抗生素
水生生态系统
环境科学
抗生素耐药性
流域
诺氟沙星
环境卫生
生态学
生物
医学
地理
环丙沙星
微生物学
地图学
作者
Haiyang Chen,Lijun Jing,Yanguo Teng,Jinsheng Wang
标识
DOI:10.1016/j.scitotenv.2017.11.054
摘要
Antibiotics and antibiotic resistance genes in the river system have received growing attention in recent years due to their potential threat to aquatic ecosystems and public health. Recognizing the occurrence and distribution of antibiotics in river environment and assessing their ecological risks are of important precondition for proposing effective strategies to protect basin safety. In this study, a comprehensive investigation was conducted to identify the contamination and risk characteristics of antibiotics in the aquatic environment of Hai River system (HRS) which is the largest water system in northern China. To attain this objective, several tools and methods were considered on the data set of water and sediment samples collected in the past ten years. The occurrence pattern, concentration levels and spatiotemporal distribution of antibiotics in the HRS were characterized utilizing statistical and comparative analysis. Risk quotients were employed to assess the adverse ecology effects caused by single antibiotic or their mixtures. Screening tool with priority factor and accumulation growth factor was used auxiliarily to prioritize antibiotics that should be of highly concern. Results indicated that the occurrence frequencies and concentration levels of 16 representative antibiotics in HRS were generally higher than those reported in global waters. Most antibiotics showed significant seasonal and spatial variations. Comparatively speaking, sulfamethoxazole, norfloxacin, erythromycin and roxithromycin posed higher risks to aquatic organisms in the HRS individually, and the combination of tetracycline and enrofloxacin indicated synergistical actions. Overall, due to their potential risks, considerable levels or quick increasing trends, 13 antibiotics were identified as priority contaminants in the HRS and should be paid special attention to be strictly regulated in the future.
科研通智能强力驱动
Strongly Powered by AbleSci AI