4.6 Article

Extraction of Ibuprofen from Natural Waters Using a Covalent Organic Framework

期刊

MOLECULES
卷 25, 期 14, 页码 -

出版社

MDPI
DOI: 10.3390/molecules25143132

关键词

covalent organic frameworks; pharmaceutical pollutants; adsorption; environmental water samples

资金

  1. Norte Portugal Regional Operational Programme (NORTE2020) under the PORTUGAL 2020 Partnership Agreement through the European Regional Development Fund (ERDF) [NORTE-01-0145-FEDER-000019]
  2. CDTi Mytitox Innterconecta through the European Regional Development Fund (ERDF)

向作者/读者索取更多资源

Ibuprofen is one of the most widely used pharmaceuticals, and due to its inefficient removal by conventional wastewater treatment, it can be found in natural surface waters at high concentrations. Recently, we demonstrated that the TpBD-(CF3)(2)covalent organic framework (COF) can adsorb ibuprofen from ultrapure water with high efficiency. Here, we investigate the performance of the COF for the extraction of ibuprofen from natural water samples from a lake, river, and estuary. In general, the complexity of the natural water matrix induced a reduction in the adsorption efficiency of ibuprofen as compared to ultrapure water. The best performance, with over 70% adsorption efficiency, was found in lake water, the sample which featured the lowest pH. According to the theoretical calculations, ibuprofen more favorably interacts with the COF pores in the protonated form, which could partially account for the enhanced adsorption efficiency found in lake water. In addition, we explored the effect of the presence of competing pharmaceuticals, namely, acetaminophen and phenobarbital, on the ibuprofen adsorption as binary mixtures. Acetaminophen and phenobarbital were adsorbed by TpBD-(CF3)(2)with low efficiency and their presence led to an increase in ibuprofen adsorption in the binary mixtures. Overall, this study demonstrates that TpBD-(CF3)(2)is an efficient adsorbent for the extraction of ibuprofen from natural waters as well.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据