单萜
臭氧分解
化学
泰加语
白天
臭氧
大气化学
大气科学
环境化学
因式分解
气溶胶
大气压化学电离
化学电离
电离
离子
有机化学
生态学
算法
计算机科学
生物
地质学
作者
Chao Yan,Wei Nie,Mikko Äijälä,Matti Rissanen,Manjula R. Canagaratna,P. Massoli,Heikki Junninen,Tuija Jokinen,Nina Sarnela,A. Hamed,Siegfried Schobesberger,Francesco Canonaco,Lei Yao,Andrê S. H. Prévôt,Tuukka Petäjä,Markku Kulmala,Mikko Sipilä,Douglas R. Worsnop,Mikael Ehn
标识
DOI:10.5194/acp-16-12715-2016
摘要
Abstract. Highly oxidized multifunctional compounds (HOMs) have been demonstrated to be important for atmospheric secondary organic aerosols (SOA) and new-particle formation (NPF), yet it remains unclear which the main atmospheric HOM formation pathways are. In this study, a nitrate-ion-based chemical ionization atmospheric-pressure-interface time-of-flight mass spectrometer (CI-APi-TOF) was deployed to measure HOMs in the boreal forest in Hyytiälä, southern Finland. Positive matrix factorization (PMF) was applied to separate the detected HOM species into several factors, relating these “factors” to plausible formation pathways. PMF was performed with a revised error estimation derived from laboratory data, which agrees well with an estimate based on ambient data. Three factors explained the majority (> 95 %) of the data variation, but the optimal solution found six factors, including two nighttime factors, three daytime factors, and a transport factor. One nighttime factor is almost identical to laboratory spectra generated from monoterpene ozonolysis, while the second likely represents monoterpene oxidation initiated by NO3. The exact chemical processes forming the different daytime factors remain unclear, but they all have clearly distinct diurnal profiles, very likely related to monoterpene oxidation with a strong influence from NO, presumably through its effect on peroxy radical (RO2) chemistry. Apart from these five “local” factors, the sixth factor is interpreted as a transport related factor. These findings improve our understanding of HOM production by confirming current knowledge and inspiring future research directions and provide new perspectives on using factorization methods to understand short-lived atmospheric species.
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