the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 17 Dec 2024
Marine emissions and trade winds control the atmospheric nitrous oxide in the Galapagos Islands
Abstract. Nitrous oxide (N2O) is a potent greenhouse gas emitted by oceanic and terrestrial sources, with its biogeochemical cycle influenced by both natural processes and anthropogenic activities. Current atmospheric N2O monitoring networks, including tall-tower and flask measurements, often overlook major marine hotspots, such as the eastern tropical Pacific Ocean. We present the first 15 months of high-frequency continuous measurements of N2O and carbon monoxide from the newly established Galapagos Emissions Monitoring Station (GEMS) in this region. Over this period, N2O mole fractions vary by approximately 5 ppb, influenced by seasonal trade winds, local anthropogenic emissions, and air masses transported from marine N2O hotspots. Notably, between February and April 2024, we observe high variability linked to the southward shift of the intertropical convergence zone and weakened trade winds over the Galapagos Islands. Increased variability during this period is driven by stagnant local winds, which accumulate emissions, and the mixing of air masses with different N2O content from the northern and southern hemispheres. The remaining variability is primarily due to differences in air mass transport and heterogeneity in surface fluxes from the eastern tropical Pacific. Air masses passing over the Peruvian and Chilean upwelling systems— key sources of oceanic N2O efflux — show markedly higher N2O mole fractions at the GEMS station.
- Preprint
(8962 KB) - Metadata XML
-
Supplement
(315 KB) - BibTeX
- EndNote
Status: closed
-
RC1: 'Comment on egusphere-2024-3769', Anonymous Referee #1, 04 Jan 2025
This study presents the first 15 months of in situ atmospheric N2O data from a newly established monitoring site on the Galapagos Islands. The site is situated between two hot spots of oceanic N2O emissions: (i) the Peruvian and Chilean and (ii) the Costa Rican upwelling systems, often referred to as the Eastern Tropical South Pacific and North Pacific, respectively. The new Galapagos site is much closer to these ETSP and ETNP hot spots than previously available data from NOAA or AGAGE. Overall, this is an exciting and innovative study that introduces a valuable new N2O monitoring site. The Introduction is also excellent, going beyond the usual statements about N2O and covering new ground relevant to the current study.
This research definitely merits publication after some relatively minor revisions. Below are some thoughts about how to make the presentation more focused and accessible to the reader.
Major thoughts:
- Sections 3.2 and 3.4 on diurnal variability and local Galapagos emissions are details that seem to digress from the big picture goals of this study but require much of the reader’s concentration to follow. On the other hand, the diurnal variability is NOT small (e.g., the diurnal cycle of 0.8 ppb in March, 2024) with respect to the big picture variability (upwelling vs. Southern Ocean vs. NH influences) shown in Figure 8. At minimum, the last paragraph of the Introduction should provide a blueprint for the reader as to why so much attention is focused on diurnal variability and local emissions. Perhaps Section 3.4 could even be moved to the Supplement. Also, when the values of I are presented in Figure 2, please provide some forewarning of why Region 3 is included, i.e., to filter local emissions. Otherwise, it is puzzling why that region was considered in the same league as the NH and ETSP upwelling regions.
- In general, this study would be more satisfying if a Figure 5-like set of results could be presented that connected logically to Figure 6.
Specific comments:
Line 59. Since the Introduction has focused entirely on N2O, a line explaining why CO is also included in the study would be useful, e.g., is this due to common physical properties of N2O and CO that allow the two gases to be measured with the same instrumentation or is it because CO serves as a useful indicator of combustion activity?
Line 111-112. The repeatability of 0.04 ppb for N2O measurements is impressive. It would seem most relevant to compare this to the repeatability of the NOAA and AGAGE measurements for the sites shown in Figure 1. For example, Lan et al., 2024 report an “uncertainty” in NOAA N2O data of 0.16 ppb following the replacement of the GC-ECD system with a TILDAS system [Lan et al., 2024]. How are uncertainty and repeatability, as defined here, related?
Line 138. Please clarify what is meant by, “the surface layer in which the fluxes occur is defined as 0-100 m” Some particle dispersion models assign a flux only if the footprint comes from the bottom half of the surface layer. Is this the case here? Also, how does the 100m surface layer correspond to the 529 m boundary layer at GAL cited on line 197?
Line 152. Please explain in more detail the significance of the histograms in Figure S5, e.g., what is the reader to understand from the broad histogram of Region 1 compared to the narrower distribution of Regions 2 and 3? In general, given that the three regions chosen are extremely disparate in terms of their areal extent, can they be compared in a meaningful way?
Line 43 and Line 152. On a related note, the Introduction mentions the Costa Rican upwelling (aka ETNP) yet Region 2 is defined as the entire NH. How does this allow the distinction of air masses specifically from the ETNP vs. from the entire NH, which, due to N2O’s well-known N-S gradient, is expected to be ~ 1 ppb higher than air coming from the SH? If it doesn’t, perhaps the motivating reference to Costa Rica on line 43 should be toned down.
Figure 3 and line 158: Why are the SIO CGO data shown as monthly means when the in situ data are available at much higher temporal resolution? Could they be shown at higher than monthly resolution without detracting from the GAL data (since CGO is offset by 1.3 ppb relative to GAL)?
Figure 3. What is the distinction between GEMS and GAL? Why is GAL used in Figure 3 but GEMS used elsewhere? Similarly, why is GSC used sometimes in the text and how is it distinguished from GEMS?
Line 213: Please define the duration of the 2023-24 El Nino event including approximate start and end months.
Line 240: Please define GSC earlier in the methods before presenting here.
Figure 5. In panels c and f, the angle of the N2O measurement doesn’t correspond to the angle of the wind direction of the ERA5 or GSC data. Please explain more clearly.
Line 246-251: The logic of these statements is confusing and “Nevertheless” is a puzzling choice of conjunction.
Figure 6. This figure raises questions about why September 2024 was chosen as the contrast for March 2024 (which clearly has the strongest NH source strength)? Based on September, 2023, there is still a NH source component in September. The lowest NH contribution appears to be in June 2024.
How do the results shown in Figure 5 relate to the information shown in Figure 6? Why is there no wind rose showing winds coming from the north or northeast and the associated N2O values? Is this the basis of the argument in Lines 246-251 (i.e., that FLEXPART is more useful than simple wind data?).
Figures 6 and 8, please explain the unit (s kg-1 pmol/pmol). In particular, what does ‘s’ refer to?
Citation: https://doi.org/10.5194/egusphere-2024-3769-RC1 -
RC2: 'Comment on egusphere-2024-3769', Damian Leonardo Arévalo-Martínez, 22 Jan 2025
Summary
The manuscript by Cinay and colleagues presents the first set of N2O (and CO) measurements of a newly stablished atmospheric monitoring site at Galápagos Islands. Based on their data, the authors conclude that the observed trends mostly result from the interplay between the seasonal shifts of the ITCZ and emissions from marine N2O hotspots in the Eastern South Pacific.
General assessment
An atmospheric monitoring station for N2O in the region represents a clear advance for the field because it allows an improvement of both top-down and bottom-up estimates of marine air-sea fluxes of N2O. Up to know, groups who did not have the instrumentation to conduct at-sea surveys of atmospheric N2O in the region had to rely on information from distant stations to compute the fluxes. While the zonal distribution of many trace gases tends to be rather homogeneous, several studies have shown that oceanic trace gas production and emissions might indeed have an imprint in the overlying atmosphere. Although the changes in atmospheric N2O observed by Cinay et al might, at first, not appear particularly large, it is precisely the monitoring of such small changes over long periods what one aims for to detect significant trends (which I would expect for this gas). Based on the evidence provided in this manuscript, it is my opinion that the resolution and accuracy at the station are suitable for this purpose.
