The Yoon-Nelson model serves as a widely used tool for describing the breakthrough behavior of organic micropollutants within fixed bed adsorbers. This study aims to augment its modeling efficacy through two proposed refinements found in the literature: a logarithmic transformation and the incorporation of steric hindrance effects. We systematically evaluated the original Yoon-Nelson model alongside the modified versions, using breakthrough data associated with micropollutant adsorption on solid materials. Three distinct cases were scrutinized: (1) caffeine adsorption on activated carbon; (2) tetracycline adsorption on hierarchical porous carbon; and (3) diclofenac adsorption on organoclay. While all three models demonstrated comparable performance with highly symmetric breakthrough data in case 1, their efficacy diverged significantly when confronted with strongly asymmetric breakthrough data in cases 2 and 3. The original Yoon-Nelson model and the logarithmically modified version fell short in accurately representing these intricate breakthrough curves. In contrast, the version incorporating steric hindrance effects showcased substantial accuracy, outperforming other models in capturing the complexities of asymmetric breakthrough data. This advancement markedly enhances the modeling accuracy and versatility of the Yoon-Nelson model, particularly in assessing the dynamic behavior of organic micropollutants within fixed bed adsorbers.
Keywords: Asymmetric breakthrough curve; Caffeine; Diclofenac; Tailing; Tetracycline.
© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.