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Ammonia Emissions from Anaerobic Swine Lagoons: Model Development

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  • a Laboratory of Applied Physical Chemistry, Faculty of Agricultural and Applied Biological Sciences, Ghent University, Ghent, Belgium
  • | b Southern Piedmont Conservation Research Unit, J. Phil Campbell Sr. Natural Resource Conservation Center, Agricultural Research Service, USDA, Watkinsville, Georgia
  • | c Department of Biological and Agricultural Engineering, North Carolina State University, Raleigh, North Carolina
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Abstract

Concentrated animal production may represent a significant source for ammonia emissions to the environment. Most concentrated animal production systems use anaerobic or liquid/slurry systems for wasteholding; thus, it is desirable to be able to predict ammonia emissions from these systems. A process model was developed to use commonly available measurements, including effluent concentration, water temperature, wind speed, and effluent pH. The developed model simulated emissions, as measured by micrometeorological techniques, with an accuracy that explains 70% of the variability of the data using average daily emissions and explains 50% of the variability of the data using 4-h average data. The process model did not show increased accuracy over a statistical model, but the deviations between model and measurement were distributed more evenly in the case of the process model than in the case of the statistical model.

Corresponding author address: Alex De Visscher, Laboratory of Applied Physical Chemistry, Faculty of Agricultural and Applied Biological Sciences, Coupure Links 653, Ghent B-9000, Belgium. alex.devisscher@rug.ac.be

Abstract

Concentrated animal production may represent a significant source for ammonia emissions to the environment. Most concentrated animal production systems use anaerobic or liquid/slurry systems for wasteholding; thus, it is desirable to be able to predict ammonia emissions from these systems. A process model was developed to use commonly available measurements, including effluent concentration, water temperature, wind speed, and effluent pH. The developed model simulated emissions, as measured by micrometeorological techniques, with an accuracy that explains 70% of the variability of the data using average daily emissions and explains 50% of the variability of the data using 4-h average data. The process model did not show increased accuracy over a statistical model, but the deviations between model and measurement were distributed more evenly in the case of the process model than in the case of the statistical model.

Corresponding author address: Alex De Visscher, Laboratory of Applied Physical Chemistry, Faculty of Agricultural and Applied Biological Sciences, Coupure Links 653, Ghent B-9000, Belgium. alex.devisscher@rug.ac.be

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