, a phenomenon that occurred for synthetic water containing HA during the bench-scale experiments with an ML greater than 38.2 mg/L. Contrary to low and medium flow experiments using HA, for all experiments performed using raw surface water, no increases in UV-abs-254 were yielded. This suggested that lower concentrations of dissolved iron were present after treatment and filtration. Similar to DOC trends, a clear relationship in the reduction of UV-abs-254 with an increase in ML was observed, for all current densities and inter-electrode gaps [see Figure 3-4]. At the lowest ML, average reductions for all current densities and inter-electrode gap experiments were 39.1±4.9%, a considerable improvement from results obtained at the same ML at bench-scale. Improved results were yielded for MLs of 38.2, 51.1 and 66.0 mg/L, with average absorbance reductions of 48.1±2.7%, 52.5±1.2% and 54.7±0.9%, respectively. Although fewer conditions could be tested at higher MLs due to power limitations, variations in reductions were much less pronounced compared to those at lower MLs.   72  Figure 3-3: Metal loading effects on the reduction of DOC, (a) 4-cell configuration, (b) 2 mm inter-electrode gap At low and medium flow experiments using synthetic water, greater reductions (%) in UV-abs-254 were observed at the highest ML, compared to these pilot results. It should however be noted that a significantly lower absolute UV-abs-254 value was achieved at the pilot-scale; at low and medium flow rates average UV-abs-254 reduction at the highest ML were 56.6% and 62.8%, corresponding to an average absolute absorbance of 0.4754 and 0.4614 cm-1, respectively. Although the average reduction at 0.00.20.40.60.81.00 10 20 30 40 50 60 70DOC/DOC 0Metal+Loading+(mg/L)1+mm2+mm10+mm0.00.20.40.60.81.00 10 20 30 40 50 60 70DOC/DOC 0Metal+Loading+(mg/L)1+Cell2+Cell4+Cell(a) (b)  73 the same ML at pilot-scale was 54.7%, this corresponded to an absolute UV-abs-254 of 0.0603 cm-1.   Figure 3-4: Metal loading effects on the reduction of UV-abs-254, (a) 4-cell configuration, (b) 2 mm inter-electrode gap  All pilot-scale experiments were analyzed with AA-spec, to quantify the residual iron concentrations. All samples tested yielded no detectable residual Fe concentration, indicating that iron was either not present in treated samples or present in concentrations below the instrument detection limit (0.5 mg/L) of the AA-spec unit. Without detectable limits of iron, a considerable improvement in EC performance is 0.000.040.080.120.160 10 20 30 40 50 60 70UV7Abs7254(cm<1)Metal+Loading+(mg/L)1+mm2+mm10+mm0.000.040.080.120.160 10 20 30 40 50 60 70UV7Abs7254+(cm<1)Metal+Loading+(mg/L)1+Cell2+Cell4+Cell(a) (b)  74 seen using natural NOM, i.e., natural surface water. As seen in Chapter 2, the solubility of iron can be greatly variable depending on the complexation that can occur with organic [52] and inorganic ligands (such as chloride) [19]. From previous lab-scale experiments, chloride was shown to greatly affect the residual iron concentrations after EC, whereby high chloride concentrations correlated to increased UV-abs-254 due to dissolved residual iron. Compared to lab-scale experiments with synthetic raw water, containing chloride ions at a concentration of 322.5 mg/L, Priest Lake surface water was found to have an average chloride composition of 2.95 mg/L over a 3 month period (see Table 2-2). The obtained results were therefore expected and consistent with lab-scale experiments which used synthetic water containing HA and a similar ion composition to that of Priest Lake (§2.2.2.3.).   3.2.2.2. Inter-Electrode Gap and Current Density Effects At low and medium flow experiments, reductions in both DOC and UV-abs-254 were characterized by significant variations at constant MLs, as the inter-electrode gap and current density varied. At pilot-scale capacity, these variations in reduction were much less pronounced and in most cases, no statistically significant variations were yielded amongst conditions at constant MLs. At the four MLs, a range of current densities, 7.35-112.61 mA/cm-2, were investigated [see Table 3-4].  At the two lowest MLs, 27.8 and 38.2 mg/L, the same trends in reduction of DOC were observed. As seen in Figure 3-5, DOC reduction increases as inter-electrode gap increases from 1 to 2 mm during 2-cell experiments. The opposite trend is observed for 4-cell experiments, as DOC reductions increase as inter-electrode gap decreases from 10 to 1 mm. Interestingly, all UV-abs-254 results show a clear trend in increased reduction with increasing inter-electrode gap at the same MLs. Although these trends  75 for DOC and UV-abs-254 exist, many of these variations are not statistically significant, numerically displayed in Table 3-5. Table 3-4: Current density values for each metal loading and cell configuration at pilot-scale Current (A) ML (mg/L) Current Density, mA/cm2 1 Cell 2 Cell 4 Cell 16.0 27.8 51.48 17.16 7.35 22.0 38.2 70.79 23.60 10.11 29.4 51.1 94.59 31.53 13.51 35.0 66.0 112.61 37.54 16.09 Many of the variations observed in Figure 3-5 are not statistically significant; however, the conflicting trend in DOC and UV-abs-254 reduction during 4-cell experiments may suggest that EC operations at lower current densities favor the removal of NOM structures with more aromatic carbon structures. It is these aromatic rings that preferentially absorb the 254 nm ultraviolet wavelengths. Although these ringed structures may be more predominantly removed at lower current densities, they may not necessarily account for the largest concentration of carbon in the samples. For the DOC and UV-abs-254 results that did yield significant differences with respect to inter-electrode gap, through HPSEC analysis it is observed that samples treated with a gap of 1 mm have a comparatively greater affinity to remove smaller MW structures, but remove the lowest fraction of larger MW structures [see Figure 3-6]. When utilizing a 2 mm inter-electrode gap, the greatest fraction of larger MW structures are removed, while smaller structures are not removed as efficiently as for the 1 mm inter-electrode gap. The 10 mm gap yielded the poorest removal of smaller MW structures and only moderate removal of large structures, when compared to the two other inter-electrode gaps. HPSEC results confirm that samples which yielded the greatest removal of DOC, but the lowest reduction in UV-abs-254 (δ=1 mm) were characterized by a greater  76 reduction in small MW structures and a lower reduction in larger MW structures; therefore, a correlation can be made between large MW structures (more aromatic carbon structures) and their effect on UV-abs-254.   Figure 3-5: Cell configuration and inter-electrode gap effects on the reduction of (a) DOC and (b) UV-abs-254    77 Table 3-5: Cell and gap effects on the reduction of DOC and UV-abs-254 DOC/DOC0 ML  1 mm 2 mm 10 mm 27.8 mg/L 2-Cell 0.780±0.05 0.681±0.1  4-Cell 0.650±0.08 0.722±0.07 0.737±0.05 38.2 mg/L 2-Cell 0.632±0.08 0.600±0.02  4-Cell 0.667±0.07 0.697±0.02 0.718±0.002 UV-Abs-254/UV-Abs-2540 ML  1 mm 2 mm 10 mm 27.8 mg/L 2-Cell 0.649±0.08 0.592±0.08  4-Cell 0.627±0.2 0.586±0.02 0.572±0.02 38.2 mg/L 2-Cell 0.492±0.08 0.493±0.02  4-Cell 0.547±0.08 0.515±0.001 0.547±0.02  At the greatest MLs, 51.1 and 66.0 mg/L, very little differences in DOC and UV-abs-254 reductions were observed for all conditions tested. For both MLs, the condition yielding the greatest reduction in DOC was that with the lowest current density and potential; i.e., the 4-cell configuration and 1 mm inter-electrode gap.  At 41.6% and 42.9% reduction, these were the sole conditions that exceeded beyond a single standard deviation of the average of all conditions tested (37.1±3.4% and 37.2±4.2%, respectively). Very little variation was also observed in reduction of UV-abs-254, whereby nearly all conditions had no statistically significant differences.  78  Figure 3-6: HPSEC analysis of NOM removal during 4-cell EC (ML=38.2 mg/L); magnified region, whereby shaded areas represent error Although no significant variations were yielded, the greatest reduction in absorbance, 55.8±0.9%, occurred at the same condition that satisfied the greatest reduction in DOC (N=4, δ=1 mm). In general, reductions in both DOC and UV-abs-254 were seen to improve as current density and inter-electrode gap both decreased. The moderate reduction in both DOC and UV-abs-254 can potentially be attributed to the specific ultraviolet absorbance characteristic of the raw water, expanded upon in the following section.   3.2.2.3. NOM Removal Characterization It has previously been observed that larger NOM structures are more predominantly removed during the electrocoagulation process [18]. HPSEC was utilized to investigate the characteristic NOM removal behavior of iron EC at a pilot-scale.  79 Additionally, specific ultraviolet absorbance (SUVA) values were also used to characterize the predominating NOM structures present in raw and treated water samples. SUVA describes the aromatic character of the dissolved organic matter in a water sample, and is calculated according to equation (E.5):   AB>C = B>DEFG254G×G100N2@  (E.5)     In general, lower SUVA values correspond to a greater reduction in large molecular weight NOM, as UV-abs-254 is more predominantly reduced compared to DOC [see §3.2.2.2.].   As discussed in §3.2.2.1, the increase in ML is characterized by the increased reduction of both DOC and UV-abs-254. In addition to DOC and UV-abs-254 results, this increased removal of NOM is seen through HPSEC analysis [see Figure 3-7]. From HPSEC, it is observed that the increase of ML is accompanied by an overall decrease of absorbance. It can also be observed that at higher MLs, a greater predominance for the removal of larger MW structures (> 750 Da) is present, relative to removal of smaller structures (< 500 Da). While very little variation in removal is yielded below 500 Da, greater variations in HPSEC results between varying MLs were yielded at > 500 Da.   80  Figure 3-7: HPSEC NOM MW removal distribution (N=4, δ=1 mm) This predominance of greater removal of larger MW structures at higher MLs is also confirmed through SUVA analysis. As ML increases, SUVA values decrease from 2.12 to 1.71 L/m!mg [see Table 3-6]. Treated waters achieving a SUVA below 1.75 indicate EC’s ability to more efficiently remove high MW fractions of NOM. This has also been suggested as a ‘stop point’ for EC’s effectiveness to further reduce DOC [17]; a phenomenon that was illustrated in this author’s results, as there was no significant reduction difference in DOC at the two highest MLs explored.  Table 3-6: Metal loading effect on SUVA (N=4, δ=1 mm)  Metal Loading Raw Water 27.8 mg/L 38.2 mg/L 51.1 mg/L 66.0 mg/L SUVA (L/m!mg) 2.20 2.12 1.81 1.78 1.71 Raw water characterized by a high SUVA (>3) suggests greater concentrations of NOM composed of hydrophobic dissolved organic carbon structures, such as high MW aquatic HA [56],[57]; which have been shown to be more easily removed using EC [18], as well as by traditional chemical coagulation [5],[6]. This phenomenon was observed in  81 the prior low (1.35 LPM) and medium (5 LPM) flow rate experiments conducted using synthetic water [see Chapter 2]. Using HA as an NOM surrogate, initial raw water samples had an average SUVA of 10.60 L/m!mg, suggesting high concentrations of predominantly large MW fractions of dissolved organic carbon structures. In the low and medium flow rate experiments, much greater removal (%) was observed with both DOC and UV-abs-254 when compared to pilot-scale experiments using Priest Lake raw water. Final SUVA values after EC treatment during lab-scale experiments are not an accurate indication of organics removal however, because of the high UV-abs-254 values yielded as a result of high concentrations of dissolved residual iron due to HA and chloride complexes [see §2.2.2.3]. Raw water samples from Priest Lake have a SUVA of 2.20 L/m!mg. It has been reported that low SUVA values (< 3) are an indication of large NOM fractions composed of small MW hydrophilic dissolved carbon having a lower charge density and are consequently less affected by coagulation treatment [57]. Although the SUVA of Priest Lake water suggests a challenging water matrix for the implementation of a coagulation process, EC was able to achieve just below 50% reduction in DOC and over a 50% reduction of UV-abs-254.  3.2.2.4. Pilot Electrocoagulation Energy Requirements Energy requirements for pilot-scale experiments largely varied, depending on the operating parameters being utilized. As described in §2.2.2.5, due to the increased potential associated with increasing metal loading, inter-electrode gap and current density, the energy requirements will also increase. This phenomenon occurs because of the increased resistance, which accompanies the increase of each of the three aforementioned parameters, thereby increasing the cell potential at constant current.  Operating potentials of EC at pilot-scale varied between 6.58 V and 31.53 V for the 4-cell, 1 mm inter-electrode gap operation, and for the single cell, 2 mm gap  82 operation, respectively. Although no significant differences in NOM removal (qualified by DOC and UV-abs-254 reductions) was observed at the two greatest metal loadings for any combination of inter-electrode gaps (1 and 2 mm) and current densities (2- and 4-cell configurations), the energy requirements vary significantly.   