Footprint Analysis of Methane Flux Measurements from Beef Cattle Feedlot Using the Eddy Covariance Technique.

Methane (CH₄) emissions from beef cattle feedlots account for a large proportion of agriculture's greenhouse gas (GHG) inventory. Accurate measurements and understanding of the variability of CH₄ emissions from these systems is a crucial step in improving current GHG inventories. Recent developments in optical sensors have allowed us to use the eddy covariance (EC) technique for continuous measurements of trace gas exchange, such as CH₄, N₂O and NH₃. However, fetch limitations and the presence of heterogeneities in the source area impose major challenges in appropriate interpretation of the EC fluxes. The measured flux is affected by CH₄ emitting surfaces (pens) and non-emitting surfaces (roads and alleys). The objectives of this study are (i) to correct CH₄ flux from the feedlot using two dimensional footprint analysis, and (ii) to demonstrate effect of choice of footprint model on the flux corrections. Methane fluxes were measured during 8 months using a closed-path EC system at 5m above the feedlot. Two analytical footprint analyzes were used to interpret and correct the flux measurements: the model by Korman and Meixner (2001) [KM01] and a parameterized version of backward Lagrangian stochastic particle dispersion model by Kljun et al. (2015) [KL015]. Our results indicate that roads and alleys contribute in average ~ 10% and ~ 12% based on KM015 and KL015 to the measured fluxes, respectively. The adjustment for these contributions for each half hour period increase the CH₄ flux by ~22% (KM01) and ~12% (KL015). The corrected flux values obtained are consistent with the values reported in the literature.