Applied Science, Faculty of
Engineering, School of (Okanagan)
DSpace
UBCO
Ketabchi, Faezeh
Master of Applied Science - MASc
University of British Columbia
The global challenge of providing clean water supply for an increasing population is growing at an unprecedented pace. The most acute public health risk associated with drinking water is the potential presence of pathogens due to ineffective treatment. Therefore, there is an essential need for effective and efficient drinking water disinfection systems. Ultraviolet (UV) radiation and photocatalytic technologies are effective light-based disinfection methods that have grown in popularity, particularly in resource-limited scenarios. Due to increased cost, maintenance, and footprint, it is desirable to omit the filtration process in treatment systems utilizing UV for disinfection. However, understanding UV effectiveness for water treatment is primarily based on studies that have assumed pre-filtration and removal of particulates. To identify potential issues with applying UV to unfiltered water sources, this study investigated the effect of the water quality characteristics of unfiltered water samples on UV disinfection efficacy. UV biodosimetry tests were conducted over a year using water samples from two treatment plants that apply UV without filtration. The results showed that instead of typical water quality parameters such as turbidity and UV absorbance, the surface charge of particulate matter is the principal characteristic that describes UV dose-response relationships for unfiltered water sources. In terms of photocatalytic disinfection, this thesis focused on identifying possible interference of background natural organic matter (NOM) on photocatalytic disinfection via a novel metal-free visible-light active material, carbon nitride (CNx). In addition, any potential changes of the photocatalytic process on the character of background NOM was investigated using fluorescence spectroscopy. The results indicated that despite decreased inactivation efficiency of UV-LED disinfection system due to the particulate effect in unfiltered water samples, particles and NOM in real water matrices promoted viral inactivation by CNx photocatalytic disinfection. In addition, the results showed that even with low CNx concentrations (50 mg/L), the viral inactivation rate increased by 43%. Last but not least, the common regulatory drinking water treatment objective of 4-log removal of viruses can be satisfied with a far lower power light source.
Evaluation of Water Matrix Effects on Light-Based Small Disinfection Systems by Faezeh Ketabchi B.Sc., Amirkabir University of Technology, 2015 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF APPLIED SCIENCE in THE COLLEGE OF GRADUATE STUDIES Civil Engineering THE UNIVERSITY OF BRITISH COLUMBIA (Okanagan) April 2023 © Faezeh Ketabchi, 2023 ii The following individuals certify that they have read, and recommend to the College of Graduate Studies for acceptance, a thesis entitled: Evaluation of Water Matrix Effects on Light-Based Small Disinfection Systems submitted by Faezeh Ketabchi in partial fulfillment of the requirements of the degree of Master of Applied Science. Dr. Nicolás Peleato, School of Engineering Supervisor Dr. Rehan Sadiq, School of Engineering Supervisory Committee Member Dr. Cigdem Eskicioglu, School of Engineering Supervisory Committee Member Dr. Kenneth Chau, School of Engineering University Examiner iii Abstract The global challenge of providing clean water supply for an increasing population is growing at an unprecedented pace. The most acute public health risk associated with drinking water is the potential presence of pathogens due to ineffective treatment. Therefore, there is an essential need for effective and efficient drinking water disinfection systems. Ultraviolet (UV) radiation and photocatalytic technologies are effective light-based disinfection methods that have grown in popularity, particularly in resource-limited scenarios. Due to increased cost, maintenance, and footprint, it is desirable to omit the filtration process in treatment systems utilizing UV for disinfection. However, understanding UV effectiveness for water treatment is primarily based on studies that have assumed pre-filtration and removal of particulates. To identify potential issues with applying UV to unfiltered water sources, this study investigated the effect of the water quality characteristics of unfiltered water samples on UV disinfection efficacy. UV biodosimetry tests were conducted over a year using water samples from two treatment plants that apply UV without filtration. The results showed that instead of typical water quality parameters such as turbidity and UV absorbance, the surface charge of particulate matter is the principal characteristic that describes UV dose-response relationships for unfiltered water sources. In terms of photocatalytic disinfection, this thesis focused on identifying possible interference of background natural organic matter (NOM) on photocatalytic disinfection via a novel metal-free visible-light active material, carbon nitride (CNx). In addition, any potential changes of the photocatalytic process on the character of background NOM was investigated using fluorescence spectroscopy. The results indicated that despite decreased inactivation efficiency of UV-LED disinfection system due to the particulate effect in unfiltered water samples, particles and NOM in real water matrices promoted viral inactivation by CNx photocatalytic disinfection. In addition, the results showed that even with low CNx concentrations (50 mg/L), the viral inactivation rate increased by 43%. Last but not least, the common regulatory drinking water treatment objective of 4-log removal of viruses can be satisfied with a far lower power light source. iv Lay Summary There is increasing demand for effective and low-cost drinking water disinfection systems. Ultraviolet radiation and photocatalytic disinfection technologies require little to no input of non-renewable energy and could be more amenable to implement in remote and resource-limited communities. In this context, pre-treatment, such as filtration, is less likely to be practiced due to maintenance requirements. This study aims to investigate the effect of water characteristics of unfiltered water on light-based disinfection systems to help identify conditions where disinfection may be compromised. Moreover, the potential for carbon nitride to provide photocatalytic disinfection under visible light was investigated. Although carbon nitride has been shown to inactivate pathogens, no studies have been conducted in natural waters, representing real disinfection systems. It was expected that the conditions in natural water would interfere with the disinfection process. Surprisingly, the study results suggested that ions or organic matter in real water promote viral inactivation by photocatalysis. v Preface This dissertation is submitted for the degree of Master of Science at The University of British Columbia. The research described herein was conducted under the supervision of Dr. Nicolas Peleato in School of Engineering of The University of British Columbia Okanagan Campus. The relative contribution of this research is as follows: Chapter 4: This part of research had been developed by Mehrnaz Soleimanpour, PhD candidate under supervision of Dr. Nicolas Peleato. She was in charge of research questions identification and research proposal development. Part of experimental bioassay execution (May 2021 – Sep. 2021), data collection and analysis, and calibration of dose received was carried out by me. This part has been published in academic journal and in conference proceedings. • Soleimanpour M, M., Ketabchi, F., Peleato, N.M., “Impact of Water Characteristics on UV Disinfection of Unfiltered Water Sample,” Presented in May 2022 at the British Columbia Water Works Association Annual Conference. • Soleimanpour M, M., Ketabchi, F., Peleato, N.M., (2022) “Impact of Water Characteristics on UV Disinfection of Unfiltered Water Sample,” Water Quality Research Journal 57 (4), 247-261. The manuscript writing of these publications was conducted in collaboration with Mehrnaz. Chapter 5 and 6: These parts of research were conducted by me under supervision of Dr. Peleato. I was in charge of literature review, research questions identification, research proposal development, experimental designs, and all the experimental work execution. • The manuscript based on Chapter 5 and Chapter 6 is in preparation for publication. vi Table of Contents Abstract ......................................................................................................................................... iii Lay Summary ............................................................................................................................... iv Preface .............................................................................................................................................v Table of Contents ......................................................................................................................... vi List of Tables ................................................................................................................................ ix List of Figures .................................................................................................................................x Nomenclature .............................................................................................................................. xii Acknowledgements .................................................................................................................... xiv Dedication .....................................................................................................................................xv Chapter 1: Introduction ................................................................................................................1 1.1 Background ................................................................................................................... 1 1.2 Problem Statement & Objectives .................................................................................. 3 Chapter 2: Literature Review .......................................................................................................5 2.1 UV Disinfection ............................................................................................................ 5 2.1.1 Water Quality Effects on UV Disinfection ............................................................. 7 2.2 UV-LED Disinfection ................................................................................................... 9 2.3 Photocatalytic Disinfection ......................................................................................... 11 2.3.1 CNx Disinfection .................................................................................................. 16 2.4 Effect of Natural Organic Matter (NOM) on Disinfection ......................................... 17 2.5 Characterization of NOM ........................................................................................... 19 Chapter 3: Experimental Methodology .....................................................................................22 3.1 UV-LED Disinfection of Unfiltered Water ................................................................ 22 3.1.1 Water Sample Preparation .................................................................................... 22 vii 3.1.2 Microorganism Propagation and MS2 Assay ....................................................... 22 3.1.3 UV-LED Disinfection: Experimental Procedure .................................................. 23 3.1.4 UV Inactivation: Kinetics of Bacteria ................................................................... 23 3.1.5 Statistical Analysis ................................................................................................ 24 3.2 Photocatalytic Disinfection ......................................................................................... 25 3.2.1 CNx Preparation.................................................................................................... 25 3.2.2 Water Sample Preparation .................................................................................... 25 3.2.3 Photocatalytic Disinfection: Experimental Procedure .......................................... 25 3.2.4 Fluorescence Analysis .......................................................................................... 27 3.2.5 Statistical Analysis ................................................................................................ 28 Chapter 4: Impact of Water Characteristics on UV Disinfection of Unfiltered Water ........29 4.1 Introduction ................................................................................................................. 29 4.2 Result and Discussion ................................................................................................. 30 4.2.1 Water Quality Characterization ............................................................................ 30 4.2.2 Average Inactivation ............................................................................................. 31 4.3 Summary ..................................................................................................................... 33 Chapter 5: Natural Water Matrix Effects on CNx Photocatalytic Disinfection ....................34 5.1 Introduction ................................................................................................................. 34 5.2 Result and Discussion ................................................................................................. 37 5.2.1 Viral Disinfection in Light & Dark Controls ........................................................ 37 5.2.2 Effect of Different CNx Doses ............................................................................. 39 5.2.3 Viral Re-activation Assessment ............................................................................ 42 5.2.4 Effect of Natural Water Matrix Effects ................................................................ 43 viii 5.2.5 CNx Adsorption .................................................................................................... 47 5.2.6 CNx Immobilization ............................................................................................. 48 5.3 Summary ..................................................................................................................... 48 Chapter 6: Impact of CNx disinfection on Natural Organic Matter using Fluorescence Spectroscopy .................................................................................................................................50 6.1 Introduction ................................................................................................................. 50 6.2 Result and Discussion ................................................................................................. 51 6.2.1 PARAFAC Analysis ................................................................................................... 51 6.3 Summary ..................................................................................................................... 59 Chapter 7: Conclusion .................................................................................................................60 7.1 Summary of Contributions .......................................................................................... 60 7.2 Suggestions for Future Studies ................................................................................... 62 Bibliography .................................................................................................................................64 Appendix .......................................................................................................................................84 ix List of Tables Table 2.1. Effect of UV-LED treatment on photocatalytic inactivation. ...................................... 15 Table 4.1. Average UV transmittance and log removal values for all water samples at three different doses over a year. All log removal values have been calculated based on interpolation........................................................................................................................................................ 33 Table 5.1. Mean daily global sunlight insolation in the city of Kelowna, BC.............................. 38 Table 5.2. Viral inactivation rates for different CNx concentrations. .......................................... 41 Table 5.3. Overview of previous studies investigating viral disinfection efficiency of graphitic-carbon nitride (CNx) ..................................................................................................................... 46 Table 6.1. Identities and related references for similar components using the OpenFluor database (Murphy, Bro, et al., 2014). .......................................................................................................... 54 x List of Figures Figure 2.1. Photocatalytic reaction process: (i) Photon absorption by semiconductor photocatalyst, (ii) Excitation of semiconductor energy level, (iii) Separation process of electrons and holes in semiconductor, (iv) Migration of electron and holes in semiconductors, (v) Interface reaction © (W. Wang et al., 2021), Page 2, Adapted with permission from publisher. ................................. 11 Figure 3.1. CNx Water Sample on Stirrer and UV-LED Bench Scale Apparatus. ....................... 26 Figure 3.2. EEM dataset decomposed into five PARAFAC components © (Murphy et al., 2013), Page 6559, CC BY-NC-SA 2.0..................................................................................................... 27 Figure 4.1. (a) Turbidity over the one-year sampling period © (Soleimanpour Makuei et al., 2022), Page 253, Used by persmission , (b) Average UV transmittance at 254 nm. ............................... 31 Figure 4.2. The average viral inactivation of MH, DC pre-UV, and DC raw over a year at four different UV doses under UV wavelength of 254 nm. Doses are adjusted based on Eq. 3.2 to estimate the actual dose delivered; exposure times were constant for all tests. Error bars represent one standard deviation (n = 11). ................................................................................................... 32 Figure 5.1. Photocatalytic inactivation efficiency against MS2 in light control (viral suspension without CNx under light exposure), dark control (CNx without light exposure) sample, and viral suspension without CNx and light exposure. ................................................................................ 