the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
12 Jan 2021
12 Jan 2021
Isotopic constraints on atmospheric sulfate formation pathways in the Mt. Everest region, southern Tibetan Plateau
- 1State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
- 2Department of Chemical Science and Engineering, School of Materials and Chemical Technology, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama, Kanagawa 226-8502, Japan
- 3State Key Laboratory of Isotope Geochemistry, Guangzhou Institute of Geochemistry, CAS, Guangzhou 510640, China
- 4National Institute of Polar Research, Research Organization of Information and Systems, Tokyo 190-8518, Japan
- 5Department of Atmospheric Sciences, University of Washington, Seattle, WA 98195, USA
- 6CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101, China
- 7Earth-Life Science Institute, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8551, Japan
- 8University of Chinese Academy of Sciences, Beijing 100049, China
- 9National Institute of Information and Communications Technology, Koganei, Tokyo 184-8795, Japan
- 10Faculty of Science and Technology, Sophia University, 7-1 Kioi-cho, Chiyoda-ku, Tokyo, 102-8554, Japan
- 11CAS Center for Excellence in Deep Earth Science, Guangzhou 510640, China
- 1State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou 730000, China
- 2Department of Chemical Science and Engineering, School of Materials and Chemical Technology, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama, Kanagawa 226-8502, Japan
- 3State Key Laboratory of Isotope Geochemistry, Guangzhou Institute of Geochemistry, CAS, Guangzhou 510640, China
- 4National Institute of Polar Research, Research Organization of Information and Systems, Tokyo 190-8518, Japan
- 5Department of Atmospheric Sciences, University of Washington, Seattle, WA 98195, USA
- 6CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101, China
- 7Earth-Life Science Institute, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8551, Japan
- 8University of Chinese Academy of Sciences, Beijing 100049, China
- 9National Institute of Information and Communications Technology, Koganei, Tokyo 184-8795, Japan
- 10Faculty of Science and Technology, Sophia University, 7-1 Kioi-cho, Chiyoda-ku, Tokyo, 102-8554, Japan
- 11CAS Center for Excellence in Deep Earth Science, Guangzhou 510640, China
Abstract. As an important atmosphere constituent, sulfate aerosols exert profound impacts on climate, ecological environment, and human health. The Tibetan Plateau (TP), identified as the Third Pole
, contains the largest land ice masses outside the poles and has attracted wide attention on its environment and climatic change. However, the mechanisms of sulfate formation in this specific region remain poorly characterized. Oxygen-17 anomaly (Δ17O) has been used as a probe to constrain the relative importance of different pathways leading to sulfate formation. Here, we report the Δ17O values in atmospheric sulfate collected at a remote site in the Mt. Everest region to decipher the possible formation mechanisms of sulfate in such a pristine environment. Throughout the sampling campaign (April–September 2018), the Δ17O in non-dust sulfate show an average of 1.7 ± 0.5 ‰ which is higher than most existing data in modern atmospheric sulfate. The seasonality of Δ17O in non-dust sulfate exhibits high values in the pre-monsoon and low values in the monsoon, opposite to the seasonality in Δ17O for both sulfate and nitrate (i.e., minima in warm season and maxima in cold season) observed from diverse geographic sites. This high Δ17O in non-dust sulfate found in this region clearly indicates the important role of the S(IV) + O3 pathway in atmospheric sulfate formation promoted by high cloud water pH condition. Overall, our study provides an observational constraint on atmospheric acidity in altering sulfate formation pathways particularly in dust-rich environments, and such identification of key processes provides an important basis for a better understanding of the sulfur cycle in the TP.
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Kun Wang et al.
