Retrieval of Atmospheric CFC-11 and CFC-12 from High-resolution FTIR Observations at Hefei and Comparisons with Satellite Data

Zeng, Xiangyu; Wang, Wei; Liu, Cheng; Shan, Changgong; Xie, Yu; Wu, Peng; Zhu, Qianqian; Polyakov, Alexander

doi:https://doi.org/10.5194/egusphere-2022-678

Preprints

https://doi.org/10.5194/egusphere-2022-678

Preprints

04 Aug 2022

| 04 Aug 2022

Retrieval of Atmospheric CFC-11 and CFC-12 from High-resolution FTIR Observations at Hefei and Comparisons with Satellite Data

Xiangyu Zeng, Wei Wang, Cheng Liu, Changgong Shan, Yu Xie, Peng Wu, Qianqian Zhu, and Alexander Polyakov

Abstract. Synthetic halogenated organic chlorofluorocarbons (CFCs) play an important role in stratospheric ozone depletion, and contribute signiﬁcantly to the greenhouse effect. In this work, the mid-infrared solar spectra measured by ground-based high-resolution Fourier transform infrared spectroscopy (FTIR) were used to retrieve atmospheric CFC-11 (CCl₃F) and CFC-12 (CCl₂F₂) at Hefei, China. We implemented a new retrieval strategy, and analyzed the retrieval errors. The CFC-11 columns observed from January 2017 to December 2020 and CFC-12 columns from September 2015 to December 2020 show a similar annual decreasing trend and seasonal cycle, with an annual rate of (−0.47 % ± 0.16) % yr⁻¹ and (−0.79 ± 0.31) % yr⁻¹, respectively. CFC-11 total columns were higher in summer, and CFC-12 total columns were higher in summer and autumn. Both of CFC-11 and CFC-12 total columns reached the lowest in spring. The annual decreasing rate of near-surface concentration is (−0.60 ± 0.26) % y⁻¹ for CFC-11, and (−0.81 ± 0.25) % y⁻¹ for CFC-12. So the decline rate of CFC-11 is significantly lower than that of CFC-12. Further, FTIR data were compared with the ACE-FTS satellite data, WACCM (Whole Atmosphere Community Climate Model) data and the data from other NDACC (Network for the Detection of Atmospheric Composition Change) station. The mean relative difference between the vertical profiles observed by FTIR and ACE-FTS is (−5.6 ± 3.3) % and (4.8 ± 0.9) % for CFC-11 and CFC-12 for altitude from 5.5 to 17.5 km, respectively. The results demonstrate our FTIR data agree relatively well with the ACE-FTS satellite data. The annual decreasing rate of CFC-11 measured from ACE-FTS and calculated by WACCM are (−1.15 ± 0.22) % and (−1.68 ± 0.18) %, respectively. The interannual decreasing rates of atmospheric CFC-11 obtained from ACE-FTS and WACCM data are higher than that from FTIR observations. Also, the annual decreasing rate of CFC-12 from ACE-FTS and WACCM is (–0.85 ± 0.15) % and (–0.81 ± 0.05) %, respectively, close to the corresponding values from the FTIR measurements. Further, the total columns of CFC-11 observed at the Hefei site are very close to those at St. Petersburg station, with a mean difference of 3.63 × 10¹² molec·cm^-2, while the total columns of CFC-12 are 1.69 × 10¹⁴ molec·cm^-2, slightly higher than those at St. Petersburg station.

Received: 26 Jul 2022 – Discussion started: 04 Aug 2022

Download & links

Preprint (PDF, 1796 KB)

Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
Preprint (1796 KB)

Download & links

The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

Journal article(s) based on this preprint

22 Nov 2022

Retrieval of atmospheric CFC-11 and CFC-12 from high-resolution FTIR observations at Hefei and comparisons with other independent datasets

Xiangyu Zeng, Wei Wang, Cheng Liu, Changgong Shan, Yu Xie, Peng Wu, Qianqian Zhu, Minqiang Zhou, Martine De Mazière, Emmanuel Mahieu, Irene Pardo Cantos, Jamal Makkor, and Alexander Polyakov

Atmos. Meas. Tech., 15, 6739–6754, https://doi.org/10.5194/amt-15-6739-2022,https://doi.org/10.5194/amt-15-6739-2022, 2022

Short summary

Xiangyu Zeng et al.

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2022-678', Anonymous Referee #1, 29 Aug 2022

General comments

The manuscript “Retrieval of Atmospheric CFC-11 and CFC-12 from High resolution FTIR Observations at Hefei and Comparisons with Satellite Data” by Zeng et al. describes the retrieval of atmospheric ozone depleting chlorofluorocarbons CFC-11 and CFC-12 from solar absorption spectra measured using a high resolution Fourier Transform infrared spectrometer at Hefei, China, and examines the resulting, multi-year timeseries, and compares it to satellite measurements and concentrations prognosed by a model.

