Author
Todd, Richard | |
Cole, Noel | |
Clark, Ray |
Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only Publication Acceptance Date: 8/30/2009 Publication Date: 11/1/2009 Citation: Todd, R.W., Cole, N.A., Clark, R.N. 2009. Diel and seasonal dynamics of ammonia emissions from cattle feedyards [abstract]. 2009 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America International Annual Meetings, November 1-5, 2009, Pittsburgh, Pennsylvania. 2009 CDROM. Interpretive Summary: Technical Abstract: Ammonia emitted from cattle feedyards is a major loss of nitrogen, ranging from 30% to 70% of nitrogen fed to animals. Ammonia emissions follow patterns that operate at different time scales in response to environmental conditions, including temperature, precipitation, wind, and atmospheric stability. Continuous measurement of atmospheric ammonia concentration using open path spectroscopy combined with an inverse dispersion model were used to estimate ammonia emissions from two Southern High Plains beef cattle feedyards on time scales ranging from 15 min to mean seasonal emissions. Diel emissions showed a typical pattern of lowest rates during nighttime between midnight and sunrise and highest rates peaking near midday. Nighttime emission rates in winter averaged 0.18 kg NH3/min, while spring, summer, and autumn nighttime emission rates averaged 0.67, 0.56, and 0.53 kg/min, respectively. Peak mean ammonia emission rates ranged from 1.33 kg/min during winter to 2.28 kg/min during summer. Summer daily emissions were about twice those during winter. Spring and autumn emission rates were intermediate between summer and winter, while spring emissions tended to be greater than autumn emissions because of greater manure nitrogen present during spring. Temperature was a major factor determining the magnitude of emissions. Understanding the dynamics of ammonia emissions from cattle feedyards will help better quantify emission rates and emission factors, and yield insights to aid process modeling of ammonia emissions. |