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INTEGRATION OF MEASURED, MODELLED & REMOTELY SENSED AIR QUALITY DATA & IMPACTS ON THE SOUTH AFRICAN HIGHVELD Kubeshnie Bhugwandin - November 2009.

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Presentation on theme: "INTEGRATION OF MEASURED, MODELLED & REMOTELY SENSED AIR QUALITY DATA & IMPACTS ON THE SOUTH AFRICAN HIGHVELD Kubeshnie Bhugwandin - November 2009."— Presentation transcript:

1 INTEGRATION OF MEASURED, MODELLED & REMOTELY SENSED AIR QUALITY DATA & IMPACTS ON THE SOUTH AFRICAN HIGHVELD Kubeshnie Bhugwandin - November 2009

2 Overview Introduction Study Area Aim of Study Data CALPUFF Modelling Results & Discussion Potential Risk Assessment

3 Introduction S.A. is a major regional contributor to aerosols and trace gases Mpumalanga Highveld is one of the most highly industrialised areas in Southern Africa Emission densities ranked amongst the highest in the world Fifteen of S.A.’s coal fired power stations are located here

4 Study Area

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6 Introduction Several datasets have been created Never been an integration of datasets derived from the different methods of air quality (AQ) monitoring & evaluation This study compared AQ data using a GIS in order to determine the most accurate estimate of ground level SO 2 and NO 2 concentrations

7 Aim of Study Overarching aim is to improve modelled air quality predictions using measured data & to integrate measured, modelled and satellite data to evaluate impacts of power station emissions on ecosystems and human health Ultimate objective is to credibly predict concentrations without reference to fixed ground based monitoring stations

8 Objectives To determine whether:- 1.Modelled ground level air pollution concentration fields can be improved by utilising measured data; 2.Satellite retrievals of SO 2 and NO 2 concentrations are representative of surface concentrations; and 3.Integration of available datasets with a GIS will improve the evaluation of impacts from power station emissions on ecosystems and health

9 Data Data & information for the project: 1.Eskom database of continuous ground based measurements for 2003 2.Modelled data derived from Calpuff dispersion modelling exercise conducted by Eskom 3.SAWS meterological data as an input for dispersion modelling 4.SCIAMACHY retrievals from TEMIS website

10 ESKOM AQ Monitoring Network

11 Eskom Monitoring Eskom AQ monitoring operations accredited with SANAS. Monitoring stations serviced and maintained according to ISO9001 site service procedures Monitoring stations visited once every 2 weeks for routine equipment service and maintenance, analyser for zero and span checks and data collection.

12 CALPUFF Background CALPUFF is a USEPA approved modelling suite. Comprises of CALMET (meteorological model), CALPUFF (dispersion model) and CALPOST (result processing module) Is a regional Langragian Puff model suitable for application in modelling domains between 50 to 200km. Model is able to account for spatial variability of meteorological conditions, dry deposition and dispersion over a variety of differing land surfaces

13 CALPUFF Background The area modelled was approx 160 km (east-west) by 108 km (north-south) The Cartesian receptor grid selected had a resolution of 1770 m by 1770 m SAWS’s ETA-model was used to provide upper air met data for 12 locations Surface met data were included for 9 Eskom monitoring stations and 10 SAWS stations

14 Validation of Model

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16 Distribution Tail Analysis

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22 Impact Assessment SO 2 & NO 2

23 Impact Assessment Model values were replaced with measured values Inverse distance weighted interpolation technique utilised

24 SO 2 Standards

25 NO 2 - Standards

26 DEAT Tolerances

27 DEAT 35Oug/m 3 - Health

28 DEAT 125ug/m 3 - health

29 DEAT 50ug/m 3

30 EC Guideline 20ug/m 3

31 EC Guidline – 30 ug/m 3

32 Thank you !


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