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United States Department of Agriculture

Agricultural Research Service

Research Project: INNOVATIVE ANIMAL MANURE TREATMENT TECHNOLOGIES FOR ENHANCED ENVIRONMENTAL QUALITY Title: Improved process model for ammonia volatilization from anaerobic swine lagoons under varying wind speeds and gas bubbling

Authors
item Ro, Kyoung
item Szogi, Ariel
item Vanotti, Matias
item Stone, Kenneth

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: November 9, 2007
Publication Date: March 3, 2008
Repository URL: http://hdl.handle.net/10113/19585
Citation: Ro, K.S., Szogi, A.A., Vanotti, M.B., Stone, K.C. 2008. Process model for ammonia volatilization from anaerobic swine lagoons incorporating varying wind speeds and gas bubbling. Transactions of the ASABE 51(1):259-270.

Interpretive Summary: Anaerobic swine lagoons are widely used for storage and treatment of liquid manure before land disposal. A major air quality concern with the this technology is the significant amounts of ammonia nitrogen volatilized into the atmosphere. Although many mathematical models have been used to predict ammonia emissions from anaerobic treatment lagoons, there is still a need for more accurate predictions. Challenges for accurate ammonia volatilization include three major factors: 1) lagoon water characteristics (ammonia concentration, solids content, and water temperature); 2) bubble formation due to microbial activities; and 3) weather conditions (wind speed and air temperature). We developed an improved mathematical model that for the first time incorporates the impacts of bubble formation and varying wind speed on the ammonia volatilization process. Therefore, our new mathematical model addresses all three major factors affecting the predictions. As a testing platform, we used the new model to predict seasonal ammonia emissions from farm scale data that was measured during one year period in three 1-ha swine lagoons with distinctly different manure management and water quality characteristics: i) traditional lagoon, ii) partially treated lagoon receiving flushed manure after liquid-solid separation, and iii) treated lagoon that received liquid manure after separation of solids and removal of N and P. Internal bubbling of the non-treated lagoon remarkably increased ammonia volatilization rate from the lagoon during warm seasons. The improved mathematical model accurately predicted the measured ammonia emissions in the three lagoon situations. Based on model theory and field measurements, we found that ammonia emission from swine lagoons would be significantly under-predicted if either bubbling-enhanced mass transport or variable wind are not taken into account. The new model not only provides more accurate predictions of ammonia emissions but also uses factors that can be conveniently constructed using easily obtained data.

Technical Abstract: Ammonia volatilization from treatment lagoons varies widely with the lagoon water total ammonia concentration, pH, temperature, suspended solids, atmospheric ammonia concentration above the water surface, and wind speed. Ammonia emissions were estimated with a process-based mechanistic model using ammonia chemistry of the lagoon and interfacial transport characteristics between air and water. This improved model incorporated the effect of internal bubble production and continuously variable wind speed on ammonia volatilization. The model made good seasonal ammonia emission predictions measured at three contrasting lagoon scenarios: i) non-treated lagoon, ii) partially pre-treated manure using solid-liquid separation; and iii) treated manure using combined solid-liquid separation with nitrogen and phosphorus removal from the liquid. The internal bubbling of the non-treated lagoon during warm seasons significantly increased its ammonia volatilization rate. Ammonia emission would be significantly under-predicted if bubbling-enhanced mass transport was not taken into account during warm seasons, as demonstrated by the improved process model and evidenced by the observed fluxes.

Last Modified: 11/22/2014
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