Using the eddy covariance technique to measure gas exchanges in a beef cattle feedlot - Prajapati, Prajaya (Kansas State University, 2018)
Measurements of methane (CH₄) emissions from livestock production could provide invaluable data to reduce uncertainties in the global CH₄ budget and to evaluate mitigation strategies to lower greenhouse gas (GHG) emissions. The eddy covariance (EC) technique has recently been applied as an alternative to measure CH₄ emissions from livestock systems, but heterogeneities in the source area and fetch limitations impose challenges to EC measurements. The main objectives of this study were to: 1) assess the performance of a closed-path EC system for measuring CH₄, CO₂, and H₂0 fluxes; 2) investigate the spatial variability of the EC fluxes in a cattle feedlot using flux footprint analysis; 3) estimate CH₄ emission rates per animal (Fanimal) from a beef cattle feedlot using the EC technique combined with two footprint models: an analytical footprint model (KM01) and a parametrization of a Lagrangian dispersion model (FFP); and 4) compare CH₄ emissions obtained using the EC technique and a footprint analysis with CH₄ emission estimates provided by a well-stablished backward-Lagrangian stochastic (bLS) model. A closed-path EC system was used to measure CH₄, CO₂, and H₂0 fluxes. To evaluate the performance of this closed-path system, a well-stablished open-path EC system was also deployed on the flux tower to measure CO₂ and H₂0 exchange. Methane concentration measurements and wind data provided by that system were used to estimate CH₄ emissions using the bLS model. The performance assessment that included comparison of gas cospectra and measured fluxes from the two EC systems showed that the closed-path system was suitable for the EC measurements. Flux values were quite variable during the field experiment. A one-dimensional flux footprint model was useful to interpret some of the flux temporal and spatial dynamics. Then, a more comprehensive data analysis was carried out using two-dimensional footprint models (FFP and KM01) to interpret fluxes and scale fluxes measured at landscape to animal level. The monthly average Fanimal, calculated using the footprint weighed stocking density ranged from 83 to 125 g animal⁻¹ d⁻¹ (KM01) and 75–114 g animal⁻¹ d⁻¹ (FFP). These emission values are consistent with the results from previous studies in feedlots however our results also suggested that in some occasions the movement of animals on the pens could have affected CH₄ emission estimates. The results from the comparisons between EC and bLS CH₄ emission estimates show good agreement (0.84; concordance coefficient) between the two methods. In addition, the precision of the EC as compared to the bLS estimates was improved by using a more rigorous fetch screening criterion. Overall, these results indicate that the eddy covariance technique can be successfully used to accurately measure CH₄ emissions from feedlot cattle. However, further work is still needed to quantify the uncertainties in Fanimal caused by errors in flux footprint model estimates and animal movement.
Keywords: Feedlot cattle methane emission measurement; Eddy covariance; Backward Lagrangian Stochastic model; Flux scaling; Flux footprint