Anaerobic Decolorization of Sulfonated Azo Dyes by Sulfate Reducing Bacteria

Aim: The present study was done to find out ability of sulfate reducing bacteria to reduce sulfonated azo dyes found in the textile effluent. Study Design: Isolate Sulfate reducing bacterial strains from dye contaminated soil samples, inoculate and incubate dye supplemented media under static anaerobic condition and measure the decolorization using UV-VIS spectrophotometer. Place and Duration of Study: The samples were collected from Travancore textiles Nemom, Thiruvananthapuram, Kerala, India. Laboratory analysis were performed at Department of Environmental Sciences, University of Kerala, Thiruvananthapuram, India. The study was done for a period of six months. Methodology: The isolated sulfate reducing bacterial (SRB) strains were screened to test the tolerance to selected sulfonated azo dye Direct blue 71. The decolorization assay was done in Postgate media and an aliquot of samples (3mL) were withdrawn periodically, centrifuged at 10,000rpm for 15min. The supernatant was used to assay azo dye reduction by measuring residual absorption at the wavelength 594 nm of the Direct Blue 71. Results were compared with the uninoculated control. The optimization of physicochemical conditions for effective decolorization of the selected bacterial strains was studied at different environmental conditions (pH, temperature, concentration and added co-substrates such as sodium acetate, lactate and mannitol). The biodegradation of sulfonated azo dye was assessed by characterizing the metabolites formed after degradation by Fourier Transform Infrared Spectroscopy (FT-IR). FT-IR analysis revealed only decolorization had occurred without degradation of the dye during the short incubation period of one week. Conclusion: Degradation of azo dyes and other recalcitrant compounds by obligate anaerobes such as sulfate reducing bacteria is a slow process. Hence, extension of incubation period is necessary for the effective and complete degradation of the dye by SRB.

Cloud Point Extraction of Direct Blue 71 Dye using Triton X-100 as Nonionic Surfactant

A surfactant-mediated cloud point extraction (CPE) method using the non-ionic surfactant Triton X-100 (TX-100) has been developed to remove the dye Direct Blue 71 (DB71) from a waste water. Most of the dye molecules are solubilized in the coacervate phase so that the dilute phase remains free of the dye. The effects of surfactant concentration, temperature and salt concentration on the different dye concentrations were studied to determine the optimal conditions for removing DB71. The concentration of DB71 in the dilute phase was measured using UV-Vis spectrophotometer. It was found that the separation of phases was complete and the recovery of DB71 was very effective in the presence of NaCl as an electrolyte. The results showed that up to 25 ppm DB71, i.e. more than 95%, can be quantitatively removed by cloud point extraction procedures in a single extraction at optimal conditions. It was also observed that at a dye concentration of 1 ppm, 100% of the blue dye DB71 can be directly removed with a TX-100 concentration of 12% by weight. At higher dye concentrations of up to 30 ppm, 94.7%-100% dye can be removed. The TX-100 concentration was 12 wt%, the salt concentration (NaCl) 0.005 M and the temperature 75°C. It is concluded that the surfactant mediated cloud point extraction method for dye removal can be an alternative to current dye removal methods.

Microbial Decolorization of Triazo Dye, Direct Blue 71: An Optimization Approach Using Response Surface Methodology (RSM) and Artificial Neural Network (ANN)

The release of wastewater from textile dyeing industrial sectors is a huge concern with regard to pollution as the treatment of these waters is truly a challenging process. Hence, this study investigates the triazo bond Direct Blue 71 (DB71) dye decolorization and degradation dye by a mixed bacterial culture in the deficiency source of carbon and nitrogen. The metagenomics analysis found that the microbial community consists of a major bacterial group of Acinetobacter (30%), Comamonas (11%), Aeromonadaceae (10%), Pseudomonas (10%), Flavobacterium (8%), Porphyromonadaceae (6%), and Enterobacteriaceae (4%). The richest phylum includes Proteobacteria (78.61%), followed by Bacteroidetes (14.48%) and Firmicutes (3.08%). The decolorization process optimization was effectively done by using response surface methodology (RSM) and artificial neural network (ANN). The experimental variables of dye concentration, yeast extract, and pH show a significant effect on DB71 dye decolorization percentage. Over a comparative scale, the ANN model has higher prediction and accuracy in the fitness compared to the RSM model proven by approximated R2 and AAD values. The results acquired signify an efficient decolorization of DB71 dye by a mixed bacterial culture.