Estimating Herd‐Scale Methane Emissions from Cattle in a Feedlot Using Eddy Covariance Measurements and the Carbon Dioxide Tracer Method

Abstract

Measurements of methane (CH4) emissions from ruminants could provide invaluable data to reduce uncertainties in the global CH4 budget and to evaluate mitigation strategies to lower greenhouse gas emissions. The main objective of this study was to evaluate a new CO2 tracer (CO2T) approach that combined CH4 and CO2 atmospheric concentrations with eddy covariance (EC) CO2 flux measurements to estimate CH4 emissions from cattle in a feedlot. A closed‐path EC system was used to measure CH4 and CO2 fluxes from a feedlot in Kansas. The EC flux measurements were scaled from landscape to animal scale using footprint analyses. Emissions of CH4 from the cattle were also estimated using the CO2T approach and measured CO2 and CH4 concentration, and scaled EC CO2 fluxes. The CH4 and CO2 concentration ratios showed a distinct diel trend with greater values during the daytime. Average monthly CH4 emission estimates using the CO2T approach ranged from 72 to 127 g animal−1 d−1, which was consistent with the values reported in other studies that had similar animal characteristics. The CO2T method CH4 emission estimates showed good agreement with scaled CH4 EC fluxes (slope = 0.9 and R2 = 0.8) for cold and dry months. However, the agreement between the two techniques was significantly reduced (slope = 1.5 and R2 = 0.6) during wet and warm months. On average, the CO2T method CH4 emission estimates were 3% greater than the EC CH4 emissions. Overall, our results suggest that the CO2T method can be used to estimate enteric feedlot CH4 emissions. Core Ideas The CO2 tracer method (CO2T) was used to estimate enteric CH4 emissions in a feedlot. The CO2T method estimates were in good agreement with eddy covariance (EC) measurements. The agreement between CO2T and EC method was reduced during the wet and warm months.

Methane efflux from an American bison herd

“…From this perspective, our simple seasonal scaling exercise may underestimate or overestimate methane emissions from bison grazing systems for multiple reasons that must be kept in mind when interpreting results. Methane emissions from cattle have been observed to be on the order of 10 %-17 % higher in summer than winter (Todd et al, 2014;Prajapati andSantos, 2018, 2019) such that our wintertime methane flux observations may be lower than what full annual measurements would yield. Our observations were similar to wintertime measurements of beef cattle in a feedlot, on the order of 75 g CH 4 per animal d −1 (Prajapati and Santos, 2019), which to a first order suggests that bison and cattle grazing systems may have similar methane efflux.…”

“…Footprint models of the type used here have been found to accurately estimate point sources of trace gas flux (Heidbach et al, 2017;Dumortier et al, 2019), but it is important to note that footprint modeling techniques play a large role in the spatial attribution of observed fluxes of ruminant trace gas flux (Felber et al, 2015). Prajapati and Santos (2018), for instance, found that an analytical model (Kormann and Meixner, 2001) predicted flux footprint areas 5 to 6 times larger than did an approximation of a Lagrangian dispersion model (Kljun et al, 2002) did such that footprint model uncertainty is a major source of uncertainty for measuring methane flux from multiple point sources as we also find here. Regarding the footprint model it is also important to note that emitted gas is warmer than the surrounding environment in our case.…”

“…Here, we measure methane flux from a bison herd on winter pasture using the eddy covariance technique (Dengel et al, 2011;Felber et al, 2015;Prajapati and Santos, 2018;Sun et al, 2015). We use flux footprint analyses combined with bison locations determined using automated cameras to estimate methane flux on a per-animal basis and discuss observations in the context of eddy covariance methane flux measurements from other ruminants.…”

“…Given that mean methane emissions were not significantly different from zero in the absence of bison -as detailed in "Results" -we assume that observed methane emissions are due to bison in the flux footprint. The relative contribution of bison to each 0.5 h eddy covariance measurement was calculated by expanding the approach of Dumortier et al (2019) (see also Prajapati and Santos, 2019) for multiple point sources. From the definition of the footprint function (e.g., Schmid, 1997), the measured density of a scalar X, F X , for our study area of 8 × 12 grid cells (Fig.…”

Livestock Agriculture Greenhouse Gases for Electricity Production: Recent Developments and Future Perspectives

“…With this method, technologies such as optimal sensors are employed to assess how gas and energy are exchanged, as well as the momentum between the different ecosystems [50]. However, to effectively use the method, knowledge of the total number of animals and their locations within the footprint is important.…”