The use of linear and nonlinear methods for adsorption isotherm optimization of basic green 4-dye onto sawdust-based activated carbon

Abstract

The abundance and low cost of sawdust as an agricultur al by - product make it a potential candidate as precursor of activated carbon preparation. In this study, the sawdust samples were chemically treated with acid (20% H 3 PO 4 ,170°C, 2h), base (20%KOH, ambient, 24h) and salt (1mol/L (NH 4 ) 2 S 2 O 8 , ambient, 24h) separately followed by pyrolysis at 600 C for 3h, resulting respectively in SD - 1, SD - 2, SD - 3 sawdust - based activated carbons respectively used as adsorbents for basic green 4 dye removal from aqueous media and the results were compared to the commercially available Merck activated carbon. Batch adsorption tests were performed and the experimental data analyzed using the Langmuir and Freundlich models in their linear and non linear forms, in order to estimate the equilibrium parameters. For optimum adsorptio n isotherm selection, a comparison of linear and nonlinear regression methods was applied. Three errors functions: Chi - square statistic ( χ 2 ), root mean square error (RMSE) and Average percentage error (APE) were used for isotherm optimization prediction. W hile the coefficient of determination ( R 2 ) was used for the best - fit linear theoretical isotherm selection