The retrieval scheme builds on work carried out at the St Petersburg NDACC-IRWG (Network for the Detection of Atmospheric Composition Change – InfraRed Working Group) station. The novelty here is the retrieval of these species from the spectra measured at Hefei, representing one of the few measurements of its kind in China. The long-term monitoring of key atmospheric constituents such as these and the understanding of their evolution within a global context is important and the publication of these results should be encouraged.

The manuscript is generally well structured and written but would benefit from further development of several sections to provide more of a thorough description of some of the important concepts as described below under specific comments.

Subject to the incorporation of these changes and the corrections suggested under technical corrections below, publication of this manuscript is recommended.

Specific comments

The manuscript presents retrievals of CFC-11 between January 2017 and December 2020 and CFC-12 between September 2015 and December 2020. The authors should explain why the two observing periods are different.

The abstract states that comparisons are made to other NDACC stations. It should be made clearer whether Hefei is or is not an NDACC-IRWG station. Also make it clear that the comparison is with NDACC-IRWG stations, not other NDACC observations.

The abstract also introduces the comparison to ACE-FTS satellite measurements and WACCMv6 model and presents quotative results of the comparison. It would provide important context here to define the spatial extent of the satellite/model data used i.e., global or coincident with Hefei.

In its current form, Section 2.2. does not provide sufficient information to allow the reader to reproduce the author’s results. For example, how was the pseudo line list produced and how can it be obtained? Also, Table 1 lists zshift and beam as background retrieval parameters for CFC-11, but these are not described or explained in the text.

In Section 2.3, How is the measurement error used to refine the regularisation strength determined? This may be covered in the cited article, but it is probably important enough to discuss within the manuscript.

It is unusual to see a column averaging kernel that contains as much structure and sharp transitions as the ones plotted in panel c of Figs 1 and 2. It would be good to include the layer averaging kernels, or a subset thereof, to see how this has come about.

Not all sources of error listed in Table 3 are mentioned in the text of Section 2.5. These sources and the associated assumptions concerning their magnitude should be discussed.

At P10L215, the sentence "The time series are fitted by a lowpass filtered fast Fourier transform (FFT) technology and a linear fitting to simulate the seasonal and interannual variation of CFC-11 and CFC-12 (Thoning et al., 1989)" may not accurately describe the timeseries decomposition process. It appears from Fig. 3 that a linear trend and multi-harmonic seasonal cycle have been fitted. The authors should consider revising this statement and state the number of harmonic terms that have been used to fit the seasonality.

In section 3.1 two retrieval products are discussed: the total columns and near surface concentrations. These products should be introduced prior to their discussion. It would be helpful to do this as part of a discussion of the information content of the retrieval process possibly as its own sub-section in section 2. The error analysis should also state how the retrieval errors propagate into these two products.

In the conclusions, the statement that "ACE-FTS and WACCM data clearly overestimated the decreasing rate,.." doesn't appear to be justified in the context of the evidence presented given the spatio-temporal differences between the measurements. This should be revised.

It would be good to see some stronger conclusions drawn, for example placing the findings of this work in the context of previously published findings and a comment on the differing types of emissions that lead to the difference between Hefei and St. Petersburg.

Are there any plans to continue or update the dataset? It would be good to include this information.

Technical corrections

P1L25 in abstract remove % sign after -0.47 to be consistent with the rest of the abstract, elsewhere when expressing a value and uncertainty the parentheses are unnecessary.

P2L56 citation should be Montzka et al., 2021.

P2L57 It might help the reader to know the type of atmospheric observations, in-situ or remote sensing.

P2L60 insert a space between CFC-11 and and.

P2L60 check the units are correct for the emission rates (Gg not kg?) and use yr^-1 to be consistent with the rest of the manuscript

P2L64 "Study of the temporal-spatial distribution and variations of CFCs in the atmosphere is of great significance to reduce stratospheric ozone depletion and greenhouse gas emissions." The study itself does not reduce the emissions, but it does improve understanding and suggest what needs to be done to facilitate reductions. Consider revising this sentence.

P3L80 this sentence may need a change of emphasis, in that HIRDLS, ILAS etc are not mainly used for CFC measurements, but they may be the main instruments used for this type of measurement.

P3L92 Throughout the manuscript there are sentences like this where the un-parenthesised citation is used at the beginning of the sentence with the parenthesised version at the end. It is unnecessary to include the citation twice in one sentence.

