Source Apportionment of PM(2.5)in Guangzhou Based on an Approach of Combining Positive Matrix Factorization with the Bayesian Mixing Model and Radiocarbon

doi:10.3390/atmos11050512

	Li, Tingting 1,2,3; Li, Jun1,2 ; Jiang, Hongxing 1,2,3; Chen, Duohong 4; Zong, Zheng 5; Tian, Chongguo 5; Zhang, Gan1,2
	Source Apportionment of PM(2.5)in Guangzhou Based on an Approach of Combining Positive Matrix Factorization with the Bayesian Mixing Model and Radiocarbon
Source Publication	ATMOSPHERE
	2020-05-01
Volume	11 Issue:5 Pages:18
DOI	10.3390/atmos11050512
Language	英语
WOS Research Area	Meteorology & Atmospheric Sciences
WOS ID	WOS:000541801900103
Indexed By	SCI
Citation statistics	Cited Times:11[WOS] [WOS Record] [Related Records in WOS]
Document Type	期刊论文
Identifier	http://ir.gig.ac.cn/handle/344008/57731
Collection	有机地球化学国家重点实验室
Corresponding Author	Li, Jun; Chen, Duohong
Affiliation	1.Chinese Acad Sci, Guangzhou Inst Geochem, State Key Lab Organ Geochem, Guangzhou 510640, Peoples R China 2.Chinese Acad Sci, Guangzhou Inst Geochem, Guangdong Prov Key Lab Environm Protect & Resourc, Guangzhou 510640, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Guangdong Environm Monitoring Ctr, Guangzhou 510308, Peoples R China 5.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Key Lab Coastal Environm Proc & Ecol Remediat, Yantai 264003, Peoples R China
Recommended Citation GB/T 7714	Li, Tingting,Li, Jun,Jiang, Hongxing,et al. Source Apportionment of PM(2.5)in Guangzhou Based on an Approach of Combining Positive Matrix Factorization with the Bayesian Mixing Model and Radiocarbon[J]. ATMOSPHERE,2020,11(5):18.
APA	Li, Tingting.,Li, Jun.,Jiang, Hongxing.,Chen, Duohong.,Zong, Zheng.,...&Zhang, Gan.(2020).Source Apportionment of PM(2.5)in Guangzhou Based on an Approach of Combining Positive Matrix Factorization with the Bayesian Mixing Model and Radiocarbon.ATMOSPHERE,11(5),18.
MLA	Li, Tingting,et al."Source Apportionment of PM(2.5)in Guangzhou Based on an Approach of Combining Positive Matrix Factorization with the Bayesian Mixing Model and Radiocarbon".ATMOSPHERE 11.5(2020):18.

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