ATMOSPHERIC IMPACT REPORT In support of

Transcription

1 ATMOSPHERIC IMPACT REPORT In support of Eskom s application for postponement of the Minimum Emission Standards compliance timeframes for the Duvha Power Station Prepared by: Naledzi Environmental Consultants (NEC) 145 Thabo Mbeki Street, Fauna Park, Polokwane, 0700 South Africa Date: November 2018 Report prepared for: Eskom SOC Ltd Version: Draft i

2 This report has been prepared by Naledzi Environmental Consultants (Pty) Ltd in association with umoya- NILU Consulting (Pty) Ltd representing Eskom SOC Ltd. No part of the report may be reproduced in any manner without written permission from Naledzi Environmental Consultants (Pty) Ltd and umoya-nilu Consulting (Pty) Ltd representing Eskom SOC Ltd. Authorship: Naledzi Environmental Consultants (Pty) Ltd (NEC) 145 Thabo Mbeki Street, Fauna Park, Polokwane, 0700 South Africa Lead Author: Sean O Beirne BA Hons (Geography) & MSc (Radar rainfall measurement) Certified Environmental Assessment Practitioner Tel: / sobeirne@tiscali.co.za and: umoya-nilu Consulting (Pty) Ltd P O Box Durban North, 4016 South Africa Co-Authors: M Zunckel A Raghunandan National Diploma (Meterology); BSc (Meterology); BSc Hons (Meterology); MSc and PHD. Professional Natural Scientist: SACNASP: /04 MA (Atmospheric Sciences); BA Hons (Environmental Sciences); BPaed (Education) Tel: / mark@umoya-nilu.co.za Report Date: November 2018 ii

3 EXECUTIVE SUMMARY Eskom s coal-fired Duvha Power Station (hereafter referred to as Duvha ) in Mpumalanga Province has a base generation capacity of MW. Power generation is a Listed Activity in terms of Section 21 of the National Environmental Management: Air Quality Act, 2004 (Act No. 39 of 2004) (NEMAQA) and Duvha currently complies with both the new plant limits for PM on units 1 to 3 and the existing plant limits for units 4 to 6. Duvha is in the process of refurbishing the ESPs and installing HFPS and postponement from the new plant standard until 2025 is requested on Units 4 to 6 until these projects are completed. From 2025 an alternate limit of 80 mg/nm3 is requested on Units 4 to 6 for the remaining life of the station. Duvha will not be able to comply with new plant MES for both NOx and SO2 due to financial, technical and water limitations. As such the power station is requesting alternative emissions limits of mg/nm 3 for NOx emissions and mg/nm 3 for SO2 emissions until the end of life of the power station. The decommissioning of Duvha is scheduled for 2030 to The purpose of this AIR has been to assess the likely implications of the postponement and the requested alternative emissions limits for human health and the environment. The AIR contains two major parts namely an analysis of the ambient air quality likely to be affected by emissions from the power station and secondly, dispersion modelling of two different emissions scenarios to predict the likely impacts of the power station on that prevailing air quality. These two emissions scenarios are: Current emissions from the power station; and, Compliance with the MES. Duvha operates in an area of elevated ambient SO2 as a result of multiple other sources in the area as indicated in the summary ambient air quality table below. This elevated loading is reflected in the ambient air quality measurements where non-compliance with the National Ambient Air Quality Standards (NAAQS) is evident in Witbank (2015 and 2016) and Komati (2016) for daily and annual average concentrations. Even where compliance with the SO2 NAAQS is implied by the monitored data full compliance cannot be assured where the data record is incomplete (less than 80% data recovery for the year). Ambient NOx measured at Komati, Middleburg and the Witbank monitoring stations indicates compliance with the hourly and annual NO2 NAAQS. Even where compliance with the NAAQS is implied by the monitored data full compliance cannot be assured where the data record is incomplete (less than 80% data recovery for the year) Summary table of compliance with the NAAQS for each of the ambient air quality monitoring stations used in this analysis. Duvha Power Station Averaging period 10 minute SO2 1 hour SO Y* Y Y Y Y N Y N Y* Middelburg 2016 NM Y* Y* Y* Y* Y* Y Y Y Y 2017 Y* Y* Y* Y* Y* N* N* N* N 2015 Y* N* Y* Y Y N N N N Witbank 2016 NM Y* N* Y* Y Y N N N N 2017 Y* Y* Y* Y* Y* N* Y* N* N* 2015 Y* Y Y* Y Y Y N N Y* Y* Komati 2016 Y* Y* N Y* Y* Y* N N N Y 2017 Y Y Y* Y Y* Y* N N N N 2015 Y* Y* Y* Y* DD DD Y Y N* N* Phola 2016 Y Y Y Y DD DD N N N N 2017 Y Y Y Y DD DD N N N N NM Not measured. DD Data Deficient. *Data set is <80% Daily SO2 Annual SO2 1 hour NO2 Annual NO2 Daily PM10 Annual PM10 Daily PM2.5 Annual PM2.5 i

4 Dispersion modelling of the current emissions for SO2, NOx and PM10 from Duvha alone, indicates compliance with the relevant NAAQS for all averaging periods. The net effect of all of the above is that PM is already and unequivocally resulting in unacceptable health risk for a large part of the Highveld. The direct contribution of Duvha alone to that situation is considered to be small even taking into account predicted concentrations of secondary PM2.5. This AIR should be read, however, in conjunction with the Summary AIR that contains the predicted concentrations as a result of the combined emissions from all the power stations. Compliance summary of the predicted ambient concentrations for the three emissions scenarios modelled for Duvha. Averaging period Scenario 1 - Actual Emissions Scenario 2 - New plant MES compliance SO2 (µg/m 3 ) 1-hour Yes Yes 24-hour Yes Yes Annual Yes Yes NO2 (µg/m 3 ) 1-hour Yes Yes Annual Yes Yes PM10 and PM2,5 (µg/m 3 ) 24-hour Yes Yes Annual Yes Yes ii

5 LIST OF ACRONYMS AND ABBREVIATIONS µm 1 µm = 10-6 m AEL Atmospheric Emission License AIR Atmospheric Impact Report APPA Atmospheric Pollution Prevention Act, 1965 (Act No. 45 of 1965) AQMP Air Quality Management Plan BID Background Information Document DEA Department of Environmental Affairs DoE Department of Energy ESP Electrostatic precipitator FFP Fabric Filter Plant FGD Flue gas desulphurisation IRP Integrated Resource Plan LNB Low NOx Burner LPG Liquid Petroleum Gas NAAQS National Ambient Air Quality Standards NEMAQA National Environment Management: Air Quality Act, 2004 (Act No. 39 of 2004) NEMA National Environmental Management Act, 1998 (Act No. 107 of 1998) NO Nitrogen oxide NO2 Nitrogen dioxide NOX Oxides of nitrogen (NOX = NO + NO2) OFA Overfire Air PM Particulate Matter PM10 Particulate Matter with a diameter of less than 10 µm PM2.5 Particulate Matter with a diameter of less than 2.5 µm SO2 TSP WHO Sulphur Dioxide Total Suspended Particulates World Health Organisation iii