Figure 3-8: Energy requirements (per unit of water treated) for N=4, 2 and δ=1, 2 mm pilot experiments Table 3-7: Energy requirements per water treated (corresponding to Figure 3-8)  2-Cell Configuration 4-Cell Configuration Metal Loading Inter-Electrode Gap Inter-Electrode Gap 1 mm 2 mm 1 mm 2 mm 27.8 mg/L 0.324 0.397 0.175 0.197 38.2 mg/L 0.532 0.732 0.300 0.367 51.1 mg/L 0.855 1.188 0.480 0.602 66.0 mg/L 1.190 1.281 0.621 0.816 At ML=51.1 mg/L, energy requirements varied between 0.480-1.188 kWh/m3 for 4- and 2-cell experiments at an inter-electrode gap of 1 and 2 mm [see Figure 3-8]. Although energy requirements varied greatly, DOC and UV-abs-254 reduction differences were observed to be negligible. Given the results for the pilot-scale studies, a set of preferred N=4,+δ=1+mmN=4,+δ=2+mmN=2,+δ=1+mmN=2,+δ=2+mm0.00.20.40.60.81.01.21.427.838.251.166.0Energy,+kWh/m3Metal+Loading,+mg/L 83 operating parameters could therefore be implemented in order to maximize the energy efficiency of the process without compromising the performance.  As outlined in §3.2.2.3, the greatest reduction in both DOC and UV-abs-254 was obtained using a 4-cell and 1 mm configuration at the highest ML. Conveniently, it is at these conditions that the energy requirements are lowest (with respect to other conditions at the same ML). When operating at these conditions, the energy required per unit of water treated is 0.621 kWh/m3, roughly corresponding to operating costs of $0.0640/m3, based on BC Hydro general business rates for small and medium users ($0.1030/kWh) [54]. It should however be noted that for statistically similar results for both DOC and UV-abs-254 reductions, the same EC efficiency could be achieved at 0.480 kWh/m3 or $0.0494/m3 (operating at N=4, δ=1, ML=51.1 mg/L).  Researchers Carlson et al. (2000) conducted a cost analysis for two enhanced chemical coagulations processes for the removal of NOM [55]. The analysis solely included the cost of chemicals and did not consider any energy costs associated with rapid mixing or slow mixing (flocculation) and coagulant chemical pumping. The analysis was also conducted on a large drinking water treatment process, with an average daily raw water flow of 100,000 m3. The first process involved the use of alum coagulant at a dosage of 90 mg/L. This process was projected to cost $18 USD per 1000 m3 of water treated [60], correlating to $0.0241/m3 in Canadian currency. This cost is roughly half of the estimated operating costs for EC operations. The second process analysis involved alum chemical coagulation at a concentration of 45 mg/L, as well as pH adjustment using sulfuric acid at 22 mg/L. This comparison is not as appropriate as the former process, as the presented EC research purposely avoided pH adjustment in order to keep the process simple. The costs associated with the alum/pH treatment amounted to $13 USD per 1000 m3 of water treated [60]. In Canadian currency, this cost is approximated to be $0.01741/m3. All of the above costs are solely a reflection of the  84 economics involved with the operations of both EC and CC and do not consider capital and equipment costs.  Although the previous cost estimate for EC does not include the cost of the consumable anode electrode, the cold-rolled iron steel used for all experiments is valued at roughly $54/m2, from a national (Canada & US) metal distributor (Metal Supermarkets™). In order to exhaust 90% of a 1 m2 iron electrode, assuming uniform current distribution on the electrode surface, it would take 20.6 days of continuous operation (single cell, ML=51.1 mg/L). At these conditions, a consumable electrode operating cost is estimated to be roughly $2.62/day. It should also be noted that including the anode costs to the overall operating costs for EC further distances the technology from CC operating costs presented above. However, the CC operating expenses do not include transportation and storage costs, as well as energy costs associated with rapid and slow mixing, and coagulant pumping. Incorporating these additional costs associated with CC may make EC comparable or better in terms of operating costs. In addition, suitable communities for the integration of EC would be remote and hard to access, which would greatly increase any shipping costs required to continuously supply a conventional CC process, therefore making EC even more attractive.  An energy requirement comparison to the incumbent water treatment technology, reverse osmosis (RO), will be explored. Reverse osmosis is similar to a filtration process, where a membrane is used to remove contaminants from water; however, it has the ability to remove much smaller dissolved solutes than even an ultrafiltration process. RO is pressure driven, where the semi-permeable membrane uses preferential diffusion for separation; a typical application is for desalination of highly ionized water. Although RO can remove much smaller contaminants than NOM, it should be noted that processes utilizing RO will also require many other RO pre-conditioning unit operations  85 (like coagulation) to minimize fouling of the RO membrane. In order for RO to operate in a seawater desalination process, a theoretical thermodynamic energy requirement minimum of 0.70 kWh/m3 is required [5]. This minimum energy simply accounts for the energy required to reach pressures needed to overcome the pressure balancing the chemical potential between the permeate and retentate (solutions separated by the RO membrane), known as the osmotic pressure. Of course in reality energy requirements for an RO process would far exceed the theoretical minimum of 0.70 kWh/m3. An investigation of 40 desalination plants using RO by Zhao et al. found that, on average, RO required at least 2.25 kWh/m3 [53], roughly four times greater requirements than EC for each cubic meter of water treated.   3.3 Chapter Conclusion In Chapter 3, the efficiency of iron EC for NOM removal was assessed at a pilot-scale, with experiments being undertaken at 10 LPM on raw surface water in the community of Van Anda. It was found that, although results did not reach the maximum DOC and UV-abs-254 reductions achieved at lab-scale using synthetic water and HA, consistent and significant reductions in both parameters were achieved for all conditions tested. Differences in reduction for the two greatest MLs tested were negligible, with an average DOC and UV-abs-254 reduction of 37.2±4.2% and 54.7±0.9%, respectively. The maximum reduction of both parameters was achieved at the highest ML (66.0 mg/L), utilizing a 4-cell and 1 mm inter-electrode gap configuration (DOC/DOC0=42.9±6.6% and UV-abs-254/UV-abs-2540=55.8±0.8%).  Differences in the reduction of DOC and UV-abs-254 in pilot and lab-scale experiments were associated with the initial organic matter compositions. Lab-scale synthetic water experiments were characterized by an initial SUVA of 10.60 L/m!mg, indicating concentrations of predominantly hydrophobic dissolved organic carbon  86 structures, which are more easily removed using EC and CC. Pilot capacity experiments using Priest Lake raw water had an initial SUVA of 2.20 L/m!mg, indicating large NOM fractions composed of small MW hydrophilic dissolved carbon structures with lower charge densities. Despite the challenge of initial water characteristics, EC effectively reduced SUVA to values below 1.75 L/m!mg, a suggested end-point for NOM removal using an EC process.   Through HPSEC analysis, it was found that EC results in preferential removal of larger MW fractions of NOM, a phenomenon that has been documented for both CC and EC in prior research. HPSEC also confirmed mechanisms responsible for variations in DOC and UV-abs-254 trends observed at the two lower MLs tested. It was observed through HPSEC that samples that yielded the greatest removal of DOC, but the poorest reduction in UV-abs-254 were characterized by greater reductions in small MW structures and lower reductions in larger MW structures.   In addition to achieving the greatest reductions in DOC and UV-abs-254, 4-cell and 1 mm gap experiments are also the least energy intensive for each respective ML. At these conditions, operations require 0.621 kWh of energy per cubic meter of water treated at the highest ML. Statistically similar results can be achieved at a lower ML, for a significantly lower energy consumption rate of 0.480 kWh/m3.    87    Chapter 4  Electrode Current Density Mapping  4.1 Chapter Introduction Electrocoagulation has shown promising results for drinking water treatment applications and is considered to be a potential alternative treatment process to traditional chemical coagulation, in particular for small and remote community applications. Although much research has been dedicated to EC’s ability to remove target contaminants, like NOM for this author’s research, not a lot of attention has been directed towards understanding the relationship between the mass transport phenomena of water across an EC electrode surface and its subsequent affect on the electrical current distribution. Furthermore, there is a knowledge gap for understanding the optimization of the electrochemical activity over electrode surfaces during EC operations. In order for EC to be considered and adopted as a potential alternative water treatment technology, optimum electrode performance at an industrial scale would need to be demonstrated; efficient and optimized utilization of the entire electrode will be one of the many important aspects needing to be accomplished.   In prior chapters it was assumed that current density remained constant over the entire electrode surface throughout EC operations (at constant current), although this is likely not realized in practice. In order to understand the variation of current  88 distribution across an electrode surface, an in-situ technique to map current density was employed. From this technique, the current density of various segments of the electrode can be attained. In combination with understanding the water flow patterns through the reactor using computational fluid dynamic (CFD) modeling, the fluid and current flow relationship can be understood. Aside from better understanding the EC reactor used in this work, insight towards future reactor design iterations could be gained, as well as fundamental understanding of current and mass transport considerations for improved and predictable EC operations. Finally, results gained could lead to improved current density distribution and consequently more economical operation.   4.2 Partial Electrode Approach In order to determine the variation of current over an electrode surface during EC operations, a method utilized for the determination of current distribution in proton exchange membrane fuel cells is utilized. This technique of current determination is known as the partial membrane electrode assembly approach [61]. In this current determination method, portions of the electrode surface are masked using an electrically inert adhesive membrane to test independent segments of the electrode. By generating polarization curves, plots of current density and electrode potential, of each individually unmasked segment of the electrode, specific performance of the various regions tested can be determined through the difference of each polarization curve. In this investigation, both vertical and horizontal segments were investigated. The following section will outline the materials and methods utilized during the partial electrode experiments.    89 4.2.1. Materials and Methods  The same reactor used for experiments outlined in Chapters 1 & 2 was used for all current distribution experiments. All experiments were single-cell configurations at inter-electrode gaps of 1, 2 and 10 mm. As with previous experiments, cathode and anode materials were austenitic, face centered cubic crystal, stainless steel alloy (trace chromium and nickel), and A1008 cold-rolled steel iron (trace carbon, manganese, phosphorus and sulfur), respectively. Both the anode and cathode had a16-gauge thickness (1.519 mm) and a single side active surface area of 310.8 cm2. New anode electrodes were used for each experiment. Distilled water with dissolved NaCl to a concentration 0.3225 g/L was used for the inlet waters, to mimic water used in previous experiments (without the addition of humic acid). All experiments were investigated at 1.35 LPM and 10 LPM for all inter-electrode gaps. Similar to the experimental procedures used in the Chapter 2 experiments, inlet water was pumped from a 100 L holding tank to the reactor using a Masterflex I/P Drive and I/P High Performance Head peristaltic pump. Experiments were performed at potentiostatic conditions using a Keithley 2260B-30-72 DC Power Supply. Experiments took place under constant voltage until a stable current was reached and stabilized for at least 30 seconds. During EC operations, voltage and current data were displayed and collected via a custom LabView program (see Appendix B for program block diagram) at a sampling rate of 5.8 Hz. After exiting the electro-active area of the reactor, water flowed into a collection tank for later disposal. The total range of potentials tested were chosen from the ranges that were observed during prior similar EC experiments from Chapter 2 and 3, and are outlined in Table 4-1. The intervals between each potential tested depended on the linearity of the polarization curve; non-linear regions of the polarization curve were examined at small voltage intervals, while linear regions of the curve could be tested at larger voltage intervals.  