the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 19 May 2025
Modeling atmospheric sulfate oxidation chemistry via the oxygen isotope mass-independent fractionation using the Community Multiscale Air Quality Model (CMAQ)
Abstract. Atmospheric sulfate formation influences climate and air quality, yet its chemical pathways remain difficult to constrain. This study utilizes the oxygen isotope anomaly (Δ17O) of sulfate aerosol (ASO4) as a tracer to distinguish formation processes. We modeled Δ17O(ASO4) using the Community Multiscale Air Quality Model (CMAQ), focusing on 2006 and 2019 to quantify key ASO4 formation pathways and their response to U.S. emission changes. In 2006, Δ17O(ASO4) values were predicted to be below 1 ‰ in the Gulf Coast indicated acidic, ASO4-rich conditions dominated by S(IV) + H2O2 oxidation, while values above 1 ‰ in the West suggested less acidic conditions, leading to enhanced ASO4 production via S(IV) + O3 oxidation. Peak Δ17O(ASO4) values of ~5 ‰ in April across the Western U.S. reflected O3-driven ASO4 formation during high ammonia (NH3) emissions from fertilization. Between 2006 and 2019, mean Δ17O(ASO4) increased by up to 2 ‰, driven by declining sulfur dioxide (SO2) emissions from regulatory measures. Model comparisons with historical measurements show reasonable agreement in the acidic southeastern U.S. (RMSE = 0.3 ‰, Baton Rouge, LA). However, the model overpredicts Δ17O(ASO4) in the West (RMSE = 0.5 ‰, La Jolla, CA; RMSE = 2.1 ‰, White Mountain Research Center, CA), particularly during periods of high NH3 emissions. This overestimation suggests an excessive model response to aqueous S(IV) + O3 reactions. These results emphasize the need for expanded Δ17O(ASO4) measurements and improved model constraints to better capture evolving emission trends and regulatory impacts on sulfate formation.
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RC1: 'Comment on egusphere-2025-923', Anonymous Referee #2, 04 Jun 2025
General comments
The paper is easy to read and of high interest for the scientific community. Indeed I really believe that including O-isotopes in the CMAQ model is the way to go. I’m not a modeler but the results coming out of the model are very intriguing. The seasonal variations are huge in terms of D17O, which reflect large variations in anthropogenic emissions and atmosphere/cloud chemistry. The same is true for the comparison between the years 2006 and 2019. Overall, the main conclusion of the paper is that the model do not predict well the measurements (overestimation of the ASO4 D17O). The authors invoke mostly a misrepresentation of NH3 emissions and their effect on the cloud pH.
- Could you develop more this aspect? Could you do a sensitivity analysis to quantify the effect of NH3 emissions on the ASO4 D17O, in order to quantify how off the model is ?
The authors also mention the fact that oxidation pathways such as S(IV) oxidation via HOX are not fully captured in the model, which could play a significant role at coastal regions. However in the marine boundary layer, the presence of alkaline aerosols can reduce the cloud pH, which would enhance O3 oxidation and lead to an ASO4 D17O increase. How this would fit in the fact that the measurements tend to show lower ASO4 D17O than what your model predict in La Jolla ?
I cannot agree more with the authors, more seasonal measurements are required to validate and extend the results from this study.
The author do not mention SO2 oxidation pathways via NO2. More and more papers invoke in polluted areas direct or induced SO2 oxidation via NO2. How this would fit in your study ? You should at least mention it.
Specific comments:
- Line 97, 173 : there is no oxygen MI-fractionation during the SO2 oxidation processes, it’s only a transfer of the isotopic anomaly so it would be more appropriate to write about the « D17O » or « MIF signature ».
- Line 210 : could you precise “this is due to efficient conversion of SO2 to ASO4” ?
- line 310 : “Primary sulfate emissions, which are not subject to isotopic fractionation”. Yes there are subject of isotopic fractionation but no MI-fractionation. What you mean is that primary sulfate do not carry any MIF-signature (or have a D17O close to 0permil)
- Fig 8 : y axis : 2006 simulated D17O. You can remove the legend (2006 simulation / simulation = measurement
Citation: https://doi.org/10.5194/egusphere-2025-923-RC1 -
CC1: 'Comments on novelty and literature context of Δ17O-sulfate modeling study using CMAQ by Fang and Walters', Shohei Hattori, 11 Jun 2025
Dear Editor and Authors
Although I was not invited to formally review this manuscript, I have been following the discussion with great interest. I was originally planning to take more time to prepare comments by June 30, but since the first reviewer’s feedback has already been posted, I would like to take this opportunity to share a few thoughts.
