the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 15 Jan 2024
The annual cycle and sources of relevant aerosol precursor vapors in the central Arctic
Abstract. In this study, we present and analyze the first continuous timeseries of relevant aerosol precursor vapors from the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. These precursor vapors include sulfuric acid (SA), methanesulfonic acid (MSA), and iodic acid (IA). We use FLEXPART simulations, inverse modeling, sulfur dioxide (SO2) mixing ratios, and chlorophyll-a (chl-a) observations to interpret the 20 seasonal variability of the vapor concentrations and identify dominant sources. Our results show that both natural and anthropogenic sources are relevant for the concentrations of SA in the Arctic, but anthropogenic sources associated with Arctic haze are the most prevalent. MSA concentrations are an order of magnitude higher during polar day than during polar night due to seasonal changes in biological activity. Peak MSA concentrations were observed in May, which corresponds with the timing of the annual peak in chl-a concentrations north of 75° N. IA concentrations exhibit two distinct peaks during 25 the year: a dominant peak in spring and a secondary peak in autumn, suggesting that seasonal IA concentrations depend on both solar radiation and sea ice conditions. In general, the seasonal cycles of SA, MSA, and IA in the central Arctic Ocean are related to sea ice conditions, and we expect that changes in the Arctic environment will affect the concentrations of these vapors in the future. The magnitude of these changes and the subsequent influence on aerosol processes remains uncertain, highlighting the need for continued observations of these precursor vapors in the Arctic.
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RC1: 'Comment on egusphere-2023-2953', Anonymous Referee #1, 07 Feb 2024
Comments to the muanuscript egusphere-2023-2953
Boyer et al. The annual cycle and sources of relevant aerosol precursor vapors in the central Arctic.
Reviewer's comments
The article presents and analyzes the first time series of aerosol precursor vapors (sulfuric acid (SA), methanesulfonic acid (MSA), and iodic acid (IA)) that are relevant to the central Arctic during MOSAiC. The authors conducted the measurements with state-of-the-art instruments, and the results are crucial in assessing the impact of anthropogenic emissions in the Arctic. The article is well structured, and well written, and only requires minor corrections before acceptance.
Minor comments
- The article discusses the crucial findings related to the concentration of atmospheric gases in the Arctic. However, the information is not presented in a concise format such as a table, which would enable the reader to easily examine the data. It is recommended to include a table that displays the monthly and seasonal averages of the primary anthropogenic pollutants.
- The date in Figure 4 is confusing. It is recommended to improve the date and use a single format.
- Figure 1 presents the gas phase time series for SA, MSA, and IA during clean and polluted periods using a violin-type scheme. This type of schematic can be a bit confusing. It is recommended to present the information in another format, for example, box-and-whisker diagrams. Could you expand the description of these results? Perhaps showing a table with the main statistical results.
- Figure 2c shows several results that are difficult to interpret. Is it possible that you could improve or present these results in another format?
- The message describing Figure 2c mentions the dashed white line denoting the monthly median latitude of Polarstern during the campaign. However, in Figure 2c no dotted line is shown. The only one observed is a continuous white line.
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RC2: 'Comment on egusphere-2023-2953', Anonymous Referee #2, 11 Apr 2024
Boyer et al. describe one year of relevant aerosol precursor in the gas phase from the central Arctic during the MOSAiC expedition from Sep 2019 to Oct 2020. The data include sulfuric acid (SA), methanesulfonic acid (MSA), and iodic acid (IA). They used the FLEXPART simulations, inverse modeling, and satellite chlorophyll-a (chl-a) to interpret the seasonal variability of the studied parameters and identify their source regions. The results conclude that natural and anthropogenic sources contribute to different aerosol types depending on the season, biotic and abiotic factors, and air mass movement. The information provided and the study's conclusions could be helpful to the scientific community. The manuscript does, however, require more explanation in some sections. The results visualizations, as I explain below, are my major concern.
General comments:
Section 2.6, Line 207: The FLEXPART and inverse modeling need further explanation on how they work. For instance, what are the frequency, timing and length of back-trajectories used? Where do the main sources of air mass dominate during the measurement period? A figure showing the air mass back-trajectories in the supplement would be beneficial. While ECLIPSE is a fundamental tool in presenting the results, no details on how It works, references and previous applications.
The conclusion section is long and has discussion sentences/cited references that might be moved to Results and Discussions. The Section shall summarize the major findings along with their implications.
Specific comments:
Line 94: Between brackets, define the HOx, for example, (OH and H2O).
Line 97: At least define what IxOy refers to at the 1st mention.
Figure 1: The data is misleading and the word “time series” in the caption is not appropriate. From the 1st glance, the readers may interpret that the colors distinguish between the input from biogenic (clean) and anthropogenic (polluted) sources. While I see the polluted cases represent the excess concentration to the biogenic one (polluted + biogenic). Indeed, I think this figure after a suitable explanation could be transferred to the supplementary material since it doesn’t contribute to the main conclusion of the study.
Line 178: A statistical test would be more robust to evaluate that there is no significant difference in medians.
Line 200: Not only cloudiness but also the low-incidence sun angle in winter hinders the measurement of chl-a from satellites at high latitudes.
Line 270: do you think the word “diurnal” fits the explanation here? Diurnal means 24-hour variations from day to night.
Figure 2: I don’t see the advantage of adding the 5-minute time resolution data in the background. The figure presents the annual cycle, so the monthly median with the shaded area or monthly box charts that describe the whole statistics is enough. Panel-A: the left y-axis is hidden. Panel C: It is better to present the missing data in chl-a as blank (white) to differentiate low values and non-measured times. Accordingly, the dotted white line must be modified.
Figure 3: Same comment as Figure 2. Presenting a time average (median) may be better to highlight the main variations throughout the time series.
Figure 4: The presentation of the data is hard to interpret. For example, the oceanic contribution in July is about 0.1 µg/m3 or (0.18 – 0.1 µg/m3). Indeed, I see Fig. S8 is worth presenting in the main manuscript rather that Fig. 4.
Figures 5, 6, and 7: In my view, the colors show the contribution of each polygon, which, when added together, gives the concentration overall.
