Response Surface Methodology: A Review on Optimization of Adsorption Studies
Simon Bbumba, Moses Kigozi, Jackline Nabatanzi, Ibrahim Karume, Chinaecherem Tochukwu Arum, Hussein Kisiki Nsamba, Ivan Kiganda, Moses Murungi, John Ssekatawa, Resty Alexandria Nazziwa
Asian Journal of Chemical Sciences · pp. 106–113 · Published 11 Nov 2024
10.9734/ajocs/2024/v14i6338Abstract
Herein, we reviewed response surface methodology (RSM), a powerful statistical tool widely used in optimizing adsorption processes to remove synthetic dyes, toxic heavy metals, and phenols from wastewater. The widely used RSM models during optimization are the central composite design and Box-Behnken, which are second-order polynomial models. The models give a predictive insight into the number of experimental runs to be carried out. Furthermore, an in-depth overview of RSM and its application in optimizing various adsorption parameters, such as adsorbent dosage, initial pollutant concentration, contact time, and pH is discussed. In addition, RSM enables researchers to efficiently determine the optimal conditions for maximum pollutant removal. Lastly, the findings of this research highlight the potential of RSM as a valuable tool for optimizing adsorption processes and contributing to sustainable water treatment technologies.
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