the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Source attribution of methane emissions from the Upper Silesian Coal Basin, Poland, using isotopic signatures
Abstract. Anthropogenic emissions are the primary source of atmospheric methane (CH4) growth. However, estimates of anthropogenic CH4 emissions still show large uncertainties on global and regional scales. Differences in CH4 isotopic source signatures δ13C and δ2H can help to constrain different source contributions (e.g. fossil, waste, agriculture, etc.). The Upper Silesian Coal Basin (USCB) represents one of the largest European CH4 emission regions, with more than 500 Gg CH4 yr-1 released from more than 50 coal mine ventilation shafts and other anthropogenic sources. During the CoMet (Carbon Dioxide and Methane Mission) campaign in June 2018 methane observations were conducted from a variety of platforms including aircraft and cars to quantify these emissions. Beside the continuous sampling of atmospheric methane concentration, numerous air samples were taken from inside and around the ventilation shafts (1–2 km distance) and aboard the High Altitude and Long Range Research Aircraft (HALO) and DLR Cessna Caravan aircraft, and analyzed in the laboratory for the isotopic composition of CH4.
The airborne samples downwind of the USCB contained methane from all sources in the region and thus enabled determining the mean signature of the USCB accurately. This mean isotopic signature of methane emissions was -50.9 ± 0.7 ‰ for δ13C and -226 ± 9 ‰ for δ2H. This is in the range of previous USCB studies based on samples taken within the mines for δ13C, but more depleted in δ2H than reported before. Signatures of methane enhancements sampled upwind of the mines and in the free troposphere clearly showed the influence of biogenic sources (e.g. wetlands, waste, ruminants). The ground-based samples taken during CoMet allowed determining the source signatures of individual coal mine ventilation shafts. These signatures displayed a considerable range between different shafts and also varied for individual shafts from day to day. Mean shaft signatures range from -60 ‰ to -42 ‰ for δ13C and from -200 ‰ to 160 ‰ for δ2H. A gradient in the signatures of sub-regions of the USCB is reflected both in the aircraft data as well as in the ground samples with emissions from the southwest being most depleted in δ2H and emissions from the south most depleted in δ13C. The average signature of -49.8 ± 5.7 ‰ in δ13C and -184 ± 32 ‰ in δ2H from the ventilation shafts fits with values from previous studies, but clearly differs from the USCB regional signature in δ2H. We assume that the USCB plume mainly contains fossil coal mine methane and biogenic methane from waste treatment, because the USCB is a highly industrialized region with few other possible methane sources. Assuming a biogenic methane signature between and -320 ‰ and -280 ‰ for δ2H, the biogenic methane emissions from the USCB account for 15–50 % of total emissions. The share of anthropogenic-biogenic emissions from this densely populated industrial region is underestimated in commonly used emission inventories. Generally, this study demonstrates the importance and usefulness of δ2H-CH4 observations for methane source attribution, but highlights the need of comprehensive and extensive sampling from all possible source sectors.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-1217', Anonymous Referee #1, 16 Jul 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1217/egusphere-2023-1217-RC1-supplement.pdf
- AC1: 'Reply on RC1', Alina Fiehn, 11 Oct 2023
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RC2: 'Comment on egusphere-2023-1217', Anonymous Referee #2, 02 Aug 2023
The authors use airborne and ground-based air samples to attribute methane emissions in the region to sources, with a focus on distinguishing coal/fossil sources from biogenic/waste sources. The ground-based samples are used to identify source signatures and then, the airborne samples are used to determine the contribution of the two source types. Overall, the study is nicely written and presented but can benefit from some editing to clarify the analysis and results.
An interesting finding from this paper is the relatively large contribution of biogenic sources in the Upper Silesian Coal Basin. Given this finding, there is a need for some introduction of these biogenic sources in the Introduction and annotations in Figure 2. Although there is some text on this towards the end, additional text earlier on would be helpful.
It appears that a lot of the data being used in this paper have been published in previous papers. However, it’s unclear if there’s new data presented in this paper. This should be clarified (see detailed comments below).
Below are detailed line-by-line comments:
L20: Replace "growth" with "concentration accumulation"
L20: Replace "on global" with "at global"
L24: are the "other anthropogenic sources" related to the coal mine or something else? Landfills and wastewater should be listed here in the abstract given the findings of the paper.
L35: "allowed for the determination of the source signatures..."
L30: what are all the sources in the region? This speaks to an earlier comment about clarifying the sources being studied.
L40: I think the main point is that the d2H is important for source attribution and that the d2H of the ventilation shafts differ from the regional d2H values. Therefore, it would be worth rephrasing this sentence to highlight this point. The fact that the d2H of ventilation shafts match previous studies is relevant but should be the secondary point.
L41-42, 34: Because wetlands and ruminants were mentioned in L34, I expected these to be significant. Suggest revising L34.
L45: It would be good to provide some quantitative comparison of underestimation. Either state that the common inventories estimate 6% biogenic or state the difference as a factor.
