A Mesoscale Study of Large Industrial Emission Impact over Madrid Mesoscale Domain by Using MM5-CMAQ Modelling System

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Abstract

The scientific interest on improving the air quality tools which are able to provide a detailed description - source oriented - of the atmospheric process and the impact of specific large industrial emission points is growing. This contribution shows the results of using a state-of-the-art 3rd generation air quality modelling system (MM5-CMAQ) over a pilot test industrial site in Madrid mesoscale domain. The MM5 model is a well known non-hydrostatic mesoscale meteorological model developed by PSU/NCAR and the CMAQ (Community Multiscale Air Quality Modelling System) is a 3rd generation air quality dispersion model developed by EPA (U.S.). Both are modular codes and include an interface called MCIP which azures full consistency on the numerical methods in the meteorological advection and difusion schemes in the meteorological module and the chemical and dispersion module. The application has been done with CBM-IV chemical scheme (simple version). The results of running the so-called ON/OFF approach - in other words the differences between the simulation with full industrial emissions and no industrial emissions - show that the MM5-CMAQ modelling system can be used as an excellent tool for evaluating the impact of different emission sources in an operational mode. Results also show that increases up to 50 % on average and larger values for hourly impacts for ozone concentrartions are found in the surrounding areas of the industrial plant. In addition, we see that the distance where the industrial emissions are impacting on the air quality can be larger than 40 km. © Springer-Verlag 2004.

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García, R. S. J., Camaño, J. L. P., Priego, R., & González Barras, R. M. (2004). A Mesoscale Study of Large Industrial Emission Impact over Madrid Mesoscale Domain by Using MM5-CMAQ Modelling System. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2907, 320–327. https://doi.org/10.1007/978-3-540-24588-9_36

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