P5L141 remove the word time and replace with either iteration or step, i.e., “iteration index i” or “step i”.

P9L207 Suggest starting the sentence introducing the error values from the Polyakov study with "At the St Petersburg site..." or similar, to avoid a little confusion.

P9L209 Last sentence should be elaborated

P9 Table 3, This table is a little hard to read, consider more use of horizontal lines to separate items

P10L219 Throughout section 3.1 trends are given the units %/yr^-1 when they should be %yr^-1 (to be consistent with the rest of the manuscript) or %/yr

P10L225 Insert a space between -0.49 and %

Figures 3, 4 and 8: Consider using the same x axis scale for both timeseries to allow the reader to see the seasonal cycles aligned.

P13L254 In this discussion, are the seasonal amplitude and variability not the same? I.e., the amplitude in units of molecules per unit area or mixing ratio is also expressed as a percentage of annual mean or detrended mean?

P13L256 consider starting a new paragraph to discuss near surface concentration seasonality

P13L271 CFC-11?

P15L304 It should be explained why the columns of dry-air mole fractions are being compared and not molecules per unit area that were discussed previously. Also, it is not apparent in the text how the dry-air column has been derived.

P16L333 Are global WACCM data used or the same spatial criteria as the ACE-FTS? This should be made clear in the text.

P17 Fig. 8. Check the y-axis label of panel (a)

P17L361 It would make life easier for the reader if the column differences were expressed as a percentage.

P18 Fig. 9. Include the parameters of the linear regression

P18L380 The meaning of the last sentence is unclear. Perhaps: "This is one of the few..."

P19L404 Start a new paragraph for the St. Petersburg comparison.

P19L407 It would be good to go on to describe the emission source differences

References: There are some inconsistencies in formatting of the references, e.g. the use of capitalised journal and article titles, which should be rectified.

Citation: https://doi.org/10.5194/egusphere-2022-678-RC1
- AC1: 'Reply on RC1', Xiangyu Zeng, 18 Oct 2022
  
  Please find our reply in the supplement.
  
  Citation: https://doi.org/10.5194/egusphere-2022-678-AC1
RC2:
'Comment on egusphere-2022-678', Anonymous Referee #2, 29 Aug 2022
General comments:

The authors used Tikhonov regularization to retrieve CFC11 and CFC 12 at Hefei station, China. They looked at the trend and seasonal cycle during 3 years for CFC 11 and 5 years for CFC 12. Although they mention new retrieval method in the abstract, they followed a very well know method of Tikhonov regularization. They also compared trends and the averaged retrieved profile shape with the ACE satellite as well as one NDACC station in St. Petersburg, Russia. Overall, there is a great value in creating independent ground data. However, the presentation and discussion of results needs to be improved. The information content of the retrieved data is only adequate for retrieving the total column for CFC 11 and maybe two column layers for CFC 12. But authors investigated the surface level value which is not meaningful information from the retrieval. They discussed that optimal estimation method (OEM) is not able to truly retrieve CFC data from FTIR sensors which is not correct. Authors wrote in a way that there is no way to constrain the results in OEM, however using more complex covariance matrix this is very possible. Also, I think the manuscript would benefit from adding a few more NDACC station rather one NDACC station to have a more meaningful comparison and discussion of the results. I would recommend a major correction is needed before publication of this manuscript. More detail comments are provided below.

Specific comments:

The general motivation of this work needs to be improved. Retrieval data has one DOF for CFC 11 and two DOF for CFC12 which means they can provide information about total column (assuming that the sensitivity is up to dominant portion of the CFC profile) and two partial columns for CFC12 (using average kernels they should identify the most meaningful layers that can be retrieved). The current motivation assumes that FTIR retrieval can retrieval a detailed profile from surface to stratosphere, which is not possible based on the sensitivity of these measurement. The motivation of the study needs to be rewritten to clarify how the retrieved information adds to the satellite and in situ measurement and the value of data based on true sensitivity of the data.

Retrieving CFC profile is named as of the main objective of the manuscript. However, considering the low DOF it seems one total column (or two partial columns for CFC12) can be retrieved.

It is not clear why only 3 years of data is used for CFC 11 while 5 years for CFC 12. Authors should clarify this inconsistency in the periods and elaborate on how that could affect their conclusions. Moreover, trend analysis with only 3 and even five years of data is not a robust conclusion. If authors include more NDACC stations and use longer period for available data, then they could discuss the overall trend of all included stations, and how a few years of Hefei compares with recent years of other stations.

