the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Quantification of Oil and Gas Methane Emissions in the Delaware and Marcellus Basins Using a Network of Continuous Tower-Based Measurements
Kenneth Davis
Natasha Miles
Scott Richardson
Aijun Deng
Benjamin Hmiel
David Lyon
Thomas Lauvaux
Abstract. According to the United States Environmental Protection Agency (US EPA), emissions from oil and gas infrastructure contribute 30 % of all anthropogenic methane (CH4) emissions in the US. Studies in the last decade have shown emissions from this sector to be substantially larger than bottom-up assessments, including the EPA inventory, highlighting both an increased importance of methane emissions from the oil and gas sector towards their overall climatological impact, and the need for independent monitoring of these emissions. In this study we present continuous monitoring of regional methane emissions from two oil and gas basins using tower-based observing networks. Continuous methane measurements were taken at 4 tower sites in the northeastern Marcellus basin from May 2015 through December 2016, and 5 tower sites in the Delaware basin in the western Permian from March 2020 through April 2022. These measurements, an atmospheric transport model, and prior emission fields, are combined using an atmospheric inversion to estimate monthly methane emissions in the two regions. This study finds the mean overall emission rate from the Delaware basin during the measurement period to be 146–210 Mg CH4 h-1 (energy-normalized loss rate of 1.1–1.5 %, gas-normalized rate of 2.5–3.5 %). Strong temporal variability in the emissions was present, with the lowest emission rates occurring during the onset of the COVID-19 pandemic. In the Marcellus, this study finds the overall mean emission rate to be 19–28 Mg CH4 h-1 (gas-normalized loss rate of 0.30–0.45 %), with relative consistency in the emission rate over time. These totals align with aircraft top-down estimates from the same time periods. In both basins, the tower network was able to constrain monthly flux estimates within ±20 % uncertainty in the Delaware and ±24 % uncertainty in the Marcellus. The results from this study demonstrate the ability to monitor emissions continuously and detect changes in the emissions field, even in a basin with relatively small emissions and complex background conditions.
- Preprint
(1382 KB) -
Supplement
(4361 KB) - BibTeX
- EndNote
Zachary Barkley et al.
Status: closed
-
RC1: 'Comment on acp-2022-709', Anonymous Referee #1, 05 Jan 2023
Overall the manuscript is very well written and gives thorough explanations of the model, the outputs and the errors, and provides important information currently beyond the abilities of satellite measurement. Quite often in the introductory sections I wrote comments only to remove them as I found the information somewhere later in the manuscript. It would be helpful to have some of this information earlier, such as the predominant winds and seasonal meteorological changes, and the inversion heights and diurnal cycles (with the associated SI figures coming much earlier) as this information is important when trying to understand the choice of tower location on the maps or the model input, rather than having to wait sometimes until the discussion for the information.
Otherwise my only other main point is that there are some SI figures that are not mentioned in the main text and others that do not appear in the order in which they are mentioned in the text, which makes for a lot of scrolling up and down when trying to consult both documents at the same time. Those figures and tables just mentioned in the SI text should be numbered after those in the main manuscript, as is Fig S21, but all should be mentioned somewhere in the text of either MS or SI.
Detailed Points / Questions
Line 59 – No explanation as to why a 4-hour period in the afternoon is taken. If it is taken as the period of maximum vertical mixing of the boundary layer does this work even in the winter months (at least 1 hour prior to sunset)? If daily afternoon averages are used for analysis, how can you have 70 and 40 background observations used per month as stated later. Needs to be clearer that the 4-hour window is just the starting point for background selection. Explanation comes too late.
Line 64 – why did the Marcellus measurements stop at the end of 2016 as there is only 20 months to work with in the model?
Fig. 1 caption – using the phrase 3-km domain for the map is confusing. This is the model resolution rather than the area of the inset boxes, presumably those given in lines 70-71. Mention of the predominant wind directions would be useful given that it is stated earlier that the locations of the towers were chosen to be downwind of the O & G production areas, which one might presume meaning predominantly westerlies in the Delaware and easterlies in the Marcellus, but from looking at SI Figs 4 and 5 (not mentioned in the main text) this is clearly an incorrect assumption. Could refer to Fig S10 for the Delaware that highlights the seasonal differences.
