PrOlor: Forecasting Odors Two Days beforehand. Case Study of An Animal By-Product Processing Plant.

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sesion04 diaz02   PrOlor is the first commercial software application in the world that is able to forecast an odor incident two days beforehand by using advanced dispersion modeling and odor measurements at the source.

   PrOlor tool was used to forecast odor incidents during 10 months in a rendering plant. The results are shown in this article.

 

Carlos Nietzsche Díaz Jiménez 1*, Cyntia Izquierdo Zamora 1, David Cartelle Fernández 2, Jose M. Vellón Graña 2, Ángel Rodríguez López 2

1. SVPA, Servicios de Protección Ambiental.
2. Troposfera Soluciones Sostenibles S.L., C/ Real 217, 15401 Ferrol, A Coruña, Spain.

   Competing interests: The author has declared that no competing interests exist.

   Academic editor: Carlos N Díaz.

   Content quality: This paper has been peer reviewed by at least two reviewers. See scientific committee here

   Citation: Carlos Nietzsche Díaz Jiménez, Cyntia Izquierdo Zamora, David Cartelle Fernández, Jose M. Vellón Graña and Ángel Rodríguez López, 2015, PrOlor: Forecasting Odors Two Days beforehand. Case Study of An Animal By-Products Processing Plant, III International Conference of Odours in the Environment, Bilbao, Spain, www.olores.org.

   Copyright: 2015 olores.org. Open Content Creative Commons license. It is allowed to download, reuse, reprint, modify, distribute, and/or copy articles in olores.org website, as long as the original authors and source are cited. No permission is required from the authors or the publishers.

   ISBN: 978-84-608-2262-2.

   Keyword: CALPUFF, PrOlor, WRF, odors, dynamic olfactometry, complaints.

Abstract

  PrOlor is the first commercial software application in the world that is able to forecast an odor incident two days beforehand by using advanced dispersion modeling and odor measurements at the source. This way, the operator of an industrial plant has time to take corrective steps before the odor incident happens. In this case study, PrOlor tool was used to forecast odor incidents during 10 months in a rendering plant. In order to check the results, odor incidents were recorded during this period of time using a webpage, accessible from mobile devices. The results show that PrOlor forecasts correctly 99.1% of all the events considering "odor" and "no-odor" events.

 

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