Page 5, ln 146 to ln150. Authors mentioned that they did not use the optical estimation method because of the high fluctuation in their results. However, they can use more constrains in OEM by incorporating more a complex covariance matrix in the retrieval to achieve a more restricted result. It is fine to use the Tikhonov regularization, but the discussion of paper is in a way that OEM is limited which is not true in there are many ways to constrain your results to prevent high fluctuations. You can find some good examples of more complex covariance matrix to constrain the OEM results in these papers and many more online

Shams, Shima Bahramvash, Von P. Walden, James W. Hannigan, and David D. Turner. "Retrievals of Ozone in the Troposphere an Lower Stratosphere Using FTIR Observations over Greenland." (2022).

Turner, David D., and W. Greg Blumberg. "Improvements to the AERIoe thermodynamic profile retrieval algorithm." 12, no. 5 (2018): 1339-1354.

There are multiple NDACC stations, it is not clear why data is only compared with St Petersburg? It looks subjective, rather than rigorous research to find relevant and meaning full stations to compare. What is the impact of transportation and local sources. I would recommend authors use multiple station data for comparison to provide a more detail context for their comparisons. Specially that seasonal cycle has a lag time in their cycle. Having a clear discussion on different sources and sinks could cause these differences.

Page 6, ln 146 to ln156. Your methodology is very similar to Polyakov et al, 2019. Please discuss if there is any difference in the method that you used. Otherwise, I would suggest to just reference their paper as the same methodology is used and there is no need to repeating the same information. Especially that authors did not show any of these matrixes in the plots. As suggested in later comments, adding plots of DOF, average kernel, and Jacobian matrix is a nice way to characterize the sensitivity of the measurements. You can add formulation of those variables to clarify their meaning. Instead use the formulation to elaborate the errors that used in the text.

Page 12, ln 250, authors investigate surface level CFC 11 and CFC 12 in multiple plots. The measured FTIR data has 1 DOF for CFC11, thus there is not enough information to extract the near-surface value. Because a profile is incorporated as a priori, there is a profile output, however, there is no meaningful information at all levels of the profile. That’s why DOF and averaging are useful information to indicate the sensitivity of the retrieval and the vertical resolution of the results. All the investigation of surface level needs to be excluded. Instead, if the DOF and average kernel show that the measurement has adequate sensitivity to one tropospheric column, the authors can analyze that data.

Writing/presentational comment

Hefei is not part of the NDACC. (Could be a great addition though)

page 3, ln 71 to 75. It is mentioned that Yi et al, 2021 used in situ measurement. Are these measurements still active? What is the in situ temporal resolution? Again, the text implies that the retrieval can provide surface-level information, which is not correct. The text needs to be updated. Moreover, authors can include those surface measurements in their plots to compare with local measurements. On page 3, ln 78 to 88 for each satellite, please include the vertical and spatial resolution of the retrieved CFC.

Page 4, ln 108. Add solar before FTIR remote sensing site.

Page 4. Ln 108 to 117: a map of the study area can be very helpful, to illustrate the location of Hefei and other NDACC stations will be added to the study.

Page 4, ln 123. It is not clear if the authors used the monthly climatology of CFC as the prior or if they used a specific prior for each month that they retrieved. (12 different profiles for each year of each gas.) also, it would be helpful to write the WACCM spatial resolution that is used in the study. I suggest the look at How the monthly variability and cycle of seasons of the received data is similar or different from prior information that is used.

Page 8, ln 225. De Maziere et al., 2018 did not talk about the trends. Clarify which citation is related to each part of statement in this line.

Page 13, ln 260. The reasons behind the one-month phase delay need to be clarified. Look at other datasets (grand measurements in particular) and investigate if this delay is persistent there.

Page 18, ln 365. The seasonal cycle in St. Petersburg happens in fall which contradicts your explanation of the seasonal cycle in Hefei on page 13, ln 265. “In addition, more use of air conditioning and other refrigeration equipment in summer, and foams releasing more CFCs 265 at high temperatures lead to high concentrations of atmospheric CFCs." Authors need to further explain the seasonal cycle and its subjectivity to locations especially by adding more stations to the study it would be interesting to see how they vary and if that could lead to an interesting conclusion.

Fig

Add a figure of study location as well as selected NDACC data stations.

Page 7. Fig 1. The total column average kernel is not very easy to comprehend I would suggest including the DOF profile, mean averaging kernel profile, and the Jacobian matrix presentations to fully characterize the retrieval information.

fig 3, and fig 5 (must check all the plots) axis has ccl2f2 on their axis while the caption says CFC. The same acronym should be used.

Fig 5. Please include the averaged seasonal cycle from WACCM and ACE for the same period to show what information this study is bringing to the table.

