Articles | Volume 20, issue 4
Atmos. Chem. Phys., 20, 2489–2512, 2020
https://doi.org/10.5194/acp-20-2489-2020
Atmos. Chem. Phys., 20, 2489–2512, 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 et al.

Data sets

Initial application of the noise-sorted scanning clustering algorithm to the analysis of composition-dependent organic aerosol thermal desorption measurements C. D. Cappa, Z. Li, E. L. D'Ambro, S. Schobesberger, J. E. Shilling, F. Lopez-Hilfiker, J. Liu, C. J. Gaston, and J. A. Thornton https://doi.org/10.25338/B87S43

Model code and software

Noise Sorted Scanning Clustering Algorithm Z. Li and C. D. Cappa https://doi.org/10.5281/zenodo.3361797

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Short summary
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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