the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 10 Mar 2025
Mid-Atlantic U.S. observations of radiocarbon in CO2: fossil and biogenic source partitioning and model evaluation
Abstract. Accurately quantifying regional anthropogenic CO2 fluxes is fundamental to improving our understanding of the carbon cycle and for creating effective carbon mitigation policies, and the radiocarbon to total carbon ratio in atmospheric CO2 (Δ14CO2) is a robust tracer of fossil fuel CO2 that can discriminate between biogenic and fossil fuel CO2 sources. NASA’s ACT-America airborne mission between 2016 and 2019 aimed to improve the accuracy of regional greenhouse gas flux estimates, through refining understanding and characterization of fluxes and flux uncertainties in models. Δ14CO2 observations from 26 flights are presented for examining seasonal CO2 source partitioning in the Mid-Atlantic U.S. Observed variability in boundary layer CO2 at time scales ranging from intra-day to seasonal was largely driven by biogenic CO2 (CO2bio) variability that ranged from -19.7 ppm in summer to 16.2 ppm in fall, while fossil fuel CO2 (CO2ff) variability remained at 3.3 ± 2.0 ppm. Carbonyl sulfide uptake was well-correlated with CO2bio uptake, and examining this relationship, and that between CO2 and CO2bio variability reinforces the seasonal extent of gross primary productivity response throughout ACT-America. We use airborne Δ14CO2 flask sampling alongside in situ carbon monoxide measurements to calculate high-frequency CO2ff and evaluate the magnitude and diurnal variability of modeled CO2ff, deducing likely transport errors in an example flight. Although ACT-America CO2ff signals were attenuated due to broad source regions sampled, results illustrate the value of D14CO2 sampling and observation-based methodologies for regional CO2 flux attribution and evaluation and improvement of modeled CO2.
- Preprint
(4571 KB) - Metadata XML
-
Supplement
(196 KB) - BibTeX
- EndNote
Status: closed
- RC1: 'Comment on egusphere-2025-821', Fabian Maier, 04 Apr 2025
-
RC2: 'Comment on egusphere-2025-821', Jocelyn Turnbull, 05 May 2025
This paper describes a set of 14CO2 measurements along with CO2 and other trace gases, made from aircraft campaigns in the Mid-Atlantic US region. It examines the relationships between the various measured species to evaluate the various CO2 sources and sinks. It also compares the results with modelled CO2 predictions.
The dataset is good, with careful measurements, and the analysis is good. The paper could be published with minor revisions as noted later, but it feels like a bit of a missed opportunity - the paper demonstrates how 14CO2 measurements *could* be used, but doesn’t go so far as to draw any strong conclusions from this dataset. Perhaps this is because this is a large dataset, and exploring all the different facets in detail is probably too much for one paper. I would like to see further analysis on several subtopics, as described below. It seems that there might be a way to do this by adding a few pointers to this paper that allow follow up papers that go into more detail on these topics (whereas as written currently, it might be difficult to write those additional papers without them seeming to be repetition).
Areas that should be expanded here or in future papers:
- To my knowledge, this is the first time 14CO2 and OCS measurements have been analysed side by side in this way. In fall, the 14CO2 and CO2 measurements imply a net biogenic CO2 source, but the OCS measurements indicate that significant CO2 drawdown may still be occurring. This is an initially surprising result that could have important implications for biogenic CO2 and potentially could contribute to biogenic model development.
- The use of CO to devolop CO2ff’. There are a few papers now that have used this method, but it is still under development, with little challenges coming up on each new environment in which it is used. In this case, the substantial variability in RCO, particularly in fall and spring, is curious. While the high RCO values in July might reasonably be explained by VOC production of CO, it seems surprising that VOC production would be important in October and May. This variability should be explored, to understand what might be driving it (biomass burning?), and to evaluate how the variability impacts the CO2ff’ calculations, and the uncertainty that it might induce. This could be expanded in a subsequent paper, but some of the issues do need to be addressed in this paper (see specific comments).
- As already noted on the paper, there is a large and surprising discrepancy between the observed CO2ff’ and modelled CO2ff in the case study from July 24th for Washington DC. The only conclusion currently drawn is that this suggests a model bias, perhaps associated with the time of day. This should be explored in detail, comparing the observed and modelled values for a larger suite of the aircraft observations.
Specific comments:
Line 32 also oceans, not just biosphere.
Line 45, suggest referencing Ingeborg Levin’s seminal 2003 paper here as well.
Line 48. “The remaining variability” rather than “any remaining variability”.
Line 82. OCS is mentioned only briefly in the introduction, yet the results and discussion use it quite strongly. Some discussion of the utility of OCS for quantifying photosynthetic drawdown should be added.
Line 90. How many flasks and 14C samples in each campaign, in total, etc?
Line 99 give approximate ABL heights and the altitudes at which the ABL samples were taken.
Line 125. The methodology was first described in Turnbull et al 2007.
Line 132. I believe the half-life was calculated as 5730 in this paper.
Line 140 in equation 1, only CO2bio is included in “other”, but in equation 2, the additional terms are added. Be consistent.
