Towards the aim of improving the air quality in the urban environment via the application of innovative TiO 2 based photocatalytic coverings, a field campaign took place within the frame of the EU PICADA project (http:// www.picada-project.com) to asses the expected depollution efficiency of such materials under realistic conditions. Furthermore, extensive numerical modeling was performed via the application of the RANS CFD code for microscale applications MIMO, in an effort to asses the sensitivity of the developing flow field and the corresponding dispersion mechanism and hence of the depollution efficiency of the PICADA products on a wide range of factors, with most notably the length of the street canyon, the thermal exchange between the heated street canyon walls and the air and the approaching wind direction. For the needs of the PICADA project a new, simple module had to be implemented into MIMO to be able to model the removal of NO x from a street canyon whose walls have been treated with a photocatalytic product. The model simulations results presented in this paper, show that MIMO is indeed capable of predicting the effectiveness of the photocatalytic products in question. At the same time, they reveal a strong dependence of the developing flow and concentration fields inside the field site street canyon configuration on most of the aforementioned factors with most notably the direction of the approaching wind.

Systems of coupled prognostic mesoscale and microscale models have been used as a tool to accurately simulate flows around artificial structures and over densely-built urban areas. Typical implementations of such systems are based on a one-way coupling scheme, where the mesoscale model provides initial and boundary conditions for each off-line application of the microscale model. While very successful in predicting steady-state flows within specific local-scale areas, such schemes fail to account for feedbacks on the mesoscale flow induced by the presence of structures in smaller scales. Unfortunately, the large gap of spatial and temporal scales practically prohibits parallel on-line execution of the mesoscale and microscale models for any significant time interval. It is therefore necessary that a simplifying approach is adopted, where the microscale feedback is spatially and temporally upscaled to interact with parts of the mesoscale domain covering the urban area. In the present work a two-way coupled model system is developed, consisting of the prognostic mesoscale model MEMO and the microscale model MIMO. The microscale feedback on the mesoscale domain is simulated using a metamodelling approach, where the effect of local flows on the vertical profiles is estimated for representative urban areas of sizes up to a few hundred meters and used as calibration input for a set of interpolating metamodels. The feedback from the microscale metamodels is then introduced back in the mesoscale grid by means of Newtonian relaxation. As an illustrative application, simulations for the city of Athens, Greece during a multi-day period are presented. Effects of the microscale feedback on the mesoscale flow become evident both as a reduction of lower-level wind speeds in urban cells as well as an overall increase in turbulent kinetic energy production over densely-built areas.Key words: metamodelling, urbanisation, mesoscale, microscale, two-way coupling. INTRODUCTIONEfforts to introduce urban effects on mesoscale models have in general followed two different approaches. In the first one, corrections are applied in the mesoscale parameterisations within the lower computational layers, in an attempt to account for the specific characteristics of the urban canopy (Baklanov, 2004). Improved parameterisations include the effects of shadowing and radiation trapping as well as the urban heat island effect (Grimmond and Oke, 1999). The effect of urban canopy on the momentum flow and turbulent kinetic energy (TKE) production is usually parameterised as additional aerodynamic drag and production terms, respectively, introduced in the dynamical equations (Dupont et al., 2004). The so-called "urbanisation" approaches have the advantage of relatively low computational requirements and offer a large degree of flexibility in adjusting the relative strength of the forcing terms, allowing a fine-tuning to the particular characteristics of different urban morphologies. On the other hand, the number of introduced parameters is ofte...

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