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Adsorption of Chloramphenicol on Commercial and Modified Activated Carbons

吸附 活性炭 化学 弗伦德利希方程 动力学 朗缪尔 扩散 介孔材料 朗缪尔吸附模型 核化学 色谱法 有机化学 催化作用 热力学 物理 量子力学
作者
Joanna Lach
出处
期刊:Water [MDPI AG]
卷期号:11 (6): 1141-1141 被引量:29
标识
DOI:10.3390/w11061141
摘要

The aim of the study was to evaluate the possibility of applying commercial activated carbons currently used in water treatment plants and modified carbon at 400 and 800 °C in the atmosphere of air, water vapour and carbon dioxide to remove chloramphenicol. Adsorption kinetics was examined for solutions with pH of 2–10. Adsorption kinetics were determined for the initial concentration of chloramphenicol of 161 mg/dm3 and the adsorption isotherm was determined for the concentrations of 161 to 1615 mg/dm3. Of the analysed activated carbons (F-300, F-100, WG-12, ROW 08 Supra and Picabiol), the highest adsorption capacity was obtained for the use of Picabiol (214 mg/g), characterized by the highest specific surface area and pore volume. The pH value of the solution has little effect on the adsorption of chloramphenicol (the highest adsorption was found for pH = 10, qm = 190 mg/g, whereas the lowest—for pH = 6, qm = 208 mg/g). Modification of activated carbon WG-12 at 800 °C caused an increase in adsorption capacity from 195 mg/g (unmodified carbon) to 343 mg/g. A high correlation coefficient was found between the capacity of activated carbons and the total volume of micropores and mesopores. Among the examined adsorption kinetics equations (pseudo-first order, pseudo-second order, Elovich, intraparticle diffusion), the lowest values of the R2 correlation coefficient were obtained for the pseudo-first order equation. Other models with high correlation coefficient values described the adsorption kinetics. The adsorption results were modelled by means of the Freundlich, Langmuir, Temkin and Dubibin–Radushkevich adsorption isotherms. For all activated carbons and process conditions, the best match to the test results was obtained using the Langmuir model, whereas the lowest was found for the Dubibin–Radushkevich model.
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