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https://doi.org/10.5194/egusphere-2023-1420
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2023-1420
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
28 Jul 2023
| 28 Jul 2023
Performance and sensitivity of column-wise and pixel-wise methane retrievals for imaging spectrometers
Abstract. Strong methane point source emissions generate large atmospheric concentrations that can be detected and quantified with infrared remote sensing and retrieval algorithms. Two standard and widely used retrieval algorithms for one class of observing platform, imaging spectrometers, include pixel-wise and column-wise approaches. In this study, we assess the performance of both approaches using the airborne imaging spectrometer (Global Airborne Observatory) observations of two extensive controlled release experiments. We find that the column-wise retrieval algorithm is sensitive to the flight line length and can have a systematic low bias with short flight lines, which is not present in the pixel-wise retrieval algorithm. However, when the flight line length is sufficiently long, the column-wise retrieval algorithms produce results that very closely match metered emission rates. Lastly, this study examines the methane plume detection performance of GAO with a column-wise retrieval algorithm, and finds minimum detection limits between 9–10 kg/hr and 90 % probability of detection between 10–45 kg/h. These results present a framework of rules for guiding proper concentration retrieval selection given conditions at the time of observation to ensure robust detection and quantification.
How to cite. Ayasse, A., Cusworth, D., O'Neill, K., Fisk, J., Thorpe, A., and Duren, R.: Performance and sensitivity of column-wise and pixel-wise methane retrievals for imaging spectrometers, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-1420, 2023.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
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Journal article(s) based on this preprint
20 Dec 2023
Performance and sensitivity of column-wise and pixel-wise methane retrievals for imaging spectrometers
Alana K. Ayasse, Daniel Cusworth, Kelly O'Neill, Justin Fisk, Andrew K. Thorpe, and Riley Duren
Atmos. Meas. Tech., 16, 6065–6074, https://doi.org/10.5194/amt-16-6065-2023, https://doi.org/10.5194/amt-16-6065-2023, 2023
Short summary
Short summary
Methane is a powerful greenhouse gas, and a significant portion of methane comes from large individual plumes. Recently, airplane-mounted infrared technologies have proven very good at detecting and quantifying these plumes. In order to extract the methane signal from the infrared image, there are two widely used approaches. In this study, we assess the performance of both approaches using controlled-release experiments. We also examine the minimum detection limit of the infrared technology.
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
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RC1: 'Comment on egusphere-2023-1420', Anonymous Referee #1, 15 Sep 2023
Please see attached PDF for detailled review.
- AC2: 'Reply on RC1', Alana Ayasse, 23 Oct 2023
-
RC2: 'Comment on egusphere-2023-1420', Anonymous Referee #2, 24 Sep 2023
The manuscript by Ayasee et al. departs from the significant difference obtained in the methane emission estimation results during two controlled emission experiments in order to understand the cause of the flux underestimation obtained in the first campaign, compare the results obtained by processing the data with two different algorithms (CMF and IMAP-DOAS) and, therefore, better understand the behavior of both algorithms and give a guide to which algorithm is more appropriate for each case. In addition, it suggests a solution to avoid obtaining underestimates from flight campaigns if the Matched Filter approach is to be used to process the data. The study has been done with data collected with the GAO sensor in the controlled release experiments organized by Standford University in 2021 and 2022 and also in previous campaigns performed in other areas of the United States, which adds robustness to the study.
I consider the methodology used in this work appropriate and the analysis of the results rigorous and valuable to the scientific community. In addition, the manuscript reads well and is easy to follow. However, I would like to see a little more elaboration on some of the points I list below and some issues need to be addressed. I recommend the publication of this article once the following points are corrected or taken into consideration:
Major comments:
- The abstract mentions that the column-wise retrieval algorithm is sensitive to the flight line length so that it can have a systematic low bias on short flight lines but does not have to be on long enough flights and that this bias is not present in the per-pixel retrieval. Reading this in the abstract, one might first think, why not always use per-pixel retrieval and avoid bias? I suggest including a line clarifying that, on the other hand, per-pixel retrieval has a much higher computational cost, so for large amounts of data processing, it is more optimal to use column retrieval.