Line 375: Refer to the polygon number.
Line 420: Citing Park et al. is not enough here because it handles the DMS rather than MSA. There are studies in the literature that have reported the link between marine biological activity and aerosol chemical composition (or MSA) in different marine environments (e.g., North Atlantic, Mediterranean and Eastern China Seas).
Line 443: Introducing an equation or more explanation on the influence index calculation and the unit used is required to make it clearer.
Line 447: It is worth highlighting that DMS emissions are mostly related to senescent phytoplankton cells rather than healthy cells.
Line 723: Who is MDO? What is the role of BH?
Typos:
Line 52: “product” instead of “byproduct”
Line 60: “sulfur” instead of “sulfate”
Line 151: -50% to …
Line 255: remove “or”
Citation: https://doi.org/10.5194/egusphere-2023-2953-RC2 -
RC3: 'Comment on egusphere-2023-2953', Anonymous Referee #3, 15 Apr 2024
The manuscript presents very interesting and useful data. It is well organized and clearly written and the elaborations and conclusions are scientifically sound. I recommend publication once the following minor issues are addressed.
Sect. 2.3. This Paragraph deals with a key issue that should be addressed more quantitatively. For the provided plots it is quite evident that pollution from the ship or ongoing surrounding activities did not spoil the measurements, nevertheless the differences should be presented more quantitatively: a statistics test should be employed to demonstrate that the data distribution are not statistically different between the “clean” and “polluted” data subsets. Furthermore, I find interesting the fact that, judging from Figure 1, MSA is more affected from pollution than SA (the difference between the “clean” and “polluted” medians is higher for the MSA case than for SA): have the authors an explanations for this? Which activity can be a source of MSA?
Sect. 2.5. Which time resolution have the CHL data?
Sect. 2.6. Please provide more information on the back trajectories: time resolution, length, frequency. Moreover, was the travelling height of the back-trajectories taken into consideration for the elaborations?
L265. Why “including SA, MSA, and IA”? Fig. 2a presents precisely SA, MSA and IA.
L280. No “dotted white line” is present in Figure 2c.
L317. “To further evaluate the sources of SO2 and SA in our measurements, we examined emissions of anthropogenic sulfate…”. I do not think this expression to be correct: by coupling the ECLIPSE v6b with flexpart trajectories the authors are not evaluating the emissions. Please reformulate the sentence.
L371. “Despite lower anthropogenic SO4-S influence from the North Asia sector during March and April”: refer to the appropriate Figure here, for major clarity.
L640. Correct in “sea-ice continues to decline”.
Citation: https://doi.org/10.5194/egusphere-2023-2953-RC3 -
RC4: 'Comment on egusphere-2023-2953', Anonymous Referee #4, 07 May 2024
The annual cycle and sources of relevant aerosol precursor vapors in
The Central Arctic by Boyer et al.
General:
This paper is potentially dangerous as it could impede our process understanding of the role of precursor gases in aerosol formation and growth. This could have long-term implications for our knowledge of cloud formation and climate change in the inner Arctic basin, affecting future generations.
The manuscript references several relevant articles from the field, but the literature survey is not comprehensive. Over the past decades, a substantial amount of observational data has been collected over the summer and early autumn pack ice, which is essential to this study’s results and conclusions and, therefore, deserves a discussion and comparison. It would be beneficial to mention or learn from the previous work by Tjernström, Leck, and their colleagues over the last 30 years on the inner Arctic pack ice area, including the marginal ice zone.
The paper gives the impression that “continuous” sampling had occurred at one Arctic location. All measurement plots, except for Fig. 2, show only time series, disregarding the variation of latitude and longitude during sampling while on a moving ship.
The inverse model uses the FLEXPART source-receptor-relationship and the measurement time series from the ship to identify potential source regions. It is unclear whether and which DMS emissions were used in the FLEXPART runs. While the inverse modeling technique results in important insights into the source regions of the aerosol precursors in different seasons, the time series analyses in the paper are superficial.
It's further unclear why no observation of particulate MSA (MSAp) or nss-SO4 was included in the manuscript. Were these parameters not measured during MOSAiC? The conclusions remain vague without an analysis of MSAp/nss-SO4 molar ratios, especially since this study’s high-MSA concentration periods provide little explanation for the low levels of particulate MSA reported from previous studies over the summer early autumn pack ice area.
The paper should be rejected foremost because of grave methodological uncertainties, which must be specified to be convincing, such as demanding a cleaned CPC record showing that decontamination resulted in CPC levels comparable to previous results over the pack ice when existing. After a convincing decontamination, the study could have made an important descriptive contribution to the sparsely sampled inner Arctic.
Detailed comments:
Line 36: Meier et al., 2014 could be replaced with a more suitable citation. Its focus is not on the air-sea exchange of particles.
Line 37: Define “in the Arctic”, “the central Arctic Ocean, “high Arctic”. Do you mean north of 80°?
Line 40: Discussing past observations made over the pack ice during summer and early autumn would be worthwhile. These observations have shown that particulate organics present in Aitken and accumulation mode aerosol and cloud water had properties like marine polymer gels. These gels were found to originate from the surface microlayer on leads. This behavior was attributed to the activity of ice microalgae, phytoplankton, and possibly bacteria. Some studies exploring these observations include Leck and Bigg 2005, Bigg and Leck 2008, Orellana et al. 2011, Karl et al. 2013, Hamacher-Barth et al. 2016, and Lawler et al. 2021.
Line 42: Please provide the exact citation indicating that 90% of CCN in the Arctic during summer is explained by NPF. Please include the latitude range and period used to define the summer Arctic.
Line 43-44: The region of the Arctic that is situated north of 80° witnesses a significant seasonal disparity all year round. The cause of this contrast can be attributed to the temperature and sea ice conditions, the uninterrupted sunlight in summer, and the prolonged polar darkness in winter. These diverse circumstances bring about significantly different atmospheric transport dynamics, atmospheric aerosol precursor gases, and their chemical reactions, which will affect the life cycle of aerosol particles over the pack ice area in distinct ways. Thus, the literature cited on a global evaluation of CCN formation by direct sea salt and ultrafine particles or CERN-CLOUD measurements of global particle formation or present and pre-industrial new particle formation does seem unrelated to this study’s observations over the pack ice area and as such, should be omitted. The only citation with some relevance is Kecorius et al., 2019.
