title: An odor interaction model of binary odorant mixtures by a partial differential equation method.
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.
authors.affiliation: School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Xueyuan Road 30, Haidian District, Beijing 100083, China. yanluchun@126.com.
authors.forename: Luchun
authors.initials: L
authors.lastname: Yan
authors.affiliation: School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Xueyuan Road 30, Haidian District, Beijing 100083, China. liujm@ustb.edu.cn.
authors.forename: Jiemin
authors.initials: J
authors.lastname: Liu
authors.affiliation: School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Xueyuan Road 30, Haidian District, Beijing 100083, China. ghwang@ustb.edu.cn.
authors.forename: Guihua
authors.initials: G
authors.lastname: Wang
authors.affiliation: School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Xueyuan Road 30, Haidian District, Beijing 100083, China. dong1035@126.com.
authors.forename: Chuandong
authors.initials: C
authors.lastname: Wu
mesh_terms: D000328:Adult; D000393:Air Pollutants / Q000032:analysis*; D000465:Algorithms; D045424:Complex Mixtures / Q000737:chemistry* / Q000502:physiology*; D003198:Computer Simulation; D005260:Female; D006801:Humans; D008297:Male; D008954:Models, Biological; D009812:Odorants / Q000032:analysis*; D055696:Olfactory Perception / Q000502:physiology*; D012684:Sensory Thresholds / Q000502:physiology*; D055815:Young Adult
chemical_list: D000393:Air Pollutants; D045424:Complex Mixtures