doctoral thesis

Access to clean water has been crucial global problem, especially with climate change, increasing population, and industrial activities. As one of Malaysia’s leading economic activities, the Oil and Gas Industry generates a massive amount of wastewater called Produced Water (PW). Dissolved organics in produced water, such as organic acids and phenolic compounds, are concerning due to the possibility that they can be toxic, non-biodegradable, and have bioaccumulation properties. Conventional treatments such as adsorption, incineration, and biological treatment seem to have difficulties treating these dilute but toxic components in an economical and environmentally friendly manner. Regulations on wastewater management has also been stricter around the globe. Therefore, there is a need on a new water treatment method to treat the diluted organics in a large volume of wastewater. Membrane technology has been of interest in the water treatment technologies’ industrial and research scenes. It offers simpler configuration and maintenance. However, the application is limited by the reduction of performance over time due to fouling phenomena. Photocatalyst offer an effective method to decompose organics in an environmentally friendly manner. This study researched on photocatalytic removal of diluted organic in water and potential of biofouling reduction by deposition of AgTiO2 coating on membrane surface. In Chapter 1: Introduction, the research background and purpose of this research were discussed. At the end of this chapter, the thesis framework was shown. In Chapter 2: Preparation and characterization of TiO2 and AgTiO2 coatings; the method to prepare AgTiO2 coatings on membrane support were explained. The prepared membranes were characterized with XPS, SEM, TEM, and ICP analysis to understand the prepared coatings. Results shows that the concentration of silver deposited on the membrane can be control by the concentration of silver in the precursor (silver acetate solution) used during the photochemical deposition step. Via XPS, it was found that the state of silver prepared through this method is oxide state. In Chapter 3: Removal of dissolved organic pollutants in water by photooxidation, the photocatalytic performance of prepared membranes was studied. Decomposition of diluted formic acid was performed under UV-light, and the concentration was evaluated using UVspectrophotometer. AgTiO2 membranes show better photocatalytic activity then TiO2 membrane. The concentration of silver on the membrane was found to influence its photocatalytic performance. In relation to PW application which commonly contain high salts, influence of salt types; NaCl, MgSO4, MgCl2 and K2SO4 and concentration were studied. All salts were found to inhibit the membranes’ photocatalytic performance. In Chapter 4: Antibacterial activity of AgTiO2 membranes, the antibacterial activity towards E. coli by prepared AgTiO2 membranes were investigated. Silver dissolution from membrane was found to be significantly increased in the presence of NaCl as compared to only water. Comparing membrane with lower Ag deposition, and around 20 times higher deposition, the silver dissolution from these membranes reached almost the same value after some time. However, as the amount of silver deposited on the membrane was higher, the antibacterial performance show around four times higher than the lower silver membrane. Based on other tests performed, it was concluded that there are potential of contribution from the silver oxide deposited on the membrane surface on the antibacterial activity of the AgTiO2 membranes In Chapter 5: Antibacterial activity in filtration system, prepared AgTiO2 membrane was used to filter E. coli suspension in water. E. coli growth was found to be inhibited by short contact with silver on the coated membrane. Finally, Chapter 6: Conclusion, the thesis was summarized, and future works were proposed.

