Numerical models are frequently used for the simulation of pollutant dispersion within the urban canopy layer.  Complex numerical tools  for urban dispersion modeling have been developed during the last decade and most of them prove themselves as a more or less perfect representation of reality in terms of the quality of physical modeling of scalar transport phenomena as well as of the quality and accuracy of the model results.  On the other hand, comparisons of model results with independent field data or results of physical dispersion modeling in boundary layer wind tunnels still show significant discrepancies in the results of a numerical simulation and physical reality.  Searching for what is causing those differences one has to subdivide the problem into two major categories of error sources.  One group is represented by differences due to the simplified physics implemented in numerical models.  There is still a lack of information on urban scale turbulence, wind fluctuations in complex urban areas as well a gap in knowledge on how to model turbulent dispersion within the urban canopy layer.  Fortunately, systematic validation and refinement of numerical models, made possible by high quality reference data, may result in a further improvement of the quality of the model physics, which is dominated by the accuracy of turbulence modeling.  The second group of differences obviously is caused by differences in the geometrical representation of the physical reality due to discretization.  Most of the numerical dispersion models available use a box-type representation of buildings for resolving limited areas of an urban roughness.  As a result, all buildings may have flat roofs instead of the variation in roof configurations in the original.  In addition, building dimensions are adapted to the more or less dense numerical grid, causing significant differences between the full scale building dimensions and the numerical representation.  Moreover, an essential number of buildings might not be well aligned with the regular structured grid that is commonly used in practical dispersion models.  Subsequently, for oblique street canyons the surrounding buildings are represented by step-like structures that might clearly affect the flow.  It is obvious, that the uncertainty caused by geometrical simplification of the physical reality may play an important role in assessing the quality of results from numerical modeling.  Even if the physics of  numerical modeling might be improved in the foreseeable future, significant geometrical simplifications will be required for practical application of numerical modeling.  Therefore, it is important to visualize and quantify the uncertainty of results inherent in every box-type numerical model in order to avoid overrating the results of numerical dispersion modeling.

The presented study gives an introduction in how physical modeling might be used for quantifying effects of geometrical simplification.  Based on the results of wind tunnel measurements from several physical models with different complexity and geometrical abstraction, the basic effects of changing the representation of buildings are documented.

Several models directly adapted from numerical grids which were used for flow and dispersion simulations have been tested in the multi-layer wind tunnel at the University of Hamburg. For example, Fig. 1 shows a simplified as well as a more detailed model representation of the "Goettinger Strasse" field site in Hanover.

Figure 1: wind tunnel models

The measurements were performed with the wind tunnel set-up presented in the wind tunnel description.
Measurements were carried out at several locations in all different models. Mean values of the emmission time series recorded were acquired for a total of 36 wind directions {0...360 in steps of 10), from all results the background concentrations of tracer have been subtracted before they were scaled to a non dimensional c* for comparison with field data and results from numerical simulations. We defined the non dimensional concentration c* like :

c : the concentration measurement in wind-tunnel
Uref: reference wind speed at 0.5m from the ground (100m high in field),
H : reference building high 0.125m (25m in field),
L : effective line source length,
Q : Ethan flow in the line source.

A typical c* over wind direction plot for two different models used is given in Figure 2

Figure 2: pollutant dispersion in Goettinger Strasse models


Request further informations on the measurements, please contact Prof Schatzmann