Jump to ContentJump to Main Navigation
Show Summary Details

Open Geosciences

formerly Central European Journal of Geosciences

Editor-in-Chief: Jankowski, Piotr

1 Issue per year

IMPACT FACTOR increased in 2015: 0.726
5-year IMPACT FACTOR: 0.898

SCImago Journal Rank (SJR) 2015: 0.349
Source Normalized Impact per Paper (SNIP) 2015: 0.753
Impact per Publication (IPP) 2015: 0.928

Open Access
See all formats and pricing

Dispersion modeling of air pollutants in the atmosphere: a review

Ádám Leelőssy
  • Department of Meteorology, Eötvös Loránd University, Budapest, Hungary
  • Email:
/ Ferenc Molnár
  • Department of Physics, Applied Physics, and Astronomy, Rensselaer Polytechnic Institute, Troy, New York, USA
  • Email:
/ Ferenc Izsák
  • Department of Applied Analysis and Computational Mathematics, Eötvös Loránd University, Budapest, Hungary
  • Email:
/ Ágnes Havasi
  • Department of Applied Analysis and Computational Mathematics, Eötvös Loránd University, Budapest, Hungary
  • Email:
/ István Lagzi
  • Department of Physics, Budapest University of Technology and Economics, Budapest, Hungary
  • Email:
/ Róbert Mészáros
  • Department of Meteorology, Eötvös Loránd University, Budapest, Hungary
  • Email:
Published Online: 2014-08-06 | DOI: https://doi.org/10.2478/s13533-012-0188-6


Modeling of dispersion of air pollutants in the atmosphere is one of the most important and challenging scientific problems. There are several natural and anthropogenic events where passive or chemically active compounds are emitted into the atmosphere. The effect of these chemical species can have serious impacts on our environment and human health. Modeling the dispersion of air pollutants can predict this effect. Therefore, development of various model strategies is a key element for the governmental and scientific communities. We provide here a brief review on the mathematical modeling of the dispersion of air pollutants in the atmosphere. We discuss the advantages and drawbacks of several model tools and strategies, namely Gaussian, Lagrangian, Eulerian and CFD models. We especially focus on several recent advances in this multidisciplinary research field, like parallel computing using graphical processing units, or adaptive mesh refinement.

Keywords: air pollution modeling; Lagrangian model; Eulerian model; CFD; accidental release; parallel computing

  • [1] Flight disruptions cost airlines $1.7bn, says IATA, BBC News, http://news.bbc.co.uk/2/hi/business/8634147.stm

  • [2] Stull R. B., An Introduction to Boundary Layer Meteorology. Kluwer Academic Publishers, 1988

  • [3] Kumar P., Sharan M., Parameterization of the eddy diffusivity in a dispersion model over homogenous terrain in the atmospheric boundary layer, Atmos. Res., 106, 2012, 30–43 [Crossref]

  • [4] Seidel D. J., Ao. C. O., Li K., Estimating climatological planetary boundary layer heights from radiosonde observations: Comparison of methods and uncertainty analysis, J. Geophys. Res., 115, 2010, D16113, doi: 10.1029/2009JD013680 [Crossref]

  • [5] Sriram G., Krishna Mohan N., Gopalasamy V., Sensitivity study of Gaussian dispersion models, Journal of Scientific and Industrial Research, 65, 2006, 321–324

  • [6] Turner D. B., The long lifetime of the dispersion methods of Pasquill in U.S. regulatory air modeling, J. Appl. Meteorol., 36, 1997, 1016–1020 [Crossref]

  • [7] Luna R. E., Church H. W., A Comparison of Turbulence Intensity and Stability Ratio Measurements to Pasquill Stability Classes, J. Appl. Meteorol., 11, 1972, 663–669 [Crossref]

  • [8] Galperin B., Sukoriansky S., Anderson P. S., On the critical Richardson number in stably stratified turbulence, Atmos. Sci. Lett., 8, 2007, 65–69 [Crossref]

  • [9] Cimorelli A. J., Perry S. G., Venkatram A., Weil J. C., Paine R. J., Wilson R. B., Lee R. F., Peters W. D., Brode R. W., AERMOD: A dispersion model for industrial source applications. Part I: General model formulation and boundary layer characterization, J. Appl. Meteorol., 44(5), 2005, 682–693 [Crossref]

  • [10] Perry S. G., CTDMPLUS: A dispersion model for sources near complex topography. Part I: Technical Formulations, J. Appl. Meteorol., 31, 1992, 633–645 [Crossref]

