Can we gain knowledge on COS anthropogenic and biogenic emissions from a single atmospheric mixing ratios measurement site?

Berchet, Antoine; Pison, Isabelle; Huselstein, Camille; Narbaud, Clément; Remaud, Marine; Belviso, Sauveur; Abadie, Camille; Maignan, Fabienne

doi:https://doi.org/10.5194/egusphere-2024-549

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https://doi.org/10.5194/egusphere-2024-549

Preprints

12 Mar 2024

| 12 Mar 2024

Can we gain knowledge on COS anthropogenic and biogenic emissions from a single atmospheric mixing ratios measurement site?

Antoine Berchet, Isabelle Pison, Camille Huselstein, Clément Narbaud, Marine Remaud, Sauveur Belviso, Camille Abadie, and Fabienne Maignan

Abstract. Lack of knowledge still remains on many processes leading to COS atmospheric ﬂuxes, either natural such as the oceanic emissions or the vegetation and soil ﬂuxes, or anthropogenic, from industrial activities and power generation. Moreover, COS atmospheric mixing ratio data are still too sparse to evaluate the estimations of these sources and sinks. This study assesses the anthropogenic and biogenic COS ﬂuxes at the regional scale, in the footprint a measurement site in Western Europe, at a seasonal to diurnal time resolution over half a decade. The continuous time series of COS mixing ratios obtained at the monitoring site of Gif-sur-Yvette (in the Paris area) from August 2014 to December 2019 are compared to simulations with the Lagrangian model FLEXPART, transporting oceanic emissions, biogenic land ﬂuxes from the process-model ORCHIDEE and anthropogenic emissions by two different inventories. The anthropogenic emission inventory based on reported industrial emissions and the characteristics of coal power plants in Europe is consistent with the observations. The ﬂat temporal variability applied to anthropogenic ﬂuxes due to lack of information on industrial and power-generation activity in viscose factories and coal-power plants and the potential mismatches in the representation of the plumes emitted from these hot-spots in the model are the main limitations of this inventory. We ﬁnd that the net ecosystem COS uptake simulated by ORCHIDEE is underestimated in winter at night, which suggests improvements in the parameterization of the nighttime uptake by plants for COS.

Received: 23 Feb 2024 – Discussion started: 12 Mar 2024

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Journal article(s) based on this preprint

16 Jul 2025

Improved understanding of anthropogenic and biogenic carbonyl sulfide (COS) fluxes in western Europe from long-term continuous mixing ratio measurements

Antoine Berchet, Isabelle Pison, Camille Huselstein, Clément Narbaud, Marine Remaud, Sauveur Belviso, Camille Abadie, and Fabienne Maignan

Atmos. Chem. Phys., 25, 7499–7525, https://doi.org/10.5194/acp-25-7499-2025,https://doi.org/10.5194/acp-25-7499-2025, 2025

Short summary

Antoine Berchet, Isabelle Pison, Camille Huselstein, Clément Narbaud, Marine Remaud, Sauveur Belviso, Camille Abadie, and Fabienne Maignan

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2024-549', Anonymous Referee #1, 24 Apr 2024

Please refer to the supplement file as a pdf.

Citation: https://doi.org/10.5194/egusphere-2024-549-RC1
- AC1: 'Reply on RC1', Isabelle Pison, 21 Aug 2024
  
  Please see attached pdf.
  
  Citation: https://doi.org/10.5194/egusphere-2024-549-AC1
RC2:
'Comment on egusphere-2024-549', M.E. Whelan, 25 Apr 2024

