the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
An evaluation of the regional distribution and wet deposition of secondary inorganic aerosols and their gaseous precursors in IFS-COMPO cycle 49R1
Abstract. Secondary Inorganic Aerosol (SIA) constitutes a considerable fraction of total particulate matter exposure, making it an important component of any atmospheric composition and air quality forecasting system. The subsequent loss of SIA to the surface, via both dry and wet deposition, determines the exposure time for humans and the extent of damage imposed on sensitive ecosystems due to increased surface acidity. This study provides a description and evaluation of recent updates to aerosol production, scavenging, and wet deposition processes in the global IFS-COMPO chemical forecasting system, used within the Copernicus Atmosphere Monitoring Service. The implementation of the EQSAM4Clim simplified thermodynamic module in IFS-COMPO cycle 49R1 alters the phase transfer efficiency of SIA precursor gases (sulphur dioxide, nitric acid, and ammonia), which significantly affects particulate SIA concentrations by modifying the fraction converted into aerosol form. Comparisons with surface observational data from Europe, the U.S., and Southeast Asia during 2018 indicate reductions in the global annual mean bias for both sulphates and nitrates. Updating the IFS-COMPO model to cycle 49R1 increases the burden and lifetime of sulphate and ammonium particles by one-third. Coupling EQSAM4Clim with IFS-COMPO improves the representation of ammonia-ammonium partitioning across regions, while the effect on sulphate is minimal. For nitric acid and nitrates, the phase partitioning is also significantly altered, with lower particulate concentrations leading to an excess of gas-phase nitric acid and an associated improvement in surface nitrate predictions. The impact on total regional wet deposition is generally positive, although sulphates in the U.S. and ammonium particles in Southeast Asia are strongly influenced by precursor emission estimates. Overall, these results provide confidence in the ability of IFS-COMPO cycle 49R1 to deliver accurate global-scale deposition fluxes of sulphur and nitrogen.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Geoscientific Model Development.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.- Preprint
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RC1: 'Comment on gmd-2024-188', Anonymous Referee #1, 03 Feb 2025
Review of the paper “An evaluation of the regional distribution and wet deposition of secondary inorganic aerosols and their gaseous precursors in IFS-COMPO cycle 49R1” by Williams et al.
The primary goal of this article is to evaluate improvements made to the next operational global composition model IFS-COMPO version (cycle 49R1), used within the Copernicus Atmosphere Monitoring Service (CAMS). By integrating updates such as the simplified thermodynamic module
EQSAM4Clim, the article aims to:
- Analyse the effects of these updates on surface distributions of nitrogen and sulfur gaseous precursors for SIA and on the associated particle concentrations and distributions.
- Assess the influence of the modifications on regional wet deposition fluxes of the various SIA precursors and particulates .The study uses three different simulations to achieve these objectives: a baseline simulation with the current operational IFS version (CY48R1); an updated simulation (CY49R1_NOE4C) that incorporates all model improvements except EQSAM4Clim; and a fully updated simulation (CY49R1) which includes EQSAM4Clim. These simulations are compared against observational data from Europe, the United States, and Asia during 2018 to evaluate the performance of the updates.
The topic is of certain interest to improve the representation of gas-particle interactions and their deposition processes. By refining the phase partitioning of SIA precursor gases (SO2, NH3, HNO3), the study enhances our understanding of the dynamics between gas-phase and particle-phase species. Through the use of three simulations (baseline, partial updates, and fully updates), the study also isolates the specific contributions of each model improvement. The paper is well organised and the methodology sufficiently clear. Nevertheless the manuscript in its current form suffers from a few weaknesses:
General comments
1- The description of the IFS-COMPO model is very succinct, and details of its main components, particularly aerosol management, would be appreciated. Schematic figures, for both model version, showing the interaction between the various modules (IFS-COMPO, IFS-AER, EQSAM4Clim, etc.) and the changes between the two versions would be relevant.
2- The observational networks (section 3) are too rapidly described. More information is needed on the different stations in each dataset (number of stations, locations, data available for the period used, etc.). Figures showing the location of the various stations and a discussion of the advantages and weaknesses of each dataset would be useful in this section. Additional information, such as the uncertainties associated with these datasets or references on their reliability, would also be useful. Putting all the necessary station information in this section will also help to lighten the text and figures in the rest of the article.
3- All figures in the article need to be greatly improved and standardized. The quality of the figures needs to be improved, with simpler, more legible titles and more complete captions. Appendix figures should be similar to those in the article (legends, curve colors, titles, etc.) and use the names of the article simulations. Many of the figure numbers in the article are also incorrect. See specific comments for details. Some of these issues should have been fixed before publication in EGUsphere.
4- Despite the improvements brought by the new version of the model, and in particular by the implementation of EQSAM4Clim, many biases are still present. Further discussion of ways to improve these biases would be relevant. Finally, this article focuses on 3 specific regions (Europe, the United States and Asia), but some informations on other parts of the world and on the various limitations of this study would also be interesting.
Specific comments
- Page 4, lines 167-168: Please add a reference.
