From the journal Environmental Science: Atmospheres Peer review history
Methane detection and quantification in the upstream oil and gas sector: the role of satellites in emissions detection, reconciling and reporting
Round 1
Manuscript submitted on 18 juin 2021![](https://www.rsc-cdn.org/pubs-core/2022.0.146/content/NewImages/icon-letter.png)
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19-Sep-2021
Dear Dr Cooper:
Manuscript ID: EA-CRV-06-2021-000046
TITLE: Methane detection and quantification in the upstream oil and gas sector: the role of satellites in emissions detection, reconciling and reporting
Thank you for your submission to Environmental Science: Atmospheres, published by the Royal Society of Chemistry. I apologize for the long turn-around time for this review, as it took a while to find suitable and available reviewers. I have now received the reviewer's reports which are copied below.
I have carefully evaluated your manuscript and the reviewers’ reports, and the reports indicate that major revisions are necessary.
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Dr Tzung-May Fu
Associate Editor
Environmental Science: Atmospheres
Royal Society of Chemistry
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Reviewer 1
General comments:
This manuscript by Cooper et al. titled “Methane detection and quantification in the upstream oil and gas sector: the role of satellites in emissions detection, reconciling and reporting ” is a well written manuscript. It successfully summarized a variety of aspects of methane. The review work of methane is quite necessary. I think it is appropriate for publication after minor revision. I only have a few specific comments below.
Specific comments:
Section 3.2 is more about background knowledge of impact factors. It could be moved to supporting information.
Table 3, first row in page 28: The “upper” is 35.4% and the “lower” is “53.4%”, which is higher than the “upper” value. Please check whether this is correct. Moreover, table 3 is not very clear to me as too many words in each grid, and it is hard to tell groups without horizonal lines.
line 195: “bottom-up methods is important”. Change “is” to “are”.
line 249: Change “possibly” to “possible”.
Line 432: “is vitally important”. Change “is” to “are”.
Line 607: Change “ad” to “and”.
In the supporting information, section 4.1: “Error! Reference source not found.” appears in several places.
In page 58, section “4.2” is missing in the “Table of Contents”.
Reviewer 2
This review is timely and needed for the use of satellite-based assessments of methane emissions from oil and gas sources. Overall I found the content to be sound and thorough but the writing and organization need to be improved. I found many instances of poorly structured sentences, and the length of the review could be reduced significantly if redundancy was addressed. My specific comments are below.
Section 2.1
Line 127: change is to are
Another shortcoming of engineering calculations: They do not address “super emitters.” They do not account for irregular or atypical operations, malfunctioning equipment, or unintended releases.
Line 128: What is meant by “other methane sources”?
Section 2.2
Line 142: Add number of sources.
Line 145: Tier 1 is not defined.
Same comment as above, Another shortcoming of emission factors: They do not address “super emitters.” They do not account for irregular or atypical operations, malfunctioning equipment, or unintended releases.
Section 2.3
Line 161: Use of “technology” here is very vague.
In this section you’ve combined direct source emissions measurements with remote sensing techniques. These are two very different approaches (also referred to as top-down and bottom-up). One could either be physically at the source location to measure a leak directly by capturing the leak itself, or one could measure from a location physically removed from the source, like in a vehicle, tower, aircraft or satellite. These approaches are very different with advantages and limitations that should be discussed separately. Remote sensing is not necessarily more accurate than engineering calculations or emissions factors approaches. Some remote sensing techniques, or example, require modeling to arrive at an emission rate and the model introduces uncertainty into the estimate. This section should be rewritten to make the distinction clearer and to correct inaccuracies. The section is also lacking in references. There are many, many papers that describe field campaigns to do both bottom-up and top-down measurements.
Figure 1 is misleading. For many, the technologies depicted are not how the detection or quantification is achieved but are the platform from which the measurement is made. Depending on how the platform and detector are utilized, they can potentially fit into any of the four circles.
