Li Jia, Zhang Haibo, Chen Yongshan, Luo Yongming, Zhang Hua
Key Laboratory of Coastal Environmental Process and Ecology Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai, 264003, China.
University of Chinese Academy of Sciences, Beijing, China.
Environ Monit Assess. 2016 Jul;188(7):430. doi: 10.1007/s10661-016-5439-4. Epub 2016 Jun 23.
To quantify the extent of antibiotic contamination and to identity the dominant pollutant sources in the Tiaoxi River Watershed, surface water samples were collected at eight locations and analyzed for four tetracyclines and three sulfonamides using ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS). The observed maximum concentrations of tetracycline (623 ng L(-1)), oxytetracycline (19,810 ng L(-1)), and sulfamethoxazole (112 ng L(-1)) exceeded their corresponding Predicted No Effect Concentration (PNEC) values. In particular, high concentrations of antibiotics were observed in wet summer with heavy rainfall. The maximum concentrations of antibiotics appeared in the vicinity of intensive aquaculture areas. High-resolution land use data were used for identifying diffuse source of antibiotic pollution in the watershed. Significant correlations between tetracycline and developed (r = 0.93), tetracycline and barren (r = 0.87), oxytetracycline and barren (r = 0.82), and sulfadiazine and agricultural facilities (r = 0.71) were observed. In addition, the density of aquaculture significantly correlated with doxycycline (r = 0.74) and oxytetracycline (r = 0.76), while the density of livestock significantly correlated with sulfadiazine (r = 0.71). Principle Component Analysis (PCA) indicated that doxycycline, tetracycline, oxytetracycline, and sulfamethoxazole were from aquaculture and domestic sources, whereas sulfadiazine and sulfamethazine were from livestock wastewater. Flood or drainage from aquaculture ponds was identified as a major source of antibiotics in the Tiaoxi watershed. A hot-spot map was created based on results of land use analysis and multi-variable statistics, which provided an effective management tool of sources identification in watersheds with multiple diffuse sources of antibiotic pollution.
为了量化抗生素污染程度并确定苕溪流域的主要污染源,在八个地点采集了地表水样本,并使用超高效液相色谱串联质谱法(UPLC-MS/MS)分析了四种四环素类和三种磺胺类药物。观察到的四环素(623 ng L⁻¹)、土霉素(19810 ng L⁻¹)和磺胺甲恶唑(112 ng L⁻¹)的最大浓度超过了它们相应的预测无效应浓度(PNEC)值。特别是在夏季多雨的潮湿季节观察到高浓度的抗生素。抗生素的最大浓度出现在集约化养殖区附近。利用高分辨率土地利用数据来识别流域内抗生素污染的分散源。观察到四环素与建设用地(r = 0.93)、四环素与裸地(r = 0.87)、土霉素与裸地(r = 0.82)以及磺胺嘧啶与农业设施(r = 0.71)之间存在显著相关性。此外,养殖密度与强力霉素(r = 0.74)和土霉素(r = 0.76)显著相关,而牲畜密度与磺胺嘧啶(r = 0.71)显著相关。主成分分析(PCA)表明,强力霉素、四环素、土霉素和磺胺甲恶唑来自养殖和生活源,而磺胺嘧啶和磺胺二甲嘧啶来自牲畜废水。养殖池塘的洪水或排水被确定为苕溪流域抗生素的主要来源。基于土地利用分析和多变量统计结果创建了热点地图,为具有多种抗生素污染分散源的流域提供了一种有效的污染源识别管理工具。