the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 04 Feb 2026
Nitrous oxide dynamics across nitrogen and pH gradients in headwater streams
Abstract. Headwater streams in agricultural landscapes can contribute substantially to nitrous oxide (N₂O) emissions, yet the environmental controls on stream N₂O dynamics remain poorly resolved, particularly in systems with low pH. We investigated 72 Danish headwater streams spanning broad gradients in pH (5.0 - 8.8), land use, and soil type to identify the main drivers of N₂O variability. Nitrate (NO₃⁻) was the strongest predictor of N₂O saturation, and its positive association with N₂O intensified under acidic conditions according to linear mixed models. Ammonium, dissolved organic carbon, and stream depth also showed significant but weaker positive relationships with N₂O. Spatial differences among streams explained considerably more variation than seasonal or regional patterns, underscoring the dominance of local factors. Streams with pH < 6 consistently exhibited higher N₂O saturation, and generalized additive modelling indicated a marked decline in N₂O levels beginning near pH 6. Despite generally high N₂O saturation, approximately 9 % of observations displayed undersaturation, which occurred mainly in streams with low NO₃⁻ concentrations and across all seasons. Our results indicate that acidic, weakly buffered catchments may enhance in‑stream N₂O accumulation even at moderate nitrogen levels. These findings highlight the need to consider pH‑related controls when assessing N₂O dynamics in freshwater networks and when designing mitigation strategies for agricultural landscapes.
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RC1: 'Comment on egusphere-2026-455', Anonymous Referee #1, 25 Feb 2026
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AC1: 'Reply on RC1', Mette Vodder Carstensen, 04 Apr 2026
Review of “Nitrous oxide dynamics across nitrogen and pH gradients in headwater streams”
Here, Carstensen et al. studied N2O dynamics in headwater streams thoroughly, in this case with streams with important differences among pH and nitrogen gradients. N2O is probably the least studied greenhouse gas in freshwater ecosystems, because its concentrations are lower than CH4 and CO2, but also due to the limited and reliable devices for its measurements compared to the other greenhouse gases. So, this work makes a relevant contribution to understanding of greenhouse gas budget and biogeochemical processes in freshwater ecosystems, specifically in streams environments. However, the manuscript contains several methodological issues that must clarify before going one step forward to the acceptance. Below see my main comments and other comments that I hope can help to improve the manuscript.
We thank the reviewer for the thoughtful and constructive assessment of our work. We are grateful for the recognition of the study’s relevance to understanding N₂O dynamics in freshwater ecosystems, as well as for the detailed methodological suggestions. We have carefully considered all comments and will revise the manuscript accordingly. We hope that the changes made successfully address the reviewer’s concerns and meet the expectations outlined in the review.
The most critical issue I see in the methodology concerns gas sample collection. Because, you introduce ambient air during the equilibration step. Therefore, if the dissolved gas concentration in the sample is already close to atmospheric equilibrium (or below it), this approach is very inaccurate for determining N2O concentrations and could strongly bias the results. Could you quantify the uncertainties associated with this procedure and include with the controls (ambient air samples collected at the site)?
We agree that introducing ambient air during the equilibration step could introduce substantial bias if not properly corrected, particularly for samples near or below atmospheric equilibrium. However, in our procedure this issue was explicitly accounted for by quantifying and removing the atmospheric background signal. For every sampling event, we collected ambient air samples on site, measured their N₂O and CO₂ concentrations, and used these values to calculate the expected contribution of atmospheric air to the headspace after equilibration. This calculated contribution was then subtracted from the measured headspace concentrations of each water sample. Because this correction is applied to every vial individually, the effect of introduced air is taken into account.
We acknowledge that this step was not described with sufficient clarity in the original Methods section. We will revise the manuscript to explicitly describe how ambient air concentrations were measured and how these measurements were used to quantify the background headspace contribution.
Regarding uncertainty the saturation states were classified as undersaturated (<95 %), approximately at atmospheric equilibrium (95–105 %), or oversaturated (>105 %), following Aho et al. (2023). These thresholds intentionally exceed the analytical precision of the gas chromatographic measurements (2.6 % CV; SD = 0.0075 µg N L⁻¹, n = 7), thereby preventing samples close to equilibrium from being misinterpreted as deviating from it. This approach provides a conservative and transparent classification that incorporates measurement uncertainty directly into the interpretation of saturation levels.
