Lagrangian stochastic models for odour dispersion
It is well known that knowledge about the mean concentration field is not sufficient in a wide range of cases, such as the dispersion of toxic, flammable and chemical reacting gases. Usually, further information about concentration fluctuations, e.g. by determining the concentration variance, is needed. In particular, it is necessary to determine the 90th percentile of the hourly concentration distribution when dealing with odour-hour modelling, whereby an odour-hour is defined by at least 6 minutes of perceivable odour concentrations within one hour. For convenience, we define R90 as the 90th percentile normalised by the mean concentration. It can be determined by assuming a PDF (Probability Density Function) that is generally completely defined by the concentration fluctuation intensity i and the mean concentration. While the latter is provided by many types of dispersion models, even very simple ones, obtaining an estimation of i requires a more sophisticated approach, that should allow estimating the concentration variance dispersion. In the frame of the Lagrangian stochastic models several approaches can be found for estimating this quantity: Thomson (1990), Borgas and Sawford (1994), Pope (1985); Cassiani et al. (2005), Yee et al. (1994); Yee and Wilson (2000); Luhar et al. (2000); Franzese (2003); Mortarini et al. (2009); Ferrero et al. (2013), Manor (2014), Ferrero et al. (2017). Lagrangian stochastic models for the assessment of odour were proposed and tested by Oettl and Ferrero (2017), and Ferrero and Oettl (2019). Extensive review can be also available: Ferrero et al. (2020), Cassiani et al. (2020).
Material
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