title: Single particle mass spectral signatures from vehicle exhaust particles and the source apportionment of on-line PM2.5by single particle aerosol mass spectrometry.
abstract: In order to accurately apportion the many distinct types of individual particles observed, it is necessary to characterize fingerprints of individual particles emitted directly from known sources. In this study, single particle mass spectral signatures from vehicle exhaust particles in a tunnel were performed. These data were used to evaluate particle signatures in a real-world PM2.5apportionment study. The dominant chemical type originating from average positive and negative mass spectra for vehicle exhaust particles are EC species. Four distinct particle types describe the majority of particles emitted by vehicle exhaust particles in this tunnel. Each particle class is labeled according to the most significant chemical features in both average positive and negative mass spectral signatures, including ECOC, NaK, Metal and PAHs species. A single particle aerosol mass spectrometry (SPAMS) was also employed during the winter of 2013 in Guangzhou to determine both the size and chemical composition of individual atmospheric particles, with vacuum aerodynamic diameter (dva) in the size range of 0.2-2μm. A total of 487,570 particles were chemically analyzed with positive and negative ion mass spectra and a large set of single particle mass spectra was collected and analyzed in order to identify the speciation. According to the typical tracer ions from different source types and classification by the ART-2a algorithm which uses source fingerprints for apportioning ambient particles, the major sources of single particles were simulated. Coal combustion, vehicle exhaust, and secondary ion were the most abundant particle sources, contributing 28.5%, 17.8%, and 18.2%, respectively. The fraction with vehicle exhaust species particles decreased slightly with particle size in the condensation mode particles.
authors.affiliation: South China Institute of Environmental Sciences, MEP, Guangzhou 510655, China.
authors.forename: Jian
authors.initials: J
authors.lastname: Yang
authors.affiliation: South China Institute of Environmental Sciences, MEP, Guangzhou 510655, China. Electronic address: mashexia@scies.org.
authors.forename: Shexia
authors.initials: S
authors.lastname: Ma
authors.affiliation: South China Institute of Environmental Sciences, MEP, Guangzhou 510655, China.
authors.forename: Bo
authors.initials: B
authors.lastname: Gao
authors.affiliation: State Joint Key Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China.
authors.forename: Xiaoying
authors.initials: X
authors.lastname: Li
authors.affiliation: State Joint Key Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China.
authors.forename: Yanjun
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: State Joint Key Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China.
authors.forename: Jing
authors.initials: J
authors.lastname: Cai
authors.affiliation: Atmospheric Environment Institute of Safety and Pollution Control, Jinan University, Guangdong 510632, China.
authors.forename: Mei
authors.initials: M
authors.lastname: Li
authors.affiliation: South China Institute of Environmental Sciences, MEP, Guangzhou 510655, China.
authors.forename: Ling'ai
authors.initials: L
authors.lastname: Yao
authors.affiliation: Guangzhou Hexin Analytical Instrument Company Limited, Guangzhou 510530, China.
authors.forename: Bo
authors.initials: B
authors.lastname: Huang
authors.affiliation: State Joint Key Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China. Electronic address: mzheng@pku.edu.cn.
authors.forename: Mei
authors.initials: M
authors.lastname: Zheng
keywords: Composition; Guangzhou; SPAMS; Single particle; Source apportionment