Remote Sensing for Quantifying Greenhouse Gas Emissions at Carbon Capture, Utilisation and Storage Facilities: A Review

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This review paper provides a comprehensive overview of remote sensing technologies for quantifying greenhouse gas (GHG) emissions from carbon capture, utilization, and storage (CCUS) facilities. The topic is highly relevant, as accurate and transparent monitoring of CO₂ and CH₄ leakage is critical for assessing the environmental integrity of CCUS projects. Overall, the paper is well organized, scientifically sound, and of broad relevance to the research community. I recommend acceptance after some revisions.

 

Major Comments

1. Please reconsider the classification of inversion methods in section 4.2.2. Dividing the approaches into Bayesian inversion, data assimilation, and influence function-based inversion may not be entirely appropriate. Bayesian inversion is fundamentally a form of data assimilation, and other major techniques such as the four-dimensional variational method (4D-Var) and the Ensemble Kalman Filter (EnKF) should also be mentioned. It is recommended to reorganize this section and strengthen the methodological discussion. The following paper may serve as a useful reference: https://doi.org/10.3390/rs17183152
2. Lines 335–336: Figure 6 does not clearly demonstrate how the three observation techniques complement each other in space and time. It is recommended to add practical examples or propose a more detailed and implementable framework illustrating such complementarity.

 

Specific comments

1.line 469: The methane budget has been updated in the 2020 version; please replace the current reference with the most recent one. https://doi.org/10.5194/essd-17-1873-2025

2. Section 4.2.1: A brief introduction to CTMs is necessary to provide sufficient background for the inversion discussion.

3.line 401: The description of FLEXPART is inaccurate. It can operate in both forward and backward modes. Please refer to the official website for clarification: https://www.flexpart.eu/

4.lines 351-372: The Retrieval algorithms section is somewhat superficial. While a concise overview is acceptable, it would be helpful to include several key references for readers who wish to explore this topic further.

Author Response

 

Major Comments

Comment 1:

Please reconsider the classification of inversion methods in section 4.2.2. Dividing the approaches into Bayesian inversion, data assimilation, and influence function-based inversion may not be entirely appropriate. Bayesian inversion is fundamentally a form of data assimilation, and other major techniques such as the four-dimensional variational method (4D-Var) and the Ensemble Kalman Filter (EnKF) should also be mentioned. It is recommended to reorganize this section and strengthen the methodological discussion. The following paper may serve as a useful reference: https://doi.org/10.3390/rs17183152

Response 1:
We thank the reviewer for this important clarification. In response, we have reorganised Section 4.2.2 to explicitly present Bayesian estimation as the overarching framework for inverse emission estimation and to position variational Ensemble Kalman Filter approaches and influence-function methods as practical implementations within this paradigm. We have also expanded the text to introduce 4D-Var and EnKF explicitly and added the suggested reference along with other foundational citations.

To improve clarity and avoid misinterpretation of the classification figure 7 was removed.

 

Comment 2:

Lines 335–336: Figure 6 does not clearly demonstrate how the three observation techniques complement each other in space and time. It is recommended to add practical examples or propose a more detailed and implementable framework illustrating such complementarity.

Response 2:
We thank both reviewers for these consistent suggestions. Figure 6 has been removed and the accompanying text has been expanded to describe in detail how satellite, airborne and in-situ observations complement each other across spatial and temporal scales. 

 

Specific comments

Comment 3:

1.line 469: The methane budget has been updated in the 2020 version; please replace the current reference with the most recent one. https://doi.org/10.5194/essd-17-1873-2025

Response 3:

Thank you for pointing this out. We have replaced the previous methane budget reference with the updated 2025 version and updated the citation in the manuscript accordingly.

 

Comment 4:

Section 4.2.1: A brief introduction to CTMs is necessary to provide sufficient background for the inversion discussion.

Response 4:

Thank you for this suggestion. We have added a brief introductory paragraph to Section 4.2.1 explaining the role of CTMs in simulating atmospheric transport and linking emissions to observed concentrations. This provides context for the subsequent inversion framework and clarifies why CTMs are a core component of top-down CCUS monitoring systems.

 

Comment 5:

line 401: The description of FLEXPART is inaccurate. It can operate in both forward and backward modes. Please refer to the official website for clarification: https://www.flexpart.eu/

Response 5:

Thank you for catching this. We corrected the text to state that FLEXPART operates in both forward and backward modes. We also added an extra citation (Pisso et al., 2019) and a reference to the official FLEXPART website.

 

Comment 6:

lines 351-372: The Retrieval algorithms section is somewhat superficial. While a concise overview is acceptable, it would be helpful to include several key references for readers who wish to explore this topic further.

Response 6:

Thank you for this helpful suggestion. We have retained the concise overview but expanded the text slightly to clarify the main retrieval approaches and added key references to guide readers to the primary literature on atmospheric trace-gas retrievals from hyperspectral satellite data. These include foundational optimal-estimation works, OCO-2/3 and TROPOMI retrieval descriptions, and recent CCUS-relevant developments.

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript, entitled “Remote Sensing for Quantifying Greenhouse-Gas Emissions at Carbon Capture, Utilization and Storage Facilities: A Review", aims to provide a comprehensive overview of contemporary approaches to quantifying and verifying greenhouse gas emissions in carbon capture, utilization, and storage facilities through the integration of sensor technologies, data extraction methods, and inversion frameworks. The authors aim to summarize and analyze existing approaches and trends in the application of remote methods and technologies for more reliable emission assessment and for determining indicative limits for leak detection. The article attempts to identify current challenges and future research directions. The review covers publications from 2001 to 2024, focusing on remote sensing sensors and algorithms for data extraction and assimilation methods to obtain reliable estimates of greenhouse gas emissions from the facility level to the regional level.

The topic is highly relevant to the scope of Remote Sensing, as review articles that synthesize our knowledge on the application of remote methods for quantifying greenhouse gas emissions are essential for guiding future research. The manuscript demonstrates considerable effort in collecting and categorizing a relatively large number of studies.

The authors provide a well-reasoned opinion on the importance of carbon capture, utilization, and storage technologies in the Introduction section, as well as their role in efforts to reduce greenhouse gas emissions. They mention difficulties related to the accurate quantification of emissions from such facilities. However, I believe that this section needs further attention and more justification as to why this review is necessary—the current research gaps should be specified in more detail. In addition, it would be good to mention in this section what criteria were used to select the publications used in the study, what type of sources were used, and what time period was covered. This would give a clear idea of the depth and scope of the current work right from the start.

The methodology of the review has a clearly defined structure and logical sequence. It systematically examines and explains the regulatory frameworks for CCUS, modern monitoring technologies and platforms, methods for data processing and emissions assessment, as well as the validation of results and their integration with national inventories. These are the main components of this type of review study, which provides the necessary depth and scope.

The authors provide a well-founded and reasoned critical analysis of the currently available techniques and methods for monitoring emissions, as well as their comparative advantages and limitations. My recommendation is that this part in particular should be presented in greater depth, with more reference to results and analyses from previous scientific publications over the last two to three years. The journal Remote Sensing alone contains a sufficient number of high-quality articles on this very topic.

Overall, the review effectively summarizes existing studies, but in some places the authors' approach is more descriptive than analytical.

I recommend that the authors synthesize the key conclusions and identify the main and most popular models and gaps—for example, which algorithms outperform others, which types of data are underutilized, etc.

The figures and tables used are sufficiently informative and logically related to the relevant context.

This study also identifies the current gaps and challenges in existing monitoring practices. Recommendations for improving CCUS monitoring practices are also presented. However, I recommend that the authors strengthen the critical analysis and reduce the descriptive nature of some of the subsections in this main part of the material. It is also advisable to include as arguments and value studies for the last two to three years in order to strengthen the specificity and broaden the scope.

In conclusion, the main findings of the review are well summarized and its contribution is clearly stated.

The main recommendation is to include a larger literature base with a focus on the last two to three years. The list of 42 sources used is relatively short and incomplete given the scope of the topic. Only 12 of these sources are from the last three years, which makes the argumentation in the main part of the article not very relevant. The authors also refer to four studies reported in the journal Remote Sensing, but I believe that this number could also be increased due to the availability of sufficient high-quality publications in this journal on the topics covered in the review.

Author Response

Comment 1:

The authors provide a well-reasoned opinion on the importance of carbon capture, utilization, and storage technologies in the Introduction section, as well as their role in efforts to reduce greenhouse gas emissions. They mention difficulties related to the accurate quantification of emissions from such facilities. However, I believe that this section needs further attention and more justification as to why this review is necessary—the current research gaps should be specified in more detail. In addition, it would be good to mention in this section what criteria were used to select the publications used in the study, what type of sources were used, and what time period was covered. This would give a clear idea of the depth and scope of the current work right from the start.

