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Aerosol mass spectrometry has proved to be a powerful tool to measuresubmicron particulate composition with high time resolution. Factor analysisof mass spectra (MS) collected worldwide by aerosol mass spectrometer (AMS)demonstrates that submicron organic aerosol (OA) is usually composed ofseveral major components, such as oxygenated (OOA), hydrocarbon-like (HOA),biomass burning (BBOA), and other primary OA. In order to helpinterpretation of component MS from factor analysis of ambient OA datasets,AMS measurements of different primary sources is required for comparison.Such work, however, has been very scarce in the literature, especially forhigh resolution MS (HR-MS) measurements, which performs improvedcharacterization by separating the ions of different elemental compositionat each m/z in comparison with unit mass resolution MS (UMR-MS)measurements. In this study, primary emissions from four types of Chinesecooking (CC) and six types of biomass burning (BB) were simulatedsystematically and measured using an Aerodyne High-Resolution Time-of-FlightAMS (HR-ToF-AMS). The MS of the CC emissions show high similarity, with m/z41 and m/z 55 being the highest signals; the MS of the BB emissions alsoshow high similarity, with m/z 29 and m/z 43 being the highest signals. TheMS difference between the CC and BB emissions is much bigger than thatbetween different CC (or BB) types, especially for the HR-MS. The O/C ratioof OA ranges from 0.08 to 0.13 for the CC emissions and from 0.18 to 0.26for the BB emissions. The UMR ions of m/z 43, m/z 44, m/z 57, and m/z 60,usually used as tracers in AMS measurements, were examined for their HR-MScharacteristics in the CC and BB emissions. In addition, the MS of the CCand BB emissions are also compared with component MS from factor analysis ofambient OA datasets observed in China, as well as with other AMSmeasurements of primary sources in the literature. The MS signatures ofcooking and biomass burning emissions revealed in this study can be used asimportant reference for factor analysis of ambient OA datasets, especiallyfor the relevant studies in East Asia

Characterization of high-resolution aerosol mass spectra of primary organic aerosol emissions from Chinese cooking and biomass burning