UAV-Based Measurements of Methane Enhancements Reveal Hotspot Structure and Wind Effects

Area of Science:

• Environmental Science
• Atmospheric Science
• Geostatistics

Background:

• Methane (CH4) emissions from confined animal feeding operations are spatially variable.
• Uncrewed aerial vehicle (UAV)-based methane concentration measurements are sensitive to atmospheric conditions.
• The impact of wind regimes on the spatial interpretability of UAV methane data is not well understood.

Purpose of the Study:

• To evaluate the spatial interpretability of UAV-derived methane enhancements (ΔCH4) under varying wind conditions.
• To integrate geostatistical analysis with atmospheric stability classification for feedlot methane emission studies.
• To determine how atmospheric stability affects the accuracy and reliability of UAV-based methane monitoring.

Main Methods:

• Conducted grid-based UAV surveys over a commercial feedlot.
• Applied anisotropy-aware geostatistical analysis to UAV-derived ΔCH4 data.
• Classified atmospheric stability based on wind speed and turbulence intensity.

Main Results:

• Weakly unstable conditions (wind speed ≳ 2 m s⁻¹, turbulence intensity ≲ 0.35) resulted in elongated, wind-aligned plumes with high directional coherence (D² up to 69%) and low interpolation uncertainty (CV-RMSE = 0.062-0.101 ppm).
• Extremely unstable conditions led to fragmented, near-isotropic ΔCH4 patterns with significantly higher uncertainty (CV-RMSE = 0.215-0.367 ppm).
• High directional coherence correlated with persistent wind direction; low coherence occurred under highly variable, extremely unstable conditions.

Conclusions:

• Wind regime and atmospheric stability are key factors controlling the spatial interpretability of UAV-derived ΔCH4.
• These findings have direct implications for designing effective UAV surveys and assessing data quality for methane emission monitoring.
• Future research should include onboard wind measurements, multi-altitude sampling, and inverse dispersion modeling for accurate flux estimation.