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SILAM is a meso-scale-to-global chemical transport model developed for a wide range of applications. It includes Eulerian (Galperin, 1999, 2000; Sofiev, 2002, Sofiev et al, 2008) and Lagrangian (Sofiev et al, 2006) transport routines. The model possesses eight chemical transformation modules including gas-phase reactions in the troposphere and the stratosphere (CB4 with updated coefficients), for secondary inorganic aerosol formation (Sofiev, 2000), linearized sulphur oxides chemistry, radioactive nuclides decay, two schemes for aerosol processes (condensation, coagulation, nucleation in progress) computed from thermodynamic equilibrium or as  dynamic processes, transformation of biological aerosols (in progress). Aerosol size spectra are described with sectional approach with user-defined bin distribution. Optical properties of aerosols and a selection of gaseous tracers are calculated following (Prank, 2008). Dry deposition scheme for aerosols is described in (Kouznetsov & Sofiev, 2012). SILAM model has been extensively evaluated against air quality observations over Europe and the globe (http://www.gmes-atmoshpere.eu, Solazzo et al., 2012, Huijnen et al, 2010, etc). 

SILAM possesses the embedded modules for emission of sea salt (Sofiev et al 2011, Tsyro et al, 2010), wild-land fires (Sofiev et al, 2009, 2012), desert dust, allergenic pollen (Sofiev et al, 2012, Siljamo et al, 2012, Prank et al, 2013) and volatile organic compounds. The BVOC source term generally follows the approach of Guenther et al, (1995) but the specific parameterizations are taken from the results of NatAir project (NatAir, 2007) presented and compared with MEGAN model by Popkou et al,, (2010).

The model is equipped with variational data assimilation tools for both 3D- and 4D-VAR, for which the adjoints to the main chemical routines (CB4 and linearized sulphur oxidation chemistry) and all dynamic modules of SILAM have been developed (Vira & Sofiev, 2010).

Silam was constructed at the Finnish Meteorological Institute and transferred to my group in the beginning of 2015.  Currently CSC (IT Center for Science in Finland), Dr Sofiev’s (the SILAM group leader at FMI) and my group are working jointly together on the optimisation of the SILAM code for Xeon architectures. This activity will enable the implementation of more computational expensive modules into SILAM. This initiative will give us the opportunity to study SOA formation, growth and transformation processes with a focus on the anthropogenic impact with high temporal-spatial resolution for large areas like Southern Finland.


