Adsorption of phenol based organic pollutants on activated carbon from multi-component dilute aqueous solutions

• Published in: Water research (Oxford) Vol. 31; no. 8; pp. 2102 - 2112
• Main Authors: Khan, A.R., Al-Bahri, T.A., Al-Haddad, A.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.08.1997; Elsevier Science
• Subjects: activated carbon; adsorption isotherm; Applied sciences; equilibrium; Exact sciences and technology; General purification processes; multi-component; organic pollutants; Pollution; Wastewaters; Water treatment and pollution; activated carbon; equilibrium; adsorption isotherm; multi-component; organic pollutants; Adsorption; Activated carbon; Phenols; Physicochemical purification; Aqueous solution; Waste water purification; Experimental study; Modeling
• ISSN: 0043-1354; 1879-2448
• DOI: 10.1016/S0043-1354(97)00043-2

Five organic phenolic compounds (phenol, o-chlorophenol, m-chlorophenol, p-chlorophenol and m-cresol) have been used to determine the adsorption isotherms for single and bisolute systems from dilute aqueous solutions on activated carbon. An experimental technique for the analysis of the equilibrium concentration of a bisolute in aqueous solutions using a UV spectrophotometer has been successfully developed and employed. Experimental data were obtained by conducting experiments in a shaker-incubator at 30°C (local average ambient temperature). All common types of reported isotherms, including Langmuir, Freundlich, BET (Brunauer, Emmett and Teller) and empirical types, were tried. For single solute systems the experimental data were found to be best represented by the Freundlich isotherm for all cases except for phenol, which followed the Langmuir isotherm. For bisolute systems, the coefficients for all the most commonly used models were determined accurately applying a modified Rosenbrock method for non-linear optimization. The present and previous published experimental data and predicted model results have been analysed statistically to validate the applicability of the models. The generalized and empirical models have shown a better fit than the other most commonly used models (Langmuir and Freundlich). The empirical model has minimal error between predicted and experimental values due to more constants in the expression as compared to the generalized model. The generalized model has a unique characteristic, covering both extremes, Langmuir as well as Freundlich type isotherms, and could represent all types of data for multi-component systems with fewer coefficients with almost the same degree of accuracy as the empirical model.