  • [11] Foken T., 50 years of the Monin-Obukhov similarity theory. Bound-Lay. Meteorol., 2006, 119, 431–447 [Crossref]

  • [12] Draxler R. R., Hess G.D., An overview of HYSPLIT_4 modelling system for trajectories, dispersion and deposition, Aust. Meteorol. Mag., 47, 1998, 295–308

  • [13] Johansson C., Smedman A-S., Högström U., Critical test of the validity of Monin-Obukhov similarity during convective conditions, J. Atmos. Sci., 58, 2001, 1549–1566 [Crossref]

  • [14] Stohl A., Forster C., Frank A., Seibert P., Wotawa, G., Technical note: The Lagrangian particle dispersion model FLEXPART version 6.2, Atmos. Chem. Phys., 5, 2005, 4739–4799 [Crossref]

  • [15] Woodward J. L., Estimating the Flammable Mass of a Vapor Cloud: A CCPS Concept Book Appendix A, doi: 10.1002/9780470935361, 1999 [Crossref]

  • [16] Lagzi I., Kármán D., Turányi T., Tomlin A. S., Haszpra L., Simulation of the dispersion of nuclear contamination using an adaptive Eulerian grid model, J. Environ. Radioact., 75, 2004, 59–82 [Crossref]

  • [17] Mészáros R., Zsély I. G., Szinyei D., Vincze C., Lagzi I., Sensitivity analysis of an ozone deposition model, Atmos. Environ., 43, 2009, 663–672 [Crossref]

  • [18] Mészáros R., Szinyei D., Vincze C., Lagzi I., Turányi T., Haszpra L., Tomlin A.S., Effect of the soil wetness state on the stomatal ozone fluxes over Hungary, Int. J. Environ. Pollut., 36, 2009, 180–194 [Crossref]

  • [19] Sportisse B., A review of parameterizations for modelling dry deposition and scavenging of radionuclides, Atmos. Environ., 41, 2007, 2683–2698 [Crossref]

  • [20] Baklanov A., Sørensen J. H., Parameterisation of radionuclide deposition in atmospheric long-range transport modelling, Phys. Chem. Earth B., 26, 2001, 787–799 [Crossref]

  • [21] Stockie J.M., Mathematics of atmospheric dispersion modelling, SIAM Rev., 53, 2011, 349–372 [Crossref]

  • [22] Namdeo A., Mitchell G., Dixon R., TEMMS: an integrated package for modelling and mapping urban traffic emissions and air quality, Environ. Model. Softw., 17, 2002, 177–188 [Crossref]

  • [23] Sharan, M. and Gopalakrishnan, S. G., Bhopal gas accident: a numerical simulation of the gas dispersion event, Environ. Model. Softw., 12, 1997, 135–141 [Crossref]

  • [24] Li Z., Briggs G. A., Simple PDF models for convectively driven vertical diffusion, Atmos. Environ., 22, 1988, 55–74 [Crossref]

  • [25] Schulman L. L., Strimaitis D. G., Scire J. S., Development and evaluation of the PRIME plume rise and building downwash model, J. Air Waste Manage. Assoc., 50, 2000, 378–390

  • [26] Abu-Allaban M., Abu-Qudais, H., Impact assessment of ambient air quality by cement industry: a case study in Jordan, Aerosol Air, Qual. Res., 11, 2011, 802–810

  • [27] Lee S-S., Keener T. C., Dispersion modeling of mercury emissions from coal-fired power plants at Coshocton and Manchester, Ohio. The Ohio J. Sci, 2008, 108, 65–69

  • [28] Bajwa K. S., Arya S. P., Aneja, V. P., Modeling studies of ammonia dispersion and dry deposition at some hog farms in North Carolina, J. Air Waste Manage. Assoc., 58, 2008, 1198–1207

  • [29] Krzyzanowski, J., Approaching cumulative effects through air pollution modelling, Water. Air Soil Pollut., 214, 2011, 253–273

  • [30] Carruthers D. J., Holroyd R. J., Hunt J. C. R., Weng W-S., Robins A. G., Thomson D. J., Smith, F. B., UKADMS, a new approach to modelling dispersion in the earth’s atmospheric boundary layer, J. Wind Eng. Ind. Aerod., 52, 1994, 139–153 [Crossref]

  • [31] Carruthers D. J., Dyster S. J., McHugh C. A., Factors affecting inter-annual variability of NOx and NO2 concentrations from single point sources, Clean Air and Environmental Protection, 33, 2003, 15–20