Fig 6 and fig 4. the information content of these measurements is not sufficient to have meaningful surface value from the FTIR retrieval to investigate the results.

Fig 8. It is not clear what information is depicted in this plot and what research questions are targeted here. There is so much subjectivity in two-point FTIR retrieval especially when they are located this far apart. I suggest removing this figure instead create some harmonic analysis of time series based on monthly CFC data for each station (as suggested before at lead 4 sites that are distributed in a different location) and discuss how the harmonic time series are similar or different.
Citation: https://doi.org/10.5194/egusphere-2022-678-RC2
- AC2: 'Reply on RC2', Xiangyu Zeng, 18 Oct 2022
  
  Please find our reply in the supplement.
  
  Citation: https://doi.org/10.5194/egusphere-2022-678-AC2

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2022-678', Anonymous Referee #1, 29 Aug 2022

General comments

The manuscript “Retrieval of Atmospheric CFC-11 and CFC-12 from High resolution FTIR Observations at Hefei and Comparisons with Satellite Data” by Zeng et al. describes the retrieval of atmospheric ozone depleting chlorofluorocarbons CFC-11 and CFC-12 from solar absorption spectra measured using a high resolution Fourier Transform infrared spectrometer at Hefei, China, and examines the resulting, multi-year timeseries, and compares it to satellite measurements and concentrations prognosed by a model.

The retrieval scheme builds on work carried out at the St Petersburg NDACC-IRWG (Network for the Detection of Atmospheric Composition Change – InfraRed Working Group) station. The novelty here is the retrieval of these species from the spectra measured at Hefei, representing one of the few measurements of its kind in China. The long-term monitoring of key atmospheric constituents such as these and the understanding of their evolution within a global context is important and the publication of these results should be encouraged.

The manuscript is generally well structured and written but would benefit from further development of several sections to provide more of a thorough description of some of the important concepts as described below under specific comments.

Subject to the incorporation of these changes and the corrections suggested under technical corrections below, publication of this manuscript is recommended.

Specific comments

The manuscript presents retrievals of CFC-11 between January 2017 and December 2020 and CFC-12 between September 2015 and December 2020. The authors should explain why the two observing periods are different.

The abstract states that comparisons are made to other NDACC stations. It should be made clearer whether Hefei is or is not an NDACC-IRWG station. Also make it clear that the comparison is with NDACC-IRWG stations, not other NDACC observations.

The abstract also introduces the comparison to ACE-FTS satellite measurements and WACCMv6 model and presents quotative results of the comparison. It would provide important context here to define the spatial extent of the satellite/model data used i.e., global or coincident with Hefei.

In its current form, Section 2.2. does not provide sufficient information to allow the reader to reproduce the author’s results. For example, how was the pseudo line list produced and how can it be obtained? Also, Table 1 lists zshift and beam as background retrieval parameters for CFC-11, but these are not described or explained in the text.

In Section 2.3, How is the measurement error used to refine the regularisation strength determined? This may be covered in the cited article, but it is probably important enough to discuss within the manuscript.

It is unusual to see a column averaging kernel that contains as much structure and sharp transitions as the ones plotted in panel c of Figs 1 and 2. It would be good to include the layer averaging kernels, or a subset thereof, to see how this has come about.

Not all sources of error listed in Table 3 are mentioned in the text of Section 2.5. These sources and the associated assumptions concerning their magnitude should be discussed.

At P10L215, the sentence "The time series are fitted by a lowpass filtered fast Fourier transform (FFT) technology and a linear fitting to simulate the seasonal and interannual variation of CFC-11 and CFC-12 (Thoning et al., 1989)" may not accurately describe the timeseries decomposition process. It appears from Fig. 3 that a linear trend and multi-harmonic seasonal cycle have been fitted. The authors should consider revising this statement and state the number of harmonic terms that have been used to fit the seasonality.

In section 3.1 two retrieval products are discussed: the total columns and near surface concentrations. These products should be introduced prior to their discussion. It would be helpful to do this as part of a discussion of the information content of the retrieval process possibly as its own sub-section in section 2. The error analysis should also state how the retrieval errors propagate into these two products.

In the conclusions, the statement that "ACE-FTS and WACCM data clearly overestimated the decreasing rate,.." doesn't appear to be justified in the context of the evidence presented given the spatio-temporal differences between the measurements. This should be revised.

It would be good to see some stronger conclusions drawn, for example placing the findings of this work in the context of previously published findings and a comment on the differing types of emissions that lead to the difference between Hefei and St. Petersburg.

Are there any plans to continue or update the dataset? It would be good to include this information.

