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

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.

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Publication Details

Journal
Atmosphere
Published
2024-10-24
DOI
https://doi.org/10.3390/atmos15111269
Citations
2
Primary Topic
Plant Water Relations and Carbon Dynamics
Type
article
Field-Weighted Citation Impact
0.57

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article

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

F. Taube, Ralf Loges, Arne Poyda, Christof Kluß et al.
2 citations
Atmosphere
Plant Water Relations and Carbon Dynamics
0.57
article

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

F. Taube, Ralf Loges, Arne Poyda, Christof Kluß, Hendrik P. J. Smit, Marie-Sophie R. Eismann
article en
2 citations

Abstract

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.

AtmosphereVol. 15(11)
Stellenbosch University (ZA), Christian-Albrechts-Universität zu Kiel (DE)
Gesellschaft für Energie und Klimaschutz Schleswig-Holstein
Openalex Percentile: Top 33%
Plant Water Relations and Carbon Dynamics
0.57
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