the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 20 Mar 2026
HTAP3-OPNS: Ozone, PM, Nitrogen and Sulphur Deposition – multi-model experiments to support the revision of the CLRTAP Gothenburg Protocol
Abstract. HTAP3-OPNS is a multi-model exercise designed to support the revision of the Gothenburg Protocol under the UNECE Convention on Long-Range Transboundary Air Pollution (CLRTAP). Using an ensemble of Chemical Transport Models (CTMs) and Chemistry-Climate Models (CCMs), this study investigates the long-range transport and impacts of ground-level ozone, particulate matter (PM), and nitrogen and sulphur deposition across different global regions. The project aims to assess the contributions of regional versus extra-regional emission sources, evaluate the suitability of current models, and project changes in air pollution under future emission scenarios and climate conditions. A series of perturbation simulations will enable the development of an ensemble emulator to explore and evaluate potential mitigation strategies efficiently. This paper outlines the scientific and policy questions motivating the study, describes the experimental design, including input datasets, model configurations, and required outputs, and discusses methodologies for data handling and analysis. The results will provide crucial insights for policy decisions aiming to improve air quality, protect human health, and protect ecosystems worldwide.
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Status: final response (author comments only)
- AC1: 'Comment on egusphere-2026-1367', Tim Butler, 23 Apr 2026
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RC1: 'Comment on egusphere-2026-1367', Anonymous Referee #1, 26 May 2026
This paper describes the experimental design of a new round of multi-model HTAP experiments aimed at quantifying the long-range contributions to ozone, PM, and the deposition of nitrogen and sulphur in order to inform the upcoming revision of the Gothenburg Protocol. The paper is well written and the described protocols are provided in sufficient detail to support the participation by various modelling groups. It will be exciting to see the results of this effort in light of new foci relative to previous HTAP assessments (especially the consideration for methane, wildfires, source-receptor relationships under future emissions scenarios, and the requirement to archive hourly surface ozone mixing ratios). I recommend publication after addressing a few comments below:
Line 51: Could you include a citation for this statement / the recent review of the GP?
Line 52: Please remove the extra period.
Line 506: Was 2015 a climatologically average year? Could source-receptor coefficients and impact metrics vary strongly from year-to-year due to inter-annual meteorological variability? I understand how it would not be possible to ask the modelling centres to repeat these experiments for multiple meteorological years, but some more justification or discussion of these caveats should be included.
Line 515: It could be nice to include a short description of the major regional differences in anthropogenic and biomass burning emissions between GAINS LRTAP CLE 2040 and GAINS LRTAP CLE 2015. Especially since a major point of this new protocol is the calculation of S-R relationships under future emissions scenarios, how much do we expect these relationships to differ under CLE 2040 relative to CLE 2015?
Line 696: Is it possible that the signal-to-noise ratio under SSP2-4.5 will be too small to quantify a climate penalty by 2050 relative to 2015? Like above, the authors could consider including a brief description of the CO2, CH4, and temperature differences expected under SSP2-4.5 by 2050 relative to 2015.
Citation: https://doi.org/10.5194/egusphere-2026-1367-RC1 -
RC2: 'Comment on egusphere-2026-1367', Anonymous Referee #2, 05 Jun 2026
This manuscript describes the requested model configurations, simulations, and output for the HTAP3-OPNS project and is thus an important contribution worthy of publication. These simulations support the upcoming assessment that will guide revisions of the Gothenburg Protocol under CLRTAP with respect to ozone, particulate matter and deposition of nitrogen and sulphur. The documentation of the modeling protocol is critical, as is clearly laying out the questions that the simulations are designed to answer.
The current version is written more like a technical report than a typical scientific article. While this is reasonable given the need to document the detailed simulations, some editing would help the reader follow how the simulations will deliver science needed to inform the GP. Merging sections avoids both redundancy (handling of agricultural waste burning, initialization) and very short sections.