Section 3
Line 219: Change is to are (data = plural).
The sentence starting on line 224 needs to be rewritten – it doesn’t make sense.
Line 291: Change data is to data are.
Section 3.2.6 on Wind could be improved if there were more specifics and less vague descriptors such as “low wind speeds,” “large errors,” etc. Just how large can the error/uncertainty be for different wind speeds?
I don’t understand the example on lines 458-462. How does this illustrate an improvement in precision? Why is cloud coverage mentioned?
Table 2 footnote: You should use the newest version of the GHGI which would show emissions for 2019 rather than 2016.
Line 508: Change is to are (data = plural). As this error has been made multiple times, I suggest searching the document for “data” and checking the verb agreement throughout.
Line 531: Adapted from what? If it’s adapted from the two referenced papers, it should look like: “adapted from Solazzo et al. (2021) and Bloom et al. (2017).” Same comment for Figure 5 caption.
Figure 5 is supposed to represent uncertainty, but the key for color gradations has an emission rate. Is the uncertainty the standard deviation of the average emission rate, or something else? The uncertainty should be defined for this figure.
Line 607: Change ad to and.
Figure 6: In the caption, twice “imagine” should I think be imaging.
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We thank the Reviewers for their time to read our manuscript and provide comments on the work presented and how the manuscript can be improved. We hope we have satisfactorily addressed all of the comments.
Referee: 1
Comments to the Author
General comments:
This manuscript by Cooper et al. titled “Methane detection and quantification in the upstream oil and gas sector: the role of satellites in emissions detection, reconciling and reporting ” is a well written manuscript. It successfully summarized a variety of aspects of methane. The review work of methane is quite necessary. I think it is appropriate for publication after minor revision. I only have a few specific comments below.
We thank Referee 1 for their comments and have amended the manuscript per your specific comments.
Specific comments:
• Section 3.2 is more about background knowledge of impact factors. It could be moved to supporting information.
Thank you for your comments and yes we agree that this Section is more background context but we feel the explanations on why certain factors impact satellite usage are important for the paper’s narrative. We have shortened Section 3.2 by moving aerosols, latitude and terrain to the Supporting Information. These have been moved as they are not referred to later on in the manuscript. The impact of clouds, albedo, wind and missing pixels are referred to later on in the manuscript and we feel the reader would benefit from an overview of why these factors can hider a satellite’s ability to take measurements.
• Table 3, first row in page 28: The “upper” is 35.4% and the “lower” is “53.4%”, which is higher than the “upper” value. Please check whether this is correct. Moreover, table 3 is not very clear to me as too many words in each grid, and it is hard to tell groups without horizonal lines.
Thank you for your comment. We agree the way the uncertainty values were presented looked incorrect. We have made the uncertainty bounds in Table 3 clearer. We have also added horizontal lines to the table to make it easier to read.
• line 195: “bottom-up methods is important”. Change “is” to “are”.
We have made this change.
• line 249: Change “possibly” to “possible”.
We have amended the typo.
• Line 432: “is vitally important”. Change “is” to “are”.
We have made this change.
• Line 607: Change “ad” to “and”.
We have corrected the typo.
• In the supporting information, section 4.1: “Error! Reference source not found.” appears in several places.
We have amended the cross-refences.
• In page 58, section “4.2” is missing in the “Table of Contents”.
The table of contents has been updated in the Supporting Information.
Referee: 2
Comments to the Author
This review is timely and needed for the use of satellite-based assessments of methane emissions from oil and gas sources. Overall I found the content to be sound and thorough but the writing and organization need to be improved. I found many instances of poorly structured sentences, and the length of the review could be reduced significantly if redundancy was addressed. My specific comments are below.
