中国东南典型富水城市的抗生素污染:对饮用水资源安全的关注

Xinyan Guo, Lv Xiaojun, Ai-mei Zhang, Zheng Yan, Siyi Chen, Na Wang
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引用次数: 14

摘要

摘要采用改进的多靶点分析方法,对南京市水环境中7个治疗类49种抗生素的发生及分布进行了调查。结果表明,这些抗生素在该市水体中广泛存在,总浓度高达1.958 μg L−1。种类最多的是四环素类,占总抗生素负担的43.7%。所有样品均检出林可霉素,其中克林霉素检出率为90.5%。通过无监督模式识别(层次聚类分析,HCA)对数据点进行了探索性分析,试图澄清不同采样区域的污染水平,并根据不同的抗生素污染物概况对数据进行了强大的聚类解决方案分组。饮用水资源的安全受到重视,河流作为该市处理和未处理废水的主要接收水体,在我们的研究和类似的研究中,无论是浓度还是检测频率,都比周围的湖泊和水库受到更严重的污染。对抗生素的存在与环境因素进行相关性分析,发现抗生素污染与水质密切相关;水质越好,抗生素污染越低。抗生素与测试的重金属之间存在正相关,抗生素与硼和砷之间也存在正相关。然而,这些相关性是由于它们的反应还是共同的来源难以确定,其机制需要进一步探索。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Antibiotic contamination in a typical water-rich city in southeast China: a concern for drinking water resource safety
Abstract The occurrence and distribution in the aquatic environment of Nanjing of 49 antibiotics from seven therapeutic classes were investigated using an improved analytical method developed for multiclass target analysis. The results showed that these antibiotics are widely present in the water bodies of this city, with a total concentration of up to 1.958 μg L−1. The most abundant class was tetracyclines, contributing 43.7% to the total antibiotic burden. Lincomycin was detected in all samples, and the detection rate of clindamycin was 90.5%. An exploratory analysis of the data points was performed by unsupervised pattern recognition (hierarchical cluster analysis, HCA) in an attempt to clarify the pollution level in different sampling areas, and robust cluster solutions grouped the data according to their different antibiotic contaminant profiles. The safety of drinking water resources was emphasized, and the rivers, as the main receiving water body for treated and untreated wastewater in this city, were more seriously contaminated than the surrounding lakes and reservoir, not only in concentration but also in detection frequency, in our study as well as in similar research studies. A correlation analysis between the presence of antibiotics and the environmental factors was conducted, and it was found that antibiotic contamination and water quality were closely connected; the better the water quality, the lower the antibiotic contamination. Positive correlations existed between the antibiotics and tested heavy metals, as well as between antibiotics and boron and arsenic. However, whether these correlations resulted from their reaction or a common source was difficult to determine, and the mechanism requires further exploration.
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