90 Table 4-1: Voltage ranges investigated for current distribution experiments Flow Rate Inter-Electrode Gap Voltage Range 1.35 LPM 1, 2, 10 mm 0.00 – 10.00 V 10 LPM 1, 2, 10 mm 0.00 – 29.00 V In order to determine the current distribution for each inter-electrode gap and flow rate, the partial electrode method was used. As introduced earlier, the above potentiostatic experiments were performed for seven different electrode configurations. One configuration included the utilization of the entire electrode area: a standard single-cell EC configuration. For the six other configurations, various segments were ‘masked’ using Kapton HN film with silicone adhesive, a polyimide film to reduce the electro-active area of the electrode. Electrodes were masked vertically and horizontally to expose equal ¼, ½, and ¾ segments of the electrode, accounting for the six other electrode configurations, as depicted in Figure 4-1. All configurations and potentials were tested in duplicates. At each voltage, a constant current was reached. The voltage and current data were used to generate polarization curves for each electrode configuration, yielding average current densities for each exposed segment (¼, ½, ¾ vertical and horizontal). The individual performance for each horizontal and vertical quarter segments of the electrode could then be determined by the difference of each polarization curve. For example, subtracting the ¼ vertically exposed segment from the ½ vertically exposed segment provides the specific performance on the second vertical quarter area (labeled “Region B” in Figure 4-2) of the electrode. The same procedure was used for horizontally masked experiments, whereby subtracting the ¼ horizontally exposed segment from the ½ horizontally exposed segment provides the specific performance on the second horizontal quarter area of the electrode (labeled “Region 2” in Figure 4-2). Current distribution results obtained from the partial electrode method were complemented with fluid transport data from CFD models generated using COMSOL Multiphysics. Specific flow  91 regimes and local flow rate variations throughout the EC reactor were modeled with single-phase 3D models. Flow rate patterns in addition to current distribution patterns were compared for potential correlating affects.  Figure 4-1: Schematic drawing of the seven electrode configurations tested  Figure 4-2: Vertical & horizontal electrode regions for current distribution determination   92 4.2.2. Results and Discussion 4.2.2.1. Low Flow Rate Current Distribution Low flow rate (1.35 LPM) experiments were performed for the range of 0 – 10 V, to parallel the voltage range yielded during prior galvanostatic low flow EC experiments [see Chapter 2].  Polarization curves of the cell voltage and current density for the four equal-area vertical and horizontal electrode segments were yielded within this voltage range for all three inter-electrode gaps (1, 2 and 10 mm). Additionally, a CFD model for each inter-electrode gap was constructed to better understand the movement of water between the electrode surfaces.  At 1 mm inter-electrode gap, current density was observed to increase in horizontal segments of the electrode in the y-direction [see Figure 4-2]; from the bottom of the electrode (nearest the inlet) to the top (nearest the outlet), as seen in Figure 4-3. Region 4 attained the greatest current density, followed by Regions 3, 2 and 1, respectively. These results suggest that greater flow velocity exists over the top region, Region 4, of the electrode. In the most ideal circumstances, flow across an electrode surface would be completely uniform to ensure more even current distribution. The fundamental effect of flow velocity on current density will be revisited in detail at the end of this section. Region 4 was observed to out-perform all other horizontal regions of the electrode at inter-electrodes gaps of both 2 and 10 mm as well [see Figure 4-4]. For all three inter-electrode gap conditions, the highest current densities were achieved at the top of the electrode, once again suggesting more uniform flow and/or less ‘dead zones’ (areas of stagnant water). Region 3 was found to have the second highest current densities at an inter-electrode gap of 2 mm, similar to 1 mm conditions. However, contrary to results obtained at 1 mm, Region 1 reached greater current densities than Region 2 during 2  93 mm inter-electrode gap experiments. Furthermore, the differences in current density among Region 1, 2 and 3 were quite small when compared to the current ranges observed at a 1 mm gap. This pattern suggests greater horizontal current uniformity at 2 mm inter-electrode gap versus a 1 mm gap.  Figure 4-3: Low flow rate (1.35 LPM) horizontal segment polarization curves for 1 mm gap   When the inter-electrode gap was increased to 10 mm, although the better performance of Region 4 was consistent with prior gaps, Region 3 was found to have the lowest current density, whereby Regions 1 and 2 had the second and third greatest performance, respectively. Similar to the results obtained with an inter-electrode gap of 2 mm, although the order of current density performance was inconsistent with previous gaps, the absolute range of current densities achieved was much smaller at a 10 mm gap. As seen in Table 4-2, at the expense of a more energy intensive process due to the much greater resistance associated with a larger inter-electrode gap, and consequently lower current densities, greater current uniformity was yielded at 10 mm and it decreased as the inter-electrode gap decreased to 2 and 1 mm. This trend in current 0246810120 10 20 30 40 50Potential(V)Current+Density+(mA/cm2)Region+1Region+2Region+3Region+4Full+ElectrodeIN#OUT#Region#4#Region#3#Region#2#Region#1# Current'Density!Lowest!Highest! 94 uniformity can be attributed to the overall decrease in current density due to increase in resistance, as well as the increased uniformity of water flow across the electrode surface as the inter-electrode gap increased; a phenomenon seen with generated CFD models, which will be discussed further in this section.  Figure 4-4: Low flow rate (1.35 LPM) horizontal segment polarization curves for (a) 2 mm and (b) 10 mm gap (a) (b) 0246810120 10 20 30 40 50Potential(V)Current+Density+(mA/cm2)Region+1Region+2Region+3Region+4Full+ElectrodeIN#OUT#Current'Density!Lowest!Highest!Region#4#Region#3#Region#2#Region#1#0246810120 2 4 6 8 10 12 14Potential(V)Current+Density+(mA/cm2)Region+1Region+2Region+3Region+4Full+ElectrodeIN#OUT#Current'Density!Lowest!Highest!Region#4#Region#3#Region#2#Region#1# 95 Table 4-2: Current density ranges at low flow (1.35 LPM) and 8 V constant cell potential   Full Electrode mA/cm2 Region 1 mA/cm2 Region 2 mA/cm2 Region 3 mA/cm2 Region 4 mA/cm2 1 mm 28.49 23.00 25.24 29.10 36.62 2 mm 25.84 23.11 21.12 25.87 33.23 10 mm 6.67 6.76 5.56 5.01 9.35 In general, a greater range in current distribution was observed during vertically segmented experiments, compared to results yielded for horizontal segments. This general trend suggests that a greater variation in flow rate exists over the length (x-axis) of the electrode, compared to variations existing in a height-wise direction (y-axis). At an inter-electrode gap of 1 mm, no current was observed in Region D (closest to the exit), while the adjacent Region C yielded the greatest current densities [see Figure 4-5].  Figure 4-5: Low flow (1.35 LPM) vertical segment polarization curves for 1 mm gap Regions A and B yielded very similar current density values. The same pattern of current density distribution for operation with a 1 mm inter-electrode gap was also 0246810120 10 20 30 40 50 60 70 80 90 100Potential(V)Current+Density+(mA/cm2)Region+ARegion+BRegion+CRegion+DFull+ElectrodeIN#OUT#Current'Density!Lowest!Highest!Region#A#Region#B#Region#C#Region#D# 96 yielded at a 2 mm gap; however, unlike operation with a 1 mm gap, current was detected in Region D during the 2 mm gap experiments [see Figure 4-6].  When the inter-electrode gap was increased to 10 mm, the patterns of current distribution changed significantly, whereby Region D yielded the greatest current density, followed by Regions A, C and B, respectively [see Figure 4-6]. It should be noted that similar to horizontal segment experiments, the 10 mm inter-electrode gap had a significantly lower current density range compared to the 1 and 2 mm gap conditions. As with horizontally segmented current distribution results, the variations in current density for the vertical segments can be explained using CFD models. Three models seen in Figure 4-7 describe flow through the EC reactor at 1.35 LPM at inter-electrode gaps of 1, 2 and 10 mm. Flow velocity is visually represented by a sliding color scale; dark blue (lowest velocity) to red (highest velocity). Colored streamlines detail the water velocity profile within the reactor, while the arrows describe the direction of water flow. The local velocity profiles and direction of flow are time-dependent, though very little variations exist with respect to time, just minor changes due to turbulence. The models presented in this chapter are the result of 50 seconds of fluid flow through the reactor, in order to represent a pseudo-steady state condition.  It is clear from the CFD models that water velocity through the electro-active area of the EC reactor is in general much greater at smaller inter-electrode gaps and vice versa. This can be attributed to the reactor chamber volumes (volume within the electro-active area of the reactor). When operating at a 1 mm gap, the chamber volume is 31.1 cm3. As the inter-electrode gap increases to 2 and 10 mm, the volume increases to 62.2 and 310.8 cm3, respectively. Due to the different chamber volumes, there is an average reactor residence time of 1.38, 2.76 and 13.8 seconds for 1, 2 and 10 mm inter-electrode gap conditions, respectively.   97  Figure 4-6: Low flow (1.35 LPM) horizontal segment polarization curves for (a) 2 mm and (b) 10 mm gap It is important to note that although the bulk water velocity increases as inter-electrode gaps decreases, greater variations in local flow velocities are encountered at smaller inter-electrode gap conditions (as seen in the CFD models). Therefore, although a greater velocity will desirably yield a greater current density at smaller inter-electrode gaps, current density distribution will be greatly varied due to the inherent local 0246810120 10 20 30 40 50 60Potential(V)Current+Density+(mA/cm2)Region+ARegion+BRegion+CRegion+DFull+ElectrodeIN#OUT#Current'Density!Lowest!Highest!Region#A#Region#B#Region#C#Region#D#0246810120 2 4 6 8 10 12Potential(V)Current+Density+(mA/cm2)Region+ARegion+BRegion+CRegion+DFull+ElectrodeIN#OUT#Current'Density!Lowest!Highest!Region#A#Region#B#Region#C#Region#D#(a) (b)  98 variations in water flow velocity. Contrarily, at larger inter-electrode gaps with greater reactor chamber volumes and residence times, improvement in current distribution will be achieved due to more uniform velocity profiles. However, larger inter-electrode gaps will also yield a slower bulk fluid velocity, and therefore despite improved current distribution, lower current densities will be achieved. It should also be noted that the increase in inter-electrode gap also increases the electrical resistance accounting for the decrease in current density despite improved current uniformity. At a 1 mm gap, Region C recorded the greatest current density. In Figure 4-7 it can been seen that Region C is occupied by a great number of streamlines at a higher velocity than regions adjacent to it (B and D). A similar result is seen for the 2 mm inter-electrode gap model, where lighter blue (high velocity) streamlines occupy Region C, as well as a high density of streamlines on the border of Regions C and D. For both 1 and 2 mm gap experiments, Region D was found to experience the lowest current densities; the CFD models once again support this phenomenon. Especially in the 1 mm gap case, very little water movement is seen to exist in Region D, which can account for the low current densities. Although most water is moving upwards towards the exit of the reactor, water movement nearest the chamber wall in Region D is seen to be moving very slowly downwards. When the inter-electrode gap was increased to 10 mm, the lowest overall current density and smallest range of current densities was observed at constant cell potentials and Region D yielded the greatest performance. From the CFD models, it is clear that the streamlines are a more uniform color describing a more constant flow rate. Consistent with the current distribution results, Regions D and A occupy high density of uniform streamlines, consequently the same regions that yielded the two greatest current densities, respectively.  