华东师范大学学报（自然科学版） ›› 2024, Vol. 2024 ›› Issue (6): 52-61.doi: 10.3969/j.issn.1000-5641.2024.06.005

• 研究方法技术与进展 • 上一篇    下一篇

基于全二维气相色谱−飞行时间质谱技术对上海农田土壤中有机污染物的高通量筛查

杨静1(), 邬言1, 李月2, 刘欣然1, 杨丁业1, 金芮合1, 丁方方1, 李晔1, 刘敏1,*()   

  1. 1. 华东师范大学 地理科学学院 地理信息科学教育部重点实验室, 上海　200241
    2. 华东师范大学 河口海岸学国家重点实验室, 上海　200241
  • 收稿日期:2024-07-30 接受日期:2024-09-05 出版日期:2024-11-25 发布日期:2024-11-29
  • 通讯作者: 刘敏 E-mail:jyang@geo.ecnu.edu.cn;mliu@geo.ecnu.edu.cn
  • 作者简介:杨　静, 女, 工程师, 研究方向为新污染物环境行为及风险评估. E-mail: jyang@geo.ecnu.edu.cn
  • 基金资助:
    国家自然科学基金 (42230505, 41730646)

High-throughput screening of organic contaminants in farmland soils in Shanghai by comprehensive two-dimensional gas chromatography-time of flight mass spectrometry

Jing YANG1(), Yan WU1, Yue LI2, Xinran LIU1, Dingye YANG1, Ruihe JIN1, Fangfang DING1, Ye LI1, Min LIU1,*()   

  1. 1. Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai　200241, China
    2. State Key Laboratory for Estuarine and Coastal Research, East China Normal University, Shanghai　200241, China
  • Received:2024-07-30 Accepted:2024-09-05 Online:2024-11-25 Published:2024-11-29
  • Contact: Min LIU E-mail:jyang@geo.ecnu.edu.cn;mliu@geo.ecnu.edu.cn

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摘要：

为探究路边农田土壤中未知有机物赋存情况, 利用全二维气相色谱−飞行时间质谱技术对上海不同道路等级路边农田土壤(n = 8)中的有机物进行了非靶向定性筛查. 通过空白过滤和谱库匹配(相似度大于700), 在所有样品中均检出了1000多个质谱峰, 其中, 与谱库保留指数偏差在 ±2%以内的物质数有275 ~ 341种. 所有采样点共同检出的有机物有66种, 信噪比较高的前10种物质主要是多环芳烃类、邻苯二甲酸酯类、苯酚类、噻吩类和四氯乙烷类. 费雪比值(Fisher ratio, FR)法分析揭示出具有明显道路等级差异的化合物有29种(FR为22.6 ~ 60.3), 而这些化合物主要来自化工产品、生物医药和个人护理品等产品, 推断其差异主要受控于邻近区域工业活动、污水灌溉和居民生活源排放的影响. 元素组成分析表明, 在所有采样点中有机物组成主要以CHO和CH为主, 峰面积占比分别为39.9% ~ 59.1%和30.2% ~ 45.8%. 对人为源有机物进一步地分类分析, 发现烷烃、多环芳烃和邻苯二甲酸酯类是上海路边农田土壤中含量较高的3类污染物, 表明汽油柴油燃烧、轮胎磨损、润滑油挥发泄漏等交通源排放对路边农田土质的影响不容忽视. 总的来说, 全二维技术能够准确地定性筛查出农田土壤中大量未关注的有机污染物, 为今后污染管控和治理提供了科学依据.

关键词: 全二维气相色谱?飞行时间质谱, 非靶向筛查, 有机污染物, 农田土壤

Abstract:

This study utilized comprehensive two-dimensional gas chromatography-time of flight mass spectrometry (GC×GC-TOFMS) to perform a non-targeted qualitative analysis of organic compounds in farmland soils (n = 8) near roads of varying grades in Shanghai. After applying blank filtering and spectral library matching with a similarity threshold in excess of 700, more than 1000 mass spectrum peaks were identified across all samples, with 275 ~ 341 compounds exhibiting an retention index (RI) deviation within ±2% of the library values. Sixty-six organic compounds were found consistently at each sampling location, with the most prevalent being polycyclic aromatic hydrocarbons, phthalates, phenols, thiophenes, and tetrachloroethanes, all of which had notably high signal-to-noise ratios. Fisher ratio (FR) analysis identified 29 compounds with marked differences across road grades, with FR values ranging from 22.6 to 60.3, which were derived primarily from chemical products, biomedicine, and personal care items. These discrepancies were likely attributable to local industrial activities, sewage irrigation practices, and residential emissions. Elemental composition analysis indicated that CHO and CH were the predominant constituents of the detected organic compounds, representing 39.9% ~ 59.1% and 30.2% ~ 45.8% of the total peak area, respectively. Additional classification of anthropogenic contaminants highlighted alkanes, polycyclic aromatic hydrocarbons, and phthalates as the primary pollutants in high concentrations within the roadside farmland soils of Shanghai. This indicated that impacts on roadside farmland soil quality from emissions from traffic sources, such as gasoline and diesel combustion, tire wear, and lubricant evaporation and leakage, cannot be ignored. In summary, the application of comprehensive two-dimensional technology enabled precise qualitative screening of numerous previously overlooked organic contaminants in farmland soils, offering a scientific foundation for future environmental management strategies.

Key words: comprehensive two-dimensional gas chromatography-time of flight mass spectrometry (GC × GC-TOFMS), non-targeted screening, organic contaminant, farmland soil

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