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Seasonal variations of sources of polycyclic aromatic hydrocarbons (PAHs) to a northeastern urban city, China

  • Wan Li Ma
  • , Yi Fan Li*
  • , Hong Qi
  • , De Zhi Sun
  • , Li Yan Liu
  • , De Gao Wang
  • *Corresponding author for this work
  • Harbin Institute of Technology
  • Environment and Climate Change Canada
  • Dalian Maritime University

Research output: Contribution to journalArticlepeer-review

Abstract

Understanding the seasonal variations of sources of polycyclic aromatic hydrocarbons (PAHs) in air in urban region is important to the effective control of air pollution in the region. Based on a year round dataset (from August 2008 to July 2009), the sources of atmospheric PAHs in Harbin, a typical Chinese northeastern urban city, were analyzed by principal component analysis (PCA) and positive matrix factorization (PMF). The average total (gas plus particulate) PAH concentration varied from 6.3 ng m-3 to 340 ng m-3 with a mean of 100 ± 94 ng m-3, with higher concentrations in heating season than those in non-heating season. PCA and PMF identified similar source factors to atmospheric PAHs with obvious seasonal variation. The results obtained by PMF method indicated that the main sources were coal-fired boiler (39%), diesel engine (34%) and coal average (22%) in heating season and traffic emissions (59%), ground evaporation (18%) and coal average (17%) in non-heating season. Excellent correlation coefficients between predicted and measured concentrations of PAHs indicated that PMF was a useful model for source apportionment of PAHs in atmosphere.

Original languageEnglish
Pages (from-to)441-447
Number of pages7
JournalChemosphere
Volume79
Issue number4
DOIs
StatePublished - Apr 2010

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Atmosphere
  • PAHs
  • Positive matrix factorization
  • Principal component analysis
  • Source apportionment

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