The presence of unpleasant odors is now considered, in all respects, as one of the representations of air pollution. The often unpleasant sensation of odor identified by the human olfactory system is generated by the presence in the atmosphere of a mixture of chemicals generically referred to as “odorous substances,” which can cause nuisance even at very low concentrations, usually much lower than those capable of causing health damage or environmental effects.
It is therefore natural to consider describing the fate of odorous substances in the atmosphere using the same dispersion models typically applied for air quality. However, the sensation of olfactory nuisance occurs during each individual human breath, which happens on very short time scales (a few seconds) compared to those typically considered in air quality applications (where interest is in hourly, daily, or annual average concentrations). Therefore, it is necessary to use models capable of describing concentration patterns over very short, or “instantaneous,” time scales to avoid potential underestimations. To address this issue, the results obtained from dispersion models are reprocessed to reconstruct, based on “average” concentrations and using the so-called peak-to-mean ratio, peak values or, more generally, to reconstruct the probability distribution by estimating at least the variance of the concentrations.
In modeling applications, it is common practice to collectively quantify effects using the odor unit (olfactometric units, ouE) (UNI EN 13725:2004) and to highlight their presence in the air through odor concentration (ouE/m³), which represents the number of dilutions required for 50% of a trained panel of assessors to no longer perceive the odor of the analyzed air sample. The dispersion of this pseudo-substance is then simulated, assuming it dilutes like a tracer in the atmosphere, emitted from the source at a given initial concentration.
The particle dispersion model SPRAY has specialized algorithms for calculating peak concentrations, which depend on the particle’s flight time, making it particularly well-suited for applications involving odors.