Articles | Volume 22, issue 21
https://doi.org/10.5194/bg-22-6669-2025
© Author(s) 2025. This work is distributed under the Creative Commons Attribution 4.0 License.
Aerodynamic flux–gradient measurements of ammonia over four spring seasons in grazed grassland: environmental drivers, methodological challenges and uncertainties
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- Final revised paper (published on 10 Nov 2025)
- Supplement to the final revised paper
- Preprint (discussion started on 11 Apr 2025)
- Supplement to the preprint
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
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RC1: 'Comment on egusphere-2025-1605', Anonymous Referee #1, 11 May 2025
- AC2: 'Authors reply to all comments', Chris Flechard, 01 Aug 2025
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CC1: 'Comment on egusphere-2025-1605', Johannes Laubach, 04 Jun 2025
- AC3: 'Authors reply to all comments', Chris Flechard, 01 Aug 2025
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RC2: 'Comment on egusphere-2025-1605', Anonymous Referee #2, 04 Jun 2025
- AC1: 'Authors reply to all comments', Chris Flechard, 01 Aug 2025
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Reconsider after major revisions (05 Aug 2025) by Ivonne Trebs
AR by Chris Flechard on behalf of the Authors (05 Aug 2025)
Author's response
Author's tracked changes
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ED: Publish as is (11 Aug 2025) by Ivonne Trebs
AR by Chris Flechard on behalf of the Authors (12 Aug 2025)
Author's response
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Post-review adjustments
AA: Author's adjustment | EA: Editor approval
AA by Chris Flechard on behalf of the Authors (06 Nov 2025)
Author's adjustment
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EA: Adjustments approved (06 Nov 2025) by Ivonne Trebs
General comments
The article ‘Aerodynamic gradient flux measurements of ammonia in intensively grazed grassland: temporal variations, environmental drivers, methodological challenges and uncertainties’ is a valuable contribution to the field of ammonia research. It presents an interesting dataset on ammonia fluxes in grazed grassland and the data treatment is conducted thoroughly and described in a transparent way.
One concern, however, is the length of the manuscript which is, based on the number of lines, roughly twice as long as is common. The length of an article has a strong influence on its accessibility. I, therefore, strongly recommend the authors to reduce the length of the manuscript by removing all lines which are not absolutely necessary. I understand that this leads to tough choices since none of the sentences are not worthy to read but all together the article length is way too long. Examples of lines which could be removed in my opinion are e.g. l35 ‘Globally – productivity’, l66 ‘It -prevalent’, l132 ‘The surface -profiles’, the section describing the Delta denuder could be roughly halved etc.
My other major concern is related to the analysis part of the article, which is rather descriptive/ phenomenological and lacks depth or real new insights on explanatory factors related to emissions of grazing events. It must be possible to dig out more from such a valuable dataset. The authors explain that a multivariate regression analysis of the EF’s didn’t work out for various reasons. However, why wasn’t an multivariate regression analysis of the fluxes attempted?
In my opinion it also could be an option to divide the article in a part 1 and part 2. Part 1 consisting of the main part of the current manuscript extended with a sensitivity analysis of the choices made in deriving the fluxes (e.g the 5 sec length of the concentration time series at each height; how sensitive are the results when 10 secs are used?, the detrending procedure, the background flux correction and the gap filling procedure). Adding such a sensitivity analysis could provide valuable extra insight in the quality of the flux dataset; which is no luxury since each half hour flux value is only based on 45 sec of actually measurement data at each height. Although the data treatment appears to be carefully conducted the fact that only so few data points are used makes it hard to believe that the flux values are robust this being the last of my larger concerns); a sensitivity analysis could help to develop more trust in the flux values. Part 2 could then consist of an elaborated version of the current results section (e.g. 3.4-3.6) extended with a statistical multivariate analysis of the fluxes; perhaps combined with a modelling part.
Due to the length of the article itself I have not taken time to study systematically the supplementary material.
Specific comments
L75-l83: this paragraph is unclear to me, what is your main message?
L157: In neutral and stable conditions it is assumed… The same assumption is usually made for convective conditions as well.
L191: what is meant with the phrase ‘the nominal precision (1-sigma)’? Why (1-sigma)?
L199: In order to check whether I understand your procedure correctly: you apply linear detrending between two consecutive timeseries at the same height, hereby using the full 30-50 seconds of data? Using timeseries 1 and 2 and then 2 and 3 and then 3 and 4? Next you use the last 5 seconds of each of the 9 time series to obtain an average representative for 30 min, this is done for every height and thus obtained profile is used to determine the flux. Maybe it helps when you add words like ‘first’, ‘second ’, ‘next’ etc in the description. Or even better, add an conceptual figure on this crucial data treatment part.
L208-214: Why is this calibration necessary when only Delta NH3 are needed for the calculation of the flux? Add one sentence explaining that it is worthwhile to have reliable estimates of the absolute NH3 concentration as well.
L229: ‘near absolute mean’ What is the uncertainty (nominal accuracy) in the concentration as measured by the Delta?
Section 2.3.6: for easy reference and in order to reduce the length of the article I suggest to put the information in this section in a Table.
L256 Storage flux correction: with a time scale of 30 minutes? Based on the measurements below z_mean? Why is this discussed here? To me it appears more suitable as part of 2.5 (see also my comment on section 2.5 below)
L273-282: I suggest to shorten this section (once more to reduce the length of the article) only mentioning what you did and skipping the explanation of the flagging policy (just give a good reference for that).
L311: small or near-zero emission or deposition: why do you assume this? In figure 3 the time series of NH3 concentration shows rather high values around 9/04, 20/04 and 22/04; fluxes around this time could be substantial (however are apparently filtered out in the quality control round) so how valid is the assumption that background fluxes are small?
Eq 8 and 9: since 9 follows easily from 8 only one of the two equations needs to be presented (and when you really want to be lean both can be removed; l318-319 is clear enough about the procedure.)
Section 2.5 I miss a discussion on systematic errors here. Of course they are difficult to determine but a few can be discussed. For example the effect of a systematic error in the determination of the sampling heights (in a Delta z of 1 m an uncertainty of several centimeters already leads to a systematic bias of several percent) and displacement height. Also the (propagated) effect of an assumed but realistic systematic uncertainty in the concentration could be taken into account. Maybe the separate discussion of the theory on random uncertainties and the actual discussion in 3.5 on values of both random and systematic uncertainties doesn’t work that well. I wouldn’t mind when you combine the two and discuss them at one place.
L355: corrected -> you mean the correction for the background from section 2.4.5
L366-368 I didn’t check the supplementary material but these sentences are unclear without doing so: why are G9 and G10 different and do they need an modified gap-filling approach?
Section 3.1 How can you be sure that the results discussed in this section don’t influence the flux measurements. E.g. doesn’t the cleanliness of the mirror affect the uncertainty in the flux?
Figure 2b: to me it makes more sense to plot the results equidistant in time, just plot lines instead of bars and adjust the length of the line according to the delta time period it is represents.
Figure 3 Please add uncertainty/error bars to the NH3 concentration values in a and b.
Table 2 SE means standard error?
Figure 4 The visualization of the data in this figure doesn’t work very well. Maybe leave out the information on the quality of the fluxes (the information in Table 2 is sufficient), plot the figures 10 by 1 instead of 5 by 2 so that the time axis can be extended and present the information on the cattle differently (only when it is present and not the variation in number since the variation is most of the times not very influential; just mention the milking times in the text and not visual in the figure since you conclude it has not real influence).
L442-446 Please refrase, your main message is difficult to grasp.
L448-451 Is this a relevant observation (here)? Could perhaps skipped?
Section 3.4 A nice description of observed correlations is given but as a whole this section is a little bit disappointing because it gets stuck at this level. In section 4.4 it is stated that no statistical multivariate analysis could be applied to derive the share of EF variance explained by variables but in my opinion it is a missed opportunity that no such analysis is applied on the fluxes! Why not try such analysis for each grazing event separately and one for all cases together in order to infer variables which explain specific events and which variables are important explaining generic behavior of emission events due to grazing. Now the reader is left with huge variability in emission over de various events and no hint at an explanation.
Figure 5 Wouldn’t be worthwhile to add an figure depicting the diurnal cycle over the ten grazing events? Either normalized or not before combining, depending on what is interesting to show?
Figure 6 Why not present these results as profiles with height labeled with time instead of height and time the other way around? I find this (and other comparable plots in the article) hard to interpret. How do the soil mineral nitrogen concentrations relate to precipitation?
Figure 7 Did you make plots with all grazing events (labeled by color and aggregated in periods of ‘days since grazing’) in one figure? Doesn’t this show a pattern?
L511 Conversely- response This is rather an stand alone observation. It would be more interesting when information would be added whether this happened (albeit on a smaller scale) more often? E.g. during events G8 and G9??
Figure 8 Isn’t this a somewhat worrisome result? The measurements are done in the constant flux layer so I would hope a smaller systematic bias was found (in absolute sense). Did you check how choices made in the determination of the flux influenced this bias? Could this be used to determine the best choices regarding the flux derivation? E.g. the length of the period chosen (now 5 secs at each height)?
Table 3 How were the urinary N excreted values determined? Did I miss this somewhere or is this not explained?
Line 646-654 Since you so nicely discuss this point it is good to add that another assumption is made. K for momentum is observed to behave differently than a K for heat or moisture. It is unknown whether it is allowed to assume that a K for ammonia behaves similarly as the K for heat.
L736-743: these lines repeat information of lines l705-712; I think L705-712 can be removed. Make ‘near the surface’ more explicit; your measurement heights are already close to the surface so I guess you mean really close? A few centimeter?
L754 How was the estimated nitrogen input from grazing events determined?
L823-825 Please rewrite, this sentence is difficult the grasp by first reading.
Maybe I missed it but did you somewhere define the actual value of displacement height d? Based on figure 3 it appears to be ~ 10cm and time dependent?
Technical corrections
L50: is ‘crucial’ the right term? Don’t you mean ‘significant’?
L93: intensively grazed grassland: LSU per ha mentioned in the table are at the lower-to middle end of the numbers presented. Is it really ‘intensively’ grazed?
L95: makes possible -> enables
L174: for me the sentence is more clear when the first ‘height’ is removed.
L198: if-profile: is this not repeating the argument? Could be removed?
L201: ‘The concentration - averaging’ can be removed without loss of information.
L214: Maybe it is good to already refer to later sections where you further discuss this choice.
L452: It is also apparent that for some grazing events (e.g. …) the valid flux data capture was patchy, not necessarily – of interest (i.e. the wind was blowing from unsuitable directions). Please shorten to ‘For some grazing events (e.g. …) the valid flux data capture was patchy due to the wind blowing from unsuitable directions.
L630: ‘with’ missing in the second half?
L675 ‘horizon’ is maybe a correct (jargon) word? Or could it be replaced by layer?