RECEPTOR MODELING


Receptor modeling is the application of multivariate statistical methods to the identification and quantitative apportionment of air pollutants to their sources. It is closely related to other applications of statistical methods in chemistry, chemometrics, to the resolution of mixtures based on spectroscopic data. We have recently been extending the field to regional and global scale source/receptor relationships by combining meteorological data with the chemical composition of collected particle samples. Many of these data analysis studies are in conjunction with major laboratories in Bangladesh, Canada, Norway, Sweden, Finland, and Korea, giving us access to interesting data sets from around the world as well as collaboration with studies across the US. We have recently started a program of chemical analysis of filters collected in the north of Finland starting in 1963. This project should lead to the longest record of aerosol compositions at any location in the world. We are now about to participate in 4 of the seven Super Sites that EPA is supporting as part of its Particulate Matter Monitoring Network. The primary receptor modeling method that we have been applying is positive matrix factorization (PMF). PMF approaches factor analysis as a least-squares problem that allows individual data point weighting and incorporation of natural constraints on the solutions. An introduction to PMF is available.

We have been exploring the use of more complex factor analysis models to incorporate meteorologicaldata or multiple sample types into the analyses.

In recent years, we have been refining these methods along with trajectory ensemble methods to identify the likely source areas for transportated pollutants. We have applied Potential Source Contribution Function Analysis, Simplified Trajectory Bias Analysis, and Residence Time Weighted Concentration methods to various data sets. For example, the figure below shows the likely source areas for the secondary sulfate observed at a site in St. Louis, MO between 2000 and 2003. It can be seen that much of the sulfate arises from SO2 emissions in the Upper Ohio River Valley area.

In the figure below, the PSCF plot for nitrate is shown. In this case, the plot shows areas like Detroit that are nitrate source regions, but the map primarily indicates locations in areas of intensive agriculture particularly large scale animal feeding operations such as in northwestern Iowa. Thus, it appears that transported ammonia is critical to determining the particulate nitrate concentraitons in urban areas.

These methods have led to a number of the recent papers listed below.

  • Spatial Distribution of Source Locations for Particulate Nitrate and Sulfate in the Upper-Midwestern United States, W. Zhao, P.K. Hopke, and L. Zhou, Atmospheric Environ. 41: 1831-1847 (2007).
  • Estimation of Source Apportionment and Potential Source Locations of PM2.5 at a West Coastal IMPROVE Site, I.J. Hwang and P.K. Hopke, Atmospheric Environ. 41: 506-518 (2007).
  • Source Characterization of Ambient Fine Particles in the Los Angeles Basin, E. Kim and P.K. Hopke, J. Environmental Engineering Science 6: 343-353 (2007).
  • Estimation of Source Locations of Total Gaseous Mercury Measured in New York State Using Trajectory Based Models, Y. Han, T.M. Holsen, and P.K. Hopke, Atmospheric Environ. 41: 6033–6047 (2007).
  • Factor Analysis of Submicron Particle Size Distributions Near a Major United States-Canada Trade Bridge, D. Ogulei, P.K. Hopke, A.R. Ferro, P.A. Jaques, J. Air Waste Manage. Assoc. 57: 190-203 (2007).
  • Modeling Source Contributions to Submicron Particle Number Concentrations Measured in Rochester, NY, D. Ogulei, P.K. Hopke, D.C. Chalupa, and M.J. Utell, Aerosol Sci. Technol. 41: 179-201 (2007).
  • Use of an Expanded Receptor Model for Personal Exposure Analysis in Schoolchildren with Asthma, W. Zhao, P.K. Hopke, E.W. Gelfand, N. Rabinovitch, Atmospheric Environ. 41: 4084-4096 (2007).
  • Source Apportionment of Time and Size Resolved Ambient Particulate Matter Measured with a Rotating DRUM Impactor, E. Pere-Trepat, P.K. Hopke, and P. Paatero, Atmospheric Environ. 41: 5921–5933 (2007).
  • Sources of Fine Urban Particulate Matter in Detroit, MI, A. Gildemeister, P.K. Hopke, and E. Kim, Chemosphere 69: 1064-1074 (2007).
  • Source Identifications of Airborne Fine Particles using Positive Matrix Factorization and U.S. Environmental Protection Agency Positive Matrix Factorization, E. Kim and P.K. Hopke, J. Air Waste Manage. Assoc. 57: 811-819 (2007).
  • Source Apportionment of Fine Particles Utilizing Partially Speciated Carbonaceous Aerosol Data at Two Rural Locations in New York State, R. Sunder Raman and P.K. Hopke, Atmospheric Environ. 41: 7923–7939 (2007).
  • Source Apportionment of Air Particulate Matter by Chemical Mass Balance (CMB) and Comparison with Positive Matrix Factorization (PMF) Model, B.A. Begum, S.K. Biswas, P.K. Hopke, Aerosol and Air Quality Research 7: 446-468 (2007).
  • Apportionment of Ambient Primary and Secondary PM2.5 at the Pittsburgh National Energy Laboratory (NETL)Pittsburgh PM Characterization Site Using Positive Matrix Factorization (PMF) and a Potential Source Contributions Function (PSCF) Analysis, D.V. Martello, N.J. Pekney, R.R. Anderson, C.I. Davidson, P.K Hopke, E. Kim, W.F. Christensen, N.F. Mangelson, and D.J. Eatough, J. Air Waste Manage. Assoc. 58: 357–368 (2008).
  • Comparison of Two Cluster Analysis Methods using Single Particle Mass Spectra, W. Zhao, P.K. Hopke, K.A. Prather, Atmospheric Environ. 42: 881-892 (2008).
  • Sources Identification of the Atmospheric Aerosol at Urban and Suburban Sites in Indonesia by Positive Matrix Factorization, M. Santoso, P.K. Hopke, A. Hidayat, Diah Dwiana L, Science of the Total Environment 397: 229-238 (2008).
  • Source Apportionment and Spatial Distributions of Coarse Particles During the Regional Air Pollution Study (RAPS), I.J. Hwang, P.K. Hopke, J.P. Pinto, Environ. Sci. Technol. 42: 3524–3530 (2008).
  • Source apportionment of ambient fine particle size distribution using positive matrix factorization in Erfurt, Germany, W. Yue, M. Stlzel, J. Cyrys, M. Pitz, J. Heinrich, W.G. Kreyling, H.-E. Wichmann, A. Peters, S. Wang, P.K. Hopke, Science of the Total Environment 398: 133–144 (2008).
  • Source Characterization of Ambient Fine Particles at Multiple Sites in the Seattle Area, E. Kim and P.K. Hopke, Atmospheric Environ. 42: 6047-6056 (2008).
  • Source apportionment of particulate matter in Europe: a review of methods and results, Viana, M., Kuhlbusch, T.A.J., Querol, X., Alastuey, A., Harrison, R.M., Hopke, P.K., Winiwarter, W., Vallius, M., Szidat, S., Prvt, A.S.H., Hueglin, C., Bloemen H., Whlin, P., Vecchi, R., Miranda, A.I., Kasper-Giebl, A., Maenhaut, W., Hitzenberger, R., J. Aerosol Sci. 39: 827–849 (2008).


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