  • [32] McHugh C. A., Carruthers D. J., Edmunds H. A., ADMS-Urban: an air quality management system for traffic, domestic and industrial pollution, Int. J. Environ. Pollut., 8, 1997, 666–674

  • [33] Holmes N. S., Morawska L., A review of dispersion modelling and its application to the dispersion of particles: An overview of different dispersion models available, Atmos. Environ., 40, 2006, 5902–5928 [Crossref]

  • [34] Rama Krishna T. V. B. P. S., Reddy M. K., Reddy R. C., Singh R. N., Impact of an industrial complex on the ambient air quality: Case study using a dispersion model, Atmos. Environ., 39(29), 2005, 5395–5407 [Crossref]

  • [35] Silverman, K. C., Tell, J. G., Sargent, E. V. and Qiu, Z., Comparison of the Industrial Source Complex and AERMOD dispersion models: Case study for human health risk assessment, J. Air Waste Manage. Assoc., 57, 2007, 1439–1446

  • [36] Athanassiadou M., Baker J., Carruthers D., Collins W., Girnary S., Hassell D., Hort M., Johnson C., Johnson K., Jones R., Thomson D., Trought N., Witham C., An assessment of the impact of climate change on air quality at two UK sites, Atmos. Environ., 44, 2010, 1877–1886 [Crossref]

  • [37] Leelossy Á., Mészáros R., Lagzi I., Short and long term dispersion patterns of radionuclides in the atmosphere around the Fukushima Nuclear Power Plant, J. Environ. Radioact., 102, 2011, 1117–1121 [Crossref]

  • [38] Bubbico R., Mazzarotta, B., Accidental release of toxic chemicals: influence of the main input parameters on consequence calculation, J. Hazard. Mater., 151, 2008, 394–406 [Crossref]

  • [39] Zhang J., Hodgson J., Erkut, E., Using GIS to assess the risks of hazardous materials transport in networks, Eur. J. Oper. Res., 121, 2000, 316–329 [Crossref]

  • [40] Pudykiewicz J., Numerical simulation of the transport of radioactive cloud from the Chernobyl nuclear accident, Tellus B, 40B, 1988, 241–259 [Crossref]

  • [41] Piedelievre J. P., Musson-Genon, L., Bompay, F., MEDIA — An Eulerian model of atmospheric dispersion: First validation on the Chernobyl release, J. Appl. Meteorol., 29, 1990, 1205–1220 [Crossref]

  • [42] Dacre H. F., Grant A. L. M., Hogan R. J., Belcher S. E., Thomson D. J., Devenish B. J., Marenco F., Hort M. C., Haywood J. M., Ansmann A., Mattis I., Clarisse L., Evaluating the structure and magnitude of the ash plume during the initial phase of the 2010 Eyjafjallajökull eruption using lidar observations and NAME simulations, J. Geophys. Res., 116, 2011, D00U03, doi: 10.1029/2011JD015608 [Crossref]

  • [43] Mészáros R., Vincze C., Lagzi I., Simulation of accidental release using a coupled transport (TREX) and numerical weather prediction (ALADIN) model, Idojárás, 114, 2010, 101–120

  • [44] Srinivas C. V., Venkatesan R., Baskaran R., Rajagopal V., Venkatraman B., Regional scale atmospheric dispersion simulation of accidental releases of radionuclides from Fukushima Dai-ichi reactor, Atmos. Environ., 61, 2012, 66–84 [Crossref]

  • [45] Brandt J., Mikkelsen T., Thykier-Nielsen S., Zlatev Z., Using a combination of two models in tracer simulations, Math. Comput. Model., 23, 1996, 99–115 [Crossref]

  • [46] Oettl D., Uhmer U., Development and evaluation of GRAL-C dispersion model, a hybrid Eulerian-Lagrangian approach capturing NO-NO2-O3 chemistry, Atmos. Environ., 45, 2011, 839–847 [Crossref]

  • [47] Pozorski J., Minier J-P., On the Lagrangian turbulent dispersion models based on the Langevin equation, Int. J. Multiphas. Flow, 24, 1998, 913–945 [Crossref]

  • [48] Williams M., Yamada T., A microcomputer-based forecasting model: potential applications for emergency response plans and air quality studies, J. Air Waste Manage. Assoc., 40, 1990, 1266–1274

