THE EXECUTION OF A HOUSEHOLD EMISSION OFFSET PILOT STUDY IN THE HIGHVELD PRIORITY AREA, MPUMALANGA

Transcription

1 THE EXECUTION OF A HOUSEHOLD EMISSION OFFSET PILOT STUDY IN THE HIGHVELD PRIORITY AREA, MPUMALANGA Final report Issue 1 INITIATED BY : Eskom Holdings SOC Limited December 2015 REPORT NO:NWU/2015/Eskom01 i

2 Table of Contents EXECUTIVE SUMMARY... xiii List of abbreviations... xxxi CHAPTER 1. Background Introduction Purpose of this report The structure of this report Background The offset concept The pre-feasibility study The pilot study Importance of pilot findings and recommendations Extension of licenses The application and conditional approval of license extensions took place during this pilot Scope of Work... 6 CHAPTER 2. Management of working groups Rationale Objective Results MSRG mandate and meetings The Local Stakeholder Reference Group (LSRG) mandate and meetings... 7 CHAPTER 3. The development of an offset methodology Rationale and objective Background Greenhouse gas offsetting Air pollution offsets Offset accounting framework Offset accounting principles formulated during the pre-feasibility study Offset principles formulated by DEA Offset accounting principles in developed protocol What is accounted for? The managed or regulated activity and the offset activity The impact pathway as basis of offset accounting Comparison criteria Inter-pollutant exchange factors Draft offset protocol Protocol, policy and programme Air pollution accounting protocol Air pollution offset policy Air pollution offset programme Interactions Draft methodologies Methodologies developed during this project Methodology testing Estimation of impact and scale of offset Conclusions CHAPTER 4. The undertaking of air quality monitoring Introduction Monitoring objectives Methodology REPORT NO:NWU/2015/Eskom01 ii

3 4.3.1 Ambient monitoring Indoor and personal exposure monitoring Results of meteorological conditions and measured air quality Meteorological conditions at the monitoring station Observed pollution concentrations Kwazamokuhle Sulphur dioxide Oxides of Nitrogen Ozone Particulate matter Indoor concentration of PM Conclusions CHAPTER 5. The undertaking of dispersion modeling Overview Baseline Emissions Inventory Preparation for Dispersion Modelling Diurnal and Seasonal Cycles Model domain Ambient data at the site Meteorological data Local source of emissions Chemical air quality modeling Dispersion Model results Temporal distribution Spatial distribution Summary and Conclusions CHAPTER 6. The completion of household surveys HEALTH ASPECTS Aims and objectives of the community survey study Results of the community survey: statistical analyses Prevalence of health outcomes (illnesses or conditions) Statistical analysis of risk factors associated with relevant health outcomes Multivariate analysis Strengths and Limitations of the study Concluding remarks Quality of Life Quality of Life status 2014 per indicator Number of households per stand Age of persons in the study communities Sex of persons in the study communities Orphans in the study communities Dominant language in the study communities Health and wellbeing Satisfaction life-as-whole (scale 0-10) Satisfaction work (scale 0-10) in the study communities Employment in the study communities Total income of household (all sources) in study communities Lower bound poverty line of the study communities Perceived good health of household in the study communities Immunisation (children under 15) in study communities Never been to a medical professional Symptoms in last 12 months (self-reported) Restricted activity days working population (sickness & hh care) REPORT NO:NWU/2015/Eskom01 iii

4 Active smoking in study communities Satisfaction with food (scale 0-10) in the study communities Frequency of fruit and/or vegetable intake in study communities Frequency of protein intake in study communities Services and infrastructure Satisfaction with water (scale 0-10) in study communities Main source of water supply in study communities Water supply unavailable in last 30 days in study communities Satisfaction getting rid of waste (scale 0-10) in study communities Access to piped or flush system in yard in study communities Flushing system failure report in study communities Access to waste collection service in study communities Waste collection failure in study communities Satisfaction with "air you breathe" (scale 0-10) Dirty energy carrier for cooking in study communities Total tons of coal burned at home per annum in study communities Satisfaction with house (scale 0-10) of study communities Housing in study communities Education Satisfaction with education (scale 0-10) in study communities Adult illiteracy level in study communities Adult population (20y+) with grade 12 competed in study communities (D3) Safety and Security in study communities (indicator E) Safety perception (E1) Victim of crime in last 12 months in the study communities (E2) Energy Aspects of Community Solid fuel use Household solid fuel use characteristics Household fire ignition patterns Characteristics if fire ignition patterns CHAPTER 7. The creation of a roll-out plan Introduction Rationale Activity objective Selection and recruiting households for in-use evaluation Primary qualification criteria Recruitment of participating households The design criteria for each intervention End-user perceptions and preferences for artefacts Intervention prototypes design Description of the potential quality of life impacts of the intervention Formulate integrated monitoring regime per intervention Safety aspects Energy use CHAPTER 8. The intervention roll-out Introduction Rationale Activity objective Establish teams Manage materials Identify suppliers and obtain quotes Procure REPORT NO:NWU/2015/Eskom01 iv

5 8.1.7 Receive and store Distribute to teams Material QC and issue management Installation Schedule Installation by teams Stove replacement: challenges and mitigation/reactive measures Progress QC on installations, corrective action and sign off Household training on use of equipment Set local up LPG distribution for duration of project Manage and distribute electricity subsidies CHAPTER 9. Macroeconomic impact assessment and social cost benefit analysis Objectives Introduction Health Impact And Health Costs Exposure Indicator Selection Exposed Population Exposure-Response Functions Health Costs GDP Contributions Job Creation Greenhouse Gas Emissions Social Cost Benefit Analysis Way Forward CHAPTER 10. Assessment of the feasibility of the interventions Introduction Objectives Rating the different interventions User Desirability Introduction Experience of life of low-income households in KwaZamokuhle Some usage patterns The choice of an energy carrier Results of the interventions The way forward Estimating the impact of the interventions on a largescale Solid fuel use reduction Eligible households Evaluation of interventions No intervention Basic retrofit and electricity Full retrofit and electricity Basic retrofit and Kitchen King Full retrofit and Kitchen King Basic retrofit and LPG Full retrofit and LPG Energy poverty alleviation Notes on poverty and sustainability CHAPTER 11. Project Management Rationale REPORT NO:NWU/2015/Eskom01 v

6 11.2 Activity objectives and implementation Programme management systems Progress tracking Commercial management Project support office Activity reporting Project Management team Financial status by end December Project modification Macro Plan for Large Scale Roll-out (LSR) REPORT NO:NWU/2015/Eskom01 vi

7 List of Figures Figure 3-1. Impact pathway used in accounting protocol Figure 4-1. A map showing the Kwazamokuhle Township on the Mpumalanga Highveld and the relative position of the long term Ambient monitoring station established for this project represented by a star (created by M Weston, E- Science, 2015) Figure 4-2. Wind roses calculated for Kwazamokuhle between December 2014 and November Figure 4-3. Hourly wind roses at the monitoring station in Kwazamokuhle for December 2014 and November Figure 4-4. Monthly wind roses measured at Kwazamokuhle monirtoring station between December 2014 and November Figure 4-5. Diurnal variation of measured meteorological parameters measured at Kwazamokuhle monitoring station between December 2014 and November Figure 4-6. Annual variation of measured meteorological parameters measured at Kwazamokuhle monitoring station between December 2014 and November Figure 4-7. Measured SO 2 at the Kwazamokuhle monitoring site between January and December Figure 4-8. Diurnal variation of SO 2 measured at Kwazamokuhle and Hendrina from January to June The Red lines represents Kwazamokuhle (µg.m -3 ) and the blue line represents Hendrina (µg.m -3 ) (Taken from M. Weston, Chapter 4 this document) Figure 4-9. Pollution rose of SO 2 for the Kwazamokuhle monitoring station between January and November Figure Measured NO at the Kwazamokuhle monitoring site between January and December Figure Measured NO 2 at the Kwazamokuhle monitoring site between January and December Figure Diurnal pattern of measured NO at the Kwazamokuhle monitoring site between January and December Figure Diurnal pattern of measured NO 2 at the Kwazamokuhle monitoring site between January and December Figure Pollution rose of NO for the Kwazamokuhle monitoring station between January and November Figure Pollution rose of NO 2 for the Kwazamokuhle monitoring station between January and November Figure Diurnal pattern of measured O 3 at the Kwazamokuhle monitoring site between January and December Figure Five minute average PM2.5 and PM10 concentrations measured at Kwazamokuhle between January and November Figure Diurnal pattern of PM2.5 and PM10 measured at Kwazamokuhle between January and November Figure Frequency a) and cumulative b) distributions of PM 4 (µg.m -3 ) for the personal SidePak monitor within the indoor environment Figure Frequency a) and cumulative b) distribution of PM 4 (µg.m -3 ) for the DustTrak monitor within the indoor environment Figure Diurnal pattern of 5-min average concentrations of indoor PM 4 for both the personal SidePak monitor and the indoor DustTrak monitor during the winter period, 6 to 22 July 2015, for a single household Figure Box-plot of the daily mean SidePak PM 4 concentrations (µg.m -3 ) experienced over the two week monitoring period during the winter period, 6 to 22 July REPORT NO:NWU/2015/Eskom01 vii

8 Figure Box-plot of the daily mean DustTrak PM 4 concentrations (µg.m -3 ) experienced over the two week monitoring period during the winter period, 6 to 22 July Figure Time series of 5-min SidePak PM 4 (µg.m -3 ) categorised by date for the period of 6 July 2015 to 22 July Figure Time series of 5-min DustTrak PM 4 averages (µg.m- 3 ) categorised by date for the period of 6 July 2015 to 21 July Figure 5-1. Flow diagram of modelling process Figure 5-2. Census sub places of the KwaZamokuhle according to the Census 2011 delineation Figure 5-3. Household fuel emission rates for a.) summer PM10, b.) summer SO2, c.) winter PM10 and d.) winter SO Figure 5-4. Diurnal cycle applied to emissions from household fuel use Figure 5-5. Diurnal cycle i-button chimney data and ambient PM Figure 5-6. Adjusted model diurnal cycle (button profile) compared to ambient PM10 and the diurnal burning cycle from the control household group Figure 5-7. a) Model domain and b) discrete receptors used in the model domain Figure 5-8. Windroses from May and June 2015 at KwaZamokuhle for Observed data Figure 5-9. Windroses from May and June 2015 at KwaZamokuhle for CALMET model Figure Ambient monitoring station location at KwaZamokuhle and Hendrina Figure Diurnal cycles of ambient PM10 at KwaZamokuhle and Hendrina monitoring stations Figure Diurnal cycles of ambient SO2 at KwaZamokuhle and Hendrina monitoring stations Figure Diurnal cycle on observed and modelled PM10 at KwaZamokuhle Figure Diurnal cycle on observed and modelled SO2 at KwaZamokuhle. These model results are a combination of regional and near field model domains where observed meteorological data was not included Figure Maximum 24-hour model concentration during winter (May-June 2015) from household emissions for a) PM10 baseline, b) SO2 baseline, c) PM10 baseline with observed meteorology and d) SO2 baseline with observed meteorology. Exceedance of the ambient limit Figure Annual average of SO2 from the three power stations closest to KwaZamokuhle, Hendrina, Arnot and Komati for a.) the model domain and b.) zoomed into KwaZamokuhle Figure Maximum 1 hour SO2 concentration from CALPUFF for the three power stations closest to KwaZamokuhle, Hendrina, Arnot and Komati for a.) concentration and b.) number of exceedances Figure Annual average of SO2 for all power stations excluding Hendrina, Arnot and Komati Figure 6-1. Kwazamokuhle where the ESKOM community survey was conducted Figure 6-2. Location of study area in relation to nearby towns Figure 6-3. Percentage of households using solid fuel in winter, pre- and postintervention Figure 6-4. Percentage of households using coal (a) and wood (b) in winter, preand post-intervention Figure 6-5. Percentage of households using solid fuel in summer, pre- and postintervention Figure 6-6. % of households using coal (a) and wood (b) in summer, pre- and post-intervention REPORT NO:NWU/2015/Eskom01 viii

9 Figure 6-7. Proportion of fire ignitions per hour of day during (a) winter and (b) spring. The black line follows the contour of the control group s graph as point of reference Figure 6-8. Improved thermal comfort reported in DES and recorded by i-buttons Figure 6-9. Average number of fire ignitions per month during (a) winter and (b) summer Figure 7-1. The Kitchen King Figure 7-2. Entry-level LPG stoves and heaters Figure 8-1. A training cubicle Figure 8-2. Training at store facility Figure 8-3. Training in in-house conditions Figure 8-4. Some progress and completion images Figure 8-5. Progress and completion images Figure 8-6. Kitchen King training for Nova staff Figure 8-7. Kitchen King training for household representatives Figure 8-8. LPG training for household representatives Figure 9-1. Components of the integrated model, their relationship to data requirements from other Work Streams, and outputs in which the results will be reported Figure 9-2. Effects of Air Pollution (EPA, 2003) Figure 9-3. KwaZamokuhle is used as the boundary for the exposed population in the preliminary model Figure 9-4. Checklist for deriving an exposure-response function (IEHIAS, 2015) Figure 9-5. Relationship between the incidence of health outcomes and exposure to pollutants as described by an exposure-response function (ERF) Figure 9-6. Greenhouse Gas Reduction Benefits Model Figure Weighting of the criteria used to evaluate proposed offset (relative % weight on y axis per criterion) Figure Ranking in order of suitability for air quality offset implementation Figure Density of the estimation of total fuel use in kg based on a bootstrapping sample of Figure Indoor temperature by intervention typoe as measured at Kwazamakhule REPORT NO:NWU/2015/Eskom01 ix

10 List of Tables Table 0-1. Prevalence of past month respiratory-related health outcomes, air pollution concentrations and risk factors by study site.... xix Table 0-2. Prevalence of ever or past year diagnosed respiratory-related health outcomes, air pollution concentrations and risk factors by study site.... xx Table 0-3. Percentage people per poverty category per town... xxii Table 0-4. Summary of the preliminary study findings.... xxvii Table 1-1. Intervention combinations per household group... 4 Table 1-2. List of contract deliverables Table 3-1. Relative risk (RR) range, averaging period and stat used per pollutant in Caincross et al. (2007) air pollution index Table 4-1. Ambient air pollution and meteorological parameters measured at Kwazamokuhle Township between January and November Table 4-2. Manufacturer specifications for the photometric instruments Table 4-3. Average hourly and daily concentrations of SO 2, NO, NO 2, PM10 and PM2.5 measured at Kwazamokuhle and Hendrina monitoring stations between January and November Table 4-4. Average daily concentrations (by month) of SO 2, NO, NO 2, PM10 and PM2.5 measured at Kwazamokuhle and Hendrina monitoring stations between January and November Table 4-5. Descriptive Statistics of Indoor PM 4 Measurements (µg.m -3 ) Table 4-6. Frequency table for SidePak measurements taken in July Table 4-7. Frequency table for DustTrak measurements taken in July Table 5-1. Model setup scenarios that were tested Table 5-2. Emission factors for household fuel use applied in (Eq 1) Table 5-3. Percentage of houses using fuel as per Census data and the survey data. Survey data reports much higher fuel use Table 5-4. Estimated fuel use per summer and winter month based on census 2011 and survey data Table 5-5. Comparison of model set-up and inputs for Preliminary B versus Final Assessment model Table 5-6. CALPUFF model scenarios for combining household and Eskom SO2 emissions Table 5-7. Statistical performance of CALPUFF PM10 and SO2 at KwaZamokuhle Table 6-1. Data on gender, age, employment and income of the different areas Table 6-2. Data on housing and assets of the different areas Table 6-3. Percentage of households with access to water and sanitation in the five areas Table 6-4. Main energy carriers used for cooking and heating in the different areas Table 6-5. Statistics on nutrition and substance use in the different areas Table 6-6. Prevalence of diagnosed acute (month preceding study) health outcomes in the five areas Table 6-7. Prevalence of diagnosed chronic illnesses and number of individuals under treatment Table 6-8. Prevalence of notifiable diseases and pneumonia diagnosed in the 12 months preceding the study Table 6-9. Symptoms experienced in the five areas during the 12 months preceding the survey Table Number of persons per household Table Number of households per stand Table Age of the population in the areas studied Table Sex of persons in the study communities Table Maternal orphans in the study communities Table Maternal and paternal orphans in the study communities REPORT NO:NWU/2015/Eskom01 x

