Todd RW, Cole NA, Waldrip HM, Aiken RM. Arrhenius equation for modeling feedyard ammonia emissions using temperature and diet crude protein.
JOURNAL OF ENVIRONMENTAL QUALITY 2013;
42:666-671. [PMID:
23673932 DOI:
10.2134/jeq2012.0371]
[Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Temperature controls many processes of NH volatilization. For example, urea hydrolysis is an enzymatically catalyzed reaction described by the Arrhenius equation. Diet crude protein (CP) controls NH emission by affecting N excretion. Our objectives were to use the Arrhenius equation to model NH emissions from beef cattle () feedyards and test predictions against observed emissions. Per capita NH emission rate (PCER), air temperature (), and CP were measured for 2 yr at two Texas Panhandle feedyards. Data were fitted to analogs of the Arrhenius equation: PCER = () and PCER = (,CP). The models were applied at a third feedyard to predict NH emissions and compare predicted to measured emissions. Predicted mean NH emissions were within -9 and 2% of observed emissions for the () and (T,CP) models, respectively. Annual emission factors calculated from models underestimated annual NH emission by 11% [() model] or overestimated emission by 8% [(,CP) model]. When from a regional weather station and three classes of CP drove the models, the () model overpredicted annual NH emission of the low CP class by 14% and underpredicted emissions of the optimum and high CP classes by 1 and 39%, respectively. The (,CP) model underpredicted NH emissions by 15, 4, and 23% for low, optimum, and high CP classes, respectively. Ammonia emission was successfully modeled using only, but including CP improved predictions. The empirical () and (,CP) models can successfully model NH emissions in the Texas Panhandle. Researchers are encouraged to test the models in other regions where high-quality NH emissions data are available.
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