- In the same way, in the text, it is mentioned that CMF is computationally more efficient than IMAP-DOAS, but I miss a more quantitative comparison of this difference to help readers better understand the difference. I think it would be helpful to add a sentence, for example, in the methodology section, with an indicative example of "for an image of x length/ xx number of pixels, processing with CMF would take about x minutes, while with IMAP-DOAS xx hours" or similar.
- Lines 169-176: here, I understand that for the CMF, you first remove the background and then obtain the mask of the plume with the values that have remained above the removed background, and in IMEP-DOAS, you first have the mask and then with the values that are not included in the mask you determine the concentration of the background. If correct, how do you calculate the initial mask with the IMAP-DOAS method? Do you do it manually? Taking first an indicative background value? I would appreciate a clarification on this in the text.
- Line 305: regarding the sentence "In practice, we anticipate the POD performance to vary across observing regions and seasons.", this was already shown in Gorroño et al., 2023 https://amt.copernicus.org/articles/16/89/2023/amt-16-89-2023.html with Sentinel 2, which it would be worth mentioning.
- Lines 324-325: the first sentence of the paragraph sounds a bit out of place. Satellites typically have a specific and invariable swath and do not take longer or shorter images. However, it may happen to get a very variable image with, for example, a large presence of water or a higher methane content than normal, preventing an appropriate formation of the covariance matrix and leading to under- or over-estimates. This is a discussion that I missed in the manuscript and could fit here to make sense of the sentence.
- Line 326: about the sentence "As a larger constellation of instruments, and specifically satellites such as EMIT and Planet/Carbon Mapper's Tanager, are used to map methane, ...", first, EMIT is not a satellite and second, why "specifically" EMIT and Planet/Carbon Mapper? If the reason is the common use of the Matched Filter to process the data, generally in studies with PRISMA, EnMAP, or Gaofen5, the CMF is also used to optimize the computational cost (e.g. Irakulis-Loitxate et al. 2021 https://www.science.org/doi/epdf/10.1126/sciadv.abf4507, Guanter et al. 2021 https://www.sciencedirect.com/science/article/abs/pii/S0034425721003916, Roger et al. 2023 https://eartharxiv.org/repository/view/5235/, Nesme et al. 2021 https://doi.org/10.3390/rs13244992). I suggest changing the sentence by removing the "and specifically satellites such as EMIT and Planet/Carbon Mapper's Tanager," and adding the reference of Jacob et al., 2022 after "... constellation of instruments", or simply removing "specifically satellites" and name the other satellites as well.
- References section: the references Ayasse et al., Foote et al., Maasakkers et al., and Ocko et al. are not mentioned in the text.
Minor corrections:
- Line 21 and 22: in addition to the references you cite there, nowadays, there are quite a lot of studies confirming that a significant component of the anthropogenic methane budget comes from a relatively small population of high emission point sources (e.g. Frenkenberg et al., 2016 PNAS, Irakulis-Loitxate et al., 2022 ES&T and ES&TL, Ehret et al., 2022 ES&T), so, for correctness, I suggest you put an "e.g." at the beginning of the list.
- Line 24: at the end of the sentence " ... effects in the next few decades.", I miss a reference that affirms the sentence. Reference to Ocko et al., 2021 would be appropriate here, which is listed in the references but not mentioned in the manuscript. Otherwise, reference to IPCC, 2023: Summary for Policymakers. doi: 10.59327/IPCC/AR6-9789291691647.001would also be appropriate.
- Line 26: I think it is not totally fair to say that airborne imaging spectrometers can repeatedly map large areas. A satellite does have the ability to map large areas every few days over long periods of time (e.g., Irakulis-Loitxate et al., 2022 https://pubs.acs.org/doi/full/10.1021/acs.est.1c04873), but airborne mapping is limited to campaign periods. It is true that in the same campaign, the same locations can be mapped several times, but then there will not be a revisit, in the best cases, before ~one year. I suggest changing the sentence to "In particular, airborne imaging spectrometers with shortwave infrared (SWIR) sensitivity have emerged as useful tools for point source quantification due to their high spatial resolution, low detection limit, and ability to map large areas for point sources" or similar.
