4.7 Article

Antibiotics and antimycotics in waste water treatment plants: Concentrations, removal efficiency, spatial and temporal variations, prediction, and ecological risk assessment

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ENVIRONMENTAL RESEARCH
卷 215, 期 -, 页码 -

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ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.envres.2022.114135

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Antibiotics; Antimycotics; Domestic waste water; Machine learning; Risk assessment

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This study investigated the concentration, removal efficiency, and spatial-temporal variations of antibiotics and antimycotics in influent and effluent of wastewater treatment plants in Tianjin. The researchers used high performance liquid chromatography tandem mass spectrometry to analyze the samples and found significant differences in concentrations between seasons and regions. By establishing predictive models based on influent and effluent data, the study provided a quantitative relationship between key features and concentration. The ecological risk was evaluated through the RQ values, which showed good agreement between predictions and observations.
For investigating the spatial, temporal variations and assessing ecological risk of 10 antibiotics and 6 antimycotics, influent sewage water and treated effluent were collected during three different seasons in 19 waste water treatment plants of Tianjin. High performance liquid chromatography tandem mass spectrometry was used to analyze 16 substances. The concentration range of influent samples was not detected (nd) -547.94 ng/L and the concentration range of effluent samples was nd-52.97 ng/L. By calculating the removal efficiency, it was found that Ciprofloxacin (CIP), Ofloxacin (OFL) and Clotrimazole (CTR) were effectively removed. There were significant spatial and temporal differences, the concentration in the dry season was evidently higher than that in the wet and normal seasons, and the northeast was lower than that in the northwest and southeast. By establishing a data set of influent and effluent, the priority features were extracted by feature engineering, which were temperature and NH3-N. Under the condition of ensuring the best performance of the models, the influent model with 9 features and the effluent model with 4 features were established, and the quantitative relationship between the above features and concentration was obtained through partial dependence analysis. Except for Moxifloxacin (MOX), Norfloxacin (NOR) and OFL in the influent samples, the RQ values for other antibiotics and antimycotics were less than 0.1. Among the effluent samples, only NOR had an RQ value greater than 0.1, and OFL, MOX, and Pefloxacin (PEF) had RQ values between 0.01 and 0.1. Comparing the observations and pre-dictions individual RQ values, the predictions were ideal and matched the observations. This work effectively assessed environmental impact and provided a valuable reference for evaluating antibiotics and antimycotics ecological toxicity.

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