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.
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