Carbon reduction requires attention to the contribution of natural gas use: Combustion and leakage

Chen, Haoyuan; Song, Tao; Chen, Xiaodong; Wang, Yinghong; Cheng, Mengtian; Wang, Kai; Liu, Fuxin; Liu, Baoxian; Tang, Guiqian; Wang, Yuesi

doi:https://doi.org/10.5194/egusphere-2024-3931

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https://doi.org/10.5194/egusphere-2024-3931

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30 Jan 2025

| 30 Jan 2025

Carbon reduction requires attention to the contribution of natural gas use: Combustion and leakage

Haoyuan Chen, Tao Song, Xiaodong Chen, Yinghong Wang, Mengtian Cheng, Kai Wang, Fuxin Liu, Baoxian Liu, Guiqian Tang, and Yuesi Wang

Abstract. Natural gas will continue to replace coal in the process of global energy structure reform, but its leakage potential can delay the realization of global carbon neutrality. To quantify its impact, we established a carbon dioxide (CO₂) and methane (CH₄) emission flux detection platform on the 220-m platform of the Institute of Atmospheric Physics, Chinese Academy of Sciences, located in northwestern Beijing. The observation results indicated that the daily mean CO₂ and CH₄ fluxes were 12.21±1.75 µmol·m⁻²·s⁻¹ and 95.54±18.92 nmol·m^-2·s^-1, respectively. The daily variations in the emissions of these two gases were highly consistent, and their fluxes were significantly correlated with natural gas consumption, indicating that natural gas has become a common source of CH₄ and CO₂. Vehicle-based identification demonstrated that methane can escape at the storage and use stages of natural gas. Based on natural gas consumption data, the upper limit of the calculated natural gas leakage rate in Beijing reached 1.12±0.22 %, indicating that the contribution of CH₄ to climate change could reach 23 % of that of CO₂ on a 20-year scale. Natural gas leakage was estimated to delay the time for China to achieve carbon neutrality by almost three years.

Received: 12 Dec 2024 – Discussion started: 30 Jan 2025

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Haoyuan Chen, Tao Song, Xiaodong Chen, Yinghong Wang, Mengtian Cheng, Kai Wang, Fuxin Liu, Baoxian Liu, Guiqian Tang, and Yuesi Wang

Status: final response (author comments only)

RC1:
'Comment on egusphere-2024-3931', Anonymous Referee #1, 18 May 2025
Review of “Carbon reduction requires attention to the contribution of natural gas use: Combustion and leakage”.

The manuscript presents the results of a 73 day long observational campaign of methane (CH4) and carbon dioxide (CO2) fluxes made on a tall tower in Beijing. In addition, surface mobile measurements over different time periods were also made to address some specific geospatial regions within the domain covered by the flux tower. The methods to prepare and analyze the data are very standard. The findings include that the emissions of CH4 are likely anthropogenic in nature due to their similarity in time and direction to those of CO2. Comparisons were made with other previous campaigns in earlier years. They then draw some conclusions about the changes in CO2 and CH4 over time and relate these to various different policies.

The authors clearly have demonstrated that their basic measurements of flux are reasonable and representative. There should be no doubt about this point, and hence the fundamental data underlying the project looks sound. However, there are many issues. One such issue about the data is that the individual half-hour averaged flux time series over the entire time studied is not available anywhere. However, the details in the figures of the entire-campaign averaged hour-by-hour data clearly demonstrates that the hour-to-hour and day-to-day variability are both important. They also demonstrate that there are issues likely occuring at the half-hour scale, but they cannot be analyzed or discussed based on the current figures and data provided. Therefore, analyzing the data or evaluating analysis done cannot be validates, and the potential strong impacts of these 30-minute scale variations cannot be analyzed or presented. This weakens the paper.

Furthermore, there are many technical issues with the paper, as outlined in detail below. Perhaps it is just writing style or many small and unintentional mistakes. However, the net of all of these small mistakes and mis-communications in tandem lead to serious doubts as to the overall findings of the work.