To illustrate the robustness of this classification, we also evaluated a scenario in which analytical uncertainty was substantially higher (±10 %). Under this assumption, the number of samples categorized as undersaturated would decrease from 35 to 23 in a worst‑case situation where air samples were overestimated by 10 % and headspace samples underestimated by 10 %. For the equilibrium category, eight samples would shift to the oversaturated class. These sensitivity tests demonstrate that while classification boundaries can influence category sizes, we believe t the overall patterns and the reported 9 % of N₂O sinks remain consistent within reasonable uncertainty limits.
Also, the manuscript does not clearly specify the volume of gas injected into the vials.
The volume added to vials was 10 mL, which will be specified in the method section.
Moreover, because you are working near atmospheric concentrations, did you verify the vacuum in the glass vials? Was the vacuum uniform among vials, and was it measured before and/or after sample filling? Any variability in the initial vacuum would increase uncertainty and could introduce systematic bias in the reported concentrations (because you are in the atmospheric ranges).
We agree that vacuum uniformity is important when working near atmospheric concentrations. All vials were pre‑evacuated by the manufacturer (LabCo). We contacted LabCo to get information about variation in initial vacuum, but we have not received a reply yet. During sampling in the field, we verified the presence of vacuum by the clear pressure “pull” that occurred when injecting the sample gas into the vial. In the few cases where this pull was absent, indicating a loss of vacuum, the vials were discarded and a new sample was taken. We therefore expect some, but low, variability in initial vacuum conditions and do not anticipate any systematic bias in the reported concentrations.
Continuing with the N2O measurements, the analytical device you used appears to have limited sensitivity for detecting small concentration changes. Although you report a detection limit of 0.15 ppm (which is close to half of the current atmospheric concentration), the sensitivity is not specified and for low values is extreme relevant. This information is essential, particularly because your measurements are close to atmospheric levels (ca. 0.336 ppm) or below. Please report the analytical sensitivity and precision in the Methods section. The concentration ranges reported in Lines 131, 132 can only be considered reliable if the sensitivity and associated uncertainties of the analysis are clearly stated. Given the reported detection limit, your theoretical lower quantification range would be approximately 55% below atmospheric concentration. Without explicitly accounting for analytical uncertainty, the reported undersaturation values may not be robust or even detectable within the methodological constraints of the instrument.
I performed a brief calculation using the values reported in Table 1, considering your sampling setup (40 mL water sample and 10 mL headspace) and assuming no initial N2O in the headspace. Using water concentrations of 0.1 (low), 2.4 (mean), and 22.2 (max) micrograms per L, and applying the temperature dependence of Henry’s law at 5, 10, and 20 °C, the expected equilibrium N2O concentrations in the headspace for the lowest concentration scenario would fall below the detection limit at all temperatures.
Given this, could you expand the Methods section to clarify
- the exact gas volume injected for analysis and the calibration curve,
The injection volume was 1000 µL with a split ratio of 2, delivered via the instrument’s automated injection system.
- the effective detection and quantification limit under your measurement configuration, and
The detection limit is 0.15 ppm.
- how you corrected headspace concentrations to N2O dissolved concentrations (including temperature corrections and blank removal)? All of this is for the 9% of N2O sinks reported.
We will expand the method section with a more detailed description of how N2O concentrations were calculated: The headspace concentration of N2O and CO2 (ppm) were then converted to moles using the ideal gas law, accounting for the headspace volume, laboratory temperature, and site‑specific atmospheric pressure. The concentrations of N2O and CO2 remaining in the water phase were calculated from the headspace gas concentrations according to Henry's law and using Henry's constant corrected for water temperature and atmospheric pressure at the sampling time (Weiss and Price, 1980). The total dissolved concentration originally present in the stream water was obtained as the sum of the gas transferred to the headspace and the remaining gas dissolved in the water. The expected headspace contribution from air was based on the ambient air sample, which was subtracted from the measured headspace values to correct for the ambient air introduced during the equilibration step. Stream water was considered undersaturated with respect to N₂O when dissolved concentrations were lower than the measured air concentration.
Other comments
Lines 31 to 33, would be relevant if you explain here which test is used for these relationships.