Line 45-48: It should be clarified that the cited studies are performed in summer to early autumn, but Koike et al., 2019, report on two years of continuous in situ measurements at the Mount Zeppelin Observatory (78°56′N, 11°53′E), in Ny-Ålesund, Spitsbergen. The relevance of the inner Arctic of Koike et al.'s 2019 study is thus questioned; please omit.
Line 46: The Mauritzen et al. (2011) result only represents the inner Arctic summer; please add this information. Mauritsen et al. (2011) estimated a threshold of 10 to 16 CCN per cm3 as a minimum for cloud formation and sustenance. Past observation also found that the CCN concentrations around the ice sheet's edge were highest but dropped almost tenfold due to wet scavenging within 1-2 days of advection from the open sea into the pack ice (Bigg and Leck, 2001; Leck and Svensson, 2015).
Line 47-48: The modeling study conducted by Bulatovic et al. in 2021 aimed to investigate whether Aitken mode particles can serve as CCN. The study simulated median supersaturations between 0.2% and 0.4%, with a range of up to 1%. The results showed that even small Aitken mode aerosols of ~30nm diameter can be activated as long as larger accumulation particles are low in number concentration, preventing the depletion of excess water vapor. The simulations used typical aerosol size distributions encountered in the central Arctic during the summer/early autumn of 1991, 1996, 2001, and 2008 (Heintzenberg and Leck, 2012). It was found that having a low concentration of accumulation mode particles and a high concentration of Aitken mode particles in the inner Arctic during summer and early autumn, which created a favorable environment for the activation of CCN in the small Aitken mode range, is a rare occurrence.
The statements that the high Arctic summer/early autumn studies by Baccarini et al., 2020, and Karlsson et al., 2021, show that very small particles can act as CCN has to be weakened. No direct evidence has been presented in the studies since the conclusions were based on inferred proofing. Please also possibly add the results of Bulatovic et al., 2021.
Line 48: A citation is missing after “exceptionally high”; clarify when and where in the Arctic.
Line 49: To ensure the continuity of in situ data archives of the high Arctic north of 80°, unique measurements have been conducted during 5 research expeditions from 1991 to 2018. (Leck et al., 1996; Leck et al., 2001; Leck et al., 2004; Tjernström et al., 2014; Leck et al., 2019). Please remind the reader of their presence.
Line 52-57: The cited references are not specific to observations/modeling during the biologically most active conditions over the pack ice and at the marginal ice zone (MIZ). I would encourage the authors to read and cite the following papers and useful references therein: Leck and Persson, 1996a,b; Kerminen and Leck, 2001; Lundén et al., 2007; 2010.
Line 58-63: An important precursor of aqueous phase-produced sulfate is the DMS oxidation product hydroperoxylmethyl orthoformate (HPMTF), which has been completely overlooked in this study. The global burden of HPMTF has been calculated to be 2.6–26 Gg S (see Cala et al., 2023). The general understanding is that HPMTF is taken up rapidly in cloud water; however, Cala et al. (2023) found that rapid cloud uptake of HPMTF worsens the model–observation comparison.
It would also be worthwhile to discuss the role of direct formation of sulfuric acid from the gas-phase oxidation of DMS with the OH radical, as demonstrated by Berndt et al. (2023). The direct production of sulfuric acid in DMS oxidation has been speculated about in the literature for decades (e.g., cite Lucas and Prinn, 2002 and Karl et al., 2007).
In fact, during summer, the gas phase data collected in the MOSAiC expedition after a convincing decontamination could potentially help understand the relevance of direct sulfuric acid formation in the central Arctic.
Line 64: Please cite Leck and Bigg, 2011, Heintzenberg et al., 2017, and Karl et al., 2019. Yet another explanation for the occurrence of high numbers of nucleation mode particles in the high Arctic, involving granular nano gels in addition to sulfuric acid, was proposed by Karl et al. (2013). The appropriate discussion of these findings on nanoparticle events observed over the Arctic Ocean must be included in the introduction.
Line 67-69: The citations report results from observations during spring and summer in the Arctic. This information is too unspecific. Please clarify for each of the citations used from where (baseline station, latitude and longitude, at the MIZ, or over the pack ice area) and more exactly during which period they represent.
Line 69-70: The cited papers are irrelevant to the present study as they provide general information or cover only a small part and a short period in the central Arctic Basin. Therefore, it is recommended that all the citations be removed.
Ghahremaninezhad et al., 2019, do not report any observations on CCN. They implemented DMS(g) in Environment and Climate Change Canada’s forecast model and compared the model simulations with DMS(g) measurements made in Baffin Bay and the Canadian Arctic Archipelago in July and August 2014.
Mayer et al., 2020, did not perform any direct measurements of CCN and only inferred them from a 6-day mesocosm experiment throughout a phytoplankton bloom.
Charlson et al., 1987, presented a hypothesis about the feedback between ocean temperature and cloud radiative properties via DMS ocean and air, particulate Sulftat, and CCN/numbers of cloud droplets. Observations from the Arctic and other marine regions have questioned the key role attributed to DMS in the CLAW hypothesis for over a decade (Leck and Bigg, 2007; Quinn and Bates, 2011).
Carslaw et al., 2010 is a review paper that discusses natural aerosols in the Earth System as a whole.
Line 72-73: I disagree; there is no direct evidence that decadal DMS emission trends are positive across the Arctic due to decreasing sea ice coverage. Both studies cited infer temporal variations in ocean dimethyl sulfide emissions using either a remote sensing algorithm based on either estimated sea-surface DMS concentration (nM) from remotely sensed chlorophyll concentration light penetration depths and photosynthetically available radiation or reconstruction of the annual and seasonal MSA flux with monthly resolution from a high-resolution ice core obtained from the SE-Dome, southeastern Greenland Ice Sheet (ca 250 masl) and satellite-derived chlorophyll-a datasets.