99  Figure 4-7: CFD generated water velocity profiles for low flow (1.35 LPM) experiments (top) and CFD models with electrode segments overlaid (bottom) As a more detailed current mapping tool, the horizontal and vertical regions can be combined to yield a pixelated view of the electrodes [see “Combined Segments” in Figure 4-2]. The average current densities of a vertical and horizontal segment operating at the same cell potential were averaged to yield the current density of that specific “pixel”. For example, the average current density of Region 1 and Region A would yield the current density of pixel A-1, as shown in Figure 4-2. ! ! !1.8$1.6$1.4$1.2$1.0$0.8$0.6$ Water&Velocity,$m/s$0.4$0.2$0$δ"="1"mm" δ"="2"mm" δ"="10"mm" 100  Figure 4-8: Low flow (1.35 LPM) current distributions for combined segments (horizontal/vertical average) at 8 V From Figure 4-8, it can be reiterated that current was more unevenly distributed at 1 and 2 mm gap conditions, when compared to operation with a 10 mm gap. Although current density was more uniformly distributed at an inter-electrode gap of 10 mm, it was at the expense of significantly reduced current densities and higher energy requirements. The phenomenon of higher fluid velocity yielding greater current densities is one that has been investigated and reported in other electrochemical research. One study investigating the effect of electrolyte flow velocity, pH and temperature on the galvanic corrosion of a carbon steel anode in a cylindrical reactor found that corrosion rates would increase when the flow velocity increased [62]. The researchers confirmed that the increased corrosion rate was due to an increase in anodic current density. Similar research explored the effect of limiting current distribution in a parallel plate electrochemical reactor as a result of mass transport effects and variations caused by a porous net controlling the inter-electrode gap (found in some aqueous-metal batteries) [63],[64]. Through CFD and numerical modeling, the authors found that the spacing net effected velocity profiles, yielding regions of relatively high velocity, and in some cases,  101 regions with no fluid velocity. It was discovered that current density “followed” the velocity profiles. Another researcher investigated the effect of flow velocity through a cylinder on the limiting current density [65]. Experimental current densities were compared to those predicted by theory, under both laminar and turbulent flow regimes. In general, the author found that experimental results were consistent with theoretical results and that as the velocity of bulk flow increased, the current density also increased. The author also noted that as fluid flow transitioned from the laminar to turbulent flow regime, a reduction in the boundary layer thickness resulted, which therefore results in a higher limiting current density.  In theory, the limiting current density can be affected by many factors including fluid velocity [66],[67]. In the EC reactor, mass transport is characterized by both diffusion (near the electrode-solution interface) and forced convection (bulk water flow through the reactor). The small layer dominated by diffusion at the electrode-electrolyte interface is known as the Nernst diffusion layer. The limiting current of a system with diffusion and convection can be calculated with (E.6), which was derived with Fick’s Law of diffusion and a flux balance of a reaction occurring at an electrode surface using Faraday’s law (introduced in Chapter 1) [67]:   :O = CP=NQRQST  (E.6)  Where A, n, F, Di, ci and δN represent the area of the electrode, number of electrons involved in the electrode reaction, Faraday’s constant, diffusivity coefficient of species i, concentration of species i and the Nernst diffusion layer thickness, respectively. Amongst all the variables that can be manipulated to change the limiting current, IL, the effect of velocity will most greatly affect the Nernst diffusion layer thickness. As the  102 velocity of fluid increases, the relative electrode-electrolyte movement is increased, therefore reducing δN and increasing IL [67].  A dimensionless numerical description of the ratio of convective mass transport to the rate of diffusive mass transport is represented with the Sherwood number (Sh). The Sherwood number can be used to characterize the mass transport phenomena through a system, based on the system’s geometry, flow rate and chemical characteristics (kinematic viscosity and diffusivity coefficient). A correlation used to calculate Sh for a parallel-plate, horizontal flow system under fully developed laminar flow conditions is as follows:  [67] Aℎ = 1.85 ∙ ?#Y/[ ∙ ARY/[ ∙ \]7 Y/[ (E.7)  Where Re, Sc, de and L are the Reynolds number, Schmidt number, hydraulic diameter and flow length, respectively. The above correlation (E.7) is used for systems with a Re < 2000, whereas a system in the turbulent flow regime (Re > 2300) use (E.8):  [67] Aℎ = 0.023 ∙ ?#_/` ∙ ARY/[ (E.8)  The Reynolds number (E.9) describes the ratio of inertial forces (causing flow) to viscous forces (impeding flow) in a moving liquid and is calculated with the kinematic viscosity (ν) and linear velocity (u) of the flowing electrolyte, as well as the ‘characteristic length’, which depends on the system’s geometry. In the case involving parallel plate electrodes, the hydraulic diameter (de) is used as the characteristic length, described by (E.10), where B and δ are the width of the electrode and inter-electrode gap, respectively.    103  [67] ?# = a ∙ \]b  (E.9)    [67] \] = 2 ∙ c ∙ Sc + S  (E.10)  The Schmidt number (E.11) represents the ratio of the molecular diffusivities associated with motion (kinematic viscosity, ν) and matter (diffusivity coefficient, D).   [67] AR = dN (E.11)  Two major assumptions were made when characterizing the EC reactor with the aforementioned correlation for Sh through parallel plate electrodes. The first assumption made is the direction of flow; although the EC reactor does involve horizontal flow, a vertical component also exists in the reactor as water moves from the inlet (below the electrodes) to the outlet (above the electrodes). The second assumption made included the flow length used to calculate Sh using (E.7); the flow length was approximated to be the linear direction from the inlet to the outlet (the vector between the x- and y-direction). An additional assumption must be made when interpreting the calculated Sh values; Sh does not provide information on the uniformity of flow, and consequently uniformity of current, over an electrode surface [67].  All inter-electrode gap (1, 2 and 10 mm) geometries yielded Re < 2000 at low flow rate (1.35 LPM) conditions, therefore (E.7) was used to calculate the respective Sh. As previously discussed, ideal mass transport conditions in an electrochemical cell would be characterized by both high and uniform fluid velocity in order to maximize current density and distribution.  Although Sh does not give insight into the current density  104 distribution over the surface of an electrode, it can give insight into overall electrode performance. Since Sh describes the ratio of convective mass transport to the rate of diffusive mass transport as a function of the reactor geometry, it is expected that conditions yielding a greater Sh be more convection dominated compared to conditions with a lower Sh. Therefore, geometries yielding a greater Sh are more desirable in terms of mass transport phenomena, without considering energy requirements and/or cell resistances. The calculated Sherwood numbers for each inter-electrode gap is summarized in Table 4-3.  Table 4-3: Sherwood numbers (Sh) for 1, 2 and 10 mm inter-electrode gap conditions at low flow (1.35 LPM), using a parallel-plate, fully developed horizontal laminar flow correlation. 1 mm 2 mm 10 mm 0.8313 1.0520 1.7100 The calculated Sh values indicated that as the inter-electrode gap increases, the reactor geometry favors convective mass transport over diffusive mass transport. Once again, Sh does not provide insight into the current density distribution and therefore cannot be the sole indicator of an idealized system; the Sh assumes even flow across the electrode. As in the case with 10 mm inter-electrode gap operations, although the mass transport phenomena may be preferred over the 1 and 2 mm gap operations, due to the increased resistance, greatly lower current densities were yielded despite a more uniform distribution.  4.2.2.2. High Flow Rate Current Distribution The same experiments outlined in §4.2.2.1 were repeated at 10 LPM (high flow) within a voltage range of 0 – 29 V that paralleled cell potentials obtained in the pilot-scale EC experiments [see Chapter 3]. From the high flow rate experiments, similar  105 trends in current distribution for both horizontal and vertical segments were observed to those attained during low flow conditions. The following section discusses the current density distribution of vertical and horizontal segments of the electrode at a pilot-scale high flow rate.  At inter-electrode gaps of 1 and 2 mm, the same trend in current density for horizontal electrode segments were yielded [see Figure 4-9]. Similar to low flow experiments, Region 4 was observed to achieve the greatest current densities. Once again, this can be attributed to higher or more uniform water flow over Region 4 in comparison to the other horizontal segments of the electrode. Regions 2 and 1 yielded the next greatest current densities, respectively, for both 1 and 2 mm gap conditions, whereby both regions had similar current density values to the average current density during fully exposed electrode conditions (single-cell experiment). The similar results of 1 and 2 mm conditions can be attributed to the similar water flow patterns through the electro-active area of the EC reaction, as seen in Figure 4-13. A further discussion on the fluid dynamics within the EC reactor at 10 LPM will be elaborated upon further in this section. It should also be noted that although all of the horizontal regions had the same current density trends for the two smallest inter-electrode gaps, a smaller absolute range of current density was experienced during 2 mm gap experiments, once again at the expense of lower overall current densities due to greater resistance.  106   Figure 4-9: High flow (10 LPM) horizontal segment polarization curves for (a) 1 mm and (b) 2 mm gap When the inter-electrode gap increased to 10 mm, different trends were observed, whereby Regions 3 and 1 yielded the two greatest current densities, respectively [see Figure 4-10]. Although this trend did not match those observed for the two smallest inter-electrode gaps, a significantly smaller standard deviation of current densities were 0510152025300 25 50 75 100 125 150 175 200Potential(V)Current+Density+(mA/cm2)Region+1Region+2Region+3Region+4Full+ElectrodeIN#OUT#Current'Density!Lowest!Highest!Region#4#Region#3#Region#2#Region#1#0510152025300 20 40 60 80 100 120 140Potential(V)Current+Density+(mA/cm2)Region+1Region+2Region+3Region+4Full+ElectrodeIN#OUT#Current'Density!Lowest!Highest!Region#4#Region#3#Region#2#Region#1#(a) (b)  107 experienced at 10 mm. While 1 and 2 mm gap conditions yielded an average current density and standard deviation of 75.38±16.80 and 46.80±11.74 mA/cm2 respectively, the 10 mm gap conditions yielded 11.26±2.17 mA/cm2 at 15 V cell potential and consequently greater current distribution uniformity. As with low flow rate experiments, this current uniformity can be attributed to greater flow uniformity and significantly decreased current densities due to significantly increased resistance.  Figure 4-10: High flow (10 LPM) horizontal segment polarization curves for 10 mm gap   Vertical segments at the two smallest inter-electrode gaps also followed the same trend, whereby Regions C and A yielded the two greatest current densities, respectively, while Region D experience the lowest [see Figure 4-11]. These results also match the results obtained for the same inter-electrode gaps at low flow rate [§4.2.2.1]. Like low flow results, higher water velocity is seen to occupy Region C for both 1 and 2 mm gap conditions [see Figure 4-13]. Streamlines representative of slower water movement (dark blue) and downward flowing water are seen to once again occupy Region D, consistent 0510152025300 5 10 15 20 25 30Potential(V)Current+Density+(mA/cm2)Region+1Region+2Region+3Region+4Full+ElectrodeIN#OUT#Current'Density!Lowest!Highest!Region#4#Region#3#Region#2#Region#1# 108 with the results obtained during low flow rate experiments accounting for the low current densities yielded.  Figure 4-11: High flow (10 LPM) vertical segment polarization curves for (a) 1 mm and (b) 2 mm gap Consistent with all other results for both low and high flow rate experiments, at an inter-electrode gap of 10 mm, the trend in current density for vertical segments did 0510152025300 20 40 60 80 100 120 140 160Potential(V)Current+Density+(mA/cm2)Region+ARegion+BRegion+CRegion+DFull+ElectrodeIN#OUT#Current'Density!Lowest!Highest!Region#A#Region#B#Region#C#Region#D#(a) (b) 0510152025300 50 100 150 200 250 300Potential(V)Current+Density+(mA/cm2)Region+ARegion+BRegion+CRegion+DFull+Electrode IN#OUT#Current'Density!Lowest!Highest!Region#A#Region#B#Region#C#Region#D# 109 not match those observed at 1 and 2 mm. However, similar to all other results obtained for 10 mm inter-electrode gap conditions, current density ranges were found to be very small when compared to other gap distances. Regions A and B were observed to yield the maximum and minimum current densities, with only a 7.74 mA/cm2 difference at a cell potential of 15 V. Regions A and C yielded very similar current densities, which parallel the CFD results. From Figure 4-13, it can be seen that very uniform flow patterns and velocities exist over these two regions. It is also important to note that Region B is predominantly occupied by more stagnant water due to the downward travelling water in Region A and upward travelling water in Regions C and D. These fluid dynamics help to explain the low current density values yielded for Region B.  