Abstract
Due to the potential ecological risks of organic pollution in sediments, aquatic ecosystems are currently facing substantial environmental threats. Assessing and controlling sediment pollution has become a huge challenge. Therefore, this study proposes a novel strategy for predicting organic pollution indicators for sediment, as well as an effective resource-utilization method. Contaminated sediments were converted into catalysts for sulfate radical advanced oxidation technologies by a one-step calcination method. The results revealed that the catalyst excelled in activating peroxymonosulfate to degrade tetracycline via a non-radical pathway. Most importantly, a predictive model of organic pollution indicators was established by machine learning. This study provides a novel approach for resource utilization and a strategy for assessing organic pollution in sediments.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.