An algorithm for automatic fitting and formula assignment in atmospheric mass spectra

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Publicado en:Atmospheric Measurement Techniques vol. 18, no. 7 (2025), p. 1537
Autor principal: Mickwitz, Valter
Otros Autores: Peräkylä, Otso, Graeffe, Frans, Worsnop, Douglas, Ehn, Mikael
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Copernicus GmbH
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Acceso en línea:Citation/Abstract
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024 7 |a 10.5194/amt-18-1537-2025  |2 doi 
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100 1 |a Mickwitz, Valter  |u Institute for Atmospheric and Earth System Research, University of Helsinki, Helsinki 00014, Finland 
245 1 |a An algorithm for automatic fitting and formula assignment in atmospheric mass spectra 
260 |b Copernicus GmbH  |c 2025 
513 |a Journal Article 
520 3 |a Mass spectrometry is an established method for studying the chemical composition of gases and particles in the atmosphere. Using this technique, signals corresponding to thousands or even tens of thousands of compounds may be detected from ambient air. The process of identifying all the peaks in the mass spectra is often arduous and time-consuming, in particular when multiple overlapping peaks are present. This manual peak fitting and identification may take even experienced analysts anywhere from weeks to months to complete, depending on the desired accuracy and completeness.In this work, we attempted to automate the fitting and formula assignment workflow and evaluate how far the process can get using a “one-button” algorithm. The algorithm constructed in this work takes in commonly known parameters specific to the instrument type, and by pressing one button it runs and ultimately provides a list of likely peaks for the mass spectrum. The algorithm utilizes weighted-least-squares fitting and a modified version of the Bayesian information criterion along with an iterative formula assignment process. We applied it to synthetic mass spectra and both a gas-phase chemical-ionization mass spectrometer (CIMS) dataset and an aerosol mass spectrometer (AMS) dataset. The results were largely comparable with manual peak fitting and identification done previously but were achieved in a fraction of the time. Erroneous assignments mainly appeared at low-intensity signals, with interference from nearby higher-intensity signals, a case that is challenging also for manual peak fitting. This algorithm provides an excellent starting point for a peak list, which, if needed, can be manually revised.The main result of this study is the algorithm itself. While further improvements and tweaks are possible, the algorithm presented here is currently being implemented into the commonly used Tofware analysis software package to allow easy utilization by the broader community. We hope this can save valuable time of researchers for data interpretation rather than data processing and curation. 
653 |a Mass spectrometry 
653 |a Volatile organic compounds--VOCs 
653 |a Data processing 
653 |a Data interpretation 
653 |a Spectra 
653 |a Datasets 
653 |a Ionization 
653 |a Algorithms 
653 |a Mass spectrometers 
653 |a Workflow 
653 |a Chemical composition 
653 |a Data analysis 
653 |a Mass spectra 
653 |a Chemistry 
653 |a Mass spectroscopy 
653 |a Automation 
653 |a Bayesian analysis 
653 |a Probability theory 
653 |a Environmental 
700 1 |a Peräkylä, Otso  |u Institute for Atmospheric and Earth System Research, University of Helsinki, Helsinki 00014, Finland 
700 1 |a Graeffe, Frans  |u Institute for Atmospheric and Earth System Research, University of Helsinki, Helsinki 00014, Finland 
700 1 |a Worsnop, Douglas  |u Institute for Atmospheric and Earth System Research, University of Helsinki, Helsinki 00014, Finland; Aerodyne Research Inc., 45 Manning Road, Billerica, Massachusetts 01821, USA 
700 1 |a Ehn, Mikael  |u Institute for Atmospheric and Earth System Research, University of Helsinki, Helsinki 00014, Finland 
773 0 |t Atmospheric Measurement Techniques  |g vol. 18, no. 7 (2025), p. 1537 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3185498909/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3185498909/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3185498909/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch