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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Discussion papers | Copyright
https://doi.org/10.5194/amt-2018-362
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 17 Oct 2018

Research article | 17 Oct 2018

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This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).

Understanding of atmospheric aerosol particles with improved particle identification and quantification by single particle mass spectrometry

Xiaoli Shen1,2, Harald Saathoff1, Wei Huang1,2, Claudia Mohr1,3, Ramakrishna Ramisetty1,a, and Thomas Leisner1,4 Xiaoli Shen et al.
  • 1Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
  • 2Institute of Geography and Geoecology, Working Group for Environmental Mineralogy and Environmental System Analysis, Karlsruhe Institute of Technology, Kaiserstr. 12, 76131 Karlsruhe, Germany
  • 3Department of Environmental Science and Analytical Chemistry, Stockholm University, Stockholm, 11418, Sweden
  • 4Institute of Environmental Physics, University Heidelberg, In Neuenheimer Feld 229, 69120 Heidelberg, Germany
  • anow at: TSI Instruments India Private Limited, Bangalore, 560102, India

Abstract. Single particle mass spectrometry (SPMS) is a useful, albeit not fully quantitative tool to determine chemical composition and mixing state of aerosol particles in the atmosphere. During a six-week field campaign in summer 2016 at a rural site in the upper Rhine valley near Karlsruhe city in southwest Germany, ~3.7 x 105 single particles were analyzed by a laser ablation aerosol particle time-of-flight mass spectrometer (LAAPTOF). Combining fuzzy classification, marker peaks, typical peak ratios, and laboratory-based reference spectra, seven major particle classes were identified. With the precise identification and well characterized overall detection efficiency (ODE) for this instrument, particle similarity can be transferred into corrected number fractions and further transferred into mass fractions. Considering the entire measurement period, Potassium rich and aromatics coated dust (class 5) dominated the particle number (46.5% number fraction) and mass (36.0% mass fraction); Sodium salts like particles (class 3) were the second lowest in number (3.5%), but the second dominating class in terms of particle mass (25.3%). This difference demonstrates the crucial role of particle mass quantification for SPMS data. Using corrections for maximum, mean, and minimum ODE, the total mass of the quantified particles measured by LAAPTOF accounts for ~12%, ~25%, and ~104% of the total mass measured by an aerosol mass spectrometer (AMS) with a collection efficiency of 0.5. These two mass spectrometers show a good correlation (correlation coefficient γ > 0.6) regarding total mass for more than 70% of the measurement time, indicating non-refractory species measured by AMS might originate from particles consisting of internally mixed non-refractory and refractory components. In addition, specific relationships of LAAPTOF ion intensities and AMS mass concentrations for non-refractory compounds were found for specific measurement periods. Furthermore, our approach allows for the first time to assign the non-refractory compounds measured by AMS to different particle classes. Overall AMS-nitrate was mainly arising from class 3, while class 5 was dominant during events rich in organic aerosol particles.

Xiaoli Shen et al.
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Based on single particle mass spectra from field measurements in the upper Rhine valley we identified characteristic particle classes, estimated their mass contributions, and achieved a better understanding of the mixing state of ambient aerosol particles. Our study opens a new way for quantitative interpretation of single particle data by comparison with complimentary bulk measurements.
Based on single particle mass spectra from field measurements in the upper Rhine valley we...
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