Development of data-driven models for the optimal design of multilayer sand filters for on-site treatment of greywater

Abstract

Greywater, with limited content of pathogens, makes up more than half of the produced wastewater in urban areas. Given the high cost of wastewater management and treatment, it causes sense to collect greywater separately at the source and employ an on-site treatment system to increase opportunities for on-site water reuse. For this purpose, this paper aims to propose a multilayer granular filter as an inexpensive and simple on-site treatment method for greywater reuse. Furthermore, as determining the optimal structure of multilayer filters is a serious challenge, a simulation-optimization model is developed for determining the best filter configuration. An Artificial Neural Network (ANN) is trained based on experimental results to simulate the filter performance with different combinations of layers and the Genetic Algorithm (GA) is used to find the optimal thickness of different layers based on ANN simulation results. The proposed filter in this paper for greywater treatment consists of silica sand (in three different gradings) and activated carbon (with fixed grading) and treatment measures for evaluation of filter performance are considered as Chemical Oxygen Demand (COD) and Electrical Conductivity (EC). Due to difficulties in collecting, transferring, and storing the real greywater, synthetic greywater was used in this study. 49 experiments with different combinations of filter media thicknesses were performed and the performance of the filter was analyzed. Generally, three-layer filters perform better in COD and EC reduction, however, the average COD and EC elimination equals 36.3% and 15.1%, respectively, which indicates more efficiency of filter in COD reduction in comparison with EC. Based on the optimization-simulation model and experimental results, a filter consisting of 33 cm of fine sand, 20 cm of activated carbon, and 7 cm of medium sand results in the maximum efficiency and can reduce the COD and EC of greywater by 72% and 30%, simultaneously. According to the optimization outputs, the ideal filter can treat greywater up to having EC of 1000 μS/cm and COD of 321 mg/L, which is generally suitable for irrigation purposes.