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PM source apportionment and health effects: 1. Intercomparison of source apportionment results

Journal of Exposure Science & Environmental Epidemiology volume 16, pages 275–286 (2006)Cite this article

Abstract

During the past three decades, receptor models have been used to identify and apportion ambient concentrations to sources. A number of groups are employing these methods to provide input into air quality management planning. A workshop has explored the use of resolved source contributions in health effects models. Multiple groups have analyzed particulate composition data sets from Washington, DC and Phoenix, AZ. Similar source profiles were extracted from these data sets by the investigators using different factor analysis methods. There was good agreement among the major resolved source types. Crustal (soil), sulfate, oil, and salt were the sources that were most unambiguously identified (generally highest correlation across the sites). Traffic and vegetative burning showed considerable variability among the results with variability in the ability of the methods to partition the motor vehicle contributions between gasoline and diesel vehicles. However, if the total motor vehicle contributions are estimated, good correspondence was obtained among the results. The source impacts were especially similar across various analyses for the larger mass contributors (e.g., in Washington, secondary sulfate SE=7% and 11% for traffic; in Phoenix, secondary sulfate SE=17% and 7% for traffic). Especially important for time-series health effects assessment, the source-specific impacts were found to be highly correlated across analysis methods/researchers for the major components (e.g., mean analysis to analysis correlation, r>0.9 for traffic and secondary sulfates in Phoenix and for traffic and secondary nitrates in Washington. The sulfate mean r value is >0.75 in Washington.). Overall, although these intercomparisons suggest areas where further research is needed (e.g., better division of traffic emissions between diesel and gasoline vehicles), they provide support the contention that PM2.5 mass source apportionment results are consistent across users and methods, and that today's source apportionment methods are robust enough for application to PM2.5 health effects assessments.

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Acknowledgements

The Workshop was organized under the auspices of the participating US EPA PM Health Effects Research Centers (Grant R827351 at NYU, R827351 at the University of Washington, R827353 at Harvard University, and R927354 at the University of Rochester). We thank the individual researchers who undertook participation in this workshop, often on their own time and resources. The information in this document has been subjected to review by EPA's National Health and Environmental Effects Research Laboratory and approved for publication. Approval does not signify that the contents reflect the views of the Agency, nor does mention of trade names or commercial products constitute endorsement or recommendation for use. Support for the organization and administration of the workshop was also provided by the New York State Energy Research and Development Authority (NYSERDA Grant 375-34215). We also thank Columbia University's Arden House Conference Center in Harriman, NY for hosting the May, 2003 workshop that led to the writing of this manuscript.

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Authors and Affiliations

  1. Center for Air Resources Engineering and Science, Clarkson University, Potsdam, NY, USA

    Philip K Hopke & Eugene Kim

  2. Institute for Environmental Medicine, New York University, Tuxedo Park, NY, USA

    Kazuhiko Ito, Ramona Lall & George D Thurston

  3. Department of Environmental Health, University of Washington, Seattle, WA, USA

    Therese Mar

  4. Department of Statistics, Brigham Young University, Provo, UT, USA

    William F Christensen

  5. Department of Chemistry and Biochemistry, Brigham Young University, Provo, UT, USA

    Delbert J Eatough

  6. Department of Civil and Environmental Engineering, Southern California University, Los Angeles, CA, USA

    Ronald C Henry

  7. Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA

    Francine Laden & Helen Suh

  8. Department of Civil and Environmental Engineering, University of Washington, Seattle, WA, USA

    Timothy V Larson

  9. Department of Biostatistics, University of Washington, Seattle, WA, USA

    Hao Liu

  10. National Health & Environmental Effects Research Laboratory, US Environmental Protection Agency, Chapel Hill, NC, USA

    Lucas Neas

  11. National Center for Environmental Assessment, US Environmental Protection Agency, Research Triangle Park, NC, USA

    Joseph Pinto

  12. Institute of Epidemiology, GSF Focus Network Aerosols and Health, GSF National Research Center for Environment and Health, Neuherberg, Germany

    Matthias Stölzel

  13. Department of Physical Sciences, University of Helsinki, Helsinki, Finland

    Pentti Paatero

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Hopke, P., Ito, K., Mar, T. et al. PM source apportionment and health effects: 1. Intercomparison of source apportionment results. J Expo Sci Environ Epidemiol 16, 275–286 (2006). https://doi.org/10.1038/sj.jea.7500458

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