@article {song2006source,
	title = {Source apportionment of PM2. 5 in Beijing using principal component analysis/absolute principal component scores and UNMIX},
	journal = {Science of the Total Environment},
	volume = {372},
	number = {1},
	year = {2006},
	pages = {278{\textendash}286},
	publisher = {Elsevier},
	abstract = {


Source apportionment\&nbsp;of fine\&nbsp;particulate matter\&nbsp;(PM2.5, i.e., particles with an aerodynamic diameter of 2.5\&nbsp;μm or less) in Beijing, China, was determined using two\&nbsp;eigenvector\&nbsp;models, principal component analysis/absolute principal component scores (PCA/APCS) and UNMIX. The data used in this study were from the chemical analysis of 24-h samples, which were collected at 6-day intervals in January, April, July, and October 2000 in the Beijing metropolitan area. Both models identified five sources of PM2.5: secondary sulfate and secondary nitrate, a mixed source of\&nbsp;coal combustion\&nbsp;and\&nbsp;biomass burning,\&nbsp;industrial emission, motor vehicles exhaust, and road dust. On average, the PCA/APCS and UNMIX models resolved 73\% and 85\% of the PM2.5 mass concentrations, respectively. The results were comparable to previous estimate using the positive matrix\&nbsp;factorization\&nbsp;(PMF) and chemical mass balance (CMB) receptor models. Secondary products and the emissions from coal combustion and biomass burning dominated PM2.5. Such comparison among various receptor models, which contain different physical constraints, is important for better understanding PM2.5 sources.
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},
	url = {https://www.sciencedirect.com/science/article/pii/S0048969706006760?via\%3Dihub},
	author = {Yu Song and Shaodong Xie and Yuanhang Zhang and Limin Zeng and Lynn G. Salmon and Mei Zheng}
}