Line 114 – It would be helpful to state the % of non-O&G sources in the Production-based inventory used in the Marcellus model. It must be much less than the 45% presumed from the PADEP, but if still 15-20% could errors in those emissions have implications for the model errors that should be mentioned in a discussion that is totally focussed on O&G?
Line 204 – boundary layers not previously mentioned. Refer to Fig S8 which could have highlighted on it the period of the afternoon data that is used, and Fig S9, which could have highlighted the time of day in UTC at which the radiosonde is profiling the boundary layer.
Fig. 2 – the observed enhancements are influenced by the boundary layer height, but how does the modelled excess, based on the inventory account for this? Not clear, but presume that the 3000m summer and 1000m winter heights are used to calculate the difference in excess produced by the different Delaware inventories.
Technical Corrections
Line 115 – likely twice in 5 words.
Line 201-202 – open parentheses incorrectly positioned.
Line 454 – basins twice.
Typographical errors on lines 13 and 132 of the SI text.
Citation: https://doi.org/10.5194/acp-2022-709-RC1 -
RC2: 'Comment on acp-2022-709', Anonymous Referee #2, 22 Mar 2023
The manuscript by Barkley et al. aims at quantification of methane emissions from two basins located in the U.S. (Delaware and Marcellus) using a combination of tower-based in-situ measurements, atmospheric transport modelling and prior emission data. The authors derive emission estimates and based on this, infer normalized loss rates for both basins. They find a temporal variability for emissions from the Delaware Basin, while emissions are found to be more or less constant over time for the Marcellus Basin. Overall, the study is well-designed and thorough. I really appreciate how careful the authors have conducted different sensitivity studies w.r.t. the impact of e.g. the background selection, the prior estimates and of intermittent emissions. I strongly recommend publication in ACP after addressing some minor points:
Line 53: Please specify the type of the PICARRO instrument series
Line 59: Please explain why you chose an 4h period and why in the afternoon. More details are found later in the manuscript, but I miss the explanation here.
Line 95ff: What about emissions from other sectors? I guess they are negligible, but you should comment on this.
Line 136ff: I somehow struggle with the selection of the background. Thinking simply, I would choose measurements from the upwind tower. You mention that background approach later in the manuscript line (line 210f). I would expect a more detailed explanation of why you are not using this – straightforward - approach already here.
Line 463ff: This is an important, but very general statement. Please be more specific. Can you use your results to better design a network for different kind of emission landscapes? Or, if this is too ambitious (what I ´d assume), what kind of input could you deliver to someone who wants to set-up a network?
Citation: https://doi.org/10.5194/acp-2022-709-RC2 -
RC3: 'Comment on acp-2022-709', Anonymous Referee #3, 28 Mar 2023
General comments
This manuscript presents results from a top-down inverse modelling study of regional methane emissions, using daily averaged mole fraction observations from two tall tower networks. Monthly fluxes are estimated for two oil and gas production regions in the USA, over two different time periods.
The manuscript’s introduction clearly presents the motivation for the study, particularly in how this work could help form an independent estimation of emissions to aid with the monitoring of new emissions legislation. However, discussion of previous similar studies, and how this method and work differs from those, is lacking.
The authors find results comparable to those made by other top-down studies using aircraft observations over the same time periods and, similarly to previous studies, find strong discrepancies between their observed methane enhancements and modelled enhancements made using data from bottom-up fossil fuel emissions inventories.
The impact of intermittent methane sources on these regional methane fluxes is also considered. This is a novel development in this type of regional methane modelling and results from this test should be emphasised as a key conclusion, alongside the methane emissions estimates.
Overall, this is a clearly written manuscript, with a strong emphasis on detailed discussion of the study’s results and sensitivity studies of key input parameters. However, some clarification on the method is required, particularly in how the observations are selected and used and in the assumptions made about non-fossil-fuel methane emissions.
This reviewer recommends that this manuscript is accepted for publication, after the minor comments below have been addressed.
Specific comments
Line 41: An additional paragraph could be added to the introduction, highlighting how others have used similar methods for independent monitoring of regional methane emissions and how the work presented in this paper differs from these previous studies.
Line 59: Only daily afternoon averages are used from all observations, presumably due to issues with transport modelling at other times of the day? More detail on this choice of observation time and averaging is included in the supplementary, but the results from this sensitivity study should also be noted here in the main paper.
Line 60: Was any filtering or data selection carried out on the observations before or after averaging? If so, please explain this process here.
