Date of Graduation
8-2024
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Engineering (PhD)
Degree Level
Graduate
Department
Biological and Agricultural Engineering
Advisor/Mentor
Zhu, Jun
Committee Member
Li, Yanbin
Second Committee Member
Zhang, Wen
Third Committee Member
Ubeyitogullari, Ali
Keywords
ANN-GA optimization; CCD-RSM; Non-thermal plasma; Photocatalytic degradation; Wastewater treatment
Abstract
Water pollution by organic pollutants poses a significant environmental threat, necessitating the development of advanced treatment technologies to ensure sustainable and efficient remediation. This dissertation explored innovative approaches to enhance the degradation of organic pollutants through the integration of photocatalytic and plasma-assisted systems, with a focus on optimizing these processes using methodologies ranging from response surface methodology (RSM) to advanced machine learning techniques. The first part of the dissertation investigated the degradation of organic pollutants in flocculated liquid digestate using photocatalytic titanate nanofibers (TNFs) synthesized via a hydrothermal method. This study represents the first application of TNFs, with a bandgap of 3.16 eV, in the photocatalytic degradation of pollutants and color removal from poultry litter digestate. Five levels of pollutant concentration (0.2 to 1.3 g·L−1) and pH (4 to 10) were examined. Central composite design (CCD) and response surface methodology (RSM) were utilized to optimize the removal rates of volatile fatty acids (VFA), chemical oxygen demand (COD), and decolorization. Optimal conditions were found to be a pH of 6.752 and a TNF dosage of 0.767 g·L−1, resulting in VFA removal of 72.9%, COD removal of 59.1%, and decolorization rate of 66.8%. These findings suggested that TNFs hold significant potential for post-treatment of anaerobic digestion effluent and other wastewater types. The second part of the dissertation introduced a cost-effective and eco-friendly corona dielectric-barrier discharge plasma device for dye wastewater treatment. Non-thermal plasma (NTP) processes are often criticized for their high operational costs due to substantial energy consumption. To address this, the study designed a low-power consumption plasma device that operates efficiently at reduced energy inputs. Using CCD and RSM, parameters such as pH and voltage were optimized to achieve a high decolorization rate of 98% for methylene blue (MB), a pharmaceutical waste, within 10 minutes. Detailed analyses of the reactive oxygen species generation mechanisms and MB degradation pathways were conducted. The device demonstrated high energy efficiency, characterized by a low energy density and an electrical energy per order (EEO) of 0.15 watt/mL and 5.79 kWh/m³/order, respectively. This research presented a sustainable solution for dye wastewater treatment, advancing the field of environmentally friendly water management. The third part of the dissertation addressed the presence of pharmaceutical residues in natural water systems using an innovative photocatalytic system comprising Ni-titanate (Ni-TNT) and graphitic carbon nitride (g-C3N4). Characterization techniques such as SEM, XRD, XPS, and UV-Vis spectrophotometry confirmed the superior properties of the Ni-TNT/g-C3N4 catalyst. The photocatalytic mechanism followed a Z-scheme heterojunction model, enhancing charge separation and promoting reactive oxygen species generation for efficient pollutant degradation. The Ni-TNT/g-C3N4 heterojunction achieved 82.3% degradation of salicylic acid within 90 minutes. Optimization using RSM and Artificial Neural Network (ANN) coupled with Genetic Algorithms (GA) demonstrated that the ANN-GA model outperformed RSM, achieving a higher optimal predicted SA removal rate of 87.04%. This study underscored the significant potential of the Ni-TNT/g-C3N4 system in wastewater treatment and highlighted the advantages of using ANN-GA for optimizing complex photocatalytic processes. In summary, the dissertation provided a comprehensive investigation into the mechanisms and optimization strategies for both photocatalytic and plasma-assisted degradation of organic pollutants. The advanced systems developed and optimized in this work demonstrated considerable potential to enhance wastewater treatment processes. These findings contribute to the field of environmental engineering by offering sustainable and efficient solutions for mitigating water pollution, ultimately promoting environmental sustainability and public health protection.
Citation
Xiao, Y. (2024). Optimization and Mechanistic Insights into Photocatalytic and Non-Thermal Plasma Degradation of Organic Pollutants for Sustainable Wastewater Treatment. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/5491