Status: closed
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RC1: 'Comment on acp-2020-1279', Anonymous Referee #1, 24 Jan 2021
This study presents two-season’s triple oxygen isotope data for atmospheric secondary sulfate (SAS) from the Mt. Everest region or Tibet Plateau (TP), a geographic-climatically unique area. The data reveal an unexpected seasonal trend with the monsoon season having higher Δ17O-SAS value than the pre-monsoon season. The data are consistent with the observed neutral to alkaline rainwater in the region, indicating an enhanced O3 pathway in S(IV) oxidation. I have some comments on lab procedures and the explanations based on simple correlations vs. GEOS-CHEM modeling.
Three major issues:
- The laboratory procedure has a discrepancy. I could not connect the heating of solid precipitates to remove organics and the IC-column separation and precipitation of Ag2SO4 (See details in my specific comments below).
- Many ad hoc explanations of the observed data seem to be unnecessary if you already have an isotopically enhanced GEOS-CHEM model to account for the Δ17O-SAS. Of course, after the modeling results, you can highlight the major factors. But any discussion on the controlling factors should not be isolated from the modeling—which seems to me is the case in the manuscript.
- The data have NOT ruled out or considered the possibility that the SAS collected in TP was already formed in the atmosphere in South Asia. That is to say that a portion or maybe a dominant fraction of the SAS collected in the field station in TP is not formed locally but transported there in long-distance. If true, local rainwater pH should not have played a role in the elevated Δ17O-SAS value. This requires the GEOS-CHEM modeling results to clarify.
Some of the specifics while I was reading over the manuscript.
Abstract: The scientific problem is not specifically expressed. Something “poorly characterized” is not a reason for research because almost everything is “poorly characterized” to an unspecified standard.
58-59: “It contains the largest land ice masses outside the poles and supplies water for more than one billion people (Immerzeel et al., 2010).” Please state the relevance of this fact to your study.
66: “a deep understanding” is vague in its meaning. Are you trying to link the secondary sulfate to the recent weakening of temperature seasonality in TP? A testable hypothesis that is related to sulfate formation pathway in TP would benefit the presentation of your research.
100-105: The need to do the SO4 collection and isotope analysis is tenuous. “No observational studies” itself is not a good reason. What I am expecting to be shown is the link of sulfate formation pathways to specific climate, environmental, or meteorological issues in TP. For example, if indeed Indian subcontinent is supplying atmospheric pollutants to TP, what should we expect to see in the Δ17O of atmospheric sulfate collected in that remote site on the northern slope of Mt. Everest? If there is an alternative source, what different Δ17O-SAS are we expecting?
140-142: Before briefing on the heat treatment of “sample precipitates”, you omitted the precipitation step (e.g., did you evaporate and acidify the solution before adding BaCl2 solution?). If this method is used, why was the method of Savarino et al (2001) and Geng et al (2013) developed specifically for smaller samples also used? If precipitates were heated at 450°C, how did you check organic matter by ion chromatography? Did you re-dissolve the precipitates? It is not mentioned in text. If the SO4 is separated and purified by IC, why is the heating solid precipitates necessary?
Section 2.4.1: Please add the relevance of black carbon data to the SO4 story in TP. It is not obvious to me.
Line 247-261: There is a distinct possibility that the CaSO4 (i.e., terrigenous sulfate has a positive Δ17O value) because a large portion of the sulfate in the arid surface salts could come from atmospheric deposition. Ignoring this possibility would increase the estimated Δ17O of SAS, although quantitatively it is not a big deal (i.e., ~6%).
341-352: Do you really need this simple estimation of minimum and maximum O3 path fraction involved in SAS formation? I am afraid that such a discussion does not add to the story. I thought you have already run modeling that incorporates meteorological data and atmospheric chemistry (isotope-enabled) and transport, i.e., GEOS-CHEM. The model should give you more accurate prediction of the respective fractions of O3 pathway during pre-monsoon and monsoon reasons. The simple minimum and maximum estimations ignore other pathways such as Mn-Fe catalyzed cloud-water O2 oxidation and mineral-surface heterogenous oxidation.
359: Please change “SR” to “solar radiation” because you only used the abbreviation twice (another in line 216) in the entire paper.