Another issue is that the subsequent analysis of the data does not present any new perspectives or science. Advances in analysis by the community over the past few years should be followed. The base 30-minute and vehicle-obtained data both need to be processed at higher temporal and spatial frequency, not a mere “summer” comparison. More rigorous techniques than simple linear correlation between concentration enhancements and single variables (the other species concentration enhancement or temperature) also need to be performed. Uncertainty in the models, in the data, and in the assumptions need to be considered. Analysis of variance and of multi-species need to be performed in tandem. Specific details are presented in more detailed comments below.

Additionally, the use of background subtraction may lead to substantial errors. First, there are the issues of the observational uncertainty in the background value. Second, there are more modern papers demonstrating that background subtraction is not needed. Third, in those cases in which long-range transport is present, background subtraction is flawed in connection with the flux tower computational assumptions. This is because the equations underlying the flux calculation assume that the upper air is clean and that the emissions come from the local surface. Recent papers have demonstrated that there is in fact long-range transport into Beijing from upwind industrial sources in central China, and therefore any such events would need to be excluded from the data before analysis is performed. I raise this point since in analysis done both by my group as well as others, the time period studied in this work contains at least one such long-range transport event. Analysis of the 30-minute time series may help identify this event, and possibly others as well. In addition, this paper introduces the use of a 5-minute window to identify background values. However, given the size of the domain, this is not consistent. The observed wind speed will take more than 5 minutes to go from the edge of the domain to the tower location, and hence the length of the averaging period must be at least this long. This will change from day-to-day and hour-to-hour. The time likely needs to be longer, to account for any atmospheric recycling occurring within the domain.

For all of these reasons, I recommend that the work undergo major revisions before it be considered further. However, due to the strong people on the team, I do believe that with a considerable amount of hard work and time, that they can raise the level of the paper to such that it will make a good ultimate contribution to ACP. I am happy to continue to work with any future revisions which are brought forward.

Specific Issues:
Line 101: Why do you use a 219ppb standard for CH4? Would the results change if a more reasonable 1900ppb or 2000ppb standard were used?

Lines 116-118: There are many studies which apply mean and standard deviation or even more complex analysis such as EOF, SVD, etc. You need to describe in more detail things such as: how many standard deviations are used, is the data normally distributed, lognormally distributed, etc. Even using the more advanced techniques you need to demonstrate the variance explained or reduced. The current work is incomplete.

Lines 134-136: This raises many issues. I will outline three of them. First, can you please show us a map of the footprint area, I cannot seem to find it anywhere. Second, it takes wind more than 5 minutes to cross the urban area of Beijing, so why do you use a 5-minute averaging time period to compute background CH4 in this case? Given the very large number of sources just upwind from your area (including oil production in nearby Hebei and Shandong), how do you work to exclude long-range transport from outside of your footprint area?

Given that the size distribution of particulate matter in Beijing (as published by others in your same institute, aerosols have a very large number in the sub-micron range) how do you filter the particles without altering the air flow? Or do you not filter these 100nm sized particles? If not filtered, how would they impact the observations?

Lines 179-182 are very hard to follow. Do you mean you are comparing a sort of summer-average from this work with summer-averaged from previous works which also used tall towers, but towers with different heights? Even if my understanding is correct, you need to re-word this sentence.

Significant digits. Can you really trust the wind and concentration measurements as well as the analysis technique to 4 digits of precision?

Lines 191-192: This is a clear mistake. The paper was submitted in 2024. How can you not know if the 30ug/m3 by 2022 was achieved or not. Also, why is this written in future tense?

Lines 205, 206, and 213: I do not agree with your statement based on the data presented in Figure 1. It looks like CH4 emissions start to rise at 5am, rise with a different rate than CO2 emissions, stay much flatter, and start to decrease at 5pm. Thus, there is a shift between these two which is not similar. However, the point is that if the entire time series were analyzed, we could be even clearer. You have 30-minute data, so please re-do this analysis more carefully and precisely.

Lines 215-216: How do you explain negative CH4 fluxes? Why are both negative and positive fluxes considered in tandem with each other? Isn’t one a source and the other a sink? A maximum R of 0.82 means that it accounts for 67% of the variability, which has some amount of correlation power. However, it is not as strong as the authors make it out to be. Introducing more advanced comparisons between the emissions of CH4 and CO2, concentrations of CH4 and CO2, Temperature, incoming surface solar radiation, and other variables in tandem will make the analysis stronger. Using EOF or even SVD to analyze the time series in tandem will also make the analysis stronger. This result looks like a reasonable start, but an insufficient analysis to support the remainder of the paper.