  • [49] Mikkelsen T., Alexandersen S., Astrup P., Champion H. J., Donaldson A. I., Dunkerley F. N., Gloster J., Sorensen J. H., Thykier-Nielsen S., Investigation of airborne foot-and-mouth disease virus transmission during low-wind conditions in the early phase of the UK 2001 epidemic, Atmos. Chem. Phys., 3, 2003, 2101–2110 [Crossref]

  • [50] Sorensen J. H., Sensitivity of the DERMA long-range Gaussian dispersion model to meteorological input and diffusion parameters, Atmos. Environ., 32, 1998, 4195–4206 [Crossref]

  • [51] Lepicard S., Heling R., Maderich V., POSEIDON/RODOS models for radiological assessment of marine environment after accidental releases: application to coastal areas of the Baltic, Black and North Seas, J. Environ. Radioact., 72, 2004, 153–161 [Crossref]

  • [52] Ghannam K., El-Fadel M., Emissions characterization and regulatory compliance at an industrial complex: An integrated MM5/CALPUFF approach, Atmos. Environ., 69, 2013, 156–169 [Crossref]

  • [53] Levy J. I., Spengler J. D., Hlinka D., Sullivan D., Moon, D., Using CALPUFF to evaluate the impacts of power plant emissions in Illinois: model sensitivity and implications, Atmos. Environ., 36, 2002, 1063–1075 [Crossref]

  • [54] Prueksakorn K., Kim T., Kim S., Kim H., Kim K. Y., Son W., Vongmahadlek C., Review of air dispersion modelling approaches to assess the risk of windborne spread of foot-and-mouth disease virus, J. Environ. Prot., 3, 2012, 1260–1267 [Crossref]

  • [55] Zhou Y., Levy J. I., Hammitt J. K., Evans, J. S., Estimating population exposure to power plant emissions using CALPUFF: a case study in Beijing, China, Atmos. Environ., 37, 2003, 815–826 [Crossref]

  • [56] Yamada T., Bunker S., and Moss M., Numerical simulations of atmospheric transport and diffusion over coastal complex terrain, J. Appl. Meteorol., 31, 1992, 565–578 [Crossref]

  • [57] Wang G., Ostoja-Starzewski M., Influence of topography on the Phoenix CO2 dome: a computational study, Atmos. Sci. Lett., 5, 2004, 103–107 [Crossref]

  • [58] Wu J., Lu C-H., Chang S-J., Yang Y-M, Chang B-J., Teng J-H., Three-dimensional dose evaluation system using real-time wind field information for nuclear accidents in Taiwan, Nucl. Instrum. Methods Phys. Res. A, 565, 2006, 812–820

  • [59] Yamada T., Merging CFD and atmospheric modeling capabilities to simulate airflows and dispersion in urban areas, Comput. Fluid Dyn. J., 2004, 13, 329–341

  • [60] Garner M. G., Hess G. D., Yang, X., An integrated modelling approach to assess the risk of wind-borne spread of foot-and-mouth disease virus from infected premises, Environ. Model. Assess., 11, 2006, 195–207 [Crossref]

  • [61] Long N. Q., Truong Y., Hien P. D., Binh N. T., Sieu L. N., Giap T. V., Phan N. T., Atmospheric radionuclides from the Fukushima Dai-ichi nuclear reactor accident observed in Vietnam, J. Environ. Radioact., 111, 2012, 53–58 [Crossref]

  • [62] McGowan H., Clark A., Identification of dust transport pathways from Lake Eyre, Australia using HYSPLIT, Atmos. Environ., 42, 2008, 6915–6925 [Crossref]

  • [63] Shan W., Yin Y., Lu H., Liang S., A meteorological analysis of ozone episodes using HYSPLIT model and surface data. Atmos. Res., 2009, 93, 767–776 [Crossref]

  • [64] Challa V. S., Indrcanti J., Baham J. M., Patrick C., Rabarison M. K., Young J. H., Hughes R., Swanier S. J., Hardy M. G., Yerramilli A., Sensitivity of atmospheric dispersion simulations by HYSPLIT to the meteorological predictions from a meso-scale model, Environ. Fluid. Mech., 8, 2008, 367–387 [Crossref]

  • [65] Wain A. G., Lee S., Mills G. A., Hess G. D., Cope M. E., Tindale N., Meteorological overview and verification of HYSPLIT and AAQFS dust forecasts for the duststorm of 22–24 October 2002, Aust. Meteorol. Mag., 55, 2006, 35–46

