Abstract

The effluents from the industries such astextile, paper and pulp, cosmetic and pharmaceutical sector consists of huge load of hazardous azo dye, which enters the water bodies and affects the environment and human health. In this work dye degrading Lysinibacillus sp.was immobilized on the surface of cow dung biochar for treatment of wastewater containing Malachite green (MG), Auramine yellow (AY) and Methyl orange (MO) azo dye in a fabricated continuous packed bed reactor (CPBR). The adsorption isotherm study suggested that Langmuir isotherm showcased comparatively a better model than Freundlich. The dye removal efficiencies were calculated as 52.360 ± 0.209 and 78.241 ± 0.211% for the free and immobilized bacterial cells in a batch study. The dye decolorization process was further investigated by performing the statistical optimization of parameters through Central composite design model-based response surface methodology (CCD-RSM) and artificial neural network (ANN). The dye removal efficiency by CCD-RSM and ANN model was found to be 98.420 and 97.320%, respectively. Prediction made by the developed models suited well with the test runs. This study suggested that RSM and ANN can be considered as effective tools to model and predict trace pollutants removal by CD biochar.

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