6 TABLE OF CONTENTS EXECUTIVE SUMMARY... i LIST OF ACRONYMS AND ABBREVIATIONS... iii TABLE OF CONTENTS... iv TABLES... v FIGURES... vi 1. Enterprise Details Enterprise Details Location and extent of the Plant Atmospheric Emission License and Other Authorisations Minimum Emission Standards National Ambient Air Quality Standards (NAAQS) Nature of the Process Listed Activity or Activities Process Description Atmospheric emissions resulting from power generation Unit Processes Technical Information Raw Materials Used Abatement Equipment Control Technology Atmospheric emissions Point source parameters Point source maximum emission rates (normal operating conditions) Point source maximum emission rates (start-up, shut-down, upset and maintenance conditions) Fugitive emissions Emergency Incidents Impact of Enterprise on the Receiving Environment Analysis of emissions Overview Prevailing climatic conditions Current status of ambient air quality Introduction Ambient air quality monitoring Sulphur dioxide (SO2) Nitrogen dioxide (NO2) Particulate Matter (PM10) Particulate Matter (PM2.5) Source apportionment Dispersion modelling Models used Model parameterisation Model accuracy Comparison between measured and modelled values Modelled ambient concentrations for Duvha Modelled operational scenarios Combined emissions scenario Annual and 99th percentile concentrations Scenario 1: Current actual emissions iv

7 Scenario 2: New Plant MES Compliance Analysis of Emissions Impact on Human Health Potential health effects Analysis Analysis of Emissions Impact on the Environment Complaints Current or planned air quality management interventions Compliance and Enforcement History Additional Information Summary and conclusion Ambient air quality Predicted ambient concentrations References Formal Declarations TABLES Table 1: Enterprise details... 9 Table 2: Site information Table 3: Current government authorisations related to air quality Table 4: Minimum Emission Standards for combustion installations (Category 1) using solid fuel for electricity generation (Sub-category 1.1) with a design capacity equal to or greater than 50 MW heat input per unit Table 5: National Ambient Air Quality Standards for SO2, NO2 and PM10 (DEA, 2009) and PM2.5 (DEA, 2012a) Table 6: Activities listed in GN 893 which are triggered by the Duvha Power Station Table 7: Unit processes at Duvha Power Station Table 8: Raw material used at Duvha Power Station Table 9: Production rates at Duvha Power Station Table 10: Energy sources used at Duvha Power Station Table 11: Abatement equipment control technology currently in use at Duvha Power Station Table 12: Point sources at Duvha Power Station Table 13: Current emission limits for normal operating conditions at Duvha Power Station Table 14: Number of start-ups at Duvha Power Station since the start of the 2016/17 financial year. 18 Table 15: Record of emergency incidents which occurred at Duvha Power Station from 1 April 2017 to 31 March Table 16: Relative positions of the ambient air quality monitoring stations used in this assessment, to the Duvha Power Station Table 17: Summary ambient 10-minute SO2 average concentrations for the Komati ambient air quality monitoring station. All concentrations are in μg/m Table 18: Summary ambient hourly SO2 average concentrations for the Komati, Middelburg and Witbank ambient air quality monitoring stations. All concentrations are in μg/m Table 19: Summary ambient 24-hour SO2 average concentrations for the Komati, Middelburg and Witbank ambient air quality monitoring stations. All concentrations are in μg/m Table 20: Summary ambient annual SO2 average concentrations for the for the Komati, Middelburg and Witbank ambient air quality monitoring stations. All concentrations are in μg/m Table 21: Summary ambient hourly NO2 average concentrations for the for the Komati, Middelburg and Witbank ambient air quality monitoring stations. All concentrations are in μg/m Table 22: Summary ambient annual NO2 average concentrations for the Komati, Middelburg and Witbank ambient air quality monitoring stations. All concentrations are in μg/m v

8 Table 23: Summary ambient 24-hour PM10 average concentrations for the Komati, Middelburg and Witbank ambient air quality monitoring stations. All concentrations are in μg/m Table 24: Summary ambient annual PM10 average concentrations for the Komati, Middelburg and Witbank ambient air quality monitoring stations. All concentrations are in μg/m Table 25: Summary ambient 24-hour PM2.5 average concentrations for the Komati, Middelburg and Witbank ambient air quality monitoring stations. All concentrations are in μg/m Table 26: Summary ambient annual PM2.5 average concentrations for the Komati, Middelburg and Witbank ambient air quality monitoring stations. All concentrations are in μg/m Table 27: Parameterisation of key variables for CALMET Table 28: Parameterisation of key variables for CALPUFF Table 29: Current average emissions (tons/annum) and Eskom requested emission limits (tons/annum) for Duvha Power Station Table 30: Maximum predicted annual average concentration and the highest 99 th percentile concentration at the points of maximum ground-level impact for the two scenarios Table 31: Summary of compliance with the NAAQS for each of the ambient air quality monitoring stations used in this analysis Table 32: Summary of compliance with the NAAQS for ambient air quality predicted for each of the emissions scenarios modelled for Duvha Table 34: Complaints register for Duvha from 2016/17 to September FIGURES Figure 1: Relative location of the Duvha Power Station (Google Earth, 2013) Figure 2: A basic atmospheric emissions mass balance for Duvha Power Station showing the key inputs and outputs. Note that all quantities are expressed in tonnes per annum unless otherwise stated and are based on the 2016/2017 financial year Figure 3: Relative location of the different process units at Duvha Power Station Figure 4: Average monthly maximum and minimum temperature, and average monthly rainfall at Loskop Dam from 1961 to Figure 5: Annual windrose for Komati 2010 to Figure 6: Relative positions of the ambient air quality monitoring stations used in this assessment, to the Duvha Power Station Figure 7: Cumulative percentage occurrence of 10-minute average SO2 concentrations measured at the Komati ambient air quality monitoring station. Only values above the 99 th percentile are shown for clarity purposes Figure 8: Cumulative percentage occurrence of hourly average SO2 concentrations measured at the Komati ambient air quality monitoring station. Only values above the 90 th percentile are shown for clarity purposes Figure 9: Cumulative percentage occurrence of hourly average SO2 concentrations measured at the Middelburg ambient air quality monitoring station. Only values above the 90 th percentile are shown for clarity purposes Figure 10: Cumulative percentage occurrence of hourly average SO2 concentrations measured at the Witbank ambient air quality monitoring station. Only values above the 90 th percentile are shown for clarity purposes Figure 11: Cumulative percentage occurrence of daily average SO2 concentrations measured at the Komati ambient air quality monitoring station Figure 12: Cumulative percentage occurrence of daily average SO2 concentrations measured at the Middelburg ambient air quality monitoring station Figure 13: Cumulative percentage occurrence of daily average SO2 concentrations measured at the Witbank ambient air quality monitoring station vi

