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AMAJUBA DISTRICT MUNICIPALITY
Draft Baseline Assessment Report
with Gap and Problem Analysis
October 2014
Prepared by
P O Box 37945 Overport, 4067
Tel: +27 31 202 2860 Fax: 0866 552 061
E-mail: [email protected]
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Document Control
Client Amajuba District Municipality Principal Contact Ms Nothile Mthimkhulu
Project Code G2002
Report Prepared By: Ms Dudu Ngubane, Dr. Njoya Silas Ngetar
Document Status and Review Schedule
Issue No. Report No. Date Status Reviewed by
1 1 10 September 2014 Draft Michelle Simon
This report has been prepared by Zanokuhle Environmental Services on behalf of the Client, taking into account the agreed scope of works. In preparing this report, by Zanokuhle Environmental Services has exercised all reasonable skill and care, taking into account the objectives and the agreed scope of work. Zanokuhle Environmental Services does not accept any liability in negligence for any matters arising outside of the agreed scope of work. When issued in electronic format, Zanokuhle Environmental Services does not accept any responsibility for any unauthorised changes made by others.
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TABLE OF CONTENTS 1. Introduction .............................................................................................................. 8 2. Area description and geography ................................................................................. 9
2.1 Introduction to Amajuba District Municipality ......................................................... 9 2.2 Population data .................................................................................................. 9 2.3 Land use and human activities ........................................................................... 11 2.4 Topographical Setting ....................................................................................... 12
2.4.1 Physical Geography of the Local Municipality .............................................. 12 3. Climate and Meteorology Description ........................................................................ 15
3.1 Introduction ...................................................................................................... 15 3.2 Synoptic meteorology ....................................................................................... 15 3.3 Local conditions ............................................................................................... 16
3.3.1 Emadlangeni Local Municipality .................................................................. 16 3.3.2 Dannhauser Local Municipality ................................................................... 17 3.3.3 Newcastle Local Municipality ...................................................................... 17
3.4 Wind Movement ............................................................................................... 20 4. Evaluation of existing ambient air quality monitoring ................................................... 27
4.1 Air Quality Standards ........................................................................................ 27 4.2 Ambient air quality monitoring ............................................................................ 28
4.2.1 Site backgrounds and measured parameters ............................................... 28 4.2.2 Monitoring results ...................................................................................... 30
5. Emission inventory .................................................................................................. 46 5.1 Introduction ...................................................................................................... 46 5.2 Atmospheric emission sources in ADM ............................................................... 47
5.2.1 Industrial sources ...................................................................................... 48 5.2.2 Waste management .................................................................................. 49 5.2.3 Mining ...................................................................................................... 50 5.2.4 Indoor air quality ....................................................................................... 51 5.2.5 Transportation and tyre burning .................................................................. 53 5.2.6 Biomass burning and agricultural activities .................................................. 54
6. Dispersion modelling ............................................................................................... 55 6.1 Introduction ...................................................................................................... 55
7. Evaluation of Current Management and tools ............................................................ 56 7.1 Legal Overview ................................................................................................ 56
7.1.1 An Air Quality Officer (AQO) ...................................................................... 56 7.1.2 Areas of responsibility for the ADM ............................................................. 57
7.2 Overview of Current Air Quality Management within ADM .................................... 58 7.3 Existing staff structure ....................................................................................... 58
8. Gap and problem analysis ....................................................................................... 60 8.1 Human resources and technical capacity ............................................................ 61 8.2 Lack of information on Air Quality Management System (AQMS) .......................... 62 8.3 Absent intergovernmental relationships .............................................................. 63 8.4 Domestic fuel burning ....................................................................................... 64
9. Goal Setting ........................................................................................................... 65 10. References .......................................................................................................... 66 Appendix 1 ..................................................................................................................... 67
Digital Elevation Model (DEM) ...................................................................................... 67
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LIST OF TABLES Table 1: Population of Amajuba Local Municipalities by geographical type (Stats SA, 2013)................. 10 Table 2: Average daily minimum and maximum temperatures for Newcastle (2007-2012) (South African Weather Services) .................................................................................................................................. 18 Table 3: South African Air Quality Standards .......................................................................................... 27 Table 4: Exceedances of the National Standard (PM10)......................................................................... 33 Table 5: Shooting Range exceedances of the National Standard (SO2) ................................................ 35 Table 6: WHO guidelines for H2S exposure ............................................................................................ 39 Table 7: Emission sources and pollutants ............................................................................................... 47 Table 8: Operational and non-operational mines .................................................................................... 50 Table 9: Sources of Common Indoor Air Pollutants (Guideline for Monitoring Domestic Indoor Air Quality in South Africa, 2009) ................................................................................................................. 53 Table 10: District's areas of responsibility ............................................................................................... 57
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LIST OF FIGURES Figure 1: Amajuba District Municipalities and it Local Municipalities within the context of South Africa (Data source: University of KwaZulu-Natal, 2013). ................................................................................... 9 Figure 2 : Population distribution in the Amajuba District Municipality (Data source: Stats SA, 2013) ... 10 Figure 3 : Location of human activities in relation to population distribution in the Amajuba District Municipality (Data source: Stats SA, 2013; Newcastle Local Municipality). ............................................ 11 Figure 4: Location of human activities in relation to topography (Data source: Stats SA, 2013; Newcastle Local Municipality; University of KwaZulu-Natal, 2013). ......................................................................... 12 Figure 5 : The topography of the Amajuba District Municipality (Data Source: University of KwaZulu-Natal, 2013). ........................................................................................................................................... 13 Figure 6: A terrain model for the Amajuba District Municipality (Data source: University of KwaZulu-Natal, 2013). ........................................................................................................................................... 14 Figure 7: Examples of summer and winter synoptic patterns over southern Africa ................................ 16 Figure 8: Rainfall in monthly daily averages – 2007 -2012 ..................................................................... 17 Figure 9: Average monthly daily minimum and maximum temperature (2007 – 2012) ........................... 18 Figure 10: Average monthly daily minimum and maximum temperature (2011 – 2013) ......................... 19 Figure 11: Average monthly daily minimum and maximum temperature (1999 – 2007) ......................... 19 Figure 12: Wind movements in summer (2003-2013) (South African Weather Services). ...................... 21 Figure 13: Wind movements in autumn (2003-2013) (South African Weather Services). ....................... 22 Figure 14: Wind movements in winter (2003-2013) (South African Weather Services). ......................... 23 Figure 15: Wind movements in spring (2003-2013) (South African Weather Services) .......................... 24 Figure 16: The annual average wind movement in the ADM (2003-2013) (South African Weather Services) ................................................................................................................................................. 24 Figure 17: Average monthly daily maximum wind speed (2011 – 2013) ................................................. 25 Figure 18: Average monthly daily maximum wind speed (2000 – 2006) ................................................. 26 Figure 19: July 2012 - May 2013 NO2 results from three monitoring sites (monthly averages) .............. 30 Figure 20: July 2012 - May 2013 SO2 results from three monitoring sites (monthly averages) .............. 30 Figure 21: July 2012 -May 2013 O3 results from three monitoring sites (monthly averages) .................. 31 Figure 22: July 2012 -May 2013 Benzene results from three monitoring sites (monthly averages) ........ 31 Figure 23: Daily average maximum PM10 from Shooting Range Station ................................................. 33 Figure 24: Daily average maximum PM10 from eMadadeni Station for year 2000 .................................. 34 Figure 25: PM10 annual averages from Shooting Range Station ............................................................ 34 Figure 26: Monthly average maximum SO2 from Shooting Range Station ............................................. 35 Figure 27: SO2 annual averages from Shooting Range Station .............................................................. 36 Figure 28: SO2 24-hour averages from eMadadeni Station .................................................................... 36 Figure 29: SO2 annual averages from eMadadeni Station ...................................................................... 37 Figure 30: NOx (standard applies to NO2) from Shooting Range Station ............................................... 38 Figure 31:NO2 annual averages from eMadadeni Station ....................................................................... 38 Figure 32: monthly maximum daily averages H2S - shooting Range Station .......................................... 40 Figure 33: Monthly average maximum O3 from Shooting Range Station ............................................... 41 Figure 34: Monthly average maximum CO from shooting Range Station ............................................... 41 Figure 35: Annual average concentrations for Cr6+ Phases 2 - 16 (CSIR, 2013) .................................. 42 Figure 36: Annual maxima concentrations for total Cr Phases 2-16 (CSIR, 2013) ................................. 43 Figure 37: NPC PM10 daily averages between 2013 and 2014 ............................................................... 45 Figure 38: Total emissions in ADM (Source: Zanokuhle - KZN-DAE&RD, 2007) ................................... 49 Figure 39: Clay brick production area in Blaauwbosch ........................................................................... 51 Figure 40: Domestic fuel use in the ADM (STATS SA census 2011) ...................................................... 52 Figure 41: Total emissions in ADM (Source: Zanokuhle - KZN-DAE&RD, 2007) ................................... 54 Figure 42: Current staff structure Planning and Development Directorate .............................................. 59 Figure 43: Proposed staff structure Environmental Management Directorate ........................................ 61
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GLOSSARY AQA Air Quality Act, (Act No. 39 of 2004) AQO Air Quality Officer CO Carbon Monoxide CO2 Carbon Dioxide DEA Department of Environmental Affairs (National) DME Department of Mineral and Energy Affairs EIA Environmental Impact Assessment NOX Nitrogen oxides, also referred to as oxides of nitrogen NO2 Nitrogen dioxide NO Nitrogen oxide O3 Ozone PM10 Particulate matter of aerodynamic diameter less than 10 μm SANAS South African National Accreditation System SO2 Sulphur dioxide TEOM Tapered Element Oscillating Membrane VOCs Volatile Organic Compounds WHO World Health Organisation ZES Zanokuhle Environmental Services
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KEY DEFINITIONS Air Quality
Management Plan
means a plan referred to in section 15 of AQA
Ambient Air Air in the environment, excluding indoor air.
