4.5 Article

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

Journal

ATMOSPHERIC MEASUREMENT TECHNIQUES
Volume 14, Issue 3, Pages 2377-2387

Publisher

COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/amt-14-2377-2021

Keywords

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Funding

  1. European Research Council (ERC-StG MAARvEL) [852161]
  2. European Research Council (ERC-StG CHAPAs) [850614]
  3. National Key R&D Program of China [2016YFC0200104, 2018YFC0213800]
  4. Academy of Finland [332547]
  5. French national program LEFE (Les Enveloppes Fluides et l'Environnement)
  6. Academy of Finland (AKA) [332547, 332547] Funding Source: Academy of Finland (AKA)
  7. European Research Council (ERC) [852161, 850614] Funding Source: European Research Council (ERC)

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The Orbitrap mass spectrometer is a powerful tool for measuring organic compounds, and the open-source software tool Orbitool facilitates the analysis of long-term data, improving mass accuracy, assigning molecular formulae, and reducing noise. Tests with laboratory and ambient data showed Orbitool's ability to automatically assign molecular formulae with high accuracy.
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, https://orbitrap.catalyse.cnrs.fr, last access: 4 February 2021) to facilitate the analysis of long-term online Orbitrap data. Orbitool can average long-term data while improving the mass accuracy by re-calibrating each mass spectrum, assign molecular formulae of compounds and their isotopes to measured signals, and export time series and mass defect plots. The noise reduction procedure in Orbitool can separate signal peaks from noise and 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 test Orbitool. For the test dataset, the average mass accuracy was improved from < 2 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, substantially helping the automatic assignment of unknown species. To illustrate the capabilities of Orbitool, we used the most challenging and complex dataset we have collected so far, which consists of ambient gas-phase measurements in urban Shanghai. These tests showed that Orbitool was able to automatically assign hundreds of molecular formulae as well as their isotopes with high accuracy.

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