Surface ozone modelling with wind field and orography in Kyiv .

1. Surface ozone modelling with wind field and orography in Kyiv. 1 A.V. Shavrina, 2V.A. Dyachuk , 3V. I.Nochvaj, 4A.A. Veles 1 Main Astronomical Observatory of National Academy of Sciences, Ukraine. 2Institute of Hydrometeorology, Ukraine. 3National University ”Kyiv-Mogyla Academy”.

2. Investigation Stages: • Observation • Modeling • Model verification and optimization • pollution forecast Objectives: • Monitoring • Air quality management

4. In the annual reporting of 1999 data on ozone concentrations and exceedances were received by the European Commission from all Member States. The 15 EU Member States provided information on ozone concentrations measured at 1 304 monitoring stations. The threshold value set for the protection of human health (55 ppb, 8h average) was exceeded substantially in all reporting countries. The threshold was exceeded on average on 25 days at each reporting station and during an exceedance the average concentration was about 63 ppb. The threshold value of 200 µg/m3 (hourly average) was exceeded largely and widely (in total 16 countries, 11 EU Member States) on a limited number of days.

6. Seasonal ozone variations at the National Botanical Garden in Kiev for year 2000 .

7. Regulating Air Pollution: One-Atmosphere Approach Mobile Sources Ozone NOx, VOC, Toxics PM (Cars, trucks, airplanes, boats, etc.) Industrial Sources Acid Rain Chemistry Meteorology Visibility NOx, VOC, SOx, Toxics (Power plants, factories, refineries/chemical plants, etc.) Air Toxics Area Sources Atmospheric Deposition NOx, VOC, Toxics (Homes, small business, farming equipment, etc.)

8. Troposphere ozone formation

9. Software for air pollution modeling • UAM-V - The Urban Airshed Model (UAM) program was originally developed by Systems Applications International (SAI)(ICF Consulting/Systems Applications International, Inc) • PMM - Prognostic Meteorological Model -Systems Applications International Mesoscale Model (SAIMM)

14. Emission from motorway traffic in Kiev (raster model).

15. Geostrophic wind direction and surface wind at 14:00h. • (19 August 2000)

16. 2 0 2 Km Surface classification from image data (Kyiv) The percent coverage of land-use categories are specified at each horizontal grid location for use in the dry deposition calculations. Land-use categories are obtained from a geographic information system for each grid cell. Gridded surface albedo indices based on land-use categories are also required for each horizontal grid location. These indices, which cross-reference the albedo values used in the photolysis rate preprocessor, are used to locate the proper photochemical reaction rates for the internal calculation of photolysis rates. • Classes • water • wood • sparse growth of trees, shrubbery • grass • idustrial urban surface • marginal land • send light surface • water protection zone Terra ASTER Image 12.08.2001

17. Wind field simulation with the surface model. Terrain Gridded terrain heights above mean sea level are specified for the coarse grid domain. The terrain file also includes the coordinates of coarse grid cell centers in latitude/longitude coordinates. Wind Components Horizontal wind components (u and v) are specified hourly for each grid cell center. Winds are used to evaluate the horizontal advection terms in the advection/diffusion equation, calculate vertical velocities, calculate surface layer parameters for deposition, determine plume rise characteristics, and diagnose diffusion coefficients.

18. Concentrations of formaldehyde, NO2 and ozone for calculated episode in Kyiv, ppm.

20. The map of simulated ozone concentrations for Kiev, 19 August 2000, at 14:00h.

21. Conclusions • Ozone distribution (for 19 Aug 2000, 14h) demonstrates, that an area of Botanic Garden is not the most polluted(about 60 ppb) and other parts of Kiev (north-east) can be characterized by more enhanced ozone concentrations (up to 104 ppb). • The use of GIS optimizes the process of data preparation and analysis. • At present, measurements of tropospheric ozone in Kyiv are inadequate, relying on a single measurement station. As such, local authorities lack adequate resources to detect, much less predict, dangerous levels of ozone throughout the metropolitan area. • Results of surface ozone modelling have shown the effectiveness of UAM-V model in the analysis of ozone pollution situation for Kiev area and developments of guidelines of the administrative solutions for reduction of enhanced ozone concentrations. • The modelling allows to interpolate the data of monitoring points, to evaluate the probability of dangerous ozone levels and to determine trends in ozone variations

22. ACKNOWLEDGEMENTS We are very grateful Sharon Douglas and Belle Hudischewsskyj from SAI for the codes UAM-V and PPM, and for help and consulting. The research described in this presentation was made possible in part by Award No. OX-4002-KY-02 of the U.S. Civilian Research & Development Foundation for the Independent States of the Former Soviet Union (CRDF)