Please replace “direct evidence” with “inferred evidence”.
It should be noted that the estimates made by Gali et al. for the central Arctic basin are subject to large uncertainties as they are based solely on inferred remote sensing. Additionally, it is important to consider the satellite orbit inclination and instrument swath, which create a data gap north of approximately 87 degrees.
Line 75-77: The paper by Schmale et al. (2022) is referenced to support the claim that DMS oxidation products in the aerosol phase over the Arctic do not show a persistent positive trend. This is not correct. Schmale et al. (2022) suggest no uniform picture of a trend in the Arctic region. The trends in particulate matter of MSA vary depending on the location and the decade.
Line 77: Which precursor vapors? Please specify.
Line 77-80: Sentence starting with “As a result….. Omit the sentence as its content falls outside the scope of this paper. As such, it is not pertinent and only useful for raising funds.
Line 104-105: “of these gas-phase species in the Arctic.” Please specify which gases were observed in the Arctic and where and when they were collected. None of the cited papers seems to report on new particle formation (observations and modeling using in situ observations) over the pack ice or any of the precursor gases discussed above. Suggested for further reading are Baccarini et al., 2020; Bigg et al., 2001; Kerminen et al., 2001; Leck and Persson, 1996a; Karl et al., 2012; 2013.
Line 113-114: The study's main weakness is the lack of analysis of MSAp/nss-SO4 molar ratios, which results in unclear conclusions on the high gas phase MSA periods observed in the present study when compared with previously reported inner Arctic low particulate MSA concentrations (e.g., Leck and Persson, 1996a).
Line 155-161: Diesel exhaust is a direct source of sulfuric acid (depending on engine load, fuel type, and fuel sulfur content), especially when run in connection with a diesel particle filter or an oxidative after-treatment system, which reduces hydrocarbon emissions but simultaneously increases SO2 to SO3 conversion, responsible for direct sulfuric acid formation. Nucleation in diesel exhaust from engines equipped with after-treatment or particle filters may result in enhanced nucleated particles, see Pirjola and Karl (2015).). Typically, reported conversion rates of SO2 to SO3 for ships using low sulfur fuels are in the range of 1–3%, leading to sulfuric acid concentrations in the range of 0.1–0.5 x 10^11 molecules/cm^3 close to ship stack (Karl et al., 2020). Give details on the ship engine of the Polarstern and possible use after treatment systems of the diesel exhaust. Did they run the ship engine all the time during the drift? Which fuel was used, and what was the sulfur content? Also, when helicopter flights and snowmobiles are considered?
Line 175-176: I firmly believe that the current data shown in panel A for respective Figs S2, S3, and S4 is inadequate in demonstrating the differences between clean and polluted periods. To better showcase these differences, it would be beneficial to include daily examples before and after applying the pollution mask. An example of this can be found in Figure S1 of Boyer et al.'s 2023 publication."
Line 188-189: An alternative and much more likely explanation for the differences between polluted and clean sampling periods would be that all data collected suffer from varying degrees of pollution. It’s naive to assume that all air pollution or conversion of SA from SO2 never recycles over the sampling platform.
Previous studies (e.g. Bigg et al., 2001) of over-the-pack ice have shown that not only necessary to be able to specify gas phase concentrations in the atmosphere and their possible sources, but we also must understand the thermodynamic structure of the lower atmosphere (typically a well-mixed shallow boundary layer at the surface, only a couple hundred meters deep, capped by a temperature inversion below the free troposphere), the dynamics of the boundary layer, and processes important in exchange between the air and ocean top layers to fully consider the short time variability on the constituents under study. Have any in situ observed meteorological analyses of your data been considered? Suggested for further reading by Tjernström et al., 2012; 2014.
Line 191: Clarify if the ppb unit is by volume or mass.
What is the meaning of a detection limit of 1 ppb for SO2?
Doesn’t it imply that any data below 1 ppb, if detected by the Thermo Fisher Scientific instrument, should be disregarded since it has significant uncertainty? This is especially important as SO2 levels in pack ice during summer and early autumn are typically in the lower 10th of a ppt(v) range (Kerminen et al., Leck and Persson, 1996a; Bigg et al., 2001).
Line 193: How much of the SO2 data was removed due to contamination? I see no black line for the SO2 mixing ratios, only black-filled circles. From this display, it’s impossible to resolve the removed data periods.
Line 315: The seasonality of observed sulfuric acid suggests that high concentrations during winter and spring are related to the Arctic haze phenomenon. Although the paper states that the sulfur chemistry and conversion from SO2to sulfuric acid is out of the scope of the study (Page 12, L 315-316), an explanation must be provided on how gaseous sulfuric acid can be produced in the absence of sunlight. Furthermore, it should be addressed over which distances sulfuric acid in the gas phase can be transported from lower latitudes, concerning its strong tendency to attach to particles and the frequent fog scavenging and wet deposition sinks during its transport from lower latitudes into the Central Arctic.
Figure 1: The frequency range of sulfuric acid, methanesulfonic acid, and iodic acid data in Figure 1 is not annotated on the x-axis.
Figure 3. Could you please specify the differences in the sampling locations with the same graphic as shown in Figure 2?
Litteratur
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Leck, C., Matrai, P., Perttu, A.-M., and Gårdfeldt, K.: Expedition report: SWEDARTIC Arctic Ocean 2018, Swedish Polar Research Secretariat, Stockholm ISBN 978-91-519-3671-0, 2019.
Lucas, D.D, R., G., Prinn, 2002, Mechanistic studies of dimethylsulfide oxidation products using an observationally constrained model, https://doi.org/10.1029/2001JD000843.
Lundén J., G. Svensson and C. Leck, 2007, Influence of meteorological processes on the spatial and temporal variability of atmospheric dimethyl sulfide in the high Arctic summer, J. Geophys. Res.,. 112, D13308.
Lundén, J., Svensson, G., Wisthaler, A., Tjernström, M., Hansel, A. and Leck, C.: The vertical distribution of atmospheric DMS in the high Arctic summer, Tellus, Series B, 62, pp. 160-171, 2010.
