中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Molecular characterization of dissolved organic matters in winter atmospheric fine particulate matters (PM2.5) from a coastal city of northeast China

文献类型:期刊论文

作者Ning, Cuiping1,2; Gao, Yuan1; Zhang, Haijun1; Yu, Haoran1,2; Wang, Lei3; Geng, Ningbo1; Cao, Rong1; Chen, Jiping1
刊名SCIENCE OF THE TOTAL ENVIRONMENT
出版日期2019-11-01
卷号689页码:312-321
ISSN号0048-9697
关键词PM2.5 DOMs FT-ICR MS Molecular characteristic
DOI10.1016/j.scitotenv.2019.06.418
通讯作者Gao, Yuan(acyoyo@dicp.ac.cn)
英文摘要Dissolved organic matters (DOM5) in fine particulate matters (PM2.5) play a crucial role in global climate change and carbon cycle. However, the chemical components of DOMs are poorly understood due to its ultra-complexity. In this study, DOM5 in atmospheric PM2.5 collected during the heating period in coastal city Dalian were analyzed with ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometer, and the molecular composition was characterized. A large number of monoisotopic molecular formulas were assigned to DOM5, which could be classified into CHO, CHNO, CHOS, and CHNOS subgroups. A total 014228 molecular formulas were identified in DOM5 collected in hazy days, while only 2313 components were found in DOM5 collected in normal days. CHO group was the dominated components in normal days, whereas CHNO group gave significantly higher contributions in hazy days. The S-containing (CHOS and CHNOS) groups posed the highest relative percentages in both normal and hazy days. In addition, potential emission sources were discussed according to the chemical component analysis. The van Kreve lent diagram illustrated that lignin-like and protein amino sugar family species were the most abundant subclasses in DOMs; and 78% and 94% of DOMs in atmospheric PM2.5 collected from Dalian could come from biogenic origins in hazy and normal days, respectively. More compounds in hazy days were derived from anthropogenic emissions. (C) 2019 Elsevier B.V. All rights reserved.
WOS关键词RESONANCE MASS-SPECTROMETRY ; HUMIC-LIKE SUBSTANCES ; FT-ICR-MS ; COMPREHENSIVE CHARACTERIZATION ; PINENE OZONOLYSIS ; AEROSOL ; WATER ; ORGANOSULFATES ; ELECTROSPRAY ; CARBON
资助项目National Natural Science Foundation of China[91643104] ; National Natural Science Foundation of China[21607152] ; National Natural Science Foundation of China[91543201]
WOS研究方向Environmental Sciences & Ecology
语种英语
出版者ELSEVIER
WOS记录号WOS:000482379400030
资助机构National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China
源URL[http://cas-ir.dicp.ac.cn/handle/321008/173107]  
专题大连化学物理研究所_中国科学院大连化学物理研究所
通讯作者Gao, Yuan
作者单位1.Chinese Acad Sci, Dalian Inst Chem Phys, CAS Key Lab Separat Sci Analyt Chem, Dalian 116023, Liaoning, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Nankai Univ, Minist Educ, Key Lab Pollut Proc & Environm Criteria, Tianjin Key Lab Environm Remediat & Pollut Contro, Tianjin 300071, Peoples R China
推荐引用方式
GB/T 7714
Ning, Cuiping,Gao, Yuan,Zhang, Haijun,et al. Molecular characterization of dissolved organic matters in winter atmospheric fine particulate matters (PM2.5) from a coastal city of northeast China[J]. SCIENCE OF THE TOTAL ENVIRONMENT,2019,689:312-321.
APA Ning, Cuiping.,Gao, Yuan.,Zhang, Haijun.,Yu, Haoran.,Wang, Lei.,...&Chen, Jiping.(2019).Molecular characterization of dissolved organic matters in winter atmospheric fine particulate matters (PM2.5) from a coastal city of northeast China.SCIENCE OF THE TOTAL ENVIRONMENT,689,312-321.
MLA Ning, Cuiping,et al."Molecular characterization of dissolved organic matters in winter atmospheric fine particulate matters (PM2.5) from a coastal city of northeast China".SCIENCE OF THE TOTAL ENVIRONMENT 689(2019):312-321.

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来源:大连化学物理研究所

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