Development of dispersion-based setback distance guidelines for Manitoba

Team:

Project leader: Qiang Zhang, Dept. Biosystems Engineering
Z. Gao, Division of Environmental Engineering, University of Saskatchewan
A. La, Department of Biosystems Engineering, University of Manitoba
H. Guo, Department of Chemical and Biological Engineering, University of Saskatchewan

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EXECUTIVE SUMMARY

Maintaining adequate separation (setback) distances is the simplest, effective way of dealing with odour from hog operations. However, determining the “right” setback distances is challenging. Large distances would negatively affect the development of hog industry, whereas insufficient distances could cause the neighbours to complain. Current methods of estimating setback distances are either experience-based or dispersion-based. While the experience-based methods are still commonly used, the dispersion-based methods have shown the advantages and are gaining wider acceptance. The goal of this study was to develop a dispersion-based odour impact assessment tool (OIAT) for determining setback distances.

The OIAT was developed by integrating three key elements: i) defining odour acceptability at community level; ii) estimating odour emission; and iii) predicting odour exposure by dispersion modelling. The OIAT developed in this study is different from the “traditional” setback distance models; it assesses the region of odour impact instead of just specifying a fixed setback distance. For example, if the distance between a residence/community and the hog operation is known, the OIAT may be used to assess the level of odour impact on the residence/community. The OIAT allows the user to specify an odour acceptable level, and then plots a map of odour impact region from which the directional setback distances can be determined. The setback distances calculated by the OIAT compared reasonably well with the Manitoba, Saskatchewan and Alberta guidelines.

A critical element in developing setback distance models is to define the acceptable odour level (exposure). In this study, extensive face-to-face interviews were conducted with residents living nearby hog operations. The level of odour tolerance (or annoyance) was quantified by the percentage of interviewed residents who did not complain about odour. This percentage reflected the odour tolerance at the community level. A mathematical model was then developed to correlate the community odour tolerance level to the odour exposure (odour hours) predicted by dispersion models (CALPUFF and AERMOD). It is interesting to note that only about 87% of residents would not complain about odour when the odour hours predicted by the dispersion models was zero (0). This implies that it was very possible some residents would complain about hog odour even if their exposure to odour was zero or close to zero. It was also found through interview that a large percentage of residents who did not complained about the current odour level indicated that they would not tolerate the same odour level from a new hog facility.