Dear Berchet et al.,
This paper is a good application of the lead author’s work making FLEXPART more accessible. The treatment of the CS2 fields here is an improvement for the field, transforming emissions of CS2 to atmospheric COS with a reasonable conversion rate.
I have a few suggestions for making this work more impactful. It is unclear why the Zumkehr inventory was used without the improvements suggested by Belviso et al., (2023). Belviso et al., demonstrated the drawbacks to this inventory fairly conclusively! It might make sense to make the necessary changes and move on. Additionally, naming the improved anthropogenic scheme “home-made” is confusing. Zumkehr was also likely working from home. Using the designation “This Study” is clearer.
To improve our understanding of the atmospheric OCS balance, it would make sense to use a different biogenic uptake dataset instead, such as SiB4. Comparing SiB4 to ORCHIDEE in this framework might yield some interesting insights into our treatment of plant uptake.
10, 15-23 and Section 3.3, Figure 4: The footprints used here are calculated throughout the day. In efforts involving WRF-STILT, one recommended approach is to average afternoon tower measurements when the boundary layer is typically well-mixed. As the authors note, it could be that there is variation in the tower concentrations because of shifts in the mixing layer rather than shifts in the plant uptake or ocean background. While OCS is undoubtedly being taken up at night by partially-closed stomata, there is also a dynamic shift in the state of the mixed layer in contact with the tower. How well does FLEXPART treat the boundary layer? Perhaps some explanation needs to be included here on the uncertainty introduced by taking footprints at different times of day. Alternatively, averaging concentrations when the layer is stable would side-step some of the synoptic-scale complications.
Minor comments
The title of the article needs to be revised. “Can we gain knowledge on COS anthropogenic and biogenic emissions from a single atmospheric mixing ratios measurement site?” is a yes or no question. Here we learn that OCS uptake is underestimated at night and that there are limitations in the anthropogenic inventory. Perhaps something like, “improvements to anthropogenic and biogenic fluxes of OCS in Western Europe”.
Abstract: use of the word “fluxes” versus “emissions” leads to confusing sentence constructions. Page 1, line 3: “Moreover, COS atmospheric mixing ratio data are still too sparse to evaluate the estimations of these sources and sinks.” - do you mean on the global scale?
4, 25: I don’t see the Mace Head data plotted on Figure 1. Is something missing in the pdf?
Figure 1. Categories in the legend are missing in the graph in (a) and (b). For (a), it appears that the brown is background and the black dots, which end in 2015, are observations from GIF?
6, 5-6: There are good reasons to leave out these fluxes. Making the assumptions explicit, e.g. these fluxes do not contribute meaningfully to the observations, would be useful here.
6, 13: similar results on the global scale?
6, 27: COS uptake is related to stomatal conductance. For C3 and C4 plants, we expect stomatal conductance to increase during the day. Stomatal conductance never quite gets to zero when closed at night or in drought. If the ORCHIDEE plant uptake is based on Berry et al 2013, uptake should vary with stomatal conductance in the model as well as in reality.
7, 7-9: It is unclear what this means. Are the national emissions erroneously attributed to urban hot spots? And we know that these hot spots are an artifact? But looking at Figure 2, it appears that Zumkehr spreads national emissions over the entire country, whereas the improved inventory locates emissions in a collection of hotspots.
Figure 2. It would be good to have a color bar or similar for the contours in 2(f) so that the figure can be understood without digging into the text.
Thanks for the work in interpreting these data. It would be excellent to use this work to initiate a COS observing network analogous to ICOS.
Sincerely,
Mary Whelan

Citation: https://doi.org/10.5194/egusphere-2024-549-RC2
- AC1: 'Reply on RC1', Isabelle Pison, 21 Aug 2024
  
  Please see attached pdf.
  
  Citation: https://doi.org/10.5194/egusphere-2024-549-AC1

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2024-549', Anonymous Referee #1, 24 Apr 2024

Please refer to the supplement file as a pdf.

Citation: https://doi.org/10.5194/egusphere-2024-549-RC1
- AC1: 'Reply on RC1', Isabelle Pison, 21 Aug 2024
  
  Please see attached pdf.
  
  Citation: https://doi.org/10.5194/egusphere-2024-549-AC1
RC2:
'Comment on egusphere-2024-549', M.E. Whelan, 25 Apr 2024

Dear Berchet et al.,
This paper is a good application of the lead author’s work making FLEXPART more accessible. The treatment of the CS2 fields here is an improvement for the field, transforming emissions of CS2 to atmospheric COS with a reasonable conversion rate.
I have a few suggestions for making this work more impactful. It is unclear why the Zumkehr inventory was used without the improvements suggested by Belviso et al., (2023). Belviso et al., demonstrated the drawbacks to this inventory fairly conclusively! It might make sense to make the necessary changes and move on. Additionally, naming the improved anthropogenic scheme “home-made” is confusing. Zumkehr was also likely working from home. Using the designation “This Study” is clearer.
To improve our understanding of the atmospheric OCS balance, it would make sense to use a different biogenic uptake dataset instead, such as SiB4. Comparing SiB4 to ORCHIDEE in this framework might yield some interesting insights into our treatment of plant uptake.
10, 15-23 and Section 3.3, Figure 4: The footprints used here are calculated throughout the day. In efforts involving WRF-STILT, one recommended approach is to average afternoon tower measurements when the boundary layer is typically well-mixed. As the authors note, it could be that there is variation in the tower concentrations because of shifts in the mixing layer rather than shifts in the plant uptake or ocean background. While OCS is undoubtedly being taken up at night by partially-closed stomata, there is also a dynamic shift in the state of the mixed layer in contact with the tower. How well does FLEXPART treat the boundary layer? Perhaps some explanation needs to be included here on the uncertainty introduced by taking footprints at different times of day. Alternatively, averaging concentrations when the layer is stable would side-step some of the synoptic-scale complications.
Minor comments
The title of the article needs to be revised. “Can we gain knowledge on COS anthropogenic and biogenic emissions from a single atmospheric mixing ratios measurement site?” is a yes or no question. Here we learn that OCS uptake is underestimated at night and that there are limitations in the anthropogenic inventory. Perhaps something like, “improvements to anthropogenic and biogenic fluxes of OCS in Western Europe”.
Abstract: use of the word “fluxes” versus “emissions” leads to confusing sentence constructions. Page 1, line 3: “Moreover, COS atmospheric mixing ratio data are still too sparse to evaluate the estimations of these sources and sinks.” - do you mean on the global scale?
4, 25: I don’t see the Mace Head data plotted on Figure 1. Is something missing in the pdf?
Figure 1. Categories in the legend are missing in the graph in (a) and (b). For (a), it appears that the brown is background and the black dots, which end in 2015, are observations from GIF?
6, 5-6: There are good reasons to leave out these fluxes. Making the assumptions explicit, e.g. these fluxes do not contribute meaningfully to the observations, would be useful here.
6, 13: similar results on the global scale?
6, 27: COS uptake is related to stomatal conductance. For C3 and C4 plants, we expect stomatal conductance to increase during the day. Stomatal conductance never quite gets to zero when closed at night or in drought. If the ORCHIDEE plant uptake is based on Berry et al 2013, uptake should vary with stomatal conductance in the model as well as in reality.
7, 7-9: It is unclear what this means. Are the national emissions erroneously attributed to urban hot spots? And we know that these hot spots are an artifact? But looking at Figure 2, it appears that Zumkehr spreads national emissions over the entire country, whereas the improved inventory locates emissions in a collection of hotspots.
Figure 2. It would be good to have a color bar or similar for the contours in 2(f) so that the figure can be understood without digging into the text.
Thanks for the work in interpreting these data. It would be excellent to use this work to initiate a COS observing network analogous to ICOS.
Sincerely,
Mary Whelan

Citation: https://doi.org/10.5194/egusphere-2024-549-RC2
- AC1: 'Reply on RC1', Isabelle Pison, 21 Aug 2024
  
  Please see attached pdf.
  
  Citation: https://doi.org/10.5194/egusphere-2024-549-AC1

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

AR by Isabelle Pison on behalf of the Authors (21 Aug 2024) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (02 Sep 2024) by Tanja Schuck

RR by Wu Sun (26 Sep 2024)

Suggestions for revision or reasons for rejection

In this manuscript, Berchet et al. use a five-year record of atmospheric COS concentrations measured at a Paris suburb site to examine anthropogenic and biogenic COS fluxes over Western Europe. Given the sparsity of COS observations globally, it is encouraging to see this work leveraging long-term COS observations at a single site to shed light on regional COS flux components, aided by a Lagrangian transport model. The study shows promise in enhancing the usability of COS as a photosynthetic tracer at regional scales.

While the revised manuscript has been improved in response to prior review comments, I find some remaining issues. I have a few suggestions for improving the robustness and clarity of the findings.