Line 67: Please add the exact latitude/longitude bounds of the two study areas, as this is not clear from Figure 1. This information would allow for easier comparison with future studies.
Line 84: Please explain what ‘analysis nudging’ means here.
Line 114: As only 55% of prior emissions from the Marcellus study area are from O&G sources, what are the other main anthropogenic sources in this region? Are there likely to be any non-anthropogenic methane sources in the region (such as wetland or fresh water sources) that have not been accounted for in the EPA gridded inventory of anthropogenic sources? If these sources are non-negligible, please note any assumptions made about these sources and whether this may have any impact on results from this study area.
Line 124: Was an alternative prior for the Delaware basin also created using the production-based method that was used for the Marcellus basin prior? If so, how did this prior compare to the satellite-based inversion prior for the Delaware basin? You could comment on the choice of using the different alternative priors here, even if this was just due to differing data availability for the two regions.
Line 172: It is stated in the supplemental that the ‘hybrid filter’ method of background site selection was the most successful, but that this would filter out many of the observation days, when there are complex background conditions. You could comment on how not filtering these days out, when the transport model may be underperforming due to the complex conditions, could potentially impact modelled emissions for that month.
Line 184: What is the resolution of the posterior emissions (the x terms), in units of latitude/longitude degrees, and was this the same as the prior resolution of 3x3km?
Line 194: Were the inversions run with errors included for the other non-O&G sectors and did this have any impact on the posterior O&G flux estimates? Please state why you are able to make the assumption that the prior non-O&G fluxes have no uncertainty, particularly in the Marcellus region where 45% of prior fluxes are non-O&G.
Line 313: The result of consistently lower posterior fluxes than the prior from the region with mostly newer activity in the Delaware basin is an interesting result, and could be further emphasised in the conclusions, if similar works have also found that emissions from regions of newer activity are being overestimated.
Line 338: This paragraph and Table S2 suggest that model is not fitting well to data for Delaware, or at least that the model’s fit to the observations does not move the total emissions estimates from the prior, despite some changes in the spatial distribution of emissions. An additional figure, showing the difference between the modelled observations made using the prior and posterior emissions estimates could simplify the discussion of ‘model-obs bias’ presented in this paragraph.
Technical corrections
Line 56: Please define AGL here.
Line 59: The use of different notation for times is a little confusing. Does 20 UT mean 8pm Universal Time? If so, this could be corrected to read: 20:00 Universal Coordinated Time (UTC), 13:00 Central Standard Time (CST).
Line 65: See comment above about use of different time notation.
Figure S7: Please correct the figure description. I think this should read ‘used in this study for the Marcellus basin’.
Some results sections are long and may benefit from being split into smaller subheadings to improve readability, (for example Sections 3.2 and 3.4) but this is at the author’s discretion.
Citation: https://doi.org/10.5194/acp-2022-709-RC3 - AC1: 'Comment on acp-2022-709: Response to reviewers', Zachary Barkley, 28 Apr 2023
Status: closed
-
RC1: 'Comment on acp-2022-709', Anonymous Referee #1, 05 Jan 2023
Overall the manuscript is very well written and gives thorough explanations of the model, the outputs and the errors, and provides important information currently beyond the abilities of satellite measurement. Quite often in the introductory sections I wrote comments only to remove them as I found the information somewhere later in the manuscript. It would be helpful to have some of this information earlier, such as the predominant winds and seasonal meteorological changes, and the inversion heights and diurnal cycles (with the associated SI figures coming much earlier) as this information is important when trying to understand the choice of tower location on the maps or the model input, rather than having to wait sometimes until the discussion for the information.
Otherwise my only other main point is that there are some SI figures that are not mentioned in the main text and others that do not appear in the order in which they are mentioned in the text, which makes for a lot of scrolling up and down when trying to consult both documents at the same time. Those figures and tables just mentioned in the SI text should be numbered after those in the main manuscript, as is Fig S21, but all should be mentioned somewhere in the text of either MS or SI.
Detailed Points / Questions
Line 59 – No explanation as to why a 4-hour period in the afternoon is taken. If it is taken as the period of maximum vertical mixing of the boundary layer does this work even in the winter months (at least 1 hour prior to sunset)? If daily afternoon averages are used for analysis, how can you have 70 and 40 background observations used per month as stated later. Needs to be clearer that the 4-hour window is just the starting point for background selection. Explanation comes too late.