Line 144 see recent Maier et al paper for a different presentation of the nuclear correction.
Line 152. See Turnbull et al 2009 about the assumption that delta-photo equals delta-bg.
Turnbull, J. C., et al. (2009). "On the use of 14CO2 as a tracer for fossil fuel CO2: quantifying uncertainties using an atmospheric transport model." Journal of Geophysical Research 114, D22302.
Line 182. There is an update on graven and gruber 2011, in:
Zazzeri, G., et al. (2018). "Global and Regional Emissions of Radiocarbon from Nuclear Power Plants from 1972 to 2016." Radiocarbon 60(4): 1067-1081.
Lines 195-200. Note that these calculated values are similar to the widely used estimates first described by turnbull et al 2006.
Line 230. The median method can be problematic when CO2ff is small. Did you consider using regression to determine RCO?
Line 235. Compare to the recent Maier paper that assessed uncertainties in the different CO2ff methods.
Maier, F., et al. (2024). "Uncertainty in continuous ΔCO-based ΔffCO2 estimates derived from 14C flask and bottom-up ΔCO ∕ ΔffCO2 ratios." Atmospheric Chemistry and Physics 24(14): 8205-8223.
Line 274 “this difference”? Not sure what is being referred to here.
Lines 280-285 it seems likely that the higher FT 14C values would be due to the 14C gradient in the FT induced by cosmogenic production. See Turnbull 2009 and others for some detail on the expected magnitude of this gradient.
Lines 315-317. Please reference this statement.
Figure 5. Use OCSxs? Confusing that this is showing the OCS enhancement over background but is labelled just as OCS.
Line 345. While the explanation for the summer, spring and winter relationships is expected, the fall data is initially surprising. It is hard to believe that soil/litter uptake of OCS would be that significant (and if it is, it is an important finding). This warrants more investigation. See my general comment earlier.
Lines 375- the substantial variability in RCO needs some investigation. VOC production of CO is exponentially related to temperature (see Vimont et al 2017), so the high RCO values in July can reasonably be explained by VOC production, but it is harder to explain the fall and spring high RCO values. The high variability for those spring and fall days also suggests that another mechanism might be occurring. I am wondering if biomass burning events could explain them? Alternatively, I wonder if using the median method to calculate RCO could be a factor in these values?
Vimont, I. J., et al. (2017). "Carbon monoxide isotopic measurements in Indianapolis constrain urban source isotopic signatures and support mobile fossil fuel emissions as the dominant wintertime CO source." Elementa: Science of the Anthropocene 5(63).
See also the recent Maier paper that investigates the uncertainty in RCO and calculated CO2ff.
Figure 9. Is there. Better way to present these figures? I found them hard to look at with the large, overlapping symbols.
Lines 414-430. This paragraph is hard to follow, suggest revising for clarity. Also, see my general comment above.
Citation: https://doi.org/10.5194/egusphere-2025-821-RC2 - AC1: 'AC: Comment on egusphere-2025-821', Bianca Baier, 26 Jun 2025
Status: closed
- RC1: 'Comment on egusphere-2025-821', Fabian Maier, 04 Apr 2025
-
RC2: 'Comment on egusphere-2025-821', Jocelyn Turnbull, 05 May 2025
This paper describes a set of 14CO2 measurements along with CO2 and other trace gases, made from aircraft campaigns in the Mid-Atlantic US region. It examines the relationships between the various measured species to evaluate the various CO2 sources and sinks. It also compares the results with modelled CO2 predictions.
The dataset is good, with careful measurements, and the analysis is good. The paper could be published with minor revisions as noted later, but it feels like a bit of a missed opportunity - the paper demonstrates how 14CO2 measurements *could* be used, but doesn’t go so far as to draw any strong conclusions from this dataset. Perhaps this is because this is a large dataset, and exploring all the different facets in detail is probably too much for one paper. I would like to see further analysis on several subtopics, as described below. It seems that there might be a way to do this by adding a few pointers to this paper that allow follow up papers that go into more detail on these topics (whereas as written currently, it might be difficult to write those additional papers without them seeming to be repetition).
Areas that should be expanded here or in future papers:
- To my knowledge, this is the first time 14CO2 and OCS measurements have been analysed side by side in this way. In fall, the 14CO2 and CO2 measurements imply a net biogenic CO2 source, but the OCS measurements indicate that significant CO2 drawdown may still be occurring. This is an initially surprising result that could have important implications for biogenic CO2 and potentially could contribute to biogenic model development.
- The use of CO to devolop CO2ff’. There are a few papers now that have used this method, but it is still under development, with little challenges coming up on each new environment in which it is used. In this case, the substantial variability in RCO, particularly in fall and spring, is curious. While the high RCO values in July might reasonably be explained by VOC production of CO, it seems surprising that VOC production would be important in October and May. This variability should be explored, to understand what might be driving it (biomass burning?), and to evaluate how the variability impacts the CO2ff’ calculations, and the uncertainty that it might induce. This could be expanded in a subsequent paper, but some of the issues do need to be addressed in this paper (see specific comments).
