Modeling and Optimization of Degradation of Dyes Present in Textile Waste Water using Supported Photocatalyst

Abstract

Synthetic dyes are mostly used in different industries like textile, paper etc. These dyes are discharged in the aqueous streams from the effluents of different industries like leather, textiles and paper etc. These dyes produce major environmental pollution problems by discharging polluting and potential carcinogenic substances. The dyeing and finishing industries are the major sources of pollutants in the industrial sector. Due to the toxicity and determination of the dyes, their removal from the textile wastewater has become an issue of interest during the last decades. The complete mineralization of the dyes is not possible by conventional methods. The present study of water decontamination processes are concerned with the oxidation of the dyes. These methods depend on the formation of highly reactive chemical species that mineralize a number of recalcitrant molecules into non-toxic compounds and are called advanced oxidation processes (AOPs). Heterogeneous photocatalytic process employs the near UV irradiation to photo-excite a semiconductor photocatalyst. Using semiconductor based photocatalysis, organic contaminants (textile dyes) can be totally mineralized, reacting with the oxidizers to produce carbon dioxide, water and dilute concentration of simple mineral acids. Among the various semiconductors employed, the anatase phase of TiO2 is known to be a good photocatalyst for the degradation of several pollutants due to its high photosensitivity and large bandgap. Despite the positive attributes of various photocatalysts, there are some drawbacks associated with their use. One of the major drawbacks is the band edge absorption threshold which does not allow the utilization of visible light. Bandgap tailoring by doping and codoping is the most efficient and frequently used approach. Photocatalytic degradation of organic dyes depends on temperature, agitation, catalyst loading, initial dye concentration, pH, geometry of reactor, flow behavior, radiation flux etc. Due to complexity of the processes, they are difficult to be modeled using conventional mathematical modeling. Artificial neural network (ANN) and response surface methodology (RSM) are the techniques that can be used for modeling and optimization of the photocatalytic treatment processes of water and wastewater. Immobilized TiO2 is an alternative solution to suspended TiO2 systems mainly because of the convenience of not requiring additional post-treatment recovery of catalyst after the reaction process. The present thesis deals with the modeling and optimization of the photocatalytic degradation (UV/TiO2) of single dye and binary mixture using ANN and RSM. For improving the photocatalytic degradation of textile dyes, different metal ions have been doped and codoped on TiO2, and immobilization of TiO2 on solid support has been carried out. Photocatalytic treatment of three textile dyes (RB5, AB113 and AR114) and binary dye mixture of AB113 and AR114 were carried out using suspension of commercially available TiO2 catalyst under ultraviolet irradiation in a shallow pond reactor with UV light irradiation (UV-C). Two different methods, namely multivariate calibration and first order derivative spectrophotometric were used to quantify each dye separately in binary dye solutions. An artificial neural network (ANN) model was developed to predict the behavior of the process. Six operational parameters for single dye solution (TiO2 dose, initial dye concentration, pH of the dye solution, area to volume ratio, UV light intensity and time) and five operational parameters (initial concentration of AB113 dye, initial concentration of AR114 dye, TiO2 dose, pH of the dye solution and time) were employed as input parameters. The decolorization and degradation efficiencies for single dye solution and decolorization efficiency of AB113 and AR114 were employed as output of the network. The outcomes have been validated experimentally indicating that the ANN provided reasonable predictive performance. The parameteric optimization was done, by using multi-response optimization with desirability function approach, to simultaneously maximize the decolorization and degradation efficiency. Optimization of photocatalytic decolorization and degradation of dye and dye mixture by RSM effectively copes with interaction between optimizing variables and its prediction agreed well with the results of ANN model and experimental run. The decolorization and degradation of the single dye solution follows the first order kinetics and decolorization of binary mixture of AB113 and AR114 follow the first order kinetics. Total organic carbon (TOC) removal and GC-MS study of all the dyes show the total mineralization. TiO2 nanoparticles have been doped and codoped with four different metal ions (Fe, Cu, V and Co) by wet impregnation method with 1 and 2 wt% metal. The doped and codoped TiO2 has been characterized by standard analytical techniques like XRD, FESEM, TEM, FTIR, UV-Vis DRS and XPS. The powder XRD technique reveals that the modified catalyst contains anatase phase and existence of metal ion in the lattice of TiO2. FESEM images reveal that average particle size of modified TiO2 lies between 18 to 24 nm due to asymmetric shape of nano-crystallite TiO2. From TEM images it is clear that the doping and codoping of metal ions do not leave any change in the shape of the nanoparticles. FTIR patterns show the stretching and vibration patterns of hydroxyl radicals present in nanoparticles. UV-Vis used to find out the energy band gap of modified nanoparticles (2.38, 2.45 and 2.53 eV for TFe1.0Cu1.0, TFe1.0V1.0 and TFe1.0Co1.0 respectively). X-ray Photoelectron Spectroscopy (XPS) showed the elemental surface composition and oxidation state of elements. The photocatalytic activity of the modified nanoparticles (Fe, Cu, V and Co doped and codoped TiO2) has been studied by photo-decolorization of three textile dyes (Reactive Black 5, Acid Red 114 and Acid Blue 113) under 250 W low pressure halogen lamp. Photocatalytic study shows that the two metal ions codoped TiO2 retained enhanced rate in comparison to doped and un-doped TiO2 for the decolorization of all the three textile dyes. The reaction kinetics show the highest rate for the photocatalytic decolorization using codoping of two metal ions for the three dyes. Further TiO2 has been immobilized on cement beads using dip coating method. The stability of immobilized beads has been checked in batch reactor and found that the immobilization of TiO2 is stable for more than 25 cycles. Baffled fixed bed reactor has been used for this study in continuous mode, and it was found that all the three dyes have been degraded up to 90% using baffled fixed bed reactor. Reaction kinetic results show that decolorization of all the three dyes follows the first order reaction kinetics.