Articles | Volume 17, issue 6
https://doi.org/10.5194/amt-17-1811-2024
https://doi.org/10.5194/amt-17-1811-2024
Research article
 | 
28 Mar 2024
Research article |  | 28 Mar 2024

Application of fuzzy c-means clustering for analysis of chemical ionization mass spectra: insights into the gas phase chemistry of NO3-initiated oxidation of isoprene

Rongrong Wu, Sören R. Zorn, Sungah Kang, Astrid Kiendler-Scharr, Andreas Wahner, and Thomas F. Mentel

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Cited articles

Äijälä, M., Heikkinen, L., Fröhlich, R., Canonaco, F., Prévôt, A. S. H., Junninen, H., Petäjä, T., Kulmala, M., Worsnop, D., and Ehn, M.: Resolving anthropogenic aerosol pollution types – deconvolution and exploratory classification of pollution events, Atmos. Chem. Phys., 17, 3165–3197, https://doi.org/10.5194/acp-17-3165-2017, 2017. 
Albrecht, S. R., Novelli, A., Hofzumahaus, A., Kang, S., Baker, Y., Mentel, T., Wahner, A., and Fuchs, H.: Measurements of hydroperoxy radicals (HO2) at atmospheric concentrations using bromide chemical ionisation mass spectrometry, Atmos. Meas. Tech., 12, 891–902, https://doi.org/10.5194/amt-12-891-2019, 2019. 
Arora, J., Khatter, K., and Tushir, M.: Fuzzy c-means clustering strategies: A review of distance measures, in: Software Engineering. Advances in Intelligent Systems and Computing, edited by: Hoda, M., Chauhan, N., Quadri, S., and Srivastava, P., Springer, Singapore. Vol. 731 https://doi.org/10.1007/978-981-10-8848-3_15, 2019. 
Berndt, T., Scholz, W., Mentler, B., Fischer, L., Herrmann, H., Kulmala, M., and Hansel, A.: Accretion Product Formation from Self- and Cross-Reactions of RO2 Radicals in the Atmosphere, Angew. Chem. Int. Edit., 57, 3820–3824, https://doi.org/10.1002/anie.201710989, 2018. 
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Short summary
Recent advances in high-resolution time-of-flight chemical ionization mass spectrometry (CIMS) enable the detection of highly oxygenated organic molecules, which efficiently contribute to secondary organic aerosol. Here we present an application of fuzzy c-means (FCM) clustering  to deconvolve CIMS data. FCM not only reduces the complexity of mass spectrometric data but also the chemical and kinetic information retrieved by clustering gives insights into the chemical processes involved.