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Preprints
https://doi.org/10.5194/acp-2019-951
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2019-951
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 31 Jan 2020

Submitted as: research article | 31 Jan 2020

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This preprint is currently under review for the journal ACP.

Source apportionment of PM2.5 in Shanghai based on hourly molecular organic markers and other source tracers

Rui Li1, Qiongqiong Wang2, Xiao He3, Shuhui Zhu3,4, Kun Zhang1, Yusen Duan5, Qingyan Fu5, Liping Qiao4, Yangjun Wang1, Ling Huang1, Li Li1,*, and Jian Zhen Yu2,3,* Rui Li et al.
  • 1School of Environmental and Chemical Engineering, Shanghai University, Shanghai, 200444, China
  • 2Department of Chemistry, Hong Kong University of Science and Technology, Hong Kong, China
  • 3Division of Environment and Sustainability, Hong Kong University of Science and Technology, Hong Kong, China
  • 4State Environmental Protection Key Laboratory of the Cause and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, 200233, China
  • 5Shanghai Environmental Monitoring Centre, Shanghai, 200235, China
  • *These authors contributed equally to this work.

Abstract. Identification of various sources and quantification of their contributions are a necessary step to formulating scientifically sound pollution control strategies. Receptor model is widely used in source apportionment of fine particles. However, most of the previous studies are based on traditional filter collection and lab analysis of aerosol chemical species (usually ions, elemental carbon (EC), organic carbon (OC) and elements) as inputs. In this study, we conducted robust online measurements of a range of organic molecular makers and trace elements, in addition to the major aerosol components (ions, OC and EC), in urban Shanghai in the Yangtze River Delta region, China. The large suite of molecular and elemental tracers, together with water-soluble ions, OC and EC, provide data for establishing measurement-based source apportionment methodology for PM2.5. We conducted source apportionment using positive matrix factorization (PMF) and compared PMF solutions with molecular makers added (i.e. MM-PMF) and those without organic markers. MM-PMF identified 11 types of pollution sources, with biomass burning, cooking and secondary organic aerosol (SOA) as the additional sources identified. The three sources accounted for 4.9 %, 2.6 % and 14.7 % of the total PM2.5 mass, respectively. During the whole campaign, the secondary source is an important source of atmospheric pollution, the average contribution of secondary pollution sources is as high as 63.8 % of the total PM2.5 mass. Grouping different sources to secondary and primary, we note that SOC and POC contributed 45.1 % and 54.9 %, respectively. It is worth noting that the contribution of cooking to PM2.5 mass only account for 2.6 %, but it contributed to 10.7 % of OC. Episodic analysis indicated that secondary nitrate was the always the main cause of PM2.5 pollution, while during non-episodic hours, vehicle exhaust made a significant contribution. Through the application of the above-mentioned techniques to the Yangtze River Delta, more insights are gained on the sources, formation mechanism and pollution characteristics of PM2.5 in this region.

Rui Li et al.

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