Overall, the manuscript is well written and structured, and figures and tables are adequate for publication. Besides some clarifications (which I list below under “Specific comments”), the only criticism I have is the inclusion of CO data throughout the manuscript. I myself work with CO and therefore recognize the immense value of such a time series. CO is a potent, yet indirect, greenhouse gas on its own right, whose atmospheric dynamics are worth looking at. In this region in particular (and because of its short lifetime) I would expect CO to be useful to investigate e.g. tropospheric convection (although land pollution did not seem to play much of a role yet). Nevertheless, it is obvious that the manuscript is focused on N2O, and therefore the appearances of CO are rather distracting. For instance, in lines 220 – 224, the authors themselves acknowledge that CO does not provide any significant hints of an alternative driver for the observed N2O mixing ratios. I would kindly suggest the authors to consider placing all the information on CO (including plots) in the supplementary because its connection with N2O is not direct (and in this case not that relevant, as also indicated in e.g. line 185). One exception of this would be the analysis done in section 3.4, where CO mixing ratios, wind stagnation and local regional influence (“I_local”) were used to evaluate small-scale N2O emission sources.
Specific comments
l.24–25: The accuracy of marine estimates is not only due to temporal and spatial gaps. There is also an important methodological issue in getting the fluxes “right”. Here the differences between using the traditional gradient method with a given air-sea gas exchange parameterization vs. top-down estimates and direct flux measurements is also a challenge.
l.28–29: As shown by (e.g. Ji et al), strong thermal-driven stratification during El Niño events results in accumulation of N2O below the mixed layer, as long as waters are not completely oxygen depleted.
l.95–97: If the analyser still measures H2O it means that there is still humidity, just in the form of water vapour. The idea of drying the samples is to reduce the extent of the water correction performed by the analyser. In my opinion this sentence needs a bit of clarification as it might lead to confusion later in the text when the authors explain that there is a water correction.
l.305–306: While forcing is similar in the Peruvian and Chilean upwelling systems, clustering them as one region has a clear bias because while upwelling off Peru is a perennial feature, upwelling off Chile has a much stronger seasonal component. Moreover, the extent of the emissions is also different. I would not expect this to change the conclusions of the study, but it certainly adds to the uncertainty of this estimate, and I would therefore recommend at least mentioning it.
Kind regards,
Damian L. Arévalo-Martínez
Citation: https://doi.org/10.5194/egusphere-2024-3769-RC2 - AC1: 'Comment on egusphere-2024-3769', Timur Cinay, 24 Feb 2025
Status: closed
-
RC1: 'Comment on egusphere-2024-3769', Anonymous Referee #1, 04 Jan 2025
This study presents the first 15 months of in situ atmospheric N2O data from a newly established monitoring site on the Galapagos Islands. The site is situated between two hot spots of oceanic N2O emissions: (i) the Peruvian and Chilean and (ii) the Costa Rican upwelling systems, often referred to as the Eastern Tropical South Pacific and North Pacific, respectively. The new Galapagos site is much closer to these ETSP and ETNP hot spots than previously available data from NOAA or AGAGE. Overall, this is an exciting and innovative study that introduces a valuable new N2O monitoring site. The Introduction is also excellent, going beyond the usual statements about N2O and covering new ground relevant to the current study.
This research definitely merits publication after some relatively minor revisions. Below are some thoughts about how to make the presentation more focused and accessible to the reader.
Major thoughts:
- Sections 3.2 and 3.4 on diurnal variability and local Galapagos emissions are details that seem to digress from the big picture goals of this study but require much of the reader’s concentration to follow. On the other hand, the diurnal variability is NOT small (e.g., the diurnal cycle of 0.8 ppb in March, 2024) with respect to the big picture variability (upwelling vs. Southern Ocean vs. NH influences) shown in Figure 8. At minimum, the last paragraph of the Introduction should provide a blueprint for the reader as to why so much attention is focused on diurnal variability and local emissions. Perhaps Section 3.4 could even be moved to the Supplement. Also, when the values of I are presented in Figure 2, please provide some forewarning of why Region 3 is included, i.e., to filter local emissions. Otherwise, it is puzzling why that region was considered in the same league as the NH and ETSP upwelling regions.
