Dispersion in canopies

Simulations confirm that these are regions where fluid trajectories are well- mixed. This provides a basis for constructing FAM s for dispersion in these regions using semi-analytical diffusivity models. 

Information about these (or any other airflow) patterns is not used as input in the fully computational models (FCM) because these models are determined by general equations and boundary conditions. However flow feature information can be used to judge and interpret the correctness and sensitivity of their predictions. 

In this section we begin by reviewing FCM methods at varying levels of complexity that can be applied on this scale before considering the different methods of FAM and their application for the different types of building/street/source configuration. Table 2.7 summarises the main points. 

The first stage in FCM calculations for complex flows is to compute the mean flow and the turbulence statistics and then to use these data in computations of the concentration distribution. As explained in Section 2.3, for well separated buildings, (b/d 1), in the atmospheric boundary layer (e.g. in the suburban situation), the usual methods 

One might conclude that because these effects of dispersion are less sensitive to turbulence structure in complex urban flows, CFD models results should be reasonably accurate provided they are applied with just sufficient detail to represent the mean flow features. This is why CFD methods are used with large computer resources by certain laboratories in the USA (e.g. Brown and Williams, 1998 [87]). On the other hand, it also means that FAMs are appropriate, using approximate models of the turbulence and mean flow for the different types of topology and pattern of the buildings and street. This is the rationale for the fast and easily-understood methods, now being used/developed in the UK and elsewhere, which we describe below. 

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In summary, these experiments indicate that the IL method can yield practically useful information about canopy source distributions from atmospheric concentration measurements. However, the method depends on several factors, any of which may be limiting (1) measured concentration profiles of sufficient accuracy and density in the vertical dimension (2) adequate and sufficiently accurate measurements of the turbulence field (3) an adequate theory of turbulent transport and dispersion in canopies, to calculate the dispersion matrix (4) an adequate procedure for doing the inversion itself Evidence presented in the next subsection indicates that all of these aspects can be combined successfully, though there is uncioubtecfly room for improvement especially in the latter two fiictors. 

Figure 2.10 Characteristic dispersion mechanisms in canopies from local sources close to an isolated obstacle source outside wake/canyon, showing impaction of the plume from Source (1), wake entrainment (E) and detrainment (D) from Sources 1 and 2. Note how the plume profile G(z) has a split structure in the wake with unentrained component Gp0 and detrained component Gpw. Gc denotes the typical outline of a cloud emitted upwind, showing the additional longitudinal dispersion associated with the blocking and wake effects. Here the reference cloud outline in the absence of buildings is shown as a dashed line with small circles, with streamwise dimension crj0.

Figure 2.12 Characteristic dispersion mechanisms in canopies in the case of multiple buildings (see also Figure 2.3) On discrete/obstacle scale (for well-separated buildings, b/d 1) plume dimensions less than obstacle width.

The first of these was supplied by Raupach [525] with his localized near field (LNF) model. This cast the problem of canopy fluxes in the Lagrangian framework which is widely used in the modelling of atmospheric dispersion from point sources such as factory chimneys. The basic physics of scalar dispersion from a point source were worked out by G.I. Taylor in the 1930 s. He showed that during dispersion in a steady wind, U, near to the source the width of a scalar plume grows at a rate proportional to Ut, the distance from the source but further downwind, far from the source, it spreads as y/Ut the square root of downwind distance. Raupach pointed... 

The main problem in forecasting urban air contamination (UAC) is the simulation of accidental release dispersion in the urban canopy or episodes with high pollutant... 

Macdonald, R.W., Hall, D.J., Griffiths, R.F. (1998) Scale model study of building effects on dispersion in the urban canopy at intermediate source distances,... 

Eastepp. E.D., 2006. The influence of individual, isolated vegetative canopies of aerosol dispersion in an urban environment, master s thesis, Texas Tech University. Lubbock, TX. 

After the fire, the pump (and others) was relocated in the open air, under a canopy, so that small leaks would be dispersed by natural ventilation. It was surrounded by a steam curtain to disperse larger leaks. This would not have been necessary if the pump could have been located more than 150 m from sources of ignition. Gas detectors were installed to give early warning of any leaks. Emergency isolation valves (Section 7.2.1) were provided so that the pumps could be isolated safely from a distance [9]. What happened when another leak occurred is described in Section 7.2.1 (d). 

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