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Chemical Characteristics and Source Apportionment by Two Receptor Models of Size-segregated Aerosols in an Emerging Megacity in China

Category: Aerosol and Atmospheric Chemistry

Accepted Manuscripts
DOI: 10.4209/aaqr.2017.10.0413
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Nan Jiang, Ke Wang, Xue Yu, Fangcheng Su, Shasha Yin, Qiang Li, Ruiqin Zhang

  • Research Institute of Environmental Science, College of Chemistry and Molecular Engineering, Zhengzhou University, Zhengzhou 450001, China


Size-segregated aerosols were collected and chemically characterized.
Annual values of PM2.5 and PM10 far exceeded the Chinese air quality standard.
As and Cd concentrations were higher than Chinese ambient air quality standard.
Dust and secondary aerosols play important roles in PM2.5-10 and PM2.5, respectively.


PM2.5, PM2.5-10 and PM10 samples were collected in Zhengzhou in 2014 to examine the chemical characteristics and sources of aerosols in this area. PM concentrations, nine water soluble inorganic ions, organic carbon, elemental carbon, and twenty-two elements were determined, and positive matrix factorization (PMF) and chemical mass balance (CMB) were used for source apportionments. Meteorological impact was also evaluated by back-trajectory cluster analysis. Severe PM pollution was present in the study area. Aerosol concentrations of PM2.5 samples (92%) and PM10 samples (85%) exceeded the levels of the Chinese National Ambient Air Quality Standard (NAAQS). Annual average mass concentrations of PM2.5 and PM10 reached 187 and 281 µg m–3, respectively, which were significantly higher than the levels of the Chinese NAAQS. Secondary inorganic aerosols were the major ions in PM, and accounted for 36%, 10%, and 27% of PM2.5, PM2.5-10, and PM10, respectively. Annual concentration of As (0.029 µg m–3) and Cd (0.010 µg m–3) in PM10 also exceeded the Chinese NAAQS levels, indicating high health risk. Results from source apportionment by PMF modelling indicated that dust, vehicular traffic, coal combustion, secondary aerosols, and industry were the main pollution sources and accounted for 13.1%, 14.1%, 16.1%, 35.8%, and 14.6% of PM2.5; 25.1%, 20.8%, 21.8%, 10.5%, and 11.6% of PM2.5-10 and 19.8%, 15.8%, 18.5%, 22.5%, and 13.5% of PM10, respectively. Dust sources play important roles in PM pollution, especially in coarse particles, and however, secondary aerosol sources contribute the most to PM2.5. Both observations were consistent with the results of mass reconstruction of size-segregated aerosols. CMB results coincided with PMF results for PM2.5. Cluster analysis showed that air quality in the study area across the four seasons was mainly affected by air masses from the northeast and east directions.


Size-segregated Positive matrix factorization Chemical mass balance Back-trajectory clustering analysis

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