title: Source apportionment of airborne particulate matter for the Speciation Trends Network site in Cleveland, OH.
abstract: Aerosol composition data from the Speciation Trends Network (STN) site (East 14th Street) in Cleveland, OH, were analyzed by advanced receptor model methods for source apportionment as well as by the standard positive matrix factorization (PMF) using PMF2. These different models are used in combination to test model limitations. These data were 24-hr average mass concentrations and compositions obtained for samples taken every third day from 2001 to 2003. The Multilinear Engine (ME) was used to solve an expanded model to estimate the source profiles and source contributions and also to investigate the wind speed, wind direction, time-of-day, weekend/weekday, and seasonal effects. PMF2 was applied to the same dataset. Potential source contribution function (PSCF) and conditional probability function (CPF) analyses were used to locate the regional and local sources using the resolved source contributions and appropriate meteorological data. Very little difference was observed between the results of the expanded model and the PMF2 values for the profiles and source contribution time series. The identified sources were as ferrous smelter, secondary sulfate, secondary nitrate, soil/combustion mixture, steel mill, traffic, wood smoke, and coal burning. The CPF analysis was useful in helping to identify local sources, whereas the PSCF results were only useful for regional source areas. Both of these analyses were more useful than the wind directional factor derived from the expanded factor analysis. However, the expanded analysis provided direct information on seasonality and day-of-week behavior of the sources.
authors.affiliation: Center for Air Resources Engineering and Science, Clarkson University, Potsdam, NY, USA.
authors.forename: Liming
authors.initials: L
authors.lastname: Zhou
authors.forename: Philip K
authors.initials: PK
authors.lastname: Hopke
authors.forename: Weixiang
authors.initials: W
authors.lastname: Zhao