In two parts, this thesis examined the perception of odour mixtures by humans. Several experiments were carried out and results shown. Part 1 established that peripheral interaction in the form of competition for transduction pathway resources is not of primary importance in determining the perceptual characteristics of odour mixtures. Other peripheral mechanisms, central factors and limitations in human cognitive processing would also appear to play an important role.Taking into account the temporal processing results found in Part 1, Part 2 sought to establish the capacity of humans to analyse odour mixtures in greater than two components in terms of the perceived order of components, and the identity of those components. Overall, the research demonstrated that two properties of simple binary odour mixtures, namely the temporal order and perceived strengths of components, are not primarily characterised by the transduction pathway those components putatively operate in human ORNs. / Doctor of Philosophy (PhD)

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The sense of smell is a primal sense for humans as well as animals.In everyday life the smells encountered are composed of dozens, even hundreds of odors; few arise from a single odorant. Enormous numbers of odors occur due to the vast variation in the concentration, size and structure of odorant molecules that makes olfaction differ from simpler visual or auditory dimensions. Accordingly, little is known about the ways in which changes in molecular structure and concentration of individual odorants change odor quality. Also, currently not much is understood about synergism/antagonism, how one odorant masks or suppresses another in mixtures and there is no method for predicting which odor will be suppressed. The two main objectives of this thesis were to determine whether a part of a molecular structure rather than the whole structure plays a key role in odor quality and whether a key part of a molecule can be used to choose antagonists for that odorant. For this study three classes of musks and two potential antagonists were used. The results of the study are discussed in some detail. It is concluded that future studies of the importance of molecular structure in mixture interactions require substantially more information on the relation between structure and odor quality to allow systematic studies to be developed. In summary the two hypotheses investigated were not supported by the results. Importantly, however, they do support the view that it is likely that odor quality is dependent on the whole structure of an odorant not a single feature. / Master of Science (Hons)

Odour emissions and instantaneous downwind odour plumes were measured on two 3000-sow swine farrowing farms located in a flat area of southern Manitoba, one farm (Farm A) with open earthen manure storage (EMS) and another (Farm B) with negative air pressure (NAP) covered EMS. Three commonly used dispersion models (ISCST3, AUSPLUME, and INPUFF-2) were used to predict downwind odour distributions on the two farms. Dispersion predictions were based on the measured odour emission data for each farm and on-site weather data recorded by a portable weather station. The peak-to-mean ratios of downwind odour intensity were computed from field odour intensity measurements and analysed against averaging time, downwind distance, and atmosphere stability class. It was found that the average odour emission rate from the negative pressure covered earthen manure storage (NAP EMS) was negligible in comparison with the open EMS (0.3 vs 20.3 OU/ s-m2). Downwind odour intensity measured by trained human sniffers on Farm A with covered manure storage was significantly (P<0.05) lower than that on Farm B with open manure storage at 100 and 500 m, but the difference in odour intensity at 1000 m was not significant (P>0.05) between the two farms. A 46% difference in odour emission rate between Farms A and B resulted in a 14% difference in the separation distance for odour annoyance-free between the two farms. When three commonly used dispersion models, namely AUSPLUME, ISCST3, and INPUFF-2, were used to predict downwind odour from the farms, the percentage of agreement between model predictions and field measurements was adequate for downwind distances of 500 and 1000 m, but relatively low for 100 m for all three models. Since the long-distance (>1000 m) predictions are of more practical value, all three models were considered to be adequate in predicting odour downwind from the swine operations. The peak-to-mean ratios of downwind odour intensity were computed from field odour intensity measurements and analysed against averaging time, downwind distance, and atmospheric stability class. The peak-to-mean ratio of field odour intensity increases with averaging time and downwind distance, and unstable atmospheric conditions.

Odour emissions and instantaneous downwind odour plumes were measured on two 3000-sow swine farrowing farms located in a flat area of southern Manitoba, one farm (Farm A) with open earthen manure storage (EMS) and another (Farm B) with negative air pressure (NAP) covered EMS. Three commonly used dispersion models (ISCST3, AUSPLUME, and INPUFF-2) were used to predict downwind odour distributions on the two farms. Dispersion predictions were based on the measured odour emission data for each farm and on-site weather data recorded by a portable weather station. The peak-to-mean ratios of downwind odour intensity were computed from field odour intensity measurements and analysed against averaging time, downwind distance, and atmosphere stability class. It was found that the average odour emission rate from the negative pressure covered earthen manure storage (NAP EMS) was negligible in comparison with the open EMS (0.3 vs 20.3 OU/ s-m2). Downwind odour intensity measured by trained human sniffers on Farm A with covered manure storage was significantly (P<0.05) lower than that on Farm B with open manure storage at 100 and 500 m, but the difference in odour intensity at 1000 m was not significant (P>0.05) between the two farms. A 46% difference in odour emission rate between Farms A and B resulted in a 14% difference in the separation distance for odour annoyance-free between the two farms. When three commonly used dispersion models, namely AUSPLUME, ISCST3, and INPUFF-2, were used to predict downwind odour from the farms, the percentage of agreement between model predictions and field measurements was adequate for downwind distances of 500 and 1000 m, but relatively low for 100 m for all three models. Since the long-distance (>1000 m) predictions are of more practical value, all three models were considered to be adequate in predicting odour downwind from the swine operations. The peak-to-mean ratios of downwind odour intensity were computed from field odour intensity measurements and analysed against averaging time, downwind distance, and atmospheric stability class. The peak-to-mean ratio of field odour intensity increases with averaging time and downwind distance, and unstable atmospheric conditions.

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