Articles | Volume 18, issue 19
https://doi.org/10.5194/gmd-18-6737-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.Evaluation of ozone and its precursors using the Multi-Scale Infrastructure for Chemistry and Aerosols Version 0 (MUSICAv0) during the Michigan–Ontario Ozone Source Experiment (MOOSE)
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- Final revised paper (published on 02 Oct 2025)
- Supplement to the final revised paper
- Preprint (discussion started on 14 Feb 2025)
- Supplement to the preprint
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Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
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RC1: 'Comment on egusphere-2025-228', Anonymous Referee #1, 26 Mar 2025
- AC1: 'Reply on RC1', Noribeth Mariscal, 27 Jun 2025
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RC2: 'Comment on egusphere-2025-228', Anonymous Referee #2, 28 Mar 2025
- AC2: 'Reply on RC2', Noribeth Mariscal, 27 Jun 2025
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AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Noribeth Mariscal on behalf of the Authors (27 Jun 2025)
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ED: Publish subject to technical corrections (15 Jul 2025) by Fiona O'Connor

AR by Noribeth Mariscal on behalf of the Authors (16 Jul 2025)
Author's response
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The manuscript analyzes the distribution of ozone and some of its precursors over the Southeast Michigan (SEMI) region during summer 2021 based on model simulations with MUSICAv0 and observations from the MOOSE filed campaign. The authors discuss the impact of grid resolution and diurnal cycle of anthropogenic NO emissions and show that night-time ozone is mostly improved by applying diurnal cycles for NO emissions, while grid resolution is found to have more impact on ozone precursors. The study also shows that using a good conceptualization of grid resolution within MUISCAv0, with finer resolution could lead to more efficient computational costs, which could be beneficial for other local-scale studies including in other regions.
The paper shows the interesting potential of using global models with zooming capabilities like MUSCIAv0 to investigate air pollution characteristics even at specific small regions like SEMI. Overall, the paper is well structured and easy to read. However, the analysis and discussion sections are in some cases rather short and could be further improved in order to better identify the processes controlling summertime ozone in different parts of the SEMI region.
I recommend the manuscript to be accepted for publication after addressing the following comments and suggestions:
Section 2.1.1: Initial conditions are considered from a restart file based on MOZART-TS1. Which initial conditions are considered for the additional species in TS2 not included in TS1?
Section 2.1.3:
- Anthropogenic emissions are considered from CAMS_GLOB_ANTv5.1. A recent study from Soulie et al. (2024, ESSD) shows significant differences in the estimated emissions between CAMS_GLOB_ANTv5.1 and the EPA inventory in USA. In particular, EPA exhibits higher NMVOCs but lower NOx and SO2 emissions. Can the authors comment on the potential impact of such uncertainties in emissions on the model results?
- It is not clear how soil NOx emissions are considered for the simulations.
- The authors include calculated NO emissions from agriculture waste burning (AWB) in Table S1, but it is not clear if emissions from this sector are considered or not. This could lead to double counting of emissions with QFED, although the contribution of NO AWB emissions seems to be minor compared to other sectors.
Section 2.1.4:
- Can the authors comment why only NO diurnal distribution is considered, while diurnal distribution of other species like VOCs or SO2 could also impact the model results?
- Including a figure showing the diurnal distribution of NO emissions from different sectors, as used in the simulation is a useful information.
Section 3.1:
- This section is rather short and doesn’t fully cover the model’s ability to capture meteorological features in the considered region. In addition to the model evaluation, this section is also expected to contain a description of the meteorological situation that characterized the SEMI/MI region during the campaign period. This section can also be significantly improved by considering other meteorological variables (e.g. wind speed/direction), other networks or datasets (e.g. reanalysis).
Section 3.2:
- The authors could elaborate a bit more the discussion on the reasons behind the diurnal changes in the model bias and link with results in Sect. 4. For this, a map showing location of the stations could be very useful.
- The night-time NO2, in particular between 00 and 05 AM, although improved, remain high and the morning peak is less visible when NO diurnal cycle is applied. The authors should discuss the impact of potential uncertainties in the considered diurnal cycle, including the fact that this was applied only for NO.
Section 3.3:
- The authors relate the differences in simulated isoprene (and hence HCHO?) to potential changes in meteorological field leading to changes in calculated BVOCs. Although this could be true, no results (i.e. changes in metorology) are provided to assess this especially in the discussion in Sect. 3.1.
- Similarly, the discrepancies in other species (hydrocarbons and aromatics) is explained by misrepresentation of their anthropogenic sources in the CAMS inventory. The authors can assess such uncertainties in the considered emissions by comparisons with EPA emissions in SEMI.
Section 3.4:
- The discussion on evaluation of modeled HCHO columns contradicts a bit the conclusion in Section 3.3: the authors say there is a combined effect of grid resolution and application NO diurnal cycle on HCHO (Line 429), whereas Sect. 3.3 states no obvious impact of NO on HCHO in the model (Line 383).
- The section could be improved by discussing the link between the location of the stations/sites and the changes in HCHO (e.g. induced impact from isoprene emissions under different Nox-regimes).
- Like for other Sect. 3 subsections, it would be useful to include the location of the monitoring sites and link the results with those discussed in Sect. 4.
Section 3.5:
- Surface maps for winds, temperature and other meteorological parameters could be added to the Supplement to better understand the conditions during the analyzed days and times.
Section 4:
- The significant changes in isoprene emissions from MEGANv2.1 depending on the grid resolution is linked to the induced changes in meterological parameters. This needs to be supported by maps of meterological fields showing these changes.
- The link between Sect 4. and Sect 3. should be strengthened in either or both sections to better understand what drives the changes in the different sites, locations, etc.
- The discussion section is rather short and could/should be improved by strong arguments on e.g. what controls O3 in different parts of the SEMI region and what mitigation strategies could be adopted to reduce the pollution.