High-resolution modelling of methane plumes: validation and sensitivity experiments to explore emission quantification approaches Article Swipe
Rakesh Yuvaraj
,
Thomas Lauvaux
,
Charbel Abdallah
,
Philippe Ciais
,
Julian Akani Guery
,
Jean‐Louis Bonne
,
Alexis Groshenry
,
Ngoc T. Hoang
,
Lilian Joly
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.26434/chemrxiv-2025-lv32x
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.26434/chemrxiv-2025-lv32x
Methane (CH4) emissions from natural gas operations, waste management, and industrial ac- tivities have been detected using satellite observations and airborne campaigns. Quantifying these emissions remains uncertain due to the complex structures of the plumes and the rapidly changing atmospheric dynamics at fine scales. In this study, we address these uncertainties by employing the Fire Dynamics Simulation (FDS) in Large Eddy Simulation (LES) mode, with mean winds from LiDAR and ERA5 datasets. The FDS model was validated with CH4 con- centration data collected by Uncrewed Aerial Vehicles (UAVs) during controlled release exper- iments. Our analysis of ten extensively sampled plumes shows that FDS accurately reproduces the magnitude and spatiotemporal variations of the observed plumes for sufficiently large pipes (< 0.6 cm diameter). We found that factors such as gas exit velocity, obstacles, and terrain topography significantly affect the near-field dynamics of the plumes. To a lesser extent, the temperature of the gas influences plume behaviour at higher mass-flow rates. We also demon- strate that using ERA5 datasets for free-stream velocity provides a reasonable alternative to in- situ meteorological measurements such as LiDAR datasets, as inputs to the model. We high- light the added value of high-resolution LES modelling to understand CH4 plume dynamics captured by various sensors, aiming to improve current emissions quantification methods.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.26434/chemrxiv-2025-lv32x
- https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/68b0175223be8e43d67aeba9/original/high-resolution-modelling-of-methane-plumes-validation-and-sensitivity-experiments-to-explore-emission-quantification-approaches.pdf
- OA Status
- gold
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4414011711
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4414011711Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.26434/chemrxiv-2025-lv32xDigital Object Identifier
- Title
-
High-resolution modelling of methane plumes: validation and sensitivity experiments to explore emission quantification approachesWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-09-05Full publication date if available
- Authors
-
Rakesh Yuvaraj, Thomas Lauvaux, Charbel Abdallah, Philippe Ciais, Julian Akani Guery, Jean‐Louis Bonne, Alexis Groshenry, Ngoc T. Hoang, Lilian JolyList of authors in order
- Landing page
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https://doi.org/10.26434/chemrxiv-2025-lv32xPublisher landing page
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https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/68b0175223be8e43d67aeba9/original/high-resolution-modelling-of-methane-plumes-validation-and-sensitivity-experiments-to-explore-emission-quantification-approaches.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/68b0175223be8e43d67aeba9/original/high-resolution-modelling-of-methane-plumes-validation-and-sensitivity-experiments-to-explore-emission-quantification-approaches.pdfDirect OA link when available
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Methane, Sensitivity (control systems), Environmental science, Resolution (logic), Atmospheric sciences, Computer science, Geology, Chemistry, Engineering, Artificial intelligence, Organic chemistry, Electronic engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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