11 Table Dominant language in the study communities Table Satisfaction life-as-whole (scale 0-10) for the study communities Table Satisfaction work (scale 0-10) in the study communities Table Employment in the study communities Table Total income of household (all sources) in study communities Table Lower bound poverty line of the study communities Table Number of persons in each poverty category in KwaZamokuhle Table Perceived good health of household in the study communities Table Immunisation (children under 15) in study communities Table Never been to a medical professional Table Symptoms in last 12 months (self-reported) Table Restricted activity days working population (sickness & hh care) Table Active smoking in study communities Table Satisfaction with food (scale 0-10) in the study communities Table Frequency of fruit and/or vegetable intake in study communities Table Frequency of protein intake in study communities Table Satisfaction with water (scale 0-10) in study communities Table Main source of water supply in study communities Table Water supply unavailable in last 30 days in study communities Table Satisfaction getting rid of waste (scale 0-10) in study communities Table Access to piped or flush system in yard in study communities Table Flushing system failure report in study communities Table Access to waste collection service in study communities Table Waste collection failure in study communities Table Satisfaction with "air you breathe" (scale 0-10) Table Dirty energy carrier for cooking in study communities Table Total tons of coal burned at home per annum in study communities Table Satisfaction with house (scale 0-10) of study communities Table Housing in study communities Table Number of RDP and non-rdp houses in KwaZamokuhle Table Number of formal and informal houses in KwaZamokuhle Table Satisfaction with education (scale 0-10) in study communities Table Adult illiteracy level in study communities Table Adult population (20y+) with grade 12 competed in study communities Table Safety perception in the study communities Table Victim of crime in last 12 months in the study communities Table Winter monthly coal use per type (kg) Table Winter monthly wood use per type (kg) Table 7-1. LPG emission factors Table 7-2. Quality control procedure for installation of ceilings Table 7-3. Quality control procedure: exterior cladding, trombe panel Table 7-4. Quality control procedure: stove replacement Table 7-5. Monitoring regime Table 8-1. Installation time requirements Table 9-1. Preliminary exposure-response functions for selected health outcomes attributable to PM10 exposure Table 9-2. Direct and indirect health cost savings attributable to interventions Table 9-3. Basic structure of a input-output model Table 9-4. GDP impacts of different interventions Table 9-5. The impacts of interventions on employment Table 9-6. The GHG emission reductions are reported on in terms of carbon dioxide equivalents (CO2e) Table 9-7. Value chain identifying the different sectors affected by intervention scenarios Table 9-8. The benefits to cost ratio of the different interventions Table Stakeholder acceptance figures REPORT NO:NWU/2015/Eskom01 xi

12 Table Consistency Table Results of bootstrapped estimate of winter coal use per month (in tonnes) Table Monthly winter coal consumption per intervention type Table Monthly wood use per intervention type Table Estimate of the number of formal and informal structures per subplace with upper and lower bound of the 95% confidence interval per subplace Table Estimate of number of households who use coal for heating with upper and lower bound of the 95% confidence interval per subplace Table Estimate of the number of RDP houses per subplace with the upper and lower bound of the 95% confidence interval per sub-place Table Number of solid fuel users among RDP house owners in KwaZamokuhle Table The project management team REPORT NO:NWU/2015/Eskom01 xii

13 EXECUTIVE SUMMARY THE EXECUTION OF A HOUSEHOLD EMISSION OFFSET PILOT STUDY IN THE HIGHVELD PRIORITY AREA, MPUMALANGA INTRODUCTION The detrimental effect that air pollution has on human health is well established, though difficult to quantify. On the Mpumalanga Highveld, people are exposed to pollutants resulting from, inter alia, natural sources, industrial sources and ground level ambient emissions such as domestic fuel use and waste burning as well as emissions from indoor sources such as domestic fuel use. South Africa has a complex mix of a developed and developing economy that makes the effective management of air pollution challenging. These challenges has been intensified by the global economic downturn as well as problems in meeting electricity demand in the country since As part of the Air Quality Act that came in to effect in 2004, air pollution emissions standards were established for all scheduled industries. More stringent emissions standards became effective in April Many scheduled industries were not able to achieve these new, more stringent, standards. Eskom was one of the industries that was unable to meet the emissions standards before April As a consequence Eskom applied for a postponement of the implementation of the new emissions standards for Sulphur Dioxide and Particulate matter at all its power stations on the Mpumalanga Highveld. Postponements were granted for all the power stations on condition that Eskom implement an offset programme to reduce PM pollution in the ambient/receiving environment. A definite offset implementation plan is expected from (Eskom) by 31 March 2016 (DEA, 2015). This project is a first step to implementing an effective offset projects to decrease the impact that domestic coal combustion has on air quality (particularly PM) in poorer communities who are potentially impacted by power station emissions. In order to do this effectively and successfully, Eskom initiated this pilot study to investigate in an integrated manner all the dynamics that influence an air pollution offset project. The principle for an effective air pollution offset project is to identify a source of air pollution that currently has a large impact on human health in communities and for which a significant reduction in emissions and hence impacts can be achieved in order to compensate society for the inability of the industry to attain its own emissions standards. The Department of the Environment (DEA) has set out the basic principles for offset projects in July OBJECTIVES Ultimately the aim is to find a set of interventions that could be applied in low income households that will reduce emissions sufficiently to affect a measurable decrease in the air pollutions levels in the selected communities. Thus the project is most interested in the reduction of ambient and indoor concentrations of particulate matter. It should be noted that the success of the interventions can not only be measured as an absolute reduction in emissions. Due to the fact that people use solid fuels (coal) for space heating and cooking other factors also REPORT NO:NWU/2015/Eskom01 xiii

14 influence the success of the interventions. These factors include subjective choices and preferences of individuals, socio-economic factors, acceptability of technology and fuel types, feasibility and ease of use of the interventions, to name a few. The objectives of this project are diverse and complex. The objectives include the following: Develop an offset methodology and conceptual framework that can be applied to all offset projects in South Africa in order to ensure parity between projects and measures of success. Establish the social and economic characteristics of the study community. Establish the baseline air pollution trends in the selected community. Implement a set of interventions in 120 selected households. The list of interventions were a. LPG gas stoves b. Kitchen King coal stoves c. Electricity subsidies These interventions where tested in a group of houses that had two different levels for thermal insulation installed a. Basic thermal insulation had: i. Ensuring that windows and doors were sealed ii. Installation of insulated ceilings b. Full thermal installation included the above and: i. Trombe wall on the north facing side of the house ii. Radiation absorbing paint on the north facing side of the house Determine, if any, the reductions in indoor air pollution as a result of the intervention sets in samples houses. A group of 20 control houses were also included in the experimental design. Determine if the emissions reductions can be quantified as a result of application of fuel/energy interventions. Determine solid fuel usage patterns and quantities in control households. Undertake appropriate dispersion modelling for Kwazamokuhle Township with appropriate emissions factors and model settings to evaluate if selected intervention sets will have the desired impact on air pollution if applied at scale. Determine the overall impact of Eskom power stations on township background air pollution concentrations using regional scale atmospheric chemistry and transport modelling. Undertake a macroeconomic impact assessment and social cost benefit analysis. The main findings, conclusions and recommendations are summarised below. REPORT NO:NWU/2015/Eskom01 xiv

15 APPROACH Each objective was assigned a series of activities to attain the required information. A short summary of the approach for each objective will be given here: Methodology and conceptual framework: Over the past two years various groups in South Africa have been working on establishing the principles of an air pollution methodology and framework. A desktop study of the existing literature, incorporating the principles outlined by DEA have been used as the basis for this objective. Socio and economic characteristics of the study community: A General Household Survey including a community health survey was conducted in greater Kwazamokuhle area, namely, Emaskopasini, Kwazamokuhle SP, Manfred, Maphela and Tycoon between March and June In addition to questions on health, questions on subjective quality of life and standard of living were included. Six field workers were recruited in the study area, and then trained over a five day period. Street blocks in each area were randomly selected after which structured interviews were held with an adult household representative that had been living in the area for more than 9 months. A total of 919 households were approached and 692 interviews of good quality could be complete. The final dataset contained information on 692 households and Responses to the questionnaires, that were piloted beforehand, were captured electronically using cell phones. The surveys also included a detailed evaluation of the energy use patterns in the community of Kwazamokuhle both pre and post the implementation of the intervention sets in the experimental houses. The surveys in this regard include and focussed on i) the percentage of households using any solid fuel in winter and spring, respectively; ii) the percentage of households using specifically coal in winter and spring, respectively; iii) the percentage of households using specifically wood in winter and spring, respectively; iv) the average proportion of fire ignitions per hour of winter and spring days; and v) the average number of fires per winter and spring months. All the parameters have been studied for each of the individual intervention types. Baseline air pollution trends: Ambient and indoor measurements of criteria pollutants have been undertaken in the Township of Kwazamokuhle on the Mpumalanga Highveld. The ambient air pollution has been monitored continuously from January to December Measurements of indoor particulate matter loading have also been undertaken for intensive periods during the late spring of Indoor measurements determined the concentration of PM4 aerosols in the living rooms of selected houses. PM4 concentrations have also been measured using personal monitors for selected individuals in each of the selected houses. The purpose is to determine the levels of exposure to particulate matter in households that burn solid fuel as well as in houses where one of the above mentioned intervention sets have been installed. Implement a set of interventions: One hundred and twenty houses were randomly selected from the survey respondents (who themselves come from a probability REPORT NO:NWU/2015/Eskom01 xv

16 sample) to install a different configuration of interventions as listed above. A group of twelve control houses were also included. Intervention acceptance, energy consumption (all sources) and thermal comfort were closely monitored during the winter and late spring of 2015 and air pollution exposure in the houses was measured in the late spring of Dispersion modelling for Kwazamokuhle Township: CALPUFF has been used to model the baseline concentration of air pollutants in the ambient environment of Kwazamokuhle Township for the winter of The modelling has been undertaken using a modified emissions inventory established specifically for this community. Background concentrations of pollutants contributed by the Eskom Power stations, which includes secondary aerosols has been modelled using CAMX. Macroeconomic impact assessment and social cost benefit analysis: To enable this assessment, the following study components were included; health impact and health costs; full time equivalent job creation; direct and indirect GDP contributions; greenhouse gas emissions and social cost benefit analysis. An integrated model was developed to quantify the impacts of interventions (Figure 0 2) using resource economic techniques. The Microsoft Excel based model is a hybrid model that has top-down and bottom-up approaches, using: Official data such as demographic and economic information from Statistics South Africa Primary data such as those collected or modelled in preceding work streams International best practice guidelines in data collection, analysis and presentation of results The health impacts and costs have been demonstrated using epidemiological evidence to link the relationship between exposure to pollutants and health outcomes. The health outcomes have been quantified using treatment costs and productivity improvements. Job creation and GDP contributions were quantified using official input-output tables describing the South African economy. The model considered the effects of the interventions as well as the changes to household income and expenditure. Greenhouse gas emissions were calculated with the reduction in coal usage due to the interventions as well as specific emission factors to determine the net effect of the interventions on greenhouse gas emissions. The social cost benefit analysis considered the impact of the project on society in an analysis that added direct costs to the quantified climate costs and productivity in monetary terms. The model and analysis will be refined by incorporating data collected directly from Kwazamokuhle. These data include; i) ambient air quality data; ii) indoor air quality data; iii) health outcomes; iv) detailed information on interventions and v) household fuel use date pre- and post the interventions. Findings from each of the above mentioned components are summarised below. RESULTS Methodology and conceptual framework REPORT NO:NWU/2015/Eskom01 xvi

17 Four methodologies that have been developed and identified to adequately quantify the impact Eskom emissions and domestic burning emissions in order to establish the scale and nature of possible offset interventions. Each of the approaches follow the same route on the impact pathway, however, have different end points. The four methods can be summarised as i) Particulate equivalence; ii) Air quality standard weighted intake; iii) health risk (single outcome or severity weighted) and iv) burden of disease (single outcome or severity weighted). The detailed methodologies are currently being finalised and tested. The testing will involve using the same inputs into all methodologies to calculate similar metric(s). The purpose of the testing includes performing sensitivity tests to better understand uncertainties and impact of assumptions in the methods, and to compare the outputs from the different methods. Socio and economic characteristics of the study community The key findings from the community health survey are summarised in Table 0-1 and Table 0-2. An attempt is made to show the relationship between air pollution concentrations and the prevalence of important risk factors associated shown to have a statistically significant association with certain illnesses. The listed risk factors may play a role in the air-quality-related health outcomes of concern. A short descriptive summary of findings for each of the five study sites is given below. Kwazamokuhle SP The socio-economic conditions in Kwazamokuhle SP were in many aspects worse than in the other four communities. The lowest percentage with access to a medical aid was from Kwazamokuhle SP. The area also had the lowest education level (about 10% with no schooling), which may be the reason why this area had the lowest percentage of economically active people who were full time employed. Furthermore this area had the highest proportion of households with no access to piped water, waste removal or a toilet, and the highest where more than 10 individuals have to share a toilet. In addition, the area had the lowest use of electricity for cooking and heating, as most households used wood and or coal for cooking and heating. Indoor pollution is thus expected to be highest in this area. The highest proportion of vulnerable people by age (<15 and >65 years) is also from Kwazamokuhle SP. As far as illnesses and conditions are concerned, this area reported the highest prevalence of the acute illness sinusitis (together with Tycoon), and the chronic illness asthma (also together with Tycoon). The most individuals under treatment of asthma, high blood pressure, diabetes and HIV were from this area as well. Tycoon Tycoon was better off in many socio-economic aspects than the other areas. For example, Tycoon had the highest level of education, the largest proportion of households with access to electricity, a toilet and piped water and they also had the least interruptions in water supply. However, the area had the lowest consumption of fruit and vegetables on a regular (at least three times a week) basis. REPORT NO:NWU/2015/Eskom01 xvii

18 As far as illnesses and conditions are concerned, it was evident that Tycoon had the highest prevalence of asthma and sinusitis (both together with Kwazamokuhle SP), diabetes (together with Maphela) and high blood pressure. Manfred In Manfred access to services was acceptable in some aspects (all households had access to a toilet) but in others not (most interruptions in water supply). The consumption of fruit, vegetables and protein was the best in this area, which is positive for their nutritional status and immune system. However, the area had the highest prevalence of bronchitis and diarrhoea. Maphela Maphela had the highest unemployment rate amongst the economically active group (20 to 59 years), which could be the reason why they had the lowest consumption rate of fruit, vegetables and protein as they may not be able to afford healthy food. Certain activities by the residents of the area would increase their exposure to air pollution. For example, in addition to having the highest prevalence of smokers and highest prevalence of individuals being exposed to second hand smoke, residents also burn waste, despite having access to regular waste removal. Maphela seems to have the worst overall health status of the five areas, as the lowest percentage (25%) of people who have never been examined by a health professional is from Maphela. The area showed the highest prevalence of ear infection, hay fever, chronic bronchitis, diabetes and cholesterol, and had the highest number of individuals under treatment for TB. Emaskopasini Emaskopasini showed the lowest unemployment rate which was probably the reason why the area had the highest access to a medical aid of the five areas. The area also had the lowest proportion of vulnerable individuals in terms of age (<15 and >65 years). Access to services in this area was considered acceptable as 95% of households had access to piped water either inside the dwelling or the yard, 98% had regular waste removal, 81% of households had a toilet in the yard and no toilet in the area had to be shared by 10 or more individuals. Although Emaskopasini did not have the highest prevalence of any of the diagnosed illnesses or conditions, it showed the highest prevalence for seven selfdiagnosed symptoms, including mouth sores, skin rash and bad teeth, feeling sad and being injured. REPORT NO:NWU/2015/Eskom01 xviii

19 Table 0-1. Prevalence of past month respiratory-related health outcomes, air pollution concentrations and risk factors by study site. Study site Emaskopa sini Kwazamo kuhle SP Air pollutant concentrations In Kwazamokuhle 95 th prc 24-h SO 2 (ppb) (48) 95 th prc -24- h PM 10 (µg/m 3 ) (75) Diagnosis (past month) Symptoms Compounding Risk factors Bronchiti s Ear infection Hay fever Sinusiti s Runny nose with body ache Runny nose without body ache % 1.3% 6.3% 0.0% 0.3% 0% 14.29% % 2.7% 2.4% 7.4% 0.3% 0.1% 21.73% Manfred % 0.0% 0.0% 6.8% 0% 0% 10.61% Maphela % 4.8% 11.9% 2.4% 0% 0.5% 0.0% Tycoon % 2.5% 4.2% 7.6% 0.4% 0% 15.32% Household use wood as one of the energy carriers for heating REPORT NO:NWU/2015/Eskom01 xix

20 Table 0-2. Prevalence of ever or past year diagnosed respiratory-related health outcomes, air pollution concentrations and risk factors by study site. Study site Emaskopa sini Kwazamo kuhle SP Air pollutant concentrations Kwazamokuhle Annual PM 10 (µg/m 3 ) (40) Ever diagnosed Chronic bronchitis Asthma TB Cancer Diagnosed in past year Pneumoni a Symptoms past year Cough (no fever, night sweats) Wheezing at night or after exercise Puss from ear Compounding Risk factors Use small containe r for coal Water supply interrupted >5 days in three months % 3.8% 1.4% 0% 0% 0% 0.9% 0% 71.67% 2.56% 2.2% % 5.1% 1.9% 0.1% 0% 0.4% 1.6% 0.1% 40.27% 5.93% 30.1% Fail to remove waste Manfred % 3.8% 2.3% 0% 0% 0% 0% 0% 25.0% 6.10% 6.1% Maphela % 4.9% 0% 0.7% 0% 0% 10.9% 0% 0.0% 1.89% 0% Tycoon % 5.4% 2.9% 0% 0% 0% 1.5% 0% 61.64% 0.69% 0% *** 0.8%* South Africa 2.3% * ** % *** >25 years WHO stats % (Household) *** SA General Household Survey SA Health Review 2013/14 REPORT NO:NWU/2015/Eskom01 xx

21 The baseline quality of life (QoL) status of people living in greater Kwazamokuhle were determined using an indicator set related to five key quality of live aspects using the General household survey. These aspects are: a) Demographics b) Health and well-being c) Services and infrastructure d) Education e) Safety and security A few key findings are, first, that the age and sex distribution is not symmetric. In populations with medium to high birth rates the population of each successive age group usually diminishes. This was not the case in Emaskopasini where the youngest group of children 0-10 are smaller than the group of young people between 10 and 20 years. This is indicative of a slowing birth rate. In Manfred there are more men in the group 0 to 30 than women, particularly in the group 20 to 30 years of age. In Maphela the number of men in the group between 30 and 40 is lower than expected and the women in the group 50 to 60 slightly higher than expected. Tycoon has quite an irregular pattern: both men and women in the age group between 20 and 30 are higher than in the 10 to 20 age group particularly the women. It is comprehensible with this large number of women in the age group 20 to 30 that there is quite a high number of children below 10 years of age in Tycoon. There are also more men and women in the age group 50 to 60 than in the group 40 to 50 years of age. The total number of maternal orphans (8.01%) in the sampled suburbs is higher than on national level (5.81%) and in Mpumalanga (6.39%) 1. The lowest number of orphans was reported in Maphela (3.08%) and the highest number in Manfred (12.94%). Manfred also has a high number of double orphans (5.88%). isizulu (75.33%) is the language most frequently used in the study area. Maphela has a fairly large isindebele group (28.42%). Results from the health and wellbeing survey show that Maphela has the highest mean household income of R3160 per month and Kwazamokuhle SP the lowest of R1557 per month. Disregarding inflation, this is much lower than the mean national household income of R and provincial household income of R as reported by Census This means that the average household in Kwazmokuhle has to survive on R51.19 per day. Taking the average number of persons per household into account, it relates to a per capita income in Kwazamokuhle SP of R377 per person per month or R12.39 per person per day. Relative to the other surveyed suburbs Manfred has a low income per household in spite of the fact that the full and part time employment (compare B3) is fairly high in comparison to the other suburbs (Table 0-3) Census figures REPORT NO:NWU/2015/Eskom01 xxi

22 Table 0-3. Percentage people per poverty category per town Emaskopasini Kwazamokuhle SP Manfred Maphela Tycoon Food poverty One twentyfive $ Lower bound poverty line Upper bound poverty line Minimum wage/ Sum The dire situation in the surveyed suburbs should be evident taken into consideration that, as shown in Table 0-1, around 90% of households in Kwazamokuhle SP and Manfred, more than 80% in Tycoon and more than 70% in Emaskopasini and Maphela live below the Lower Bound Poverty Line (LBPL). Interestingly the perceived health is the best in the two suburbs with the highest number of persons living below the LBPL namely Kwazamokuhle SP (74.9%) and Tycoon (76.58%). This phenomenon, namely, that people from low-income areas can score high on health satisfaction is known in literature. The creation of job opportunities will remain a crucial challenge in the pursuit of an increased quality of life of the study suburbs. Kwazamokuhle SP (16.96%) has the least and Maphele (29.6%) the highest number of full time employed persons of the suburbs surveyed. Almost all children are reported to having being immunised, except in Manfred, where only 94.12% of children have been vaccinated. A very high 52.35% of persons in Manfred have never been to a medical professional. In Kwazamokuhle SP the figure is also high at 41.68%. Of the suburbs surveyed the community who seems to have the greatest access to medical services is Maphela where only 24.35% of persons have never been to a medical professional. The frequency of daily fruit and vegetable intake is very low in the surveyed suburbs and only 24.71% of households report that they take in either fruit or vegetables every day. The situation in Tycoon is statistically significantly better than in the other surveyed suburbs with 45.32% of households who report that they do eat fruit or vegetables every day. Residents of Manfred report significantly less protein intake than the other suburbs with only 73.72% of households reporting that they take in protein daily. This is a matter of concern. Services and infrastructure Kwazamokuhle SP (31.15%) has significantly more informal houses than the other suburbs surveyed. This also explains the challenges regarding services and infrastructure. Only 70.5% of households in Kwazamokuhle SP have a tap or borehole in the yard and this is significantly lower than the rest of the surveyed suburbs. Only 17.23% of households in Kwazamokuhle SP have piped water in their houses. In both Emaskopasini (45.05%) and Manfred (28.79%) less than half of the surveyed households have piped water in their homes. Tycoon is the best off in terms of water service delivery where 72.97% of households have piped water in their homes and a full 100% of households report they have a tap or borehole in the yard. REPORT NO:NWU/2015/Eskom01 xxii

23 All residents of Maphela and Tycoon have access to a flush toilet system in their yards, but in the other suburbs there is still a minority of persons with no access to such a system. In Kwazamokuhle SP only 91.83% of households have a flush system in the yard and in Manfred only 93.94%. The proportion of households with access to flush toilets in all suburbs is significantly higher than the national (60.11%) and provincial (43.80%) proportions (2011 Census figures). Flushing system failure reports are slightly higher in Emaskopasini than in the other suburbs surveyed. It is reported that only 87.64% of flush toilets in Emaskopasini are always working. In Maphela and Tycoon all households have access to waste collection services. The waste collection service delivery challenge is the largest in Kwazamokuhle SP, where only 69.97% of households have a waste collection service. This is significantly lower than in any other community surveyed. In Manfred only 93.94% of households have a waste collection service. Many people in all the surveyed suburbs use dirty energy carriers for cooking (67.1%) and heating (74.31%). Several people use electricity to cook, but during the winter they use coal because it heats up the house and cooks at the same time. The Census 2011 figures for dirty energy carriers for cooking and heating in the Kwazamokuhle area are much lower than the results as reported by this study. The difference between this study and Census 2011 can be explained by the fact that Census 2011 only asked about the primary energy carrier. This study is more concerned with capturing the full range of energy carriers in use and not just the main carrier as is the case with Census 2011 data and as such we consider the above result to be more usable as an indicator of the extent of dirty fuel use than the Census 2011 figures. Education Only about a third of the working population above 20 years of age in all suburbs have completed grade 12. Tycoon (43.13%) has somewhat more adult residents that have completed grade 12 than the other suburbs. The adult illiteracy level does not differ significantly between suburbs. The percentage of persons 20 years and older without any schooling in all suburbs is 13.84%, which is close to the Mpumalanga provincial figure of 14.00% and somewhat higher than the national figure of 8.60% (Census 2011). Safety and security People in Kwazamokuhle SP feel significantly less safe than residents of the other suburbs surveyed: only 55.09% of households in this community reported that they think the area is safe, however, the reported victim of crime rates in the last 12 months are not significantly higher than in the other sampled suburbs. The National Planning Commission (NPC) adopted the use of the LBPL with regard to its poverty targets. They have set the ambitious target of eliminating all poverty below this line by From the results of this study it is deducted that around 90% of households in Kwazamokuhle SP and Manfred and more than 70% in the other suburbs surveyed live below the LBPL. At the same time close to 80% of households in Kwazamokuhle SP and close to 70% of households in Manfred report that they use an unclean energy carrier for heating. In the cold Highveld REPORT NO:NWU/2015/Eskom01 xxiii

24 winter low-income households revert to dirty energy carriers in order to fulfil their need for space heating. In these communities poverty is a driver for ambient and indoor air pollution and this can only change if either poverty is alleviated or the need for space heating is reduced while at the same time affordable and accessible cleaner domestic energy options are available for low-income households. The extent of the challenge is evident from the results of this study. This result emphasises the importance of gaining a holistic understanding of the problem of air quality in these environments in order to find solutions for the problem. It is not enough to study the state of the ambient air and the resulting exposures and effects. It is also important to understand the drivers and the resulting pressures causing the particular state of the ambient and indoor air. The results show that the communities are extremely vulnerable due to poverty which implies many challenges in terms of service delivery especially in Kwazamokuhle SP and Manfred. It provides statistics on various quality of life aspects that can be addressed. As such the indicators are intended as baseline indicators to measure the future impact of interventions on quality of life. Energy usage Energy usage in Kwazamokuhle has been documented in the experimental houses and the control houses before and after the intervention sets were implemented. The results indicate that only energy carrier intervention that reduced solid fuel with statistical significance was the LPG intervention. In these households coal stoves were replaced with LPG stoves. The other interventions, except for the elec-basic, seem to also have had positive effects on solid fuel use, but the reduction were not statistically significant. It has shown that the full retrofit insulation interventions outperformed the basic retrofit in the control group with regard to indoor thermal comfort. At 5am on a typical winter morning, the full retrofit houses were on average 6 7 degrees Celsius warmer than the control group houses and 1 4 degrees Celsius warmer than the basic retrofit houses. The improved thermal performance of the houses seems to be associated with a reduction in early morning fires, especially in the case of the full retrofit households. Once again, however, the effects are not at this large enough to be deemed statistically significant given the sample size and the monitoring period. Despite the reduction in early morning fires and overall increase in thermal performance, the interventions (except the LPG interventions) did not facilitate a statistically significant reduction in either the average number of fires made per month or the average mass of solid fuels used per month. With more coal available due to fewer morning fires, it seems as if households then simply tend to make more evening or social fires. In fact, in the case of the households who received electricity subsidies, it seems as if the average monthly coal use during winter increased (where the monthly coal use of the control group is estimated at 227 kg, the electricity households usage is estimated at kg per month). Baseline air pollution trends Measurements of ambient pollution concentrations and meteorology have been successfully undertaken at Kwazamokuhle since December 2014 until November The most important meteorological finding is high percentage calm periods (wind speeds below 1 m.s -1 ) at Kwazamokuhle (61.4 %). This has significant REPORT NO:NWU/2015/Eskom01 xxiv

25 implications for the accumulation of especially low level emissions such as those emanating from domestic burning. Sulphur dioxide was shown to have elevated concentrations at distinct time of the day that varied by season. During the summer concentrations where found to be highest during the middle of the day. This is indicative of a tall stack impact most likely to be from Hendrina Power Station. In general it is not likely that SO 2 exceeds the ambient air quality standards. Oxides of nitrogen show a distinct diurnal pattern that is not consistent with impacts from power station emissions. This needs further investigation as it is unlikely to detect SO 2 and not NO from the Hendrina power station. NO levels are highest during the morning peak while NO 2 concentrations are highest during the evening peak. High concentration of Ozone have been detected at Kwazamokuhle during the sampling period. Concentrations reach 85 ppb throughout the year with no distinct pattern during the increase of these maximum levels during summer (during maximum photolysis). The diurnal cycle of Ozone is a typical for the production of Ozone though photolysis. Particulate matter concentrations represent the biggest risk to health impacts on the local communities as well as being the single biggest emission from domestic coal burning. PM10 and PM2.5 concentrations were found to be high in the ambient environment in Kwazamokuhle with the signature bimodal peak concentrations associated with domestic cooking and space heating. PM2.5 made up a significant fraction of the aerosol loading. PM10 and PM2.5 concentrations are significantly elevated from end of May to middle of August. This time of the year coincides with a higher number of cold days. Domestic coal combustion is a significant source of pollution in Kwazamokuhle. This was illustrated by a comparison between data collected at Kwazamokuhle and Hendrina (a stations in a residential area with little to no domestic coal combustion). PM10 and PM2.5 levels in Kwazamokuhle are a factor of 2-5 during the morning and evening burning periods, respectively, than the same time at Hendrina. Hourly and daily mean concentrations of SO 2, PM10 and PM2.5 are twice as high at Kwazamokuhle as Hendrina. The highest concentration of PM occur at both sites during the winter months (may to August). The average difference is highest during the winter months at Kwazamokuhle. The indoor environment had significantly high concentrations of respirable particulate matter associated with the morning and evening burning periods identified in the diurnal pattern. During these burning period 32% to 57% of the reading exceed the 24-hour 75 µg.m -3 standard for ambient PM10. The 24-hour PM10 standard is exceeded by up to a factor of 10. A significant finding is that in times where no indoor combustion of solid fuel took place there is only a slight increase in the level o indoor PM4 (based on data from one control house). This could possibly be the result of ambient PM infiltrating into the indoor environment. Implement a set of Interventions A series of important learnings have been gained from the implementation of the interventions in households in Kwazamokuhle. First, participation rates in the REPORT NO:NWU/2015/Eskom01 xxv

26 intervention requests were high amongst the residence of Kwazamokuhle. Acceptance rates range from 66% the ceiling and coal stove group, 88% for the full retrofit and coal stove group, 83% for the ceiling and LPG group and 87% for the Full retrofit and LPG group. Recipients were generally positive about all the intervention combinations. The combination of insulation (either basic or full insulation) and an LPG stove and heater are generally acceptable and even desirable and may make it possible that a good majority of people move away from coal completely. The project indicates that installing ceilings is the intervention that makes the biggest difference for many reasons, include i) it improves the thermal conditions in the house during hot and cold weather; ii) it also keeps dust; smoke and rats out; iii) it decreases noise and iv) it makes the house beautiful. The ceiling makes such an impact that - if only perceptions of recipients are considered - it overshadows the other interventions, especially the wall cladding. The retrofit insulation of ceilings and walls resulted in drastic improvement in thermal comfort: Minimum temperature is raised by 4 C by basic retrofit, and by 5.5 C by the full retrofit in winter. Insulated houses stay warmer for 2-3 hours longer in winter. Residents tend to ascribe the improvement in indoor thermal conditions to the ceiling rather than to the wall cladding. It was pleasing to note the high level of permanent uptake of the LPG stoves (100% for the ceiling and LPG and 98% for the full retrofit and LPG) and Kitchen King low smoke stoves (98% ceiling and coal stoves and 095% for the full retrofit and coal stoves) by the participating households. The electricity subsidy means more cash in peoples pockets, but it does not bring about a substantial shift away from coal to electricity. People still make fire when it is cold. The electrical subsidy, therefore, did not result in any coal use reduction in spite of houses being retrofitted as well the coal stoves could not be removed due to potential power outages. While the Kitchen King has brought many improvements, some adjustments to its design are recommended. The critical question is how long it will take before it also becomes old and begins to show the same dysfunctionality as the stoves that were replaced. The LPG stove, and to some extent the LPG heater, is experienced in a very positive way, although LPG is seen as dangerous, and some adjustments to the design of the stove are recommended. It is, for example, seen as too weak to take a full load, and the oven is not functioning well. Houses with roofs that are leaking may become a major problem for the long-term sustainability of ceilings. Utilising local, unemployed staff proved to be a success. The surveys showed that there is an estimated 2072 informal dwellings in Kwazamokuhle of which 89.6% uses solid fuel. REPORT NO:NWU/2015/Eskom01 xxvi

27 Waste burning takes place in spite of municipal waste removal services in some areas while poor waste removal in other areas contributes to air pollution. The sample survey indicated that 25% of households practise waste burning. Dispersion modelling for Kwazamokuhle Township Initial dispersion modelling using CALPUFF has been undertaken using a modified emissions inventory for Kwazamokuhle. The baseline emissions inventory simulated concentrations of the same order of magnitude as the observed morning and evening peaks for PM10 and evening peak for SO 2. The baseline emissions, without any correction to the meteorology slightly underestimate PM10 (due to underestimating the evening peak) with a RMSE of 33 ug.m -3 for 24 hour averages. Daily SO 2 is overestimated due to the inclusion of a morning peak that is not present in the observed data with an RMSE of 27.4 ug.m -3. Household emissions are a more significant source of SO 2 than regional sources with peak concentrations occurring in the evening. Households accounted for about 75% of the peak concentration. Regional industry contributed about 25% of the peak concentrations. The inclusion of observed meteorological data significantly improved model performance for PM10 evening peaks by assimilating calm conditions. There is no observed morning peak of SO 2 to match the morning peak in PM10. This may be due to reactions that occur in the morning that effectively convert SO 2. The emissions inventory in its current form is adequate for modelling potential changes in ambient concentration due to interventions if rolled out at scale. Macroeconomic impact assessment and social cost benefit analysis Preliminary inputs have been used to demonstrate the effectiveness of the model and estimate the broad impact of interventions. The results are indicative of the impacts of interventions, but need additional work to make recommendations on specific interventions. A summary of the preliminary results are presented in Table 0-4. Table 0-4. Summary of the preliminary study findings. In, general some indicative results are that health impacts and costs will be reduced due to the reduction in coal consumption through the interventions efficiency improvements and fuel substitutions. The interventions will create jobs and REPORT NO:NWU/2015/Eskom01 xxvii

28 contribute to GDP. The interventions will reduce greenhouse gas emissions. The interventions are likely to have a benefit-cost ratio of less than 1, indicating that benefits of the interventions will be less than the costs over a 20 year timeframe. However, if Eskom is able to be excused from the emission standards, these savings will greatly shift the benefits to cost ratio. CONCLUSIONS This project set out to implement an air pollution offset project in Kwazamokuhle Township on the Mpumalanga Highveld for Eskom to test a series of intervention sets. The purpose of the project was diverse but essentially aims to evaluate whether offset interventions will meet the requirements outlined by DEA successfully reduce ambient air quality in low income communities and will be acceptable to these communities given their socio and economic realities. A series of intervention sets have been rolled out in 120 households in Kwazamokuhle with an additional 20 control houses. Detailed household surveys have described in detail demographics, socio-economics, health, quality of life and energy use patterns of the communities of Kwazamokuhle. Ambient air pollution monitoring between January 2015 and December 2015 has given a good baseline assessment of the current air quality as well as the prevailing metrological conditions that are so important in determining the accumulation of air pollutants on the Highveld. Domestic combustion of coal adds a significant ambient PM load at Kwazamokuhle when compared to Hendrina monitoring station. The highest PM and SO 2 concentrations are recorded during the winter at both monitoring stations. The average differences between Kwazamokuhle and Hendrina increase sharply during the winter (June, July and August). Dispersion modelling and a macro-economic and cost benefit analysis have indicated that interventions can reduce air pollution in the township and produce economic benefits as well as greenhouse gas emission reductions. Currently the cost benefit analysis indicates a ration of less than 1. This could improve if the offsets result in a longer term postponement of emissions standards implementation for Eskom. Based on the fact that a high proportion of the Kwazamokuhle community live below the LBPL the reality of energy poverty should be taken into consideration when designing a community offset project since the combination of accessibility, availability and affordability influences choices of energy carriers along with desirability. The participation uptake rates were relative high probably due to a combination of local stakeholder sessions, utilisation of local staff and intensive interaction by experienced Nova staff being available in the local office. The very high permanent uptake of the stove swopping is due to the positive experience during the winter months from both the retrofit thermal comfort improvement and utilising LPG stoves/heaters or the Kitchen King low smoke stove. Coal burning is largely driven by the need for thermal comfort during cold periods thus a coal stove swop with an LPG stove needs to be accompanied with a retrofit or alternative thermal comfort solution. REPORT NO:NWU/2015/Eskom01 xxviii

29 The full retrofit with the LPG stove swop intervention performed the best from a thermal comfort and PM10 reduction point of view. Due to the 30% (2072) informal dwellings of which 90% (1857) use solid fuels, a proven solution needs to be found for informal dwelling solid fuel users. A solution will also have to be found for waste burning. It is not certain why waste burning takes place in areas which has waste removal services. Part of such a solution may be an education programme. The electricity subsidy may still be viable together with a stove swop if combined with a standby stove for use during power failures. There are single and double plate LPG stoves as well as other non-solid fuel stoves. RECOMMENDATIONS 1. The most promising interventions consists of the households choice of either full retrofit or basic retrofit and a coal stove for LPG stove exchange. The reason why uers should be given a choice of retrofit type is that, although full retrofit is much more effective, some people prefer not to install it for aesthetic reasons (such as having a face brick house). Detail planning for such an intervention in the whole of Kwazamokuhle should proceed. 2. The participatory approach, which involves not only communication and consultation with the community but also recuitement and training of project staff from the local community should continue in subsequent phases. 3. The proposed intervention is only suitable for areas where domestic fuel use by residents of formal dwellings make a large contribution to ambient air pollution. Air pollution eminating from fuel use in informal dwellings, of which there are a significant number, and domestic waste burning is not addressed by the proposed intervention. In order to sustainably address air pollution, sollutions that address these sources must also be developed through the normal project development phases of pre-feasibility, feasibility, pilot and full scale roll-out. 4. An air pollution offset project that improves quality of life and contributes to energy poverty alleviation will be more sustainable when it facilitates a movement on the energy ladder towards cleaner energy with long term advantages. Against this background policy makers should be encouraged to recognise benefits that promote poverty alleviation in particular the elimination of drivers that lead to domestic practices resulting in the emissions or air pollution. As such the link between poor air quality and poverty should be acknowledged and addressed in a holistic manner. 5. The LPG sollution is dependent an a certain price stability. The risk of LPG supply problems and measures to mitigate this should be investigated. 6. During the lead implementation, the business processes needed for a national implementation should be developed. This includes record keeping and quality control procedures and a central implementation database. REPORT NO:NWU/2015/Eskom01 xxix

30 KEY WORDS Air pollution, air pollution impacts of health, emissions standards, domestic coal combustion, air pollution offsets REPORT NO:NWU/2015/Eskom01 xxx

31 LIST OF ABBREVIATIONS Abbreviation AQ EOP GHS Definition Air Quality Eskom offset pilot General household survey LBPL ` Lower-Bound Poverty Line NDP NO NO 2 O 3 PM National Development Plan Nitrogen Oxide Nitrogen dioxide Ozone Particulate Matter PM10 Particulate Matter smaller than 10 µm PM2.5 Particulate matter smaller than 2.5 µm PM4 Particulate matter smaller than 4.0 µm QoL SO 2 Quality of life Sulphur dioxide REPORT NO:NWU/2015/Eskom01 xxxi

32 CHAPTER 1. BACKGROUND 1.1 Introduction Purpose of this report This document provides a comprehensive report of the pilot study results conducted for Eskom in preparation of a large scale roll-out program to offset PM10 and SO 2 as part of their license extension conditions. Tender invitation and contracting Under the leadership of North-West University an experienced team responded to an invitation to tender for Request for Quote (RFQ) no. corp2915 in March 2014: The execution of a household emission offset pilot study in the Highveld priority area, Mpumalanga for the period of eighteen (18) months. The contract no commenced on 1 July 2014 and was modified in November 2015 to include additional assistance with the large scale roll-out planning and costing. A report issue 2 will be submitted once the contract extension has been completed and will include updated findings and recommendations as ongoing stakeholder consultation is taking place in preparation of the large scale rollout The structure of this report The project has been planned and implemented as 10 activities each with progress and final deliverables. The structure of this report will be a separate chapter for each activity as follow: Activity 1 - Management of working groups Activity 2 - The development of an offset methodology Activity 3 - The undertaking of air quality monitoring Activity 4 - The undertaking of dispersion modelling Activity 5 - The completion of household surveys Activity 6 - The creation of a roll-out plan Activity 7 - The intervention roll-out Activity 8 - Macro economic impact assessment and social cost benefit analysis Activity 9 - Assessment of the feasibility of the interventions Activity Background -Project Management Some background to the pilot project has been included in this report as new stakeholders, team members and client staff becomes involved in the program of activities. REPORT NO:NWU/2015/Eskom01 1

33 The program of activity (PoA) concept is well established in the carbon sector and is used to structure and manage multiple projects running for multiple years. There are similarities between carbon and air quality type projects and therefore the PoA concept is very useful in order to execute, manage and monitor a large scale offset program. In the carbon context a coordinating managing entity (CME) is usually appointed to manage and coordinate the activities important for the sustainable implementation of projects. In section 24 of the Constitution it is stated that: Everyone has the right to an environment that is not harmful to their health and wellbeing There are certain areas in South Africa where this constitutional right is particularly under pressure from an air quality perspective, and against this background the Highveld, Gauteng and recently also the Waterberg areas has been declared as air quality priority areas. The levels of emissions from power stations are required to comply with the Minimum Emission Standards (MES), which come into effect in terms of section 21 of the National Environmental Management: Air Quality Act (Act No. 39 of 2004) (NEM:AQA) since 1 April Since Eskom power stations were not able to meet these MES it had to apply to the Department of the Environment to grant a temporary postponement of the application of the new emissions requirements. Eskom applied successfully for postponement of the MES, as most of Eskom s power stations are unable to comply with the stringent emission levels set by these standards within the compliance timeframes. In many cases, Eskom power stations will not be complying with the MES within their remaining lifespans, and will not be compliant before these stations are decommissioned. The authorities set licensing conditions that offset projects are mandatory to improve ambient air quality in the direct surroundings of Eskom s power stations, and that such offset projects need to be implemented in support of the granted postponements to achieve a greater improvement in ambient air quality than would be achieved by emission retrofits The offset concept Human exposure to ground level ambient Particulate Matter (PM) emissions arguably represents the most important health related concern when it comes to ambient air quality. Household emission offset interventions aim to trade stack emissions for reduced exposure at ground level. Since domestic fuel use is such an important contributor to the overall health impact of air pollution, intervention types that reduce or eliminate domestic coal and wood burning will play an important role in improving ambient air quality. This offset pilot study together with another pilot study for Sasol in KwaDela, paves the way for Eskom s air quality offset journey, to improve the Highveld Priority Area s ambient air quality and to better general quality of life in the region. REPORT NO:NWU/2015/Eskom01 2

34 Offsets provide a particular opportunity to address domestic fuel burning emissions in the South African context, where economic growth, poverty alleviation and environmental integrity are all important issues to address in order for all South Africans to attain and maintain a decent quality of life. Offsets are tied to Minimum Emission Standard postponements, and needs to be sustained for the duration of the postponement (or for the life of the station, whichever comes first). It is proposed that offsetting is to be done on human health equivalence, using dose equivalence as a substitute. Offsets are to be developed in consultation with relevant stakeholders The pre-feasibility study The initial steps by Eskom in the offsets journey included a pre-feasibility study conducted by E-Science and Nova in The pre-feasibility study was undertaken to determine the feasibility of a PM10 and SO 2 offset programme. It had to access how an offset programme could assist in meeting ambient air quality standards in the area of its air quality impact in such a way that the offset programme leads to reduced human exposure of harmful pollution within the airsheds of existing Eskom generating power plants. The study designed the required field test project phases going forward where key design parameters for the most feasible interventions could be determined. An important finding from the structured intervention selection criteria applied in the pre-feasibility study is that households are the dominant stakeholders in air quality offset initiatives aimed at reducing pollution from domestic burning and that intensive consultation by experienced staff has to be factored in all future projects 2 The results from this desktop study and other research done for Sasol led to this accelerated air quality offset pilot study. The feasibility and pilot phases were combined due to time pressures and license postponed discussions The pilot study The current report contains the results of the Eskom pilot air quality offset study. As mentioned in the previous paragraph, the pilot contains elements of a feasibility study and as such it can be considered a phase 1 pilot. It is recommended that a phase 2 pilot or a lead implementation is done before any large scale roll-out is commissioned as a result of this phase 1 pilot results. Pilot study objective The objective of the pilot study was to test the effectiveness of the most promising household emission offset interventions identified during Eskom s pre-feasibility study including the associated emission reductions, improvement in air quality, and acceptability to households. 2 The summarised pre-feasibility report is available on internet REPORT NO:NWU/2015/Eskom01 3

