Enhanced degradation of pharmaceuticals in wastewater by coupled radical and non-radical pathways: Further unravelling kinetics and mechanism.

Journal of hazardous materials(2023)

引用 0|浏览9
暂无评分
摘要
Advanced oxidation processes based on radicals and/or non-radical catalysis are emerging as promising technologies for eliminating pharmaceuticals (PhACs) from wastewater. However, the respective contributions of different removal pathways (radicals or non-radical) for PhAC degradation still lacks quantitative investigation. Zero-valent iron and carbon nanotubes are frequently used to generate both radicals and non-radical species via the activation of persulfate (Fe/SWCNT/PDS). Herein, the removal kinetics of 1 μM PhACs are depicted, and the corresponding synergistic mechanism of the Fe/SWCNT/PDS process is discussed. Coupled removal pathways showed the higher degradation of PhACs than the individual pathways. Radicals quenching studies combined with electron spin resonance characterisation suggested that the radical-based removal pathway tends to attack electron-deficient organics, whereas its counterpart is more likely to work on electron-rich organics. From the perspectives of the contribution rate, the redox cycles of conjugated Fe species play a more important role in the generation of radicals than free Fe species, and the faster electron transfer in the conductive bridge offered by SWCNT is responsible for the effective corrosion of Fe and the decomposition of PDS. Six real wastewater samples were used to prove the generality of the above removal contribution, regardless of the wastewater samples, and the results suggested that identical attack patterns were obtained in all real wastewater samples, although coexistence matrix slightly suppressed PhAC removal. This work provides a deeper insight into the high-performance working mechanism on synergistic interactions and contaminant removal in a combined catalysis system.
更多
查看译文
关键词
Advanced oxidation process,Combined catalysis,PhACs degradation,Removal pathways,Wastewater
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要