Abstract
Positive matrix factorization (PMF) and convenient factor analysis (CFA) models have been tested using a large aerosol
database measured in Hong Kong. As many as possible chemical components (good elements or so-called weak elements)
[Atmos. Environ. 33 (1999) 2169] were selected to compose as large as possible a database. Error estimates and enforced
rotation techniques were used in the PMF model trial. These important aspects were not included in a recently published work
[Atmos. Environ. 33 (1999) 2169]. The test results of the two models mentioned above were assessed qualitatively by analyzing
factor characteristics, and quantitatively by comparing factor mass profiles. CFA model has been shown to be a convenient tool
for aerosol source identification and can qualitatively treat the elements that can serve as source tracers as well as PMF model
does. PMF model provides expert tool for the identification of aerosol sources and source contribution estimation. It can treat
the chemical components from various sources by apportioning these chemical components among the factors more reasonably
than CFA model can. Quantitatively, the factor mass profiles produced by a PMF model are better at describing the source
structure than those derived by a CFA model.
Original language | English |
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Pages (from-to) | 75-87 |
Number of pages | 12 |
Journal | Chemometrics and Intelligent Laboratory Systems |
Volume | 61 |
Issue number | 1-2 |
DOIs | |
Publication status | Published - Feb 2002 |
Keywords
- Positive matrix factorization
- Convenient factor analysis
- Respirable suspended particulate
- Source identification