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

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

doi:10.5194/gmd-19-4601-2026

Articles | Volume 19, issue 10

https://doi.org/10.5194/gmd-19-4601-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-19-4601-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 10

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

Download

Final revised paper (published on 28 May 2026)
Supplement to the final revised paper
Preprint (discussion started on 30 Jan 2026)
Supplement to the preprint

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2025-4673', Anonymous Referee #1, 11 Mar 2026

General Comments
This paper is a foundational work for developing tools to benefit organic aerosol numerical modelling. It is a very well written manuscript which walks the line nicely between providing enough detail to understand the tools developed but not so much that the paper becomes a technical document. The description also discusses prior work and how they built upon it. The tools developed will be helpful to the community in developing simplified SOA mechanisms for a whole suite of precursors. I recommend the manuscript be published with minimal technical changes outlined below.
Specific Comments
- The paper is a little redundant in spots and thus could be shortened (e.g., line 362).
- It would be helpful to provide the reader with an approximate conversion from saturation vapor pressures (in Pa) to the C* variable (in ug/m3) that is common in literature for VBS. I know this depends on molecular weight. I assumed a 200 g/mol molecular weight and used gas law to create an equivalent scale to help me interpret the figures. Maybe the authors could consider labeling an upper x-axis with C* assuming an average molecular weight.
- The clustering algorithm seems like a novel approach with solid results. Even the simplified topologies give reasonable errors.
- I have one recommendation. I am wondering if the authors could create and additional table with results from a 1x3 parameter space. Where the 3 separates mass between water soluble, partially water soluble and water insoluble. Can the authors calculate the fraction of product mass and average ACR in these 3 bins for the two precursors (toluene, a-pinene)? Or if the readers feel more appropriate using 4 polarity bins to better resolve partial solubility space. I think this info would be very helpful to constrain chemical transport models. Most chemical transport models only resolve the 1D volatility space. Or maybe the mass concentration data from Figures 8b and 10b can be provided in tables so that readers could manipulate data to their model needs.
Technical Correction
- Please check the grammar on line 351 after words "activity coefficients ..."

Citation: https://doi.org/10.5194/egusphere-2025-4673-RC1
- AC2: 'Reply on RC1', Andreas Zuend, 20 Apr 2026
  
  see attachment
  
  Citation: https://doi.org/10.5194/egusphere-2025-4673-AC2
CEC1:
'Comment on egusphere-2025-4673 - No compliance with the policy of the journal', Juan Antonio Añel, 11 Mar 2026

Dear authors,
Unfortunately, after checking your manuscript, it has come to our attention that it does not comply with our "Code and Data Policy".
https://www.geoscientific-model-development.net/policies/code_and_data_policy.html
You have archived the code necessary to perform your study mostly on GitHub, and also in some other sites that you cite. However, GitHub is not a suitable repository for scientific publication. GitHub itself instructs authors to use other long-term archival and publishing alternatives, such as Zenodo. Most of the sites that you list do not fulfil GMD’s requirements for a persistent data archive because:
- They do not appear to have a published policy for data preservation over many years or decades (some flexibility exists over the precise length of preservation, but the policy must exist).

- They do not appear to have a published mechanism for preventing authors from unilaterally removing material. Archives must have a policy which makes removal of materials only possible in exceptional circumstances and subject to an independent curatorial decision,

- They do not appear to issue a persistent identifier such as a DOI or Handle for each precise dataset.
If we have missed a published policy which does in fact address this matter satisfactorily, please post a response linking to it. If you have any questions about this issue, please post them in a reply.
The GMD review and publication process depends on reviewers and community commentators being able to access, during the discussion phase, the code and data on which a manuscript depends, and on ensuring the provenance of replicability of the published papers for years after their publication. Please, therefore, publish your code and data in one of the appropriate repositories and reply to this comment with the relevant information (link and a permanent identifier for it (e.g. DOI)) as soon as possible. We cannot have manuscripts under discussion that do not comply with our policy.
The 'Code and Data Availability’ section must also be modified to cite the new repository locations, and corresponding references added to the bibliography.
I must note that if you do not fix this problem, we cannot continue with the peer-review process or accept your manuscript for publication in GMD.
Juan A. Añel

Geosci. Model Dev. Executive Editor

Citation: https://doi.org/10.5194/egusphere-2025-4673-CEC1
- AC1:
  'Reply on CEC1', Andreas Zuend, 11 Mar 2026
  Thank you for pointing out the non-compliance of our original code and data availability section with the GMD journal's Code and Data Policy.
  