We thank Referee 2 for their comments and hope the writing and organisation is now satisfactory. We agree with Referee 2 in that the paper is long and can be made shorter. We have removed sections which are redundant to the overall narrative to the paper (moved aspects of Section 3.2 into the Supporting Information) and have removed redundancy in the form of repetitiveness. However, we feel that the level of detail discussed in Sections 2 and 3 are important to help guide the reader into understanding how satellites work, which is fundamental to understanding their role in oil and gas methane detection and quantification. We have written the manuscript such that a reader with little knowledge on satellites can understand how they are able to detect and measure satellites. Given the level of knowledge of the Journal’s readership (wider environmental science and climate change communities, as stated in the Journal’s mission statement) is broad, we feel the level of detail discussed in the manuscript make it accessible to readers of all levels.
We have addressed your specific comments and hope these are satisfactory.
Section 2.1
• Line 127: change is to are
Another shortcoming of engineering calculations: They do not address “super emitters.” They do not account for irregular or atypical operations, malfunctioning equipment, or unintended releases.
We have made the change. We have also added that engineering calculations cannot account for super-emitters.
• Line 128: What is meant by “other methane sources”?
We have clarified what us meant by other methane sources.
Section 2.2
• Line 142: Add number of sources.
We have added known number of sources to the list of activity factor examples.
• Line 145: Tier 1 is not defined.
Same comment as above, Another shortcoming of emission factors: They do not address “super emitters.” They do not account for irregular or atypical operations, malfunctioning equipment, or unintended releases.
We have defined what is meant by Tier 1 and have added that emission factors are not able to account for super-emitters.
Section 2.3
• Line 161: Use of “technology” here is very vague.
In this section you’ve combined direct source emissions measurements with remote sensing techniques. These are two very different approaches (also referred to as top-down and bottom-up). One could either be physically at the source location to measure a leak directly by capturing the leak itself, or one could measure from a location physically removed from the source, like in a vehicle, tower, aircraft or satellite. These approaches are very different with advantages and limitations that should be discussed separately. Remote sensing is not necessarily more accurate than engineering calculations or emissions factors approaches. Some remote sensing techniques, or example, require modeling to arrive at an emission rate and the model introduces uncertainty into the estimate. This section should be rewritten to make the distinction clearer and to correct inaccuracies. The section is also lacking in references. There are many, many papers that describe field campaigns to do both bottom-up and top-down measurements.
Thank you for your comment and we agree the way this section was written does aggregate together bottom-up and top-down technologies, which can be misleading when comparing the pros and cons of direct measurement to engineering calculations and emissions factors. We also acknowledge the section overlooks the disadvantages of direct measurement. We have re-written this section to make it clearer the distinction of the different technology types used in direct measurement (between bottom-up and top-down). We have added a subsection on bottom-up and top-down and a subsection on the differences between the two. Section 2.3 now reads as:
“In the direct measurement method, emissions (venting, fugitives and incomplete combustion) are quantified at the source (Haugland, 2019, Heath et al., 2015, National Academies of Sciences and Medicine, 2018). A combination of technologies (see Table S4 in the SI for examples) are typically applied, with one used to detect the presence of methane (e.g., parts per billion) and another to measure a flowrate or flux, from which an emissions rate is determined (Haugland, 2019, Methane Guiding Principles, 2020, MARCOGAZ, 2020). There are many technologies which are used to either detect or quantify methane emissions in the oil and gas sector, which can be classified as bottom-up or top-down (Figure 1).
2.3.1. Bottom-up approach and technologies
In the bottom-up approach, emissions are measured at the source e.g. valve, pump, wellhead (Methane Guiding Principles, 2020, National Academies of Sciences and Medicine, 2018). The emission estimates are then multiplied by the number of components to estimate total facility or basin emissions. In this aspect, they are similar to emission factors. There is a wide range of bottom-up technologies, including point source, enclosed chambers and external tracers (Figure 1) (Brown et al., 2020, Haugland, 2019, Methane Guiding Principles, 2020).