Line 64 – why did the Marcellus measurements stop at the end of 2016 as there is only 20 months to work with in the model?
Fig. 1 caption – using the phrase 3-km domain for the map is confusing. This is the model resolution rather than the area of the inset boxes, presumably those given in lines 70-71. Mention of the predominant wind directions would be useful given that it is stated earlier that the locations of the towers were chosen to be downwind of the O & G production areas, which one might presume meaning predominantly westerlies in the Delaware and easterlies in the Marcellus, but from looking at SI Figs 4 and 5 (not mentioned in the main text) this is clearly an incorrect assumption. Could refer to Fig S10 for the Delaware that highlights the seasonal differences.
Line 114 – It would be helpful to state the % of non-O&G sources in the Production-based inventory used in the Marcellus model. It must be much less than the 45% presumed from the PADEP, but if still 15-20% could errors in those emissions have implications for the model errors that should be mentioned in a discussion that is totally focussed on O&G?
Line 204 – boundary layers not previously mentioned. Refer to Fig S8 which could have highlighted on it the period of the afternoon data that is used, and Fig S9, which could have highlighted the time of day in UTC at which the radiosonde is profiling the boundary layer.
Fig. 2 – the observed enhancements are influenced by the boundary layer height, but how does the modelled excess, based on the inventory account for this? Not clear, but presume that the 3000m summer and 1000m winter heights are used to calculate the difference in excess produced by the different Delaware inventories.
Technical Corrections
Line 115 – likely twice in 5 words.
Line 201-202 – open parentheses incorrectly positioned.
Line 454 – basins twice.
Typographical errors on lines 13 and 132 of the SI text.
Citation: https://doi.org/10.5194/acp-2022-709-RC1 -
RC2: 'Comment on acp-2022-709', Anonymous Referee #2, 22 Mar 2023
The manuscript by Barkley et al. aims at quantification of methane emissions from two basins located in the U.S. (Delaware and Marcellus) using a combination of tower-based in-situ measurements, atmospheric transport modelling and prior emission data. The authors derive emission estimates and based on this, infer normalized loss rates for both basins. They find a temporal variability for emissions from the Delaware Basin, while emissions are found to be more or less constant over time for the Marcellus Basin. Overall, the study is well-designed and thorough. I really appreciate how careful the authors have conducted different sensitivity studies w.r.t. the impact of e.g. the background selection, the prior estimates and of intermittent emissions. I strongly recommend publication in ACP after addressing some minor points:
Line 53: Please specify the type of the PICARRO instrument series
Line 59: Please explain why you chose an 4h period and why in the afternoon. More details are found later in the manuscript, but I miss the explanation here.
Line 95ff: What about emissions from other sectors? I guess they are negligible, but you should comment on this.
Line 136ff: I somehow struggle with the selection of the background. Thinking simply, I would choose measurements from the upwind tower. You mention that background approach later in the manuscript line (line 210f). I would expect a more detailed explanation of why you are not using this – straightforward - approach already here.
Line 463ff: This is an important, but very general statement. Please be more specific. Can you use your results to better design a network for different kind of emission landscapes? Or, if this is too ambitious (what I ´d assume), what kind of input could you deliver to someone who wants to set-up a network?
Citation: https://doi.org/10.5194/acp-2022-709-RC2 -
RC3: 'Comment on acp-2022-709', Anonymous Referee #3, 28 Mar 2023
General comments
This manuscript presents results from a top-down inverse modelling study of regional methane emissions, using daily averaged mole fraction observations from two tall tower networks. Monthly fluxes are estimated for two oil and gas production regions in the USA, over two different time periods.
The manuscript’s introduction clearly presents the motivation for the study, particularly in how this work could help form an independent estimation of emissions to aid with the monitoring of new emissions legislation. However, discussion of previous similar studies, and how this method and work differs from those, is lacking.
The authors find results comparable to those made by other top-down studies using aircraft observations over the same time periods and, similarly to previous studies, find strong discrepancies between their observed methane enhancements and modelled enhancements made using data from bottom-up fossil fuel emissions inventories.
The impact of intermittent methane sources on these regional methane fluxes is also considered. This is a novel development in this type of regional methane modelling and results from this test should be emphasised as a key conclusion, alongside the methane emissions estimates.
Overall, this is a clearly written manuscript, with a strong emphasis on detailed discussion of the study’s results and sensitivity studies of key input parameters. However, some clarification on the method is required, particularly in how the observations are selected and used and in the assumptions made about non-fossil-fuel methane emissions.