Orellana M.V., P.A. Matrai, C. Leck, C. D. Rauschenberg, A. M. Lee, and E. Coz 2011, Marine microgels as a source of cloud condensation nuclei in the high Arctic, PNAS, 108 (33): 13612-13617.
Quinn and Bates, 2011
Pirjola, L., Karl, M., Rönkkö, T., and Arnold, F.: Model studies of volatile diesel exhaust particle formation: are organic vapours involved in nucleation and growth?, Atmos. Chem. Phys., 15, 10435–10452, https://doi.org/10.5194/acp-15-10435-2015, 2015.
Tjernström, M., C. E. Birch, I. M. Brooks, M. D. Shupe, P. O. G. Persson, J. Sedlar, T. Mauritsen, C. Leck, J. Paatero, M., Szczodrak, and C. R. Wheeler, 2012, Meteorological conditions in the central Arctic summer during the Arctic Summer Cloud Ocean Study (ASCOS), Atmos. Chem. Phys., 12, 1-27.
Tjernström, M., Leck, C., Birch, C. E., Bottenheim, J.W., Brooks, B. J., Brooks, I. M., Bäcklin, L., Chang, R. Y.-W., Granath, E., Graus, M., Hansel, A., Heintzenberg, J., Held, Hind, A., de la Rosa, S., Johnston, P., Knulst, J., de Leuuw, G., di Liberto, L., Martin, M., Matrai, P. A., Mauritsen, T., Muller, M., Norris, S. J., Orellana, M. V., Orsini, D. A., Paatero, J., Persson, P. O. G., Gao, Q., Rauschenberg, C., Ristovski, Z., Sedlar, J., Shupe, M. D., Sireau, B., Sirevaag, A., Sjogren, S., Stetzer, O., Swietlicki, E., Szczodrak, M., Vaattovaara, P., Wahlberg, N., Westberg, M., and Wheeler, C. R., 2014, The Arctic Summer Cloud-Ocean Study (ASCOS): overview and experimental design, Atmos. Chem. Phys., 14, 2823-2869.
Citation: https://doi.org/10.5194/egusphere-2023-2953-RC4 - AC1: 'Comment on egusphere-2023-2953', Matthew Boyer, 15 Jun 2024
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-2953', Anonymous Referee #1, 07 Feb 2024
Comments to the muanuscript egusphere-2023-2953
Boyer et al. The annual cycle and sources of relevant aerosol precursor vapors in the central Arctic.
Reviewer's comments
The article presents and analyzes the first time series of aerosol precursor vapors (sulfuric acid (SA), methanesulfonic acid (MSA), and iodic acid (IA)) that are relevant to the central Arctic during MOSAiC. The authors conducted the measurements with state-of-the-art instruments, and the results are crucial in assessing the impact of anthropogenic emissions in the Arctic. The article is well structured, and well written, and only requires minor corrections before acceptance.
Minor comments
- The article discusses the crucial findings related to the concentration of atmospheric gases in the Arctic. However, the information is not presented in a concise format such as a table, which would enable the reader to easily examine the data. It is recommended to include a table that displays the monthly and seasonal averages of the primary anthropogenic pollutants.
- The date in Figure 4 is confusing. It is recommended to improve the date and use a single format.
- Figure 1 presents the gas phase time series for SA, MSA, and IA during clean and polluted periods using a violin-type scheme. This type of schematic can be a bit confusing. It is recommended to present the information in another format, for example, box-and-whisker diagrams. Could you expand the description of these results? Perhaps showing a table with the main statistical results.
- Figure 2c shows several results that are difficult to interpret. Is it possible that you could improve or present these results in another format?
- The message describing Figure 2c mentions the dashed white line denoting the monthly median latitude of Polarstern during the campaign. However, in Figure 2c no dotted line is shown. The only one observed is a continuous white line.
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RC2: 'Comment on egusphere-2023-2953', Anonymous Referee #2, 11 Apr 2024
Boyer et al. describe one year of relevant aerosol precursor in the gas phase from the central Arctic during the MOSAiC expedition from Sep 2019 to Oct 2020. The data include sulfuric acid (SA), methanesulfonic acid (MSA), and iodic acid (IA). They used the FLEXPART simulations, inverse modeling, and satellite chlorophyll-a (chl-a) to interpret the seasonal variability of the studied parameters and identify their source regions. The results conclude that natural and anthropogenic sources contribute to different aerosol types depending on the season, biotic and abiotic factors, and air mass movement. The information provided and the study's conclusions could be helpful to the scientific community. The manuscript does, however, require more explanation in some sections. The results visualizations, as I explain below, are my major concern.
General comments:
Section 2.6, Line 207: The FLEXPART and inverse modeling need further explanation on how they work. For instance, what are the frequency, timing and length of back-trajectories used? Where do the main sources of air mass dominate during the measurement period? A figure showing the air mass back-trajectories in the supplement would be beneficial. While ECLIPSE is a fundamental tool in presenting the results, no details on how It works, references and previous applications.
The conclusion section is long and has discussion sentences/cited references that might be moved to Results and Discussions. The Section shall summarize the major findings along with their implications.
Specific comments:
Line 94: Between brackets, define the HOx, for example, (OH and H2O).
Line 97: At least define what IxOy refers to at the 1st mention.
Figure 1: The data is misleading and the word “time series” in the caption is not appropriate. From the 1st glance, the readers may interpret that the colors distinguish between the input from biogenic (clean) and anthropogenic (polluted) sources. While I see the polluted cases represent the excess concentration to the biogenic one (polluted + biogenic). Indeed, I think this figure after a suitable explanation could be transferred to the supplementary material since it doesn’t contribute to the main conclusion of the study.
Line 178: A statistical test would be more robust to evaluate that there is no significant difference in medians.
Line 200: Not only cloudiness but also the low-incidence sun angle in winter hinders the measurement of chl-a from satellites at high latitudes.
Line 270: do you think the word “diurnal” fits the explanation here? Diurnal means 24-hour variations from day to night.