360: Change “hypothesize” to “explain”.
363: Change “hypothesis” to “explanation”.
375-381: Now, my understanding here is that the GEOS-CHEM atmospheric chemistry-transport model (isotopically enabled) could not offer a prediction on the SAS Δ17O value for the pre-monsoon and monsoon reasons. Correct? If true, what’s the point of doing the modeling?
398-406: There could be no major problem with an acidic cloud-water in these cited models. The problem could be the poor parametrization of heterogeneous oxidation of SO2 or aqueous S(IV) on dust surface.
Section 3.3.4.: Your explanation of the higher Δ17O during monsoon season is due to the enhanced moisture on alkaline dust surface which increases the overall fraction of the S(IV) + O3 reaction pathway than during the pre-monsoon when the air is relatively drier. If so, it is worth of another repeat here. Please also link and explain the opposite trends in the Δ17O between NO3- and SO4 in this framework (it can be explained).
Importantly, if none of these surface heterogeneous reaction, nature and flux of dust particles, or the enhancing effect of moisture was incorporated in the GEOS-CHEM model, I wonder why you need to do the GEOS-CHEM modeling at all. On the other hand, if the model can do the job in explaining the observed Δ17O data, why would you need to single out some of the factors and do the simple minimum/maximum estimates and interpretation? That is something that confuses me.
Summary: I think the Δ17O-SO4 data are solid, unique, interesting, and can be explained by known reaction mechanisms. With proper cleaning-up and reorganization of the flow of the manuscript, the data may reveal important unknown parameters we need to calibrate and therefore quantitatively improve the isotope prediction of the GEOS-CHEM model.
- AC2: 'Reply on RC1', Shohei Hattori, 02 Apr 2021
- AC3: 'Reply on RC1', Shohei Hattori, 02 Apr 2021
-
RC2: 'Comment on acp-2020-1279', Anonymous Referee #2, 17 Feb 2021
This study presents triple oxygen isotope data on sulfate aerosols sampled in the Tibetan Plateau. The data reveal an interesting Δ17O-seasonal trend with the monsoon season which would be explained by an enhanced O3 oxidation pathway in SO2 oxidation. The data obtained are valuable, the quality of the measurement seems solid to me. The importance of the alkalinity on the sulfate aerosols emphasized in this study is relevant as there are still many uncertainties on the sulfate formation, highlighting the exploration of new perspectives.
However, I have some comments and some suggestions related on how the results are discussed as listed above:
- I am not sure to understand why the Tibetan Plateau is an important region and why it is called “Third Pole”. Please describe the importance of this area.
- In the Method l.155. It is unclear how the authors reported the D17O. Is it the raw or the corrected values? In the latter case, how did the authors proceed? A reference is at least required.
- I expected to see a calculation based on Na to exclude the contribution of sea-salt, which would be confirmed by the study of Cong et al. Using only Cong study seems insufficient to me.
- Knowing that the Ca/Al ratio vary in Asian dust from 0.1 to 35%, how would this affect your result? Ratio from anthropogenic dust is also expected to vary. I also didn’t find the values cited by the authors in the literature.
- It is unclear if the SO2 concentration has been measured, but adding a discussion using the SO2 concentration in particular with the use of SOR could help convince me about the predominance of secondary sulfate.
- l. 320 Are the HYSPLIT results consistent with your conclusion ?
- l. 341 A comparison and discussion with the D17O modelled using GEOS-Chem would have been a great addition to the paper. Considering the O3 concentration, and the kinetic reaction, what D17O values are expected and how does it compare to both min and max fraction you deduced ? I am confused on the fact that GEOS-Chem model is only used in cloud pH model
- AC1: 'Reply on RC2', Shohei Hattori, 02 Apr 2021
Status: closed
-
RC1: 'Comment on acp-2020-1279', Anonymous Referee #1, 24 Jan 2021
This study presents two-season’s triple oxygen isotope data for atmospheric secondary sulfate (SAS) from the Mt. Everest region or Tibet Plateau (TP), a geographic-climatically unique area. The data reveal an unexpected seasonal trend with the monsoon season having higher Δ17O-SAS value than the pre-monsoon season. The data are consistent with the observed neutral to alkaline rainwater in the region, indicating an enhanced O3 pathway in S(IV) oxidation. I have some comments on lab procedures and the explanations based on simple correlations vs. GEOS-CHEM modeling.
