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Characterization and Spatial Source Apportionments of Ambient PM10 and PM2.5 during the Heating Period in Tian’jin, China

Category: Aerosol and Atmospheric Chemistry

Volume: 20 | Issue: 1 | Pages: 1-13
DOI: 10.4209/aaqr.2019.06.0281
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To cite this article:
Liu, B., Sun, X., Zhang, J., Bi, X., Li, Y., Li, L., Dong, H., Xiao, Z., Zhang, Y. and Feng, Y. (2020). Characterization and Spatial Source Apportionments of Ambient PM10 and PM2.5 during the Heating Period in Tian’jin, China. Aerosol Air Qual. Res. 20: 1-13. doi: 10.4209/aaqr.2019.06.0281.

Baoshuang Liu1, Xiaoyun Sun1, Jiaying Zhang1, Xiaohui Bi 1, Yafei Li1, Liwei Li2, Haiyan Dong2, Zhimei Xiao2, Yufen Zhang1, Yinchang Feng1

  • 1 State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control and Center for Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tian’jin 300350, China
  • 2 Tianjin Eco-Environment Monitoring Center, Tian’jin 300071, China


  • Impact of sources was assessed by the relationship between SO42−/NO3 and PM.
  • Error estimation diagnostics was applied to choose an optimal factor number.
  • The contributions of most sources show significant spatial-differences.


We collected ambient PM10 and PM2.5 samples from six sites in Tian’jin, China, from February to March 2016 and then analyzed their chemical compositions and identified the emission sources using the positive matrix factorization model. The mean concentrations of the PM10 and PM2.5 were 98 and 71 µg m–3, respectively, with a mean PM2.5/PM10 ratio of 0.67. The average concentrations of the combined SO42–, NO3, and NH4+ were 19.9–23.4 µg m–3, accounting for 72.4–77.1% of the total measured ions. The concentrations and percentages were significantly higher for NO3 and OC than for other species. The SO42–/NO3 ratio showed a decreasing tendency as the PM10 and PM2.5 concentrations increased, implying a strong influence from mobile sources. The mean OC/EC ratios for PM10 and PM2.5 were 3.1 and 3.2, respectively, with small spatial differences. The most abundant elements were crustal, accounting for 73.2–84.2% of the total detected elemental mass, and mainly enriched in the PM10. The optimal number of factors for PM2.5 and PM10 was selected via PMF analysis: the decrease in the Q/Qexcept values of these two fractions lessened when choosing six instead of five factors, indicating that five factors may be optimal. All the factors were mapped in bootstrap (BS) for 100% of the runs, and no swaps occurred with the displacement of factor elements (DISP) for five factors. Secondary inorganic aerosol, coal combustion, crustal dust, vehicle exhaust, and biomass burning contributed 28–30%, 20–21%, 18–21%, 17–20%, and 4%, respectively. Secondary inorganic aerosol displayed less spatial heterogeneity than the other sources in its contributions. Backward trajectory and PSCF analysis showed that air masses affecting Tian’jin mainly originated in the northwest during the heating period, and northeastern He’nan, southwestern Shan’dong, Bei’jing, and Tian’jin itself were major potential source areas.


Chemical species Source apportionment Heating period Error estimation PMF

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