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| 03 Apr 2024
Diurnal, seasonal, and interannual variations in δ(18O) of atmospheric O2 and its application to evaluate changes in oxygen, carbon, and water cycles
Abstract. Variations in the δ(18O) of atmospheric O2, δatm(18O), is an indicator of biological and water processes associated with the Dole-Morita effect (DME). The DME and its variations have been observed in ice cores for paleoclimate studies, however, variations in present-day’s δatm(18O) have never been detected so far. Here, we present diurnal, seasonal, and interannual variations of δatm(18O) based on observations at a surface site in central Japan. The average diurnal δatm(18O) cycle reached a minimum during the daytime, and its amplitude was larger in summer than in winter. We found that use of δatm(18O) enabled separation of variations of atmospheric δ(O2/N2) into contributions from biological activities and fossil fuel combustion. The average seasonal δatm(18O) cycle reached at a minimum in summer, and the peak-to-peak amplitude was about 2 per meg. A box model that incorporated biological and water processes reproduced the general characteristics of the observed diurnal and seasonal cycles. A slight but significant secular increase of δatm(18O) by (0.22 ± 0.14) per meg a−1 occurred during 2013–2022. The box model could reproduce the secular trend if consideration was given to long-term changes of terrestrial gross primary production (GPP), photorespiration, and δ(18O) of leaf water (δLW(18O)). We calculated changes of δLW(18O) using a state-of-the-art, three-dimensional model, MIROC5-iso. A comparison between the observed and simulated δatm(18O) values suggested that there had been a recent increase of global GPP, a slight decrease of photorespiration, and an increase of carboxylation (total carbon fixation).
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Status: open (until 15 May 2024)
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RC1: 'Comment on egusphere-2024-654', Anonymous Referee #1, 15 Apr 2024
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Review of “Diurnal, seasonal, and interannual variations in δ(18O) of atmospheric O2 and its application to evaluate changes in oxygen, carbon, and water cycles” by Ishidoya et al., 2024
General:
The manuscript presents a study of highest relevance for the linkages among the carbon, oxygen and water cycles. For the first time, a research group has analysed long-term measurements of the atmospheric oxygen isotope ratio (18O/16O) intending to see the impact of natural (biospheric fluxes) and anthropogenic (fossil fuel combustion). It is a fascinating manuscript to read and I would like to congratulate them for their long-term measurement effort as well as their in-depth analyses.
The manuscript is nicely written and organized and can be considered for publication with minor changes outlined below.
Major points:
(1) As already estimated in former studies, the expected signal in the atmospheric δ(18O) by the above mentioned isotope fluxes is minimal. This requires high precision measurements over an extended period in order to see such a small signal as the single uncertainty is about 10 times larger. The required precision and accuracy, especially important for trend analysis, can only be achieved by averaging over many measurements as shown in the manuscript.
I am not sure whether the mass spectrometer was dedicated only to these measurements and whether it was run day and night autonomously. Controlling the long-term stability only every month is quite rare because the mass spectrometers behavior can change suddenly due to maintenance (filament change, ion source tuning etc). Can you please comment on these points and maybe add an additional short section about it.
(2) Regarding the long-term estimated change in d18O(O2), the authors assume a constant increase rate of the GPP per year. For me, this does not make sense as there are many studies out there discussing the CO2 fertilization effect. Therefore, I would rather assume a scaling based on the excess CO2 level (CO2actual – CO2 preindustrial). Even though this will most probably not affect their results significantly (Fig. 8), but it still better than use a constant increase rate. In particular as the authors have used a CO2-dependent photorespiration rate (eq. 5).
Minor points:
Title: Diurnal, seasonal, and interannual variations in δ(18O) of atmospheric O2 and its application to evaluate changes in oxygen, carbon, and water cycles.
What kind of changes do you mean here? Changes in trend, seasonality, fossil fuel influence, natural changes?L15-16 the amplitude is very small, how about its uncertainty? Because it is a mean of about 11 seasons, the seasonality could be smoothed.
L18 The secular increase is even more delicate to determine, which requires an extreme stability of the instrument and the standard gas measurements. What about the influence of filament changes, power interruptions, ion source tunings, inlet system, gas flow regime. I am amazed about the stability that is required. Isotope ratio may be less prone to changes but elemental ratios as O2/N2 or Ar/N2 are generally more dependent on such changes. Can you comment on these. Thank you.
L26-28 consider rewording to:
The 18O/16O ratio of atmospheric O2, datm(18O), is about 24 ‰ higher than that of ocean water (per definition 0 ‰ on the Vienna-Standard Mean Ocean Water (V-SMOW)) due to various processes in the global oxygen and water cycle (e.g. Craig, 1961; Barkan and Luz, 2005)L35-36 Please give corresponding references. There are many more than given here
L37 ..of present air, ...
L37 ….and that variations of the DME from the average are ±0.2 ‰. This addition is not clear, please be more specific here.
