Short-term gas dispersion in idealised urban canopy in street parallel with flow direction
1 Charles University in Prague, Faculty of Mathematics and Physics, Czech Republic
2 Institute of Thermomechanics Academy of Sciences of the Czech Republic, v.v.i. Dolejškova 1402/5, Prague 182 00, Czech Republic
a Hana Chaloupecká: firstname.lastname@example.org
Published online: 28 March 2016
Chemical attacks (e.g. Syria 2014-15 chlorine, 2013 sarine or Iraq 2006-7 chlorine) as well as chemical plant disasters (e.g. Spain 2015 nitric oxide, ferric chloride; Texas 2014 methyl mercaptan) threaten mankind. In these crisis situations, gas clouds are released. Dispersion of gas clouds is the issue of interest investigated in this paper. The paper describes wind tunnel experiments of dispersion from ground level point gas source. The source is situated in a model of an idealised urban canopy. The short duration releases of passive contaminant ethane are created by an electromagnetic valve. The gas cloud concentrations are measured in individual places at the height of the human breathing zone within a street parallel with flow direction by Fast-response Ionisation Detector. The simulations of the gas release for each measurement position are repeated many times under the same experimental set up to obtain representative datasets. These datasets are analysed to compute puff characteristics (arrival, leaving time and duration). The results indicate that the mean value of the dimensionless arrival time can be described as a growing linear function of the dimensionless coordinate in the street parallel with flow direction where the gas source is situated. The same might be stated about the dimensionless leaving time as well as the dimensionless duration, however these fits are worse. Utilising a linear function, we might also estimate some other statistical characteristics from datasets than the datasets means (medians, trimeans). The datasets of the dimensionless arrival time, the dimensionless leaving time and the dimensionless duration can be fitted by the generalized extreme value distribution (GEV) in all sampling positions except one.
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