应用自动识别与定量分析数据库筛查黄河和长江水中有机污染物

采用气质联用分析,并应用自动识别与定量分析数据库(AIQS-DB)对黄河下游和长江下游水样中近1000种有机污染物进行了筛查.结果表明,黄河下游山东段和长江下游江苏段水样分别检出95种和121种化合物,主要包括正构烷烃、多环芳烃、酚类、硝基化合物、酞酸酯类、农药和药物等.其中,黄河和长江水样中正构烷烃平均浓度分别为1806ng/L和720ng/L;16种优控PAHs平均浓度分别为27ng/L和30ng/L;6种优控PAEs的平均浓度分别为77ng/L和2166ng/L;黄河和长江水样分别检出9种和17种农药.黄河各采样点间污染物浓度差别较大,而长江采样点间浓度相差较小.研究表明,气质联用结合AIQS-DB可有效用于区域性污染物的筛查.

Application of Automated Identification and Quantification System with a Database (AIQS-DB) to Screen Organic Pollutants in Surface Waters from Yellow River and Yangtze River

Approximately 1000 chemicals were screened in surface waters from downstreams of Yellow River and Yangtze River using GC-MS coupled with Automated Identification and Quantification System with a Database (AIQS-DB). 95 pollutants were detected in water samples from Yellow River in Shandong Province and 121 in those from Yangtze River in Jiangsu Province. The pollutants involved n-alkanes, PAHs, phenols, nitro compounds, phthalates esters (PAEs), pesticides and pharmaceuticals, etc. The average concentrations of n-alkanes, 16 priority PAHs and 6 priority PAEs were 1806 ng/L, 27 ng/L, 77 ng/L in water samples from Yellow River and 720 ng/L, 30 ng/L, 2166 ng/L in water samples from Yangtze River respectively. Besides, 9 and 11 pesticides were detected in water samples from Yellow River and Yangtze River respectively. The levels of pollutants showed stronger site dependence in samples from Yellow River than those from Yangtze River. Combination of GC-MS and AIQS-DB shows high efficiency in regional pollutants survey.