We note that my collaborators and I are currently preparing a more detailed comment on the manuscript, including some technical feedback on the modeling aspects, which we plan to submit by June 30. I hope these are received in the spirit of constructive academic exchange.
In both the abstract (PDF version) and short summary, the manuscript describes this work as being done “for the first time.” However, a similar approach—using the CMAQ model to calculate Δ17O values based on sulfate formation pathways—was previously applied in the following study:
- Itahashi, S., Hattori, S., Ito, A., Sadanaga, Y., Yoshida, N., & Matsuki, A. (2022). Role of dust and iron solubility in sulfate formation during the long-range transport in East Asia evidenced by 17O-excess signatures. Environmental Science & Technology, 56(19), 13634–13643.
In addition, we recently published another study that also used the CMAQ model to investigate interannual variability in sulfate formation in East Asia:
- Lin, Y., Zhao, Y., Zhang, Y., Hong, Y., Hattori, S., Itahashi, S., Fan, M., Xie, F., Zhao, Z., Yu, M., Cao, F., Xu, R., Li, J., Kawamura, K., & Thiemens, M. H. (2025). China’s SO₂ emission reductions enhance atmospheric ozone–driven sulfate aerosol production in East Asia. Proceedings of the National Academy of Sciences of the United States of America, 122(24), e2414064122. https://doi.org/10.1073/pnas.2414064122
Given this background, I feel the statement that this study is being done “for the first time” could be reconsidered.
I also noticed that the manuscript does not refer to several recent studies that used Δ17O of sulfate and chemical transport models (either GEOS-Chem or CMAQ) to analyze sulfate formation pathways. I’m not pointing this out just to have our papers cited. Rather, I believe that a broader review of recent literature could help position the current study more clearly and fairly within the context of existing research.
For example, in Line 105, the manuscript references Sofen et al. (2011) to discuss the potential of Δ17O as a diagnostic tool. But more recent studies have used this tool to examine long-term changes (1) comparison between Pre-industrial and Present-day and (2) trend since the 1960-70s, especially by combining GEOS-Chem modeling with ice core observations. These include:
- Hattori, S., Alexander, B., Sofen, E., Kunasek, S., Bauer, S., & Thiemens, M. H. (2021). Isotopic evidence for acidity-driven enhancement of sulfate formation after SO₂ control. Science Advances, 7(19), eabd4610.
- Peng, Y., Hattori, S., Zuo, P., Ma, H., & Bao, H. (2023). Record of industrial atmospheric sulfate in continental interiors. Nature Geoscience, 16, 619–624.
In light of these studies, I would kindly suggest revising the relevant parts of the manuscript to better reflect recent progress in this field, and to clarify the specific role and contribution of this CMAQ-based work.
Furthermore, since the present study focuses on sulfate in the U.S., I may propose to take a look the existing observational studies from North America, such as:
- Moon, A., Jongebloed, U., Dingilian, K. K., Schauer, A. J., Chan, Y. C., Cesler-Maloney, M., ... & Alexander, B. (2023). Primary sulfate is the dominant source of particulate sulfate during winter in Fairbanks, Alaska. ACS Es&t Air, (3), 139-149.
Fairbanks is a highly relevant location for wintertime sulfate pollution, and could be useful for validating model performance.
Finally, I’d like to echo the point made by Reviewer #1 regarding the importance of seasonal measurements. Several our studies have already looked into seasonal variation in sulfate formation using Δ17O observations and modeling in different regions:
Antarctica
- Ishino, S., Hattori, S., Legrand, M., Chen, Q., Alexander, B., Shao, J., Huang, J., Jaeglé, L., Jourdain, B., Preunkert, S., & Yamada, A. (2021). Regional characteristics of atmospheric sulfate formation in East Antarctica imprinted on 17O‐excess signature. Journal of Geophysical Research: Atmospheres, 126(6), e2020JD033583.Mt Everest region
- Wang, K., Hattori, S., Yao, T., & Kang, S. (2021). Isotopic constraints on atmospheric sulfate formation pathways in the Mt. Everest region, Southern Tibetan Plateau. Atmospheric Chemistry and Physics, 21, 8357–8376.East Asia
- Itahashi, S., Hattori, S., Ito, A., Sadanaga, Y., Yoshida, N., & Matsuki, A. (2022). Role of dust and iron solubility in sulfate formation during the long-range transport in East Asia evidenced by 17O-excess signatures. Environmental Science & Technology, 56(19), 13634–13643.These studies may offer useful references for future extensions of the present work.
Once again, I hope these comments are constructive and helpful, and I look forward to further discussion. Thank you again for your attention and consideration.
