Articles | Volume 20, issue 4
https://doi.org/10.5194/acp-20-2489-2020
https://doi.org/10.5194/acp-20-2489-2020
Research article
 | 
02 Mar 2020
Research article |  | 02 Mar 2020

A robust clustering algorithm for analysis of composition-dependent organic aerosol thermal desorption measurements

Ziyue Li, Emma L. D'Ambro, Siegfried Schobesberger, Cassandra J. Gaston, Felipe D. Lopez-Hilfiker, Jiumeng Liu, John E. Shilling, Joel A. Thornton, and Christopher D. Cappa

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Cited articles

Abdalmogith, S. S. and Harrison, R. M.: The use of trajectory cluster analysis to examine the long-range transport of secondary inorganic aerosol in the UK, Atmos. Environ., 39, 6686–6695, https://doi.org/10.1016/j.atmosenv.2005.07.059, 2005. 
Beddows, D. C. S., Dall'Osto, M., and Harrison, R. M.: Cluster Analysis of Rural, Urban, and Curbside Atmospheric Particle Size Data, Environ. Sci. Technol., 43, 4694–4700, https://doi.org/10.1021/es803121t, 2009. 
Cape, J. N., Methven, J., and Hudson, L. E.: The use of trajectory cluster analysis to interpret trace gas measurements at Mace Head, Ireland, Atmos. Environ., 34, 3651–3663, https://doi.org/10.1016/S1352-2310(00)00098-4, 2000. 
Cappa, C. D., Li, Z., D'Ambro, E. L., Schobesberger, S., Shilling, J. E., Lopez-Hilfiker, F., Liu, J., Gaston, C. J., and Thornton, J. A.: Initial application of the noise-sorted scanning clustering algorithm to the analysis of composition-dependent organic aerosol thermal desorption measurements, UC Davis Dash, Dataset, https://doi.org/10.25338/B87S43, 2019. 
D'Ambro, E. L., Lee, B. H., Liu, J., Shilling, J. E., Gaston, C. J., Lopez-Hilfiker, F. D., Schobesberger, S., Zaveri, R. A., Mohr, C., Lutz, A., Zhang, Z., Gold, A., Surratt, J. D., Rivera-Rios, J. C., Keutsch, F. N., and Thornton, J. A.: Molecular composition and volatility of isoprene photochemical oxidation secondary organic aerosol under low- and high-NOx conditions, Atmos. Chem. Phys., 17, 159–174, https://doi.org/10.5194/acp-17-159-2017, 2017. 
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We discuss the development and application of a robust clustering method for the interpretation of compound-specific organic aerosol thermal desorption profiles. We demonstrate the utility of clustering for analysis and interpretation of the composition and volatility of secondary organic aerosol. We show that the thermal desorption profiles are represented by only 9–13 distinct clusters, with the number of clusters obtained dependent on the precursor and formation conditions.
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