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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  12 Aug 2020

12 Aug 2020

Review status
A revised version of this preprint was accepted for the journal AMT.

Orbitool: A software tool for analyzing online Orbitrap mass spectrometry data

Runlong Cai1,, Yihao Li2,3,, Yohann Clément4, Dandan Li5, Clément Dubois5, Marlène Fabre5, Laurence Besson5, Sebastien Perrier5, Christian George5, Mikael Ehn1, Cheng Huang2, Ping Yi3, Yingge Ma2, and Matthieu Riva5 Runlong Cai et al.
  • 1Institute for Atmospheric and Earth System Research/ Physics, Faculty of Science, University of Helsinki, Helsinki, 00140, Finland
  • 2State Environmental Protection Key Laboratory of Formationand Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, 200233, China
  • 3School of Electronic, Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
  • 4Univ Lyon, Université Claude Bernard Lyon 1, CNRS, Institut des Sciences Analytiques, UMR 5280, 5 rue de la Doua, 69100 Villeurbanne, France
  • 5Univ. Lyon, Université Claude Bernard Lyon 1, CNRS, IRCELYON, 69626, Villeurbanne, France
  • These authors contributed equally to this work.

Abstract. The Orbitrap mass spectrometer has recently been proved to be a powerful instrument to accurately measure gas-phase and particle-phase organic compounds with a greater mass resolving power than other widely-used online mass spectrometers in atmospheric sciences. We develop an open-source software tool (Orbitool, to facilitate the analysis of long-term online Orbitrap data. Orbitool can average long-term data while maintaining the mass accuracy by re-calibrating each mass spectrum, identify chemical compositions and isotopes of measured signals, and export time series and mass defect plots. The noise reduction procedure in Orbitool can separate signal peaks from noise and greatly reduce the computational and storage expenses. Chemical-ionization Orbitrap data from laboratory experiments on ozonolysis of monoterpenes and ambient measurements in urban Shanghai were used to successfully test Orbitool. For the test dataset, the average mass accuracy was improved from < 2 ppm to < 0.5 ppm by mass calibrating each spectrum. The denoising procedure removed 97 % of the noise peaks from a spectrum averaged for 30 min while maintaining the signal peaks, greatly helping the automatic identification of unknown species. To illustrate the capabilities of Orbitool, we used the most challenging/complex dataset we have collected so far, which consists of ambient measurements in urban Shanghai. These tests showed that Orbitool was able to automatically separate and identify hundreds of compounds as well as their isotopes with a very high accuracy.

Runlong Cai et al.

Interactive discussion

Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

Runlong Cai et al.

Runlong Cai et al.


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Latest update: 27 Nov 2020
Publications Copernicus
Short summary
Orbitool is an open-source software tool, mainly coded in Python, with a graphical user interface (GUI), specifically developed to facilitate the analysis of online Orbitrap mass spectrometric data. It is notably optimized for long-term atmospheric measurements and laboratory studies.
Orbitool is an open-source software tool, mainly coded in Python, with a graphical user...