Ambient air
quality standards
values that define targets for air quality management and establish the permissible amount or concentration of a particular substance in or property of discharges to air based on what a particular receiving environment can tolerate without significant deterioration
Baseline air
quality assessment
A compilation of existing or current data and knowledge on air quality in a particular area. It forms an essential input into the subsequent formulation of the AQMP. It comprises an assessment of the current ambient air quality status; an assessment of current organisational structures for air quality management; and an assessment of current air quality initiatives to reduce air pollution.
Emission Pollution discharged into the atmosphere from a range of stationary and mobile sources. These include smokestacks, vents and surface areas of commercial or industrial facilities; residential sources; motor vehicles and other transport related sources.
Emission inventory a listing or register of the amount of pollution entering the atmosphere from all sources within a given time and geographic boundaries
Exceedances A situation in which a measured ambient air quality concentration (or emission rate) of a particular pollutant exceeds the ambient air quality guideline or standard (or emission limit) for that pollutant. Exceedances are normally expressed as a total number per time period and give an indication of the severity of the air pollution problem.
Mitigation measures
Efforts to attempt to prevent pollution or to reduce the effects of pollution that occur
Monitoring Periodic or continuous surveillance or testing to determine the level of compliance with statutory requirements and/or pollutant levels in various media or in humans, plants, and animals.
Priority pollutant Pollutants which, through ambient concentrations, bioaccumulation, deposition or in any other way, present a threat to health, well-being or the environment. Factors that may influence whether a pollutant is identified as such include: its toxicity; the volume of emissions; or the proximity of the emission relative to sensitive receptors. A list of priority pollutants is contained in Chapter 5.3.2 of the National Framework (2007), Table 23.
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1. Introduction The baseline assessment is undertaken to understand the current status of air quality within an Amajuba District Municipal (ADM) area and to assess the compliance with ambient air quality standards. The assessment is designed to also evaluate the current management tools within the municipality.
The assessment encompasses the identification of pollutants, pollutant sources and areas of concern based on measured / and existing knowledge of ambient air pollution concentrations within ADM area. The activities that may influence air quality within ADM would also determine the complexity of the air quality management plan.
The Section 15(2) of National Environmental Management: Air Quality Act, (Act No. 39 of 2004) requires each municipality to include an Air Quality Management Plan ( AQMP) in its integrated development plan (IDP) required in terms of Chapter 5 of the Municipal Systems Act.
The Act designated district and metropolitan municipalities as Atmospheric Emission Licensing authorities. In addition, they are responsible for air quality function including air quality monitoring.
ADM baseline assessment further provides the basis for planning the requirements of an Air Quality Management System (AQMS). For example:
• Areas where air quality monitoring, emission inventories and air quality assessment are not adequate.
• Cases when the baseline studies clearly reveal that air quality standards are violated.
The baseline assessment report comprises the following sections:
Section 1: Provides a short introduction to the baseline assessment.
Section 2 Area description and geography – Details the area under review and describes the geography.
Section 3: Meteorology and Climate Description – This section provides a summary of the meteorological conditions within the area.
Section 4: Evaluation of air quality information – Gives an analysis of the ambient air monitoring data and emission inventory currently available within the municipality. Section 5: Evaluation of Current Management – An evaluation of the current management tools in place within the municipality.
Section 6: gap and problem analysis – Provide gaps and analysis of problems identified during baseline assessment
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2. Area description and geography
2.1 Introduction to Amajuba District Municipality
The Amajuba District Municipality is one of eleven District Municipalities in KwaZulu-Natal province, located at the far north-western part of the province. It is bounded to the north by Mpumalanga Province and to the west by Free State. Its southern, south-eastern and eastern boundaries are the Uthugela, Umzimyathi and Zululand District municipalities respectively. The District Municipality is made up of three local municipalities namely Newcastle in the west, Dannhauser in the south and Emadlangeni in the east (Figure 1). The total surface area of the District municipality is estimated at about 6,910 km2, subdivided into Newcastle (1,855 km2), Dannhauser and Emadlangeni (3,539 km2) (Amajuba District Municipality, 2012).
Figure 1: Amajuba District Municipalities and it Local Municipalities within the context of South Africa (Data source: University of KwaZulu-Natal, 2013). 2.2 Population data
The collection of population distribution data serves as an input to the emission inventory and to the air pollution exposure estimates. The Geographical presentation of area-distributed population statistics as well as consumption of fossil fuels and direct emissions gives a good overview of where to expect elevated air pollution impacts.
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The human geography of the Amajuba District Municipality describes its population distribution pattern and human activities that have likely impacts on air quality.
The population of the Amajuba District Municipality is estimated at 499,828 (Stats SA, 2013), distributed among the three Local Municipalities (Table 1). The Newcastle Local Municipality has the highest population, concentrated mostly in the urban areas while the Emadlangeni Local Municipality has the lowest population but highly concentrated in the farms. Population distribution by geographical type shows that overall, the combined urban areas for the Amajuba District Municipality has the greatest population concentration followed by the tribal areas and then the farms. That urban areas have the highest concentration of population is an indicator of their vulnerability to air urban pollution. Detail population distributions by main places show three areas with high population concentration namely Newcastle, Madadeni and Osizweni (Figure 2). Of these three main places, Madadeni has the greatest concentration of population approximately 119,497 inhabitants (Stats SA, 2013).
Table 1: Population of Amajuba Local Municipalities by geographical type (Stats SA, 2013)
Local Municipalities Urban area Tribal or Traditional area Farm Total
Newcastle 257314 90787 15125 363225 Emadlangeni 8942 - 25500 34442 Dannhauser 10357 83901 7903 102161
Total 276613 174688 48528 499828
Figure 2 : Population distribution in the Amajuba District Municipality (Data source: Stats SA, 2013)
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2.3 Land use and human activities
Some human activities impact on air quality through the release of air pollutants into the atmosphere. Amajuba District Municipality (ADM) human activities include the air polluting industries, use of domestic fuel such as coal and paraffin, vehicles, mining (both legal and illegal) and agricultural activities. In the ADM, most human activities with the propensity to affect air quality are located in the urban areas and adjacent to townships (Figure 3). Industries are categorized into low, medium and high impact industries.
Figure 3 : Location of human activities in relation to population distribution in the Amajuba District Municipality
(Data source: Stats SA, 2013; Newcastle Local Municipality). High impact industries (Industrial High Impact 1) are sandwiched between the very populated areas of Newcastle, Madadeni and Osizweni, making these areas vulnerable to any industry-related air pollution. However these depend among others on factors like the type and concentration of air pollutants, wind direction and speed, and topography. In relation to topography discussed later under the physical geography sub-section, human activities together with population occupy the low-lying areas of the Amajuba District Municipality and are exposed in the south (S) to the SSE (south south east) and SE (south east) winds (Figure 4).
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Figure 4: Location of human activities in relation to topography (Data source: Stats SA, 2013; Newcastle Local Municipality; University of KwaZulu-Natal, 2013).
2.4 Topographical Setting
2.4.1 Physical Geography of the Local Municipality The physical geography of the District Municipality as related to air quality management can be divided into its physiography and the climate. Physiography relates to the physical geographic features located within the confines of the District Municipality. These include among others its topography or terrain, river networks and vegetation cover. The topography of the District Municipality is uneven, with its central and south-eastern sections generally characterized by low lying terrain, while the far western margins and the northern sections are situated on relatively higher grounds (Figure 5). Of the three Local Municipalities in the District Municipality, Emadlangeni displays the most uneven topography which probably explains its sparse human occupation especially to the north and north-eastern half. Its highest and the lowest points, 2000 m and 1200 m are situated to its northern and southern portions respectively.
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Figure 5 : The topography of the Amajuba District Municipality (Data Source: University of KwaZulu-Natal, 2013).
The Newcastle local municipality displays a contrasting topography, a generally elevated western half culminating at 2050 m (the highest point of the entire District Municipality), descending to 1300 m in its eastern section. Like the Newcastle local municipality, the Dannhauser Local Municipality is elevated in the west (1800 m) while its central and eastern section is characterised by a generally low lying terrain varying between 1300 and 1400 m. This topographical presentation of the Amajuba District Municipality can be better visualized from the terrain model (Figure 6) and Digital Elevation Model (DEM) (Appendix 1), which shows that generally, its central portion, is a saucer-like basin. Depending on the dominant wind direction, sources of air pollutants, and season, the marginal mountain barriers surrounding the District Municipality are likely to prevent the escape of air pollutants exposing the enclosed areas to a degree of pollution risks. In addition, mountain winds from the west could play a major role in the distribution of any air pollutants towards the east. There is also a likelihood of temperature inversion in winter, trapping any air pollutants to the detriment of settlements in the lowlands east of the District Municipality.
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Figure 6: A terrain model for the Amajuba District Municipality (Data source: University of KwaZulu-Natal, 2013).
