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Nutritional and Environmental Effects on Ammonia Emissions from Dairy Cattle Housing: A Meta-Analysis

Adeline Bougouin, April Leytem, Jan Dijkstra, Robert S. Dungan, Ermias Kebreab
Journal of environmental quality 2016 v.45 no.4 pp. 1123-1132
United States Environmental Protection Agency, ammonia, barns, cattle housing, crude protein, dairy cows, data analysis, dry matter accumulation, dry matter intake, emissions, environmental factors, excretion, humans, inventories, manure handling, meta-analysis, milk consumption, milk yield, models, nitrogen, nitrous oxide, odors, prediction, urine, United States
Nitrogen excreted in dairy manure can be potentially transformed and emitted as NH₃, which can create livestock and human respiratory problems and be an indirect source of N₂O. The objectives of this study were to: (i) investigate environmental factors influencing NH₃ emissions from dairy housing; and (ii) identify key explanatory variables in the NH₃ emissions prediction from dairy housing using a meta-analytical approach. Data from 25 studies were used for the preliminary analysis, and data from 10 studies reporting 87 treatment means were used for the meta-analysis. Season and flooring type significantly affected NH₃ emissions. For nutritional effect analysis, the between-study variability (heterogeneity) of mean NH₃ emission was estimated using random-effect models and had a significant effect (P < 0.01). Therefore, random-effect models were extended to mixed-effect models to explain heterogeneity regarding the available dietary and animal variables. The final mixed-effect model included milk yield, dietary crude protein, and dry matter intake separately, explaining 45.5% of NH₃ emissions heterogeneity. A unit increase in milk yield (kg d⁻¹) resulted in a 4.9 g cow⁻¹ d⁻¹ reduction in NH₃ emissions, and a unit increase in dietary crude protein content (%) and dry matter intake (kg d⁻¹) resulted in 10.2 and 16.3 g cow⁻¹ d⁻¹ increases in NH₃ emissions, respectively, in the scope of this study. These results can be further used to help identify mitigation strategies to reduce NH₃ emissions from dairy housing by developing predictive models that could determine variables with strong association with NH₃ emissions.