Lines 246-247: I cannot access the document.

Lines 247-249: There is a distance that the wind must travel from the source to the observation point, and what time lag would this produce between the production time and the observed time? Please demonstrate using the 30-minute flux time data and the day-by-day electricity data.

Lines 255-257: This is not logical. There was a paper published in Communications Earth and Environment in 2025 which showed that CO emissions from central China are much higher in November-January due to increases in production to meet the end of the year production cycle, as well as possibly due to more small and remote emissions (possibly heating or small business energy needs in winter). This CO would then be transported to Beijing in part and chemically decay into CO2 as it is being transported. You need to consider these findings before you make such statements.

Lines 264-265: This point is raised earlier. Since it takes more than 5 minutes for the wind to flow from the edges of the footprint to the flux tower observation point, why do you use a 5-minute window? Furthermore, why do you choose the 5^th percentile? What happens if you choose the minimum value? Or the 1^st percentile? Or the 10^th percentile? We know what the large-scale average CH4 measurements are from the long-term base station in Shangdiaizi, why not use their value? You need to carefully consider the error introduced by such a sweeping set of assumptions. Please quantify how a change in the calculation of the background changes the results? Please quantify how the observational uncertainty could lead to the value of the 5^th percentile background value to change? How would this uncertainty propagate into the calculation of the enhancement, when it is applied at both the lower and upper ends simultaneously?

Of course, there are newer techniques such as published in ACP in 2025 this year based on a study of CH4 in central China which completely does away with background subtraction and enhancement calculation. You could consider this new approach as well and completely avoid the issues of enhancement and background subtraction. Or you can work hard to justify why your background subtraction is valid and how it contributes to overall uncertainties in the conclusions.

Lines 281-283: This is an interesting finding. However, the scaling of the plots and the lack of data make it impossible to validate. I am happy to support the authors to improve upon this, but at the present time have insufficient data or readability to do so.

Figure 5 is scaled differently on each plot. It makes comparison of the already very small data points nearly impossible.

Lines 21-22: Natural gas contains a very large amount of CH4, but does not contain CO2. You need to explain how these could be co-emitted? If you mean that more natural gas being used for combustion produces more CO2, and that it also leads to more leaks, than this could be one such way to analyze this. But the way it is currently written raises questions about the rest of the paper since it is in the abstract.

Line 32: the second sentence requires a reference.

Line 95: please do not use so many abbreviations.

Again, in specific refer to line 135: “the flux source area covers most of the urban area of Beijing and reflects the average emission characteristics at the regional scale.” Could the author add a figure to describe the space covered.

Again, in specific refer to line 110, the observation period of the article is between June 11 and September 7, 2022. Is the data from this time period really sufficient to reflect the characteristics of emissions of CH4 and CO2 over this region? If so, provide evidence to support this.

Again, in specific line 162: “Before the particulate matter entered the instrument, it was removed using a filter head.” What are the components of this filter head? Can it filter without disturbing the airflow? I have seen a patent and a paper describing such a material in China, but it can only filter down to about 300nm particles. Would this possibly have an impact, especially since your claim is that combustion is the source of the CH4 and the CO2 and that there is a large amount of small BC particles also produced by such combustion? There was a paper in the Chinese-Language GuangXueXueBao journal specifically raising issue with this topic.

Lines 180-182: Please provide a map, which will make it much easier for the audience to follow.

Section 3.2: The results from Figure 6 do not demonstrate that the concentration enhancements are well correlated, especially given that positive and negative enhancements are needed to be used in tandem for the analysis. How can someone conclude that the fluxes are linearly correlated? Especially so when the 30-minute data is not presented directly.

Line 272: What are the units of E-CH4 and E-CO2? How are they computed?

Usually, discussion comes after the results are fully presented. However, line 234 is “DISCUSSION”, while the later line 235 is “3.3 Driver of the homology between CO2 and CH4”. Please carefully considering re-structuring or change around header titles.

Why is there no summary or conclusion section?