9 Figure 14: Cumulative percentage occurrence of hourly average NO2 concentrations measured at the Komati ambient air quality monitoring station. Only values above the 90 th percentile are shown for clarity purposes Figure 15: Cumulative percentage occurrence of hourly average NO2 concentrations measured at the Middelburg ambient air quality monitoring station. Only values above the 90 th percentile are shown for clarity purposes Figure 16: Cumulative percentage occurrence of hourly average NO2 concentrations measured at the Witbank ambient air quality monitoring station. Only values above the 90 th percentile are shown for clarity purposes Figure 17: Cumulative percentage occurrence of daily average PM10 concentrations measured at the Komati ambient air quality monitoring station Figure 18: Cumulative percentage occurrence of daily average PM10 concentrations measured at the Middelburg ambient air quality monitoring station Figure 19: Cumulative percentage occurrence of daily average PM10 concentrations measured at the Witbank ambient air quality monitoring station Figure 20: Cumulative percentage occurrence of daily average PM2.5 concentrations measured at the Komati ambient air quality monitoring station Figure 21: Cumulative percentage occurrence of daily average PM2.5 concentrations measured at the Middelburg ambient air quality monitoring station Figure 22: Cumulative percentage occurrence of daily average PM2.5 concentrations measured at the Witbank ambient air quality monitoring station Figure 23: Area plot of the range of average diurnal SO2 concentrations for all monitoring stations across the Mpumulanga Highveld ( ) Figure 24: Area plot of the range of average diurnal NO2 concentrations for all monitoring stations across the Mpumulanga Highveld ( ) Figure 25: Area plot of the range of average diurnal PM10 concentrations for all monitoring stations across the Mpumulanga Highveld ( ) Figure 26: Area plot of the range of average diurnal PM2.5 concentrations for all monitoring stations across the Mpumulanga Highveld ( ) Figure 27: Area plot of the range of average diurnal SO2, NO2, PM10 and PM2.5 concentrations for all monitoring stations across the Mpumulanga Highveld ( ) Figure 28: TAPM and CALPUFF modelling domains for Duvha Figure 29: Conceptual illustration of the method used to compare modelled and measured ambient hourly SO2 concentrations Figure 30: Comparison between modelled and measured hourly SO2 concentrations at the Middelburg ambient air quality monitoring station. An exact correlation would mean 100% Figure 31: Comparison between modelled and measured hourly SO2 concentrations at the Witbank ambient air quality monitoring station. An exact correlation would mean 100% Figure 32: Comparison between modelled and measured hourly SO2 concentrations at the Komati ambient air quality monitoring station. An exact correlation would mean 100% Figure 33: Predicted annual average SO2 concentrations (µg/m 3 ) resulting from actual emissions for Duvha Power Station (Scenario 1) Figure 34: 99 th percentile concentration of the predicted 24-hour SO2 concentrations for actual emissions for Duvha Power Station (Scenario 1) Figure 35: 99 th percentile of the predicted 1-hour SO2 concentrations resulting from actual emissions for Duvha Power Station (Scenario 1) Figure 36: Predicted annual average NO2 concentrations (µg/m 3 ) resulting from actual emissions for Duvha Power Station (Scenario 1) Figure 37: 99 th percentile of the predicted 1-hour NO2 concentrations resulting from actual emissions for Duvha Power Station (Scenario 1) vii

10 Figure 38: Predicted annual average PM10 concentrations (µg/m 3 ) resulting from actual emissions for Duvha Power Station (Scenario 1) Figure 39: 99 th percentile of the predicted 24-hour PM10 concentrations resulting from actual emissions for Duvha Power Station (Scenario 1) Figure 40: Predicted annual average PM2.5 concentrations (µg/m 3 ) resulting from actual emissions for Duvha Power Station (Scenario 1) Figure 41: 99 th percentile of the predicted 24-hour PM2.5 concentrations resulting from actual emissions for Duvha Power Station (Scenario 1) Figure 42: Predicted annual average secondary particulate concentrations (µg/m 3 ) resulting from actual emissions for Duvha Power Station (Scenario 1) Figure 43: 99 th percentile of the predicted 24-hour secondary particulate concentrations resulting from actual emissions from Duvha Power Station (Scenario 1) Figure 44: Predicted annual average SO2 concentrations (µg/m 3 ) assuming new plant MES for Duvha Power Station (Scenario 2) Figure 45: 99 th percentile concentration of the predicted 24-hour SO2 concentrations assuming new plant MES for Duvha Power Station (Scenario 2) Figure 46: 99 th percentile of the predicted 1-hour SO2 concentrations assuming new plant MES emission for Duvha Power Station (Scenario 2) Figure 47: Predicted annual average NO2 concentrations resulting assuming new plant MES for Duvha Power Station (Scenario 2) Figure 48: 99 th percentile of the predicted 1-hour NO2 concentrations assuming new plant MES for Duvha Power Station (Scenario 2) Figure 49: Predicted annual average PM10 concentrations resulting from new plant MES for Duvha Power Station (Scenario 2) Figure 50: 99 th percentile of the predicted 24-hour PM10 concentrations resulting from new plant MES from Duvha Power Station (Scenario 2) Figure 51: Predicted annual average PM2.5 concentrations (µg/m 3 ) assuming new plant MES for Duvha Power Station (Scenario 2) Figure 52: 99 th percentile of the predicted 24-hour PM2.5 concentrations assuming new plant MES from Duvha Power Station (Scenario 2) Figure 53: Predicted annual average secondary particulate concentrations (µg/m 3 ) assuming new plant MES for Duvha Power Station (Scenario 2) Figure 54: 99 th percentile of the predicted 24-hour secondary particulate concentrations assuming new plant MES for Duvha Power Station (Scenario 2) viii

11 1. Enterprise Details 1.1 Enterprise Details Entity details for Eskom s Duvha Power Station are listed in Table 1. Table 1: Enterprise details Entity Name: Eskom Holdings SOC Limited Trading as: Type of Enterprise, e.g. Company/Close Corporation/Trust, etc.: Company/Close Corporation/Trust Registration Number (Registration Numbers if Joint Venture): Registered Address: Duvha Power Station State owned company 2002/015527/06 Megawatt Park, Maxwell Drive, Sunninghill, Sandton Postal Address: PO Box 2199 Witbank 1035 Telephone Number (General): Fax Number (General): Company Website: Coal-fired power stations that generate electricity. Listed activity (Sub-category 1.1) in terms of the NEMAQA Industry Type/Nature of Trade: (Section 21), i.e. combustion installations using solid fuels (excluding biomass) primarily for steam raising or electricity generation (DEA, 2013). Land Use Zoning as per Town Agricultural/Heavy industry Planning Scheme: Land Use Rights if outside Town - Planning Scheme: Responsible Person: Anthony Kuzelj Emissions Control Officer: Anthony Kuzelj Telephone Number: Cell Phone Number: Fax Number: Address: kuzelja@eskom.co.za After Hours Contact Details:

12 1.2 Location and extent of the Plant Duvha Power Station (hereafter referred to as Duvha ) is located in the Mpumalanga Province, 15 km southeast of emalahleni. The surrounding land use includes coal mining, brick manufacturing, agriculture and residential areas. Site information is provided in Table 2 and the relative location to key landmarks is shown in Figure 1. Figure 1: Relative location of the Duvha Power Station (Google Earth, 2013) Table 2: Site information Physical Address of the Licensed Premises: Description of Site (Where No Street Address): Duvha Power Station, Off Bethal Road Duvha Kragstasie 337 JS Property Registration Number (Surveyor-General Code): - Coordinates (latitude, longitude) of Approximate Centre of Operations (Decimal Degrees): Coordinates (UTM) of Approximate Centre of Operations: Extent (km²): Elevation Above Mean Sea Level (m) Province: District/Metropolitan Municipality: Local Municipality: Designated Priority Area (if applicable): S E E S ( ha) m Mpumalanga Province Nkangala District Municipality Emalahleni Local Municipality Highveld Priority Area 10