38 Figure 5.2. a) Photocatalytic inactivation efficiency against MS2 in the presence of different doses of CNx under visible light irradiation, b) Variations of final viral inactivation after 6 hours with different CNx concentrations. ....................................................................................................... 40 Figure 5.3. Variations of UVTs @254 nm and @365 nm, and turbidity with different CNx concentrations. .............................................................................................................................. 41 Figure 5.4. MS2 plaque formation before and after CNx photocatalytic disinfection with CNx concentration of 150 mg/L. ........................................................................................................... 42 xi Figure 5.5. Photocatalytic inactivation efficiency against MS2 for RO and DC raw water samples of CNx under 365 nm light irradiation. ........................................................................................ 45 Figure 5.6. Photocatalytic inactivation efficiency against MS2 for filtered and un-filtered water samples of CNx under 365 nm light irradiation............................................................................ 47 Figure 5.7. Photocatalytic inactivation efficiency against MS2 for immobilized CNx under 365 nm light irradiation.............................................................................................................................. 48 Figure 6.1. Example of flouresence EEMs. .................................................................................. 52 Figure 6.2. Loadings for components (C1 - C6) from PARAFAC model. ................................... 52 Figure 6.3. Scores (Fmax) of fluorescence components identified by PARAFAC analysis. ......... 56 Figure 6.4. a) Proportion of PARAFAC components to total Fmax in each Water Sample. b) Removal percentage of PARAFAC components normalized to DC raw water components. ...... 58 xii Nomenclature 𝐴𝐴254 UV absorbance at 254 nm (Unitless) CNx Carbon nitride D Delivered 𝑈𝑈𝑈𝑈𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 (mJ/cm2) DBP Disinfection by product DOC Dissolved organic carbon 𝑑𝑑 Depth of the suspension (cm) 𝐸𝐸𝐷𝐷 Average UV intensity (measured before and after irradiating the sample) (mW/cm2) k1 First-order inactivation rate constant for UV-susceptible fraction k2 First-order inactivation rate constant for UV-resistance fraction 𝐿𝐿 Distance from lamp centerline (cm) LP Low-pressure mercury lamp MP Medium-pressure mercury lamp 𝑁𝑁 Residual number of culturable MS2 after UV exposure in plaque-forming unit (PFU) N0 Initial number of culturable phages (PFU) NOM Natural organic matter 𝑃𝑃𝑓𝑓 Petri Factor (Unitless) PBS Phosphate-buffered saline POC Particulate organic carbon xiii 𝑅𝑅 Reflectance at the air-water interface at 254 nm (Unitless) ROS Reactive oxygen species 𝑡𝑡 Exposure time (s) TOC Total organic carbon β Fraction of UV-resistant phages ζ Zeta potential xiv Acknowledgements This research cannot be done without help from multiple resources. I would like to express my heartfelt appreciation to my supervisor Dr. Nicolas Peleato. During the past two years, he kindly devoted numerous time and effort to teaching and guiding me on this project, so that I have been always encouraged, enlightened, and inspired by him. Even sometimes when I made mistakes and faced experimental issues, he still gave me the chance allowing me to correct and improve myself. What I learned from him in the past two years not only helped me accomplish this project, but also will continuously benefit me for the whole life. I am truly grateful to my friend, PhD candidate under supervision of Dr. Peleato, Mehrnaz Soleimanpour. Whenever I need help and want to learn on unfamiliar topics, she is always willing to give me a hand and generously share her knowledge. Special thanks to her for teaching me microbial assay techniques when I had a hard time initiating the microbial tests. I also would like to sincerely acknowledge work-study student, Kate Alexander, who actively helped me to accomplish heavy workload of bioassay experiments. Many thanks to Brayden Jones, for his active participation in preparing required material for bioassay experiments. Also, I would like to thank Dr. Robert Godin from Chemistry department of UBC for sharing facilities of his lab and to her undergraduate student, Kadie Wert, for her generous help in photocatalyst preparation. I would also like to appreciate Dr. Sepideh Pakpour in Engineering Department and cordially thanked her research group, Rita Lam and Sahar Alousi, for their help in microbial tests. Finally, I would like to acknowledge the financial support from Natural Sciences and Engineering Research Council of Canada (NSERC) and Regional District of North Okanagan. I would like to express my gratitude to the personnel at the Regional District of North Okanagan including Zee Marcolin, Tricia Brett, Dustin Heidt, and Taylor Dufaut as well as Stephen Horsman with WSP for their support. Last but not least, I would like to acknowledge the support and encouragement of my family and friends, who stood by me during the ups and downs of this journey. Thank you all for your contributions, support, and encouragement. xv Dedication To my family, my mother, my father, and my brother, for their love, understanding, and supporting my pursuit of M.Sc. study abroad. To all my compatriots, who are bravely fighting for their fundamental rights. To whoever is impacted by tyranny and sincerely wishes #Woman_Life_Freedom. 1 Chapter 1: Introduction 1.1 Background The worldwide problem of providing an adequate, safe, and clean water supply for increasing populations is growing at an unprecedented pace. According to Centers for Disease Control and Prevention (CDC), worldwide, approximately 780 million people lack access to clean water (CDC, 2022) . The annual deaths of 1.5 million people, of whom over 90% are children, have been attributed to drinking contaminated water (Kalt et al., 2014). Microorganisms are responsible for the majority of diseases associated with contaminated water consumption (Rananga & Magadzu, 2015). In order to inactivate and eliminate pathogens to reduce health risks, water disinfection is a crucial step in a water treatment process. Water disinfection has been traditionally achieved by addition of chlorine. However, the major concern with chlorination is potentially mutagenic and carcinogenic disinfection by products (DBPs) that are being formed during water chlorination. In addition, some organisms can develop resistance to chlorine or require higher than normal doses for complete inactivation, which can make smell and taste of drinking water unpleasant. As a result, many alternative processes for the disinfection of drinking water have been developed (Dalrymple et al., 2010). Among several alternative disinfection methods, ozonation, chlorine dioxide, advanced filtration processes, and germicidal ultraviolet (UV) radiation have received particular interest. Even though they can be effective, most alternative approaches are generally associated with increased cost and complexity compared to chlorination (Dalrymple et al., 2010). UV disinfection is one practical technique that meets the requirements of being safe, easy to use and free of chemicals (Parrotta & Bekdash, 1998). UV disinfection is particularly attractive for small water systems, which need simple and low-cost methods. Low and medium-pressure (LP and MP) mercury UV lamps have been the most common illumination technology used (Eskandarian et al., 2016). However, short bulb lifetime, power instability during lifetime operation, need for cooling, low energy efficiency, and mercury pollution potential are some shortcomings associated with conventional mercury UV lamps (Eskandarian et al., 2016; Natarajan, Thomas, et al., 2011). To replace mercury UV lamps, light emitting diodes (LEDs) have been recognized as a more cost-effective, environmentally friendly, and sustainable source of UV (Korovin et al., 2015; Verma & Sillanpää, 2015). Several advantages are associated with LED lamps, including low power requirement, operation at low voltage, low warm-up time, no mercury 2 disposal problem, stability, and easy handling (Eskandarian et al., 2016). It has been reported that the potential lifetime of LEDs is 35,000-50,000 h, which is much longer than that of low/medium pressure UV lamps, which is estimated to be only 9,000-12,000 h (Eskandarian et al., 2016; Ibrahim et al., 2014). However, there are some limitations associated with UV disinfection systems. For instance, since no residual disinfectant is generated, inactivated microorganisms might become viable again in the distribution system. In addition, UV disinfection effectiveness depends on water quality conditions and type of microorganisms present in influent water (S. B. Khan & Akhtar, 2019). Photocatalytic technologies have been investigated for the augmentation of UV-based inactivation of wide range of microorganisms (Adán et al., 2017; Cruz-Ortiz et al., 2017; Pulgarin, 2015). It is worth mentioning that UV photocatalytic disinfection systems are typically expensive and energy-intensive processes due to additional infrastructure, maintenance supplies, set up of expensive lighting equipment, and other capital costs (C. Zhang, Li, Shuai, Shen, Xiong, et al., 2019). Therefore, it is crucial to develop a water disinfection system that relies on a renewable energy source, such as solar energy, to supply drinking water, particularly in remote communities which face serious challenges to meet the energy demand. Titanium Dioxide (TiO2) has been shown to be the most mature photocatalytic material due to its non-toxicity and low price, leading to improved water treatment system performance (W. Wang et al., 2017; Q. Zheng et al., 2017). However, it is mainly activated under high-energy ultraviolet radiation (UVA), which makes up only 4% of the solar spectrum. Therefore, utilizing a visible-light-active photocatalyst, which can potentially harvest more sunlight (as 40% of solar energy is composed of visible light) for reactions, is more promising for a sustainable water purification system. Since 2009, graphitic carbon nitride (CNx), a metal-free organic polymeric nanomaterial, has emerged as a promising visible-light responsive photocatalyst (W. Wang et al., 2017; Q. Zheng et al., 2017). Carbon nitride is expected to have broad applications in energy, environmental, and biomedical areas (Hao et al., 2020). For example, the photocatalytic reduction reaction of CNx, leads the water to be split, resulting in hydrogen as zero-emission fuel, which has higher calorific value than fossil fuel. In addition, its unique optical and electronic properties have been recognized as promising for diagnostic imaging, therapeutic applications, biosensors, and antibacterial applications (Liao et al., 2020). The backbone of CNx only contains earth-abundant 3 elements of carbon and nitrogen, which enable inexpensive, large-scale material fabrication (Q. Zheng et al., 2017). In addition, proper bandgap and good photoelectric characteristics have made CNx a prominent visible light-activated photocatalyst for water disinfection. As a result of light exposure of CNx, a variety of reactive oxygen species (ROS), including ȮH, H2O2, Ȯ2− would be formed to oxidize or remove organic substances and bacteria (Wang et al., 2021) 1.2 Problem Statement & Objectives To reduce interference of particles with exposure of pathogens to light, light-based disinfection methods are usually applied following a filtration process. In some cases, such as in small systems, it would be desirable to omit the filtration process due to the additional infrastructure that leads to increased cost, maintenance, and footprint (Christensen & Linden, 2003). However, the elevated levels of particulates and organic compounds in unfiltered water supplies are of concern since they are known to interfere with UV or light-based disinfection by scattering or absorbing the light. Currently, the acceptable water quality conditions for the application of UV disinfection for unfiltered water supplies in water treatment plants and small systems has not been thoroughly investigated. Although some considerable progress has been made in CNx use for water treatment, several challenges still need to be addressed before practical application. A significant research gap is the previous studies have utilized pure water with few to no additives. As such, there is limited knowledge of the effect of real water matrices and the potential quenching effect from natural organic matter on disinfection performance. Since CNx will produce reactive oxygen species that are not selective to inactivating microorganisms, the side reactions with abundant organic matter in natural waters must be considered. In addition, the effectiveness of CNx using low-power light sources like UV-LED system needs to be investigated, as the light sources used in previous studies for CNx were high power Xenon lamps (Wang et al., 2021). Given the aforementioned issues, the overall objective of this research is to evaluate the impacts of the water matrix on light-based disinfection for small systems. The specific objectives of this thesis are listed below: 1. Under specific circumstances, treatment systems may utilize UV or other wavelengths of light for disinfection without pre-filtration. It is desirable to omit the filtration process due to the additional infrastructure that leads to increased cost, maintenance, and footprint. 4 Microorganisms can be surrounded, enmeshed, or otherwise shielded by particles. It is expected that the interaction of microorganisms with particles (organic, inorganic) and flocs (biological, chemical) may inhibit them from disinfection. This study aims to investigate UV-LED dose-response when pre-filtration is not practiced. In addition, the feasibility of predicting UV-LED water disinfection only based on UVT/turbidity measurement will also be examined. 2. Studies on photocatalytic disinfection using CNx have primarily focused on the disinfection of bacteria, with limited attention to virus disinfection. The unique composition, structure, and resistance to oxidative stresses for viruses should be considered. In addition, the light sources used in previous studies for CNx were high-power Xenon lamps, covering a range of visible wavelengths. The effectiveness of CNx using low-power light source emmiting single wavelength needs to be investigated. This study aims to examine the efficacy of CNx photocatalysis for viral inactivation using a low-power UV-LED light source, radiating single wavelength. 3. It is expected that increasing photocatalyst loading would increase active sites as well as the disinfection rate. Accordingly, this study investigated the effectiveness of different CNx doses as a slurry and immobilized on glass for viral disinfection performance. 4. Due to interference of natural organic matter present in water sources, reactive oxygen species (ROS) generation may be prevented, generated ROS may be consumed, or the presence of NOM may impede active sites on the CNx. Accordingly, the inactivation efficiency of CNx disinfection in a natural water resource compared to RO water sample will be investigated. It is expected that the presence of NOM will reduce the overall disinfection rate. 5. Due to the anticipated reactions between the CNx, generated ROS, and NOM, it is expected that the characteristics and concentrations of NOM will change due to exposure to CNx and light. Therefore, the impact of CNx on natural organic matter inactivation using fluorescence spectroscopy will be investigated to identify possible changes to the background NOM. Changes in organic matter in response to different concentrations of CNx will be characterized using parallel factor analysis (PARAFAC). 5 Chapter 2: Literature Review 2.1 UV Disinfection Ultraviolet (UV) disinfection is a physical disinfection process that has several advantages, including low cost, no chemical input, low formation of disinfection by product (DBPs) and small footprint (Sun et al., 2022). UV light inactivates microorganisms by damaging their nucleic acids, lipids, and proteins, thereby preventing them from replicating. The damage can inhibit their ability to reproduce and thus prevent infection (Hijnen et al., 2006; Sun et al., 2022). For effective disinfection, it is also necessary to weaken or prevent DNA repair for microorganism inactivation. This can be prevented by damaging repair enzymes, which are proposed to be more vulnerable to high UV intensities (Sommer et al., 1998). UV disinfection dates back to early 1900s when Peter Cooper Hewitt correlated the germicidal effectiveness of UV wavelengths between 200 and 300 nm to the relative absorbance of DNA (Gates, 1929). Currently, there are more than 7,000 municipal UV installations worldwide (Song et al., 2016). Compared to ozone, it is a cost-effective technology, in which 3 log removal of Cryptosporidium could be achieved with 40 percent of the cost of 2 log inactivation by ozone (Hargy, 2002). Since UV technology does not provide residual disinfectant, it has been slower to take hold in larger municipal drinking water applications. However, for small non-community treatment systems where residual disinfectant is not necessary, UV is widely used for primary disinfection (Dotson et al., 2012). Two mercury lamp types emitting UV light in the germicidal range have been commonly used for commercial, industrial, and municipal applications. Nearly monochromatic UV radiation with a peak wavelength of 254 nm is emitted by low-pressure (LP) mercury lamps. The UV radiation from LP mercury lamp is strongly adsorbed by DNA of microorganisms, resulting in direct DNA damage and making them unable to replicate. It is worth mentioning that for some microorganisms, 254 nm wavelength radiation is not the most effective wavelength for inactivation. For example, the inactivation action spectrum of Bacillus subtilis was investigated by Chen et al., who found the highest inactivation rate at 270 nm wavelength (R. Z. Chen et al., 2009). The studies on UV disinfection for Cryptosporidium parvum oocysts also indicated that 270 nm is more effective than 254 nm in terms of germicidal effects (Linden et al., 2001). 