Figure 4-12: High flow (10 LPM) vertical segment polarization curves for 10 mm gap By qualitatively assessing the high flow CFD models [see Figure 4-13], it can easily be seen that a significantly more uniform flow distribution occurs during 10 mm gap conditions, supporting the current distribution results for both vertical and horizontal segment experiments discussed earlier. At a 1 mm gap, the CFD models 0510152025300 5 10 15 20 25 30 35Potential(V)Current+Density+(mA/cm2)Region+ARegion+BRegion+CRegion+DFull+ElectrodeIN#OUT#Current'Density!Lowest!Highest!Region#A#Region#B#Region#C#Region#D# 110 indicate a more variant flow distribution throughout the reactor chamber when compared to all other gap distances, once again agreeing with current distribution results. In particular, greater fluid velocity is seen to occur in Regions C and A for 1 and 2 mm gap models, the regions that were found to have the greatest current densities, respectively. It can also be observed that a more uniform flow pattern, and in some cases slightly higher velocities, increase in a vertical direction of the electrode (closer to the reactor’s exit). This once again supports the horizontal segment results discussed earlier. Figure 4-13: CFD generated water velocity profiles for high flow (10 LPM) experiments (top) and CFD models with electrode segments overlaid (bottom) !!!12#10#8#6#4#2#0#Water&Velocity,#m/s#δ"="1"mm" δ"="2"mm" δ"="10"mm" 111 Once again, the average current density of each horizontal and vertical segment is calculated, in order to yield a rough two dimensional current distribution map over the electrode surface [see Figure 4-14]. The combined segments for all inter-electrode gap conditions confirm earlier discussed results, as well as parallel the results obtained during low flow experiments. In general, it can be seen that the greatest current density variations exist at a 1 mm inter-electrode gap. Current density variations reduce as the inter-electrode gap increases to 2 mm, while current variations are minimal during 10 mm gap conditions.  Figure 4-14: High flow (10 LPM) current distributions for combined segments (horizontal/vertical average) Although current density uniformity is maximized as the inter-electrode gap increases, the current density of the system is greatly reduced due to greater cell resistance.  From Figure 4-14, the effect of x-direction (vertical segments) flow variation has a clear effect on current distribution. For the 1 and 2 mm inter-electrode gaps, a pronounced region of high current density is seen (Region C). In practice, these current density ‘hot spots’ could have detrimental effects on the economy of the process, as it is these areas that will be exhausted of materials first (i.e., increase dissolution of the Fe),  112 potentially rendering the entire electrode unusable. If current is distributed evenly across the entire electrode, materials will corrode evenly and therefore the lifetime of the electrodes is maximized.  Sherwood correlations were once again used to understand the ratio of convective mass transport to diffusive mass transport at the increased flow rate. At 10 LPM, the Reynolds numbers for all three inter-electrode gaps were in the turbulent flow regime (Re > 2300), therefore (E.8) was used to calculate Sh. Calculated Sh values for each inter-electrode gap is summarized in Table 4-4.  Table 4-4: Sherwood numbers (Sh) for 1, 2 and 10 mm inter-electrode gap conditions at high flow (10 LPM), using a parallel-plate, turbulent flow correlation 1 mm 2 mm 10 mm 4.3397 4.3623 4.1039 Using the turbulent flow correlation, the determining factor of the Sh value was the Re of the system. Since the 2 mm inter-electrode gap geometry yielded the greatest Re, it consequently yielded the greatest Sh. This indicates that in theory, the 2 mm inter-electrode gap condition at 10 LPM has greater rate of convective mass transport to diffusive mass transport, compared to 1 and 10 mm inter-electrode gap conditions. From the CFD models it can be seen that the 2 mm gap yielded more turbulent flow with a large eddy near the inlet of the reactor, agreeing with the calculated Sh. Although the 2 mm inter-electrode gap yielded the greatest Sh, the 1 mm inter-electrode gap yielded very similar results, suggesting that the two reactor conditions theoretically operate similarly with respect to mass transport phenomena. Experimental and CFD model results both confirm the calculated Sh values. In addition to similar fluid flow patterns and velocity variations at 1 and 2 mm inter-electrode gaps, current density trends for the vertical and horizontal electrode segments were the same at both inter-electrode gaps. In general, Sh values for 10 LPM conditions greatly exceeded the Sh values  113 calculated for low flow experiments. This is to be expected, as the flow velocity increases and consequently decreases the Nernst diffusion layer, thereby decreasing diffusive mass transport.  When comparing low and high flow rate polarization curves, it would be expected that higher flow rate conditions yield greater current densities based on the aforementioned mass transport effects. For 1 mm inter-electrode experiments, this hypothesis is confirmed; single cell electrode and individual horizontal and vertical electrode segments yielded greater current densities at constant voltages, in almost all cases. Experiments operating at 2 and 10 mm inter-electrode gap conditions however did not follow the expected trend. For nearly all electrode segments investigated, greater current densities were observed at low flow rate experiments. This loss of performance at a high flow rate, in spite of increased convective mass transport, may suggest a reduction in the limiting current due to increased resistance. Resistance loss can be due to a number of variables, but those that may be more likely to occur during higher flow rate experiments include a decrease in the active electrode area and/or the increase of ‘gas blinding’ [67]. The active electrode area may decrease during high flow rate operations due to the local velocity variations in the electro-active area, as previously discussed. As turbulence in the reactor increases (consequently increasing Re and Sh), one could expect to have more ideal conditions due the greater ratio of convective mass transport to diffusive mass transport, although some detrimental effects may also arise. If the turbulence through the reactor create stagnant water due to eddies, the active electrode area will decrease due to current distributing to non-stagnant regions of the electrode. For example, the CFD models for 2 mm inter-electrode gap conditions at low and high flow rate are shown in Figure 4-15. A large eddy is observed in the high flow rate CFD model, yielding a large area of very slow moving water, effectively decreasing  114 the electrode area and increasing the resistance of the system. In the low flow CFD model, a smaller area of the electrode is occupied by stagnant water.  Figure 4-15: CFD generated water velocity profiles for 2 mm inter-electrode gap conditions at: (a) low flow (1.35 LPM) and, (b) high flow (10 LPM) experiments The introduction and obstruction of the electrode surface with gas bubbles may also increase the cell resistance; this phenomenon is known as ‘gas blinding’. Gas bubbles may enter the electro-active area of the reactor through the electrochemical synthesis of H2 and/or O2 at the cathode and anode respectively, or enter with the water being pumped into the reactor. The introduction of gas into the reactor may be more likely to happen at a higher flow rate due to aeration, as water travels through the reactor inlet channel, baffle and electro-active area much more violently when compared to the fully developed laminar flow observed at low flow rate experiments.  4.3 Chapter Conclusion In Chapter 4, the current density distribution over the electrode surface was determined for 1, 2 and 10 mm inter-electrode gap conditions using the partial electrode (a) (b)  115 method. This in-situ technique of current density determination allowed for the investigation of the previously utilized EC reactor at bench- and pilot-scale flow rates. To complement and help explain the yielded current density results, CFD models were generated to evaluate the flow pattern and velocity changes for the various inter-electrode gaps and flow rates. Low and high flow experiments were in good agreement for both horizontal and vertical segments. Both flow rates saw increased current uniformity with the increase of the inter-electrode gap, at the expense of reduced overall current densities (due to Ohmic losses). From the CFD models, fluid flow uniformity was also observed to increase with an increasing inter-electrode gap, helping to explain the current density results. In general, regions of the electrode that were occupied by higher velocity or more uniform flow also had comparatively greater current densities. In contrast, regions of the electrode that were seen to have low flow velocity or non-uniformity tended to yield lower current densities.  Although current distribution is maximized at an inter-electrode gap of 10 mm (for both low and high flow rates), the reduction in current density greatly increases the energy requirements of the process. From these results, it is clear that future design iterations for EC reactors should carefully consider the fluid dynamics of the system in order to maximize both current densities and current distribution. Areas of the electrode experiencing greater current densities will be exhausted more quickly. In practice, this could have severe economical effects on the process, as more frequent electrode replacements may be required.    116    Chapter 5  Conclusion  This thesis investigated the electrochemical water treatment technology of electrocoagulation, for the removal of NOM from surface water. EC experiments began at a bench scale (1.35 and 5 LPM) in the laboratory and were scaled-up to a pilot-capacity. Pilot field experiments took place in Van Anda, Texada Island (British Columbia) at 10 LPM using the community’s drinking water supply in Priest Lake. A further investigation was directed towards understanding the electrical current distribution on the electrode surface during EC operations using the partial electrode method. Results of all experiments are summarized in the following section.  5.1 Summary of Results The efficacy of iron EC for the removal of HA was first investigated at bench-scale low and medium flow rates of 1.35 and 5 LPM. Four variables were monitored: flocculation time, metal loading, current density and inter-electrode gap. The following outline the key research outcomes from the in-lab, bench-scale EC experiments: •! At both flow rates, flocculation time was found to have no effect on DOC or UV-abs-254 reductions.   117 •! Clear trends in both DOC and UV-abs-254 were unable to be determined with respect to inter-electrode gap and current density. A number of unmonitored factors could be responsible for the results yielded, such as effect of DO, pH and iron speciation effects.  •! Metal loading was found to have the greatest impact on HA removal, with respect to all other variables tested. A clear trend of increased reductions in both DOC and UV-abs-254 were yielded with increased ML. Increases in UV-abs-254 were observed initially at lower MLs, which was confirmed to be due to the presence of high dissolved residual iron concentrations after filtration using AA-spectroscopy.  •! High chloride and humic concentrations were found to function as ligands increasing the solubility of iron, thereby providing the mechanism contributing to the high concentrations of dissolved iron present after EC at lower MLs. •! The EC process has a low energy footprint, whereby the conditions providing the great reductions in DOC and UV-abs-254 at the highest ML also tended to be the least energy intensive (low current density and inter-electrode gap).    After the bench-scale investigation, EC was assessed at a pilot-scale with experiments being undertaken at 10 LPM on raw surface water in the community of VAID. Although results did not reach the maximum DOC and UV-abs-254 reductions achieved at lab-scale, consistent reductions in both parameters were achieved for all conditions tested. The following outline the key research outcomes achieved during pilot-scale experiments: •! Reduction differences at the greatest two MLs tested were negligible, with an average DOC and UV-abs-254 reduction of 37.2±4.2% and 54.7±0.9%, respectively.   