Source Apportionment Using Positive Matrix Factorization on Daily Measurements of Inorganic and Organic Speciated PM2.5

Details

• Personal Author:
  Dutton SJ ; Hannigan MP ; Milford JB ; Miller SL ; Piedrahita R ; Vedal S
• Description:
  Particulate matter less than 2.5 microns in diameter (PM2.5) has been linked with a wide range of adverse health effects. Determination of the sources of PM2.5 most responsible for these health effects could lead to improved understanding of the mechanisms of such effects and more targeted regulation. This has provided the impetus for the Denver Aerosol Sources and Health (DASH) study, a multi-year source apportionment and health effects study relying on detailed inorganic and organic PM2.5 speciation measurements. In this study, PM2.5 source apportionment is performed by coupling positive matrix factorization (PMF) with daily speciated PM2.5 measurements including inorganic ions, elemental carbon (EC) and organic carbon (OC), and organic molecular markers. A qualitative comparison is made between two models, PMF2 and ME2, commonly used for solving the PMF problem. Many previous studies have incorporated chemical mass balance (CMB) for organic molecular marker source apportionment on limited data sets, but the DASH data set is large enough to use multivariate factor analysis techniques such as PMF. Sensitivity of the PMF2 and ME2 models to the selection of speciated PM2.5 components and model input parameters was investigated in depth. A combination of diagnostics was used to select an optimum, 7-factor model using one complete year of daily data with pointwise measurement uncertainties. The factors included 1) a wintertime/methoxyphenol factor, 2) an EC/sterane factor, 3) a nitrate/polycyclic aromatic hydrocarbon (PAH) factor, 4) a summertime/selective aliphatic factor, 5) an n-alkane factor, 6) a middle-oxygenated PAH/alkanoic acid factor and 7) an inorganic ion factor. These seven factors were qualitatively linked with known PM2.5 emission sources with varying degrees of confidence. Mass apportionment using the 7-factor model revealed the contribution of each factor to the mass of OC, EC, nitrate and sulfate. On an annual basis, the majority of OC and EC mass was associated with the summertime/selective aliphatic factor and the EC/sterane factor, respectively, while nitrate and sulfate mass were both dominated by the inorganic ion factor. This apportionment was found to vary substantially by season. Several of the factors identified in this study agree well with similar assessments conducted in St. Louis, MO and Pittsburgh, PA using PMF and organic molecular markers. [Description provided by NIOSH]
• Subjects:
  Air Pollution Environmental Monitoring Epidemiology Occupational Health Particulate Matter Safety
• Keywords:
  Air Pollution Author Keywords: Particulate Matter Denver Environmental Monitoring Health Effects Organic Molecular Markers Particulates PM2.5 Positive Matrix Factorization Source Apportionment
• ISSN:
  1352-2310
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  Colorado ; North Carolina ; OSHA Region 10 ; OSHA Region 4 ; OSHA Region 8 ; Washington
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  44
• Issue:
  23
• NIOSHTIC Number:
  nn:20055155
• Citation:
  Atmos Environ 2010 Jul; 44(23):2731-2741
• Contact Point Address:
  Michael P. Hannigan, Department of Mechanical Engineering, College of Engineering and Applied Science, University of Colorado, Boulder, CO 80309, USA
• Email:
  hannigan@colorado.edu
• Federal Fiscal Year:
  2010
• Performing Organization:
  University of Washington
• Peer Reviewed:
  True
• Start Date:
  20050701
• Source Full Name:
  Atmospheric Environment
• End Date:
  20250630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:5d1730a9201e8c11c85833dff28395acad4edd5dcffe33ead42b0e8d997e4b16d89d6a5e897ce0d78b8cf946a3da40e280df8c0ea5feab79e3e2ec71e99130ca
• Download URL:
  https://stacks.cdc.gov/view/cdc/217516/cdc_217516_DS1.pdf
• File Type:
  [PDF - 463.00 KB ]