  • [66] Stohl A., Hittenberger M., Wotawa G., Validation of the Lagrangian particle dispersion model FLEXPART against large-scale tracer experiment data, Atmos. Environ., 32, 1998, 4245–4264 [Crossref]

  • [67] Ryall D. B., Maryon R. H., Validation of the UK Met Office’s NAME model against the ETEX dataset, Atmos. Environ., 32, 1998, 4256–4276

  • [68] de Foy B., Burton S. P., Ferrare R.A., Hostetler C. A., Hair J. W., Wiedinmyer C., Molina, L. T., Aerosol plume transport and transformation in high spectral resolution lidar measurements and WRF-FLEXPART simulations during the MILAGRO Field Campaign, Atmos. Chem. Phys., 11, 2011, 3543–3563 [Crossref]

  • [69] Warneke C., Froyd K. D., Brioude J., Bahreini R., Brock C. A., Cozic J., de Gouw J. A., Fahey D. W., Ferrare R., Holloway J. S., Middlebrook A. M., Miller L., Montzka S., Schwarz J. P., Sodemann H., Spackman J. R., Stohl, A., An important contribution to springtime Arctic aerosol from biomass burning in Russia, Geophys. Res. Lett., 37, 2010, L01801, doi: 10.1029/2009GL041816 [Crossref]

  • [70] Stohl A., Seibert P., Wotawa G., Arnold D., Burkhart J. F., Eckhardt S., Tapia C., Vargas A., Yasunari T. J., Xenon-133 and caesium-137 releases into the atmosphere from the Fukushima Dai-ichi nuclear power plant: determination of source term, atmospheric dispersion, and deposition, Atmos. Chem. Phys., 11, 2011, 28319–28394 [Crossref]

  • [71] Koracin D., Vellore R., Lowenthal D. H., Watson J. G., Koracin J., McCord T., DuBois D. W., Chen L-W. A., Kumar N., Knipping E. M., Wheeler N. J. M., Craig K., Reid S., Regional source identification using Lagrangian stochastic particle dispersion and HYSPLIT backward-trajectory models, J. Air Waste Manage. Assoc., 61, 2011, 660–672

  • [72] Povinec P.P., Sykora I., Gera M., Holy K., Brestaková L., Kovácik A., Fukushima-derived radionuclides in ground-level air of Central Europe: a comparison with simulated forward and backward trajectories, J. Radioanal. Nucl. Ch., 295, 2013, 1171–1176 [Crossref]

  • [73] Bey I., Jacob D., Yantosca M., Logan J., Field B., Fiore A., Li Q, Liu H, Mickley L, Schultz M., Global modeling of tropospheric chemistry with assimilated meteorology: Model description and evaluation, J. Geophys.Res., 106, 2001, 23073–23096 [Crossref]

  • [74] Grell G. A., Peckham S. E., McKeen S., Schmitz R., Frost G., Skamarock W. C., Eder B., Fully coupled “online” chemistry within the WRF model, Atmos. Environ., 39, 2005, 6957–6975 [Crossref]

  • [75] Wang K., Zhang Y., Jang C., Phillips S., Wang B., Modeling intercontinental air pollution transport over the trans-Pacific Region in 2001 using Community Multiscale Air Quality modeling system, J. Geophys. Res., 114, 2009, D04307 [Crossref]

  • [76] Garcia-Menendez F., Odman M. T., Adaptive grid use in air quality modeling, Atmosphere, 2, 2011, 484–509

  • [77] Ghorai S., Tomlin A. S., Berzins M., Resolution of pollutant concentrations in the boundary layer using a fully 3D adaptive gridding technique, Atmos. Environ., 34, 2000, 2851–2863

  • [78] Lagzi I., Tomlin A. S., Turányi T., Haszpra L., Mészáros R., Berzins M., The simulation of photochemical smog episodes in Hungary and Central Europe using adaptive gridding models, Lect. Notes Comp. Sci., 2074, 2001, 67–77 [Crossref]

  • [79] Lagzi I., Tomlin S. A., Turányi T., Haszpra, L., Modelling photochemical air pollutant formation in Hungary using an adaptive grid technique, Int. J. Environ. Pollut., 36, 2009, 44–58 [Crossref]

  • [80] Tomlin A. S., Ghorai S., Hart G., Berzins M., 3-D Multi-scale air pollution modelling using adaptive unstructured meshes, Environ. Model. Softw., 15, 2000, 681–692 [Crossref]

