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A numerical simulation of urban and regional meteorology and assessment of its impact on pollution transport A. Starchenko Tomsk State University.

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Presentation on theme: "A numerical simulation of urban and regional meteorology and assessment of its impact on pollution transport A. Starchenko Tomsk State University."— Presentation transcript:

1 A numerical simulation of urban and regional meteorology and assessment of its impact on pollution transport A. Starchenko Tomsk State University

2 Modeling system TSU-IAO was developed To simulate meteorology and pollution transport during historical dates for understanding and management of urban air quality To execute scenario analysis for assessment of possible impact of designed plants, factories, airports or motorways

3 Components of the MS TSU-IAO Model initialization block (terrestrial data, ground-based observations, data of vertical distributions of meteorological parameters, data base of point, area and mobile sources of air pollution) Nonhydrostatic meteorological model Pollution transport model Data visualization block

4 Model initialization block Terrestrial data: topography, land use categories (albedo, soil thermal conductivity, heat capacity, density, evaporation, surface roughness, emissivity, deep soil temperature) Ground-based and vertical observations of wind velocity and direction, air temperature and humidity, atmospheric pressure

5 Numerical nonhydrostatic model Terrain following (zeta) coordinate system Nonhydrostatic hydrodynamic 3D equations 3D equations of heat and humidity exchange Two-equation “k-l” turbulence model 2D equation for surface temperature Assimilation of observed data Nesting technology

6 Pollution transport model Eulerian 3D equations for basic anthropogenic pollutants of near surface layer (dust, CO, SO 2, NO 2 ) Dry deposition (resistance model) Photochemical reactions of Hurley’s GRS- mechanism of troposphere ozone and PM10 generation Data base of distributed point, area, mobile (linear) sources

7 Computational approaches Finite-volume method, 2 nd -order approximations for temporal and spatial derivatives, implicit or explicit-implicit schemes Grids: 50x50x30 for meteorology, 100x100x28 for pollution transport High-performance computations on multiprocessor systems with distributed memory

8 Land use categories (200x200km 2 ) Tomsk Kemerovo r. Tom r. Ob

9 Surface elevation (200x200km 2 ) and roughness Water: 0,0001m Few vegetation: 0,15m Farmland: 0,15m Deciduous forest: 0,5m Mixed forest: 0,7m Evergreen forest: 1,0m Urban area: 1,0m

10 Comparison of predictions with observations

11 Mesoscale model MEMO http://www.auth.gr The original version of the nonhydrostatic model MEMO was developed at the Universitat Karlsruhe. In the last years MEMO has been installed and utilized at several research institutions through Europe.  -z vertical coordinate Nesting technology Horizontal resolution from 1km

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15 Regional (200x200km 2 ) and urban (50x50km 2 ) scales

16 Horizontal wind field at 10:00 15 August 2000

17 Horizontal wind field at 10:00 29 June 2000

18 Vertical wind field at 10:00 26 June 200015 August 2000

19 Prediction of pollutant concentrations

20 Prediction of ozone concentrations (29-30 July 2000)

21 Index of pollution (CO+NO 2 +SO 2 )

22 Conclusions The developed modeling system was applied to investigate a wind field and pollution dispersion nearby Tomsk industrial center The predictions showed a close connection between a local meteorology and air quality in the city and suburban area.Undesirable meteorological situation is calm wind in conjunction with temperature inversion


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