13 Receptor Distance (km) Direction emalahleni 15 NW Witbank Dam 7.5 NW Residential area 2 S Residential area 3 SSW Agricultural land Immediate Surrounding Mining Surrounding Surrounding Brick Making 15 NW Figure 2: Land-use and sensitive receptors within a 30 x 30 km block of the Duvha Power Station (shown by the white square) 1.3 Atmospheric Emission License and Other Authorisations Duvha currently holds a valid Atmospheric Emission Licence (AEL) (Ref no. 17/04/AEL/MP312/11/07) for electricity production, the storage and handling of ore and coal, and the storage of petroleum products in terms of the listed activities promulgated in the Minimum Emission Standards (GNR 893 November 2013) under the National Environmental Management: Air Quality Act, 2004 (Act No. 39 of 2004) [NEMAQA]. The AEL specifies permissible stack emission concentrations for NOx, SO2 and for PM. The licence specifies a number of compliance conditions as well as conditions for emission monitoring and management of abnormal releases. The current governmental authorisations, permits and licenses related to air quality management are provided in Table 3. 11

14 Table 3: Current government authorisations related to air quality AEL Reference number: Date of AEL: Category of the listed activity* 17/04/AEL/MP312/11/07 28/06/2017 *See Table 6 for more detail Minimum Emission Standards Category 1 Category 2 Category 5 In terms of NEMAQA, all of Eskom's coal- and liquid fuel-fired power stations are required to meet the Minimum Emission Standards (MES) contained in GNR 893 of 22 November 2013 ("GNR 893"), as amended promulgated in terms of Section 21 of the NEMAQA. GNR 893 does provide for transitional arrangements in respect of the requirement for existing plants to meet the MES and provides that less stringent limits had to be complied to achieved by existing plants by 1 April 2015, and more stringent new plant limits need to be achieved by existing plants by 1 April The MES are listed in Table 4. Table 4: Minimum Emission Standards for combustion installations (Category 1) using solid fuel for electricity generation (Sub-category 1.1) with a design capacity equal to or greater than 50 MW heat input per unit Substance Plant status MES mg/nm 3 under normal conditions of 10% O2, 273 K and kpa Particulate Matter New 50 Existing 100 Sulphur dioxide New Existing Oxides of nitrogen New 750 Existing National Ambient Air Quality Standards (NAAQS) The effects of air pollutants on human health are plentiful with short-term, or acute effects, and chronic, or long-term, effects. Different groups of people are affected differently, depending on their level of sensitivity, with the elderly and young children being more susceptible. Factors that link the concentration of an air pollutant to an observed health effect are the magnitude of the concentration and the duration of the exposure to that particular air pollutant concentration. Criteria pollutants occur throughout urban and industrial environments. Their effects on human health and the environment are well documented (e.g. WHO, 1999; 2003; 2005). South Africa has accordingly established NAAQS for the criteria pollutants, i.e. sulphur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), respirable particulate matter (PM10), ozone (O3), lead (Pb), benzene (C6H6) (DEA, 2009) and PM2.5 (DEA, 2012a). The NAAQS for SO2, NO2, PM10 and PM2.5 are listed in Table 5. The NAAQS consist of a limit value and a permitted frequency of exceedances. The limit value is the fixed concentration level aimed at reducing the harmful effects of a pollutant. The permitted frequency of exceedance represents the acceptable number of exceedances of the limit value expressed as the 99 th percentile. Compliance with the ambient standard implies that the frequency of exceedance of the limit value does not exceed the permitted tolerance. Being a health-based standard, ambient concentrations that comply with the standard imply that air quality poses a tolerable risk to human 12

15 health, while exposure to ambient concentrations that do not comply with the standard, implies that there is an intolerable risk to human health. Table 5: National Ambient Air Quality Standards for SO 2, NO 2 and PM 10 (DEA, 2009) and PM 2.5 (DEA, 2012a) Pollutants Averaging period Limit value (µg/m 3 ) Number of permissible exceedances per annum 1 hour SO2 24 hour year 50 0 NO2 1 hour year 40 0 PM10 24-hour 75 4 Calendar year 50 (40) 0 PM hour 40 (25) 4 Calendar year 20 (15) 0 Figures in brackets are due for implementation on 1 January Nature of the Process 2.1 Listed Activity or Activities Table 6: Activities listed in GN 893 which are triggered by the Duvha Power Station. Category of Listed Activity 1: Combustion Installations 2: Petroleum Industry, the production of gaseous and liquid fuels as well as petrochemicals from crude oil, coal, gas or biomass 5: Mineral Processing, Storage and Handling Sub-category of the Listed Activity 1.1: Solid Fuel Combustion Installations 2.4: Storage and Handling of Petroleum Products 5.1 Storage and Handling of Ore and Coal Description of the Listed Activity Solid fuels (excluding biomass) combustion installations used primarily for steam raising or electricity generation. All installations with design capacity equal to or greater than 50 MW heat input per unit, based on the lower calorific value of the fuel used. All permanent immobile liquid storage facilities at a single site with a combined storage capacity of greater than 1000 cubic meters. Storage and handling of ore and coal not situated on the premises of a mine or works as defined in the Mines Health and Safety Act 29/ Process Description Eskom Holdings SOC Limited is a South African utility that generates, transmits and distributes electricity. The bulk of that electricity is generated in large coal-fired power stations that are situated close to the sources of coal, with most of the stations occurring on the Mpumalanga Highveld. Duvha is one such station (Figure 1). Duvha has a total installed capacity of MW, generated in 6 units, each with a total installed capacity of approximately 600 MW. At Duvha, and indeed all the coal-fired power stations, pulverised coal is combusted in order to heat water in boilers to generate steam at high temperatures (between 500 C and 535 C) and pressures. The steam, in turn, is used to drive the 13

16 turbines, which are connected, to rotating magnets and electricity is generated. The energy in the fuel (coal) is thus converted to electricity. Figure 2: A basic atmospheric emissions mass balance for Duvha Power Station showing the key inputs and outputs. Note that all quantities are expressed in tonnes per annum unless otherwise stated and are based on the 2016/2017 financial year. Duvha receives nearly 17 million tons of coal from the mine per annum. The coal is conveyed from the mine to the coal stockyard on site where it is milled to pulverised fuel and fed to the six boilers. The coal used at Duvha has a sulphur content of between 0.6 and 1.2% and an ash content of 27 to 30%. Combustion of the coal in the boilers heats water to superheated steam, which drives the turbines. In turn, the turbines drive the generators which generate MW of electricity. By-products from coal combustion include SO2, NOX and Particulate Matter. Atmospheric emissions resulting from power generation Emissions from coal combustion include SO2, NOX and particulate matter. SO2 is produced from the combustion of sulphur that is bound in coal. NOX is produced from thermal fixation of atmospheric nitrogen in the combustion flame and from oxidation of nitrogen bound in the coal. The quantity of NOX produced is directly proportional to the temperature of the flame. PM, SO2 and NOX are released to the atmosphere via the power station stacks. The non-combustible portion of the fuel remains as solid waste. The coarser, heavier waste from the combustion process, is called bottom ash and is extracted from the boiler. The lighter, finer portion is fly ash and, in the absence of abatement, it is emitted as particulates through the stacks. At Duvha, the majority (more than 99%) of the particulates (or ash) are removed from the flue gas stream before they are emitted into the atmosphere by the Fabric Filter plant (FFP units 1-3) and electrostatic precipitators (ESPs units 4-6) and collected in hoppers before being transported to the ash disposal facility. 14

17 2.3 Unit Processes A summary of the different unit process is provided in Table 7. The relative location of these is shown in Figure 3. Table 7: Unit processes at Duvha Power Station Unit Process Function of Unit Process Batch or Continuous Process Boiler Unit 1 Power generation process Continuous Boiler Unit 2 Power generation process Continuous Boiler Unit 3 Power generation process Continuous Boiler Unit 4 Power generation process Continuous Boiler Unit 5 Power generation process Continuous Boiler Unit 6 Power generation process Continuous Coal stockpile Storage of coal Continuous Fuel oil storage tanks Storage of fuel oil Continuous Boilers 1-6 Figure 3: Relative location of the different process units at Duvha Power Station 15

18 3. Technical Information 3.1 Raw Materials Used The permitted raw materials consumption rate, the permitted production rates and the energy sources at Duvha are listed in Table 8 to Table 10 according to the AEL. Table 8: Raw material used at Duvha Power Station Raw material Maximum permitted consumption rate (Volume) Units (quantity / period) Coal tons/month Fuel oil tons/month Table 9: Production rates at Duvha Power Station Product/by-product Maximum Production capacity permitted (Volume) Units (quantity / period) Electricity MW Table 10: Energy sources used at Duvha Power Station Energy source Sulphur content of fuel (%) Ash content of fuel (%) Maximum permitted consumption rate (Volume) Units (quantity / period) Coal <0.6 to 1.2% 27-30% Tons/month Fuel Oil Tons/month 3.2 Abatement Equipment Control Technology Abatement equipment control technology at Duvha is presented in Table 11. It should be noted that the abatement equipment is only for the control of PM emissions. The ESPs and FFPs have a minimum control efficiency of 99% and 99.6%, respectively. Neither NOx nor SO2 emissions are controlled directly at the power station. Table 11: Abatement equipment control technology currently in use at Duvha Power Station Appliance Name Pulse Jet Fabric Filter Plant Stack 1 (units 1-3) Electrostatic Precipitators (ESPs) Stack 2 (units 4-6) SO3 Plant Stack 2 (units 4-6) Appliance Type/ Description Pulse Jet Fabric Filter Plant (FFP) Electrostatic Precipitator (ESPs) SO3 Injection Appliance Function / Purpose Removes fly ash from the gas stream (i.e. reduces PM load) An ESP removes particles from the flue stream using the force of an induced electrostatic charge on the ash particle that is then attracted to and held on a plate. The efficiency of ESPs is dependent on the electrical resistivity of the ash particles (and the particle size). High frequency power supply with further enhance performance. SO3 injection decreases the resistivity of the particles, and significantly improves the performance of the ESP. 16

19 4. Atmospheric emissions 4.1 Point source parameters The physical data for the stacks at Duvha are listed in Table 12. Emission concentrations and emission rates for current production and proposed operational levels are shown in Table 13. The boiler units operate continuously, i.e. 24 hours a day. Table 12: Point sources at Duvha Power Station Point Source Code Source name Latitude (UTM) (m) Longitude (UTM) (m) Height of Release Above Ground (m) Height above nearby building (m) Diameter at Stack Tip / Vent Exit (Effective Diameter) (m) Actual Gas Exit Temp ( 0 C) Actual gas volumetric flow (m 3 /hr) Actual Gas Exit Velocity (m/s) Type of emission (continuous/ batch) Stack 1 Boiler unit S E * ** 23.2 Continuous Stack 2 Boiler unit S * ** 23.2 Continuous * Effective stack diameter, each flue has a diameter of 7.20m **Gas volumetric flow is per flue. 4.2 Point source maximum emission rates (normal operating conditions) Table 13: Current emission limits for normal operating conditions at Duvha Power Station Point source code Subcategory of Listed Activity Pollutant name Maximum emission rate (mg/nm 3 ) Date to be achieved by Averaging period Duration of emissions Immediately SO April 2020to 31 March April 2025 Daily Continuous Stack 1 (Units 1-3) Stack 2 (Units 4-6) 1.1 NOx Immediately April 2020 to 31 March April 2025 Daily Continuous PM 100 Immediately 50 1 April 2020 Daily Continuous 17

20 4.3 Point source maximum emission rates (start-up, shut-down, upset and maintenance conditions) Duvha maintains a record of all start-ups that occur. A total of 41 and 45 start-ups occurred during the 2016 and 2017 financial years, respectively (Table 14). 33 start-ups so far within the 2018/19 financial year. Table 14: Number of start-ups at Duvha Power Station since the start of the 2016/17 financial year Month Number of Startups Type of Start-up Month Number of Startups Type of Start-up Month Number of Startups Type of Startup April 2016 to March 17 April 2017 to March 2018 April 2018 to September 2019 April 3 Cold April 5 Cold April 2 Cold May 4 Cold May 5 Cold April 1 Warm June 1 Cold May 1 Warm May 3 Cold July 6 Cold June 5 Cold May 2 Warm August 2 Cold July 1 Cold June 2 Cold September 4 Cold July 1 Warm July 4 Cold November 1 Cold August 4 Cold July 3 Warm December 3 Cold October 5 Cold August 5 Cold January 6 Cold October 1 Warm September 10 Cold January 1 Warm November 1 Cold September 1 Warm February 4 Cold November 2 Warm March 5 Cold December 2 Cold March 1 Warm December 1 Warm January 2 Cold February 5 Cold March 3 Cold March 1 Warm 4.4 Fugitive emissions Fugitive emissions at Duvha result from coal storage and handling, and ash handling, which must be controlled through the implementation of dust management plans. Fugitive emission management is guided by the National Dust Control Regulations (GNR November 2013) as promulgated under NEMAQA. Such fugitive emissions are not assessed in this AIR. Duvha s dust management plan is included as Annexure A where dust emission sources and measures that have been put in place to manage these, are presented. Fugitive emissions are extremely difficult to quantify, as they are highly variable in time and space. Fugitive emissions from the ashing facility are highest on the active face (especially in the case of dry ashing) and when wind speeds are high. Fugitive emissions also depend on measures that have been put in place to suppress dust generation, for example vegetation of the ashing facility and sprinklers to suppress dust. The dust fall-out resulting from the fugitive emissions is monitored with dust buckets. 18

21 4.5 Emergency Incidents A record is maintained of all emergency incidents occurring at Eskom Power Stations reported in terms of section 30 of the National Environmental Management Act. Duvha has incurred 9 NEMA Section 30 incidents from 1 April 2017 to 31 March 2018, details of which are provided below (Table 15). Table 15: Record of emergency incidents which occurred at Duvha Power Station from 1 April 2017 to 31 March Date of Incident 30- June July Aug Aug Sept Jan- 18 Unit Nature and Cause of the Incident Actions taken immediately Actions taken subsequently Duvha Unit 5 Duvha Unit 4 Duvha Unit 5 Duvha Unit 5 Duvha Unit 5 Duvha Unit 1 The 48 hours allowable for Maintenance and Upset condition was exceeded. Root cause: Ineffective work coordination to effective implementation of work. The 48 hours allowable for Online Maintenance was exceeded. Root cause: Poor management of resources The 48 hours allowable, for upset condition was exceeded. Root cause: Poor management of operating resources The 72 hours allowable for a cold start up was exceeded. Root Cause: Assumed that Southey accidently closed valves when building scaffold when the unit was off. The 48 hours allowable for a hot start was exceeded. Root cause: Project not properly closed and handed over after implementation The 48 hours allowable for upset conditions was exceeded. Root Cause: Incorrect Technical Evaluation Criteria development due to lack of awareness in the procurement process. Lack of prioritization and resource availability in Boiler Engineering and Procurement Departments. New motor was installed on sluice pump 5B realigned. Reset relay for sluice pump 5A was replaced. Replaced airlift nozzle. Inspect the condition of the other airlift vessel at unit 5-6 Electricity maintenance and electricity engineering attended the defective fields and managed to bring back all the fields that were tripping. Transformer open circuit tests were conducted. Conducted interim training for the HFT. LH Air lifts vessel nozzle replacement. Load losses were taken. Blocked hoppers were unblocked and emptied. 90MW load loss was taken. Precipitator fields were switched off due to high hoppers to prevent further damage which could prolong the incident. A max of 179 MW load loss was taken to reduce emissions. Right and left hand side back end temperatures were dropped from 137 C to 127 C. Communication error on the right hand side Precipitator fields was resolved. DHP LHS Row 4 and RHS Row 5 were unblocked None Production to develop/review procedure to address priority plants. Management to conduct disciplinary inquiries into the conduct of the key individuals involved leading to the incident. Operating manager to implement the 5 th shift. Risk assessment to be conducted by Southey before erecting any scaffold in the plant with the supervisor present. Ensure proper modification handover and close out for the Electrostatic Precipitator plant is done as per the engineering change management process Procurement to develop a project timeline for each project with procurement milestones following all procurement processes approved by project. Include emissions projects on Boiler Engineering green area meeting agenda. 19

22 Temperature (⁰C) 5. Impact of Enterprise on the Receiving Environment 5.1 Analysis of emissions Overview The application for alternate limits does not mean that Komati s SO2 emissions will change from what they are currently and particulate emissions and NOx will improve over the next 5 years. The requested interim emissions limits have been expressed as a ceiling limit to ensure that Eskom can comply with the same under all normal operating circumstances given the variability of emissions from day to day. This assessment is based on a detailed analysis of the prevailing climate together with an analysis of air quality monitoring data. Thereafter dispersion modelling is used to predict ambient air pollution concentrations in the areas where there are no physical measurements for worst case scenario under the requested interim SO2, NOx and PM10 emission limits. This analysis is presented in the following section. Prevailing climatic conditions Temperature and rainfall The climate of a location is affected by its latitude, terrain, and altitude, as well as nearby water bodies and their currents. Climates can be classified according to the average and the typical ranges of different variables, most commonly temperature and precipitation. The Mpumalanga Highveld is located in temperate latitudes between 25 and 26 o S and 28 to 29 o E, and approximately m above sea level. As a result, it experiences a temperate climate with summer rainfall and dry winters according to the Köppen Climate Classification system. Temperature and rainfall over the north-eastern parts of the Mpumalanga Highveld are best illustrated by the long term measurements at the South African Weather Service station at the Loskop Dam Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Average monthly rainfall (mm) Mean maximum temperature Mean minimum temperature Average monthly rainfall Figure 4: Average monthly maximum and minimum temperature, and average monthly rainfall at Loskop Dam from 1961 to 1990 Winters are mild and dry with average maximum temperatures dropping below 25 C in May, June, July, and August but cold at night in June and July when temperatures drop below 7 C. Average summer maximums exceed 27 C from September to March, with extremes reaching more than 30 C particularly from December to January. 20

23 Wind The Mpumalanga Highveld is relatively flat with little influence by topography on the wind flow. Winds at Duvha are best represented by the wind measured at Eskom s Komati monitoring station, 17km southeast of the Duvha Power Station. The windrose in Figure 5 illustrates the frequency of hourly wind from the 16 cardinal wind directions, with wind indicated from the direction it blows, i.e. easterly winds blow from the east. It also illustrates the frequency of average hourly wind speed in six wind speed classes. The winds are predominantly northeasterly to easterly and north-westerly (Figure 5). The winds are generally light with 53% of all winds less than 5 m/s. Winds occasionally exceed 12 m/s, accounting for 5% of all winds. Figure 5: Annual windrose for Komati 2010 to Current status of ambient air quality Introduction In this section an analysis of ambient air quality from the Middelburg, Witbank and Komati air quality monitoring stations is presented. Ambient data for the three-year period 2015, 2016 and 2017 at the three monitoring stations provide a direct physical measure of ambient air quality in the area and of the sources that influence air quality at the monitoring site, including emissions from Duvha. The information is framed within the context of the National Ambient Air Quality Standards (NAAQS), and compliance-related conclusions are drawn as a function of those standards. The NAAQS are in turn made up of two components namely a limit value (as defined by a particular threshold concentration) together with the number of times the limit may be may be exceeded. As such, compliance is a function of not where there are exceedances of the limit value but whether the number of exceedances of the limit value is within the allowable number of exceedances. If the allowed frequency of limit-valueexceedances is surpassed, then there is non-compliance with the standard. 21

24 Ambient air quality monitoring The positions of the ambient air quality monitoring stations used in this assessment are summarised in Table 16 and illustrated in Figure 6. Ambient SO2, NO2 and PM10 concentrations and meteorological parameters are routinely monitored at the stations. In the following sections, the data are presented in frequency distributions that serve to indicate the occurrence of different concentrations measured. In presenting that information it is necessary to detail the data recovery at the station. Data quality Data quality is variable and there was poor data recovery for some of the stations in some of the monitoring years. Reasons for poor data recovery can include power and equipment failures, theft and vandalism. Data recovery of 80% and above is generally considered acceptably representative of the monitoring year. Where data recovery is less than 80%, the results must be treated with caution and cannot be viewed as definitive. The data are included simply for the sake of completeness, where data recovery is seen to be less than 80%. Table 16: Relative positions of the ambient air quality monitoring stations used in this assessment, to the Duvha Power Station. Site Name From Power Station Distance Direction From Power Station Latitude Longitude Phola (PO) 30.6 km West-South-West Komati (KM) 18.8 km South-West Middelburg 21.8 km North-East 25 47'45.82"S 29 27'51.51"E Witbank 17.0 km North-West 25 52'40.12"S 29 11'19.19"E Figure 6: Relative positions of the ambient air quality monitoring stations used in this assessment, to the Duvha Power Station. Sulphur dioxide (SO 2) 10-minute averages A cumulative percentage occurrence graph of 10-minute average SO2 concentrations is shown in Figure 7, together with a summary table of compliance with the NAAQS in Table 17. It can 22

25 be seen from the figure that 99.4% of the measured concentrations are below 400 μg/m 3 and from the table that full compliance with the NAAQS is implied in the monitored data. Data recovery in 2015 and 2016 is too poor, however, to conclude definitively that there was compliance for that monitoring year. Figure 7: Cumulative percentage occurrence of 10-minute average SO 2 concentrations measured at the Komati ambient air quality monitoring station. Only values above the 99 th percentile are shown for clarity purposes. Table 17: Summary ambient 10-minute SO 2 average concentrations for the Komati ambient air quality monitoring station. All concentrations are in μg/m 3. Station Year No of exceedances Allowable Maximum Average % data recovery ,3 40,0 44,8% Komati ,2 55,4 69,9% ,7 44,1 84,8% * Compliance with the NAAQS indicated by green, non-compliance by red. ** Light green data recovery is 80% or higher, light red less than 80%. Hourly averages Hourly average sulphur dioxide concentrations are shown in a cumulative percentage occurrence graph in Figure 8, Figure 9 and Figure 10 together with a summary table of compliance with the NAAQS in Table 18. It can be seen from the graph that full compliance with the NAAQS for SO2 is implied, however the poor data recovery, in 2016 for Komati and in all three years for the other two stations means that compliance cannot be assured. Witbank shows the greatest number of exceedances of the limit value. 23

26 Figure 8: Cumulative percentage occurrence of hourly average SO 2 concentrations measured at the Komati ambient air quality monitoring station. Only values above the 90 th percentile are shown for clarity purposes. Figure 9: Cumulative percentage occurrence of hourly average SO 2 concentrations measured at the Middelburg ambient air quality monitoring station. Only values above the 90 th percentile are shown for clarity purposes. 24

27 Figure 10: Cumulative percentage occurrence of hourly average SO 2 concentrations measured at the Witbank ambient air quality monitoring station. Only values above the 90 th percentile are shown for clarity purposes. Table 18: Summary ambient hourly SO 2 average concentrations for the Komati, Middelburg and Witbank ambient air quality monitoring stations. All concentrations are in μg/m 3. Station Year No of exceedances Allowable Maximum Average % data recovery ,3 36,4 91,1% Komati ,7 55,2 74,3% ,1 44,1 92,0% ,6 16,3 78,9% Middelburg ,2 18,8 58,2% ,2 15,7 43,2% ,8 50,4 64,8% Witbank ,1 39,8 61,4% ,4 25,9 53,6% * Compliance with the NAAQS indicated by green, non-compliance by red. ** Light green data recovery is 80% or higher, light red less than 80%. Daily averages Daily average sulphur dioxide concentrations are shown in a cumulative percentage occurrence graph in Figure 11, Figure 12 and Figure 13 together with a summary table of compliance with the NAAQS in Table 19. It can be seen from the graphs and the table that there was noncompliance with the NAAQS at the Komati station in 2016 and at Witbank in 2015 and Poor data recovery for the remaining years means that compliance cannot be assured for the other years even though full compliance is implied. Again, Witbank that is seen to have the highest concentrations although there is a marked reduction from 2016 to

28 Figure 11: Cumulative percentage occurrence of daily average SO 2 concentrations measured at the Komati ambient air quality monitoring station. Figure 12: Cumulative percentage occurrence of daily average SO 2 concentrations measured at the Middelburg ambient air quality monitoring station. 26

29 Figure 13: Cumulative percentage occurrence of daily average SO 2 concentrations measured at the Witbank ambient air quality monitoring station. Table 19: Summary ambient 24-hour SO 2 average concentrations for the Komati, Middelburg and Witbank ambient air quality monitoring stations. All concentrations are in μg/m 3. Station Year No of exceedances Allowable Maximum Average % data recovery Komati ,0 36,1 94,0% ,5 55,0 76,7% ,1 43,3 95,1% Middelburg ,7 15,3 91,2% ,8 18,0 63,6% ,2 15,6 51,0% Witbank ,0 49,5 73,2% ,8 39,2 66,3% ,3 25,6 61,1% * Compliance with the NAAQS indicated by green, non-compliance by red. ** Light green data recovery is 80% or higher, light red less than 80%. Annual averages Annual average concentrations are summarised in Table 20. Non-compliance is evident for 2016 for Komati but compliance is implied for the other stations for the three monitored years. Again the poor data recovery means that compliance cannot be assured. 27

30 Table 20: Summary ambient annual SO 2 average concentrations for the for the Komati, Middelburg and Witbank ambient air quality monitoring stations. All concentrations are in μg/m 3. Station Year Compliance Maximum Average % data recovery 2015 Yes 134,0 36,1 94,0% Komati 2016 No 172,5 55,0 76,7% 2017 Yes 122,1 43,3 95,1% 2015 Yes 125,7 15,3 91,2% Middelburg 2016 Yes 106,8 18,0 63,6% 2017 Yes 86,2 15,6 51,0% 2015 Yes 238,0 49,5 73,2% Witbank 2016 Yes 203,8 39,2 66,3% 2017 Yes 107,3 25,6 61,1% Nitrogen dioxide (NO 2) Hourly averages Hourly average nitrogen dioxide concentrations are shown in a cumulative percentage occurrence graph in Figure 14, Figure 15 and Figure 16, together with a summary table of compliance with the NAAQS in Table 21. It can be seen from the graphs and the table that full compliance with the NAAQS is implied. With data recoveries at less than 80% it must be recognised that full compliance cannot be confirmed. Figure 14: Cumulative percentage occurrence of hourly average NO 2 concentrations measured at the Komati ambient air quality monitoring station. Only values above the 90 th percentile are shown for clarity purposes. 28

31 Figure 15: Cumulative percentage occurrence of hourly average NO 2 concentrations measured at the Middelburg ambient air quality monitoring station. Only values above the 90 th percentile are shown for clarity purposes. Figure 16: Cumulative percentage occurrence of hourly average NO 2 concentrations measured at the Witbank ambient air quality monitoring station. Only values above the 90 th percentile are shown for clarity purposes. 29

32 Table 21: Summary ambient hourly NO 2 average concentrations for the for the Komati, Middelburg and Witbank ambient air quality monitoring stations. All concentrations are in μg/m 3. Station Year No of exceedances Allowable Maximum Average % data recovery ,6 21,6 97,5% Komati ,9 23,8 74,9% ,0 20,3 71,4% ,5 30,4 92,4% Middelburg ,1 36,2 78,2% ,0 14,9 52,3% ,8 34,3 83,2% Witbank ,3 29,4 90,1% ,4 19,0 35,4% * Compliance with the NAAQS indicated by green, non-compliance by red. ** Light green data recovery is 80% or higher, light red less than 80%. Annual averages Annual average concentrations are summarised in Table 22. Full compliance is implied for all three stations for the three monitored years. Again the poor data recovery means that compliance cannot be assured especially for 2017 at Middelburg and 2017 at Witbank. Table 22: Summary ambient annual NO 2 average concentrations for the Komati, Middelburg and Witbank ambient air quality monitoring stations. All concentrations are in μg/m 3. Station Year Compliance Maximum Average % data recovery 2015 Yes 119,6 21,6 97,5% Komati 2016 Yes 114,9 23,8 74,9% 2017 Yes 106,0 20,3 71,4% 2015 Yes 227,5 30,4 92,4% Middelburg 2016 Yes 275,1 36,2 78,2% 2017 Yes 94,0 14,9 52,3% 2015 Yes 456,8 34,3 83,2% Witbank 2016 Yes 152,3 29,4 90,1% 2017 Yes 88,4 19,0 35,4% Particulate Matter (PM 10) Daily averages Daily average particulate matter (PM10) concentrations are shown in a cumulative percentage occurrence graphs in Figure 17, Figure 18 and Figure 19 together with a summary table of compliance with the NAAQS in Table 23. It can be seen from the graph and the table that there is non-compliance with the NAAQS for all stations and for all years except for 2016 at Middelburg. The full extent of the non-compliance must not be underestimated with 117, 114 and 112 days where the limit was exceeded compared to the allowable 4 days. Again, even if compliance is implied by the data, compliance cannot be assured where data recovery is seen to be less than 80%compliance. 30

33 Figure 17: Cumulative percentage occurrence of daily average PM 10 concentrations measured at the Komati ambient air quality monitoring station. Figure 18: Cumulative percentage occurrence of daily average PM 10 concentrations measured at the Middelburg ambient air quality monitoring station. 31

