Optimal conditions for the biological removal of ammonia from wastewater of a petrochemical plant using the response surface methodology

High concentrations of nitrogen compounds, such as ammonia observed in the petrochemical industry, are the major environmental pollutants. Therefore, effective and inexpensive methods are needed for its treatment. Biological treatment of various pollutants is a low cost and biocompatible replacement for current physico-chemical systems. The use of aquatic plants is an effective way to absorb the nutrient pollutants. In this study, the optimal operating conditions in the biological removal of ammonia from the urea-ammonia wastewater of Kermanshah Petrochemical Company by Lemna gibba were determined using the response surface methodology. Lemna gibba was collected from the ponds around Kermanshah and maintained in a nutrient medium. Effect of the main operational variables such as ammonia concentration, residence time and Lemna gibba to surface ratio on optimal conditions of ammonia removal from wastewater has been analyzed using the Box-Behnken model design of experiments. Model numerical optimization was performed to achieve the maximum amount of ammonia removal from wastewater. The ammonia removal percentage varied from 13% to 88%, but the maximum amount of ammonia removal was determined atammonia concentration of 5 ppm and Lemna gibba residence time of 11 days in wastewater based on the quadratic model. Lemna gibba to surface ratio of 2:5 was measured at 96.449%. After optimization, validation of ammonia removal was performed under optimum conditions and measured at 92.07%. Based on the experimental design and the predicted under model conditions, the maximum amounts of ammonia removal percentage in the experiments were 82.84% and 88.33% respectively, indicating the high accuracy of the model to determine the optimum conditions for the ammonia removal from wastewater.

Keywords:

Ammonia removal , Lemna gibba , Optimization , Petrochemical wastewater , Response surface methodology