Modelling of manure production by pigs and NH3, N2O and CH4 emissions. II. Effect of animal housing, manure storage and treatment practices

• Published in: Animal (Cambridge, England) Vol. 4; pp. 1413 - 1424
• Main Authors: Rigolot, C, Espagnol, S, Robin, P, Hassouna, M, Béline, F, Paillat, J.M, Dourmad, J.Y
• Format: Journal Article
• Language: English
• Published: 2010
• Subjects: ammonia; animal housing; animal manure management; carbon dioxide; composting; environmental factors; floors; gas emissions; greenhouse gases; litter (bedding); mathematical models; methane; nitrous oxide; odor control; odor emissions; pig manure; probabilistic models; simulation models; storage conditions; swine; waste management
• ISSN: 1751-7311; 1751-732X

A model has been developed to predict pig manure evolution (mass, dry and organic matter, N, P, K, Cu and Zn contents) and related gaseous emissions (methane (CH4), nitrous oxide (N2O) and ammonia (NH3)) from pig excreta up to manure stored before spreading. This model forms part of a more comprehensive model including the prediction of pig excretion. The model simulates contrasted management systems, including different options for housing (slatted floor or deep litter), outside storage of manure and treatment (anaerobic digestion, biological N removal processes, slurry composting (SC) with straw and solid manure composting). Farmer practices and climatic conditions, which have significant effects on gaseous emissions within each option, have also been identified. The quantification of their effects was based on expert judgement from literature and local experiments, relations from mechanistic models or simple emission factors, depending on existing knowledge. The model helps to identify relative advantages and weaknesses for each system. For example, deep-litter with standard management practices is associated with high-greenhouse gas (GHG) production (+125% compared to slatted floor) and SC on straw is associated with high NH3 emission (+15% compared to slatted floor). Another important result from model building and first simulations is that farmer practices and the climate induce an intra-system (for a given infrastructure) variability of NH3 and GHG emissions nearly as high as inter-system variability. For example, in deep-litter housing systems, NH3 and N2O emissions from animal housing may vary between 6% and 53%, and between 1% and 19% of total N excreted, respectively. Thus, the model could be useful to identify and quantify improvement margins on farms, more precisely or more easily than current methodologies.