AQF MODEL INFO

The Air Quality Forecast Modelling system in development at Barcelona Supercomputing Center-Centro Nacional de Supercomputación (BSC-CNS) bases on the integrated modelling system: WRF/CMAQ/BSC-DREAM). The major components are (see Figure below):

Air Quality Forcasting System

  1. The Meteorological Forecast Modelling system run at Barcelona Supercomputing Center-Centro Nacional de Supercomputación (BSC-CNS) bases on the Weather Research & Forecasting (WRF) model (Michalakes et al., 2005; Skamarock et al., 2005).  The WRF modeling system is a portable code that is efficient in a massively parallel computing environment. A modular single-source code is maintained that can be configured for both research and operations. It is suitable for use in a broad spectrum of applications across scales ranging from meters to thousands of kilometers. Such applications include research and operational numerical weather prediction (NWP), data assimilation and parameterized-physics research, downscaling climate simulations, driving air quality models, atmosphere-ocean coupling, etc. The WRF Software Framework (WSF) provides the infrastructure that accommodates multiple dynamics solvers, physics packages that plug into the solvers through a standard physics interface, programs for initialization, and the WRF variational data assimilation (WRF-Var) system. As of this writing there are two dynamics solvers in the WSF: the Advanced Research WRF (ARW) solver (originally referred to as the Eulerian mass or “em” solver) developed primarily at NCAR, and the NMM (Nonhydrostatic Mesoscale Model) solver developed at NCEP, which will be documented and supported to the community by the Developmental Testbed Center (DTC).
     

  2. Emissions used for the domain of Europe are derived from EMEP emissions database, on an hourly basis and lumped according to Carbon Bond IV chemical mechanism (Gery et al., 1989). Chemical species considered are NOx, non-methane volatile organic compounds (NMVOCs), sulfur dioxide (SO2), carbon monoxide (CO) and particulate matter (ammonia, nitrates, sulphates, etc.). The vertical distribution of emissions is implemented following EMEP national profiles. Cells from the European EMEP mesh have a resolution of 50-km in polar coordinates.

    High-Elective Resolution Modelling Emissions System (HERMES) is used to generate the emission inventory in Spain (Baldasano et al., 2008). HERMES takes the year 2004 as the reference period, estimates the atmospheric emissions with a temporal resolution of 1 h and a spatial resolution of 1 km2 and generates results according to the European Environmental Agency’s Selected Nomenclature for Air Pollution (SNAP), which is the official activity classification system applied by the European Commission in the CORINAIR emission inventory. Furthermore, HERMES has the capacity of presenting results according to individual installation, industrial activities, land use classification or type of pollutants or process (fugitive, evaporative, hot or cold emissions).

    HERMES considers as primary air pollutants nitrogen oxide (NOx), non-methane volatile organic compounds (NMVOC), carbon monoxide (CO), sulphur dioxide (SO2), total suspended particles (TSP) and particulate matter (PM10 and PM2.5). For power generation, industrial sources, use of fossil fuels by residential and commercial sectors and road transport the following greenhouse gases (GHG) have been estimated: carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O).

  3. The chemical transport model used to compute the concentrations of photochemical pollutants is Community Multiscale Air Quality (CMAQ) (Byun and Ching, 1999). For the domain of the Iberian Peninsula, static initial and boundary conditions are considered. The chemical mechanism selected for simulations is CBM-IV, including aerosols and heterogeneous chemistry. Nitrogen oxides (NOx) and volatile organic compounds (VOCs) specification of emissions, as required by CBM-IV, could be found in Parra et al. (2006). The algorithm chosen for the resolution of tropospheric chemistry is the Modified Euler Backward Iterative (MEBI) method (Huang and Chang, 2001).
     
  4. The natural dust is estimated with the Dust REgional Atmospheric Model (DREAM) (Nickovic et al., 2001). The Dust REgional Atmospheric Model (BSC/DREAM) predicts the atmospheric life cycle of the eroded desert dust and was developed as a pluggable component of the NCEP/ETA model. It solves the Euler-type partial differential non-linear equation for dust mass continuity. DREAM is fully inserted as one of the governing equations in the atmospheric NCEP/Eta atmospheric model. In the current operational configuration of the model, four particle size classes (clay, small silt, large silt and sand) are estimated with particle size radii of 0.73, 6.1, 18 and 38 m, respectively. For long-range transport, only the first two dust classes are relevant since their life time is larger than about 12 hours.

References

  • Baldasano J.M., L. P. Güereca, E. López, S. Gassó, P. Jimenez-Guerrero (2008). “Development of a high-resolution (1 km x 1 km, 1 h) emission model for Spain: the High-Elective Resolution Modelling Emission System (HERMES)”. Atmospheric Environment, 42 (31): 7215-7233, doi:10.1016/j.atmosenv.2008.07.026. ISSN: 1352-2310, October.

     

  • Byun, D.W., Ching, J.K.S. (Eds.), (1999). “Science algorithms of the EPA Models-3 Community Multiscale Air Quality (CMAQ) Modeling System”. EPA Report N. EPA-600/R-99/030, Office of Research and Development. U.S. Environmental Protection Agency, Washington, DC.

     

  • Michalakes, J., J. Dudhia, D. Gill, T. Henderson, J. Klemp, W. Skamarock, and W. Wang, (2005): “The Weather Research and Forecasting Model: Software architecture and performance. Proceedings of the Eleventh ECMWF Workshop on the Use of High Performance Computing in Meteorology”. Eds. W. Zwiefhofer and G. Mozdzynski, World Scientific, pp 156 – 168.

     

  • Nickovic, S., A. Papadopoulos, O. Kakaliagou, G. Kallos, (2001). “Model for prediciton of desert dust cycle in the atmosphere”. Journal of Geophysical Research 106, 18113-18129.

     

  • Parra, R., Jiménez, P., Baldasano, J.M. (2006). “Development of the high spatial resolution EMICAT2000 emission model for air pollutants from the north-eastern Iberian Peninsula (Catalonia, Spain)”. Environmental Pollution 140, 200-219.

     

  • Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, W. Wang and J. G. Powers, (2005). “A Description of the Advanced Research WRF Version 2”. NCAR Technical note NCAR/TN-468+STR.