A collaborative research effort by several institutions is investigating odor emissions from swine production facilities, and the impacts of those emissions on farm neighbours. Trained human receptors were used to measure the downwind odor concentrations from four tunnel ventilated swine barns near Story City, Iowa. Twenty-six measurement events were conducted between June and November 2004 and modeled using a specially coded short time-step version of CALPUFF to predict short time step durations. Source emission measurements and extensive meteorological data were collected along with ambient olfactometry analysis using the Nasal Ranger™ device (St. Croix Sensory, St. Paul MN). Approximately 64% of measured odor generally falls within the range of modeled values. Analysis of measured odor concentration and corresponding meteorology indicate that maximum ambient odor impacts occur with lower ambient temperature during non-turbulent conditions. Analysis of the data set did not yield a strong relationship directly (R2=0.33), but a regression analysis indicated that the modified CALPUFF model yielded a slope or scaling factor of 0.99, indicating overall a good relationship between model and observed. However, when the data is tested with the Spearman’s rank correlation coefficient an rs of 0.17 was calculated, indicating a poor rank correlation and was not significant (p=0.05). Statistical analysis is inconclusive as to whether the results have bias, but indicate large error in the results. Given that there were no scaling or peak to mean ratio adjustments to the model predictions, the results are very promising for predicting odors using CALPUFF.