Three major issues:
- The laboratory procedure has a discrepancy. I could not connect the heating of solid precipitates to remove organics and the IC-column separation and precipitation of Ag2SO4 (See details in my specific comments below).
- Many ad hoc explanations of the observed data seem to be unnecessary if you already have an isotopically enhanced GEOS-CHEM model to account for the Δ17O-SAS. Of course, after the modeling results, you can highlight the major factors. But any discussion on the controlling factors should not be isolated from the modeling—which seems to me is the case in the manuscript.
- The data have NOT ruled out or considered the possibility that the SAS collected in TP was already formed in the atmosphere in South Asia. That is to say that a portion or maybe a dominant fraction of the SAS collected in the field station in TP is not formed locally but transported there in long-distance. If true, local rainwater pH should not have played a role in the elevated Δ17O-SAS value. This requires the GEOS-CHEM modeling results to clarify.
Some of the specifics while I was reading over the manuscript.
Abstract: The scientific problem is not specifically expressed. Something “poorly characterized” is not a reason for research because almost everything is “poorly characterized” to an unspecified standard.
58-59: “It contains the largest land ice masses outside the poles and supplies water for more than one billion people (Immerzeel et al., 2010).” Please state the relevance of this fact to your study.
66: “a deep understanding” is vague in its meaning. Are you trying to link the secondary sulfate to the recent weakening of temperature seasonality in TP? A testable hypothesis that is related to sulfate formation pathway in TP would benefit the presentation of your research.
100-105: The need to do the SO4 collection and isotope analysis is tenuous. “No observational studies” itself is not a good reason. What I am expecting to be shown is the link of sulfate formation pathways to specific climate, environmental, or meteorological issues in TP. For example, if indeed Indian subcontinent is supplying atmospheric pollutants to TP, what should we expect to see in the Δ17O of atmospheric sulfate collected in that remote site on the northern slope of Mt. Everest? If there is an alternative source, what different Δ17O-SAS are we expecting?
140-142: Before briefing on the heat treatment of “sample precipitates”, you omitted the precipitation step (e.g., did you evaporate and acidify the solution before adding BaCl2 solution?). If this method is used, why was the method of Savarino et al (2001) and Geng et al (2013) developed specifically for smaller samples also used? If precipitates were heated at 450°C, how did you check organic matter by ion chromatography? Did you re-dissolve the precipitates? It is not mentioned in text. If the SO4 is separated and purified by IC, why is the heating solid precipitates necessary?
Section 2.4.1: Please add the relevance of black carbon data to the SO4 story in TP. It is not obvious to me.
Line 247-261: There is a distinct possibility that the CaSO4 (i.e., terrigenous sulfate has a positive Δ17O value) because a large portion of the sulfate in the arid surface salts could come from atmospheric deposition. Ignoring this possibility would increase the estimated Δ17O of SAS, although quantitatively it is not a big deal (i.e., ~6%).
341-352: Do you really need this simple estimation of minimum and maximum O3 path fraction involved in SAS formation? I am afraid that such a discussion does not add to the story. I thought you have already run modeling that incorporates meteorological data and atmospheric chemistry (isotope-enabled) and transport, i.e., GEOS-CHEM. The model should give you more accurate prediction of the respective fractions of O3 pathway during pre-monsoon and monsoon reasons. The simple minimum and maximum estimations ignore other pathways such as Mn-Fe catalyzed cloud-water O2 oxidation and mineral-surface heterogenous oxidation.
