AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA

AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
AN AIR QUALITY BASELINE
ASSESSMENT FOR THE VAAL AIRSHED
IN SOUTH AFRICA
by
René Georgeinna Thomas
A dissertation submitted in partial fulfilment of the requirements
for the degree of
MASTER OF SCIENCE
in the
Department of Geography, Geoinformatics and Meteorology
Faculty of Natural and Agricultural Science
UNIVERSITY OF PRETORIA
November 2008
© University of Pretoria
DECLARATION
I hereby declare that the dissertation that I hereby submit for the degree MSc (Meteorology)
at the University of Pretoria is my own work, and that it has not been previously submitted by
me for degree purposes at any other university. I also declare that all the sources I have
quoted have been indicated and acknowledged by complete references.
This dissertation reflects my input into the Vaal Triangle Priority Area Air Quality
Management Plan – Baseline Characterisation report to the Department of Environmental
Affairs and Tourism (DEAT). A formal letter by DEAT where permission is given for my input
to be used as an MSc dissertation is provided.
____________________
Signature
____________________
Date
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
i
AN AIR QUALITY BASELINE ASSESSMENT FOR THE
VAAL AIRSHED IN SOUTH AFRICA
René Georgeinna Thomas
Promoter:
Department:
University:
Degree:
Prof. C.J.deW. Rautenbach
Geography, Geoinformatics and Meteorology
University of Pretoria
Master of Science (Meteorology)
Summary
The Vaal Triangle is renowned for its highly industrialised activities. With the addition of domestic fuel
burning, vehicle exhaust, mining and agricultural activities, the Vaal Airshed has become highly
polluted. The concerns of the elevated concentrations in the area were raised by the Department of
Environmental Affairs and Tourism (DEAT) when the Vaal Region was declared the first priority area
on 21 April 2006. The basis for this declaration includes: areas that exceed or may exceed air quality
standards, areas associated with significant air quality impacts and areas requiring specific air quality
management actions to rectify the situation.
The purpose of this study is to determine the Status Quo of the Vaal Airshed. The emissions
inventory for the study area includes industrial operations, mining activities, domestic fuel burning and
vehicle tailpipe emissions along major national and regional routes. Priority pollutants (i.e. sulphur
dioxide, nitrogen dioxide and inhalable particulate matter) are assessed with the aid of the US
Environmental Protection Agency approved CALPUFF modelling suite, a non-steady-state
Lagrangian Gaussian puff dispersion model.
From the dispersion simulations an air quality impact assessment is undertaken. The major findings
of the air quality assessment indicate that particulate concentrations are elevated over most areas of
the Vaal Airshed, particularly in residential areas where domestic coal burning occurs and areas
neighbouring major industrial operations. Similarly, elevated sulphur dioxide concentrations occur
over industrial and domestic coal burning areas. Elevated nitrogen dioxide concentrations have a
regional impact over the Vaal Airshed.
Priority areas are identified based on the predicted ambient air concentrations from the priority
pollutants and exposure potential. Source contributions are investigated based on the extent of their
emissions and basis of impacts.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
iv
ACKNOWLEDGEMENTS
The author wishes to express her appreciation to the following persons and organisations for
their assistance and contribution to make this dissertation possible:
•
Dr L Burger, Ms Y Scorgie and Ms H Liebenberg-Enslin from Airshed Planning
Professionals (Pty) Ltd for their guidance and support with this study.
•
Ms N Walton from Gondwana Environmental Solutions (Pty) Ltd for her assessment
on the ambient concentrations in the study area.
•
To industry and the South African Weather Services (SAWS) for the provision of
data for the study.
•
To the Department of Environmental Affairs and Tourism (DEAT) for providing the
opportunity to undertake this study and for providing permission to use this work in
the partial fulfilment of the requirements for the degree of Master of Science.
•
My husband Robert von Gruenewaldt for his unwavering encouragement and
support during the course of this study.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
v
This dissertation is dedicated to my husband
Robert von Gruenewaldt
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
vi
TABLE OF CONTENTS
CHAPTER 1: BACKGROUND ............................................................................................1-1
1.1
1.2
1.3
1.4
1.5
1.6
Introduction ............................................................................................................1-1
The Vaal Airshed Declared a Priority Area ............................................................1-2
Aim of Study ..........................................................................................................1-3
Assumptions and Limitations .................................................................................1-4
Hypotheses............................................................................................................1-5
Outline of report.....................................................................................................1-6
CHAPTER 2: LEGAL REQUIREMENTS AND HUMAN HEALTH CRITERIA ....................2-1
2.1
2.2
2.3
Suspended Particulate Matter ...............................................................................2-2
Sulphur Dioxide .....................................................................................................2-6
Nitrogen Dioxide ....................................................................................................2-9
CHAPTER 3:
DISPERSION SIMULATION AND EMISSIONS QUANTIFICATION
METHODOLOGY..................................................................................................................3-1
3.1
Dispersion Simulation Methodology ......................................................................3-1
3.1.1
CALMET Meteorological Model .....................................................................3-2
3.1.2
CALPUFF Dispersion Model..........................................................................3-9
3.1.3
Model Accuracy ...........................................................................................3-15
3.1.4
Dispersion Model Data Inputs for the Study Area........................................3-15
3.2
Emissions Quantification Methodology................................................................3-18
3.2.1
Industrial Sources ........................................................................................3-18
3.2.2
Domestic Fuel Burning ................................................................................3-18
3.2.3
Mining Operations........................................................................................3-19
3.2.4
Wind Blown Dust from Eskom’s Ash Dams and Dumps..............................3-20
3.2.5
Vehicle Emissions........................................................................................3-21
CHAPTER 4: REGIONAL CLIMATE AND ATMOSPHERIC DISPERSION POTENTIAL
OVER THE VAAL AIRSHED ................................................................................................4-1
4.1
General Synoptic Circulations that Influence Weather over Southern Africa ........4-1
4.1.1
Subtropical Systems ......................................................................................4-2
4.1.2
Tropical Systems ...........................................................................................4-3
4.1.3
Temperate Systems.......................................................................................4-3
4.2
Persistent Elevated Inversions ..............................................................................4-5
4.3
Trans-Boundary Transportation of Air Masses over Southern Africa ....................4-7
4.4
Thermo-Topographic Influences............................................................................4-9
4.4.1
Urban Boundary Layer...................................................................................4-9
4.4.2
Valley Atmospheres.....................................................................................4-11
4.5
Meso-scale Ventilation and Site-specific Dispersion Potential. ...........................4-13
4.5.1
Local Wind Field ..........................................................................................4-17
4.5.2
Temperature Trends ....................................................................................4-22
4.5.3
Precipitation .................................................................................................4-27
4.5.4
Relative Humidity.........................................................................................4-31
4.5.5
Incoming Solar Radiation (Insolation)..........................................................4-33
4.5.6
Surface Pressure Levels..............................................................................4-35
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
vii
CHAPTER 5: MEASURED AMBIENT AIR QUALITY WITHIN THE STUDY AREA...........5-1
5.1
5.2
5.3
5.4
Data Availability .....................................................................................................5-5
Ambient Particulate Concentrations ......................................................................5-7
Ambient Sulphur Dioxide Concentrations ............................................................5-10
Ambient Nitrogen Dioxide Concentrations...........................................................5-13
CHAPTER 6: EMISSIONS INVENTORY FOR THE STUDY AREA....................................6-1
6.1
Industrial Sources ..................................................................................................6-2
6.2
Domestic Fuel Burning ........................................................................................6-16
6.3
Mining Operations ...............................................................................................6-23
6.4
Wind-blow Dust from Eskom’s Ash Dams and Dumps........................................6-24
6.5
Vehicle Emissions ...............................................................................................6-25
6.6
Waste Treatment and Disposal Areas .................................................................6-30
6.6.1
Landfill operations........................................................................................6-30
6.6.2
Incinerator Operations .................................................................................6-31
6.6.3
Waste Water Treatment Works ...................................................................6-32
6.7
Agriculture ...........................................................................................................6-32
6.8
Railway Transport................................................................................................6-32
6.9
Airport Emissions.................................................................................................6-33
6.10 Spontaneous Combustion ...................................................................................6-34
6.11 Transboundary Sources ......................................................................................6-35
6.12 Summary of Emissions Quantified.......................................................................6-35
CHAPTER 7: DISPERSION SIMULATION AND IMPACT ASSESSMENT ........................7-1
7.1
Simulated Results..................................................................................................7-1
7.2
Predicted Data Validation (Measured vs. Modelled)..............................................7-6
7.2.1
Comparison of Measured and Modelled Sulphur Dioxide..............................7-6
7.2.2
Comparison of Measured and Modelled Nitrogen Dioxide ............................7-6
7.2.3
Comparison of Measured and Modelled Inhalable Particulate ....................7-17
7.2.4
Summary of Measured versus Modelled Results ........................................7-17
7.3
Compliance with Ambient Air Quality Guidelines/Standards ...............................7-17
7.4
Priority Areas .......................................................................................................7-31
7.4.1
Exposure Potential of Predicted Ambient Air Concentrations......................7-32
7.4.2
“Hot Spot” Areas ..........................................................................................7-32
CHAPTER 8: CONCLUSIONS ............................................................................................8-1
8.1
8.2
Priority Pollutants within the Vaal Airshed .............................................................8-1
Priority Sources within the Vaal Airshed................................................................8-2
REFERENCES......................................................................................................................9-1
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
viii
LIST OF APPENDICES
APPENDIX
A: Questionnaire to Quantify Industrial Emissions within the Vaal
Airshed……………………………………………………………..…………..…..A-1
APPENDIX B:
Industrial Emissions for the Vaal Airshed………..………………..………B-1
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
ix
LIST OF SYMBOLS
C
CD
:
:
Ground-level concentration (g/m³)
Surface drag coefficient
C
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
:
Average concentration
Distance (m) from the puff centre to the receptor in the along-wind direction
Distance (m) from the puff centre to the receptor in the cross-wind direction
The incremental X and Y distances travelled by the puff
Local Froude number
Gravitational acceleration constant (9.8 m/s²)
Effective height (m) above the ground of the puff centre
Mixed-layer height (m)
Terrain height
An effective obstacle height (m)
Stability-dependent coefficient of exponential decay
Equilibrium length scale
Brunt-Väisälä frequency
Pollutant mass (g) in the puff
Distance from the observational station k to the grid point
User defined weighting parameter for the Step 1 wind field
Distance (m) from the centre of the puff to the receptor
Equilibrium speed of the slope flow
Distance (m) travelled by the puff
The initial value of s at the start of the sampling step
Horizontal wind components
Domain-mean wind
Speed of the domain-mean wind
Vertical wind component (m/s) in Cartesian coordinates
Distance to the crest of the hill
Terrain-following vertical coordinate (m)
Cartesian vertical coordinate (m)
Potential temperature (K)
Potential temperature deficit with respect to the environment
Angle of the terrain relative to the horizontal
Maximum allowable divergence
Standard deviation (m) of the Gaussian distribution in the along-wind direction
Standard deviation (m) of the Gaussian distribution in the cross-wind direction
Standard deviation (m) of the Gaussian distribution in the vertical direction
da
dc
dx, dy
Fr
g
H
h
ht
∆ht
k
Le
N
Q
Rk
R
R
Se
s
s0
u,v
V
|V|
w
x
Z
z
θ
∆θ
α
ε
σx
σy
σz
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
x
LIST OF TABLES
Table 2-1:
Table 2-2:
Table 2-3:
Table 2-4:
Table 2-5:
Table 2-6:
Table 2-7:
Table 2-8:
Table 2-9:
Table 2-10:
Table 2-11:
Table 2-12:
Table 2-13:
Table 2-14:
Table 2-15:
Table 2-16:
Table 2-17:
Table 3-1:
Table 3-2:
Table 3-3:
Table 3-4:
Table 3-5:
Table 3-6:
Table 3-7:
Table 3-8:
Table 3-9:
Table 3-10:
Table 3-11:
Air quality standards for inhalable particulate matter (PM10) for various
countries and organisations. ............................................................................2-4
WHO air quality guideline and interim targets for particulate matter (annual
mean) (WHO, 2005).........................................................................................2-5
WHO air quality guideline and interim targets for particulate matter (daily mean)
(WHO, 2005) ....................................................................................................2-5
National Ambient Air Quality Standards – AQA Schedule 2 ............................2-5
National Ambient Air Quality Standards – Interim Level 1 at 99% ...................2-6
National Ambient Air Quality Standards – Interim Level 2 at 99.5% ................2-6
National Ambient Air Quality Standards at 99.9%............................................2-6
Ambient air quality guidelines and standards for sulphur dioxide for various
countries and organisations .............................................................................2-7
WHO air quality guidelines and interim guidelines for sulphur dioxide (WHO,
2005) ................................................................................................................2-8
National Ambient Air Quality Standards – AQA Schedule 2 at 99% ................2-8
National Ambient Air Quality Standards – Interim Level 1 at 99.5% ................2-8
National Ambient Air Quality Standards – Interim Level 2 at 99.9% ................2-9
Ambient air quality guidelines and standards for nitrogen dioxide for various
countries and organisations .............................................................................2-9
National Ambient Air Quality Standards – AQA Schedule 2 ..........................2-10
National Ambient Air Quality Standards – Interim Level 1 at 99% .................2-10
National Ambient Air Quality Standards – Interim Level 2 at 99.5% ..............2-11
National Ambient Air Quality Standards at 99.9%..........................................2-11
Major features of the CALMET meteorological model. ....................................3-2
A summary of source groups and parameters required as input data into the
CALMET model................................................................................................3-2
Major features of the CALPUFF model ............................................................3-9
Summary of input data used by the CALPUFF dispersion model using the
CALMET meteorological model .....................................................................3-10
Data availability for surface data from industrial and South African Weather
Service (SAWS) meteorological stations within the study area and calculated
upper air from ETA modelled data obtained from the SAWS for the period 2004
to 2006. ..........................................................................................................3-16
Emission factors selected for use in estimating atmospheric emission occurring
as a result of coal, paraffin and wood combustion by households.................3-19
Sources of energy used by households within the Vaal Airshed (based of 2001
Census data and given as a percentage of total energy consumption). ........3-19
Particle size distribution for the typical materials found on the ash dumps (as
obtained from measured data from the Matimba Power Station operations). 3-20
Leaded and unleaded petrol sales within the Vaal Airshed during 2006 as
obtained from Anton Moldan, South African Petroleum Industry Association.......
.....................................................................................................................3-21
Emission factors for non-catalytic converter equipped petrol-driven vehicles
used for the estimation of vehicle emissions..................................................3-22
Emission factors for catalytic converter equipped petrol-driven vehicles used for
the estimation of vehicle emissions................................................................3-22
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
xi
Table 3-12: Diesel sales within the Vaal Airshed during 2006 as obtained from Anton
Moldan, South African Petroleum Industry Association. ................................3-23
Table 3-13: Highveld emission factors for diesel-driven vehicles used in the quantification of
vehicle emissions for the Vaal Airshed. .........................................................3-24
Table 4-1: Evaluation of meteorological stations operated by the SAWS, industry and
various spheres of Government .....................................................................4-15
Table 4-2: Long-term minimum, maximum and mean temperatures measured at SAWS
stations over the study area (as obtained from the SAWS: WB42 – Climate
Statistics)........................................................................................................4-22
Table 4-3: Minimum, maximum and mean temperatures measured at various monitoring
stations operated by industry, various spheres of government and SAWS within
the study area for the period 2006. ................................................................4-23
Table 4-4: Monthly rainfall figures (mm) for the meteorological monitoring stations within
the study area. ...............................................................................................4-28
Table 5-1: Evaluation of monitoring stations operated by industry and various spheres of
Government (after Liebenberg-Enslin et al., 2007). .........................................5-2
Table 5-2: Data availability for monitoring stations in the Vaal Airshed operated by industry
and various spheres of Government (after, Liebenberg-Enslin et al, 2007) (1).5-6
Table 5-3: Monitored inhalable particulate matter at ambient stations operated by industry
and various spheres of government within the Vaal Airshed (after LiebenbergEnslin et al, 2007) (1).........................................................................................5-7
Table 5-4: Measured frequency of daily inhalable particulate exceedance of the SANS limit
of 75 µg/m³ (proposed SA standard) at various monitoring stations operated by
industry and various spheres of government within the study area (after
Liebenberg-Enslin et al, 2007). ........................................................................5-8
Table 5-5: Monitored sulphur dioxide concentrations at ambient stations operated by
industry and government within the Vaal Airshed (after Liebenberg-Enslin et al,
2007) (1). .........................................................................................................5-10
Table 5-6: Measured frequency of hourly and daily sulphur dioxide exceedance of the
SANS limit of 350 µg/m³ and 125 µg/m³ respectively (proposed SA standard) at
various monitoring stations operated by industry and government within the
Vaal Airshed (after Liebenberg-Enslin et al, 2007). .......................................5-11
Table 5-7: Monitored nitrogen dioxide concentrations at ambient stations operated by
industry and government within the Vaal Airshed (after Liebenberg-Enslin et al,
2007) (1). .........................................................................................................5-13
Table 5-8: Measured frequency of hourly nitrogen dioxide exceedance of the SANS limit of
200 µg/m³ (proposed SA standard) at various monitoring stations operated by
government and industry within the Vaal Airshed (after Liebenberg-Enslin et al,
2007). .............................................................................................................5-14
Table 6-1: Industrial sources of atmospheric emissions within the Vaal Airshed and their
associated emissions. ......................................................................................6-5
Table 6-2: Estimated total annual domestic fuel burning emissions (in tons/annum) for the
entire study area (a).........................................................................................6-20
Table 6-3: Inhalable particulate emissions as quantified for various mining activities within
the Vaal Airshed.............................................................................................6-24
Table 6-4: Total annual tailpipe emissions due to vehicle activity calculated per magisterial
area within the Vaal Airshed. .........................................................................6-25
Table 6-5: Landfill operations located within the Vaal Airshed (after Liebenberg-Enslin et al
(2007))............................................................................................................6-31
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
xii
Table 7-1:
Table 7-2:
Table 7-3:
Table 7-4:
Table 7-5:
Table 7-6:
Table 7-7:
Table 7-8:
Table 7-9:
Table 8-1:
Isopleth plots presented in the current section.................................................7-1
Comparison of monitored and modelled sulphur dioxide ground level
concentrations for current baseline conditions within the Vaal Airshed. ..........7-7
Comparison of monitored and modelled nitrogen dioxide ground level
concentrations for current baseline conditions within the Vaal Airshed. ..........7-8
Comparison of monitored and modelled inhalable particulate ground level
concentrations for current baseline conditions within the Vaal Airshed. ..........7-9
Comparison of monitored and modelled sulphur dioxide frequencies of
exceedance of air quality limits due to baseline conditions (Data availabilities
given in brackets after measured frequencies.) .............................................7-10
Comparison of monitored and modelled nitrogen dioxide and inhalable
particulate frequencies of exceedance of air quality limits due to baseline
conditions (Data availabilities given in brackets after measured frequencies.).....
.....................................................................................................................7-10
Predicted maximum air pollutant concentrations due to all source activity within
the Vaal Airshed based on 2004, 2005 and 2006 meteorological conditions (h)....
.....................................................................................................................7-19
Number of people residing in non-compliance (a) areas within Vaal Airshed
exposed to sulphur dioxide, inhalable particulate and nitrogen dioxide
concentrations................................................................................................7-32
Priority “hotspot” zones within the Vaal Airshed indicating the sensitive
receptors and the main contributing sources. ................................................7-34
Priority pollutants and their associated contributing sources and main impact
areas within the Vaal Airshed...........................................................................8-3
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
xiii
LIST OF FIGURES
Figure 1-1:
Figure 1-2:
Boundaries of the Vaal priority area, as declared on 21 April 2006. ................1-2
The extent of the area assessed during the current study including the Vaal
Triangle and the major metropolitan areas of Johannesburg, Soweto, Lenasia,
Ennerdale, Orange Farm, Evaton, Sebokeng and Meyerton. ..........................1-3
Figure 2-1: The effects of inhaled particulate matter to the human lung (after Maddox,
2006). ...............................................................................................................2-3
Figure 3-1: An overview of the CALMET/CALPUFF modelling system (after Scire et al,
2000a). .............................................................................................................3-1
Figure 4-1: Major synoptic circulation types affecting southern Africa and their monthly
frequencies of occurrence over a five year period (after Preston-Whyte and
Tyson, 1988 and Garstang et al., 1996)...........................................................4-2
Figure 4-2: The occurrence of absolutely stable layers over South Africa by circulation type
and time of year. Absolutely stable layers are indicated in block shading,
showing base heights (with 95% confidence limits) and depths (horizontal
dimension is arbitrary) (a) for spatial distribution across South Africa, (b) by
circulation type, and (c) by time of year. (d) Locations of stations. The results
are based on the analysis of a total of 2925 radiosonde ascents taken over the
period 1986-92 (Tyson et al., 1996c). ..............................................................4-6
Figure 4-3: Schematic representation of major low-level transport trajectory models likely to
result easterly or westerly exiting of material from southern African or in
recirculation over the subcontinent (Tyson et al, 1996c)..................................4-8
Figure 4-4: Sketch of the urban boundary layer structure indicating the various (sub) layers
and their names (from Rotach et al., 2004, modified after Oke, 1987). An
unstable daytime urban boundary layer is shown. .........................................4-10
Figure 4-5: Configurations of urban pollution. (a) Urban pollution dome and (b) urban
pollution plume in a stable environment (i.e. early morning following a clear
night). Fanning is indicative of vertical atmospheric stability (after Barry and
Chorley, 1992)................................................................................................4-11
Figure 4-6: Along-valley winds: (a) daytime valley and anti-valley winds; and (b) night time
mountain and anti-mountain winds (after Stull, 1997)....................................4-12
Figure 4-7: Idealised evolution of the cross-valley circulations during a diurnal cycle.
Potential temperature profile corresponds to sounding made from the centre of
the valley (after Stull, 1997). ..........................................................................4-13
Figure 4-8: Locations of surface meteorological stations operated by industry, government
and the SAWS and calculated ETA data points within the study area for which
data were obtained for the study....................................................................4-14
Figure 4-9: Period average wind roses for various monitoring stations operated by industry,
various spheres of government and SAWS within the study area for the period
2004 to 2006 (with the exception of the Makalu monitoring station that has been
assessed for the period 2004 (due to it being decommissioned) and the five
Sasol monitoring stations that were only assessed for October to December
2006 as this was the only data available for the study)..................................4-19
Figure 4-10: Day-time average wind roses for various monitoring stations operated by
industry, various spheres of government and SAWS within the study area for
the period 2004 to 2006 (with the exception of the Makalu monitoring station
that has been assessed for the period 2004 (due to it being decommissioned)
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
xiv
Figure 4-11:
Figure 4-12:
Figure 4-13:
Figure 4-14:
Figure 4-15:
Figure 4-16:
Figure 4-17:
Figure 4-18:
Figure 4-19:
Figure 4-20:
Figure 4-21:
Figure 5-1:
Figure 5-2:
Figure 5-3:
Figure 5-4:
Figure 5-5:
Figure 5-6:
and the five Sasol monitoring stations that were only assessed for October to
December 2006 as this was the only data available for the study). ...............4-20
Night-time average wind roses for various monitoring stations operated by
industry, various spheres of government and SAWS within the study area for
the period 2004 to 2006 (with the exception of the Makalu monitoring station
that has been assessed for the period 2004 (due to it being decommissioned)
and the five Sasol monitoring stations that were only assessed for October to
December 2006 as this was the only data available for the study). ...............4-21
Mean diurnal temperature variations measured at various monitoring stations
operated by industry, various spheres of government and SAWS within the
study area for the period 2006. ......................................................................4-26
Average monthly temperatures measured at various monitoring stations
operated by industry, various spheres of government and SAWS within the
study area for the period 2006. ......................................................................4-26
Monthly measured rainfall for the SAWS meteorological station of
Johannesburg (OR Tambo) for the period 2004 – 2006. ...............................4-30
Monthly measured rainfall for the SAWS meteorological station of Vereeniging
for the period 2004 – 2006. ............................................................................4-30
Monthly measured rainfall for the SAWS meteorological station of Springs for
the period 2005 – 2006. .................................................................................4-31
Mean diurnal variation of relative humidity measured at various monitoring
stations operated by industry, various spheres of government and SAWS within
the study area for the period 2004 -2006. ......................................................4-32
Mean monthly variation of relative humidity measured at various monitoring
stations operated by industry, various spheres of government and SAWS within
the study area for the period 2004 -2006. ......................................................4-33
Mean diurnal variation of solar radiation measured at the Sasol monitoring
station (Steam Station) for the period 2004 -2006. ........................................4-34
Mean monthly variation of solar radiation measured at the Sasol monitoring
station (Steam Station) for the period 2004 -2006. ........................................4-34
Measured surface pressure levels from SAWS monitoring stations over the
study area for the period 2004 - 2006. ...........................................................4-35
Location of Ambient Air Quality Monitoring Stations (including stations owned
by City of Johannesburg (COJ), Sedibeng District Municipality (SDM),
Department of Environmental Affairs and Tourism (DEAT) and Industry). ......5-1
Location of the Sasol ambient monitoring stations within the study area (after
Liebenberg-Enslin et al, 2007). ........................................................................5-4
Location of the ArcelorMittal Steel Vanderbijlpark Steel ambient monitoring
stations (after Liebenberg-Enslin et al, 2007). .................................................5-5
Diurnal profile of monitored inhalable particulate ground level concentrations at
various monitoring stations operated by industry and government within the
study area (after Liebenberg-Enslin et al, 2007). .............................................5-9
Diurnal profile of monitored sulphur dioxide ground level concentrations from
various monitoring stations operated by industry and government within the
Vaal Airshed (after Liebenberg-Enslin et al, 2007). .......................................5-12
Diurnal profile of monitored nitrogen dioxide ground level concentrations from
various monitoring stations operated by industry and government within the
Vaal Airshed (after Liebenberg-Enslin et al, 2007). .......................................5-15
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
xv
Figure 6-1:
Figure 6-2:
Figure 6-3:
Figure 6-4:
Figure 6-5:
Figure 6-6:
Figure 6-7:
Figure 6-8:
Figure 6-9:
Figure 6-10:
Figure 6-11:
Figure 6-12:
Figure 6-13:
Figure 6-14:
Figure 6-15:
Figure 6-16:
Figure 6-17:
Figure 6-18:
Figure 7-1:
Figure 7-2:
Figure 7-3:
Figure 7-4:
Figure 7-5:
Location of the main industrial and mining activities within the Vaal Airshed that
were quantified for the study. ...........................................................................6-4
Total annual sulphur dioxide source emission distribution from industrial,
commercial and institutional sources within the Vaal Airshed........................6-15
Total annual inhalable particulate source emission distribution from industrial,
commercial and institutional sources within the Vaal Airshed........................6-15
Total annual oxides of nitrogen emission distribution from industrial, commercial
and institutional sources within the Vaal Airshed. ..........................................6-16
Spatial distribution of household coal burning within the Vaal Airshed (based on
2001 Census data).........................................................................................6-17
Spatial distribution of household wood burning within the Vaal Airshed (based
on 2001 Census data)....................................................................................6-18
Spatial distribution of household paraffin burning within the Vaal Airshed (based
on 2001 Census data)....................................................................................6-19
Location of household fuel burning areas simulated for the baseline
assessment of the Vaal Airshed.....................................................................6-21
Monthly variations in domestic fuel burning activities that were taken into
account during the simulation of this source (after Annegarn and Sithole, 1999).
.....................................................................................................................6-22
Diurnal variation in domestic fuel burning activities that were taken into account
during the simulation of this source (after Annegarn and Grant, 1999). ........6-22
Layout of the regional and national road network and magisterial districts within
the study area. ...............................................................................................6-27
The layout of the road sources for the quantification of tailpipe emissions and
identification of dispersion modelling areas. ..................................................6-28
Spatial apportionment of vehicle emissions over the highly congested
residential area of Johannesburg and surrounding areas..............................6-29
Diurnal profile of vehicles along national routes within the Vaal Airshed as
obtained from vehicle count data (as obtained from Micros Traffic Monitoring)....
.................................................................................................................6-30
Spectral image for the New Vaal Colliery area, illustrating apparent incidences
of spontaneous coal combustion sites as bright red areas (indicated by circles).
The Lethabo ...................................................................................................6-34
Total annual sulphur dioxide emission distribution from all quantified sources of
emission within the Vaal Airshed. ..................................................................6-36
Total annual inhalable particulate emission distribution from all quantified
sources of emission within the Vaal Airshed..................................................6-36
Total annual oxides of nitrogen emission distribution from all quantified sources
of emission within the Vaal Airshed. ..............................................................6-37
Highest hourly (99.99th percentile) predicted sulphur dioxide ground level
concentrations (µg/m³) within the study area. ..................................................7-2
Highest daily (99.7th percentile) predicted sulphur dioxide ground level
concentrations (µg/m³) within the study area. ..................................................7-2
Annual average predicted sulphur dioxide ground level concentration (µg/m³)
within the study area. .......................................................................................7-3
Highest hourly (99.99th percentile) predicted nitrogen dioxide ground level
concentration (µg/m³) within the study area. ....................................................7-3
Highest daily (99.7th percentile) predicted nitrogen dioxide ground level
concentration (µg/m³) within the study area. ....................................................7-4
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
xvi
Figure 7-6:
Figure 7-7:
Figure 7-8:
Figure 7-9:
Figure 7-10:
Figure 7-11:
Figure 7-12:
Figure 7-13:
Figure 7-14:
Figure 7-15:
Figure 7-16:
Figure 7-17:
Figure 7-18:
Figure 7-19:
Figure 7-20:
Figure 7-21:
Figure 7-22:
Figure 7-23:
Annual average predicted nitrogen dioxide ground level concentration (µg/m³)
within the study area. .......................................................................................7-4
Highest daily (99.7th percentile) predicted inhalable particulate ground level
concentration (µg/m³) within the study area. ....................................................7-5
Annual average predicted inhalable particulate ground level concentration
(µg/m³) within the study area. ..........................................................................7-5
Comparison of simulated highest hourly (99.99th percentile) sulphur dioxide
concentrations with measured highest hourly concentrations (for the period
2006) within the study area. ...........................................................................7-11
Comparison of simulated highest daily (99.7th percentile) sulphur dioxide
concentrations with measured highest daily concentrations (for the period 2006)
within the study area. .....................................................................................7-11
Comparison of simulated annual average sulphur dioxide concentrations with
measured annual average concentrations (for the period 2006) within the study
area. ...............................................................................................................7-12
Comparison of simulated frequency of exceedance of the hourly sulphur dioxide
SA standard of 350 µg/m³ with measured frequencies (for the period 2006)
within the study area. .....................................................................................7-12
Comparison of simulated frequency of exceedance of the daily sulphur dioxide
SA standard of 125 µg/m³ with measured frequencies (for the period 2006)
within the study area. .....................................................................................7-13
Comparison of simulated highest hourly (99.99th percentile) nitrogen dioxide
concentrations with measured highest hourly concentrations (for the period
2006) within the study area. ...........................................................................7-13
Comparison of simulated highest daily (99.7th percentile) nitrogen dioxide
concentrations with measured highest daily concentrations (for the period 2006)
within the study area. .....................................................................................7-14
Comparison of simulated annual average nitrogen dioxide concentrations with
measured annual average concentrations (for the period 2006) within the study
area. ...............................................................................................................7-14
Comparison of simulated frequency of exceedance of the hourly nitrogen
dioxide SANS limit (proposed SA standard) of 200 µg/m³ with measured
frequencies (for the period 2006). ..................................................................7-15
Comparison of simulated highest daily (99.7th percentile) inhalable particulate
concentrations with measured highest daily concentrations (for the period 2006)
within the study area. .....................................................................................7-15
Comparison of simulated annual average inhalable particulate concentrations
with measured annual average concentrations (for the period 2006) within the
study area. .....................................................................................................7-16
Comparison of simulated frequency of exceedance of the daily inhalable
particulate SANS limit (proposed SA standard) of 75 µg/m³ with measured
frequencies (for the period 2006) within the study area. ................................7-16
Hourly predicted exceedance of the SA standards for sulphur dioxide of 350
µg/m³ within the study area............................................................................7-29
Daily predicted exceedance of the SA standards for sulphur dioxide of 125
µg/m³ within the study area............................................................................7-29
Hourly exceedance of various relevant standards/limits for nitrogen dioxide
concentrations within the study area..............................................................7-30
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
xvii
Figure 7-24: Daily exceedance of of various relevant standards/limits for inhalable particulate
concentrations within the study area..............................................................7-30
Figure 7-25: Six priority “hotspot” areas identified within the Vaal Airshed based on predicted
inhalable particulate ground level concentrations. .........................................7-33
Figure 7-26: Sources of potential emissions within the identified priority “hotspot” zone 1
(including sensitive receptors of Sasolburg, Coalbrook and Zamdela) within the
Vaal Airshed...................................................................................................7-35
Figure 7-27: Sources of potential emissions within the identified priority “hotspot” zone 2
within the Vaal Airshed...................................................................................7-36
Figure 7-28: Sources of potential emissions within the identified priority “hotspot” zone 3
(including sensitive receptors of Vanderbijlpark and Sebokeng) within the Vaal
Airshed. ..........................................................................................................7-37
Figure 7-29: Sources of potential emissions within the identified priority “hotspot” zone 4
(including sensitive receptors of Vereeniging and Meyerton) within the Vaal
Airshed. ..........................................................................................................7-38
Figure 7-30: Sources of potential emissions within the identified priority “hotspot” zone 5
(including sensitive receptors of Orange Farm, Evaton and Ennerdale) within
the Vaal Airshed.............................................................................................7-39
Figure 7-31: Sources of potential emissions within the identified priority “hotspot” zone 6
(including the sensitive receptor of Soweto) within the Vaal Airshed.............7-40
Figure 7-32: Receptors assessed for the long-term ground level concentrations ..............7-41
Figure 7-33: Predicted source contributions to total annual sulphur dioxide, nitrogen dioxide
and inhalable particulate emissions and concentrations at various impact
contribution for identified priority “hotspot” zone 1 (including sensitive receptors
of Sasolburg, Coalbrook and Zamdela) within the Vaal Airshed....................7-44
Figure 7-34: Predicted source contributions to total annual sulphur dioxide, nitrogen dioxide
and inhalable particulate emissions and concentrations at various impact
contribution for identified priority “hotspot” zone 2 within the Vaal Airshed....7-45
Figure 7-35: Predicted source contributions to total annual sulphur dioxide, nitrogen dioxide
and inhalable particulate emissions and concentrations at various impact
contribution for identified priority “hotspot” zone 3 (including sensitive receptors
of Vanderbijlpark and Sebokeng) within the Vaal Airshed. ............................7-46
Figure 7-36: Predicted source contributions to total annual sulphur dioxide, nitrogen dioxide
and inhalable particulate emissions and concentrations at various impact
contribution for identified priority “hotspot” zone 4 (including sensitive receptors
of Vereeninging and Meyerton) within the Vaal Airshed. ...............................7-47
Figure 7-37: Predicted source contributions to total annual sulphur dioxide, nitrogen dioxide
and inhalable particulate emissions and concentrations at various impact
contribution for identified priority “hotspot” zone 5 (including sensitive receptors
of Orange Farm, Evaton and Ennerdale) within the Vaal Airshed. ................7-48
Figure 7-38: Predicted source contributions to total annual sulphur dioxide, nitrogen dioxide
and inhalable particulate emissions and concentrations at various impact
contribution for identified priority “hotspot” zone 6 (including sensitive receptors
of Soweto) within the Vaal Airshed. ...............................................................7-49
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
xviii
LIST OF ACRONYMS AND ABBREVIATIONS
APPA
AQA
AQG
ASTER
BNM
CAPCO
CH4
CO
CO2
COJ
DEAT
EC
EHS
EIA
HC
HCV
H2S
LCV
LTO
MAS
MCV
MSVS
NATIS
NOx
NO
NO2
N2O
NMVOC
O3
PM
PM2.5
PM10
ROM
SA
SABS
SANAS
SANS
SAPIA
SAWS
SDM
SO2
TSP
µ
UK
The Atmospheric Pollution Prevention Act (No.45 of 1965)
Air Quality Act
Air Quality Guidelines
Advanced Spaceborne Thermal Emission and Reflection
Radiometer
Basa Njengo Magogo
Chief Air Pollution Control Officer
Methane
Carbon Monoxide
Carbon Dioxide
City of Johannesburg
The Department of Environmental Affairs and Tourism.
The European Community
Environmental, Health and Safety
Environmental Impact Assessment
Hydrocarbons
Heavy commercial vehicles
Hydrogen Sulphide
Light commercial vehicles
Land-take-off cycle
Magical-angle-spinning
Medium commercial vehicles
ArcelorMittal Steel Vanderbijlpark Steel
National Traffic Information System
Nitrogen Oxides
Nitric oxide
Nitrogen Dioxide
Nitrogen Oxide
Non Methane Volatile Organic Compounds
Ozone
Particulate Matter
Particulate Matter with an aerodynamic diameter of less than 2.5µm
Particulate Matter with an aerodynamic diameter of less than 10µm
Run of Mine
South African
South African Bureau of Standards
South African National Accreditation System
South African National Standards
South African Petroleum Industry Association
South African Weather Service
Sedibeng District Municipality
Sulphur Dioxide
Total Suspended Particulates
Micron
United Kingdom
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
xix
US-EPA
UV
VKT
VOC
WB
WHO
United States Environmental Protection Agency
Ultra Violet
Vehicle Kilometre Travelled
Volatile Organic Compounds
The World Bank Group
The World Health Organisation
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
xx
1
CHAPTER 1
BACKGROUND
1.1
Introduction
The Vaal Triangle is a highly industrialised area, encompassing numerous industries (such
as petrochemical, iron and steel, ferro-alloy, etc.), a coal fired power station, and various
smaller industrial and commercial activities giving rise to noxious and offensive gases. In
addition to the industrial activities, the Vaal Triangle is also home to large informal
settlements (viz. Boipatong, Bophelong, Evaton, Orange Farm, Sebokeng, Sharpville and
Zamdela) using coal, wood and paraffin as a fuel source. A few mining operations, mainly
coal collieries are located within this Airshed. Other sources of concern contributing to the
pollution mixture within the area include vehicle tailpipe emissions, biomass burning, water
treatment works and landfill areas, agricultural activities and various other fugitive sources.
Due to the various emission release sources within the Vaal Airshed, significant health
impacts have been identified as occurring in the region specifically due to the high airborne
particulate concentrations.
The air quality within the Vaal Triangle region was extensively investigated during the 1990s
with a range of air pollution and human health assessment studies undertaken. These
studies, amongst others, included the Vaal Triangle Air Pollution Health Study that was
initiated in 1990 to determine the effects of air pollution on human health (Terblanche et al,
1992). This study included the indoor, outdoor and personal exposure to pollutants over a
three year period.
Other studies compiled by Muller (1992) and van Nierop (1994) investigated the emissions
within the Vaal Triangle. Muller (1992), undertook a qualitative assessment of the industrial
sources (including iron and steel operations, non-ferrous metal processing, coal fired power
plants, coal-to-oil conversion plants, a manganese foundry, quarries, wood and rubber
products and fertiliser factories) and area sources (including domestic fuel burning, veld fires,
vegetation burning, wind blown dust, agricultural and construction soil dust and fugitive
emissions from paved and unpaved road surfaces). Van Nierop (1994) extended this
information by quantifying these emissions for a base case period of 1992. In 1999,
Liebenberg, extended this study by investigating the exposure potential of inhalable
particulate matter within the region. These earlier studies were important in terms of
highlighting certain pollutants, areas and sources of concern in the Vaal Triangle.
In 2003, research was undertaken to consolidate the results of past studies (Scorgie, 2003).
In addition, research aimed at quantifying the contribution of fuel-burning within various
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
1-1
sectors to human health impacts and the costs associated with such impacts was also
undertaken (Scorgie et al., 2003a; 2003b).
1.2
The Vaal Airshed Declared a Priority Area
Considerable attention was placed on the Vaal Airshed when the Minister of Environmental
Affairs and Tourism declared the Vaal Region a priority area on 21 April 2006. The
boundaries of this area are illustrated in Figure 1-1. This region was the first to be declared a
priority area within the country. Following the declaration government (national or provincial)
is responsible for coordinating the development of a Priority Area Air Quality Management
Plan. In order to undertake an Air Quality Management Plan it was essential to determine
the status quo of the Vaal Airshed.
Figure 1-1:
Boundaries of the Vaal priority area, as declared on 21 April 2006.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
1-2
1.3
Aim of Study
The aim of the study was to determine the current air quality and impact sources within the
Vaal Airshed. The original industrialised Vaal Triangle included an area stretching from
Randvaal in the north to Sasolburg in the southwest and Deneysville in the east. The study
area, however, extended to include in addition the major metropolitan areas of
Johannesburg, Soweto, Lenasia, Ennerdale, Orange Farm, Evaton, Sebokeng and Meyerton
which have the potential to influence the Airshed within the Vaal Triangle (Figure 1-2).
0km
20km
40km
60km
80km
Figure 1-2: The extent of the area assessed during the current study including the Vaal
Triangle and the major metropolitan areas of Johannesburg, Soweto, Lenasia, Ennerdale,
Orange Farm, Evaton, Sebokeng and Meyerton.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
1-3
The objectives of the research are as follows:
•
•
•
•
•
•
•
1.4
Describe the synoptic climatology and meso-scale atmospheric dispersion potential
based on available literature and meteorological data;
Review legislative and regulatory requirements pertaining to air pollution control
and air quality management, specifically local and international ‘good practice’
emission limits and air quality limits;
Characterise existing air quality including the identification of existing sources and
the analysis of existing air quality monitoring data;
Compile an emissions inventory for the current emission sources within the Vaal
Airshed, including industrial, commercial and residential activities;
Application of the CALPUFF/CALMET dispersion modelling suit to predict baseline
sulphur dioxide, nitrogen dioxide and inhalable particulate concentrations;
Evaluate the compliance of air pollutant concentrations based on both local and
international ‘good practice’ limits;
Identify priority pollutants, sources and areas within the Vaal Airshed.
Assumptions and Limitations
The following limitations and assumptions were taken in consideration for this research:
•
•
•
•
Limited background ambient air quality data was available since the Department of
Environmental Affairs and Tourism (DEAT) monitoring network has only
commenced during February to March 2007. Eskom’s Makalu station was
decommissioned at the end of 2004 thus providing mainly historical data. Some of
the ambient monitoring stations are not SANAS accredited and it was assumed that
the data obtained was correct. Ambient monitoring data was mainly limited to
criteria pollutants.
The Sasol stations (with the exception of Grootvlei) only had wind speed and wind
direction data available for the last 3 months of 2006 due to technical problems
experienced with the data averaging.
No upper air meteorological data is recorded within the Vaal Airshed with the
nearest station located at Irene in Pretoria. Use was therefore made of the South
African Weather Services ETA data model results for the required period.
A questionnaire was compiled for industrial and mining operations requesting all
emissions data (Liebenberg-Enslin et al, 2007). A reply of 51% was received from
the industries. Of the 51% updated emissions received, the main industries of
Sasol, ArcelorMittal, Natref, Omnia, Eskom and Metalloys were included. For the
mining operations use was made of information contained in previous
Environmental Impact Assessments (EIAs).