118 •! SUVA reductions as low as 1.71 L/m!mg were achieved from an initial SUVA of 2.20 L/m!mg, reaching previously published minimum values suggested as being feasible using EC •! The maximum reductions in DOC and UV-abs-254 were achieved at the highest ML, utilizing a 4-cell configuration and 1 mm inter-electrode gap (DOC/DOC0=42.9±6.6% and UV-abs-254/UV-abs-2540=55.8±0.8%).  •! Through HPSEC analysis, it was found that EC has preferential removal of larger MW fractions of NOM, a phenomenon that has been documented for both CC and EC in prior research.  •! The conditions which achieved the greatest reductions in DOC and UV-abs-254 (4-cell, 1 mm gap) were also the least energy intensive. At these conditions, operations require 0.621 kWh of energy per cubic meter of water treated. Statistically similar results can be achieved at a lower ML, for a significantly lower energy consumption rate of 0.480 kWh/m3.  Current density distribution over the electrode surfaces was determined for 1, 2 and 10 mm inter-electrode gap conditions using the partial electrode method. This in-situ technique of current density determination was utilized in order to investigate the reactor and configurations utilized during bench- and pilot-scale experiments. CFD models were generated to evaluate the water velocity patterns for the various inter-electrode gaps and flow rates. The following outline the key research outcomes achieved from utilizing the partial electrode method for current distribution determination: •! 1.35 and 5 LPM flow rate experiments were in good agreement for both horizontal and vertical segments.  •! At both flow rates, increased current uniformity was observed with an increase of the inter-electrode gap, at the expense of reduced overall current densities.   119 •! CFD models showed fluid flow uniformity also increased with an increasing inter-electrode gap.  •! In general, regions of the electrode that were occupied by higher velocity or more uniform flow also achieved greater current densities. In contrast, regions of the electrode that were occupied by low flow velocity or non-uniformity tended to yield lower current densities.  •! Although current distribution was maximized at an inter-electrode gap of 10 mm, the reduction in current density greatly increased the energy requirements of the process.  •! Future design iterations for the EC reactor should more carefully consider the fluid dynamics of the system in order to maximize both current densities and current distribution. In practice, areas of highly undistributed flow and consequently highly variable current during continuous EC operations could repeatedly exhaust certain areas of an electrode. This would create a greater operating cost, due to more frequent electrode replacement.  From the aforementioned results and experimental outcomes, the project has yielded a variety of advancements in the field of electrocoagulation. From the scale-up work and eventual integration into a drinking water pilot-plant, proof of concept for NOM removal in a continuously operating drinking water treatment process was demonstrated. The technology achieved adequate reductions of NOM with comparatively low power requirements with respect to conventional chemical coagulation and incumbent water treatment technologies like reverse osmosis. For the first time in EC research, current density distribution was demonstrated and taken in to consideration. The results demonstrated that a large variation in current distribution exists, a phenomenon overlooked by prior EC research. This knowledge provides  120 impactful insight into EC reactor design and efficiency, a realistic image of operating current densities, as well as provides an in-situ process by which future researchers can determine current distribution during an EC process.   5.2 Recommended Future Work Based on promising results achieved in this research, further work in the area of iron electrocoagulation is recommended in order to continue to evaluate the technology’s viability as a drinking water treatment for remote community applications. Below are recommended areas for further research pursuits: •! Research directed towards the in-situ determination of iron hydr(oxide) speciation during EC operations is recommended to further understand some of the variations in the yielded DOC and UV-abs-254 results. There are many factors that will affect the predominating species being synthesized, understanding the species present would give greater insight into trends in contaminant reductions.  •! Prior EC speciation research has found that iron hydr(oxide) species have a varying affinity for contaminant removal [20]. Research investigating a variety of species and their effect on varying contaminants could provide insight for targeted contaminant removal. Process conditions could be adjusted to selectively produce a desired species for greater removal of a certain contaminant.   •! A potentially powerful treatment technology for remote community applications could be the coupled process of EC and electro-ferration – the electrochemical synthesis of highly oxidative iron hydro(oxide) species known as ferrates. This would combine an advanced oxidation process with a coagulation process. Techniques utilizing the iron introduced to the water through EC for the formation of ferrate species in neutral pH water are possible. Further research  121 into the combination of these two processes present an exciting avenue for future EC research. •! It is recommended that future EC research include the addition of chloride into raw surface water to confirm the effect of chloride on increased residual iron concentrations and consequently increased UV-abs-254 obtained using synthetic surface water. •! From the results outlined in Chapter 4, it is recommended that a thorough investigation directed towards reactor design be undertaken. With the gained insight describing the effect of water flow on current density distribution, optimal EC reactor designs targeting current uniformity, while minimizing cell potentials should be explored.  •! Continued piloting at various surface water sources is essential for the continued efforts in confirming the viability of EC for small community applications. Pilot work should focus on contaminant removal efficiency with respect to various water matrices, as well as scaling-up capacity to >30 LPM.    122      Bibliography  [1] Governmetn of Canada, “Status of Off-Grid/Remote Communities in Canada,” Ottawa, 2011. [2] E. Lui, “On Notice for a Drinking Water Crisis in Canada,” Ottawa, 2015. [3] M. Kot, G. A. Gagnon, and H. Castleden, “Water compliance challenges: How do Canadian small water systems respond?,” Water Policy, vol. 17, no. 2, pp. 349–369, 2015. [4] K. Bakker and C. Cook, “Water governance in Canada: Innovation and fragmentation,” Int. J. Water Resour. Dev., vol. 27, no. 2, pp. 275–289, 2011. [5] J. C. Crittenden, Trussell, D. W. Hand, K. J. Howe, and G. Tchobanoglous, MWH’s Water Treatment: Principles and Design: Third Edition. 2012. [6] M. Y. Mollah, R. Schennach, J. R. Parga, and D. L. Cocke, “Electrocoagulation (EC)--science and applications.,” J. Hazard. Mater., vol. 84, no. 1, pp. 29–41, Jun. 2001. [7] D. Wang, J. R. Bolton, S. A. Andrews, and R. Hofmann, “Formation of disinfection by-products in the ultraviolet/chlorine advanced oxidation process,” Sci. Total Environ., vol. 518–519, pp. 49–57, 2015. [8] S. D. Richardson, M. J. Plewa, E. D. Wagner, R. Schoeny, and D. M. DeMarini, “Occurrence, genotoxicity, and carcinogenicity of regulated and emerging disinfection by-products in drinking water: A review and roadmap for research,” Mutat. Res., vol. 636, no. 1–3, pp. 178–242, 2007. [9] U. von Gunten and J. Hoigne, “Bromate Formation during Ozonation of Bromide-Containing Waters: Interaction of Ozone and Hydroxyl Radical Reactions,” vol. 28, no. 7, pp. 1234–1242, 1994.  123 [10] J. Wilson, J. Aramini, S. Clarke, M. Novotny, M. Quist, and V. Keegan, “Retrospective Surveillance for Drinking Water - Related Illnesses in Canada,” Final Report. Novometrix Research Inc., Moffat, ON., 2009. . [11] M. Kot, H. Castleden, and G. A. Gagnon, “Unintended consequences of regulating drinking water in rural Canadian communities: Examples from Atlantic Canada,” Heal. Place, vol. 17, no. 5, pp. 1030–1037, 2011. [12] H. Haider, R. Sadiq, and S. Tesfamariam, “Performance indicators for small- and medium-sized water supply systems$: a review,” Environ. Rev., vol. 22, no. March, pp. 1–40, 2014. [13] D. A. Forrer, M. Zimmerman, and A. Mannix, “Water Issues that Affect Affordability and Safety in a Community: the Camden Ohio Experience,” J. Bus. Case Stud., vol. 9, no. 1, pp. 63–74, 2013. [14] G. L. Rupp, “The challenges of installing innovative treatment in small water systems,” Environ. Heal., vol. July/Augus, pp. 22–25, 2001. [15] Z. Gu, Z. Liao, M. Schulz, J. R. Davis, J. C. Baygents, and J. Farrell, “Estimating dosing rates and energy consumption for electrocoagulation using Iron and aluminum electrodes,” Ind. Eng. Chem. Res., vol. 48, no. 6, pp. 3112–3117, 2009. [16] P. Vanýsek, CRC Handbook of Chemistry and Physics, 87th Edition, 87th ed. Boca Raton, FL: CRC Press, 2006. [17] K. L. Dubrawski, M. Fauvel, and M. Mohseni, “Metal type and natural organic matter source for direct filtration electrocoagulation of drinking water.,” J. Hazard. Mater., vol. 244–245, pp. 135–41, Jan. 2013. [18] K. L. Dubrawski, “Reactor design parameters, in-situ speciation identification, and potential balance modeling for natural organic matter removal by electrocoagulation,” University of British Columbia, 2012. [19] R. M. Cornell and U. Schwertmann, The Iron Oxides: Structure, Properties, Reactions, Occurrences and Uses, vol. 39, no. 8. 2003. [20] K. L. Dubrawski and M. Mohseni, “In-situ identification of iron electrocoagulation speciation and application for natural organic matter (NOM) removal.,” Water Res., vol. 47, no. 14, pp. 5371–80, Sep. 2013. [21] H. A. Moreno-Casillas, D. L. Cocke, J. A. G. Gomes, P. Morkovsky, J. R. Parga, and E. Peterson, “Electrocoagulation mechanism for COD removal,” Sep. Purif. Technol., vol. 56, no. 2, pp. 204–211, 2007.  124 [22] M. Pourbaix, Atlas of Electrochemical Equilibria in Aqueous Solutions, 2nd ed. Houston, TX: National Association of Corrosion Engineers, 1974. [23] T. H. Kim, C. Park, E. B. Shin, and S. Kim, “Decolorization of disperse and reactive dyes by continuous electrocoagulation process,” Desalination, vol. 150, no. 2, pp. 165–175, 2002. [24] A. S. Koparal, Y. Ş. Yildiz, B. Keskinler, and N. Demircioǧlu, “Effect of initial pH on the removal of humic substances from wastewater by electrocoagulation,” Sep. Purif. Technol., vol. 59, no. 2, pp. 175–182, 2008. [25] Y. Ş. Yildiz, A. S. Koparal, and B. Keskinler, “Effect of initial pH and supporting electrolyte on the treatment of water containing high concentration of humic substances by electrocoagulation,” Chem. Eng. J., vol. 138, no. 1–3, pp. 63–72, 2008. [26] N. Esmaeilirad, K. Carlson, and P. Omur Ozbek, “Influence of softening sequencing on electrocoagulation treatment of produced water,” J. Hazard. Mater., vol. 283, pp. 721–729, 2015. [27] N. Mameri, A. R. Yeddou, H. Lounici, D. Belhocine, H. Grib, and B. Bariou, “Defluoridation of septentrional Sahara water of north Africa by electrocoagulation process using bipolar aluminium electrodes,” Water Res., vol. 32, no. 5, pp. 1604–1612, 1998. [28] N. Mameri, H. Lounici, D. Belhocine, H. Grib, D. L. Piron, and Y. Yahiat, “Defluoridation of Sahara water by small plant electrocoagulation using bipolar aluminium electrodes,” Sep. Purif. Technol., vol. 24, no. 1–2, pp. 113–119, 2001. [29] J. Zhu, H. Zhao, and J. Ni, “Fluoride distribution in electrocoagulation defluoridation process,” Sep. Purif. Technol., vol. 56, no. 2, pp. 184–191, Aug. 2007. [30] P. K. Holt, G. W. Barton, M. Wark, and C. A. Mitchell, “A quantitative comparison between chemical dosing and electrocoagulation,” vol. 211, no. 2002, pp. 233–248, 2002. [31] S. E. A. Addy, “Electrochemical Arsenic remediation for Rural Bangladesh,” University of California, Berkeley, 2008. [32] E. a. Vik, D. a. Carlson, A. S. Eikum, and E. T. Gjessing, “Electrocoagulation of potable water,” Water Res., vol. 18, no. 11, pp. 1355–1360, Jan. 1984. [33] J. Q. Jiang, N. Graham, C. Andr??, G. H. Kelsall, and N. Brandon, “Laboratory  125 study of electro-coagulation-flotation for water treatment,” Water Res., vol. 36, no. 16, pp. 4064–4078, 2002. [34] K. L. Dubrawski and M. Mohseni, “Standardizing electrocoagulation reactor design: iron electrodes for NOM removal.,” Chemosphere, vol. 91, no. 1, pp. 55–60, Mar. 2013. [35] K. L. Dubrawski, C. Du, and M. Mohseni, “General potential-current model and validation for electrocoagulation,” Electrochim. Acta, vol. 129, pp. 187–195, 2014. [36] X. Chen, G. Chen, and P. L. Yue, “Investigation on the electrolysis voltage of electrocoagulation,” Chem. Eng. Sci., vol. 57, no. 13, pp. 2449–2455, Jul. 2002. [37] M. Ben Sasson, W. Calmano, and A. Adin, “Iron-oxidation processes in an electroflocculation (electrocoagulation) cell,” J. Hazard. Mater., vol. 171, no. 1–3, pp. 704–709, 2009. [38] Department of Environment and Conservation (Newfoundland Labrador), “Study on Characteristics and Removal of Natural Organic Matter in Drinking Water Systems in Newfoundland and Labrador,” 2011. [39] E. E. Lavonen, M. Gonsior, L. J. Tranvik, P. Schmitt-Kopplin, and S. J. K??hler, “Selective chlorination of natural Organic Matter: Identification of previously unknown disinfection byproducts,” Environ. Sci. Technol., vol. 47, no. 5, pp. 2264–2271, 2013. [40] S. Richardson, “Disinfection by-products and other emerging contaminants in drinking water,” TrAC Trends Anal. Chem., vol. 22, no. 10, pp. 666–684, 2003. [41] H. R. Schulten and M. Schnitzer, “A state of the art structural concept for humic substances,” Naturwissenschaften, vol. 80, no. 1, pp. 29–30, 1993. [42] R. L. Malcolm, “Concentration and composition of dissolved organic carbon in soils, streams, and groundwaters,” Spec. Publ. R. Soc. Chem., vol. 193, pp. 19–29, 1993. [43] F. J. Stevenson, Humus Chemistry: Genesis, Composition, Reactions. 