6 Unlike LP mercury lamps, polychromatic spectrum with various wavelengths from UVC to UVA and visible light are emitted by MP mercury lamps. The output power of MP mercury lamp is much higher compared to LP mercury lamp (Bolton & Cotton, 2011). In addition, MP mercury lamps can disinfect faster and have greater penetration capability compared to LP lamps, resulting in germicidal UV intensity of approximately 15 to 20 times higher than LP lamps (Hijnen et al., 2006). The multiple wavelengths from MP lamps have the advantage of damaging other components of cells like the membrane and proteins in microorganisms in addition to DNA, resulting in higher inactivation by MP lamps (Kalisvaart, 2004). Moreover, polychromatic UV radiation emitted by MP mercury lamps is more beneficial in reducing photoreactivation after UV radiation. It has been reported that while some microorganisms (e.g. E. coli) can be reactivated after exposure to LP mercury lamps, they cannot self-repair after exposure to MP mercury lamps (Oguma et al., 2002; Zimmer & Slawson, 2002; Zimmer-Thomas et al., 2007). It should be noted that since the broad polychromatic spectrum from MP mercury lamps is fixed and is not adjustable, the energy associated with non-germicidal wavelengths is wasted. Several studies have evaluated UV disinfection technology for microbial inactivation. Pathogens of concern in water treatment systems consist of bacteria, viruses, and protozoans. UV irradiation effectively inactivates all three types of pathogens at practical doses (Malley, 2004). Six bacterial species in a laboratory UV device were investigated by Hassen et al. (Hassen et al., 2000). Three groups of different UV sensitivity were determined based on kinetic constants. Two strains of Pseudomonas aeruginosa ATCC 15442 and B. subtilis 6633 were found as resistant group, and the strain of Escherichia coli ATCC 11229 was considered as sensitive group to UV radiation. Three strains of Enterococcus faecalis ATCC 19433, Serratia marcescens ATCC 8100 and P. aeruginosa S21 represented a medium level of UV radiation sensitivity. All bacterial strains except P. aeruginosa ATCC 15442, P. aeruginosa ATCC 15442 mutant m1, and Enterococcus hirae ATCC 10541 photo-reactivated after UV disinfection. Fitzhenry et al. evaluated the efficacy of pulsed UV (PUV) for bacterial inactivation under flow-through conditions (Fitzhenry et al., 2021). The potential for photo-reactivation or dark repair post-PUV flow-through disinfection of bacterial pathogens, including Escherichia coli, Staphylococcus aureus and Listeria innocua (surrogate for L. monocytogenes) were investigated. E. coli exhibited greatest sensitivity to PUV treatment, while Listeria innocua showed highest PUV resistance under similar treatment 7 conditions. In addition, they found that to minimize photoreactivation exposure of treated bacteria to natural light immediately after flow-through PUV disinfection should be avoided. In terms of viral disinfection, Guerrero-Latorre et al. evaluated the ability of UV radiation to reduce Hepatitis E Virus (HEV). The results showed that UV-irradiation tests had 4 log removal inactivation for HEV with UV fluence of 232 J/m2, which was under the baseline of reduction (4.5 log removal value) proposed by WHO guidelines (Guerrero-Latorre et al., 2016). Zyara et al. disinfected drinking water with Miniature Spheroid (MS2) bacteriophage and 18 different coliphages isolated from municipal wastewater. The results indicated that a high dose of 117 mWs/m2 caused only 3 log removal in some UV-resistance coliphages, including MS2, which is a good indicator for viruses in UV-disinfection tests. The combined treatment of chlorine followed by UV-disinfection inactivated all coliphages by > 3.6 log removal, which was higher than that of high dose of chlorine or UV disinfection alone (Zyara et al., 2016). Augusburger et al. investigated the appropriate UV-dose or fluence (mJ/cm2) to combat enteric viruses in surface or treated water. The results showed that the required range of UV fluence needed for 4 log inactivation of adenovirus using LP-UV was higher compared to that of other enteric viruses such as Caliciviridae and Picornaviridae family and rotavirus. In addition, lower UV fluence was required for 4 log removal in UV-LED technology compared to that of LP-UV for most examined strains (Augsburger et al., 2021). The effect of UV light on the inactivation of five strains of Cryptosporidium parvum oocysts, including Iowa, Moredun, Texas A&M, Maine, and Glasgow strains, were investigated by Clancy et al. (Clancy et al., 2004). The result showed that all five strains of C. parvum were highly susceptible to low levels of UV light, resulting in at least 4 log inactivation under UV light dose of 10 mJ/cm2 in all strains. The germicidal effect of polychromatic ultraviolet radiation emitted by either a medium-pressure, continuous-wave UV lamp or a pulsed-UV lamp on oocysts of Cryptosporidium parvum was examined by Mofidi et al. (Mofidi et al., 2001). They found that there was no significant difference in disinfection power between the MP and pulsed UV lamps. 2.1.1 Water Quality Effects on UV Disinfection In terms of the effect of water quality characteristics, several studies have evaluated effects of particulates on UV disinfection. Previous work has focused on identifying the critical particle size, above which the particles could shield microorganisms from UV-light. The reported influential 8 ranges are 7-11 µm (Cantwell et al., 2010; Caron et al., 2007; Jolis et al., 2001), 11-25 µm (Kollu & Örmeci, 2012), and 263 µm and larger (Ko et al., 2000). The critical particle size would be expected to vary with the size of microorganisms (Ko et al., 2000; Kollu & Örmeci, 2012; Winward et al., 2008). According to previous studies, UV-light inactivation of microorganisms typically follows a log-linear trend up to a specific dose, after which continuing UV-light irradiation results in a limited increase in disinfection performance. This tailing effect, or diminishing disinfection at high UV doses, is due to shielded microorganisms by particulate matter or aggregation of organisms into clusters, providing some degree of protection from UV-light irradiation (Tan et al., 2017). Accordingly, to achieve the desired level of disinfection and prevent overestimation of the delivered UV dose, the tailing effect is important to be considered. To find the percentage of microorganisms contributing to tailing effect, a comprehensive model was developed by Tan et al. to quantify the impact of dose and UV absorbance on tailing phenomena (Tan et al., 2017). Considering that UV transmittance (UVT) is the primary water quality parameter used to assess if UV disinfection will be effective, most developed models account for UV absorbance or UVT as the only and most influential process control parameter (Tan et al., 2017). However, according to Farrel et al., the observed dose response cannot solely be explained by UV absorbance or UVT. They found that to justify variability in dose-response curves between distinct water sources, other water quality parameters need to be considered (Farrell et al., 2018). Since turbidity is a water quality measurement that does not distinguish particle characteristics e.g. particle size and surface charge, water samples with the same turbidity but different compositions can show unexpected behaviour after UV exposure (Farrell et al., 2018). For instance, if the main reason for the tailing effect is organism-particle association, the electrostatic attraction between particle and organism will largely determine the probability of shielded organisms (Farrell et al., 2018). Handling the target pathogens for UV disinfection tests in operating water treatment systems is neither practical nor in the best interest of public health (EPA, 2006). Therefore, a challenge microorganism whose sensitivity to UV light is similar to the target pathogen should be used in all experiments. Male-specific-2 bacteriophage (MS2) historically has been used for UV disinfection experiments to receive treatment credit for Cryptosporidium. Bacteriophages and viruses are both 9 types of infectious agents that can cause diseases, but they differ in several keyways. Bacteriophages, also known as phages, are viruses that specifically infect bacteria. On the other hand, viruses are infectious agents that can infect a wide range of hosts, including bacteria, plants, animals, and humans (Ackermann, 2003; Suttle, 2005). It should be noted that to account for bias and uncertainty associated with using challenge microorganisms instead of the target pathogens, a validation factor should be considered. The effect of water quality and sample depth on MS2 coliphage inactivation in 17 filtered water samples was evaluated by Batch et al. (Batch et al., 2004). The result indicated that UV inactivation of MS2 was not affected by turbidity, particle count, and absorbance. In addition, MP lamp types showed more beneficial for MS2 inactivation compared to LP lamps. The inactivation kinetics of MS2 bacteriophage under UV-A and UV-B radiation have been evaluated by Lee and Ko (Lee & Ko, 2013). While MS2 was highly resistant to UV-A, UV-B effectively inactivated MS2 by 4 log removal. 2.2 UV-LED Disinfection Following the recent emergence of UV-LED lamps as a UV radiation source, UV-LED water treatment technology has been increased (Jo & Tayade, 2014; Song et al., 2016). Several unique advantages associated with UV-LEDs including environmental friendliness (no mercury), faster start-up (no warm-up time), potentially less energy consumption, longer life time, and improved durability (Würtele et al., 2011). Fabrication and utilization of UV-LEDs for water disinfection is still under development. One of the major constraints associated with UV-LEDs application is the high cost (Kebbi et al., 2020). Some studies investigated the economic feasibility of UV-LED systems compared to conventional mercury lamps. For example, a cost analysis was conducted by Crook et al. to assess the future economic cost of UV-LED systems compared to conventional UV lamps for greywater disinfection (Crook et al., 2014). They found that current UV-LEDs are not economically competitive in this application. However, if anticipated technological development and cost reduction over the next 15+ years is realized, the technology may be viable. Nevertheless, Ibrahim et al. predicted that UV-LEDs would compete with traditional UV lamps by the year 2020 (Ibrahim et al., 2014). In addition, based on the cost analysis conducted by Autin et al. UV-LEDs over 10 mercury UV lamps for photocatalytic disinfection will become economically viable, assuming development follows the prediction (Autin et al., 2013). These factors make UV-LEDs a promising alternative to conventional UV mercury lamps for water disinfection technology. It should be noted that the DNA absorbance spectrum does not necessarily follow microorganism spectral sensitivity, leading germicidal effectiveness of the UV disinfection process to be highly dependent on UV wavelength (R. Z. Chen et al., 2009; Mamane-Gravetz et al., 2005). Different UV wavelengths, including UVA (315-400 nm), UVB (280-315 nm), and UVC (<280 nm) have been applied for microorganism inactivation. Hamamoto et al. investigated E. coli disinfection using UVA radiation with 365 nm in UVA-LED system. The result showed that the UV dose response was 55,263 mJ/cm2 per E. coli log inactivation (Hamamoto et al., 2007). Mori et al. achieved 3.9 log inactivation at 54,000 mJ/cm2 UVA fluence in UVA-LED system (13,846 mJ/cm2 per E. coli log inactivation) (Mori et al., 2007). UVA has a much weaker disinfection effect compared to higher energy UVC light. The UV dose required from mercury lamps emitting at 254 nm is 2 mJ/cm2 per E. coli log removal. As such, UVA-LEDs are likely too inefficient for practical E. coli inactivation (Bolton & Cotton, 2011; EPA, 2006). Previous work has shown improved inactivation under UVB compared to UVA. Oguma et al. reported a required dose of 94.8 mJ/cm2 at 310 nm (UVB-LED) per 1 log inactivation, which is significantly lower than that of 365 nm UVA-LEDs (Oguma et al., 2013). Nonetheless, the required UV dose per log inactivation reported for various microorganisms under UVC-LEDs ranged from 1.0 to 30.5 mJ/cm2 (Song et al., 2016), showing that UVB-LEDs alone are not highly effective for microorganisms disinfection as well. The effectiveness of 255 nm and 280 nm UVC-LEDs for the inactivation of bacteriophages φX174, Qβ, and MS2 was investigated by Aoyagi et al. (Aoyagi et al., 2011). The results indicated that UV dose responses at 280 nm per log inactivation for all three microorganisms (2.8, 28.7, 30.5 mJ/cm2, respectively) were higher than those of 255 nm (1,7, 12.5, 12.8 mJ/cm2, respectively). Another study investigated the inactivation effectiveness of UVC-LEDs at 255 nm and 275 nm for MS2, T7, and E. coli (Bowker et al., 2011). Greater inactivation of E. coli and MS2 was observed from the use of an LP mercury lamp compared to a UVC-LED light source. However, T7 showed similar inactivation under LP lamps and 275 nm UV-LED light. In addition, the inactivation of MS2 under 255 nm light was more effective than that of 275 nm, while 275 nm UV-LED resulted 11 in higher inactivation for T7 and E. coli. This result confirms that the action spectrum peak of MS2 and T7 are around 260 nm and 270 nm, respectively (Beck et al., 2015; Mamane-Gravetz et al., 2005; Rontó et al., 1992). Furthermore, it can be concluded that generally UVC-LED wavelength has the most antimicrobial effect for water disinfection. 2.3 Photocatalytic Disinfection Photocatalytic disinfection is a novel and effective method against a broad range of pollutants not easily removed by conventional water treatment processes (Byrne & Fernández-Ibáñez, 2012). In this process, a semi-conductor photocatalyst is activated by UV or visible light radiation to generate reactive oxygen species (ROS). When photons irradiate a photocatalyst, valence band electrons are excited to the conduction band, creating electron-hole pairs. These electron-hole pairs can react at particle interface with water and oxygen to produce ROS, including hydroxyl radicals (𝑂𝑂𝑂𝑂)̇ , which serves as the main oxidant, superoxide radical anions (𝑂𝑂2̇−), singlet oxygen (1O2), and hydrogen peroxide (H2O2). ROS can be generated by both valence band holes (hVB+), which drives oxidation, and conduction band electrons (eCB-) driving reduction. These ROS and other radicals such as chlorine would damage cell wall and cell membrane of microorganisms, resulting in a loss of respiratory activity and leakage of intracellular components (Cruz-Ortiz et al., 2017). A schematic view of photocatalytic reaction process has been shown in Figure 2.1. Figure 2.1. Photocatalytic reaction process: (i) Photon absorption by semiconductor photocatalyst, (ii) Excitation of semiconductor energy level, (iii) Separation process of electrons and holes in semiconductor, (iv) Migration of electron and holes in semiconductors, (v) Interface reaction © (W. Wang et al., 2021), Page 2, Adapted with permission from publisher. 12 UV-LED technology can activate photocatalysis in order to produce highly strong oxidizing radical species such as hydroxyl radicals (𝑂𝑂?̇?𝑂). Several studies have evaluated UV-LED technology for microbial inactivation using photocatalysts (summarized in Table 2.1). Natarajan et al. used UV-LEDs to investigate the effect of operational parameters such as catalyst loading, initial dye concentration, pH, and presence of metal ions (Zn2+, Ag+, Fe3+, Cu2+ and Cd2+) on photocatalytic the degradation of Rhodamine B (RhB) dye (Natarajan, Thomas, et al., 2011). According to the experiments, the presence of metal ions negatively affects the degradation of RhB dye due to the decrease in the adsorption of dye molecules on the catalyst surface. In addition, the effectiveness of the UV-LED/TiO2 process in RhB dye degradation was demonstrated well in this study. Degradation of anatoxin-a applying UVC-LED photolysis and UVC/H2O2 processes was evaluated by Verma and Sillanpää (Verma & Sillanpää, 2015). They achieved anatoxin-a removal of 79% and 96% by UVC-LED photolysis and UVC/H2O2, respectively. Kuipers et al. examined the effect of the distribution of UV-LED light source in a photocatalytic slurry reactor in order to increase photon transfer efficiency (Kuipers et al., 2015). They found that the removal rate of distributed UV-LEDs throughout the reactor is higher than that of UV-LEDs concentrated on one plane in the reactor by 30%. Eskandarian et al. investigated direct photolytic and TiO2 photocatalytic decomposition of model pharmaceuticals, including acetaminophen (ACT), diclofenac (DCF), ibuprofen (IBP), and sulfamethoxazole (SMX) under different UV-LED wavelengths. They found that UV wavelength was a more influential parameter describing decomposition than light intensity. As such, shorter wavelengths in the UVC region have more significant impact on the deterioration of pharmaceutical compounds compared to UVB and UVA (Eskandarian et al., 2016). Davididou et al. studied the photocatalytic degradation of bisphenol-A (BPA) under various radiation sources, including UV-LEDs, LP UV light source, and natural sunlight. The results showed that LED-driven photocatalysis is more advantageous than conventional TiO2/UV-BL systems in terms of performance and sustainability. In addition, it is an appropriate alternative to solar photocatalysis in areas where sunlight is inadequate (Davididou et al., 2018). The photocatalytic reduction of CO2 by UV-LED process under periodic illumination was investigated by Ku et al. (Ku et al., 2020). They reported an approximately linear increase of CO2 reduction rate with increasing Iaverage under continuous or periodic illumination. The highest CO2 reduction efficiency achieved in the experiments was 86.31%. 13 Recently, the performance of the world’s first commercial UVC-LED water disinfection reactor was compared side by side with an existing chlorination system at a small water treatment plant in Colorado. The reactor demonstrated viral and bacterial efficacy and resilience equivalent to the chlorination system, validating municipal UVC-LEDs water treatment application (Hull et al., 2019). It is worth mentioning that fundamental requirements for large-scale UV photocatalytic disinfection systems, including infrastructure, maintenance supplies, set up of expensive lighting equipment, and capital cost imply UV photocatalytic disinfection systems are energy-intensive (C. Zhang, Li, Shuai, Shen, Xiong, et al., 2019). Therefore, it is of interest to develop a water disinfection system that relies on a renewable energy source, such as solar energy, particularly in remote communities that face serious challenges in meeting the energy demand. Titanium Dioxide (TiO2) has been shown to be the most mature photocatalytic material due to its non-toxicity and low price, leading to improved water treatment system performance (W. Wang et al., 2017; Q. Zheng et al., 2017). However, it is mainly activated under UVA radiation, which makes up only 4% of the solar spectrum. Therefore, utilizing a visible-light-active photocatalyst, which can potentially harvest more sunlight (as 40% of solar energy is composed of visible light) for reactions, is more promising for a sustainable water purification system. Several studies have investigated visible-light-responsive photocatalysts for lab-scale water treatment. The effect of Sulfur-doped titanium dioxide on disinfection of the gram-positive bacterium micrococcus Iylae has been reported by Yu et al. (Yu et al., 2005). The results showed a 0.2 mg/mL dosage of S-doped-TiO2 would reduce viable organisms by 96.7% in 1-hour treatment process under visible light source of 100 W halogen lamp with 420 nm cut off filter. Wu et al. evaluated the effect of titanium dioxide nanoparticles co-doped with N and Ag on photocatalytic inactivation of E. coli under visible light (Wu et al., 2010) . They observed that after 30 minutes of visible-light irradiation, E.coli inactivation of 5-log was achieved. Kim et al. introduced Pt/WO3 as a viable solar photocatalyst for water treatment due to the generation of OH radicals under visible light irradiation, stability, and high efficiency of mineralization (Kim et al., 2010). Zyoud et al. demonstrate that although CdS sensitized TiO2 can efficiently inactivate phenazopyridine under visible light, it would leach out hazardous Cd2+ ions in water as a result of decomposition (Zyoud et al., 2010). Hence, CdS sensitized TiO2 seems to have limited future 14 applications in solar water treatment systems unless the Cd2+ leaching out tendency is prevented. The effect of bismuth vanadate (BiVo4), which can be activated by visible light, on water purification has been examined by Yoon et al. (Yoon et al., 2016). They found that the photocatalyst had a minor influence (less than 10%) on the purification process under indoor lighting conditions. Other visible-light-responsive photocatalysts such as bismuth oxyhalides, Silver Phosphate (Ag3PO4), and upconversion materials have also been investigated (Cates et al., 2012; G.