- Line 29: at the end of the sentence "... environmental variables including surface illumination and atmospheric transport.", a reference is missing. An appropriate reference would be Gorroño et al., 2023 https://amt.copernicus.org/articles/16/89/2023/amt-16-89-2023.html
- Line 31: for the sentence "... and complexity.", please add a reference, e.g., Jacob et al., 2022 https://acp.copernicus.org/articles/22/9617/2022/acp-22-9617-2022.html
- Line 62: I think here you are referring to this other paper by Sherwin et al. https://www.nature.com/articles/s41598-023-30761-2 not listed in the references.
- Lines 74 and 79: add space between 3 and km.
- Line 96: Please add a reference at the end of the sentence "... CH4 has known absorption properties.”. The reference of your paper, Ayasse et al., 2018, listed in the bibliography (but not mentioned in the text) would work great.
- Line 97, 176, 260: for consistency, matched filter => CMF. It also looks like there is a formatting error on this line.
- Line 98, 101, 196: for consistency, methane => CH4
- Line 112, 147, 244, 303: for consistency with the rest of the citations, Thorpe et al., 2017 (without the name/acronyms).
- Line 144: add Where before So to make it easier to read.
- Line 155: again, for consistency with other citations, Frankenberg et al. 2016 (without the name)
- Line 213: for clarity, add "CMF results" or "left panel" after Figure 1.
- Lines 232-234 and 273/Figure 4: add a) and b) in the panels of the figure, or change the test to Figure 4 left and right.
- Line 250: section S2 => Section 2 or Methodology section
- Line 259, 285, 287: the F in capital letter in "figure 5" and "figure 7"
- Line 293: POD should also be defined in the test
- Line 304: Solar Zenit Angle (SZA)
- Figure 2: for completeness, I think it is worth including in this figure the flight line length of the second controlled release experiment in 2022.
- Figure 2: in the figure caption, it should be explained what the gray bar and black circles are.
- Figure 4: in the title of the plots, what does CM mean? If it refers to Comparison of Methods, I suggest removing it.
Citation: https://doi.org/10.5194/egusphere-2023-1420-RC2 - AC1: 'Reply on RC2', Alana Ayasse, 23 Oct 2023
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
-
RC1: 'Comment on egusphere-2023-1420', Anonymous Referee #1, 15 Sep 2023
Please see attached PDF for detailled review.
- AC2: 'Reply on RC1', Alana Ayasse, 23 Oct 2023
-
RC2: 'Comment on egusphere-2023-1420', Anonymous Referee #2, 24 Sep 2023
The manuscript by Ayasee et al. departs from the significant difference obtained in the methane emission estimation results during two controlled emission experiments in order to understand the cause of the flux underestimation obtained in the first campaign, compare the results obtained by processing the data with two different algorithms (CMF and IMAP-DOAS) and, therefore, better understand the behavior of both algorithms and give a guide to which algorithm is more appropriate for each case. In addition, it suggests a solution to avoid obtaining underestimates from flight campaigns if the Matched Filter approach is to be used to process the data. The study has been done with data collected with the GAO sensor in the controlled release experiments organized by Standford University in 2021 and 2022 and also in previous campaigns performed in other areas of the United States, which adds robustness to the study.
I consider the methodology used in this work appropriate and the analysis of the results rigorous and valuable to the scientific community. In addition, the manuscript reads well and is easy to follow. However, I would like to see a little more elaboration on some of the points I list below and some issues need to be addressed. I recommend the publication of this article once the following points are corrected or taken into consideration:
Major comments:
- The abstract mentions that the column-wise retrieval algorithm is sensitive to the flight line length so that it can have a systematic low bias on short flight lines but does not have to be on long enough flights and that this bias is not present in the per-pixel retrieval. Reading this in the abstract, one might first think, why not always use per-pixel retrieval and avoid bias? I suggest including a line clarifying that, on the other hand, per-pixel retrieval has a much higher computational cost, so for large amounts of data processing, it is more optimal to use column retrieval.
- In the same way, in the text, it is mentioned that CMF is computationally more efficient than IMAP-DOAS, but I miss a more quantitative comparison of this difference to help readers better understand the difference. I think it would be helpful to add a sentence, for example, in the methodology section, with an indicative example of "for an image of x length/ xx number of pixels, processing with CMF would take about x minutes, while with IMAP-DOAS xx hours" or similar.
