Case study: a comparison of predicted odour exposure levels using 2D and 3D windfields in CALPUFF model
The use of general purpose steady state Gaussian models (e.g. AERMOD) for predicting Odour exposure levels around the vicinity of an industrial site has been considered an accepted practice for many countries around the world for more than a decade now.
Murguia Walter1, Pagans Estel·la2, Heike Hauschildt3
1. Odournet México, Jardines de Madrid 7622, Monterrey, México. T. +52 (55) 5677 1319
2. Odournet SL, Parc de Recerca UAB · Edificio Eureka, Barcelona, Spain.
3. Odournet Gmbh, Frauenhoferstr. 13, Kiel, Germany.
While there is currently a huge gap between odor and gases, since the smell is a complex mixture of gases which are capable of interact between each other. Therefore various gaseous compounds might generate different odorant stimuli than the single gas compound, so you may consider that monitoring gaseous emissions as a valid alternative as an operational tool.
In this article we make a comparative analysis of the performance of the AERMOD and SYMOS’97 dispersion models for simulating the dispersion of odorous compounds in the atmosphere. Although there are a large amount of air dispersion models in literature, there are few data bases that allow the assessment of results obtained by the dispersion simulation of odorous compounds.