  • [81] Zegeling P. A., R-refinement with finite elements or finite differences for evolutionary PDE models, Appl. Numer. Math., 26, 1998, 97–104 [Crossref]

  • [82] Zegeling P. A., Lagzi I., Izsak F., Transition of Liesegang precipitation systems: simulations with an adaptive grid PDE method, Commun. Comput. Phys., 10, 2011, 867–881

  • [83] Ascher U., Numerical methods for evolutionary differential equations. Computational science and engineering. Society for Industrial and Applied Mathematics (SIAM), Philadelphia, 2008

  • [84] Grossmann C., Roos H., Stynes M., Numerical Treatment of Partial Differential Equations. Universitext, Springer, Berlin, 2007

  • [85] Thomas J. W., Numerical partial differential equations: finite difference methods, volume 22 of Texts in Applied Mathematics. Springer-Verlag, New York, 1995

  • [86] Versteeg H., Malalasekera W., An introduction to computational fluid dynamics: the finite volume method. Pearson Education Australia, 2007

  • [87] Huebner K., The Finite Element Method for Engineers. A Wiley-Interscience publication. Wiley, New York, 2001

  • [88] Nair R. D., Thomas S. J., Loft R. D., A discontinuous Galerkin transport scheme on the cubed sphere. Mon. Weather Rev., 2005, 133, 814–828

  • [89] Faragó I., Havasi Á., Operator splitting and their applications, Mathematics Research Development Series, Nova Science Publishers, Inc., New York, 2009

  • [90] Lanser D., Verwer J. G., Analysis of operator splitting for advection-diffusion-reaction problems in air pollution modelling, J. Compute. Appl. Math., 111, 1999, 201–216 [Crossref]

  • [91] Marchuk G. I., Methods of Splitting. Nauka, Moscow, 1988 (in Russian)

  • [92] Yanenko N. N., On convergence of the splitting method for heat equation with variable coefficients. Journal of Computational Mathematics and Mathematical Physics 2, 1962 (in Russian)

  • [93] Zlatev Z., Computer Treatment of Large Air Pollution Models, Kluwer Academic Publisher, 1995

  • [94] Dimov I., Faragó I., Havasi Á., Zlatev Z., Operator splitting and commutativity analysis in the Danish Eulerian Model, Math. Comput. Simul, 67, 2003, 217–233

  • [95] Dimov I., Faragó I., Havasi Á., Zlatev, Z., Different splitting techniques with application to air pollution models, Int. J. Environ. Pollut., 32(2), 2008, 174–199 [Crossref]

  • [96] Strang G., On the construction and comparison of difference schemes, SIAM J. Numer. Anal., 5, 1968, 506–517 [Crossref]

  • [97] Csomós P., Havasi Á., Faragó I., Weighted sequential splittings and their analysis, Comp. Math. Appl., 50, 2005, 1017–1031 [Crossref]

  • [98] Strang G., Accurate partial difference methods I: Linear Cauchy problems, Arch. Ration. Mech. An., 12, 1963, 392–402 [Crossref]

  • [99] Foster I., Kesselman C., Tuecke S., The anatomy of the grid, Intl. J. High Perf. Comput. Appl, 15, 2001, 200–222

  • [100] Jacob B., Brown M., Fukui K., Trivedi N., Introduction to Grid computing. IBM Redbooks, Vervante, Springville, Utah, 2005

  • [101] Sterling T. L, Bell G., Beowulf Cluster Computing With Linux, MIT Press, 2002

  • [102] Adiga N. R., Blumrich M. A., Chen D., Coteus P., Gara A., Giampapa M. E., Heidelberger P., Singh S., Steinmacher-Burow B. D., Takken T., Tsao M., Vranas P., Blue Gene/L torus interconnection network, IBM J. Res. Dev., 49, 2005, 265–276

  • [103] Hempel R., The MPI standard for message passing. Proc. Intl. Conf. and Exhibit. On High Perf. Comp and Networking II, 1994, 247–252

  • [104] Sunderam V. S., PVM: A framework for parallel distributed computing, Concurrency-Pract. Ex., 2, 1990, 315–339 [Crossref]

  • [105] Sun X.-H., Chen Y., Reevaluating Amdahl’s law in the multicore era, J. Parallel Distrib. Comput., 70, 2010, 183–188 [Crossref]

  • [106] General Purpose Computation on Graphics Hardware, http://gpgpu.org/

  • [107] Mészáros R., Molnár F., Izsák F., Kovács T., Dombovári P., Steierlein Á., Nagy R., Lagzi I., Environmental modeling using graphical processing unit with CUDA, Idojárás, 116, 2012, 237–251