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3. Climate and Meteorology Description
3.1 Introduction
The climate describes the long-term atmospheric conditions while the meteorology describes the variability in the atmospheric parameters that can affect dispersion. Meteorological parameters such as wind speed and direction, temperature, pressure and atmospheric stability are responsible for transportation of pollutants which in turn determine the levels of concentrations.
Stable atmospheric conditions result to accumulation of air pollutants while unstable atmosphere is associated with dispersion of pollutants. Dispersion takes place through horizontal transport and vertical mixing in the lower atmosphere. Horizontal transport depends on location as well as on elevation above ground, and to some extent on time of day (White, 1998).
The magnitude of the horizontal transport on a given day depends greatly on the synoptic scale air flow that can range from week-long stagnation to swift unidirectional transport (White, 1998).
A brief overview of the synoptic influences over southern Africa is provided in Section 3.2. This in turn controls meteorological conditions and air pollution dispersion experienced in the Amajuba District Municipality. The meteorological overview specific to the ADM was compiled using South African Weather Service (SAWS) data from Newcastle automated meteorological weather station. The presented data is based on 10 year averages for years from 2003 to 2013. No SAWS automated stations situated at Dannhauser and Emadlangeni local municipalities.
In addition, data was received from the KwaZulu-Natal Department of Agriculture, Environment Affairs and Rural Development and Arcelormittal ambient air quality monitoring station for a period of 1999 to 2013. The data is presented in figures 10, 11, 17 and 18 of this report.
3.2 Synoptic meteorology
Southern Africa is situated in the subtropical high pressure belt and as such the meteorology is controlled by several high pressure cells interrupted by westerly wave and tropical easterly perturbations. Three high pressure cells (anticyclones) dominate, viz. the south Atlantic anticyclone, the south Indian anticyclone and the Continental anticyclone over the interior.
In winter the high pressure belt intensifies and moves northward, but is interrupted by a series of cold fronts associated with westerly perturbations that move west to east across the southern part of the country (Figure 7). The cold fronts are accompanied by clouds and sometimes rain and are associated with decreases in temperature and wind shifts from northerly prior to the front, followed by westerly winds.
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However, during the winter months, the interior is dominated by high pressure with a maximum frequency of occurrence of 79% in June and July (Tyson, 1988). During summer, the high pressure belt weakens and is only present some 11% of the time and the systems shift southwards allowing tropical easterly perturbations to influence the climate. The easterly waves and lows occur almost exclusively during the summer months, and are responsible for the summer rainfall and northerly component winds that flow over the interior.
Summer Winter
Figure 7: Examples of summer and winter synoptic patterns over southern Africa 3.3 Local conditions
3.3.1 Emadlangeni Local Municipality The climate of the Amajuba District Municipality varies with the local municipalities within the District Municipality. Emadlangeni is divided into two climatic regions (Korsman and Van Wyk Consortium, 2002), the northern Highland Sourveld characterised by an average annual rainfall between 800 and
1500 mm, two to three dry months and average yearly temperature fluctuating between 13°C and 15°C.
The average minimum atmospheric temperature of the coldest month is 0°C while the average
maximum temperature for the warmest month is 29°C (Korsman and Van Wyk Consortium, 2002).
The second climatic region is called the Semi-Highland veld, a dry grassland veld occupying the southern hills and plains with average annual rainfall varying between 600 and 800 mm (including four
to five dry months). Its average annual temperature varies between 16°C and 18°C. The average
minimum air temperature for the coldest month is 0°C, and the average maximum temperature for the
warmest month is 30°C (Korsman and Van Wyk Consortium, 2002).
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3.3.2 Dannhauser Local Municipality The Dannhauser Local Municipality also shows a variation of climate with an average annual rainfall of 671 mm which occurs mostly during mid-summer (December and January). The monthly distribution of average daily maximum temperatures ranges from 18.5°C in June to 26.2°C in January, the coldest month being July (2.1°C during the night) (http://www.saexplorer.co.za).
3.3.3 Newcastle Local Municipality The average annual rainfall in the Newcastle Local Municipality is estimated at 874 mm, much of which also occurs in December and January.
Figure 8: Rainfall in monthly daily averages – 2007 -2012
Its average annual temperature ranges between 13.2°C and 18.2°C. However, the average hourly temperatures can sometimes be as high as 34°C with the lowest being -4.1oC (Thornhill et al., 2013).
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Figure 9: Average monthly daily minimum and maximum temperature (2007 – 2012)
The lowest and highest average daily minimum temperatures are 5°C (in June) and 16.9oC (in January), while the lowest and highest average daily maximum are 21.2°C (in June and July) and 29.3°C in February (Table 2). Figures 10 and 11, data from the KwaZulu-Natal Department of Agriculture, Environment Affairs and Rural Development (KZN- DAEA) and Arcelormittal ambient air quality monitoring stations respectively are in good agreement with SAWS data except that daily maximums are higher. The highest maximum is 45°C recorded in December 2004 from Arcelormittal station. Cold months are likely to be characterized by temperature inversion given the western and northern highlands, inhibiting the escape of atmospheric pollutants while generally, warmer mouths would likely encourage the escape of air pollutants due to rising warm air. Table 2: Average daily minimum and maximum temperatures for Newcastle (2007-2012) (South African Weather Services)
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Average daily min 16.9 16.7 15.5 11.2 7.7 5 4.2 6.9 11 12.9 14.9 16.6
Average daily max 28.5 29.3 28.3 24.9 24 21.2 21.2 24 24.5 26.7 28.2 28.8
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Figure 10: Average monthly daily minimum and maximum temperature (2011 – 2013)
Figure 11: Average monthly daily minimum and maximum temperature (1999 – 2007)
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3.4 Wind Movement
The motion of air plays a major role in determining the distribution of emissions in the atmosphere. Wind direction (WD) and wind speed (WS) are very useful in diluting and rapidly dispersing air pollutants. Wind speed determines the distance a pollutant can be transported downwind and the rate of dilution and can influence the turbulence and hence uplift, or stability and mixing. The calmer the winds, the poorer the dispersion potential. Conversely, higher wind speeds will lead to improved dispersion. The wind direction determines the general path of pollutants and area of impact of a pollutant source. It is also important to consider that surface winds are influenced by topography. Wind roses show the predominant direction from which the wind blows and are reflected according to compass point direction and wind speed categories, which for the purposes of this report are as follows: Yellow: 0.5 – 2.5 m/s Pink: 2.5 – 3.5 m/s Red: 3.5 – 5.6 m/s Turquoise: 5.6 – 8.7 m/s Green: 8.7 – 10.7 m/s Blue: > 10.7 m/s Wind movement in the Amajuba District Municipality vary with season (Figure12). A clear pattern of wind movement exists for summer and autumn. During summer (mid-October to mid-February), more than 10% of the dominant winds blow from the SE and ESE directions. Wind speed varies from 0.5 - 10.7 m/s, the most frequent being 3.5 - 5.6 m/s (approximately 4-5%).
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Figure 12: Wind movements in summer (2003-2013) (South African Weather Services). In autumn (mid-February to April), the pattern remains almost the same except that a third dominant wind direction SSE is added and wind speeds of 0.5 – 2.5 become more frequent (Figure 13). The likely implications are that since the densely populated areas of Osizweni and Madadeni are located on the windward side while industries with high impacts (Industrial High Impact 1) are located on the leeward side (Figure 3), their impact on these areas are likely to be low. Since part of Newcastle is located behind the high impact industries, it may suffer from any air pollutants blown onto it by the SE and ESE winds.
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Figure 13: Wind movements in autumn (2003-2013) (South African Weather Services).
The winter season (May to July) display two dominant wind patterns (Figure 14), one from the SSE and the other from the west (and WSW in the last month of the season). The westerlies are probably mountain winds originating from the western highlands (Figure 6) during winter. Wind speed during this season vary between 0.5 and > 10.7 m/s, the most frequent being 0.5-2.5 m/s. The WSW winds likely blow any air pollutants from the high impacts industries into the Osizweni, Madadeni and other settlements in the east.
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Figure 14: Wind movements in winter (2003-2013) (South African Weather Services). The first month of spring (August) display characteristics similar to the last month of winter (July), showing two dominant wind patterns (from the SE and in the west) (Figure 15). Stronger winds (10.7 m/s) blow increasingly from the west. Figures 17 and 18 confirmed August as being windy months with maximum wind speed of 19 m/s and 13 m/s recorded from Arcelormittal and KZN- DAEA ambient air quality monitoring stations respectively. However during the last month of spring (September), the dominant wind direction switches to the SE and ESE, mimicking the pattern of the first summer month (October). Two likely scenarios are envisioned, one during August when the W, WNW and NW winds dominate spreading any atmospheric pollutants from the high impact industries in the west to eastern settlements (notably the highly populated areas of Madadeni, Osizweni and others in the east). In September when the dominant wind direction switches to the SSE, SE and ESE, some areas may
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experience a relieve since the high impact industries are once more located on the leeward side of these winds and a majority of settlements (except the western part of Newcastle on the path of any air-blown pollutants from the high impact industries).
Figure 15: Wind movements in spring (2003-2013) (South African Weather Services)
The average annual dominant wind direction for the Amajuba District Municipality blow from the SSE, SE and ESE (Figure 16); almost similar to the situation in summer, autumn and the last month of spring (September).
