Further analysis and PMF application to the chemical composition data of IPCAJ's Kashima SPM study Online publication date: Tue, 23-Feb-2010
by Prapat Pongkiatkul, Nguyen Thi Kim Oanh, Arpa Wangkiat, Shin'ichi Okamoto
International Journal of Environment and Pollution (IJEP), Vol. 40, No. 4, 2010
Abstract: The Industrial Pollution Control Association of Japan (IPCAJ) has conducted an air quality study. A brief summary has already appeared in previous papers. This set of data was not sufficiently analysed. This study attempts to examine the performance of the Positive Matrix Factorisation (PMF), a recently introduced technique in this field, on this multiple-site Kashima data set. The source apportionment study using the PMF model conducted for the Kashima data set identified six factors for each fine and coarse fraction. This result also seems to be appropriate, because spatial distribution and seasonal variation of the contributions for each emission source category could be explained reasonably. The PMF can analyse a data set that may be extracted from different populations, and it seems to be a powerful tool available for these kinds of complicated data sets.
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