- As already noted on the paper, there is a large and surprising discrepancy between the observed CO2ff’ and modelled CO2ff in the case study from July 24th for Washington DC. The only conclusion currently drawn is that this suggests a model bias, perhaps associated with the time of day. This should be explored in detail, comparing the observed and modelled values for a larger suite of the aircraft observations.
Specific comments:
Line 32 also oceans, not just biosphere.
Line 45, suggest referencing Ingeborg Levin’s seminal 2003 paper here as well.
Line 48. “The remaining variability” rather than “any remaining variability”.
Line 82. OCS is mentioned only briefly in the introduction, yet the results and discussion use it quite strongly. Some discussion of the utility of OCS for quantifying photosynthetic drawdown should be added.
Line 90. How many flasks and 14C samples in each campaign, in total, etc?
Line 99 give approximate ABL heights and the altitudes at which the ABL samples were taken.
Line 125. The methodology was first described in Turnbull et al 2007.
Line 132. I believe the half-life was calculated as 5730 in this paper.
Line 140 in equation 1, only CO2bio is included in “other”, but in equation 2, the additional terms are added. Be consistent.
Line 144 see recent Maier et al paper for a different presentation of the nuclear correction.
Line 152. See Turnbull et al 2009 about the assumption that delta-photo equals delta-bg.
Turnbull, J. C., et al. (2009). "On the use of 14CO2 as a tracer for fossil fuel CO2: quantifying uncertainties using an atmospheric transport model." Journal of Geophysical Research 114, D22302.
Line 182. There is an update on graven and gruber 2011, in:
Zazzeri, G., et al. (2018). "Global and Regional Emissions of Radiocarbon from Nuclear Power Plants from 1972 to 2016." Radiocarbon 60(4): 1067-1081.
Lines 195-200. Note that these calculated values are similar to the widely used estimates first described by turnbull et al 2006.
Line 230. The median method can be problematic when CO2ff is small. Did you consider using regression to determine RCO?
Line 235. Compare to the recent Maier paper that assessed uncertainties in the different CO2ff methods.
Maier, F., et al. (2024). "Uncertainty in continuous ΔCO-based ΔffCO2 estimates derived from 14C flask and bottom-up ΔCO ∕ ΔffCO2 ratios." Atmospheric Chemistry and Physics 24(14): 8205-8223.
Line 274 “this difference”? Not sure what is being referred to here.
Lines 280-285 it seems likely that the higher FT 14C values would be due to the 14C gradient in the FT induced by cosmogenic production. See Turnbull 2009 and others for some detail on the expected magnitude of this gradient.
Lines 315-317. Please reference this statement.
Figure 5. Use OCSxs? Confusing that this is showing the OCS enhancement over background but is labelled just as OCS.
Line 345. While the explanation for the summer, spring and winter relationships is expected, the fall data is initially surprising. It is hard to believe that soil/litter uptake of OCS would be that significant (and if it is, it is an important finding). This warrants more investigation. See my general comment earlier.
Lines 375- the substantial variability in RCO needs some investigation. VOC production of CO is exponentially related to temperature (see Vimont et al 2017), so the high RCO values in July can reasonably be explained by VOC production, but it is harder to explain the fall and spring high RCO values. The high variability for those spring and fall days also suggests that another mechanism might be occurring. I am wondering if biomass burning events could explain them? Alternatively, I wonder if using the median method to calculate RCO could be a factor in these values?
Vimont, I. J., et al. (2017). "Carbon monoxide isotopic measurements in Indianapolis constrain urban source isotopic signatures and support mobile fossil fuel emissions as the dominant wintertime CO source." Elementa: Science of the Anthropocene 5(63).
See also the recent Maier paper that investigates the uncertainty in RCO and calculated CO2ff.
Figure 9. Is there. Better way to present these figures? I found them hard to look at with the large, overlapping symbols.
Lines 414-430. This paragraph is hard to follow, suggest revising for clarity. Also, see my general comment above.
Citation: https://doi.org/10.5194/egusphere-2025-821-RC2 - AC1: 'AC: Comment on egusphere-2025-821', Bianca Baier, 26 Jun 2025
Data sets
ACT-America In Situ and Flask Data K .J. Davis et al. https://doi.org/10.3334/ORNLDAAC/1593
ACT-America Flask Data C. Sweeney et al. https://doi.org/10.3334/ORNLDAAC/1575
ACT-America Meteorological and Aircraft Navigational Data M. M. Yang et al. https://doi.org/10.3334/ORNLDAAC/1574
NOAA GGGRN D14CO2 and CO Flask Data B. Baier et al. https://doi.org/10.15138/87ny-6277
WRF-Chem Baseline Simulations for North America, 2016-2019 S. Feng et al. https://doi.org/10.3334/ORNLDAAC/1884
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 274 | 53 | 17 | 344 | 37 | 18 | 23 |
- HTML: 274
- PDF: 53
- XML: 17
- Total: 344
- Supplement: 37
- BibTeX: 18
- EndNote: 23
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1