- In general, this study would be more satisfying if a Figure 5-like set of results could be presented that connected logically to Figure 6.
Specific comments:
Line 59. Since the Introduction has focused entirely on N2O, a line explaining why CO is also included in the study would be useful, e.g., is this due to common physical properties of N2O and CO that allow the two gases to be measured with the same instrumentation or is it because CO serves as a useful indicator of combustion activity?
Line 111-112. The repeatability of 0.04 ppb for N2O measurements is impressive. It would seem most relevant to compare this to the repeatability of the NOAA and AGAGE measurements for the sites shown in Figure 1. For example, Lan et al., 2024 report an “uncertainty” in NOAA N2O data of 0.16 ppb following the replacement of the GC-ECD system with a TILDAS system [Lan et al., 2024]. How are uncertainty and repeatability, as defined here, related?
Line 138. Please clarify what is meant by, “the surface layer in which the fluxes occur is defined as 0-100 m” Some particle dispersion models assign a flux only if the footprint comes from the bottom half of the surface layer. Is this the case here? Also, how does the 100m surface layer correspond to the 529 m boundary layer at GAL cited on line 197?
Line 152. Please explain in more detail the significance of the histograms in Figure S5, e.g., what is the reader to understand from the broad histogram of Region 1 compared to the narrower distribution of Regions 2 and 3? In general, given that the three regions chosen are extremely disparate in terms of their areal extent, can they be compared in a meaningful way?
Line 43 and Line 152. On a related note, the Introduction mentions the Costa Rican upwelling (aka ETNP) yet Region 2 is defined as the entire NH. How does this allow the distinction of air masses specifically from the ETNP vs. from the entire NH, which, due to N2O’s well-known N-S gradient, is expected to be ~ 1 ppb higher than air coming from the SH? If it doesn’t, perhaps the motivating reference to Costa Rica on line 43 should be toned down.
Figure 3 and line 158: Why are the SIO CGO data shown as monthly means when the in situ data are available at much higher temporal resolution? Could they be shown at higher than monthly resolution without detracting from the GAL data (since CGO is offset by 1.3 ppb relative to GAL)?
Figure 3. What is the distinction between GEMS and GAL? Why is GAL used in Figure 3 but GEMS used elsewhere? Similarly, why is GSC used sometimes in the text and how is it distinguished from GEMS?
Line 213: Please define the duration of the 2023-24 El Nino event including approximate start and end months.
Line 240: Please define GSC earlier in the methods before presenting here.
Figure 5. In panels c and f, the angle of the N2O measurement doesn’t correspond to the angle of the wind direction of the ERA5 or GSC data. Please explain more clearly.
Line 246-251: The logic of these statements is confusing and “Nevertheless” is a puzzling choice of conjunction.
Figure 6. This figure raises questions about why September 2024 was chosen as the contrast for March 2024 (which clearly has the strongest NH source strength)? Based on September, 2023, there is still a NH source component in September. The lowest NH contribution appears to be in June 2024.
How do the results shown in Figure 5 relate to the information shown in Figure 6? Why is there no wind rose showing winds coming from the north or northeast and the associated N2O values? Is this the basis of the argument in Lines 246-251 (i.e., that FLEXPART is more useful than simple wind data?).
Figures 6 and 8, please explain the unit (s kg-1 pmol/pmol). In particular, what does ‘s’ refer to?
Citation: https://doi.org/10.5194/egusphere-2024-3769-RC1 -
RC2: 'Comment on egusphere-2024-3769', Damian Leonardo Arévalo-Martínez, 22 Jan 2025
Summary
The manuscript by Cinay and colleagues presents the first set of N2O (and CO) measurements of a newly stablished atmospheric monitoring site at Galápagos Islands. Based on their data, the authors conclude that the observed trends mostly result from the interplay between the seasonal shifts of the ITCZ and emissions from marine N2O hotspots in the Eastern South Pacific.