We thank the reviewer for this comment. We will specify in the revised manuscript that linear mixed‑effects models were used to evaluate these relationships.
Please explain why the pH of soils was taken from the 30-60cm data from Adhikari (2013).
We appreciate the reviewer’s question regarding the choice of soil pH data. In Figure 1, we used the 30–60 cm soil pH data from Adhikari (2013) to illustrate the national‑scale variation in soil pH, particularly to highlight the generally lower pH in the western part of the country. We chose this depth interval rather than topsoil measurements to avoid potential confounding effects of liming which is commonly used to improve agricultural soils. When screening variables for inclusion in the linear mixed model, we tested all five available soil‑depth categories (0-15, 15-30, 30–60, 60-100, and 100-200 cm depth) and found no significant effect of neither category on N₂O saturation.
Line 102, vegetation cover is very subjective with visual estimated, please elaborate a better approach to indicate such %, or remove it.
We thank the reviewer for this remark. We will expand the description of the vegetation cover estimation procedure: In-stream vegetation cover was visually estimated and recorded as a percentage, while the presence of iron ochre deposits in the stream was assessed on a scale from 0 to 3 (low to high abundance). To maintain consistency, the same observer conducted all assessments along a 2‑m stream reach at each sampling location.
Lines 121-123, Did you test if the sampling bottle and filters leach DOC. How TOC was handle, it is considering the POC or just the soluble?
Thank you for raising this point. The filters were rinsed thoroughly with 300 mL of demineralized water prior to use to minimize potential DOC or phosphate leaching. The TOC measurements include both dissolved and particulate organic carbon. This is because organic matter in both dissolved (DOC) and particulate (POC) fractions is oxidized during high‑temperature catalytic combustion in the TOC analyzer.
You can add the sediment analysis in the 2.5 section, also why did not measure soil pH?
We appreciate the reviewer’s suggestion. We will remove the paragraph on sediment C:N ratios because these data were not ultimately used. The C:N ratio showed no significant relationship with N₂O saturation according to the linear mixed model.
We also acknowledge the reviewer’s comment concerning sediment pH. The sampling campaign was designed primarily to characterize water‑column chemistry and dissolved greenhouse gas dynamics, and for that reason sediment pH was not measured.Figure 1A is reporting CO2, but in methods it is not included, please correct it.
We apologize for this oversight. A description of the CO₂ measurements will be added to Section 2.4.
Figure 1A N2O should be Log transformed values? If not, Pearson correlation would not work, please indicate it clear
Yes, N₂O saturation values were log‑transformed prior to Pearson correlation analysis. This information will be added clearly in the figure caption.
Citation: https://doi.org/10.5194/egusphere-2026-455-AC1
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AC1: 'Reply on RC1', Mette Vodder Carstensen, 04 Apr 2026
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RC2: 'Comment on egusphere-2026-455', Anonymous Referee #2, 14 Mar 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2026-455/egusphere-2026-455-RC2-supplement.pdf
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AC2: 'Reply on RC2', Mette Vodder Carstensen, 04 Apr 2026
General comments:
This paper presents the results of a study of stream water N2O saturation measured from 72 sites in headwater streams in Denmark. The authors examined additional chemical and physical parameters and found that N2O saturation increased with nitrate and was higher at low pH. The authors tied this relationship with pH to potential management of N2O emissions from headwater streams in areas with acidic soils. Overall, the study was well presented, and the paper was very well written.
We would like to thank the reviewer for the constructive and insightful comments provided. We appreciate the careful reading of our manuscript and thoughtful suggestions, which will help clarify several methodological details and strengthen the interpretation of our results. We will address all comments point by point below and will incorporate the corresponding revisions into the manuscript.
I would have appreciated a few more methodological details. In particular, CO2 concentrations are shown in the appendix, but the methods section does not explain where these measurements were taken—is this dissolved CO2 in the stream water or CO2 in the ambient air? As mentioned, pH and CO2 are highly correlated, so I was surprised this information was not included. Based on Figure A5, the clearest relationship is between CO2 and N2O. If the CO2 was measured in the stream water, it could be very relevant to the stated relationship between N2O and pH. For example, aerobic respiration of organic carbon material in sediments could produce CO2 in the sediments, which is then released to the surface water, decreasing pH. This aerobic respiration also consumes oxygen, leading to anerobic conditions that could favor heterotrophic denitrification and production of N2O. So, I think it is important to include a discussion of CO2 and why it is related to pH—is the lower pH causing more N2O production (or less N2O reduction via inhibition of nosZ), or is the lower pH a result of sedimentary reactions that also increase denitrification? Below are some additional questions related to the study.