  • [108] Molnár F., Szakály T., Mészáros R., Lagzi I., Air pollution modelling using a Graphics Processing Unit with CUDA, Comput. Phys. Commun., 181, 2010, 105–112 [Crossref]

  • [109] Pardyjak E. R., Singh B., Norgren A., Willemsen P., Using video gaming technology to achieve low-cost speed up of emergency response urban dispersion simulations, in: Seventh Symposium on the Urban Environment, University of Utah, Salt Lake City and University of Minnesota, Duluth, 2007

  • [110] Senocak I., Thibault J., Caylor M., Rapid-response urban CFD simulations using a GPU computing paradigm on desktop supercomputers, in: Eighth Symposium on the Urban Environment, Phoenix, Arizona, 2009, J19.2

  • [111] Simek V., Dvorak R., Zboril F., Kunovsky J., Towards accelerated computation of atmospheric equations using CUDA, in: Proceedings of the UK Sim 2009. 11th International Conference on Computer Modelling and Simulation, 2009, 449–454

  • [112] Januszewski M., Kostur M., Accelerating numerical solution of stochastic differential equations with CUDA, Comput. Phys. Commun., 181, 2010, 183–188 [Crossref]

  • [113] Michéa D., Komatitsch D., Accelerating a threedimensional finite-difference wave propagation code using GPU graphics cards, Geophys. J. Int., 182, 2010, 389–402

  • [114] Micikevicius P., 3D Finite difference computation on GPUs using CUDA. Proc. 2nd Workshop General Purpose Processing on Graphics Processing Units, ACM, 2009, 79–84

  • [115] Molnár F., Izsák F., Mészáros R., Lagzi I., Simulation of reaction-diffusion processes in three dimensions using CUDA, Chemometr. Intell. Lab., 108, 2011, 76–85 [Crossref]

  • [116] Sanderson A. R., Meyer M. D., Kirby R. M., Johnson C. R., A framework for exploring numerical solutions of advection-reaction-diffusion equations using a GPU-based approach, Comput. Vis. Sci., 12, 2009, 155–170 [Crossref]

  • [117] Che S., Boyer M., Meng J., Tarjan D., Sheaffer J. W., Skadron K., A performance study of general purpose applications on graphics processors using CUDA. J. Parallel Distr. Com., 2008, 68, 1370–1380 [Crossref]

  • [118] Garland M., Le Grand S., Nickolls J., Anderson J., Hardwick J., Morton S., Phillips E., Zhang Y., Volkov, V., Parallel computing experiences with CUDA, Micro IEEE, 28, 2008, 13–27

  • [119] Krishnaprasad S., Uses and abuses of Amdahl’s law, J. Comp. Sci. Coll., 17, 2001, 288–293

  • [120] Gustafson J., Re-evaluating Amdahl’s law, Communications of the ACM, 31, 1988, 532–533

  • [121] El-Nashar A. I., To Parallelize or not to parallelize, speed up issue, Int. J Dist. Parallel Syst., 2, 2011, 2

  • [122] Ostromsky T., Zlatev Z., Parallel and GRID implementation of a large scale air pollution model. Numerical Methods and Applications Lect., Notes Comput. Sc., 4310, 2007, 475–482

  • [123] Todorova A., Syrakov D., Gadjhev G., Georgiev G., Ganev K.G., Prodanova M., Miloshev N., Spiridonov V., Bogatchev A., Slavov K., Grid computing for atmospheric composition studies in Bulgaria, Earth Sci. Inf., 3, 2010, 259–282 [Crossref]

  • [124] Roberti D. R., Souto R, P., de Campos Velho H. F., Degrazia G. A., Anfossi D., Parallel implementation of a Lagrangian stochastic model for pollutant dispersion, Int. J. Parallel Program., 33, 2005, 485–498

  • [125] Srinivas C. V., Venkatesan R., Muralidharan N. V., Das S., Dass H., Kumar P.E., Operational mesoscale atmospheric dispersion prediction using a parallel computing cluster, J. Earth Syst. Sci., 115, 2006, 315–332 [Crossref]

  • [126] Alexandrov V. N., Owczarz W., Thomson P. G., Zlatev Z., Parallel runs of a large air pollution model on a grid of Sun computers, Math. Comput. Simul., 65, 2004, 557–577 [Crossref]

