|Rotz, Clarence - Al|
Submitted to: Proceedings of the American Society of Agricultural and Biological Engineers International (ASABE)
Publication Type: Proceedings
Publication Acceptance Date: 1/29/2008
Publication Date: 7/2/2008
Citation: Montes, F., Rotz, C.A., Chaoui, H. 2008. Process Modeling of Ammonia Volatilization from Ammonium Solution and Manure Surfaces. Proceedings: 2008 American Society of Agricultural and Biological Engineers International Meeting (ASABE). Providence, Rhode Island, June 29-July 2, 2008. ASABE Paper No. 083584. Interpretive Summary: An interpretivwe summary is not required.
Technical Abstract: Ammonia emissions occur from manure surfaces on the barn floor, during storage, and following field application. Based upon theoretical principles and associated published information on ammonia emission, relationships were refined for modeling the dissociation constant (Ka), Henry’s law constant (Kh) and mass transfer coefficient (hm) to better predict ammonia loss from manure surfaces. Refined expressions were obtained that relate these coefficients to the temperature, pH and electrical conductivity of the material, and the air speed over the material. Best estimates of parameters Ka and Kh in pure aqueous solutions were developed based on an extensive literature review. These estimates were extended to manure and other aqueous ammonium solutions by using electrical conductivity measurements to estimate appropriate activity coefficient corrections. Using the best estimates for Ka and Kh, together with these corrections for the interaction of ammonia and ammonium with other ions in solution, improved the prediction of ammonia volatilization from buffered ammonium-water solutions and dairy cattle manure under controlled laboratory conditions. The use of a theoretically-based mass transfer coefficient reported in the literature for similar dynamic conditions as those used in the laboratory experiments, was successfully used to predict measured ammonia volatilization rates, but only when best estimates for Ka and Kh together with adequate activity correction were included. Translating the conditions achieved in the laboratory to barn and manure storages is still needed. These process-based relationships will provide a basis for developing predictive tools that quantify management effects on ammonia emissions from farms and thus assist in the development and evaluation of strategies for reducing emissions.