Assessment of Green Catalysts for Wastewater Treatment Efficiency

Thesis Abstract

Increasing concerns over environmental pollution and the limitations of conventional wastewater treatment methods necessitate the exploration of sustainable and eco-friendly alternatives. The study addresses the critical need to evaluate green catalysts as viable options for enhancing wastewater treatment efficiency, focusing on their environmental compatibility, availability, cost-effectiveness, and catalytic performance. The primary aim is to assess the effectiveness of selected green catalysts derived from plant-based and bio-based materials in degrading key pollutants, including dyes, heavy metals, and organic contaminants, in wastewater systems. Specific objectives include characterizing the physicochemical properties of the catalysts, determining their catalytic activity under varying operational conditions, comparing their performance with traditional catalysts, and evaluating their environmental impact through toxicity assessments. The research adopts a mixed-method approach, combining experimental laboratory studies with statistical and analytical techniques. The experimental component involves screening five different green catalysts—namely, biochar derived from agricultural waste, natural zeolites modified with plant extracts, enzyme-based bio-catalysts, chitosan-based composites, and nanocellulose-supported catalysts—using synthetic wastewater samples prepared to simulate industrial effluents. A total of 150 samples are tested across a range of parameters such as catalyst dosage, pH, contact time, and temperature to optimize removal efficiencies. Data collection employs spectrophotometric analysis (UV-Vis spectroscopy) for dye degradation, atomic absorption spectroscopy (AAS) for heavy metal removal, and total organic carbon (TOC) analysis for organic contaminants. The catalysts’ physicochemical properties are characterized through Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), Brunauer–Emmett–Teller (BET) surface area analysis, and X-ray diffraction (XRD). Data analysis involves descriptive statistics to summarize performance outcomes, analysis of variance (ANOVA) to evaluate the significance of operational variables, and regression analysis to model the relationships between catalyst properties and removal efficiencies. Kinetic studies are conducted using pseudo-first-order and pseudo-second-order models to elucidate reaction mechanisms. The environmental impact of each catalyst is assessed through toxicity testing on aquatic organisms, using bioassays conforming to OECD guidelines, and Energy Dispersive X-ray Spectroscopy (EDX) for quantifying residual metals or toxic byproducts. Expected findings anticipate that biochar and nanocellulose-supported catalysts will demonstrate the highest removal efficiencies for dyes and organic pollutants, with some catalysts—particularly biochar—exhibiting up to 95% degradation of dyes within 60 minutes. Catalysts modified with natural plant extracts are expected to enhance heavy metal adsorption, achieving removal rates exceeding 90%. The study also aims to establish that these green catalysts operate efficiently under mild pH and temperature conditions, with negligible environmental toxicity, aligning with principles of green chemistry. Regression models are projected to yield high coefficients of determination (R² ? 0.85), confirming strong predictive capabilities for process optimization. This research contributes novel empirical data on the performance of eco-friendly catalysts in wastewater remediation, filling gaps related to their comparative efficiencies, operational parameters, and environmental safety profiles. By integrating characterization techniques, kinetic modeling, and toxicity assessments, the study advances understanding of sustainable treatment alternatives, grounded in the principles of green chemistry and circular economy. The main conclusion underscores the potential of selected green catalysts as sustainable, cost-effective solutions for industrial wastewater treatment, encouraging their adoption in environmental management practices. It recommends further scale-up studies, lifecycle assessments, and economic analyses to facilitate real-world application. Additionally, future research should explore catalyst regeneration techniques, long-term stability, and the integration of green catalysts within existing treatment frameworks to optimize environmental and economic benefits.