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the Creative Commons Attribution 4.0 License.
| 07 Feb 2024
Working standard gas saving system for in-situ CO2 and CH4 measurements and calculation method for concentrations and their uncertainty
Abstract. We have developed a container system for in-situ measurement of CO2 and CH4 that significantly reduces the consumption of working standard gases to a level less than one order of magnitude smaller than that required by a common method. It uses on-site compressed air to track the baseline drift of sensors. JR-STATION (Japan-Russia Siberian Tall Tower Inland Observation Network) consisted of this system installed at nine sites in Siberia. The system acquires semi-continuous data by recording several minutes of averaged data after gas replacement time. We have updated the calculation method for deriving CO2 and CH4 concentrations to determine their uncertainty for each data simultaneously. Furthermore, we estimated the system's reproducibility based on the repeated measurement of on-site compressed air. The CO2 and CH4 concentration reproducibility mostly varied by less than 0.2 ppm and five ppb, respectively. Uncertainties of time-averaged data were sometimes higher than the measurement uncertainty for each period, suggesting that the data include atmospheric variability during the measurement period of several minutes. Data users should consider the difference between the two uncertainties to select optimal data, depending on their focusing spatial scale. The CO2 and CH4 data measured with the NDIR and the tin dioxide sensor exhibited good agreement with those measured by the CRDS, respectively.
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RC1: 'Comment on amt-2023-246', Anonymous Referee #1, 26 Mar 2024
The manuscript by Sasakawa et al. describes the analytical set-up, the standardization and uncertainty evaluation of CO2 and CH4 measurements at several tall tower observational stations in Siberia over several years. Those data have been made available recently and such measurements are of immense scientific value as they are extremely scarce in that part of the world. They provide constraints for global inversion studies needed to improve the assessment of the carbon cycle. Therefore, it is very appropriate to publish all details that allow an assessment of the accuracy of this data set and AMT certainly is a magazine where such an article is well placed.
While acknowledging the relevance of the subject the manuscript there are several topics where I would ask the authors for revisions.
General comments:
- The manuscript title suggests that the gas saving system is being published in this manuscript. However, the setup has already been described earlier (as cited in the manuscript) so a rewording of the title might be considered.
- A detailed report of the uncertainty should consist of a complete list of the uncertainty components. While the manuscript addresses instrument repeatability, the calibration procedure and the reproducibility within about one week, there are some topics (listed below) not being included. For a subset of sites results of a comparison between two different analyzers calibrated by the same set of standard gases are presented. The assessment of the uncertainty is found to be consistent with the comparison results for CO2 and at two of the three test sites for CH4 which seems to be taken by the authors as a confirmation for the completeness of the uncertainty evaluation. Yet, I see the following aspects either missing or not adequately accounted for in this uncertainty assessment:
- The accuracy of the assignments of the standard gases is not discussed. An estimate for the uncertainty introduced by the calibration transfer procedure from the respective NIES calibration scales to each individual standard is not provided nor the analytical method for the calibration transfer. It is described that the standard gases were prepared from pure CO2 diluted with purified air. This could mean that the isotopic composition of the CO2 in these synthetic standard gases is different to the atmospheric CO2 which would cause different sensitivities of the NDIR analyzer to the standard gas and the sample CO2, respectively. A respective clarification should be provided and if needed an uncertainty term for the isotopic discrimination be added.
- The stability of the CO2 mole fraction of a standard gas during the entire period of usage cannot be assumed to be certain. At least at the KRS site calibration standards apparently have been replaced. Have those standards been recalibrated after usage at the NIES laboratory for confirmation of their stability?
- For the scale relationship between the NIES scale and the WMO scale the results of the WMO Round Robin 6 Experiment are quoted. However, the period under review extends from 2005 to 2019 and three Round Robin Exercises (4-6) have taken place during that time. It would appear reasonable to consider all these results and deduce an uncertainty of the scale relationship. If other evidence for the relationship between the WMO scale and the NIES scale existed that might further help to get a better constrained uncertainty for this.
- The NDIR detection with the specified instrument is known to be not perfectly linear. In the manuscript no test results for this are being presented / discussed. A different presentation of the NDIR-CRDS differences (residuals, i.e. difference NDIR-CRDS vs CO2 plots instead of CO2(CRDS) vs CO2(NDIR) plots) could allow to judge how significant this non-linearity is (taking the CRDS as a linear reference).
