Comparison Method Of Odour Impact Evaluation Using Calpuff Dispersion Modelling And On-Site Odour Monitoring

Odour Impact Monitoring for Landfills

Odour dispersion modelling with Lagrangian and Gaussian models

The Lagrange particle diffusion model LASAT and the Gaussian Austrian Odour Dispersion Model AODM are used to calculate direction-dependent separation distances around livestock farms. As the method has been published already in several papers, the focus is here on the differences of the results due to model physics. With both models, the same peak-to-mean algorithm is used to calculate short-t...

Experimental Approach for the Validation of Odour Dispersion Modelling

Experimental Approach for the Validation of Odour Dispersion Modelling Laura Capelli*, Licinia Dentoni, Selena Sironi, Jean-Michel Guillot Politecnico di Milano, Department of Chemistry, Materials and Chemical Engineering “Giulio Natta”, Piazza Leonardo da Vinci 32, 20133 Milano, Italy Ecole des Mines d’Alès, Laboratoire Génie de l’Environment Industriel, 6 Av. de Clavières, F-30319 Ales Cedex,...

Odour impact determination of a MSW treatment plant: dispersion modelling and electronic nose

One of the most important research topics at the Olfactometric Laboratory of the Politecnico di Milano is the study and the development of a system for the continuous monitoring of environmental odours. The experimental methods adopted are laboratory tests, with samples of known quality and odour concentration, and field tests, represented by experimental monitorings of limited duration. This s...

Evaluation of Air Dispersion Models for Livestock Odour Application

Instantaneous downwind malodours from two swine farrowing facilities were assessed in the field by 15 trained human sniffers. A total of 34 1-hour field monitoring sessions were carried out on the two farms between June and October in 2003 and 2004. Odour emissions from the farm were measured and weather conditions were monitored simultaneously. Four air dispersion models, ISCST3, AUSPLUME, IN-...