34 Figure 19: Cumulative percentage occurrence of daily average PM 10 concentrations measured at the Witbank ambient air quality monitoring station. Table 23: Summary ambient 24-hour PM 10 average concentrations for the Komati, Middelburg and Witbank ambient air quality monitoring stations. All concentrations are in μg/m 3. Station Year No of exceedances Allowable Maximum Average % data recovery ,0 63,9 96,4% Komati ,3 55,3 80,5% ,1 70,8 92,6% ,6 37,9 95,9% Middelburg ,8 21,9 82,7% ,2 40,3 26,6% ,8 67,3 87,7% Witbank ,8 53,4 95,9% ,6 32,4 36,4% * Compliance with the NAAQS indicated by green, non-compliance by red. ** Light green data recovery is 80% or higher, light red less than 80%. Annual averages Annual average concentrations are summarised in Table 24. Compliance is evident for 2015 and 2016 in Middelburg but the data record for 2017 in Witbank is too poor to draw any definitive conclusions on compliance. Elsewhere there is non-compliance for the remaining years and stations. 32

35 Table 24: Summary ambient annual PM 10 average concentrations for the Komati, Middelburg and Witbank ambient air quality monitoring stations. All concentrations are in μg/m 3. Station Year Compliance Maximum Average % data recovery 2015 No 179,0 63,9 96,4% Komati 2016 No 165,3 55,3 80,5% 2017 No 248,1 70,8 92,6% 2015 Yes 145,6 37,9 95,9% Middelburg 2016 Yes 122,8 21,9 82,7% 2017 No 162,2 40,3 26,6% 2015 No 290,8 67,3 87,7% Witbank 2016 No 215,8 53,4 95,9% 2017 Yes 111,6 32,4 36,4% Particulate Matter (PM 2.5) Daily averages Daily average particulate matter (PM2.5) concentrations are shown in a cumulative percentage occurrence graph in Figure 20 together with a summary table of compliance with the NAAQS in Table 25. It can be seen from the graph and the table that there is general non-compliance the NAAQS. Figure 20: Cumulative percentage occurrence of daily average PM 2.5 concentrations measured at the Komati ambient air quality monitoring station. 33

36 Figure 21: Cumulative percentage occurrence of daily average PM 2.5 concentrations measured at the Middelburg ambient air quality monitoring station. Figure 22: Cumulative percentage occurrence of daily average PM 2.5 concentrations measured at the Witbank ambient air quality monitoring station. 34

37 Table 25: Summary ambient 24-hour PM 2.5 average concentrations for the Komati, Middelburg and Witbank ambient air quality monitoring stations. All concentrations are in μg/m 3. Station Year No of exceedances Allowable Maximum Average % data recovery ,9 14,9 13,7% Komati ,1 19,6 87,9% ,2 32,5 87,1% ,7 16,9 95,9% Middelburg ,8 10,6 82,7% ,9 23,9 40,0% ,5 27,8 87,7% Witbank ,0 22,9 95,9% ,7 28,8 42,2% * Compliance with the NAAQS indicated by green, non-compliance by red. ** Light green data recovery is 80% or higher, light red less than 80%. Annual averages Annual average concentrations are summarised in Table 26. Compliance is evident for 2015 and 2016 at Komati and 2015 and 2016 in Middleburg. Elsewhere the data record is either incomplete or seen to be non-compliant. Table 26: Summary ambient annual PM 2.5 average concentrations for the Komati, Middelburg and Witbank ambient air quality monitoring stations. All concentrations are in μg/m 3. Station Year Compliance Maximum Average % data recovery 2015 Yes 25,9 14,9 13,7% Komati 2016 Yes 100,1 19,6 87,9% 2017 No 104,2 32,5 87,1% 2015 Yes 61,7 16,9 95,9% Middelburg 2016 Yes 38,8 10,6 82,7% 2017 No 209,9 23,9 40,0% 2015 No 145,5 27,8 87,7% Witbank 2016 No 85,0 22,9 95,9% 2017 No 118,7 28,8 42,2% Source apportionment Source apportionment is particularly difficult, but essential to the analysis presented here. Perhaps the most instructive way of considering source apportionment on the basis of the ambient air quality data, without conducting physical pollutant speciation studies, is through presenting the diurnal variation in pollutant concentrations. This is because the creation of air pollution follows trends in space and time that make it possible to distinguish, by means of insinuation/ implication, between air pollution sources. For example, air pollution stemming from low-level burning practices associated with low-income community activities for heating and cooking, tends to arise in the early mornings and the early evenings, and so it is to be expected that measured peaks in pollutant concentrations during these times could be attributed to sources at a community level. Conversely, it can be assumed that power station emissions are most likely to reach the ground during the middle of the day when the atmosphere is unstable due to increased mixing activities, and so pollution peaks in the daytime can be attributed to industrial sources. As such, diurnal variability in pollutant concentrations is illustrated in 35

38 Figure 23 to Figure 27, as area plots of average hourly concentrations for each of the stations for each of the years ( ). For SO2 (Figure 23) a clear midday peak is evident of approximately 120 ug/m 3 with generally lower concentrations below 50 ug/m 3 from 17:00 through to 06:00, whereafter concentrations are seen to increase again to the midday peaks. For NO2, two peaks are evident, the first at 06:00 and the second at 18:00-19:00 (Figure 24). The lowest concentrations occur between 10:00 and 11:00. A similar pattern is seen for PM10 and PM2.5 where, for both pollutants, a morning peak is evident at between 06:00 and 07:00 and an evening peak at 18:00 (Figure 25 and Figure 26). When overlaid, the patterning of the pollutant peaks suggests that the primary sources of SO2 are different from the primary sources of NO2, PM10, and PM2.5 (Figure 27). What is postulated is that the SO2 peak sources are high elevation emissions while the NO2, PM10 and PM2.5 peaks are primarily sourced at ground level. 250 Concentra on in μg/m Hours of the day Figure 23: Area plot of the range of average diurnal SO 2 concentrations for all monitoring stations across the Mpumulanga Highveld ( ). 36

39 250 Concentra on in μg/m Hours of the day Figure 24: Area plot of the range of average diurnal NO 2 concentrations for all monitoring stations across the Mpumulanga Highveld ( ). 250 Concentra on in μg/m Hours of the day Figure 25: Area plot of the range of average diurnal PM 10 concentrations for all monitoring stations across the Mpumulanga Highveld ( ). 37

40 250 Concentra on in μg/m Hours of the day Figure 26: Area plot of the range of average diurnal PM 2.5 concentrations for all monitoring stations across the Mpumulanga Highveld ( ). 250 PM 10 PM 10 Concentra on in μg/m PM 2.5 NO 2 SO 2 PM 2.5 NO Hours of the day Figure 27: Area plot of the range of average diurnal SO 2, NO 2, PM 10 and PM 2.5 concentrations for all monitoring stations across the Mpumulanga Highveld ( ). The use of domestic fuels for cooking and space heating is a well-known phenomenon in South Africa, most notable in low-income dense settlements, even where electricity may be available. These sources result in emissions of SO2, NO2 and PM10 at ground level, particularly so during the early hours of the morning and the late hours of the afternoon/ early hours of the evening when the need for cooking and space heating peaks. The diurnal patterns described above can be explained as follows: During the night the atmosphere becomes stable with inversions often occurring. When the atmosphere is stable, emissions from elevated sources (e.g. stacks) do not come to ground-level as they are released into a stable atmosphere and simply cannot 38