Source apportionment of the ambient PM2.5 across St. Louis using constrained positive matrix factorization

In most cases, receptor models are applied to data from a single monitoring site even if there are multiple sampling locations in a given urban area. When it can be reasonably expected that the sites are affected by the same set of sources, it is possible to use the spatial variability of the source contributions to enhance the source apportionment. With the framework of positive matrix factorization, it is possible to enhance the results through an effective use of multiple site data. There have been several previous studies of the sources of ambient PM2.5 in St Louis, MO based on data from the US EPA chemical speciation network and the St Louis-Midwest Supersite. However, these different analyses identified different sets of sources including the omission of known major emission sources. A re-examination of the previous studies was undertaken using knowledge of the existing sources based on independent data and the resulting profiles were used to constrain the solution. These new solutions provide more realistic results in which the source impacts of all of the major sources could be assessed at each site. (C) 2011 Elsevier Ltd. All rights reserved.