Surface ozone modelling Surface ozone modelling with wind field and with wind field and orography in Kyivorography in Kyiv..

11 A.V. Shavrina, A.V. Shavrina, 22V.A. Dyachuk , V.A. Dyachuk , 33V. I.Nochvaj, V. I.Nochvaj, 44A.A. Veles A.A. Veles

11 Main Astronomical Observatory of National Academy of Main Astronomical Observatory of National Academy of Sciences, Ukraine.Sciences, Ukraine.22 Institute of Hydrometeorology, Ukraine.Institute of Hydrometeorology, Ukraine.33National University ”Kyiv-Mogyla Academy”.National University ”Kyiv-Mogyla Academy”.

Investigation Investigation StagesStages: : Observation Observation ModelingModeling Model verification and optimizationModel verification and optimization pollution forecastpollution forecastObjectivesObjectives:: MonitoringMonitoring Air quality managementAir quality management

Directive 2002/3/EC of the European Parliament and of theCouncil of 12 February 2002 relating toozone in ambient air. OJ L 67, 3 March 2002.

Table. Threshold values for ozone concentrations (in ppb)threshold for: concentr

ationaveragingperiod

health protectionvegetation protection

population informationpopulation warning

551003290

180

8 h1 h

24 h1 h1 h

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.

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

Air Toxics

PM

Acid Rain

Visibility

Ozone

Regulating Air Pollution: One-Regulating Air Pollution: One-Atmosphere ApproachAtmosphere ApproachMobile Mobile

SourcesSources

Industrial Industrial SourcesSources

Area Area SourcesSources

(Cars, trucks, airplanes, boats, etc.)

(Power plants, factories, refineries/chemical plants, etc.)

(Homes, small business, farming equipment, etc.)

NOx, VOC,NOx, VOC,ToxicsToxics

NOx, VOC, NOx, VOC, SOx, ToxicsSOx, Toxics

NOx, VOC,NOx, VOC,ToxicsToxics

Chemistry

Meteorology

Atmospheric Deposition

Troposphere ozone formationTroposphere ozone formation

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)

The SAIMM is a primitive-equation mesoscale meteorologicalmodel, designed for simulation of mesoscale airflows generated bydifferential surface heating and terrain irregularities. The model ishydrostatic and incompressible. The model includes a detailedtreatment of the atmospheric surface and planetary boundary layers,along with the underlying soil layer. The soil layer is coupled to theatmospheric surface layer via a surface heat budget.

The model utilizes a terrain-following vertical coordinate system withvariable vertical grid spacing. The model generates three-dimensionalfields of wind (horizontal and vertical components), potentialtemperature, and specific humidity and planetary-boundary-layerheight field which can be processed to represent "mixing height" in anair quality model.

The SAIMM is based on the Colorado State University MesoscaleModel originally developed by Pielke (1974) and modified over pastyears by Pielke and his colleagues at the University of Virginia andColorado State University.

The Urban Airshed Model (UAM) program wasoriginally developed by Systems Applications International(SAI) and has been maintained by SAI for over 25 years.

The UAM-V is a three-dimensional photochemical gridmodel designed to calculate the concentrations of both inertand chemically reactive pollutants by simulating the physicaland chemical processes in the atmosphere that affect pollutantconcentrations.

The basis for the model is the atmospheric diffusion orspecies continuity equation. This equation represents a massbalance in which all of the relevant emissions, transport,diffusion, chemical reactions, and removal processes areexpressed in mathematical terms. The model is usuallyexercised over a 48- to 120-hour ozone episode period.

Emission from motorway traffic in Kiev (raster model).

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

Surface classification from image data (Kyiv)

Terra ASTER Image 12.08.2001

2 2 Km

0

Classes

- water

- wood

- sparse growth of trees, shrubbery

- grass

- idustrial urban surface

- marginal land

-send light surface

- water protection zone

The percent coverage of land-use categories are specified at each horizontal gridlocation for use in the dry deposition calculations. Land-use categories are obtainedfrom 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 ratesfor the internal calculation of photolysis rates.

Wind field simulation with the surface model.

TerrainGridded 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 ComponentsHorizontal wind components (u and v) are specified hourly foreach 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.

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

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

OZONE, c (ppb)

Value

0 - 12

12-24

24-36

36-48

48-60

60-72

72-54

84-96

96-108

¥

11 380 0 Meters

#0Botanic Garden

ConclusionsConclusions Ozone distribution (for 19 Aug 2000, 14h) demonstrates, that an area of 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 Botanic Garden is not the most polluted(about 60 ppb) and other parts of Kiev (north-east) can be characterized by more enhanced ozone Kiev (north-east) can be characterized by more enhanced ozone concentrations (up to 104 ppb). concentrations (up to 104 ppb).

The use of GIS optimizes the process of data preparation and analysis.The use of GIS optimizes the process of data preparation and analysis.

At present, measurements of tropospheric ozone in Kyiv are inadequate, At present, measurements of tropospheric ozone in Kyiv are inadequate, relying on a single measurement station. As such, local authorities lack relying on a single measurement station. As such, local authorities lack adequate resources to detect, much less predict, dangerous levels of adequate resources to detect, much less predict, dangerous levels of ozone throughout the metropolitan area.ozone throughout the metropolitan area.

Results of surface ozone modelling have shown the effectiveness of UAM-Results of surface ozone modelling have shown the effectiveness of UAM-V model in the analysis of ozone pollution situation for Kiev area and V model in the analysis of ozone pollution situation for Kiev area and developments of guidelines of the administrative solutions for reduction developments of guidelines of the administrative solutions for reduction of enhanced ozone concentrations.of enhanced ozone concentrations.

The modelling allows to interpolate the data of monitoring points, to The modelling allows to interpolate the data of monitoring points, to evaluate the probability of dangerous ozone levels and to determine evaluate the probability of dangerous ozone levels and to determine trends in ozone variationstrends in ozone variations

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)