Application of multigene genetic programming and water evaporation optimization technique for modeling and optimization of removal of heavy metals from ash pond water using cyanobacterial consortium

Abstract

Abstract Heavy metals such as Lead(II), Nickel(II), Manganese(II), Cadmium(II), Chromium(VI), etc., are leached from the coal ash of thermal power plants. These metals contaminate ash pond water and subsequently contaminate groundwater. Phycoremediation using microalgae/cyanobacteria is an emerging technology for removal of heavy metals. The present study aims at phycoremediation of the said heavy metals from ash pond water using cyanobacterial consortium of Limnococcus limneticus and Leptolyngbya subtilis followed by the development of an accurate data-driven Multigene Genetic Programing (MGGP) approach for modeling and optimization of the process. The developed model was used to obtain a correlation between the average removal of metals and biomass production with all input factors such as the initial metal concentrations, pH, and days of incubation. To maximize metal removal and biomass production, the Water Evaporation Optimization (WEO) technique was applied to determine optimal values of input parameters. The application of WEO for the optimization of the phycoremediation process is the first of its kind and here lies the novelty of the study.