35 Pilot study design The pilot study design consisted of 6 test groups of 20 households per group, which each received a different combination of interventions plus a control group of 20 with no intervention. Thus, a total of 140 subject households. Three interventions in household domestic energy patterns, namely, a new stove, a LPG stove and heater or a pre-paid voucher where combined with two thermal intervention options, namely, either a full retrofitting of the house or only a ceiling retrofit. A summary of the combinations per household group is given in Table 1-1. Table 1-1. Intervention combinations per household group Retrofitted Ceiling Control New stove LPG stove & heater Pre-paid voucher Full retrofit The full retrofit intervention entails the retrofit of a full suite of thermal shell insulation (ceilings and walls), draft proofing and Trombe walls on potentially all existing RDP houses and other suitable formal houses in the target area. Space heating is a major driver for domestic air pollution in the study area. A reduction in the need for space heating through increased thermal comfort is expected to lead to a reduction in the use of solid fuels and therefore to a reduction in household PM10 and SO 2 emissions. Basic retrofit The retrofit of ceilings and ceiling insulation to existing formal houses is intended as minimal variant of the full retrofit intervention. Although it will be less effective in terms of its thermal performance, it is cheaper and faster to implement. The assumption to test was if emission reductions are proportional to the improvement in thermal comfort inside the structure. If this is the case, one could expect emission reduction close to 70% of the reduction that can be achieved by a full retrofit. This, however, does not account for the influence of human behaviour. Ceilings can potentially be implemented in all formal houses that do not have ceilings. New stove The new stove intervention implemented a stove exchange programme where old stoves were replaced with a new smokeless model. This new stove can perform cooking, water heating and space heating tasks similar to the cast iron and welded stoves that were in use. Electricity voucher The electricity subsidy intervention provided adequate free electricity for basic domestic purposes and as such the assumption to test was if solid fuel use will become uneconomical for heating. A pre-paid voucher of R per winter REPORT NO:NWU/2015/Eskom01 4

36 month was provided. Due to power outages and power cuts the coal stoves had to remain. LPG intervention This intervention consisted of a stove swop for a LPG stove and heater. Intensive LPG training was given to all households and field workers Importance of pilot findings and recommendations The importance of this pilot study results cannot be over emphasized as the Large Scale Rollout Plan will largely be based on the findings and recommendations of the pilot and pilot extension. Challenge going forward Someone defined leadership as taking decisions with insufficient data. The offset concept and interventions are relative new and immature. However, progress must be made and some brave decisions lie ahead. Water challenge Eskom has indicated that the new emissions abatement technology required to meet the minimum emission standards at existing coal-fired power stations requires additional water resources which are currently not available: The trade-offs between meeting the air quality standards with our country s limited and scarce water resources and the need for us to reduce water consumption requires alignment between different Government departments, or a feasible plan to achieve both objectives of emissions reduction and water conservation. Eskom is in discussions with the Departments of Environmental Affairs and Public Enterprises as well as other stakeholders to find a balanced solution between the need for cleaner power and the need for security of supply. 1.3 Extension of licenses The application and conditional approval of license extensions took place during this pilot. The general condition is as follow: You are to implement an offset programme to reduce PM pollution in the ambient/receiving environment. A definite offset implementation plan is expected from yourselves by 31 March More specific conditions as per relevant licensing authorities are: Nkangala: Submit an Emission Offset Programme to reduce PM pollution in the ambient/receiving environment by the 31th March 2016 Gert Sibande: Submit to the National Air Quality and licencing Officers for approval the offset program/plan that will mitigate the priority pollutants REPORT NO:NWU/2015/Eskom01 5

37 applied for postponement including details of implementation in the surrounding affected communities/plant impact zones and timeframes by the 01 June 2015 Fezile Dabi: A definite offset implementation plan to reduce PM pollution in the ambient/receiving environment is to be presented to the NAQO and Licencing Authority by 31 March 2016 and followed by an appropriate public participation process 1.4 Scope of Work A list of the deliverables expected for this contract are summarised in Table 1-2. Table 1-2. List of contract deliverables. REPORT NO:NWU/2015/Eskom01 6

38 CHAPTER 2. MANAGEMENT OF WORKING GROUPS Christiaan Pauw, Henry Murray 2.1 Rationale The success of the project depends on the contribution of a variety of stakeholders. These interactions have to be coordinated and managed. 2.2 Objective The objective of activity 1 is to communicate with key stakeholders about the project objectives and processes and to gain their input and support in order to ensure the success of the project. This is to be done through the formation of a Technical Working Group and a Multi-Stakeholder Reference Group. 2.3 Results Due to the absolute importance of the local community and households (refer to pre-feasibility findings) it was agreed to rather have a local stakeholder reference group than a Technical Working Group. The members of the consulting team already represent most if not all of the technical knowledge required for the pilot MSRG mandate and meetings A MSRG mandate was compiled to make it clear to prospective members what their relevant responsibilities and rolls were. The team compiled a long list of potential candidates and this was reduced to a shorter list in consultation with the Eskom Client. They were then invited to the kickoff meeting which took place on 16 July All relevant documentation, such as agendas, minutes, mandate, pre-feasibility report, TOR etc. are made available to members and any interested stakeholders on the web: The intended 2nd MSRG during June 2015 was replaced with an end June 2015 progress report as the winter intervention results were not yet fully available. The feedback meeting to the MSRG was then held on 4 November Due to the relative immaturity of the AQ off-set concept these meetings were valuable to get questions and suggestions from interested members The Local Stakeholder Reference Group (LSRG) mandate and meetings Through the facilitation of Nova, communities were engaged through their representatives. These representatives were from a wide spectrum in order to not benefit just one set of representatives (e.g. only elected political leaders. The REPORT NO:NWU/2015/Eskom01 7

39 following are key stakeholder representatives were approached on the onset of the community communication: All households through elected leadership and community structures Households participating in the current project Political leadership - councillors, ward committees, community associations etc. Social leadership - religious leaders, traditional leaders, educators etc. Government - district and local South African Police Service Relevant local NGOs The project implementer and its partners/subcontractors The project sponsor The Kwazamokuhle community has a typical community structure found throughout South African townships. The groups listed above are all active in the community and do represent a wide spectrum of people. The Nova project coordinator compiled a list of contacts from each of the above sectors by visiting the relevant offices, officials and/or known persons. These individuals were invited to the first LSRG meeting held on 24 July A subsequent feedback meeting focusing on the implementation results was held on 3 November Please see Chapter 6 paragraph 3.1 for a description of the proceedings. REPORT NO:NWU/2015/Eskom01 8

40 CHAPTER 3. THE DEVELOPMENT OF AN OFFSET METHODOLOGY Rebecca Garland and Christiaan Pauw, Roelof Burger 3.1 Rationale and objective A rational, robust, transparent and workable offset protocol together with an accompanying project-type specific monitoring and reporting methodologies are essential for the success of a future air quality offset dispensation. The objectives of activity 2 are to: 3.2 Background Develop an offset protocol Demonstrate the feasibility of the protocol by developing and implementing one or more monitoring and reporting methodologies aligned with the protocol for the interventions under consideration (i.e. stationary combustion process, namely coal combustion for electricity generation, being offset with intervention(s) to decrease particulate matter (PM) emissions from stationary combustion of domestic fuels) Greenhouse gas offsetting Although air quality offsets are a relatively new field with very few examples where it has been implemented on scale, greenhouse gas offsetting is a much more established field that operate on a global scale. During the pre-feasibility phase it was recommended that the relevant principles and practices used in greenhouse gas offsetting be used as a basis for developing a workable air quality offsetting practice. The pre-feasibility study noted that, virtually all greenhouse gas offset schemes contain rules around the definition of the project activity, the project boundary (both geographical and duration), the eligibility of pollutants and offset practices, and additionality, and recommended that similar rules will have to be developed for the proposed (air quality) offset scheme. The report furthermore recommended that the emerging air quality offsets practise also follow the benchmark set by greenhouse gas offsetting by making use of standardised approaches and methodologies where similar activities be measured using the same methodologies and that procedures be put in place for developing new methodologies and modifying existing ones. The pre-feasibility study furthermore recommended that some form of third party verification be considered. The legal review also emphasised the importance of taking note of best practices in the field of greenhouse gas offsetting. Reference to compatible international and/or foreign examples is necessitated by section 39(1) of the Constitution. Hence, the competent authority must consider REPORT NO:NWU/2015/Eskom01 9

41 international law on emission trading and offset schemes, as provided in the Kyoto Protocol and the Marakesh Agreement in terms of the UNFCC. This means that the CDM project requirements must be considered as a possible benchmark for evaluating the proposed emission offset plan for the power plants. In addition, reference may be had to applicable experiences in foreign jurisdictions for example the regulatory systems that are found in various regions of the United States, European Union, Australia and New Zealand. (EHEO PFS Objective F) Greenhouse gas offsetting began in 1998 when WBCSD and WRI start working to standardise methods for GHG accounting. The Corporate Accounting Standard launched in 2001, and the Calculation tool and the GHG Protocol for Project Accounting followed. The Kyoto protocol came into effect on 16 February In 2006, the International Organization for Standardization (ISO) adopted the Corporate Standard as the basis for its ISO I: Specification with Guidance at the Organization Level for Quantification and Reporting of Greenhouse Gas Emissions and Removals. The GHG protocol had a marked influence on the CDM project standard Air pollution offsets The US Environmental Protection Agency (EPA) was the only formal regulatory air quality offsetting program found that allowed for inter-pollutant offsetting. Air quality offsetting is one of the US EPA s Economical Incentive Programs (EIPs) (US EPA, 2001). The principles of these programs are 1) integrity, 2) equity, and 3) environmental benefit. Offsetting is just one of the EIPs that can be used in the US; this may be a key point for the South African air quality landscape, that offsets are only one regulatory option in a full regulatory toolbox. In May 2008, the US EPA issued final rules governing the implementation of the New Source Review (NSR) program for particulate matter less than 2.5 micrometers in diameter (USEPA, 2008). This rule allows for inter-pollutant offset trading under the PM2.5 nonattainment NSR (US EPA, 2008). In inter-pollutant offsetting, only precursor species and their resultant secondary pollutant can be offset for each other (e.g. SO2 and NOx for PM and vice versa, and SO2 for NOx (as related to PM)) (US EPA, 2008). The inter-pollutant exchange is based on the particulate equivalency of the precursors (US EPA, 2008 and 2011). This interpollutant exchange factor that states use must have a detailed technical assessment that demonstrates the net air quality benefit of such a ration for the nonattainment area where it will be applied. A method was developed for this project that developed such a ratio for this project and was based upon the US EPA method, 3.3 Offset accounting framework Offset accounting principles formulated during the pre-feasibility study The pre-feasibility study recommended that air quality offsetting follow the best practices in greenhouse gas offsetting to the extent reasonable. This includes the idea of formulating an offset accounting protocol and thereafter to formulate a series of methodologies under that protocol. These recommendations are followed in the current project. REPORT NO:NWU/2015/Eskom01 10

42 3.4 Offset principles formulated by DEA The Department of Environmental Affairs published a notice in the Government Gazette in June 2015 for a Draft Air Quality Offsets Guideline (DEA, 2015). In this document, an environmental offset is defined as,...measures that counterbalance, counteract, or compensate for the adverse impacts of an activity on the environment. An air quality offset was defined as, an intervention, on interventions, specifically implemented to counterbalance the adverse environmental impact of atmospheric emissions in order to deliver a new ambient air quality benefit within the affected airshed/s. Wherein affected airshed means the closest area to the facility in question, wherein ambient air quality standards are being or have the potential to be exceeded and opportunities for offsetting exist. The DEA draft guideline highlights the importance of offsets and offsetting being implemented in line with the Constitution and other relevant legislation. In the document, six principles for air quality offsetting are outlined. Outcome based: Offsets must improve ambient air quality within the airshed, other positive outcomes are of secondary consideration. No like for like : It is not necessary to offset like pollutants for like pollutants (i.e. offset SO2 emissions from one source with SO2 emissions from another source). Rather, the proposed offset projects(s) should address pollutants(s) whose ambient concentration is/are of concern in a particular area, and not necessarily the pollutant(s) whose emission from a particular facility is/are of concern [emphasis in original] Transparency and acceptability: Applicants and authorities must follow an open, fair and accountable process, including public consultation processes to ensure public buy-in of offset projects. Additionality: The offsets should complement emission reduction efforts by a facility, not be seen as a replacement for such efforts. Sustainability: The offset projects should be based on long-term air quality improvement without impeding on other socio-economic and environmental objectives. Measurable and scientifically robust: Outcomes must be measurable, and the accounting of emissions must be complete and accurate. The measurement of the impact on air quality should be based on relevant and sound science. These principles in the draft guideline highlight the key features of an offsetting program in South Africa. The importance of offsetting to have a positive, sustainable and measureable impact on air quality is a clear goal; and thus it is critical to have a robust accounting framework for calculating impact. In this project, an overarching accounting protocol was developed together with methodologies for calculating impact that is aligned with the protocol for the interventions under consideration. REPORT NO:NWU/2015/Eskom01 11

43 3.5 Offset accounting principles in developed protocol A protocol was developed to provide the framework that would guide the accounting of offsetting projects. The protocol is in Appendix A. This protocol details the considerations and principles that should be applied when accounting for the air quality impacts of an activity. In addition, this protocol contains guidance on how to apply this protocol for an air quality offsetting project. Thus, this protocol can be used as an accounting or offset framework. The proposed protocol is based on six accounting principles that were first used in the WBCSD/WRI GHG Protocol and are also widely used in other forms of environmental accounting (WBCSD and WRI, 2005:22ff). They are: Transparency: Provide clear and sufficient information for reviewers and interested parties to assess the credibility and reliability of air pollution impact claims. Accuracy: Reduce uncertainties as much as is practical and put in place needed measures to improve accuracy over time. Relevance: Use data, methods, criteria, and assumptions that are appropriate for the intended use of reported information Completeness: Consider all relevant information that may affect the accounting and quantification of air pollution impacts, and complete all requirements. Conservativeness: Use conservative assumptions, values, and procedures when uncertainty is high. This means that, where uncertainty exists, the assumptions that lead to a lower estimate of the improvement in air pollution impact have to be chosen Consistency: Use data, methods, criteria, and assumptions that allow meaningful and valid comparisons. Consistency has to be maintained over time, between activity types and between effects (i.e. the secondary effects cannot be treated differently from the primary effect) These principles are applicable individually and in combination. Other principles such as simplicity and efficiency were considered, but are more suited as programme principles and not as accounting principles. Principles relating to macroeconomic cost effectiveness are in the domain of policy What is accounted for? What is accounted for is the impact pathway of an activity. For the purposes of air pollution offset accounting as considered here, this impact pathway is qualified in two ways: The medium of the impact must be the atmosphere The type of impact must be related to human health and well-being Offset accounting means to account for the impact pathways of two scenarios. In the one scenario, referred to as the project scenario, an activity is implemented specifically and intentionally to lower air pollution impact of a managed or regulated activity. The baseline scenario is then the state of affairs that would exist in the REPORT NO:NWU/2015/Eskom01 12