References

  • Galperin, M. V.: Approaches for improving the numerical solution of the advection equation. In Z. Zlatev (Ed.), Large-Scale Computations in Air Pollution Modelling, Proc. NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bistritza (pp. 161–172). Sofia: Kluwer Academic Publishers, Dordrecht, The Netherlands, 1999.
  • Galperin, M. V.: The Approaches to Correct Computation of Airborne Pollution Advection. In Problems of Ecological Monitoring and Ecosystem Modelling. XVII (in Russian) (pp. 54–68). St.Petersburg: Gidrometeoizdat, 2000.
  • Guenther, A., Hewitt, N., Erickson, D., Fall, R., Geron, C., Graedel, T., Harley, P., Klinger, L., Lerdau, M., McKay, W., Pierce, T., Scholes, B., Steinbrecher, R., Tallamraju, R., Taylor, J., Zimmerman, P.: A global model of natural volatile organic compound emissions. J. Geophys. Res. 100, 8873-8892, 1995.
  • Kouznetsov, R., & Sofiev, M.: A methodology for evaluation of vertical dispersion and dry deposition of atmospheric aerosols. Journal of Geophysical Research, 117(D01202), 2012.
  • NatAir: Improving and applying methods for the calculation of natural and biogenic emissions and assessment of impacts to the air quality. Final report of NAtAir project, contract No. 513 699, Ed. R.Friedrish, University of Stuttgart, 193 pp, 2007.
  • Poupkou, A., T. Giannaros, K. Markakis, I. Kioutsioukis, G. Curci, D. Melas, C. Zerefos: A model for European Biogenic Volatile Organic Compound emissions: Software development and first validation, Atm.Environ., 25, 1845-1856, 2010.
  • Prank, M.: Evaluation of atmospheric composition simulations via comparison with remote-sensing and in-situ observations. University of Tartu, Faculty of science and technology, institute of physics. Master thesis, 75pp, 2008.
  • Prank, M. Chapman, D.S. Bullock, J.M., Belmonte Soler, J. Berger, U., Dahl, A., Jäger, S., Kovtunenko, I., Magyar, D., Niemelä, S., Rantio-Lehtimäki, A., Rodinkova, V., Sauliene, I., Severova, E., Sikoparija, B., Sofiev, M.: An operational model for forecasting ragweed pollen release and dispersion in Europe. Agriculture and forest meteorology doi: 10.1016/j.agrformet.2013.08.003, 182–183, 43–53, 2013.
  • Siljamo, P., Sofiev, M., Filatova, E.‏, Grewling, L., Jäger, S., Khoreva, E., Linkosalo, T., Jimenez, S.O.‏, Ranta, H., Rantio-Lehtimäki, A., Svetlov, A., Veriankaite, L.‏, Yakovleva, E., Kukkonen, J.: A numerical model of birch pollen emission and dispersion in the atmosphere. Model evaluation and sensitivity analysis. Int. J. Biometeorology, DOI 10.1007/s00484-012-0539-5, PMID 22434484, 2012.
  • Sofiev, M.: A model for the evaluation of long-term airborne pollution transport at regional and continental scales.Atmospheric Environment. 34, No.15, pp. 2481-2493, 2000.
  • Sofiev, M.: Extended resistance analogy for construction of the vertical diffusion scheme for dispersion models. J. of Geophys.Research – Atmosphere, 107, D12, 2002.
  • Sofiev, M., Galperin, M. V, & Genikhovich, E.: Construction and evaluation of Eulerian dynamic core for the air quality and emergency modeling system SILAM. In C. Borrego & A. I. Miranda (Eds.), NATO Science for piece and security Serties C: Environmental Security. Air pollution modelling and its application, XIX (pp. 699–701). SPRINGER-VERLAG BERLIN., 2008.
  • Sofiev, M., Siljamo, P., Ranta, H., Linkosalo, T., Jaeger,S., Rasmussen, A., Rantio-Lehtimaki, A., Severova, E., Kukkonen, J.: A numerical model of birch pollen emission and dispersion in the atmosphere. Description of the emission module. Int. J. Biometeorology, DOI 10.1007/s00484-012-0532-z, PMID 22410824, 2012.
  • Sofiev, M., Soares, J., Prank, M., de Leeuw, G., Kukkonen, J.: A regional-to-global model of emission and transport of sea salt particles in the atmosphere. JGR, 116, D21302, 2011.
  • Sofiev,M., Vankevich,R., Lotjonen,M., Prank,M., Petukhov,V., Ermakova,T., Koskinen, J. Kukkonen, J.: An operational system for the assimilation of satellite information on wild-land fires for the needs of air quality modelling and forecasting. Atmos. Chem. Phys.,9, 6833-6847, 2009.
  • Solazzo, E., Bianconi, R., Pirovano, G., Matthias, V., Vautard, R., Moran, M. D., … Galmarini, S.: Operational model evaluation for particulate matter in Europe and North America in the context of AQMEII. Atmospheric Environment, 53, 75–92. 2012.
  • S. Tsyro, W. Aas, J. Soares, M. Sofiev, H. Berge, and G. Spindler: Modelling of sea salt pollution over Europe: key uncertainties and comparison with observations Atmos. Chem. Phys.,11, 10367-10388, doi:10.5194/acp-11-10367-2011, 2011.
  • Vira, J., M.Sofiev: On variational data assimilation for estimating the model initial conditions and emission fluxes for the short-term forecasting of SOx concentrations. Atmosph. Environ., 46, pp.318-328, 2012.

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