- The authors state that “From the point of this procedure, the SWS-gas equates with the 'target tank' or 'surveillance tank' mentioned in the GAW report (WMO, 2018)”. However, the scatter of the SWS target with a usage time of ca 1 week mostly reflects the output drifts within 12 hours that are not accounted for with the employed calibration approach. This SWS target gases can certainly not assess the long-term reproducibility throughout many years or even just one year (where different seasonal temperatures within the measurement container could cause an effect). For this a real long-term surveillance tank would be needed. A stronger independent check is the parallel measurement by the CRDS instruments. It is very convincing that the two measurements agree within the expectation and the annual mean differences remain pretty constant. I propose to add another figure for the Supplement displaying the NDIR-CRDS differences and TOS-CRDS differences vs time. This would allow to identify or exclude any season dependent inter-instrument offsets.
- Reference is being made to the GAW report with the WMO CO2 Expert’s meeting recommendations. However, the compatibility goals that are specified in this report for such background observations are not quoted (0.1 µmol/mol for CO2 and 2 nmol/mol for CH4). It is fully appreciated that the immense logistical challenge to operate these measurements at such remote places set boundary conditions that take their toll. I encourage the authors to actively discuss the discrepancy between the WMO compatibility goals and the results they achieved. The measurement uncertainties achieved should also been put into the context of the signals observed in the records and into the context of the gradients within this JR-STATION network (e.g. as presented in the Sasakawa et al 2010 paper) or relative to global reference stations (e.g. Mauna Loa, Alert, Mace Head). As stated these data are extremely scarce and will certainly be valuable for many applications also with larger uncertainty as targeted with the WMO compatibility goals. This could be an additional summarizing section 3. Currently if feels that after the individual descriptions of uncertainties in sectin 2.4.2, 2.4.3 and 2.5 a summarizing part is missing.
- Comparison measurements are available only for some stations and the last few years. The case of the failing catalyst for the TOS CH4 sensor at NOY demonstrates that an independent long-term check is needed to realize instrumental failures that can happen. The authors should comment if this failure could have been detected also by other measurement parameters not related to the CRDS measurement.
Specific comments
l. 27: “A CRDS (Cavity Ring-Down Spectroscopy) analyzer is more stable and does not need frequent checks of the drift (ICOS RI, 2020).” I feel this might be misinterpreted in a way that you do not take care of response drift. The ICOS document recommends as starting point bi-weekly calibration and 7 hourly target gas measurements so perhaps that could be presented as an example.
l. 51: “The measurement system was housed in a freight container insulated to reduce temperature variation.” There is no further detail given on whether any active temperature control was performed within the container, whether the temperature was recorded and what temperature changes occurred within the container over the years and within the 12 h calibration intervals.
l. 79: “To protect the cavity of the CRDS from an inflow of the dissolved chemical desiccant (Mg(ClO4)2 or P2O5) in the accidental case of a broken pump etc., we equipped the CRDS with two poppet check valves (“PCV” in the analyzer unit)”. As I understand Figure 1 the CRDS is not positioned downstream of P2O5 or Mg(ClO4)2 so perhaps either the figure or the text need an update.
l. 82: pure CO2: If the CO2 in the working standard gases is entirely from pure CO2 the isotopic composition matters. Is this available? If purified air means that the matrix is ambient air already containing natural CO2 and only moderate amounts of pure CO2 are added that might matter less.
l. 84: it would be good to rather refer to WMO X2019 than to X2007 scale (or provide in addition the information of the WMO X2007 to X2009 conversion term).
l. 85: As stated before it is not clear why only two data points from one WMO Round Robin are being taken as basis for the NIES – WMO scale relationship whereas more Round Robin data is available.
l. 170 “The analysis precision for this system was uniformly estimated as 0.3 ppm for CO2 (Watai et al., 2010).” I suggest to add: The reported precision for this system under laboratory conditions was estimated as 0.3 ppm (Watai et al., 2010)
l. 180 To make it clear, the language of this sentence needs a bit of rephrasing like: “We estimated the outputs in voltage of three standard gases at [..] difference of the outputs in voltage of the SWS-gas only when both standard gas measurements satisfied the criteria described in section 2.3”
l. 249: The GAW report 255 (WMO, 2020) explicitely states: “Standard deviations are distinct from measurement uncertainty and should be reported in addition to rather than in lieu of measurement uncertainty. Standard deviations provide a measure of atmospheric variability (AV) plus instrument noise.”. So a better metric for the repeatability term might refer to the repeatability of the adjacent SWS measurements rather than the standard deviation of 3 min of atmospheric measurement.
