COBRA: A Computational Brewing Application for Predicting the Molecular Composition of Organic Aerosols

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• 作者：David R. Fooshee ; Tran B. Nguyen ; Sergey A. Nizkorodov ; Julia Laskin ; Alexander Laskin ; Pierre Baldi
• 刊名：Environmental Science & Technology (ES&T)
• 出版年：2012
• 出版时间：June 5, 2012
• 年：2012
• 卷：46
• 期：11
• 页码：6048-6055
• 全文大小：355K
• 年卷期：v.46,no.11(June 5, 2012)
• ISSN：1520-5851

文摘

Atmospheric organic aerosols (OA) represent a significant fraction of airborne particulate matter and can impact climate, visibility, and human health. These mixtures are difficult to characterize experimentally due to their complex and dynamic chemical composition. We introduce a novel Computational Brewing Application (COBRA) and apply it to modeling oligomerization chemistry stemming from condensation and addition reactions in OA formed by photooxidation of isoprene. COBRA uses two lists as input: a list of chemical structures comprising the molecular starting pool and a list of rules defining potential reactions between molecules. Reactions are performed iteratively, with products of all previous iterations serving as reactants for the next. The simulation generated thousands of structures in the mass range of 120鈥?00 Da and correctly predicted 70% of the individual OA constituents observed by high-resolution mass spectrometry. Select predicted structures were confirmed with tandem mass spectrometry. Esterification was shown to play the most significant role in oligomer formation, with hemiacetal formation less important, and aldol condensation insignificant. COBRA is not limited to atmospheric aerosol chemistry; it should be applicable to the prediction of reaction products in other complex mixtures for which reasonable reaction mechanisms and seed molecules can be supplied by experimental or theoretical methods.