Xiaohan Liu, Nan Jiang , Xue Yu, Ruiqin Zhang, Shengli Li, Qiang Li, Panru Kang

Key Laboratory of Environmental Chemistry and Low Carbon Technologies of Henan Province, Research Institute of Environmental Science, College of Chemistry and Molecular Engineering, Zhengzhou University, Zhengzhou 450001, China


Received: February 15, 2019
Revised: May 20, 2019
Accepted: September 2, 2019
Download Citation: ||https://doi.org/10.4209/aaqr.2019.02.0076  

Cite this article:

Liu, X., Jiang, N., Yu, X., Zhang, R., Li, S., Li, Q. and Kang, P. (2019). Chemical Characteristics, Sources Apportionment, and Risk Assessment of PM2.5 in Different Functional Areas of an Emerging Megacity in China. Aerosol Air Qual. Res. 19: 2222-2238. https://doi.org/10.4209/aaqr.2019.02.0076


  • Collected PM2.5 samples in urban, industrial, scenic, traffic and rural areas.
  • Annual mean concentrations of PM2.5 far exceed the Chinese standards.
  • Secondary aerosol and coal combustion contribute highly of PM2.5 in Zhengzhou.
  • PM2.5-bound As and Pb have intolerable health risks.



The mass concentration, chemical composition, and source apportionment of PM2.5 in the urban, industrial, scenic, traffic, and rural sites of Zhengzhou were studied from February to December of 2016. The average annual concentration of PM2.5 in these five sites was 119 µg m–3, which was lower than the annual average between 2013 and 2015. However, PM2.5 pollution remains serious in Zhengzhou. PM2.5, elemental carbon (EC), organic carbon (OC), and water-soluble inorganic ions (WSIIs)—with the exception of F, Ca2+, and Mg2+—showed a relatively homogeneous spatial distribution in this area. Among these pollutants, WSIIs, carbonaceous species (EC and OC), and elements accounted for 47.7%, 14.4%, and 9.6% of PM2.5 concentration in Zhengzhou, respectively. The annual OC/EC ratio in Zhengzhou was 8.3, which indicates the possible presence of a secondary organic carbon. Six main sources of PM2.5 in Zhengzhou, namely, soil dust (15.1%), coal combustion (17.6%), secondary aerosol (35.1%), vehicle traffic (17.3%), industry (7.3%), and biomass burning (7.7%), were identified by using a positive matrix factorization model. The results of the back trajectory and potential source contribution function analysis revealed that the air mass from regions of the Shandong and Hubei Provinces aggravated the pollution in Zhengzhou, and Puyang, Hebi, Xinxiang, and Kaifeng were the main potential sources of PM2.5, respectively. The carcinogenic risks of As to children through the ingestion pathway exceeded the acceptable level. The findings of this work can provide an in-depth understanding of the PM2.5 pollution in Zhengzhou.

Keywords: PM2.5; Spatial distribution; Positive matrix factorization; Coefficients of divergence; Health risk assessment.


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