For the remaining sources of
emissions for which no reply was received 37% could be covered by the NEDLAC
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
1-4
•
•
•
•
1.5
Dirty Fuels study or available EIA information. These industries include small boiler
operations, brickworks, etc. The NEDLAC data is however based on pre-2004
information. Thus a total of 88% of the identified sources were included into the
baseline study with 12% not accounted for.
Based on the emissions information available only criteria pollutants were
assessed. These were limited to inhalable particulate matter, sulphur dioxide and
oxides of nitrogen. These criteria pollutants however are stipulated within the
Atmospheric Pollution Prevention Act (No.45 of 1965) (APPA), Air Quality Act
(AQA) and South African (SA) standards have been assigned to these pollutants to
regulate ground level concentrations in terms of the legislation.
Domestic fuel burning emissions were based on 2001 Census data for household
coal, wood and paraffin use within the Vaal Airshed. Factors influencing emissions:
type of house (formal house, planned / unplanned / backyard shack), whether or
not a household is electrified, the number of people living in the house, the season,
the availability of fuel types, the price of fuels and the household income. More
recent surveys (2004/2005) conducted in Zamdela on the type of energy sources
utilised were made available for use by the NOVA Institute. A current survey has
been completed by NOVA including information on the number of household using
the BNM method but this information was complete during the commencement of
this study and thus could not be included.
Vehicle emissions were limited to national and regional roads within the Vaal
Airshed and the more congested areas within were treated as area sources.
Total particulate matter from Sasol point sources were conservatively assumed to
be inhalable particulate matter of <10µm in diameter as the inhalable particulate
fraction was unknown for the current study.
Hypotheses
The hypotheses to be tested are as follows:
•
•
•
•
•
•
Inhalable particulate concentrations are elevated within the Vaal Airshed;
The main sources of inhalable particulate emissions are industrial, commercial and
domestic fuel burning activities;
Sulphur dioxide concentrations are elevated over built-up areas within the Vaal
Airshed;
The main sources of sulphur dioxide emissions are due to industrial, commercial
and domestic fuel burning activities;
Elevated nitrogen dioxide concentrations are limited within the Vaal Airshed;
The main sources of nitrogen dioxide emissions are due to industrial activities;
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
1-5
1.6
Outline of report
The dissertation consists of eight chapters. Chapter 1 describes the background research
undertaken over the Vaal Airshed and the need for a baseline assessment of the area. The
objectives and hypothesis of the research are introduced in this chapter. Chapter 2
introduces the ambient air quality evaluation criteria that are available to assess the air
quality within the study area. The dispersion simulation methodology is discussed in
Chapter 3 with the regional climate and atmospheric dispersion potential provided in
Chapter 4. The measured ambient air quality in the study area is discussed in Chapter 5.
The emissions inventory of the baseline emissions for the Vaal Airshed is given in Chapter 6
and the impact assessment provided in Chapter 7. Chapter 8 summarizes and concludes
the findings of this research.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
1-6
2
CHAPTER 2
LEGAL REQUIREMENTS AND HUMAN HEALTH CRITERIA
In order to assess the impacts due to emission sources within the Vaal Airshed, reference
needs to be made to local and international guidelines/standards that regulate pollution
concentrations at ground level.
Ambient air quality guideline values and standards provide safe daily exposure levels for the
majority of the population, including the very young and the elderly, throughout an
individual’s lifetime. Air quality guidelines and standards are normally given for specific
averaging periods which refer to the time-span over which the air concentration of the
pollutant was monitored at a location. There are generally five averaging periods that are
applicable (viz. instantaneous peak, 1-hour average, 24-hour average, 1-month average, and
annual average).
The South African Bureau of Standards (SABS) was engaged to assist the department of
Environmental Affairs and Tourism (DEAT) with the development of ambient air quality
standards. A technical committee was established to provide input to the development of
these standards. The technical committee came up with three working groups, namely (i)
sulphur dioxide, particulates, oxides of nitrogen and ozone, (ii) lead and (iii) volatile organic
compounds, specifically benzene. The process resulted in the publication of: (a) SANS 69 South African National Standard - Framework for setting and implementing national ambient
air quality standards, and (b) SANS 1929 - South African National Standard - Ambient Air
Quality - Limits for common pollutants. The latter document includes air quality limits for
particulate matter less than 10 µm in aerodynamic diameter (inhalable particulates), dustfall,
sulphur dioxide, nitrogen dioxide, ozone, carbon monoxide, lead and benzene. The SANS
documents were approved by the technical committee for gazetting for public comment, were
made available for public comment during the May/June 2004 period and were finalized and
published during November 2004.
The Department of Environmental Affairs and Tourism, however, adopted the outdated Chief
Air Pollution Control Officer (CAPCO) guidelines as national standards on 11 September
2005 in the National Environmental: Air Quality Act1.
The Minister has since announced his intention of setting new ambient air quality standards
in terms of Section 9(1) (a) and (b) of the Air Quality Act on 2 June 2006. The proposed new
standards (an adoption of the SANS limits) for all criteria pollutants were published for public
comment in the Government Gazette of 9 June 2006. .
1
th
The National Environmental Management: Air Quality Act (Act no.39 of 2004) commenced with on the 11 of
September 2005 as published in the Government Gazette on the 9th of September 2005. Sections omitted from
the implementation are Sections 21, 22, 36 to 49, 51(1)(e),51(1)(f), 51(3),60 and 61.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
2-1
A document for the Establishment of National Standards for Ambient Air Quality was drafted
on 24 October 2007 and circulated in a multi-stakeholder workshop for comment. This
document is yet to be finalised and the figures provided in the following sections have been
released for discussion purposes only.
As of 30 April 2007, new versions of the World Bank Group Environmental, Health, and
Safety Guidelines (known as the 'EHS Guidelines') are now in use. They replace those
documents previously published in Part III of the Pollution Prevention and Abatement
Handbook and on the IFC website.
The local and international ambient air quality guidelines and standards for pollutants
relevant to the current study are presented in subsequent subsections. Air quality limits
issued nationally by the DEAT and SABS are reflected together with limits published by the
World Health Organisation (WHO), European Community (EC), World Bank (WB), United
Kingdom (UK), and the United States Environmental Protection Agency (US-EPA).
2.1
Suspended Particulate Matter
Particulate matter is the suspension of air-borne solid particles of various sizes. A single
particle may be made up of sulphate, nitrate, ammonia, chloride, elemental and organic
carbon and crustal and biological materials (Vallius, 2005). Inhalable particulate matter with
a diameter of < 10 µm (PM10) is able to reach the upper part of the lung. Smaller particles of
this size fraction (i.e. PM2.5 and PM1.0) are able to penetrate deeper into the lung and reach
the alveolar region (Figure 2-1). Particles with a diameter of less than 2.5 µm are often
referred to as the “fine fraction” with particles with a diameter of between 2.5 µm and 10 µm
referred to as the “coarse fraction” (Yu, 2001).
Although the size and composition of particulate matter depends on the emission process,
these attributes will be influenced by atmospheric processes as well. Fine particulate fraction
of ~ 1 µm form during high temperature processes in the atmosphere and carry inorganic
and organic compounds. The mechanical processes of corrosion, erosion, etc. give rise to
coarser particles (Vallius, 2005).
Numerous studies conducted on the health effects of particulate matter have shown
increases in lower respiratory systems and reduced lung function in children with chronic
obstructive pulmonary disease and reduced lung function in adults (Maddox, 2006; NRC,
2004).
In addition to health effects in humans, particulate matter has been found to cause
environmental effects. Fine particulates (PM2.5) for instance, are a source of visibility
reduction (haze). Larger particles that settle on water bodies, on the other hand, change the
acidity and nutrient balance in these environments and thus the diversity of ecosystems.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
2-2
Deposition of particulate matter has also been found to stain and damage stone and other
materials resulting in the destruction of monuments and statues2.
Air quality guidelines for particulates are given for various particle size fractions, including
total suspended particulates, inhalable particulates or PM10 (i.e. particulates with an
aerodynamic diameter of less than 10 µm), and respirable particulates of PM2.5 (i.e.
particulates with an aerodynamic diameter of less than 2.5 µm). PM10 and PM2.5 are of
concern due to their health impact potentials as they are able to deposit and damage the
lower airways and gas-exchanging portions of the lung.
Figure 2-1:
2006).
The effects of inhaled particulate matter to the human lung (after Maddox,
Inhalable particulate limits and standards issued locally and abroad are given in Table 2-1.
The averaging periods for which inhalable particulate health standards and limits have been
established consists of daily and annual time-frames. In addition to the inhalable particulate
standards published in schedule 2 of the SA Air Quality Act, the Act also includes standards
2
http://www.epa.gov/oar/particlepollution/health.html
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
2-3
for total suspended particulates, viz. a 24-hour average maximum concentration of 300 µg/m³
not to be exceeded more than three times in one year and an annual average of 100 µg/m³.
During 1990 the World Health Organisation (WHO) established that no safe thresholds could
be determined for particulate exposures.
It thus established linear dose-response
relationships for PM10 and PM2.5 concentrations (WHO, 2000). This approach, however,
was not well accepted by air quality managers and policy makers, as explicit objectives could
not be extracted from the dose-response relationships. The WHO Working Group of Air
Quality Guidelines thus recommended that the updated WHO air quality guideline document
contain guidelines that define concentrations which, if achieved, would be expected to result
in significantly reduced rates of adverse health effects. As developing countries would
inevitably exceed the recommended WHO air quality guidelines (AQGs), the Working Group
also proposed interim targets (IT) levels, in excess of the WHO AQGs themselves, to
promote steady progress towards meeting the WHO AQGs (WHO, 2005). The air quality
guidelines and interim targets issued by the WHO in 2005 for particulate matter are given in
Tables 2-2 and 2-3.
Table 2-1:
Air quality standards for inhalable particulate matter (PM10) for various
countries and organisations.
Authority
SA standards (Air Quality Act)
RSA SANS limits
(SANS:1929,2004)
Australian standards
European Community (EC)
World Bank (General
Environmental Guidelines)
United Kingdom
United States EPA
World Health Organisation
Maximum 24-hour
Concentration (µg/m³)
180
75(a)
50(b)
50(e)
50(f)
Annual Average
Concentration (µg/m³)
60
40(c)
30(d)
40(g)
(h)
(h)
50(i)
150(k)
50(m)
40(j)
50(l)
20(m)
Notes:
(a) Limit value. Permissible frequencies of exceedance, margin of tolerance and date by which limit value should be complied
with not yet set.
(b) Target value. Permissible frequencies of exceedance and date by which limit value should be complied with not yet set.
(c) Limit value. Margin of tolerance and date by which limit value should be complied with not yet set.
(d) Target value. Date by which limit value should be complied with not yet set.
(e) Australian ambient air quality standards. (http://www.deh.gov.au/atmosphere/airquality/standards.html). Not to be exceeded
more than 5 days per year. Compliance by 2008.
(f) EC Directive, 2008/50/EC (http://ec.europa.eu/environment/air/quality/legislation/directive.htm). Already in force since 1
January 2005. Not to be exceeded more than 35 times per calendar year.
(g) EC Directive, 2008/50/EC (http://ec.europa.eu/environment/air/quality/legislation/directive.htm). Already in force since 1
January 2005.
(h) World Bank Group, 2007.
EHS Guidelines (http://www.ifc.org/ifcext/enviro.nsf/Content/EnvironmentalGuidelines).
Guidelines state that pollutant concentrations do not reach or exceed relevant ambient quality guidelines and standards by
applying national legislated standards, or in their absence, the current WHO Air Quality Guidelines, or other internationally
recognized sources.
(i) UK Air Quality Objectives. www.airquality.co.uk/archive/standards/php. Not to be exceeded more than 35 times per year.
Compliance by 31 December 2004
(j) UK Air Quality Objectives. www.airquality.co.uk/archive/standards/php. Compliance by 31 December 2004
(k) US National Ambient Air Quality Standards (www.epa.gov/air/criteria.html). Not to be exceeded more than once per year.
(l) US National Ambient Air Quality Standards (www.epa.gov/air/criteria.html). To attain this standard, the 3-year average of the
weighted annual mean PM10 concentration at each monitor within an area must not exceed 50 µg/m³.
(m) WHO (2000) issued linear dose-response relationships for PM10 concentrations and various health endpoints with no
specific guideline provided. WHO (2005) made available during early 2006 proposes several interim target levels (see Table 22 and 2-3).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
2-4
Table 2-2:
WHO air quality guideline and interim targets for particulate matter (annual
mean) (WHO, 2005)
WHO interim target-1 (IT-1)
PM10
(µg/m³)
70
PM2.5
(µg/m³)
35
WHO interim target-2 (IT-2)
50
25
WHO interim target-3 (IT-3)
30
15
WHO Air Quality Guideline
(AQG)
20
10
Annual Mean Level
Basis for the selected level
These levels were estimated to be associated with about
15% higher long-term mortality than at AQG
In addition to other health benefits, these levels lower risk
of premature mortality by approximately 6% (2-11%)
compared to WHO-IT1
In addition to other health benefits, these levels reduce
mortality risks by another approximately 6% (2-11%)
compared to WHO-IT2 levels.
These are the lowest levels at which total,
cardiopulmonary and lung cancer mortality have been
shown to increase with more than 95% confidence in
response to PM2.5 in the American Cancer Society (ACS)
study (Pope et al., 2002 as cited in WHO 2005). The use
of the PM2.5 guideline is preferred.
Table 2-3:
WHO air quality guideline and interim targets for particulate matter (daily
mean) (WHO, 2005)
WHO interim target-1 (IT-1)
PM10
(µg/m³)
150
PM2.5
(µg/m³)
75
WHO interim target-2 (IT-2)*
100
50
WHO interim target-3 (IT-3)**
75
37.5
Annual Mean Level
Basis for the selected level
Based on published risk coefficients from multi-centre
studies and meta-analyses (about 5% increase of shortterm mortality over AQG)
Based on published risk coefficients from multi-centre
studies and meta-analyses (about 2.5% increase of shortterm mortality over AQG)
Based on published risk coefficients from multi-centre
studies and meta-analyses (about 1.2% increase of shortterm mortality over AQG)
Based on relation between 24-hour and annual levels
WHO Air Quality Guideline
50
25
(AQG)
th
*
99 percentile (3 days/year)
**
for management purposes, based on annual average guideline values; precise number to be determined
on basis of local frequency distribution of daily means
The South African National Standards for inhalable particulate matter of diameter <10 µm (as
provided in a draft document on 24 October 2007) is given in Table 2-4 to Table 2-7.
Table 2-4:
National Ambient Air Quality Standards – AQA Schedule 2
Averaging Period
24 hour
1 year
Concentration
(µg/m³)
180
60
Frequency of
Exceedance
0
0
Compliance Date
Immediate
Immediate
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
2-5
Table 2-5:
National Ambient Air Quality Standards – Interim Level 1 at 99%
Averaging Period
24 hour
1 year
Table 2-6:
24 hour
1 year
2.2
Compliance Date
2012
2012
Concentration
(µg/m³)
100
45
Frequency of
Exceedance
44
0
Compliance Date
2017
2017
National Ambient Air Quality Standards at 99.9%
Averaging Period
24 hour
1 year
Frequency of
Exceedance
88
0
National Ambient Air Quality Standards – Interim Level 2 at 99.5%
Averaging Period
Table 2-7:
Concentration
(µg/m³)
127
50
Concentration
(µg/m³)
75
40
Frequency of
Exceedance
9
0
Compliance Date
2022
2022
Sulphur Dioxide
Sulphur dioxide is a colourless gas that is highly soluble in water (ATSDR, 1999; WHO,
2000). On inhalation, a large portion of sulphur dioxide is absorbed through the nasal
mucosa (Speizer and Frank, 1966). Penetration to the alveoli is greater when inhaled
through the mouth than through the nose (Calabrese et al, 1981).
The critical effect of sulphur dioxide is irritation of the upper respiratory tract. When exposed
to large quantities of sulphur dioxide the outcome is burning of the nose and throat, breathing
difficulties and severe airway obstruction. Long-term exposure of sulphur dioxide can affect
human health with changes in lung function occurring (ATSDR, 1999). These changes may
be in the form of damage to the epithelium of the airways followed by epithelial hyperplasia, a
dose-related increase in goblet cells and hypertrophy of the submucosal glands (WHO,
2000). Sensitive populations (i.e. asthmatics) have been observed to be sensitive to
respiratory effects at low concentrations of sulphur dioxide (ATSDR, 1999, Bethal et al, 1985,
WHO, 2000). These effects are exacerbated through increased levels of exercise (Bethal et
al, 1985).
Animal studies have also shown that exposure to high concentrations of sulphur dioxide have
resulted in decreased respiration, inflammation of the airways and destruction of areas of the
lung. No studies have clearly shown carcinogenic effects in human and animals (ATSDR,
1999).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
2-6
Ambient air quality guidelines and standards issued for various countries and organisations
for sulphur dioxide are given in Table 2-8.
Table 2-8:
Ambient air quality guidelines and standards for sulphur dioxide for various
countries and organisations
Authority
SA standards (Air Quality Act)
RSA SANS limits
(SANS:1929,2004)
Australian standards
European Community (EC)
World Bank (General
Environmental Guidelines)
United Kingdom
United States EPA
World Health Organisation
Maximum 10minute
Average
(µg/m³)
500(a)
Maximum 1hourly Average
(µg/m³)
-
125(a)
Annual
Average
Concentration
(µg/m³)
50
500(b)
-
125(b)
50
-
524(c)
350(d)
209 (c)
125(e)
52
20(f)
(g)
(g)
(g)
(g)
266(h)
-
350(i)
-
125(j)
365(l)
500(m)
350(m)
125(m)
20(k)
80
50(m)
10-30(n)
Maximum 24hour Average
(µg/m³)
Notes:
(a) No permissible frequencies of exceedance specified
(b) Limit value. Permissible frequencies of exceedance, margin of tolerance and date by which limit value should be complied
with not yet set.
(c) Australian ambient air quality standards. (http://www.deh.gov.au/atmosphere/airquality/standards.html). Not to be exceeded
more than 1 day per year. Compliance by 2008.
(d) EC Directive, 2008/50/EC (http://ec.europa.eu/environment/air/quality/legislation/directive.htm). Already in force since 1
January 2005. Limit to protect health (not to be exceeded more than 24 times per calendar year).
(e) EC Directive, 2008/50/EC (http://ec.europa.eu/environment/air/quality/legislation/directive.htm). Already in force since 1
January 2005. Limit to protect health (not to be exceeded more than 3 times per calendar year).
(f) EC Directive, 2008/50/EC (http://ec.europa.eu/environment/air/quality/legislation/directive.htm). Limited value to protect
ecosystems.
(g) World Bank Group, 2007.
EHS Guidelines (http://www.ifc.org/ifcext/enviro.nsf/Content/EnvironmentalGuidelines).
Guidelines state that pollutant concentrations do not reach or exceed relevant ambient quality guidelines and standards by
applying national legislated standards, or in their absence, the current WHO Air Quality Guidelines, or other internationally
recognized sources.
(h) UK Air Quality Objective for 15-minute averaging period (www.airquality.co.uk/archive/standards/php). Not to be exceeded
more than 35 times per year. Compliance by 31 December 2005.
(i) UK Air Quality Objective (www.airquality.co.uk/archive/standards/php). Not to be exceeded more than 24 times per year.
Compliance by 31 December 2004.
(j) UK Air Quality Objective (www.airquality.co.uk/archive/standards/php). Not to be exceeded more than 3 times per year.
Compliance by 31 December 2004.
(k) UK Air Quality Objective (www.airquality.co.uk/archive/standards/php). Compliance by 31 December 2000.
(l) US National Ambient Air Quality Standards (www.epa.gov/air/criteria.html). Not to be exceeded more than once per year.
(m) WHO Guidelines for the protection of human health (WHO, 2000).
(n) Represents the critical level of eco toxic effects (issued by WHO for Europe); a range is given to account for different
sensitivities of vegetation types (WHO, 2000).
It should be noted that the WHO Air Quality Guidelines (AQG) for sulphur dioxide as
published in 2000 have recently been revised (WHO, 2005). Although the 10-minute AQG
(500 µg/m³) has remained unchanged, the previously published daily guideline has been
significantly reduced from 125 µg/m³ to 20 µg/m³. The previous daily guideline was based on
epidemiological studies. WHO (2005) makes reference to more recent evidence which
suggests the occurrence of health risks at lower concentrations. Although WHO (2005)
acknowledges the considerable uncertainty as to whether sulphur dioxide is the pollutant
responsible for the observed adverse effects (may be due to ultra-fine particles or other
correlated substances), it took the decision to publish a stringent daily guideline in line with
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
2-7
the precautionary principle. The WHO (2005) stipulates an annual guideline is not needed
for the protection of human health, since compliance with the 24-hour level will assure
sufficiently lower levels for the annual average. Given that the 24-hour WHO AQG
(20 µg/m³) is anticipated to be difficult for some countries to achieve in the short term, the
WHO (2005) recommends a stepped approach using interim goals as shown in Table 2-9.
Table 2-9:
2005)
WHO air quality guidelines and interim guidelines for sulphur dioxide (WHO,
WHO interim target-1 (IT-1) (2000 AQF
level)
WHO interim target-2 (IT-2)
WHO Air Quality Guideline (AQG)
24-hour Average
Sulphur Dioxide
(µg/m³)
125
50(a)
20
10-minute Average
Sulphur Dioxide
(µg/m³)
500
(a) Intermediate goal based on controlling either (i) motor vehicle (ii) industrial emissions and/or (iii) power
production; this would be a reasonable and feasible goal to be achieved within a few years for some
developing countries and lead to significant health improvements that would justify further improvements (such
as aiming for the guideline).
The South African National Standards for sulphur dioxide (as provided in a draft document
on 24 October 2007) is given in Table 2-10 to Table 2-12.
Table 2-10:
National Ambient Air Quality Standards – AQA Schedule 2 at 99%
Averaging Period
10 minute
(calculated on
running averages)
1 hour
24 hours
1 year
Table 2-11:
Concentration
(µg/m³)
Frequency of
Exceedance
Compliance Date
500
526
Immediate
350
125
50
88
4
0
Immediate
Immediate
Immediate
National Ambient Air Quality Standards – Interim Level 1 at 99.5%
Averaging Period
10
minute
(calculated
on
running averages)
1 hour
24 hours
1 year
Concentration
(µg/m³)
Frequency of
Exceedance
Compliance Date
500
263
2012
350
125
50
44
2
0
2012
2012
Immediate
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
2-8
Table 2-12:
National Ambient Air Quality Standards – Interim Level 2 at 99.9%
Averaging Period
Concentration
(µg/m³)
Frequency of
Exceedance
Compliance Date
500
50
2017
350
125
50
9
1
0
2017
2017
Immediate
10 minute
(calculated on
running averages)
1 hour
24 hours
1 year
2.3
Nitrogen Dioxide
Nitrogen dioxide is an oxidised gas that forms from the oxidation of nitric oxide in the
presence of ozone and UV-light. It is a reddish-brown gas and is relatively insoluble in water
(Mukala, 1999).
The health effects of nitrogen dioxide are not well understood despite the extensive
epidemiological studies that have been undertaken. Animal studies have suggested,
however, that higher concentrations of nitrogen dioxide can cause susceptibility to bacterial
lung infections and irreversible emphysema-like structural changes (Mukala, 1999). Longterm effects of nitrogen dioxide have also been associated with increased respiratory
disorders and impaired lung function in children (EPA, 1993; Pershagen et al, 1995; WHO,
1995).
Sensitive population groups to nitrogen dioxide exposure include children, cigarette smokers
and asthmatics (Mukala, 1999).
The standards and guidelines of most countries and organisations are given exclusively for
nitrogen dioxide concentrations. South Africa's nitrogen dioxide standards are compared to
various widely referenced foreign standards and guidelines in Table 2-13.
Table 2-13: Ambient air quality guidelines and standards for nitrogen dioxide for various
countries and organisations
Authority
SA standards (Air
Quality Act)
RSA SANS limits
(SANS:1929,2004)
Australian standards
European Community
(EC)
Instantaneous Peak
(µg/m³)
Maximum 1hourly
Average
(µg/m³)
Maximum
24-hour
Average
(µg/m³)
Maximum 1month
Average
(µg/m³)
Annual
Average
Concentration (µg/m³)
941(a)
376(a)
188(a)
151(a)
94
-
200(b)
-
-
40(b)
226(c)
-
200(d)
56
-
-
40(e)
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
2-9
Authority
World Bank (General
Environmental
Guidelines)
United Kingdom
United States EPA
World Health
Organisation (2000,
2005)
Instantaneous Peak
(µg/m³)
Maximum 1hourly
Average
(µg/m³)
Maximum
24-hour
Average
(µg/m³)
Maximum 1month
Average
(µg/m³)
Annual
Average
Concentration (µg/m³)
(f)
(f)
(f)
(f)
(f)
-
200(h)
-
-
-
-
-
-
40(i)
30(j)
100(k)
-
200(l)
-
40(l)
Notes:
(a) No permissible frequencies of exceedance specified
(b) Limit value. Permissible frequencies of exceedance, margin of tolerance and date by which limit value should be complied
with not yet set.
(c) Australian ambient air quality standards. (http://www.deh.gov.au/atmosphere/airquality/standards.html). Not to be exceeded
more than 1 day per year. Compliance by 2008.
(d) EC Directive, 2008/50/EC (http://ec.europa.eu/environment/air/quality/legislation/directive.htm). Not to be exceeded more
than 18 times per year. This limit is to be complied with by 1 January 2010.
(e) EC Directive, 2008/50/EC (http://ec.europa.eu/environment/air/quality/legislation/directive.htm). Already in force since 1
January 2005. Annual limit value for the protection of human health, to be complied with by 1 January 2010.
(f) World Bank Group, 2007.
EHS Guidelines (http://www.ifc.org/ifcext/enviro.nsf/Content/EnvironmentalGuidelines).
Guidelines state that pollutant concentrations do not reach or exceed relevant ambient quality guidelines and standards by
applying national legislated standards, or in their absence, the current WHO Air Quality Guidelines, or other internationally
recognized sources.
(g) UK Air Quality Provisional Objective for nitrogen dioxide (www.airquality.co.uk/archive/standards/php). Not to be exceeded
more than 18 times per year. Compliance by 31 December 2005.
(h) UK Air Quality Provisional Objective for nitrogen dioxide (www.airquality.co.uk/archive/standards/php). Compliance by 31
December 2005.
(i) UK Air Quality Objective for NOx for protection of vegetation (www.airquality.co.uk/archive/standards/php). Compliance by
31 December 2000.
(j) US National Ambient Air Quality Standards (www.epa.gov/air/criteria.html).
(k) WHO Guidelines for the protection of human health (WHO, 2000). AQGs remain unchanged according to WHO (2005).
The South African National Standards for nitrogen dioxide (as provided in a draft document
on 24 October 2007) is given in Table 2-14 to Table 2-17.
Table 2-14:
National Ambient Air Quality Standards – AQA Schedule 2
Averaging Period
1 hour
1 year
Table 2-15:
Frequency of
Exceedance
0
0
Compliance Date
Immediate
Immediate
National Ambient Air Quality Standards – Interim Level 1 at 99%
Averaging Period
1 hour
1 year
Concentration
(µg/m³)
376
100
Concentration
(µg/m³)
288
70
Frequency of
Exceedance
88
0
Compliance Date
2012
2012
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
2-10
Table 2-16:
National Ambient Air Quality Standards – Interim Level 2 at 99.5%
Averaging Period
1 hour
1 year
Table 2-17:
Frequency of
Exceedance
44
0
Compliance Date
2017
2017
National Ambient Air Quality Standards at 99.9%
Averaging Period
1 hour
1 year
Concentration
(µg/m³)
244
55
Concentration
(µg/m³)
200
40
Frequency of
Exceedance
9
0
Compliance Date
2022
2022
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
2-11
3
CHAPTER 3
DISPERSION SIMULATION AND EMISSIONS QUANTIFICATION
METHODOLOGY
3.1
Dispersion Simulation Methodology
Dispersion models are useful tools to compute ambient concentrations as a function of
source configurations, emission strengths and meteorological characteristics. With the use
of this tool, the spatial and temporal patterns in the ground level concentrations arising from
the emissions of various sources can thus be ascertained. Increasing reliance has been
placed on ground level air pollution concentration estimates from models as the primary
basis for environmental and health impact assessments, risk assessments and determining
emission control requirements. Care was therefore taken in the selection of a suitable
dispersion model for the task at hand. The US Environmental Protection Agency approved
CALPUFF modelling suite was selected for use in the baseline assessment, comprising the
CALMET meteorological model, the CALPUFF dispersion model and the CALPOST resultprocessing module (Figure 3-1) (Scire et al, 2000a).
Figure 3-1:
2000a).
An overview of the CALMET/CALPUFF modelling system (after Scire et al,
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-1
3.1.1
CALMET Meteorological Model
CALMET is a meteorological model which includes a diagnostic wind field generator, taking
into account slope flows, kinematic terrain effects and terrain blocking effects. CALMET also
includes a divergence minimisation procedure and a micrometeorology model for overland
and overwater boundary layers (EPA, 1995a). Major features of the CALMET model are
summarised in Table 3-1 and input data required for CALMET is given in Table 3-2 (Scire et
al, 2000a).
Table 3-1:
Major features of the CALMET meteorological model.
Module
Boundary Layer Module
Diagnostic
Module
Wind
-
Field
-
Contents
Overland boundary layer – Energy balance method
Overwater boundary layer – Profile method
Produces gridded fields of:
Surface friction velocity
Convective velocity scale
Monon-Obukhov length
Mixing height
Pasquill-Gifford-Turner (PGT) Stability class
Air temperature (3-D)
Precipitation rate
Slope flows
Kinematic terrain effects
Terrain blocking effects
Divergence minimisation
Produces gridded fields of U, V, W wind components
Inputs include domain-scale winds, observations
(optionally) coarse-grid prognostic model winds
Lambert conformal projection capability.
and
Table 3-2:
A summary of source groups and parameters required as input data into the
CALMET model.
Meteorological Data
Surface meteorological data
Upper air data
Parameters
Hourly observations of:
- wind speed
- wind direction
- temperature
- cloud cover
- ceiling height
- surface pressure
- relative humidity
- precipitation rates
- precipitation type code
Twice-daily observed vertical profiles of:
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-2
Meteorological Data
Overwater observations (optional)
Geophysical data
Parameters
-
wind speed
wind direction
temperature
pressure
elevation
air-sea temperature difference
air temperature
relative humidity
over water mixing height
wind speed
wind direction
overwater temperature gradients above and below
mixing height
Gridded fields of:
- terrain elevations
- land use categories
- surface roughness length (optional)
- albedo (optional)
- Bowen ratio (optional)
- Soil heat flux constant (optional)
- Anthropogenic heat flux (optional)
- Vegetative leaf area index (optional)
The CALMET model operates in a terrain-following vertical coordinate system (Scire et al,
2000a):
Z = z − ht
where,
Z
z
ht
-
is the terrain-following vertical coordinate (m),
is the Cartesian vertical coordinate (m), and
is the terrain height
The vertical velocity, W, in the terrain-following coordinate system is defined as (Scire et al,
2000a):
W = w−u
∂ht
∂h
−v t
∂y
∂x
where,
w
u,v
-
is the physical vertical wind component (m/s) in Cartesian coordinates,
are the horizontal wind components
The CALMET diagnostic wind field model has a two-step approach to the computation of the
wind field. Step 1, an initial guess wind field is adjusted for:
• Kinematic effects of terrain
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-3
•
•
•
Slope flows
Blocking effects
Three dimensional divergence minimisation
CALMET parameterises the kinematic effects of terrain using the methodology by Liu and
Yocke (1980). The Cartesian vertical velocity, w, is quantified as follows:
w = (V .∆ht ) exp(− kz )
where,
V
z
ht
k
-
is the domain-mean wind,
is the vertical coordinate,
is the terrain height, and,
is a stability-dependent coefficient of exponential decay.
The exponential decay coefficient increases with increase in atmospheric stability (Scire et
al, 2000a):
k=
N
V
⎡⎛ g ⎞ dθ ⎤
N = ⎢⎜ ⎟ ⎥
⎣⎝ θ ⎠ dz ⎦
1 2
where,
N
is the Brunt-Väisälä frequency (1/s) in a layer from the ground through
a user-input height (m)
θ
is the potential temperature (K),
g
is the acceleration due to gravity (m/s²), and,
|V|
is the speed of the domain-mean wind
CALMET makes use of an empirical scheme to estimate the magnitude of slope flows in
complex terrain. The slope flow vector is added to Step 1 of the gridded wind field,
producing an adjusted Step 1 wind field (Scire et al, 2000a):
′
u1 = u1 + us
′
v1 = v1 + vs
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-4
where,
(u1,v1)
are the components of Step 1 wind field (m/s) before
considering slope flow effects,
(us,vs)
are the slope flow wind components, and,
(u1’,v1’)
are the components of Step 1 wind field (m/s) after considering
slope flow effects.
This slope flow parameterisation follows the methodology of Mahrt (1982), whereby it is
assumed (for the derivation of the slope flow speed only) that the flow is steady, its depth is
constant and the terrain slope is constant. Coriolus effects and cross-slope components are
neglected. The slope flow is given as (Scire et al, 2000a):
⎡
⎛
⎞⎤
S = S e ⎢1 − exp⎜ − x ⎟⎥
Le ⎠⎦
⎝
⎣
( )
1 2
⎤
Se = ⎡hg ∆θ sin α
(CD + k )⎥⎦
θ
⎢⎣
Le = h
1 2
(CD + k )
where,
Se
Le
x
∆θ
θ
CD
h
α
k
g
-
is the equilibrium speed of the slope flow,
is the equilibrium length scale,
is the distance to the crest of the hill,
is the potential temperature deficit with respect to the environment,
is the potential temperature of the environment,
is the surface drag coefficient,
is the depth of the slope flow,
is the angle of the terrain relative to the horizontal,
is the entrainment coefficient at the top of the slope flow layer, and,
is the gravitational acceleration constant (9.8 m/s²).
As the flow moves down slope, it is cooled by the local heat flux. The constant depth of the
slope flow and sensible heat flux is determined using the assumptions of Briggs (1979).
The thermodynamic blocking effects of terrain on the wind flow are determined in terms of
the local Froude number (Allwine and Whiteman, 1985):
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-5
Fr =
V
N∆ht
∆ht = (hmax )ij − ( z )ijk
where,
Fr
is the local Froude number,
V
is the wind speed (m/s) at the grid point,
N
is the Brunt-Väisälä frequency,
∆ht
is an effective obstacle height (m),
(hmax)ij is the highest gridded terrain height within a radius of influence of the
grid point (i,j), and,
(z)ijk
is the height of level k of grid point (i,j) above the ground.
Step 2 consists of four sub steps due to the introduction of observational data (Douglas and
Kessler, 1988):
• Interpolation
• Smoothing
• O’Brien adjustment of vertical velocities
• Divergence minimisation
Observational data are excluded from the interpolation if the distance between the station
and a particular grid point exceeds the maximum radius of influence specified (EPA, 1995b;
Scire and Robe, 1997).
An inverse-distance method is utilised to introduce observational data into the Step 1 wind
field (Scire et al, 2000a):
(u, v )2′ =
(u, v )1 +
R
2
∑
(uobs , vobs )k
Rk2
1
1
+∑ 2
2
R
Rk
k
where,
(uobs, vobs)k
(u,v)1
(u,v)2’
Rk
R
-
are the observed wind components at station k,
are the Step 1 wind components at a particular grid point,
are the initial Step 2 wind components,
is the distance from the observational station k to the grid point,
is a user defined weighting parameter for the Step 1 wind field.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-6
The interpolation scheme allows data to be heavily weighted in the vicinity of the observed
station.
Once observational data has been introduced to Step 1 wind data, the wind field is subject to
smoothing to reduce resultant discontinuities in the wind field. Smoothing is undertaken
using the following equation (Scire et al, 2000a):
(u ) ″ = 0.5u
i, j 2
i, j
[
+ 0.125 ui −1, j + ui +1, j + ui , j −1 + ui , j +1
]
where,
(ui,j)” (ui,j) -
is the u wind component at grid point (i,j) after smoothing, and
is the u wind component before smoothing
A similar equation is supplied for the v wind component.
Two methods are available for calculating vertical velocities in CALMET (Scire et al, 2000a):
• Method 1: vertical velocities are computed directly from the incompressible
conservation of mass equation using the smooth horizontal and vertical wind
components;
• Method 2: adjusts the vertical velocity profile so that the values at the top of the
modelling domain are zero. The horizontal wind components are, hereafter,
readjusted to be mass consistent with the new vertical velocity field.
Method 1 is calculated as follows:
″
″
du
dv
dw
+
+ 1 =0
dx
dy
dz
where,
w1
u”,v”
-
is the vertical velocity in terrain-following coordinates, and
are the horizontal wind components after smoothing.
This procedure, however, may lead to unrealistically large vertical velocities in the top layers
of the grid (Godden and Lurmann, 1983). To avoid this problem, Method 2 is provided (a
procedure suggested by O’Brien (1970) to adjust w1:
⎛
⎞
w2 (z ) = w1 ( z ) − ⎜ z
⎟ w1 (z = ztop )
z
top
⎝
⎠
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-7
The three-dimensional divergence in the wind field is minimised by making use of the
procedure provided by Goodin et al. (1980). With the use of this procedure, the horizontal
wind components (u,v) are iteratively adjusted for a fixed vertical velocity field so that at each
grid point, the divergence is less than a user-specified maximum value.
du dv dw
+
+
<ε
dx dy dz
where,
u,v
w
ε
-
are the horizontal wind components
is the vertical velocity in terrain following coordinates, and,
is the maximum allowable divergence
The horizontal wind components are defined at the grid points, whereas the vertical velocities
are defined at the vertical grid cell faces. Therefore, the divergence (D) at grid point (i,j,k) is:
Dijk =
wi , j ,k +1 / 2 − wi , j ,k −1 / 2
z k +1 / 2 − z k −1 / 2
+
u i +1, j ,k − u i −1, j ,k
2∆x
+
vi , j +1,k − vi , j −1,k
2 ∆y
where ∆x and ∆y are the sizes of the grid cell in the x and y direction respectively.
At each grid point, divergence is calculated. The u and v components at the surrounding
cells are adjusted so that the divergence at the grid cell point is zero. The adjustments are
as follows:
(u new )i +1, j ,k
= u i +1, j ,k + u adj
(u new )i −1, j ,k
= u i −1, j ,k − u adj
(vnew )i , j +1,k
= vi , j +1,k + v adj
(v new )i , j −1,k
= vi , j −1,k − v adj
where the adjustment velocities (uadj, vadj) are:
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-8
u adj =
v adj =
− Dijk ∆x
2
− Dijk ∆y
2
It should be noted that as divergence is eliminated at a particular grid point, it is created at
surrounding grid points. However, through an iterative procedure, the divergence is
minimised to a threshold value (ε) throughout the grid.
3.1.2
CALPUFF Dispersion Model
CALPUFF is a non-steady-state Lagrangian Gaussian puff dispersion model which is able to
simulate the effects of time- and space-varying meteorological conditions, and thus is able to
predict the pollutant transport, transformation and eventual removal from the atmosphere.
The CALPUFF model is suitable for application in modelling domains of 50 km to 200 km.
The model contains modules for complex terrain effects, overwater transport, coastal
interaction effects, building downwash, wet and dry removal and simple chemical
transformation (EPA, 1995a). Major features of the CALPUFF model is summarised in Table
3-3 and input data required for CALPUFF is given in Table 3-4 (Scire et al, 2000b).
Table 3-3:
Major features of the CALPUFF model
Feature
Sources types
Non-steady-state emissions
and
meteorological
conditions
-
-
Efficient sampling functions
Dispersion coefficient (σy,σz)
options
Vertical wind shear
-
Contents
Point sources (constant or variable emissions)
Line sources (constant or variable emissions)
Volume sources (constant or variable emissions)
Area sources (constant or variable emissions)
Gridded 3-D fields of meteorological variables (winds,
temperatures)
Spatially-variable fields of mixing height, friction velocity,
convection
velocity
scale,
Monon-Obukhov
length,
precipitation rate
Vertical and horizontally-varying turbulence and dispersion
rates
Time-dependent source and emissions data
Integrated Puff formulation
Elongated Puff (slug) formulation
Direct measurements of σv and σw
Estimated values of σv and σw based on the similarity theory
Pasquill-Gifford (PG) dispersion coefficients (rural areas)
McElroy-Pooler (MP) dispersion coefficients (urban areas)
CTDM dispersion coefficients (neutral/stable)
Puff splitting
Differential advection and dispersion
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-9
Feature
Plume rise
Contents
Building downwash
Subgrid
terrain
scale
complex
-
Interface to the Emissions
Production Model (EPM)
Dry Deposition
-
Overwater
and
interaction effects
-
coastal
-
Chemical
options
transformation
-
Wet removal
Graphical User Interface
-
Partial penetration
Buoyant and momentum rise
Stack tip effects
Vertical wind shear
Building downwash effects
Huber-Snyder method
Schulman-Scire method
Dividing streamline, Hd:
Above Hd, puff flows over the hill and experiences
altered diffusion rates
Below Hd, puff deflects around the hill, splits and
warps around the hill
Time-varying heat flux and emissions from controlled burns
and wildfires
Gases and particulate matter
Three options:
Full treatment of space and time variations of
deposition with a resistance model
User-specified diurnal cycles for each pollutant
No dry deposition
Overwater boundary layer parameters
Abrupt change in meteorological conditions, plume dispersion
at coastal boundary
Plume fumigation
Option to introduce subgrid scale Thermal Internal Boundary
Layers (TIBLs) into coastal grid cells
Pseudo-first-order chemical mechanism for sulphur dioxide,
SO4, NOx, HNO3 and NO3 (MESOPUFF II method)
User-specific diurnal cycles of transformation rates
No chemical conversion
Scavenging coefficient approach
Removal rate a function of precipitation intensity and
precipitation type
Point-and-click module setup
Enhanced error checking of model inputs
On-line Help files
Table 3-4:
Summary of input data used by the CALPUFF dispersion model using the
CALMET meteorological model
Input Data
Geophysical
data
(CALMET.DAT)
Meteorological
(CALMET.DAT)
data
Contents
Gridded fields of:
- surface roughness lengths (z0)
- land use categories
- terrain elevations
- leaf area indices
Gridded fields of:
- u,v,w wind components (3-D)
- air temperature (3-D)
- surface friction velocity (u*)
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-10
Input Data
Restart
Data
(RESTARTB.DAT)
Emissions
Data
(CALPUFF.INP,
PTEMARB.DAT,
BAEMARB.DAT,
VOLEM.DAT,
LNEMARB.DAT)
Deposition
Velocity
Data (VD.DAT)
Ozone
Monitoring
Data (OZONE.DAT)
Chemical
Transformation Data
(CHEM.DAT)
Hill Data (HILL.DAT)
CTSG
Receptors
(HILLRCT.DAT)
Subgrid Scale Coastal
Boundary
Data
(COASTLN.DAT)
Boundary Data for
Diagnostic Mass Flux
Option
(FLUXBDY.DAT
Contents
- convective velocity scale (w*)
- mixing height (zi)
- Monon-Obukhov length (L)
- PGT stability class
- Precipitation rate
Hourly values of the following parameters at surface meteorological stations:
- air density (ρa)
- air temperature
- short-wave solar radiation
- relative humidity
- precipitation type
Model puff data generated from a previous run (allows continuation of a
pervious model run)
Point source emissions:
- Source and emissions data for point sources with constant or
cyclical emission parameters (CALPUFF.INP)
- Source and emissions data for point sources with arbitrary-varying
emission parameters (PTMARB.DAT)
Area source emissions:
- Emissions and initial size, height and location for area sources with
constant or cyclical emission parameters (CALPUFF.INP)
- Gridded emissions data for buoyant area sources with arbitraryvarying emission parameters (BAEMARB.DAT)
Volume source emissions:
- Emissions, height, size and location of volume sources with constant
or cyclical emission parameters (CALPUFF.INP)
- Emissions data for volume sources with arbitrary-varying emission
parameters (VOLEM.DAT)
Line source emissions:
- Source and emissions data, height, length, location, spacing and
orientation of buoyant line sources with constant or cyclical emission
parameters (CALPUFF.INP)
- Emissions data for buoyant line sources with arbitrary-varying
emission parameters (LNEMARB.DAT)
Deposition velocity for each user-specified species for each hour of a diurnal
cycle
Hourly ozone measurements at one or more monitoring stations
Species-dependent chemical transformation rates for each hour of a diurnal
cycle
Hill shape and height parameters in CTDMPLUS format for use in the subgrid scale complex terrain module (CTSG)
Receptor locations and associated hill ID in CTDMPLUS format
File containing X,Y coordinates of subgrid scale coastlines to be treated by
CALPUFF
File containing X,Y coordinates of boundaries used to evaluate hourly mass
transport
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-11
The CALPUFF (puff-based) dispersion model has numerous features as discussed in Table
3-3 and contains complex algorithms for the computation of the dispersion of pollutants
taking into consideration the:
• Atmospheric turbulence (with the use of methods provided by Arya (1984), Briggs
(1985), Caughey (1981), Draxler (1976), Gifford (1976), Hanna et al. (1977), Heffter
(1965), Hicks (1985), Nieuwstadt (1984), Panofsky et al. (1977) and Weil (1985));
• Buoyancy (with the use of methods provided by Pasquill (1976) and Irwin (1979));
• Initial plume size;
• Puff-splitting
• Convective boundary layer (with the use of methods provided by Hanna et al.
