Sustainable and optimized values for municipal wastewater: The removal of biological oxygen demand and chemical oxygen demand by various levels of geranular activated carbon- and genetic algorithm-based simulation

Municipal wastewater treatment in Mashhad, Iran, became increasingly concerned with removing hazardous organic matter. Granular activated carbon (GAC) units downstream are necessary to minimize chemical oxygen demand (COD) and biological oxygen demand (BOD) concentrations by 80–94% to meet effluent treatment; secondary treatment from municipal wastewater only reduces 47% of residual COD and BOD. This study analyzes different types of GAC for COD and BOD adsorption at different contact times and dosages. The dosage of GACs is 0.15, 0.2, and 0.25, with a surface area of 644.5 m2/g and a suitable size of 14.89 nm. Using and genetic algorithms-artificial neural networks (GA-ANNs), sustainable and optimization values are determined for municipal wastewater. Despite that, it can find solutions to difficult or impossible problems using traditional methods. Another advantage is that GA-ANN can be used to solve problems that have multiple objectives or constraints. They can be used either in conjunction with the biological process or as a tertiary stage after the advanced wastewater treatment process. GAC = 0.25 also confirmed the effectiveness of COD and BOD removal, removing 91% and 93%, respectively.