Articles | Volume 22, issue 10
https://doi.org/10.5194/acp-22-6489-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-6489-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Technical note: Interpretation of field observations of point-source methane plume using observation-driven large-eddy simulations
Anja Ražnjević
CORRESPONDING AUTHOR
Meteorology and Air Quality Group, Wageningen University, Wageningen, the Netherlands
Chiel van Heerwaarden
Meteorology and Air Quality Group, Wageningen University, Wageningen, the Netherlands
Bart van Stratum
Meteorology and Air Quality Group, Wageningen University, Wageningen, the Netherlands
Arjan Hensen
Department of Environmental Modelling, Sensing & Analysis, Organisation for Applied Scientific Research, Utrecht, the Netherlands
Ilona Velzeboer
Department of Environmental Modelling, Sensing & Analysis, Organisation for Applied Scientific Research, Utrecht, the Netherlands
Pim van den Bulk
Department of Environmental Modelling, Sensing & Analysis, Organisation for Applied Scientific Research, Utrecht, the Netherlands
Maarten Krol
Meteorology and Air Quality Group, Wageningen University, Wageningen, the Netherlands
Institute for Marine and Atmospheric Research Utrecht, Utrecht University, Utrecht, the Netherlands
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Cited
11 citations as recorded by crossref.
- The dynamics of concentration fluctuations within passive scalar plumes in a turbulent neutral boundary layer M. Cassiani et al. 10.1017/jfm.2024.861
- Evaluation of two common source estimation measurement strategies using large-eddy simulation of plume dispersion under neutral atmospheric conditions A. Ražnjević et al. 10.5194/amt-15-3611-2022
- Assessing the representativity of NH3 measurements influenced by boundary-layer dynamics and the turbulent dispersion of a nearby emission source R. Schulte et al. 10.5194/acp-22-8241-2022
- Passive-tracer modelling at super-resolution with Weather Research and Forecasting – Advanced Research WRF (WRF-ARW) to assess mass-balance schemes S. Fathi et al. 10.5194/gmd-16-5069-2023
- A Bayesian technique for quantifying methane emissions using vehicle-mounted sensors with a Gaussian plume model D. Blackmore et al. 10.1016/j.atmosenv.2024.121002
- Local-to-regional methane emissions from the Upper Silesian Coal Basin (USCB) quantified using UAV-based atmospheric measurements T. Andersen et al. 10.5194/acp-23-5191-2023
- Tightening up methane plume source rate estimation in EnMAP and PRISMA images E. Ouerghi et al. 10.5194/amt-18-4611-2025
- Deep Learning-Based quantifications of methane emissions with field applications I. Jahan et al. 10.1016/j.jag.2024.104018
- Evaluating NOx stack plume emissions using a high-resolution atmospheric chemistry model and satellite-derived NO2 columns M. Krol et al. 10.5194/acp-24-8243-2024
- Mixtures of Gaussian processes for robotic environmental monitoring of emission sources I. Waarum et al. 10.1007/s10661-025-14059-6
- The Benefits and Challenges of Downscaling a Global Reanalysis With Doubly‐Periodic Large‐Eddy Simulations B. van Stratum et al. 10.1029/2023MS003750
11 citations as recorded by crossref.
- The dynamics of concentration fluctuations within passive scalar plumes in a turbulent neutral boundary layer M. Cassiani et al. 10.1017/jfm.2024.861
- Evaluation of two common source estimation measurement strategies using large-eddy simulation of plume dispersion under neutral atmospheric conditions A. Ražnjević et al. 10.5194/amt-15-3611-2022
- Assessing the representativity of NH3 measurements influenced by boundary-layer dynamics and the turbulent dispersion of a nearby emission source R. Schulte et al. 10.5194/acp-22-8241-2022
- Passive-tracer modelling at super-resolution with Weather Research and Forecasting – Advanced Research WRF (WRF-ARW) to assess mass-balance schemes S. Fathi et al. 10.5194/gmd-16-5069-2023
- A Bayesian technique for quantifying methane emissions using vehicle-mounted sensors with a Gaussian plume model D. Blackmore et al. 10.1016/j.atmosenv.2024.121002
- Local-to-regional methane emissions from the Upper Silesian Coal Basin (USCB) quantified using UAV-based atmospheric measurements T. Andersen et al. 10.5194/acp-23-5191-2023
- Tightening up methane plume source rate estimation in EnMAP and PRISMA images E. Ouerghi et al. 10.5194/amt-18-4611-2025
- Deep Learning-Based quantifications of methane emissions with field applications I. Jahan et al. 10.1016/j.jag.2024.104018
- Evaluating NOx stack plume emissions using a high-resolution atmospheric chemistry model and satellite-derived NO2 columns M. Krol et al. 10.5194/acp-24-8243-2024
- Mixtures of Gaussian processes for robotic environmental monitoring of emission sources I. Waarum et al. 10.1007/s10661-025-14059-6
- The Benefits and Challenges of Downscaling a Global Reanalysis With Doubly‐Periodic Large‐Eddy Simulations B. van Stratum et al. 10.1029/2023MS003750
Latest update: 10 Oct 2025
Short summary
Mobile measurement techniques (e.g., instruments placed in cars) are often employed to identify and quantify individual sources of greenhouse gases. Due to road restrictions, those observations are often sparse (temporally and spatially). We performed high-resolution simulations of plume dispersion, with realistic weather conditions encountered in the field, to reproduce the measurement process of a methane plume emitted from an oil well and provide additional information about the plume.
Mobile measurement techniques (e.g., instruments placed in cars) are often employed to identify...
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