Figure 16: The annual average wind movement in the ADM (2003-2013) (South African Weather Services)
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The average annual wind characteristics for the Amajuba District Municipality is composed of approximately 3-4% of winds with speed 0.5-2.5 m/s, 3% of winds with speed 2.5-3.5 m/s, 3-4% of winds with speed 3.5-5.6 m/s and 1-2% of winds with speed 5.6-8.7 m/s. These average yearly wind characteristics suggests that for most part of the year, except for the western part of Newcastle, most settlements east of the high impact industries (Figure 3) likely suffer less from air-driven pollutants from the west since the dominant winds during the year emanate from the SSE, SE and ESE.
However, the likely source of air pollutants in the District Municipality may not only be the high, medium and low impact industries (Figure 3) but other sources like automobile and household energy types (coal and paraffin). The possible existence of these other energy sources within the District Municipality would compound air pollution distribution more locally irrespective of the wind direction.
Figure 17: Average monthly daily maximum wind speed (2011 – 2013)
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Figure 18: Average monthly daily maximum wind speed (2000 – 2006)
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4. Evaluation of existing ambient air quality monitoring An evaluation of the air quality in an area using existing data provides an understanding of the population exposure to air pollutants based on comparisons against air quality standards. This would also provide further baseline information for control actions, identification of the impacts caused by specific sources, and implementation of emission reduction programs. The Amajuba District Municipality is rated is a "potentially poor" air quality area in Table 18 of the National Framework - NEMA 2004: (Act No. 39 of 2004) Government Gazette Vol. 919 29 November 2013 Number 37078. This means the air quality may be poor at times or deteriorating and the municipality is required to undertake a detailed AQMP. This section of the report presents an understanding of the current data and information available on air quality and the management of air quality within the ADM.
4.1 Air Quality Standards
The South African ambient air quality standards are presented in Table 2 below as per 24 December 2009 Government Gazette No. 32816. These air quality standards are taken into account during the interpretation of the available measured data which is presented in Section 4.2. Table 3: South African Air Quality Standards
Pollutant Averaging Period Limit Value
(µg/m3) Limit Value
(ppb) Frequency of exceedance
Sulphur dioxide (SO2)
10 minutes 500 191 526
1-hour 350 134 88
24-hour 125 48 4
Annual average 50 19 0
Nitrogen dioxide (NO2) 1-hour 200 106 88
Annual average 40 21 0
Carbon monoxide (CO) 1-hour 30 26 000 (26 ppm) 88
8-hour 10 8 700 (8.7 ppm) 11
Ozone (O3) 8-hours (running) 120 61 11
Particulate Matter (PM10) 24-hour 120 - 4
Annual average 50 - 0
Benzene (C6H6) Annual average 10 3.2 0
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4.2 Ambient air quality monitoring
The baseline air quality data used for the assessment was sourced from a combination of data gathered through field monitoring and data compiled from previous studies. There are four continuous air quality monitoring systems in the area, three of which are owned and operated by industries and one by government. These systems comprise:
• Arcelor Mittal
• Lanxess
• NPC-Cimpor and
• The KwaZulu-Natal Department of Agriculture, Environment and Rural Development In addition, the National Department of Environment Affairs (DEA) conducts passive sampling in the following areas:
• Madadeni SAPS Station,
• Semi Industrial Area and
• Industrial Area.
4.2.1 Site backgrounds and measured parameters The KwaZulu-Natal Department of Agriculture, Environment and Rural Development commissioned a continuous air quality monitoring station in 2005 and is situated at the AMCO Dam. Pollutant data was not available from this site for the study. The following parameters are monitored:
Station name & location Monitoring equipment Measured parameters
Newcastle - AMCO Dam
Thermo Electron analysers for gaseous components, Beta Gauge for PM10 and RM Young for meteorological parameters.
SO2, O3, NOx, CO and PM10 Wind speed, wind direction, rain, humidity and ambient temperature
The Arcelor Mittal SA Limited - Newcastle Works started monitoring air quality in 1999 at Madadeni Township. The station was decommissioned in 2007 owing to vandalism and was relocated to Arcelor Mittal premises and is currently awaiting repairs and commissioning to the new site. In 2009 Arcelor Mittal procured a second station and is located within their premises at the shooting range field. The following parameters that were/are measured at Arcelor Mittal are as follows:
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Station name Measured parameters
Arcelor 1
Madadeni (1999-2007)
SO2, PM10, NOx, wind speed and wind direction and temperature.
Arcelor 2 Shooting range (2009-current)
SO2, CO, PM10, NOx, O3, H2S, wind speed and wind direction, humidity, pressure, rainfall, solar radiation and temperature.
In 2012 the DEA initiated the Table 24 Ground Truthing Project where passive samplers were used to measure the following pollutants:
Site name Measured parameters
Madadeni SAPS Station SO2, NO2, O3, benzene, toluene, ethyl benzene and xylene (BTEX)
Industrial Area SO2, and NO2
Semi Industrial Area SO2, NO2, O3, benzene, toluene, ethyl benzene and xylene
Lanxess has been conducting air quality monitoring since 1996. The air quality monitoring programme is based on a networked system of monitors strategically placed at various geographical locations to determine concentrations of hexavalent chromium (Cr6+) in ambient air as an indication of the impact of emissions from their plant. The monitoring station locations were established through a meteorological assessment, modelling and receptor area identification. To date Lanxess has completed 16 air monitoring phases. Data presented here is based on Phase 16, encompassing the period between 12th September 2012 and 30th September 2013. The Lanxess network comprises a total of four monitoring sites located within 0.3 - 2.9 km of the plant in four receptor directions as follows:
• Station A: Effluent Plant approx 0.3 km south of the plant.
• Station B: Arbor Park School approx 2.9 km west of the plant.
• Station C: Keyway Motors approx 2.5 kilometres east of the plant.
• Station D: Airport approx 1 km north of the plant.
The monitoring sites are designed to gather data on Total Suspended Particle Matter (TSP), Total Chromium (Cr3+ + Cr6+) and Hexavalent Chromium (Cr6+). The CSIR is responsible for the analysis of the samples, the compilation of two interim data reports and one final interpretive report for each phase while Lanxess personnel attend to the fieldwork. NPC-Cimpor established PM10 monitoring in 2013 using the Tapered Element Oscillating Microbalance (TEOM) continuous particulate monitor.
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4.2.2 Monitoring results 4.2.2.1 Data from DEA passive monitoring The DEA is conducting passive sampling in areas listed in Table 24 of the National Framework. The areas identified included the Amajuba District Municipality as a result of the area being rated as a potentially poor air quality zone. The results presented in Figures 19 to 22 below are based on the 2012 - 2013 passive sampling campaign.
Figure 19: July 2012 - May 2013 NO2 results from three monitoring sites (monthly averages)
Figure 20: July 2012 - May 2013 SO2 results from three monitoring sites (monthly averages)
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Figure 21: July 2012 -May 2013 O3 results from three monitoring sites (monthly averages)
Figure 22: July 2012 -May 2013 Benzene results from three monitoring sites (monthly averages)
The monthly average ambient measured concentrations are not always strictly comparable to the South African average standard concentrations. Compliance evaluations for measured pollutants are
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therefore only reported for general reference purposes in some instances and as an estimation of compliance. Figure 19 shows the average ambient air quality concentrations of NO2 from Madadeni SAPS, Semi industrial and Industrial Area. The monthly maximum average of 22.7µg/m3 was recorded in July 2012 at the Madadeni Industrial Area. It was not possible to calculate the annual average for comparison with the Ambient Standard as data capture for the annual period was only 50%, less than 75% as required by USEPA and EC Directive. The average ambient concentrations of SO2 from the Madadeni SAPS, Semi industrial and Industrial Area sites are represented in Figure 20. The highest average concentration of 42µg/m3 was measured at Madadeni Semi Industrial Area. The annual maximum average of 22.4µg/m3 was recorded at the same site. The value is less than the SO2 annual ambient standard (50µg/m3). The maximum monthly measured average for O3 was 110μg/m3 also recorded at the Madadeni Semi Industrial Area (see figure 21). The annual average of 61µg/m3 for O3 was recorded at this site. There are no guidelines or standards to which to compare these results since South Africa and other international bodies have an 8-hour average standard of 20μg/m3. The monthly average ambient concentration of Benzene at Madadeni SAPS Station and Madadeni Industrial is shown in Figure 22. The highest average concentration of Benzene was measured at the Madadeni SAPS Station at 4.1μg/m3. The annual average was 1.9μg/m3.
4.2.2.2 Arcelor Mittal data Data reported in this section was collected between 1999 and 2013. During this period, Arcelor Mittal had no data validation or verification systems in place. Data was made available on goodwill and Arcelor Mittal cannot be held responsible for the misuse or misinterpretation. ZES exercised all reasonable skill and care during data analysis and interpretation in the absence of quality assurance/quality control (QA/QC) documentation in order to present a meaningful understanding of the data. Furthermore, an effort was made to align the reported data with relevant air quality standards; however, it was impossible to compare some data due to the averaging time. Such data include the Shooting Range O3 and CO that was supplied in daily averages.