- Page 5, lines 214, 227: As mentioned above, indicate the number of stations, develop selection criteria, etc.
- Page 5, line 232: “Acid Deposition Monitoring Network in East Asia” – > “EANET” (acronym already explained line 225).
- Page 6, line 253: “Nitrate#1” – > fine mode nitrate?
- Page 6, line 255: A map with station locations would be useful here. Refer to section 3 if such a map is added.
- Page 6, line 259: “we show monthly mean regional differences for July and December 2018” – > Why did you choose these two months?
- Page 6, line 268: Bias already cited in the literature?
- Page 7, Table 2: RMSE line missing. Indicate the relative differences (in %) between the two cycles as done in other Tables. Remove “diagnostic” and add “SO2” to harmonize with other tables.
- Page 7, Table 3: Harmonize the legend of all tables in the article. “Percentage difference changes are calculated as …” or “with the associated relative differences provided in parenthese …”: Choose one sentence and use it for all the Tables.
- Page 7, line 312: “Figure 1A” – > Figure A1
- Page 7, line 312: “the region with the highest surface SO₂ concentrations is the northeastern U.S.” – > Please rephrase the sentence, not consistent with the figure.
- Page 7, line 313: “There is little seasonality in the weekly observational composites” – > consistent with literature?
- Page 7, lines 318-319: “SO₂ emissions in the global inventory are significantly overestimated” – > What about the literature? Has this problem ever been reported or documented?
- Page 8, Figure 1: Please give each figure a simpler, clearer title (ex: SO2 - Europe, SO2 - US, SO2 - China). Also use a vertical title for the two figure lines, to the left of the first figure of each line. Put a title on the y axis of the figures. Complete the legend with all the necessary information, but do not include this information in the figure titles. Also describe the second line of figures in the legend. See also to put only one curve legend for each set of figures to lighten the figures. In the caption, please refer to section 3 for the description of the different observation datasets. The figure is not very sharp, please use a PDF or EPS file.- Page 8, Figure 2: Please give a simpler and clearer title (ex: SO4 - Europe). Put a title on the y axis. In the caption, please refer to section 3 for the description of the different stations used.
- Page 10, Figure 3: Review the titles of the various figures (unclear and illegible). Put a title for each column (ex: CY48R1 and CY49R1) and each row (ex: SO4 - Europe, SO4 - US, SO4 - Asia). Put only one colorbar per line to make it more legible and add its own unit. In the caption, please refer to section 3 for the description of the different observation datasets.
- Page 12, Figure 4: Please give a simpler and clearer title for each figure (ex: NH3 – Europe and NH4 -Europe). Put a title on the y axis. In the caption, please refer to section 3 for the description of the different stations used. Harmonize all figure captions of the article. “The corresponding biases are shown in the bottom panel.” is not appropriate here.
- Page 15, Figure 5: Same as Figure 3.
- Page 16, lines 513-519: You refer twice to Figure A7, but it's Figure 6, isn't it?
- Page 16, line 520: I think this is Figure A6 and not Figure A7.
- Page 17, Figure 6: Same as Figure 4.
- Page 19, Figure 7: Same as Figure 3.
- Page 20, Table 8: Remove % from this table to harmonize with other tables. Please correct ug – > µg (also for Table 4 and 6)
- Page 20, lines 621-630: Not the same font.
- Page 22, line 664: Here too, I think it's Figure 8 and not Figure 11.
- Page 23, Figure 8: Same as Figure 3.
- Page 25, Figure 9: Same as Figure 3.
- Page 26, lines 780-781: Figure 13 – > Figure 10. Please check that the text and figure numbers are consistent throughout the article.
- Page 27, Figure 10: Same as Figure 3.
- Page 29, Figure A1: Make a more legible figure. For example, use clear headings for each column (ex: NH3 - CY48R1, Diff A, Diff B, Diff C). Also include Europe, US and Asia, as well as July and December for the corresponding vertical rows on the left of the figure. Delete sub-figure headings for greater legibility.
- Page 30, Figure A2: Harmonize the titles (ex: NH3 – US and NH4 – US), axes, axis titles and legend with the figures in the article. Use the same curve colors as the other figures (keep the same color for observations and different versions throughout the article).
- Page 31, Figure A3: Same as Figure A1.
- Page 32, Figure A4: Same as Figure A2.- Page 33, Figure A5: Harmonize the figure with the other figures in the article. Put the names of the versions used in the article and add observations in the caption. Use station name as sub-figure title.
- Page 33, Table A1: Add NH3 to the table to harmonize with the other tables. In the caption, please refer to section 3 for the description of the different stations used here.
- Page 34, Figure A6: Same as Figure A1.
- Page 35, Figure A7: Same as Figure A2.
- Page 35, line 916 (Zenodo file): Several errors in the data description text (Partcile – > Particle ; surafec – > surface). A more precise description of the data would also be appreciated.
Citation: https://doi.org/10.5194/gmd-2024-188-RC1 - RC2: 'Comment on gmd-2024-188', Anonymous Referee #2, 14 Feb 2025
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