The goal of this paper is to model the activated carbon adsorption capacity of cadmium using a polynomial regression model. The properties that influence the removal of heavy metals by activated carbon must be taken into consideration in order to synthesize materials specific to the characteristics of the pollutant.
Multivariable analysis applications allow a comprehensive description of the relationship between activated carbon surface properties and heavy metal adsorption.
The authors use a second-grade polynomial regression model to determine the influence of porosity and surface acidity in cadmium adsorption by activated carbon.
The authors propose a statistic analysis to correlate the carbon properties with its cadmium adsorption capacity. Model coefficient analysis will give a better comprehension of the influence of activated carbon porosity and surface acidity of cadmium removal.
