Modelling and prediction of toluene adsorption saturation basing on characteristic values of activated carbons.

Herein, the association between the dynamic adsorption capacity of toluene and several important characteristic values on activated carbon (AC) samples was investigated by multidimensional linear regression. Among the characteristic values, the carbon tetrachloride (CTC) adsorption value has demonstrated relatively stronger correlation with the toluene adsorption capacity on AC samples with diverse sources and forms, particularly in exposure to high-concentration toluene. Notably, the relevance of the toluene adsorption capacity to the CTC value could also be extended to a series of other porous adsorbents, which proved the wide applicability of CTC value in characterizing the adsorption behaviors. Based on these results, a mathematical and visual model was then established to predict the toluene adsorption saturation under different conditions (inlet concentration, adsorption time, initial CTC value, etc.) on diverse AC samples, of which the accuracy has later been verified by experimental data. As such, a fast and accurate estimation of the adsorption behaviors over AC samples, and possibly other porous adsorbents, was realized.