Yun Zhang1, Kai Wang2, Haijie Tong3, Ru-Jin Huang4, Thorsten Hoffmann1. 1. Department of Chemistry, Johannes Gutenberg University, Mainz, 55128, Germany. 2. Key Laboratory of Plant-Soil Interactions of MOE, College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, China Agricultural University, Beijing, 100193, China. 3. Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China. 4. State Key Laboratory of Loess and Quaternary Geology, Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China.
Abstract
RATIONALE: Organic aerosols (OA) account for a large fraction of atmospheric fine particulate matter and thus are affecting climate and public health. Elucidation of the chemical composition of OA is the key for addressing the role of ambient fine particles at the atmosphere-biosphere interface and mass spectrometry is the main method to achieve this goal. METHODS: High-resolution mass spectrometry (HRMS) is on its way to becoming one of the most prominent analytical techniques, also for the analysis of atmospheric aerosols. The combination of high mass resolution and accurate mass determination allows the elemental compositions of numerous compounds to be easily elucidated. Here a new parameter for the improved classification of OA is introduced - the maximum carbonyl ratio (MCR) - which is directly derived from the molecular composition and is particularly suitable for the identification and characterization of secondary organic aerosols (SOA). RESULTS: The concept is exemplified by the analysis of ambient OA samples from two measurement sites (Hyytiälä, Finland; Beijing, China) and of laboratory-generated SOA based on ultrahigh-performance liquid chromatography (UHPLC) coupled to Orbitrap MS. To interpret the results, MCR-Van Krevelen (VK) diagrams are generated for the different OA samples and the individual compounds are categorized into specific areas in the diagrams. The results show that the MCR index is a valuable parameter for representing atmospheric SOA components in composition and structure-dependent visualization tools such as VK diagrams. CONCLUSIONS: The MCR index is suggested as a tool for a better characterization of the sources and the processing of atmospheric OA components based on HRMS data. Since the MCR contains information on the concentration of highly electrophilic organic compounds in particulate matter (PM) as well as on the concentration of organic (hydro)peroxides, the MCR could be a promising metric for identifying health-related particulate matter parameters by HRMS.
RATIONALE: Organic aerosols (OA) account for a large fraction of atmospheric fine particulate matter and thus are affecting climate and public health. Elucidation of the chemical composition of OA is the key for addressing the role of ambient fine particles at the atmosphere-biosphere interface and mass spectrometry is the main method to achieve this goal. METHODS: High-resolution mass spectrometry (HRMS) is on its way to becoming one of the most prominent analytical techniques, also for the analysis of atmospheric aerosols. The combination of high mass resolution and accurate mass determination allows the elemental compositions of numerous compounds to be easily elucidated. Here a new parameter for the improved classification of OA is introduced - the maximum carbonyl ratio (MCR) - which is directly derived from the molecular composition and is particularly suitable for the identification and characterization of secondary organic aerosols (SOA). RESULTS: The concept is exemplified by the analysis of ambient OA samples from two measurement sites (Hyytiälä, Finland; Beijing, China) and of laboratory-generated SOA based on ultrahigh-performance liquid chromatography (UHPLC) coupled to Orbitrap MS. To interpret the results, MCR-Van Krevelen (VK) diagrams are generated for the different OA samples and the individual compounds are categorized into specific areas in the diagrams. The results show that the MCR index is a valuable parameter for representing atmospheric SOA components in composition and structure-dependent visualization tools such as VK diagrams. CONCLUSIONS: The MCR index is suggested as a tool for a better characterization of the sources and the processing of atmospheric OA components based on HRMS data. Since the MCR contains information on the concentration of highly electrophilic organic compounds in particulate matter (PM) as well as on the concentration of organic (hydro)peroxides, the MCR could be a promising metric for identifying health-related particulate matter parameters by HRMS.