Size-resolved simulations of the aerosol inorganic composition with the new
hybrid dissolution solver HyDiS-1.0: description, evaluation and first
global modelling results

Benduhn, François; Mann, Graham W.; Pringle, Kirsty J.; Topping, David O.; McFiggans, Gordon; Carslaw, Kenneth S.

doi:https://doi.org/10.5194/gmd-9-3875-2016

Articles | Volume 9, issue 11

https://doi.org/10.5194/gmd-9-3875-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/gmd-9-3875-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 9, issue 11

Model description paper

|

01 Nov 2016

Model description paper |

| 01 Nov 2016

Size-resolved simulations of the aerosol inorganic composition with the new hybrid dissolution solver HyDiS-1.0: description, evaluation and first global modelling results

François Benduhn, Graham W. Mann, Kirsty J. Pringle, David O. Topping, Gordon McFiggans, and Kenneth S. Carslaw

Download

Final revised paper (published on 01 Nov 2016)
Preprint (discussion started on 17 Feb 2016)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

- Printer-friendly version

- Supplement

RC1: 'Review', Anonymous Referee #1, 30 Mar 2016
- AC1: 'Author reply to reviewer #1', François Benduhn, 18 Jun 2016
RC2: 'Review', Anonymous Referee #2, 22 May 2016
- AC2: 'Reply to reviewer #2', François Benduhn, 18 Jun 2016

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by François Benduhn on behalf of the Authors (18 Jun 2016) Author's response Manuscript

ED: Referee Nomination & Report Request started (28 Jun 2016) by Holger Tost

RR by Anonymous Referee #1 (09 Jul 2016)

RR by Anonymous Referee #2 (29 Jul 2016)

Suggestions for revision or reasons for rejection

I thank the authors for clarifying a few things in the revised manuscript. However, my main concerns were only superficially addressed. The manuscript continues to be difficult to understand and the core issues regarding accuracy and efficiency still remain unresolved. As a result, I cannot recommend publication in GMD, unfortunately.

Major Comments

1) Figure 1. Thanks for clarifying the confusion surrounding Figure 1, but I am still not sure I fully understand it. In the caption it says that the initial aerosol is monodisperse with a dry radius of 50 nm, the RH = 80% and the aqueous phase contains no dissolved species. So is this a pure water droplet at 80% RH? How is this even possible, and what is the dry particle made up of?

2) There appears to be something wrong in the predicted NH4 concentrations in Figure 5. According to the initial conditions given in the manuscript, I estimated about 9.2e-4 ppb of SO4 in the Aitken bin and about 0.023 ppb of SO4 in both the accumulation and coarse bins. Assuming the NO3 predictions are correct, then NH4 in the Aitken bin should not exceed 0.00184 ppb and about 0.046 ppb in the accumulation and coarse bins, which correspond to full neutralization of SO4. Instead, the predicted values (by TRANS, HYBR, and PSEUDO) in the manuscript are 10 times higher.

3) The predictions by EQUIL model also do not make sense in Fig 5-7. All the bins should have the same NH4/SO4 and NO3/SO4 ratios at equilibrium (ignoring the Kelvin effect for the nucleation bin). In other words, all the bins should have the same fractional composition at equilibrium. Since accumulation and coarse bins have the same amount of H2SO4 initially, they should have identical NH4 and NO3 concentrations at equilibrium. However, the EQUIL predictions in the manuscript are not at all consistent with this expectation.

4) Quite large discrepancies are seen between TRANS (used as benchmark) and HYBR or PSEUDO are seen in Fig 9 for all species, but especially for Cl in the coarse bin. Moreover, no proper evaluation of the HYBR/PSEUDO models against a benchmark was shown for the high concentration cases (Fig. 7 and 10).

5) Independent confirmation of both time evolution and equilibrium results are needed for all figures (1-10) to have any confidence in the dynamic model used by authors as benchmark. I also strongly suggest including additional monodisperse cases (similar to Fig 1) to clearly show that the dynamic models match the equilibrium predictions by an independent benchmark such as AIM.

6) With the above discrepancies and errors in the dynamic and equilibrium predictions, it is difficult to make claims about computational efficiency. As I said in my previous review, any model can be made fast by sacrificing its accuracy. The authors have argued against doing a proper evaluation of speed vs. accuracy and comparison with existing models in the literature. As a result, the revised manuscript continues to be very weak in this area and their claim that their proposed solver is efficient has not been properly demonstrated.

7) Finally, for the new solver to be worthy of publication it must have reasonable applicability and longevity. As it currently stands, it does not handle mass transfer coupled with phase transition and heterogeneous reactions. So the question is will this solver still work when these missing processes are included?

8) It’s still not clear what the “passive” anions and cations mean? Please, just give an actual list of all the ions (and their designations – active, passive, etc.) in a Table.

Hide

ED: Reconsider after major revisions (01 Aug 2016) by Holger Tost

AR by Svenja Lange on behalf of the Authors (14 Sep 2016) Author's response

ED: Referee Nomination & Report Request started (16 Sep 2016) by Holger Tost

RR by Anonymous Referee #2 (28 Sep 2016)

ED: Publish subject to minor revisions (Editor review) (29 Sep 2016) by Holger Tost

AR by François Benduhn on behalf of the Authors (05 Oct 2016) Author's response Manuscript

ED: Publish as is (07 Oct 2016) by Holger Tost

Short summary

We present a new mathematical formalism that serves to represent exchanges of inorganic matter between the atmosphere gas phase and the aerosol aqueous phase. In a global modelling framework, taking into account these processes may help represent many important features more accurately, such as the formation of cloud droplets or the radiative properties of the atmosphere. The formalism strives to keep an appropriate balance between accuracy and computation efficiency requirements.