44 absence of a project activity. The question of additionality is already addressed in the definition of the baseline and project scenario because the project scenario would not exist where it not for a specific and intentional activity to lower air pollution impact The managed or regulated activity and the offset activity In an offset scenario one accounts for two activities, a managed or regulated activity, and an offset activity. The term managed activity is more suited to use in the case of voluntary air quality offsets which the term regulated activity is more suitable for a compliance scenario. One possibility for the definition of the managed or regulated activity is to leave this open to any activity that emits harmful agents to the atmosphere. This does not mean that all such activities can be accounted for in a satisfactory manner because the understanding of the emissions, its dispersion and transformation, and the resultant atmospheric states, exposures and effects may be lacking. The attempt at accounting will fail then, but not because the activity is not admissible by definition but because the minimum information to adhere to the accounting principles are lacking. In a compliance scenario, a certain class of regulated activities may be defined as eligible offset activities. The organisational boundaries of the managed or regulated activity can be drawn in a number of ways (a single process or a whole facility of a series of facilities). Chapter 3 and 4 of the Corporate Accounting Standard of the GHG Protocol (WBCSD et al., 2004) can help to guide this. The key is to choose an approach and use it consistently. In a compliance scenario the regulations will provide this definition because the regulated activity will be explicitly described. The offset activity is therefore that activity undertaken specifically to counterbalance the adverse atmospheric environmental effect of the managed or regulated activity. This definition also contains the idea of the baseline scenario and therefore of additionality. The baseline scenario is what the situation would have been in the absence of the project activity. The offset activity is per definition additional because it is undertaken with the specific aim of being an offset. In an offset program there may be specific rules regarding the way in which additionality is proven. 3.6 The impact pathway as basis of offset accounting The rationale for accounting for air pollution in the first place is its adverse effects. All accounting must relate to that rationale in some way. The fact that avoiding the adverse effect of air pollution is the context of justification for air pollution accounting does not necessarily mean that is has to be the unit of comparison in every case. It does, however, mean that the unit of comparison must be justified in terms of the rationale at all times (see Fischer, Theo E and Pauw, Christiaan J, 2012:5). The atmosphere as medium must play a critical part in the protocol. The atmospheric environmental effects of an activity are all significant primary and secondary effects of an activity by way of the atmosphere that result from the REPORT NO:NWU/2015/Eskom01 13

45 activity. An impact pathway is the causal route through which an atmospheric emission brings about an effect in living or inanimate objects and thereby in changes physical or living systems (Figure 3-1). An air pollution offset can only be considered in cases where there is an overlap in the impact pathways of two or more sources. The impact pathway is therefore the basis of offset accounting. Figure 3-1. Impact pathway used in accounting protocol The implication of this formulation is that the effects of an activity are the total impact pathway. Significance means up to the point where the effect size is of no practical significance or where the effect may not be reasonably detected. The impact pathway includes the emissions, its atmospheric transport and conversion, the exposure to receptors of value and their uptake of the pollution, and the resultant impact. The unique problem of air pollution accounting is that the receptors of value will typically be people something that cannot be aggregated or exchanged. This means that in principle the primary effect has to be estimated for every receptor because of the inherent spatial and temporal nature of air pollution. The disaggregation to receptor level is an unavoidable aspect of air pollution accounting. It does not however mean that such an estimate will have to be done on an interval scale but for offset accounting to work this must be done at least on an ordinal scale (see Krupnick, Oates and Van De Verg, 1982) 3.7 Comparison criteria Unlike greenhouse gases, air pollutants are short lived (e.g. minutes to week), and thus vary greatly spatially and temporally. Thus, when considering the impact pathways of two different sources (i.e. managed activity and project activity) it is very likely that while these pathways will intersect, they will not be identical. For example, when considering air quality offsets, factors that may differ between the sources include, Seasonality and timing of emissions and ambient pollution levels Receptors are at different distance from the source, and thus may have different impacts Injection height Airshed(s) that are impacted (e.g. managed activity may impact larger airshed) Populations that are impacted (including differences in vulnerability and exposure) And when considering the not like for like principle from DEA, which is called inter-pollutant offsetting here, factors to consider include, Different health impacts from different pollutants Threshold levels for impact REPORT NO:NWU/2015/Eskom01 14

46 Exposure periods that lead to impacts - acute vs chronic Absorption into body Dose-response functions Different lifetimes Different reactivity When accounting for the impacts from an offset, the protocol recommends to map out the full impact pathway for both activities. This will assist in highlighting the overlaps in the pathways, as well as the key differences that must be considered when crafting and implementing an offsets project. Only those activities that have intersecting and overlapping impact pathways can be used in an offsets project. 3.8 Inter-pollutant exchange factors A key principle of the South African air quality offsetting discussion is inter-pollutant offsetting. This adds a level of complexity, as it is necessary to convert between pollutants. The impact of an emission source is a function of the ambient concentrations resulting from that source at each receptor location. In cases where the pollutants for the managed source (the source to be offset) and the project source (the source whose emissions are reduces as an offset) are the same, a comparison of impact can simply be made by comparing the ambient concentrations of the pollutant of concern at each receptor point in the target area. Where pollutants differ, the pollutants have to be transformed to a common unit for comparison. There are different approaches to such an impact calculation that all have merits but also limitations. In this project, methodologies were drafted to account for impacts of Eskom emissions and domestic burning emissions from Kwazamokuhle as well as the exchange factor to equate SO2 emissions from Eskom to PM emissions from domestic burning. These four methodologies convert between the two pollutants at various steps along the impact pathway. These approaches are listed below, with their place on the impact pathway in italics. Particulate equivalence (ambient concentration) Air quality standard weighted intake (uptake) Health risk (single outcome or severity weighted) (impact) Burden of disease (single outcome or severity weighted) (impact) The draft methodologies for particulate equivalence and burden of disease are attached as Appendices B and C, respectively. A brief description of each is presented below, while the appendices contain more detailed information on the different approaches. Particulate equivalence is the approach that views gaseous pollutants such as SO2 and NO2 as particle precursors and directly compares the total particulate load (primary and secondary) resulting from each source. In this method, equivalencies REPORT NO:NWU/2015/Eskom01 15

47 are calculated to relate the emissions from each source with its PM ambient concentrations at the receptor. This method was based upon the inter-pollutant exchange methodologies for the US EPA. Air quality standard weighted intake transforms the ambient concentrations to an intake for each member of the affected population and weights the intake of each pollutant by the ambient standard for that pollutant in such a way that all the intake of pollutants are expressed in PM10 intake. The standardised intake of the exposed individual is then summed obtain a population intake. The health risk approach is a rights-based approach that compared the risk posed to a single sensitive individual at each receptor point by the ambient concentrations of pollutants resulting from each source. The end-point in terms of which the risk is defined is an important consideration. By default, mortality risk is used. An example of this approach is the air pollution index based on daily mortality risk of a series of pollution proposed by Cairncross et al. (2007). The relative risk (RR) associated with a 10 µg/m3 increase in daily exposure to particulate matter, sulfur dioxide, ozone and nitrogen dioxide that they propose is given below (Table 3-1). Table 3-1. Relative risk (RR) range, averaging period and stat used per pollutant in Caincross et al. (2007) air pollution index RR.low RR.central RR.high Averaging Period (hr) Value used PM mean PM mean SO mean O max O3.1hr max NO max The burden of disease approach is more comprehensive but requires extensive population characteristics to implement since it calculates the attribution of each source to a series of health endpoints that are aggregated once it has been weighed for severity and duration. It is clear that the information required by the different calculation approaches are different. The ambient as concentrations shown above is all that the particulate equivalence approach needs as long as that include both primary and secondary particles. The health risk approach needs only choose a risk metric and calculate the risk posed by the ambient concentrations at each reception location for every period. The air pollution index proposed by Cairncross, John and Zunckel (2007) is used in this example. 3.9 Draft offset protocol Protocol, policy and programme There is a difference between an offset accounting protocol, an offset accounting policy and an offsetting programme. REPORT NO:NWU/2015/Eskom01 16

48 3.9.2 Air pollution accounting protocol The purpose of an offset accounting protocol is to provide the basis for consistent air pollution accounting and reporting as a minimum set of principles and procedures. As such it is formulated in a policy neutral way to the largest extent possible. It addresses the question what air pollution accounting and reporting is and what its minimum requirements are without explicit reference to policy decisions like particular regulations, standards, permissions, liabilities or ownership. Although it is policy neutral by design, it is not completely value neutral. It embodies the precautionary principle because the accounting for air pollution is done in a conservative manner, i.e. the risk of understating air pollution is avoided rather than the risk of overstating air pollution. An air pollution accounting protocol aims to improve the consistency and quality of reporting on air pollution, be it for regulatory, management or strategic purposes. One expects that the formulations contained in the protocol will not change much over time and that it should be acceptable to a broad range of stakeholder even though their interests and policy views may differ Air pollution offset policy A policy pursues particular societal or environmental goals through regulation or interventions. It contains decisions regarding the balancing of rights and goals. A regulatory policy describes or brings into existence rights and duties. As such it is political in nature because it embodies a set a values and interests in the way that it balances different competing societal goals and interests. Policy may change as political ideology or the power of interest groups change Air pollution offset programme An air pollution offset programme functions within the context of a policy that allows air pollution offsetting. A programme contains the mechanisms and institutional structures needed to make the goal set in policy a reality. As such, the goals of a programme relates to efficient and effective realisation of the policy objectives. A programme makes use of a protocol for a specific purpose. It contains further requirements suites for its purpose, such as particular calculation methodologies. Issues around project registration, third party validation and verification belong to programme domain Interactions The practice of emissions offsetting involves all three these aspects. Reporting of the air pollution resulting from the regulated (in a compliance scenario) or managed (in a voluntary offset scenario) facility and the offset source(s) have to be quantified and reported in a consistent way (i.e. in accordance with an existing or implied protocol). In a voluntary offset scenario there need not be any further interaction on a programme or (external) policy level although voluntary reporting programmes may exist and it is often of strategic importance for firms to pre-empt regulation by understanding their own environmental impact and engaging in self-regulation. In the compliance scenario the regulator will likely require that emissions be reported in a specific format, perhaps audited and submitted to the regulator though a prescribed procedure. All of these are programme aspects. What the programme seeks to achieve is a policy matter. REPORT NO:NWU/2015/Eskom01 17

49 The draft protocol is in attached in Appendix A. This protocol must be fully tested and examples provided in the text before it is finalised Draft methodologies The Air Pollution Impacts Protocol provides a framework for air pollution impact accounting. It does not however give specific and detailed guidance for the application to particular activities. Activity or project-type specific methodologies can be developed under the protocol to fulfil this need. Appendix D contains the guidance on development of methodologies. Briefly, methodologies must at the minimum contain information on: Activity type Definition of the valued states or objects on which the accounting is orientated Definition of the aspects of the impact pathway to be quantified Applicability conditions Project boundary Baseline impacts Project impacts Monitoring These headings are the same headings in the protocol, and thus the protocol guidance must be followed in developing these activity/project specific methodologies. A methodology is not a calculation tool, these tools can be referred to separately as similar calculation tools may be used across methodologies Methodologies developed during this project For this project methodologies were developed to estimate the impact from emission from a stationary combustion process, namely coal combustion for electricity generation as the managed activity, and emissions from domestic solid fuel use as the project activities. In addition, methodologies estimating this impact in four different metrics were developed, namely, Particulate equivalence Air quality standard weighted intake Health risk (single outcome or severity weighted) Burden of disease (single outcome or severity weighted) The two in bold have complete draft methodologies that are undergoing testing. The other two methodologies are currently in development for later testing Methodology testing All developed methodologies will be tested using the scenario of the impact of the Hendrina power station on Kwazamokhule, and the impact of domestic burning in Kwazamokhule on the ambient air in Kwazamokuhle. CAMx modelled output will be REPORT NO:NWU/2015/Eskom01 18

50 used for the Eskom impact, and CalPuff output used for the domestic burning impact. All four methodologies will be tested using the same inputs. In this scenario, the Eskom emissions that need to be offset are 85% of monthly SO2 emissions per month. In addition, the testing will provide an opportunity to test potential sensitivities in methodologies, such as sensitivity to spatial and temporal resolution. The outline of the methodology testing procedure is in Appendix E. Testing is ongoing for two of the four methodologies Estimation of impact and scale of offset For the methodology testing, each methodology will use the same input to calculate a similar metric. In this first round of testing, two metrics are tested. Both calculate the number of households needed for Hendrina to meet its MES for SO2 (i.e.. 85% decrease in emissions). The first metric is max potential, which was calculated assuming that the house goes from kg coal use per month to 0 kg coal use per month. The coal use figures are for Kwazamokuhle from Nova for the control houses. The second metric is basic retrofit, which was calculated assuming a decrease of 28kg of coal per month. This value was the calculated coal savings from the Nova data for the houses ladled basic insulation. Preliminary results from the testing of the particulate equivalence method (Appendix F) and health impact methods (Appendix G) are attached as appendices. These preliminary results are based on preliminary model output, and thus the absolute numbers may change drastically when the final model outputs are used. In addition, the testing of the methodologies is focussing on testing sensitivities of the methods, as well as comparing the output of the methods, and less on calculating the actual impact Conclusions Work Package two has focussed on developing the framework and protocol for accounting for the impact of air pollution, and air pollution offsetting. This protocol was developed to be policy-neutral, and thus could inform the quantification of impacts of air pollution from many projects, and not just offsetting. The protocol is currently being tested through the development, application and testing of associated methodologies. In this study, there are four methodologies that have been developed in order to quantify the impact Eskom emissions and domestic burning emissions. They all follow the same path on the impact pathway, however have different end points. These four methods are currently being finalized and tested. The testing will involve using the same inputs into all methodologies to calculate similar metric(s). The purpose of the testing includes performing sensitivity tests to better understand uncertainties and impact of assumptions in the methods, and to compare the outputs from the different methods. REPORT NO:NWU/2015/Eskom01 19

