An integrated multimedia fate modeling framework for identifying mitigation strategy of antibiotic ecological risks: A case study in a peri-urban river.

Environ Res

Engineering Research Center of Groundwater Pollution Control and Remediation, Ministry of Education, College of Water Sciences, Beijing Normal University, No 19, Xinjiekouwai Street, Beijing, 100875, China. Electronic address:

Published: December 2023

AI Article Synopsis

  • Antibiotic pollution is a significant concern, as their widespread use has led to frequent detections in rivers, posing ecological risks to aquatic life and public health.
  • An integrated framework using multimedia fugacity modeling and ecotoxicological risk assessment was developed to identify management strategies for mitigating these antibiotic ecological risks (AERs) in a river in Beijing.
  • The study found that most detected antibiotics present medium to high risks to aquatic organisms, with certain classes like macrolides and fluoroquinolones being more hazardous, and it suggests that both reducing antibiotic consumption and improving removal rates are effective strategies for risk mitigation.

Article Abstract

Antibiotics have been heavily used over the past decades, resulting in their frequent detections in rivers and increasing ecological risks. Recognizing characteristics of antibiotic ecological risks (AERs) and making effective strategies to mitigate the AERs are essential to ensure the safety of aquatic ecosystem and public health. In this study, an integrated technological framework has been proposed toward identifying management options for reducing AERs by jointly utilizing multimedia fugacity modelling and ecotoxicological risk assessment, and applied to characterize the AERs in a peri-urban river in Beijing. Specifically, a level III fugacity model has been successfully established to simulate the fate of antibiotics in the environment, and the manageable parameters have been screened out via sensitivity analysis of the model. Then the validated fugacity model has been used for scenario modellings to optimize mitigation strategies of AERs. Results show most of the antibiotics considered are frequently detected in the river, and pose medium or high risks to aquatic organisms. Relatively, the macrolides and fluoroquinolones present higher ecotoxicological risks than sulfonamides and tetracyclines. Furthermore, the mixture risk quotient and predictive equation of concentration addition suggest joint and synergistic/antagonistic effects of AERs for multiple or binary antibiotics in the environment. Largely, the concentrations of antibiotics in the river are determined by the source emissions into water and soil. Scenario modellings show the improvement of antibiotic removal rates would be considered preferentially to mitigate the AERs. Also, controlling human consumption is conducive to reducing the risks posed by tetracyclines, macrolides and trimethoprim, while controlling animal consumption would benefit the reduction for sulfonamides. Overall, the joint strategy presents the greatest reduction of AERs by reducing antibiotic consumption and together improving sewage treatment rate and antibiotic removal rate. The study provides us a useful guideline to make ecological risk-based mitigation strategy for reducing AERs in environment.

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Source
http://dx.doi.org/10.1016/j.envres.2023.117225DOI Listing

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