Investigation of removal of phenol and methylene bluefrom water solutions by photocatalitic degradation

Industrial activities have an important place in the world and in our country. Industrial activities are increasing due to many factors such as urbanization, developments in technology and growing population day by day and natural resources are running out. Besides that, wastewater from industrial processes occurs environmental pollution with various chemicals, heavy metals, etc. in their contents and it threatens the health of people and the lives of other living things in nature. Phenol and dyestuffs, which are included in the aromatic compounds class, are among the most important pollutants found in industrial wastewater. Treatment of wastewater containing aromatic compounds of industrial origin is difficult and requires advanced purification techniques. In recent years, advanced oxidation processes have been developed as an alternative method for effective waste water treatment. Photocatalytic oxidation is one of the advanced oxidation processes that break down organic pollutants into end products such as CO2 and H2O. In this study, photocatalytic reactor to be designed and manufactured for the removal of phenol and methylene blue, which can be highly found in industrial wastewater, in batch system using ZnO photocatalyts is investigated In this context, the effects of parameters such as photocatalyst amount, initial phenol concentration, air inlet velocity, initial solution pH, photocatalytic reactor operating temperature on photocatalytic degradation efficiency were investigated and time depending phenol and methylene blue removal as well as total organic carbon (TOC) removal levels have been investigated. Response Surface Method (RSM) was used to examine the effects of important advanced oxidation parameters such as pH, temperature, initial dyestuff concentration and ZnO concentration on decolorization. ANOVA analysis was used to obtain the interaction between responses and process variables and to examine the data. Second order regression models for estimation of removal percentages were developed using the Design Expert10 software program. Optimum advanced oxidation parameters obtained by classical method were compared with optimum parameters found by RSM. Keywords: Methylene blue, phenol, dyestuff, photocatalytic degradation, TOC, response surface method.