-F. Huang et al., 2013; Ye et al., 2014). However, some issues such as low photocatalytic activity, released toxic chemicals, and the potentially high cost of fabrication have limited their application for water treatment systems (Cates et al., 2012; G.-F. Huang et al., 2013; Pelaez et al., 2012). Therefore, considering an alternative material as a visible-light-responsive photocatalyst is essential. 15 Table 2.1. Effect of UV-LED treatment on photocatalytic inactivation. Contaminants Treatment Media UV-LED Wave Length Findings References Rhodamine B dye Aqueous Medium 390–410 nm • The presence of metal ions (Zn2+, Ag+, Fe3+, Cu2+ and Cd2+) negatively affects degradation of RhB dye (Natarajan, Thomas, et al., 2011) Anatoxin-a Pitkäjäärvi Lake Water 260 nm • Anatoxin-a removal of 79% by UVC/H2O2 process was achieved, which was 19% lower than that of aqueous medium due to the presence of high amount of natural organic matter (NOM) (Verma & Sillanpää, 2015) Methylene Blue Demineralized Water (375nm) 375nm • The removal rate of distributed UV-LEDs throughout the reactor is higher than that of UV-LEDs concentrated on one plane in the reactor by 30% (Kuipers et al., 2015) Acetaminophen (ACT), Diclofenac (DCF), Ibuprofen (IBP), and Sulfamethoxazole (SMX) High purity water from a Milli-Q-Water System 365 ± 10 nm, 365 ± 5 nm, 300 ± 5 nm, and 260 ± 10 nm for UVA, high-intensity UVA (UVAH), UVB, and UVC, respectively • UV wavelength was a more effective parameter in decomposition compared to light intensity, meaning that shorter wavelength in order of UVC, UVB, and UVA, has more significant impact on decomposition of pharmaceutical compounds (Eskandarian et al., 2016) Bisphenol-A (BPA) Ultra-pure water (UPW; 18.2MU cm at 25 _C, ELGA LabWater) 365 nm • BPA was completely degraded within 20, 30, and 120min under UV-LED, solar, and LP UV light source) irradiation, respectively (Davididou et al., 2018) 16 2.3.1 CNx Disinfection Since 2009, graphitic carbon nitride (CNx), a metal-free organic polymeric nanomaterial, has emerged as a promising visible-light responsive photocatalyst (W. Wang et al., 2021; Q. Zheng et al., 2017). The backbone of CNx only contains earth-abundant elements of carbon and nitrogen, which enable inexpensive, large-scale material fabrication (Q. Zheng et al., 2017). In addition, proper bandgap and good photoelectric characteristics are other advantages of CNx (W. Wang et al., 2021). Fine-tunning of CNx surface properties has the potential to adapt to different environmental conditions. The ability to alter the reactivity of CNx has made it a powerful resource regardless of water conditions (Quattrini et al., 2016). Viral proteins are effectively oxidized by CNx. According to Zhang et al., viral protein bands observed through Polymer Chain Reaction (PCR) decreased or even disappeared after treatment, manifesting the remarkable breakage of viral surface proteins induced by CNx, which will more likely result in the loss of viral infectivity and the leakage of enveloped RNA. It has also been proven that the most important component of viruses, nucleic acids, can be seriously damaged by CNx photocatalysis under visible-light irradiation (C. Zhang, Li, Shuai, Shen, Xiong, et al., 2019). Similarly, the inactivation of Cryptosporidium parvum in solar disinfection is caused by damage to the oocyst wall, which is made up of over 90% protein (McGuigan et al., 2006). Accordingly, since MS2 is a positive-sense single-standard RNA virus, it can be considered a challenge microorganism for the target pathogen of Cryptosporidium parvum in CNx disinfection experiments. Li et al. explored the effect of polymeric graphitic carbon nitride (CNx) on virus inactivation (Y. Li et al., 2016a). They observed that over 360 min, with CNx loading of 150 mg/L, MS2 with an initial concentration of 1×108 was completely inactivated. It should be noted that no decrease in CNx virucidal performance was observed over five sequential MS2 photocatalytic inactivation cycles. Since a relatively long period was required to inactivate MS2 pathogens completely, Zhang et al. optimized operational parameters such as light intensity, material loading, and reaction temperature. Under the optimized conditions of 200 mW/cm2 light intensity, 135 mg/L material loading, and 24oC reaction temperature, the required inactivation time for 8-log MS2 was reduced to 240 min under visible light irradiation (C. Zhang, Li, Zhang, et al., 2018). Wei et al. observed a complete inactivation of all bacteria within 120 min using improved graphitic 17 carbon nitride with the assistance of Ag (Wei et al., 2020). Huang et al. found that a graphitic carbon nitride polymer is a practical and recyclable catalyst for bacterial inactivation with no bacterial regrowth (J. Huang et al., 2014). The available surface area on the photocatalyst may be important to consider. The mesoporous CNx whose surface area was 20 times larger than bulk CNx inactivated all bacteria, whereas only 50% of bacteria inactivated by its bulk counterpart within 4 hours of visible light exposure (J. Huang et al., 2014). CNx has shown outstanding performance in other photocatalysis applications such as nitrogen fixation, water splitting, CO2 reduction, antibacterial treatment, pollutant degradation, etc (Y. Li et al., 2018; Mao et al., 2018; Yi et al., 2019). For example, Wu et al. used CNx-based material for wound healing, indicating that this material's photothermal effect and antibacterial treatment of sterilization are promising (Y. Li et al., 2018). Although considerable progress has been made in improving CNx performance, several challenges still prevent practical application. Since pristine CNx has limited visible light response and active sites, many modification methods (morphology controlling, structural design and heterojunctions, etc.) have been applied to address mentioned limitations (W. Wang et al., 2021). As a result, it is becoming increasingly difficult to understand the photocatalyst interface properties, particularly on the nanometer scale, which determines their final efficiency. In addition, since most of the CNx-based photocatalytic inactivation systems have been studied under laboratory conditions, for large-scale application significant issues such as immobilization of photocatalyst, recycling methods, and photocatalytic reactor designs need to be addressed. Moreover, there is no oxidation selectivity by ROS produced during photocatalysis. As a result, various microorganisms or other background materials in the water, whether harmful or not, will be removed through this method (W. Wang et al., 2021). 2.4 Effect of Natural Organic Matter (NOM) on Disinfection The decomposition of organic materials and synthetic activities of microorganisms produce organic compounds such as largely aliphatic, highly coloured, aromatic, hydrophobic, hydrophilic, charged, and uncharged components, which are defined as natural organic matter (S. Liu et al., 2013; Matilainen & Sillanpää, 2010). In terms of water quality, NOM can cause taste, colour, and odour, bringing several challenges to drinking water treatment process. For instance, NOM competes with target pollutant removal, affecting the efficiency of activated carbon processess 18 (Ding, 2010). Also, the rate of fouling in membrane filtration systems is impacted by the present of NOM (Amy, 2008; Fan et al., 2001). In addition, NOM causes attenuation of light penetration in UV disinfection, reducing the performance of UV disinfection (Rezaei, 2017). In terms of photocatalytic degradation, NOM can have a significant effect on photocatalytic disinfection. NOM interferes with the adsorption of micropollutants by competing and occupying available binding sites and altering surface charge of photocatalysts through adsorption (G. Liu et al., 2008). In natural waters, NOM typically is at a relatively high concentration (mg/L) compared to trace organics that are the target of removal (e.g. trace pharmaceuticals in the ng/L to µg/L range). Previous studies have shown that the removal of trace organic compounds such as iomeprol, clofibric acid, carbamazepine, 4-chlorophenol, and 1,2,3-trichlorobenzene by TiO2 is reduced in the presence of NOM due to competition for active sites on the TiO2 (Doll & Frimmel, 2005a; Lin & Lin, 2007). However, the parameters affecting the extent of competition, such as pH, was not investigated. Liu et al. investigated the impact of NOM on photocatalytic inactivation of arsenic at different pH, resulting in a reduction of 40% of arsenic adsorption at low pH (G. Liu et al., 2008). Further to the high concentration of NOM competing for active adsorption sites, contaminant adsorption also depends on the chemical structure of NOM. For example, due to the negative charge of some of the NOM components (e.g. with phenolic and carboxylic functional groups) the surface charge of TiO2 would be neutralized or made negative, resulting in a reduction of adsorption of contaminants in anionic form at low pH (J.-K. Yang & Lee, 2006). On the other hand, according to Drosos et al., NOM can also enhance the adsorption of target micropollutants on its surface, providing a high concentration of reactants near the surface of the photocatalysts. Without the support of NOM, reactants collide with photocatalysis only by Brownian motion, while NOM provides sufficient contact for photocatalysis to react with micropollutants (Drosos et al., 2015). The presence of NOM can also decrease photocatalytic oxidation efficiency due to the inner filter effects or blocking/adsorption of UV radiation before reaching the photocatalyst surface. For example, aromatic and olefinic moieties in NOM structure absorb UV at 254 nm and partially filter UV radiation, resulting in fewer generated reactive oxygen species due to the less photons received by photocatalyst (Matilainen & Sillanpää, 2010). 19 NOM can act as a scavenger for generated oxidant species in the system. For instance, positive holes from the surface of the photocatalyst would be scavenged by NOM, which is electron-rich, leading to a reduced oxidation rate (Doll & Frimmel, 2005a; Lin & Lin, 2007; J.-K. Yang & Lee, 2006). In addition, free hydroxyl radicals or ROS in the solution would be scavenged by NOM, resulting in a reduced oxidative effect on the target micropollutants (Doll & Frimmel, 2005a; Rezaei & Mohseni, 2017). There are two oxidation mechanisms, direct oxidation via positive holes on the surface of the photocatalyst, and indirect oxidation, where hydroxyl radicals created by the photocatalytic reaction act as the oxidizer (Rezaei, 2017). While some studies have evaluated the impact of NOM on overall photocatalytic performance, NOM interference with photocatalytic oxidation mechanisms has not been routinely separated. For instance, Lin & Lin and Doll & Frimmel showed that, in general, the presence of NOM negatively affects photocatalysis due to the combination of light attenuation, inhibition and competition effects (Doll & Frimmel, 2005b; Lin & Lin, 2007). 2.5 Characterization of NOM As discussed above, the role and impact of NOM on photocatalytic processes warrants further investigation. However, it is clear that the chemical characteristics of NOM components will influence the overall effect. Numerous organic compounds with distinct properties are defined as NOM. Due to the abundance and variability of compounds classified as NOM in natural waters, it is typically difficult to individually identify and quantify components of NOM. Several surrogates are used to provide an overall indication of NOM concentration, including TOC, DOC, UV absorbance, UV transmittance and chemical oxygen demand (Sillanpää et al., 2015). TOC quantifies all organic carbon in a water sample and is the sum of POC (particulate organic carbon) and DOC (dissolved organic carbon). It should be noted that TOC and DOC are measured indirectly from the carbon dioxide produced by UV-catalyzed chemical oxidation or by high-temperature combustion (Karanfil et al., 2002). It should be noted that accurate measurement of organic carbon can be challenging due to several factors. Organic carbon can be present in water in many different forms, such as dissolved organic matter, suspended solids, and colloids. The presence of these different forms can affect the accuracy and precision of measurements, as they can interfere with analytical methods and cause variations in results. Moreover, other substances present in water can interfere with organic carbon measurements. For example, some inorganic 20 compounds and gases (such as carbonate and methane) can be oxidized by the same reagents used for organic carbon analysis, leading to overestimation of organic carbon concentrations (Kellerman et al., 2014; Stedmon et al., 2003). UV absorbance at 254 nm can also be employed to measure aromatic moieties, providing a good indication of changes in NOM (Pernitsky, 2003; Wright et al., 2016). UV light absorbance can be correlated to DOC concentration in some freshwater systems. Since the relationship between NOM and UV absorbance is unique to each source, correlations should be developed on a source-specific basis (Pernitsky, 2003). It should be noted that the correlation between UV254 and DOC cannot always be established (Cho et al., 2010; Minor et al., 2014; Sadrnourmohamadi et al., 2013). This lack of correlation may be attributed to the presence of NOM that has low UV absorbance (e.g. proteins, sugars) or high nitrate content, which may interfere with this measurement (Leenheer & Croué, 2003). In some cases monitoring UV light absorbance over broader range of wavelengths may provide more advanced characterization (Wright et al., 2016). Chemical oxygen demand measures the concentration of oxidizable organic matter in a water sample (Frisch & Kunin, 1960; Stoddart & Gagnon, 2014). However, it has been demonstrated that the chemical oxygen demand is not sensitive enough for drinking water (Rittmann et al., 1989). Accordingly, a more sensitive photoelectrochemical oxygen demand (peCOD) has been developed and is now commercially available (Stoddart & Gagnon, 2014; Zhao et al., 2004). Although these methods provide valuable insight into the nature of NOM, they are often time-consuming and laborious, necessitating an alternative quantification method for NOM measurement (Baghoth et al., 2011). A recently popular technique for NOM characterization due to its sensitivity and selectivity is fluorescence spectroscopy (W.-T. Li et al., 2014). Fluorescence data is usually collected as high dimensional excitation-emission matrices (EEM). Since NOM is not a homogeneous mixture, it includes many types of organic compounds. In the fluorescence characterization method, compounds with specific molecular structures will be identifiable through their unique excitation/emission regions. The unique fluorescence signatures of chemically distinct components of NOM allow for some degree of separation and characterization. However, in most natural waters, the fluorescence regions of NOM components have a high degree of commonality among individual components, resulting in highly convoluted fluorescence 21 spectra of natural waters (Persson & Wedborg, 2001). Many previous applications of fluorescence characterization of NOM have relied on peak picking, where the intensity at specific excitation/emission pairs is used, or integration over a small range of excitation/emission wavelengths (Chen et al. 2003; He et al., 2011; Nemani et al. 2016). These fluorescence analysis methods are limited in distinguishing between changes to compound concentrations that may fluoresce in the same region. To account for the overlapping nature of organic classes within high-dimensional EEMs multi-way parallel factor analysis (PARAFAC) has been applied (Murphy et al., 2011). While PARAFAC aims to elucidate underlying components which vary in data sets, several studies have shown inconsistencies between observed similar components (Ishii & Boyer, 2012). Therefore, each PARAFAC component likely indicates several organic compounds. However, the variance between samples within defined spectral regions can be represented by the grouping of fluorophores, which show distinct molecular structures (Stedmon & Markager, 2005). 22 Chapter 3: Experimental Methodology This chapter describes the experimental apparatus, material, procedures, and data analysis method to fulfil research objectives. 3.1 UV-LED Disinfection of Unfiltered Water The experiment procedure to investigate the particulate effect of unfiltered water samples on viral UV-LED disinfection is described below. 3.1.1 Water Sample Preparation Water samples were taken immediately before UV disinfection at two full-scale water treatment plants: Duteau Creek Water Treatment Plant (DCWTP) and Mission Hill Water Treatment Plant (MHWTP) in Kelowna, British Columbia. Additionally, a sample of untreated intake water from DCWTP was used (referred to as DC raw) to represent the worst-case scenario of no treatment. Since no treatment was applied before UV disinfection at MHWTP, no additional sample was needed. Samples were collected monthly from October 2020 to August 2021. The water samples were collected in dark glass bottles to prevent photoreactivation and were sanitized and pre-washed with the source water before sampling (Crittenden et al., 2012; Song et al., 2019). Water sample characteristics were measured using the following instruments. Particle size distribution and particle counts were assessed using Zetasizer Nano ZS (Malvern Instruments, Ltd., Westborough, MA). UV light absorbance of water samples (UVA) was measured using HORIBA Scientific – Aqualog, and the zeta potential (ζ) was measured by Zetasizer Nano ZS (Malvern Panalytical). VWR® Turbidity Meter was used to measure sample turbidities, and pH was measured using Thermo Scientific™ Orion™ 3-Star Benchtop pH Meter. TOC and UV intensity were assessed using TOC Analyzer (Shimadzu TOC-L) and ILT2400 Optical “Light” Meter, respectively. It should be noted that all measurements were taken in triplicate to check the repeatability of the results obtained. 