Response 1:

We thank the reviewer for this constructive feedback. The introduction has been expanded to better justify the need for this review, emphasizing the research gap in integrated remote-sensing applications for CCUS monitoring. The section now also outlines the criteria and scope of the literature selection. Several recent references have been incorporated to reflect the latest developments and ensure the review remains comprehensive and up to date.

 

Comment 2:

The methodology of the review has a clearly defined structure and logical sequence. It systematically examines and explains the regulatory frameworks for CCUS, modern monitoring technologies and platforms, methods for data processing and emissions assessment, as well as the validation of results and their integration with national inventories. These are the main components of this type of review study, which provides the necessary depth and scope.

The authors provide a well-founded and reasoned critical analysis of the currently available techniques and methods for monitoring emissions, as well as their comparative advantages and limitations. My recommendation is that this part in particular should be presented in greater depth, with more reference to results and analyses from previous scientific publications over the last two to three years. The journal Remote Sensing alone contains a sufficient number of high-quality articles on this very topic.

Response 2:

We thank the reviewer for this valuable suggestion. The sections discussing monitoring technologies and data processing have been expanded with additional references from recent peer-reviewed studies, including several from Remote Sensing.

 

Comment 3:

Overall, the review effectively summarizes existing studies, but in some places the authors' approach is more descriptive than analytical.

I recommend that the authors synthesize the key conclusions and identify the main and most popular models and gaps—for example, which algorithms outperform others, which types of data are underutilized, etc.

Response 3:

We thank the reviewer for this helpful suggestion. The conclusion section has been expanded with a new paragraph summarizing the relative strengths of current retrieval and inversion frameworks and identifying key research gaps, such as limited use of SWIR and hyperspectral data for CCUS applications and insufficient uncertainty propagation. 

 

Comment 4:

The figures and tables used are sufficiently informative and logically related to the relevant context.

This study also identifies the current gaps and challenges in existing monitoring practices. Recommendations for improving CCUS monitoring practices are also presented. However, I recommend that the authors strengthen the critical analysis and reduce the descriptive nature of some of the subsections in this main part of the material. It is also advisable to include as arguments and value studies for the last two to three years in order to strengthen the specificity and broaden the scope.

Response 4:

We thank the reviewer for this thoughtful and constructive comment. The discussion throughout Sections 3 and 4 has been revised to emphasize a more critical analysis of monitoring methodologies, retrieval algorithms and inversion techniques rather than purely descriptive summaries. Comparative evaluations of recent approaches have been added, highlighting methodological strengths and limitations. In addition, several recent peer-reviewed studies have been incorporated to broaden the temporal scope and strengthen the empirical basis of the analysis. These updates ensure that the review presents a balanced and up-to-date assessment of CCUS monitoring practices and their ongoing challenges.

 

Comment 5:

In conclusion, the main findings of the review are well summarized and its contribution is clearly stated.

The main recommendation is to include a larger literature base with a focus on the last two to three years. The list of 42 sources used is relatively short and incomplete given the scope of the topic. Only 12 of these sources are from the last three years, which makes the argumentation in the main part of the article not very relevant. The authors also refer to four studies reported in the journal Remote Sensing, but I believe that this number could also be increased due to the availability of sufficient high-quality publications in this journal on the topics covered in the review.

Response 5:

We thank the reviewer for this important comment. In the revised version, the reference list has been expanded from 42 to 66 entries, including 24 recent papers from 2022–2025. The number of references from Remote Sensing has increased from four to six.

Reviewer 3 Report

Comments and Suggestions for Authors

This Review Paper provides a study on the strength and limitations of remote sensing sensors and retrieval methods to estimate greenhouse gas emissions at Carbon capture, utilisation and storage (CCUS) facilities. It also investigates regulatory schemes to evaluate the performance of such systems. The aim is to help determining net reductions in greenhouse gases emissions in the CCUS facilities. The research has been well-structured and the manuscript has been well-written and includes all the supporting information. I would recommend this manuscript for publication. I only have a few recommendations:

Line 34: I would recommend elaborating more on the CCUS technologies and provide more information about it.

Table 1: This table is more appropriate to be placed in section 3.3.

Line 72: Could you provide information on the number of CCUS facilities in 2025?

Fig. 1: This figure has not been discussed in the text. I would recommend to remove it or provide a description about it in the body of the manuscript.

Line 150: This is a very vague sentence. Improve the language, expand it and provide clarifications.

Fig. 2: I would recommend removing this figure and instead summarizing it in the body of the manuscript.

Line 151-156: I would recommend providing more information about each scheme.