l. 255 “The fourth term expresses the contribution from the variation in x. In most cases, the uncertainty for the concentration of standard gases is not given, or it can be negligible compared with other uncertainties. Thus, we neglected this term.” That it is negligible appears like a speculative statement that I do not feel can be kept as is. To justify the neglect of this term there needs to be a quantified small uncertainty for the assignment and also the stability of the mole fractions for the period of use.
l. 265: We calculated a calibration line only when the SWS-gas measurements closest to both sides of the sample measurements were normal.
l. 267: The following text should be reformulated: “However, a gap would appear if the system temporarily became unstable. To detect any gap, ..” The gap only appears when the criteria are applied that are explained below. If I got it right I guess a sentence like the following describes it better: “When the system temporarily became unstable the corresponding large changes of the analyzer output could not be corrected by the SWS to a sufficient degree. To identify such occasions…”
l. 280: “We determined a threshold for the standard deviation (σsws; 1 ppm for CO2, 10 ppb for CH4) and the fluctuation range (5 ppm for CO2 and 20 ppb for CH4) obtained from the estimated independent data set. All the data that exceeded the threshold were deleted.” Does one outlier invalidate the entire week? From this text I would assume YES, from Figure 5 I would guess that NO.
l. 284: “From the point of this procedure, the SWS-gas equates with the 'target tank' or 'surveillance tank' mentioned in the GAW report (WMO, 2018).” I do not fully agree, see general comment above.
l. 285: GAW report 242 (WMO, 2018) has a more up-to-date succeeding GAW report 255 (WMO, 2020).
l. 303f: “Only data from the period when the system was normal was extracted.” I propose to rephrase: Only data from periods was extracted when the SWS results fulfilled the reproducibility criteria outlined in the previous section.
l. 310: Please add “No significant difference in the instrument offset between the different intake heights was found for CH4 concentration either.” Else the sentence contradicts the following sentence.
l. 311-316: Reading “it is expected that the temperature regulation of the catalytic unit did not work well and the catalyst did not function” it remains unclear to me if there were any other indications other than the increasing and instable bias from the TOS to the CRDS that allowed to identify the problem with the TOS catalyst (e.g. more variable calibration fit residuals or clearly implausible atmospheric CH4 mole fractions). Fig. S5 and S6 do not reveal any problem. If there is no such additional indicator that raises the question if the same problem might also have happened unrecognized at one of the sites without CRDS?
l. 320 / 328: Figures 6 and 7: to judge the agreement between the two instruments the way of display is not ideal: presenting the residuals (NDIR – CRDS) would allow to zoom in to the differences which is more informative
Figure S1-6: black dots are named to represent the “uncertainty for the CO2 measurement”. As stated above (specific comment to l. 290) uncertainty is not appropriate term if the standard deviation of 60 three second averages of atmospheric measurements is referred to. Please change the terminology in the caption here.
If it does not need too detailed descriptions some short general explanations could be considered what general problems have caused the large data gaps in the beginning.
The supplement figures S1-S6 only display data from the NOY site, so there is no information on the relative performance at the other sites. It might help if not only NOY as an example was presented but also the same information of the other stations.
Figure S2: The sample uncertainty (black dots) of NOY in the last months of 2012 has a remarkable two level pattern. Is this a 12 hour shift day-night pattern of atmospheric variability? Something else? Why only in that year?
Figures S7 and S9: The legend description "WBT unstable" is not further explained in the caption and the abbreviation WBT not used anywhere in the manuscript.
Figure S10: The data of NOY 2018 appear to group along two lines. Is there any explanation that the authors could offer?
Citation: https://doi.org/10.5194/amt-2023-246-RC1 -
RC2: 'Comment on amt-2023-246', Anonymous Referee #2, 13 Apr 2024
Review of “Working standard gas saving system for in-situ CO2 and CH4 measurements and calculation method for concentrations and their uncertainty”
Sasakawa et al.
General Comments
This is a useful paper, describing GHG measurements in a poorly measured part of the world. Furthermore, the description and evaluation of this technique for using locally-prepared artifacts for tracking instrument drift is valuable for the community.