Technical corrections

P1L25 in abstract remove % sign after -0.47 to be consistent with the rest of the abstract, elsewhere when expressing a value and uncertainty the parentheses are unnecessary.

P2L56 citation should be Montzka et al., 2021.

P2L57 It might help the reader to know the type of atmospheric observations, in-situ or remote sensing.

P2L60 insert a space between CFC-11 and and.

P2L60 check the units are correct for the emission rates (Gg not kg?) and use yr^-1 to be consistent with the rest of the manuscript

P2L64 "Study of the temporal-spatial distribution and variations of CFCs in the atmosphere is of great significance to reduce stratospheric ozone depletion and greenhouse gas emissions." The study itself does not reduce the emissions, but it does improve understanding and suggest what needs to be done to facilitate reductions. Consider revising this sentence.

P3L80 this sentence may need a change of emphasis, in that HIRDLS, ILAS etc are not mainly used for CFC measurements, but they may be the main instruments used for this type of measurement.

P3L92 Throughout the manuscript there are sentences like this where the un-parenthesised citation is used at the beginning of the sentence with the parenthesised version at the end. It is unnecessary to include the citation twice in one sentence.

P5L141 remove the word time and replace with either iteration or step, i.e., “iteration index i” or “step i”.

P9L207 Suggest starting the sentence introducing the error values from the Polyakov study with "At the St Petersburg site..." or similar, to avoid a little confusion.

P9L209 Last sentence should be elaborated

P9 Table 3, This table is a little hard to read, consider more use of horizontal lines to separate items

P10L219 Throughout section 3.1 trends are given the units %/yr^-1 when they should be %yr^-1 (to be consistent with the rest of the manuscript) or %/yr

P10L225 Insert a space between -0.49 and %

Figures 3, 4 and 8: Consider using the same x axis scale for both timeseries to allow the reader to see the seasonal cycles aligned.

P13L254 In this discussion, are the seasonal amplitude and variability not the same? I.e., the amplitude in units of molecules per unit area or mixing ratio is also expressed as a percentage of annual mean or detrended mean?

P13L256 consider starting a new paragraph to discuss near surface concentration seasonality

P13L271 CFC-11?

P15L304 It should be explained why the columns of dry-air mole fractions are being compared and not molecules per unit area that were discussed previously. Also, it is not apparent in the text how the dry-air column has been derived.

P16L333 Are global WACCM data used or the same spatial criteria as the ACE-FTS? This should be made clear in the text.

P17 Fig. 8. Check the y-axis label of panel (a)

P17L361 It would make life easier for the reader if the column differences were expressed as a percentage.

P18 Fig. 9. Include the parameters of the linear regression

P18L380 The meaning of the last sentence is unclear. Perhaps: "This is one of the few..."

P19L404 Start a new paragraph for the St. Petersburg comparison.

P19L407 It would be good to go on to describe the emission source differences

References: There are some inconsistencies in formatting of the references, e.g. the use of capitalised journal and article titles, which should be rectified.

Citation: https://doi.org/10.5194/egusphere-2022-678-RC1
- AC1: 'Reply on RC1', Xiangyu Zeng, 18 Oct 2022
  
  Please find our reply in the supplement.
  
  Citation: https://doi.org/10.5194/egusphere-2022-678-AC1
RC2:
'Comment on egusphere-2022-678', Anonymous Referee #2, 29 Aug 2022
General comments:

The authors used Tikhonov regularization to retrieve CFC11 and CFC 12 at Hefei station, China. They looked at the trend and seasonal cycle during 3 years for CFC 11 and 5 years for CFC 12. Although they mention new retrieval method in the abstract, they followed a very well know method of Tikhonov regularization. They also compared trends and the averaged retrieved profile shape with the ACE satellite as well as one NDACC station in St. Petersburg, Russia. Overall, there is a great value in creating independent ground data. However, the presentation and discussion of results needs to be improved. The information content of the retrieved data is only adequate for retrieving the total column for CFC 11 and maybe two column layers for CFC 12. But authors investigated the surface level value which is not meaningful information from the retrieval. They discussed that optimal estimation method (OEM) is not able to truly retrieve CFC data from FTIR sensors which is not correct. Authors wrote in a way that there is no way to constrain the results in OEM, however using more complex covariance matrix this is very possible. Also, I think the manuscript would benefit from adding a few more NDACC station rather one NDACC station to have a more meaningful comparison and discussion of the results. I would recommend a major correction is needed before publication of this manuscript. More detail comments are provided below.

