4.7 Article

Source apportionment of urban fine particle number concentration during summertime in Beijing

Journal

ATMOSPHERIC ENVIRONMENT
Volume 96, Issue -, Pages 359-369

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.atmosenv.2014.06.055

Keywords

Number size distribution; Chemical composition; Positive matrix factorization; Source apportionment; Fine particle

Funding

  1. National Natural Science Foundation of China [41230642]
  2. Science and Technology Project of Beijing [D09040903670902]

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Continuous particle number size distributions (15 nm-2.5 mu m), particle chemical compositions, gaseous species and meteorological variables were collected at an urban site in Beijing to investigate the source apportionment of ambient fine particle number concentrations. Hourly data sets were analyzed using the positive matrix factorisation (PMF) which identified a total of eight factors: two traffic factors, two combustion factors, secondary nitrate factors, secondary sulfate secondary organic aerosol (SOA), fugitive dust and regionally transported aerosol. Traffic (47.9%) and combustion (29.7%) aerosol were found to dominate the particle number concentrations, whereas the most important sources for particle volume concentrations were found to be regionally transported aerosol (30.9%) and combustions (30.1%). Although the diurnal pattern of each of the two traffic factors closely followed traffic rush hour for Beijing, their size modes were different suggesting that these factors might represent local and remote emissions. Biomass burning and coal-fired power plant aerosol were distinguished according to their size modes and chemical species associated with them. Secondary compounds showed similar bimodal particle number size distribution, the distinct diurnal pattern distinguished these factors as secondary nitrate and mixed source of secondary sulfate and SOA. Regionally transported material was characterized by accumulation mode particles. Overall, the introduction of combinations of particle number size distributions and chemical composition data in PMF model is successful at separating the components and quantifying relative contributions to the particle number and volume size distributions in the complex urban atmosphere. (C) 2014 Elsevier Ltd. All rights reserved.

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