Nutrient pollution is one of our most pervasive, expensive, and challenging environmental problems, according to the United States Environmental Protection Agency (EPA). Phosphorus is one of the nutrients that are essential for the growth of living organisms. However, excessive amounts of nutrients released into the environment by human activities can harm ecosystems and impact human health. In surface waters, phosphorus can contribute to an overgrowth of algae called algal "blooms" that can sicken or kill wildlife and endanger aquatic habitats. Algal blooms consume dissolved oxygen in the water, leaving little or no oxygen for fish and other aquatic organisms. Algal blooms can harm aquatic plants by blocking the sunlight they need to grow. Some algae produce toxins and encourage the growth of bacteria that can make people sick who are swimming or drinking water or eating contaminated fish or shellfish. Phosphorus is often a major limiting nutrient freshwater system. Consequently, many of the wastewater treatment plant discharged into freshwater systems such as lakes, ponds, and rivers have phosphorus discharge limits. In an attempt to prevent harmful environmental effects of excess phosphorus, several techniques have been designed to remove phosphorus from wastewater. These techniques range from adsorption and precipitation to enhanced biological phosphorus removal and constructed wetlands. Biological phosphorus removal (BPR) was first used at a few water resource recovery facilities in the late 1960s. A common element in EBPR implementation is the presence of an anaerobic tank (no nitrate and oxygen) before the aeration tank. In the next aerobic phase, these bacteria can accumulate large amounts of polyphosphate in their cells and phosphorus removal is said to be increased. The group of microorganisms that are largely responsible for P removal are known as the phosphorus accumulating organisms (PAOs). One of the options to remove phosphorus is to utilize bacteria from nature, besides being easy to obtain and inexpensive. The application of bacteria from sediment and seawater was able to reduce phosphorus in wastewater. In this study, for screening salt-tolerant phosphorus accumulating organisms (PAOs) and investigating the P release and uptake of the organisms in saline wastewater. The samples used were sediment and seawater from Yamaguchi Bay, Yamaguchi, Japan. Sediment and seawater added 150 mL of artificial saline wastewater with media (anaerobic media). The samples were then cultured and given feed media every three hours day at 25 °C and shaken at 140 rpm. The hydraulic retention time of the cultivation was 16 h and 8 h under anaerobic and aerobic conditions, respectively. 10 sponges made of polyurethane with dimensions of 2 cm were put in Erlenmeyer flasks and was used as a bio-carrier surface for microorganisms to adhere to. Water was passed over the sponge surface to acclimatize the microorganisms growing outside the sponge as well as within its pores, ensuring sufficient growth surface. The cultivation duration was 112 days. Batch experiments were conducted over 98 days in solutions with a salinity of 3.5% and P concentrations of 1, 5, 10, and 20 mg-P/L. The P-uptake ability of microorganisms increased by increasing P concentration from 1 to 20 mg-P/L. A high P removal percentage with an average of 85% was obtained at 10 mg-P/L after day 56. The uptake and release of P were observed in saline wastewater, signifying that salt-tolerant PAOs could grow in the saline solution. Bacterial screening by isolation and sequence analysis using 16S rRNA demonstrated that two cultivated strains, TR1 and MA3, had high similarity with Bacillus sp. and Thioclava sp. EIOx9, respectively. The colony morphology analysis showed that the colonies of TR1 were rod-shaped, milky-colored, round, shiny-viscous, smooth with a defined margin, while colonies of MA3 were cream-colored with smooth surfaces and raised aspect. The TR1 was gram-stain-positive with approximately 6-10 μm long and 1.2 μm wide cells, and MA3 was gram-stain-negative with about 0.9 μm long and 0.5 μm wide cells. The results demonstrated the involvement of Bacillus sp., and Thioclava sp. in the release and uptake of P, owing to their ability to grow in saline wastewater. Furthermore, Bacillus sp. (TR1) and Thioclava sp. (MA3) were assessed for their abiotic adaptability and phosphorus removal efficiency in saline wastewater. The effects of abiotic factors such as carbon source, pH, temperature, and salinity on bacterial growth were examined through a series of batch experiments. Both bacteria used carbon sources such as glucose, sucrose, and CH3COONa for their growth. The pH study indicated that Bacillus sp. (TR1) preferred the pH range of 6 8 and Thioclava sp. (MA3) preferred the pH range of 6-9. Bacillus sp. favorably multiplied in the temperature range of 25- 40 °C, while 25 35 °C was preferred by Thioclava sp. Salinity range of 0% 10% was favorable for TR1, with optimum growth observed at 3.5% 5%, and Thioclava sp. (MA3) preferred the salinity range of 1% 10% with optimal growth at 4%, but was absent in non-saline water. Bacillus sp. and bacterial combination (TR1 and MA3) showed similar values for phosphorus removal efficiency (100%) at 1.0 mg-P/L total P compared to Thioclava sp. (38.2%). The initial phosphorus concentration of 2.5 mg-P / L showed a slightly higher 72.35% P removal efficiency compared to the individual strains. However, phosphorus removal did not increase, but showed a downward trend with increasing at initial phosphorus. The combination possibly built a synergistic activity between the individual strains to remove phosphorus. The results demonstrated that when used individually, Bacillus sp. showed a reasonably high phosphorus removal ability than Thioclava sp., and exhibited good synergy when used in combination to remove phosphorus from saline wastewater.