  Our intent was to add the Zenodo-archived versions of the introduced models as part of the final article version. However, we now understand that GMD requires such archived versions already with the preprint. Accordingly, we have revised the manuscript text und references and provide now Zenodo archives and pertaining links for the S2AS model as well as the 2D polarity–volatility framework, both referring to the exact model versions used to generated the data and findings in the manuscript. Zenodo archives for the exact UManSysProp code used as well as the data underlying all the figures and tables were already part of the original preprint submission. We further clarify, with added citations, that the Master Chemical Mechanism and related AtChem model are third-party software.
  The revised code and data availability section reads as follows:
  Code and data availability. The current Python code of the S2AS model and related documentation are available via an online code repository (https://github.com/andizuend/S2AS__SMILES_to_AIOMFAC) under the GNU General Public License v3.0. The exact version of the S2AS model (v1.0) applied to produce the results used in this article is archived on Zenodo under https://doi.org/10.5281/zenodo.18968164(Amaladhasan and Zuend, 2026b). The current Fortran code of the 2D polarity–volatility framework as well as an associated plotting program and documentation are available via an online repository (https://github.com/andizuend/2D_Polarity_Volatility_lumping) under the GNU General Public License v3.0. The exact version of this framework (v1.0) applied to produce the results used in this article is archived on Zenodo under https://doi.org/10.5281/zenodo.18968224 (Amaladhasan and Zuend, 2026a). The UManSysProp code (v1.0) by Topping et al. (2016a) is available via an online code repository (https://github.com/loftytopping/UManSysProp_public; last access: 18 September 2025). The specific version of the used UManSysProp code, including the adaptations for temperature-dependent pure-component vapour pressure parameterizations used in this work, is archived on Zenodo under https://doi.org/10.5281/zenodo.17172675 (Zuend et al., 2025). The Master Chemical Mechanism (v3.3.1) (Jenkin et al., 1997; Saunders et al., 2003; Jenkin et al., 2003) and the related AtChem online box model are available online via https://mcm.york.ac.uk/MCM/ (last access: 18 September 2025). Predicted SOA mass concentrations and hygroscopicity parameters for various surrogate methods and polarity metrics used in this article are summarized in the electronic Supplement. The data underlying the shown figures and tables, as well as related output from the property prediction tools and the 2D lumping framework, are archived on Zenodo under https://doi.org/10.5281/zenodo.17088391 (Amaladhasan et al., 2025).
  The manuscript's list of references now includes the following entries (the first two are new additions):
  Amaladhasan, D. A. and Zuend, A.: 2D polarity–volatility lumping framework, https://doi.org/10.5281/zenodo.18968224, 2026a.
  
  Amaladhasan, D. A. and Zuend, A.: SMILES to AIOMFAC subgroups (S2AS) tool, https://doi.org/10.5281/zenodo.18968164, 2026b.
  
  Amaladhasan, D. A., Zuend, A., and Hassan-Barthaux, D.: Alpha-pinene and Toluene SOA System data used in Amaladhasan et al for 2D lumping, https://doi.org/10.5281/zenodo.17088391, data set, 2025.
  
  Zuend, A., Hassan-Barthaux, D., and Amaladhasan, D. A.: SMILES_to_sat_vapour_pressure, https://doi.org/10.5281/zenodo.17172675, 2025.
  
  Citation: https://doi.org/10.5194/egusphere-2025-4673-AC1
  - CEC2: 'Reply on AC1', Juan Antonio Añel, 12 Mar 2026
    
    Dear authors,
    Many thanks for addressing this matter so quickly. With the new Code and Data Availability section we can consider the current version of your manuscript in compliance with the policy of the journal.
    Juan A. Añel
    Geosci. Model Dev. Executive Editor
    
    Citation: https://doi.org/10.5194/egusphere-2025-4673-CEC2
RC2:
'Comment on egusphere-2025-4673', Anonymous Referee #2, 17 Mar 2026

The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2025-4673/egusphere-2025-4673-RC2-supplement.pdf

Citation: https://doi.org/10.5194/egusphere-2025-4673-RC2
- AC3: 'Reply on RC2', Andreas Zuend, 20 Apr 2026
  
  see attachment
  
  Citation: https://doi.org/10.5194/egusphere-2025-4673-AC3

Peer review completion

AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload

AR by Andreas Zuend on behalf of the Authors (24 Apr 2026) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (05 May 2026) by Christoph Knote

RR by Anonymous Referee #2 (05 May 2026)

RR by Anonymous Referee #1 (11 May 2026)

ED: Publish as is (11 May 2026) by Christoph Knote

AR by Andreas Zuend on behalf of the Authors (11 May 2026) Manuscript

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.

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

Download

Interactive discussion

Peer review completion

Suggestions for revision or reasons for rejection