L50: “at limiting” to “to limit”
L52: the Global Methane Pledge is specifically for methane emission reductions, not all greenhouse gas emission reductions. Replace “greenhouse gas” with “methane”
L53: Replace "localize" with "locate"
L116: define what is meant by "regional perspective". What is the scale of "regional"? It sounds as though the authors are re-analyzing existing data. Either way, this needs to be clarified. A clearer description of what new analysis is being performed here would be helpful.
L136: Pniowek is not shown in Figure 2. It should be identified.
L141: Define FUB at first mention.
L153-154: Were the data published already? This needs to be clarified
L171: "...concentrations and isotopic composition of CH4 were..."
L218: how can the standard errors be small if the variance is large?
L226: the location of Silesia needs to be shown in Figure 2.
L261: the locations of the cow farm, landfills, manholes and wastewater facilities need to be shown in Figure 2.
L266: what is meant by vicinity? In the conclusions, 1-2km is mentioned. It's surprising that the samples taken directly within the shafts are similar to those taken 1-2 km away.
Figure 5: Specify where in the mines the "mining" samples were taken.
Figure 5: Is the data from the MEMO2 dataset? Also specify that this is from ground-based studies.
Figure 6: Specify whether the data is from ground-based measurements in the caption.
Figure 7: specify that EMID fossil fuel data is ground-based.
Overall, there are a lot of acronyms that are used interchangeably. For the ground-based data, it's referred to as MEMO2, EMID, and "ground-based". I suggest simply calling it "ground-based", if possible, and not using multiple names for the same datasets.
L324: Given the importance of the waste sector in this region, there is a need to describe these sources more. How big are the landfills and wastewater treatment plants both spatially and in terms of waste volumes? Also, is there an inventory of all methane sources in the USCB?
L333: the better discrimination of d2H signatures than d13C is interesting. Therefore, it would be helpful to see what the error would be if only d13C was used in source attribution.
L359: can the locations of these landfills and wastewater treatment plants be shown in Figure 2?
Figure 8: The authors assume that waste is the dominant biogenic source in the area. However, there may be natural (and agricultural) sources that may be contributing more than assumed. The authors are probably right but it may be worth pointing out that there still are uncertainties in the biogenic methane source.
L398: how much do the signatures vary over time? How does this affect uncertainties and the comparisons/analysis presented in this paper?
Citation: https://doi.org/10.5194/egusphere-2023-1217-RC2 - AC2: 'Reply on RC2', Alina Fiehn, 11 Oct 2023
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RC3: 'Comment on egusphere-2023-1217', Amy Townsend-Small, 10 Aug 2023
A couple of major takeaways: Some coal mines have methane formed through biogenic carbonate reduction, and some coal mines can emit thermogenic methane more isotopically similar to natural gas. You could highlight your results more clearly in the abstract – it seems that your study, using both isotopes, identifies these mines as clearly emitting thermogenic methane. I believe most papers have previously only used carbon isotopes? E.g. Zazzeri et al., 2016
Another thing that your study clearly shows is that the use of hydrogen stable isotopes is really essential for source apportionment in regions with a mix of thermogenic and biogenic sources. I was excited to see this result because I have also found similar results in Los Angeles, the Barnett Shale, and in Denver, Colorado. I see you mention this in the last sentence of your abstract – can you highlight it more? For example, I think Figure 5 also illustrates this well. In your Figure 5, for carbon isotopes, your mining samples are both above and below the isotopic composition of air. This makes it very, very difficult to use carbon isotopes as a tracer of this source in air. This has global implications because carbon isotopes are being used to track methane sources at background monitoring sites – not hydrogen! My group has found similar results with ground samples taken at natural gas methane sources – as an example see Townsend-Small et al., 2016, Geophysical Research Letters - Using stable isotopes of hydrogen to quantiy biogenic and thermogenic atmospheric methane sources: A case study from the Colorado Front Range.
Citation: https://doi.org/10.5194/egusphere-2023-1217-RC3 - AC3: 'Reply on RC3', Alina Fiehn, 11 Oct 2023
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-1217', Anonymous Referee #1, 16 Jul 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1217/egusphere-2023-1217-RC1-supplement.pdf
- AC1: 'Reply on RC1', Alina Fiehn, 11 Oct 2023
-
RC2: 'Comment on egusphere-2023-1217', Anonymous Referee #2, 02 Aug 2023
The authors use airborne and ground-based air samples to attribute methane emissions in the region to sources, with a focus on distinguishing coal/fossil sources from biogenic/waste sources. The ground-based samples are used to identify source signatures and then, the airborne samples are used to determine the contribution of the two source types. Overall, the study is nicely written and presented but can benefit from some editing to clarify the analysis and results.
An interesting finding from this paper is the relatively large contribution of biogenic sources in the Upper Silesian Coal Basin. Given this finding, there is a need for some introduction of these biogenic sources in the Introduction and annotations in Figure 2. Although there is some text on this towards the end, additional text earlier on would be helpful.
It appears that a lot of the data being used in this paper have been published in previous papers. However, it’s unclear if there’s new data presented in this paper. This should be clarified (see detailed comments below).
