Investigation of Nigerian Coconut Shell and Banana Peels for the Removal of Carbon Monoxide (CO) in Indoor Environment

T.O. Ogunjinmi^1, , O.F. Ogayemi², F. A. Akeredolu¹ and J. A. Sonibare¹

¹Department of Chemical Engineering, Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria

²Institute for Sustainable Development, First Technical University Ibadan, Oyo State, Nigeria

Cite this paper:
T.O. Ogunjinmi, O.F. Ogayemi, F. A. Akeredolu and J. A. Sonibare. Investigation of Nigerian Coconut Shell and Banana Peels for the Removal of Carbon Monoxide (CO) in Indoor Environment. American Journal of Environmental Protection. 2023; 11(1):7-14. doi: 10.12691/env-11-1-2

Abstract

In this study, copper chloride modified activated carbon was synthesised by thermal monolayer dispersion (deposition) process. Characterization of the adsorbents were carried out using Fourier Transform Infrared Spectroscopy (FTIR), proximate analysis and ultimate analysis. Furthermore, Response Surface Methodology (RSM) and Artificial Neural Network (ANN) were combined to determine the optimum conditions at which the synthesised adsorbent can remove carbon monoxide from the ambient environment. It cost implication was also determined. This was with a view to examine the Carbon Monoxide removal potential of the synthesised adsorbent. The characterization results showed that the prepared activated carbon are suitable precursor for the impregnation of copper (I) chloride. The RSM showed the optimum condition to be 20g CuCl/CSAC for 10mins with predicted CO adsorption of 77.01% with R² value of 0.9843 and 15g of CuCl/BPAC for 10mins with predicted CO adsorption of 69.71% with R² value of 0.9759. The ANN results were 25g CuCl/CSAC for 10mins with predicted CO adsorption of 77.15% with R² value of 1 and 20g of CuCl/BPAC for 10mins with predicted CO adsorption of 69.17% with R² value of 1. The ANN model indicates a better accuracy over RSM.

Keywords:
adsorption carbon monoxide RSM and ANN

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