To alleviate potential bias from nighttime boundary layer parameterization, I suggest running additional tests to re-examine the diagnostics for different flux combinations (Table 2) using only mid-afternoon COS observations. Parameterization of the nighttime boundary layer is notoriously challenging and can lead to transport errors (e.g., Díaz-Isaac et al., 2018; Lopez-Coto et al., 2020; Monteiro et al., 2024). As a result, most Lagrangian inverse modeling studies assimilate only observations during well-mixed afternoon conditions, which both the authors and the reviewer, Dr. Whelan, have acknowledged. Lacking information on how well FLEXPART represents the nighttime boundary layer, I am not confident that bias in simulated nighttime concentrations could be attributed solely to the representation of nighttime stomatal conductance in terrestrial biosphere models (ORCHIDEE and SiB4). While I agree with some of the reasoning in the authors’ response, I do not see this issue fully addressed. I reckon that the simplest way to test this issue could be to redo a set of analyses using only mid-afternoon COS observations and see if error diagnostics still follow the patterns in Table 2. As the atmosphere integrates fluxes day and night, afternoon observations should still be sensitive to fluxes in previous nights within the footprint area.

On the evaluation of anthropogenic COS flux estimates, because point sources of viscose and coal industries are largely collocated (Fig. 2c), their influences on observed COS concentrations would be highly correlated. Therefore, it seems challenging to evaluate COS fluxes from these two sectors separately. On the other hand, because changes in the wind direction may allow the site to pick up flux signals coming from different regions (Paris/Rouen, Benelux, British Isles, etc.), it would seem more helpful to focus on contributions from different regions rather than different industries that are collocated in space.

On the evaluation of biogenic COS fluxes, given that the focus is on nighttime bias, presumably resulting from underestimated nighttime stomatal conductance, and on summertime bias caused by potential emissions from certain crops, it may help to further assess bias, RMSE, and correlation (following Table 2) for daytime and nighttime measurements and by season. Model bias in representing nighttime COS uptake has been known since Kooijmans et al. (2017), and it would be better to give quantitative insights beyond reiterating this message. I suggest some simple tests along this line, for example, treating nighttime and daytime ecosystem fluxes as two separate tracers and checking how much nighttime fluxes need to be bumped up in order to match observed COS concentrations. This would provide more detailed insights into model bias and help inform relevant process representations in terrestrial biosphere models.

Lastly, the study could give readers a high-level view of whether anthropogenic or biogenic COS fluxes dominate the variability in observed COS drawdown or enhancement (ΔCOS). Comparing Fig. 1d and Fig. 4, it appears the study domain is dominated by biogenic COS fluxes, but I’m not sure. I suspect that many in the carbon cycle research community would care about this question, but I don’t see it explicitly answered.

Specific comments

L4: "at a better scale than the global scale" –> "at the regional scale"

L13–14: "We find that the net ecosystem COS uptake simulated by both ORCHIDEE and SiB4 is underestimated in winter at night" - As I suggested above, it would be better to redo the evaluation with mid-afternoon COS observations only to confirm if the bias results from nighttime stomatal conductance representation.

L16–17: "In Summer, both models properly represents fluxes, with better agreement from ORCHIDEE in terms of magnitudes." - What about potential COS emission episodes?

L24–37: Since this study is not an atmospheric inversion, I don't see a need to introduce it. Consider focusing on the forward model application of linking flux fields to mixing ratios.

L40–80: This part feels overly detailed as an introduction. I suggest consolidating these bullet points into a coherent paragraph and emphasizing the key uncertainties this study aims to tackle. To tidy it up, it may help to list the magnitudes of different COS flux components in a table.

L100–L110: This paragraph needs to give a clear roadmap of what the study aims to achieve. Currently, it sounds like this study is picking on the bias in Zumkehr et al. (2018) inventory, but there is more to be said about biogenic COS fluxes and the underlying physiological processes.

L121–122: How often was the calibration carried out?

L134: Here, it would help to refer to Sect. 2.3 for background calculation (L232–238). Or move that paragraph on background calculation here.

L148: "DMS emissions can only be non natural ..." - Wetlands and the ocean do emit DMS. I get the point of this sentence, but the logic does not follow.

L151: "box models" - I would call them spatially resolved box models to avoid potential confusion.

L165–168: Does this mean that ORCHIDEE and SiB4 COS flux fields used here are optimized posterior estimates?

L172: "In particular, biogenic fluxes exhibit a significant diurnal cycle." - I am confused here. Aren’t the posterior fluxes from Remaud et al. (2022) and Ma et al. (2021) monthly?

