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龙山环境论坛(第61期):特邀加州大学尔湾分校覃意茗博士来我校作学术报告
2022年11月14日    作者:     发布 : 李梦轩    

 

报告题目:Toward a molecular understanding of the surface composition of atmospherically relevant organic particle

报告人:覃意茗 博士

报告时间:20221116上午1200

腾讯会议728-123-031

主持人: 汪俊峰 博士

专家简介:博士毕业于哈佛大学,现任加州大学尔湾分校博士后研究员。先后发表SCI论文20篇,其中以第一作者发表8包括PNASEST及多篇ACP

 

Abstract:

Airborne particles play an important role in human health, air quality, and global climate. Historically, aerosol particles were considered to be uniform in composition. It has recently been discovered that many aerosol particles can be highly viscous and therefore have very long mixing times, potentially causing chemical inhomogeneities. Less viscous particles may experience liquid - liquid phase separation, also making them inhomogeneous. While the surface makes up a small fraction of the particle mass, incoming gases interact at this interface first. Thus, the surface can determine how particles take up vapors to grow to the size that scatters light, take up water vapor leading to cloud condensation nuclei, and interact with biological systems up on inhalation.

Many mass spectrometry methods using various ionization sources provide the bulk composition of airborne particles, but little is known about what molecules are on the particle surface. Our recent work shows that the composition of surface layers of atmospherically relevant sub-micron organic particles can be probed without the use of an external ionization source. Solid dicarboxylic acid particles are used as models, with glutaric acid being the most efficient at generating ions. Coating with small diacids or products from a - pinene ozonolysis demonstrates that ions are ejected from the surface, providing a surface molecular characterization of organic particles on-the-fly. This unique approach provides a path forward for elucidating the role of the surface in determining the chemical and physical properties of particles, including heterogeneous reactions, particle growth, water uptake, and interactions with biological system.

 

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20221114


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