Figure 2: I don’t see the advantage of adding the 5-minute time resolution data in the background. The figure presents the annual cycle, so the monthly median with the shaded area or monthly box charts that describe the whole statistics is enough. Panel-A: the left y-axis is hidden. Panel C: It is better to present the missing data in chl-a as blank (white) to differentiate low values and non-measured times. Accordingly, the dotted white line must be modified.
Figure 3: Same comment as Figure 2. Presenting a time average (median) may be better to highlight the main variations throughout the time series.
Figure 4: The presentation of the data is hard to interpret. For example, the oceanic contribution in July is about 0.1 µg/m3 or (0.18 – 0.1 µg/m3). Indeed, I see Fig. S8 is worth presenting in the main manuscript rather that Fig. 4.
Figures 5, 6, and 7: In my view, the colors show the contribution of each polygon, which, when added together, gives the concentration overall.
Line 375: Refer to the polygon number.
Line 420: Citing Park et al. is not enough here because it handles the DMS rather than MSA. There are studies in the literature that have reported the link between marine biological activity and aerosol chemical composition (or MSA) in different marine environments (e.g., North Atlantic, Mediterranean and Eastern China Seas).
Line 443: Introducing an equation or more explanation on the influence index calculation and the unit used is required to make it clearer.
Line 447: It is worth highlighting that DMS emissions are mostly related to senescent phytoplankton cells rather than healthy cells.
Line 723: Who is MDO? What is the role of BH?
Typos:
Line 52: “product” instead of “byproduct”
Line 60: “sulfur” instead of “sulfate”
Line 151: -50% to …
Line 255: remove “or”
Citation: https://doi.org/10.5194/egusphere-2023-2953-RC2 -
RC3: 'Comment on egusphere-2023-2953', Anonymous Referee #3, 15 Apr 2024
The manuscript presents very interesting and useful data. It is well organized and clearly written and the elaborations and conclusions are scientifically sound. I recommend publication once the following minor issues are addressed.
Sect. 2.3. This Paragraph deals with a key issue that should be addressed more quantitatively. For the provided plots it is quite evident that pollution from the ship or ongoing surrounding activities did not spoil the measurements, nevertheless the differences should be presented more quantitatively: a statistics test should be employed to demonstrate that the data distribution are not statistically different between the “clean” and “polluted” data subsets. Furthermore, I find interesting the fact that, judging from Figure 1, MSA is more affected from pollution than SA (the difference between the “clean” and “polluted” medians is higher for the MSA case than for SA): have the authors an explanations for this? Which activity can be a source of MSA?
Sect. 2.5. Which time resolution have the CHL data?
Sect. 2.6. Please provide more information on the back trajectories: time resolution, length, frequency. Moreover, was the travelling height of the back-trajectories taken into consideration for the elaborations?
L265. Why “including SA, MSA, and IA”? Fig. 2a presents precisely SA, MSA and IA.
L280. No “dotted white line” is present in Figure 2c.
L317. “To further evaluate the sources of SO2 and SA in our measurements, we examined emissions of anthropogenic sulfate…”. I do not think this expression to be correct: by coupling the ECLIPSE v6b with flexpart trajectories the authors are not evaluating the emissions. Please reformulate the sentence.
L371. “Despite lower anthropogenic SO4-S influence from the North Asia sector during March and April”: refer to the appropriate Figure here, for major clarity.
L640. Correct in “sea-ice continues to decline”.
Citation: https://doi.org/10.5194/egusphere-2023-2953-RC3 -
RC4: 'Comment on egusphere-2023-2953', Anonymous Referee #4, 07 May 2024
The annual cycle and sources of relevant aerosol precursor vapors in
The Central Arctic by Boyer et al.
General:
This paper is potentially dangerous as it could impede our process understanding of the role of precursor gases in aerosol formation and growth. This could have long-term implications for our knowledge of cloud formation and climate change in the inner Arctic basin, affecting future generations.
The manuscript references several relevant articles from the field, but the literature survey is not comprehensive. Over the past decades, a substantial amount of observational data has been collected over the summer and early autumn pack ice, which is essential to this study’s results and conclusions and, therefore, deserves a discussion and comparison. It would be beneficial to mention or learn from the previous work by Tjernström, Leck, and their colleagues over the last 30 years on the inner Arctic pack ice area, including the marginal ice zone.
The paper gives the impression that “continuous” sampling had occurred at one Arctic location. All measurement plots, except for Fig. 2, show only time series, disregarding the variation of latitude and longitude during sampling while on a moving ship.
The inverse model uses the FLEXPART source-receptor-relationship and the measurement time series from the ship to identify potential source regions. It is unclear whether and which DMS emissions were used in the FLEXPART runs. While the inverse modeling technique results in important insights into the source regions of the aerosol precursors in different seasons, the time series analyses in the paper are superficial.
It's further unclear why no observation of particulate MSA (MSAp) or nss-SO4 was included in the manuscript. Were these parameters not measured during MOSAiC? The conclusions remain vague without an analysis of MSAp/nss-SO4 molar ratios, especially since this study’s high-MSA concentration periods provide little explanation for the low levels of particulate MSA reported from previous studies over the summer early autumn pack ice area.
The paper should be rejected foremost because of grave methodological uncertainties, which must be specified to be convincing, such as demanding a cleaned CPC record showing that decontamination resulted in CPC levels comparable to previous results over the pack ice when existing. After a convincing decontamination, the study could have made an important descriptive contribution to the sparsely sampled inner Arctic.
Detailed comments:
Line 36: Meier et al., 2014 could be replaced with a more suitable citation. Its focus is not on the air-sea exchange of particles.
Line 37: Define “in the Arctic”, “the central Arctic Ocean, “high Arctic”. Do you mean north of 80°?
Line 40: Discussing past observations made over the pack ice during summer and early autumn would be worthwhile. These observations have shown that particulate organics present in Aitken and accumulation mode aerosol and cloud water had properties like marine polymer gels. These gels were found to originate from the surface microlayer on leads. This behavior was attributed to the activity of ice microalgae, phytoplankton, and possibly bacteria. Some studies exploring these observations include Leck and Bigg 2005, Bigg and Leck 2008, Orellana et al. 2011, Karl et al. 2013, Hamacher-Barth et al. 2016, and Lawler et al. 2021.
