Source Apportionment of PM_2.5at an Urban IMPROVE Site in Seattle, Washington

Abstract

The multivariate receptor models Positive Matrix Factorization (PMF) and Unmix were used along with the EPA's Chemical Mass Balance model to deduce the sources of PM2.5 at a centrally located urban site in Seattle, WA. A total of 289 filter samples were obtained with an IMPROVE sampler from 1996 through 1999 and were analyzed for 31 particulate elements including temperature-resolved fractions of the particulate organic and elemental carbon. All three receptor models predicted that the major sources of PM2.5 were vegetative burning (including wood stoves), mobile sources, and secondary particle formation with lesser contributions from resuspended soil and sea spray. The PMF and Unmix models were able to resolve a fuel oil combustion source as well as distinguish between diesel emissions and other mobile sources. In addition, the average source contribution estimates via PMF and Unmix agreed well with an existing emissions inventory. Using the temperature-resolved organic and elemental carbon fractions provided in the IMPROVE protocol, rather than the total organic and elemental carbon, allowed the Unmix model to separate diesel from other mobile sources. The PMF model was able to do this without the additional carbon species, relying on selected trace elements to distinguish the various combustion sources.

Source Apportionment: Findings from the U.S. Supersites Program

“…Thermally derived C fractions, [53][54][55][56] which are a free byproduct of thermal/optical C analyses, have been found useful for distinguishing between diesel exhaust and other C source types. [57][58][59][60][61] For example, high-temperature EC (e.g., EC2, EC evolved at 740°C in a 98% helium [He]/2% oxygen [O 2 ] atmosphere) dominates particulate emissions from diesel engines. 54 Specific organic markers (Table 2) have also proven useful in PMF modeling studies, [63][64][65][66] but advances are needed to make them more available in source and receptor samples.…”

Impact of anions on the surface organisation of lipid monolayers at the air–water interface

“…[ 3 À are the dominant ions for marine cloud water collected over the eastern Pacific Ocean. [20][21][22][23][24] They also contribute 24.5 % of PM2.5 mass from continental sources. [25] Based on the Hofmeister series, ions can be divided into kosmotropes and chaotropes, which have opposing affinities towards the interface.…”

UNMIX modeling of ambient PM2.5 near an interstate highway in Cincinnati, OH, USA

“…UNMIX has been recently utilized to establish ambient aerosol sources and was reported to provide good agreement with predictions of other multivariate receptor models (e.g. PCA/MLR, PMF), especially in identifying the dominant source categories (Henry, 2000;Lewis et al, 2003;Larsen and Baker, 2003;Maykut et al, 2003;Mukerjee et al, 2004). A summary of various recent UNMIX applications are outlined in Table 1.…”

“…The authors delineated between gasoline and diesel engine sources; the EC/OC ratio for the diesel source was 0.66, whereas it was 0.32 for the gasoline sources. Maykut et al (2003) and Kim et al (2004) reported UNMIX results for the Seattle, WA area. Maykut et al (2003) reported that carrying out the analysis with EC and OC components resulted in a composite traffic factor.…”

“…Maykut et al (2003) and Kim et al (2004) reported UNMIX results for the Seattle, WA area. Maykut et al (2003) reported that carrying out the analysis with EC and OC components resulted in a composite traffic factor. However, by using subfractions of OC and EC from the temperature programmed thermooptical analysis, they could delineate between gasoline and diesel engine sources.…”