Source-specific risk apportionment and critical risk source identification of antibiotic resistance in Fenhe River basin, China

中游 抗生素耐药性 风险分析(工程) 环境科学 废水 流域 抗生素 抗性(生态学) 兽医学
作者
Yifan Wang,Linfang Wang,Ruimin Liu,Lin Li,Leiping Cao,Lijun Jiao,Xinghui Xia
出处
期刊:Chemosphere [Elsevier]
卷期号:287: 131997-131997
标识
DOI:10.1016/j.chemosphere.2021.131997
摘要

A comprehensive understanding of the sources and distribution of antibiotic resistance risk is essential for controlling antibiotic pollution and resistance. Based on surface water samples collected from the Fenhe River basin in the flood season, using the positive matrix factorization (PMF) model, the risk quotient (RQ) method and the multiple attribute decision making (MADM) method, the resistance risk and source-specific resistance risk of antibiotics were analyzed in this study. The results showed that sulfonamides (SAs) were the dominant antibiotics with a mean concentration of 118.30 ng/L, whereas tetracyclines (TCs) and macrolides (MLs) had the highest detection frequencies (100%). The significant resistance risk rate of antibiotics in the entire river basin was 48%, but no high risk occurred. The significant resistance risk rate of quinolones (QNs) was the highest (100%), followed by that of MLs and TCs. Owing to human activities, the most serious resistance risk occurred in the midstream of the river basin. The resistance risk was the lowest upstream. The antibiotics were mainly contributed by six sources. Pharmaceutical wastewater was the main source, accounting for 30%, followed by livestock discharge (22%). The resistance risk from the six sources showed clear differences, but none of the sources caused a high risk of antibiotic resistance. Pharmaceutical wastewater poses the greatest risk of antibiotic resistance in the Fenhe River basin and is widely distributed. The second greatest source was livestock discharge, which was mainly concentrated in the upstream and midstream areas. The critical sources upstream, midstream, and downstream were all pharmaceutical wastewater, whereas the sequences of other sources were different because different areas were affected by different human activities. The proposed method might provide an important reference for the identification the key source of antibiotics and management of antibiotic pollution, as well as help for the management of antibiotics in Fenhe and Shanxi Province. • ARR and source-specific ARR were analyzed based on RQ method and PMF model. • Affected by human activities, ARR was mainly distributed in midstream. • Six sources were identified, the contributions varied with sources and locations. • Pharmaceutical wastewater was critical sources, livestock discharge was the second.

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