Line 42: Please provide the exact citation indicating that 90% of CCN in the Arctic during summer is explained by NPF. Please include the latitude range and period used to define the summer Arctic.
Line 43-44: The region of the Arctic that is situated north of 80° witnesses a significant seasonal disparity all year round. The cause of this contrast can be attributed to the temperature and sea ice conditions, the uninterrupted sunlight in summer, and the prolonged polar darkness in winter. These diverse circumstances bring about significantly different atmospheric transport dynamics, atmospheric aerosol precursor gases, and their chemical reactions, which will affect the life cycle of aerosol particles over the pack ice area in distinct ways. Thus, the literature cited on a global evaluation of CCN formation by direct sea salt and ultrafine particles or CERN-CLOUD measurements of global particle formation or present and pre-industrial new particle formation does seem unrelated to this study’s observations over the pack ice area and as such, should be omitted. The only citation with some relevance is Kecorius et al., 2019.
Line 45-48: It should be clarified that the cited studies are performed in summer to early autumn, but Koike et al., 2019, report on two years of continuous in situ measurements at the Mount Zeppelin Observatory (78°56′N, 11°53′E), in Ny-Ålesund, Spitsbergen. The relevance of the inner Arctic of Koike et al.'s 2019 study is thus questioned; please omit.
Line 46: The Mauritzen et al. (2011) result only represents the inner Arctic summer; please add this information. Mauritsen et al. (2011) estimated a threshold of 10 to 16 CCN per cm3 as a minimum for cloud formation and sustenance. Past observation also found that the CCN concentrations around the ice sheet's edge were highest but dropped almost tenfold due to wet scavenging within 1-2 days of advection from the open sea into the pack ice (Bigg and Leck, 2001; Leck and Svensson, 2015).
Line 47-48: The modeling study conducted by Bulatovic et al. in 2021 aimed to investigate whether Aitken mode particles can serve as CCN. The study simulated median supersaturations between 0.2% and 0.4%, with a range of up to 1%. The results showed that even small Aitken mode aerosols of ~30nm diameter can be activated as long as larger accumulation particles are low in number concentration, preventing the depletion of excess water vapor. The simulations used typical aerosol size distributions encountered in the central Arctic during the summer/early autumn of 1991, 1996, 2001, and 2008 (Heintzenberg and Leck, 2012). It was found that having a low concentration of accumulation mode particles and a high concentration of Aitken mode particles in the inner Arctic during summer and early autumn, which created a favorable environment for the activation of CCN in the small Aitken mode range, is a rare occurrence.
The statements that the high Arctic summer/early autumn studies by Baccarini et al., 2020, and Karlsson et al., 2021, show that very small particles can act as CCN has to be weakened. No direct evidence has been presented in the studies since the conclusions were based on inferred proofing. Please also possibly add the results of Bulatovic et al., 2021.
Line 48: A citation is missing after “exceptionally high”; clarify when and where in the Arctic.
Line 49: To ensure the continuity of in situ data archives of the high Arctic north of 80°, unique measurements have been conducted during 5 research expeditions from 1991 to 2018. (Leck et al., 1996; Leck et al., 2001; Leck et al., 2004; Tjernström et al., 2014; Leck et al., 2019). Please remind the reader of their presence.
Line 52-57: The cited references are not specific to observations/modeling during the biologically most active conditions over the pack ice and at the marginal ice zone (MIZ). I would encourage the authors to read and cite the following papers and useful references therein: Leck and Persson, 1996a,b; Kerminen and Leck, 2001; Lundén et al., 2007; 2010.
Line 58-63: An important precursor of aqueous phase-produced sulfate is the DMS oxidation product hydroperoxylmethyl orthoformate (HPMTF), which has been completely overlooked in this study. The global burden of HPMTF has been calculated to be 2.6–26 Gg S (see Cala et al., 2023). The general understanding is that HPMTF is taken up rapidly in cloud water; however, Cala et al. (2023) found that rapid cloud uptake of HPMTF worsens the model–observation comparison.
It would also be worthwhile to discuss the role of direct formation of sulfuric acid from the gas-phase oxidation of DMS with the OH radical, as demonstrated by Berndt et al. (2023). The direct production of sulfuric acid in DMS oxidation has been speculated about in the literature for decades (e.g., cite Lucas and Prinn, 2002 and Karl et al., 2007).
In fact, during summer, the gas phase data collected in the MOSAiC expedition after a convincing decontamination could potentially help understand the relevance of direct sulfuric acid formation in the central Arctic.
Line 64: Please cite Leck and Bigg, 2011, Heintzenberg et al., 2017, and Karl et al., 2019. Yet another explanation for the occurrence of high numbers of nucleation mode particles in the high Arctic, involving granular nano gels in addition to sulfuric acid, was proposed by Karl et al. (2013). The appropriate discussion of these findings on nanoparticle events observed over the Arctic Ocean must be included in the introduction.
Line 67-69: The citations report results from observations during spring and summer in the Arctic. This information is too unspecific. Please clarify for each of the citations used from where (baseline station, latitude and longitude, at the MIZ, or over the pack ice area) and more exactly during which period they represent.
Line 69-70: The cited papers are irrelevant to the present study as they provide general information or cover only a small part and a short period in the central Arctic Basin. Therefore, it is recommended that all the citations be removed.
Ghahremaninezhad et al., 2019, do not report any observations on CCN. They implemented DMS(g) in Environment and Climate Change Canada’s forecast model and compared the model simulations with DMS(g) measurements made in Baffin Bay and the Canadian Arctic Archipelago in July and August 2014.
Mayer et al., 2020, did not perform any direct measurements of CCN and only inferred them from a 6-day mesocosm experiment throughout a phytoplankton bloom.
Charlson et al., 1987, presented a hypothesis about the feedback between ocean temperature and cloud radiative properties via DMS ocean and air, particulate Sulftat, and CCN/numbers of cloud droplets. Observations from the Arctic and other marine regions have questioned the key role attributed to DMS in the CLAW hypothesis for over a decade (Leck and Bigg, 2007; Quinn and Bates, 2011).
