Removal of COD and color from textile industrial wastewater using wheat straw activated carbon: an application of response surface and artificial neural network modeling.

A novel approach has been undertaken wherein chemically modified wheat straw activated carbon (WSAC) as adsorbent is developed, characterized, and examined for the removal of COD and color from the cotton dyeing industry effluent. Thirty experimental runs are designed for batch reactor study using the central composite method (CCM) for optimizing process parameters, namely biochar dose, time of contact, pH, and temperature, for examining the effect on COD and color-removing efficiency of WSAC. The experimental data have been modeled using the machine learning approaches such as polynomial quadratic regression and artificial neural networks (ANN). The determined optimum conditions are pH: 7.18, time of contact: 85.229 min, adsorbent dose: 2.045 g/l, and temperature: 40.885 °C, at which the COD and color removal efficiency is 90.92 and 94.48%, respectively. The nonlinear pseudo-second order (PSO) kinetic model shows good coefficient of determination (R ~ 1) values. The maximum adsorption capacity for COD and color by WSAC is at the pH of 7, the temperature of 40 °C, adsorbent dose of 2 g/l is obtained at the contact time of 80 min is 434.78 mg/g and 331.55 PCU/g, respectively. The COD removal and decolorization is more than 70% in the first 20 min of the experiment. The primary adsorption mechanism involves hydrogen bonding, electrostatic attraction, n-π interactions, and cation exchange. Finally, the adsorbent is environmentally benign and cost-effective, costing 16.66% less than commercially available carbon. The result of the study indicates that WSAC is a prominent solution for treating textile effluent. The study is beneficial in reducing the pollutants from textile effluents and increasing the reuse of treated effluent in the textile industries.