通过染色学与高分辨率质谱学相结合的化的量化 - - 部分A:气体染色学和电离源参数的影响
Cherine Amoura1, Frédéric Larvor1, Philippe Marchand1
1Oniris, INRAE, LABERCA, F-44300, Nantes, France.
优化气体染色学 (GC) 和电子捕获负电离高分辨率质谱学 (ECNI-HRMS) 参数,改善了对多化n- (PCAs) 的分析,多化 (CPs) 的主要成分. 这有助于加强环境监测和暴露评估.
科学领域:
- 环境化学环境化学
- 分析化学 分析化学
- 质谱测量质量谱测量
背景情况:
- 甲 (CPs) 分析存在重大挑战.
- 多化n- (PCA) 是CP的主要成分.
- 对于GC和ECNI参数对PCA分析的影响尚不清楚.
研究的目的:
- 调查GC柱特征,烤箱,进口和源温度对PCA分析的影响.
- 优化PCA与链条长度从10到20个碳素 (PCAs-C10-20) 的同时分析的条件.
- 检查参数对绝对响应和PCA同类组模式的影响.
主要方法:
- 气色谱与电子捕获负电离高分辨率质谱学 (GC-ECNI-HRMS) 相结合.
- GC柱属性的系统变化 (类型,长度,薄膜厚度).
- 优化烤箱,GC入口和离子源温度.
主要成果:
- 确定了GC入口 (220-240°C),最终梯度 (340°C) 和离子源 (200°C) 温度的最佳条件.
- 优选5HT列 (12.5米,0.25微米) 的反应比优选1列的反应更高.
- 同类组模式受到源/入口温度,薄膜厚度和静止相组成的显著影响.
结论:
- 推的GC-ECNI-HRMS条件改善了PCA模式的表征.
- 增强分析有助于更好地了解PCA在环境监测中的发生情况.
- 这项研究为改善CP的暴露评估提供了基础.
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