Below are detailed line-by-line comments:
L20: Replace "growth" with "concentration accumulation"
L20: Replace "on global" with "at global"
L24: are the "other anthropogenic sources" related to the coal mine or something else? Landfills and wastewater should be listed here in the abstract given the findings of the paper.
L35: "allowed for the determination of the source signatures..."
L30: what are all the sources in the region? This speaks to an earlier comment about clarifying the sources being studied.
L40: I think the main point is that the d2H is important for source attribution and that the d2H of the ventilation shafts differ from the regional d2H values. Therefore, it would be worth rephrasing this sentence to highlight this point. The fact that the d2H of ventilation shafts match previous studies is relevant but should be the secondary point.
L41-42, 34: Because wetlands and ruminants were mentioned in L34, I expected these to be significant. Suggest revising L34.
L45: It would be good to provide some quantitative comparison of underestimation. Either state that the common inventories estimate 6% biogenic or state the difference as a factor.
L50: “at limiting” to “to limit”
L52: the Global Methane Pledge is specifically for methane emission reductions, not all greenhouse gas emission reductions. Replace “greenhouse gas” with “methane”
L53: Replace "localize" with "locate"
L116: define what is meant by "regional perspective". What is the scale of "regional"? It sounds as though the authors are re-analyzing existing data. Either way, this needs to be clarified. A clearer description of what new analysis is being performed here would be helpful.
L136: Pniowek is not shown in Figure 2. It should be identified.
L141: Define FUB at first mention.
L153-154: Were the data published already? This needs to be clarified
L171: "...concentrations and isotopic composition of CH4 were..."
L218: how can the standard errors be small if the variance is large?
L226: the location of Silesia needs to be shown in Figure 2.
L261: the locations of the cow farm, landfills, manholes and wastewater facilities need to be shown in Figure 2.
L266: what is meant by vicinity? In the conclusions, 1-2km is mentioned. It's surprising that the samples taken directly within the shafts are similar to those taken 1-2 km away.
Figure 5: Specify where in the mines the "mining" samples were taken.
Figure 5: Is the data from the MEMO2 dataset? Also specify that this is from ground-based studies.
Figure 6: Specify whether the data is from ground-based measurements in the caption.
Figure 7: specify that EMID fossil fuel data is ground-based.
Overall, there are a lot of acronyms that are used interchangeably. For the ground-based data, it's referred to as MEMO2, EMID, and "ground-based". I suggest simply calling it "ground-based", if possible, and not using multiple names for the same datasets.
L324: Given the importance of the waste sector in this region, there is a need to describe these sources more. How big are the landfills and wastewater treatment plants both spatially and in terms of waste volumes? Also, is there an inventory of all methane sources in the USCB?
L333: the better discrimination of d2H signatures than d13C is interesting. Therefore, it would be helpful to see what the error would be if only d13C was used in source attribution.
L359: can the locations of these landfills and wastewater treatment plants be shown in Figure 2?
Figure 8: The authors assume that waste is the dominant biogenic source in the area. However, there may be natural (and agricultural) sources that may be contributing more than assumed. The authors are probably right but it may be worth pointing out that there still are uncertainties in the biogenic methane source.
L398: how much do the signatures vary over time? How does this affect uncertainties and the comparisons/analysis presented in this paper?
Citation: https://doi.org/10.5194/egusphere-2023-1217-RC2 - AC2: 'Reply on RC2', Alina Fiehn, 11 Oct 2023
-
RC3: 'Comment on egusphere-2023-1217', Amy Townsend-Small, 10 Aug 2023
A couple of major takeaways: Some coal mines have methane formed through biogenic carbonate reduction, and some coal mines can emit thermogenic methane more isotopically similar to natural gas. You could highlight your results more clearly in the abstract – it seems that your study, using both isotopes, identifies these mines as clearly emitting thermogenic methane. I believe most papers have previously only used carbon isotopes? E.g. Zazzeri et al., 2016
Another thing that your study clearly shows is that the use of hydrogen stable isotopes is really essential for source apportionment in regions with a mix of thermogenic and biogenic sources. I was excited to see this result because I have also found similar results in Los Angeles, the Barnett Shale, and in Denver, Colorado. I see you mention this in the last sentence of your abstract – can you highlight it more? For example, I think Figure 5 also illustrates this well. In your Figure 5, for carbon isotopes, your mining samples are both above and below the isotopic composition of air. This makes it very, very difficult to use carbon isotopes as a tracer of this source in air. This has global implications because carbon isotopes are being used to track methane sources at background monitoring sites – not hydrogen! My group has found similar results with ground samples taken at natural gas methane sources – as an example see Townsend-Small et al., 2016, Geophysical Research Letters - Using stable isotopes of hydrogen to quantiy biogenic and thermogenic atmospheric methane sources: A case study from the Colorado Front Range.
Citation: https://doi.org/10.5194/egusphere-2023-1217-RC3 - AC3: 'Reply on RC3', Alina Fiehn, 11 Oct 2023
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