(1986), Hicks (1985) and Weil et al. (1997));
• Vertical puff stretching;
• Building downwash (with the use of algorithms provided by Huber and Snyder
(1976), Huber (1977), Scire and Schulman (1980) and Schulman and Hanna
(1986));
• Plume rise (with the use of methods provided by Briggs (1973), Briggs (1975),
Hanna and Chang (1991), Hoult and Weil (1972) and Weil (1988)); and,
• Complex terrain.
In a simplistic review, puff models (such as the CALPUFF model) represent a continuous
plume of pollutant material as a number of discreet packets with the basic equation for the
contribution of a puff at a receptor given as (Scire et al, 2000b):
C=
Q
2πσ xσ y
g=
2
[
∑ exp[− (H
∞
(2π ) σ z n=−∞
1/ 2
( )] [
( )]
g exp − d a2 / 2σ x2 exp − d c2 / 2σ y2
]
+ 2nh ) / (2σ z2 )
2
e
where,
C
Q
σx
wind direction
σy
wind direction
σz
direction
da
wind direction
is the ground-level concentration (g/m³)
is the pollutant mass (g) in the puff
is the standard deviation (m) of the Gaussian distribution in the alongis the standard deviation (m) of the Gaussian distribution in the crossis the standard deviation (m) of the Gaussian distribution in the vertical
is the distance (m) from the puff centre to the receptor in the along-
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-12
dc
wind direction
g
H
h
-
is the distance (m) from the puff centre to the receptor in the crossis the vertical term (m) of the Gaussian equation
is the effective height (m) above the ground of the puff centre
is the mixed-layer height (m)
For a horizontal symmetric puff, with σx = σy, the puff equation can be simplified as follows
(Scire et al, 2000b):
C (s ) =
Q (s )
g (s ) exp − R 2 (s ) (2σ y2 (s ))
2πσ y2 (s )
[
]
where,
R
s
-
is the distance (m) from the centre of the puff to the receptor, and,
is the distance (m) travelled by the puff
Integrating the above equation over the distance of puff travel, ds, during the sampling step,
dt, gives the time averaged concentration, C (Scire et al, 2000b):
C=
1 s0 + ds Q(s )
g (s ) exp − R 2 (s ) (2σ y2 (s )) ds
2
∫
s
ds 0 2πσ y (s )
[
]
where s0 is the initial value of s at the start of the sampling step.
A systematic solution of this equation can be obtained if it is assumed that the puff distance
descrepencies during the sampling step are in the R(s) and Q(s) terms. Assuming the
trajectory segment is a straight line, and transforming s to a dimensionless trajectory variable
(p) the radial distance to the receptor at (xr,yr) is (Scire et al, 2000b):
[
R ( s ) = ( x1 − x r + pdx ) + ( y1 − y r + pdy )
2
]
2 1 2
where,
p
is zero at the start of the trajectory segment (x1,y1)
p
is 1 at the end of the trajectory segment (x1,y1), and
dx, dy are the incremental X and Y distances travelled by the puff (dx=x2-x1,
and dy=y2-y1).
The exponential variation of Q, taking into account the removal and chemical transformation
process, is expressed as a linear function of the sampling interval (Scire et al, 2000b):
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-13
Q(s ) = Q(s 0 ) + p[Q(s 0 + ds ) − Q(s 0 )]
Transforming to p coordinates, the equation becomes (Scire et al, 2000b):
C=
1
1
⎧
⎫
2
2
2
2
(
)
(
)
(
)
(
)
Q
s
exp
R
p
(
2
σ
)
dp
[
Q
s
ds
Q
s
]
−
+
+
−
⎨
0 ∫
0
0 ∫ p exp − R ( p ) (2σ y ) dp ⎬
y
2
2πσ y ⎩
0
0
⎭
[
g
]
[
]
The solution of the integrals of the above equation is expressed in terms of error functions
and exponentials (Scire et al, 2000b):
C=
g
2πσ y2
{Q(s0 )I1 + [Q(s0 + ds ) − Q(s0 )]I 2 }
where,
⎡π ⎤
I1 = ⎢ ⎥
⎣ 2a ⎦
12
⎡ b ⎤ ⎫⎪
⎡ b 2 c ⎤ ⎧⎪ ⎡ a + b ⎤
−
erf
exp ⎢ − ⎥ ⎨erf ⎢
⎥
⎢
12
1 2 ⎥⎬
⎣ 2a 2 ⎦ ⎪⎩ ⎣ (2a ) ⎦
⎣ (2a ) ⎦ ⎪⎭
and,
I2 =
⎡−1⎛
⎡ b 2 c ⎤ ⎧⎪ ⎡ − b 2 ⎤
− bI 1 1
b 2 ⎞⎤ ⎫⎪
⎜
⎟⎟⎥ ⎬
+ exp ⎢ − ⎥ ⎨exp ⎢
−
a
+
b
=
exp
2
⎢ ⎜
⎥
a
a
a
2
⎣ 2a 2 ⎦ ⎪⎩ ⎣ 2a ⎦
⎝
⎠⎦ ⎪⎭
⎣
with reference to,
(
)
a = dx 2 + dy 2 σ y2
b = [dx(x1 − x r ) + dy ( y1 − y r )] σ y2
[
c = ( x1 − x r ) + ( y1 − y r )
2
2
]σ
2
y
The horizontal dispersion coefficient (σy) and the vertical term (g) are evaluated and held
constant throughout the trajectory segment.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-14
3.1.3
Model Accuracy
Comparisons between CALPUFF results, and results generated by the Industrial Source
Complex Model Short Term version 3 (ISCST3) model, have shown that predictions form the
CALPUFF model are generally more conservative (Strimaitis, et al., 1998). From numerous
investigations, modelled predictions from the ISC model is typically within a factor of 2 to 10
for areas of complex topography with a high incidence of calm wind conditions. When
applied in flat or gently rolling terrain, the United States Environmental Protection Agency
(US-EPA) (EPA, 1986) considers the range of uncertainty of the ISC to be -50% to 200%.
Predicted average concentrations using CALPUFF has a greater correlation with
observations in comparison to ISCST3 (Wang et al., 2006). The accurate prediction of
instantaneous peaks, however, are the most difficult with the CALPUFF and ISCST3 models
becoming less accurate (Wang et al., 2006). Instantaneous peak releases are therefore
normally performed with more complicated dispersion models specifically fine-tuned and
validated for the location. The duration of these short-term, peak concentrations are
frequently limited to a few minutes and on-site meteorological data are then essential for
accurate predictions.
CALPUFF has undergone sufficient testing to secure its accuracy for assessing impacts on
air quality related studies. The public comments on the CALPUFF model have provided
general consensus that the technical basis of the CALPUFF modeling system has merit and
provides substantial capabilities to not only address long range transport, but to address
transport and dispersion effects in complex wind situations. Commenters generally agreed
that the CALPUFF modeling system has adequate accuracy for use in the 50 km to 200 km
range, with some studies showing that acceptable results can be achieved on larger areas of
200 km to 300 km (EPA, 2003).
3.1.4
Dispersion Model Data Inputs for the Study Area
3.1.4.1 Receptor Locations and Modelling Domain
A modelling domain was defined in order to encapsulate the Vaal Airshed. The extent of this
domain is demonstrated in Figure 1-1. The meteorology was modelled and the dispersion of
pollutants simulated for the entire area covering ~120 km (east-west) by 135 km (northsouth), with ambient ground-level concentrations and deposition levels being predicted for
over 16 200 receptor points. The regular Cartesian receptor grid selected has a resolution of
1 000 m by 1 000 m. Discrete receptor points were specified for each of the monitoring
station locations to facilitate the simulation of concentrations at these locations for application
in the validation and calibration of the model.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-15
3.1.4.2 Meteorological Data Inputs
CALMET was used to simulate the meteorological field within the study area, including the
spatial variations – both in the horizontal and in the vertical - and temporal variations in the
windfield and atmospheric stability. Upper air data required by CALMET include pressure,
geopotential height, temperature, wind direction and wind speed for various levels. No upper
air monitoring stations are located within the study area with the nearest SAWS station being
located at Irene, City of Tshwane Metropolitan Municipality. Use was therefore made of
ETA-model data for four locations as obtained from the SAWS. Twice daily data were
obtained for five sounding levels. The initial guess field in CALMET was therefore
determined as a combined weighing of surface winds at one Eskom monitoring station, one
ArcelorMittal monitoring station, six Sasol monitoring stations and three SAWS stations,
vertically extrapolated using Similarity Theory (Stull, 1997) and upper air winds. Eskom
monitoring station included Makalu, with the Sasol monitoring sites for which data were
obtained including Hospital, AJ Jacobs, Boiketlong, Leitrim, Steam Station 2 and Grootvlei.
The SAWS stations used in the study were Johannesburg (OR Tambo), Vereeniging and
Springs (Figure 4-8) (see Section 4.5 for a description on dispersion potential).
The CALMET meteorological model requires hourly average surface data as input; including
wind speed, wind direction, ceiling height, cloud cover, temperature, relative humidity,
pressure and precipitation. The data availability for each of the surface and upper-air
stations used in the current study is given in Table 3-1.
Table 3-5:
Data availability for surface data from industrial and South African Weather
Service (SAWS) meteorological stations within the study area and calculated upper air from
ETA modelled data obtained from the SAWS for the period 2004 to 2006.
Data
Period
Station
Surface
(SAWS)
data
Surface
(Eskom)
data
2004
2005
2006
Johannesburg
98%
98%
98%
Vereeniging
99%
96%
95%
Springs
99%
100%
100%
Makalu (a)
100%
-
-
-
-
100%
-
-
100%
99%
99%
99%
-
-
100%
Leitrim (b)
99%
93%
96%
Grootvlei
94%
84%
85%
55%
62%
65%
Hospital (b)
AJ Jacobs
Surface
(Sasol)
Surface
(b)
data Steam Station 2
Boiketlong (b)
data Jabavu
(b)
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-16
Data
Station
(City
of
Orange Farm
Johannesburg)
Surface data
ArcelorMittal
(ArcelorMittal)
Upper air data
ETA
Period
2004
2005
2006
62%
84%
84%
65%
89%
88%
88%
97%
96%
Notes:
(a) Makalu was decommissioned in December 2004.
(b) A problem was identified in the averaging wind speed and wind direction data from 10 minute to hourly
averages. Unfortunately the 10 minute data was over written with the averaged data and was subsequently lost
for the period 2004 and 2005 and was only available for October to December 2006 (pers comm. Ristoff van Zyl
from Sasol).
A three dimensional meteorological data set for the region was output by the CALMET model
for application in the CALPUFF model. This data set parameterised spatial (horizontal and
vertical) and temporal variations in the parameters required to model the dispersion and
removal of pollutants, including: vertical wind speed, wind direction, temperature, mixing
depths, atmospheric stability, (etc.). Meteorological parameters were projected at various
heights above the ground, viz.: 20m, 200m, 500m, 1500m, and 3000m. In projecting vertical
changes in the windfield, temperature (etc.) it was possible to accurately parameterize the
atmospheric conditions characteristic of within valley layers, transitional layers and
atmospheric layers located above the terrain. The three-dimensional data set was generated
for the base-case years selected (2004 to 2006) and comprised hourly averages for each
parameter, thus providing information for each time interval required by the non-steady state
CALPUFF dispersion model.
3.1.4.3 Source and Emissions Data Inputs
Point, area and volume sources (in the form of CALPUFF.INP files) were inputted into the
CALPUFF model. Source parameter requirements for input into the CALPUFF model
include stack height, stack diameter, exit temperature, exit velocity, elevation of stack base
above sea level and source location. For fugitive emission sources, the dimensions of the
source as well as the location are required. Emissions rates for each pollutant and source
were also required as input to the model. The emissions data input in the dispersion
simulations are provided in Chapter 6.
3.1.4.4 Chemical Transformation
CALPUFF allows for first order chemical transformation modelling to determine gas phase
reactions for SOx and NOx. Chemical transformation rates were computed internally by the
model using the RIVAD/ARM3 Scheme. This scheme allows for the separate modelling of
nitrogen dioxide and nitric oxide, whereas the default MESOPUFF II Scheme only makes
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-17
provision for the combined modelling of NOx. The RIVAD/ARM3 scheme treats the nitric
oxide and nitrogen dioxide conversion process in addition to the nitrogen dioxide and total
NO3 and sulphur dioxide to SO4 conversions, with equilibrium between gaseous HNO3 and
ammonium nitrate aerosol (Scire et al, 2000b). The scheme uses user-input ozone data
(together with modelled radiation intensity) as surrogates for the OH concentration during the
daytime when gas phase free radical chemistry is active. Measured ambient ozone
concentrations were used for input into the dispersion model for the chemical transformation
modelling.
3.2
3.2.1
Emissions Quantification Methodology
Industrial Sources
In order to obtain recent emissions data from industry, a detailed questionnaire was compiled
and sent out to all identified industries within the Vaal Airshed (Liebenberg-Enslin et al.,
2007) (see Appendix A for example). Of all identified industries and mines, 51% responded
with updated emissions information reflecting current operating conditions (as for 2006).
Information for 37% of the remaining industries was obtained from the NEDLAC Dirty Fuels
study conducted in 2004 and EIA information with 12% of the sources unaccounted for.
3.2.2
Domestic Fuel Burning
The numbers and spatial distribution of households using various fuel types were estimated
based on energy use statistics and household numbers from the 2001 Census. A more
recent study undertaken by the Bureau of Market Research at UNISA (2006) indicated that
the African population for the Free State and Gauteng provinces has increased by 0.47%
and 0.97% from 2001 to 2006, respectively. Thus there may be an under prediction for
domestic fuel burning of less than 1% based on population predictions. Due to the 2001
Census data being outdated reference was also made to a study conducted by NOVA during
2003 – 2004 in Zamdela where coal burning households were surveyed. The aim of this
study, however, was to determine the reduction in coal use due to the introduction of the
Basa Njengo Magogo coal burning method. This information was therefore not useful in
determining the actual amount of coal per household.
Typical monthly fuel use figures, given by Afrane-Okese (1998) for various house types,
were used together with the numbers of households using the various fuel types to estimate
the total quantities of fuels being consumed. Quantities of fuels used were estimated on a
community-by-community basis and selected emission factors applied to calculate resultant
emissions. The emission factors selected for use in the study are given in Table 3-6.
Table 3-7 provides the estimated total amount of fuel used within the Vaal Airshed.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-18
Table 3-6:
Emission factors selected for use in estimating atmospheric emission
occurring as a result of coal, paraffin and wood combustion by households.
Fuel
SO2 (g/kg)
11.6(a)
0.1(b)
0.2(c)
Coal
Paraffin
Wood
Emission Factors
NO (g/kg)
4(d)
1.5(e)
1.3(c)
PM10 (g/kg)
12(f)
0.2(e)
17.3(c)
Notes:
(a) Based on sulphur content of 0.61% and assuming 95% of the sulphur is emitted.
(b) Based on sulphur content of paraffin (<0.01% Sulphur).
(c) Based on US-EPA emission factor for residential wood burning (EPA, 1996).
(d) Based on the AEC household fuel burning monitoring campaign (Britton, 1998) which indicated that an
average of 150 mg/MJ of NOx were emitted during cooking and space heating. Given a calorific value of 27
MJ/kg, the emission rate was estimated to be ~4 g/kg.
(e) US-EPA emission factors for kerosene usage (EPA, 1996).
(f) Initially taken to be 6 g/kg based on 2001 synopsis of studies pertaining to emissions from household coal
burning (Scorgie et al., 2001). Results from simulations using this emission factor undertaken as part of the
current study indicated that fine particulate concentrations within household coal burning areas are under
predicted by a factor of two. This emission factor was therefore scaled to 12 g/kg in order to facilitate the more
accurate simulation of airborne fine particulates within household coal burning areas.
Table 3-7:
Sources of energy used by households within the Vaal Airshed (based of
2001 Census data and given as a percentage of total energy consumption).
Source
Electricity
Gas
Paraffin
Wood
Coal
Animal dung
Solar
Other
Lighting (%)
86
0.1
2
N/A
N/A
N/A
0.1
0.1
Cooking (%)
79
1
17
1
2
0.2
0.2
0.1
Heating (%)
74
1
10
2
11
0.1
0.2
2
N/A: Not Applicable
3.2.3
Mining Operations
In quantifying the fugitive emissions from the Sigma and New Vaal collieries, use was made
of the US-EPA emission factors as no locally derived emission factors are available. The
US-EPA has derived emission factors for numerous mining activities which have been
summarised in the AP42 documents under Section 11.9 (Western Surface Coal Mining)3.
3
http://www.epa.gov/ttn/chief/ap42/
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-19
3.2.4
Wind Blown Dust from Eskom’s Ash Dams and Dumps
The calculation of an emission rate for every hour of the simulation period was carried out
using the ADDAS model. This model, developed by Airshed for specific use by Eskom in the
quantification of fugitive emissions from its ash dumps, is based on the dust emission model
proposed by Marticorena and Bergametti (1995). This model accounts for the variability in
source erodibility through the parameterisation of the erosion threshold (based on the particle
size distribution of the source) and the roughness length of the surface. In the quantification
of wind erosion emissions, the model incorporates the calculation of two important
parameters: (i) the threshold friction velocity of each particle size, and (ii) the vertically
integrated horizontal dust flux, in the quantification of the vertical dust flux (i.e. the emission
rate).
The location, dimensions and orientations of the ash dumps were taken from recent satellite
imagery and topographical maps. Particle size distribution data from the Matimba ash dump
(Scorgie et al, 2006) (Table 3-8) were used in the emission estimates given that no sitespecific data in this regard could be obtained.
Table 3-8:
Particle size distribution for the typical materials found on the ash dumps (as
obtained from measured data from the Matimba Power Station operations).
Ash
µm
600
404.21
331.77
272.31
223.51
183.44
150.57
123.59
101.44
83.26
68.33
56.09
46.03
37.79
31.01
25.46
17.15
14.08
7.78
3.53
Fraction of Total Mass
0.0472
0.0269
0.0296
0.0336
0.0404
0.0503
0.0609
0.0687
0.0728
0.0739
0.072
0.0669
0.0607
0.0537
0.0471
0.0407
0.0628
0.0528
0.0285
0.0105
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-20
3.2.5
Vehicle Emissions
In estimating petrol-driven vehicle emissions the following steps were followed:
•
The petrol-driven vehicle fleets were characterised based on the vehicle sales for
2000 (obtained from Anton Moldan of SA Petroleum Industry Association). The
vehicle sales for 2000 comprise detailed information on petrol-driven vehicles sold
between including: engine capacity and catalytic converters (etc.).
•
A more recent national vehicle population data base was obtained from the
National Transport Information System (NATIS) for the period of 2005 to
supplement the spatially-resolved 2000 engine capacity data obtained from SA
Petroleum Industry Association.
•
Annual leaded and unleaded petrol sales data, obtained from South African
Petroleum Industry Association (SAPIA) per magisterial district for 2004 (Table 39), obtained from SAPIA data per magisterial district for 2006, were used to
estimate the total vehicle kilometers travelled using fuel consumption rates suited to
each engine capacity class and general fuel type. (Petrol consumption rates range
from 7.7 to 15.1 litres per 100 km) (Wong, 1999).
•
Locally developed emission factors published by Wong (1999) were applied taking
into account variations in such factors for different energy capacities. Emission
factors used are given in Table 3-10 and Table 3-11. Emissions were calculated by
multiplying the emission factors by the total vehicle kilometers travelled (VKT)
estimated on the basis of the 2006 fuel sales data.
Table 3-9:
Leaded and unleaded petrol sales within the Vaal Airshed during 2006 as
obtained from Anton Moldan, South African Petroleum Industry Association.
Magisterial District
Alberton
Benoni
Boksburg
Brakpan
Brits
Bronkhorstspruit
Balfour
Cullinan
Frankfort
Germiston
Heilbron
Heidelberg (Tvl)
Johannesburg
Krugersdorp
2006 Fuel Sales within the Vaal Airshed (Litres/Annum)
Lead Replacement Petrol
Unleaded Petrol
63 103 689
74 761 516
68 445 049
75 322 346
58 772 808
82 142 120
29 951 228
27 698 022
25 778 315
32 799 595
15 904 413
20 043 790
5 251 026
10 780 033
6 274 607
4 764 748
4 043 998
3 288 779
84 113 076
133 712 749
3 143 949
2 255 120
11 857 863
17 615 396
415 893 559
542 370 272
45 169 509
52 356 568
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-21
2006 Fuel Sales within the Vaal Airshed (Litres/Annum)
Lead Replacement Petrol
Unleaded Petrol
103 944 224
131 702 687
2 106 858
5 112 227
12 470 450
10 911 712
335 171 318
511 348 121
5 208 162
5 155 609
25 182 024
31 663 236
21 604 667
18 588 473
74 087 410
128 281 483
122 602 264
345 380 532
67 316 725
34 720 763
37 170 449
35 894 568
46 132 668
46 130 541
54 879 358
74 082 905
20 725 082
13 111 435
42 239 158
55 318 351
Magisterial District
Kempton Park
Koppies
Nigel
Pretoria
Parys
Potchefstroom
Randfontein
Roodepoort
Randburg
Sasolburg
Springs
Vanderbijlpark
Vereeniging
Westonaria
Wonderboom
Table 3-10: Emission factors for non-catalytic converter equipped petrol-driven vehicles
used for the estimation of vehicle emissions
Pollutant
THC
NOX
CO
CO2
SO2
CH4
NMTOC
1,3 Butadiene
Benzene
Formaldehyde
Acetaldehyde
Lead
N2O
Units
Highveld
Leaded Petrol
g/km
g/km
g/km
g/km
g/km
g/km
g/km
g/km
g/km
mg/km
mg/km
g/km
mg/km
Unleaded Petrol
1.79
1.99
16.13
188.00
0.05
0.06
1.74
0.02
0.03
14.57
4.93
0.02
5.00
1.63
2.15
10.70
190.00
0.04
0.04
1.59
0.03
0.02
16.50
11.30
5.00
Sources: Wong (1999), Copert (2000) for lead and N2O
Table 3-11: Emission factors for catalytic converter equipped petrol-driven vehicles used
for the estimation of vehicle emissions
Pollutant
THC
NOX
CO
CO2
SO2
Units
g/km
g/km
g/km
g/km
g/km
Highveld
Leaded Petrol
Unleaded Petrol
0.54
0.86
3.63
257.00
0.01
1.03
0.93
4.30
243.00
0.02
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-22
Pollutant
CH4
NMTOC
1,3 Butadiene
Benzene
Formaldehyde
Acetaldehyde
Lead
N2O
Highveld
Units
Leaded Petrol
g/km
g/km
g/km
g/km
mg/km
mg/km
g/km
mg/km
Unleaded Petrol
0.03
0.51
0.00
0.02
3.47
4.93
0.02
5.00
0.05
0.98
0.00
0.02
3.60
8.00
5.00
Source: Wong (1999), Copert (2000) for lead and N2O
In estimating diesel-driven vehicle emissions the following steps were followed:
•
Average percentages of light commercial vehicles (LCVs) and medium and heavy
commercial vehicles (M&HCVs) within the national diesel vehicle fleet were
obtained from the NATIS 2005 vehicle population data for Gauteng, Free State,
Mpumalanga and the North West Province.
•
Diesel consumption rates were obtained for LCVs, MCVs and HCVs for highveld
applications from Stone (2000) and Wong (1999). Such rates varied from 10.5 to
24.4 litres per 100 km.
•
Annual diesel sales data, obtained from SAPIA per magisterial district for 2006
(Table 3-12), were used to estimate the total vehicle kilometres travelled using fuel
consumption rates suited to each vehicle weight category.
•
Locally developed emission factors published by Stone (2000) were applied taking
into account variations in vehicle weight categories (highveld factors) (Table 3-13).
Emissions were calculated by multiplying the emission factors by the total vehicle
kilometres travelled (VKT) estimated on the basis of the 2006 fuel sales data.
Table 3-12: Diesel sales within the Vaal Airshed during 2006 as obtained from Anton
Moldan, South African Petroleum Industry Association.
Magisterial District
Alberton
Benoni
Boksburg
Brakpan
Brits
Bronkhorstspruit
Balfour
2006 Fuel Sales within the Vaal Airshed (litres/annum)
Diesel
142 600 629
65 286 343
59 905 659
36 071 165
62 528 175
23 156 394
12 229 861
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-23
2006 Fuel Sales within the Vaal Airshed (litres/annum)
Diesel
6 609 371
10 388 670
141 789 939
3 935 819
19 335 318
558 673 261
85 876 185
126 789 531
16 598 418
28 909 287
463 496 496
8 196 844
26 888 137
24 793 638
53 546 946
123 332 507
137 603 263
25 346 532
54 671 269
74 281 995
17 179 230
35 050 176
Magisterial District
Cullinan
Frankfort
Germiston
Heilbron
Heidelberg (Tvl)
Johannesburg
Krugersdorp
Kempton Park
Koppies
Nigel
Pretoria
Parys
Potchefstroom
Randfontein
Roodepoort
Randburg
Sasolburg
Springs
Vanderbijlpark
Vereeniging
Westonaria
Wonderboom
Table 3-13: Highveld emission factors for diesel-driven vehicles used in the quantification
of vehicle emissions for the Vaal Airshed.
Pollutant
Units
THC
g/km
NOX
g/km
CO
g/km
CO2
g/km
SO2
g/km
CH4
g/km
NMTOC
g/km
1,3 Butadiene
g/km
Benzene
g/km
Formaldehyde
mg/km
Acetaldehyde
mg/km
Particulates
g/km
N2O(a)
mg/km
FUEL CONSUMPTION (l/km)
Sources: Wong (1999)
Diesel – LCVs
1.010
11.680
3.540
739.000
1.540
0.147
0.863
0.007
0.008
0.016
0.010
0.640
30.000
0.239
Source: Stone (2000)
Diesel - M&H
1.010
11.680
3.540
739.000
1.540
0.088
0.922
0.004
0.000
0.016
0.010
0.640
30.000
0.244
(a) Use was made of Coppert emission factors for the estimation of N2O emissions given the absence of local
emission factors for this pollutant
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
3-24
4
CHAPTER 4
REGIONAL CLIMATE AND ATMOSPHERIC DISPERSION
POTENTIAL OVER THE VAAL AIRSHED
The meteorological characteristic of a site governs the transport (viz. wind speed and wind
direction) and dispersion (viz. turbulence and mixing height of lower boundary layer) of
pollutants in the atmosphere (Pasquill and Smith, 1983; Godish, 1990). The extent to which
pollution will accumulate or disperse in the atmosphere is dependent on the vertical (defined
by the stability of the atmosphere and the depth of the surface mixing layer) and horizontal (a
function of the wind field) components of motion. The speed of the wind field in turn will
determine the distance the plume will travel before it reaches ground level and the rate of
plume dilution (Shaw and Munn, 1971; Pasquill and Smith, 1983; Preston-Whyte and Tyson,
1989, Oke, 1990).
Variations in spatial, diurnal and seasonal wind field and stability changes are functions of
atmospheric processes (Goldreich and Tyson, 1988). It is therefore necessary to consider
processes at macro- and meso-scales in order to accurately parameterise the atmospheric
dispersion potential of a particular area. Macro-scale ventilation characteristics of an area
are determined by the general circulation, and thus synoptic systems that dominate, within
the region. Meso-scale processes include thermo-topographically induced circulations.
4.1
General Synoptic Circulations that Influence Weather over Southern Africa
The general circulation over southern Africa is influenced by systems that originate in the
tropics in the north, and temperate latitudes to the south. The high pressure systems or
subtropical high pressure cells also influence the general circulation over the southern
hemisphere (The Standard Encyclopaedia of Southern Africa, 1971; Preston-Whyte and
Tyson, 1989; Garstang et al, 1996; Tyson, 1997) (Figure 4-1).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-1
Figure 4-1: Major synoptic circulation types affecting southern Africa and their monthly
frequencies of occurrence over a five year period (after Preston-Whyte and Tyson, 1988 and
Garstang et al., 1996).
4.1.1
Subtropical Systems
The mean circulation over southern Africa is dominated by anticyclonic systems, creating
highly stable atmospheric conditions (Taljaard, 1955; The Standard Encyclopaedia of
Southern Africa, 1971; Tyson et al., 1976; Preston-Whyte et al., 1977; Tyson et al., 1988;
Preston-Whyte and Tyson, 1989; Cosijn and Tyson, 1996, Tyson et al., 1996c; Tyson and
Gatebe, 2001) with a 70% frequency of occurrence in the middle of winter (July) (Tyson et
al., 1996c). These systems are deep and tilt towards the northwest with height. The semiAN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-2
permanent anticyclonic systems that influence the circulation over southern Africa consist of
the South Atlantic Anticyclone, South Indian Anticyclone and Continental High. In winter the
anticyclonic systems intensify and move northward with the migration of the Inter-Tropical
Convergence Zone (The Standard Encyclopaedia of Southern Africa, 1971; Preston-Whyte
and Tyson, 1989). The South Atlantic and South Indian anticyclones move ~6° north in
winter (Preston-Whyte and Tyson, 1989). The South Indian Anticyclone fluctuates more on a
longitudinal scale than the Atlantic Anticyclone (The Standard Encyclopaedia of Southern
Africa, 1971) with the South Indian Anticyclone migrating as much as 24° west during winter
and the South Atlantic Anticyclone moving ~13° east (Preston-Whyte and Tyson, 1989). In
summer, the Continental High is observed to weaken and move southward (The Standard
Encyclopaedia of Southern Africa, 1971).
Stable conditions with low wind speeds reduce mixing and thus dispersion of pollutants in the
atmosphere.
4.1.2
Tropical Systems
Tropical disturbances occur as easterly waves and lows. Easterly waves are semi-stationary
and form in deep easterly currents in the vicinity of the easterly jet. The axes of the systems
are not displaced with height with convergence occurring east of the trough and divergence
above the flow at ~ 500 hPa. This results in strong uplift and rainfall. In unstable conditions
and associated northerly winds, rainy periods will occur east of the trough over wide areas
(Preston-Whyte and Tyson, 1989). The unstable atmospheric conditions enhance the
dispersion of pollutants form emission sources. The pollutant concentrations are thus diluted
before coming down to ground level.
Easterly lows are associated with convergence at the surface (as with easterly waves) but
divergence occurs higher up in the troposphere (Preston-Whyte and Tyson, 1989).
Surface troughs are usually associated with moist air to the northeast and dry air to the
southwest, with thunderstorms occurring in the convergence zone (Preston-Whyte and
Tyson, 1989; The Standard Encyclopaedia of Southern Africa, 1971). Thus the storms occur
in two opposing currents, viz. a warm humid surface current and a cool subsiding
southwestern current at a height of 4 km. The primary thermal surface convection initiates
the instability of the atmosphere, while the convergence of the surface air over the
southwestern air feeds the instability and results in heavy thundershower activity (The
Standard Encyclopaedia of Southern Africa, 1971).
4.1.3
Temperate Systems
Temperate systems are made up of westerly waves, cut-off lows, southerly meridional flow,
ridging anticyclones, west coast troughs and cold fronts (Preston-Whyte and Tyson, 1989).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-3
4.1.3.1 Westerly Waves
Westerly wave systems slope westward with height with convergence occurring at the
surface to the rear of the trough and divergence ahead of the trough line. Although the
systems may bring about rainfall, this will normally occur over coastal regions and seldom
extend over the interior (Preston-Whyte and Tyson, 1989).
4.1.3.2 Cut-Off Lows
Cut-off lows are an intense form of a westerly wave. These systems are unstable and slope
westward with height with strong convergence and vertical motion (aiding in the dispersion
potential of pollutants). With these characteristics, cut-off lows are associated with flood
producing rains over South Africa (Preston-Whyte and Tyson, 1989).
4.1.3.3 Southerly Meridional Flow
This system is a surface circulation pattern over the south of the subcontinent. The system
has a strong pressure gradient with a high to the west and a low to the east. This results in a
region of upper level divergence overlying an area of convergence west of the cold front.
The resultant vertical motion gives rise to light rainfall over coastal regions and the Lowveld
(Preston-Whyte and Tyson, 1989).
4.1.3.4 Ridging Anticyclones
Ridging anticyclones are associated with westerly waves in the upper atmosphere (500 hPa).
They develop due to the steep pressure gradient over the Indian Ocean and adjacent inland
areas, promoting strong advection of moist unstable air over land (aiding in the dispersion
potential of pollutants). Weakening inland pressure gradient and meso-scale orographic
forcing with upper level divergence results in wide spread uplift and general rainfall over the
eastern regions of southern Africa (aiding in wet deposition of pollutants within the
atmosphere) (Preston-Whyte and Tyson, 1989).
4.1.3.5 West Coast Troughs
West coast troughs are systems that occur due to a surface trough over the west coast and
an upper level westerly wave to the west of the continent. Surface convergence and upper
level divergence allows for upward vertical; motion (aiding in the dispersion potential of
pollutants) and thus general rainfall over the central and western regions of southern Africa
(aiding in wet deposition of pollutants within the atmosphere) (Preston-Whyte and Tyson,
1989).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-4
4.1.3.6 Cold Fronts
Cold fronts (also known as mid-latitude frontal depressions) are systems that occur together
with westerly waves and cut-off lows, and therefore cannot be seen to occur in isolation
(Preston-Whyte and Tyson, 1989). Frontal depressions form in the westerlies and move
eastwards towards the sub-continent (The Standard Encyclopaedia of Southern Africa,
1971). Pre-frontal conditions are associated with northwesterly air flow with post-frontal
associated with southwesterly. The systems result in sharp decreases in temperature and
generally occur in winter. Pre-frontal conditions give rise to Berg Wind conditions due to the
occurrence of Coastal Lows that precede the front. Coastal Lows result in the movement of
air from the interior to coastal areas increasing in temperature with the adiabatic lapse rate
as it descends the escarpment. Convection occurs to the rear of the front and rainfall
generally occurs as a result over the coastal areas (The Standard Encyclopaedia of Southern
Africa, 1971; Preston-Whyte and Tyson, 1989). As the cold air circulates over land, the
continental warm air will undercut the cold air forcing it to rise. This causes a natural
inversion layer to develop between the two layers of air. If sources of pollutant emissions are
below this inversion, the pollutants will be trapped within this layer. Higher wind speeds
associated with this temperate system, however, will aid in the dispersion potential of
pollutants (Preston-Whyte and Tyson, 1989).
4.2
Persistent Elevated Inversions
The impact of synoptic systems and weather disturbances on the dispersion potential of the
atmosphere is dependent on the occurrences of elevated inversions (Figure 4-2). Elevated
inversions restrict the vertical dispersion of pollutants by reducing the height by which
pollutants are able to mix while confining horizontal transport to between layers (Tyson et al.,
1996a; Tyson et al., 1996c; Freiman and Tyson, 2000; Tyson and Gatebe, 2001). These
elevated inversions also play an important role in the long-range and re-circulated transport
of pollutants.
Persistent stable discontinuities (representing the predominant type of elevated inversion
over South Africa) develop due to the dominant anticyclonic activities over the subcontinent
(Tyson et al., 1996a; Tyson et al., 1996b; Tyson, 1997). The subsiding air that is
characteristic of the anticyclonic activity warms up adiabatically with temperatures in excess
of the mixed boundary layer. The interface between the mixed boundary layer and the
subsiding air is characterised by elevated inversions. These persistent stable discontinuities
are consistent over large distances and have very little diurnal variation (Tyson et al., 1996c).
Persistent elevated inversions over the plateau occur in the middle to upper troposphere at
~700 hPa (~3 km), ~500 hPa (~5 km) and ~ 300 hPa (~7 km), with a forth inversion present
at ~800hPa over coastal areas (Diab, 1975; Cosijn, 1996; Cosijn and Tyson, 1996; Tyson et
al., 1996c; Tyson, 1997; Tyson and Gatebe, 2001). The spatial, circulation type and
seasonal distribution of these absolute stable layers is illustrated in Figure 2-2. These
features are generally shallow with depths varying between a minimum of 51 hPa (for the ~
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-5
800 hPa layer) to a maximum of 66 hPa (for the 300 hPa layer) and seldom more than 1 km
on average (Cosijn and Tyson, 1996).
Figure 4-2: The occurrence of absolutely stable layers over South Africa by circulation
type and time of year. Absolutely stable layers are indicated in block shading, showing base
heights (with 95% confidence limits) and depths (horizontal dimension is arbitrary) (a) for
spatial distribution across South Africa, (b) by circulation type, and (c) by time of year. (d)
Locations of stations. The results are based on the analysis of a total of 2925 radiosonde
ascents taken over the period 1986-92 (Tyson et al., 1996c).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-6
The ~800, ~700 and ~500 hPa elevated inversions show little variation in mean base height
of occurrence and depth throughout the year. During winter the 500 hPa layer is slightly
more frequent and a little higher over the eastern areas. During summer, this layer is slightly
higher over the west (Cosijn and Tyson, 1996). The ~700 hPa layer is slightly more frequent
in winter, but the seasonal contrast in occurrence and depth throughout the year is slight.
The ~ 800 hPa layer is least frequent in winter. Of all the layers, the elevated inversion at
~300 hPa is the most constantly present and provides the largest seasonal change in height,
with the layer being highest in winter and lowest in summer (Cosijn and Tyson, 1996).
Circulation changes do not rapidly affect the occurrence of elevated inversions due to the
circulation over the area being mainly anticyclonic in nature (Preston-Whyte and Tyson,
1989; Cosijn and Tyson, 1996, Cosijn, 1996; Freiman and Tyson, 2000). Even with the
passage of a cold –front, the layer persists, with pre-frontal conditions tending to lower the
base of the elevated inversion, and so reducing the mixing depth (Cosijn and Tyson, 1996,
Cosijn, 1996; Preston-Whyte and Tyson, 1989). Following the passage of the front, a
gradual rise in the mixing depth occurs over the interior (Cosijn, 1996; Preston-Whyte and
Tyson, 1989). It is generally only with the passage of deep and unstable systems or with
deep and vigorous cumulus convection, associated with westerly and easterly wave
disturbances, that the formation of inversions is hindered or that the inversion layers are
destroyed (Cosijn, 1996; Preston-Whyte and Tyson, 1989; Freiman and Tyson, 2000).
These conditions occur for ~18% of the days in a year, producing ~ 86% of the rainfall over
the Highveld (Cosijn and Tyson, 1996). However, although the elevated inversion layers will
dissipate locally, the general spatial and temporal trends of these layers will not alter
significantly (Cosijn and Tyson, 1996; Freiman and Tyson, 2000).
The 500hPa elevated inversion is the most persistent stable layer (Freiman and Tyson, 2000;
Tyson and Gatebe, 2001) and may on occasion prevail without disruption for 40 days over
South Africa during winter and early spring (Freiman and Tyson, 2000; Tyson and Gatebe,
2001). The 500 hPa absolutely stable layer controls the distribution of pollutants over South
Africa and marks the top of the haze layer both in summer and in winter (Freiman and Tyson,
2000; Tyson and Gatebe, 2001).
4.3
Trans-Boundary Transportation of Air Masses over Southern Africa
The two main transport modes of air masses consist of direct transport, in which air masses
are advected directly from the subcontinent to the oceans beyond, and re-circulated
transport, in which air masses re-circulates to the point of origin (Tyson et al., 1996a, Tyson
et al., 1996c) (Figure 4-3). Direct transport is made up of the four cardinal compass
directions, viz. westerly, easterly, northerly and southerly. Westerly transport (within the
Natal Plume) is influenced by the westerly waves (Fishman, 1991; Pickering et al., 1994;
Krishnamurti et al., 1993; Benkovitz et al., 1994; Tyson et al., 1996a, Tyson et al., 1996b)
moving air from the highveld to the Indian Ocean at north-to-central Kwa-Zulu Natal or
southern Mozambique (Tyson et al., 1996a). Air transported in the Natal Plume takes place
at high levels of ~525 hPa (Tyson et al., 1996a). Easterly transport takes place by means of
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-7
easterly waves to move air masses to the Atlantic Ocean. Air masses that move towards the
Atlantic Ocean are transported in the Angolan Plume at low levels due to the subsidence
over the western subcontinent and South Atlantic Ocean. Northerly and southerly transport
moves air masses to equatorial Africa and to the South Indian Ocean respectively (Tyson et
al., 1996a).
Figure 4-3: Schematic representation of major low-level transport trajectory models likely
to result easterly or westerly exiting of material from southern African or in recirculation over
the subcontinent (Tyson et al, 1996c).
