A Meteorological Indicator for Particulate Matter Emissions: Adapting the Hot-Dry-Windy Index to Predict Feedlot Evening Dust Peaks

Sirapoom Peanusaha, Guillermo Marcillo, Brent W Auvermann

Particulate matter emissions from cattle feedlot operations pose significant challenges to both livestock productivity and air quality in surrounding communities. The evening dust peak (EDP) has been documented for decades, but comprehensive long-term studies examining its meteorological drivers are very limited. While laboratory and field-scale investigations have demonstrated that feedlot surface moisture strongly influences dust emissions, direct moisture measurements are labor-intensive, limiting their operational utility. This study presents a novel framework for estimating feedlot surface moisture conditions using readily available meteorological data by adapting the Hot-Dry-Windy Index (HDW). An empirical water balance model integrating HDW with precipitation inputs was developed to characterize the dynamic interplay between atmospheric drying demand and moisture availability. Under the driest surface conditions, HDW explained 43% of the variability in evening PM₁₀ concentrations (R² = 0.433, r = 0.658, p < 0.001), demonstrating substantial predictive capability when atmospheric drying demand is the primary driver of emission potential. Using a comprehensive 10-year dataset, we quantified EDP characteristics and their relationship with meteorological conditions. Results confirm that the dust concentration in the evening hours consistently contributes 40-60% of 24-hour cumulative emitted mass of PM10 concentration. Analysis of atmospheric stability effects, characterized by vertical temperature gradients, revealed that temperature inversion alone cannot cause elevated dust concentrations but rather modulate the dispersion of emissions driven primarily by animal activity. These findings indicate that robust operational dust prediction models require animal activity parameters to describe emission mechanisms comprehensively.