Biological Systems Engineering, Department of


Date of this Version

Winter 12-4-2009

Document Type



A DISSERTATION Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Doctor of Philosophy, Major: Interdepartmental Area of Engineering (Agricultural and Biological Systems Engineering); Under the Supervision of Professor Dennis D. Schulte
Lincoln, Nebraska: December, 2009
Copyright (c) 2009 Christopher G. Henry


This dissertation is organized as four stand-alone papers. Paper No. 1 describes the development of the Mask Scentometer and reports dilution ratios measured during use by twelve different people. Dilution ratios at the Mask Scentometer’s five dilution-to-threshold (D/T) settings were found to be 0.35, 1, 2, 4.5 and 18. In Paper No.’s 2 and 4, ambient odor assessment methods were compared in both controlled laboratory conditions and in the field. Laboratory analysis of ambient air samples using dynamic triangular forced-choice olfactometry (DTFCO) did not correlate well with any of the ambient odor assessment methods. Average intensity-predicted D/T was roughly five times higher than D/T measured using a Nasal Ranger®, and D/T obtained using a Nasal Ranger® was roughly two to five times higher than corresponding D/T from a Mask Scentometer. In Paper 3, odor intensity ratings and Mask Scentometer readings were used to calibrate the AERMOD dispersion model for predicting odor concentrations downwind of area sources. Dispersion of odor from a swine waste treatment lagoon and two cattle feedlots was modeled with AERMOD and the predictions were compared to the observations using a statistical approach to develop scaling factors. These were found to be 12 for odor intensity and 0.15 for the Mask Scentometer (although a scaling factor between 0.5 and 0.7 is also justified). Random effects and autocorrelation were found to be significant in ambient odor assessment data. In Paper 4, the dispersion of odors from a swine production building complex was studied. CALPUFF and AERMOD were used to predict short-time-step (one minute) odor concentrations. Source emission measurements and meteorological data were collected to coincide with ambient odor measurements obtained using the Nasal Ranger®, Mask Scentometer, field odor intensity ratings, and DTFCO. In general, odor concentrations predicted using CALPUFF were found to be about twice those predicted by AERMOD. Model predictions agreed best with the readings from the Nasal Ranger® and Mask Scentometer; and both of these ambient odor assessment methods are suited for ground truthing AERMOD and CALPUFF, although some model scaling factor adjustment is needed.

Adviser: Dennis D. Schulte