1. INTEGRATION OF MEASURED, MODELLED & REMOTELY SENSED AIR QUALITY DATA & IMPACTS ON THE SOUTH AFRICAN HIGHVELD Kubeshnie Bhugwandin - October 2007

2. Overview Introduction Aim of Study Hypothesis Data and Methodology Preliminary Results Problems Encountered

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. Introduction

5. Several datasets have been created Never been an integration of datasets derived from the different methods of air quality This study proposes to compare surface data using a GIS in order to determine the most accurate estimate of ground level SO 2 and NO 2 concentrations

6. Introduction

7. Aim of Study To integrate air quality data to determine most accurate ground level SO 2 and NO 2 concentrations Improvement of modelled concentration fields using measurements Determine how satellite retrievals compare to ground based measurements Limited studies conducted to assess impacts

8. Aim of Study To assist Eskom in quantifying impacts and assessing potential risk To produce one integrated set of: - ambient air quality data - maps of potentially sensitive ecosystems -Maps of potential exposure to poor air quality by population groupings Over arching aim to improve model accuracy to assist in better predicts and decion making in this region

9. Hypotheses That modelled air quality predictions can be improved using measured data That satellite retrievals of SO 2 and NO 2 concentrations are representative of surface concentrations That integration of available datasets with a GIS will improve the evaluation of impacts from power station emissions on ecosystems and human health

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

11. Data & Methodology Comparisons to be made a) SCIAMACHY & MODELLED {annual avg} b) SCIAMACHY & MEASURED {monthly and annual avg} c) MODELLED & MEASURED {maximum hourly,daily and annual avg} Modelled fields adjusted by a correction factor New layer overlayed with population density, towns, land cover, vegetation and ecosystem datasets to assess risk from power station emissions

12. Preliminary Results

16. Problems Encountered Unavailablity of 2003 SCIAMACHY data Earliest files from September 2004. Unable to geo-reference files in TNT MIPS, GEO MEDIA & ERDAS Files in HDF version 4 formatt TEMIS website gives global / daily coverage. Suggestion is to allow user to retrieve data for a specific location.

17. Problems Encountered

18. Thank you !