It is suggested to encourage modeling groups to document many choices left at their discretion (for example lines 227-228, 243, 267-269, 301-303). Collecting this information in a publicly available table or website would facilitate future use and interpretation of the simulations. Suggest adding a request to describe nitrate aerosol and SOA in the models. A new section that includes all requested additional documentation may lower the barrier for modeling groups to deliver it. For example, the request for the machine-readable model chemical mechanism is easy to miss (459-461). This section could follow lines 477-480.
The emphasis of HTAP-O3PNS is heavily slanted towards ozone (Table 2). Seeing as SO2 and NH3 perturbations are not prioritized, how useful are these runs for long-range transport of PM and deposition of S or N?
Section 3
- Given that the emission reference is only to the data files, the impact of this paper would increase by adding figures showing the emissions under these scenarios; even more useful would be to compare them with the SSP2-4.5 so a reader can see they are “broadly consistent”.
- HILO: Since a similar sounding scenario is being used in CMIP7 to indicate high-to-low CO2 emissions (Van Vuuren et al., 2026), the authors might consider renaming to clarify that this is high methane – low air pollution.
Section 4. Seeing as modeling groups and future analysts of the data are most likely to want the details of individual sets of simulations, I suggest removing the overview and instead breaking it into substantive individual sections that include the details (combine 4.2 with 7.4, 4.3 with 7.5, etc) to avoid referring to multiple sections with redundant text.
4.1 Map experiments to Questions in Section 2 and/or emissions in Section 3?
4.2 What specifically is being assessed about the GAINS LRTAP scenarios? How is climate change represented in the scenario design?
4.2 and 7.4.1 The questions driving the recommendations for the Atmosphere-Only runs in Table 4 need to be stated more clearly. Those questions should determine the required specifications. It is not yet clear whether the design will accomplish the intended outcomes. For example, the requested decoupling of composition is confusing given the recommendation that modelers use decadally averaged SSTs and sea ice as in a CMIP6-AMIP configuration. Since the SSTs can’t respond to the radiation scheme in this setup and the SSTs are the dominant driver on the atmospheric climate, why the need to decouple from radiation? If the goal is to force the model to the same meteorology, why not nudge?
4.3 What historical global emission inventory is used? Elaborating on the evaluation plan in 8.2.1 including some discussion of datasets would be helpful. Will COVID period emissions and responses be used as a test of the models?
Section 5. Merge with Section 3 so that a reader can easily find all emissions information?
Section 6. A table to clarify what is needed for the Edwards and Evans (2017) approach would be helpful either here or in the supplemental spreadsheet. Are any idealized tracers (age of air, biomass burning, etc) requested to aid interpretation of the runs?
Section 7:
The organization of this section is confusing. Aren’t the simulations described in section 7.2 a subset of the 14 discussed in 7.1? Why are regional perturbations under global?
Please provide more background on this HTAP3 ensemble emulator. Is it ozone-only? How will it support the GP revision?
How is NOx from fertilizer handled in the inventories and in the perturbation simulations?
From a policy standpoint, would it be more relevant to increase aviation and biomass burning sources rather than decrease them?
Any prioritization between the source-receptor versus transient simulations?
Section 7.3.2. Why only specify methane at lateral boundaries rather than throughout the regional domain? Why the focus on Europe?
Section 9. It would be useful to give a very brief overview of what was learned from earlier efforts to motivate the need for this new effort. Please provide references to overview papers for these MIPs as the current text is only useful to those who already know them.
Section 10. Something like the last paragraph would be helpful context earlier in the paper.
Detailed comments.
Lines 149-151. State that tagging and adjoint approaches are in addition to the standard perturbation runs to allow apples-to-apples comparison?
Lines 285-287. Include emission and concentration time series in a figure?
Lines 292-293. Why 5 years of spinup if methane and hydrogen concentrations are fixed?
Line 401. Time scale of this request for total atmospheric deposition?
Lines 472-474. Can ERF be calculated from only knowing SARF and IRF? I thought the CMIP6 ERF protocol relied on targeted simulations with fixed SSTs as described in Pincus, Forster & Stevens (2016).
Line 625. Consider adding a separate request in the supplemental spreadsheet for this high frequency output
Line 751. Provide a specific lat/lon resolution recommendation?