Thank you for pointing out the missing methodological details regarding CO₂ measurements. We agree that the absence of this information created unnecessary ambiguity, especially given the strong correlations among CO₂, pH, and N₂O dynamics. This omission will be corrected, and the CO₂ measurement procedure will be explicitly described:
2.4 Dissolved gas analysis
The headspace concentrations of N2O and CO2 in headspace samples and ambient air samples were determined using a dual-inlet Agilent 7890 GC system interfaced with a CTC CombiPal autosampler (Agilent, Denmark) configured and calibrated with standard gases according to Petersen et al. (2012), with detection limits of 0.15 ppm for N2O. The headspace concentration of N2O and CO2 (ppm) were converted to moles using the ideal gas law, accounting for the headspace volume, laboratory temperature, and site-specific atmospheric pressure. The aqueous concentrations of N2O and CO2 remasampling water phase were calculated from the headspace gas concentrations according to Henry's law and using Henry's constant corrected for water temperature and atmospheric pressure at the sampling time (Weiss and Price, 1980). The total dissolved concentration originally present in the stream water was obtained as the sum of the gas transferred to the headspace and the remaining gas dissolved in the water. The expected headspace contribution from air was based on the ambient air sample, which was subtracted from the measured headspace values to correct for the ambient air introduced during the equilibration step. Stream water was considered undersaturated with respect to N₂O when dissolved concentrations were lower than the measured air concentration. The saturation levels were classified as undersaturated (<95 %), ∼atmospheric equilibrium (95 %–105 %), and oversaturated (>105 %) following Aho et al. (2023). These threshold intervals were applied to explicitly incorporate the measurement uncertainty associated with the gas concentration determinations and the subsequent saturation calculations. Analytical precision of the GC measurements was quantified to be 2.6 % CV (SD = 0.0075 µg L⁻¹, n = 7).
The reviewer rightly highlights that sedimentary aerobic respiration can elevate CO₂ concentrations in porewater, which, when released to the overlying stream water, can reduce pH. This respiration simultaneously consumes oxygen, potentially creating microsites of anaerobic conditions that promote heterotrophic denitrification and N₂O production. We will include this in the discussion of indirect factors:
In addition to these pathways, the strong relationship between CO₂ and N₂O suggests that sedimentary carbon cycling may indirectly influence N₂O dynamics via its effect on pH. Aerobic respiration in sediments produce CO₂ which can lower pH locally, while the associated oxygen consumption may create micro‑anoxic zones that promote heterotrophic denitrification and N₂O production. Elevated CO₂ may also directly affect nitrification, as recent sediment incubations showed that higher in‑stream CO₂ concentrations increased the abundance of ammonia‑oxidizing bacteria and enhanced N₂O production, particularly under low DOC:NO₃⁻ ratios (Mwanake et al., 2025). Together, these findings highlight the complexity of the CO₂–N₂O relationship, as CO₂ and pH are tightly linked, and both can regulate microbial respiration, nitrification, and denitrification.
Specific Comments:
Line 72: Were samples collected from 72 different streams, or were there some streams with multiple sampling sites?
They were collected from 72 independent streams systems.
Line 84: Were these soil types determined 30-60 below the stream bed, or on the banks?
We extracted data from 5 depths (below land surface) based on geological GIS maps to use in our linear mixed model, but none of them was significant. The depth 30-60 was the one with the highest correlation with stream pH and we used this in the map to illustrate the national differences in geology.
Line 85: What is the resolution of the Danish Area Information System source?
We will add the information to section 2.1: Land use within each catchment was quantified by calculating the percentage cover of major land‑use categories using the polygon‑based national land‑use map (scale 1:25,000) from the Danish Area Information System (Nielsen et al., 2000).