1994. [44] S. Vasudevan, J. Jayaraj, J. Lakshmi, and G. Sozhan, “Removal of iron from drinking water by electrocoagulation: Adsorption and kinetics studies,” Korean J. Chem. Eng., vol. 26, no. 4, pp. 1–7, 2009. [45] K. L. Dubrawski, C. M. Van Genuchten, C. Delaire, S. E. Amrose, A. J. Gadgil, and M. Mohseni, “Production and transformation of mixed-valent nanoparticles generated by Fe(0) electrocoagulation,” Environ. Sci. Technol., vol. 49, no. 4, pp.  126 2171–2179, 2015. [46] Health Canada, Guidelines for Canadian Drinking Water Quality. Canada, 2014, p. 22. [47] K. Kaiser and W. Zech, “Dissolved Organic Matter sorption by mineral constituents of subsoil clay fractions,” J. Plant Nutr. Soil Sci., vol. 163, no. 5, pp. 531–535, 2000. [48] C. R. Evanko and D. A. Dzombak, “Surface complexation modeling of organic acid sorption to goethite,” J. Colloid Interface Sci., vol. 214, no. 2, pp. 189–206, 1999. [49] C. R. Evanko and D. A. Dzombak, “Influence of structural features on sorption of NOM-analogue organic acids to goethite,” Environ. Sci. Technol., vol. 32, no. 19, pp. 2846–2855, 1998. [50] M. J. Avena and L. K. Koopal, “Kinetics of humic acid adsorption at solid-water interfaces,” Environ. Sci. Technol., vol. 33, no. 16, pp. 2739–2744, 1999. [51] M. J. Avena and L. K. Koopal, “Desorption of Humic Acids from an Iron Oxide Surface,” Environ. Sci. Technol., vol. 32, no. 17, pp. 2572–2577, 1998. [52] E. M. Murphy, J. M. Zachara, S. C. Smith, and J. L. Phillips, “The Sorption of Humic Acid to Mineral Surfaces and Their Role in Contaminant Binding,” Sci. Total Environ., vol. 118, pp. 413–423, 1991. [53] R. Zhao, S. Porada, P. M. Biesheuvel, and A. Van der Wal, “Energy consumption in membrane capacitive deionization for different water recoveries and flow rates, and comparison with reverse osmosis,” Desalination, vol. 330, pp. 35–41, 2013. [54] BC Hydro, “General Service Business Rates,” 2016. [Online]. Available: https://www.bchydro.com/accounts-billing/rates-energy-use/electricity-rates/business-rates.html. [Accessed: 30-Apr-2016]. [55] K. Carlson, S. Via, B. Bellamy, M. Carlson, and K. Carlson, “Secondary effects of enhanced coagulation and softening,” J. Am. Water Work. Assoc., vol. 92, no. 6, pp. 63–75, 2000. [56] J. K. Edzwald, “Coagulation in drinking water treatment: Particles, organics and coagulants,” in Water Science and Technology, 1993, vol. 27, no. 11, pp. 21–35. [57] J. K. Edzwald, “Coagulation concepts for removal of TOC,” in AWWA WQTC, 1994.  127 [58] G. L. Amy, “Using NOM Characterization for the Evaluation of Treatment,” in AWWA Proceedgins Workshop of NOM in Drinking Water, 1993. [59] S. . Randtke, “Coagulation of NOM: An Overview of the Science and US Practice,” in AWWA Proceedgins Workshop of NOM in Drinking Water, 1993. [60] J. Bratby, Coagulation and Flocculation in Water and Wastewater Treatment, vol. 2nd. IWA Publising, 2006. [61] J. Stumper, S. A. Campbell, D. P. Wilkinson, M. C. Johnson, and M. Davis, “In-situ methods for the determination of current distributions in PEM fuel cells,” Electrochim. Acta, vol. 43, no. 24, pp. 3773–3783, 1998. [62] J. G. Kim, Y. S. Choi, H. D. Lee, and W. S. Chung, “Effects of flow velocity, pH, and temperature on galvanic corrosion in alkaline-chloride solutions,” Corrosion, vol. 59, no. 2, pp. 121–129, 2003. [63] M. Venkatraman and J. W. Van Zee, “Effect of a net on the limiting current distribution in a parallel plate electrochemical reactor. Part I: Individual Effects,” J. Appl. Electrochem., vol. 39, no. 9, pp. 1425–1436, 2009. [64] M. Venkatraman and J. W. Van Zee, “Effect of a net on the limiting current distribution in a parallel plate electrochemical reactor. Part II: Combined effects,” J. Appl. Electrochem., vol. 39, no. 9, pp. 1437–1442, 2009. [65] T.-J. Wang, “An Aspect of the Limiting Current Density Along the Circumference of s Steel Cylinder by the Effect of the Flow Velocity,” Florida Atlantic University, 1986. [66] A. J. Bard, L. R. Faulkner, N. York, C. @bullet, W. Brisbane, and S. E. Toronto, ELECTROCHEMICAL METHODS Fundamentals and Applications, 2nd ed. New York: John Wiley & Sons, Inc., 1944. [67] F. Walsh, A First Course in Electrochemical Engineering. Hants, England: The Electrochemical Consultancy, 1993.  128    Appendix A  Raw Experimental Data  A.1 Low Flow Electrocoagulation Raw Data Table A-1: Low flow (1.35 LPM) EC experiment: I=2A, ML=25.5mg/L, N=1, δ=1mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 11.03 ± 0.02 1.1020 ± 0.009 2.5 0 5.931 ± 1 2.1374 ± 0.2 5 6.006 ± 2 2.0771 ± 0.3 30 5.186 ± 0.4 2.0332 ± 0.2 60 6.449 ± 1 2.1315 ± 0.2  Table A-2: Low flow (1.35 LPM) EC experiment: I=3A, ML=38.3mg/L, N=1, δ=1mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 11.03 ± 0.02 1.1020 ± 0.009 3.3 0 1.623 ± 0.1 1.6707 ± 0.1 5 2.322 ± 0.8 1.8696 ± 0.3 30 3.058 ± 0.2 2.0319 ± 0.1 60 2.118 ± 0.5 1.8573 ± 0.1     129 Table A-3: Low flow (1.35 LPM) EC experiment: I=4A, ML=51.1mg/L, N=1, δ=1mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 11.03 ± 0.02 1.1020 ± 0.009 3.8 0 0.980 ± 0.1 1.0860 ± 0.01 5 1.013 ± 0.1 1.2377 ± 0.3 30 1.042 ± 0.2 1.1772 ± 0.4 60 0.910 ± 0.2 1.0926 ± 0.4  Table A-4: Low flow (1.35 LPM) EC experiment: I=5A, ML=63.8mg/L, N=1, δ=1mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 11.03 ± 0.02 1.1020 ± 0.009 5.3 0 1.766 ± 0.09 0.2971 ± 0.01 5 2.065 ± 0.04 0.2869 ± 0.01 30 2.108 ± 0.01 0.3245 ± 0.02 60 2.390 ± 0.08 0.2708 ±0.03  Table A-5: Low flow (1.35 LPM) EC experiment: I=2A, ML=25.5mg/L, N=1, δ=2mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 9.567 ± 1 1.0818 ± 0.006 3.1 0 7.836 ±  0.3 2.4062 ±  0.04 5 7.062 2.4081 ±  0.08 30 6.723 2.3839 ±  0.09 60 7.156 2.3811 ± 0.001  Table A-6: Low flow (1.35 LPM) EC experiment: I=3A, ML=38.3mg/L, N=1, δ=2mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 9.567 ± 1 1.0818 ± 0.006 4.0 0 2.002 ±  0.3 1.9437 ±  0.3 5 2.784 2.1036±  0.3 30 3.789 1.9475 ±  0.04 60 4.539 2.0085 ±  0.2     130 Table A-7: Low flow (1.35 LPM) EC experiment: I=4A, ML=51.1mg/L, N=1, δ=2mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 9.567 ± 1 1.0818 ± 0.006 5.0 0 1.549 ±  1.6 0.6032 ± 0.3 5 1.246± 0.01 0.9360 ± 0.1 30 1.315 ± 0.01 0.9404 ± 0.1 60 0.849 ± 0.6 0.9693±  0.04  Table A-8: Low flow (1.35 LPM) EC experiment: I=5A, ML=63.8mg/L, N=1, δ=3mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 9.567 ± 1 1.0818 ± 0.006 5.8 0 2.495 ± 0.8 0.3276 ± 0.1 5 1.649 0.3809 ± 0.2 30 1.886 0.3678 ± 0.2 60 1.817 0.3947 ± 0.1  Table A-9: Low flow (1.35 LPM) EC experiment: I=2A,ML=25.5mg/L,N=1,δ=10mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 13.61 ± 0.9 1.3063 ± 0.002 8.91 0 11.37 ± 2 1.4646 ± 0.2  Table A-10: Low flow (1.35 LPM) EC experiment: I=3A,ML=38.3mg/L,N=1,δ=10mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 13.61 ± 0.9 1.3063 ± 0.002 12.44 0 10.27 ± 0.2 1.5983  0.06  Table A-11: Low flow (1.35 LPM) EC experiment: I=4A,ML=51.1mg/L,N=1,δ=10mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 13.61 ± 0.9 1.3063 ± 0.002 15.76 0 7.430 ± 0.2 1.4512  0.1   131 Table A-12: Low flow (1.35 LPM) EC experiment: I=5A,ML=63.8mg/L,N=1,δ=10mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 13.61 ± 0.9 1.3063 ± 0.002 18.87 0 4.252 ± 1 1.2849 ± 0.2  Table A-13: Low flow (1.35 LPM) EC experiment: I=2A,ML=25.5mg/L,N=2,δ=1mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 9.446 ± 0.7 1.0960 ± 0.00 1.4 0 5.702 ± 0.6 1.6604 ± 0.1 5 6.909 ± 0.3 1.7958 ± 0.01 30 6.669 ± 0.3 1.7352 ± 0.04 60 6.745 ± 0.4 1.7438 ± 0.1  Table A-14: Low flow (1.35 LPM) EC experiment: I=3A,ML=38.3mg/L,N=2,δ=1mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 9.446 ± 0.7 1.0960 ± 0.00 1.7 0 2.477 ± 0.2 1.3717 ± 0.02 5 2.829 ± 0.6 1.4731 ± 0.04 30 2.973 ± 0.5 1.4351 ± 0.04 60 2.424 ± 1 1.3648 ± 0.2  Table A-15: Low flow (1.35 LPM) EC experiment: I=4A,ML=51.1mg/L,N=2,δ=1mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 9.446 ± 0.7 1.0960 ± 0.00 2.0 0 1.304 ± 0.1 0.7884 ± 0.03 5 1.380 ± 0.02 0.9519 ± 0.05 30 1.328 ± 0.09 0.8139 ± 0.1 60 1.338 ± 0.3 0.9751 ± 0.03     132 Table A-16: Low flow (1.35 LPM) EC experiment: I=5A,ML=63.8mg/L,N=2,δ=1mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 9.446 ± 0.7 1.0960 ± 0.00 2.3 0 1.281 ± 0.07 0.5943 ± 0.1 5 1.356 ± 0.05 0.5467 ± 0.001 30 1.289 ± 0.01 0.5490 ± 0.05 60 1.252 ± 0.1 0.5350 ± 0.04  Table A-17: Low flow (1.35 LPM) EC experiment: I=2A,ML=25.5mg/L,N=2,δ=2mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 10.19 ± 1 1.1493 ± 0.02 1.6 0 5.820 ± 0.1 1.7221 ± 0.07 5 6.037 ± 0.9 1.7505 ± 0.09 30 7.075 ± 1 1.8199 ± 0.03 60 7.470 ± 0.4 1.8425 ± 0.07  Table A-18: Low flow (1.35 LPM) EC experiment: I=3A,ML=38.3mg/L,N=2,δ=2mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 10.19 ± 1 1.1493 ± 0.02 2.0 0 2.249 ± 0.1 1.5803 ± 0.1 5 2.628 ± 0.2 1.6630 ± 0.04 30 3.153 ± 0.4 1.7494 ± 0.1 60 3.431 ± 0.7 1.7383 ± 0.1  Table A-19: Low flow (1.35 LPM) EC experiment: I=4A,ML=51.1mg/L,N=2,δ=2mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 10.19 ± 1 1.1493 ± 0.02 2.4 0 1.201 ± 0.04 1.0925 ± 0.2 5 1.316 ± 0.01 1.1916 ± 0.03 30 1.388 ± 0.2 1.1751 ± 0.2 60 1.523 ± 0.4 1.3151 ± 0.2   133 Table A-20: Low flow (1.35 LPM) EC experiment: I=5A,ML=63.8mg/L,N=2,δ=2mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 10.19 ± 1 1.1493 ± 0.02 2.7 0 1.156 ± 0.1 0.9005 ± 0.04 5 1.249 ± 0.03 0.7396 ± 0.01 30 1.228 ± 0.05 0.9540 ± 0.03 60 1.120 ± 0.03 0.9876 ± 0.1  Table A-21: Low flow (1.35 LPM) EC experiment: I=2A,ML=25.5mg/L,N=2,δ=10mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 7.719 ± 0.7 0.9361 ± 0.002 4.5 0 4.455 ± 0.3 1.4102 ± 0.03 5 4.303 ± 0.05 1.4058 ± 0.04 30 4.497 ± 0.3 1.4177 ± 0.03 60 4.817 ± 0.3 1.4984  Table A-22: Low flow (1.35 LPM) EC experiment: I=3A,ML=38.3mg/L,N=2,δ=10mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 7.719 ± 0.7 0.9361 ± 0.002 5.9 0 1.474 ± 0.2 1.1251 ± 0.03 5 1.493 ± 0.03 1.1178 ± 0.002 30 1.712 ± 0.03 1.2077 ± 0.04 60 2.332 ± 0.2 1.3321 ± 0.02  Table A-23: Low flow (1.35 LPM) EC experiment: I=4A,ML=51.1mg/L,N=2,δ=10mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 7.719 ± 0.7 0.9361 ± 0.002 7.3 0 1.044 ± 0.1 0.6784 ± 0.1 5 1.041 ± 0.09 0.6521 ± 0.1 30 1.086 ± 0.1 0.8054 ± 0.2 60 1.217 ± 0.03 0.9053 ± 0.06   134 Table A-24: Low flow (1.35 LPM) EC experiment: I=5A,ML=63.8mg/L,N=2,δ=10mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 7.719 ± 0.7 0.9361 ± 0.002 8.6 0 1.595 ± 0.5 0.4638 ± 0.1 5 2.424 ± 1.6 0.5091 ± 0.1 30 3.420 ± 2.9 0.6282 ± 0.2 60 3.586 ± 2.7 0.6348 ± 0.1  Table A-25: Low flow (1.35 LPM) EC experiment: I=2A,ML=25.5mg/L,N=4,δ=1mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 9.524 ± 1 1.0945 ± 0.003 1.1 0 4.347 ± 0.05 1.5768 ± 0.1 5 5.721 ± 0.5 1.6967 ± 0.06 30 5.873 ± 0.4 1.7579 ± 0.09 60 5.192 ± 0.7 1.6090 ± 0.2  Table A-26: Low flow (1.35 LPM) EC experiment: I=3A,ML=38.3mg/L,N=4,δ=1mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 9.524 ± 1 1.0945 ± 0.003 1.3 0 1.762 ± 0.05 1.2679 ± 0.03 5 1.898 ± 0.1 1.3447 ± 0.01 30 2.176 ±0.3 1.2897 ± 0.1 60 2.205 ± 0.3 1.4029 ± 0.01  Table A-27: Low flow (1.35 LPM) EC experiment: I=4A,ML=51.1mg/L,N=4,δ=1mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 9.524 ± 1 1.0945 ± 0.003 1.5 0 1.259 ± 0.1 0.5898 ± 0.04 5 1.061 ± 0.02 0.06269 ± 0.1 30 1.097 ± 0.04 0.6781 ± 0.1 60 0.9980 ± 0.01 0.6708 ± 0.1   135 Table A-28: Low flow (1.35 LPM) EC experiment: I=5A,ML=63.8mg/L,N=4,δ=1mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 9.524 ± 1 1.0945 ± 0.003 1.7 0 1.227 ± 0.1 0.3857 ± 0.03 5 1.146 ± 0.01 0.3971 ± 0.002 30 1.162 ± 0.04 0.4385 ± 0.1 60 1.179 ± 0.2 0.4776 ± 0.1  Table A-29: Low flow (1.35 LPM) EC experiment: I=2A,ML=25.5mg/L,N=4,δ=2mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 9.481 ± 0.7 1.0955 ± 0.01 1.3 0 5.119 ± 1 1.6399 ± 0.2 5 5.411 ± 0.6 1.7190 ± 0.05 30 5.963 ± 0.1 1.7907 ± 0.05 60 6.074 ± 0.4 1.7601 ± 0.09  Table A-30: Low flow (1.35 LPM) EC experiment: I=3A,ML=38.3mg/L,N=4,δ=2mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 9.481 ± 0.7 1.0955 ± 0.01 1.5 0 1.874 ± 0.1 1.3384 ± 0.04 5 1.668 ± 0.4 1.3266 ± 0.1 30 1.993 ± 0.4 1.5019 ± 0.04 60 2.580 ± 0.1 1.6486 ± 0.01  Table A-31: Low flow (1.35 LPM) EC experiment: I=4A,ML=51.1mg/L,N=4,δ=2mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 9.481 ± 0.7 1.0955 ± 0.01 1.7 0 1.061 ± 0.1 0.7217 ± 0.1 5 1.053 ± 0.03 0.7058 ± 0.1 30 1.115 ± 0.05 0.8464 ± 0.02 60 1.028 ± 0.07 0.8036 ± 0.02   136 Table A-32: Low flow (1.35 LPM) EC experiment: I=5A,ML=63.8mg/L,N=4,δ=2mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 9.481 ± 0.7 1.0955 ± 0.01 1.9 0 1.467 ± 0.3 0.3587 ± 0.1 5 1.350 ± 0.2 0.3709 ± 0.1 30 1.433 ± 0.5 0.4995 ± 0.1 60 1.485 ± 0.5 0.4628 ± 0.1  Table A-33: Low flow (1.35 LPM) EC experiment: I=2A,ML=25.5mg/L,N=4,δ=10mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 