Modeling of pharmaceuticals removal from wastewater for urban wastewater reuse

Release of pharmaceuticals into the water resources and environment is considered an emerging problem. That is to say that their removal from aquatic environments or reuse of wastewater is considered a big challenge. Conventional biological treatment methods are failed to completely remove these compounds. For example, the three-dimensional (3D) electrochemical process is an effective method to remove pharmaceuticals from the wastewater for urban wastewater reuse. Modeling of pharmaceuticals removal in a 3D electrochemical process is of great importance to predict the performance of this process. This study is aimed to develop the most appropriate predictive model, to estimate the percentage of pharmaceuticals removal from wastewater in a 3D electrochemical process with granular activated carbon (GAC). To this end, an adaptive neuro-fuzzy inference system (ANFIS) is used with respect to the real measured data of carbon granule amount, sodium chloride concentration, contact time, and pH values. Superior model possesses the minimum value of root mean squared errors and the best squared correlation coefficient in calibration and validation. Results reveal that the developed method based on ANFIS is a beneficial tool to evaluate the performance of pharmaceuticals removal in a 3D electrochemical process with GAC. The developed model can be a very powerful substitute for time-consuming costly experimental methods.

Keywords:

wastewater reuse , modeling , pharmaceuticals , 3D electrochemical process , ANFIS , wastewater treatment.