Size-segregated particle number and mass concentrations from different emission sources in urban Beijing

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 mu gm(-3); 2.4 +/- 1.8 x 10(3) cm(-3) and 5.5 +/- 2.8 x 10(3) cm(-3) for two traffic-related components), cooking emissions (2.6 +/- 1.9 mu gm(-3) and 5.5 +/- 3.3 x 10(3) cm(-3)) and secondary aerosols (51 +/- 41 mu gm(-3) and 4.2 +/- 3.0 x 10(3) 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 re-sults 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.Peer reviewe

Unprecedented Ambient Sulfur Trioxide (SO3) Detection : Possible Formation Mechanism and Atmospheric Implications

Sulfur trioxide (SO3) is a crucial compound for atmospheric sulfuric acid (H2SO4) formation, acid rain formation, and other atmospheric physicochemical processes. During the daytime, SO3 is mainly produced from the photo-oxidation of SO2 by OH radicals. However, the sources of SO3 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 SO3 and H2SO4. Our results show the level of SO3 was higher during the winter than during the summer, with high SO3 levels observed especially during the early morning (similar to 05:00 to similar to 08:30) and night (similar to 18:00 to similar to 05:00 the next day). On the basis of analysis of SO2, NOx, black carbon, traffic flow, and atmospheric ions, we suggest SO3 could be formed from the catalytic oxidation of SO2 on the surface of traffic-related black carbon. This previously unidentified SO3 source results in significant H2SO4 formation in the early morning and thus promotes sub-2.5 nm particle formation. These findings will help in understanding urban SO3 and formulating policies to mitigate secondary particle formation in Chinese megacities.Peer reviewe

Climatic responses of tree-ring widths of Larix gmelinii on contrasting north-facing and south-facing slopes in central Siberia

The original publication is available at www.springerlink.com.ArticleJournal of Wood Science. 53(2): 87-93 (2007)journal articl