51 CHAPTER 4. THE UNDERTAKING OF AIR QUALITY MONITORING Stuart Piketh, Roelof Burger, Gabi Mkhatshwa, Brigitte Language and Michael Weston 4.1 Introduction South Africa adopted a new Air Quality Act (AQA) in The new act is a significant departure from the Air Pollution Control Act of 1969). In the old legislation air pollution was controlled exclusively from the point of emission. As a result the ambient concentrations were seldom considered an important determinant in deciding on the emission permits of industrial and other major sources. In comparison, AQMA is based exclusively on the status of air pollution in the ambient environment. In order to effectively implement and control air quality, it is necessary to monitor and measure the concentrations of criteria pollutants in the ambient atmosphere to understand the mitigation measures required at the sources to adequately control ambient air quality. Ambient air quality is still controlled by the three tiers of government by imposing restrictions or emissions standards on contributing source in a particular air shed. Over the past decade managing poor air quality has become increasingly complex due to several factors that include, poor economic growth and high unemployment in South Africa, increasingly difficult economic climate and currency weakness and restricted electricity supply. To date the scheduled industries have made important steps to comply with revised emissions standards for their activities. Although much work still needs to be done, the major challenge to Government in controlling air quality in South Africa townships remains the extensive use of domestic burning for cooking and space heating. Exposure to ambient particulate matter is currently the single biggest challenge to the authorities. Emissions calculations reveal that scheduled industries contribute the biggest fraction of particulate matter to the atmosphere on an annual basis. This, however, is misleading in that if the exposure fraction is taken into account, particulate emissions from domestic fuel burning in townships represent by far the highest risk to the population. Ambient concentrations of particulate matter constitute a significant health risk to exposed populations around the globe. It has recently been estimated that approximately 3 million deaths annually worldwide, are directly related to fine particulate (PM2.5 aerodynamic diameter < 2.5 µm) air pollution levels (Lim, 2012 and WHO, 2013). The problem is most prevalent in developing countries with the biggest burden carried by the poor and vulnerable population groups. This is particularly true of the South African context. The burning of coal and wood as a primary fuel source is restricted to the poorest communities in South Africa. Wood is used mostly used by rural households who fall below the 40% income decile. Coal is used mostly in cold urban areas near the coal mines on the Mpumalanga Highveld (Friedl et al., 2008: 17-34) Previous studies in South Africa have identified domestic coal and wood burning as the most significant source of suspended particulate matter (PM) to the ambient environment (Annegarn et al., 1998; Engelbrecht et al., 2000; Engelbrecht et al. 2001; Engelbrecht et al., 2002; Mdluli et al., 2005 and Worobeic et al., 2011). Other significant sources of PM in the townships were identified as the burning of waste, biomass burning, motor vehicle emissions, resuspended aeolian dust (Annegarn et REPORT NO:NWU/2015/Eskom01 20

52 al., 1998 and ; Engelbrecht et al., 2002). Few studies have considered the air quality simultaneously in both the ambient and the indoor environments. It has been shown that in poorly ventilated households the exposure of inhabitants to PM during the burning of coal or wood is extreme (Mdluli et al., 2005). The purpose of this Chapter is to outline the monitoring activities that were undertaken as part of the Eskom initiated Offset project in The activities for this component of the project have been conducted jointly by the Air Quality division of Eskom RT&D and North-West University. 4.2 Monitoring objectives The overall objectives of the air quality monitoring component of the project are: 4.3 Methodology To establish the current status of air quality in Kwazamokuhle township. Determine the relative contribution of domestic solid fuel burning compared to other pollutant sources. Determine the current status of indoor air quality (in particular particulate matter) in Kwazamokuhle Determine the level of personal exposure to particulate matter loading in Kwazamokuhle. Establish if indoor particulate matter concentrations drop in houses that have been fitted with cleaner cooking and space heating interventions. Establish the spatial homogeneity of particulate matter ambient concentrations in the Kwazamokuhle township (this objective was added as an additional objective and will not be addressed in this report) Ambient monitoring Eskom RT&D in conjunction with The Climatology Research Group at North-West University established a permanent air pollution monitoring station on the western side of Kwazamokuhle Township (Figure 1) in Mpumalanga that was regarded as being representative of air quality of the study area. Meteorological parameters have been monitored simultaneously at the site. A detailed list of the pollutants and meteorological parameters monitored are given in Table 4-1. Data presented and discussed in this report were collected between January and November A map showing the relative position of the monitoring station is given in Figure 4-1. REPORT NO:NWU/2015/Eskom01 21

53 Figure 4-1. A map showing the Kwazamokuhle Township on the Mpumalanga Highveld and the relative position of the long term Ambient monitoring station established for this project represented by a star (created by M Weston, E-Science, 2015). REPORT NO:NWU/2015/Eskom01 22

54 Table 4-1. Ambient air pollution and meteorological parameters measured at Kwazamokuhle Township between January and November Measured Parameter Instrument type Units Range Air pollution parameters 1 Sulphur dioxide (SO 2) Thermo 45i ppb Nitrous Oxide (NO) Thermo 42C ppb Nitrogen dioxide (NO 2) Thermo 42C ppb *Ozone (O 3) Thermo 49C ppb Carbon monoxide (CO) ppm Carbon dioxide (CO 2) ppm Particulate matter (PM10) THERMO Beta g.m gauge 8 Particulate matter (PM2.5) THERMO Beta gauge g.m Meteorological parameters 9 Wind Speed RM Young m.s Wind direction RM Young degrees Atmospheric Pressure RM Young hpa Solar radiation Licor W.m Temperature Vaisala (y50) C Relative humidity Vaisala (y50) % Rainfall Campbell Scientific mm Indoor and personal exposure monitoring Indoor PM levels were measured using a Dusttrak The Dusttrak is a lightscattering nephelometer that utilises a longwavelength laser (λ = 780 nm) and is calibrated at the factory with Arizona road dust. Air is sampled through a PM10 inlet at 1.7 L.min-1, providing output in mg.m-3 (Watson et al., 2011). Due to the nature of the measurement the results have been found to range between 2 and 3 times higher than measurements taken with standard gravimetric sampling (Kim, et al., 2004 and Watson et al., 2011). A site specific correction factor has been calculated for Kwazamohuhle during this project. A discussion of this methodology is described below. The instruments were used in conjunction with a 10-mm Nylon Dorr-Oliver Cyclone which is able to discriminate between the respirable fraction and larger aerosols. The cyclone, operated at 1.7 L.min -1, provides a 50 % cut-off at 4 μm (TSI, 2010). A total of 9 different houses had Dusttrak samplers installed that are discussed in this report. Additional sampling will be undertaken in 20 houses in total during A local operator who checked that the instruments everyday was employed as previous experiments showed that this was necessary. Personal exposure measurements were taken using TSI Sidepak AM510 instruments. These instruments are also scattering nephelpometers (laser has λ = 680 nm). The instruments are light weight and also equipped with 10-mm Nylon Dorr-Oliver Cyclones effecting the same 50 % cut-off at 4 μm (Klepeis et al., 2007, TSI, 2010 and Jianga et al., 2011). The battery life of the personal monitors was between 8 and 12 hours. Individuals were therefore requested to carry the monitors only during the daytime 07H00 to 19H00. Exposure for the night was recorded by the Dusttrak instruments inside the households. A total of 8 individuals were asked to carry the personal samplers over the sampling campaign. Additional measurements will be made of personal exposure during Data capture for these instruments were interrupted by several factors: REPORT NO:NWU/2015/Eskom01 23

55 Electrical supply problems. Households switching off the instruments during the evening (this was resolved by visiting the site everyday) Data download errors Instrument failure Correction factor measurements and calculations The respirable fraction of indoor particulate matter (PM4) matter was evaluated for a two week period during July 2015 (6 July, 2015 to 22 July, 2015). The sampling occurred within a single household as to obtain a baseline for the PM4 concentration experienced within the indoor environment. The house for this period of sampling was selected based on three main criteria. Firstly the household had to actively partake in the burning of solid fuel/coal within the indoor environment; secondly daily access to the sampling site was required and the thirdly it should not have been subjected to any structural changes/retrofit. The monitoring incorporated two different methodological approaches, namely, (i) the direct-reading photometric instruments used for the continuous monitoring and (ii) the gravimetric sampling used to evaluate the previously mentioned. Sampling occurred in 12 hour intervals from 10h00 to 22h00 and again from 22h00 to 10h00. These specific sampling times were chosen as to avoid a sample collecting PM over multiple peak burning periods found in these types of settlement; which could result in filter overloading in the gravimetric sampling. Direct-Reading Photometric Instruments (Continuous Monitoring Instruments) PM 4 concentrations in indoor air has been measured using three direct-reading photometric instruments, namely the SidePak AM510, DustTrak Model 8520 and DustTrak II Model 8530 (TSI Inc., Shoreview, MN, USA). A 10-mm Nylon Dorr Oliver Cyclone inlet (TSI Inc., Shoreview, MN, USA) was used with each instrument, at a flow rate of 1.7 L.min-1, to acquire the required 50% cut size at 4 μm. The output for the particulate mass concentration is given in milligram per cubic meter (mg.m-3). An averaging period of five minutes was used. These instruments are factory calibrated using the respirable fraction of standards ISO , A1 Arizona test dust. Prior to the start of the sampling campaign the photometric monitors were inspected for calibration to confirm that the instruments calibrations were still valid. The instrument flows were checked (Gilian Gilibrator 2 Calibration System) and recorded prior to and after each sampling event to ensure that the instrument sampled within 5% of the required 1.7 L.min-1. Additionally these instruments were fitted with an inline TSI flow meter to continuously record the instrument flow during each sampling event. Zero-calibration was also conducted, before each sampling event, by attaching the zero-filter as per manufacturer s specifications. The Dorr-Oliver Cyclone inlets were check and cleaned as needed. Table 4-2 provides the manufacturers specification for the above mentioned instruments. REPORT NO:NWU/2015/Eskom01 24

56 Table 4-2. Manufacturer specifications for the photometric instruments. SidePak AM510 DustTrak Model DustTrak II Model Flow Rate (L/min) (1.7) (1.7) (1.7) Particle Size Range (μm) ± ± ±10 Mass Concentration Range (mg/m 3 ) Laser Beam Wavelength (nm) Operating Temperature ( C) Temp. Coefficient (mg/m3 per C) Zero Stability (mg/m3) over 24-hr at 10 second timeconstant ±0.001 ±0.001 ±0.001 Calibration Arizona Test Dust Arizona Test Dust Arizona Test Dust Gravimetric Sampling Method The gravimetric sampling was done by exposing 37 mm cassettes, at a constant flow rate of 1.7 L.min -1, using Gilian GilAir Plus (Sensidyne, Clearwater, FL, USA) pumps. The gravimetric sampling occurred collocated with the photometric monitors. Thirty-seven millimetre Mixed Cellulose Ester (MCE) filters, used in the 37 mm cassettes, were weighed in a weighing lab prior to and after sampling. Weighing was done by making use of a XP26 DeltaRange Microbalance (Mettler- Toledo AG, Greifensee, CH) having a sensitivity of 1μg. Filters were handled with powder free gloves as to prevent contamination. The micro-balance scale was checked and calibrated according to manufacturer s specifications prior to each weighing session. The Gilian GilAir Plus pumps were calibrated for flow at 1.7 L.min -1 using the Gilian Gilibrator 2 Calibration System. The calibration system required the use of a loaded cassette and the inlet to ensure that these sections do not compromise or impede the flow in any way during active sampling. As previously mentioned the cyclone inlets were checked and cleaned as needed. The actual mass collected on the filter during gravimetric sampling was calculated by using equation (1): M PM = (M f M i )10 6 (Equation 4-1) where MPM is the actual mass collected on the filter in μg, Mf is the post-exposure filter weight in g, Mi is the pre-exposure filter weight in g, and 106 is the unit conversion from g to μg. The total volume of air sampled was calculated with equation (2): V T = (F ave )(t) 10 3 (Equation 4-2) where VT is the total volume of air sampled in m3, Fave is the average flow rate in L.min-1, and t represents the elapsed time in minutes. The gravimetric PM4 concentration was calculated from the laboratory data and the sampler volume using the equation (3): PM = M PM V T (Equation 4-3) REPORT NO:NWU/2015/Eskom01 25

57 where PM is the gravimetric PM4 concentration in μg/m3, MPM is the actual mass collected on the filter in μg, and VT is the total volume of air sampled in m3. The photometric calibration factor for each instrument was calculated by the equation below, where the 12 hour gravimetric concentrations were divided by the 12 hour time-integrated mass concentration averages of the continuous photometric instruments. Cal. Factor = 12hr Grav.Conc. 12hr Time Integrated Inst.Conc. (Cur. Cal. Fac. ) (Equation 4-4) The continuous respirable PM4 measurements were then corrected by dividing the five minute averages with the specific photometric calibration factor assigned to each instrument. Photometric Calibration Factors A total of 102 samples were collected during the sampling campaign of which 72 filter samples were valid (SidePak AM510 = 26; DustTrak 8520 = 20; and DustTrak 8530 = 26). The 30 invalid filter samples were mainly excluded due to the power outages experienced during the sampling campaign and flow errors experienced by the instruments. For the purpose of this report only the SidePak AM510 and DustTrak Model 8530 results will be considered. The custom photometric calibration factors, obtained by the gravimetric sampling, for the SidePak and DuatTrak instruments are 1.40 and 1.38 respectively. The datasets have been corrected by applying these calibration factors. Statistical Analysis All statistical analyses were performed with a 0.95 confidence and a 0.05 significance. Descriptive statistical analyses were done to obtain the general statistics such as the sample size, mean, standard deviation, and range of the individual datasets. Additional analyses included (i) frequency and cumulative distributions; (ii) simple time series were plotted as to identify the average diurnal PM4 patterns of the specific household; and (iii) daily box- and scatter plots to identify day-to-day variations in measurements within the single household. 4.4 Results of meteorological conditions and measured air quality Meteorological conditions at the monitoring station Wind data collected at Kwazamokuhle show that the winds are predominantly calm. Wind speeds less than 1 m.s -1 occur % of the time at this site (Figure 4-2). This is an important finding especially in light of dispersion modelling activities for this project. Dispersion models are not able to effectively deal with calm conditions. It should also be noted that any emissions into the atmosphere under these stagnant conditions will have adverse implication for air pollution pollutants will accumulate in the local atmosphere. Wind roses for Kwazamokuhle show a predominance of wind from a north-westerly (8.9 %) and easterly (10.6 %) sectors. The wind blows from a south-south-easterly REPORT NO:NWU/2015/Eskom01 26

58 direction for approximately 4.5 % of the time (Figure 4-2). The wind speeds never exceed 8 m.s -1. The wind direction is highly diurnal in nature. During the daytime the wind blows predominantly from the north-westerly sector, while at night the wind blows from the east and south-east throughout the year (Figure 4-3). The southsouth-easterly wind starts to form at about 21h00 and continues to strengthen until sunrise (Figure 4-3). This very prominent direction of the wind is a winter phenomenon and is almost certainly associated with the topography of the region and the light winds that occur under dominant high pressure circulation (Figure 4-4). Figure 4-2. Wind roses calculated for Kwazamokuhle between December 2014 and November REPORT NO:NWU/2015/Eskom01 27

59 Figure 4-3. Hourly wind roses at the monitoring station in Kwazamokuhle for December 2014 and November REPORT NO:NWU/2015/Eskom01 28

