Combining size distribution and chemical species measurements into a multivariate receptor model of PM2.5

We introduce an extended receptor model, implemented with the multilinear engine ME2, which combines simultaneous but separate filter-based species information with size-resolved particle volume information. Our chemical data set consisted of 24-hour filter measurements reported by the EPA Speciation Trends Network at Beacon Hill in Seattle, Washington, from February 2000 to June 2003. We measured the particle size distribution at this site from December 2000 to April 2002 using a differential mobility particle sizer (DMPS) and an aerodynamic particle sizer (APS). The combined model extends the traditional chemical mass balance approach by including a simultaneous set of conservation equations for both particle mass and volume, linked by a unique value of apparent particle density for each source. The model distinguished three mobile source features, two consistent with previous identifications of "gasoline" and "diesel" sources, and an additional minor feature enriched in EC, Fe and Mn and ultrafine particle mass that would have been difficult to interpret in the absence of particle size information. This study has also demonstrated the feasibility of defining missing mass as an additional variable, and thereby providing additional useful model constraints and eliminating the posthoc regression step that is traditionally used to rescale the results.