L45 Which value is now used? You may write...and have obtained a range of 22.4 to 23.3 for DME.
L63-65 This is a very interesting statement.
L82-83 Switch sentence structure, 2nd part first and vice versa.
For the continuous measurements of stable isotopic ratios of O2, N2, and Ar (datm(18O), datm(15N), and datm(40Ar)) as well as the O2/N2 ratio and amount fraction of CO2, we repeatedly conducted alternate analyses of the sample and reference air.L84 how come to determine a trend of 0.22 permeg or a seasonality of 2 permeg with a standard deviation of 20 permeg. This requires an well-defined long-term stability.
L86 …calculated by ...Keeling…
L88-89 For this purpose, the measured values of the datm(18O) for the same air sample needed to not show any temporal drift, at least during the averaging period.
not clear what you want to say here, maybe you combine it with the previous sentence to
This averaging results theoretically in a standard error of the observed datm(18O) of less than 0.6 per meg assuming no temporal drift during the averaging period.L106 …an uncertainty of ±0.13 per meg a–1….how was this calculated?
L113-114 As seen in Figure 3a, datm(18O) increased linearly with increasing amount fractions of CO2.
Why, what are the reasons? There is no isobaric interference. Has it to do with isotope exchange between CO2 and O2? Have you done CO2 additions with O2 labelling?L120-121 reword to …....in our earlier flask studies in 2013.
L135-136 RTS and RST denote the ratios of the annual fluxes of O2 between the troposphere and stratosphere, respectively.
to what? It is a ratio.L140 …the amount fraction of O2 calculated by the 140 box model was converted to d(O2/N2).
how? Assuming a norm atmosphere or using the measurements to do it correctly. I ask this because of dilution effects.L152-153 Here, eST was set to –4 per meg so that the diminution of datm(18O) at equilibrium was –0.4 ‰.
How come?L161-162 This uncertainty complicates the problem of inter-annual datm(18O) change and suggests that gravitational separation may be involved in small fluctuations in the DME.
One needs to look into O3 and 14C variations at high altitudes, ideally close to the tropopause.L204-205 …and artificial inlet fractionation induced by radiative heating of an air intake (e.g., 205 Blaine et al., 2006).
You mentioned that thermal diffusion is not affecting the measurements due to the high flow rate.L234 1.46 ….in graph 1.45
L239 why only to terrestrial and not to marine biosphere activities?
L243-244 (https://www.enecho.meti.go.jp/statistics/energy_consumption/ec002/results.html#headline2, last access: 28 March 2024, in Japanese) (Ishidoya et al., 2020).
paper in 2020, reference in 2024?L244-246 The implication is therefore that the isotopic discrimination of O2 during activities of the terrestrial biosphere was the main cause of the observed summertime diurnal datm(18O) and d(O2/N2) cycles, and the isotopic discrimination of O2 during fossil fuel combustion was very small or negligible.
The same conclusion could be drawn by radiocarbon measurements. I guess 14C measurements are being done at your station. Why not use and show it?L254-256 This method, hereafter referred to as the “datm(18O)-method”, enabled us to remove the impact on d(O2/N2) of not only the activities of the 255 terrestrial biosphere but also the contributions due to the air–sea O2 flux, which is driven mainly by activities in the marine biosphere (e.g., Nevison et al., 2012; Eddebbar et al., 2017), from the estimated dFF(O2/N2).
Not clear as you first make the balance between observed and bio to obtain the FF. By doing this you cannot disentangle the air-sea O2 flux from the terrestrial O2 flux.L267-268 It is noteworthy that propane (CH3CH2CH3), for which the ORFF is 1.67 for complete combustion, should also be considered as the household gas consumed in the TKB area.
This is very interesting.L278-281 y. Similar separation has been carried out for CO2 based on the simultaneous analysis of the D(14C) and amount fraction of CO2 (e.g., Basu et al., 280 2020) or based on the simultaneous analysis of d(O2/N2) and the amount fraction of CO2 by assuming an average ORFF based on a statistical assessment (Pickers et al., 2022).
There are more publications available that might be cited!L291-292 Figure 7a therefore shows 116 and 120 datm(18O) and d(O2/N2) data, respectively.
rewriteL306-309 Keeling (1995) expected datm(18O) to be lower in summer than in winter by 2 per meg based on the assumption that the 100 per meg seasonal increase of d(O2/N2) was driven by the input of photosynthetic O2, the d(18O) of which is about 20 ‰ lower than datm(18O).
Show how to calculate it!L316 We found that the box model could reproduce the observed seasonal datm(18O) cycles
You adjusted the corresponding values. Questions are remaining as to whether the used model values fall within known ranges.L355-357 see major point 2
Fig. 2 The measurements are not equally distributed over time, this influences the uncertainty per year. Have you considered this?
Citation: https://doi.org/10.5194/egusphere-2024-654-RC1
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