A livestock odor dispersion model (LODM) was developed to predict mean odor concentration, odor frequency, instantaneous odor concentration, and peak odor concentration from livestock operations. This model is based on the Gaussian fluctuating plume model and has the ability to consider the instantaneous concentration fluctuations and the differences between odor and traditional air pollutants. It can predict odor frequency from the routine hourly meteorological data input and deal with different types of sources and multiple sources. Also, the relationship between odor intensity and odor concentration was incorporated into the model. INTRODUCTIONResearchers have used industrial air dispersion models to predict livestock odors downwind of livestock operations since the 1980s. The main drawback of these industrial air dispersion models is that most of them can only calculate long time average concentration. However, a series of short exposures to detectable odors can cause nuisances and generate community complaints although the hourly averaged concentrations remain at very low or undetectable levels (Ͻ1 odor unit [OU]/m

A livestock odor dispersion model (LODM) was developed to predict odor concentration and odor frequency using routine hourly meteorological data input. The odor concentrations predicted by the LODM were compared with the results obtained from other commercial models (Industrial Source Complex Short-Term model, version 3, CALPUFF) to evaluate its appropriateness. Two sets of field odor plume measurement data were used to validate the model. The model-predicted mean odor concentrations and odor frequencies were compared with those measured. Results show that this model has good performance for predicting odor concentrations and odor frequencies.

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