Measurement and Modeling Ammonia Emissions from Broiler Litter

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Title: Measurement and Modeling Ammonia Emissions from Broiler Litter
Author: Liu, Zifei
Advisors: Peter Bloomfield, Committee Member
Sanjay Shah, Committee Member
David Beasley , Committee Co-Chair
Lingjuan Wang, Committee Chair
Abstract: Ammonia is a very important atmospheric pollutant. Agricultural activities, livestock production in particular, have been reported to be the largest contributor of ammonia emissions into the atmosphere. Accurate estimation of ammonia emission rate from individual operations or sources is important and yet a challenging task for both regulatory agencies and animal producers. The overall research objective of this study was to develop an emission model which can be used to estimate ammonia emission from broiler litter. In the reported model, the ammonia flux is essentially a function of the litter's total ammoniacal nitrogen (TAN) content, moisture content, pH, and temperature, as well as the Freundlich partition coefficient (Kf), mass transfer coefficient (KG), ventilation rate (Q), and emission surface area (A). A dynamic flow-through chamber system and a wind tunnel were designed to measure ammonia fluxes from broiler litter. The dynamic flow-through chamber experiments evaluated the reported model with various litter samples under a constant temperature and wind profile. The wind tunnel experiments evaluated the reported model under various temperatures and wind profiles. Model parameters such as Kf and KG were estimated. The results from the two experiments were consistent with each other. The estimated KG ranged from 1.11 to 27.64 m h-1, and the estimated Kf ranged from 0.56 to 4.48 L kg-1. Regression sub-models were developed to estimate Kf as a function of litter pH and temperature and to estimate KG as a function of air velocity and temperature. Sensitivity analysis of the model showed that ammonia flux is very sensitive to litter pH and to a lesser extent temperature. A validation metric based on the mean and covariance in the measurement and in the model parameters were used to validate the ammonia emission model in the presence of measurement and model parameter uncertainties.
Date: 2009-12-03
Degree: PhD
Discipline: Biological and Agricultural Engineering

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