Re-circulated transport is confined to levels of less than 200 hPa and is mainly anticyclonic
(Tyson et al., 1996a). Local and regional recirculation extends over the highveld and
surrounding neighbouring countries, such as Mozambique, Zimbabwe and Botswana (Tyson
et al., 1996a; Tyson and Gatebe, 2001). Analysis of trajectory fields undertaken by Tyson et
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-8
al. (1996c) has revealed that air masses emanating from a particular point of origin follow
anticyclonic curving streams with radii of 500 – 700 km. The recirculation vortex is evident
from the surface to the persistent stable layer of 500 hPa. Above 500 hPa, due to the
influence of the circumpolar westerlies, recirculation diminishes rapidly and transport patterns
become more zonal. Local and sub-continental re-circulation over the interior makes up for
~44% of total air mass transportation (Tyson et al., 1996c; Tyson and Gatebe, 2001) with a
recirculation time frame of 2-9 days (Tyson et al., 1996a). Up to a quarter of re-circulated air
masses are observed to re-circulate a second time (Tyson et al., 1996c). Thus, the greatest
impact of pollutants on neighbouring countries is under re-circulating air and prolonged
residence time (Tyson et al., 1996a).
More than 75% of all air circulating over the southern African continent exits to the Indian
Ocean, either by direct or re-circulated transportation (Tyson and Gatebe, 2001).
4.4
Thermo-Topographic Influences
Due to the persistence of anticyclonic activity over the southern African continent, conditions
are typically, to large extent, free of cloud, thus maximising daytime insolation. Similarly,
clear nights result in maximum nocturnal cooling at the surface. The result is the generation
of local and meso-scale thermo-topographic wind systems (Tyson, 1967; Tyson and PrestonWhyte 1972; Tyson et al., 1988; Preston-Whyte and Tyson, 1989; Annegarn et al., 1993;
Held et al., 1994; Piketh, 1995).
4.4.1
Urban Boundary Layer
The urban boundary layer is a complex three-dimensional structure (Rotach et al., 2002) as
shown in Figure 4-4. The main origin of the urban boundary layer (and its differences to the
natural forming boundary layer) is its modified surface roughness elements (i.e. buildings,
tress, etc.).
Horizontally, the urban environment is made up of changes in the roughness and thermal
surface properties (viz. heat capacity and albedo). These changes in surfaces may lead to
the formation of internal boundary layers (Raupach et al., 1991) (Figure 4-4a).
Vertically, the lowest distinct layer is the urban canopy layer that ranges from the ground up
to the average height of roughness elements (i.e. buildings and trees) (Figure 4-4c). Within
the urban canopy layer, the micro scale environments of street canyons develop (ideally
when straight buildings of equal height on either side of a street exist) (Raupach et al., 1991).
The urban canopy layer forms part of the roughness sub layer (Figure 4-4b) (Raupach et al.,
1991) with the inertial sub layer above (Tennekes and Lumley, 1972).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-9
Figure 4-4: Sketch of the urban boundary layer structure indicating the various (sub)
layers and their names (from Rotach et al., 2004, modified after Oke, 1987). An unstable
daytime urban boundary layer is shown.
Due to the characteristic urban boundary layer, pollution domes may form due to the
collection of pollution below the inversion (Barry and Chorley, 1992) (Figure 4-5a). Figure 45b, shows a section of an urban plume. Fumigation is when an inversion lid prevents upward
dispersion and downward lofting occurs above the temperature inversion at the top of a rural
boundary layer dispersing pollution upwards.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-10
Figure 4-5: Configurations of urban pollution. (a) Urban pollution dome and (b) urban
pollution plume in a stable environment (i.e. early morning following a clear night). Fanning
is indicative of vertical atmospheric stability (after Barry and Chorley, 1992).
4.4.2
Valley Atmospheres
The differential heating of slopes gives rise to anabatic (up-valley) flow during the day and
katabatic (down-valley) flow during the night. In order to compensate for the valley flow, a
return current develops above the near-surface flows known as the “anti-wind” (Figure 4-6).
A third distinct layer then completing the valley circulation is the gradient wind just above the
anti-wind (Preston-Whyte and Tyson, 1989; Stull, 1997).
The near-valley flow is characterised by moderate wind speed of 1-5m/s. During the
dissipation of anabatic winds and the development of katabatic flow, brief periods of calm
conditions occur (Stull, 1997).
During night-time conditions, cold descending air accumulates within the valley with the
upper slopes remaining warmer. This results in a layer of warm air above cooler air which in
turn creates a valley inversion. The warmer air migrates upslope until the colder air
completely covers the valley. Thus the valley inversion occurs from the ground upwards,
replacing the turbulent mixing layer and resulting in low level stability (Preston-Whyte and
Tyson, 1989; Stull, 1997) (Figure 4-7). Due to the combination of the stable layer near the
surface and the elevated inversion, pollutants within the valley become suppressed. In turn,
the gradual development of a mixing layer beneath the valley inversion results in fumigation
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-11
conditions with the valley inversion acting as a lid trapping the pollution. Maximum ground
level pollutant concentrations therefore develop in the early morning and at night due to the
dissipation and development of valley inversions (Rautenbach, 2006).
Figure 4-6: Along-valley winds: (a) daytime valley and anti-valley winds; and (b) night time
mountain and anti-mountain winds (after Stull, 1997).
During day-time conditions, surface heating of the valley due to incoming solar radiation
results in low-level mixing and anabatic flow up the valley sides. The subsiding air in turn
heats adiabatically as the valley inversion subsides until a well mixed atmosphere fills the
valley (Preston-Whyte and Tyson, 1989; Rautenbach, 2006). Due to the well mixed layer,
the potential for vertical and horizontal dispersion of pollutants is improved (Rautenbach,
2006).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-12
Figure 4-7: Idealised evolution of the cross-valley circulations during a diurnal cycle.
Potential temperature profile corresponds to sounding made from the centre of the valley
(after Stull, 1997).
4.5
Meso-scale Ventilation and Site-specific Dispersion Potential.
The analysis of hourly average meteorological data is necessary to facilitate a
comprehensive understanding of the ventilation potential of the site, and to provide the input
requirements for the dispersion simulations. A comprehensive data set for three years of
detailed hourly average wind speed, wind direction and temperature data are needed for the
dispersion simulations (as specified by the US-EPA for CALMET/CALPUFF suite models).
The period covered included January 2004 to December 2006.
Surface meteorological data was obtained from the South African Weather Service (SAWS)
stations of Vereeniging, Johannesburg (OR Tambo Airport) and Springs and the monitoring
stations of the City of Johannesburg (COJ). In addition use was made of the meteorological
data supplied by various industries in the Vaal Airshed including Sasol, ArcelorMittal Steel
Vanderbijlpark Steel and Eskom (only for 2004 since it was decommissioned). Upper air
meteorological data was obtained from SAWS ETA data model. The information from these
stations was used to simulate a three-dimensional wind field for the study area, taking into
account the land use and topographical data.
A summary of all the meteorological stations used for the current assessment are provided in
Table 4-1, stating the parameters measured and the operational status of each station
amongst other information. The locations of these stations are reflected in Figure 4-8.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-13
Figure 4-8: Locations of surface meteorological stations operated by industry, government
and the SAWS and calculated ETA data points within the study area for which data were
obtained for the study.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-14
Table 4-1:
Monitoring
Agency
Evaluation of meteorological stations operated by the SAWS, industry and various spheres of Government
Station
Name
Longitude
(°E)
Latitude
(°S)
Status
Monitoring
Period
Parameters Measured
Averaging
Period
Type of
Equipment
SANAS
Accredited Yes/No
Jabavu
27.872
-26.253
Active
2004 Present
Wind speed, Wind direction, Temperature,
Relative humidity, Pressure, Rainfall
10 min
intervals
Met One
No
Orange
Farm
27.867
-26.480
Active
2004 Present
Wind speed, Wind direction, Temperature,
Relative humidity, Pressure, Rainfall
10 min
intervals
Met One
No
Makalu
27.903
-26.835
Decommissioned
1984 - 2004
Wind speed, Wind direction, Temperature,
Relative humidity, Sigma Theta
Hourly
RM Young
Yes
Station 620
27.822
-26.673
Active
2005 Present
Wind speed, Wind direction, Temperature
10 min
intervals
RM Young
No
Station 350
27.834
-26.655
Active
2005 Present
Wind speed, Wind direction, Temperature
10 min
intervals
RM Young
No
Caravan
(mobile)
27.788
-26.645
Active
2006 Present
Wind speed, Wind direction, Temperature
10 min
intervals
RM Young
No
AJ Jacobs
27.826
-26.823
Active
2003 Present
Wind speed, Wind direction
10 min
intervals
RM Young
Yes
Boiketlong
27.846
-26.836
Active
2003 Present
Wind speed, Wind direction
10 min
intervals
RM Young
Yes
Grootvlei
28.479
-26.754
Active
-
Wind speed, Wind direction, Temperature
10 min
intervals
RM Young
Yes
COJ
Eskom
ArcelorMitt
al Steel
(MSVS)
Sasol
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-15
Monitoring
Agency
SAWS
Notes:
Station
Name
Longitude
(°E)
Latitude
(°S)
Status
Monitoring
Period
Parameters Measured
Averaging
Period
Type of
Equipment
SANAS
Accredited Yes/No
Hospital
27.826
-26.803
Active
2003 Present
Wind speed, Wind direction
10 min
intervals
RM Young
Yes
Steam
Station
27.853
-26.820
Active
2003 Present
Wind speed, Wind direction, Temperature,
Humidity, Pressure, Rainfall, Solar Radiation
10 min
intervals
RM Young
Yes
Leitrim
27.871
-26.850
Active
2003 Present
Wind speed, Wind direction, Temperature,
Humidity
10 min
intervals
RM Young
Yes
OR Tambo
International
Airport
28.230
-26.150
Active
1960 Present
Wind speed, Wind direction, Temperature,
Humidity, Pressure, Rainfall, Ceiling Height,
Cloud Cover
5 min
intervals
-
-
Springs
28.433
-26.200
Active
1993 Present
Wind speed, Wind direction, Temperature,
Humidity, Pressure, Rainfall
5 min
intervals
-
-
Vereeniging
27.950
-26.567
Active
1993 Present
Wind speed, Wind direction, Temperature,
Humidity, Pressure, Rainfall
5 min
intervals
-
-
COJ - City of Johannesburg, SAWS - South African Weather Services
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-16
Parameters that characterise the meso-scale ventilation potentials of an area include: (i)
wind speed, (ii) wind direction, (iii) ambient air temperature (which in turn is a function of
solar radiation), (iv) precipitation and (v) mixing depth.
4.5.1
Local Wind Field
Wind is an important parameter in the transportation, dispersion and eventual removal of
pollutants. The stronger the wind speed, the more rapid the dilution of pollutants and thus
the lower the concentrations at ground level. Conversely, the lower the wind speeds, the
less dilution of pollutant and thus the higher the concentrations at ground level.
The wind roses provided for the monitoring stations consist of sixteen cardinal wind
directions, with the frequency of wind indicated with the dotted circles. Each circle indicates
a 5% frequency of occurrence. The figure indicated in the centre of each circle is the
percentage calm conditions (wind speeds of <1m/s).
Period average wind roses are reflected in Figure 4-9 with the day-time and night-time
average wind roses provided in Figure 4-10 and 4-11, respectively. The wind roses are
provided for the SAWS stations (OR Tambo, Springs and Vereeniging) and the two stations
owned by the City of Johannesburg (namely Jabavu and Orange Farm) for the period 2004
to 2006. In addition data for three year period received from ArcelorMittal Steel and the
Sasol Grootvlei station are also included. The Eskom Makalu station was decommissioned
in December 2004 and the other five Sasol stations had only three months of data available
(October to December 2006) due to technical problems experienced with the averaging of
the 10-minute data (Personal Communication, Ristoff van Zyl from Sasol, 2007).
The spatial and annual variability in the wind field is clearly evident in the wind roses. OR
Tambo station located furthest north, and to the northeast of the study area, has prevailing
northerly winds with strong wind speeds (5-10 m/s) occurring for ~5% of the period. Springs
located approximately 20 km east-southeast of OR Tambo reflects a different airflow pattern
with dominant easterly winds and fairly low wind speeds supported by frequent calm
conditions. Jabavu is situated in the northern outskirts of the study area reflecting weak
winds on average with a slight dominance of northeasterly winds. The number of calm
conditions is very high at 53%. Orange Farm on the other hand is located ~25 km directly
south of Jabavu and generally has strong winds primarily from the northwest to westsouthwest directions. The Vereeniging station has a slight resemblance of the OR Tambo
airflow with prevailing northwesterly and northerly winds. Wind speeds recorded at
Vereeniging have a higher frequency of lower wind speeds (1-3 m/s) with high incidences of
calm conditions (24%). Grootvlei located on the eastern side of the study area and
ArcelorMittal Steel station located almost on the same latitude but ~75 km to the west reflects
similar wind fields. Both stations have almost no airflow from the north with the prevailing
wind fields from the northeast. Frequent winds are also detected from the west-southwest
and easterly sector. The main difference between these two stations is the highest
percentage calms (35%) that occur at the Grootvlei station in comparison to the ArcelorMittal
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-17
Steel station (9%). Makalu (for the period 2004) reflects frequent high wind speeds (between
5 m/s and 10 m/s) mainly from the east and north-northwest. The five Sasol stations are all
located in close proximity to each other within a radius of ~8 km. Steam Station, Leitrim and
Boiketlong reflect similar flow patterns (northwesterly and easterly) with moderate wind
speeds. AJ Jacobs, located within Sasolburg, has a different dominant wind direction from
the northeasterly flow at the Hospital station reflecting very low and infrequent winds (see
Figure 4-9).
Diurnal airflow for the area, as presented in Figure 4-10, reflects similar patterns than for
period averages. In general all the stations with prevailing northwesterly airflow indicate an
increase in winds from this sector during the day. At ArcelorMittal Steel and Grootvlei an
increase in airflow from the southwest is also noted. AJ Jacobs (Sasol station) also indicates
an increase in northwesterly winds during the day. The general daytime airflow shows lower
incidences of calm conditions.
Night-time conditions are characterised by lower wind speeds and higher incidences of calm
conditions. These are clearly reflected in the various wind roses provided in Figure 4-11.
Only Springs and AJ Jacobs have lower incidences of calm conditions than during the
daytime conditions. The wind speeds, however, have decreased significantly at both stations
for night-time conditions. In general, airflow from the southwest decreases during the night
with a slight increase in winds from the easterly to northeasterly sectors observed.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-18
Figure 4-9:
Period average wind roses for various monitoring stations operated by industry, various spheres of government and SAWS within the study area for the
period 2004 to 2006 (with the exception of the Makalu monitoring station that has been assessed for the period 2004 (due to it being decommissioned) and the five Sasol
monitoring stations that were only assessed for October to December 2006 as this was the only data available for the study).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-19
Figure 4-10:
Day-time average wind roses for various monitoring stations operated by industry, various spheres of government and SAWS within the study area for the
period 2004 to 2006 (with the exception of the Makalu monitoring station that has been assessed for the period 2004 (due to it being decommissioned) and the five Sasol
monitoring stations that were only assessed for October to December 2006 as this was the only data available for the study).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-20
Figure 4-11:
Night-time average wind roses for various monitoring stations operated by industry, various spheres of government and SAWS within the study area for the
period 2004 to 2006 (with the exception of the Makalu monitoring station that has been assessed for the period 2004 (due to it being decommissioned) and the five Sasol
monitoring stations that were only assessed for October to December 2006 as this was the only data available for the study).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-21
4.5.2
Temperature Trends
Air temperature is an important parameter for the development of the mixing and inversion
layers. It also determines the effect of plume buoyancy as the larger the temperature
difference between ambient air and the plume, the higher the plume will rise. This in turn will
affect the rate of dissipation of pollutants before it reaches ground level.
Long-term monthly temperatures for the SAWS monitoring stations in the study area are
given in Table 4-2. The maximum temperatures occur during December, January and
February with the minimum temperatures occurring during June and July. The mean
monthly temperatures range between 10.3°C – 20.0°C for Johannesburg and 9.1°C – 21.9°C
for Vereeniging.
Station
Table 4-2:
Long-term minimum, maximum and mean temperatures measured at SAWS
stations over the study area (as obtained from the SAWS: WB42 – Climate Statistics).
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
JHB
25.5
25.1
24.1
21.6
19.2
16.7
16.9
19.5
22.9
23.9
24.3
25.1
Ver
Maximum
27.9
27.4
26.3
23.2
20.7
17.7
18.5
21.4
24.9
26.0
26.6
27.7
JHB
20.0
19.6
18.7
15.9
13.1
10.3
10.3
12.7
16.1
17.5
18.4
19.5
Ver
Mean
21.9
21.3
19.9
16.4
12.6
9.1
9.3
12.4
16.7
18.9
20.2
21.3
JHB
14.6
14.2
13.2
10.1
7.0
3.9
3.7
5.8
9.2
11.1
12.5
13.8
Ver
Minimum
15.9
15.2
13.6
9.6
4.4
0.4
0.2
3.4
8.6
11.8
13.8
15.0
Notes:
JHB (Johannesburg) had a monitoring period from 1975 to 2004 at OR Tambo airport
Ver (Vereeniging) had a monitoring period from 1961 to 1990
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-22
The mean monthly temperatures measured during 2006 (Table 4-3) provide similar ranges of
9.9°C – 20.5°C for Johannesburg (OR Tambo) and 9.0°C – 21.9°C for Vereeniging. At
Johannesburg, maximum temperatures are below 25°C with minimums reaching below 5°C
during June. Vereeniging measures maximum temperatures in exceedance of 25°C during
summer (January – February and October to December) and minimum temperatures of
below 5°C in winter (May to July). Springs, unfortunately does not have a long-term
temperature record for comparison but measured mean monthly temperatures range
between 8.4°C – 20.8°C during the period of 2006. Makalu was decommissioned in
December 2004. Therefore the measured temperature for Makalu during the period 2004
was assessed for comparison. The mean temperature ranges for the period were 8.8°C –
22.7°C. A minimum temperature of 2.8°C was measured at Leitrim and Steam Station and
1.4°C was measured at Grootvlei during June 2006. The maximum recorded temperature of
29.7°C (Leitrim), 28.2°C (Steam Station), and 28.9°C (Grootvlei) occurred during December
with a mean temperature range of 10.7°C - 23.0°C (Leitrim), 10.4°C – 22.5°C (Steam
Station) and 8.2°C – 20.4°C (Grootvlei). The mean temperature ranges for Jabavu and
Orange Farm was 10.3°C – 21.9°C and 11.5°C – 21.9°C respectively. The mean
temperature range for ArcelorMittal Steel monitoring station was 9.8°C – 21.3°C.
Station
Table 4-3:
Minimum, maximum and mean temperatures measured at various monitoring
stations operated by industry, various spheres of government and SAWS within the study
area for the period 2006.
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
JHB
22.8
23.3
20.9
20.1
16.7
16.6
18.4
16.8
21.9
24.6
23.2
25.1
Ver
25.6
25.2
23.1
22.0
18.1
18.5
20.7
18.5
24.3
26.9
25.4
27.3
Spr
23.7
23.6
20.9
21.2
17.7
17.6
19.5
18.0
23.1
26.1
23.9
25.8
Jab
21.9
25.2
23.5
20.5
17.9
17.7
19.9
18.5
24.2
26.8
25.5
27.9
OF
26.3
25.4
24.4
23.5
20.0
19.9
20.1
19.1
25.0
27.4
25.8
28.0
Lei
Maximum
26.1
27.1
23.3
24.1
20.2
20.4
22.3
20.1
26.2
28.5
27.2
29.7
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-23
Station
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
SS
25.4
25.8
22.9
22.0
17.9
18.9
20.2
18.9
24.9
27.5
26.1
28.2
Mitt
23.6
24.4
21.5
20.7
17.4
17.9
19.9
17.2
23.0
26.2
24.7
26.8
GV
24.8
24.6
22.3
21.0
17.5
17.0
18.5
20.3
24.6
26.0
26.7
28.9
MA
31.1
29.4
27.5
27.8
29.0
23.2
22.2
26.4
27.8
29.9
33.2
30.2
JHB
19.3
19.1
16.7
15.4
11.1
9.9
12.3
11.0
15.6
19.3
18.6
20.5
Ver
21.2
20.7
17.8
15.5
10.0
9.0
11.4
11.3
16.3
20.3
19.8
21.9
Spr
19.9
19.5
15.7
14.3
9.4
8.4
10.1
10.4
15.2
19.4
18.4
20.8
Jab
21.9
20.5
18.3
14.6
11.3
10.3
12.5
11.9
17.0
20.2
19.9
21.6
OF
21.0
20.3
18.0
16.6
12.4
11.5
12.5
12.4
17.6
20.5
19.8
21.9
Lei
21.4
21.7
17.4
16.9
11.5
10.7
12.6
12.1
17.2
20.9
20.9
23.0
SS
20.8
20.6
17.9
16.1
10.8
10.4
12.0
11.4
17.2
21.1
20.6
22.5
Mitt
19.9
20.0
17.2
15.8
10.4
9.8
12.6
11.0
16.2
19.7
19.3
21.3
GV
20.4
19.9
16.8
14.9
9.6
8.2
10.0
11.7
16.6
19.2
20.0
18.1
MA
Mean
22.3
21.0
19.1
16.9
13.6
9.4
8.8
14.2
15.7
19.7
22.7
21.7
7.2
6.1
9.4
14.2
14.1
16.4
JHB
Minimum
16.2
15.9
13.3
11.1
6.1
4.3
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-24
Station
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Ver
17.3
16.5
13.7
9.6
3.1
0.8
3.4
5.0
8.2
13.8
14.3
17.0
Spr
16.6
15.9
11.3
8.3
2.4
0.9
1.8
3.8
6.7
13.3
13.2
16.2
Jab
21.9
16.7
14.2
8.8
4.8
3.8
6.1
5.8
9.8
14.6
14.5
15.9
OF
16.5
16.2
13.4
11.4
5.9
5.0
6.1
7.1
10.1
14.3
14.2
16.3
Lei
17.0
17.2
13.1
11.0
4.7
2.8
4.6
5.7
8.2
13.8
14.8
17.3
SS
17.0
16.4
14.0
10.7
4.1
2.8
4.6
4.8
9.2
14.8
15.2
17.9
Mitt
16.2
16.1
13.7
11.1
3.6
2.4
5.5
5.3
8.6
13.5
13.9
17.1
GV
16.4
16.0
12.7
9.8
3.3
1.4
3.0
5.0
9.7
13.1
14.3
15.9
MA
15.2
14.0
12.8
8.4
2.0
-1.3
-1.3
3.6
5.3
10.4
13.1
14.3
Notes:
JHB:
Ver:
Spr:
Jab:
OF:
Lei:
SS:
Mitt:
GV:
MA:
Johannesburg
Vereeniging
Springs
Jabavu
Orange Farm
Leitrim
Steam Station
MittalSteel
Grootvlei
Makalu
Diurnal and seasonal temperature profiles are clearly evident over the study area for the
period 2006 (Figure 4-12 and Figure 4-13 respectively). As the earth cools during night-time,
the air in direct contact with the earth’s surface is forced to cool accordingly. The coldest
temperatures occur between 06:00 and 08:00, which is just after sunrise. As the sun rises,
the incoming solar radiation warms the surface of the earth, which in turn will heat up the
layer of air directly above to reach a maximum at approximately 15:00 in the afternoon.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-25
Mean Diurnal Temperature Profile for the Monitoring Stations for the Period
2006
30
25
Temperature (°C)
20
15
10
5
Leitrum
Steam Station
OR Tambo
Vereeniging
Springs
Mittal Steel
Makalu (2004)
Grootvlei
Jabavu
Orange Farm
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Hour
Figure 4-12: Mean diurnal temperature variations measured at various monitoring stations
operated by industry, various spheres of government and SAWS within the study area for the
period 2006.
Average Monthly Temperatures for the Monitoring Stations for the Period
2006
25
Temperature (°C)
20
15
10
5
Leitrum
Steam Station
OR Tambo
Vereeniging
Springs
Mittal Steel
Makalu (2004)
Grootvlei
Jabavu
Orange Farm
0
1
2
3
4
5
6
7
8
9
10
11
12
Month
Figure 4-13: Average monthly temperatures measured at various monitoring stations
operated by industry, various spheres of government and SAWS within the study area for the
period 2006.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-26
4.5.3
Precipitation
Precipitation can have a beneficial effect by washing pollutant particles from the air and
helping to minimize particulate matter formed by activities such as construction and some
industrial processes. Precipitation, however, can also act on pollutants in the air to create
more dangerous secondary pollutants, such as the substances responsible for acid rain. The
rainfall monitoring stations over the study area that were obtained for assessment consist of
3 SAWS stations.
Mean monthly rainfall for the monitoring stations are summarised in Table 4-4. The longterm rainfall records varied were provided for a length of 30 years (as obtained from the
South African Weather Services: WB42 – Climate Statistics).
It can be observed from the long-term record from Johannesburg and Vereeniging that
November to February is the main rainy season, with mean monthly rainfall ranging between
3 mm and 134 mm. The long-term rainfall showed highest rainfall occurring in January for
both stations. The annual average long-term rainfall ranges from 671 mm at Vereeniging to
751 mm at Johannesburg. The dry season extends from about June to August.
During 2004, Vereeniging (Figure 4-15) measured below (27%) long-term average rainfall
(27%). For the period 2005, all stations had below average rainfall from 12% at Vereeniging
to 27% at Johannesburg (Figure 4-14). The period 2006 was an exceptionally wet year, with
all stations measuring above long-term average rainfall (Johannesburg (50%) and
Vereeniging (105%)).
At Springs the annual precipitation was measured at 364 mm and 425 mm for the period
2005 and 2006 respectively (Figure 4-16).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-27
Table 4-4:
Monthly rainfall figures (mm) for the meteorological monitoring stations within
the study area.
Month
Springs
Johannesburg
Vereeniging
Long-term monthly rainfall figures (mm) (SAWS: WB42)
(1)(2)
January
-
134
125
February
-
114
74
March
-
100
68
April
-
36
56
May
-
18
14
June
-
8
8
July
-
3
5
August
-
8
10
September
-
28
25
October
-
79
72
November
-
104
95
December
-
118
119
Annual
-
751
Monthly rainfall figures (mm) for the period 2004 (3)
671
January
-
171.0
123.4
February
-
206.6
85.0
March
-
114.8
24.8
April
-
48.8
26.8
May
-
0.0
0.0
June
-
0.6
3.0
July
-
16.2
12.6
August
-
0.2
23.8
September
-
0.0
0.0
October
-
14.6
28.2
November
-
49.4
27.6
December
-
203.6
126.4
Annual
-
825.8
481.6
(3)
Monthly rainfall figures (mm) for the period 2005
January
85.0
154.8
173.2
February
39.0
73.2
40.8
March
49.0
102.0
121.6
April
50.0
88.6
73.4
May
3.0
1.6
5.3
June
0.0
0.0
0.0
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-28
Month
Springs
Johannesburg
Vereeniging
July
0.0
0.0
0.0
August
4.0
0.0
0.2
September
4.0
0.0
0.2
October
12.0
0.0
12.6
November
75.0
100.0
93.8
December
43.0
72.6
58.6
Annual
364.0
592.8
579.7
Monthly rainfall figures (mm) for the period 2006(3)
January
58.0
353.2
306.0
February
73.0
301.2
206.0
March
68.0
149.2
179.6
April
16.0
68.4
66.6
May
7.0
4.0
21.2
June
0.0
0.0
0.0
July
0.0
0.0
0.0
August
26.0
62.8
44.4
September
3.0
1.6
7.6
October
31.0
42.2
56.4
November
73.0
110.8
247.6
December
70.0
127.2
215.2
Annual
425.0
1220.6
1350.6
Notes:
1. JHB (Johannesburg) had a monitoring period from 1975 to 2004 at OR Tambo airport
2. Ver (Vereeniging) had a monitoring period from 1961 to 1990
3. The monitoring station at Johannesburg is at the OR Tambo airport
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-29
Monthly Precipitation (mm) for OR Tambo for the Period 2004 - 2006
400
2004
2005
2006
350
Precipitation (mm)
300
250
200
150
100
50
Figure 4-14: Monthly measured rainfall for the SAWS
Johannesburg (OR Tambo) for the period 2004 – 2006.
D
ec
em
be
r
N
ov
em
be
r
ct
ob
er
O
Se
pt
em
be
r
Au
gu
st
Ju
ly
Ju
ne
M
ay
Ap
ril
ar
ch
M
Fe
br
ua
ry
Ja
nu
ar
y
0
meteorological
station
of
Monthly Precipitation (mm) for Vereeniging for the Period 2004 - 2006
350
2004
2005
2006
300
Precipitation (mm)
250
200
150
100
50
D
ec
em
be
r
N
ov
em
be
r
ct
ob
er
O
Se
pt
em
be
r
Au
gu
st
Ju
ly
Ju
ne
M
ay
Ap
ril
ar
ch
M
Fe
br
ua
ry
Ja
nu
ar
y
0
Figure 4-15: Monthly measured rainfall for the SAWS meteorological station of Vereeniging
for the period 2004 – 2006.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-30
Monthly Precipitation (mm) for Springs for the Period 2005 - 2006
90
2005
2006
80
Precipitation (mm)
70
60
50
40
30
20
10
De
ce
m
be
r
N
ov
em
be
r
ct
ob
er
O
Se
pt
em
be
r
Au
gu
st
Ju
ly
Ju
ne
M
ay
Ap
ril
ar
ch
M
Fe
br
ua
ry
Ja
nu
ar
y
0
Figure 4-16: Monthly measured rainfall for the SAWS meteorological station of Springs for
the period 2005 – 2006.
4.5.4
Relative Humidity
Relative humidity is an inverse function of ambient air temperature. As the ambient air
temperature increases, so the relative humidity in the atmosphere will decrease. This is
clearly observed in the diurnal trend in Figure 4-17.
Relative humidity will increase during the night to reach a maximum just after sunrise (07:00).
This coincides with coldest observed ambient air temperatures (Figure 4-12). As the air
temperature begins to increase, the relative humidity decreases to reach a minimum during
the warmest part of the day (14:00 to 15:00). The maximum measured relative humidity for
the period 2004 to 2006 ranged from 96% - 100% with the minimum ranging from 0% - 12%.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-31
Mean Diurnal Variation of Relative Humidity (%)
100
90
80
Relative Humidity (%)
70
60
50
40
30
20
10
Springs
Jabavu
Orange Farm
OR Tambo
Vereeniging
Steam Station
Leitrum
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Hour of Day
Figure 4-17: Mean diurnal variation of relative humidity measured at various monitoring
stations operated by industry, various spheres of government and SAWS within the study
area for the period 2004 -2006.
Mean monthly relative humidity values for the monitoring stations over the study area are
summarised in Figure 4-18. As with temperature, the mean monthly relative humidity values
decrease during the dryer winter months (May to September) and increase during the wetter
summer months (January to April and October to December). The mean monthly relative
humidity range is 24% - 61% (Jabavu), 28% - 63% (Orange Farm), 31% - 72% (Leitrim), 35%
- 80% (Vereeniging), 38% - 73% (OR Tambo) and 45% - 91% (Springs).
The relative humidity for Steam Station seams to be suspicious as it does not follow the
general diurnal and monthly trends. The trend may be due to the influence of the closely
located Sasol Power Station, in which case the relative humidity would not be reflective of
ambient conditions.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-32
Mean Monthly Variation of Relative Humidity (%)
100
90
80
Relative Humidity (%)
70
60
50
40
30
20
10
Springs
Jabavu
Orange Farm
OR Tambo
Vereeniging
Steam Station
Leitrum
0
1
2
3
4
5
6
7
8
9
10
11
12
Month
Figure 4-18: Mean monthly variation of relative humidity measured at various monitoring
stations operated by industry, various spheres of government and SAWS within the study
area for the period 2004 -2006.
4.5.5
Incoming Solar Radiation (Insolation)
Solar radiation was measured at the Sasol monitoring station (Steam Station). Incoming
solar radiation determines the rate of development and dissipation of the mixing layer. It
increases from sunrise (06:00) to reach a maximum at midday (12:00 – 13:00) and then
decreases till sunset (19:00) (Figure 4-19). The maximum solar radiation measured at
Steam Station was 1251 W/m² (13:00).
Monthly solar radiation reaches a maximum during January (280 W/m²) and a minimum
during June (185 W/m²) (Figure 4-20).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-33
Mean Diurnal Variation of Solar Radiation (W/m²) for Steam Station
800
700
Solar Radiation (W/m²)
600
500
400
300
200
100
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Hour of Day
Figure 4-19: Mean diurnal variation of solar radiation measured at the Sasol monitoring
station (Steam Station) for the period 2004 -2006.
Mean Monthly Variation of Solar Radiation (W/m²) for Steam
Station
300
Solar Radiation (W/m²)
250
200
150
100
50
0
1
2
3
4
5
6
7
8
9
10
11
12
Month
Figure 4-20: Mean monthly variation of solar radiation measured at the Sasol monitoring
station (Steam Station) for the period 2004 -2006.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-34
4.5.6
Surface Pressure Levels
Surface pressure was measured at the SAWS stations for the period 2004 – 2006 (Figure 421). The average pressure for the various stations was 845 hPa (Springs), 855 hPa
(Vereeniging) and 834 hPa (OR Tambo). The highest surface pressure is observed at
Vereeniging due to its lower altitude, with the lowest surface pressure observed at OR
Tambo.
Pressure Levels at SAWS Stations Over the Study Area for the Period 2004 to 2006
880
Max
Min
Ave
870
860
Pressure (hPa)
850
840
830
820
810
800
790
Vereeniging
OR Tambo
Springs
Figure 4-21: Measured surface pressure levels from SAWS monitoring stations over the
study area for the period 2004 - 2006.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
4-35
5
CHAPTER 5
MEASURED AMBIENT AIR QUALITY WITHIN THE STUDY AREA
In the analysis of ambient air quality monitoring data, use was made of all data to which a
reasonable level of accuracy could be attached for the period 2004 - 2006. Data were
obtained from industry- and government-run monitoring stations. A list of the sampling
stations and pollutants measured is given in Table 5-1. The locations of the various
monitoring stations are illustrated in Figure 5-1.
Figure 5-1: Location of Ambient Air Quality Monitoring Stations (including stations owned
by City of Johannesburg (COJ), Sedibeng District Municipality (SDM), Department of
Environmental Affairs and Tourism (DEAT) and Industry).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
5-1
Table 5-1:
Monitoring
Agency
Evaluation of monitoring stations operated by industry and various spheres of Government (after Liebenberg-Enslin et al., 2007).
Longitude
(°E)
Latitude
(°S)
Status
Monitoring
Period
Pollutants
Measured
Averaging
Period
Jabavu
27.872
-26.253
Active
2004 Present
PM10, SO2
10 min
intervals
Orange Farm
27.867
-26.480
Active
2004 Present
PM10, SO2
10 min
intervals
1984 - 2004
NO, NO2, O3,
PM10, SO2
Hourly
3 months
Station Name
COJ
Eskom
ArcelorMittal
Steel
(MSVS)
Calibration
Undertaken
Frequency
by
Climatology
Quarterly
Research
Group
Climatology
Quarterly
Research
Group
Type of
Equipment
SANAS
Accredited Yes/No
Thermo
No
Thermo
No
Eskom
Thermo,
Dasibi and
Monitor
Labs
Yes
Makalu
27.903
-26.835
Decommissioned
Station 620
27.822
-26.673
Active
2005 Present
CO, NO2, O3,
PM10, H2S, SO2
10
minutes
3 months
C&M
Engineers
API, Opsis
Open Path
No
Station 350
27.834
-26.655
Active
2005 Present
CO, NO2, O3,
PM10, H2S, SO2
10
minutes
3 months
C&M
Engineers
API, Opsis
Open Path
No
Caravan
(mobile)
27.788
-26.645
Active
2006 Present
CO, NO2, O3,
PM10, H2S, SO2
10
minutes
3 months
C&M
Engineers
API
No
10 min
intervals
2
x
per
months,
external
SANAS
calibration
done
annually
API,
Opsis,
Opsis
Open
Path, API
Yes
Sasol (1)
AJ Jacobs
27.826
-26.823
Active
2003 Present
SO2, H2S, NO,
NO2, NOX
Sasol
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
5-2
Calibration
Undertaken
Frequency
by
2
x
per
months,
external
2003 10 min
Sasol
SANAS
H2S, SO2
Boiketlong
27.846
-26.836
Active
Present
intervals
calibration
done
annually
2
x
per
months,
external
2003 10 min
Sasol
SANAS
H2S, SO2
Hospital
27.826
-26.803
Active
Present
intervals
calibration
done
annually
2
x
per
months,
NOx, O3, PM10,
external
H2S, SO2, NH3,
10 min
2003 Sasol
SANAS
Steam Station
27.853
-26.820
Active
intervals
Present
CH4, Noncalibration
Methane
done
annually
2
x
per
months,
external
2003 BTEX, CO, NO2,
10 min
Sasol
SANAS
Leitrim
27.871
-26.850
Active
Present
O3, PM10, SO2
intervals
calibration
done
annually
COJ - City of Johannesburg, DEAT - Department of Environmental Affairs and Tourism, SDM – Sedibeng District Municipality
(1) Sasol monitoring stations were accredited in 2004
Monitoring
Agency
Notes:
Station Name
Longitude
(°E)
Latitude
(°S)
Status
Monitoring
Period
Pollutants
Measured
Averaging
Period
Type of
Equipment
SANAS
Accredited Yes/No
API,
Opsis,
Opsis
Open
Path, API
Yes
API,
Opsis,
Opsis
Open
Path, API
Yes
API,
Opsis,
Opsis
Open
Path, API
Yes
API,
Opsis,
Opsis
Open
Path, API
Yes
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
5-3
Sasol operate five monitoring stations, viz. AJ Jacobs, Sasolburg Hospital, Boiketlong,
Leitrim and Steam Station (Figure 5-2). Hospital and AJ Jacobs monitoring stations are
located within Sasolburg, Boiketlong and Leitrim to the north and east of Zamdela residential
area respectively and Steam Station, within the Sasolburg Chemical Industrial Complex.
Figure 5-2: Location of the Sasol ambient monitoring stations within the study area (after
Liebenberg-Enslin et al, 2007).
ArcelorMittal Steel Vanderbijlpark Steel (MSVS) operate two ambient monitoring stations, viz.
Station 350 and Station 620, on the plant boundary, and a mobile station, viz. Caravan
(Figure 5-3).
The department of Environmental Affairs and Tourism has recently (February – March 2007)
established and commissioned six ambient monitoring stations in and around the Vaal
Triangle.
These stationed are located in Diepkloof (Soweto), Kliprivier, Sebokeng,
Sharpville, Three Rivers and Zamdela. However, due to the limited data available, this
information was not assessed in the current study.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
5-4
Figure 5-3: Location of the ArcelorMittal Steel Vanderbijlpark Steel ambient monitoring
stations (after Liebenberg-Enslin et al, 2007).
As the criteria pollutants of sulphur dioxide, nitrogen dioxide, and inhalable particulate matter
were quantified for the current assessment, only ambient monitored data for these pollutants
has been discussed in the following sections.
5.1
Data Availability
The data availability of the monitoring stations for the period 2004 – 2006 is given in Table 52. It should be noted that a minimum data availability of 80% is required to achieve data
quality assurance.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
5-5
Table 5-2:
Data availability for monitoring stations in the Vaal Airshed operated by
industry and various spheres of Government (after, Liebenberg-Enslin et al, 2007) (1).
Monitoring
Agency
City of
Johannesburg
ArcelorMittal
Steel
Vanderbijlpark
Steel
Sasol
Eskom
City of
Johannesburg
ArcelorMittal
Steel
Vanderbijlpark
Steel
Sasol
Eskom
City of
Johannesburg
ArcelorMittal
Steel
Vanderbijlpark
Steel
Sasol
Eskom
Data Availability (%)
2004
2005
Inhalable Particulate Matter
Jabavu
89
60
Orange Farm
79
70
Station620
67
Station 350
75
Caravan
Station
AJ Jacobs
Boiketlong
Hospital
Leitrim
Makalu
Jabavu
Orange Farm
Station620
Station 350
Caravan
AJ Jacobs
Boiketlong
Hospital
Leitrim
Makalu
Jabavu
Orange Farm
Station620
Station 350
Caravan
2006
73
79
24
24
70
99
80
Sulphur Dioxide
85
88
-
93
-
99
-
62
83
77
96
73
83
86
70
-
-
69
100
99
100
91
99
Nitrogen Dioxide
-
100
100
100
93
-
99
99
99
99
-
77
96
86
74
-
-
75
91
98
100
93
-
99
99
-
AJ Jacobs
Boiketlong
Hospital
Leitrim
Makalu
(1) Data with less than 80% availability is given in bold.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
5-6
5.2
Ambient Particulate Concentrations
Elevated levels of airborne particulates are known to occur over the Vaal Triangle. This
subsection aims to provide an overview of the extent of such concentrations and to reflect on
diurnal trends which are able to assist in determining the nature of sources contributing to
such concentrations.
The monitored particulate matter for the period 2004 – 2006 is given in Table 5-3, with the
frequency of exceedance of the SANS daily limit (proposed SA standard) given in Table 5-4.
Monitored data , shows elevated inhalable particulate concentrations over the Vaal Airshed
with daily and annual (with the exception of Makalu) ground level concentrations exceeding
the SANS limits (proposed SA standards)at all monitoring stations.
Table 5-3:
Monitored inhalable particulate matter at ambient stations operated by
industry and various spheres of government within the Vaal Airshed (after Liebenberg-Enslin
et al, 2007) (1).
Monitoring
Agency
City of
Johannesburg
ArcelorMittal
Steel
Vanderbijlpark
Steel
Sasol
Eskom
City of
Johannesburg
ArcelorMittal
Steel
Vanderbijlpark
Steel
Sasol
Eskom
Station
Jabavu
Orange Farm
Station620
Station 350
Caravan
AJ Jacobs
Boiketlong
Hospital
Leitrim
Makalu
Jabavu
Orange Farm
Station620
Station 350
Caravan
AJ Jacobs
Boiketlong
Hospital
Leitrim
Makalu
Jabavu
Monitored PM10 Concentrations (µg/m³)
2004
2005
2006
(2)
Highest Hourly
785
820
932
996
993
933
347
217
376
217
-
-
594
999
647
Highest Daily (3)
291
228
-
942
-
947
-
232
252
210
221
215
233
125
173
-
-
212
275
145
Annual Average (4)
-
314
-
294
-
88
66
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
5-7
Monitoring
Agency
City of
Johannesburg (5)
ArcelorMittal
Steel
Vanderbijlpark
Steel
Sasol
Eskom
Station
Jabavu
Orange Farm
Station620
Station 350
Caravan
AJ Jacobs
Boiketlong
Hospital
Leitrim
Makalu
Monitored PM10 Concentrations (µg/m³)
2004
2005
2006
88
66
78
66
103
54
91
52
-
-
96
53
34
105
-
41
-
Notes:
(1) Exceedances of the SANS limits (proposed SA standards) is given in bold.
(2) No inhalable particulate limits/ standards are available for an hourly averaging period.
