Evaluation of commercial air dispersion models for livestock odour dispersion simulation
Date
2006-12
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
ORCID
Type
Degree Level
Masters
Abstract
The public nuisance and health concerns caused by odours from livestock facilities are among the key issues that affect neighbouring communities and the growth of the livestock industry across Canada. A setback distance is the common regulatory practice to reduce odour impact on the neighbouring areas. The air dispersion modeling method may be a more accurate tool for establishing setback distances since it considers site-specific airborne emissions, such as odour and gases from the animal production site as well as weather conditions and then estimates a concentration of the pollutant (odour, ammonia, etc.). Although various dispersion models have been studied to predict odour concentration from agricultural sources, limited field data exist to evaluate their applicability in agricultural odour dispersion. Thus, the purpose of this project was to evaluate the selected commercial air dispersion models with field plume measurements from swine operations. Firstly, this thesis describes a sensitivity analysis of how the climatic parameters affect model simulations for four selected air dispersion models, ISCST3, AUSPLUME, CALPUFF, and CALPUFF. Under the steady state weather condition, mixing height had no effect on the livestock odour dispersion, while atmospheric stability, wind speed and wind direction had great effect on the livestock odour dispersion. Ambient temperature had a moderate effect compared with other parameters. Under variable weather conditions, the predicted odour concentrations were much lower than the results under steady state weather conditions. A series of comparisons between model predictions of the same four models and field odour measurements were conducted. When using the livestock odour plume measurement data from University of Manitoba, three equations were used to convert the model predicted odour concentration to field measured odour intensity. The equations did not predict odour intensity very well. No model showed obvious better performance than the others. Scaling factors did not improve the results considerably. When using the odour plume measurement data from University of Minnesota, INPUFF2 performed better than CALPUFF. Scaling factors did improve the modeled results. When using the odour plume measurement data from University of Saskatchewan, INPUFF2 also performed better than CALPUFF. Scaling factors were still useful for the results improvements.Finally, because CALPUFF is the US EPA preferred model and predicted the highest values under variable weather conditions in the sensitivity study, we used it to simulate odour plumes on selected three swine sites using hourly weather data from 1993 to 2002 in Yorkton, Saskatchewan. The maximum predicted distance were 2.9 km for 1 OU, which was lower than the recommended maximum setback distance of 3.2 km. It is recommended that the variable weather conditions be used in the setback distance determination. CALPUFF is the preferred model and INPUFF2 is another option for field odour plume simulation, however scaling factors are needed to bring the model predictions close to the field measured results. Because the models evaluated were not developed for odour dispersion simulation, a model that can accurately predict livestock odour dispersion should be developed to take into account of the difference between odour and gas and wind direction shifts within the simulation time interval.
Description
Keywords
odour, Air dispersion model, simulation
Citation
Degree
Master of Science (M.Sc.)
Department
Agricultural and Bioresource Engineering
Program
Agricultural and Bioresource Engineering