Bio-coagulation-flocculation (BCF) of municipal solid waste leachate using Picralima nitida extract: RSM and ANN modelling

Abstract

The performance of Picralima nitida extract (PNE) in bio-coagulation-flocculation (BCF) for the reduction of chemical oxygen demand (COD) in municipal solid waste leachate (MSWL) was studied. The PNE was characterised via Scanning electron microscopy (SEM) and Fourier transform infrared (FTIR). The process was modelled using both the response surface methodology (RSM) and artificial neural network (ANN) methods, and their prognostic capabilities established. The coagulant precursor was found to contain protein (28.4%) which is an active component of a good coagulant for neutralisation and adsorption of the colloidal particles. C=O, O–H, and N-H functional groups were present in the extract which are preferred for BCF process. This process was effectively optimised (COD ​= ​75.25 ​± ​0.5%) to achieve the best removal at pH ​= ​2.3, PNE dosage ​= ​0.38 ​g/L, and time ​= ​28.22. min. The analysis of variance indicated that the RSM model was statistically suitable for the interpretation of the processes at the studied range. The RSM and ANN were capable of predicting the COD reduction process with the latter giving the best prediction with lesser error and nonlinear relationship. Though ANN had superior accuracy, RSM has the advantage of giving a predictive equation and showing the effect of operating factors and their interactions on the response compared. The mechanisms of the process were charge neutralisation, adsorption and bridging.