- Lines 169-176: here, I understand that for the CMF, you first remove the background and then obtain the mask of the plume with the values that have remained above the removed background, and in IMEP-DOAS, you first have the mask and then with the values that are not included in the mask you determine the concentration of the background. If correct, how do you calculate the initial mask with the IMAP-DOAS method? Do you do it manually? Taking first an indicative background value? I would appreciate a clarification on this in the text.
- Line 305: regarding the sentence "In practice, we anticipate the POD performance to vary across observing regions and seasons.", this was already shown in Gorroño et al., 2023 https://amt.copernicus.org/articles/16/89/2023/amt-16-89-2023.html with Sentinel 2, which it would be worth mentioning.
- Lines 324-325: the first sentence of the paragraph sounds a bit out of place. Satellites typically have a specific and invariable swath and do not take longer or shorter images. However, it may happen to get a very variable image with, for example, a large presence of water or a higher methane content than normal, preventing an appropriate formation of the covariance matrix and leading to under- or over-estimates. This is a discussion that I missed in the manuscript and could fit here to make sense of the sentence.
- Line 326: about the sentence "As a larger constellation of instruments, and specifically satellites such as EMIT and Planet/Carbon Mapper's Tanager, are used to map methane, ...", first, EMIT is not a satellite and second, why "specifically" EMIT and Planet/Carbon Mapper? If the reason is the common use of the Matched Filter to process the data, generally in studies with PRISMA, EnMAP, or Gaofen5, the CMF is also used to optimize the computational cost (e.g. Irakulis-Loitxate et al. 2021 https://www.science.org/doi/epdf/10.1126/sciadv.abf4507, Guanter et al. 2021 https://www.sciencedirect.com/science/article/abs/pii/S0034425721003916, Roger et al. 2023 https://eartharxiv.org/repository/view/5235/, Nesme et al. 2021 https://doi.org/10.3390/rs13244992). I suggest changing the sentence by removing the "and specifically satellites such as EMIT and Planet/Carbon Mapper's Tanager," and adding the reference of Jacob et al., 2022 after "... constellation of instruments", or simply removing "specifically satellites" and name the other satellites as well.
- References section: the references Ayasse et al., Foote et al., Maasakkers et al., and Ocko et al. are not mentioned in the text.
Minor corrections:
- Line 21 and 22: in addition to the references you cite there, nowadays, there are quite a lot of studies confirming that a significant component of the anthropogenic methane budget comes from a relatively small population of high emission point sources (e.g. Frenkenberg et al., 2016 PNAS, Irakulis-Loitxate et al., 2022 ES&T and ES&TL, Ehret et al., 2022 ES&T), so, for correctness, I suggest you put an "e.g." at the beginning of the list.
- Line 24: at the end of the sentence " ... effects in the next few decades.", I miss a reference that affirms the sentence. Reference to Ocko et al., 2021 would be appropriate here, which is listed in the references but not mentioned in the manuscript. Otherwise, reference to IPCC, 2023: Summary for Policymakers. doi: 10.59327/IPCC/AR6-9789291691647.001would also be appropriate.
- Line 26: I think it is not totally fair to say that airborne imaging spectrometers can repeatedly map large areas. A satellite does have the ability to map large areas every few days over long periods of time (e.g., Irakulis-Loitxate et al., 2022 https://pubs.acs.org/doi/full/10.1021/acs.est.1c04873), but airborne mapping is limited to campaign periods. It is true that in the same campaign, the same locations can be mapped several times, but then there will not be a revisit, in the best cases, before ~one year. I suggest changing the sentence to "In particular, airborne imaging spectrometers with shortwave infrared (SWIR) sensitivity have emerged as useful tools for point source quantification due to their high spatial resolution, low detection limit, and ability to map large areas for point sources" or similar.
