Combining the Eddy Covariance Method and Dry Matter Intake Measurements for Enteric Methane Emission Estimation from Grazing Dairy Cows

• Published in: Atmosphere 2024-11, Vol.15 (11), p.1269
• Main Authors: Eismann, Marie-Sophie R., Smit, Hendrik P. J., Poyda, Arne, Loges, Ralf, Kluß, Christof, Taube, Friedhelm
• Format: Article
• Language: English
• Subjects: Agricultural industry; Biomass; Cattle; Climate change; climate smart agriculture; Covariance; Cow's milk; Dairy cattle; Dry matter; eco-efficiency; Eddies; Eddy covariance; Emission measurements; Emissions; Emissions control; Environmental aspects; Environmental assessment; Environmental impact; Farm buildings; Feed quality; Feeds; Fermentation; Fluxes; Food and nutrition; Global positioning systems; GPS; Grazing; greenhouse gas mitigation; Greenhouse gases; Intergovernmental Panel on Climate Change; low-input system; Methane; Methane emissions; Methods; Milk; Milk production; Mitigation; Pasture; Precipitation; sustainable agriculture; Trace gases; Vortices
• ISSN: 2073-4433; 2073-4433
• DOI: 10.3390/atmos15111269

Effective greenhouse gas mitigation strategies in the agricultural sector are crucial for reducing emissions. Methane (CH4) emissions associated with agriculture are predominantly the result of enteric fermentation from ruminant production systems. Accurate measurement of these emissions is essential for assessing environmental impacts and developing effective mitigation strategies. The eddy covariance (EC) method is widely used to measure trace gas and energy fluxes and has since also been adapted to measure enteric CH4 emissions from grazing ruminants effectively. This study combined EC measurements of CH4 emissions from pasture-based Jersey cows with milk production, feed intake data and CH4 prediction equations during four measurement campaigns between September and November 2022 in northern Germany. Cows’ distance relative to the EC station was controlled by a specialized fencing system and its effect on the measured CH4 fluxes was adjusted by means of footprint (FP) flux allocation based on a two-dimensional FP model. The EC method presented very low daily emissions of 205 g CH4 cow−1 day−1, below the estimations based on the Intergovernmental Panel on Climate Change (IPCC) Tier 2 default values and other equations based on feed intake and feed quality parameters. The results of this study indicated that the EC method, in combination with a specialized fencing design, is an appropriate method to measure enteric CH4 emissions of dairy cows in pasture-based systems. Moreover, this study showed that a comprehensive dataset of animal-related data is a practical tool to contextualize the results.