Lines 98-109: For future researchers, it would be helpful to indicate other sampling details, such as if the sampling bottles were triple rinsed with site water, etc. Was stream velocity measured at 0.4d from the streambed, the middle depth, etc.? Was discharge calculated using the area-velocity method? Does “vegetation cover” refer to overhead canopy cover or something else? Where were the iron ochre deposits? What was measured in the ambient air sample? Were samples refrigerated? It would help to clarify how both headspace vials and water sample bottles were stored.
Stream velocity and discharge: Stream velocity was measured at 0.4 × depth from the streambed, following standard practice for estimating mean velocity in streams. Discharge was calculated using the area–velocity method. These details will be added to the sampling subsection.
Vegetation cover: “Vegetation cover” refers specifically to in‑stream macrophyte cover, not overhead canopy cover.
Iron ochre deposits: Iron deposits refer to iron ochre accumulating on the streambed, typically associated with groundwater discharge zones.
Ambient air samples: Ambient air samples were analyzed for N₂O and CO₂, collected at each site during sampling to quantify background atmospheric concentrations.
Storage of samples: As specified in line 117 (water samples) and line 111 (air samples). Water samples were kept refrigerated until analysis to minimize microbial activity and gas exchange. Headspace vials were stored in the dark to avoid photochemical reactions and temperature fluctuations.
We will ensure these details are presented more clearly.
Line 114: What were unfiltered samples used for? Were the samples for SRP filtered twice? (0.45 um and 0.22 um)?
The unfiltered samples can indirectly be used to test if particulate compounds were important for N2O dynamics, but we found no evidence of this. Yes, SRP was filtered twice.
Line 125: What kind of detector was used with the GC?
Thank you for pointing this out. The Methods section will be updated to specify the detector used with the GC system. The gas chromatograph (GC 7890A, Agilent Technologies) was equipped with an electron capture detector (ECD) for N₂O analysis and a thermal conductivity detector (TCD) for CO₂ measurements. We will add this information to the revised manuscript to ensure full methodological transparency.
Line 160: To me, “across individual streams” sounds like there are multiple samples from the same stream that show variation. Using “across streams” might be clearer if you are referring to different streams having different concentrations.
We will correct this to avoid confusion as we sampled distinct and independent streams.
Line 211: CO2 is reported, but I don’t think I saw this described in the methods. Is this dissolved CO2 in the stream water or CO2 in the ambient air sample? Please clarify in the methods and throughout when it is mentioned (Figure A1, A4, Table A2, etc.).
We apologise for this inconvenience, and this will be added throughout the manuscript.
Line 235: Could you explain a “semi-natural stream?”
Thank you for asking for clarification. In the Danish context, we use the term “semi‑natural stream” because truly natural streams—i.e., streams entirely uninfluenced by agriculture or human land use—are essentially absent. Therefore, semi‑natural streams refer to streams that are less impacted by agricultural activities, typically characterized by lower nitrate concentrations, reduced hydromorphological modification, and generally better ecological status compared with intensively drained or straightened agricultural streams. We will clarify this in the revised manuscript.
Line 259: Please clarify the relationship between stream depth and pH. What causes this?
We do not have further suggestions than what was discussed in the manuscript line 259-263: This pattern may be partially explained by the negative association between stream depth and lower pH levels. Physical constraints on gas exchange may also contribute, as deeper water bodies typically have lower surface area-to-260 volume ratios, potentially limiting the evasion of N₂O to the atmosphere, leading to higher N₂O concentrations in the water column.
Figure A5: Why is CO2 not mentioned in the caption? Please specify where CO2 was measured. Is this dissolved in the stream water?
This was an oversight as the CO2 figure was added later than the other parameters. It will be included in the caption.
Technical/Minor Comments:
Line 40: Capitalize IPCC
This will be changed in the manuscript.
Figure 2: Consider changing “identity” in the caption to stream number for clarity. It also might be helpful to indicate the time range of the photos.
This will be changed in the manuscript.
Line 135: Dry organic matter content?
This section will be deleted, as we did not use the data.
Line 143: correlations (plural)
This will be changed in the manuscript.
Line 153; Define REML.
This will be changed in the manuscript.
Line 154: Is there a word missing after smooth?
To avoid jargon we will add the word term after smooth.
Line 158: mean annual precipitation? Could you include total n for all the streams and seasons?
Information about the precipitation will be added to section 2.1. Table A2 shows sample size per season.
Line 159: subject/verb agreement. Specify that these are stream water N2O concentrations.
