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Updated: May 13, 2026

The Use of an Automated System GreenFeed to Monitor Enteric Methane and Carbon Dioxide Emissions from Ruminant Animals
Published on: September 7, 2015
Model Adaptation and Validation for Estimating Methane and Ammonia Emissions from Fattening Pig Houses: Effect of
Paria Sefeedpari1, Seyyed Hassan Pishgar-Komleh1, Andre J A Aarnink1
1Wageningen Livestock Research, Wageningen University and Research, P.O. Box 135, 6700 AC Wageningen, The Netherlands.
Abstract:
This paper describes a model for the prediction of methane and ammonia emissions from fattening pig houses. This model was validated with continuous and discrete measurements using a reference method from two manure management systems (MMS): long storage (LS) in deep pits and short storage (SS) by daily flushing of a shallow pit with sloped walls and partial manure dilution. The average calculated methane and ammonia emissions corresponded well with the measured values. Based on the calculated and measured results, the average calculated CH4 emission (18.5 and 4.3 kg yr-1 per pig place) was in between the means from the continuous data from sensors (15.9 and 5.6 kg yr-1 per pig place) and the means from the discrete measurements using the reference method (22.0 and 3.1 kg yr-1 per pig place) for the LS and SS systems, respectively. The average calculated NH3 emission (2.6 and 1.4 kg yr-1 per pig place) corresponded well with the continuous data (2.6 and 1.2 kg yr-1 per pig place) and the discrete measurements using the reference method (2.7 and 1.0 kg yr-1 per pig place) from LS and SS, respectively. This model was able to predict the reduction potential for methane and ammonia emissions by the application of mitigation options. Furthermore, this model can be utilized as a predictive tool, enabling timely actions to be taken based on the emission prediction. The upgraded model with robust calculation rules, extensive validations, and a simplified interface can be a useful tool to assess the current situation and the impact of mitigation measures at the farm level.
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