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Methods of determining meteorological data used in air pollution dispersion models.

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Warianty tytułu
PL
Metody wyznaczania danych meteorologicznych użytych w modelach rozprzestrzeniania się zanieczyszczeń.
Języki publikacji
EN
Abstrakty
EN
The methods of determining meteorological data used in air pollution dispersion models are classified and each class is described. Relationships between these methods and different groups of air pollution dispersion models are presented.
PL
Modele rozprzestrzeniania się zanieczyszczeń w powietrzu atmosferycznym wymagają wielu danych wejściowych takich jak: dane o emisji, dane meteorologiczne i dane fizjograficzne. Dane meteorologiczne są wyznaczane za pomocą metod tradycyjnych, preprocesorów meteorologicznych, meteorologicznych modeli diagnostycznych i meteorologicznych modeli prognostycznych. Można zauważyć, że zazwyczaj bardziej skomplikowany model rozprzestrzeniania się zanieczyszczeń wymaga stosowania bardziej zaawansowanych metod wyznaczania pól meteorologicznych. Najczęściej spotykane powiązania między technikami wyznaczania pól meteorologicznych i modelami rozprzestrzeniania się zanieczyszczeń w powietrzu przedstawiono w tabeli 3.
Rocznik
Strony
75--86
Opis fizyczny
Bibliogr. 46 poz.
Twórcy
  • Institute of Environmental Engineering Systems, Warsaw University of Technology, 00-665 Warszawa, ul. Nowowiejska 20, Poland.
Bibliografia
  • [1] MARKIEWICZ M., The fundamentals of air pollution dispersion modelling (in Polish), Warsaw University of Technology Publishing Office, Warsaw, 2004.
  • [2] PASQUILL F., The estimation of the dispersion of windburn material, Meteorol. Magazine, 1963, 90.
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  • [6] LITYŃSKA Z., Determination of the boundary height and the wind shear for Pasquill stability classes based on the data from the four aerological stations and chosen synoptic stations located in Poland for the period of 1966–1980 (in Polish), technical report prepared for Warsaw University of Technology, 1985, PR-8 7.2.2.2, Warsaw.
  • [7] CHRÓŚCIEL St., Calculation of the air contamination based on the ministry guidance (in Polish), Protection of the Atmosphere, 1985, PZiTS, XIII, 470, Warszawa.
  • [8] A meteorological catalogue IMGW (in Polish), MAGTOS, Warsaw, 1979.
  • [9] HOLTSLAG A.A.M., VAN ULDEN A.P., A simple scheme for daytime estimates of the surface fluxes from routine weather data, J. Climate Appl. Meteorol., 1983, 22, 517–529.
  • [10] HOLTSLAG A.A.M., Estimation of atmospheric boundary layer parameters for diffusion applications, J. Climate Appl. Meteorol., 1985, 24, 1196–1207.
  • [11] WIERINGA J., Estimation of mesoscale and local scale roughness for atmospheric transport modelling, Proceedings from the 11th International Conference on “Air Pollution Modelling and its Application”,November, 1980, Amsterdam, the Netherlands, Plenum Press, New York, 1981, 279–295.
  • [12] Proceedings of the workshop on “Objectives for Next Generation Practical Short-Range Atmospheric Dispersion Models”, editors: Olesen H.R., Mikkelsen T., Riso, Denmark, May, 1992.
  • [13] Proceedings of the workshop on “Intercomparision of Advanced Practical Short-Range Atmospheric Dispersion Models”, editor: Cuvelier C., Manno, Switzerland, September, 1993, Joint Research Center, Ispra.
  • [14] Proceedings from the workshop on “Operational Short-Range Atmospheric Dispersion Models for Environmental Impact Assessment in Europe”, editors: Kretzschmar J., Maes G., Cosemans G., Belgium, November, 1994, published in: International Journal of Environment and Pollution, 1995, 5.
  • [15] Proceedings of the workshop on “Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes”, Ostend, Belgium, May, 1996, published in: International Journal of Environment and Pollution, 1997, 8.
  • [16] Proceedings of the workshop on: “Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes”, Rodos, Greece, May, 1998, published in: International Journal of Environment and Pollution, 2000, 14.
  • [17] Proceedings of the workshop on: “Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes”, Rouen, France, October, 1999, published in: International Journal of Environment and Pollution, 2001, 16.
  • [18] Proceedings of the workshop on: “Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes, Belgirate, Italy, May, 2003.
  • [19] OLESEN H.R. et al., An improved dispersion model for regulatory use – the OML, Proceedings from the 19th International Conference on “Air Pollution Modelling and its Application”, editors: Van Dop H., Kallos G., Ierapetra, September, 1991, Plenum Press, New York.
  • [20] HANNA S.R., PAINE J.R., Hybrid plume dispersion model (HPDM) development and evaluation, J. Appl. Meteorol., 1989, 28, 206–224.
  • [21] HANNA S.R., CHANG J.C., HPDM improvements and testing at three field sites, Atmos. Environ., 1992, 27A, 1491–1508.