Thanks!
Line 164: mean saturation measurements…were (subject/verb agreement)
Thanks!
Table 1: Please include n and units for temperature. It might be helpful to list the definitions in the heading in the same order as in the table (and include CO2)
This will be changed in the manuscript.
Table 2: Consider defining SE and DF in the table heading.
This will be changed in the manuscript.
Line 225: This sentence refers to saturation but the numbers shown are concentrations.
We apologise, units should have been %.
Line 232: Please include n. Is it normal for this journal to have a space between a number and the % sign? (Multiple instances)
The sample size will be added.
Line 233: Add comma after 69%, consider rewording to “with a range of …”
This will be changed in the manuscript.
Line 308: change to “undersaturation”
Thanks.
Line 494: Dry organic matter content?
This will be deleted, as we did not use it.
Figures A2-A4: It might be helpful to include the precent agriculture for each stream’s watershed in the legend, as in Figure 3.
Thanks for your suggestion, this will be added.
Table A3: Define SE and DF in heading.
This will be changed in the manuscript.
Citation: https://doi.org/10.5194/egusphere-2026-455-AC2
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AC2: 'Reply on RC2', Mette Vodder Carstensen, 04 Apr 2026
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- 1
Review of “Nitrous oxide dynamics across nitrogen and pH gradients in headwater streams”
Here, Carstensen et al. studied N2O dynamics in headwater streams thoroughly, in this case with streams with important differences among pH and nitrogen gradients. N2O is probably the least studied greenhouse gas in freshwater ecosystems, because its concentrations are lower than CH4 and CO2, but also due to the limited and reliable devices for its measurements compared to the other greenhouse gases. So, this work makes a relevant contribution to understanding of greenhouse gas budget and biogeochemical processes in freshwater ecosystems, specifically in streams environments. However, the manuscript contains several methodological issues that must clarify before going one step forward to the acceptance. Below see my main comments and other comments that I hope can help to improve the manuscript.
The most critical issue I see in the methodology concerns gas sample collection. Because, you introduce ambient air during the equilibration step. Therefore, if the dissolved gas concentration in the sample is already close to atmospheric equilibrium (or below it), this approach is very inaccurate for determining N2O concentrations and could strongly bias the results. Could you quantify the uncertainties associated with this procedure and include with the controls (ambient air samples collected at the site)? Also, the manuscript does not clearly specify the volume of gas injected into the vials. Moreover, because you are working near atmospheric concentrations, did you verify the vacuum in the glass vials? Was the vacuum uniform among vials, and was it measured before and/or after sample filling? Any variability in the initial vacuum would increase uncertainty and could introduce systematic bias in the reported concentrations (because you are in the atmospheric ranges).
Continuing with the N2O measurements, the analytical device you used appears to have limited sensitivity for detecting small concentration changes. Although you report a detection limit of 0.15 ppm (which is close to half of the current atmospheric concentration), the sensitivity is not specified and for low values is extreme relevant. This information is essential, particularly because your measurements are close to atmospheric levels (ca. 0.336 ppm) or below. Please report the analytical sensitivity and precision in the Methods section. The concentration ranges reported in Lines 131, 132 can only be considered reliable if the sensitivity and associated uncertainties of the analysis are clearly stated. Given the reported detection limit, your theoretical lower quantification range would be approximately 55% below atmospheric concentration. Without explicitly accounting for analytical uncertainty, the reported undersaturation values may not be robust or even detectable within the methodological constraints of the instrument.
I performed a brief calculation using the values reported in Table 1, considering your sampling setup (40 mL water sample and 10 mL headspace) and assuming no initial N2O in the headspace. Using water concentrations of 0.1 (low), 2.4 (mean), and 22.2 (max) micrograms per L, and applying the temperature dependence of Henry’s law at 5, 10, and 20 °C, the expected equilibrium N2O concentrations in the headspace for the lowest concentration scenario would fall below the detection limit at all temperatures. Given this, could you expand the Methods section to clarify (i) the exact gas volume injected for analysis and the calibration curve, (ii) the effective detection and quantification limit under your measurement configuration, and (iii) how you corrected headspace concentrations to N2O dissolved concentrations (including temperature corrections and blank removal)? All of this is for the 9% of N2O sinks reported.
Other comments