Optimization of parameters using response surface methodology and genetic algorithm for biological denitrification of wastewater

Abstract

In the present study the removal of nitrates from wastewater using Pseudomonas stutzeri microorganism in a Gas–Liquid–Solid bioreactor at the concentration of 200 ppm was studied for a period of 12 h. The response surface methodology with the help of central composite design and genetic algorithm were employed to optimize the process parameters such as airflow rate, biofilm carrier, carbon source, temperature and pH which are responsible for the removal of nitrates. The optimized values of parameters found from RSM are airflow rate 2.41 lpm, biofilm carrier 15.15 g/L, carbon source 85.0 mg/L, temperature 29.74 °C, pH 7.47 and nitrate removal 193.16. The optimized parameters obtained from genetic algorithm are airflow rate 2.42 lpm, biofilm carrier 15.25 g/L, carbon source 84.98 mg/L, temperature 29.61 °C, pH 7.51 and nitrate removal is 194.14. The value of R2 > 0.9831 obtained for the present mathematical model indicates the high correlation between observed and predicted values. The optimal values for nitrate removal at 200 ppm are suggested according to genetic algorithm and at these optimized parameters more than 96 % of nitrate removal was estimated, which meets the standards for drinking water.