Preprints
https://doi.org/10.5194/acp-2016-189
https://doi.org/10.5194/acp-2016-189

  19 Apr 2016

19 Apr 2016

Review status: this preprint was under review for the journal ACP but the revision was not accepted.

Source Apportionment of Urban Particulate Matter using Hourly Resolved Trace Metals, Organics, and Inorganic Aerosol Components

Cheol-Heon Jeong, Jon M. Wang, and Greg J. Evans Cheol-Heon Jeong et al.
  • Southern Ontario Centre for Atmospheric Aerosol Research, University of Toronto, Toronto, M5S 3E5, Canada

Abstract. Source apportionment analysis of hourly resolved particulate matter (PM) speciation data was performed using positive matrix factorization (PMF). The data were measured at an urban site in downtown Toronto, Canada during two campaign periods (April–July, 2013; November, 2013–February, 2014), and included trace metals, black carbon, and mass spectra for organic and inorganic species (PMFFull). The chemical composition was measured by collocated high time resolution instrumentation, including an Aerosol Chemical Speciation Monitor, an Xact metals monitor, and a seven-wavelength Aethalometer. Separate PMF analyses were conducted using the trace metal only data (PMFmetal) and organic mass spectra only (PMForg), and compared with the PMFFull results. Comparison of these three PMF analyses demonstrated that the full analysis offered many advantages in the apportionment of local and regional sources compared to using the organic or metals data individually. In combining the high time resolution data, this analysis enabled i) the quantification of metal-rich sources of PM2.5 (PM < 2.5 μm), ii) the resolution of more robust factor profiles and contributions, and iii) the identification of additional organic aerosol sources.

Nine factors were identified through the PMFFull analysis: five local factors (i.e. Road Dust, Primary Vehicle Emissions, Tire Wear, Cooking, and Industrial Sector) and four regional factors (i.e. Biomass Burning, Oxidised Organics, Sulphate and Oxidised Organics, and Nitrate and Oxidised Organics). The majority of the metal emissions (83 %) and almost half of the black carbon (49 %) were associated with the three traffic-related factors which, on average, contributed a minority (17 %) of the overall PM2.5 mass. Strong seasonal patterns were observed for the traffic-related emissions: higher contributions of resuspended road dust in spring vs. a winter high for tire wear related emissions. Biomass Burning contributed the majority of the PM2.5 mass (52 %) in June and July due to a major forest fire event. Much of this mass was due to photochemical aging of the biomass burning aerosol. On average, industrially related factors contributed almost half (49 %) of the PM2.5; most of this mass was secondary aerosol species. Nitrate coupled with highly oxidised organics was the largest contributor, accounting for 30 % of PM2.5 on average, with higher levels in winter and at night. Including the temporal variabilities of inorganic ions and trace metals in the PMFFull analysis provided additional structure to subdivide the low volatility oxidised organic aerosol into three sources. Resuspended road dust was identified as a potential source of aged organic aerosol.

The novelty of this study is the application of PMF receptor modeling to hourly resolved trace metals in conjunction with organic mass spectra, inorganic species, and black carbon for different seasons, and the comparison of separate PMF analyses applied to metals or organics alone. The inclusion of these different types of hourly data allowed more robust apportionment of PM sources, as compared to analysing organic or metals data individually.

Cheol-Heon Jeong et al.

 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Cheol-Heon Jeong et al.

Cheol-Heon Jeong et al.

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Short summary
The source identification and quantification analysis of hourly resolved particulate matter chemical speciation data in downtown Toronto, Canada offered many advantages in terms of the identification of more sources and the resolution of more robust factor profiles and contributions. The results provide additional insight into sources of fine particle pollutants that have high temporal variations and thereby support the development of more effective control strategies for ambient pollutants.
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