3.1.2 Microorganism Propagation and MS2 Assay Male Specific MS2 bacteriophage was used as a conservative surrogate for Cryptosporidium, a widely used method in UV studies (Beck et al., 2016; MaCkey et al., 2002). Freeze-dried vials of Escherichia coli bacteriophage MS2 (American Type Culture Collection (ATCC) 15597-B1) and its host Escherichia coli (ATCC 15597) were rehydrated and propagated following their respective 23 ATCC product sheets. To culture E. coli, LB broth (Miller formulation; Fisher Scientific) was chosen as media for host bacteria. 10 mL of LB was inoculated with 20 μL of frozen E. coli and grown overnight at 37ᵒC. 50 mL of fresh LB was then inoculated with 1 mL of overnight cultured E. coli, followed by incubation at 37ᵒC with continuous shaking at 100 rpm to obtain a culture in its log growth phase. All water samples containing MS2 phage were serially diluted using LB broth medium. Then 50 μL of host cell solution, 0.1 mL of diluted MS2 phage sample and 2-3 mL of molten soft agar (0.6% agar, 40-45ᵒ) were combined. The mixture was then poured onto the solidified 1.5% agar in petri dishes. After hardening the top layer agar, plates were covered and incubated upside down for 16-24 hours at 35-37ᵒ. Observed plaques identified as clear circular zones were counted, multiplied by dilution factor and divided by the sample volume in milliliter to determine the titer in plaque-forming-unit per mL (PFU/mL) (Templeton, 2006). According to USEPA, log-inactivation values of MS2 should be multiplied by 1.77 to represent Cryptosporidium log removal (EPA, 2006). 3.1.3 UV-LED Disinfection: Experimental Procedure A UV-LED system consisting of multichip arrays of UV-LEDs enclosed in a glass housing (PearlLab BeamTM, AquiSense Technologies) was used to carry out inactivation experiments. Water samples containing MS2 were irradiated under LEDs at a wavelength of 256 nm with an average intensity of 478 μW/cm2, measured using an ILT2400 radiometer (International Light Technologies). A petri dish with 70 mm diameter containing 20 mL solution (comprising water sample + MS2 bacteriophage) was placed under the LEDs, and the complete petri dish was illuminated. In all experiments, samples were exposed to four different doses from which 20 μL of the sample was taken at each dose level to conduct serial dilution and MS2 enumeration. All dose-response measurements were taken in triplicate. 3.1.4 UV Inactivation: Kinetics of Bacteria The reduction in the abundance of bacteriophage (N0) due to UV exposure can be described by a double-exponential model as follows (Azimi et al., 2012; Tan et al., 2017): 𝑁𝑁 = (1 − 𝛽𝛽)𝑁𝑁0𝑒𝑒−𝑘𝑘1𝑈𝑈𝑈𝑈𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 + 𝛽𝛽𝑁𝑁0𝑒𝑒−𝑘𝑘2𝑈𝑈𝑈𝑈𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 Eq. (3.1) Where N is the residual number of culturable MS2 after UV exposure in plaque-forming unit (PFU), N0 is the initial number of culturable phages in PFU, and delivered 𝑈𝑈𝑈𝑈𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 is in mJ/cm2. 24 In addition, β (unitless) indicates the fraction of UV-resistant phages, and finally, k1 (cm2/mJ), and k2 (cm2/mJ) represent first-order inactivation rate constants for UV-susceptible and UV-resistance fractions, respectively. 𝑈𝑈𝑈𝑈𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 (mJ/cm2) delivered to the sample is calculated using the following equation (EPA, 2006): 𝑈𝑈𝑈𝑈𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 = 𝐸𝐸𝐷𝐷𝑃𝑃𝑓𝑓(1 − 𝑅𝑅) 𝐿𝐿𝑑𝑑 + 𝐿𝐿 (1 − 10−𝐴𝐴254𝑑𝑑)𝐴𝐴254 𝑑𝑑 ln(10) 𝑡𝑡 Eq. (3.2) Where, 𝐸𝐸𝐷𝐷 = Average UV intensity (measured before and after irradiating the sample) (mW/cm2) 𝑃𝑃𝑓𝑓 = Petri Factor (Unitless) 𝑅𝑅 = Reflectance at the air-water interface at 254 nm (Unitless) 𝐿𝐿 = Distance from lamp centerline (cm) 𝑑𝑑 = Depth of the suspension (cm) 𝐴𝐴254 = UV absorbance at 254 nm (Unitless) 𝑡𝑡 = Exposure time (s) The average UV intensity is calculated from the measured UV intensity incident on the surface of the microbial suspension using the ILT2400 optical light meter, which is 0.478 mW/cm2. Reflectance (R) at the air-water interface can be calculated using Fresnel’s Laws as 0.025. In addition, the Petri Factor term compensates for the fact that the irradiance is not uniform over the entire surface area of the sample container. To calculate this factor, the average irradiance across the sample surface was determined by measuring specific irradiance at a specific distance from the petri dish center along two perpendicular lines that intersect in the middle of the dish. The ratio of the average irradiance to the center irradiance determined the petri factor, which was measured as 0.99 in the experimental setup (Zimmer & Slawson, 2002). It should be noted that the distance from the lamp centerline (L) and depth of suspension (d) were equal to 9.4 cm and 0.52 cm in the experiments, respectively. 3.1.5 Statistical Analysis The statistical significance of the results was determined using Student’s t-test. The difference between two samples was deemed to be statistically significant if the calculated p value was smaller than 0.05. 25 3.2 Photocatalytic Disinfection The experimental procedure to examine the effectiveness of CNx photocatalysis for viral inactivation using MS2 as a challenge microorganism is described in this section. 3.2.1 CNx Preparation Researchers from the UBCO chemistry department made the CNx powders (Wert, 2022). To form CNx powders, 10 g of dicyandiamide was weighed and ground into a fine powder using a mortar and pestle. The powder was then heated to 550 ֯C for 4 hours, cooled to room temperature, ground to fine powder, and then washed using a centrifuge. Finally, the powder was dried at 70oC overnight, yielding roughly 40% CNx by weight each time. 3.2.2 Water Sample Preparation For CNx experiments, water samples of untreated intake water from DCWTP was used (referred as DC raw) to investigate the inactivation efficiency of photocatalytic disinfection on the worst-case scenario of untreated water. 100 mL of microbial suspension in 150 mL beaker was prepared, following the addition of 5, 10, 15, 20 mg of freshly prepared CNx photocatalyst to achieve the desired concentration of CNx for viral inactivation. As described in section 3.1.1, UV light transmittance and turbidity of CNx water samples were measured using HORIBA Scientific – Aqualog, and VWR® Turbidity Meter, respectively. 3.2.3 Photocatalytic Disinfection: Experimental Procedure The disinfection reactions were carried out at room temperature under a UV-LED light source of 365 nm wavelength with an average illumination intensity of 88 mW/cm2. To prevent contamination from the surrounding environment, the beaker was sealed with parafilm. The suspension was stirred with constant speed using a magnetic stirrer throughout the experiment. The system was left in the dark for 30 mins under continuous stirring to establish adsorption-desorption equilibrium before starting experiments. The prepared CNx water sample on stirrer and UV-LED bench scale apparatus have been shown in Figure 3.1. 26 Figure 3.1. CNx Water Sample on Stirrer and UV-LED Bench Scale Apparatus. The total irradiation time was 6 hours, in which the bacteriophage suspension was sampled following 0, 60, 120, 180, 240, 360 mins of illumination. A light control experiment was conducted in which virus suspension without photocatalysis was irradiated under the same condition. In addition, the reaction of virus suspension containing photocatalysis without being exposed to light irradiation was considered a dark control experiment. The inactivation efficiency of photocatalytic viral disinfection is reported as Log (Ct/C0), where C0 and Ct are concentration of bacteriophage before and after irradiation, respectively. Moreover, some experiments were performed in RO water to investigate the effect of water matrix on photocatalytic disinfection. To investigate the effect of CNx adsorption on viral inactivation performance, the concentration of bacteriophage in two sets of samples (using DC raw and RO water as their base water matrix) were enumerated before and after filtration. Samples were irradiated under light UV-LED Bench Scale Apparatus Stirrer Prepared CNx Water Sample 27 source, a portion of which was filtered at specific time interval, and MS2 of both filtered and unfiltered samples were enumerated. 0.2 µm disposable sterile syringe filter was the filter type used in experiments. 3.2.4 Fluorescence Analysis Fluorescence spectra were collected using HORIBA Scientific – Aqualog. Excitation and emission wavelengths were between 240-500 nm (5 nm increments) and 240-830 nm (2 nm increments), respectively. A fluorescence spectrum of RO water was collected and subtracted from each sample to account for the solvent background. The parallel factor analysis (PARAFAC) was applied to analyze the fluorescence excitation emission matrix (EEMs). Based on previous studies., a methodology in which the drEEM toolbox of MATLAB has been used is followed in this investigation (Murphy et al., 2013). The result would give a component model, each of which represents NOM sub-groups that vary independently over the dataset. As indicated in Figure 3.2 EEM dataset would be decomposed into several PARAFAC components. In order to meet the linear assumptions required for PARAFAC analysis Rayleigh and Raman Scatter regions were removed. To validate PARAFAC analysis, the component spectral loadings were compared to general expectations of organic fluorophore signals (e.g. only one emission peak, no abrupt changes in loading) (Peleato et al., 2017). Based on a randomized split of the dataset split-half validation was also performed. An independent PARAFAC model was developed for each unique half, and the components were matched to all other combinations and the complete model. Model results are reported as Fmax values in RU (Residual Unit). Figure 3.2. EEM dataset decomposed into five PARAFAC components © (Murphy et al., 2013), Page 6559, CC BY-NC-SA 2.0. 28 3.2.5 Statistical Analysis To statistically analyze the experiments, linear regressions were compared using a hypothesis test to determine whether the differences between the coefficients and constants in different regression models were significantly important. The proper interaction term needs to be included in the model to identify any significant differences between CNx concentrations and resulting disinfection performance. After creating the categorical variable, the regression model was fitted in which interaction terms, different conditions, and exposure time was defined as independent variables, and log removal of viral inactivation was considered the dependent variable. To derive interaction terms, time was multiplied by different conditions. The coefficients of other conditions indicate whether the differences between regression model constants are significant. It should be noted that the coefficients of varying interaction terms represent if the difference between line slopes of two conditions (the condition multiplied by time and reference condition) is significant. 29 Chapter 4: Impact of Water Characteristics on UV Disinfection of Unfiltered Water 4.1 Introduction UV disinfection is usually recommended to be applied following the filtration process to reduce the concentration of particulates that may interfere with the irradiated light reaching pathogens. The filtration process requires additional infrastructure, leading to increased cost, maintenance, and footprint. Health Canada and USEPA have established exemption criteria, based on which water treatment plants can omit the filtration stage (Health Canada, 2021; USEPA, 2004). These criteria usually specify limits on the number of the particles in water and concentration of pathogens , including influent turbidity levels of less than 1.0 Nephelometric Turbidity Unit (NTU), and consistently low levels of fecal indicator bacteria such as E. coli determined by regular water quality testing (USEPA, 2004). As a result, specific treatment systems may omit the filtration process once they meet the exemption criteria. In addition, due to the low maintenance and operational requirements of small and point-of-use UV disinfection systems, it is more desirable to avoid filtration process utilization. UV reactor would be more prone to high particle concentration of entering water if pre-treatment measures like filtration is not practiced. These particles would cause UV light to be scattered, reflected, or absorbed, reducing disinfection efficiency (Christensen & Linden, 2003). It should be noted that UV disinfection requires a sufficient amount of UV light delivered to target microorganisms to function as intended. Microorganisms might be protected from UV radiation, since they might be surrounded, enmeshed, or otherwise shielded by particles, leading them to survive the disinfection stage (Templeton et al., 2008). The interaction of microorganisms with particles is hypothesized to cause a tailing effect in disinfection performance, where inactivation rate decreases in higher dose. The association with particulate matter provides some degree of protection for microorganisms in a way that additional UV-light irradiation above a specific threshold results in diminishing returns of disinfection performance (Tan et al., 2017). Physical and chemical properties of particles, including size, concentration, surface charge, and hydrophobicity, as well as characteristics of microorganisms, are crucial factors in defining the strength and extent of microorganisms-particle association (Cantwell & Hofmann, 2008; 30 Farrell et al., 2018; Templeton et al., 2008). Currently, the acceptable water quality condition for the application of UV disinfection for unfiltered water supplies in water treatment plants and small systems has not been sufficiently investigated. Therefore, this chapter wants to identify if water quality characteristics that account number of particles (e.g. turbidity/UVT) can be considered as effective disinfection-performance indicator. 4.2 Result and Discussion 4.2.1 Water Quality Characterization This study used three different sources of untreated water, each with different levels of treatment. Two of the sources were taken from upstream UV disinfection at two different water treatment plants (DCWTP and MHWTP), while the third source was taken directly from the influent source water of DCWTP (DC raw). The raw water from DCWTP was treated by dissolved air flotation process using poly aluminum chloride, coagulation and flocculation aid (Epi Amine and Hydrofloc) before undergoing UV disinfection. On the other hand, no treatment was applied before UV disinfection at MHWTP. The water samples were collected over a year to account for seasonal variations in water quality, and no filtration process was employed in either case. This was done to evaluate the effectiveness of UV disinfection at two unfiltered facilities. Water chrachteristics, including turbidity and UVT, were recorded during sampling period, which was from May 2021 to September 2021. As has been indicated in Figure 4.1(a), there is an increasing trend in turbidity during summer (July-August 2021) for the two non-treated water samples (MH pre-UV and DC raw water). There are various reasons that can cause turbidity changes, including recreational activities or the formation of calcite due to a rise in water temperature. (Korchef & Touaibi, 2020; Schafft et al., 2021). Calcite precipitation is more likely to occur in MHWTP, whereas DCWTP is affected by rainfall and runoff. It is worth mentioning that the pH variation for all three water samples over the year was between 6.9-8.2. 31 Figure 4.1. (a) Turbidity over the one-year sampling period © (Soleimanpour Makuei et al., 2022), Page 253, Used by persmission , (b) Average UV transmittance at 254 nm. Figure 4.1(a) illustrates that turbidity levels of pre-UV samples were consistently less than 1.0 NTU until August 2021, owing to the pre-treatment at DCWTP. However, the turbidity levels of DC raw water samples varied between 1.1 and 3.5 NTU. UV transmittance at 254 nm was recorded during sampling period from October 2020 to August 2021. Figure 4.1(b) indicateds that both pre-UV water samples had a constant high UV transmittance above 85%, indicating that the UV light easily penetrated the water. The DC raw water, which was the most coloured sample, had an average UV transmittance of 45.23% and reached a minimum of 33.94% in April 2021. 4.2.2 Average Inactivation Throughout December 2020 to September 2021, three water samples were collected each month from three specified locations for analysis. Figure 4.2 shows the average UV inactivation of each sample over the year. Given that the exposure times were constant at 15, 25, 80, and 100 seconds during all experiments, UV doses depicted on figure are adjusted based on water quality using Eq. 3.2. According to Figure 4.2, the inactivation efficiency does not significantly improve with additional UV dose over 30 mJ/cm2 (p > 0.05 in all water samples, n=11). Therefore, applying an additional UV dose may not be worth the associated cost. While the control experiment (RO water with no particulates) showed higher disinfection performance than the other three samples, it followed a similar tailing effect at UV dose above 30 mJ/cm2 as indicated in Figure 4.2. The higher disinfection rate in the control experiment shows that water quality is an influential factor that dampens UV disinfection effects. Even in the control experiment, a sample without particulates or a) b) 32 other components, tailing effects still occur. This could be attributed to the clumping of organisms in the solution, which may result in some microorganisms surviving the UV exposure. Since the initial phage concentration in all experiments was 108 PFU/mL, the plateau occurs after 30 mJ/cm2 does not indicate complete elimination of MS2. While tailing effect significantly pronounced in MH pre-UV water sample, a high quality water sample which shows turbidity level less than 1.0 NTU, and UVT higher than 85% most time of the year (Figure 4.1), DC pre-UV (turbidity < 1.0 NTU, UVT > 85%) exhibits a considerable increase in inactivation compared to the other two water samples, specially above UV dose of 30 mJ/cm2. As indicated, DC pre-UV sample displays statistically significant improvement in viral inactivation performance compared to DC raw water and MH pre-UV samples at two high doses of 30 mJ/cm2 (1.2 log increase) and 50 mJ/cm2 (1.1 log increase) (p < 0.001). It can be concluded that although the tailing effect is present in all types of samples after approximately 30.0 mJ/cm2, treatment process through coagulation and dissolved air floatation before disinfection stage significantly improves the average viral inactivation at higher UV doses. Figure 4.2. The average viral inactivation of MH, DC pre-UV, and DC raw over a year at four different UV doses under UV wavelength of 254 nm. Doses are adjusted based on Eq. 3.2 to estimate the actual dose delivered; exposure times were constant for all tests. Error bars represent one standard deviation (n = 11). 