Scale-adaptive morphometric analysis for urban air quality and ventilation applications

A novel, flexible method to derive urban morphometric parameters is presented. Through selected examples, it demonstrates its employability in a wide range of applications. This method builds upon an extension of an image-based technique for the treatment of building data to discuss objective criteria for model grid choice and related consequences. Starting from an estimation of aerodynamic parameters, and their validation by computational fluid dynamics using an existing simulation of downtown Oklahoma City in the US, the method is used to evaluate improvements in the performance of an operational dispersion model. Results are applied to flow over a neighbourhood for the determination of ventilation parameters. It is suggested that the grid used for calculation of morphometric parameters provides the best agreement with data from laboratory experiments when the selection of grid size is made upon the spatial profile of building height standard deviation and maximum building height. The implication is that when a mesoscale numerical model is employed, morphometric parameters should be calculated by positioning the computational grid based on physical boundaries, while for finer resolution (namely, smaller scale) numerical models, morphometric parameters should be calculated using the street grid as external boundary, and the maximum building height criterion performs well.