Abstract
Antibiotic residues in reservoirs threatens ecosystems and human health. Whereas numerous studies have been conducted on their occurrence and distribution, overall quantitative and comparative analysis of antibiotic contamination in reservoirs is challenging due to scattered data and scale differences. Here, we integrate antibiotic data from 520 samples in 80 reservoirs and provide an overview of the distribution, determinants, and potential risks of these emerging contaminants in reservoirs at a cross-continental scale. A total of 69 antibiotics were detected in reservoirs, with sulfonamides, fluoroquinolones, tetracyclines, macrolides, and β-lactams occurring more frequently. Concentration and type of antibiotics varied among continents and reservoirs between data generated from sediment and water. Geographic location, seasonal variation, artificial impervious area around the reservoir, reservoir characteristics, and water quality also influenced reservoir antibiotic distributions. These factors enhanced the explanatory power of antibiotic distribution through linear or non-linear interactions. Cumulative risk for 44 antibiotics in reservoirs is low, but it is essential to further assess the environmental behavior and integrated risk of antibiotics from an interdisciplinary perspective and at the human-food chain-ecosystem interface, particularly antibiotic resistance under “One Health” framework.
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The data supporting results and related information extracted from papers are available from the Supplementary Data file and at Zenodo: https://doi.org/ 10.5281/zenodo.5565706.
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Acknowledgements
This study was funded by the Ministry of Science and Technology of China (MSTC) with the National Key Research and Development Program (2017YFE0119000) and the Alliance of International Science Organizations (ANSO) with the Key Collaborative Research Program (ANSO-CR-KP-2020-03). Special thanks to Prof. Andrew A. Meharg and the two anonymous reviewers for their constructive comments and suggestions on the improvement of this manuscript. The views expressed are those of the authors and do not necessarily reflect the views of MSTC and ANSO.
Funding
Ministry of Science and Technology of the People’s Republic of China,2017YFE0119000,Yaoyang Xu, Alliance of International Science Organizations, ANSO-CR-KP-2020-03,Yong Guan Zhu
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ZG: conceptualization, Methodology, Formal analysis, Writing & editing. WJB: Methodology, Formal analysis, Writing & editing. YX: conceptualization, Data curation, Visualization, Writing & editing, Supervision, Funding acquisition. EB: Analysis, and interpretation of data, Writing & editing. DL: analysis, Writing & editing. Y-GZ: writing, reviewing and editing.
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Guo, ZF., Boeing, W.J., Xu, YY. et al. A Systematic Workflow of Data Mining Confirms Widespread Occurrence of Antibiotic Contamination in Freshwater Reservoirs. Expo Health 15, 889–901 (2023). https://doi.org/10.1007/s12403-022-00529-6
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DOI: https://doi.org/10.1007/s12403-022-00529-6