A crude monte carlo analysis for treating the influence of olfactometric uncertainty

This work discusses the implementation of a Crude Monte Carlo, algorithm applied to an olfactometric case study. In particular, the study analyses the influence of uncertainty of the odour concentration measurement, by dynamic olfactometry, on experimental measurements, which employ a sequence of olfactometric analysis i.e. the estimation of Odour Emission Capacity per unit of volume, OEC. The evaluation of these physical quantities is function of a fixed number of odour concentrations data. According to the new provisional version of EN13725, each odour concentration measurement is affected by a degree of uncertainty, which follows a lognormal probability distribution function. In order to consider the uncertainty associated to each single odour concentration, a Crude Monte Carlo simulation has been carried out, obtaining 106 iterations of odour concentration datasets. The obtained data have been statistically analysed, highlighting that OEC follows a lognormal distribution function as well.