Sleep is an essential physiological process for the human body. People spend about one-third of their lives sleeping. Both sleep duration and sleep quality are important to human health. Sleep quality describes how restful and restorative the sleep process is. Over 80 sleep disorders are known to affect sleep quality. Among them, sleep-related breathing disorder (SRBD) is the second factor. Sleep-related breathing disorders are sleep disorders in which breathing abnormalities occur during sleep. Abnormal snoring and respiratory arrest or abnormally low breathing during sleep reduce oxygen levels in the blood, increasing the risk of depression, cardiovascular disease, stroke and even death. Therefore, monitoring and analysis of respiration during sleep is gaining increasing importance in healthcare. Polysomnography (PSG) is considered the gold standard for diagnosing sleep disorders, but PSG is usually performed in an unfamiliar sleep laboratory under the supervision of a medical technician and is often worn with many sensors that interfere with sleep. It is often the case. This research group is developing a breathing sound measurement system that constantly monitors the quality of sleep in general home environment. This system can easily measure breath sounds during sleep all night with high accuracy without disturbing sleep. The purpose of this research is to develop a technique to classify patterns of breathing sounds and to analyze the quality of breathing in order to more accurately analyze the state of sleep from breath sound information. There are various patterns of sleep breath sounds, such as normal breath sounds and snoring, and abnormal breath sounds and snoring. To develop a method to classify these patterns, to develop an algorithm to calculate ventilation from breath sounds, to estimate the sleep apnea index (AHI), and to assess the quality of breathing during sleep. try. Specifically, the temporal feature waveform (TCW) is calculated after partly removing the noise of the breathing sounds of sleep with a band-pass filter. Based on the time feature waveform, a respiratory signal effective for analysis is extracted from low-level signals and phase-divided into a respiratory phase and an apnea or low signal. Mel-frequency cepstrum coefficients (MFCC) are then obtained for the respiratory phases, and an agglomerative hierarchical clustering (AHC) algorithm is applied to distinguish between normal/abnormal breathing, normal/abnormal snoring, and normal/abnormal breathing. , tossing and turning, etc., which are less relevant to breathing. The categorized breathing patterns are analyzed every 30 seconds and the relative tidal volume of the breath is calculated. In addition to verifying the effectiveness and accuracy of the technology and analysis method proposed in this study, a method of estimating the apnea syndrome index (AHI) and converting the ventilation volume into high, medium, and low levels, We propose a method to evaluate the quality of breathing in a patient and verify its effectiveness. This paper consists of six chapters, including an introduction and conclusion. Chapter 1 introduces the background and overview of this research. Chapter 2 describes a signal-processing technique for analyzing breath sounds during sleep and a method for classifying breathing patterns. Breathing sound data during sleep often includes disturbed breathing due to bruxism or body movement, ambient environmental noise, etc. In this chapter, the Time Characteristic Waveform (TCW) and the Characteristic Moment Waveform (CMW) are calculated for respiratory sound signals that have undergone preprocessing, such as filtering noise to preprocess the respiratory sounds, and the segmentation of inspiration and expiration is performed. The Mel-Frequency Cepstrum Coefficients (MFCC) are obtained for each respiratory cycle and applied as a feature vector to the Agglomerative Hierarchical Clustering (AHC) algorithm. This method is used to classify ordinary respiratory signals (normal and abnormal breathing, normal and abnormal snoring) from signals less relevant to respiration, such as tossing and turning and environmental noise. In Chapter 3, using the technology described in Chapter 2, breathing sound data during sleep are classified into apnea, hypopnea, normal breathing, abnormal breathing, normal snoring, and abnormal breathing for each 30-second frame. In addition, we describe a method for classifying events such as no snoring and rolling over and determining the respiratory state. In Chapter 4, we propose a method for estimating the apnea-hypopnea Apnea-Hypopnea Index (AHI) for classified abnormal breath sounds and low-level breath sound signals, compare it with the diagnostic results of PSG, and examine its validity. And verify usefulness. Chapter 5 describes a method for estimating ventilation volume from breath sounds. Because normal breath sounds are correlated with ventilation, this study used a quantitative approach to calculate normal breathing and normal snoring and a qualitative method to calculate apnea/hypopnea and abnormal breath sounds. We will propose and compare it with the diagnosis result of PSG and verify its validity. In Chapter 6, as an application development, an example of applying the breathing sound classification method proposed in this study to heart sound analysis is presented. Finally, we will explain the construction of a data collection distribution system for sharing auscultation data collected at different facilities and hospitals using blockchain technology. Chapter 7 presents the conclusions and prospects of this study.