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Figure 23 shows the highest daily maximum PM10 for each month at the Shooting Range Station. The majority of elevated concentrations were recorded between the months of May and September. During this period the area is dominated by two wind patterns, south easterly and westerly. Four (4) exceedances of the daily average National Standard (120µg/m3) were recorded between 2010 and 2013 while 15 exceedances were recorded at the Madadeni station as noted in Table 4 below. . Table 4: Exceedances of the National Standard (PM10)
Station 2013 2012 2011 2010 2009 2000 (guideline value of 180 µg/m3 applied)
Shooting Range 2 0 1 1 0 -
Madadeni 15
Total 2 0 1 1 0 15
PM10 data
Figure 23: Daily average maximum PM10 from Shooting Range Station
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Figure 24: Daily average maximum PM10 from eMadadeni Station for year 2000
No exceedances of the PM10 annual average standard were measured at the Shooting range station. All values were below the target limit. In 2009 the annual average concentration averaged below 30µg/m3 and in 2012 dropped to 20µg/m3, decreasing further in 2013 to below 20µg/m3.
Figure 25: PM10 annual averages from Shooting Range Station
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SO2 data Trends in maximum daily and annual averages SO2 at the Shooting Range Station are provided in Figures 26 and 27. The National standards for each pollutant are indicated in red on each graph. The number of exceedances for the daily average (48ppb) and annual means (19ppb) concentrations are also presented in Table 5 below. The majority of the elevated SO2 concentrations were recorded during 2011 and 2012 during the summer months. During the period in question the National standard was exceeded 52 times (2011&2012). Other notable peaks that exceeded the National standard were measured in 2009 and 2013. There were a total of seven (7) exceedances.
Figure 26: Monthly average maximum SO2 from Shooting Range Station
Table 5: Shooting Range exceedances of the National Standard (SO2) Year 2013 2012 2011 2010 2009
Daily averages 4 23 27 0 3
Annual means 0 1 1 n/a 0
Total 4 24 28 0 3
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Figure 27: SO2 annual averages from Shooting Range Station
Figure 28: SO2 24-hour averages from eMadadeni Station
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Figure 29: SO2 annual averages from eMadadeni Station
The National standard for both daily and annual averages was not exceeded at the Emadadeni Station as shown in Figures 28 and 29.
NO2 data The NO2 (NOx) annual average National standard was not exceeded at the Shooting Range Station as shown in Figures 30. The annual maximum of 5ppb was measured in 2013.
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Figure 30: NOx (standard applies to NO2) from Shooting Range Station
Figure 31 presents annual averages for NO2 from Emadadeni Station. The standard was not exceeded.
Figure 31:NO2 annual averages from eMadadeni Station
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H2S data Hydrogen sulphide (H2S) presents health hazards that are dependent on both exposure duration and concentration as this is very toxic gas. This gas has varied risks as an irritant to the lungs but mainly at low concentrations it will irritate the eyes and respiratory tract. The smell of H2S is nuisance and its exposure may result in varied symptoms such as those of headaches, fatigue, dizziness, and staggering gait to diarrhea which is sometimes followed by bronchitis and bronchopneumonia. The risk of very large concentrations may result to paralysis of the respiratory centre causing breathing to stop and potentially death, which if does not occur during exposure where recovery will generally occur without later medical complications (Snyder et al., 1995).
Guidelines There are no international health-based standards for H2S. The World Health Organization (WHO) had an air quality guideline implemented in 1997 based on the avoidance of eye irritation. WHO recommends that H2S concentrations not exceed 5 ppb, over a 30-minute period, to avoid substantial complaints about odour. Table 6 below notes these WHO guidelines.
Table 6: WHO guidelines for H2S exposure Parameter Averaging Period Concentration
H2S 30 Minutes 5 ppb
24 Hours 10.6 ppb
Figure 32 shows elevated H2S concentrations at the Shooting Range Station during the months of January, February, April, May and December 2013. Exceedances recorded during monitoring period 2009-2013 at Shooting Range Station are as follows:
H2S Daily Exceedances
>10.6ppb
2009 6
2010 144
2011 116
2012 202
2013 115 Statistical information is awaited for data validity from Arcelor Mittal
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Figure 32: monthly maximum daily averages H2S - shooting Range Station
Other pollutant data The Ozone (O3) and Carbon Monoxide (CO) data was supplied in daily averages. The South African Standard for O3 is 61 ppb 8-hours (running). The CO has two target limits, 8.7 ppm for 8-hour and 26 ppm for 1-hour averages. Data for both pollutants is only presented for general reference purposes and as an estimation of compliance. This is represented in Figures 33 and 34 below
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Figure 33: Monthly average maximum O3 from Shooting Range Station
Figure 34: Monthly average maximum CO from shooting Range Station
4.2.2.3 Lanxess The phase 16 chromium data has revealed much lower Cr6+ levels than the first nine phases (see figures 35 and 36 below). This may be attributed to the new analytical method being applied. The
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"current analysis (since Phase 10) of Cr6+ by Ion Chromatography (IC) with post-column derivatization
compared to the previous phases where analysis was performed by spectrophotometry. As the IC
method of analysis is more selective, the detection limit is lower (0.0001 μg/m3) and results for Cr6+ may
now be reported in μg/m3 to the fourth decimal (CSIR, 2013, p.2-3).”
Phase 16 reveals the following:
• Recorded levels of Cr6+ are lower than the levels recorded in the first three phases.
• The higher concentrations of chromium were recorded during winter months, this being attributed to the effect of meteorological conditions on ground level ambient concentrations of chromium. Conversely, the summer conditions result in the lowest concentrations of chromium.
In addition, since Phase 3 a Human Health Risk Assessment (HRA) component was built into the analysis annually and is vital to making informed management decisions. A HRA entails the identification of the probable negative effects of exposure to a hazardous substance, transit of substance and receptors. The research methods applied in the analysis of the data for the HRA were both qualitative and quantitative.
Figure 35: Annual average concentrations for Cr6+ Phases 2 - 16 (CSIR, 2013)
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Figure 36: Annual maxima concentrations for total Cr Phases 2-16 (CSIR, 2013)
The qualitative HRA performed on the monitored data concluded that "the non-cancer risk for exposure
to Cr6+ particulates and aerosols revealed that it would be unlikely for any individual, even sensitive
individuals, to develop non-cancer health effects when exposed to the concentrations measured during
Phase 16" (CSIR, 2013, p.iii). Hexavalent chromium is a confirmed human carcinogen, causing lung cancer. The CSIR determined the incremental cancer risk through a quantitative method. "If it is assumed that soluble Cr6+ is not
carcinogenic (according to the literature), then no incremental cancer risk is anticipated, as Lanxess
emits only soluble forms of Cr6+. However, should the monitored concentrations of Cr6+ contain
insoluble Cr6+, the incremental cancer risks would be as follows:
• Should 1% of the Cr6+ be considered insoluble, the incremental cancer risk is predicted to range
between no risks at all, to a risk between 0.4 and 0.6 in 10 million.
• Should the concentrations of Cr6+ contain 10% insoluble Cr6+, the incremental cancer risk ranges
between no risks at all, to a risk between 0.4 and 0.6 in 1 million.
• Should all of the Cr6+ emitted be considered insoluble, the incremental cancer risk could range
between no risks at all, to a risk between 3.6 in 1 million at Stations B, C and D and 6.0 in 1 million
at Station A (the Effluent Plant)."
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The CSIR (2013, p. 29) concluded in the HRA that it would be "highly unlikely for any individual, even
sensitive individuals, to develop non-cancer health effects (such as irritation or nasal septum atrophy)
as a result of airborne Cr6+ exposure as found during Phase 16."
Lanxess emits a soluble form of Cr6+, and the HRA states that "no incremental cancer risk is
anticipated."
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4.2.2.4 NPC-Cimpor NPC-Cimpor measures PM10 using the TEOM monitor. Data presented below are maximum daily averages for each month. The daily average National Standard of 120µg/m³ was exceeded four (4) times between June 2013 and April 2014. The exceedances were recorded during June, August, September and October 2013 with a maximum value of 157µg/m³ measured in September 2013.
Figure 37: NPC PM10 daily averages between 2013 and 2014
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5. Emission inventory
5.1 Introduction
An emission inventory is a listing of all sources of air pollution within a defined region for a specified period of time, and is an essential tool for air quality management planning. It provides information on the types of emission sources in a region, their location and the quantity of air pollution emitted, for a given period. The development of a complete emission inventory is an important step in an air quality management planning process. An emission inventory involves estimating and compiling a directory of emissions activities from different point, area and mobile sources in an area. Emission inventories are an important tool for the management of air quality and can be used to:
• establish emission trends over time
• support air quality modelling;
• support health assessments;
• estimate future emissions based on projected likely changes in socio-economic indices and setting of targets
• determine significant sources of air pollutants
• analyse emission control costs
• planning of policy and measures and target regulatory actions and
• develop possible control strategies. Typical sources of emissions are defined as point, non-point and mobile. Point sources are defined as a single identifiable source with high stacks and high emission loads and a fixed location of atmospheric emissions. Point sources include major industrial facilities like chemical plants, steel mills, oil refineries, power plants, and hazardous waste incinerators. Mobile sources include on-road and off-road sources. On-road include cars and light trucks, heavy trucks and buses, off-road recreational vehicles (such as dirt bikes and snowmobiles), farm and construction machines, lawn and garden equipment, marine engines, aircraft, and locomotives. Non-point source emissions means a source of atmospheric emissions which cannot be identified as having emanated from a single identifiable source or fixed location, and includes veld, forest and open fires, mining activities, agricultural activities and stockpiles. They are often more difficult to control than point source pollution.