Carslaw et al., 2010 is a review paper that discusses natural aerosols in the Earth System as a whole.
Line 72-73: I disagree; there is no direct evidence that decadal DMS emission trends are positive across the Arctic due to decreasing sea ice coverage. Both studies cited infer temporal variations in ocean dimethyl sulfide emissions using either a remote sensing algorithm based on either estimated sea-surface DMS concentration (nM) from remotely sensed chlorophyll concentration light penetration depths and photosynthetically available radiation or reconstruction of the annual and seasonal MSA flux with monthly resolution from a high-resolution ice core obtained from the SE-Dome, southeastern Greenland Ice Sheet (ca 250 masl) and satellite-derived chlorophyll-a datasets.
Please replace “direct evidence” with “inferred evidence”.
It should be noted that the estimates made by Gali et al. for the central Arctic basin are subject to large uncertainties as they are based solely on inferred remote sensing. Additionally, it is important to consider the satellite orbit inclination and instrument swath, which create a data gap north of approximately 87 degrees.
Line 75-77: The paper by Schmale et al. (2022) is referenced to support the claim that DMS oxidation products in the aerosol phase over the Arctic do not show a persistent positive trend. This is not correct. Schmale et al. (2022) suggest no uniform picture of a trend in the Arctic region. The trends in particulate matter of MSA vary depending on the location and the decade.
Line 77: Which precursor vapors? Please specify.
Line 77-80: Sentence starting with “As a result….. Omit the sentence as its content falls outside the scope of this paper. As such, it is not pertinent and only useful for raising funds.
Line 104-105: “of these gas-phase species in the Arctic.” Please specify which gases were observed in the Arctic and where and when they were collected. None of the cited papers seems to report on new particle formation (observations and modeling using in situ observations) over the pack ice or any of the precursor gases discussed above. Suggested for further reading are Baccarini et al., 2020; Bigg et al., 2001; Kerminen et al., 2001; Leck and Persson, 1996a; Karl et al., 2012; 2013.
Line 113-114: The study's main weakness is the lack of analysis of MSAp/nss-SO4 molar ratios, which results in unclear conclusions on the high gas phase MSA periods observed in the present study when compared with previously reported inner Arctic low particulate MSA concentrations (e.g., Leck and Persson, 1996a).
Line 155-161: Diesel exhaust is a direct source of sulfuric acid (depending on engine load, fuel type, and fuel sulfur content), especially when run in connection with a diesel particle filter or an oxidative after-treatment system, which reduces hydrocarbon emissions but simultaneously increases SO2 to SO3 conversion, responsible for direct sulfuric acid formation. Nucleation in diesel exhaust from engines equipped with after-treatment or particle filters may result in enhanced nucleated particles, see Pirjola and Karl (2015).). Typically, reported conversion rates of SO2 to SO3 for ships using low sulfur fuels are in the range of 1–3%, leading to sulfuric acid concentrations in the range of 0.1–0.5 x 10^11 molecules/cm^3 close to ship stack (Karl et al., 2020). Give details on the ship engine of the Polarstern and possible use after treatment systems of the diesel exhaust. Did they run the ship engine all the time during the drift? Which fuel was used, and what was the sulfur content? Also, when helicopter flights and snowmobiles are considered?
Line 175-176: I firmly believe that the current data shown in panel A for respective Figs S2, S3, and S4 is inadequate in demonstrating the differences between clean and polluted periods. To better showcase these differences, it would be beneficial to include daily examples before and after applying the pollution mask. An example of this can be found in Figure S1 of Boyer et al.'s 2023 publication."
Line 188-189: An alternative and much more likely explanation for the differences between polluted and clean sampling periods would be that all data collected suffer from varying degrees of pollution. It’s naive to assume that all air pollution or conversion of SA from SO2 never recycles over the sampling platform.
Previous studies (e.g. Bigg et al., 2001) of over-the-pack ice have shown that not only necessary to be able to specify gas phase concentrations in the atmosphere and their possible sources, but we also must understand the thermodynamic structure of the lower atmosphere (typically a well-mixed shallow boundary layer at the surface, only a couple hundred meters deep, capped by a temperature inversion below the free troposphere), the dynamics of the boundary layer, and processes important in exchange between the air and ocean top layers to fully consider the short time variability on the constituents under study. Have any in situ observed meteorological analyses of your data been considered? Suggested for further reading by Tjernström et al., 2012; 2014.
Line 191: Clarify if the ppb unit is by volume or mass.
What is the meaning of a detection limit of 1 ppb for SO2?
Doesn’t it imply that any data below 1 ppb, if detected by the Thermo Fisher Scientific instrument, should be disregarded since it has significant uncertainty? This is especially important as SO2 levels in pack ice during summer and early autumn are typically in the lower 10th of a ppt(v) range (Kerminen et al., Leck and Persson, 1996a; Bigg et al., 2001).
Line 193: How much of the SO2 data was removed due to contamination? I see no black line for the SO2 mixing ratios, only black-filled circles. From this display, it’s impossible to resolve the removed data periods.
Line 315: The seasonality of observed sulfuric acid suggests that high concentrations during winter and spring are related to the Arctic haze phenomenon. Although the paper states that the sulfur chemistry and conversion from SO2to sulfuric acid is out of the scope of the study (Page 12, L 315-316), an explanation must be provided on how gaseous sulfuric acid can be produced in the absence of sunlight. Furthermore, it should be addressed over which distances sulfuric acid in the gas phase can be transported from lower latitudes, concerning its strong tendency to attach to particles and the frequent fog scavenging and wet deposition sinks during its transport from lower latitudes into the Central Arctic.
Figure 1: The frequency range of sulfuric acid, methanesulfonic acid, and iodic acid data in Figure 1 is not annotated on the x-axis.
Figure 3. Could you please specify the differences in the sampling locations with the same graphic as shown in Figure 2?
Litteratur
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Citation: https://doi.org/10.5194/egusphere-2023-2953-RC4 - AC1: 'Comment on egusphere-2023-2953', Matthew Boyer, 15 Jun 2024
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Andreas Stohl
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