大气细颗粒PM2.5中非目标未知有机污染物的全二维气相色谱-飞行时间质谱的甄别

Particles smaller than 2.5μm (PM2.5) in the air, have potentially significant health effects, so changes in concentration profiles of these compound in the the atmosphere are of particular interest. The fully analysis of the all kinds of organic compounds by one-dimensional gas chromatography is a difficult task beacause the the complexity of the mixtures coeluting with many compounds of interest. The methodology for the analysis of some target compounds such as polycyclic aromatic hydrocarbons, polychlorinated biphenyls, polychlorinated naphthalenes, polychlorinated dibenzo-p-dioxins and dibenzofurans, polybrominated diphenyl ethers were developed. However, there is no anlytical method for the thousands of organic compounds in the PM2.5. Analysis of organic compounds in PM2.5 by comprehensive two-dimensional gas chromatography (GC×GC) coupled to time-of-flight mass spectrometry will be established in this program. GC×GC parameters including selection of the first and second columns, temperature programs, carrier gas flow rate and modulation period etc will be optimized. More than 10000 organic compounds will be seperated and detected by comprehensive two-dimensional gas chromatography (GC×GC) coupled to time-of-flight mass spectrometry. Then the mass defect technology will be used to qualitative the no target organic compounds. And then some kinds of the organic compounds will be quantified. The results of this study will be very useful for the further research of potential health effects of these compounds.

近年来随着工业的快速发展，大气污染加剧，大气中细颗粒物尤其是PM2.5的污染引起广泛关注。目前，由于分离分析方法等限制，对大气中有机物的报道多集中于多环芳烃和少数烷烃类，也有少数利用HRGC-HRMS分离分析PCBs，PCDD/Fs和PBDEs等，但针对PM2.5中复杂的有机物组分仍不清楚。本课题拟利用全二维气相色谱-飞行时间质谱的甄别剧大气中细颗粒物PM2.5中的有机污染物组分。通过对全二维气相色谱的进样口温度，色谱柱组合、升温程序、调制器等进行优化，达到对PM2.5中上万种有机化合物的分离，与一维色谱相比大大提高分离效率。然后利用飞行时间质谱Mass-defect技术，对大气细颗粒物中的有机污染物进行分离及定性分析，并在此基础上对部分化合物进行定量分析，以此全面了解细颗粒中有机污染物的种类及分布水平，为污染控制及生态风险评估提供依据。

在本项目执行3年过程中，按计划进展顺利，采集了北京地区不同粒径的大气颗粒物，包括上百个大气PM2.5样品，以此为研究对象，开展了有机污染物的分析。通过优化全二维气相色谱的条件，包括色谱柱的组合优化，调制周期的优化，使用新型的第二根极性色谱短柱，实现了上万种有机物的分离。利用全二维气相色谱高分辨质谱结合傅里叶变换质谱对大气中有机污染进行分类，包括烷烃、烯烃、醇、醛、酮、酸、酯、吡啶、喹啉、及一至五环多环芳烃类等。利用KMD技术，结合谱库检索等技术，发现了痕量未知的有机污染物，并对部分有机物进行了定量分析，了解了其在大气颗粒物中的浓度水平、分布组成情况，为进一步的研究提供了技术支持及积累数据。通过本研究，可以提高对大气PM2.5中有机污染物的全组分污染现状的认识，为大气污染控制和人类健康风险防范提供参考。