I have a few general comments for improvement:
- It seems to me that an opportunity has been lost to explore the performance of the sub-working standards. Twice a day for the week or so duration of a given SWS (A or B), you have assessments of the SWS concentration, using both the NDIR / TOS system and the CRDS. Do you observe a clear dependence of the reported concentration from the SWS over time after filling? Any dependence on the cylinder itself? Dependence on ambient temperature? Dependence on the concentration of the gas? Dependence on pressure in the cylinder? Similiarly, there are 100-200 measurements of each SWS using the CRDS, which would show the behavior of the SWS with much higher temporal resolution. Correlations to ambient temperature, pressure, etc could be performed with much higher fidelity. These would be interesting statistics to collect and present. It would allow those who want to use this approach to have some idea of ways in which the recipe could be modified without danger of exceeding the boundaries of the validation that you have done. I would like to see some of these data explored, summarized in the main text with additional data in the supplement.
- In a similar vein, you have long time series measurements of the WS tanks, both with the CRDS and the other sensors. The CRDS could give you some idea of WS variability and WS to WS accuracy as new WS tanks are swapped in, and would help you tie your measurements down to the absolute scale. And the WS measurements on the NDIR and TOF would give an idea of the nature of the drift of these sensors. In particular, it would give insight into whether drifts appear as an offset in voltage or span change in voltage (see comment #3, below), and the nature in the errors in the sensor with ambient temperature, ambient pressure, time of year, etc. These analyses would be helpful to the readers of this article.
- The approach to using the SWS to extend the life of the WS is essentially to perform linear interpolation in voltage from the twice daily calibration of the SWS using the three WS tanks. That assumes that the correction to the sample data from the SWS measurements is applied as an offset to the sample voltage, regardless of the SWS measured. But could the correction also be applied as a slope correction? That is, a correction that is proportional to the measured voltage? How do you know which is the right approach for each sensor? Similarly, NDIR is known to have a nonlinear response. Does the TOS also have a non-ideal (i.e., not logarithmic) response? Are these nonlinearities significant relative to your target uncertainties? Do your data shed any light on these concerns? Please add some discussion of these issues in the text.
Specific Comments
- In general, there are too few references. It would be good to add a few more references pointing to other calibration strategies used in the GHG monitoring community for CO2 and CH4, references to the individual measurement technologies, references to similar data sets in the regions (e.g. ZOTTO), etc. It would help to put this manuscript in better context relative to similar work.
- L105-108: It’s not clear the sequence of preparing and using the two SWS cylinders A and B. For example, when A is being used, is B being filled? Does a cylinder ever get used once it drops below 0.1 MPa? Is the cylinder pumped out prior to refilling? Do you have a time delay to allow the gas in the cylinder to equilibrate? Do you fill the cylinders at a certain time in the day?
- The plumbing schematic of the SWS and associated manifold for filling and dispensing gas, with the double arrows and the 3-way valve bridge, is confusing. Showing the NC, NO, and COM on the valves, and then a table with the states (e.g., FILL A, USE B, etc..) would be helpful here in reproducing the setup.
- L126-127: “had a more significant standard deviation than a determined threshold (2 mV for CO2, 5 mV for CH4).” Reporting fluctuations in mV without describing the mapping of voltage to concentration, it difficult to understand the context of what this noise, and the selected thresholds, mean. A short section describing the response of the detectors prior to this would be good.
- L135: It’s often considered a good idea not to perform calibrations at exactly the same day and time. Why was 12 hours chosen as the interval? Do you see persistent differences between the day and night calibrations?
- L319 and L327: Correlation plots are useful, but residual plots (TOS – CRDS and NDIR – CRDS) would be instructive in understanding any concentration dependence to the results.
- Similarly, residual plots over time in the supplement would help understand the potential for biases in the measurements.
- A particularly useful plot would be to show σsws vs the std. deviation of the difference between the sensor data and the CRDS over time and/or as a scatter plot. A plot like these would illuminate whether your uncertainty estimates properly capture the actual uncertainties in the sensor measurements using the SWS.
- L319: There is a striking set of outliers just below the 1:1 line in the 2018 panel (at about 415 ppm CO2). There are two similar though less obvious outlier groupings in the 2020 data panel as well. What is the cause of these discrepancies? Shouldn’t they have been trapped by the data quality checks? Some explanation in the text would be helpful.
Technical Corrections
L12: “to a level less than one order of magnitude smaller” – unclear whether change is greater than or less than 1 order of magnitude. Reword for clarity.
L14: “…consisted of this system installed at nine sites…” – awkward. Reword, please.
L22: “respectively” – unnecessary.
L50: “sucked” – colloquial language. Try “pulled” or another word.
Citation: https://doi.org/10.5194/amt-2023-246-RC2
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