L175: "We assess the sensitivity of our simulations to daily varying biogenic fluxes by using 3-hourly vegetation uptake as simulated by ORCHIDEE and SiB4 for the year 2016." - Are these posterior flux estimates or unadjusted prior flux estimates?

L183–184: The components sum to 61.4 GgS per year not 62.1 GgS per year. Are there other minor components not listed here?

L186: I think you mean "effective" not "efficient".

L220: One advantage of a Lagrangian model over an Eulerian model is the flexible resolution at which transport is resolved. As a result, Lagrangian models can use meteorological input at a finer resolution than the resolution at which footprints are aggregated. Is there a reason to run FLEXPART with 1° meteorology input instead of the native resolution (0.25°) of ERA5?

L243: An RMSE of 35 ppt does not feel like a small error; it seems to be around 1/3 of the seasonal cycle amplitude of COS (Fig. 1b).

L246–248: Again, here it is crucial to clarify whether the three-hourly flux estimates are optimized posterior estimates or prior estimates coming out directly from terrestrial biosphere models.

L249: "from 0.74 to 0.72" - The decrease in correlation is a bit surprising because, all else being equal, I would expect the correlation to stay unchanged or increase slightly with the inclusion of diurnal variability. Are these correlation coefficients just for the year 2016 or the entire period?

L249: "The variability is not better reproduced when adding the natural emissions to the background" - Which component(s) of "natural emissions"?

L276–291: Unclear from this paragraph how the contributions of biogenic, anthropogenic, and oceanic COS fluxes to observed COS concentrations compare with each other. I suggest adding a table to list their respective contributions to ΔCOS.

Fig. 1: In panel a, it's quite challenging to distinguish between GIF (afternoon) from GIF (all). Consider enhancing the color contrast or use different symbols. In the caption, background calculation should refer to Sect. 2.3 not 2.1.

Fig. 2: In panel e, it would be more helpful to show the summed footprint map over the entire study period to check the influence area coverage. Readers may not know if the footprint map for May 2019 is representative of the whole period (2014–2019).

Fig. 4: Unclear what "growths" means in the figure legend. For panel c, it would be better to report COS fluxes in pmol m^-2 s^-1.

References cited

Díaz-Isaac, L. I., Lauvaux, T., & Davis, K. J. (2018). Impact of physical parameterizations and initial conditions on simulated atmospheric transport and CO2 mole fractions in the US Midwest. Atmospheric Chemistry and Physics, 18(20), 14813–14835. https://doi.org/10.5194/acp-18-14813-2018

Kooijmans, L. M. J., Maseyk, K., Seibt, U., Sun, W., Vesala, T., Mammarella, I., Kolari, P., Aalto, J., Franchin, A., Vecchi, R., Valli, G., & Chen, H. (2017). Canopy uptake dominates nighttime carbonyl sulfide fluxes in a boreal forest. Atmospheric Chemistry and Physics, 17(18), 11453–11465. https://doi.org/10.5194/acp-17-11453-2017

Lopez-Coto, I., Hicks, M., Karion, A., Sakai, R. K., Demoz, B., Prasad, K., & Whetstone, J. (2020). Assessment of Planetary Boundary Layer Parameterizations and Urban Heat Island Comparison: Impacts and Implications for Tracer Transport. Journal of Applied Meteorology and Climatology, 59(10), 1637–1653. https://doi.org/10.1175/JAMC-D-19-0168.1

Ma, J., Kooijmans, L. M. J., Cho, A., Montzka, S. A., Glatthor, N., Worden, J. R., Kuai, L., Atlas, E. L., & Krol, M. C. (2021). Inverse modelling of carbonyl sulfide: Implementation, evaluation and implications for the global budget. Atmospheric Chemistry and Physics, 21(5), 3507–3529. https://doi.org/10.5194/acp-21-3507-2021

Monteiro, V., Turnbull, J. C., Miles, N. L., Davis, K. J., Barkley, Z. R., & Deng, A. (2024). Assimilating Morning, Evening, and Nighttime Greenhouse Gas Observations in Atmospheric Inversions [preprint]. ESS Open Archive. https://doi.org/10.22541/essoar.171007090.01499748/v1