Line 180-182: This part is vague and needs clarity.

Line 187-197: I recommend providing references for each verification framework.

Line 273: Provide examples of some research studies which used NDIR and TDLAS.

Line 293: Explain more about Fig. 3.

Fig. 3: What is the x-axis in Fig. 3 (a)?

Line 300-302: I would recommend providing research examples which used these processing methods as citations.

Line 316: This section lacks the explanation about Fig. 4a, b, and C, and Fig. 5.

Fig. 6: This figure should be removed and substituted by text in the manuscript.

Line 452: Provide citations for top-down approach.

Comments on the Quality of English Language

The English could use some improvements in the manuscript.

Author Response

Comment 1:

Line 34: I would recommend elaborating more on the CCUS technologies and provide more information about it.

Response 1:

Thank you for this suggestion. We have expanded the introduction to briefly describe the main CCUS technology pathways, including typical industrial applications and associated monitoring needs.

 

Comment 2:

Table 1: This table is more appropriate to be placed in section 3.3.

Response 2:

Thank you for the suggestion. We have moved Table 1 to Section 3.3, where it aligns better with the discussion and improves the manuscript flow.

 

Comment 3:

Line 72: Could you provide information on the number of CCUS facilities in 2025?

Response 3:

Thank you for the suggestion. We have updated the manuscript to include the most recent available deployment statistics for CCUS.

 

Comment 4:

Fig. 1: This figure has not been discussed in the text. I would recommend to remove it or provide a description about it in the body of the manuscript.

Response 4:

Thank you for pointing this out. To improve clarity and maintain focus, we have removed Figure 1 from the manuscript. The surrounding text has been updated accordingly to ensure a smooth flow without the figure.

 

Comment 5:

Line 150: This is a very vague sentence. Improve the language, expand it and provide clarifications.

Response 5:

Thank you for identifying this. The sentence has been expanded as suggested.

 

Comment 6:

Fig. 2: I would recommend removing this figure and instead summarizing it in the body of the manuscript.

Response 6:

Thank you for the suggestion. We have removed Figure 2 and incorporated a concise textual summary of its content directly into the manuscript.

 

Comment 7:

Line 151-156: I would recommend providing more information about each scheme.

Response 7:

Thank you for the suggestion. We have expanded this section to briefly describe the main operating carbon trading schemes.

 

Comment 8:

Line 180-182: This part is vague and needs clarity.

Response 8:

Thank you for pointing this out. We have rewritten the relevant sentences to clarify the meaning of “Tier” within the EU ETS framework and to specify the methodological requirements for Category A installations.

 

Comment 9:

Line 187-197: I recommend providing references for each verification framework.

Response 9:

We thank the reviewer for this valuable suggestion. The section describing the major verification frameworks has been revised to include specific, peer-reviewed references. 

 

Comment 10:

Line 273: Provide examples of some research studies which used NDIR and TDLAS.

Response 10:

We thank the reviewer for this suggestion. The text has been expanded to include examples of peer-reviewed studies employing NDIR and TDLAS techniques for CO₂ and CH₄ monitoring.

 

Comment 11:

Line 293: Explain more about Fig. 3.

Response 11:

We thank the reviewer for this suggestion. We have expanded the accompanying text to provide a clearer explanation of Figure 3.

 

Comment 12:

Fig. 3: What is the x-axis in Fig. 3 (a)?

Response 12:

The caption of Figure 3 has been revised to specify that the x-axis represents time for both panels.

 

Comment 13:

Line 300-302: I would recommend providing research examples which used these processing methods as citations.

Response 13:

We thank the reviewer for this recommendation. The paragraph discussing data‐processing methods has been enhanced with three recent peer‐reviewed studies. 

 

Comment 14:

Line 316: This section lacks the explanation about Fig. 4a, b, and C, and Fig. 5.

Response 14:

We thank the reviewer for this helpful comment. We have expanded the text and captions for Figures 4 and 5 to provide detailed explanations of what each panel represents and how the two figures complement one another. 

 

Comment 15:

Fig. 6: This figure should be removed and substituted by text in the manuscript.

Response 15:

We thank both reviewer one and two for these consistent suggestions. Figure 6 has been removed and the accompanying text has been expanded to describe in detail how satellite, airborne and in-situ observations complement each other across spatial and temporal scales. 

 

Comment 16:

Line 452: Provide citations for top-down approach.

Response 16:

We thank the reviewer for this suggestion. The paragraph describing the top-down approach has been expanded with peer-reviewed references that document its theoretical basis and recent applications.