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5.2 Atmospheric emission sources in ADM
Amajuba District Municipality has a strong industrial infrastructure, particularly Newcastle. The town of Newcastle is an economic hub of the district and hosts a variety of well-developed economic sectors (LED: ADM, 2013). Air pollution emission sources within the ADM are as a result of the following economic activities:
• Food production and textile manufacturing
• Mineral extraction mainly coal and industrial processes
• Agricultural activities Dannhauser is the smallest municipality within the ADM, but has been a key contributor as a coal producer and as a small rural service centre for the commercial, agricultural and industrial sectors. While mining and agriculture were previously on a larger-scale, the trend has moved towards smaller operations such as small-scale mining of coal, clays and reworking mine dumps. eMadlangeni is one of the oldest towns in KwaZulu-Natal with a large land area in the ADM yet it has the smallest population. Mining activity is limited with agriculture being the dominant economic activity. Other emission sources that are common to all three municipalities include waste disposal sites, domestic and biomass burning. Table 7 below provides a list of emission sources and relevant pollutants within Amajuba District Municipal area. Table 7: Emission sources and pollutants
Source SO2 NOX PM CO CO2 CH4 VOCs Chrome
Industrial (incl mining) x x x x x x x X Agriculture x Biomass burning x x x x x x x Traffic emissions x x x x x x x Landfill sites x x x x Tailings dams x Domestic Fuel Burning x x x x x x x Waste (Incineration, Landfills and Sewage) x x x x x x x
Petrol Stations x x x x x
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5.2.1 Industrial sources The majority of economic activities are concentrated in Newcastle with core economic activities being mining, industrial, manufacturing and agriculture. These activities include heavy and small
industries and most of them fall under the List of activities as contemplated in Section 21(1)(a) of the National Environmental Management: Air Quality Act, 2004 (Act No.39 of 2004) and the minimum emission standards for these listed activities as contemplated in Section 21 (3)(a) and (b) of the Act as set out in the Schedule and include:
• Lanxess Chrome International SA (Pty) Ltd
• SA Calcium Carbide (Pty) Ltd
• NPC Cimpor
• Newcastle Cogeneration (Pty) Ltd
• Silicon Technology (Pty) Ltd
• ArcelorMittal
• Karbochem and
• African Amines (Pty) Ltd. The industrial emissions are released via a total of 30 individual stacks. Pollutant releases include carbon monoxide, particulate Matter, sulphur dioxide, nitrogen oxides, and total organic compounds. The industrial processes are centered on the Riverside Industrial Park or are within the airport industrial area further south. The residential areas of Newcastle central, Ncandu Park and Madadeni lie approximately 1 to 2km to the west, north and east respectively. The majority of these industries have Atmospheric Emission Licences (AEL) issued by the ADM as the Licencing Authority.
5.2.1.1 Results of industrial emission inventory A district emissions inventory does not currently exist; therefore data collected by the KwaZulu-Natal Department of Agriculture and Environmental Affairs in 2007 is the only current information on hand. The inventory presented below only addresses industrial sources and transportation emissions. As part of this AQMP, a baseline emission inventory will be developed. This will serve as a basis for predictions of ground level pollutant concentrations. Predictions will be carried out for each pollutant based on the averaging periods stipulated in the National Ambient Air Quality Standards. Figure 38 shows that 51% of the industrial emissions in the study area is attributed to PM10 while the contribution by VOCs is minimal.
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Figure 38: Total emissions in ADM (Source: Zanokuhle - KZN-DAE&RD, 2007)
In addition, there are a number of small stationary sources that are classified as a controlled emitter in terms of section 23(1) of the National Environmental Management: Air Quality Act, 2004 that are operational in the ADM. The inventory for these sources is currently being undertaken.
5.2.2 Waste management Air pollution and nuisance odour from waste disposal and waste treatment sites negatively affects the health and well-being of the nearby residents. Health risks include significantly reduced height among children, lung and heart diseases and cancer (New York State Department of Health: 2008). Pollutants that emanate from these facilities include volatile organic compounds, methane, ammonia, hydrogen sulphide and particulates from vehicles. The ADM has permitted and non-permitted sites operating within her jurisdiction. According to South African Waste Information Centre (SAWIC), the ADM has 12 permitted waste management sites. Nine (9) of these are classified as hazardous sites, of which seven (7) are managed by industries and the balance fall under general waste.
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The Dannhauser and Watervaal waste disposal sites are operating without a permit and are poorly managed. The Charlestown waste site has no permit but operations are well managed. Like all other municipalities, ADM is plagued with illegal dumping and burning of waste. The illegal dumping causes havoc to municipal infrastructure as storm water drainage and manholes are being blocked and result in flooding (Newcastle IDP: 2013).
5.2.3 Mining The ADM is characterized by mining, both operational and non-operational as listed in Table 8. Many collieries have shutdown owing to the decline in mining and, local economic development has been forced to refocus (Urban-Econ & Sabalala, 2011). This has resultant to illegal activities from abandoned mines. Hauling, blasting, drilling, collection and transportation are part of the mining operations and are major sources of emissions and pollution. Pollution from coal mining is mainly due to emissions of particulate matter and gases including methane (CH4), sulphur dioxide (SO2), and oxides of nitrogen (NOx), as well as carbon monoxide (CO). Dust and coal particles stirred up during the mining process, as well as soot released during coal transport, contributes to emissions and respiratory problems. Elevated concentrations of suspended particulate matter stirred up during mining process and coal transportation can cause respiratory illnesses such as bronchitis and asthma, while gaseous fumes aggravate respiratory, cardiovascular, and cerebral problems. Coal additionally contains methane (CH4), a toxic greenhouse gas that contributes to global warming, which is discharged into the atmosphere during mining. Generally, the deeper a mine, the more methane it generates, despite the fact that methane outflow relies on the mining strategies, profundity of coal mining, coal quality, and entrapped gas content in coal seams.
Table 8: Operational and non-operational mines
Operational mines and quarries Non operational mines Kangra - Welgedacht, Utrecht Horn River U/S of Natal Coal Exploration
Iscor - Durnacol, Dannhauser Natal Coal Exploration Seepage
Utrecht Mine (S 702) Horn River D/S of Natal Exploration
Romad Mine (S 4051) Kliprand Dam
Zinoju Investments Kliprand Decant
Ngagane Quarry
Sunshine Crushers
In addition, the ADM has four known substantial brick production sites created in the abandoned coal mines in the Blaauwbosch area using clamp kilns. "Clamp kiln firing can take up to three weeks and
although the bricks might have finished burning in that time, it may take longer before they are cool
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enough to be sorted. Temperatures can be as high as 1 400 ̊C in the centre of the clamp” (Clay Brick
Association, 2002). Most likely air pollutants from the activities are SO2, dust and methane and heavy metals during mining. These are informal businesses and the operations have not fulfilled any licensing requirements,
business, environmental, air emissions, mining, land use and engineering and have led to serious impacts at a social level with underground mining leading to sink holes causing roads and school structures to collapse. Clay Brick Clamp Kilns is a listed activity as per section 21, Subcategory 5.2 of the NEM: AQA, 2004 (Act No. 39 of 2004).
Figure 39: Clay brick production area in Blaauwbosch
5.2.4 Indoor air quality Across much of the ADM, exposure to indoor air pollution is particularly influenced by indoor fuel combustion. This also affects the outdoor air quality and therefore merely venting the emissions outdoors may not be the best long-term solution, even though it effectively reduces pollutant levels indoors. In many situations, indoor air quality problems may be attributable to the lack of technology necessary to eliminate indoor air pollution (e.g. chimneys, ventilation and use of clean fuels) (Zanokuhle, 2009). There are many potentially hazardous compounds released indoors due to combustion, emissions from building materials, household equipment and consumer products. Microbial pollution also originates from hundreds of species of bacteria, fungi, and moulds found indoors (Zanokuhle, 2009).
