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The significance of granular activated carbon pore structure in modeling dissolved organic carbon removal in fixed-bed filters

吸附 传质 活性炭 扩散 微型多孔材料 化学 化学工程 碳纤维 溶解有机碳 过滤(数学) 生物降解 色谱法 材料科学 热力学 有机化学 环境化学 复合材料 数学 复合数 工程类 物理 统计
作者
Tobias Kaiser,Vanessa Acevedo Alonso,Thomas Fundneider,Susanne Lackner
出处
期刊:Chemical Engineering Journal [Elsevier]
卷期号:464: 142729-142729 被引量:1
标识
DOI:10.1016/j.cej.2023.142729
摘要

A reliable model that describes DOC removal during biological-active granular activated carbon filtration for advanced wastewater treatment has to cover several aspects that influence biological and adsorptive removal processes. For this purpose, this work introduces a two-domain internal diffusion approach to a multicomponent adsorption model, which is combined with a traditional biofilm model for the first time. DOC was divided into fictive components according to biodegradability and adsorbability to calculate multicomponent adsorption equilibrium based on the ideal adsorbed solution theory. Adsorption kinetics included external mass transfer (diffusion through a boundary layer and a biofilm) and internal mass transfer (fast pore diffusion in the larger pores and slow surface diffusion in the micropores). Mass transfer in the micropore domain was implemented by adjusting the adsorptive driving force depending on the available internal surface area for DOC adsorption based on an empirical surface diffusion model. Simulated DOC breakthrough curves were sensitive to model parameters related to the pore structure of the granular activated carbon (GAC). The model was validated with two GAC types and empty bed contact times ranging between 6 and 33 min. The model results showed a good agreement with measured DOC breakthrough curves over the entire operation time, demonstrating the applicability and transferability of the model. In particular, the initial DOC breakthrough was well represented. However, some systematic deviations between measured and simulated DOC breakthrough curves were observed, which are probably due to the level of detail of the implemented biofilm model.
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