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

Methane (CH4) emissions from confined animal feeding operations are spatially heterogeneous, and uncrewed aerial vehicle (UAV)-based concentration measurements depend critically on atmospheric conditions. Yet the limits of spatial interpretability under varying wind regimes remain poorly characterized. This study integrates anisotropy-aware geostatistical analysis with atmospheric stability classification to evaluate the spatial interpretability of UAV-derived near-field methane enhancements (ΔCH4) over a commercial feedlot. Grid-based UAV surveys under contrasting wind regimes show that weakly unstable conditions (wind speed ≳ 2 m s-1, turbulence intensity ≲ 0.35) produce elongated, wind-aligned plume structures with strong directional coherence (D2 up to 69%; |Δφ| ≤ 13.5°) and low interpolation uncertainty (CV-RMSE = 0.062-0.101 ppm). Extremely unstable conditions yield fragmented, near-isotropic ΔCH4 patterns with substantially higher uncertainty (CV-RMSE = 0.215-0.367 ppm). High directional coherence (D2 > 36%) coincided with persistent wind direction and low coherence (D2 < 12%) occurred exclusively under highly variable, extremely unstable conditions. These results demonstrate that the wind regime and atmospheric stability govern the spatial interpretability of UAV-derived ΔCH4 fields, with direct implications for survey design and data quality assessment. Future work should incorporate onboard wind measurements, multialtitude sampling, and inverse dispersion modeling to enable quantitative flux estimation at the facility scale.