This reviewer recommends that this manuscript is accepted for publication, after the minor comments below have been addressed.
Specific comments
Line 41: An additional paragraph could be added to the introduction, highlighting how others have used similar methods for independent monitoring of regional methane emissions and how the work presented in this paper differs from these previous studies.
Line 59: Only daily afternoon averages are used from all observations, presumably due to issues with transport modelling at other times of the day? More detail on this choice of observation time and averaging is included in the supplementary, but the results from this sensitivity study should also be noted here in the main paper.
Line 60: Was any filtering or data selection carried out on the observations before or after averaging? If so, please explain this process here.
Line 67: Please add the exact latitude/longitude bounds of the two study areas, as this is not clear from Figure 1. This information would allow for easier comparison with future studies.
Line 84: Please explain what ‘analysis nudging’ means here.
Line 114: As only 55% of prior emissions from the Marcellus study area are from O&G sources, what are the other main anthropogenic sources in this region? Are there likely to be any non-anthropogenic methane sources in the region (such as wetland or fresh water sources) that have not been accounted for in the EPA gridded inventory of anthropogenic sources? If these sources are non-negligible, please note any assumptions made about these sources and whether this may have any impact on results from this study area.
Line 124: Was an alternative prior for the Delaware basin also created using the production-based method that was used for the Marcellus basin prior? If so, how did this prior compare to the satellite-based inversion prior for the Delaware basin? You could comment on the choice of using the different alternative priors here, even if this was just due to differing data availability for the two regions.
Line 172: It is stated in the supplemental that the ‘hybrid filter’ method of background site selection was the most successful, but that this would filter out many of the observation days, when there are complex background conditions. You could comment on how not filtering these days out, when the transport model may be underperforming due to the complex conditions, could potentially impact modelled emissions for that month.
Line 184: What is the resolution of the posterior emissions (the x terms), in units of latitude/longitude degrees, and was this the same as the prior resolution of 3x3km?
Line 194: Were the inversions run with errors included for the other non-O&G sectors and did this have any impact on the posterior O&G flux estimates? Please state why you are able to make the assumption that the prior non-O&G fluxes have no uncertainty, particularly in the Marcellus region where 45% of prior fluxes are non-O&G.
Line 313: The result of consistently lower posterior fluxes than the prior from the region with mostly newer activity in the Delaware basin is an interesting result, and could be further emphasised in the conclusions, if similar works have also found that emissions from regions of newer activity are being overestimated.
Line 338: This paragraph and Table S2 suggest that model is not fitting well to data for Delaware, or at least that the model’s fit to the observations does not move the total emissions estimates from the prior, despite some changes in the spatial distribution of emissions. An additional figure, showing the difference between the modelled observations made using the prior and posterior emissions estimates could simplify the discussion of ‘model-obs bias’ presented in this paragraph.
Technical corrections
Line 56: Please define AGL here.
Line 59: The use of different notation for times is a little confusing. Does 20 UT mean 8pm Universal Time? If so, this could be corrected to read: 20:00 Universal Coordinated Time (UTC), 13:00 Central Standard Time (CST).
Line 65: See comment above about use of different time notation.
Figure S7: Please correct the figure description. I think this should read ‘used in this study for the Marcellus basin’.
Some results sections are long and may benefit from being split into smaller subheadings to improve readability, (for example Sections 3.2 and 3.4) but this is at the author’s discretion.
Citation: https://doi.org/10.5194/acp-2022-709-RC3 - AC1: 'Comment on acp-2022-709: Response to reviewers', Zachary Barkley, 28 Apr 2023
Zachary Barkley et al.
Data sets
Marcellus Tower Dataset N. L. Miles, D. K. Martins, S. J. Richardson, T. Lauvaux, K. J. Davis, B. J. Haupt, C. Rella https://doi.org/10.18113/D3SG6N
Permian Tower Dataset V. Monteiro, N. L. Miles, S. J. Richardson, Z. Barkley, B. J. Haupt, K. J. Davis https://doi.org/10.26208/98y5-t941
Zachary Barkley et al.
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 379 | 161 | 15 | 555 | 41 | 4 | 9 |
- HTML: 379
- PDF: 161
- XML: 15
- Total: 555
- Supplement: 41
- BibTeX: 4
- EndNote: 9
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1