2.3.2. Top-down approach and technologies
The top-down approach estimates emissions by measuring the atmospheric concentration of methane, over a given area, and then disaggregating this to derive the emission rate per component or facility (Allen, 2014, National Academies of Sciences and Medicine, 2018). Essentially, it is the opposite to bottom-up. Remote sensing technologies (aircrafts, satellites, observation towers etc. (Figure 1)) are typical examples of top-down technologies (Brown et al., 2020, National Academies of Sciences and Medicine, 2018).
2.3.3. Comparing bottom-up to top-down and direct measurement to engineering calculations and emission factors
There is no clear distinction between bottom-up and top-down technologies as the main difference is the method used to estimate emissions; extrapolated up or disaggregated (National Academies of Sciences and Medicine, 2018). Therefore, for some technologies the mode in which they are used can shift it between the two and consequentially, some technologies can be both bottom-up and top-down. When comparing the direct measurement method to engineering calculations and emission factors, the direct measurement method is more accurate, as the level of detail and granularity in the emissions data are typically much greater (IPCC, 2006, CCAC, 2020).
While considered to be more accurate, the emission estimates are subject to uncertainties. In addition to instrument uncertainty, in the bottom-up approach assumptions are made on the representativeness of the measurement sample when extrapolating (Methane Guiding Principles, 2020). Similarly, in the top-down approach assumptions are made in the modelling to convert the methane concentration into a flow rate, as well as in disaggregating emissions (National Academies of Sciences and Medicine, 2018). Therefore, it can be argued that direct measurement is not necessarily more accurate than engineering calculations and emission factors. However, this is the only method which can verify emission estimates and the data collected from measurement studies are crucial for updating emission factors and data used in engineering calculations. This method is also the only one out of the three that can identify previously unknown emission sources and account for super-emitters.
An important limitation in the accuracy of direct measurement emission estimates is the reconciling of emissions estimates (Allen, 2014). Numerous studies have compared bottom-up emission estimates to top-down estimates and have found significant differences. Alvarez et al. (2018) found that emissions reported by the USA’s Environmental Protection Agency (EPA) could be underreporting emissions by 60% compared to emissions measured in independent field studies. Similarly Chan et al. (2020) found Canadian emissions could be underreported in Government inventories by a factor of two. Also, Kayrros, using data from the Sentinel-5P satellite, found emission events from Russian gas pipelines in 2020 were 40% higher than in 2019, despite the impacts on gas exports due to COVID-19 (Neill, 2021). In general, top-down estimates tend to overestimate while bottom-up estimates tend to underestimate (Allen, 2016).
In recent years, satellites have emerged as a promising technology which could aid the sector by providing site-level emission estimates (European Commission, 2020, Zhang et al., 2020, Zhang et al., 2019, Elkind et al., 2020). They have numerous benefits over other technologies but for them to benefit the sector, verifying the accuracy and usability of their data and derived results are imperative. Therefore, the questions raised regarding reconciling emissions estimated through top-down and bottom-up methods are important for establishing how useful satellites are and how they can be used to aid the sector in its emissions reporting.”
• Figure 1 is misleading. For many, the technologies depicted are not how the detection or quantification is achieved but are the platform from which the measurement is made. Depending on how the platform and detector are utilized, they can potentially fit into any of the four circles.
We have edited the figure caption to make it clear that the examples shown in the figure are for reference only and that depending on the mode a technology is used, it can be classified in a different category. The figure caption now reads as:
“Figure 1: Illustration of the categorisation of technologies used to detect and quantify methane emissions in the oil and gas sector. The technologies shown are examples and a larger list of technologies can be found in the SI. The figure is adapted from one developed by National Academies of Sciences and Medicine (2018). Please note that the figure gives examples of what kinds of technologies are top-down/bottom-up and detection/quantification and is not definitive. The classification of some technologies will vary depending on how it is used e.g., an OGI camera can be a quantification technology depending on whether or not a quantitative system is used (Teledyne FLIR, 2021); mobile labs can be a quantification technology if the measurement campaign intends to use the data collected to estimate emission rates.”
Section 3
• Line 219: Change is to are (data = plural).