  • [22] CARRUTHERS D.J. et al., UK atmospheric dispersion modelling system, Proceedings of the 19th NATO/CCMS International Conference on: “Air Pollution Modelling and Application”, editors: Van Dop H., Steyn D.G., September, 1991, Ierapetra, Greece, Plenum Press, New York.
  • [23] CARRUTHERS D.J. et al., Validation of ADMS against wind tunnel data of dispersion from chemical warehouse fires, Atmos. Environ., 1999, 33, 1973–1953.
  • [24] BOHLER T., GUERREIRO C., Verification of the meteorological pre-processor MEPDIM, Proceedings from the 4th workshop on “Harmonisation within Dispersion Modelling for Regulatory Purposes”, May, 1996, Belgium.
  • [25] LEE R.F. et al., AERMOD – the development evaluation, Proceedings from the 21st international conference on “Air Pollution Modelling and its Application”, editors: Gryning S.E., Schiermeier F.A., November, 1995, Baltimore, Maryland, USA, Plenum Press, New York.
  • [26] ŁOBOCKI L., ULIASZ M., A method of boundary layer parameters determination based on the data from routine meteorological station. Technical report (in Polish), Warsaw University of Technology, Warsaw, 1989.
  • [27] SEIBERT P. et al., Mixing height determination for dispersion modelling, Report of working group 2, COST Action 710. Pre-processing of meteorological data for dispersion modelling, 1997.
  • [28] RATTO C.F. et al., Mass consistent models for wind fields over complex terrain: the state of the art, Materials from the Summer School in Truest, 1994, Institute of Theoretical Physics.
  • [29] SEAMAN N.L., Meteorological modelling for air-quality assessments, Atmos. Environ., 2000, 34, 2231–2259.
  • [30] SEINFELD J.H., Ozone air quality models. A critical review, J. Air Pollut. Assoc., 1988, 38, 616–623.
  • [31] SHERMAN C.A., A mass-consistent model for wind fields over complex terrain, J. Appl. Meteorol., 1978, 17, 312–319.
  • [32] DAVIS C.G. et al., Atmospheric transport models for complex terrain, J. Clim. Appl. Meteorol., 1984, 23, 235.
  • [33] GOODIN W.R. et al., A comparison of interpolation methods for sparse data: application to wind and concentration fields, J. Appl. Meteorol., 1979, 18, 761.
  • [34] SCIRE J.S. et al., A user quide for the CALMET meteorological model, Earth Tech. Inc., Concord, MA, 1977.
  • [35] PIELKE R.A., Mesoscale meteorological modelling, Academic Press, Inc, New York, 1986, 2002.
  • [36] STAUFFER D.R., SEAMAN N.L., Use of four-dimensional data assimilation in a limited-area mesoscale model. Part I. Experiments with synoptic-scale data, Mon. Weather Meteorol., 1990, 33, 416–434.
  • [37] STAUFER D.R. et al., Use of four-dimensional data assimilation in a limited-area mesoscale model. Part II. Effects of data assimilation within the planetary boundary layer, Mon. Weather Meteorol., 1991, 119, 734–754.
  • [38] STAUFFER D.R., SEAMAN N.L., Multiscale four-dimensional data assimilation, J. Appl. Meteorol, 1994, 33, 416–434.
  • [39] SEAMAN N. L. et al., Multiscale four-dimensional data assimilation system applied in the San Joaquin Valley during SARMAP. Part I. Modelling design and basic performance characteristics, J. Appl. Meteorol., 1995, 34, 1739–1761.
  • [40] ARDAO-BADEJRO J., STAUFFER D.R., On the relative contribution of the Newtonian relaxation term in a non-hydrostatic mesoscale model used for dynamic analysis, Proceedings from the 11th American Meteorological Society Conference on “Numerical Weather Prediction, Norfolk”, VA, August, 1996.
  • [41] BARNA M., LAMB B., Improving ozone modelling in regions of complex terrain using observational nudging in a prognostic meteorological model, Atmos. Environ., 2000, 34, 4889–4906.
  • [42] JACOBS H.J. et al., The use of nested models for air pollution studies: an application of the EURAD model to SANA episode, J. Appl. Meteorol., 1995, 34, 1301–1319.
  • [43] PIELKE R.A., ULIASZ M., Use of meteorological models as input to regional and mesoscale air quality models, Atmos. Environ., 1998, 32, 1455–1466.
  • [44] SCHAYES G. et al., Topographic vorticity mode mesoscale (TVM) model. Part I. Formulation, J. Appl. Meteorol., 1996, 35, 1815–1823.
  • [45] TANGUAY M. et al., A semi-implicit semi-lagrangian fully compressible regional forecast model, Monthly Weather Rev., 1990, 118, 1970–1980.
  • [46] MARKIEWICZ M., A review of air pollution dispersion models (in Polish), scientific publication of Warsaw University of Technology, 1996, 27, 34–67.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPW6-0008-0030
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