359: Please change “SR” to “solar radiation” because you only used the abbreviation twice (another in line 216) in the entire paper.
360: Change “hypothesize” to “explain”.
363: Change “hypothesis” to “explanation”.
375-381: Now, my understanding here is that the GEOS-CHEM atmospheric chemistry-transport model (isotopically enabled) could not offer a prediction on the SAS Δ17O value for the pre-monsoon and monsoon reasons. Correct? If true, what’s the point of doing the modeling?
398-406: There could be no major problem with an acidic cloud-water in these cited models. The problem could be the poor parametrization of heterogeneous oxidation of SO2 or aqueous S(IV) on dust surface.
Section 3.3.4.: Your explanation of the higher Δ17O during monsoon season is due to the enhanced moisture on alkaline dust surface which increases the overall fraction of the S(IV) + O3 reaction pathway than during the pre-monsoon when the air is relatively drier. If so, it is worth of another repeat here. Please also link and explain the opposite trends in the Δ17O between NO3- and SO4 in this framework (it can be explained).
Importantly, if none of these surface heterogeneous reaction, nature and flux of dust particles, or the enhancing effect of moisture was incorporated in the GEOS-CHEM model, I wonder why you need to do the GEOS-CHEM modeling at all. On the other hand, if the model can do the job in explaining the observed Δ17O data, why would you need to single out some of the factors and do the simple minimum/maximum estimates and interpretation? That is something that confuses me.
Summary: I think the Δ17O-SO4 data are solid, unique, interesting, and can be explained by known reaction mechanisms. With proper cleaning-up and reorganization of the flow of the manuscript, the data may reveal important unknown parameters we need to calibrate and therefore quantitatively improve the isotope prediction of the GEOS-CHEM model.
- AC2: 'Reply on RC1', Shohei Hattori, 02 Apr 2021
- AC3: 'Reply on RC1', Shohei Hattori, 02 Apr 2021
-
RC2: 'Comment on acp-2020-1279', Anonymous Referee #2, 17 Feb 2021
This study presents triple oxygen isotope data on sulfate aerosols sampled in the Tibetan Plateau. The data reveal an interesting Δ17O-seasonal trend with the monsoon season which would be explained by an enhanced O3 oxidation pathway in SO2 oxidation. The data obtained are valuable, the quality of the measurement seems solid to me. The importance of the alkalinity on the sulfate aerosols emphasized in this study is relevant as there are still many uncertainties on the sulfate formation, highlighting the exploration of new perspectives.
However, I have some comments and some suggestions related on how the results are discussed as listed above:
- I am not sure to understand why the Tibetan Plateau is an important region and why it is called “Third Pole”. Please describe the importance of this area.
- In the Method l.155. It is unclear how the authors reported the D17O. Is it the raw or the corrected values? In the latter case, how did the authors proceed? A reference is at least required.
- I expected to see a calculation based on Na to exclude the contribution of sea-salt, which would be confirmed by the study of Cong et al. Using only Cong study seems insufficient to me.
- Knowing that the Ca/Al ratio vary in Asian dust from 0.1 to 35%, how would this affect your result? Ratio from anthropogenic dust is also expected to vary. I also didn’t find the values cited by the authors in the literature.
- It is unclear if the SO2 concentration has been measured, but adding a discussion using the SO2 concentration in particular with the use of SOR could help convince me about the predominance of secondary sulfate.
- l. 320 Are the HYSPLIT results consistent with your conclusion ?
- l. 341 A comparison and discussion with the D17O modelled using GEOS-Chem would have been a great addition to the paper. Considering the O3 concentration, and the kinetic reaction, what D17O values are expected and how does it compare to both min and max fraction you deduced ? I am confused on the fact that GEOS-Chem model is only used in cloud pH model
- AC1: 'Reply on RC2', Shohei Hattori, 02 Apr 2021
Kun Wang et al.
Kun Wang et al.
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