Line 790. Is this only ozone or also S, N deposition and PM?
Lines 803-805. How will the reliability of these results be assessed and communicated?
Lines 831-833. Are emitted VOC like acetone that photolyze to produce OH included?
Lines 862-863. Hourly surface fields were requested in earlier assessments (e.g., Reidmiller et al., 2009); the “aerhourly” table in the supplemental file does not include hourly deposition fluxes for N and S species?
Table 1. What is Met.no? The Hamilton et al. reference is missing.
Comments on requested diagnostics listed in the supplemental file:
The file provides important information not only for the current modellers but also for those using the modelled datasets in the future. With this future use in mind, it seems important to document the scientific rationale for the aerzonal, aerzonal-vert, ModelLevelAtStations and “List of TOAR2 HEGIFTOM” stations worksheets in the manuscript.
aerhourly: Is jNO2 an appropriate proxy for ozone production or would it require additional variables to solve for steady state? Why not request o3prod or tropdo3chm instead?
aermonthly_3d: Artificial tracers (aoanh, cofire25d, and o3ste) are requested but not documented in the manuscript. Are long-lived greenhouse gases emitted? If not, why are 3D distributions being requested?
Is it possible to indicate which variables are most critical for a model to produce? Are some of the requests such as PAH for other HTAP projects? Can the variables for HTAP3-OPNS request be differentiated here?
Are monthly deposition fluxes sufficient for meeting the policy needs for N and S deposition?
If PPFD is not available, would providing total downwelling shortwave radiation be useful?
References:Pincus, R., Forster, P. M., and Stevens, B.: The Radiative Forcing Model Intercomparison Project (RFMIP): experimental protocol for CMIP6, Geosci. Model Dev., 9, 3447–3460, https://doi.org/10.5194/gmd-9-3447-2016, 2016.
Reidmiller, D. R., Fiore, A. M., Jaffe, D. A., Bergmann, D., Cuvelier, C., Dentener, F. J., Duncan, B. N., Folberth, G., Gauss, M., Gong, S., Hess, P., Jonson, J. E., Keating, T., Lupu, A., Marmer, E., Park, R., Schultz, M. G., Shindell, D. T., Szopa, S., Vivanco, M. G., Wild, O., and Zuber, A.: The influence of foreign vs. North American emissions on surface ozone in the US, Atmos. Chem. Phys., 9, 5027–5042, https://doi.org/10.5194/acp-9-5027-2009, 2009.s
Van Vuuren, D. P., O'Neill, B. C., Tebaldi, C., Sanderson, B. M., Chini, L. P., Friedlingstein, P., Hasegawa, T., Riahi, K., Govindasamy, B., Bauer, N., Eyring, V., Fall, C. M. N., Frieler, K., Gidden, M. J., Gohar, L. K., Högner, A., Jones, A. D., Kikstra, J., King, A., Knutti, R., Kriegler, E., Lawrence, P., Lennard, C., Lowe, J., Mathison, C., Mehmood, S., Nicholls, Z., Prado, L. F., Zhang, Q., Rose, S. K., Ruane, A. C., Sandstad, M., Schleussner, C.-F., Seferian, R., Sillmann, J., Smith, C., Sörensson, A. A., Panickal, S., Tachiiri, K., Vaughan, N., Vishwanathan, S. S., Yokohata, T., Zecchetto, M., and Ziehn, T.: The Scenario Model Intercomparison Project for CMIP7 (ScenarioMIP-CMIP7), Geosci. Model Dev., 19, 2627–2656, https://doi.org/10.5194/gmd-19-2627-2026, 2026.
Citation: https://doi.org/10.5194/egusphere-2026-1367-RC2
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- 1
We recently noticed that Figure 1 in our preprint is using an outdated graphic. The new graphic is included in this author comment. The only difference is the boundary between the EMEP-West and EMEP-East source regions. The new graphic reflects the correct boundary between these regions as contained in the referenced dataset available on zenodo https://zenodo.org/records/17712022. We will make sure that this figure is updated in the revised manuscript.