Remaud, M., Chevallier, F., Maignan, F., Belviso, S., Berchet, A., Parouffe, A., Abadie, C., Bacour, C., Lennartz, S., & Peylin, P. (2022). Plant gross primary production, plant respiration and carbonyl sulfide emissions over the globe inferred by atmospheric inverse modelling. Atmospheric Chemistry and Physics, 22(4), 2525–2552. https://doi.org/10.5194/acp-22-2525-2022

Zumkehr, A., Hilton, T. W., Whelan, M., Smith, S., Kuai, L., Worden, J., & Campbell, J. E. (2018). Global gridded anthropogenic emissions inventory of carbonyl sulfide. Atmospheric Environment, 183, 11–19. https://doi.org/10.1016/j.atmosenv.2018.03.063

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RR by Anonymous Referee #4 (29 Sep 2024)

Suggestions for revision or reasons for rejection

This is an interesting paper that performs a detailed analysis of a long time series of COS measurements in GIF, France. Although the wording should be improved (I had difficulties understanding the manuscript at several places), I particularly like the systematic analysis of the impact of different fluxes on the simulated mixing ratios. This allows the authors to draw conclusions about the quality of the anthropogenic emission inventory, and the performance of the biosphere model.
Nevertheless, I would like to suggest a couple of checks and/improvements that could further improve the understanding.

(1) CS2 is emitted by industry (VI in their homemade inventory). CS2 is converted in the model to COS with a prescribed timescale. It would be instructive to test (a) the impact of the implied timescale (conversion rate is not very well known and depends on season) (b) the impact of a diurnal variation on the CS2  COS conversion. Since the conversion is performed by the OH radical, these impacts are vital to analyze

(2) The model uncertainty is not discussed in any detail. The authors employ a Lagrangian particle model, and it would be instructive to know what is the impact of the number of particles released every six hours, the effect of resolution on the results, etc. Since the analysis is based on only one station, a proper representation of that station in the model is important. How well is the planetary boundary layer height simulated? What about wind validation?

(3) The final analysis of the paper investigates concentration changes between 6 a.m and 6 p.m., and between 6 p.m. and 6 a.m. the next day. In spring the diurnal variation in the biogenic fluxes greatly improves the comparison to simulations. In summer, this is not the case, but this is not analyzed further. My first guess would be that the effects on the diurnal fluxes interfere with the (changing) effect of entrainment from the atmosphere aloft. I would suggest to perform a budget analysis in which the concentration changes are attributed to (1) the effect of the fluxes (2) the effects of vertical transport (i.e. entrainment or detrainment) and (3) advection.

Further remarks and suggestions are provided in the annotated pdf.

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ED: Publish subject to minor revisions (review by editor) (10 Oct 2024) by Tanja Schuck

AR by Isabelle Pison on behalf of the Authors (04 Apr 2025) Author's response Author's tracked changes Manuscript

ED: Publish as is (10 Apr 2025) by Tanja Schuck

AR by Isabelle Pison on behalf of the Authors (10 Apr 2025) Author's response Manuscript

Journal article(s) based on this preprint

16 Jul 2025

Improved understanding of anthropogenic and biogenic carbonyl sulfide (COS) fluxes in western Europe from long-term continuous mixing ratio measurements

Antoine Berchet, Isabelle Pison, Camille Huselstein, Clément Narbaud, Marine Remaud, Sauveur Belviso, Camille Abadie, and Fabienne Maignan

Atmos. Chem. Phys., 25, 7499–7525, https://doi.org/10.5194/acp-25-7499-2025,https://doi.org/10.5194/acp-25-7499-2025, 2025

Short summary

Antoine Berchet, Isabelle Pison, Camille Huselstein, Clément Narbaud, Marine Remaud, Sauveur Belviso, Camille Abadie, and Fabienne Maignan

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We use the measurements of atmospheric carbonyl sulfide (COS) concentrations at the monitoring site of Gif-sur-Yvette (in the Paris area) from August 2014 to December 2019, combined with existing knowledge on COS fluxes in the atmosphere and and transport model to gain insight on COS fluxes, either natural such as the oceanic emissions or the vegetation and soil fluxes, or anthropogenic, from industrial activities and power generation.


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Can we gain knowledge on COS anthropogenic and biogenic emissions from a single atmospheric mixing ratios measurement site?

Journal article(s) based on this preprint

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