Sincerely,
Shohei Hattori, ICIER, Nanjing University
Citation: https://doi.org/10.5194/egusphere-2025-923-CC1 -
CC2: 'Correction to reference list', Shohei Hattori, 11 Jun 2025
I found some problem/mistake in the previous post. Please see the following reference list.
- Hattori, S., Iizuka, Y., Alexander, B., Ishino, S., Fujita, K., Zhai, S., ... & Yoshida, N. (2021). Isotopic evidence for acidity-driven enhancement of sulfate formation after SO2 emission control. Science Advances, 7(19), eabd4610.
- Wang, K., Hattori, S., Lin, M., Ishino, S., Alexander, B., Kamezaki, K., ... & Kang, S. (2021). Isotopic constraints on atmospheric sulfate formation pathways in the Mt. Everest region, southern Tibetan Plateau. Atmospheric Chemistry and Physics, 21(10), 8357-8376.
- Ishino, S., Hattori, S., Legrand, M., Chen, Q., Alexander, B., Shao, J., ... & Savarino, J. (2021). Regional characteristics of atmospheric sulfate formation in East Antarctica imprinted on 17O‐excess signature. Journal of Geophysical Research: Atmospheres, 126(6), e2020JD033583.
- Itahashi, S., Hattori, S., Ito, A., Sadanaga, Y., Yoshida, N., & Matsuki, A. (2022). Role of dust and iron solubility in sulfate formation during the long-range transport in East Asia evidenced by 17O-excess signatures. Environmental Science & Technology, 56(19), 13634-13643.
- Lin, Y., Zhao, Y., Zhang, Y., Hong, Y., Hattori, S., Itahashi, S., Fan, M., Xie, F., Zhao, Z., Yu, M., Cao, F., Xu, R., Li, J., Kawamura, K., & Thiemens, M. H. (2025). China’s SO₂ emission reductions enhance atmospheric ozone–driven sulfate aerosol production in East Asia. Proceedings of the National Academy of Sciences of the United States of America, 122(24), e2414064122. https://doi.org/10.1073/pnas.2414064122
- Peng, Y., Hattori, S., Zuo, P., Ma, H., & Bao, H. (2023). Record of pre-industrial atmospheric sulfate in continental interiors. Nature Geoscience, 16(7), 619-624.Citation: https://doi.org/10.5194/egusphere-2025-923-CC2
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CC2: 'Correction to reference list', Shohei Hattori, 11 Jun 2025
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CC3: 'Comment on egusphere-2025-923', Syuichi Itahashi, 20 Jun 2025
Dear Editor and Authors,
I would like to share our comments with the community. My collaborator, Dr. Shohei Hattori, has already posted an initial comment, and I would like to add my perspectives, especially regarding the model configuration and interpretation. Since this study presents a potentially important aspect of sulfate oxidation pathway changes derived from a modeling approach, we hope our comments can help enhance the clarity and scientific robustness of the manuscript. Given the significance of the findings, we believe clarification is essential and therefore share our remarks in addition to the official review process. We appreciate your attention and look forward to further discussions.
Please find our detailed comments below.
Major Comment 1: Novelty
The manuscript claims that this is the first study to perform Δ17O calculations using CMAQ modeling. However, similar approaches have been previously published, for example:
- Itahashi, S., et al. (2022), Environmental Science & Technology, https://doi.org/10.1021/acs.est.2c03574
- Lin, Y., et al. (2025), PNAS, https://doi.org/10.1073/pnas.2414064122
While it is difficult to track all related CMAQ studies, the expression "for the first time" appears to be inaccurate and should be reconsidered to avoid misleading the readers.
Major Comment 2: Gas-phase SO₂ + OH Reaction
The description of the model configuration regarding gas-phase reactions is unclear and potentially inconsistent. In Table 1, the gas-phase SO₂ + OH pathway is marked as "not included" in the CMAQ configuration. This suggests that this critical oxidation pathway—generally responsible for 30–40% of sulfate production—is not considered in the simulation.
However, L126 states:
“This mechanism includes both gas-phase and aqueous-phase oxidation processes of SO₂, essential for accurately modeling ASO₄ formation. Specifically, it involves the oxidation of SO₂ by OH in the gas phase and by H₂O₂ and O₃ in cloud droplets and aqueous environments.”
Furthermore, the manuscript reports that the contribution of gas-phase SO₂ oxidation by OH is only 0.2% of total sulfate production (L200), which appears inconsistent with prior knowledge. In fact, in the two CMAQ-based studies cited above, the contribution of SO₂ + OH ranged from 20% to 70%, depending on the season.
