Improved temporal resolution in process-based modelling of agricultural soil ammonia emissions

• Published in: Atmospheric environment (1994) 2008-05, Vol.42 (14), p.3253-3265
• Main Authors: Beuning, J.D., Pattey, E., Edwards, G., Van Heyst, B.J.
• Format: Article
• Language: English
• Subjects: Ammonia volatilization; Analysis methods; Applied sciences; Atmospheric pollution; Bare soil; Dispersed sources and other; Exact sciences and technology; Pollution; Pollution sources. Measurement results; Process-based model; Slurry application; Total ammoniacal nitrogen
• ISSN: 1352-2310; 1873-2844
• DOI: 10.1016/j.atmosenv.2007.04.057

An emerging environmental issue in Canada is how to quantify the contribution of agricultural soil emissions of ammonia (NH 3) to environmental pollution. Emission inventories are essential to predict these emissions and their subsequent atmospheric transportation, transformation, and deposition. Due to the high spatial and temporal variability associated with NH 3 emissions, emission inventories based on measurements become expensive and emission factors lose accuracy. Process-based models are capable of accounting for the complex soil interactions, but current models lack temporal refinement and few models consider NH 3 emissions. This paper presents the development of a one-dimensional (vertical), time-dependent model capable of predicting NH 3 emissions from a slurry applied to a bare soil. The model is based on chemical, physical and biological relationships that govern soil heat, moisture, and nitrogen movement. Processes considered include convection, diffusion, decomposition, nitrification, denitrification, and surface to atmosphere transport. The model is tested with experimental data from Agriculture and Agri-Food Canada which conducted NH 3 measurements following application of dairy cattle slurry to a bare field. An investigation into the sensitivity of emissions to pH and slurry infiltration rate is conducted and model predictions are best fit to measurements based on this investigation. Testing demonstrated the model's ability to predict the large NH 3 emissions immediately following application and subsequent emission trends associated with diurnal patterns that emission factors cannot capture. Results showed that model performance could benefit from a more in depth measurement program and empirical or process models of surface pH. Potential exists for the model to become a useful tool in predicting emissions on local, regional, or national scales.