Specific comments:

The general motivation of this work needs to be improved. Retrieval data has one DOF for CFC 11 and two DOF for CFC12 which means they can provide information about total column (assuming that the sensitivity is up to dominant portion of the CFC profile) and two partial columns for CFC12 (using average kernels they should identify the most meaningful layers that can be retrieved). The current motivation assumes that FTIR retrieval can retrieval a detailed profile from surface to stratosphere, which is not possible based on the sensitivity of these measurement. The motivation of the study needs to be rewritten to clarify how the retrieved information adds to the satellite and in situ measurement and the value of data based on true sensitivity of the data.

Retrieving CFC profile is named as of the main objective of the manuscript. However, considering the low DOF it seems one total column (or two partial columns for CFC12) can be retrieved.

It is not clear why only 3 years of data is used for CFC 11 while 5 years for CFC 12. Authors should clarify this inconsistency in the periods and elaborate on how that could affect their conclusions. Moreover, trend analysis with only 3 and even five years of data is not a robust conclusion. If authors include more NDACC stations and use longer period for available data, then they could discuss the overall trend of all included stations, and how a few years of Hefei compares with recent years of other stations.

Page 5, ln 146 to ln150. Authors mentioned that they did not use the optical estimation method because of the high fluctuation in their results. However, they can use more constrains in OEM by incorporating more a complex covariance matrix in the retrieval to achieve a more restricted result. It is fine to use the Tikhonov regularization, but the discussion of paper is in a way that OEM is limited which is not true in there are many ways to constrain your results to prevent high fluctuations. You can find some good examples of more complex covariance matrix to constrain the OEM results in these papers and many more online

Shams, Shima Bahramvash, Von P. Walden, James W. Hannigan, and David D. Turner. "Retrievals of Ozone in the Troposphere an Lower Stratosphere Using FTIR Observations over Greenland." (2022).

Turner, David D., and W. Greg Blumberg. "Improvements to the AERIoe thermodynamic profile retrieval algorithm." 12, no. 5 (2018): 1339-1354.

There are multiple NDACC stations, it is not clear why data is only compared with St Petersburg? It looks subjective, rather than rigorous research to find relevant and meaning full stations to compare. What is the impact of transportation and local sources. I would recommend authors use multiple station data for comparison to provide a more detail context for their comparisons. Specially that seasonal cycle has a lag time in their cycle. Having a clear discussion on different sources and sinks could cause these differences.

Page 6, ln 146 to ln156. Your methodology is very similar to Polyakov et al, 2019. Please discuss if there is any difference in the method that you used. Otherwise, I would suggest to just reference their paper as the same methodology is used and there is no need to repeating the same information. Especially that authors did not show any of these matrixes in the plots. As suggested in later comments, adding plots of DOF, average kernel, and Jacobian matrix is a nice way to characterize the sensitivity of the measurements. You can add formulation of those variables to clarify their meaning. Instead use the formulation to elaborate the errors that used in the text.

Page 12, ln 250, authors investigate surface level CFC 11 and CFC 12 in multiple plots. The measured FTIR data has 1 DOF for CFC11, thus there is not enough information to extract the near-surface value. Because a profile is incorporated as a priori, there is a profile output, however, there is no meaningful information at all levels of the profile. That’s why DOF and averaging are useful information to indicate the sensitivity of the retrieval and the vertical resolution of the results. All the investigation of surface level needs to be excluded. Instead, if the DOF and average kernel show that the measurement has adequate sensitivity to one tropospheric column, the authors can analyze that data.

Writing/presentational comment

Hefei is not part of the NDACC. (Could be a great addition though)

page 3, ln 71 to 75. It is mentioned that Yi et al, 2021 used in situ measurement. Are these measurements still active? What is the in situ temporal resolution? Again, the text implies that the retrieval can provide surface-level information, which is not correct. The text needs to be updated. Moreover, authors can include those surface measurements in their plots to compare with local measurements. On page 3, ln 78 to 88 for each satellite, please include the vertical and spatial resolution of the retrieved CFC.

Page 4, ln 108. Add solar before FTIR remote sensing site.

Page 4. Ln 108 to 117: a map of the study area can be very helpful, to illustrate the location of Hefei and other NDACC stations will be added to the study.

Page 4, ln 123. It is not clear if the authors used the monthly climatology of CFC as the prior or if they used a specific prior for each month that they retrieved. (12 different profiles for each year of each gas.) also, it would be helpful to write the WACCM spatial resolution that is used in the study. I suggest the look at How the monthly variability and cycle of seasons of the received data is similar or different from prior information that is used.

Page 8, ln 225. De Maziere et al., 2018 did not talk about the trends. Clarify which citation is related to each part of statement in this line.