The discrepancy is significant and requires further explanation. The result also contradicts model results in USA region modeled by GEOS-Chem (e.g., Hattori et al., 2021 Sci. Adv.), where gas-phase oxidation remains a major contributor. Could the authors clarify how this pathway was treated in the model and why its contribution is so minor here?
This is especially critical because the Δ17O value of sulfate produced by gas-phase SO₂ + OH is known to be low. If this pathway is not properly considered, the Δ17O of modeled sulfate may be overestimated.
Major Comment 3: TMI-Catalyzed Sulfate Formation
The inclusion of TMI (transition metal ion) catalyzed oxidation of S(IV) by O₂ is also unclear. Table 1 suggests that this process is not included. However, L185 states that sulfate formation via TMI catalysis is considered. This inconsistency needs to be addressed.
Moreover, if TMI catalysis is included, the concentrations of Fe and Mn must be specified, along with how they were estimated. Additionally, pH plays a key role in this process. These factors should be explicitly described if TMI reactions are accounted for.
Taken together with Comment 2, one could suspect that the high Δ17O of modeled sulfate may result from neglecting low-Δ17O processes such as gas-phase oxidation and TMI catalysis. Without inclusion of these key processes, the comparison with observational data becomes difficult to interpret. We also ask: has this model been validated in terms of sulfate concentration? Excluding key formation pathways may lead to an underestimation of sulfate mass as well.
Major Comment 4: Validity of the Observational Comparison
While we understand the limited availability of observational Δ17O data, the comparison in Figure 3 appears too loose. The observational sites—La Jolla, White Mountain Research Station (both in CA, from the late 1990s), and Baton Rouge, LA (early 2000s)—are used to evaluate model results from 2006 and beyond. However, multiple environmental changes have occurred since then, affecting sulfate oxidation pathways. What is the intended scientific implication of this comparison? It may not offer a meaningful validation of the model output.
Minor Comments and Specific Issues
L167: Shouldn't Xi include all forms of sulfate? In Itahashi et al. (2022), boundary conditions for Δ17O are estimated and used. We suggest referring to that method.
L174: The Δ17O of sulfate from TMI-catalyzed oxidation is not strictly 0‰. See Hattori et al. (2021) and Itahashi et al. (2022) for detailed discussion.
L185: SO₂ is not directly oxidized by TMIs. Rather, O₂ oxidizes S(IV) with TMI as a catalyst. This reaction also seems to be excluded in Table 1—please clarify.
L197–200: If the model does not include gas-phase reactions, how were contributions from FEMN, MHP, PAA, etc., determined in Figure 1? The relationship between Table 1 and Figure 1 must be clearly explained.
L205: Citation is needed.
We provide these comments in the spirit of scientific discussion and mutual improvement. We hope they are helpful in revising the manuscript or in future work.
Sincerely,
Syuichi Itahashi, RIAM, Kyushu University
Citation: https://doi.org/10.5194/egusphere-2025-923-CC3 -
RC2: 'Comment on egusphere-2025-923', Anonymous Referee #3, 27 Jun 2025
Review of “Modeling atmospheric sulfate oxidation chemistry via the oxygen isotope mass-independent fractionation using the CMAQ” by Fang and Walters
This manuscript investigates the role of different chemical pathways contributing to sulfate aerosol formation using simulated isotopic fractionation in the US. First of all, this kind of detailed methodology to evaluate the processes in the model is highly welcome and can bring significant advances to the community. The manuscript is well written and easy to understand, and the simulated results over the contiguous US are well analyzed.
However, I am concerned about the conclusion drawn based on the model results. The keys determining the difference of oxygen isotopic fractionation are oxidation pathways by H2O2 and O3 to produce sulfate aerosols and they are sensitively dependent on pH values of cloud droplets as clearly demonstrated in the manuscript. Therefore, in order to simulate the oxygen isotopic fractions, an accurate simulation of cloud droplet pH is essential, but I could not find any detailed description of how the model calculates cloud pH.
Can the evaluation of cloud pH be included in the revised manuscript?
In addition, the authors argue that the errors in simulated oxygen isotope values are driven mainly by errors with NH3 emission, which resulted in too high Delta O17 values. I could not agree with this conclusion because other organic acids in the atmosphere could be important in affecting cloud pH. I hope the authors respond to my comments above and revise the manuscript to reflect their thoughts on those issues.
Citation: https://doi.org/10.5194/egusphere-2025-923-RC2
Data sets
Simulating Δ17O of sulfate aerosol within the contiguous United States to trace the formation processes Huan Fang https://doi.org/10.5281/zenodo.14954960
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