(3) The SANS daily limit for inhalable particulates is 75 µg/m³.
(4) The SANS annual limit for inhalable particulates is 40 µg/m³.
(5) Annual average not calculated for 2004 for Jabavu and Orange Farm as monitoring commenced in the second
half of 2004.
Table 5-4:
Measured frequency of daily inhalable particulate exceedance of the SANS
limit of 75 µg/m³ (proposed SA standard) at various monitoring stations operated by industry
and various spheres of government within the study area (after Liebenberg-Enslin et al,
2007).
Monitoring
Agency
City of
Johannesburg (1)
ArcelorMittal
Steel
Vanderbijlpark
Steel
Sasol
Eskom
Station
Jabavu
Orange Farm
Station620
Station 350
Caravan
AJ Jacobs
Boiketlong
Hospital
Leitrim
Makalu
Frequency of exceedance (days)
2004
2005
2006
90
184
154
154
182
196
188
24
168
56
-
-
180
84
24
162
-
50
-
(1) Frequency of exceedance for Jabavu and Orange Farm were based on the City of Johannesburg guideline of
50 µg/m³.
Figure 5-4 provides the diurnal profile of the monitored inhalable particulate concentrations
over the Vaal Airshed. Areas of domestic fuel burning activities (i.e. Jabavu and Orange
Farm) have a distinct diurnal profile with increases in concentrations in the early morning
(06:00 – 10:00) and evening (17:00 – 21:00). Peak pollutant concentrations from industry
monitoring stations are noted to occur between 10:00 and 16:00. This diurnal trend is
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
5-8
generally indicative of ground level concentrations occurring due to elevated stack, with the
plume typically being “brought to ground” during periods of atmospheric instability. Such
vertical turbulence due to convective mixing occurs during the daytime.
Figure 5-4: Diurnal profile of monitored inhalable particulate ground level concentrations
at various monitoring stations operated by industry and government within the study area
(after Liebenberg-Enslin et al, 2007).
Key findings in terms of ambient particulate concentrations (based on ambient monitored
data within the Vaal Airshed for the period 2004 – 2006) are as follows:
•
Exceedances of current inhalable particulate SA standards and significant
exceedances of the proposed inhalable particulate SA standards (SANS limits)
have been measured to occur over the Vaal Airshed.
•
In/ adjacent to domestic fuel burning areas (viz. Jabavu, Orange Farm and Leitrim)
average annual inhalable particulate concentrations were found to range from 66 to
105 µg/m³ with maximum daily inhalable particulate concentrations in the order of
215 to 314 µg/m³.
•
Maximum daily inhalable particulate levels were observed to be in the range of 125
to 221 µg/m³ in industrial areas (viz. Station 620, Station 350, Caravan and
Makalu), with annual average concentrations of 34 to 103 µg/m³.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
5-9
The main conclusions to be drawn are that ambient inhalable particulate concentrations
continue to be elevated across the Vaal Triangle region. Such concentrations represent a
significant health risk.
5.3
Ambient Sulphur Dioxide Concentrations
The highest monitored sulphur dioxide ground level concentrations over the Vaal Airshed is
given in Table 5-5 with the frequency of exceedance of SA standards (and SANS limits)
given in Table 5-6. Short-term (hourly) sulphur dioxide concentrations at all monitoring
stations (with the exception of Caravan) exceeded the SA standards for the period 2004 –
2006. At the domestic fuel burning areas of Jabavu and Orange Farm, the highest daily
monitored concentrations exceeded the SA standards for the period 2005 – 2006 and 2006
respectively. Despite apparent reductions in sulphur dioxide levels in the Sasolburg
industrial area, exceedances of SA standard for daily average concentrations continue to
occur at the Sasol monitoring stations of AJ Jacobs and Boiketlong (for the period 2004 –
2006).
Table 5-5:
Monitored sulphur dioxide concentrations at ambient stations operated by
industry and government within the Vaal Airshed (after Liebenberg-Enslin et al, 2007) (1).
Monitoring
Agency
City of
Johannesburg
ArcelorMittal
Steel
Vanderbijlpark
Steel
Sasol
Eskom
City of
Johannesburg
ArcelorMittal
Steel
Vanderbijlpark
Steel
Sasol
Station
Jabavu
Orange Farm
Station620
Station 350
Caravan
AJ Jacobs
Boiketlong
Hospital
Leitrim
Makalu
Jabavu
Orange Farm
Station620
Station 350
Caravan
AJ Jacobs
Boiketlong
Hospital
Monitored Sulphur Dioxide Concentrations (µg/m³)
2004
2005
2006
(2)
Highest Hourly
401
1350
2032
530
1069
2109
512
754
698
793
-
-
190
752
1865
737
566
624
Highest Daily (3)
74
107
-
754
773
665
523
-
788
1310
557
666
-
185
76
114
110
149
140
109
116
-
-
53
271
155
145
205
183
164
197
190
119
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
5-10
Monitoring
Agency
Station
Leitrim
Makalu
Eskom
City of
Johannesburg (5)
ArcelorMittal
Steel
Vanderbijlpark
Steel
Sasol
Eskom
Jabavu
Orange Farm
Station620
Station 350
Caravan
AJ Jacobs
Boiketlong
Hospital
Leitrim
Makalu
Monitored Sulphur Dioxide Concentrations (µg/m³)
2004
2005
2006
106
108
113
124
Annual Average (4)
27
27
13
15
38
31
28
23
-
-
11
39
37
36
26
21
35
41
33
29
-
37
43
27
32
-
Notes:
(1) Exceedances of the SANS limits (also current SA standards) is given in bold.
(2) The SANS hourly limit for sulphur dioxide is 350 µg/m³.
(3) The SANS daily limit for sulphur dioxide is 125 µg/m³.
(4) The SANS annual limit for sulphur dioxide is 50 µg/m³.
(5) Annual average not calculated for 2004 for Jabavu and Orange Farm as monitoring commenced in the second
half of 2004.
Table 5-6:
Measured frequency of hourly and daily sulphur dioxide exceedance of the
SANS limit of 350 µg/m³ and 125 µg/m³ respectively (proposed SA standard) at various
monitoring stations operated by industry and government within the Vaal Airshed (after
Liebenberg-Enslin et al, 2007).
Monitoring
Agency
City of
Johannesburg
ArcelorMittal
Steel
Vanderbijlpark
Steel
Sasol
Station
Jabavu
Orange Farm
Station620
Station 350
Caravan
Eskom
AJ Jacobs
Boiketlong
Hospital
Leitrim
Makalu
City of
Johannesburg
ArcelorMittal
Steel
Jabavu
Orange Farm
Station620
Station 350
Frequency of exceedance
2004
2005
Hourly Exceedance
1
2
11
1
5
3
2006
22
25
5
4
-
-
0
53
50
20
5
16
Daily Exceedance
0
0
-
48
83
36
31
-
59
91
18
12
-
1
0
0
0
3
6
0
0
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
5-11
Monitoring
Agency
Vanderbijlpark
Steel
Sasol
Eskom
Station
Caravan
AJ Jacobs
Boiketlong
Hospital
Leitrim
Makalu
2004
Frequency of exceedance
2005
2006
-
-
0
6
3
2
0
0
7
8
3
0
-
9
8
0
0
-
Figure 5-5: Diurnal profile of monitored sulphur dioxide ground level concentrations from
various monitoring stations operated by industry and government within the Vaal Airshed
(after Liebenberg-Enslin et al, 2007).
Distinct diurnal trends in sulphur dioxide concentrations are noted to occur (Figure 5-5).
Concentration peaks observed during the morning at AJ Jacobs, Hospital, Boiketlong, Leitrim
and Makalu are associated with emissions from tall stacks in the region. During the nighttime the plumes from elevated sources emitting above or within the surface inversion layer
are unable to penetrate to ground level. The dissipation of the surface inversion from the
base upwards due to day-time convection and the entrainment and down-mixing of plumes
from elevated plumes results in the peak concentrations noted.
Within domestic fuel burning areas, such as Jabavu, Orange Farm and Leitrim, bi-modal
peaks occur in the diurnal trends. The first peak is observed to occur at 09:00 – 10:00 and
the second at 19:00. The Leitrim site is primarily influenced by low level domestic fuel
burning emissions and industrial emissions in the area.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
5-12
Key findings in terms of ambient sulphur dioxide concentrations are as follows:
5.4
•
Maximum hourly average sulphur dioxide concentrations of between 512 µg/m³ and
2109 µg/m³ have been recorded to occur at the monitoring stations within the Vaal
Airshed.
•
Maximum daily concentrations of between 53 µg/m³ and 271 µg/m³ have been
recorded at the monitoring stations within the Vaal Airshed for the period 2004 –
2006.
•
A general increase in short-term sulphur dioxide ground level concentrations have
been observed from the period 2005 to 2006 at all monitoring station within the
Vaal Airshed.
Ambient Nitrogen Dioxide Concentrations
The highest measured nitrogen dioxide ground level concentrations for the period 2004 –
2006 is given Table 5-7 and the frequency of hourly exceedances of the SANS limit
(proposed SA standard) is given in Table 5-8. Few exceedances of the proposed SA hourly
standard are observed with Leitrim recording 5 (in 2004), Station 620 recording 1 (in 2005
and 2006) and AJ Jacobs recording 1 (in 2006).
Table 5-7:
Monitored nitrogen dioxide concentrations at ambient stations operated by
industry and government within the Vaal Airshed (after Liebenberg-Enslin et al, 2007) (1).
Monitoring
Agency
City of
Johannesburg
ArcelorMittal
Steel
Vanderbijlpark
Steel
Sasol
Station
Jabavu
Orange Farm
Station 620
Station 350
Caravan
Eskom
AJ Jacobs
Boiketlong
Hospital
Leitrim
Makalu
City of
Johannesburg
Jabavu
Orange Farm
Monitored Nitrogen Dioxide Concentrations
(µg/m³)
2004
2005
2006
(2)
Highest Hourly
241
294
158
134
-
-
53
583
100
Highest Daily (3)
-
198
143
-
227
120
-
-
-
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
5-13
Monitoring
Agency
ArcelorMittal
Steel
Vanderbijlpark
Steel
Sasol
Eskom
City of
Johannesburg (5)
ArcelorMittal
Steel
Vanderbijlpark
Steel
Sasol
Eskom
Station
Station 620
Station 350
Caravan
AJ Jacobs
Boiketlong
Hospital
Leitrim
Makalu
Jabavu
Orange Farm
Station620
Station 350
Caravan
AJ Jacobs
Boiketlong
Hospital
Leitrim
Makalu
Monitored Nitrogen Dioxide Concentrations
(µg/m³)
2004
2005
2006
64
71
67
81
-
-
37
122
55
Annual Average (4)
-
79
57
-
87
72
-
31
32
28
33
-
-
6
28
16
28
23
-
28
27
-
Notes:
(1) Exceedances of the SANS limits (proposed SA standards) is given in bold.
(2) The SANS hourly limit for nitrogen dioxide is 200 µg/m³.
(3) No SANS daily limit is available for nitrogen dioxide.
(4) The SANS annual limit for nitrogen dioxide is 40 µg/m³.
(5) Annual average not calculated for 2004 for Jabavu and Orange Farm as monitoring commenced in the second
half of 2004.
Table 5-8:
Measured frequency of hourly nitrogen dioxide exceedance of the SANS limit
of 200 µg/m³ (proposed SA standard) at various monitoring stations operated by government
and industry within the Vaal Airshed (after Liebenberg-Enslin et al, 2007).
Monitoring
Agency
City of
Johannesburg
ArcelorMittal
Steel
Vanderbijlpark
Steel
Sasol
Station
Jabavu
Orange Farm
Station620
Station 350
Caravan
AJ Jacobs
Boiketlong
Hospital
Leitrim
Frequency of hourly exceedance
2004
2005
2006
1
1
0
0
-
-
0
5
0
0
1
0
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
5-14
Monitoring
Agency
Eskom
Station
Makalu
Frequency of hourly exceedance
2004
2005
2006
0
-
Distinct diurnal profile in measured nitrogen dioxide ground level concentrations is observed
with peaks occurring in the morning at 06:00 (at the Station 350, Station 620, AJ Jacobs and
Leitrim monitoring stations) and 09:00 (at the monitoring stations of Makalu and Caravan)
and in the evening 19:00. This diurnal pattern may be due to the diurnal trend of vehicle and
domestic fuel burning activity.
Figure 5-6: Diurnal profile of monitored nitrogen dioxide ground level concentrations from
various monitoring stations operated by industry and government within the Vaal Airshed
(after Liebenberg-Enslin et al, 2007).
Key findings in terms of ambient nitrogen dioxide concentrations are as follows:
•
Maximum hourly average nitrogen dioxide concentrations of between 53 µg/m³ and
583 µg/m³ have been recorded to occur at the monitoring stations within the Vaal
Airshed.
•
Few hourly exceedances of the SANS limit (proposed SA standard) is observed
over the period 2004 – 2006, with less than 2 exceedances observed for the period
2006.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
5-15
6
CHAPTER 6
EMISSIONS INVENTORY FOR THE STUDY AREA
The identification and quantification of existing sources of emissions in the region, together
with the characterisation of ambient pollutant concentrations is fundamental to the
assessment of the potential for cumulative impacts given the existing operations and their
associated emissions. Sources of air pollution within the study area and pollutants
associated with such source types are identified with the aim of understanding which
pollutants may be of importance in terms of cumulative impact potentials.
Sources of emissions are generally placed into categories with the most frequent distinctions
being made between mobile and stationary sources, industrial and non-industrial sources,
point and area sources and regulated and unregulated sources.
An emissions inventory for the study area was established for sources where information
was available (viz, industry) or where emission factors could be utilised to quantify sources.
Sources which contribute to ambient air pollutant concentrations within the study region
include:
• Stack, vent and fugitive emissions from industrial operations;
• Fugitive emissions from mining operations, including mechanically generated dust
emissions and gaseous emissions from blasting and spontaneous combustion of
exposed coal seams;
• Vehicle entrainment of dust from paved and unpaved roads;
• Vehicle tailpipe emissions;
• Domestic fuel burning (particularly use of coal, wood and paraffin);
• Biomass burning (viz., veld fires); and,
• Various other fugitive dust sources, such as agricultural activities and wind erosion
of open areas.
Atmospheric emissions were quantified and simulated for the following sources during the
current study:
• Gaseous and particulate emissions from industrial operations;
• Domestic fuel burning (particularly coal, wood and paraffin used by informal
communities/settlements);
• Fugitive emissions from open cast coal mining operations;
• Wind-blown dust emissions from ash dumps; and
• Vehicle tailpipe emissions.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-1
The extent and spatial location of atmospheric emissions from vehicle entrainment, biomass
burning and spontaneous combustion that may contribute significantly to air pollution
concentrations in certain parts of the study area could not be accurately quantified and were
therefore omitted from the simulations.
Pollutants that were assessed for the baseline study included the criteria pollutants of
nitrogen dioxide, sulphur dioxide and inhalable particulates. These pollutants are stipulated
in the South African Standards, with adequate data available from industries to be quantified.
6.1
Industrial Sources
Significant and potentially significant emitters within the Vaal Triangle are generally grouped
within larger industrial sectors within Vanderbijlpark, Vereeniging, Sasolburg and Meyerton.
The main contributing sources within these sectors include:
Vanderbijlpark - ArcelorMittal Steel Vanderbijlpark Steel, Vitro Building Products and
Davesteel (Cape Gate) are significant sources of particulates.
Other
potentially significant sources include Africa Cables and Dorbyl Heavy
Engineering.
Sasolburg - Significant sources of emissions include: the Sasol Chemical Industries
Complex, Natref, Omnia Fertiliser, Safripol and Sigma Colliery.
Vereeniging - ArcelorMittal Vaal Works, Rand Water Board and the New Vaal Colliery
represents the most significant sources of particulate emissions. Other
sources include Brickveld Stene, Concord Foundry and Lime Distributers.
Meyerton - Based on the emission estimates the largest sources of industrial/mining related
emissions within Meyerton include the industries of Metalloys and EMSA in
addition to various ceramic processes, viz. Ocon Bricks and Vaal Potteries.
The Glen Douglas Dolomite Quarry is the only known quarrying/mining activity
in the area which could not be quantified due to insufficient available data.
The use of coal, coking coal and HFO by industries within the Vaal Triangle is responsible for
a large portion of the total particulate emissions from the industrial / institutional / commercial
fuel use sector. Much of the particulate emissions associated with coking coal are due to the
production of this fuel. Coal represents the main fuel type used by the commercial and
institutional sector although anthracite, diesel and wood are also used to a lesser extent.
The most significant group contributing to fuel burning emissions from the industrial,
commercial, institutional fuel burning sector within the Vaal Triangle include:
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-2
•
Iron and steel industries - associated with 38% of the total particulate emissions
from the industrial / institutional / commercial fuel use sector (includes ArcelorMittal
Steel Vanderbijlpark Steel and ArcelorMittal Vaal Works).
•
Chemical and petrochemical sector - associated with 12% of the total particulate
emissions from this sector (includes Sasol Chemical Industries and NATREF which
are located in Sasolburg).
•
Power generation – associated with 19% of the total particulate emissions from the
industrial / commercial sector (includes Lethabo Power Station).
Other groups include: brick manufacturers which use coal (e.g. Brickveld Stene, Ocon
Bricks) and other industries (use coal and to a lesser extent HFO for steam generation). The
contribution of fuel combustion (primarily coal) by institutions such as schools and hospitals
is relatively small given the extent of emissions from other groups.
Emissions from the industrial sectors were quantified based on emissions data obtained from
industries, data which were already in the public domain and emission estimates from
emission factor application. Appendix B provides a complete list of industries and their
emissions within the Vaal Airshed.
The area of interest extended beyond the Vaal Triangle to incorporate industrial activity
within the Ekurhuleni Metropolitan Municipality so as to take into account cross boundary
cumulative effects. Table 6-1 provides an overview of the information gathered. The spatial
distribution of the industries within the Vaal Airshed is provided in Figure 6-1. The
contribution of sulphur dioxide, inhalable particulate matter and oxides of nitrogen emissions
from industrial sources is illustrated in Figures 6-2, 6-3 and 6-4 respectively.
It should be noted that total suspended particulate emissions from Sasol sources were
provided for the assessment. As a conservative approach, the particulate matter from these
stack sources were assumed to be of the inhalable particulate fraction.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-3
Figure 6-1: Location of the main industrial and mining activities within the Vaal Airshed
that were quantified for the study.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-4
Industrial sources of atmospheric emissions within the Vaal Airshed and their associated emissions.
Industry Name
Returned (Yes)
Table 6-1:
Pollutants
Process Description
NOx
A & I Brake & Clutch
Brake&Clutch Production-Asbestos Process
Ab Brickworks (Pty) Ltd (Closed Down)
Brick Works
Aca
Brake&Clutch Production-Asbestos&Metal Recovery
Acix Div Of Ncp-(Now Isegen Sa)
Plasticisers&Anhydrides
Active Foundries
Aero Dry Cleaners
Afcat (Now Sud-Chemie)
African Brick Lenasia
African Cables
African Detinning
African Pegmatite
African Zinc Mills
Yes (LM)
Yes
Yes (LM)
SO2
PM
Closed Down
Bronze Ignot Casting Into Moulds
Dry Cleaning
Metal Recovery And Phosphorous Process
Only Emits Po4
Clay Bricks Production
Lead Process-Scrap Lead Recovery
Metal Recovery-Tin Scraps
Milling Of Zinc In Ball Mills
Agricultural Research Council
Air Products
Comments
Waste Incineration-Animal Carcasses And Biological Materials
Yes (LM)
Acetylene Production From H2o&Calcium Carbide
Akulu Marchon
Albras Foundry
Produce H2SO3 Used In Soap Production
Melting Non-Ferrous Scrap Metal
Alfred Teves Eng Sa (Pty) Ltd
Brake Calisters
Alvoer (Pty) Ltd
Ambijo Lounges
Cattle Feedlot(Barley) Distribution
Wood Burning/Drying-Incinerator
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-5
American Iron & Brass
Analysis System Consultant (Ansynco
Sa Cc)
Aquaplus
Returned (Yes)
Industry Name
Pollutants
Process Description
Comments
NOx
SO2
PM
Cast Iron Production
Yes
Supply Installation Of On Line Analysers
Yes
No Emissions
No Emissions
Bandag (Pty) Ltd
Besaans-Duplessis (Watt Rd)
Cast Iron Production
Blitz Concrete Works (Westongoud)
Concrete Products
Blue Armor
Bosworth
Brick & Clay (Nigel)
Brickveld Stene
British American Tobacco
Britti Cc
Cargo Carriers
Cas Ice Cream (Pty) Ltd
Central Hotel
Chamber Of Commerce
Brick And Clay Products
Bricks Production
Tobacco Products
Yes
Chubby Chick(Now Fourie's Poultry)
Claasens Tegniek
Clover
Concorde Foundry
Transportation Of Cargo
Ice Cream (Dairy)
Waste Incinerator
Waste Incinerator
Meat Rendering
Yes (LM)
Waste Incinerator
Dairy Products
Steel Products
Consol Glass (Pretoria)
Glass Manufacturing-Use Fluorspar
Consol Ltd (Wadeville)
Glass Manufacturing
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-6
Returned (Yes)
Industry Name
Pollutants
Process Description
NOx
Consolidated Wire Industries
Galvanised Wire Products
Cord Chemicals
Sodium Carbonate And Silica Are Melted To Glass Then
Dissolved To Sodium Silicate.
Coverland
Roofing)
Roof
Tiles(Now
Lafarge
Craneware Ceramics
Yes (LM)
Yes (LM)
Dimpho Foods
Dixon
Battery
Supplies
(Donaventa Holdings)
(Pty)Ltd
Dorbyl Heavy Engineering (Ptyltd
Drie Riviere Primary
Driefontein Gold Mine
Driehoek
Drive In Dry Cleaners
Drive-In Cleaners
Eco Monitor Cc (Klipriver Forum)
SO2
PM
Clay Tiles
Yes
Cresent Packaging
Crystal Papers
Davesteel (Cape Gate)
Df Malherbe
Die Anker Skool
Comments
Bathroom Accessories
Do Not Know
Their Emissions
Plastic
Paper Production
Steel Production From Scrap
Waste Incinerator
Waste Incinerator
Yes
Fresh Food Processing
Yes
Automotive Battery Manufacturer
Do Not Know
Their Emissions
Yes
Manufacture Large Mining Items
Do Not Know
Their Emissions
Yes (LM)
Yes (LM)
No Emissions
Waste Incinerator
Gold Mining
Waste Incinerator
Dry Cleaning
Dry Cleaning
Yes
No Emissions
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-7
Returned (Yes)
Industry Name
Egoli Tissues
Emsa
Environ Drum (Pty) Ltd(Jhb Drum
Reconditioning)
Era Stene
Process Description
NOx
SO2
PM
Yes
Brick Manufacturing
Animal Reduction-Cooking Pig Waste Products To Make
Carcass Meal
Power Generation
Leather Tanning
Asbestos Sheets
Asbestos Sheets
Excelsior Brickworks Edms Mpk
Brick Manufacturing
First Garment Rental
Flexilube
Frikkie Meyer
Dry Cleaning
Refined Used Motor Oil
Waste Incinerator
Yes (LM)
Fry's Metals (Germiston)
Recovery Of Lead From Scrap
G Parkin Brick - Balfour
Brick Manufacturing
General Smuts High
Geotech (Lower Wonderfonteinspruit
Forum)
Geotron Systems (Pty)Ltd
Waste Incinerator
Yes
Consultants
Gillyfrost 3 (Pty)Ltd
Yes
Small Farmimg Operation
Grifo Foundry Cc
Handhawer Primary
Comments
Reconditioned Drums
Escort
Eskom
Eu & La Sheepskin
Everite
Building
Products(Everite
Limited)
Everite Ltd (Klip River)
Pollutants
No Emissions
Emissions
Unknown
Ferrous&Non-Ferrous Castings
Waste Incinerator
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-8
Returned (Yes)
Industry Name
Hb Casting
Heidelberg Hospital
Hendrik Van Derbijl Primary
Henkel
Historia Primary
Hoer Tegnies
Yes (LM)
Yes (LM)
Holfontein Steenwerke E/B
Pollutants
Process Description
Comments
NOx
SO2
PM
Aluminium Castings
Medical Waste Incineration
Waste Incinerator
Waste Incinerator
Waste Incinerator
Brick Manufacturing
Ice Cold Bodies
Impala Plat. (Ni/Cu) (Springs)
Platinum Mining&Refinery
Jhb. Mun Kelvin Power Station
Power Generation-Coal
Johan Heyns
J & J Rubber Linings
Yes (LM)
Waste Incinerator
Karan Beef
Yes
Cattle Feedlot
Do Not Know
Their Emissions
Karbochem
Yes
Rubber Latex
Do Not Know
Their Emissions
Killarney Hotel
Yes (LM)
King Food Corporation
Kloof
Gold
Mine
Wonderfonteinspruit Forum)
Kollegepark
Krugerln School
Yes
(Lower
Waste Incinerator
Sorghum&Maize Milling(Steam Generation)
Do Not Know
Their Emissions
Gold Mining
Yes (LM)
Waste Incinerator
Waste Incinerator
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-9
Kynoch Fertilizer (Pty)Ltd
Langsley Ventures Cc
Lime Distributors
Magistrate's Court
Marievale Brickworks
Returned (Yes)
Industry Name
Pollutants
Process Description
Comments
NOx
SO2
PM
Fertilizers
Yes (LM)
Lime (Limestone) And Distribution
Waste Incinerator
Brick Manufacturing
Mckeown Industries Sa (Pty)Ltd
Mighty Products
Yes
ArcelorMittal Steel - Dunswart
ArcelorMittal Steel Sa Vanderbijlpark
Emissions
Unknown
Iron And Steel Making
Yes
ArcelorMittal Steel Sa Vereeniging
Much Asphalt
Multispray
Nampak
Malt Manufacturers (Cereals)
Iron And Steel Making
Iron And Steel Making
Yes (LM)
Production Of Hot Premix Asphalt
Spray Painted Automobiles
Plastic, Paper, Glass & Metal Packagings
Naschem
Yes
Ammunition Manufacturing (Large Calibre)
Natalspruit Hospital
Natref
Yes
Waste Incineration
Crude Oil Refinery
Ncp (Chloorkop)-(Now Isegen)
Production Of Phthalic Anhydride
Ncp Tvl (Germiston)(Now Isegen)
Production Of Phthalic Anhydride
New Century Bricks
Brick Manufacturing
Updated
Emissions
Inventory Will Be
Available In June
Emissions
Unknown
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-10
New Vaal Colliery
Nkululeko Traders
Non-Ferrous Cast Products
Noordhoek
Oceanside Trading 456
Ocon Bricks
Olifantsfontein Bricks
Oliver Lodge
Omnia Fertiliser (Pty)Ltd
Oospark
Overvaal High
Pampino One
Park Panel Beaters
Park Ridge Primary
Petronet
Returned (Yes)
Industry Name
Process Description
Comments
NOx
SO2
PM
Yes
Yes (LM)
Yes (LM)
Yes
Yes (LM)
Yes (LM)
Yes (LM)
Yes
Pfg Building Glass (Pty) Ltd
Pinedene Primary
Pollutants
Brick Manufacturing
Melting And Moulding Of Aluminium Products
Waste Incinerator
Brick Manufacturing
Brick Manufacturing
Waste Incinerator
Fertilizer
Waste Incinerator
Waste Incinerator
Waste Incinerator
Sanded And Sprayed Automobiles
Waste Incinerator
Underground Pipeline Transportation
Flat Glass Manufacturing
Yes (LM)
Waste Incinerator
Polifin Ltd - Midland Factory(Now Sasol
Polymers)
Chemical Production
PPC (Pretoria)
Cement Production
Premier Hollow Brick & Tile Co
Stock Brick Manufacturing
Pretoria Brickworks
Brick Manufacturing
Pretoria Kragsentrale(Pta-Wes)
Power Generation
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-11
Returned (Yes)
Industry Name
Pollutants
Process Description
NOx
Pretoria Metal Pressing - Oos
Explosive Waste Recovery&Incineration
Protein Products
Protein Products
Rand Water, Vereeniging
Yes
Clay Brick Manufacturing
Waste Incinerator
Clay Brick Manufacturing
S Bothma & Seun Transport (Pty)Ltd
Bulk Transportation& Small Scale Sand Surface Mining
S.A. Breweries Ltd (Alberton)
Sorghum & Malt Products
Sabrix Boekenhoutkloof
Brick Manufacturing
Sabrix Vaal
Safripol
Yes
Brick Manufacturing
Polyethylene And Polypropylene
Samancor-Metalloys (Manganese)
Yes
Ferro Manganese Smelters
Yes (LM)
Yes
Yes
Print
Waste Incinerator
Chemical Manufacturing
Steel Scrap Melting To Produce Grinding Media
Senmin
Paper
PM
Pulp And Paper
Scaw Metals Ltd (Alberton)
Shem Energy
Association
SO2
(Power Generation - Decommissioned End March 2006)
Rayton Bricks
Riverside High
Rosema Stene
Rwb Blr
Sap
Sappi Fine Papers (Springs)(Enstra
Mill)
Sasol
Comments
Mining Chemical Detergents
No Emissions
Wood
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-12
Sigma Colliery
Slagment
Smx Sasolburg (Sasol Nitro)
South African Breweries
Returned (Yes)
Industry Name
Yes (LM)
Sterkfontein Brick Works
Sun Crest High
Suncrush
Sunel Boerderye
Superior
Casting
Makers
Superp Dry Cleaners
Process Description
Comments
NOx
SO2
PM
Slag And Blended Cement
Chemical Manufacturing
Sorghum And Malt Products
Brick Manufacturing-Using Coal Duff (Mined On Site)
Yes (LM)
Yes (LM)
Supplies/Pattern
Waste Incinerator
Iron Castings
Dry Cleaners
Supreme
Yes (LM)
Tanker Services
Yes (LM)
Technical Manuf & Distrib
Tnt Panel Beaters
Tosa (Tubemakers Of Sa)
Totius Primary
Transvalia
Uniresins
Unitaspark Primary School
Vaal High
Vaal Portugese Bakery
Vaal Potteries
Vaal Technikon
Vaalmed
Pollutants
Closed Down
Fuel Storage&Transportation
Iron Scrap Melting Into Fine Products
Yes (LM)
Yes (LM)
Yes (LM)
Yes (LM)
Yes (LM)
Yes (LM)
Yes (LM)
Sanded And Sprayed Automobiles
Zinc Galvanized Tubes And Fittings
Waste Incinerator
Waste Incinerator
Waste Incinerator
Waste Incinerator
Bakery
Ceramic Products
Waste Incinerator
Medical Waste Incinerator
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-13
Van Leer Sa
Van Zyl Panelbeaters
Vanderbijlpark High
Vereeniging Abbatoir
Vereeniging Crushers
Vereeniging High School
Returned (Yes)
Industry Name
Yes (LM)
Yes (LM)
Pollutants
Process Description
NOx
Refractory Bricks
Verref Minerals
Vesuvius
Victoria Brick Pty Ltd
Pitch Bonded Refractory Bricks
Treated Dolomite &Clay Bricks
Clay Brick Manufacturing
Viljoen And Associates
Organic&Inorganic Soil Remedation Consultants
Vitro Building Products
Voorslag
Vryheidsmonument Laerskool
Wesbrix
Willies Confectionary
Yara
Zimmerman And Jansen Sa
Zincor
Clay Products
Waste Incinerator
Waste Incinerator
Brick Manufacturing
Zwartkoppies Pumping Station
SO2
PM
Gas Cylinder Coating By Zinc Spray
Sanded & Sprayed Automobiles
Waste Incinerator
Meat Reduction
Crushed Sand
Waste Incinerator
Vereeniging Refr. (Springs)-(Verref)
Yes (LM)
Comments
No Emissions
Yes (LM)
Metallic Zinc & Sulphuric Acid
Steam Generation-Water Pumping Power
The red ticks are updated/ current information; the blue ticks
where emissions will exist but no information is available.
LM:
Local Municipality
indicate information obtained from the NEDLAG Dirty Fuels study (Scorgie et al, 2004); and the grey ticks
are
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-14
CURRENT INDUSTRIAL BASELINE
Industrial Source Contribution of Sulphur Dioxide Emissions
Smaller Industries
0.07%
Boilers
0.02%
Brickworks
0.001%
Petrochemical
13.95%
Iron and Steel Processes
6.32%
Power Generation
79.63%
Figure 6-2: Total annual sulphur dioxide source emission distribution from industrial,
commercial and institutional sources within the Vaal Airshed.
CURRENT INDUSTRIAL BASELINE
Industrial Source Contribution of Inhalable Particulate Emissions
Power Generation
19.22%
Ferroalloys
2.57%
Mines
15.16%
Brickworks
1.43%
Boilers
0.16%
Smaller Industries
9.99%
Phosphate Fertilizer Process
1.31%
Iron and Steel Processes
37.83%
Petrochemical
12.33%
Figure 6-3: Total annual inhalable particulate source emission distribution from industrial,
commercial and institutional sources within the Vaal Airshed.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-15
CURRENT INDUSTRIAL BASELINE
Industrial Source Contribution of Oxides of Nitrogen Emissions
Boilers
0.01%
Brickworks
0.001%
Smaller Industries
0.04%
Phosphate Fertilizer Process
0.08%
Petrochemical
15.56%
Iron and Steel Processes
13.47%
Power Generation
70.84%
Figure 6-4: Total annual oxides of nitrogen emission distribution from industrial,
commercial and institutional sources within the Vaal Airshed.
6.2
Domestic Fuel Burning
Although an intensive national electrification programme is in progress a large number of
households continue to burn fuel to meet all or a portion of their energy requirements. The
main fuels with air pollution potentials used by households within the Vaal Airshed are coal,
wood and paraffin. These fuels continue to be used for primarily two reasons: (i) rapid
urbanisation and the growth of informal settlements has exacerbated backlogs in the
distribution of basic services such as electricity and waste removal, and (ii) various electrified
households continue to use coal due particularly to its cost effectiveness for space heating
purposes and its multi-functional nature (supports cooking, heating and lighting functions).
The extent of household coal, wood and paraffin burning is illustrated in Figures 6-5, 6-6 and
6-7 respectively. The distribution patterns of fuel use are linked with the former townships
and informal residential areas.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-16
Figure 6-5: Spatial distribution of household coal burning within the Vaal Airshed (based
on 2001 Census data).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-17
Figure 6-6: Spatial distribution of household wood burning within the Vaal Airshed (based
on 2001 Census data).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-18
Figure 6-7: Spatial distribution of household paraffin burning within the Vaal Airshed
(based on 2001 Census data).
Coal is relatively inexpensive and is easily accessible in the region due to the proximity of the
region to coal mines and the well-developed local coal merchant industry. Coal burning
emits a large amount of gaseous and particulate pollutants including sulphur dioxide, heavy
metals, total and respirable particulates including heavy metals and inorganic ash, carbon
monoxide, polycyclic aromatic hydrocarbons (a recognised carcinogen), and benzo(a)pyrene
(Scorgie, 2006). Pollutants arising due to the combustion of wood include respirable
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-19
particulates, nitrogen dioxide, carbon monoxide, polycyclic aromatic hydrocarbons,
particulate benzo(a)pyrene and formaldehyde (Scorgie, 2006). Wood burning is less widely
used compared to coal burning. Although many of the wood burning residential areas tend
to coincide with areas of coal burning there are some exceptions where only wood is burned,
e.g. sections of Vereeniging and Vanderbijlpark. The main pollutants emitted from the
combustion of paraffin are nitrogen dioxide, particulates, carbon monoxide and polycyclic
aromatic hydrocarbons (Scorgie, 2006). The use of paraffin is of concern not only due to
emissions from its combustion within the home, but also due to its use being associated with
accidental poisonings (primarily of children), burns and fires.
The study area included the Emfuleni Local Municipality, Midvaal Local Municipality,
Metsimaholo Local Municipality as well as the more distant Ekurhuleni Local Municipality,
Mogale City Local Municipality and parts of the City of Johannesburg so as to take into
consideration the cross boundary cumulative effect of this source. Total annual domestic
fuel burning emissions calculated for the entire study area are summarised in Table 6-2.
Table 6-2:
Estimated total annual domestic fuel burning emissions (in tons/annum) for
the entire study area (a).
Sulphur Dioxide
Oxides of Nitrogen
Inhalable Particulate Matter
3 442
1 365
1 904
(a) Emissions estimated based on emission factors given in Table 6-2.
Emissions were calculated individually for a total of 65 area sources so as to accurately
account for spatial distributions in fuel consumption intensities and hence emissions. The
location of the 65 household fuel burning sources (burning coal, wood, and/or paraffin) in the
study area is shown in Figure 6-8.
The demand for residential space heating, and hence the amount of fuel burning, has been
found to be strongly dependent on the minimum daily temperature. Seasonal trends in
space heating needs, and therefore in coal burning emissions, were estimated by calculating
the quantity of "heating-degree-days" (HDD), i.e. the degrees below a minimum daily
temperature of 8°C (Annegarn and Sithole, 1999) (Figure 6-9). Diurnal trends in fuel burning,
documented in the local literature, were also taken into account in estimating temporal
variations in household fuel burning emissions (Annegarn and Grant, 1999) (Figure 6-10).
Taking seasonal and diurnal variations in fuel use, and therefore emissions, into account it
was estimated that the maximum emissions during an hour of peak burning (e.g. cold winter
day, between 06:00 and 07:00 or 18:00 and 20:00) were a factor of 10 higher than an hourly
emission rate taken as an average throughout the year.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-20
Domestic Fuel Burning Areas
0km
20km
40km
60km
Figure 6-8: Location of household fuel burning areas simulated for the baseline
assessment of the Vaal Airshed.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-21
Monthly Variation of Domestic Fuel Burning
0.250
0.200
Ratio
0.150
0.100
0.050
0.000
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Month
Figure 6-9: Monthly variations in domestic fuel burning activities that were taken into
account during the simulation of this source (after Annegarn and Sithole, 1999).
Diurnal Trend for Domestic Fuel Burning Activities
3.00
2.50
Fraction
2.00
1.50
1.00
0.50
0.00
0
4
8
12
16
20
Hour of Day
Figure 6-10: Diurnal variation in domestic fuel burning activities that were taken into
account during the simulation of this source (after Annegarn and Grant, 1999).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-22
6.3
Mining Operations
Mining operations within the Vaal Airshed almost exclusively include coal mining activities.
Three mines are operational within the Study Area, namely New Vaal Colliery (in
Vereeniging), Sigma Colliery (in Sasolburg) and Glen Douglas Dolomite Quarry (in
Meyerton). Fugitive emissions from the Sigma and New Vaal opencast collieries were
quantified for the baseline study (Table 6-5). Emissions emanating from the Glen Douglas
Dolomite Quarry, however, could not be quantified due to insufficient available data.
Mining operations represent potentially significant sources of fugitive dust emissions, with
particulate emissions being the main pollutant of concern. Fugitive dust sources associated
with coal mining activities include drilling and blasting activities, materials handling activities,
vehicle-entrainment by haul trucks, crushing and screening activities and wind-blown dust
from stockpiles and exposed surfaces.
Typical operations associated with opencast mining operations include the pre-operational
phase where the area is cleared by removal of vegetation, topsoil and overburden. The
second phase is the operational phase usually including the movement of ore bearing rock or
coal seam, and exposure of erodible surfaces prone to wind erosion. The final phase entails
reclamation where the mined area is restored to its original state.
The initial operation entails the removal of topsoil and subsoil with large scrapers. The
topsoil and subsoil is stored in storage piles which are later used for reclamation purposes.
In the case of coal mines and quarries, drilling and blasting would be required. The blasted
material is then removed by a shovel and truck operation (or in some cases by dragline
operations) loading the material into haul trucks, and taking it out of the pit along graded haul
roads to the tippler, or truck dump. Run of mine (ROM) material may sometimes be dumped
onto a temporary storage pile and later re-handled by a front-end loader or bulldozer.
At most operations the material will undergo primary and sometimes secondary crushing and
screening. These are large sources of dust if not controlled. The material may be
transported to further processing operations by means of conveyors or front end loaders.
The material could also be stored on storage piles which are prone to wind erosion if not
enclosed.
Experience has shown that fugitive dust emissions due to on-site mining operations are
typically only of concern within 3 km of the mine boundary. This is of course dependent on
the dispersion potential of the site and the extent of the mining operations (including dust
suppression methods. The most frequently used dust suppression methods in local mining
operations include the wet suppression and the chemical stabilization of haul roads and
storage piles.
Materials handling operations associated with the activities at the collieries include the
transfer of material by means of tipping, loading and off-loading of trucks. The quantity of
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-23
dust that will be generated from such loading and off-loading operations will depend on
various climatic parameters, such as wind speed and precipitation, in addition to non-climatic
parameters such as the nature (i.e. moisture content) and volume of the material handled.
Fine particulates are most readily disaggregated and released to the atmosphere during the
material transfer process, as a result of exposure to strong winds. Increases in the moisture
content of the material being transferred would decrease the potential for dust emissions,
since moisture promotes the aggregation and cementation of fines to the surfaces of larger
particles.
Significant emissions arise due to the mechanical disturbance of granular material from open
areas and storage piles. Parameters which have the potential to impact on the rate of
emission of fugitive dust include the extent of surface compaction, moisture content, ground
cover, the shape of the storage pile, particle size distribution, wind speed and precipitation.
The quantity of dust emissions from unpaved roads varies linearly with the volume of traffic.
In addition to traffic volumes, emissions also depend on a number of parameters which
characterise the condition of a particular road and the associated vehicle traffic, including
average vehicle speed, mean vehicle weight, silt content of road surface material and road
surface moisture.
Table 6-3:
Inhalable particulate emissions as quantified for various mining activities
within the Vaal Airshed.
Mine
New Vaal Colliery
Sigma Colliery
6.4
PM10 (tons/annum)
3 467
1 087
Wind-blow Dust from Eskom’s Ash Dams and Dumps
The emissions from the various ash dumps within the Vaal Airshed were taken from the Vaal
South Environmental Impact Assessment undertaken by Airshed (Thomas and Scorgie,
2006). Parameters which have the potential to impact on the rate of emission include the
extent of surface compaction, the particle size distribution, the moisture content of the
material, the shape of the dam/dump, ground cover, wind speed and precipitation. Any
factor that binds the erodible material, or reduces the erodible surface area, decreases the
fugitive emissions from the source. High moisture content (due to precipitation or deliberate
wetting) will increase the aggregation and cementation of fines, thus decreasing the potential
for dust emissions. Similarly, surface compaction and ground cover will reduce the potential
for dust generation. The shape of a dump has the potential to influence dust emissions
through the modification of the airflow field. The particle size distribution of the material on
the dump is important since it determines the rate of entrainment of material from the
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-24
surface, the nature of dispersion of the dust plume, and the rate of deposition, which may be
anticipated (Burger, 1994; Burger et al., 1995).
6.5
Vehicle Emissions
Air pollution from vehicle emissions may be grouped into primary and secondary pollutants.
