气候变化领域集成服务门户(CCPortal): Constructing a data-driven receptor model for organic and inorganic aerosol - A synthesis analysis of eight mass spectrometric data sets from a boreal forest site

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DOI	10.5194/acp-19-3645-2019
	Constructing a data-driven receptor model for organic and inorganic aerosol - A synthesis analysis of eight mass spectrometric data sets from a boreal forest site
	Äijälä M.; Daellenbach K.R.; Canonaco F.; Heikkinen L.; Junninen H.; Petäjä T.; Kulmala M.; Prévôt A.S.H.; Ehn M.
发表日期	2019
ISSN	16807316
起始页码	3645
结束页码	3672
卷号	19 期号:6
英文摘要	The interactions between organic and inorganic aerosol chemical components are integral to understanding and modelling climate and health-relevant aerosol physicochemical properties, such as volatility, hygroscopicity, light scattering and toxicity. This study presents a synthesis analysis for eight data sets, of non-refractory aerosol composition, measured at a boreal forest site. The measurements, performed with an aerosol mass spectrometer, cover in total around 9 months over the course of 3 years. In our statistical analysis, we use the complete organic and inorganic unit-resolution mass spectra, as opposed to the more common approach of only including the organic fraction. The analysis is based on iterative, combined use of (1) data reduction, (2) classification and (3) scaling tools, producing a data-driven chemical mass balance type of model capable of describing site-specific aerosol composition. The receptor model we constructed was able to explain 83±8 % of variation in data, which increased to 96±3 % when signals from low signal-to-noise variables were not considered. The resulting interpretation of an extensive set of aerosol mass spectrometric data infers seven distinct aerosol chemical components for a rural boreal forest site: ammonium sulfate (35±7 % of mass), low and semi-volatile oxidised organic aerosols (27±8 % and 12±7 %), biomass burning organic aerosol (11±7 %), a nitrate-containing organic aerosol type (7±2 %), ammonium nitrate (5±2 %), and hydrocarbon-like organic aerosol (3±1 %). Some of the additionally observed, rare outlier aerosol types likely emerge due to surface ionisation effects and likely represent amine compounds from an unknown source and alkaline metals from emissions of a nearby district heating plant. Compared to traditional, ion-balance-based inorganics apportionment schemes for aerosol mass spectrometer data, our statistics-based method provides an improved, more robust approach, yielding readily useful information for the modelling of submicron atmospheric aerosols physical and chemical properties. The results also shed light on the division between organic and inorganic aerosol types and dynamics of salt formation in aerosol. Equally importantly, the combined methodology exemplifies an iterative analysis, using consequent analysis steps by a combination of statistical methods. Such an approach offers new ways to home in on physicochemically sensible solutions with minimal need for a priori information or analyst interference. We therefore suggest that similar statistics-based approaches offer significant potential for un- or semi-supervised machine-learning applications in future analyses of aerosol mass spectrometric data. © 2019 Author(s).
语种	英语
scopus关键词	aerosol; atmospheric modeling; boreal forest; chemical composition; data set; mass spectrometry; physicochemical property
来源期刊	Atmospheric Chemistry and Physics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/144556
作者单位	Institute for Atmospheric and Earth System Research/Physics, University of Helsinki, Helsinki, Finland; Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen, Switzerland; Laboratory of Environmental Physics, University of Tartu, Tartu, Estonia
推荐引用方式 GB/T 7714	Äijälä M.,Daellenbach K.R.,Canonaco F.,et al. Constructing a data-driven receptor model for organic and inorganic aerosol - A synthesis analysis of eight mass spectrometric data sets from a boreal forest site[J],2019,19(6).
APA	Äijälä M..,Daellenbach K.R..,Canonaco F..,Heikkinen L..,Junninen H..,...&Ehn M..(2019).Constructing a data-driven receptor model for organic and inorganic aerosol - A synthesis analysis of eight mass spectrometric data sets from a boreal forest site.Atmospheric Chemistry and Physics,19(6).
MLA	Äijälä M.,et al."Constructing a data-driven receptor model for organic and inorganic aerosol - A synthesis analysis of eight mass spectrometric data sets from a boreal forest site".Atmospheric Chemistry and Physics 19.6(2019).