Surface- and Substrate-Coated Catalytic Membrane for Mitigating Interference of Water Matrix Species in Intensified Micropollutant Confinement Oxidation
JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING(2024)
Abstract
The integration of advanced oxidation processes (AOPs) with membrane technology offers benefits for catalyst recovery and reducing membrane fouling. However, the application of the hybrid process could be hampered by the background species in water matrix. This study addresses this challenge by developing catalytic ceramic membranes (CCMs) with dual mechanisms to intensify acetaminophen (ACT) removal in water. The CCMs effectively activated peroxymonosulfate (PMS), achieving ACT degradation of 85 % and 93 % in real water matrices (reverse osmosis retentate and settled water, respectively) and 99 % in MQ water. The CCMs demonstrated consistent performance across multiple operational cycles, even in the presence of humic acid (HA) (96 % ACT reduction). The CCM design features Co3O4 catalytic layer on CCM surface, facilitating surface oxidation, reducing fouling, and TiO2 intermediate rejection layers serving as barrier for bulk organic pollutants, achieving 50 % HA removal through rejection and 70 % with 1.5 mM PMS. This design facilitates catalytic degradation at the membrane surface, allowing retention and degradation of bulk organic pollutants and intermediates, while ACT permeates into CCM substrate. The surface oxidation and rejection enhanced confinement oxidation within the Co3O4-coated macropores, minimizing interference from background species. LC-QTOF analysis identified multiple degradation pathways, including hydroxylation, acetyl-amino group cleavage, side chain oxidation and benzene ring cleavage, with intermediates showing reduced toxicity. Reactive oxygen species involved in the system were identified and PMS activation mechanism was proposed. This research highlights the potential of the hybrid process, enhancing micropollutant removal by mitigating interference from background species, providing practical implications in water treatment applications.
MoreTranslated text
Key words
Fouling mitigation,Catalytic separation layer,Hierarchical porosity,Hybrid membrane reactor,Persulfate
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined