Articles | Volume 18, issue 20
https://doi.org/10.5194/amt-18-5349-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.A relaxed eddy accumulation flask sampling system for 14C-based partitioning of fossil and non-fossil CO2 fluxes
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- Final revised paper (published on 15 Oct 2025)
- Preprint (discussion started on 10 Jan 2025)
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-2024-3175', Anonymous Referee #1, 25 Feb 2025
- AC1: 'Reply on RC1', Ann-Kristin Kunz, 24 Jun 2025
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RC2: 'Comment on egusphere-2024-3175', Anonymous Referee #2, 02 Jun 2025
- AC2: 'Reply on RC2', Ann-Kristin Kunz, 25 Jun 2025
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Ann-Kristin Kunz on behalf of the Authors (17 Jul 2025)
Author's response
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ED: Publish as is (02 Aug 2025) by Daniela Famulari

AR by Ann-Kristin Kunz on behalf of the Authors (04 Aug 2025)
This is a technical paper, describing a “relaxed eddy accumulation” (REA) system to collect air for 14C analysis, in conjunction with CO2 eddy covariance systems. Adding 14C allows the partitioning of CO2 into fossil and non-fossil components. REA is designed to separate and capture air from updrafts and downdrafts, to separate (in this case) 14C values for up and down drafts, and therefore calculate fluxes. The paper gives very detailed information on the REA system design, as well as carefully evaluating the sources of uncertainty in the system.
This is, I believe, the first time an REA system has been built for 14C sample collection, and while REA is conceptually straightforward, it is quite technically challenging to implement. Thus the level of detail in system design and evaluation is appropriate. The detail provided would allow others to mimic the system – although my suspicion is that this system is complex enough that there will be few takers.
The paper is well written, and I have only a few minor comments. I recommend acceptance with the minor revisions I have noted.
Page 2 line 36. I agree that EC is the only method to directly measure fluxes. Given the discussion in the previous paragraph of inventory methods, it would be worthwhile to mention that there are multiple other atmospheric methods available besides EC. This is particularly relevant to this paper because while this paper presents the first time 14C has been used in REA, 14C measurements are widely used in other urban atmospheric methods, such as tracer ratios.
Page 2 line 44. Human respiration is more typically ~5% of the total annual CO2 flux, and it depends not only on population density, but on emissions density.
Page 2 lines 49-51. Suggest rephrasing this sentence, as it implies that in situ 14CO2 measurements are available, just not at fast-response. In fact, 14CO2 measurements can not yet be made in situ at all, except a few novel laser-based measurements that have not yet acheived the precision or method development to allow them to be used for atmospheric applications such as this.
Page 13. Line 286. Suggest renumbering the 3 points as 5.1, 5.2, 5.3 to match the following section labels.
Page 14. Line 308. Here it says that the difference between two buffer fillings is 0 ± 52 ppm. In the next sentence, the additional uncertainty is estimated at 0.15 ppm. I don’t quite follow how this is calculated, and wonder whether the ± 52 ppm is a typo?
Page 21. Line 470. Consider adding Turnbull et al 2015, Miller et al 2020 as additional references.
Turnbull JC, Sweeney C, Karion A, Newberger T, Lehman SJ, Tans PP, Davis KJ, Lauvaux T, Miles NL, Richardson SJ et al. 2015. Toward quantification and source sector identification of fossil fuel CO2 emissions from an urban area: Results from the INFLUX experiment. Journal of Geophysical Research: Atmospheres. 120.
Miller JB, Lehman SJ, Verhulst KR, Miller CE, Duren RM, Yadav V, Newman S, Sloop CD. 2020. Large and seasonally varying biospheric CO2 fluxes in the Los Angeles megacity revealed by atmospheric radiocarbon. Proceedings of the National Academy of Sciences of the United States of America.
Page 21-22 section 6. ∆CO2 partitioning. The authors note that the ∆14C differences between up and downdrafts are small relative to the measurement uncertainty, resulting in many of the differences being indistinguishable from zero. There is some discussion in this section and also in appendix D about this, but the paper would benefit from expanding this discussion.
First, the actual ∆14C measurement precision acheived for these samples is not given, instead the uncertainty in calculated ∆ffCO2 is reported. It would be helpful to indicate what the ∆14C uncertainties are for these measurements. My estimate from the reported ∆ffCO2 uncertainties is that the ∆14C measurement uncertainties are around 2‰. Reducing these uncertainties would go a long way to improving the utility of the method. Several other labs are now reporting around 1.5‰ uncertainty on 14C measurements, and this modest improvement would make a significant difference to the fraction of usable measurements.
Since the REA method doesn’t appear to be sample size limited, one could also consider measuring multiple graphite targets to reduce the overall uncertainties. This would of course come at considerable cost in money and instrument time, but might be worth considering in the future.
Another option would be to make these REA measurements at EC sites that are closer to the surface and/or to sources, so that the ∆14C differences are larger. This would certainly be useful in demonstrating the technique, and could be a necessary constraint for the foreseeable future if ∆14C uncertainties cannot be beaten down further.
I don’t suggest that the authors try to implement these things in this paper, but some discussion of these points would be helpful.
Page 23. Lines 508-518. The same comments as above apply – indeed the signal-to-noise seems to be the main challenge.
Page 23 line 522. Including CO and/or other species in these analyses would be very interesting. I wonder if incorporating CO measurements could also help resolve the signal-to-noise issues?