Secondary organic aerosol (SOA) contributes a significant fraction to aerosol mass and toxicity.Low-volatility organic vapors are critical intermediates connecting the oxidation of volatile organic compounds (VOCs) to SOA formation. However, the direct measurement of intermediate vapors poses a great challenge, further compounded by the difficulty of linking them to specific precursors from a cocktail of complex emission sources in the vast urbanized areas. Here, we present coordinated measurements of low-volatility oxidation products, termed oxygenated organic molecules (OOMs) in three most urbanized regions in China. With a newly-developed analysis methodology, we are able to assign these OOMs to their likely precursors and ultimately connect SOA formation to various VOCs. At all measurement locations, we find similar OOM

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Abstract. Oxygenated organic molecules (OOMs) are crucial for atmospheric new particle formation and secondary organic aerosol (SOA) growth. Therefore, understanding their chemical composition, temporal behavior, and sources is of great importance. Previous studies on OOMs mainly focus on environments where biogenic sources are predominant, yet studies on sites with dominant anthropogenic emissions, such as megacities, have been lacking. Here, we conducted long-term measurements of OOMs, covering four seasons of the year 2019, in urban Beijing. The OOM concentration was found to be the highest in summer (1.6×108 cm−3), followed by autumn (7.9×107 cm−3), spring (5.7×107 cm−3) and winter (2.3×107 cm−3), suggesting that enhanced photo-oxidation together with the rise in temperature promote the formation of OOMs. Most OOMs contained 5 to 10 carbon atoms and 3 to 7 effective oxygen atoms (nOeff=nO-2×nN). The average nOeff increased with increasing atmospheric photo-oxidation capacity, which was the highest in summer and the lowest in winter and autumn. By performing a newly developed workflow, OOMs were classified into the following four types: aromatic OOMs, aliphatic OOMs, isoprene OOMs, and monoterpene OOMs. Among them, aromatic OOMs (29 %–41 %) and aliphatic OOMs (26 %–41 %) were the main contributors in all seasons, indicating that OOMs in Beijing were dominated by anthropogenic sources. The contribution of isoprene OOMs increased significantly in summer (33 %), which is much higher than those in the other three seasons (8 %–10 %). Concentrations of isoprene (0.2–5.3×107 cm−3) and monoterpene (1.1–8.4×106 cm−3) OOMs in Beijing were lower than those reported at other sites, and they possessed lower oxygen and higher nitrogen contents due to high NOx levels (9.5–38.3 ppbv – parts per billion by volume) in Beijing. With regard to the nitrogen content of the two anthropogenic OOMs, aromatic OOMs were mainly composed of CHO and CHON species, while aliphatic OOMs were dominated by CHON and CHON2 ones. Such prominent differences suggest varying formation pathways between these two OOMs. By combining the measurements and an aerosol dynamic model, we estimated that the SOA growth rate through OOM condensation could reach 0.64, 0.61, 0.41, and 0.30 µg m−3 h−1 in autumn, summer, spring, and winter, respectively. Despite the similar concentrations of aromatic and aliphatic OOMs, the former had lower volatilities and, therefore, showed higher contributions (46 %–62 %) to SOA than the latter (14 %–32 %). By contrast, monoterpene OOMs and isoprene OOMs, limited by low abundances or high volatilities, had low contributions of 8 %–12 % and 3 %–5 %, respectively. Overall, our results improve the understanding of the concentration, chemical composition, seasonal variation, and potential atmospheric impacts of OOMs, which can help formulate refined restriction policy specific to SOA control in urban areas.

Sulfur trioxide (SO 3 ) is a crucial compound for atmospheric sulfuric acid (H 2 SO 4 ) formation, acid rain formation, and other atmospheric physicochemical processes. During the daytime, SO 3 is mainly produced from the photo-oxidation of SO 2 by OH radicals. However, the sources of SO 3 during the early morning and night, when OH radicals are scarce, are not fully understood. We report results from two field measurements in urban Beijing during winter and summer 2019, using a nitrate-CI-APi-LTOF (chemical ionization-atmospheric pressure interface-long-time-offlight) mass spectrometer to detect atmospheric SO 3 and H 2 SO 4 . Our results show the level of SO 3 was higher during the winter than during the summer, with high SO 3 levels observed especially during the early morning (∼05:00 to ∼08:30) and night (∼18:00 to ∼05:00 the next day). On the basis of analysis of SO 2 , NO x , black carbon, traffic flow, and atmospheric ions, we suggest SO 3 could be formed from the catalytic oxidation of SO 2 on the surface of traffic-related black carbon. This previously unidentified SO 3 source results in significant H 2 SO 4 formation in the early morning and thus promotes sub-2.5 nm particle formation. These findings will help in understanding urban SO 3 and formulating policies to mitigate secondary particle formation in Chinese megacities.

Abstract. Although secondary particulate matter is reported to be the main contributor of PM2.5 during haze in Chinese megacities, primary particle emissions also affect particle concentrations. In order to improve estimates of the contribution of primary sources to the particle number and mass concentrations, we performed source apportionment analyses using both chemical fingerprints and particle size distributions measured at the same site in urban Beijing from April to July 2018. Both methods resolved factors related to primary emissions, including vehicular emissions and cooking emissions, which together make up 76 % and 24 % of total particle number and organic aerosol (OA) mass, respectively. Similar source types, including particles related to vehicular emissions (1.6±1.1 µg m−3; 2.4±1.8×103 cm−3 and 5.5±2.8×103 cm−3 for two traffic-related components), cooking emissions (2.6±1.9 µg m−3 and 5.5±3.3×103 cm−3) and secondary aerosols (51±41 µg m−3 and 4.2±3.0×103 cm−3), were resolved by both methods. Converted mass concentrations from particle size distributions components were comparable with those from chemical fingerprints. Size distribution source apportionment separated vehicular emissions into a component with a mode diameter of 20 nm (“traffic-ultrafine”) and a component with a mode diameter of 100 nm (“traffic-fine”). Consistent with similar day- and nighttime diesel vehicle PM2.5 emissions estimated for the Beijing area, traffic-fine particles, hydrocarbon-like OA (HOA, traffic-related factor resulting from source apportionment using chemical fingerprints) and black carbon (BC) showed similar diurnal patterns, with higher concentrations during the night and morning than during the afternoon when the boundary layer is higher. Traffic-ultrafine particles showed the highest concentrations during the rush-hour period, suggesting a prominent role of local gasoline vehicle emissions. In the absence of new particle formation, our results show that vehicular-related emissions (14 % and 30 % for ultrafine and fine particles, respectively) and cooking-activity-related emissions (32 %) dominate the particle number concentration, while secondary particulate matter (over 80 %) governs PM2.5 mass during the non-heating season in Beijing.