Page 13, ln 260. The reasons behind the one-month phase delay need to be clarified. Look at other datasets (grand measurements in particular) and investigate if this delay is persistent there.

Page 18, ln 365. The seasonal cycle in St. Petersburg happens in fall which contradicts your explanation of the seasonal cycle in Hefei on page 13, ln 265. “In addition, more use of air conditioning and other refrigeration equipment in summer, and foams releasing more CFCs 265 at high temperatures lead to high concentrations of atmospheric CFCs." Authors need to further explain the seasonal cycle and its subjectivity to locations especially by adding more stations to the study it would be interesting to see how they vary and if that could lead to an interesting conclusion.

Fig

Add a figure of study location as well as selected NDACC data stations.

Page 7. Fig 1. The total column average kernel is not very easy to comprehend I would suggest including the DOF profile, mean averaging kernel profile, and the Jacobian matrix presentations to fully characterize the retrieval information.

fig 3, and fig 5 (must check all the plots) axis has ccl2f2 on their axis while the caption says CFC. The same acronym should be used.

Fig 5. Please include the averaged seasonal cycle from WACCM and ACE for the same period to show what information this study is bringing to the table.

Fig 6 and fig 4. the information content of these measurements is not sufficient to have meaningful surface value from the FTIR retrieval to investigate the results.

Fig 8. It is not clear what information is depicted in this plot and what research questions are targeted here. There is so much subjectivity in two-point FTIR retrieval especially when they are located this far apart. I suggest removing this figure instead create some harmonic analysis of time series based on monthly CFC data for each station (as suggested before at lead 4 sites that are distributed in a different location) and discuss how the harmonic time series are similar or different.
Citation: https://doi.org/10.5194/egusphere-2022-678-RC2
- AC2: 'Reply on RC2', Xiangyu Zeng, 18 Oct 2022
  
  Please find our reply in the supplement.
  
  Citation: https://doi.org/10.5194/egusphere-2022-678-AC2

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

AR by Xiangyu Zeng on behalf of the Authors (18 Oct 2022) Author's response Author's tracked changes Manuscript

ED: Publish as is (21 Oct 2022) by Sandip Dhomse

AR by Xiangyu Zeng on behalf of the Authors (25 Oct 2022)

Journal article(s) based on this preprint

22 Nov 2022

Retrieval of atmospheric CFC-11 and CFC-12 from high-resolution FTIR observations at Hefei and comparisons with other independent datasets

Xiangyu Zeng, Wei Wang, Cheng Liu, Changgong Shan, Yu Xie, Peng Wu, Qianqian Zhu, Minqiang Zhou, Martine De Mazière, Emmanuel Mahieu, Irene Pardo Cantos, Jamal Makkor, and Alexander Polyakov

Atmos. Meas. Tech., 15, 6739–6754, https://doi.org/10.5194/amt-15-6739-2022,https://doi.org/10.5194/amt-15-6739-2022, 2022

Short summary

Xiangyu Zeng et al.

Viewed

Total article views: 348 (including HTML, PDF, and XML)

HTML	PDF	XML	Total	BibTeX	EndNote
251	83	14	348	2	3

HTML: 251
PDF: 83
XML: 14
Total: 348
BibTeX: 2
EndNote: 3

Views and downloads (calculated since 04 Aug 2022)

Month	HTML	PDF	XML	Total
Aug 2022	152	50	7	209
Sep 2022	37	13	2	52
Oct 2022	49	16	5	70
Nov 2022	13	4	0	17
Dec 2022	0
Jan 2023	0
Feb 2023	0
Mar 2023	0
Apr 2023	0

Cumulative views and downloads (calculated since 04 Aug 2022)

Month	HTML	PDF	XML	Total
Aug 2022	152	50	7	209
Sep 2022	37	13	2	52
Oct 2022	49	16	5	70
Nov 2022	13	4	0	17
Dec 2022	0
Jan 2023	0
Feb 2023	0
Mar 2023	0
Apr 2023	0

Viewed (geographical distribution)

Total article views: 336 (including HTML, PDF, and XML) Thereof 336 with geography defined and 0 with unknown origin.

Country	#	Views	%

Latest update: 30 Apr 2023

Download

The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

Preprint (1796 KB)
Metadata XML

Short summary

CFC-11 and CFC-12, which are classified as ozone depleting substances, also have high global warming potentials. This paper describes obtaining the CFC-11 and CFC-12 vertical profiles and total columns from the solar spectra based on ground-based Fourier transform infrared spectroscopy at Hefei, China. The seasonal variation and annual trend of the two gases are analyzed, and then the data are compared with other independent datasets.


Total:	0
HTML:	0
PDF:	0
XML:	0