- Line 29: at the end of the sentence "... environmental variables including surface illumination and atmospheric transport.", a reference is missing. An appropriate reference would be Gorroño et al., 2023 https://amt.copernicus.org/articles/16/89/2023/amt-16-89-2023.html
- Line 31: for the sentence "... and complexity.", please add a reference, e.g., Jacob et al., 2022 https://acp.copernicus.org/articles/22/9617/2022/acp-22-9617-2022.html
- Line 62: I think here you are referring to this other paper by Sherwin et al. https://www.nature.com/articles/s41598-023-30761-2 not listed in the references.
- Lines 74 and 79: add space between 3 and km.
- Line 96: Please add a reference at the end of the sentence "... CH4 has known absorption properties.”. The reference of your paper, Ayasse et al., 2018, listed in the bibliography (but not mentioned in the text) would work great.
- Line 97, 176, 260: for consistency, matched filter => CMF. It also looks like there is a formatting error on this line.
- Line 98, 101, 196: for consistency, methane => CH4
- Line 112, 147, 244, 303: for consistency with the rest of the citations, Thorpe et al., 2017 (without the name/acronyms).
- Line 144: add Where before So to make it easier to read.
- Line 155: again, for consistency with other citations, Frankenberg et al. 2016 (without the name)
- Line 213: for clarity, add "CMF results" or "left panel" after Figure 1.
- Lines 232-234 and 273/Figure 4: add a) and b) in the panels of the figure, or change the test to Figure 4 left and right.
- Line 250: section S2 => Section 2 or Methodology section
- Line 259, 285, 287: the F in capital letter in "figure 5" and "figure 7"
- Line 293: POD should also be defined in the test
- Line 304: Solar Zenit Angle (SZA)
- Figure 2: for completeness, I think it is worth including in this figure the flight line length of the second controlled release experiment in 2022.
- Figure 2: in the figure caption, it should be explained what the gray bar and black circles are.
- Figure 4: in the title of the plots, what does CM mean? If it refers to Comparison of Methods, I suggest removing it.
Citation: https://doi.org/10.5194/egusphere-2023-1420-RC2 - AC1: 'Reply on RC2', Alana Ayasse, 23 Oct 2023
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Alana Ayasse on behalf of the Authors (23 Oct 2023)
Author's response
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ED: Publish subject to technical corrections (27 Oct 2023) by Christoph Kiemle
AR by Alana Ayasse on behalf of the Authors (31 Oct 2023)
Author's response
Manuscript
Journal article(s) based on this preprint
20 Dec 2023
Performance and sensitivity of column-wise and pixel-wise methane retrievals for imaging spectrometers
Alana K. Ayasse, Daniel Cusworth, Kelly O'Neill, Justin Fisk, Andrew K. Thorpe, and Riley Duren
Atmos. Meas. Tech., 16, 6065–6074, https://doi.org/10.5194/amt-16-6065-2023, https://doi.org/10.5194/amt-16-6065-2023, 2023
Short summary
Short summary
Methane is a powerful greenhouse gas, and a significant portion of methane comes from large individual plumes. Recently, airplane-mounted infrared technologies have proven very good at detecting and quantifying these plumes. In order to extract the methane signal from the infrared image, there are two widely used approaches. In this study, we assess the performance of both approaches using controlled-release experiments. We also examine the minimum detection limit of the infrared technology.
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Latest update: 30 Aug 2024
Alana Ayasse
CORRESPONDING AUTHOR
Carbon Mapper Inc., Pasadena, CA 91101, USA
Daniel Cusworth
Carbon Mapper Inc., Pasadena, CA 91101, USA
Kelly O'Neill
Carbon Mapper Inc., Pasadena, CA 91101, USA
Justin Fisk
Carbon Mapper Inc., Pasadena, CA 91101, USA
Andrew Thorpe
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
Riley Duren
Carbon Mapper Inc., Pasadena, CA 91101, USA
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
University of Arizona, Tucson, AZ 85721, USA
Download
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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Short summary
Methane is a powerful greenhouse gas and a significant portion of methane comes from large individual plumes. Recently, airplane mounted infrared technologies have proven very good at detecting and quantifying these plumes. In order to extract the methane signal from the infrared image there are two widely used approaches, in this study we assess the performance of both approaches using controlled release experiments. We also examine the minimum detection limit of the infrared technology.
Methane is a powerful greenhouse gas and a significant portion of methane comes from large...