Model Adaptation and Validation for Estimating Methane and Ammonia Emissions from Fattening Pig Houses: Effect of Manure Management System

• Published in: Animals (Basel) Vol. 14; no. 6; p. 964
• Main Authors: Sefeedpari, Paria, Pishgar-Komleh, Seyyed Hassan, Aarnink, Andre J A
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 20.03.2024; MDPI
• Subjects: Air quality management; Ammonia; ammonia emission; Analysis; Climate change; Drinking water; Emissions; Farms; Feeds; Hogs; Livestock; manure; Manures; Metabolism; Methane; methane emission; modelling; pig house; Swine; Urine; Netherlands; Germany; pig house; manure; methane emission; modelling; ammonia emission
• ISSN: 2076-2615; 2076-2615
• DOI: 10.3390/ani14060964

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 CH emission (18.5 and 4.3 kg yr per pig place) was in between the means from the continuous data from sensors (15.9 and 5.6 kg yr per pig place) and the means from the discrete measurements using the reference method (22.0 and 3.1 kg yr per pig place) for the LS and SS systems, respectively. The average calculated NH emission (2.6 and 1.4 kg yr per pig place) corresponded well with the continuous data (2.6 and 1.2 kg yr per pig place) and the discrete measurements using the reference method (2.7 and 1.0 kg yr 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.