Rethinking Turbulence Intensity: A Smarter Approach to Methane Dispersion Modeling
Emission models are just as important as the devices used to detect methane.
Here, we show how we have improved our emissions model to better account for turbulence, the rapid fluctuations in wind direction and speed that drive dispersion.
Traditional plume models estimate turbulence intensity using averaged environmental conditions. In practice, that often misses what is happening moment to moment. We have incorporated two key learnings to better model methane emissions, and results from our recent METEC ADED2.0 testing confirm the impact of these improvements in blind, third-party studies.
Key learnings:
Wind variability
Averaged values miss important short-term changes in the wind field. Our model relies more heavily on observed wind variability rather than general stability classifications. This allows us to use physics-based modeling with real environmental inputs, while minimizing the computational cost.
Nighttime pooling
At first, we assumed reduced wind speeds were the cause of emission pooling at night. But even after controlling for wind speed, the behavior persisted. The missing factor was solar heating. During the day, sunlight warms the ground and creates convective turbulence that helps disperse methane. At night, without solar heating, the atmosphere becomes more stable and dispersion drops sharply. With this improvement, our model better captures both daytime and nighttime dispersion.
What it means for operators:
Better data
Better emissions modeling
Better methane localization and quantification