1 research outputs found
Source Apportionment of PM<sub>2.5</sub> at an Urban IMPROVE Site in Seattle, Washington
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