We have made the change.
• The sentence starting on line 224 needs to be rewritten – it doesn’t make sense.
This has been re-written to be clearer. This now reads as:
“Inverse modelling is utilised to quantify emissions as tracking back methane in time from raw satellite measurements incurs high uncertainties. Consequentially, details in flux measurements are lost (Blayo et al., 2015); inverse modelling lowers these uncertainties.”
• Line 291: Change data is to data are.
We have made the change
• Section 3.2.6 on Wind could be improved if there were more specifics and less vague descriptors such as “low wind speeds,” “large errors,” etc. Just how large can the error/uncertainty be for different wind speeds?
We have added specific values where possible. This section now reads as:
“Depending on the method used to covert XCH4 into a flux, low wind speeds (~2 m/s) are suitable for detection but result in larger uncertainties (~50%), which are bad for quantification (Varon et al., 2018).”
• I don’t understand the example on lines 458-462. How does this illustrate an improvement in precision? Why is cloud coverage mentioned?
This has been re-written to be clearer on how cloud coverage can improve precision. This particular section now reads as:
“This is because increasing the number of measurements increases confidence in the recorded values. For example, the MDL of Sentinel-5P could reach 500 kg CH4/h/pixel assuming a 17% measurement success rate and 5 km/h wind speed over a year (Jacob et al., 2016). Therefore, decreasing the effects of cloud coverage would effectively decrease the MDL over a prolonged measurement campaign as more days can be measured.”
• Table 2 footnote: You should use the newest version of the GHGI which would show emissions for 2019 rather than 2016.
We have amended the values to the most recent IPCC GWP values for methane.
• Line 508: Change is to are (data = plural). As this error has been made multiple times, I suggest searching the document for “data” and checking the verb agreement throughout.
We have made the change and have gone through the entire document to check the verb agreement. Changes have been made throughout the manuscript.
• Line 531: Adapted from what? If it’s adapted from the two referenced papers, it should look like: “adapted from Solazzo et al. (2021) and Bloom et al. (2017).” Same comment for Figure 5 caption.
The citation in the text and figure caption has been amended.
• Figure 5 is supposed to represent uncertainty, but the key for color gradations has an emission rate. Is the uncertainty the standard deviation of the average emission rate, or something else? The uncertainty should be defined for this figure.
The figure legend has been amended to make it clearer that the figure is showing the uncertainty in units of kg/km2/h.
• Line 607: Change ad to and.
We have fixed the typo.
• Figure 6: In the caption, twice “imagine” should I think be imaging.
Thank you, we have fixed this.
Round 2
Revised manuscript submitted on 08 oct. 2021![](https://www.rsc-cdn.org/pubs-core/2022.0.146/content/NewImages/icon-letter.png)
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03-Nov-2021
Dear Dr Cooper:
Manuscript ID: EA-CRV-06-2021-000046.R1
TITLE: Methane detection and quantification in the upstream oil and gas sector: the role of satellites in emissions detection, reconciling and reporting
Thank you for submitting your revised manuscript to Environmental Science: Atmospheres. After considering the changes you have made, I am pleased to accept your manuscript for publication in its current form, subject to a few minor edits. I have copied any final comments from the reviewer(s) below. Please kindly address these issues when you upload your final version.
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With best wishes,
Dr Tzung-May Fu
Associate Editor
Environmental Science: Atmospheres
Royal Society of Chemistry
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Reviewer 1
The authors addressed my questions well. This manuscript is much more clear now. It is appropriate for publication. I just have a few comments below.
Specific comments:
494: refraction may occur and lead to ...
748: repeat measurements -> repeated measurements, same for 749
750: increases confidence -> increases confidence level
Supporting information,Section 4.2: “15.00 and 18.00 UTC” should be “15:00 and 18:00 UTC”.
Figures of SI are blurry. Please increasing the resolution of the figures.
Reviewer 2
The authors have sufficiently addressed my comments.
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