Primary pollutants are those emitted directly into the atmosphere, and secondary, those
pollutants formed in the atmosphere as a result of chemical transformation, such as
hydrolysis, oxidation, or photochemical reactions. The significant primary pollutants emitted
by motor vehicles include carbon dioxide, carbon monoxide, hydrocarbon compounds,
sulphur dioxide, oxides of nitrogen and particulate matter. Secondary pollutants include
nitrogen dioxide, photochemical oxidants (e.g. ozone), hydrocarbon compounds, sulphur
acid, sulphates, nitric acid and nitrate aerosols (Copert, 2000). Emission estimates where
undertaken for sulphur dioxide, nitric oxide, nitrogen dioxide and particulate matter for the
current study.
The study area taken into consideration for this source extends beyond the Vaal Triangle
(Emfuleni Local Municipality, Midvaal Local Municipality and Metsimaholo Local Municipality)
to include Mogale City Local Municipality, Ekurhuleni Local Municipality and parts of City of
Johannesburg. The study area was selected to take the highly congested traffic areas to the
north of the Vaal Triangle into account which may add to the cumulative impact within the
area.
The vehicle emissions were calculated per magisterial district within the study area (Table 64). These emissions were assigned to various national and regional routes (see Figure 6-11)
by applying vehicle count data obtained from Mikros Traffic Monitoring (Pty) Ltd for the
period 2004 to 2006. The remaining emissions data that could not be assigned to specific
routes were then distributed over the remaining regional roads within the Vaal Airshed.
Table 6-4:
Total annual tailpipe emissions due to vehicle activity calculated per
magisterial area within the Vaal Airshed.
Magisterial Area
Alberton
Balfour
Benoni
Boksburg
Brakpan
Brits
Bronkhorstspruit
Culinan
Sulphur
Dioxide
149
12
94
89
45
65
25
7
Emissions tons/annum
Nitric
Nitrogen
Oxide
Dioxide
4 984
413
3 495
3 342
1 603
2 094
858
254
554
46
388
371
178
233
95
28
PM
394
30
180
165
100
173
58
16
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-25
Magisterial Area
Frankfort
Germiston
Heilbron
Heidelberg
Krugersdorp
Johannesburg
Kempton Park
Nigel
Roodepoort
Randburg
Pretoria
Sasolburg
Springs
Westonaria
Wonderboom
Koppies
Parys
Potch
Randfontein
Vereeniging
Vanderbijlpark
Sulphur
Dioxide
9
174
4
20
94
717
169
25
104
240
612
118
35
23
57
9
10
22
23
82
60
Emissions tons/annum
Nitric
Nitrogen
Oxide
Dioxide
276
6 170
136
710
3 220
25 816
6 132
812
4 137
9 556
22 193
3 711
1 345
860
2 183
305
350
977
894
2 916
2 114
31
686
15
79
358
2 868
681
90
460
1 062
2 466
412
149
96
243
34
39
109
99
324
235
PM
26
392
10
48
237
1 543
350
72
148
341
1 280
342
63
47
97
25
24
16
36
185
136
As the routes were assumed to be straight lines (see Figure 6-12), the length of the roads
obtained were multiplied by a factor of 1.4 to accommodate the curved nature of these
sources. In addition, based on vehicle emissions from the N4, it was calculated that 20%
and 10% of the fuel usage from light and heavy commercial vehicles respectively, would be
used outside the study area. As the routes within the Johannesburg magisterial districts are
largely congested, emissions were assigned to the main national routes that pass over this
area (i.e. the N4, N1, M1, N12, N17 and the N3). The remaining emissions were distributed
over area sources assigned to built-up areas (see Figure 6-13).
The diurnal profile of vehicle activity was taken into account for regional and national routes
for which vehicle count data was available (as obtained from Micros Traffic Monitoring). The
diurnal profiles of the national routes are indicated in Figure 6-14. For roads without vehicle
count data readily available, the hourly median was taken for the diurnal profile from all
vehicle count data within the Vaal Airshed.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-26
Figure 6-11: Layout of the regional and national road network and magisterial districts
within the study area.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-27
Figure 6-12: The layout of the road sources for the quantification of tailpipe emissions and
identification of dispersion modelling areas.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-28
Figure 6-13: Spatial apportionment of vehicle emissions over the highly congested
residential area of Johannesburg and surrounding areas.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-29
Diurnal Vehicle Count Data for National Roads
10000
N1
N12 through Westonaria MD
N12 through Benoni MD
N3 through the Alberton MD
N17
9000
Vehicle Counts (vehicles/hour)
8000
7000
6000
5000
4000
3000
2000
1000
0
1
3
5
7
9
11
13
15
17
19
21
23
Hour of Day
Figure 6-14: Diurnal profile of vehicles along national routes within the Vaal Airshed as
obtained from vehicle count data (as obtained from Micros Traffic Monitoring).
6.6
Waste Treatment and Disposal Areas
Specific industrial activities are related to toxic emissions and waste disposal sites, i.e.,
landfills, waste water treatment works and waste incinerator facilities. Sufficient emissions
and air quality data are, however, currently unavailable on which to base a comprehensive
assessment of these sources.
6.6.1
Landfill operations
The majority of the waste collected by the local authority is disposed to landfill, usually within
10-20 km radius of the residential areas within which the waste was generated. At present,
the Vaal Airshed has 12 regional disposal facilities as depicted in Table 6-13. Detailed
landfill information, however, could not be obtained from the City of Johannesburg and
Metsimaholo Local Municipality.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-30
Table 6-5:
al (2007)).
Landfill operations located within the Vaal Airshed (after Liebenberg-Enslin et
Municipality
City
of
Johannesburg
Metropolitan Municipality
Metsimaholo
Local
Municipality
Emfuleni Local Municipality
Midvaal Local Municipality
Name
Grootkoppies
Palm Springs
Deneysville
Oranjeville
Sasolburg
Boitshepi
Palm Springs
Waldrift
Zuurfontein
Vaal Marina
Henley on Klip
Walkerville / De Deur
Type
G:L:B+ (provisional)
G:S:Bor
(provisional)
G:L:B- (provisional)
G:L:B- (provisional)
G:C:B- (expected)
G:C:B- (expected)
G:C:B- (expected)
G:M:B-
Notes:
G: General waste
C: Communal landfill (<25 tonnes/day)
S: Small landfill (>25 tonnes/day but <150 tonnes/day)
L: Large landfill (>500 tonnes/day)
B: is the Climatic Water Balance.
B- : A site is classified as B- if there is no significant leachate generation and only dry waste is disposed of
B+ : A site is classified as B+ if there is significant leachate generation and such leachate requires management.
All the waste disposal sites within the Vaal Airshed are predominantly used for general waste
disposal, including domestic, commercial and industrial waste. It is unknown to what extent
co-disposal of domestic and industrial/commercial hazardous waste occurs at the general
waste sites. Limited information is available on the practical volumes and quantities of
hazardous waste disposed at the landfill sites in Vaal Airshed, or on the volumes and
masses of hazardous waste stored on-site by industrial operations.
6.6.2
Incinerator Operations
All identified incineration processes within the Vaal Airshed were included in the industrial
source quantification. The emission rates of incinerator operations are a function of fuel
usage, waste composition, incinerator design characteristics and operating conditions.
Gaseous emissions from incinerator operations may be grouped into: (i) criteria pollutants
(viz. sulphur dioxide, oxides of nitrogen, carbon monoxide, lead and particulates), (ii) acid
gases (viz. hydrogen chloride, hydrogen bromide and hydrogen fluoride), (iii) metal gases
(viz. chromium, arsenic, cadmium, mercury, manganese, etc.), and (iv) dioxins and furans
(viz. polychlorinated dibenzo-p-dioxins and dibenzo furans) (Scorgie, 2006).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-31
Emissions due to incinerator operations have a greater sphere of influence than landfills and
waste water treatment plants due to the elevated nature of the emission source and the
larger quantities being released.
6.6.3
Waste Water Treatment Works
Insufficient information was available for waste water treatment facilities within the Vaal
Airshed, to quantify these emission sources.
Pollutant sources of waste water treatment works include odourants such as hydrogen
sulphide, mercaptans, ammonia and various fatty acids, as well as formaldehyde, acetone,
toluene, ethyl benzene, xylenes and perchloroethylene (Scorgie, 2006).
Theoretical estimates of air pollutant emission rates emanating from sewer treatment
facilities can be done by means of US-EPA emission factors. In order to calculate these
emissions, however, detailed information regarding the process and the volumes treated is
required.
6.7
Agriculture
Agricultural activities including field cultivation (with the principal crops being maize, sorghum
and sunflower) and pastoral farming make up ~60% of the study area. These activities can
be responsible for the emission of large quantities of particulates. Fallow fields in the dry
winter months and ploughing and harvesting activities in the summer months result in the
potential for fugitive dust.
Using data on agricultural land use and on the erosion potential of soils from the Department
of Agriculture and US-EPA emission factors, van Nierop (1995) estimated total suspended
particulates and inhalable particulate emissions due to agricultural activities as being
2886 tons/annum and 683 tons/annum respectively.
6.8
Railway Transport
Internationally, very few studies have been undertaken to accurately investigate these
emissions, with emission estimates for the railway network in Europe having only been made
in the last 10 years (Jorgensen and Sorenson, 1997). No emission factors are available
locally for the calculation of emissions from railway transport.
Railway transport in the Vaal Triangle consists of electric, steam and diesel-powered
locomotives. Diesel locomotives are generally used for the transportation of bulk material to
and from industries. In order to calculate these emissions, reference may be made to the
emission factors for railway traffic emissions estimated by the Department of Energy
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-32
Engineering at the University of Denmark (Jorgensen and Sorenson, 1997). However,
detailed information, that was not available for the current assessment would be required
including: inventory of train types (diesel, steam, electric), average train speed, number of
passengers per seat (0-100%), topography of the distance travelled, slopes and hills, wind
speed, number of cold starts (for diesel powered trains), average distance between train
stations, and degree of reuse of braking energy.
6.9
Airport Emissions
Airports and airstrips within the Vaal Triangle include the Aerovaal Airport, Deneysville
Landing Strip, Star Landing Ground and Vanderbijlpark Aerodrome. These airstrips/aircrafts
accommodate infrequent small aircrafts, gliders, etc.
Although extensive studies have been undertaken in countries such as the United States to
estimate airport emissions, local studies have been limited to air quality impact assessments
for Cape Town and Johannesburg International Airports.
The extent of various pollutant emissions from the aircraft engine is depended on the mode
of operation of the aircraft. The largest pollutant emitted from aircraft is oxides of nitrogen,
with carbon monoxide forming the second largest emission. Other pollutants emitted consist
of sulphur dioxide, total suspended particulates and volatile organic compounds. The extent
of sulphur dioxide emissions is dependent on the sulphur dioxide content of the fuel. Carbon
monoxide and hydrocarbon emissions are a result of incomplete or poor combustion and are
generally greater during idle operations. Oxide of nitrogen emissions on the other hand are
associated with the oxidation of atmospheric nitrogen during combustion processes and is
generally greatest during take-off when the aircraft engine is producing maximum power
(NPi, 2003).
Emission factors are available for the estimation of emissions of the various gaseous
emissions from aircraft engines. Such factors are given in kg of pollutant per land-take-off
cycle (LTO) and are refined for approach, taxi, take-off and climb-out operations. Emission
factors are given for specific aircraft type with large variations in emissions from different
aircraft types apparent (NPi, 2003).
Thus, in order to estimate emissions from aircraft engines and auxiliary power units, detailed
information would need to be collated, including: inventory of aircraft types, average
durations of taxi, take-off, approach and climb-out operations, sulphur content of fuels, (etc.).
The estimation of evaporative emissions from fuel storage and handling would also require
detailed information regarding storage conditions and handling operations. This information
was not available for the current assessment. The emissions from this source, however, are
expected to be low due to the infrequent traffic and small aircraft sizes at the Vaal Triangle
airstrips/ airports.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-33
6.10 Spontaneous Combustion
Spontaneous combustion occurs on discard dumps and underground. No known information
is available in open literature for the quantification of spontaneous combustion emissions.
However, in attempt to identify the occurrence of spontaneous combustion use has been
made of satellite-based remote sensing products such as ASTER (Advanced Spaceborne
Thermal Emission and Reflection Radiometer) which is a high resolution imaging instrument
that is flying on the Terra satellite and MAS (Magical-Angle-Spinning) which is a new
technique for high-resolution quadrupolar NMR.
Figure 6-15: Spectral image for the New Vaal Colliery area, illustrating apparent incidences
of spontaneous coal combustion sites as bright red areas (indicated by circles). The Lethabo
Power Station is located at the bottom right of the image. (Work undertaken by Prof. Harold
Annegarn and the Atmosphere and Energy Research Group, Wits University, 2002.)
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-34
Figure 6-15, provides a spectral image of the New Vaal Colliery area, illustrating areas of
spontaneous combustion as bright red areas. The MAS bands which were used in the image
consisted of 18, 12 and 1 corresponding to wavelengths 2.005, 1.75 and 0.465 respectively.
This is the visible region of the spectrum.
Additional research into the occurrence, extent and duration of spontaneous combustion
episodes is being conducted as part of the COALTECH 2020 initiative which aims to quantify
greenhouse gas emissions arising due to this source. The research is however not
sufficiently advanced as to provide a source of quantitative emission information.
6.11 Transboundary Sources
Dispersion of pollutants is influenced by large-scale circulations (as discussed in detail in
Section 4.3). Pollutants from adjacent areas to the Vaal triangle as well as further afield may
influence the air quality within the region. Similarly, the pollutants originating in the Vaal
Triangle may impact the air quality of surrounding areas.
Source apportionment studies have identified four main source types of regional significance
to the atmospheric aerosol loading, i.e. (i) aeolian crustal material consisting of mineral soil
dust, (ii) marine aerosols from the two adjacent oceans (iii) biomass burning particles
occurring mainly north of 20°S and (iv) aerosols from industrial emissions. These four
sources groups have been identified in remote areas of South Africa (Piketh, 1995; Piketh et
al., 1996; Salma et al., 1992; Maenhaut et al., 1996).
6.12 Summary of Emissions Quantified
The contribution of sulphur dioxide, inhalable particulate matter and oxides of nitrogen
emissions from all quantified sources of emissions is illustrated in Figures 6-16, 6-17 and 618 respectively.
The main contributor to sulphur dioxide emissions is from power generation (~77%) with
notable contributions from petrochemical (~13%) and iron and steel processes (~6%). The
notable sources of inhalable particulate matter emissions within the study area are made up
of industrial and non-industrial groups. The main contributors to the oxides of nitrogen
emissions within the study area are vehicle exhaust (~44%) and power generation (38%).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-35
CURRENT BASELINE (ALL SOURCES)
Source Contribution of Sulphur Dioxide Emissions
Other Industries
Commercial
0.07%
0.02%
Iron and Steel Processes
6.15%
Vehicles
1.09%
Domestic Fuel Burning
1.55%
Petrochemical
13.59%
Ferroalloys
0.00%
Power Generation
77.53%
Figure 6-16: Total annual sulphur dioxide emission distribution from all quantified sources
of emission within the Vaal Airshed.
CURRENT BASELINE (ALL SOURCES)
Source Contribution of Inhalable Particulate Emissions
Commercial
0.13%
Other Industries
10.33%
Mines and Ash Dumps
12.30%
Vehicles
13.71%
Iron and Steel Processes
30.70%
Domestic Fuel Burning
5.14%
Petrochemical
10.01%
Ferroalloys
2.08%
Power Generation
15.60%
Figure 6-17: Total annual inhalable particulate emission distribution from all quantified
sources of emission within the Vaal Airshed.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-36
CURRENT BASELINE (ALL SOURCES)
Source Contribution of Oxides of Nitrogen Emissions
Iron and Steel Processes
7.33%
Petrochemical
8.46%
Other Industries
0.07%
Commercial
0.01%
Vehicles
44.92%
Power Generation
38.54%
Domestic Fuel Burning
0.67%
Figure 6-18: Total annual oxides of nitrogen emission distribution from all quantified
sources of emission within the Vaal Airshed.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
6-37
7
CHAPTER 7
DISPERSION SIMULATION AND IMPACT ASSESSMENT
7.1
Simulated Results
Simulations were undertaken to determine particulate matter, sulphur dioxide and nitrogen
dioxide concentrations within the Vaal Airshed due to all quantifiable sources of emissions.
Isopleth plots reflecting hourly and daily averaging periods contain only the highest (99.99th
and 99.7th percentile respectively) predicted ground level concentrations for that averaging
period, over the entire period for which simulations were undertaken. It is therefore possible
that even though a high hourly or daily concentration is predicted to occur at certain
locations, that this may only be true for one hour or day during the entire period.
The plots provided for the baseline assessment is given in Table 7-1. Isopleth plots are only
provided for averaging periods for which ambient air quality guidelines/standards are
available.
Table 7-1:
Isopleth plots presented in the current section.
Pollutant
Sulphur Dioxide
Nitrogen Dioxide
Inhalable
Matter
Particulate
Averaging period
Highest hourly (4)
Highest daily (5)
Annual average
Highest hourly (4)
Highest daily (5)
Annual average
Highest daily (5)
Annual average
Guideline/Standard
(µg/m³)
350 (1)(2)(3)
125 (1)(2)(3)
50 (1)(2)(3)
376 (1), 200(2)(3)
188(1)
(1)
94 , 40(2)(3)
180(1), 75(2), 50(3)
60(1), 40(2), 30(3)
Figure
7-1
7-2
7-3
7-4
7-5
7-6
7-7
7-8
Notes:
(1) Current SA Standard as adopted by DEAT on 11 September 2005.
(2) Proposed SA standard (SANS limit)
(3) EC Limit
(4) 99.99th percentile
th
(5) 99.7 percentile
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-1
HIGHEST HOURLY AVERAGE SULPHUR DIOXIDE CONCENTRATIONS (µg/m³)
ALL CURRENT SOURCES
200 µg/m³
350 µg/m³
500 µg/m³
0km
HIGHEST DAILY AVERAGE SULPHUR DIOXIDE CONCENTRATIONS (µg/m³)
ALL CURRENT SOURCES
35 µg/m³
50 µg/m³
125 µg/m³
20km
40km
60km
80km
0km
20km
40km
th
60km
80km
th
Figure 7-1:
Highest hourly (99.99 percentile) predicted sulphur Figure 7-2:
Highest daily (99.7 percentile) predicted sulphur
dioxide ground level concentrations (µg/m³) within the study area.
dioxide ground level concentrations (µg/m³) within the study area.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-2
ANNUAL AVERAGE SULPHUR DIOXIDE CONCENTRATIONS (µg/m³)
ALL CURRENT SOURCES
100 µg/m³
200 µg/m³
300 µg/m³
10 µg/m³
15 µg/m³
30 µg/m³
0km
HIGHEST HOURLY AVERAGE NITROGEN DIOXIDE CONCENTRATIONS (µg/m³)
ALL CURRENT SOURCES
20km
40km
60km
80km
0km
20km
40km
60km
80km
th
Figure 7-3:
Annual average predicted sulphur dioxide ground Figure 7-4:
Highest hourly (99.99 percentile) predicted nitrogen
level concentration (µg/m³) within the study area.
dioxide ground level concentration (µg/m³) within the study area.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-3
HIGHEST DAILY AVERAGE NITROGEN DIOXIDE CONCENTRATIONS (µg/m³)
ALL CURRENT SOURCES
5 µg/m³
8 µg/m³
15 µg/m³
20 µg/m³
30 µg/m³
40 µg/m³
0km
ANNUAL AVERAGE NITROGEN DIOXIDE CONCENTRATIONS (µg/m³)
ALL CURRENT SOURCES
20km
40km
60km
80km
0km
20km
40km
60km
80km
th
Figure 7-5:
Highest daily (99.7 percentile) predicted nitrogen Figure 7-6:
Annual average predicted nitrogen dioxide ground
dioxide ground level concentration (µg/m³) within the study area.
level concentration (µg/m³) within the study area.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-4
HIGHEST DAILY AVERAGE INHALABLE PARTICULATE CONCENTRATIONS (µg/m³)
ALL CURRENT SOURCES
10 µg/m³
40 µg/m³
60 µg/m³
50 µg/m³
75 µg/m³
180 µg/m³
0km
ANNUAL AVERAGE INHALABLE PARTICULATE CONCENTRATIONS (µg/m³)
ALL CURRENT SOURCES
20km
40km
60km
80km
0km
20km
40km
th
60km
80km
Figure 7-7:
Highest daily (99.7 percentile) predicted inhalable Figure 7-8:
Annual average predicted inhalable
particulate ground level concentration (µg/m³) within the study area.
ground level concentration (µg/m³) within the study area.
particulate
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-5
7.2
Predicted Data Validation (Measured vs. Modelled)
Modelled sulphur dioxide, nitrogen dioxide and inhalable particulate concentrations simulated
for current baseline conditions within the Vaal Airshed are compared to monitored
concentrations (where data availability was >80%) in Table 7-2 to Table 7-4. Measured
(99.99th percentile of hourly and 99.7th percentile daily concentrations) and modelled highest
hourly (99.99th percentile), highest daily (99.7th percentile) and annual average air pollutant
concentrations are given in the table for each of the monitoring stations. The ratio between
measured and modelled concentrations is also presented. Given that the US-EPA gives the
range of uncertainty in dispersion model results as being –50% to 200% only model
predictions falling outside of this range when compared to monitored concentrations were
flagged as being unrepresentative (i.e. modelled to monitored ratios of <0.5 or >2.0).
Flagged values are indicated in bold print in the table. The measured and modelled
frequencies of exceedance of air quality limits are compared in Table 7-5 to Table 7-6.
Modelled and monitored air pollutant concentrations and modelled and measured
frequencies of exceedance of air quality limits are depicted in Figures 7-9 to 7-20 for the
three pollutants being investigated (Figures 7-9 to 7-13 for sulphur dioxide, Figure 7-14 to 717 for nitrogen dioxide, and Figure 7-18 to 7-20 for inhalable particulates).
7.2.1
Comparison of Measured and Modelled Sulphur Dioxide
The predicted ground level concentrations compared well with ambient measured sulphur
dioxide levels for all averaging periods with the exception of the Sasol stations (i.e. modelled
to monitored ratios of between 0.5 and 2.0). The predicted concentrations at the Sasol
stations compared well for highest hourly and daily averaging periods, with the modelled
predictions slightly under predicting on daily monitored concentrations, but still generally
within the range of model uncertainty given by the US-EPA. On an annual averaging period,
with the exception of the Leitrim monitoring station, the modelled concentrations under
predict by 70% - 80%. The general model bias is to under predict on the medium- (daily) to
long-term (annual) averaging periods.
7.2.2
Comparison of Measured and Modelled Nitrogen Dioxide
Modelled nitrogen dioxide concentrations compared generally well for highest hourly and
daily averaging periods but under predicted for annual averaging periods for all monitoring
stations.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-6
Table 7-2:
Comparison of monitored and modelled sulphur dioxide ground level concentrations for current baseline conditions within the
Vaal Airshed.
Highest Hourly Average (1)
Highest Daily Average (2)
2004
2005
2006
2004
2005
2006
Measured Sulphur Dioxide (µg/m³)
Monitoring Agency
Station
City of
Johannesburg
Orange Farm
-
237
395
Station 620
Station 350
AJ Jacobs
Boiketlong
Hospital
Leitrim
Makalu
546
515
639
477
581
398
701
664
633
461
-
472
Orange Farm
342
272
ArcelorMittal Steel
Sasol
Eskom
City of
Johannesburg
ArcelorMittal Steel
Sasol
Eskom
City of
Johannesburg
ArcelorMittal Steel
Sasol
Station 620
Station 350
AJ Jacobs
Boiketlong
Hospital
Leitrim
Makalu
-
-
621
109
104
1285
92
111
479
84
84
947
70
78
59
Modelled Sulphur Dioxide (µg/m³)
230
56
44
2004
Annual Average
2005
2006
64
-
13
15
69
110
104
81
153
-
39
37
36
26
20
28
36
41
33
31
-
37
38
27
32
-
48
10
8
9
20
20
12
13
10
21
10
22
18
7
11
6
20
10
23
20
10
11
8
19
11
457
430
389
86
128
111
432
366
406
64
44
48
609
688
626
63
65
64
498
444
696
61
44
56
453
296
669
53
47
54
717
509
768
101
61
60
575
515
474
45
41
60
Ratio between Measured and Modelled Sulphur Dioxide Concentrations
Orange Farm
-
1.1
0.6
-
1.2
0.7
-
0.6
0.6
Station 620
-
-
0.8
-
-
1.6
-
-
0.8
Station 350
AJ Jacobs
Boiketlong
1.1
1.0
0.9
1.0
0.7
1.0
0.5
0.6
0.7
0.7
0.6
0.4
0.6
0.5
0.3
0.3
0.6
0.2
0.3
0.3
0.3
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-7
(1)
Monitoring Agency
Station
Eskom
Hospital
Leitrim
Makalu
Highest Hourly Average
2004
2005
2006
0.7
0.5
1.4
1.5
1.1
0.8
1.0
-
(2)
Highest Daily Average
2004
2005
2006
0.6
0.6
0.7
0.4
1.4
0.8
0.8
-
2004
0.3
0.8
0.5
Annual Average
2005
0.2
0.6
-
2006
0.3
0.6
-
Notes:
(1)
99.99th percentile
(2)
th
99.7 percentile
Table 7-3:
Comparison of monitored and modelled nitrogen dioxide ground level concentrations for current baseline conditions within the
Vaal Airshed.
Monitoring Agency
ArcelorMittal Steel
Sasol
Eskom
ArcelorMittal Steel
Sasol
Eskom
ArcelorMittal Steel
Sasol
Station
Station 620
Station 350
AJ Jacobs
Leitrim
Makalu
Station 620
Station 350
AJ Jacobs
Leitrim
Makalu
Station 620
Station 350
AJ Jacobs
Leitrim
Highest Hourly Average (1)
Highest Daily Average (2)
2004
2005
2006
2004
2005
2006
Measured nitrogen dioxide (µg/m³)
274
48
140
55
181
161
63
54
177
144
117
68
48
51
95
33
Modelled nitrogen dioxide (µg/m³)
291
124
296
31
22
21
145
130
169
26
23
26
256
149
243
31
25
25
200
287
136
40
28
21
172
186
212
26
17
32
Ratio between Measured and Modelled nitrogen dioxide Concentrations
0.4
1.1
0.4
0.9
0.4
0.8
1.5
0.5
2.0
0.4
1.1
1.2
0.6
0.6
2004
Annual Average
2005
2006
28
16
29
28
23
-
28
28
27
-
6
6
6
8
6
5
5
4
7
6
6
6
4
7
6
0.3
0.2
0.1
0.3
0.2
0.2
0.2
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-8
(1)
Monitoring Agency
Station
Eskom
Makalu
Highest Hourly Average
2004
2005
2006
1.8
-
(2)
Highest Daily Average
2004
2005
2006
0.8
-
2004
0.4
Annual Average
2005
-
2006
-
Notes:
(1)
99.99th percentile
(2)
th
99.7 percentile
Table 7-4:
Comparison of monitored and modelled inhalable particulate ground level concentrations for current baseline conditions within
the Vaal Airshed.
Monitoring Agency
City of
Johannesburg
Sasol
Eskom
City of
Johannesburg
Sasol
Eskom
City of
Johannesburg
Sasol
Eskom
Station
Highest Hourly Average (1)
Highest Daily Average (2)
2004
2005
2006
2004
2005
2006
Measured inhalable particulate (µg/m³)
Orange Farm
979
929
933
Leitrim
Makalu
998
605
905
947
Orange Farm
770
526
558
Leitrim
Makalu
154
2004
Annual Average
2005
2006
78
66
176
152
168
254
97
Modelled inhalable particulate (µg/m³)
153
53
34
105
41
99
15
12
12
36
20
25
18
29
18
0.2
0.2
0.2
0.7
133
84
1051
1014
1174
171
130
135
479
494
726
87
75
69
Ratio between Measured and Modelled inhalable particulate Concentrations
Orange Farm
0.8
0.6
0.6
0.9
0.5
0.6
Leitrim
Makalu
1.1
0.8
1.1
1.2
1.0
0.9
0.5
0.9
0.7
0.6
Notes:
(1)
th
99.99 percentile
(2)
th
99.7 percentile
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-9
Table 7-5:
Comparison of monitored and modelled sulphur dioxide frequencies of exceedance of air quality limits due to baseline conditions
(Data availabilities given in brackets after measured frequencies.)
Monitoring
Station
Hourly SO2 air quality
target of 350 µg/m³
Measured
Predicted
2004
Orange
Data <80%
Farm
Station 620 Data <80%
Station 350
NM
AJ Jacobs 53 (100%)
Boiketlong
50 (99%)
Hospital
20 (100%)
Leitrim
5 (91%)
Makalu
16 (99%)
NM – not measured
Frequencies of Exceedance (hours or days per year) of:
Hourly SO2 air quality
Hourly SO2 air quality
Daily SO2 air quality
Daily SO2 air quality
target of 350 µg/m³
target of 350 µg/m³
target of 125 µg/m³
target of 125 µg/m³
Measured
Predicted Measured
Predicted
Measured Predicted Measured Predicted
2005
2006
2004
2005
Daily SO2 air quality
target of 125 µg/m³
Measured Predicted
2006
0
1 (83%)
0
25 (83%)
0
Data <80%
0
0 (86%)
0
6 (88%)
0
4
3
6
9
2
6
2
Data <80%
3 (96%)
48 (100%)
83 (100%)
36 (100%)
31 (93%)
NM
3
1
1
1
0
4
3
5 (86%)
4 (70%)
59 (99%)
91 (99%)
18 (99%)
12 (99%)
NM
1
2
6
1
7
2
5
Data <80%
NM
6 (100%)
3 (99%)
2 (100%)
0 (91%)
0 (100%)
0
0
0
0
0
0
0
0 (74%)
7 (100%)
8 (100%)
3 (100%)
0 (95%)
NM
2
0
0
0
0
0
0
0 (92%)
0 (79%)
9 (98%)
8 (99%)
0 (99%)
0 (93%)
NM
0
0
0
0
0
0
0
Table 7-6:
Comparison of monitored and modelled nitrogen dioxide and inhalable particulate frequencies of exceedance of air quality limits
due to baseline conditions (Data availabilities given in brackets after measured frequencies.)
Hourly NO2 air quality
Monitoring
target of 200 µg/m³
Station
Measured
Predicted
2004
Orange
NM
0
Farm
Station 620
NM
1
Station 350
NM
0
AJ Jacobs
NM
2
Leitrim
5 (91%)
1
Makalu
0 (98%)
0
Frequencies of Exceedance (hours or days per year) of:
Hourly NO2 air quality
Hourly NO2 air quality
Daily PM10 air quality
Daily PM10 air quality
target of 200 µg/m³
target of 200 µg/m³
target of 75 µg/m³
target of 75 µg/m³
Measured
Predicted
Measured
Predicted Measured Predicted Measured Predicted
2005
2006
2004
2005
Daily PM10 air quality
target of 75 µg/m³
Measured Predicted
2006
NM
1
NM
1
154 (87%)
8
182 (77%)
6
196 (88%)
6
0 (77%)
0 (96%)
0 (100%)
0 (93%)
NM
0
0
0
1
0
Data <80%
0 (74%)
1 (99%)
0 (99%)
NM
1
0
2
0
1
NM
NM
NM
84 (80%)
24 (82%)
51
62
6
37
3
Data <80%
Data <80%
NM
162 (71%)
NM
99
61
2
18
2
Data <80%
Data <80%
NM
50 (99%)
NM
105
80
4
25
4
NM – not measured
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-10
HIGHEST HOURLY AVERAGE SULPHUR DIOXIDE CONCENTRATIONS (µg/m³)
ALL CURRENT SOURCES
HIGHEST DAILY AVERAGE SULPHUR DIOXIDE CONCENTRATIONS (µg/m³)
ALL CURRENT SOURCES
395
64
472
69
479
621
1285
947
81
110
104
153
200 µg/m³
350 µg/m³
500 µg/m³
0km
35 µg/m³
50 µg/m³
125 µg/m³
20km
40km
60km
80km
0km
20km
40km
60km
80km
Comparison of simulated highest daily (99.7th
Figure 7-9:
Comparison of simulated highest hourly (99.99th Figure 7-10:
percentile) sulphur dioxide concentrations with measured highest percentile) sulphur dioxide concentrations with measured highest daily
hourly concentrations (for the period 2006) within the study area.
concentrations (for the period 2006) within the study area.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-11
ANNUAL AVERAGE SULPHUR DIOXIDE CONCENTRATIONS (µg/m³)
ALL CURRENT SOURCES
FREQUENCY OF EXCEEDANCE OF HOURLY SO2 LIMIT OF 350 µg/m³
ALL CURRENT SOURCES
22
15
25
0
30
27
37
38
18
59
32
10 µg/m³
15 µg/m³
30 µg/m³
0km
4
5
91
12
1 hour
4 hours
24 hours
20km
40km
60km
80km
0km
20km
40km
60km
80km
Comparison of simulated frequency of exceedance
Figure 7-11:
Comparison of simulated annual average sulphur Figure 7-12:
dioxide concentrations with measured annual average concentrations of the hourly sulphur dioxide SA standard of 350 µg/m³ with measured
frequencies (for the period 2006) within the study area.
(for the period 2006) within the study area.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-12
FREQUENCY OF EXCEEDANCE OF DAILY SO2 LIMIT OF 125 µg/m³
ALL CURRENT SOURCES
HIGHEST HOURLY AVERAGE NITROGEN DIOXIDE CONCENTRATIONS (µg/m³)
ALL CURRENT SOURCES
3
6
0
0
274
0
0
9
8
161
117
0
100 µg/m³
200 µg/m³
300 µg/m³
1 day
3 days
10 days
0km
20km
40km
60km
80km
0km
20km
40km
60km
80km
Comparison of simulated highest hourly (99.99th
Figure 7-13:
Comparison of simulated frequency of exceedance Figure 7-14:
of the daily sulphur dioxide SA standard of 125 µg/m³ with measured percentile) nitrogen dioxide concentrations with measured highest
frequencies (for the period 2006) within the study area.
hourly concentrations (for the period 2006) within the study area.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-13
HIGHEST DAILY AVERAGE NITROGEN DIOXIDE CONCENTRATIONS (µg/m³)
ALL CURRENT SOURCES
16
ANNUAL AVERAGE NITROGEN DIOXIDE CONCENTRATIONS (µg/m³)
ALL CURRENT SOURCES
3
43
38
46
15
38
14
5 µg/m³
8 µg/m³
15 µg/m³
20 µg/m³
30 µg/m³
40 µg/m³
0km
18
15
20km
40km
60km
80km
0km
20km
40km
60km
80km
Comparison of simulated annual average nitrogen
Figure 7-15:
Comparison of simulated highest daily (99.7th Figure 7-16:
percentile) nitrogen dioxide concentrations with measured highest dioxide concentrations with measured annual average concentrations
(for the period 2006) within the study area.
daily concentrations (for the period 2006) within the study area.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-14
FREQUENCY OF EXCEEDANCE OF HOURLY NO2 LIMIT OF 200 µg/m³
ALL CURRENT SOURCES
HIGHEST DAILY AVERAGE INHALABLE PARTICULATE CONCENTRATIONS (µg/m³)
ALL CURRENT SOURCES
152
0
0
1
1
5
153
50 µg/m³
75 µg/m³
180 µg/m³
1 hour
4 hours
18 hours
0km
20km
40km
60km
80km
0km
20km
40km
60km
80km
Comparison of simulated highest daily (99.7th
Figure 7-17:
Comparison of simulated frequency of exceedance Figure 7-18:
of the hourly nitrogen dioxide SANS limit (proposed SA standard) of percentile) inhalable particulate concentrations with measured highest
200 µg/m³ with measured frequencies (for the period 2006).
daily concentrations (for the period 2006) within the study area.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-15
ANNUAL AVERAGE INHALABLE PARTICULATE CONCENTRATIONS (µg/m³)
ALL CURRENT SOURCES
FREQUENCY OF EXCEEDANCE OF DAILY PM10 LIMIT OF 75 µg/m³
ALL CURRENT SOURCES
154
66
196
180
41
50
10 µg/m³
40 µg/m³
60 µg/m³
0km
56
24
1 day
5 days
35 days
20km
40km
60km
80km
0km
20km
40km
60km
80km
Comparison of simulated frequency of exceedance
Figure 7-19:
Comparison of simulated annual average inhalable Figure 7-20:
particulate concentrations with measured annual average of the daily inhalable particulate SANS limit (proposed SA standard) of
75 µg/m³ with measured frequencies (for the period 2006) within the
concentrations (for the period 2006) within the study area.
study area.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-16
7.2.3
Comparison of Measured and Modelled Inhalable Particulate
At Orange Farm, the predicted ground level concentration compared well to monitored data
for highest hourly and daily ground level concentrations, but under predicted on annual
averages.
The predicted concentrations at the Leitrim monitoring station were comparative to monitored
data with the exception of the annual averaging period of 2005.
Predicted ground level concentrations at Makalu correlated well for all averaging periods.
7.2.4
Summary of Measured versus Modelled Results
In general, a good correlation was found between modelled and monitored concentrations for
the short and medium term exposures. This confirms that the model is interpreting the zones
of impact correctly and the concentrations related to short-term health exceedance impacts.
Over the long term (annual averages) the ground level concentrations were generally under
predicted due to sources that could not be accounted for in the current study. These sources
would include agricultural activities and biomass burning as well as sources outside the study
area that would have an impact within the Vaal Airshed due to trans-boundary transportation
of pollutants.
The hourly and daily frequency of SO2 exceedances provided by the model is notably under
predicting the monitored number of exceedances (especially at the Sasol monitoring
stations). Similarly, the daily frequency of exceedances modelled is under predicted when
compared to monitored exceedances for inhalable particulate concentrations. Spatially,
however, the model has interpreted the areas of highest concentration exceedance fairly
accurately.
7.3
Compliance with Ambient Air Quality Guidelines/Standards
In the comparison of simulated ambient pollutant concentrations due to the current activities
within the Vaal Airshed, reference is made to the current SA standards as well as the SANS
limits (proposed SA standards) and “best practice” EC limits.
In assessing compliance of current baseline operations attention is paid to cumulative air
pollutant concentrations due to all quantified emissions within the Vaal Airshed. Where
applicable, emphasis was placed on:
•
the magnitude of the exceedance (i.e. extent to which pollutant concentrations
exceed the permissible limit value);
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-17
•
the frequency of exceedance (i.e. how many times, given as hours or days a year,
air quality limit values are exceeded); and
•
the spatial extent of exceedances (i.e. the area over which frequencies of
exceedance are expected to occur.)
The dispersion results are represented in Table 7-7 as the highest (99.99th percentile for
hourly averaging periods and 99.7th percentile for daily averaging periods) predicted
cumulative concentrations in the Vaal Airshed in comparison to the relevant ambient air
quality standards/limits. The table includes the predicted ground level concentrations and
the relevant air quality standards/limits. Section 7.1 includes the isopleth plots indicating the
concentration contours. It should be noted that the plots reflecting hourly and daily averaging
periods contain second maximum predicted ground level concentrations, for those averaging
periods, over the entire period for which simulations were undertaken. It is therefore possible
that even though a high hourly or daily average concentration is predicted to occur at certain
locations, that this may only be true for one hour or one day during the year.
Predicted air pollutant concentrations and frequencies of exceedance due exclusively to
current conditions are summarised in Tables 7-7. The spatial extent of exceedances of
sulphur dioxide, nitrogen dioxide and inhalable particulate limits are given in Figures 7-21, 722, 7-23 and 7-24, respectively.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-18
Sensitive
Receptor
Table 7-7:
Predicted maximum air pollutant concentrations due to all source activity within the Vaal Airshed based on 2004, 2005 and 2006
meteorological conditions (h).