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Figure 40: Domestic fuel use in the ADM (STATS SA census 2011)
Electricity is predominantly used for all household activities in Newcastle. Dannhauser uses mixed fuels with electricity being primary and coal secondary. Wood is the dominant fuel used for heating in the Emadlangeni area (48.5%) followed by coal. Animal dung is an alternative fuel predominantly used for heating in the Emadlangeni and Dannhauser areas. Solid fuels combustion are frequently incomplete using poorly vented combustion devices such as open fires and conventional stoves. This inefficient combustion of these fuels are the main causes of fuel toxic pollutants such particles of varying sizes, carbon monoxide (CO), nitrogen dioxide, volatile and semivolatile organic compounds (e.g., formaldehyde and benzo[a]pyrene), methylene chloride, and dioxins (Naeher et al. 2007)., sulphur oxides, heavy metals such as arsenic, and fluorine (WHO, 2006). Other indoor pollutants include biological agents largely attributable to dampness and inadequate ventilation. Excess moisture on any material leads to growth of microbes such as moulds, fungi and bacteria, which subsequently emit spores, cells, fragments and volatile organic compounds into the indoor air. Moreover, dampness initiates chemical and/or biological degradation of materials which also causes pollution of the indoor air. Dampness has been suggested to be the strongest and most consistent indicator of risk for asthma and respiratory symptoms (WHO, 2006). Paraffin is nearly as popular as wood for cooking in low-income households using this fuel. Paraffin is one of the primary commercial sources of energy in low-income rural and urban households. According
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to STATS SA census 2011, less than 10% households in ADM use paraffin. Hydrocarbons, VOCs and the carbon monoxide are emitted during paraffin burning. Table 9 provides a more comprehensive list of indoor air contaminants. Table 9: Sources of Common Indoor Air Pollutants (Guideline for Monitoring Domestic Indoor Air Quality in South Africa, 2009)
Pollutant Origin
Infiltrating from Outdoors Emitted Indoors
NOx, CO, SO2 Traffic, fuel combustion Combustion appliances, smoking
CO2 Traffic, fuel combustion, biological processes
Human occupants, combustion appliances, smoking
Ozone Action of sunlight on NOx and VOCs Office equipment
Particulates Natural processes, traffic, combustion Cooking, smoking, combustion appliances, furnishings
Benzene Vehicles, petrol stations Smoking, solvents
VOCs Industry, vehicles, petrol stations Building and decorating materials, furnishings, consumer products
PAHs Traffic, combustion Cooking, smoking, combustion appliances
Aldehydes Traffic, industry, combustion. Less significant than for indoor sources
Smoking, resins, wood products, wall insulation, textiles
5.2.5 Transportation and tyre burning Mobile sources results included in this report are cars, trucks, motorbikes and buses. Emissions were calculated using total fuel used or purchased in the ADM. Emissions of SO2 were calculated using a simple mass balance approach (i.e. assuming that all of the sulphur in the fuel is converted to SO2), which is a commonly-used approach. Emissions of other pollutants (NOx, VOC, PM and CO) have also been calculated based on fuel use, with emission factors derived from the "Brown Haze Study" used to estimate pollutant emissions. Figure 41 highlights the air pollutants from vehicle emissions and shows the vehicles are the main contributors of carbon monoxide in ADM followed by particulate matter and volatile organic compounds. Illegal tyre burning was not considered during KZN 2007 inventory but are a major challenge in the ADM air quality. A cocktail of pollutants is released during the process including criteria pollutants such as PM10, PM2.5, CO, SO2 and NO2 (SAEO, 2012).
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Figure 41: Total emissions in ADM (Source: Zanokuhle - KZN-DAE&RD, 2007)
5.2.6 Biomass burning and agricultural activities "Biomass burning is the burning of living and dead vegetation. It includes the human-initiated burning of
vegetation for land clearing and land-use change as well as natural, lightning-induced fires. Scientists
estimate that humans are responsible for about 90% of biomass burning with only a small percentage of
natural fires contributing to the total amount of vegetation burned (http://earthobservatory.nasa.gov) ".
Biomass burning in ADM is used for clearing weeds and waste after harvesting on agricultural land, shifting crops and greening for grazing. Most of these fires are controlled and mainly by farmers. The ADM also experiences wildfires that are caused through negligence. These fires often get out of control and pose a risk to life, property, and the environment. Smoke emitted during biomass burning includes a mixture of gases. These gases include methane, oxides of nitrogen, volatile organic compounds, carbon dioxide, carbon monoxide, particulate matter in varying sizes and hydrocarbons depending on the composition of the source. The ADM major crops are maize and wheat (Udidi, 2003) and are responsible for dust challenges experienced.
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6. Dispersion modelling
6.1 Introduction
Emissions are dispersed and diluted in the atmosphere before reaching people or different receptor points. Air quality modelling seeks to combine knowledge of pollutant source strengths (i.e. emitted quantities per unit time) with meteorological data to estimate concentrations at the receptor points. Models have varying degrees of sophistication and accuracy and are rarely better than approximately 20 to 30 percent of the "actual value", unless the model is "tuned" by use of pollution monitoring data (stochastic modelling). Air quality models are used to establish a relationship between emissions and air quality. Dispersion models applied as well as related sources of pollution are often divided into spatial scales such as indicated below:
Area Spatial scale Typical sources Pollutants
Local 10 - 500 m Points, low stacks, low-level area sources and traffic
SO2, NO2, PM, CO
Urban 1 - 50 km Multiple sources, low-level area sources, small industries, traffic and general human activities
PM, NO2, SO2, Oxidants
Regional 100 - 1000 km Power plants, large industrial areas, urban areas
PM10, PM2,5, O3, secondary pollutants
Meteorological data and knowledge of physical and chemical reactions in the atmosphere are used to calculate the air concentrations of one or more pollutants as a function of time and space. Observed concentrations at the monitoring stations are used to validate the calculated concentrations from model descriptions of emission and atmospheric dispersion. Measurements may also be used to improve the accuracy of calculated concentration fields when they are treated statistically along with results of dispersion models. The municipality has not conducted any type of air dispersion modelling.
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7. Evaluation of Current Management and tools
7.1 Legal Overview
The legislation governing the management of air quality with the ADM includes but not limited to:
• Constitution of the Republic of South Africa Act, 1996 (Act No. 108 of 1996)
• Criminal Procedures Act, 1977 (Act No. 51 of 1977)
• Municipal by-laws
• Municipal Structures Act, 1998 (Act No. 107 of 1998) & Municipal Systems Act, 2000 (Act No. 32 of 2000)
• National Environmental Management: Air Quality Act, Act No. 39 of 2004 (AQA)
• National Framework for Air quality Management in South Africa, 2007
• National Health Act, 2003 (Act No. 61 of 2003)
7.1.1 An Air Quality Officer (AQO) In terms of the AQA Section 14, each municipality must designate an air quality officer (AQO) from its administration to be responsible for co-ordinating matters pertaining to air quality management within the municipality. Since the AQO will deal with specific air quality management issues, he/ she must have some knowledge of air quality management. The profile of an AQO is likely to be:
• A person who is specifically responsible for air quality management within the municipality;
• A person who has a broad knowledge and understanding of air quality related issues and air quality management;
• A person who can be mandated to represent the municipality in meetings with other AQO's;
• A person who has sufficient authority to make technical decisions on AQO issues.
• A middle- to senior-level manager; The ADM has an AQO and recently appointed an assistant air quality director.
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7.1.2 Areas of responsibility for the ADM The current air quality governance approach driven primarily by the AQA, necessitates that district municipalities fulfil the functions listed in Table 10 below. The table highlights the requirements in terms of the legal aspects and also notes the current status of the service within the ADM based on the information received from the municipality. Table 10: District's areas of responsibility Area of responsibility Output required Current status of
Appointment of an AQO Designation of an AQO Appointed
To monitor ambient air quality and point , non-point and mobile source emissions
Show compliance to South African emission and ambient air quality standards through monitoring & reporting. Dealing with complaints.
Not implemented
Development of air quality management plan, aligned to the IDP and local municipal AQMP's as required by the Municipal Systems Act.
Preparation of reports In progress
The setting of municipal standards for emissions from point, non-point or mobile sources in the municipality in respect of identified substances or mixtures of substances in ambient air which, through ambient concentrations, bioaccumulation, deposition or in any other way, present a threat to health, well-being or the environment in the municipality.
Set local bylaws on air quality standards In progress
Implement the AQA AE Licensing system referred and for this purpose perform the functions of licensing authority as set out in Chapter 5 and other provisions of the AQA.
Monitoring against standards & policing of list compliance In place
Monitoring potential illegal listed activities Action against offenders In progress
Monitoring compliance with emission standards in respect of the manufacture, sale or use any appliance or conducting of an activity declared as a controlled emitter.
Enforcing section 23 of AQA In progress
Monitoring compliance with conditions or requirements of an atmospheric emission licence.
Set local bylaws on air quality standards. In progress
Monitoring any application for an atmospheric emission licence, or for the transfer, variation or renewal of such a licence to ensure that it does not contain false or misleading information
Ongoing
Appointment of Emission Control Officers Appointment of Emission Control Officer by Atmospheric Emission License Holder through the authority of the AQO.
ADM looking at handing down the responsibility to municipality and play overseeing role
Prosecution of offenders wrt section 51 of the AQA Collation of complaints and investigations, laying of charges with the National Prosecution Authority
Not implemented
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7.2 Overview of Current Air Quality Management within ADM
7.3 Existing staff structure
The environmental management sub-directorate has two staff members i.e. Deputy Director Environmental Management and Assistant Director Air Quality management. The department falls under the Planning and Development directorate. The function of Deputy Director Environmental Management is to coordinate, facilitate and oversee the effective functioning of Environmental Management sections such as, Air Quality Management, Environmental Planning, Waste Management and Pollution Control in order to ensure sustainable use and protection of the environment through appropriate regulatory mechanisms. Manage and Control functions relating to the protection of the environment in accordance with the provisions of the National Environmental Management Act (Act 107 of 1998), Environmental Conservation Act (Act 73 of 1989), and National Water Act (Act 36 of 1998). This includes:
• Development of the district Air quality management plan, implementation and control in terms of the Air Quality Act
• Assess, process and advise on Air Emission licences
• Assess, comment and advise on environmental application documents
• Manage activities related to environmental protection
• Plan and coordinate environmental capacity building and awareness initiatives
• Coordinate the development and maintenance of systems , policies, procedures and processes
• Plans and manages utilisation of resources
• Compliance Monitoring and Enforcement
• Monitor the section's budget The Assistant Director Air Quality is responsible for the following:
• Plan and co-ordinate implementation of environmental management programmes
• Co-ordinate and facilitate air quality management, clean and green (including climate change) activities
• Participating in the Environmental Impact Assessment Process
• Plan, coordinate and participate in the drafting and implementation of environmental management plans
• Processing of Air Emission Licences
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The staff structure for the Planning and Development Directorate within the ADM is presented in Figure 42 below. The organogram indicates that there are two sections within the Planning and Development Services. It is indicated that these sections run independently of each other and each with varying numbers of staff.