General assessment
An atmospheric monitoring station for N2O in the region represents a clear advance for the field because it allows an improvement of both top-down and bottom-up estimates of marine air-sea fluxes of N2O. Up to know, groups who did not have the instrumentation to conduct at-sea surveys of atmospheric N2O in the region had to rely on information from distant stations to compute the fluxes. While the zonal distribution of many trace gases tends to be rather homogeneous, several studies have shown that oceanic trace gas production and emissions might indeed have an imprint in the overlying atmosphere. Although the changes in atmospheric N2O observed by Cinay et al might, at first, not appear particularly large, it is precisely the monitoring of such small changes over long periods what one aims for to detect significant trends (which I would expect for this gas). Based on the evidence provided in this manuscript, it is my opinion that the resolution and accuracy at the station are suitable for this purpose.
Overall, the manuscript is well written and structured, and figures and tables are adequate for publication. Besides some clarifications (which I list below under “Specific comments”), the only criticism I have is the inclusion of CO data throughout the manuscript. I myself work with CO and therefore recognize the immense value of such a time series. CO is a potent, yet indirect, greenhouse gas on its own right, whose atmospheric dynamics are worth looking at. In this region in particular (and because of its short lifetime) I would expect CO to be useful to investigate e.g. tropospheric convection (although land pollution did not seem to play much of a role yet). Nevertheless, it is obvious that the manuscript is focused on N2O, and therefore the appearances of CO are rather distracting. For instance, in lines 220 – 224, the authors themselves acknowledge that CO does not provide any significant hints of an alternative driver for the observed N2O mixing ratios. I would kindly suggest the authors to consider placing all the information on CO (including plots) in the supplementary because its connection with N2O is not direct (and in this case not that relevant, as also indicated in e.g. line 185). One exception of this would be the analysis done in section 3.4, where CO mixing ratios, wind stagnation and local regional influence (“I_local”) were used to evaluate small-scale N2O emission sources.
Specific comments
l.24–25: The accuracy of marine estimates is not only due to temporal and spatial gaps. There is also an important methodological issue in getting the fluxes “right”. Here the differences between using the traditional gradient method with a given air-sea gas exchange parameterization vs. top-down estimates and direct flux measurements is also a challenge.
l.28–29: As shown by (e.g. Ji et al), strong thermal-driven stratification during El Niño events results in accumulation of N2O below the mixed layer, as long as waters are not completely oxygen depleted.
l.95–97: If the analyser still measures H2O it means that there is still humidity, just in the form of water vapour. The idea of drying the samples is to reduce the extent of the water correction performed by the analyser. In my opinion this sentence needs a bit of clarification as it might lead to confusion later in the text when the authors explain that there is a water correction.
l.305–306: While forcing is similar in the Peruvian and Chilean upwelling systems, clustering them as one region has a clear bias because while upwelling off Peru is a perennial feature, upwelling off Chile has a much stronger seasonal component. Moreover, the extent of the emissions is also different. I would not expect this to change the conclusions of the study, but it certainly adds to the uncertainty of this estimate, and I would therefore recommend at least mentioning it.
Kind regards,
Damian L. Arévalo-Martínez
Citation: https://doi.org/10.5194/egusphere-2024-3769-RC2 - AC1: 'Comment on egusphere-2024-3769', Timur Cinay, 24 Feb 2025
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 199 | 53 | 12 | 264 | 29 | 8 | 10 |
- HTML: 199
- PDF: 53
- XML: 12
- Total: 264
- Supplement: 29
- BibTeX: 8
- EndNote: 10
Viewed (geographical distribution)
| Country | # | Views | % |
|---|---|---|---|
| United States of America | 1 | 106 | 43 |
| Germany | 2 | 14 | 5 |
| Australia | 3 | 13 | 5 |
| China | 4 | 12 | 4 |
| France | 5 | 12 | 4 |
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
- 106