Jeff Wagner , Zhong-Min Wang, Sutapa Ghosal, Stephen Wall


Environmental Health Laboratory, California Department of Public Health, Richmond, CA 94804, USA


Received: May 29, 2019
Revised: September 11, 2019
Accepted: October 9, 2019
Download Citation: ||https://doi.org/10.4209/aaqr.2019.05.0276 

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Cite this article:
Wagner, J., Wang, Z.M., Ghosal, S. and Wall, S. (2019). Source Identification on High PM2.5 Days Using SEM/EDS, XRF, Raman, and Windblown Dust Modeling. Aerosol Air Qual. Res. 19: 2518-2530. https://doi.org/10.4209/aaqr.2019.05.0276


Highlights

  • Multi-analysis approach identifies causes of high PM2.5 when limited samples are available.
  • Optical, Raman, and electron microscopy performed on individual particles on filters.
  • Supporting XRF, wind roses, GIS, FRM inlet and windblown dust modeling data employed.
  • Three distinct causes determined: windblown dust, ammonia emissions, and filter error.
 

ABSTRACT


When community exposures to PM2.5 are high, identification of the particle sources enables more effective control and assessment of health impacts. This study demonstrates forensic particle analysis methods that can be used when only limited, archived samples are available. Federal reference method (FRM) filters from seven high PM2.5 days were analyzed using optical and electron microscopy, X-ray fluorescence, and Raman micro-spectroscopy to determine individual particle morphology and composition, together with supplemental wind roses, GIS mapping, FRM inlet penetration calculations, and windblown dust modeling. This approach identified three distinct sources of high PM2.5 measurements: 1) local, wind-blown dust from an atypical direction, consistent with modeling predictions for a normally operating PM2.5 inlet challenged with a high concentration of windblown dust particles, potentially enhanced by re-entrainment of particles from within the inlet, 2) wintertime, regional, hygroscopic, nitrogen- and sulfur-rich salts, consistent with ammonium nitrate and ammonium sulfate, and 3) sampling or documentation error. This approach can be used in any location in which regulatory PM filters and other air quality data are available.


Keywords: Air quality; Area sources, Mineral dust; Measurement techniques; PM2.5; Secondary aerosol; Source apportionment.




Impact Factor: 2.735

5-Year Impact Factor: 2.827


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