13.61 ± 0.9 1.3062 ± 0.002 1.99 0 11.44 ± 3 1.7467 ± 0.06  Table A-34: Low flow (1.35 LPM) EC experiment: I=3A,ML=38.3mg/L,N=4,δ=10mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 13.61 ± 0.9 1.3062 ± 0.002 2.60 0 12.43 ± 0.08 1.9811 ± 0.2  Table A-35: Low flow (1.35 LPM) EC experiment: I=4A,ML=51.1mg/L,N=4,δ=10mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 13.61 ± 0.9 1.3062 ± 0.002 3.23 0 11.58 ± 0.2 1.9851 ± 0.3  Table A-36: Low flow (1.35 LPM) EC experiment: I=5A,ML=63.8mg/L,N=4,δ=10mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 13.61 ± 0.9 1.3062 ± 0.002 3.75 0 7.17 ± 5 1.9609 ± 0.04     137 A.2 Medium (Med) Flow Electrocoagulation Raw Data Table A-37: Med flow (5 LPM) experiment: I=8 A, ML=13.9 mg/L, N=1, δ=1 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 11.87 ± 0.7 1.1541 ± 0.005 3.78 0 11.77 ± 0.4 1.8018 ± 0.03  Table A-38: Med flow (5 LPM) experiment: I=11 A, ML=38.2 mg/L, N=1, δ=1 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 11.87 ± 0.7 1.1541 ± 0.005 7.66 0 4.236 ± 0.4 1.3495 ± 0.09  Table A-39: Med flow (5 LPM) experiment: I=14.7 A, ML=51.1 mg/L, N=1, δ=1 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 11.87 ± 0.7 1.1541 ± 0.005 9.42 0 1.239 ± 0.01 0.8452 ± 0.6  Table A-40: Med flow (5 LPM) experiment: I=19 A, ML=66.0 mg/L, N=1, δ=1 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 11.87 ± 0.7 1.1541 ± 0.005 11.40 0 1.254 ± 0.01 0.2501 ± 0.06  Table A-41: Med flow (5 LPM) experiment: I=8 A, ML=13.9 mg/L, N=1, δ=2 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 11.87 ± 0.7 1.1541 ± 0.005 5.13 0 12.18 ± 0.5 1.8679 ± 0.02     138 Table A-42: Med flow (5 LPM) experiment: I=11 A, ML=38.2 mg/L, N=1, δ=2 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 11.87 ± 0.7 1.1541 ± 0.005 11.39 0 5.861 ± 2.8 2.0173 ± 0.3  Table A-43: Med flow (5 LPM) experiment: I=14.7 A, ML=51.1 mg/L, N=1, δ=2 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 11.87 ± 0.7 1.1541 ± 0.005 14.31 0 0.9165 ± 0.03 0.5205 ± 0.1  Table A-44: Med flow (5 LPM) experiment: I=19 A, ML=66.0 mg/L, N=1, δ=2 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 11.87 ± 0.7 1.1541 ± 0.005 16.90 0 1.008 ± 0.06 0.4957 ± 0.06  Table A-45: Med flow (5 LPM) experiment: I=8 A, ML=13.9 mg/L, N=1, δ=10 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 13.61 ± 0.9 1.3063 ± 0.002 17.19 0 12.755 ± 0.3 1.6957 ± 0.04  Table A-46: Med flow (5 LPM) experiment: I=8 A, ML=13.9 mg/L, N=2, δ=1 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 11.70 ± 0.3 1.2149 ± 0.004 3.3 0 8.324 ± 1 2.1865 ± 0.1 60 9.833 ± 0.07 2.4525 ± 0.07     139 Table A-47: Med flow (5 LPM) experiment: I=11 A, ML=38.2 mg/L, N=2, δ=1 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 11.70 ± 0.3 1.2149 ± 0.004 4.2 0 3.937 ± 1 1.6155 ± 0.2 60 6.147 ± 0.4 2.1750 ± 0.1  Table A-48: Med flow (5 LPM) experiment: I=14.7 A, ML=51.1 mg/L, N=2, δ=1 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 11.70 ± 0.3 1.2149 ± 0.004 5.0 0 1.458 ± 0.5 1.2355 ± 0.1 60 2.399 ± 0.5 1.4790 ± 0.1  Table A-49: Med flow (5 LPM) experiment: I=19 A, ML=66.0 mg/L, N=2, δ=1 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 11.70 ± 0.3 1.2149 ± 0.004 5.9 0 2.157 ± 0.3 0.3300 ± 0.01 60 1.721 ± 0.6 0.4700 ± 0.09  Table A-50: Med flow (5 LPM) experiment: I=8 A, ML=13.9 mg/L, N=2, δ=2 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 11.70 ± 0.3 1.2149 ± 0.004 4.2 0 8.473 ± 3 1.8065 ± 0.02 60 9.234 ± 4 2.1045 ± 0.2  Table A-51: Med flow (5 LPM) experiment: I=11 A, ML=38.2 mg/L, N=2, δ=2 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 11.70 ± 0.3 1.2149 ± 0.004 5.2 0 1.294 ± 0.06 1.0485 ± 0.04 60 2.230 ± 0.6 1.3435 ± 0.2     140 Table A-52: Med flow (5 LPM) experiment: I=14.7 A, ML=51.1 mg/L, N=2, δ=2 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 11.70 ± 0.3 1.2149 ± 0.004 6.3 0 1.063 ± 0.3 0.2480 ± 0.04 60 1.360 ± 0.5 0.3720 ± 0.06  Table A-53: Med flow (5 LPM) experiment: I=19 A, ML=66.0 mg/L, N=2, δ=2 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 11.70 ± 0.3 1.2149 ± 0.004 7.6 0 0.7883 ± 0.1 0.3635 ± 0.2 60 3.020 ± 1.8 2.365 ± 0.6  Table A-54: Med flow (5 LPM) experiment: I=8A, ML=13.9 mg/L, N=2, δ=2=10 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 12.73 ± 0.4 1.2720 ± 0.01 12.3 0 7.194 ± 0.3 1.7270 ± 0.06 60 8.740 ± 0.1 1.8580 ± 0.00  Table A-55: Med flow (5 LPM) experiment: I=11 A, ML=38.2 mg/L, N=2, δ=10 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 12.73 ± 0.4 1.2720 ± 0.01 15.9 0 3.537 ± 1.4 1.3885 ± 0.07 60 5.170 ± 1.1 1.6195 ± 0.1  Table A-56: Med flow (5 LPM) experiment: I=14.7A, ML=51.1mg/L, N=2, δ=10 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 13.61 ± 0.9 1.3063 ± 0.002 19.4 0 1.944 ± 0.5 1.3476 ± 0.1     141 Table A-57: Med flow (5 LPM) experiment: I=19 A, ML=66.0 mg/L, N=2, δ=10 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 13.61 ± 0.9 1.3063 ± 0.002 24.0 0 1.199 ± 0.06 1.1516 ± 0.03  Table A-58: Med flow (5 LPM) experiment: I=8 A, ML=13.9 mg/L, N=4, δ=1 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 12.73 ± 0.4 1.2720 ± 0.01 2.3 0 9.175 ± 1 2.2110 ± 0.2 60 9.886 ± 0.1 2.3750 ± 0.06  Table A-59: Med flow (5 LPM) experiment: I=11 A, ML=38.2 mg/L, N=4, δ=1 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 12.73 ± 0.4 1.2720 ± 0.01 2.6 0 6.225 ± 2.2 2.0470 ± 0.4 60 9.169 ± 0.2 2.6279 ± 0.02  Table A-60: Med flow (5 LPM) experiment: I=14.7 A, ML=51.1 mg/L, N=4, δ=1 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 12.73 ± 0.4 1.2720 ± 0.01 3.1 0 1.722 ± 0.5 1.2810 ± 0.2 60 5.665 ± 0.4 2.4130 ± 0.1  Table A-61: Med flow (5 LPM) experiment: I=19 A, ML=66.0 mg/L, N=4, δ=1 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 12.73 ± 0.4 1.2720 ± 0.01 3.6 0 0.326 ± 0.01 0.0430 ± 0.03 60 0.356 ± 0.02 0.0390 ± 0.03     142 Table A-62: Med flow (5 LPM) experiment: I=8 A, ML=13.9 mg/L, N=4, δ=2 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 12.98 ± 0.5 1.2760 ± 0.007 2.7 0 9.692 ± 0.5 2.3165 ± 0.08 60 10.98 ± 0.1 2.5350 ± 0.05  Table A-63 Med flow (5 LPM) experiment: I=11 A, ML=38.2 mg/L, N=4, δ=2 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 12.98 ± 0.5 1.2760 ± 0.007 3.2 0 7.411 ± 1 2.3615 ± 0.1 60 9.664 ± 0.3 2.619  Table A-64: Med flow (5 LPM) experiment: I=14.7 A, ML=51.1 mg/L, N=4, δ=2 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 12.98 ± 0.5 1.2760 ± 0.007 3.7 0 1.674 ± 0.7 1.1070 ± 0.3 60 5.837 ± 1.4 2.4500 ± 0.4  Table A-65: Med flow (5 LPM) experiment: I=19 A, ML=66.0 mg/L, N=4, δ=2 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 12.98 ± 0.5 1.2760 ± 0.007 4.4 0 1.075 ± 0.06 0.5955 ± 0.005 60 1.196 ± 0.4 1.1740 ± 0.03  Table A-66: Med flow (5 LPM) experiment: I=8 A, ML=13.9 mg/L, N=4, δ=10 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 12.98 ± 0.5 1.2760 ± 0.007 6.3 0 9.537 ± 0.1 1.5480 ± 0.01 60 9.810 ± 0.3 1.6190 ± 0.009     143 Table A-67: Med flow (5 LPM) experiment: I=11 A, ML=38.2 mg/L, N=4, δ=10 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 12.98 ± 0.5 1.2760 ± 0.007 8.2 0 7.783 ± 1.8 1.9010 ± 0.1 60 9.228 ± 0.8 1.9620 ± 0.01  Table A-68: Med flow (5 LPM) experiment: I=14.7A, ML=51.1mg/L, N=4, δ=10 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 12.98 ± 0.5 1.2760 ± 0.007 10.3 0 4.843 ± 0.7 1.8995 ± 0.2 60 7.264 ± 0.06 2.3850 ± 0.03  Table A-69: Med flow (5 LPM) experiment: I=19 A, ML=66.0 mg/L, N=4, δ=10 mm Floc Time DOC UV-abs-254 Potential (min) (mg/L) (cm-1) (V) Raw 12.98 ± 0.5 1.2760 ± 0.007 12.6 0 1.959 ± 0.2 2.0995 ± 0.5 60 3.808 ± 0.1 2.0175 ± 0.6   A.3 Pilot-Scale, Raw Water Electrocoagulation Raw Data Table A-70: Pilot-scale (10 LPM) EC experiment: I=16 A, N=1, δ=1 mm ML DOC UV-abs-254 Potential (mg/L) (mg/L) (cm-1) (V) 27.8 3.926 ± 0.2 0.0728 ± 0.0002 26.26 ± 0.1  Table A-71: Pilot-scale (10 LPM) EC experiment: N=2, δ=1 mm ML I DOC UV-abs-254 Potential (mg/L) (A) (mg/L) (cm-1) (V) 27.8 16.0 4.710 ± 0.3 0.0863 ± 0.01 12.14 ± 0.8 38.2 22.0 3.815 ± 0.5 0.0655 ± 0.01 14.52 ± 0.7 51.1 29.4 3.971 ± 0.2 0.0654 ± 0.0001 17.45 ± 0.8 66.0 38.0 3.776  0.0613 ± 0.0002 20.4 ± 0.8  144  Table A-72: Pilot-scale (10 LPM) EC experiment: N=4, δ=1 mm ML I DOC UV-abs-254 Potential (mg/L) (A) (mg/L) (cm-1) (V) 27.8 16.0 3.924 ± 0.5 0.0834 ± 0.03 6.58 ± 0.7 38.2 22.0 4.027 ± 0.4 0.0728 ± 0.01 8.18 ± 0.4 51.1 29.4 3.528 ± 0.1 0.0630 ± 0.0005 9.79 ± 0.1 66.0 38.0 3.448 ± 0.4 0.0588 ± 0.001 10.64 ± 0.1  Table A-73: Pilot-scale (10 LPM) EC experiment: N=1, δ=2 mm ML I DOC UV-abs-254 Potential (mg/L) (A) (mg/L) (cm-1) (V) 27.8 16.0 4.296 ± 0.1 0.0917 ± 0.01 32.52  Table A-74: Pilot-scale (10 LPM) EC experiment: N=2, δ=2 mm ML I DOC UV-abs-254 Potential (mg/L) (A) (mg/L) (cm-1) (V) 27.8 16.0 4.109 ± 0.7 0.0788 ± 0.001 14.9 38.2 22.0 3.622 ± 0.1 0.0659 ± 0.003 19.95 ± 0.5 51.1 29.4 3.934 ± 0.1 0.0615 ± 0.002 24.25 ± 0.1 66.0 38.0 3.887 ± 0.1 0.0612 ± 0.0004 24.75 ± 0.2  Table A-75: Pilot-scale (10 LPM) EC experiment: N=3, δ=2 mm ML I DOC UV-abs-254 Potential (mg/L) (A) (mg/L) (cm-1) (V) 27.8 16.0 4.358 ± 0.4 0.779 ± 0.002 7.39 ± 0.5 38.2 22.0 4.210 ± 0.1 0.0685 ± 0.0001 10.00 ± 0.4 51.1 29.4 3.761 ± 0.1 0.0629 ± 0.0001 12.28 ± 0.04 66.0 38.0 4.044 ± 0.1 0.0596 ± 0.0001 13.98 ± 0.1  Table A-76: Pilot-scale (10 LPM) EC experiment: N=4, δ=10 mm ML I DOC UV-abs-254 Potential (mg/L) (A) (mg/L) (cm-1) (V) 27.8 16.0 4.450 ± 0.3 0.0761 ± 0.002 26.12 ± 0.1 38.2 22.0 4.336 ± 0.01 0.0727 ± 0.002 30.30 ± 0.7  145     146     147     148     149     150     151     152     153     154     155     156  157    Appendix B  Reactor & Software Design  B.1 Electrocoagulation Reactor & Electrode Design  Figure B-1: Technical drawing of the electrocoagulation reactor used for all experiments    320  290  295  290  290  270  250  20  15  10  15  15  30  35  140  25  10  5  10  50  38  36  58 Reactor without slottedinsertsAll dimensions in mm 158  Figure B-2: Technical side view drawing of the EC reactor (units in mm)      Figure B-3: Technical top (a) and front (b) view drawings of the EC reactor (units in mm)    320  290  295  290  290  270  250  20  15  10  15  15  30  35  140  25  10  5  10  50  38  36  58 Reactor without slottedinsertsAll dimensions in mm 320  290  295  290  290  270  250  20  15  10  15  15  30  35  140  25  10  5  10  50  38  36  58 Reactor without slottedinsertsAll dimensions in mm 320  290  295  290  290  270  250  20  15  10  15  15  30  35  140  25  10  5  10  50  38  36  58 Reactor without slottedinsertsAll dimensions in mm(a) (b)  159  Figure B-4: (a) Electrode holder inserts for inter-electrode gap adjustment; (b) Technical top view drawing of electrode holder; (c) Technical side view drawing of electrode holder, [mm]   Figure B-5: Technical drawing of anode/cathode electrode (units in mm)  280  126  30  10  20  250  270  96  43  10  7  1.50  10  5  20  250  270  96  43  10  7  1.50  10  5  20  250  270  96  43  10  7  1.50  10  5 (a) (b) (c)  160 B.2 LabVIEW Program Design   Figure B-6: Screenshot of custom LabVIEW program interface for current/voltage control and data logging, used for current density determination experiments   161 Figure B-7: Block diagram of the custom LabVIEW program for current/voltage control and data logging  162    Appendix C  Synthetic Water Preparation  The following will outline the procedures developed to prepare the humic acid synthetic surface water solution used the in laboratory scale-up low flow (1.35 LPM) and medium flow (5 LPM) experiments. Section C.1 will outline the preparation of the concentrated humic acid stock solution, while section B.3.2 will summarise the final steps taken to prepare the synthetic water used for experiments.   C.1 Humic Acid Stock Solution Preparation A 2 N sodium hydroxide (NaOH) solution is prepared to dissolve a high concentration of humic acid. Humic acid is added to the NaOH solution, followed by a dilution to the desired concentration (1000 mg/L). The resulting HA solution is used to prepare synthetic surface water solutions, as needed. The following steps are taken: (1) In a 500 mL beaker, add 260 mL of deionized water (2) Add a magnetic stir bar to the deionized water and place on stirrer, set stir speed to > 100 rpm (3) Add 20.8 g of NaOH to the water; allow the NaOH to completely dissolve (4) Slowly add 4 g of humic acid to the NaOH solution and allow adequate time for dissolution of HA into NaOH solution  163 (5) In a 4 L Erlenmeyer flask filled 3 L of deionized water, add the NaOH-HA solution (6) Place a large magnetic stir bar inside the Erlenmeyer flask and place on stir plate, set stir speed to > 300 rpm (7) Using sulfuric acid, titrate the contents of the Erlenmeyer flask to a near neutral pH (~6.5-7) (8) Fill the remainder of the flask to the 4 L mark The above steps yield 4 L of 1000 mg/L HA concentration solution. Stock solution that is not immediately used to prepare synthetic surface water should be stored at 4°C.  C.2 Synthetic Surface Water Preparation  Using the stock HA solution outlined above, the synthetic HA surface water solution can be prepared for experiments. The following summarises the steps taken to prepare the synthetic surface water: (1) Fill a 100 L tank with 96 L of distilled water (2) Add 4 L of the 1000 mg/L HA stock solution to the 100 L tank (3) Using an electric motor mixer, mix the HA-distilled water solution for several minutes (4) Check pH and conductivity (5) Collect samples for DOC and UV-abs-254 analysis 

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