33 Table 4.1 confirms that UVT is not an effective indicator of viral disinfection performance of water. As shown, there is a significant difference in UV transmittance between DC raw and MH pre-UV water samples; however, difference in the viral log removal in these samples is not significant. Table 4.1. Average UV transmittance and log removal values for all water samples at three different doses over a year. All log removal values have been calculated based on interpolation. DC raw DC pre-UV MH pre-UV Control Avg. UVT (%) 45.23 86.94 93.74 99.99 Log removal @ 15 mJ/cm2 1.15 1.10 0.97 1.65 Log removal @ 30 mJ/cm2 2.17 2.49 1.90 3.67 Log removal @ 45 mJ/cm2 2.56 3.14 2.44 4.22 4.3 Summary The aim of this research was to provide guidance for drinking water treatment plants when pre-filtration is not practiced. In addition, quality characteristics of unfiltered systems that may interfere with UV disinfection has ben investigated. The results show that UV dose response curve could not be attributed to the conventional treatment indicators such as turbidity and UV transmittance. Even high-quality unfiltered water supplies with less than 1 NTU turbidity could significantly protect microorganisms from UV light due to enmeshment or attachment mechanism of particles. In summary, uniform turbidity level or UVT can not be considered as effective performance indicators for unfiltered UV disinfection system. Additionally, the results suggest that pre-treatment should be considered for high-quality surface waters with pathogenic contamination to minimize public health risks. To accurately assess the potential of UV disinfection, it is necessary to characterize water quality beyond just turbidity and UVA/UVT. 34 Chapter 5: Natural Water Matrix Effects on CNx Photocatalytic Disinfection 5.1 Introduction A prevalent concern with chlorination is the formation of potentially mutagenic and carcinogenic disinfection by-products (DBPs). Many alternative processes for the disinfection of drinking water have been developed in an effort to decrease public exposure to chlorination DBPs (Dalrymple et al., 2010). Among the alternatives, photocatalysis is a promising advanced oxidation method that utilizes visible and/or UV light to inactivate of wide range of microorganisms (Adán et al., 2017; Cruz-Ortiz et al., 2017; Pulgarin, 2015). Titanium Dioxide (TiO2) has been shown to be the most mature photocatalytic material used in water treatment due to its non-toxicity and low price (W. Wang et al., 2017; Q. Zheng et al., 2017). However, it would be mainly activated under ultraviolet (UVA) high-energy radiation, which makes up only 4% of the solar spectrum. Therefore, utilizing a visible-light-active photocatalyst, which can potentially make better use of sunlight (as 40% of solar energy is composed of visible light), is more promising for a sustainable water purification system. Since 2009, graphitic carbon nitride (CNx), a metal-free organic polymeric nanomaterial, has emerged as a promising visible-light responsive photocatalyst (W. Wang et al., 2017; Q. Zheng et al., 2017). Many factors may affect the antibacterial activity of photocatalysts, including light wavelength, irradiation patterns, water quality (dissolved oxygen (DO), natural organic matter (NOM), temperature, pH, inorganic ions, etc.), bacterial types and concentration, and photocatalytic loading (Ishiguro et al., 2011; Rincón & Pulgarin, 2003). Previous studies have shown that increased light intensity can improve the inactivation efficiency of semiconductor photocatalysts (Rincón & Pulgarin, 2003; C. Zhang, Li, Zhang, et al., 2018). However, higher light intensity could cause the waste of energy and increase recombination of photogenerated carriers, resulting in lower inactivation efficiency (Gupta & Pal, 2014; Tanveer & Tezcanli Guyer, 2013; C. Zhang, Li, Shuai, Shen, & Wang, 2019). The concentration or amount of available photocatalyst may also impact the level of inactivation achieved. Previous studies have confirmed that an optimal loading of CNx based photocatalysts for wastewater disinfection exists (Y. Li et al., 2016b; C. Zhang, Li, Shuai, Shen, & Wang, 2019). Increasing CNx loading would result in more active sites and inactivation efficiency improvement. However, as CNx loading increases, light penetration decreases and 35 therefore, excessive amounts of CNx would lead to reduced disinfection efficiency (Gong et al., 2017; Ng et al., 2016). Factors like dissolved oxygen (DO), natural organic matter (NOM) concentration and character, temperature, pH, inorganic ions, and turbidity on photocatalytic disinfection must be considered. Increased dissolved oxygen is conducive to ROS production and improves photocatalytic disinfection activity (C. Zhang, Li, Shuai, et al., 2018). Furthermore, antibacterial effects will be promoted by lowering pH due to synthesizing acid shock proteins. However, the influence of pH on viral inactivation is more varied (Chong et al., 2010; L. Lei et al., 2020; Ng et al., 2016). Zhang et al. observed that lowering pH improved virus (MS2) inactivation by g-C3N4/EP-520. The authors noted that this might be due to electrostatic repulsion between photocatalysts and viruses, which is decreased at lower pH (C. Zhang, Li, Shuai, et al., 2018). NOM is present in all natural waters, and its influence on photocatalytic behaviour should be considered. Previous work has shown that NOM can inhibit the generation of reactive oxygen species leading to reduce photocatalytic inactivation rate (Tong et al., 2013). Organic matter can inhibit the inactivation process in two different ways. The low molecular weight fraction of NOM could consume ROS, reducing ROS concentrations available to react with bacteria. Larger molecular weight NOM can protect bacteria from photocatalytic inactivation by forming a protective layer on the surface of microorganisms (Guo et al., 2018). Partial inorganic ions, including Fe2+, Co2+, and Cu2+ can significantly improve photocatalytic efficiency via Fenton reaction or Fenton-like reaction (Cheng et al., 2019). On the other hand, other inorganic ions (PO43-, SO42-, and CO32-) could be adsorbed on the surface of CNx that capture free radicals, leading to the inhibition of bacterial inactivation (J. Wang et al., 2017; W. Wang et al., 2018). It should be noted that viral inactivation efficiency can be promoted by salinity (NaCl) and hardness (Ca2+) (C. Zhang, Li, Shuai, et al., 2018). Some ions, such as Na+, Cl-, and Br- have negligible effects on photocatalytic disinfection (Koizumi & Taya, 2002). The adsorption process of microorganisms on the photocatalyst surface can enhance viral removal in photocatalytic disinfection (X. Zheng et al., 2018). Niu et al. and Kang et al. modified surface property of CNx to control carrier recombination and increase reactant adsorption on its surface, resulting in accelerated surface catalytic reactions (Kang et al., 2016; Niu et al., 2014). Koizumi and Taya reported that once some inorganic ions lowered the adsorption of viral particles 36 to TiO2 surface, the viral inactivation efficiency was significantly decreased (Koizumi & Taya, 2002). Moreover, the photocatalytic reactions of TiO2 can be improved by polar attractions between TiO2 and charged anionic organic compounds that result in intensified adsorption onto the photon-activated TiO2 surface (Gogniat et al., 2006). CNx photocatalysts in the reactors can be dispersed in the liquid phase by mechanical agitation, immobilized on a surface, supported on particles, or forming a catalytic bed. Using a slurry system is challenging since the complexity of the overall process would be increased due to necessitating further separation steps, such as filtration or centrifugation. However, the suspensions are easier to work with and provide higher efficiencies than immobilized catalysts because of the higher ratio of active catalytic surface to reaction volume and fewer mass transfer limitations (Augugliaro et al., 2006). On the other hand, immobilizing a powdered photocatalyst onto a suitable support would also lead to reduced operation time and cost. Furthermore, fixing the photocatalyst avoids the potential risk of releasing nanomaterials to the environment or potable water supply. Therefore, it is of interest to improve supported photocatalytic systems, as their efficiencies are currently lower than that of slurry systems. Faraji et al. immobilized CNx and SnO2 on TiO2 NTs/Ti plates, resulting in the highest antimicrobial activity under UV or visible light irradiation compared with CNx / TiO2 NTs/Ti and SnO2 / TiO2 NTs/Ti plates (Faraji et al., 2018). This chapter evaluates the effect of CNx photocatalytic disinfection in real water matrices, considering the quenching effect from natural organic matter. In addition, the light sources used in previous studies for CNx were high-power Xenon lamps. In this chapter, CNx disinfection efficiency will be investigated using low power light source of LED. Other parameters have been investigated, including the effects of CNx loading, CNx adsorption, and CNx immobilization on viral inactivation performance. It should be noted that unless otherwise mentioned, all viral samples for this chapter’s experiments have been prepared using DC raw water without applying any filtration. 37 5.2 Result and Discussion 5.2.1 Viral Disinfection in Light & Dark Controls As indicated in Figure 5.1, the dark control sample (CNx without light exposure) started with 0.59 log removal after one-hour of exposure, reaching 0.56 log removal at the end of the experiment, which shows no significant change (p = 0.20, n=7). The initial inactivation observed (0.59 log) could be due to the CNx interfering with the MS2 bioassay or adsorption of MS2 to the CNx, which would limit the ability to form plaques. The consistent inactivation level with time suggests that if MS2 is being adsorbed to the CNx or if there is some other inhibitory effect, it is maximized quickly. Increasing holding times do not increase MS2 loss. The light control indicated that, compared to the dark control experiment, MS2 were considerably inactivated by direct photolysis to 2.60 log removal under light irradiation of 88 mW/cm2 at 365 nm (dose range of 316,800 mJ/cm2 (3.168 MJ/m2) - 1,900,800 mJ/cm2 (19.008 MJ/m2)). As indicated in Table 5.1, Kelowna's mean daily global sunlight insolation (13 MJ/m2) is in the same range of irradiated dose in the experiments. Therefore, this study can provide a valuable estimation of CNx performance under solar irradiation. It should be noted that in these experiments, the light irradiated in a single wavelength (365 nm), while the solar spectrum covers wavelengths ranging from Gama rays (< 10 pm) to Radio waves (> 1 mm), which can help in increasing photocatalytic reactions (Q. Zhang et al., 2021). Previous studies have also shown photolytic treatment of MS2 bacteriophage under solar irradiation. Mahon et al. found MS2 as the most resistant phage compared to PR772 and ΦX174, reaching 3.8 log removal after 4 hours of exposure (Mac Mahon et al., 2017). The reported higher inactivation rate of MS2 compared to the current study could have been attributed to the solar reactor structure leading to higher radiation intensity and the wide range of the irradiated solar light spectrum. In another study, 2.5 log removal of MS2 was observed after 7 hours of natural sunlight exposure, which had an average higher intensity than the current study (Misstear & Gill, 2012). According to Misstear and Gill, phages may behave very differently under not precisely the same experimental conditions due to the variation in meteorological conditions from completely overcast to fully sunny. 38 Figure 5.1. Photocatalytic inactivation efficiency against MS2 in light control (viral suspension without CNx under light exposure), dark control (CNx without light exposure) sample, and viral suspension without CNx and light exposure. Comparing all three plots shown in Figure 5.1, it is evident that light is the most influential parameter, leading CNx to have a possible toxic effect on MS2 virus particles after the first hours of exposure. In other words, CNx has no toxic effect on MS2 in the dark (Y. Li et al., 2016a). Table 5.1. Mean daily global sunlight insolation in the city of Kelowna, BC. Month Mean daily global insolation (MJ/m2) January 3.7 February 6.9 March 12 April 17.2 May 20.4 June 22.2 July 23.3 August 19.8 September 14.3 October 8.6 November 4.1 December 2.9 Annual 13 39 5.2.2 Effect of Different CNx Doses The performance of viral photocatalytic disinfection for different doses of CNx is shown in Figure 5.2 (a)&(b). It should be noted that according to the linear regression hypothesis test (described in section 3.2.5), the co-existence of CNx and light has significantly improved viral inactivation performance for the CNx concentrations of 50 mg/L, 150 mg/L, and 200 mg/L, compared to the light control condition (p < 0.005). As indicated in Table 5.2, a small amount of CNx (50 mg/L) results in a viral inactivation rate increase of 43%. Increased inactivation rates of 57% and 43% for CNx concentrations of 150 mg/L and 200 mg/L were also observed. Figure 5.2 (b) demonstrates that even with a small amount of CNx (50 mg/L) the viral inactivation rate has increased by 43%. After introducing CNx, the inactivation increased from ~ 2.6 log (light control) to 3.4 - 4.2 log at CNx concentrations of 50 - 200 mg/L. Maximum inactivation was observed (4.2 log) at a photocatalyst concentration of 150 mg/L after 360 min of exposure. It should be noted that the CNx disinfection rate at a photocatalyst concentration of 100 mg/L was not significantly different from the light control experiment condition, showing less disinfection rate than other CNx concentrations (p = 0.76). The uniquely low performance at 100 mg/L could have been due to possible errors in the experiments, including agglomerating MS2 in the water sample during the experiment leading to decrease plaque formation. It is also possible that, while increasing photocatalyst concentrations can increase active sites and reaction rate in water, light penetration could be restricted and decrease viral inactivation efficiency (C. Zhang, Li, Zhang, et al., 2018). As indicated in Figure 5.3, UV Transmittances of DC raw water samples at 365 nm, considerably decrease with the increase of CNx concentration (p = 0.004). Furthermore, increasing CNx concentrations significantly affect turbidity (p = 0.005), decreasing light penetration. High photocatalyst loading could also promote particle agglomeration, causing a reduction in active sites, which results in lower inactivation efficiency (Chong et al., 2009; Ochuma et al., 2007). As has been confirmed in previous studies, an optimal photocatalyst concentration exists for water viral disinfection (Y. Li et al., 2016b; C. Zhang, Li, Shuai, Shen, & Wang, 2019). 40 Figure 5.2. a) Photocatalytic inactivation efficiency against MS2 in the presence of different doses of CNx under visible light irradiation, b) Variations of final viral inactivation after 6 hours with different CNx concentrations. -2.60-3.62-2.54-4.18-3.41-4.50-4.00-3.50-3.00-2.50-2.00-1.50-1.00-0.500.000 50 100 150 200Final Viral Inactivation after 6 Hours (Log C/C0)CNx Concentration (mg/L)(b) (a) 41 Table 5.2. Viral inactivation rates for different CNx concentrations. CNx Concentration (mg/L) Log Removal Rate (Log/min) 0 (Light Control) -0.007 ± 0.001 50 -0.010 ± 0.002 150 -0.011 ± 0.002 200 -0.010 ± 0.002 Figure 5.3. Variations of UVTs @254 nm and @365 nm, and turbidity with different CNx concentrations. Therefore, it can be concluded that, in general, CNx addition could improve disinfection efficiency. Since 150 mg/L was the most effective concentration, all subsequent experiments were conducted with the CNx loading of 150 mg/L. The inactivation of MS2 with an initial concentration of 1×108 PFU/mL within 360 mins with 150 mg/L CNx loading is visualized in Figure 5.4. MS2 bacteriophages can form plaques on agar plates that are generally small and clear in appearance. These plaques are circular or irregular in shape, and are often surrounded by a slightly hazy or cloudy zone of bacterial growth. 42 Figure 5.4. MS2 plaque formation before and after CNx photocatalytic disinfection with CNx concentration of 150 mg/L. It should be noted that no significant improvement in disinfection efficiency between different CNx concentrations was noted, indicating only a small amount of CNx is needed to enhance disinfection performance. It was expected that increasing CNx concentrations would result in higher inactivation rates. However, as described in section 2.3, the photocatalytic reaction process comprises a chain of events, taking time for reactive oxygen species to be formed and then react with organisms to perform disinfection. Therefore, the rate of the disinfection process may depend on the time required for ROS formation, which does not depend on CNx concentration. As indicated in Figure 5.3, the light transmittance of DC raw water sample (CNx concentration = 0 mg/L) at 365 nm is 63% higher than that of 254 nm. This means that if DC raw water needs to be disinfected using a photocatalytic method, CNx may be more proficient photocatalyst compared to TiO2, which is being activated under UV light. 5.2.3 Viral Re-activation Assessment Viral re-activation tests were also conducted for filtered and unfiltered samples (using both DC raw and RO water as base water) to provide further insight into virucidal effects. After 72 hours of incubation in the dark for viral self-repair, no additional plaques were formed for both filtered and unfiltered samples (in both base waters), indicating that the re-activation mechanism of MS20 min 120 min 240 min 360 min Control 43 1Fe2++H2O2 → Fe3++HO-+HȮ Fe3++H2O2 → Fe2++H++HȮ Cu++H2O2 → Cu2++HO-+HȮ had been permanently disabled instead of suppressing reproduction ability. According to the experiment results for RO water sample, MS2 concentration was decreased by 62% after 72 hours of incubation. A similar result has been reported by many studies, confirming that photocatalysis leads to permanent inactivation (Gelover et al., 2006; Y. Li et al., 2016b; C. Zhang, Li, Shuai, et al., 2018; C. Zhang, Li, Zhang, et al., 2018). However, specific studies do identify the reactivation of resistant pathogens after illumination of 360 mins with high UV doses (147 and 439 mW s/ cm-2) without photocatalysis presence (Gilboa & Friedler, 2008). Therefore, photocatalysis in comparison with UV-light may be a more proficient approach for viral disinfection. 