Pollutant
Johannesburg (g)
Sulphur
Dioxide
Nitrogen
Dioxide
Inhalable
Particulate
Matter
Averaging period
Calculated 10-minute average
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 350µg/m³ (hours/year)
Frequency of daily exceedance of 125µg/m³ (days/year)
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 376µg/m³ (hours/year)
Frequency of hourly exceedance of 288µg/m³ (hours/year)
Frequency of hourly exceedance of 244µg/m³ (hours/year)
Frequency of hourly exceedance of 200µg/m³ (hours/year)
Highest daily average (b)
Annual average
Frequency of daily exceedance of 180µg/m³ (days/year)
Frequency of daily exceedance of 127µg/m³ (days/year)
Frequency of daily exceedance of 100µg/m³ (days/year)
Frequency of daily exceedance of 75µg/m³ (days/year)
Frequency of daily exceedance of 50µg/m³ (days/year)
Predicted
Maximum
Concentrations
(µg/m³)/ No. of
exceedances
Current SA
Standards
(µg/m³)
1560
1090
243
55
400
70
500
100
28
12
40
80
240
580
110
55
88
120
170
230
500
350
125
50
376
188
94
180
60
-
SANS Limits
(proposed SA
standards)
(µg/m³) /
proposed
frequency of
exceedance
500
350
125
50
88(c),44(d),9(e)
4(c),2(d),1(e)
200
40
0(c)
88(d)
44(e)
9(f)
75
40
0(c)
88(d)
44(e)
9(f)
-
EC Limits
(µg/m³) /
allowable
frequency of
exceedance
350
125
50
24
3
200
40
18
50
40
35
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-19
Sensitive
Receptor
Pollutant
Sulphur
Dioxide
Soweto
Nitrogen
Dioxide
Lenasia
Inhalable
Particulate
Matter
Sulphur
Dioxide
Averaging period
Calculated 10-minute average
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 350µg/m³ (hours/year)
Frequency of daily exceedance of 125µg/m³ (days/year)
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 376µg/m³ (hours/year)
Frequency of hourly exceedance of 288µg/m³ (hours/year)
Frequency of hourly exceedance of 244µg/m³ (hours/year)
Frequency of hourly exceedance of 200µg/m³ (hours/year)
Highest daily average (b)
Annual average
Frequency of daily exceedance of 180µg/m³ (days/year)
Frequency of daily exceedance of 127µg/m³ (days/year)
Frequency of daily exceedance of 100µg/m³ (days/year)
Frequency of daily exceedance of 75µg/m³ (days/year)
Frequency of daily exceedance of 50µg/m³ (days/year)
Calculated 10-minute average
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 350µg/m³ (hours/year)
Frequency of daily exceedance of 125µg/m³ (days/year)
Predicted
Maximum
Concentrations
(µg/m³)/ No. of
exceedances
Current SA
Standards
(µg/m³)
644
450
85
25
7
0
160
38
15
0
0
0
0
150
44
0
10
25
53
93
644
450
65
7
20
0
500
350
125
50
376
188
94
180
60
500
350
125
50
-
SANS Limits
(proposed SA
standards)
(µg/m³) /
proposed
frequency of
exceedance
500
350
125
50
88(c),44(d),9(e)
4(c),2(d),1(e)
200
40
0(c)
88(d)
44(e)
9(f)
75
40
0(c)
88(d)
44(e)
9(f)
500
350
125
50
88(c),44(d),9(e)
(c) (d) (e)
4 ,2 ,1
EC Limits
(µg/m³) /
allowable
frequency of
exceedance
350
125
50
24
3
200
40
18
50
40
35
350
125
50
24
3
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-20
Sensitive
Receptor
Pollutant
Nitrogen
Dioxide
Inhalable
Particulate
Matter
Ennerdale
Sulphur
Dioxide
Nitrogen
Dioxide
Averaging period
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 376µg/m³ (hours/year)
Frequency of hourly exceedance of 288µg/m³ (hours/year)
Frequency of hourly exceedance of 244µg/m³ (hours/year)
Frequency of hourly exceedance of 200µg/m³ (hours/year)
Highest daily average (b)
Annual average
Frequency of daily exceedance of 180µg/m³ (days/year)
Frequency of daily exceedance of 127µg/m³ (days/year)
Frequency of daily exceedance of 100µg/m³ (days/year)
Frequency of daily exceedance of 75µg/m³ (days/year)
Frequency of daily exceedance of 50µg/m³ (days/year)
Calculated 10-minute average
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 350µg/m³ (hours/year)
Frequency of daily exceedance of 125µg/m³ (days/year)
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 376µg/m³ (hours/year)
Frequency of hourly exceedance of 288µg/m³ (hours/year)
Frequency of hourly exceedance of 244µg/m³ (hours/year)
Predicted
Maximum
Concentrations
(µg/m³)/ No. of
exceedances
Current SA
Standards
(µg/m³)
200
37
5.5
0
0
0
7
90
9
0
0
0
5
10
715
500
100
25
15
0
360
45
5.5
0
1
1
376
188
94
180
60
500
350
125
50
376
188
94
-
SANS Limits
(proposed SA
standards)
(µg/m³) /
proposed
frequency of
exceedance
200
40
0(c)
88(d)
44(e)
9(f)
75
40
0(c)
88(d)
44(e)
9(f)
500
350
125
50
(c)
88 ,44(d),9(e)
4(c),2(d),1(e)
200
40
0(c)
88(d)
(e)
44
EC Limits
(µg/m³) /
allowable
frequency of
exceedance
200
40
18
50
40
35
350
125
50
24
3
200
40
-
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-21
Sensitive
Receptor
Pollutant
Inhalable
Particulate
Matter
Orange Farm
Sulphur
Dioxide
Nitrogen
Dioxide
Inhalable
Particulate
Matter
Averaging period
Frequency of hourly exceedance of 200µg/m³ (hours/year)
Highest daily average (b)
Annual average
Frequency of daily exceedance of 180µg/m³ (days/year)
Frequency of daily exceedance of 127µg/m³ (days/year)
Frequency of daily exceedance of 100µg/m³ (days/year)
Frequency of daily exceedance of 75µg/m³ (days/year)
Frequency of daily exceedance of 50µg/m³ (days/year)
Calculated 10-minute average
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 350µg/m³ (hours/year)
Frequency of daily exceedance of 125µg/m³ (days/year)
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 376µg/m³ (hours/year)
Frequency of hourly exceedance of 288µg/m³ (hours/year)
Frequency of hourly exceedance of 244µg/m³ (hours/year)
Frequency of hourly exceedance of 200µg/m³ (hours/year)
Highest daily average (b)
Annual average
Frequency of daily exceedance of 180µg/m³ (days/year)
Frequency of daily exceedance of 127µg/m³ (days/year)
Frequency of daily exceedance of 100µg/m³ (days/year)
Predicted
Maximum
Concentrations
(µg/m³)/ No. of
exceedances
Current SA
Standards
(µg/m³)
2
160
38
0
1
1
40
80
1073
750
200
45
100
18
360
42
7.5
0
1
1
3
280
60
9
30
42
180
60
500
350
125
50
376
188
94
180
60
-
SANS Limits
(proposed SA
standards)
(µg/m³) /
proposed
frequency of
exceedance
9(f)
75
40
0(c)
88(d)
44(e)
9(f)
500
350
125
50
88(c),44(d),9(e)
4(c),2(d),1(e)
200
40
0(c)
88(d)
44(e)
9(f)
75
40
0(c)
88(d)
(e)
44
EC Limits
(µg/m³) /
allowable
frequency of
exceedance
18
50
40
35
350
125
50
24
3
200
40
18
50
40
-
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-22
Sensitive
Receptor
Pollutant
Sulphur
Dioxide
Evaton
Nitrogen
Dioxide
Sebokeng
Inhalable
Particulate
Matter
Sulphur
Dioxide
Averaging period
Frequency of daily exceedance of 75µg/m³ (days/year)
Frequency of daily exceedance of 50µg/m³ (days/year)
Calculated 10-minute average
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 350µg/m³ (hours/year)
Frequency of daily exceedance of 125µg/m³ (days/year)
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 376µg/m³ (hours/year)
Frequency of hourly exceedance of 288µg/m³ (hours/year)
Frequency of hourly exceedance of 244µg/m³ (hours/year)
Frequency of hourly exceedance of 200µg/m³ (hours/year)
Highest daily average (b)
Annual average
Frequency of daily exceedance of 180µg/m³ (days/year)
Frequency of daily exceedance of 127µg/m³ (days/year)
Frequency of daily exceedance of 100µg/m³ (days/year)
Frequency of daily exceedance of 75µg/m³ (days/year)
Frequency of daily exceedance of 50µg/m³ (days/year)
Calculated 10-minute average
Highest hourly average (a)
Highest daily average (b)
Annual average
Predicted
Maximum
Concentrations
(µg/m³)/ No. of
exceedances
Current SA
Standards
(µg/m³)
70
120
930
650
130
32
30
5
310
40
6.5
0
2
3
9
280
50
10
15
27
55
100
544
380
80
22
500
350
125
50
376
188
94
180
60
500
350
125
50
SANS Limits
(proposed SA
standards)
(µg/m³) /
proposed
frequency of
exceedance
9(f)
500
350
125
50
88(c),44(d),9(e)
4(c),2(d),1(e)
200
40
0(c)
88(d)
44(e)
9(f)
75
40
0(c)
88(d)
44(e)
9(f)
500
350
125
50
EC Limits
(µg/m³) /
allowable
frequency of
exceedance
35
350
125
50
24
3
200
40
18
50
40
35
350
125
50
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-23
Sensitive
Receptor
Pollutant
Nitrogen
Dioxide
Inhalable
Particulate
Matter
Meyerton
Sulphur
Dioxide
Nitrogen
Dioxide
Averaging period
Frequency of hourly exceedance of 350µg/m³ (hours/year)
Frequency of daily exceedance of 125µg/m³ (days/year)
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 376µg/m³ (hours/year)
Frequency of hourly exceedance of 288µg/m³ (hours/year)
Frequency of hourly exceedance of 244µg/m³ (hours/year)
Frequency of hourly exceedance of 200µg/m³ (hours/year)
Highest daily average (b)
Annual average
Frequency of daily exceedance of 180µg/m³ (days/year)
Frequency of daily exceedance of 127µg/m³ (days/year)
Frequency of daily exceedance of 100µg/m³ (days/year)
Frequency of daily exceedance of 75µg/m³ (days/year)
Frequency of daily exceedance of 50µg/m³ (days/year)
Calculated 10-minute average
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 350µg/m³ (hours/year)
Frequency of daily exceedance of 125µg/m³ (days/year)
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 376µg/m³ (hours/year)
Predicted
Maximum
Concentrations
(µg/m³)/ No. of
exceedances
Current SA
Standards
(µg/m³)
5
0
300
32
6
0
1
1
5
3151
456
90
120
130
170
200
1002
700
30
7
2
0
200
23
4
0
376
188
94
180
60
500
350
125
50
376
188
94
-
SANS Limits
(proposed SA
standards)
(µg/m³) /
proposed
frequency of
exceedance
88(c),44(d),9(e)
4(c),2(d),1(e)
200
40
0(c)
88(d)
44(e)
9(f)
75
40
0(c)
88(d)
44(e)
9(f)
500
350
125
50
88(c),44(d),9(e)
4(c),2(d),1(e)
200
40
(c)
0
EC Limits
(µg/m³) /
allowable
frequency of
exceedance
24
3
200
40
18
50
40
35
350
125
50
24
3
200
40
-
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-24
Sensitive
Receptor
Pollutant
Inhalable
Particulate
Matter
Vereeniging
Sulphur
Dioxide
Nitrogen
Dioxide
Inhalable
Particulate
Matter
Averaging period
Frequency of hourly exceedance of 288µg/m³ (hours/year)
Frequency of hourly exceedance of 244µg/m³ (hours/year)
Frequency of hourly exceedance of 200µg/m³ (hours/year)
Highest daily average (b)
Annual average
Frequency of daily exceedance of 180µg/m³ (days/year)
Frequency of daily exceedance of 127µg/m³ (days/year)
Frequency of daily exceedance of 100µg/m³ (days/year)
Frequency of daily exceedance of 75µg/m³ (days/year)
Frequency of daily exceedance of 50µg/m³ (days/year)
Calculated 10-minute average
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 350µg/m³ (hours/year)
Frequency of daily exceedance of 125µg/m³ (days/year)
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 376µg/m³ (hours/year)
Frequency of hourly exceedance of 288µg/m³ (hours/year)
Frequency of hourly exceedance of 244µg/m³ (hours/year)
Frequency of hourly exceedance of 200µg/m³ (hours/year)
Highest daily average (b)
Annual average
Frequency of daily exceedance of 180µg/m³ (days/year)
Predicted
Maximum
Concentrations
(µg/m³)/ No. of
exceedances
Current SA
Standards
(µg/m³)
0
0
0
1095
200
70
100
110
135
170
1560
1090
60
10
6
0
350
32
5.5
0
1
1
3
420
90
30
180
60
500
350
125
50
376
188
94
180
60
-
SANS Limits
(proposed SA
standards)
(µg/m³) /
proposed
frequency of
exceedance
88(d)
44(e)
9(f)
75
40
0(c)
88(d)
44(e)
9(f)
500
350
125
50
88(c),44(d),9(e)
4(c),2(d),1(e)
200
40
0(c)
88(d)
44(e)
9(f)
75
40
(c)
0
EC Limits
(µg/m³) /
allowable
frequency of
exceedance
18
50
40
35
350
125
50
24
3
200
40
18
50
40
-
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-25
Sensitive
Receptor
Pollutant
Vanderbijlpark
Sulphur
Dioxide
Nitrogen
Dioxide
Inhalable
Particulate
Matter
Averaging period
Frequency of daily exceedance of 127µg/m³ (days/year)
Frequency of daily exceedance of 100µg/m³ (days/year)
Frequency of daily exceedance of 75µg/m³ (days/year)
Frequency of daily exceedance of 50µg/m³ (days/year)
Calculated 10-minute average
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 350µg/m³ (hours/year)
Frequency of daily exceedance of 125µg/m³ (days/year)
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 376µg/m³ (hours/year)
Frequency of hourly exceedance of 288µg/m³ (hours/year)
Frequency of hourly exceedance of 244µg/m³ (hours/year)
Frequency of hourly exceedance of 200µg/m³ (hours/year)
Highest daily average (b)
Annual average
Frequency of daily exceedance of 180µg/m³ (days/year)
Frequency of daily exceedance of 127µg/m³ (days/year)
Frequency of daily exceedance of 100µg/m³ (days/year)
Frequency of daily exceedance of 75µg/m³ (days/year)
Frequency of daily exceedance of 50µg/m³ (days/year)
Predicted
Maximum
Concentrations
(µg/m³)/ No. of
exceedances
Current SA
Standards
(µg/m³)
70
72
80
115
1145
800
85
25
8
0
488
36
8
0
1
2
7
1095
180
50
88
90
115
150
500
350
125
50
376
188
94
180
60
-
SANS Limits
(proposed SA
standards)
(µg/m³) /
proposed
frequency of
exceedance
88(d)
44(e)
9(f)
500
350
125
50
88(c),44(d),9(e)
4(c),2(d),1(e)
200
40
0(c)
88(d)
44(e)
9(f)
75
40
0(c)
88(d)
44(e)
9(f)
-
EC Limits
(µg/m³) /
allowable
frequency of
exceedance
35
350
125
50
24
3
200
40
18
50
40
35
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-26
Sensitive
Receptor
Pollutant
Sulphur
Dioxide
Sasolburg
Nitrogen
Dioxide
Inhalable
Particulate
Matter
Averaging period
Calculated 10-minute average
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 350µg/m³ (hours/year)
Frequency of daily exceedance of 125µg/m³ (days/year)
Highest hourly average (a)
Highest daily average (b)
Annual average
Frequency of hourly exceedance of 376µg/m³ (hours/year)
Frequency of hourly exceedance of 288µg/m³ (hours/year)
Frequency of hourly exceedance of 244µg/m³ (hours/year)
Frequency of hourly exceedance of 200µg/m³ (hours/year)
Highest daily average (b)
Annual average
Frequency of daily exceedance of 180µg/m³ (days/year)
Frequency of daily exceedance of 127µg/m³ (days/year)
Frequency of daily exceedance of 100µg/m³ (days/year)
Frequency of daily exceedance of 75µg/m³ (days/year)
Frequency of daily exceedance of 50µg/m³ (days/year)
Predicted
Maximum
Concentrations
(µg/m³)/ No. of
exceedances
Current SA
Standards
(µg/m³)
1545
1080
80
18
10
0
280
32
6.5
0
0
1
2
800
200
80
120
122
150
180
500
350
125
50
376
188
94
180
60
-
SANS Limits
(proposed SA
standards)
(µg/m³) /
proposed
frequency of
exceedance
500
350
125
50
88(c),44(d),9(e)
4(c),2(d),1(e)
200
40
0(c)
88(d)
44(e)
9(f)
75
40
0(c)
88(d)
44(e)
9(f)
-
EC Limits
(µg/m³) /
allowable
frequency of
exceedance
350
125
50
24
3
200
40
18
50
40
35
(a) 99.99th percentile
th
(b) 99.7 percentile
(c) Air Quality Act, Schedule 2, to be complied by immediately (as provided in the draft document on 24 October 2007). It should be noted that this document has not been
finalised.
(d) National Ambient Air Quality Standard – interim level 1, to be complied by 2012 (as provided in the draft document on 24 October 2007). It should be noted that this
document has not been finalised.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-27
(e) National Ambient Air Quality Standard – interim level 2, to be complied by 2017 (as provided in the draft document on 24 October 2007). It should be noted that this
document has not been finalised.
(f) National Ambient Air Quality Standard, to be complied by 2022 (as provided in the draft document on 24 October 2007). It should be noted that this document has not been
finalised.
(g) Highest concentrations within Johannesburg within the study area.
(h) Exceedances of all relevant guidelines are provided in bold.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-28
FREQUENCY OF EXCEEDANCE OF HOURLY SO2 LIMIT OF 350 µg/m³
ALL CURRENT SOURCES
88 hours/year [Draft: Air Quality Act, Schedule 2, complied by immediately]
44 hours/year [Draft: National Ambient Air Quality Standard - interim level 1, 2012]
9 hours/year [Draft: National Ambient Air Quality Standard - interim level 2, 2017]
24 hours/year [EC allowable frequency]
0km
20km
40km
60km
80km
FREQUENCY OF EXCEEDANCE OF DAILY SO2 LIMIT OF 125 µg/m³
ALL CURRENT SOURCES
4 days/year [Draft: Air Quality Act, Schedule 2, complied by immediately]
2 days/year [Draft: National Ambient Air Quality Standard - interim level 1, 2012]
1 days/year [Draft: National Ambient Air Quality Standard - interim level 2, 2017]
3 days/year [EC allowable frequency]
0km
20km
40km
60km
80km
Figure 7-21:
Hourly predicted exceedance of the SA standards for Figure 7-22:
Daily predicted exceedance of the SA standards for
sulphur dioxide of 350 µg/m³ within the study area.
sulphur dioxide of 125 µg/m³ within the study area.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-29
FREQUENCY OF EXCEEDANCE OF VARIOUS HOURLY NO2 CONCENTRATIONS
ALL CURRENT SOURCES
88 hours/year [Draft: National Ambient Air Quality Standard - IL1 (288 µg/m³), 2012]
44 hours/year [Draft: National Ambient Air Quality Standard - IL2 (244 µg/m³), 2017]
9 hours/year [Draft: National Ambient Air Quality Standard (200 µg/m³), 2022]
18 hours/year [EC allowable frequency (200 µg/m³)]
0km
20km
40km
60km
80km
FREQUENCY OF EXCEEDANCE OF VARIOUS DAILY PM10 CONCENTRATIONS
ALL CURRENT SOURCES
88 days/year [Draft: National Ambient Air Quality Standard - IL1 (127 µg/m³), 2012]
44 days/year [Draft: National Ambient Air Quality Standard - IL2 (100 µg/m³), 2017]
9 days/year [Draft: National Ambient Air Quality Standard (75 µg/m³), 2022]
35 days/year [EC allowable frequency (50 µg/m³)]
0km
20km
40km
60km
80km
Figure 7-23:
Hourly
exceedance
of
various
relevant Figure 7-24:
Daily
exceedance
of
of
various
relevant
standards/limits for nitrogen dioxide concentrations within the study standards/limits for inhalable particulate concentrations within the
area.
study area.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-30
The main findings are as follows:
•
Sulphur Dioxide – Sulphur dioxide short-term SA standards, SANS limits and EC
limits are significantly exceeded due to current emitting sources in terms of the
magnitude. However, when allowable frequency of exceedance is assessed, areas
of Johannesburg, Orange Farm and Evaton are predicted to exceed the EC
allowable hourly and daily frequency of 24 and 3 respectively as well as the
proposed National Ambient Air Quality Standard allowable hourly and daily
frequency of 9 and 1 respectively (as provided in the draft document (for discussion
purposes only) on 24 October 2007).
•
Nitrogen dioxide - Ambient hourly nitrogen dioxide SA standard, SANS limit and
EC limit exceedances occur mainly over the built up areas of the Vaal Airshed
(numbers of hourly exceedances over the Vaal Airshed, however, are within the
limit permitted by the EC and proposed National Ambient SA Air Quality Standards
(draft document on 24 October 2007) of 18 times and 9 times per year respectively
(Figure 7-23)).
•
Inhalable particulates – Ambient inhalable particulate daily SA standards, SANS
limits and EC limits are significantly exceeded due to current emitting sources in
terms of the magnitude, frequency and spatial extent of exceedance (Figure 7-24).
The main conclusion reached is that current baseline emissions are associated with
significant non-compliance with relevant ambient inhalable particulate matter target
levels. Ambient short-term sulphur dioxide concentrations exceed the hourly target levels
over large areas of the Vaal Airshed. The occurrences of these hourly exceedances are
however, generally within the limit permitted by the EC and proposed National Ambient SA
Air Quality Standards (draft document on 24 October 2007) with the exception of
Johannesburg, Orange Farm and Evaton. Ambient nitrogen dioxide concentrations exceed
the hourly target levels over the built up areas of the Vaal Airshed. The occurrences of these
hourly exceedances are however, generally infrequent (within the limit permitted by the EC
and proposed National Ambient SA Air Quality Standards (draft document on 24 October
2007) of 18 and 9 times per year respectively).
7.4
Priority Areas
Priority areas are identified based on the predicted ambient air concentrations from the
priority pollutants and exposure potential.
The prioritisation of sources is ranked on the basis of impacts rather than the extent of their
emissions. This ensures that the main contributing sources resulting in non-compliance with
the Vaal Airshed ambient air quality targets and hence pose the greatest risk to human
health and the environment, be addressed as priority. In addition, this will clearly define the
problems within the area.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-31
7.4.1
Exposure Potential of Predicted Ambient Air Concentrations
In order to determine the significance of the areas where the ambient air quality standards or
Vaal Airshed ambient air quality objectives are exceeded, the predicted contours were
superimposed onto the population density (based on 2001 Census). A synopsis of the
findings of this analysis is presented in Table 7-8 for inhalable particulate matter, sulphur
dioxide and nitrogen dioxide.
Table 7-8:
Number of people residing in non-compliance (a) areas within Vaal Airshed
exposed to sulphur dioxide, inhalable particulate and nitrogen dioxide concentrations.
Source Group
All quantifiable sources
No. of Persons Residing within Vaal Airshed Predicted to Exceed the
SANS limits (assessing the limits in conjunction with the proposed
National Ambient Air Quality Standards, draft document 24 October
2007 (b))
9 exceedances
Single
9 exceedances
9 exceedances of
of the SO2
exceedance of
of the NO2
PM10 daily
hourly
SO2 daily
hourly
75 µg/m³ Limit
350 µg/m³ Limit 125 µg/m³ Limit 200 µg/m³ Limit
52 936
3 930
0
860 584
(a) With accordance to the SANS limits (proposed SA standards)
(b) The draft document drafted on the 24 October 2004 was for discussion purposes only.
More than 860 000 people are currently exposed to more than 9 exceedances of the
proposed inhalable particulate SA standards of 75 µg/m³. A total of ~53 000 people are
exposed to more than 9 hourly SO2 exceedances of the SA standard of 350 µg/m³ and
~4 000 people are exposed to more than a single daily exceedance of the SA sulphur dioxide
standard of 125 µg/m³. Less than 9 hourly exceedances of the proposed SA nitrogen dioxide
standards are currently predicted over the Vaal Airshed.
7.4.2
“Hot Spot” Areas
Although ambient monitoring data indicated the pollutants of concern and the ambient
concentrations associated with these pollutants, monitoring stations are single points
reflecting a specific geographic location. Dispersion modelling on the other hand is a useful
tool in determining the zones of impact and the magnitude of the impact zone.
From predicted ground level concentrations through dispersion modelling, verified with
ambient monitored data, the main pollutant of concern within the Vaal Airshed is inhalable
particulates. Six priority areas were identified within the Vaal Airshed based on highest
inhalable particulate concentration zones or “hotspots” (Figure 7-25). The areas were also
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-32
selected to correspond with impact zones due to acute exposures to sulphur dioxide and
nitrogen dioxide.
The sensitive receptors together with the emissions sources and main pollutants of concern
are provided in Table 7-9 for each of the identified priority zones.
FREQUENCY OF EXCEEDANCE OF VARIOUS DAILY PM10 CONCENTRATIONS
ALL CURRENT SOURCES
6
5
3
4
2
1
88 days/year [Draft: National Ambient Air Quality Standard - IL1 (127 µg/m³), 2012]
44 days/year [Draft: National Ambient Air Quality Standard - IL2 (100 µg/m³), 2017]
9 days/year [Draft: National Ambient Air Quality Standard (75 µg/m³), 2022]
35 days/year [EC allowable frequency (50 µg/m³)]
0km
20km
40km
60km
80km
Figure 7-25: Six priority “hotspot” areas identified within the Vaal Airshed based on
predicted inhalable particulate ground level concentrations.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-33
Table 7-9:
Hotspot
Zone
1
2
3
4
5
6
Priority “hotspot” zones within the Vaal Airshed indicating the sensitive receptors and the main contributing sources.
Sensitive Receptors
within Zone
Emission Sources within the Zone
Additional sources not quantified
and included
Pollutants of
concern
Residential areas of
Sasolburg, Zamdela and
Coalbrook
Located just south of the
residential area of
Vereeniging – no residential
areas included in this zone
but potential for
environmental impacts
Residential areas of
Vanderbijlpark and
Sebokeng
Industrial activities (viz. Sasol, Omnia and
Natref), mining activities (viz. Sigma Colliery)
and domestic fuel burning
Mining activities (viz. New Vaal Colliery),
power generation (viz. Lethabo Power
Station) and other industrial activities
Agricultural activities and biomass
burning
Industrial activities (viz. Iron and Steel
process (ArcelorMittal and Davesteel),
commercial boilers and other smaller
industrial activities), and domestic fuel
burning
PM10, SO2,
NO2, odours,
Ozone and
VOCs
Figure 7-28
Residential areas of
Vereeniging and Meyerton
Industrial activities (viz. ArcelorMittal Vaal
Works, ArcelorMittal Klip Works, Metalloys,
commercial boilers, and other small industrial
activities) and domestic fuel burning
Domestic fuel burning
Industrial activities just north of
ArcelorMittal (viz. a ceramics
manufacturing facility, a brickworks
and a quarry), water treatment works,
biomass burning and agricultural
activities
Agricultural activities and large areas
of biomass burning
PM10, SO2
NO2, Ozone
and VOCs
Figure 7-29
Large areas of biomass burning
PM10, SO2
NO2 and
VOCs
PM10, SO2,
NO2 and
VOCs
Figure 7-30
Residential areas of Orange
Farm, Evaton and
Ennerdale
Residential area of Soweto
Domestic fuel burning
Agricultural activities and water
treatment works which may result in
odour impacts
Wind blown dust from gold tailings
dams
PM10, SO2
NO2, H2S
and VOCs
PM10, SO2,
and NO2.
Figure
indicating
Hotspot Zone
Figure 7-26
Figure 7-27
Figure 7-31
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-34
Figure 7-26: Sources of potential emissions within the identified priority “hotspot” zone 1
(including sensitive receptors of Sasolburg, Coalbrook and Zamdela) within the Vaal Airshed.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-35
Figure 7-27: Sources of potential emissions within the identified priority “hotspot” zone 2
within the Vaal Airshed.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-36
Figure 7-28: Sources of potential emissions within the identified priority “hotspot” zone 3
(including sensitive receptors of Vanderbijlpark and Sebokeng) within the Vaal Airshed.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-37
Figure 7-29: Sources of potential emissions within the identified priority “hotspot” zone 4
(including sensitive receptors of Vereeniging and Meyerton) within the Vaal Airshed.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-38
Figure 7-30: Sources of potential emissions within the identified priority “hotspot” zone 5
(including sensitive receptors of Orange Farm, Evaton and Ennerdale) within the Vaal
Airshed.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-39
Figure 7-31: Sources of potential emissions within the identified priority “hotspot” zone 6 (including the sensitive receptor of Soweto) within the
Vaal Airshed.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-40
The contributing emission sources as well as the long-term ground level concentrations per
priority “hotspot” zone have been identified and are provided in Figure 7-33 to Figure 7-38.
In order to assess the predicted ground level concentration contributions within the area, a
number of discreet receptors within the zones were assessed (see Figure 7-32). The
sources identified as contributing to ambient air quality consists of industrial activities, mining
activities, domestic fuel burning and vehicle activities. It should be noted that the particulate
emissions from Sasol were provided as total suspended particulates from their stack sources
and as a conservative approach the total suspended particulates were assessed as inhalable
particulate fraction.
0km
20km
40km
60km
80km
Figure 7-32: Receptors assessed for the long-term ground level concentrations
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-41
7.4.2.1 “Hot Spot” Zone 1 (Sasolburg, Coalbrook, Zamdela)
At priority “hotspot” zone 1 the main sources of emissions are petrochemical processes. For
sulphur dioxide and oxides of nitrogen petrochemical processes contribute more than 90% of
the emissions. For inhalable particulate emissions within the area, petrochemical processes
contribute 70% and mining activities 18%. The main contributors of sulphur dioxide and
nitrogen dioxide ground level concentrations in ranking order is a combination of
petrochemical processes, power generation, iron and steel processes and domestic fuel
burning. For inhalable particulate impacts the main contributing source is mining operations
(>86%) (Figure 7-33).
7.4.2.2 “Hot Spot” Zone 2 (New Vaal, Eskom Area)
For priority “hotspot” zone 2, emissions are due primarily to power generation and mining
activities in terms of inhalable particulates. Annual average ground level concentrations for
sulphur dioxide and nitrogen dioxide are mainly from a combination of iron and steel
processes, power generation, petrochemical processes and domestic fuel burning. Inhalable
particulate ground level concentrations occur mainly due to small industries, fertilizer
processes and mining activities (Figure 7-34).
7.4.2.3 “Hot Spot” Zone 3 (Vanderbijlpark, Sebokeng)
Priority “hotspot” zone 3 is situated in an area of elevated industrial activity. The main
sources of emissions are from iron and steel processes (contributing more than 78% of
sulphur dioxide, oxides of nitrogen and inhalable particulate matter) and vehicle activity
(contributing 20% of inhalable particulates). For sulphur dioxide and nitrogen dioxide ground
level concentrations, the main contributing sources in ranked order are iron and steel
processes and then a combination of power generation, petrochemical processes and
domestic fuel burning. For inhalable particulates, the main sources of annual ground level
concentrations are iron and steel processes (50%) and other smaller industrial activities
(45%) (Figure 7-35).
7.4.2.4 “Hot Spot” Zone 4 (Vereeniging, Meyerton)
The main sources of emissions within the priority “hotspot” zone 4 are vehicles to the
contribution of sulphur dioxide and nitrogen dioxide. For inhalable particulate emissions the
main contributing sources consist of smaller industrial activities (49%) and ferroalloy
processes (39%). Nitrogen dioxide and sulphur dioxide annual ground level concentrations
are due mainly to iron and steel processes with a combination of petrochemical processes,
power generation, domestic fuel burning and vehicle activity (for oxides of nitrogen only)
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-42
contributing to a lesser extent. The inhalable particulate impacts are due mainly to (in
ranking order); smaller industrial activities, ferroalloy processes, iron and steel processes
and mining activities (Figure 7-36).
7.4.2.5 “Hot Spot” Zone 5 (Orange Farm, Evaton, Ennerdale)
Priority “hotspot” zone 5 consists of a lower income population group with the main source of
inhalable particulate and sulphur dioxide emissions being domestic fuel burning. Vehicle
tailpipe emissions contribute <70% of the nitrogen dioxide emissions in the area. The main
source of long-term ground level concentrations are from domestic fuel burning for sulphur
dioxide and inhalable particulates (>90%). Nitrogen dioxide ground level concentrations are
made up of domestic fuel burning (58%), and to a lesser extent iron and steel processes
(21%), power generation (9%), petrochemical processes (7%) and vehicle exhaust (5%)
(Figure 7-37).
7.4.2.6 “Hot Spot” Zone 6 (Soweto)
Priority “hotspot” zone 6 is situated in an area of domestic fuel burning and vehicle activity.
Long-term ground level concentrations are therefore mainly due to domestic fuel burning
contributing >87% for sulphur dioxide and inhalable particulates and 32% for nitrogen
dioxide. Other sources contributing to annual ground level concentrations are vehicle activity
(59% for nitrogen dioxide and 10% for inhalable particulates) (Figure 7-38).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-43
Emissions
Long-term Ground Level Concentrations
Sulphur Dioxide
4%
29%
53%
99.6%
Oxides of Nitrogen
13%
Nitrogen Dioxide
3%
16%
44%
35%
96%
Inhalable Particulates
18%
7%
6%
86%
70%
LEGEND
Power Generation
Iron and Steel Process
Petrochemical Processes
Ferroalloy Processes
Phosphate Fertilizer Processes
Smaller Industries
Vehicles
Mines
Domestic Fuel Burning
Figure 7-33: Predicted source contributions to total annual sulphur dioxide, nitrogen dioxide
and inhalable particulate emissions and concentrations at various impact contribution for
identified priority “hotspot” zone 1 (including sensitive receptors of Sasolburg, Coalbrook and
Zamdela) within the Vaal Airshed.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-44
Emissions
Long-term Ground Level Concentrations
Sulphur Dioxide
16%
23%
16%
44%
100%
Oxides of Nitrogen
Nitrogen Dioxide
6%
9%
9%
18%
99.7%
56%
Inhalable Particulates
37%
34%
63%
4%
23%
38%
LEGEND
Power Generation
Iron and Steel Process
Petrochemical Processes
Ferroalloy Processes
Phosphate Fertilizer Processes
Smaller Industries
Vehicles
Mines
Domestic Fuel Burning
Figure 7-34: Predicted source contributions to total annual sulphur dioxide, nitrogen dioxide
and inhalable particulate emissions and concentrations at various impact contribution for
identified priority “hotspot” zone 2 within the Vaal Airshed.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-45
Emissions
Long-term Ground Level Concentrations
Sulphur Dioxide
9%
9%
11%
70%
99%
Oxides of Nitrogen
Nitrogen Dioxide
6%
7%
94%
17%
9%
10%
56%
Inhalable Particulates
20%
78%
45%
50%
LEGEND
Power Generation
Iron and Steel Process
Petrochemical Processes
Ferroalloy Processes
Phosphate Fertilizer Processes
Smaller Industries
Vehicles
Mines
Domestic Fuel Burning
Figure 7-35: Predicted source contributions to total annual sulphur dioxide, nitrogen dioxide
and inhalable particulate emissions and concentrations at various impact contribution for
identified priority “hotspot” zone 3 (including sensitive receptors of Vanderbijlpark and
Sebokeng) within the Vaal Airshed.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-46
Emissions
Long-term Ground Level Concentrations
Sulphur Dioxide
15%
22%
10%
13%
17%
50%
68%
Oxides of Nitrogen
Nitrogen Dioxide
9%
9%
7%
10%
17%
90%
56%
Inhalable Particulates
8%
49%
4%
4%
39%
7%
25%
62%
LEGEND
Power Generation
Iron and Steel Process
Petrochemical Processes
Ferroalloy Processes
Phosphate Fertilizer Processes
Smaller Industries
Vehicles
Mines
Domestic Fuel Burning
Figure 7-36: Predicted source contributions to total annual sulphur dioxide, nitrogen dioxide
and inhalable particulate emissions and concentrations at various impact contribution for
identified priority “hotspot” zone 4 (including sensitive receptors of Vereeninging and
Meyerton) within the Vaal Airshed.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-47
Emissions
Long-term Ground Level Concentrations
Sulphur Dioxide
91%
97%
Oxides of Nitrogen
Nitrogen Dioxide
9%
29%
21%
58%
71%
5%
7%
Inhalable Particulates
12%
88%
90%
LEGEND
Power Generation
Iron and Steel Process
Petrochemical Processes
Ferroalloy Processes
Phosphate Fertilizer Processes
Smaller Industries
Vehicles
Mines
Domestic Fuel Burning
Figure 7-37: Predicted source contributions to total annual sulphur dioxide, nitrogen dioxide
and inhalable particulate emissions and concentrations at various impact contribution for
identified priority “hotspot” zone 5 (including sensitive receptors of Orange Farm, Evaton and
Ennerdale) within the Vaal Airshed.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-48
Emissions
Long-term Ground Level Concentrations
Sulphur Dioxide
5%
38%
61%
91%
Oxides of Nitrogen
Nitrogen Dioxide
32%
98%
5% 3%
59%
Inhalable Particulates
10%
32%
68%
87%
LEGEND
Power Generation
Iron and Steel Process
Petrochemical Processes
Ferroalloy Processes
Phosphate Fertilizer Processes
Smaller Industries
Vehicles
Mines
Domestic Fuel Burning
Figure 7-38: Predicted source contributions to total annual sulphur dioxide, nitrogen dioxide
and inhalable particulate emissions and concentrations at various impact contribution for
identified priority “hotspot” zone 6 (including sensitive receptors of Soweto) within the Vaal
Airshed.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
7-49
8
CHAPTER 8
CONCLUSIONS
8.1
Priority Pollutants within the Vaal Airshed
Pollutants in South Africa for which health based standards exists include particulate matter
(both total suspended particulates and particulates with a diameter of less than 10
micrometer (inhalable particulate matter)), sulphur dioxide, oxides of nitrogen, ozone and
lead. The proposed standards include carbon monoxide and benzene.
Based on the available monitoring data, the major findings of the air quality assessment
indicate that:
• Particulate concentrations are elevated over most areas of the Vaal Triangle,
particularly in residential areas where domestic fuel burning occurs and areas
neighbouring major industrial operations.
• Sulphur dioxide concentrations are reduced in both the residential and industrial
monitoring stations, although exceedances were recorded on several occasions at
Jabavu, Orange Farm and in Sasolburg.
• Nitrogen dioxide concentrations are low in the Vaal Triangle, although a seasonal
signature is observed in nitrogen dioxide concentrations.
Nitrogen dioxide
concentrations have a regional impact within the Vaal Triangle.
• Carbon monoxide concentrations are not considered to be significant in the Vaal
Triangle.
• Ozone concentrations are elevated in areas surrounding major industrial operations
with exceedances of the one hour average target recorded on numerous occasions.
Ozone concentrations measured at Makalu are representative of known
background concentrations in South Africa.
Based on predicted dispersion modelled data, the major findings of the air quality
assessment indicate that:
•
Sulphur dioxide short-term SA standards, SANS limits and EC limits are
significantly exceeded due to current emitting sources in terms of the magnitude.
However, when allowable frequency of exceedance is assessed, areas of
Johannesburg, Orange Farm and Evaton are predicted to exceed the EC allowable
hourly and daily frequency of 24 and 3 respectively as well as the proposed
National Ambient Air Quality Standard allowable hourly and daily frequency of 9
and 1 respectively (as provided in the draft document (for discussion purposes
only) on 24 October 2007).
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
8-1
•
Ambient hourly nitrogen dioxide SA standard, SANS limit and EC limit exceedances
occur mainly over the built up areas of the Vaal Airshed (numbers of hourly
exceedances over the Vaal Airshed, however, are within the limit permitted by the
EC and proposed National Ambient SA Air Quality Standards (draft document on
24 October 2007) of 18 times and 9 times per year respectively (Figure 7-23)).
•
Ambient inhalable particulate daily SA standards, SANS limits and EC limits are
significantly exceeded due to current emitting sources in terms of the magnitude,
frequency and spatial extent of exceedance (Figure 7-24).
The main conclusion reached is that current baseline emissions are associated with
significant non-compliance with relevant ambient inhalable particulate matter target
levels. Ambient short-term sulphur dioxide concentrations exceed the hourly target levels
over large areas of the Vaal Airshed. Although the occurrences of these hourly exceedances
are predicted to be within the limit permitted by the EC and proposed National Ambient SA
Air Quality Standards (draft document on 24 October 2007) with the exception of
Johannesburg, Orange Farm and Evaton, exceedances of the permitted EC limits and
proposed SA Standards are measured at the Sasol monitoring stations (viz. 91 hourly and 8
daily exceedances at Boiketlong for the period 2006).
Ambient nitrogen dioxide
concentrations exceed the hourly target levels over the built up areas of the Vaal Airshed.
The occurrences of these hourly exceedances are however, generally infrequent (within the
limit permitted by the EC and proposed National Ambient SA Air Quality Standards (draft
document on 24 October 2007) of 18 and 9 times per year respectively).
8.2
Priority Sources within the Vaal Airshed
Emission sources within the Vaal Airshed include a wide range of industries; a coal fired
power station, household coal and wood combustion, vehicle emissions, filling stations,
brickworks, mining operations and other sources such as waste disposal facilities, fugitive
dust sources and biomass burning.
All of these sources to a larger and lesser extend contribute to inhalable particulate
concentrations, with most of the industrial sources, the domestic fuel burning and vehicle
tailpipe emissions contributing to sulphur dioxide and nitrogen dioxide ground level
concentrations.
The main source contributions have been identified together with the priority areas and these
are reflected in Table 8-1.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
8-2
Table 8-1:
Priority pollutants and their associated contributing sources and main impact
areas within the Vaal Airshed.
Pollutant
Discussion
Suspended Particulate Concentrations (in the inhalable fractions)
Concentrations of inhalable particulates within domestic coal burning areas are well in excess of
Levels
health guidelines. Significant health impacts and associated health costs have found to be
(Particulate
associated with exposures to this pollutant. Ambient inhalable particulate levels within Soweto
Matter)
and Orange Farm measure frequent exceedances of the SANS limits (proposed SA standards)
of 75 µg/m³.
Fine particulate concentrations are elevated throughout much of the Vaal Airshed, even areas
more remote from heavy industrial and domestic coal burning areas. Exceedances of the SANS
limits (proposed SA standards) over the Vaal Airshed occurs on a frequent basis.
Main
impact
areas
(Particulate
Matter)
A large portion of the Vaal Airshed is in non-compliance.
Domestic fuel burning areas - coincides with un-electrified areas (informal settlements, backyard
shacks) and poorer electrified areas in former townships.
Areas in close proximity to: large industries (particularly industries with smelting and/or
combustion-related emissions), mines and quarries, busy unpaved roads, large exposed soil
areas and agricultural activities, and open grass areas which frequently experience fires. Areas
noted to be significantly impacted include Vanderbijlpark - particularly the northern suburbs,
Bophelong, Boipatong, Sharpville, Vereeninging – particularly the western suburbs, Meyerton,
Zamdela, the eastern suburbs of Sasolburg, Soweto and Orange Farm.
Elevated throughout the Vaal Airshed even within non-fuel burning residential areas located fair
distances from localised sources indicated above.
Sources
(Particulate
Matter)
Main sources of total airborne particulate concentrations in the fine fraction (<10µm in diameter)
in ambient exposure areas - ranked:
- Domestic fuel burning (primarily coal and to a lesser extent wood)
- Fugitive soil dust including fugitive emissions from vehicle entrainment, industrial operations,
wind erosion, mining activities, agricultural activities (etc.)
- Industrial operations - particularly large industries undertaking smelting and fuel combustion
related processes
- Domestic fuel burning within Johannesburg transported into the region
- Energy generation (fly ash)
- Diesel-driven vehicle tailpipe emissions
- Regional aged aerosol component due to pollution from distant sources being transported into
the Region's airshed, specifically elevated power generation and industrial emissions located on
the highveld and large-scale biomass burning to the north.
Main sources of combustion-generated airborne particulate concentrations in the fine fraction
(<10µm in diameter) in ambient exposure areas :
- Domestic fuel burning
- Industrial and energy generation processes
Minor, localised and/or episodic sources of total particulates include:
- Large-scale construction activities
- Wild fires and tyre burning (can be significant contributors to acute exposures)
- Spontaneous combustion
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
8-3
Pollutant
Discussion
Sulphur Dioxide
Levels (Sulphur Concentrations of sulphur dioxide within domestic coal burning areas are well in excess of health
Dioxide)
guidelines. Ambient sulphur dioxide levels within Soweto and Orange Farm measure frequent
exceedances of the ambient hourly SA standards of 350 µg/m³.
Sulphur dioxide concentrations are elevated throughout much of the Vaal Airshed, with ambient
measured levels in exceedances of the hourly air quality targets at Soweto, Orange Farm,
Sasolburg, and Vanderbijlpark were monitored data was available for analysis.
A large portion of the Vaal Airshed is in non-compliance.
Main
impact
areas (Sulphur
Dioxide)
Residential areas within Sasolburg located in close proximity to the Sasolburg industrial area are
a key zone of impact. Hourly health target levels have been measured to be exceeded by up to
th
a factor of 6 (hourly concentration of 2109 µg/m³ measured on the 19 of January 11:00 2006 in
Orange Farm).
Residential areas elsewhere located in close proximity to sulphur dioxide emitting industrial
activities or within the impact zone of down-mixed plumes from elevated power station
emissions.
Such areas include: Zamdela, Three Rivers, Bedworth Park, Vereeniging,
Vanderbijlpark and Boipatong.
Domestic coal burning areas, and in particular Soweto, Orange Farm and Zamdela.
The main sources of ambient sulphur dioxide concentrations are likely to be:
- industrial operations particularly chemical and petrochemical operations (e.g. Sasol, Natref)
and operations with large-scale combustion-related processes (e.g. ArcelorMittal iron and steel
plants, Rand Water Board, various brickworks including Ocon Brickworks)
- Power generation. (The elevated release of Lethabo Power Station's emission, 275 m,
significantly reduces the potential for high near ground sulphur dioxide concentrations. Downmixing of the plume during turbulent atmospheric conditions does however provide the potential
for intermittently increasing the ground level concentrations in certain areas.)