In the supporting information section, the entire content is a long sentence, making it difficult to understand. Furthermore, I cannot find the underlying datasets and therefore it makes it very difficult for me to properly review.
Citation: https://doi.org/10.5194/egusphere-2024-3931-RC1
- AC1: 'Reply on RC1', Guiqian Tang, 23 Jul 2025
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2024-3931/egusphere-2024-3931-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2024-3931-AC1
RC2:
'Comment on egusphere-2024-3931', Anonymous Referee #2, 15 Jun 2025

General:
The authors report a combination of local scale measurements made with an eddy covariance tower and a mobile unit in the city of Beijing, and inventorial data to assess the impact of methane usage (e.g combustion) and leakage once scaled to China GHG budgets, especially considering the trajectory of replacing coal with natural gas.
The objective of the paper is very important and very ambitious. The authors report leakages are not included in China emission inventory and attempt to provide estimates.
However they base the analysis on local and sporadic measurements, and scale them to the expected carbon neutrality trajectory for entire China. This is an interesting exercise but arbitrary, without any uncertainty analysis, assuming leaks computed (partially) on a local scale are valid elsewhere.

Temporal representativity:
L109-112 (on eddy data): "This measurement lasted from June 11 to September 7, 2022, during which the nitrogen cylinder was replaced, and the instrument was debugged on June 18 and 19. From July 12 to 26, the experiment was stopped due to failure of the tower power supply.
L152-153 (on mobile measurements): “Vehicle-based experiments were conducted in the urban area of Beijing in the winter of 2023 and the summer of 2024”.
It appears that the eddy covariance measurements were made only on summer 2022, with also a data gap; while mobile measurements were made sporadically in the winter and summer of two different years.
This setup poses a serious concern on emission measurements and the fact that those data are scaled to derive country based estimates.
Seasonality is very important on any GHG flux including urban natural gas that is used for heating. This short campaign does not allow any trend or seasonal analysis, while authors claim CO2 and CH4 emission are increasing due to increased natural gas usage. This is not clear.
L175-185 Results: authors report flux data on multiple years and multiple tower elevations, but it’s not clear if there are other towers or where these data originate from. Methods report one tower for only few weeks of measurements.

Spatial representativity:
Footprint analysis of eddy covariance appears lacking and incorrect:
L134-136: “In addition, the flux source area was evaluated via the method of Kljun et al. (Text. S1), and the flux source area covers most of the urban area of Beijing and reflects the average emission characteristics at the regional scale.” This is a totally erroneous definition of a footprint, that does not cover the urban area of Beijing nor a regional scale but instead a limited area around the tower. No footprint analysis is reported.
No attempt to assess the spatial representativeness of the eddy covariance footprint, nor that of the mobile measurements, is made, challenging any spatial upscale from these data.
Overall, the measurements appear insufficient and not properly used to infer larger scale estimates. Annual budgets and country scale budgets for the entire China couldn’t be made with such few data in any case.

Minor comments:
Title appears misleading: "Carbon reduction"
in Fig 4 different units are used for the past and future trends
units missing at line 335
L339-341: "we assume that the leakage rate does not have significant seasonal variability because of the positive correlation between methane flux and natural gas consumption". This is not clear, and seasonality in leak fluxes has been reported in several studies.
ref 40 (likely inventory emission trajectories) does not point to any docuement that can be found online.

Citation: https://doi.org/10.5194/egusphere-2024-3931-RC2
- AC2: 'Reply on RC2', Guiqian Tang, 23 Jul 2025
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2024-3931/egusphere-2024-3931-AC2-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2024-3931-AC2

Haoyuan Chen, Tao Song, Xiaodong Chen, Yinghong Wang, Mengtian Cheng, Kai Wang, Fuxin Liu, Baoxian Liu, Guiqian Tang, and Yuesi Wang

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Haoyuan Chen, Tao Song, Xiaodong Chen, Yinghong Wang, Mengtian Cheng, Kai Wang, Fuxin Liu, Baoxian Liu, Guiqian Tang, and Yuesi Wang

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Short summary

The methane leakage from natural gas may offset the reduced CO₂ emissions from its combustion, To quantify its effect, we established the flux observation platform in the urban area of Beijing, the results showed that natural gas has become a common source of both after the transformation of energy structure, the natural gas could escape during storage and use. Although the natural gas leakage rate is not high (1.12 %), the greenhouse effect caused by natural gas leakage can not be ignored.


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