5.2.4 Effect of Natural Water Matrix Effects A comparative experiment was done using RO as background water to investigate the effect of the natural water matrix. It was expected that the efficiency of photocatalytic disinfection would be reduced due to the presence of organic impurities. As mentioned previously, organic impurities can inhibit inactivation either by consuming ROS or protecting organisms by forming a protective layer on the surface of microorganisms (Guo et al., 2018). Incident light can also be reflected, scattered, or absorbed due to the high turbidity and/or the presence of NOM in natural water matrices (Chong et al., 2010; C. Zhang, Li, Shuai, Shen, & Wang, 2019). However, as indicated in Figure 5.5, the inactivation efficiency of CNx in RO water after 6 hours of exposure was 38% lower than that of CNx in DC raw water (p = 0.000). The increased performance in a natural water matrix may be attributed to the increase of hardness or humic acid in the DC raw water sample. The metal ions in DC raw water (e.g. Ca2+) can coordinate with abundant negatively charged nitrogen in CNx to help in charge separation (Gao et al., 2014). Ions could also bridge CNx and MS2 to enhance electrostatic attraction between the photocatalyst and viruses (C. Zhang, Li, Shuai, et al., 2018). Moreover, inorganic ions, including Fe2+, Co2+, and Cu2+ can significantly improve photocatalytic efficiency via Fenton reaction or Fenton-like reaction (Cheng et al., 2019). These reactions feature in advanced oxidation technologies to remediate organic pollutants1. In addition, some previous studies confirmed that increasing influent humic acid (HA) concentration had a 44 positive effect on E. coli removal efficiency by photocatalysis (J. Du et al., 2021; X. Li et al., 2022; H. Liu et al., 2020; Porras et al., 2018). It should be noted that there exists an optimal value for humic acid concentration, as further increase would result in more adsorption between humic acid and E. coli. Therefore, contact between reactive species and E. coli would be inhibited, decreasing bacterial removal efficiency (X. Li et al., 2022). It is worth mentioning that the effect of inorganic ions in TiO2-UV systems has shown varying results. For instance, Ca2+ was found to reduce the adsorption of viral particles to TiO2 surface, resulting in significantly compromised viral inactivation (Koizumi & Taya, 2002). Interestingly, results from this study showed that despite a decrease in inactivation efficiency of UV-LED disinfection systems due to the particulate effect of unfiltered water samples (Chapter 4), the presence of organic matter or ions in natural water matrices promoted viral inactivation performance in a CNx photocatalytic disinfection system. Therefore, CNx may offer a low-cost and environmental-friendly approach for the next generation of sustainable antimicrobial materials that can be used for drinking water viral disinfection systems (W. Wang et al., 2019). 45 Figure 5.5. Photocatalytic inactivation efficiency against MS2 for RO and DC raw water samples of CNx under 365 nm light irradiation. The difference in maximum viral inactivation of the dark control experiment from that of viral suspension with neither light nor CNx exposure has been indicated in Figure 5.5, with the difference α, showing the effect of CNx addition individually on maximum disinfection performance. Similarly, the difference in maximum viral inactivation of light control experiment from that of viral suspension with neither light nor CNx exposure has been indicated with up-down arrow β, representing the effect of light irradiation individually on maximum disinfection performance. It would be expected that, if applying CNx and light irradiation does not have synergistic effect, the maximum viral inactivation would reach the point shown by λ in Figure 5.5 once both CNx photocatalyst (with same dose) and light irradiation are applied simultaneously in the experiment. However, as indicated in Figure 5.5, due to the synergistic effect of CNx photocatalyst under light irradiation, the maximum inactivation efficiency of viral DC raw water sample containing CNx dose of 150 mg/L reached to 4.2 log removal, which was higher than expected. Table 5.3 shows an overview of previous studies investigating viral disinfection efficiency of graphitic-carbon nitride (CNx). Due to the variation of photocatalyst dose, light source and 46 intensity, water matrix, water temperature, ionic species, etc., a wide range of disinfection efficiencies for viral inactivation have been reported. In this study, the light was irradiated at a single wavelength (365 nm) with comparatively lower intensity (~half intensity of Xenon lamp experiments). Light sources used in previous studies were high-power Xenon lamps covering visible wavelengths, which can help increase photocatalytic reactions (Q. Zhang et al., 2021). In addition, quenching effects from natural organic matter in real water matrices have also contributed to lower disinfection efficiency compared to previous studies. Table 5.3. Overview of previous studies investigating viral disinfection efficiency of graphitic-carbon nitride (CNx) Material Virus Catalyst Loading (mg/L) Virus Level (PFU/mL) Light Source Light Intensity (mW/cm2) Water Matrix Time (min) Reduction Ref. CNx Phage MS2 150 1ₓ108 300W Xenon lamp with a 400 nm cutoff filter 150 PBS 300 8-log (Y. Li et al., 2016b) CNx Phage MS2 135.4 1ₓ108 Xenon lamp with a 400 nm cutoff filter 199.8 PBS 240 8-log (C. Zhang, Li, Zhang, et al., 2018, p. 4) CNx Phage MS2 150 1ₓ108 60 W UV-LED Light Source @ 365 nm 88 DC raw Water 360 4.2-log Present Study PBS: phosphate-buffered saline. 47 5.2.5 CNx Adsorption To investigate the influence of CNx adsorption on disinfection performance, MS2 in filtered RO and DC raw water samples was also enumerated (Figure 5.6). According to regression analysis performed for all filtered and unfiltered samples, filtration did not significantly improve disinfection performance for both DC raw and RO water samples (p = 0.072 for DC raw water, p = 0.53 for RO water). This result supports the argument that MS2 is not adsorbed considerably on the CNx photocatalyst surface due to the electrostatic repulsion between CNx and MS2. According to previous studies, both MS2 and CNx show predominantly negative charge in water, leading to the repulsion force between CNx and MS2 (Michen & Graule, 2010; Zhu et al., 2015). The results confirm that adsorption played a less important role than photocatalysis in this system in the presence of light irradiation. This result has also been confirmed by the dark control experiment shown in Figure 5.1 where the difference between the dark control sample and the viral sample with neither CNx nor light radiation was insignificant (p = 0.35) (Figure 5.1). The efficiency of viral removal in dark conditions may indicate the level of CNx adsorption and its marginal contribution to overall disinfection. As Figure 5.1 shows, the maximum removal efficiency in dark control was 0.56 log, indicating that adsorption plays a less important role than photocatalysis in this system's inactivation mechanism. Similar results have been reported by Zheng et al. in Cu-TiO2 disinfection system (X. Zheng et al., 2018). Figure 5.6. Photocatalytic inactivation efficiency against MS2 for filtered and un-filtered water samples of CNx under 365 nm light irradiation 48 5.2.6 CNx Immobilization The effectiveness of immobilized CNx on glass for viral inactivation was also investigated. CNx was immobilized on glass slides using an aminosilanization method for this experiment. The regression hypothesis test (described in section 3.2.5) confirmed that CNx aminosilanized glass slides did not improve inactivation efficiency compared to the light control experiment (p = 0.34, Figure 5.7). Compared to the slurry system, the immobilized CNx provides a lower ratio of active catalytic surface to reaction volume and has higher mass transfer limitations of microorganisms to the surface of the catalyst, leading to lower efficiency than that of a slurry system (Augugliaro et al., 2006). A similar trend has been reported in previous studies (Alrousan et al., 2012; S. J. Khan et al., 2012; van Grieken, Marugán, Sordo, Martínez, et al., 2009; van Grieken, Marugán, Sordo, & Pablos, 2009). None of these cases shows inactivation efficiency for an immobilized system outperforming a slurry photocatalyst system. Figure 5.7. Photocatalytic inactivation efficiency against MS2 for immobilized CNx under 365 nm light irradiation. 5.3 Summary Carbon nitride (CNx) is a metal-free organic polymeric nanomaterial which shows a promising performance as a visible-light responsive photocatalyst. In this chapter, the performance of CNx for viral inactivation was investigated. The results indicated that while CNx has no toxic effect on MS2 in the dark, exposure to light at 365 nm from a UV-LED system led to photocatalytic 49 disinfection of MS2. It was found that only a small amount of CNx is needed to enhance disinfection performance overexposure to light. Although CNx concentration did not significantly impact overall disinfection performance, the greatest inactivation performance was seen with 150 mg/L CNx as a slurry. Results also suggest that it is possible that an optimal concentration of CNx exists, where excessive amounts could inhibit light penetration and overall effectiveness. Moreover, the results demonstrate that CNx can permanently inactivate MS2, preventing MS2 from re-activating in the dark. Importantly, despite a decrease in inactivation efficiency of UV-LED disinfection system due to the particulate effect of unfiltered water samples, the presence of particles and organic impurities in real water matrices promoted viral inactivation performance in CNx photocatalytic disinfection system. Furthermore, the results indicate that adsorption plays a less important role than photocatalysis in this system. Although it would be desirable to have immobilized CNx to negate the need for downstream processes to remove CNx, CNx attached to aminosilanized glass slides did not improve inactivation efficiency compared to the light control experiment. 50 Chapter 6: Impact of CNx disinfection on Natural Organic Matter using Fluorescence Spectroscopy 6.1 Introduction The efficiency of drinking water treatment is significantly impacted by natural organic matter (NOM) present in the source waters. Regarding water quality, NOM causes taste, colour, and odour, bringing several challenges to water treatment. In addition, commonly used disinfectants such as chlorine react with organic matter to form a range of disinfection by-products, which result in some degree of public health risk (Hrudey, 2009). Water facilities often implement several processes contributing to the overall removal of natural organic matter. For instance, the application of enhanced coagulation practices to remove TOC, thereby controlling the formation of trihalomethanes (THMs) and haloacetic acid (HAAs) in drinking water systems, has been advised by the USEPA (USEPA, 1999). Photocatalytic oxidation methods have emerged as an alternative to degrade or remove NOM (Bekbolet et al., 2005). Generally, oxygen radicals produced by advanced oxidation processes attack NOM at rich electron sites, resulting in NOM breakdown and mineralization to form carbon dioxide and water (Soliman et al., 2021). The hydroxyl radicals (ȮH) are one of the most powerful oxidants that can react with NOM compounds. To generate hydroxyl radicals (ȮH) numerous photocatalysts have been used to inactivate microorganisms (Natarajan, Natarajan, et al., 2011). NOM can inhibit viral or bacterial photocatalytic inactivation in three different ways. The incident light may be blocked out or absorbed by NOM, known as the inner filter effect (Brame et al., 2015). The second inhabitation mechanism is when the photocatalyst surface accumulates NOM, resulting in a reduced number of active sites to generate ROS. A third mechanism of inhabitation is acting as a scavenger of ROS, quenching holes and hydroxyl radicals (Birben et al., 2017). It is worth mentioning that while NOM often interferes with bacterial or viral inactivation by photocatalysis, the specific UV absorbance of solution is gradually reduced with exposure time. This bleaching of the NOM suggests degradation and affirms competitive scavenging of ROS, but also increases the effectiveness of UV-based disinfection as the reaction proceeds (Fouad et al., 2021). NOM is a mixture of complex heterogeneous organic compounds, such as humic substances (humic acid, fulvic acid humans, and tannic acid), proteins, and carbohydrates (Peleato et al., 2017; Soliman et al., 2021). The definition of NOM includes breadth of chemical 51 characteristics. Therefore, the analysis techniques, which provide information regarding specific subfractions are advantageous as opposed to the measurement of total quantity. These distinct NOM sub-fractions would have varying responses to treatment and distinctive impact on final water quality (Peleato et al., 2017). Fluorescence spectroscopy is a sensitive and selective technique that can be used to identify NOM sub-fractions (W.-T. Li et al., 2014). Fluorescence data is usually collected as high dimensional excitation-emission matrices (EEM). NOM sub-fractions with varying molecular properties and structures will fluoresce in distinct regions of the EEM. While this allows for some separation of sub-fractions, the fluorescence regions of many NOM constituents have a high degree of commonality, resulting in highly convoluted fluorescence spectra of natural waters (Persson & Wedborg, 2001). To account for the overlapping nature of organic classes within high-dimensional EEMs, multi-way parallel factor analysis (PARAFAC) has been applied (Murphy et al., 2011). While PARAFAC aims to elucidate underlying components, several studies have shown inconsistencies between observed similar components (Ishii & Boyer, 2012). Therefore, each PARAFAC component likely indicates several organic compounds. However, variance between samples within defined spectral regions can be represented by the grouping of fluorophores which indicate distinct molecular structures (Stedmon & Markager, 2005). In this chapter, the fluorescence spectroscopy technique has been applied to characterize the impact of photocatalytic oxidation on organic matter of DC raw water prior and after light irradiation. Results from this work will be useful to investigate the influence of organic matter character on photocatalytic disinfection process efficiency and resulting water quality. 6.2 Result and Discussion 6.2.1 PARAFAC Analysis A sample of collected flouresence spectra of one water sample before being decomposed by PARAFAC method has been indicated in Figure 6.1. EEMs display peak locations and intensities that can be used to compare molecular composition and quantification. Application of parallel factor analysis (PARAFAC) to a set of 53 samples resulted in a 6-component model. The number of components represents the number of NOM sub-groups that vary independently over the dataset. Assessment of loading values and split-half validation 52 finalized the total number of components (Murphy et al., 2013). Loading plots of 6 PARAFAC components have been indicated in Figure 6.2. Figure 6.1. Example of flouresence EEMs. Figure 6.2. Loadings for components (C1 - C6) from PARAFAC model. The result of cross-referenced fluorescence components based on OpenFluor data base are shown in Table 6.1 (Murphy, Stedmon, et al., 2014). OpenFluor can further characterize the result by comparing components’ spectra with previous studies. According to OpenFluor results, except Component 1 (C1), all other components were found to match at least one other study. 53 As mentioned in Table 6.1, unique organic compound would not necessarily be identified using PARAFAC analysis, but groupings of compounds that vary concurrently in the dataset should be identified (He & Hur, 2015; Ishii & Boyer, 2012). Groupings are expected to be associated with the sample set's observed variance. Average raw water Raman corrected values for fluorescence components of C1 to C6 are as follows respectively: 98.16±65.14, 14.33±2.13, 9.87±2.47, 7.92±2.45, 2.36±2.21, 4.54±3.20. 