DETERMINATION OF ODOR SOURCES FOR CONTROL
The successful solution of odor pollution problems first requires an assessment of the nature and extent of the problems. A plant or facility that emits odor from a single source (such as ii stack or vent) requires less effort than a plant with a variety of odor sources that may number in the hundreds. In the latter case, there is a need to assess the problem in such terms as to achieve maximum reduction in odor at a minimal control cost. Quantitative and accurate measurements of the various emission sources and their contribution to the odor in the ambient air must be determined in order to identify and rank the various sources that should receive priority for control. Accurate measurements of odor strength relative to concentration are also useful for defining the degree of control necessary for the single-source situation. Attempts to relate source odor measurements with ambient odors by the use of diffusion equations have met with varying degrees of success.1.2 Wohlers,l utilizing an evacuated bulb technique for sampling stack gases from a petroleum coking plant, a kralt paper mill, an anion-garlic dehydrating plant, and a rotogravure printing plant, found that odor measurements at the stacks did not agree in all cases with the calculated dilutions at the distances in the field where the odors were noted. Hogstrom2 demonstrated that a fluctuating plume dispersion model can be used to give realistic estimates of odor frequencies around a point source when the odor thresholds of the chimney gases (sulphate pulp factory) are determined by sampling and sensory methods described by Lindvall.3 Our experience in sampling and evaluating odors has indicated that existing sampling techniques such as ASTM syringe method have seriously underestimated the magnitude of odors emitted by a factor in the range of 2OO-2O,OOO.4 We believe that inadequate sampling and evaluation techniques are the major reasons for reported “failures” of dispersion estimates in predicting ambient odors. In our technique, we use trained odor chemists to carry out odor surveys of the surrounding areas to define the odor types and intensities perceived off-site and to conduct in-plant surveys to identify all significant odor sources. T o supplement this, we have developed a source-sampling detailed laboratory odor-evaluation technique to allow comparison of the various odor sources and to make use of predictions based on dispersion equations. We have observed reasonably good correlation between predicted odor intensities from the source analyses determined in the laboratory and those observed by our analysts in the field. OFF-SITE SURVEY
Analysis of odor compounds in feces of mice that were exposed to various stresses during breeding.
In order to provide healthy experimental animals, it is important to find and remove animals that have been accidentally exposed to various stresses during breeding. This study focuses mouse health-care management. Here we used human olfaction and gas chromatography-mass spectrometry to assess odor intensity and determine the concentrations of odor components. The feces were collected from mice that were exposed to 4 different stresses (no bedding chips, shaking, fasting, and movement restriction). These stresses caused a change in odor intensity as assessed by 6 panelists. Seventeen components were identified as dominant components in the odor that was emitted from feces. The concentration of each compound was converted to relative values versus its odor threshold levels in order to select ones effective for the quality of the odor. As a result, 12 selected components were found to be a useful set for the recognition of mice bred under different stress conditions. The present results may provide useful information for the development of standard fecal odor materials that may be used for the training of mouse care personnel.
Statistical Properties of a Fluctuating Plume Dispersion Model
A mathematical model of continuous source, turbulent dispersion has been presented and rationalized. This differs from those now in use in that provision is made for fluctuations of the plume to occur, by separating the total plume dispersion into two components, spreading and meandering. Various properties of the resulting material concentration distribution are then deduced. The mean concentration distribution derived from the fluctuating plume model is identical with the material distribution in present, steady plume models. Other important properties can also be derived, particularly the variance of point concentrations, and the frequency distribution of point concentrations, that do not follow from present plume models. The fluctuating plume model, in this way, provides a rational approach to practical air pollution problems that depend on concentration properties other than the mean level of concentration. Two independent dispersion parameters are involved; that describing the instantaneous dispersion, or spreading, of a plume element and that describing the overall dispersion, or meandering, of the plume centre relative to the fixed x-axis. These are identified with dispersion functions discussed theoretically by Batchelor, Brier, and Taylor. As far as the mean concentration distribution is concerned, dispersion coefficients of the fluctuating plume model have an immediate interpretation in terms of the steady plume models of Sutton, and Frenkiel (or of any other, essentially Gaussian plume dispersion model). Because of the variety of predictions concerning various statistical properties of the fluctuating plume model, many observed characteristics of concentration statistics, so far largely ignored in practical pollution studies, may now be related to dispersion. These include the form, and location and intensity of the maximum point, of the concentration frequency distribution, the variance of the distribution, and so on. A small amount of detailed concentration data is available for comparison with the fluctuating plume model. These permit verification of certain of the predicted features, particularly the form of the concentration frequency distribution, and the behaviour of its maximum point as a function of atmospheric stability and dispersion time. The form of the ratio of peak to average concentration values, as a function of dispersion time, also follows from the fluctuating plume model and is verified by comparison with concentration data.