@article{env20231112,
author={{Ogunjinmi, T.O. and Ogayemi, O.F. and Akeredolu, F. A. and Sonibare, J. A.},
title={Investigation of Nigerian Coconut Shell and Banana Peels for the Removal of Carbon Monoxide (CO) in Indoor Environment},
journal={American Journal of Environmental Protection},
volume={11},
number={1},
pages={7--14},
year={2023},
url={http://pubs.sciepub.com/env/11/1/2},
issn={2328-7233},
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 R<SUP>2</SUP> value of 0.9843 and 15g of CuCl/BPAC for 10mins with predicted CO adsorption of 69.71% with R<SUP>2</SUP> value of 0.9759. The ANN results were 25g CuCl/CSAC for 10mins with predicted CO adsorption of 77.15% with R<SUP>2</SUP> value of 1 and 20g of CuCl/BPAC for 10mins with predicted CO adsorption of 69.17% with R<SUP>2</SUP> value of 1. The ANN model indicates a better accuracy over RSM.},
doi={10.12691/env-11-1-2}
publisher={Science and Education Publishing}
}