Abstract
A novel odor interaction model was proposed for binary mixtures of benzene and substituted benzenes by a partial differential equation (PDE) method. Based on the measurement method (tangent-intercept method) of partial molar volume, original parameters of corresponding formulas were reasonably displaced by perceptual measures. By these substitutions, it was possible to relate a mixture's odor intensity to the individual odorant's relative odor activity value (OAV). Several binary mixtures of benzene and substituted benzenes were respectively tested to establish the PDE models. The obtained results showed that the PDE model provided an easily interpretable method relating individual components to their joint odor intensity. Besides, both predictive performance and feasibility of the PDE model were proved well through a series of odor intensity matching tests. If combining the PDE model with portable gas detectors or on-line monitoring systems, olfactory evaluation of odor intensity will be achieved by instruments instead of odor assessors. Many disadvantages (e.g., expense on a fixed number of odor assessors) also will be successfully avoided. Thus, the PDE model is predicted to be helpful to the monitoring and management of odor pollutions.
Highlights
Odor measurement is essential for odor control and management, and odor sensory methods are normally employed except for some instrumental methods
A novel odor interaction model was proposed for binary mixtures of benzene and substituted benzenes
The binary odor mixture was explored in forms of partial differential equations (PDE) by simulating the measurement method of partial molar volume
Summary
Odor measurement is essential for odor control and management, and odor sensory methods are normally employed except for some instrumental methods. In the field of air pollution, most of related control standards mainly focus on the concentration limits of several targeted contaminants [2,3]. Several typical kinds of odor interaction (synergism, antagonism, averaging effect, etc.) have already been researched and reported in forms of various models [4,5] These models mainly focus on methods relating individual odorants to their joint odor property (i.e., odor quality, odor concentration and odor intensity). Several models have been proposed and they mainly focus on the relationship between the perceived odor intensity of a mixture and the individual odor intensities of its unmixed components [9]. In order to get rid of odor assessors, the individual odor intensities of each unmixed component in the above mentioned odor interaction models have to be displaced. OI can be better applied in the monitoring and management of odor pollution by combining with portable gas detectors and on-line monitoring systems
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