Sources
(Sulphur
Dioxide)
Other minor, localised and/or episodic sources include:
- Domestic and other (industrial, commercial) fuel burning appliances
- Vehicle exhaust emissions, particularly diesel-powered vehicles
Nitrogen Dioxide
Exceedances of the hourly SANS limits (proposed SA standards) of 200 µg/m³ have been
Levels
measured at the Sasol (AJ Jacobs) and ArcelorMittal (Station 620) monitoring stations. The
(Nitrogen
occurrence of the hourly exceedances is however infrequent with 5 exceedances measured at
Dioxide)
AJ Jacobs and only 1 at Station 650.
Main
impact
areas (Nitrogen
Dioxide)
Sources
(Nitrogen
Dioxide)
Areas of impact are anticipated to be Vanderbijlpark, Boipatong Sebokeng and Orange Farm
Primarily:
- Vehicle tailpipe emissions
- Industrial activities – power generation, petrochemical process, commercial boilers, etc.
Other minor, localised and/or episodic sources include:
- Domestic and other fuel burning appliances
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
8-4
9
REFERENCES
Afrane-Okese, Y. (1998). Domestic energy use database for integrated energy planning,
Energy and Development Research Centre: University of Cape Town. EDRC/98/D1.
Allwine, K.J. and Whiteman, C.D. (1985). MELSAR: A Mesoscale Air Quality Model for
Complex Terrain: Volume 1 – Overview, Technical Description and User’s Guide. Pacific
Northwest Laboratory, Richland Washington.
Andreae M.O. (1991). Biomass Burning. Its history use, and distributions and its impacts on
environmental quality and global climate, J.S. Levine (ed.), Global biomass burning,
atmospheric, climatic, and biospheric implications, The MIT Press, Cambridge, 240-244.
Annegarn, H.J., Kneen, M.A., Piketh, S.J., Home, A.J., Hlapolosa, H.S.P., and Kirkman,
G.A. (1993). Evidence for large-scale circulation of sulphur over South Africa. Proc. National
Association for Clean Air Annual Conf. Dikhololo, South Africa, Nat. Assoc. for Clean Air.
Annegarn H.J. and Grant M.R. (1999). Direct Source Apportionment of Particulate
Pollution within a Township, Final Report submitted to the Department of Minerals and
Energy, Low Smoke Coal Programme, 10 July 1999.
Annegarn H.J. and Sithole J.S. (1999). Soweto Air Monitoring – SAM Trend Analysis of
Particulate Pollution 1992 – 1999, Supplementary Report to the 1998 Annual Report, Report
AER99.163 S SOW, 10 January 1999.
Arya, S.P.S. (1984). Parametric Relations for the Atmospheric Boundary Layer. Bound.
Layer Meteor. 30. 57-73.
ATSDR (1999). Sulphur Dioxide, A report by the Agency for Toxic Substances and Disease
Registry (ATSDR). June 1999.
Barry, R.G. and Chorley, R.J. (1992). Atmosphere, Weather and Climate. Sixth Edition.
Methuen and Co. Ltd. London. pp 392.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
9-1
Benkovitz, C.M., Berkowitz, C.M., Easter, R.C., Nemesure, s., Wagenerand, R., nad
Schwartz, S.E. (1994). Sulphate over the North Atlantic and adjacent continental regions:
Evaluation for October and November 1986 using a three-dimensional model driven by
observation-driven meteorology. J. Geophys.Res. 99. 20 578 – 20 586.
Bethal, R.A., Sheppard, D., Geffroy, B., Tam, E., Nadel, J.A. and Boushey, H.A. (1985).
Effect of 0.25 ppm Sulphur Dioxide on Airway Resistance in Freely Breathing, Heavily
Exercising, Asthmatic Subjects. Am. Rev. Respir. Dis. 131, 659-661.
Briggs, G.A. (1973). Plume Rise. U.S. Atomic Energy Commission. TID-25075. Oak Ridge,
TN.
Briggs, G.A. (1975). Diffusion Estimates for Small Emissions (Draft).
Atmospheric Turbulence and Diffusion Laboratory. ATOL No. 19.
Air Resources
Briggs, G.A. (1979). Analytical Modelling of Drainage Flows, Draft document, Atmospheric
Turbulence and Diffusion Laboratory, NOAA.
Briggs, G.A. (1985). Analytical Parameterisations of Diffusion: The Convective Boundary
Layer. J. Clim. and Appl. Meteor. 24. 1 167 – 1 186.
Britton M.S.T. (1998).
Low-smoke Fuel Programme: Laboratory Technical Tests,
Determination of Emission Factors, Department of Minerals and Energy, Report No. ES9606,
July 1998.
Bureau of Market Research (2006). Population estimates for South Africa by Magisterial
District and Province, 2001 and 2006, A report by the Bureau of Market Research.
Burger L. W. (1994). Analysis of Meteorological and Airborne Pollutant Data Collected in
the Vaal Triangle for the Period 1990 to 1993, Report on project done on behalf of the
Department of National Health and Population Development, 12 December 1994.
Burger L W, Held G and Snow N H (1995). Ash Dump Dispersion Modeling Sensitivity
Analysis of Meteorological and Ash Dump Parameters, Eskom Report TRR/S95/077,
Cleveland, 18 pp.
Calabrese, E., Sacco, C., Moore, G. and DiNardi, S. (1981). Sulphite Oxidase Deficiency:
A High Risk Factor in SO2, Sulphite and Bisulphite Toxicity? Med. Hypotheses 7,133-145.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
9-2
Caughey, S.J. (1981). Observed Characteristics of the Atmospheric Boundary Layer. In:
Atmospheric Turbulence and Air Pollution Modelling. F.T.M. Nieuwstadt and H. Van Dop,
Eds., D. Reidel Publishing Company, Boston, MA.
Copert III (2000). Computer Programme to Calculate Emissions from Road Transport –
Methodology and Emission Factors, European Topic Centre on Air Emissions.
Cosijn C. (1996). Elevated Absolutely Stable Layers: A Climatology for South Africa,
Unpublished Msc. Proposal submitted to the Department of Geography and Environmental
Studies, University of the Witwatersrand, Johannesburg.
Cosijn C., and Tyson P.D. (1996). Stable discontinuities in the atmosphere over South
Africa. South African Journal of Science. 92, 381-386.
Diab R. D. (1975). Stability and Mixing Layer Characteristics over Southern Africa,
Unpublished Msc Thesis, University of Natal, Durban, 203 pp.
Douglas, S. and Kessler, R. (1988). User’s Guide to the Diagnostic Wind Field Model
(Version 1.0). Systems Applications, Inc., San Rafael, CA, 48pp.
Draxler, R.R. (1976). Determination of Atmospheric Diffusion Parameters. Atmospheric
Environ. 10. 99 – 105.
EPA (1986). Air Pollution. Improvements Needed in Developing and Managing EPA's Air
Quality Models, GAO/RCED-86-94, B-220184, General Accounting Office, Washington, DC.
EPA (1993). Air quality criteria for oxides of nitrogen. Volumes I-III. United States
Environmental Protection Agency (USEPA) Office of Research and Development,
Washington, DC. EPA Publication No. EPA/600/8-91/049aF-cF.
EPA (1995a). A User’s Guide for the CALPUFF Dispersion Model. U.S. Environmental
Protection Agency. EPA Publication No. EPA-454/B-95-006.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
9-3
EPA (1995b). Testing the Meteorological and Dispersion Models for Use in Regional Air
Quality Modelling. Report prepared for U.S. Environmental Protection Agency by Sigma
Research/EARTH TECH, Concord, MA.
EPA (1996). Compilation of Air Pollution Emission Factors (AP-42), 6th Edition, Volume 1,
as contained in the AirCHIEF (AIR Clearinghouse for Inventories and Emission Factors) CDROM (compact disk read only memory), US Environmental Protection Agency, Research
Triangle Park, North Carolina.
EPA (2003). Revision to the Guideline on Air Quality Models: Adoption of a Preferred Long
Range Transport Model and Other Revisions; Final Rule, Federal Register - 40 CFR Part 51.
68. 18 440 – 18 482.
Fishmen, J. (1991). Probing Planetary Pollution from Space. Environ. Sci. Technol., 25, 612621.
Freiman, M.T. and Tyson, P.D. (2000). The thermodynamic structure of the atmosphere
over South Africa: implications for water vapour transport. Water SA. 26. 153-158.
Garstang, M., Tyson, P.D., Swap, R. and Edwards, M. (1996). Horizontal and vertical
transport of air over southern Africa. J. of Geophy. Res. 101. 23 721 – 23 736.
Gifford, F.A., Jr. (1976). Turbulent Diffusion – Typing Schemes: A Review. Nucl. Saf. 17. 68
– 86.
Godden, D. and Lurmann, F. (1983). Development of the PLMSTAR Model and its
Application to Ozone Episode Conditions in the South Coast Air Basin. Environmental
Research and Technology, Inc., Western Village, CA.
Godish R. (1990). Air Quality, Lewis Publishers, Michigan, 422 pp.
Goldreich, Y. and Tyson, P.D. (1988). Diurnal and inter-diurnal variations in large-scale
atmospheric turbulence over southern Africa, South African Geographical Journal, 70, 48-56.
Goodin, W.R. McRae, G.J. and Seinfeld, J.H. (1980). An Objective Analysis Technique for
Constructing Three-Dimensional Urban Scale Wind Fields. J. Appl. Meteor. 19. 98 – 108.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
9-4
Hanna, S.R., Briggs, G.A., Deardorff, J., Egan, B.A., Gifford, F.A., and Pasquill, F.
(1977). AMS Workshop on Stability Classification Schemes and Sigma Curves – Summery of
Recommendations. Bull. Am. Meteor, Soc. 58. 1 305 – 1 309.
Hanna, S.R., Weil, J.C. and Paine, R.J. (1986). Plume Model Development and Evaluation.
Report Number D034-500. Electric Power Research Institute, Palo Alto, CA.
Hanna, S.R. and Chang, J.C. (1991). Modifications of the Hybrid Plume Dispersion Model
(HPDM) for Urban Conditions and its Evaluation Using the Indianapolis Data Set, Volume I:
User’s Guide for HPDM-URBAN. EPRI Project No. RFP-02736-1, Palo Alto, CA 94303.
Heffter, J.L. (1965). The Variations of Horizontal Diffusion Parameters with Time for Travel
Periods of One Hour or Longer. J. Appl. Meteor. 4. 153 – 156.
Held G.H. Scheifinger, H., and Snyman, G.M. (1994). Recirculation of pollutants in the
atmosphere of the South African highveld. S. Afr. J. Sci. 90. 91 – 97.
Hicks, B.B. (1985). In: Critical Assessment Document on Acid Deposition (Chapter VII-Dry
Deposition). ATDL Contribution File No. 81/24. Atmospheric Turbulence and Diffusion
Laboratory, NOAA, Oak Ridge, TN.
Hoult, D.P. and Weil, J.C. (1972). A Turbulent Plume in a Laminar Crossflow. Atmos.
Environ. 6. 513 – 531.
Hubber, A.H. (1977). Incorporating Building/Terrian Wake Effects on Stack Effluents.
Preprint volume for the Joint Conference on Applications of Air Pollution Meteorology,
American Meteorological Society, Boston, MA.
Hubber, A.H. and Snyder, W.H. (1976). Building Wake Effects on Short Stack Effluents.
Preprint volume for the Third Symposium on Atmospheric Diffusion and Air Quality, American
Meteorological Society, Boston, MA.
Irwin, J.S. (1979). Scheme for Estimating Dispersion Parameters as a Function of Release
Height. EPA-600/4-74-062, U.S. Environmental Protection Agency, Research Triangle Park,
NC.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
9-5
Jorgensen MW and Sorenson SC (1997). Estimating Emissions from Railway Traffic,
Report for the project MEET: Methodologies for Estimating Air Pollutant Emissions from
Transport, funded by the European Commission under the Transport RTD Programme of the
4th Framework Programme, Report No. ET-EO-97-03, July 1997.
Krishnamurti, T.N., Fuelberg, H.E., Sinha, M.C., Oosterhof, d., Bensman, E.L., and
Kumai, V.B. (1993). The meteorological environment of the tropospheric ozone maximum
over the tropical South African Ocean. J. Geophys. Res. 98. 10 621 – 10 641.
Liebenberg, H. (1999). Air Pollution Population Exposure Evaluation in the Vaal Triangle
using GIS. Unpublished MSc thesis, Geography and Environmental Management
Department. Johannesburg: Rand Afrikaans University.
.
Liebenberg-Enslin, H., Thomas, R.G., Walton, N. and van Nierop, M. (2007): Vaal
Triangle Priority Area Air Quality Management Plan – Baseline Characterisation. Department
of Environmental Affairs and Tourism – Environmental Quality and Protection.
Liu, M.K. and Yocke, M.A. (1980). Siting of Wind Turbine Generators in Complex Terrain. J.
Energy. 4. 10 – 16.
Maddox, R. (2006). Be Particular about Particulate Matter. Maryland department of the
Environment. Volume 1, number 12, April 2006.
Maenhaut, W., Salma, I., Cafmeyer, J., Annegarn, H.J. and Andreae, M.O. (1996).
Regional atmospheric aerosol composition and sources in the eastern Transvaal, South
Africa, and impacts of biomass burning, J. Geophys. Res. 101. 23 631 – 23 650.
Mahrt, L. (1982). Momentum Balance of Gravity Flows. J of Atmos. Sci. 39. 2 701 – 2 711.
Marticorena B. and Bergametti G. (1995). Modeling the Atmospheric Dust Cycle. 1.
Design of a Soil-Derived Dust Emission Scheme. J. Geophys. Res. 100. 16 415 - 16430.
Mukala, K. (1999). Personnel Exposure to Nitrogen Dioxide and Health Effects Among
Preschool Children. Academic Dissertation for the Faculty of Medicine of the University of
Helsinki, November, 1999.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
9-6
Muller, C (1992). Source Apportionment Study of Atmospheric Particulates in the Vaal
Triangle, MSc Dissertation, University of the Witwatersrand, Johannesburg.
Nieuwstadt, F.T.M. (1984). Some Aspects of the Turbulent Stable Boundary Layer. Bound.
Layer Meteor. 30, 31 – 55.
NRC (National Research Council), (2004). Research Priorities for Airborne Particulate
Matter. Board on Environmental studies and Toxicology, Division of Earth and Life Studies.
The National Academic Press. Pp 355.
O’Brien, J.J. (1970). A note on the Vertical Structure of the Eddy Exchange Coefficient in
the Planetary Boundary Layer. J. Atmos. Sci. 27, 1 213 – 1 215.
Oke, T. R. (1987). Boundary Layer Climates, 2nd edition, Routledge, London.
Oke, T.R. (1990). Boundary Layer Climates, Routledge, London and New York, 435 pp.
Panofsky, H.A., Tennekes, H., Lenschow, D.H. and Wyngaard, J.C. (1977). The
Characteristics of Turbulent Velocity Components in the Surface Layer under Convective
Conditions. Bound. Layer Meteor. 11 355 – 361.
Pasquill, F. (1976). Atmospheric Dispersion Parameters in Gaussian Plume Modelling: Part
II. Possible requirements for change in the Turner workbook values. EPA-600/4-76-030b,
U.S. Environmental Protection Agency, Research Triangle Park, NC, 53pp.
Pasquill, F. and Smith, F.B. (1983). Atmospheric Diffusion. Study of the Dispersion of
Windborne Material from Industrial and Other Sources, Ellis Horwood Ltd., Chichester, 437
pp.
Pershagen, G., Rylander, E., Norberg, S., Eriksson, M. and Nordvall, S.L. (1995). Air
Pollution Involving Nitrogen Dioxide Exposure and Wheezing Bronchitis in Children.
International Journal of Epidemiology.24. 1 147 – 1 153.
Pickering, K.E., Thompson, A.M., McNamara D.P.Schoeberl, M.R., Lait L.R., Newman,
P.A., Justice C.O., and Kendall J.D. (1994). A trajectory modeling investigation of the
biomass burning tropical ozone relationship. Proc. Quad. Ozone Symp., NASA, 101-104.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
9-7
Piketh, S.J. (1995). Generation and transportation characteristics of suspended particles in
the eastern Transvaal. M.S. dissertation, University of the Witwatersrand, 148 pp.
Piketh, S.J., Annegarn, H.J. and Kneen, M.A. (1996). Regional scale impacts of biomass
burning emissions over southern Africa, in J.S. Levine (ed.), Biomass Burning and Global
Change, MIT Press, Cambridge, 320-326.
Preston-Whyte R.A., Diab, R.D., Tyson, P.D. (1977). Towards an inversion climatology of
southern Africa: Part II, Non-surface inversions in the lower atmosphere. S. Afr. Geogr. J. 59.
47-59.
Preston-Whyte R. A. and Tyson P. D. (1988). The Atmosphere and Weather over South
Africa, Oxford University Press, Cape Town, 374 pp.
Preston-Whyte R. A. and Tyson P. D (1989). The Atmosphere and Weather over South
Africa, Oxford University Press, Cape Town, 374 pp.
Raupach M. R., Antonia R. A. and Rajagopalan S. (1991). Rough-Wall Turbulent
Boundary Layers. Appl. Mech. Rev. 44. 1 - 25.
Rautenbach, H. (2006). Air Pollution Meteorology, lecture notes for the Air Quality
Management course, University of Johannesburg, Soweto campus.
Rotach, M. W., Fisher, B., Piringer, M. (2002). COST 715 Workshop on Urban Boundary
Layer Parameterizations, Bulletin of the American Meteorological Society. 83. 1 501 – 1 504.
Rotach, M. W., Vogt, R., Bernhofer, C., Batchvarova, E., Christen, A., Clappier, A.,
Feddersen, B., Gryning, S.E., Mayer, H., Mitev, V., Oke, T. R., Parlow, E., Richner, H.,
Roth, M., Roulet,Y.A., Rueux, D., Salmond, J., Schatzmann, M. and Voogt, J. A. (2004).
BUBBLE - an Urban Boundary Layer Project. Theor. Appl. Climatol. 81. 231 - 261.
Salma, I., Maenhaut, W., Cafmeyer, J., Annegarn, H.J., Andreae, M.O. (1992). PIXE
analysis of cascade impactor samples collected at the Kruger National Park, South Africa,
Nuclear Instruments and Methods in Physics Research B. 85. 849 – 855.
Schulman, L.L. and Hanna, S.R. (1986). Evaluation of Downwash Modifications to the
Industrial Source Complex Model. JAPCA.36. 258 – 264.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
9-8
Scire, J.S. and Schulman, L.L. (1980). Modelling Plume Rise form Low-Level Bouyant Line
and Point Sources. Proceedings Second Point Conference on Applications of Air Pollution
Meteorology. 24-28 March, New Orleans, LA, 133 – 139.
Scire, J.S. and Robe, F.R. (1997). Fine-Scale Application of the CALMET Meteorological
Model to a Complex Terrain Site. Paper 97-A1313, AWMA 90th Annual Meeting & Exhibition,
June 8-13, Toronto, Ontario, Canada.
Scire, J.S., Robe, F.R., Fernau, M.E. and Yamartino, R.J. (2000a). A User’s Guide for the
CALMET Meteorological Model. Version 5. Earth Tech, Inc., 196 Baker Avenue, Concord,
MA 01742.
Scire, J.S., Strimaitis, D.G. and Yamartino, R.J. (2000b). A User’s Guide for the CALPUFF
Dispersion Model. Version 5. Earth Tech, Inc. 196 Baker Avenue, Concord, MA 01742.
Scorgie, Y., Burger, L.W. and Sowden, M. (2001). Analysis, Synthesis and Consolidation
of the Qalabotjha and Embhalenhle Experiments, Including Other Investigations. Report No.
EMS/01/DME-01.
Scorgie, Y. (2003). Air Quality Situation Assessment for the Vaal Triangle, Draft Final,
Report compiled on behalf of the Legal Resource Centre, Report no. MTX/02/LRC-07a, April
2003.
Scorgie, Y., Burger L.W., and Annegarn H.J. (2003a). Socio-Economic Impact of Air
Pollution Reduction Measures - Task 2: Establishment of Source Inventories, and Task 3:
Identification and Prioritisation of Technology Options, Report compiled on behalf of
NEDLAC, 25 June 2003.
Scorgie, Y., Burger L.W., and Annegarn H.J. (2003b). Socio-Economic Impact of Air
Pollution Reduction Measures - Task 4: Quantification of Environmental Benefits Associated
with Fuel Use Interventions, Report compiled on behalf of NEDLAC, 30 September 2003.
Scorgie, Y., Paterson, G., Burger, L.W., Annegarn, H.J. and Kneen, M.A. (2004). SocioEconomic Impact of Air Pollution Reduction Measures – Task 4a Supplementary Report:
Quantification of Health Risks and Associated Costs Due to Fuel Burning Source Groups;
Report compiled on behalf of NEDLAC, 2004.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
9-9
Scorgie, Y. Krause, N. and Petzer, G. (2006). Air Quality Assessment for the Proposed
New Coal-Fired Power Station in the Lephalale Area, Limpopo Province, Report No.
APP/06/BWK-01 Rev1.0, May 2006.
Scorgie, Y. (2006). Sources of Air Pollution – Identification, Emission Quantification and
Control, lecture notes for the Air Quality Management course, University of Johannesburg,
Soweto campus.
Shaw, R.W., and Munn, R.E. (1971). Air Pollution Meteorology, in B.M. McCormac (Ed.),
Introduction to the Scientific Study of Air Pollution, Reidel Publishing Company, DordrechtHolland, 53-96.
Speizer, F.E. and Frank, N.R (1966). The Uptake and Release of SO2 by the Human Nose.
Arch. Environ. Health 12, 725-728.
Strimaitis D.G., Scire J.S. and Chang J.C. (1998). Evaluation of the CALPUFF Dispersion
Model with Two Power Plant Data Sets, Preprints 10th Joint Conference on the Applications
of Air Pollution Meteorology, 11-16 January 1998, Phoenix, Arizona.
Stone A (2000). South African Vehicle Emissions Project: Phase II, Final Report: Diesel
Engines, February 2000.
Stull, R.B. (1997). An Introduction to Boundary Layer Meteorology, Kluwer Academic
Publishers, The Netherlands, 670 pp.
The Standard Encyclopedia of Southern Africa (1971). Aspects of weather and climate
over southern Africa. 3, 258-269
Tennekes H. and Lumley J. J. (1972). A First Course in Turbulence. MIT Press.
Terblanche P, Nel R, Reinach G and Opperman L (1992). Personal Exposures to Total
Suspended Particulates from Domestic Coal Burning in South Africa, NACA Clean Air
Journal, vol. 8 no. 6, November 1992, 15-17.
Thomas RG and Scorgie Y (2006). Air Quality Impact Assessment for the Proposed New
Coal-Fired Power Station (Vaal South) In the Northern Free State Area. Report No.:
APP/06/NMS-02 Rev 0.1. December 2006.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
9-10
Tyson, P.D. (1967). Some characteristics of the mountain wind over Pietermaritzburg. Proc.
Jubilee Conf. South African Geographic Society, Durban South Africa, S. Afr. Geogr. Soc.
103 – 128.
Tyson, P.D. and Preston-Whyte, R.A. (1972). Observations of regional topographically
induced wind systems in Natal., J. Appl. Meteor. 11, 643 – 650.
Tyson, P.D., Preston-Whyte, R.A., and Diab, R.D. (1976). Towards an inversion
climatology of southern Africa: Part I, Surface inversions. S. Afr. Geogr. J. 58. 151 – 163.
Tyson, P.D., Kruger, F.J. and Louw, C.W. (1988). Atmospheric pollution and its
implications in the eastern Transvaal Highveld. S.A. National Scientific Progress Rep. 150,
Foundation for Research Development, Pretoria, South Africa, 114 pp.
Tyson P.D., Garstang M., Swap R., Kallberg P., and Edwards M. (1996a). An air transport
climatology for subtropical southern Africa. Int. J. Climatol. 16, 265-291.
Tyson P.D., Garstang M., Swap R., Browell, E.V., Diab, R.D., and Thompson, A.M.
(1996b). Transport and vertical structure of ozone and aerosol distributions over southern
Africa. In: Biomass Burning and Global Change, J.S. Levine, Ed., MIT Press, 403 – 421.
Tyson P.D., Garstang M., and Swap R (1996c). Large-scale recirculation of air over
southern Africa. J. Appl. Meteor. 35. 2218 – 2236.
Tyson, P.D. (1997). Atmospheric transport of aerosols and trace gases over southern Africa.
Prog. in Phy. Geog. 21. 79 – 101.
Tyson P.D. and Gatebe, C.K. (2001). The atmosphere, aerosols, trace gases and
biogeochemical change in southern Africa: a regional integration. SA J. of Sci. 97. 106 - 118.
Van Nierop P.G. (1995). An Emission Inventory of Particulate Air Pollution in the Vaal
Triangle, MSc Dissertation, Faculty of Engineering, University of the Witwatersrand.
Vallius, M. (2005). Characteristics and Sources of Fine Particulate Matter in Urban Air.
National Public Health Institute. 6. 81 pp.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
9-11
Wang, L., Parker, D.B., Parnell, C.B., Lacey, R.E. and Shaw, B.W. (2006). Comparison of
CALPUFF and ISCST3 Models for Predicting Downwind Odor and Source Emission Rates.
J. Amos. Environ. 40. 4 663 – 4 669.
Weil, J.C. (1985). Updating Applied Diffusion Models. J. Clim. Appl. Meteor. 24. 1 111 –
1 130.
Weil, J.C. (1988). Plume Rise. Lectures on Air Pollution Modelling. Editors, Venkatram, A.
and Wyngaard, J.C. 119 – 166.
Weil, J.C., Corio, L.A. and Brower, R.P. (1997). A PDF Model for Bouyant Plumes in the
Convective Boundary Layer. J Appl. Meteor. 36. 982 – 1 003.
WHO (1995). Update and revision of the air quality guidelines for Europe. Meeting of the
Working Group on “Classical” Air Pollutants, 11-14 October 1994, Bilthoven, the
Netherlands. Regional Office for Europe, Report EUR/ICP/EHAZ9405/PB01 (EUR/HFA
target 21). 29 pp.
WHO (2000). Sulphur Dioxide, Report prepared by the WHO Regional Office for Europe
Copenhagen, Denmark.
Wong (1999). Vehicle Emissions Project (Phase II). Volume I, Main Report, Engineering
Research, Report No. CER 161, February 1999.
Yu, M. (2001). Environmental Toxicology: Impacts of Environmental Toxicants on Living
Systems, CRC Press, 225 pp.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
9-12
APPENDIX A
QUESTIONARE TO QUANTIFY INDUSTRIAL EMISSIONS WITHIN THE VAAL AIRSHED
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
A-1
Request for Information Cover Letter:
15 December 2006
Dear Sir / Madam
Of: INDUSTRY NAME
Re: Request for Information for the Development of the Vaal Triangle Air Shed Priority Area Air
Quality Management Plan (AQMP)
The Department of Environmental Affairs and Tourism (DEAT) has appointed Gondwana
Environmental Solutions in association with Airshed Planning Professionals and Zitholele Consulting
to assist government to develop an air quality management plan for the area known as the Vaal
Triangle. The background information document to the project is included herewith.
This letter serves as a request for affected industry to participate in this project and to provide the
data as outlined in the attached questionnaire. The scope of work to be undertaken by the
consultants for the Department does not include the source quantification of all emissions and
therefore great reliance is placed on industry for data that is reflective of their activities. In the event
that data is not forwarded by the stipulated dates, available data as per the environmental impact
assessment and/or environmental management plan; and the APPA permit conditions will be utilised
where available. All data is to be forwarded to Lerato Mudeme or Patricia Mashilo by the 13th of
February 2007.
Your assistance in the completion of the attached questionnaire is highly appreciated.
Should you have any further queries pertaining to this project; please do not hesitate to contact us.
Kind regards
Hanlie Liebenberg-Enslin
Lerato Mudeme or Patricia Mashilo
Airshed Planning Professionals (Pty) Ltd
PO Box 5260, Halfway House, 1685
Tel: 011 805 1950
Fax: 011 805 7010
E-mail: [email protected] or [email protected]
Airshed Planning Professionals
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
A-2
Questionnaire:
QUESTIONNAIRE:
INFORMATION REQUIRED FOR INCORPORATION INTO THE DEVELOPMENT OF AN AQMP FOR
THE VAAL TRIANGLE PRIORITY AREA.
A. Facility and Contact Information
Aspect
Item
ID.
A.1
Name of Firm:
A.2
Physical Address:
A.3
Postal Address:
A.4
Telephone Number:
A.5
Fax Number:
A.6
Name of Safety, Health and
Environmental Official:
Email Address:
A.7
A.8
A.9
A.10
Information Required
Name of emission control
officer:
Email Address:
A.11
Name of alternate contact
person:
Email Address:
A.12
Website address:
A.13
Industry Type / Nature of
Trade:
Item
ID.
B.1
Aspect
B. Nature of Process
B.2
Information Required
Brief description of entire
production
process
including
current
and
approved processes that
would be implemented in
2007:
List of Scheduled Processes conducted at the premises by the industry:
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
A-3
Scheduled process number
Schedule process description
C. Raw Material
Raw Material type
Maximum permitted
Consumption Rate
(Volume)
Product Name
Maximum Production
Capacity Permitted
(Volume)
Design
Consumption
Rate
Actual
Consumption
Rate
Units (quantity/
period)
Actual
Consumption
Rate (Volume)
Units (quantity/
period)
D. Production Rates
Design
Production Rate
(Volume)
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
A-4
E. Energy Sources Used
Energy
Source
Sulphur Content
of Fuel (%)
(if applicable)
Ash Content of Fuel (%)
(if applicable)
Maximum Permitted
Consumption Rate
(Volume)
Design
Consumption
Rate (Volume)
Actual
Consumption
Rate (Volume)
Units
(quantity/ period)
F. Sources of Atmospheric Emissions
PLEASE PROVIDE SOURCE EMISSIONS REPRESENTATIVE OF 2007 OPERATIONS
A MAP DEPICTING THE LOCATION OF THE POINT SOURCES IS TO BE PROVIDED
F.1 POINT source parameters
Source name
Height of
release above
ground (m)
Height above
nearby building
(m)
Nature of
pollutants
Concentration
of pollutants
(mg/Nm³ (for all
listed
pollutants
Emission
velocity
(Nm³/s)
1
% Routine or
2
upset
emissions
Emission
Temperature
(K)
Control
equipment %
efficiency
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
A-5
NOTES:
1. Routine emissions- emissions to atmosphere with control equipment in place
2. Upset emissions- venting directly to atmosphere either during maintenance of equipment or incidental releases.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
A-6
F. Sources of Atmospheric Emissions
PLEASE PROVIDE SOURCE EMISSIONS REPRESENTATIVE OF 2007 OPERATIONS
A MAP DEPICTING THE LOCATION OF THE AREA SOURCES IS TO BE PROVIDED
F.2 Area1 source parameters
Area Source
Pollutant name
Maximum Daily
Release Rate
(tons/ annum)
Average Annual
Release Rate
(tons/annum)
Type of emission
(Continuous/
intermittent)
Wind
dependent
(yes/no)
Dimensions (where applicable)
Length
Width
Height
NOTES:
1. Area sources include roads and stockpiles
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
A-7
G. Meteorological Monitoring
(Please tick where appropriate)
G.1
Meteorological station:
G.2
Sampling Date Initiation (D/M/Y):
G.3
G.4
Sampling Date Closure (if Applicable):
Station Location (provide coordinates and a map)
G.5
Instrumentation Type:
G.6
Frequency of full calibration:
G.7
Parameters measured:
Humidity
Pressure
Rainfall / Precipitation
Sigma Theta
Temperature
Wind direction
Wind speed
Wind velocity
G.8
OTHER - Please Specify
In which format is the data available:
G.9
Consent to use data
H.1
Type of monitoring undertaken:
(continuous, passive, dust fallout monitoring)
Name of contact person for monitoring activities:
Telephone number:
Email address:
H.3 Ambient continuous monitoring
Parameter measured:
Sampling date initiation (D/M/Y):
Sampling date closure (if applicable):
Station type:
Station location (please provide coordinates and
map):
Frequency of full calibration:
Frequency of measurement:
Format of data:
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
No
No
No
No
No
No
No
Yes
No
H. Monitoring
H.2
i
ii
iii
iv
v
vi
vii
viii
i
Parameter measured:
ii
iii
iv
v
Sampling date initiation (D/M/Y):
Sampling date closure (if applicable):
Station type:
Station location (please provide coordinates and
map):
Frequency of full calibration:
Frequency of measurement:
Format of data:
vi
vii
viii
i
ii
Parameter measured:
Sampling date initiation (D/M/Y):
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
A-8
iii
iv
v
vi
vii
viii
I
ii
iii
iv
v
vi
vii
viii
i
ii
iii
iv
v
i
ii
iii
i
ii
iii
Sampling date closure (if applicable):
Station type:
Station location (please provide coordinates and
map):
Frequency of full calibration:
Frequency of measurement:
Format of data:
Parameter measured:
Sampling date initiation (D/M/Y):
Sampling date closure (if applicable):
Station type:
Station location (please provide coordinates and
map):
Frequency of full calibration:
Frequency of measurement:
Format of data:
H.4 Passive Monitoring
Parameter measured:
Sampling date initiation (D/M/Y):
Sampling date closure (if applicable):
Sampling location (please provide coordinates
and map):
Sampling averaging period in which data is
presented:
H.5 Dust fallout monitoring
Methodology utilised:
Number of sampling points:
Location of sampling points:
(please provide coordinates and map)
H.6 Emissions monitoring/ continuous monitoring
Methodology utilised:
Number of sampling points:
Location of sampling points:
(please provide coordinates and map)
Thank you for your invaluable contribution
to this study.
Airshed Planning Professionals
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
A-9
Follow up letter:
26 April 2007
Dear Sir / Madam
Of: INDUSTRY NAME
Re: Request for Information for the Development of the Vaal Triangle Air Shed Priority Area Air
Quality Management Plan (AQMP)
The Department of Environmental Affairs and Tourism (DEAT) has appointed Gondwana
Environmental Solutions in association with Airshed Planning Professionals and Zitholele Consulting
to assist government to develop an air quality management plan for the area known as the Vaal
Triangle Priority Area.
A letter was sent to you by the consultants in December 2006 requesting your participation in this
process by providing information pertaining to the specific processes including a process description,
type and amount of raw material used, and emission rates for the associated pollutants. The scope of
work to be undertaken by the consultants for the Department does not include the source
quantification of all emissions and therefore great reliance is placed on industry for data. To date no
response has been received from your company and this letter serves as a final request to provide the
requested information. In the event where no emissions data is available, you are still requested to
provide a short process description and amount of raw materials used.
All data is to be forwarded to Airshed Planning Professionals by the 14th of May 2007. The
Department will take further steps in this regard should no response be received by the due date.
Your assistance ire is highly appreciated. Should you have any further queries pertaining to this
project; please do not hesitate to contact us.
Best regards
Mr Peter Lukey
Chief Directorate: Air Quality Management & Climate Change
Department of Environmental Affairs and Tourism
Information to be sent to: Lerato Mudeme or Patricia Mashilo
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
A-10
Airshed Planning Professionals (Pty) Ltd, Tel: 011 805 1950, Fax: 011 805 7010
E-mail: [email protected] or [email protected]
Airshed Planning Professionals
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
A-11
APPENDIX B
INDUSTRIAL EMISSIONS FOR THE VAAL AIRSHED4
4
The industrial emissions inventory includes the local municipality areas of Emfuleni, Midvaal and
Metsimaholo, but excludes the Ekurhuleni Local Municipality.
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
B-1
Process
Ferroalloys
Ferroalloys Total
Petrochemical
Company
Phosphate Fertilizer Process Total
Boilers
Emissions (tons/annum)
NO
NO2
PM10
Source
Type
Release Height
Metalloys
0.00
0.00
0.00
772.08
Stacks
and
Fugitive
From ground level to stack heights of 30m
Sasol
SMX Sasolburg
Natref
0.00
18520.70
0.00
11605.25
30125.94
0.00
13305.71
0.00
0.00
13305.71
0.00
4968.03
0.00
870.39
5838.42
772.08
1972.43
675.32
1058.98
3706.73
Stacks
Stacks
Stacks
Release height from 12m to 145m
Release height from 40m to 75m
145 m
Omnia Fertilizer
0.00
84.01
9.33
394.78
Stacks
and
Fugitive
Ground level to 60m
Aero Dry Cleaners
African Detinning
Air Products
Cargo Carriers
Central Hotel
Clover
DF Malherbe
Die Anker Skool
Drie Riviere Primary
Driehoek
Drive-In cleaners
Frikkie Meyer
General Smuts High
Handhawer Primary
Hendrik van Derbijl Primary
Historia Primary
Hoer Tegnies
Johan Heyns
Kaponong Hospital
Killarney Hotel
Kollegepark
Krugerln School
Magistrate's Court
0.00
0.00
2.80
0.02
0.05
0.00
3.06
0.04
0.04
0.00
0.04
2.62
0.04
0.00
0.00
0.04
0.04
0.00
12.10
0.51
0.06
0.04
0.00
0.01
84.01
0.01
1.02
0.05
0.12
0.00
1.12
0.00
0.00
0.00
0.00
0.94
0.00
0.00
0.00
0.00
0.00
0.00
4.41
0.13
0.02
0.00
0.00
0.02
9.33
0.00
0.11
0.01
0.01
0.00
0.12
0.00
0.00
0.00
0.00
0.10
0.00
0.00
0.00
0.00
0.00
0.00
0.49
0.01
0.00
0.00
0.00
0.00
394.78
0.00
3.36
0.00
0.05
0.00
3.69
0.00
0.00
0.00
0.00
3.18
0.00
0.00
0.00
0.00
0.00
0.00
14.55
0.18
0.07
0.00
0.00
0.00
Stacks
Range from approximately 2 m to 30 m
Petrochemical Total
Phosphate Fertilizer Process
SO2
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
B-2
Process
Company
Multispray
Noordhoek
Oliver Lodge
Oospark
Overvaal High
Park Panel Beaters
Park Ridge Primary
Pinedene
Riverside High
SAP
Sasolburg Hospital
Slagment
Sun Crest High
Suncrush
Superp Dry Cleaners
Supreme
Tanker Services
TNT Panel Beaters
Totius Primary
Transvalia
Unitaspark Primary School
Vaal High
Vaal Portugese Bakery
Vaal Technikon
Vaalmed
Van Zyl Panelbeaters
Vanderbijlpark High
Vereeniging High School
Voorslag
Willies Confectionary
Boilers Total
Brickworks
Brickworks Total
Ocon Bricks
Brickveld Stene
African Brick Lenasia
SO2
Emissions (tons/annum)
NO
NO2
PM10
0.02
0.04
0.04
0.04
0.00
0.02
0.04
0.04
0.00
0.02
0.00
11.97
0.04
6.15
0.11
0.00
0.02
0.02
0.04
0.04
0.00
0.04
0.03
0.00
0.00
0.02
0.04
0.00
0.04
0.05
40.33
0.00
0.05
0.00
0.00
0.00
0.00
0.05
0.00
0.00
0.00
0.01
0.00
4.36
0.00
2.24
0.03
0.03
0.05
0.05
0.00
0.00
0.00
0.00
0.08
0.00
0.01
0.05
0.00
0.00
0.00
0.12
15.01
0.00
0.01
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.48
0.00
0.25
0.00
0.00
0.01
0.01
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.01
0.00
0.00
0.00
0.01
1.67
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.00
14.39
0.00
7.40
0.04
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.01
46.98
430.22
0.00
2.02
2.02
0.00
0.53
0.53
0.00
0.06
0.06
0.19
0.70
431.11
Source
Type
Stacks
and
Fugitive
Release Height
From ground level to 4 m
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
B-3
Process
Iron and Steel Processes
Iron and Steel Processes Total
Power Generation
Power Generation Total
Mines
Mines Total
Smaller Industries
Company
ArcelorMittal Vaal Works
ArcelorMittal Klip Works
ArcelorMittal Steel Vanderbijlpark Steel
Davesteel (Cape Gate)
Lethabo
New Vaal Colliery
Sigma Colliery
African Cables
African Catalysts
African Pegmatite
Ambijo Lounges
Blitz Concrete Works (Westongoud)
Blue Armor
Brickveld Stene
Claasens Tegniek
Concorde Foundry
Consolidated Wire Industries
Coverland Roof Tiles
Dixon Batteries
Dorbyl Heavy Engineering
EMSA
Everite Building Products
Flexilube
Lime Distributors
Much Asphalt
Nampak
Non-Ferrous Cast Products
Polifin (AECI Midlands)
Rand Water Board
Safripol
Slagment
Superior Casting Supplies/Pattern Makers
SO2
11.24
0.00
13648.62
0.00
13659.86
171929.00
171929.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.59
0.00
0.00
1.97
0.00
0.00
1.95
30.67
0.00
6.85
20.49
0.00
0.00
0.00
Emissions (tons/annum)
NO
NO2
142.29
25.28
14740.85
0.00
14740.85
76374.00
76374.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.51
0.00
0.00
0.19
7.99
0.00
1.78
5.34
0.00
0.00
0.00
22.25
2.81
125.99
0.00
151.06
2390.00
2390.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.00
0.00
0.02
0.89
0.00
0.20
0.59
0.00
0.00
0.00
PM10
81.82
0.00
5559.98
1022.98
6582.97
5776.00
5776.00
3467.00
1087.23
4554.23
65.83
0.00
0.02
0.01
5.68
0.00
42.60
0.00
50.44
0.41
4.67
0.23
41.01
95.32
44.17
0.34
99.06
0.11
10.65
0.42
445.65
7.11
219.71
0.97
5.81
Source
Type
Release Height
Stacks
and
Fugitive
From ground level to stack heights of 145m
Stacks
275m
Fugitive
Ground level
Stacks
From 2 m to 100 m
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
B-4
Process
Company
Suprachem
TOSA (Tubemakers of SA)
Vaal Potteries
Van Leer SA
Vereeniging Abbatoir
Vereeniging Crushers
Vitro Building Products
Vryheidsmon
Zimmerman and Jansen SA
Zwartkoppies Pumping Station
Smaller Industries Total
SO2
0.00
0.00
1.10
0.00
1.55
0.00
0.00
0.00
0.00
93.99
159.16
Emissions (tons/annum)
NO
NO2
0.00
0.00
0.29
0.00
0.40
0.00
0.00
0.00
0.00
24.49
41.01
0.00
0.00
0.03
0.00
0.04
0.00
0.00
0.00
0.00
2.72
4.56
PM10
Source
Type
Release Height
0.74
1.45
166.02
0.10
0.54
0.02
1658.65
0.00
0.24
32.65
3000.62
AN AIR QUALITY BASELINE ASSESSMENT FOR THE VAAL AIRSHED IN SOUTH AFRICA
B-5
Was this manual useful for you? yes no
Thank you for your participation!

* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project

Download PDF

advertisement