  • [127] Georgiev K., An algorithm for parallel implementations of an Eulerian smog model. Numerical Methods and Applications Lect., Notes Comput. Sc., 2542, 2003, 463–470

  • [128] Georgiev K., Ostromsky T., Zahari Z., New parallel implementation of an air pollution computer model — performance study on an IBM blue gene/p computer. Large-Scale Scientific Computing Lect. Notes Comput. Sc., 7116, 2012, 283–290 [Crossref]

  • [129] Ostromsky T., Zlatev Z., Parallel implementation of a large-scale 3-D air pollution model. Large-Scale Scientific Computing Lect, Notes Comput. Sc., 2179, 2001, 309–316

  • [130] Philippe C., Coppalle A., Atmospheric dispersion and chemical pollutant transformation simulated with parallel calculations using two PC clusters, Int. J. Environ. Pollut., 22, 2004, 133–143 [Crossref]

  • [131] Chen Q., Prediction of room air motion by Reynoldsstress models. Build. Environ., 1996, 31(3), 233–244 [Crossref]

  • [132] Rossi R., Iaccarino G., Numerical simulation of scalar dispersion downstream of a square obstacle using gradient-transport type models, Atmos. Environ., 43, 2009, 2518–2531 [Crossref]

  • [133] Baklanov A., Application of CFD methods for modelling in air pollution problems: possibilities and gaps, Environ. Monit. Assess., 65, 2000, 181–189 [Crossref]

  • [134] Cheng W. C., Liu, C-H., Large-eddy simulation of flow and pollutant transports in and above twodimensional idealized street canyons, Bound-Lay. Meteorol., 139, 2011, 411–437 [Crossref]

  • [135] Li X-X., Liu C-H., Leung D. Y. C., Large-eddy simulation of flow and pollutant dispersion in high-aspectratio urban street canyons with wall model, Bound-Lay. Meteorol., 129, 2008, 249–268 [Crossref]

  • [136] Balczó M., Balogh M., Goricsán I., Nagel T., Suda J. M., Lajos T., Air quality around motorway tunnels in complex terrain: computational fluid dynamics modeling and comparison to wind tunnel data, Idojárás, 115, 2011, 179–204

  • [137] Di Sabatino S., Buccolieri R., Pulvirenti B., Britter R. E., Flow and pollutant dispersion in street canyons using FLUENT and ADMS-Urban. Environ. Model. Assess., 13, 2008, 369–381 [Crossref]

  • [138] Milliez M., Carissimo B., Numerical simulations of pollutant dispersion in an idealized urban area, for different meteorological conditions, Bound-Lay. Meteorol., 122(2), 2007, 321–342 [Crossref]

  • [139] Tominaga Y., Mochida A., Yoshie R., Kataoka H., Nozu T., Yoshikawa M., Shirasawa, T., AIJ guidelines for practical applications of CFD to pedestrian wind environment around buildings, J. Wind Eng. Ind. Aerod., 96, 2008, 1749–1761 [Crossref]

  • [140] Tewari M., Kusaka H., Chen F., Coirier W.J., Kim S., Wyszogrodzki A. A., Warner, T. T., Impact of coupling a microscale computational fluid dynamics model with a mesoscale model on urban scale contaminant transport and dispersion, Atmos. Res., 96, 2010, 656–664 [Crossref]

  • [141] Van Dop, H., Addis, R., Fraser, G., Girardi, F., Graziani, G., Inoue, Y., Kelly, N., Klug, W., Kulmala, A., Nodop, K., Pretel, J., ETEX: A Europian Tracer Experiment; Observations, dispersion modelling and emergency response, Atmos. Environ. 32, 1998, 4089–4094

  • [142] Zhang, Y: Online-coupled meteorology and chemistry models: history, current status, and outlook, Atmos. Chem. Phys., 8, 2008, 2895–2932 [Crossref]

  • [143] Molteni, F.; Buizza, R.; Palmer, T. N.; Petroliagis, T., The ECMWF Ensemble Prediction System: Methodology and validation, Q. J. Roy, Meteor. Soc., 122, 1996, 73–119 [Crossref]

About the article

Published Online: 2014-08-06

Published in Print: 2014-09-01

Citation Information: Open Geosciences, ISSN (Online) 2391-5447, DOI: https://doi.org/10.2478/s13533-012-0188-6. Export Citation

© 2014 Versita Warsaw. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. (CC BY-NC-ND 3.0)

Comments (0)

Please log in or register to comment.
Log in