ArticleEnvironmental science and pollution research international2021
Objective odor analysis of incidentally emitted compounds using the Langage des Nez® method: application to the industrial zone of Le Havre.
Article in Environmental science and pollution research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.
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- Erratum issued
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7 authors.
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Abstract
Environmental odor studies are usually done using two approaches: nuisance impact assessment and source identification. The latter may be done using chemical analysis or sensory analysis. While sensory analyses offer many advantages, they also face the main obstacle: odor nature description still uses conventional methods based on subjective evocations as odor descriptors. This makes the sensory method ineffective especially when the expected outcome is the source identification in the context of an industrial accident. This work wants to fulfill this gap proposing to build an objective database including the odor nature description of selected potentially emitted compounds using a promising approach: the Langage des Nez® (LdN). Using definite odorous compounds as odor referents, this work provides the odor nature description of 44 compounds, reported as potential incidentally released chemical compounds in the industrial zone of Le Havre. The city of Le Havre, France, was chosen as a model due to a history of odorous emissions of industrial origins. A trained panel described the odor of each compound using up to three referents of the LdN referents collection and attributed a score to each referent. A data analysis method was developed based on the frequency of citation of the referents and the attributed scores allowing the categorization of each compound in three types of consensus categories. The data analysis results showed that around 80% of compounds were described with a good consensus, showing the LdN as a well-adapted lexicon. This study does not point to any correlation between the chemical structures of the compounds of interest and their relative referents. When compared to conventional methods, LdN revealed a more objective and precise approach. The proposed experimental method and the results provided in this work offer the first insight for time-efficient approaches to objectively describe environmental odors, especially potentially emitted odors during incidents. This work may be supplemented by abatement and mixture effect investigations for a complete understanding of odor dispersion.
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