54 1 A total of 47 studies were identified with at least one component with >0.95 similarity score. Highest similarity scores are shown. Table 6.1. Identities and related references for similar components using the OpenFluor database (Murphy, Bro, et al., 2014). Component Excitation/Emission maximum(s) (nm) Similarity Score1 Description & possible identity References C1 250/362 nm Protein – like, soluble microbial by-product-like (W. Chen et al., 2003) C2 250/413 nm 315/413 nm 0.98 Marine humic-like (M. Chen et al., 2018) (C2) 0.98 Microbial humic-like in the sediments of the Arctic Ocean (J. Lei et al., 2021) (C2) 0.97 Microbial humic-like (Murphy et al., 2011) (C2) C3 275/401 nm 0.98 Marine humic-like associated with phytoplankton degradation (Dainard et al., 2015) (C5) 0.96 Anthropogenic microbial humic-like found in agricultural catchments and urbanized areas (Lambert et al., 2017) (C6) C4 260/498 nm 0.99 Terrestrial humic-like (Guéguen et al., 2016) (C1) 0.99 Terrestrial humic-like (Shutova et al., 2014) (C1) 0.99 Terrestrial humic-like (Peleato et al., 2016) (C2) C5 250/438 nm 345/438 nm 0.99 Terrestrial humic-like (similar to syringaldehyde) (Peleato et al., 2017) (C1) 0.99 Ubiquitous humic-like component mainly from terrestrial sources (L. Yang et al., 2019) (C1) 0.99 Ubiquitous humic-like (Wünsch et al., 2017) (C510) C6 250/308 nm 300/308 nm 0.98 Protein - tyrosine-like (Murphy et al., 2011) (C4) 0.98 Amino-acid like substance, polyphenol-like substance, a mixture of a protein-like and polyphenol (Y. Du et al., 2019) (C1) 0.97 Tyrosine-like, microbial processing in aquatic environments (D’Andrilli et al., 2017, p. 00) (C1) 55 Components C2-C5 were all found to be forms of humic-like matter. The presence of humic-like components in the PARAFAC analysis indicates that the NOM in the water sample contains organic matter with fluorescence properties that are similar to those of humic substances. It should be noted that humic-like components are not necessarily the same as humic substances, but they have similar fluorescence properties. This means that they may have similar sources, chemical structures, or environmental behaviors, but they are not necessarily identical. Therefore, the presence of humic-like components can provide valuable information about the nature and sources of NOM in the water sample, but further analysis is needed to confirm the exact composition and properties of the organic matter. C2 has a spectrum similar to microbial humic-like sediment in the Arctic Ocean (J. Lei et al., 2021; Murphy et al., 2011). A PARAFAC component similar to C3 was discussed by Dainard et al., indicating that C3 may be attributed to a marine humic-like component, which may be produced from phytoplankton degradation (Dainard et al., 2015). Another reference reported by OpenFluor suggests that this humic-like component (C3) may result from microbial activity found in agricultural catchments and urbanized areas (Lambert et al., 2017). The longer emission wavelength of C4 represents a higher molecular weight material identified as a terrestrial humic-like component (Peleato et al., 2016; Shutova et al., 2014). Similar to C2 and C3, the shorter emission wavelength of C5 indicates an overall lower molecular weight, which has fewer aromatic structure, conjugated bonds, and lower hydrophobicity (Fellman et al., 2010; Ishii & Boyer, 2012; Peleato et al., 2017). The protein-like components of PARAFAC analysis are C1 and C6. C1 resembles a soluble microbial protein-like component (W. Chen et al., 2003). The excitation/emission maxima of the C6 component are similar to a mixture of a protein-like and polyphenol (Y. Du et al., 2019). The component scores are reported as Fmax and represent the relative concentrations of these components in a sample (Figure 6.3). The humic-like C4 and C5 components appear to be photobleached by exposure to light, losing the ability to fluoresce due to photon-induced chemical damage. Additional degradation of C4 and C5 by CNx did not appear to be significant since the light control showed an equal response. In addition, dark control results for these two components do not show substantial changes, confirming that the CNx alone does not affect C4 and C5 56 component inactivation. In addition, the C1 component is likely a substance that is coming off the CNx since the light control sample does not show any of this substance, but the dark control does. As shown in Figure 6.3, C1 scores are directly proportional to the CNx concentration, increased in higher CNx loading. Moreover, the comparison between C1 concentration of the dark control sample containing 150 mg/L CNx and that of viral suspension with 150 mg/L CNx concentration exposed to light irradiation shows that light irradiation may cause an increase in C1 component release from CNx photocatalyst. It can be concluded that while CNx concentration individually plays a significant role in C1 scores (as has been confirmed by dark control experiment), light irradiation in the presence of CNx also influenced the concentration of C1. Results indicate that the C2 component is a substance that is initially available in all samples, including the original water (Figure 6.3). According to regression analysis, C2 was the only component that reduced in concentration under dark control conditions. In all other experiments, including the light control, the variations of C2 with respect to time were insignificant. Therefore, it can be concluded that light irradiation would help this component to survive degradation. C3 was found to increase during CNx photocatalysis. This substance initially exists in all water samples, including the light control. The variation of C3 concentration is not significant for light control and dark control samples, indicating CNx material and light irradiation need to be simultaneously present to result in an increase in C3. Figure 6.3. Scores (Fmax) of fluorescence components identified by PARAFAC analysis. 57 Figure 6.4 (a) shows the proportion of PARAFAC components to total Fmax in each sample after the disinfection process. As indicated, except for the light control, C1 constitutes the highest relative proportion after 6 hours of CNx disinfection process (representing 67%-84% of the total Fmax). As explained above, C1 is likely a substance that is coming off of CNx, which does not exist in DC raw water sample. The relative changes of each component with respect to the original water character is presented in Figure 6.4 (b). The CNx disinfection process in this study was most effective in removing the humic-like C5 and C4, even in the dark control water sample. It is worth mentioning that light irradiation plays a crucial role in improving C4 and C5 reduction since the removal percentage of C4 and C5 components was drastically reduced in the dark control experiment. In addition, as Figure 6.4 (b) shows percentage removal of C4 and C5 components for light control experiment is greater (if not equal) than other experiments. This result confirms that light exposure causes a photobleaching effect on C4 and C5 components. In fact, CNx has an insignificant role in C4 and C5 photobleaching effect. Especially for C5 component, which has the highest percentage removal in light control sample, CNx has an inhibitory effect, reducing light penetration or protecting this compound from the photobleaching effect. The reduction of C4 and C5 suggests that humic-like components at higher excitation/emission wavelengths could be more amenable to photobleaching. Higher excitation/emission wavelengths are usually associated with higher molecular weights (Fellman et al., 2010). This result has been confirmed by previous studies, where hydrogen peroxide is more effective in higher molecular weight removal (Sarathy & Mohseni, 2007). It should be noted that a relatively small fraction of moieties within a compound determines the overall fluorescence of the whole humic (W.-T. Li et al., 2013). This fact should always be considered as the molecular weight of the fractions is not being measured directly and is only inferred from the fluorescence fingerprint (Peleato et al., 2017). There was a correlation between CNx concentrations and increasing C6 Fmax after 6 hours of exposure. Given that increased C6 scores were seen in both the light and dark control, results suggest that CNx with light exposure increases C6 through the breakdown of other matter (i.e. C6 results from the decomposition of other materials), or increases the quantum efficiency of this fluorophore. Suppose C6 is indeed the emission of tryptophan or tyrosine in a larger protein. In that case, changes to protein folding or structure due to adsorption to CNx or exposure to light may 58 alter the resulting efficiency of fluorescence. This effect was observed to occur in the light control, suggesting a photoeffect, and to a relatively more significant degree just due to the presence of CNx (dark control). In summary, CNx photocatalysis will not help in concentration reduction of organic compounds of DC raw water in this study. In fact, the removal of some organic compounds can be satisfied by the CNx or light irradiation. Figure 6.4. a) Proportion of PARAFAC components to total Fmax in each Water Sample. b) Removal percentage of PARAFAC components normalized to DC raw water components. a) b) 59 6.3 Summary In this chapter, the influence of the photocatalytic CNx disinfection process on organic matter has been characterized using PARAFAC analysis. PARAFAC identified 4 independent humic-like (C2-C5) and 2 independent protein-like components. The results indicated that the humic-like C5 and C4 components were photobleached by exposure to light. The largest degree of C5 and C4 reduction occurred under light control conditions, indicating that light was the primary driver of this photobleaching effect and the presence of CNx possibly had an inhibitory effect. Active CNx under light exposure did increase the abundance or fluorescence efficiency of protein-like fluorophores C1 & C6. Light irradiation alone was found to prevent the removal of humic-like C2. For some other humic-like components (component C3), CNx material and light irradiation must be simultaneously present to increase their concentration. In conclusion, CNx photocatalysis (CNx and light simultaneous presence) was not found to decrease the abundance of natural fluorophores in DC raw water. Instead, the removal of some organic compounds can be achieved either by the CNx or by light irradiation. Furthermore, it was seen that specific fluorophores either increased in concentration or fluorescence efficiency due to exposure to either or both light exposure and CNx. 60 Chapter 7: Conclusion 7.1 Summary of Contributions This research evaluated light-based small disinfection systems for viral inactivation and natural organic matter removal. First, the potential for applying UV-LED disinfection for unfiltered natural waters was explored with a particular focus on particle effects. Second, the disinfection performance of CNx photocatalyst under high wavelength irradiation of UV-LED system was investigated for viral organic matter inactivation. Changes to NOM due CNx photocatalysis were characterized using fluorescence-PARAFAC analysis. The outcome of this research can serve to develop effective and efficient systems for the practical application of UV-LEDs in a small system context. The investigation into CNx photocatalytic disinfection systems contributes to the fundamental knowledge regarding the effects of water matrix on viral disinfection. The contribution of this thesis can be summarized as follows: 1. This study investigated UV-LED dose-response when pre-filtration is not practiced. The water quality characteristics of unfiltered water samples indicated that conventional treatment indicators, including turbidity, TOC, and UV adsorption at 254 nm could not be correlated to UV disinfection response. Particulates with more neutral surface charges could significantly protect microorganisms from UV light, even in high-quality unfiltered water supplies with less than 1 NTU turbidity. In other words, UVA/UVT are not, by themselves, appropriate performance indicators for unfiltered UV disinfection performance. It was observed that zeta potential could predict the tailing behaviour of UV disinfection performance more effectively than turbidity and UVA. In addition, based on the examined water sources, water pre-treatment, such as coagulation and DAF, plays a significant role in reducing the tailing effect in UV dose-response curve. To reduce public health risk, water quality characterization, in addition to turbidity and UVA/UVT, is needed for high quality surface waters subject to pathogenic contamination. 2. Carbon nitride (CNx) is a metal-free organic polymeric nanomaterial, which shows a promising performance as a visible-light responsive photocatalyst. Previous studies examined CNx performance under light irradiation from high-power Xenon lamps and 61 were carried out in pure water rather than a natural water matrix. In this study performance of CNx disinfection mechanism for viral inactivation was investigated using UV-LED as the low-power light source with irradiation of half intensity compared to previous studies. The results indicated that the system could provide 4-log removal of MS2 bacteriophage for DC raw water (1.56 NTU, 53.53% UVT @ 254 nm, 87.36% UVT @ 365 nm), meeting one of the requirements for drinking water treatment objectives for groundwater in B.C. (‘Ground Water Treatment Objectives’, 2022). This means that the objective of 4-log removal can be satisfied with a far lower power light source, which is more cost-effective. 3. Due to interference of natural organic matter present in natural water resources, reactive oxygen species (ROS) generation may be prevented, generated ROS may be consumed, or NOM may impede active sites on the CNx. This study investigated the inactivation efficiency of CNx disinfection in a natural water resource compared to an RO water sample. Interestingly, a comparative experiment between DC raw water and RO as background water showed that despite decrease in inactivation efficiency of UV-LED disinfection system due to the particulate effect of unfiltered water samples, the presence of particles and organic impurities in real water matrices promotes viral inactivation performance in CNx photocatalytic disinfection system. In fact, natural water matrices could positively affect CNx viral disinfection mechanisms. In addition, this study indicated that only small amount of CNx can enhance disinfection performance. Therefore, CNx offers a low-cost (~110 CAD per gram) and environmental-friendly candidate for the next generation of sustainable antimicrobial materials that can be used for drinking water viral disinfection systems (Graphitic Carbon Nitride (g-C3N4) Powder | Nanochemazone, 2020). 4. The impact of CNx on natural organic matter inactivation using fluorescence spectroscopy is investigated in this study to identify possible changes to the background NOM. Changes in organic matter in response to different concentration of CNx was characterized using parallel factor analysis (PARAFAC). The highest removal percentage values were attributed to humic-like components, which are photobleached by exposure to light. Greater removal of organic components was not observed when CNx photocatalysis occurred, suggesting marginal changes to the NOM character due to CNx. In addition, it 62 was found that CNx disinfection process may have some inhibitory impact on removal of protein-like fluorophores. In this study, CNx photocatalysis (CNx and light simultaneous presence) did not help in inactivation of organic compounds of DC raw water. Instead, the removal of some organic compounds can be achieved either by the CNx or by light irradiation. The implication is that viral disinfection occurred and was augmented by CNx, but did not result in any measurable changes to NOM character by fluorescence. 7.2 Suggestions for Future Studies • Although zeta potential can predict the tailing behavior of UV disinfection performance more effectively than turbidity and UVA, there might be potential for cross-correlations between zeta potential and other water quality parameters (e.g., turbidity, UVT, particle size) that could be considered in future studies. • Immobilizing of the powdered photocatalyst onto suitable support would facilitate the adoption of this technology. CNx fixed to a support would reduce operation time and cost and avoid the potential risk of released nanomaterials to the environment and human health. Therefore, further investigation into methods to fix the CNx to a solid support and increase disinfection performance is warranted. • To correlate the effect of CNx disinfection on MS2 bacteriophage to that of Cryptosporidium, a CNx disinfection experiment needs to be conducted directly on Cryptosporidium to ensure the similarity of dose-response curves and derive correction factor that accounts for differences between the influence of CNx disinfection on target pathogen and challenge microorganism. • For water drinking applications, the stability of CNx plays a significant role. Therefore, it is recommended to evaluate the durability and robustness of the material over multiple cycles of MS2 photocatalytic inactivation to ensure the virucidal effect remains constant. • Viral inactivation is potentially caused by several main ROSs generated from photocatalyst. The roles of various ROSs are recommended to be examined in future studies to specify the most effective ones for the viral disinfection mechanism of this system. 63 • To achieve large-scale application, a solar photocatalytic reactor needs to be designed and the performance of CNx photocatalytic disinfection be investigated under solar light. • A comprehensive characterization of the components identified by fluorescence analysis is recommended. For instance, it is significant to know if C1 (being added by CNx) is harmful to people or perhaps would cause issues with other treatment methods. • Using other NOM charachterization methods including TOC, DOC, and chemical oxygen demand is recommended for future studies to investigate the effect of CNx disinfection. 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Journal of Hazardous Materials, 173(1), 318–325. https://doi.org/10.1016/j.jhazmat.2009.08.093 84 Appendix Here are sample raw data of CNx experiments and water qualities measurements. CNx Load (mg/L) CNx Condition 200 Slurry Time (min) Phage Concentration (PFU/100 µL) Log Removal Avg. Log Removal SD Replicate 1 Replicate 2 Replicate 3 Replicate 1 Replicate 2 Replicate 3 0 5.00E+09 1.00E+09 0 0 0.00 0.00 60 8.40E+08 1.01E+09 -0.77469 0.004321 -0.39 0.55 120 1.49E+08 1.58E+08 -1.52578 -0.80134 -1.16 0.51 180 6.60E+07 3.50E+07 -1.87943 -1.45593 -1.67 0.30 240 1.13E+07 7.70E+06 -2.64589 -2.11351 -2.38 0.38 300 1.65E+06 1.66E+06 -3.48149 -2.77989 -3.13 0.50 360 9.50E+05 8.00E+05 -3.72125 -3.09691 -3.41 0.44 CNx Load (mg/L) CNx Condition 150 Slurry Time (min) Phage Concentration (PFU/100 µL) Log Removal Avg. Log Removal SD Replicate 1 Replicate 2 Replicate 3 Replicate 1 Replicate 2 Replicate 3 0 2.13E+08 1.13E+09 1.88E+08 0 0 0 0.00 0.00 60 6.63E+07 7.10E+07 2.63E+07 -0.50617 -1.19989 -0.7569 -0.85 0.35 120 9.63E+06 3.40E+07 6.94E+06 -1.34396 -1.51967 -1.37823 -1.43 0.09 180 1.61E+06 1.01E+07 1.55E+06 -2.11986 -2.04683 -2.05875 -2.08 0.04 240 2.16E+05 2.14E+06 2.61E+05 -2.99291 -2.72074 -2.85988 -2.86 0.14 300 2.27E+04 7.00E+05 4.83E+04 -3.97133 -3.20605 -3.4789 -3.59 0.38 360 7.30E+03 1.41E+05 1.23E+04 -4.46404 -3.90193 -4.17679 -4.18 0.28 85 CNx Load (mg/L) CNx Condition 100 Slurry Time (min) Phage Concentration (PFU/100 µL) Log Removal Avg. Log Removal SD Replicate 1 Replicate 2 Replicate 3 Replicate 1 Replicate 2 Replicate 3 0 3.00E+09 9.90E+09 0 0 0.00 0.00 60 7.10E+08 8.70E+08 -0.62586 -1.05612 -0.84 0.30 120 2.16E+08 1.91E+08 -1.14267 -1.7146 -1.43 0.40 180 1.43E+08 1.17E+08 -1.32179 -1.92745 -1.62 0.43 240 1.39E+07 2.10E+07 -2.33411 -2.67342 -2.50 0.24 300 1.87E+07 1.81E+07 -2.20528 -2.73796 -2.47 0.38 360 1.21E+07 2.00E+07 -2.39434 -2.69461 -2.54 0.21 CNx Load (mg/L) CNx Condition 50 Slurry Time (min) Phage Concentration (PFU/100 µL) Log Removal Avg. Log Removal SD Replicate 1 Replicate 2 Replicate 3 Replicate 1 Replicate 2 Replicate 3 0 1.15E+09 5.70E+08 0 0 0.00 0.00 60 3.30E+08 2.10E+08 -0.54218 -0.43366 -0.49 0.08 120 8.00E+07 8.70E+07 -1.15761 -0.81636 -0.99 0.24 180 3.70E+06 3.00E+07 -2.4925 -1.27875 -1.89 0.86 240 1.18E+06 9.20E+06 -2.98882 -1.79209 -2.39 0.85 300 5.00E+05 1.50E+06 -3.36173 -2.57978 -2.97 0.55 360 6.90E+04 5.50E+05 -4.22185 -3.01551 -3.62 0.85 86 Turbidity Oct-20 Nov-20 Dec-20 Jan-21 Feb-21 Mar-21 Apr-21 May-21 Jun-21 Jul-21 Aug-21 Sep-21 DCWTP- Headgates 1.54 1.11 1.26 1.43 1.15 1.18 3.52 1.57 1.54 1.32 1.65 1.55 DCWTP-Pre UV 0.35 0.35 0.41 0.32 0.39 0.40 0.58 0.33 0.51 0.26 0.26 0.30 Kal- lake 0.62 0.50 0.52 0.41 0.79 0.57 1.23 0.37 0.76 0.73 1.65 MHWTP- Pre UV 0.62 0.50 0.35 0.27 0.37 0.57 0.83 0.37 0.76 0.73 1.38 1.16 UVT Oct-20 Nov-20 Dec-20 Jan-21 Feb-21 Mar-21 Apr-21 May-21 Jun-21 Jul-21 Aug-21 DCWTP- Headgates 48.35 49.91 50.27 51.08 52.29 52.03 33.94 51.66 44.72 44.23 45.98 DCWTP-Pre UV 86.25 91.66 88.90 90.63 86.65 87.51 84.87 87.01 86.33 86.69 87.20 Kal- lake 90.17 90.56 90.60 91.72 88.95 89.80 87.96 90.43 91.54 91.16 90.04 MHWTP- Pre UV 91.07 87.00 91.60 87.95 89.12 90.06 86.45 90.43 91.54 91.16 92.57
Thesis/Dissertation
eng
Civil Engineering
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Peleato, Nicolas M.
Evaluation of water matrix effects on light-based small disinfection systems
Text