Interactive effects of urine components and treatment conditions on antibiotic degradation of combined system integrating thermally activated peroxydisulfate and membrane distillation using machine learning

Chemical Engineering Journal(2024)

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摘要
The antibiotic degradation in urine is gaining focus as it’s essential for resource recovery. Complex organic and inorganic substances in urine impact degradation efficiency through their involvement in radical-type chain reactions. In this study, more than 95 % of sulfamethoxazole (SMX) in urine was successfully degraded in both concurrent and sequential modes of a combined system integrating thermally activated peroxydisulfate and membrane distillation (TAP-MD), previously shown to be effective for resource recovery. Three algorithms, including random forest (RF), XGBoost, and support vector machine (SVM), were applied to model the impact of urine components and treatment conditions on SMX degradation. The XGBoot and RF models, fine-tuned by Bayesian optimization, are accurate and credible in both prediction and interpretation (R2 > 0.90). The models suggest that the improvement of SMX degradation by the MD process is due to PDS enrichment, with high PDS concentrations significantly promoting SMX degradation. Urea and HCO3− are the key factors impacting SMX degradation efficiency, followed by temperature, PDS, Cl−, and NH4+. Additionally, strong interaction effects between urine components were found on SMX degradation, contrasting with results from individual ions that were present in isolation. At high urea concentration (>100 mM), increasing concentrations of Cl−, NH4+, and HCO3− significantly inhibited SMX degradation. As the second key factor on SMX degradation, HCO3− can react with S2O82− without producing free radicals, resulting in a reduction in its yield. Furthermore, in the presence of high concentrations of HCO3−, the Cl− and NH4+ negatively affect the kobs of SMX degradation. The HCO3− competes with SMX for Cl to produce the weak oxidant CO3∙−, which reacts quickly with NH2∙ without producing other free radicals, causing a loss of free radicals.
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关键词
Antibiotic degradation,Human urine,Machine learning,SHAP (SHapley Additive exPlanations),Thermally-activated persulfate
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