Keywords: fluid dynamics, turbulence, air pollution, CFD.

This paper shows the integration of mesoscale meteorological and air quality models, based on three dimensional Eulerian numerical solvers of the turbulent fluid dynamics Navier-Stokes partial differential equation system and the computational fluid dynamics models, which are applied to high resolution urban environs such as urban streets, squares, blocks, etc. Some state-of-the-art third generation Eulerian air pollution models such as CMAQ (US EPA) and MM5 (PSU/NCAR) are used together with an adapted version of the emission model EMIMO (UPM) which includes a cellular automata model called CAMO to produce realistic simulations of traffic at street urban levels based on the von Newman approach in the cellular automata. An adapted version of the MIMO model [7], developed at the University of Karlsruhe, is implemented as a CFD problem at street level which receives boundary and initial conditions from the MM5-CMAQ system and emission from the EMIMO-CAMO system.

In this contribution we have applied the microscale dispersion model MIMO [7] to simulate different emission reduction scenarios in Madrid (Spain) related to the vehicle traffic conditions. The MIMO CFD code has been adapted and incorporated into a mesoscale air quality modelling system (MM5-CMAQ-EMIMO) to fit into the one-way nesting structure. MM5 is a meteorological mesoscale model developed at the Pennsylvania State University (USA) and the NCAR (National Centre for Atmospheric Research, USA) [4]. The CMAQ model is the Community Multiscale Air Quality Modelling System developed by EPA (USA) [1] and EMIMO is the Emission Model [6]. MM5 is a well recognized non-hydrostatic mesoscale meteorological model which uses global meteorological data produced by global models such as the GFS model (NCEP, USA) to produce high resolution detailed three dimensional fields of wind, temperature and humidity which are used in our case as an input for the photochemical dispersion model CMAQ [5]. In addition of MM5 output data, EMIMO model produces for the specific required spatial resolution, hourly emission data for different inorganic pollutants such as particulate matter, sulphur dioxide, nitrogen oxides, carbon monoxide and total volatile organic compounds VOCs. The VOCs are split according to sparse matrix operator kernel emissions (SMOKE) [2,3].

The MM5-CMAQ-EMIMO modelling system has been used to provide detailed initial and boundary conditions to a system called MICROSYS which is composed by the MIMO CFD microscale dispersion model and CAMO which is a cellular automata traffic model. The results show that the air quality modelling system offers realistic results although no comparison with an eddy-correlation measurement system has been performed in the area. The tool can be used for many air quality impact studies but in particular for traffic emission reduction strategies.

The need to have air quality forecasts in detail in space and time is becoming more important since the environmental authorities and citizens require air quality information in advance in order to take measures and actions to be eventually protected from pollution episodes but also to have a proper knowledge of the air quality in the areas where they live or they are going to visit.

1

D.W. Byun, J. Young, G. Gipson, J. Godowitch, F. Binkowsky, S. Roselle, B. Benjey, J. Pleim, J.K.S. Ching, J. Novak, C. Coats, T. Odman, A. Hanna, K. Alapaty, R. Mathur, J. McHenry, U. Shankar, S. Fine, A. Xiu, and C. Lang, "Description of the Models-3 Community Multiscale Air Quality (CMAQ) model", Proceedings of the American Meteorological Society 78th Annual Meeting Phoenix, AZ, Jan. 11-16, 1998. pp. 264-268, 1998.

2

CIESIN, Center for International Earth Science Information Network (CIESIN). Global Rural-Urban Mapping Project (GRUMP): Urban/Rural population grids. Palisades, NY: CIESIN, Columbia University. http://sedac.ciesin.columbia.edu/gpw, 2004.

3

C.J. Coats, Jr. "High Performance Algorithms in the Sparse Matrix Operator Kernel Emissions (SMOKE) Modelling System", Microelectronics Center of North Carolina, Environmental Systems Division, Research Triangle Park, NC, 6 pp. 1995.

4

G. Grell, J. Dudhia, and D. Stauffer, "A Description of the Fifty Generation Penn State/NCAR Mesoscale Model (MM5)", NCAR Tech. Note, TN-398+STR, 117 pp, 1994.

5

R. San José, J.F. Prieto, N. Castellanos and J.M. Arranz. "Sensititivity study of dry deposition fluxes in ANA air quality model over Madrid mesoscale area", Measurements and Modelling in Environmental Pollution, Ed. San José and Brebbia, pp. 119-130, 1997

6

San José R., Peña J.I., Pérez J.L. and González R.M., "EMIMO: an emission model", 292-298. ISBN: 3-540-00840-3 Springer-Verlag, 2003

7

Ehrhard, J., Khatib I.A., Winkler, C., Kunz, R. Moussiopoulos, N. and Ernst, G., "The microscale model MIMO: development and assessment", Journal of Wind Engineering and Industrial Aerodynamics, 85, 163-176, 2000. doi:10.1016/S0167-6105(99)00137-3

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