the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 14 Jul 2026
From research to reality: Academic methane measurement systems tested at the TADI controlled release facility
Abstract. Accurate methane emission quantification is critical for climate mitigation efforts in the oil and gas industry. This study evaluates the performance of five academic methane measurement systems through single-blind controlled release testing at the TotalEnergies Anomaly Detection Initiatives (TADI) facility in France during June and September 2024. Vehicle-based teams from Technical University of Denmark, Heidelberg University, and a collaborative team from Utrecht University/LSCE/Cyprus Institute/Royal Holloway deployed mobile in situ measurement systems, while aircraft-based solutions from Empa/UZH and FAAM BAe-146 utilized hyperspectral imaging and airborne in situ measurements, respectively. Vehicle-based systems demonstrated strong detection capabilities with true positive rates of 93–100 % and minimum detection thresholds below 1 kg CH₄ h⁻¹. Quantification accuracy varied significantly, with slopes ranging from 0.38 to 1.04 when comparing estimated versus true emission rates. Aircraft systems showed more variable performance due to operational constraints and limited data availability. Post-unblinding analysis revealed critical insights into systematic errors, including background concentration calculation issues and wind measurement limitations. Low wind conditions (<2 m s⁻¹) particularly challenged quantification accuracy across all platforms. These findings highlight the importance of robust validation procedures and high-quality meteorological data for reliable methane emission quantification in real-world applications.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Measurement Techniques.
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 paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
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Status: open (until 18 Aug 2026)
- RC1: 'Comment on egusphere-2026-1744', Anonymous Referee #2, 03 Aug 2026 reply
Data sets
amcmanemin2/TADI_controlled_release_2024: Commercial team publication Audrey McManemin https://doi.org/10.5281/zenodo.18381031
Model code and software
amcmanemin2/TADI_controlled_release_2024: Commercial team publication Audrey McManemin https://doi.org/10.5281/zenodo.18381031
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General Comments:
This paper details results from a 2024 controlled release campaign evaluating methane leak detection and quantification from five academic teams at the TADI controlled release site in Pau, France. A variety of teams conducted measurements of single-blind releases with sampling occurring on vehicle and aircraft platforms. Details of detection and quantification for all teams are provided, along with analysis detailing the effect of atmospheric conditions on the ability of each team to identify a release and provide accurate quantification. Overall, the results are well-presented and within the scope of AMT. Publication is recommended with the following minor revisions.
Specific Corrections:
One methodological point on quantification accuracies (i.e. regressions Figure 8 and related analysis) that could be considered: All participating teams provide uncertainty estimates along with quantified emission rates; however, all regressions between estimated and true emission rates use ordinary least squares. The authors could consider utilizing generalized least squares (i.e. uncertainty-weighted), which can explicitly account for the variable uncertainty on each data point when calculating regressions for quantification accuracies. The primary benefit of this method would be to reduce the effect of outliers with large uncertainties on regressions (which doesn’t seem to be driving quantification errors in this study), and better-use the uncertainty estimates provided for each quantification. As this study is a follow-on piece to McManemin 2026 which evaluated commercial methane detection and quantification technologies with similar methods during the same controlled release, it is acceptable if the authors wish to maintain consistency with this earlier paper.
75: “in situ sensors” are defined, but “active scanning systems” are left undefined. Do active scanning systems not also measure local concentrations? As all sensors in this paper are either vehicle based (in situ) or aircraft (remote imaging systems), I recommend defining active scanning systems or removing the discussion for this piece entirely.
281: RHUL’s method undefined. “a traditional determination process based on the cloud coverage and the wind speed at the time of measurements” Please provide a citation or more description of the methodology used.
Figure 3d is very hard to read, and missing labels or what the cells (Letters A-F?) indicate. Please improve readability of this figure.
341: Is the LGR precision at a given averaging time available? All other in situ sensors present a similar metric and would be helpful in comparing the different sensors used in this study.
436: The definition of “smaller releases” is ambiguous in this section. I believe that it refers to less than 100 kg/hr, but please clarify. Additionally, plots of POD are shown for less than 30kg/hr, but this section segments at 100kg/hr. Please provide a small justification for the different choices made in what constitutes a “smaller” release magnitude.
475: “Low wind speed conditions (below 1 m/s) are correlated with increased scatter and underestimation.” The reader can look to Figure 9 and observe differences in r^2 across wind speed bins, however these are segmented from 0-2 m/s and the text claims “below 1 m/s”. If the authors are attempting to comment on differences between the 2 m/s threshold and the displayed 0-2m/s binning, some additional statistics would be helpful to make this claim.
478 and later: Here and after the term “stable wind conditions” may be confusing. At first read, I thought this was referring to atmospheric stability class, rather than the within-period variation. Recommend making this distinction clear, or using alternative language (i.e. consistent wind conditions). In this section is the CoV calculated over a specific time duration, or is this referring to the r^2 values in Figure 9? Some additional definitions and specificity would benefit this section.
510 & 517: Be specific about “reproducing” and “on par” mean. Does this mean results demonstrating quantification accuracy with a similar order of magnitude? Within XXX%?
Technical Corrections:
244: The authors use both British and American spellings of some words (i.e. modelling & modeling). Please be consistent throughout the manuscript
329: It seems that the ddeq package has a corresponding GMD paper (https://doi.org/10.5194/gmd-17-4773-2024). Add this citation?
480: please define CoV parenthetically.