Articles | Volume 19, issue 10
https://doi.org/10.5194/gmd-19-4601-2026
https://doi.org/10.5194/gmd-19-4601-2026
Model description paper
 | 
28 May 2026
Model description paper |  | 28 May 2026

S2AS v1.0 and 2D polarity–volatility lumping framework v1.0: automated compound classification and scalable lumping for organic aerosol modelling

Dalrin Ampritta Amaladhasan, Dan Hassan-Barthaux, and Andreas Zuend

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Cited articles

Allen, F., Pon, A., Greiner, R., and Wishart, D.: Computational prediction of electron ionization mass spectra to assist in GC/MS compound identification, Anal. Chem., 88, 7689–7697, 2016. a
Amaladhasan, D. A. and Zuend, A.: 2D polarity–volatility lumping framework, Zenodo [code], https://doi.org/10.5281/zenodo.18968224, 2026a. a
Amaladhasan, D. A. and Zuend, A.: SMILES to AIOMFAC subgroups (S2AS) tool, Zenodo [code], https://doi.org/10.5281/zenodo.18968164, 2026b. a
Amaladhasan, D. A., Zuend, A., and Hassan-Barthaux, D.: Alpha-pinene and Toluene SOA system data used in Amaladhasan et al. for 2D lumping, Zenodo [data set], https://doi.org/10.5281/zenodo.17088390, 2026. a
Armeli, G., Peters, J.-H., and Koop, T.: Machine-Learning-Based Prediction of the Glass Transition Temperature of Organic Compounds Using Experimental Data, ACS Omega, 8, 12298–12309, https://doi.org/10.1021/acsomega.2c08146, 2023. a
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Short summary
A 2-dimensional polarity–volatility framework is introduced. It enables the automated characterization of thousands of organics and their systematic lumping into adjustable sets of surrogate components. A new polarity metric based on an activity coefficient ratio is presented for use in this framework. A related molecule substructure parsing tool for input file generation is introduced. This framework enables reduced-complexity representations of near-explicit organic aerosol systems.
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