2016
DOI: 10.1016/j.atmosenv.2015.12.051
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Conversion of the chemical concentration of odorous mixtures into odour concentration and odour intensity: A comparison of methods

Abstract: Research Highlights Concentration of odorous substances as surrogate for odour concentration/intensity  Comparison of conversion methods with various degrees of complexity  Model evaluation by seven VOCs: 23 binary mixtures and 5 mixtures of 7 substances  Model input: odour threshold concentration and the slope of the Weber-Fechner law  No further calibration by olfactometric measurements necessary Wu et al.: Conversion of the chemical concentration of odorous mixtures into odour concentration and odour i… Show more

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Cited by 65 publications
(33 citation statements)
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“…NSE < 0 indicates an even worse performance than using the mean value. The calculations of these statistical parameters are described in detail in Wu, et al [27] and are calculated according to:…”
Section: Discussionmentioning
confidence: 99%
“…NSE < 0 indicates an even worse performance than using the mean value. The calculations of these statistical parameters are described in detail in Wu, et al [27] and are calculated according to:…”
Section: Discussionmentioning
confidence: 99%
“…Based on its strong regression ability, more reliable data was collected and it helped to explore the odor interaction more intuitively. Although the odor interaction has been widely studied by many empirical models who have made very accurate explanations [5,6,11,43], the machine learning method still has distinct advantages like visual analysis and low time/economic cost. As we found in this study, enough olfactory measured data was an essential guarantee to the accuracy of machine learning models.…”
Section: Similarity Of Binary Odor Interaction Patternmentioning
confidence: 99%
“…However, the test cost (e.g., a panel of specialized assessors, professional testing laboratory, long sampling, and testing cycles) of olfactory evaluation is much higher than regular chemical analysis [4]. Therefore, the relationship between the chemical composition and the odor intensity of odor mixtures have been widely researched in related fields [5]. The odor intensity prediction models and electronic nose are also urgently needed for both research and application purposes [6].…”
Section: Introductionmentioning
confidence: 99%
“…The first ones allow one to identify and quantify specific odor compounds consisting of air samples. It should be considered that the odor sensation in environmental contexts is produced in general by complex mixtures of chemical compounds, with odor intensity depending on both concentration and odor threshold of the components of the mixtures [16,17], making low concentration components with a low odor threshold (e.g., reduced sulfur compounds) very relevant in determining the sensorial response.Electronic noses are useful instruments, responsive to the presence of mixtures of odorant compounds of variable and only partially known composition, at concentrations relevant for human odor sensation (ppb v , or low ppm v ), with a high sampling frequency [18][19][20][21]. Electronic noses are generally constituted by (1) a sampling device, pumping air in a controlled way to (2) a system of sensors producing a multivariate signal after reversible interaction with the mixture of compounds present in the gaseous sample; and (3) multivariate signals are processed identifying patterns related to the presence or absence of odorants and/or to odor intensity and/or to discrimination among odor sources.…”
mentioning
confidence: 99%
“…The first ones allow one to identify and quantify specific odor compounds consisting of air samples. It should be considered that the odor sensation in environmental contexts is produced in general by complex mixtures of chemical compounds, with odor intensity depending on both concentration and odor threshold of the components of the mixtures [16,17], making low concentration components with a low odor threshold (e.g., reduced sulfur compounds) very relevant in determining the sensorial response.…”
mentioning
confidence: 99%