Figure 42: Current staff structure Planning and Development Directorate
In addition, the air quality staff is responsible for:
• Complaints investigation and feedback to complainants.
• Guiding other spheres of government with regards to air quality issues e. g. Blaauwbosch concern where Department of Mineral Resources and Department of Cooperative Governance and Traditional Affairs (CoGTA) are involve on illegal mining.
• Interdepartmental air quality issues e. g. Air quality issues from waste management facilities
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8. Gap and problem analysis
A gap analysis is undertaken to evaluate whether institutional functions and resources available within the district municipality is sufficient to address air quality issues within the area. This is why the consultation with stakeholders, other spheres of government and public participation is necessary to understand the potential air quality issues and what may need to be incorporated to “address the gaps.”
Once management gaps are analysed, a problem analysis follows to determine problems, associated cause of the problems and the effects.
During the development of the baseline assessment, the following immediate issues (gaps) in terms of air quality management within the ADM were highlighted:
• Limited human resources and technical capacity to effectively manage air quality in the ADM.
• Lack of air quality management information to help make informed and health-protection decisions
• Lack of inter-governmental relationships
• Domestic fuel burning
• Agricultural activities
• Limitations on monitoring atmospheric emission licences.
• Monitoring of waste management facilities
Each of the problems noted above are interrogated using the Logical Framework Approach (LFA). The analysis of each of the problems is presented in sections 8.1 to 8.6.
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8.1 Human resources and technical capacity
Limited human resources and lack of technical skills does not allow the effective execution of the responsibilities noted in job description and falls short on service delivery in this area.
Human resources and capacity encompasses institutional capacity within the municipality and technical skills.
Problem analysis 1. The current staff constraint within the municipality compromises on delivery of service within the municipal
2. Skills’ shortage to existing staff to effecting function
Problem cause 1. Shortage of allocation of funds and human resources for the air quality management function.
2. Skills shortage 3. The air quality function is competing with other functions and is not given the
priority it requires 4. Training of staff is not sufficient and 5. Lack of available resources including equipment.
Problem effects 1. Legal responsibilities are not fulfilled owing to limited human resources.
Objectives 1. To ensure that staff are designated to the required roles for effective air quality management and that they are adequately trained for their roles (see proposed structure in figure 43)
2. To ensure that sufficient funds are allocated for the air quality management function.
Figure 43: Proposed staff structure Environmental Management Directorate
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8.2 Lack of information on Air Quality Management System (AQMS)
ADM have no air quality management information to help make informed and health-protective decisions. The lacking AQMS information include:
• Ambient air monitoring
• Emission inventory
• Air dispersion modelling
Problem analysis
1. No ambient air quality monitoring information for meaningful decision making.
2. The stations operated by the Province and industries are not operated strictly within a quality system and the data validity cannot be verified.
3. Inventory of emission sources is not available except information supplied with listed activities applications
4. Existing modelling studies were done by industries
Problem cause
1. Shortage of allocation of funds for the air quality management function. 2. The air quality function is competing with other functions and is not given the
priority it requires 3. Lack of an integrated approach to the management of an AQMS between
stakeholders (provincial, district, local municipality and industry). 4. No cooperative governance particularly between local and district spheres
Problem effects
1. No quality assurance/ quality control in place for existing data 2. unable to assess the exposure of vulnerable receptors 3. No established list of sources of emissions or their contribution. 4. Haphazard approach to air quality management (AQM).
Objectives 1. Ambient air quality data spatially representative of the area. 2. Inventory of all emission sources in order to respond to AQA (Section 21 &
23) 3. Undertake air dispersion model especially for hot spot areas
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8.3 Absent intergovernmental relationships
There is no formally established cooperative governance between Newcastle Local Municipality (NLM) and the Amajuba District Municipality in relation to air quality issues.
Problem analysis 1. No communication between local and district with regards to air quality issues.
2. Lack of initiative at the two spheres of government to initiate this cooperative approach to the management of air quality in the area.
Problem cause 1. Roles and responsibilities need to be clearly defined. 2. Assignment of the responsibility at the ADM level to initiate
communication with the NLM,
Problem effects 1. Confusing stakeholders. 2. Wastage of funds. 3. Duplication of services. 4. Ineffective management of air quality in the area.
Objectives 1. Shared responsibilities and vision. 2. Setting up an air quality forum between the NLM and the ADM to ensure
that air quality management is addressed effectively.
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8.4 Domestic fuel burning
Low income households in rural (mainly Emadlangeni and Utrecht) and some urban areas within the ADM use wood, paraffin and coal for cooking and space heating. Other biomass fuels such as crop residues are sometimes also used (STATSA, 2011). This results in emissions that could lead to environmental and adverse health impacts. Problem analysis
1. Geographical location, as well as income, is a strong determinant of fuel use. Generally low-income households in densely populated areas (urban or peri-urban) rely on domestic fuel as an energy source for household needs.
2. Domestic fuel use increases in winter in this region due to lower ambient temperatures.
Problem cause
1. Given the availability of inexpensive coal and the relatively low temperatures in winter, coal consumption figures are elevated within this region.
2. Increasing electricity prices causes a problem for majority of low income households, thus household energy needs in most low income homes are met by use of fuels like paraffin, wood and coal for space heating.
3. Lack of mitigation methods for domestic fuel burning. 4. Poor household ventilation. 5. Poor fuel use techniques.
Problem effects
1. Exposure to emissions from fuel burning causing adverse health effects especially upper respiratory problems.
2. Ambient air pollution..
Objectives 1. Improve the efficiency of fuel burning. 2. Electrification of households. 3. Use of renewable energy sources.
Source: ZES, 2008
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9. Goal Setting
The vision and mission of the AQMP are underpinned by the following:
• Current air quality legislation “Vision Amajuba will be a leading and pioneering District characterised by sustainable development
and quality services
Mission The Amajuba District Municipality will champion good governance through:
• Effective public participation
• Vibrant Local Economic Development
• Integrated Service Delivery
• Intergovernmental Relations”
Vision To provide an integrated approach to the management of air quality in the ADM towards a sustainable environment.
Mission To support an inter-governmental approach to managing air quality in the district to ensure sustainability and effective public participation.
Goals The AQMP has three primary goals reflected in the vision and mission statements.
1. To develop and maintain governmental capacity for continued air quality management within the district.
2. To ensure effective communication and stakeholder participation relating to air quality issues.
3. To minimise the negative impacts of poor air quality on health and the environment.
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10. References
Clay Brick Association, 2002. Clay brick manufacture; technical guide – CIDB
Clean Air Assistance Program: Environmental Science and Services Division Michigan Department of Environmental Quality, January 2004, Calculating air emissions for the Michigan Air Emissions
Department of Environmental Affairs, 2012, South Africa Environment Outlook, Chapter 5: Air Quality (Draft 2)
(http://earthobservatory.nasa.gov)
http://www.saexplorer.co.za
Korsman and Van Wyk Consortium., 2002. Utretch IDP- Data and Munnicipal Analysis. The Utretch Local Municipality.
Naeher LP, Brauer M, Lipsett M, Zelikoff JT, Simpson CD, Koenig JQ, et al. 2007. Woodsmoke health effects: a review. Inhal Toxicol 19(1):67–106.
National Environmental Management: Air Quality Act, Act No. 39 of 2004 (AQA)
Newcastle Municipality Integrated Development Plan, 2012 – 2017. First Draft
South African Weather Services
Statistics South Africa (Stats SA), 2011: Amajuba District Municipality. Pretoria: Statistics South Africa,
Thornhill, M., Richardson, J., and George, S., 2013: Updated Status Quo Report for the Newcastle Environmental Management Framework. Report No TX2013/C037, Pietermaritzburg, South Africa.
Tyson, P.D., 1987: Climatic Change and Variability in Southern Africa, Oxford University Press, Cape Town.
Udidi Project Development Company, 2003, Amajuba District Municipality Environmental Management Plan
Urban-Econ KZN and Sabalala Consulting Africa, 2011: Amajuba District Municipality Review of the Local Economic Development Strategy
University of KwaZulu-Natal., 2013: The GIS unit, School of Agricultural, Earth and Environmental Sciences.
WHO, 2006: Development of WHO Guidelines for Indoor Air Quality. Report on a Working Group Meeting Bonn, Germany 23-24 October 2006. EUR/05/5067585
Zanokuhle Environmental Services, 2007, Emission inventory for KwaZulu-Natal, Department of Agriculture, Environment Affairs and Rural Development
Zanokuhle Environmental Services, 2009: guidelines for monitoring indoor air pollution in South Africa, Department of Health
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Appendix 1
Digital Elevation Model (DEM)
![Energy XT PRO BaseLine Application [A00003xx-A00013xx]mosinv.ru/Documentation/XT-PRO/8MA10073 EXT Pro Baseline... · Energy XT PRO BaseLine Application [A00003xx-A00013xx] BaseLine](https://img.dokumen.tips/doc/110x75/5ca5dcdf88c99388188d3802/energy-xt-pro-baseline-application-a00003xx-a00013xx-ext-pro-baseline-energy.jpg)
