Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 5.668 IF 5.668
  • IF 5-year value: 6.201 IF 5-year
    6.201
  • CiteScore value: 6.13 CiteScore
    6.13
  • SNIP value: 1.633 SNIP 1.633
  • IPP value: 5.91 IPP 5.91
  • SJR value: 2.938 SJR 2.938
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 174 Scimago H
    index 174
  • h5-index value: 87 h5-index 87
Preprints
https://doi.org/10.5194/acp-2020-248
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2020-248
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 12 May 2020

Submitted as: research article | 12 May 2020

Review status
This preprint is currently under review for the journal ACP.

Size segregated particle number and mass emissions in urban Beijing

Jing Cai1,2, Biwu Chu1,2,3,4, Lei Yao2, Chao Yan1,2, Liine M. Heikkinen1,2, Feixue Zheng1, Chang Li1, Xiaolong Fan1, Shaojun Zhang5, Daoyuan Yang5, Yonghong Wang2, Tom V. Kokkonen1,2, Tommy Chan1,2, Ying Zhou1, Lubna Dada1,2, Yongchun Liu1, Hong He3,4, Pauli Paasonen1,2, Joni T. Kujansuu1,2, Tuukka Petäjä1,2, Claudia Mohr6, Juha Kangasluoma1,2, Federico Bianchi1,2, Yele Sun7, Philip L. Croteau8, Douglas R. Worsnop2,8, Veli-Matti Kerminen1,2, Wei Du1,2, Markku Kulmala1,2, and Kaspar R. Daellenbach1,2 Jing Cai et al.
  • 1Aerosol and Haze Laboratory, Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing,100029, China
  • 2Institute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, Helsinki, 00014, Finland
  • 3Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China
  • 4State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
  • 5School of Environment, Tsinghua University, Beijing,100084, China
  • 6Department of Environmental Science, Stockholm University, Stockholm, 11418, Sweden
  • 7State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing,100029, China
  • 8Aerodyne Research, Inc., Billerica, MA,01821, USA

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 night-time diesel vehicle PM2.5 emissions estimated for the Beijing area, Traffic-fine, 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 (14 % and 30 % for ultrafine and fine particles, respectively) and cooking (32 %) emissions dominate the particle number concentration while secondary particulate matter (over 80 %) governs PM2.5 mass during the non-heating season in Beijing.

Jing Cai et al.

Interactive discussion

Status: open (until 07 Jul 2020)
Status: open (until 07 Jul 2020)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement

Jing Cai et al.

Metrics will be available soon.
Latest update: 24 May 2020
Publications Copernicus
Download
Short summary
By applying both OA-PMF and Size-PMF at the same urban measurement site in Beijing, similar particle source-types, including vehicular emissions, cooking emissions and secondary formation-related sources were resolved by both frameworks and agreed well. It is also found that in the absence of new-particle formation, vehicular and cooking emissions dominate the particle number concentration while secondary particulate matter governed PM2.5 mass during spring and summer in Beijing.
By applying both OA-PMF and Size-PMF at the same urban measurement site in Beijing, similar...
Citation