60 Figure 4-4. Monthly wind roses measured at Kwazamokuhle monirtoring station between December 2014 and November Pollution roses have been constructed for collected ambient meteorological and pollution data at Kwazamokuhle. The measured pollution data, are represented as percentiles: the minimum detectable limit and the 25% percentile, the 25% percentile and the 50% percentile, the 50% percentile and the 95% percentile and the 95% percentile to the maximum measured value. When calculating the percentiles, the data below the minimum detectable limit has been excluded. The legs of the pollution rose represent the frequency that the wind was blowing from the direction the leg is pointing. The diurnal variation of all the meteorological parameters measured are summarised in Figure 4-5. It is interesting to note that the majority of rainfall occurs during the daytime between 10h00 and 13h00. The variation of the meteorological parameters for the year is summarised in Figure 4-6. REPORT NO:NWU/2015/Eskom01 29

61 Figure 4-5. Diurnal variation of measured meteorological parameters measured at Kwazamokuhle monitoring station between December 2014 and November REPORT NO:NWU/2015/Eskom01 30

62 Figure 4-6. Annual variation of measured meteorological parameters measured at Kwazamokuhle monitoring station between December 2014 and November Observed pollution concentrations Kwazamokuhle Sulphur dioxide The highest concentration of SO 2 measured during the monitoring period was just over 200 ppb (Figure 4-7). SO 2 does not exceed the ambient air quality standards at Kwazamokuhle despite the extensive use of coal as a solid fuel source. The diurnal variation of the SO 2 concentrations at Kwazamokuhle show a distinct tall REPORT NO:NWU/2015/Eskom01 31

63 stack pattern during the summer months (Jan and Feb) which then becomes more complex as winter approaches. During winter (represented by June) a very prominent evening peak is detected at Kwazamokuhle showing the influence of the coal burning in the township (Figure 4-8). This peak in the evening is absent at Hendrina monitoring station which is not directly impacted by the domestic burning emissions. It should be noted that the emissions from Kwazamokuhle are kept local during the winter evening due to the very low wind speeds observed from approximately 22h00 until sunrise the next morning (Figure 4-5). Figure 4-7. Measured SO 2 at the Kwazamokuhle monitoring site between January and December Figure 4-8. Diurnal variation of SO 2 measured at Kwazamokuhle and Hendrina from January to June The Red lines represents Kwazamokuhle (µg.m -3 ) and the blue line represents Hendrina (µg.m -3 ) (Taken from M. Weston, Chapter 4 this document) A SO 2 pollution rose suggests that the highest concentrations of this pollutant originate from the north-west, west and south-west (Figure 4-9). As indicate in Figure 4-1, the monitoring station is in the south-eastern corner of the township. The peak coming from the north-west is likely to be the daytime maximum occurring in the summer months from the down washing plume from Hendrina Power Station. REPORT NO:NWU/2015/Eskom01 32

64 Figure 4-9. Pollution rose of SO 2 for the Kwazamokuhle monitoring station between January and November Oxides of Nitrogen NO and NO 2 reach peak concentrations of 193 and 174 ppb respectively during the winter of 2015 (August) (Figure 4-10 and Figure 4-11). A period of elevated concentrations of both species occur during July and August The diurnal patterns show and morning (06h00-10h00) and evening peak (17h00-22h00) for both NO and NO 2 (Figure 4-12 and Figure 4-13). The NO concentrations are higher in the morning peak while the opposite is true for NO 2. The pollution roses for NO and NO 2 show slightly different patterns. The north-west is a direction that contributes both pollutants (Figure 4-14 and Figure 4-15). This was also a dominant direction for SO 2. Hendrina Power station is in this northwestern sector approximately 18 km from the township. REPORT NO:NWU/2015/Eskom01 33

65 Figure Measured NO at the Kwazamokuhle monitoring site between January and December Figure Measured NO 2 at the Kwazamokuhle monitoring site between January and December REPORT NO:NWU/2015/Eskom01 34

66 Figure Diurnal pattern of measured NO at the Kwazamokuhle monitoring site between January and December Figure Diurnal pattern of measured NO 2 at the Kwazamokuhle monitoring site between January and December REPORT NO:NWU/2015/Eskom01 35

67 Figure Pollution rose of NO for the Kwazamokuhle monitoring station between January and November Figure Pollution rose of NO 2 for the Kwazamokuhle monitoring station between January and November REPORT NO:NWU/2015/Eskom01 36

68 4.5.3 Ozone Ozone concentrations are always closely associated with the nitrogen species. Ozone values were detected well above background concentrations (20 ppb) during the daytime and are representative of a typical urban or suburban environment (Figure 4-16). Ozone concentrations frequently exceeded 85 ppb. Concentrations reach 85 ppb throughout the year with no distinct pattern during the increase of these maximum levels during summer (during maximum photolysis). The ozone concentrations detected at the site do not exceed the national ambient air quality standards. The diurnal signature of the impact of Ozone is given in Figure It shows a typical photochemistry signature. Figure Diurnal pattern of measured O 3 at the Kwazamokuhle monitoring site between January and December Particulate matter Particulate matter levels in the ambient environment Particulate matter concentrations represent the biggest risk to health impacts on eth local communities as well as being the single biggest emission from domestic coal burning. A successful emissions offset programme is most likely to be focused on the reduction of particulate matter emissions from solid fuel fires in low income homes. Hourly PM10 and PM2.5 concentrations at Kwazamokuhle reached over 400 µg.m -3 during the one year of sampling (Figure 4-17). Average PM10 concentrations range between 50 and 150 ug.m -3, while the PM2.5 concentrations vary between 25 and 50 µg.m -3. Both components have distinctive seasonal patterns. PM10 and Pm2.5 increase significantly during the winter season (beginning of May to middle of August). The concentrations for PM2.5 increase by as much as a factor of 3 and the PM10 slight more to a factor as much as 5. In the time series of the PM10 the increase is not only evident in the average values but there is a distinct shift in the baseline levels during this time. It is evident from eth time series that PM2.5 makes up a significant fraction of the total aerosol loading. This should be investigate as a possible signature fingerprint for low temperature fires for future studies. REPORT NO:NWU/2015/Eskom01 37

69 A distinct diurnal pattern of the ambient concentration emerged. Both the PM10 and PM2.5 fractions have two peak concentrations, early morning and evening. PM concentrations decline during the daytime, in particular the PM2.5 (Figure 4-18). Concentrations remain elevated throughout the night. These patterns of PM are similar to previous studies and are closely tied to the cooking and space heating habits of the township inhabitants (see fire ignition behavior in Section 6.7.4). The elevated concentrations at night are a result of a low mixing boundary layer caused by the formation of a surface inversion layers on all cloud free nights as well as the low wind speeds discussed above. Figure Five minute average PM2.5 and PM10 concentrations measured at Kwazamokuhle between January and November Figure Diurnal pattern of PM2.5 and PM10 measured at Kwazamokuhle between January and November REPORT NO:NWU/2015/Eskom01 38

70 Comparison of ambient SO 2, PM10 and PM2.5 between Kwazamokuhle and Hendrina monitoring stations The Department of Environment (DEA) maintains an ambient air quality monitoring station at the nearby town of Hendrina. SO 2, PM10, PM2.5 and NO X data were obtained from the SAAQIS data base for Hendrina for January November 2015 from the South African Weather Services to compare the two monitoring stations. Kwazamokuhle monitoring station records SO 2, PM10 and PM2.5 concentrations that are twice as high as values at Hendrina monitoring station for both hourly and daily averages (Table 4-3). The NO and NO2 concentrations are higher at Hendrina. This is difficult to explain and needs to be investigate. From a seasonal point of view the highest concentration of the PM10 and PM2.5 are measured at both sites between May and August. The concentrations are between 1.2 and 2.2 times higher at Kwazamokuhle with the biggest differences also occurring during the winter months (Table 4-3Table 4-4). Table 4-3. Average hourly and daily concentrations of SO 2, NO, NO 2, PM10 and PM2.5 measured at Kwazamokuhle and Hendrina monitoring stations between January and November Hendrina Kwazamokuhle Hourly Daily Hourly Daily Count Mean Count Mean Count Mean Count Mean SO2 (ppb) NO (ppb) NO2 (ppb) PM110 (µg.m-3) PM2.5 (µg.m-3) REPORT NO:NWU/2015/Eskom01 39

71 Table 4-4. SO2 (ppb) NO (ppb) NO2 (ppb) PM10 (µg.m-3) PM2.5 (µg.m-3) Average daily concentrations (by month) of SO 2, NO, NO 2, PM10 and PM2.5 measured at Kwazamokuhle and Hendrina monitoring stations between January and November Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Hendrina Count Mean Kwazamokuhle Count Mean Hendrina Count Mean Kwazamokuhle Count Mean Hendrina Count Mean Kwazamokuhle Count Mean Hendrina Count Mean Kwazamokuhle Count Mean Hendrina Count Mean Kwazamokuhle Count Mean Indoor concentration of PM Exposure to Indoor PM 4 intensive campaign Mean indoor PM 4 mass concentrations as measured by the SidePak and DustTrak instruments within the indoor environment are ± (SD) µg.m -3 and ± (SD) µg/m3 respectively. The PM 4 concentrations range from a minimum of 0 to a maximum of and µg.m -3 (Table 4-5). Table 4-5. Descriptive Statistics of Indoor PM 4 Measurements (µg.m -3 ). N M SD Min Max LQ UQ SE SidePak AM DustTrak N - Sample size M Mean SD Standard Deviation Min Minimum Value Max Maximum Value LQ Lower Quantile UP Upper Quantile SE Standard Error The cumulative distributions (Figure 4-19(b) and Figure 4-20(b)) indicate that the 99th percentile values for the SidePak and DustTrak PM 4 measurements are 990 REPORT NO:NWU/2015/Eskom01 40

72 µg/m3 and 1205 µg.m -3. The majority of the PM 4 measurements (62.29% SidePak and 57.63% DustTrak) are less than 75 µg.m -3, thus 37.71% and 52.36% of the measurements during the two week period exceeded the 75 µg.m -3 set standards for 24-hour PM 10. ( REPORT NO:NWU/2015/Eskom01 41

73 Table 4-6 & Table 4-7 below supported by Figure 4-19 (a) & Figure 4-20 (a)). a) b) Figure Frequency a) and cumulative b) distributions of PM 4 (µg.m -3 ) for the personal SidePak monitor within the indoor environment. REPORT NO:NWU/2015/Eskom01 42

74 Table 4-6. Frequency table for SidePak measurements taken in July From... to... Count (N) Cumulative Count (N) Percent (%) Cumulative Percent (%) 0.00 < < < < < < < < < a) b) Figure Frequency a) and cumulative b) distribution of PM 4 (µg.m -3 ) for the DustTrak monitor within the indoor environment. Table 4-7. Frequency table for DustTrak measurements taken in July From... to... Count (N) Cumulative Cumulative Percent Percent (%) Count (N) (%) 0.00 < < < < < < < < < < REPORT NO:NWU/2015/Eskom01 43

75 The diurnal pattern (Figure 4-21) is typical to what we would expect to see in a house that practices an activity such as the indoor low level combustion of solid fuels. There is an identifiable burning cycle over the 24-hour time period. During the morning there is a peak in PM 4 mass concentrations between 05h00 and 10h00, while the evening peak shows an increase in PM 4 mass concentrations between 16h00 and 22h00. These peaks indicate that the burning of solid fuels within the household can be directly linked to the increase in PM 4 concentrations in the indoor environment. The residents are exposed to greater levels of PM 4 during these times. Figure Diurnal pattern of 5-min average concentrations of indoor PM 4 for both the personal SidePak monitor and the indoor DustTrak monitor during the winter period, 6 to 22 July 2015, for a single household. The daily mean indoor PM 4 mass concentrations were found to exceed the 24-hour National Ambient PM 10 Standard of 75 µg.m -3 for 12 and 13 days of the 17 day sampling period by a factor of at least 10 (Figure 4-22 and Figure 4-23) (It is important to note that these readings are the 5-min averages and not averaged over a 24-hour period, thus it cannot be directly compared as it is only used as a reference.). REPORT NO:NWU/2015/Eskom01 44

76 Figure Box-plot of the daily mean SidePak PM 4 concentrations (µg.m -3 ) experienced over the two week monitoring period during the winter period, 6 to 22 July Figure Box-plot of the daily mean DustTrak PM 4 concentrations (µg.m -3 ) experienced over the two week monitoring period during the winter period, 6 to 22 July REPORT NO:NWU/2015/Eskom01 45

77 The concentrations (Figure 4-24 and Figure 4-25) are highly variable within this single household as it represents the 5-min mass concentration averages over a two week period, which includes both burning and non-burning days. These measurement are also affected by the infiltration of ambient particulate matter, into the indoor environment, though open windows, doors and the lack of proper insulation. The mornings of the 14, 15, 17, and 18 July represents times at which no burning took place; (household did not have a coal supply available) however, there is still a slight increase in the level of PM 4 measured during the above mentioned peak burning times. This might indicate the infiltration of ambient PM 4 into the house from the ambient environment. Figure Time series of 5-min SidePak PM 4 (µg.m -3 ) categorised by date for the period of 6 July 2015 to 22 July REPORT NO:NWU/2015/Eskom01 46

78 Figure Time series of 5-min DustTrak PM 4 averages (µg.m- 3 ) categorised by date for the period of 6 July 2015 to 21 July Conclusions Measurements of ambient pollution concentrations and meteorology have been successfully undertaken at Kwazamokuhle since December 2014 until November The most important meteorological finding is high percentage calm periods (wind speeds below 1 m.s -1 ) at Kwazamokuhle (61.4 %). This has significant implications for the accumulation of especially low level emissions such as those emanating from domestic burning. Sulphur dioxide was shown to have elevated concentrations at distinct time of the day that varied by season. During the summer concentrations where found to be highest during the middle of the day. This is indicative of a tall stack impact most likely to be from Hendrina Power Station. In general it is not likely that SO 2 exceeds the ambient air quality standards. Oxides of nitrogen show a distinct diurnal pattern that is not consistent with impacts from power station emissions. This needs further investigation as it is unlikely to detect SO 2 and not NO from the Hendrina power station. NO levels are highest during the morning peak while NO 2 concentrations are highest during the evening peak. High concentration of Ozone have been detected at Kwazamokuhle during the sampling period. Concentrations reach 85 ppb throughout the year with no distinct pattern during the increase of these maximum levels during summer (during maximum photolysis). The diurnal cycle of Ozone is a typical for the production of Ozone though photolysis. Particulate matter concentrations represent the biggest risk to health impacts on eth local communities as well as being the single biggest emission from domestic coal REPORT NO:NWU/2015/Eskom01 47

79 burning. PM10 and PM2.5 concentrations were found to be high in the ambient environment in Kwazamokuhle with the signature bimodal peak concentrations associated with domestic cooking and space heating. PM2.5 made up a significant fraction of the aerosol loading. PM10 and PM2.5 concentrations are significantly elevated from end of May to middle of August. This time of the year coincides with a higher number of cold days. The indoor environment had significantly high concentrations of respirable particulate matter associated with the morning and evening burning periods identified in the diurnal pattern. During these burning period 32% to 57% of the reading exceed the 24-hour 75 µg.m -3 standard for ambient PM10. The 24-hour PM10 standard is exceeded by up to a factor of 10. A significant finding is that in times where no indoor combustion of solid fuel took place there is only a slight increase in the level of PM4. This could possibly be the result of ambient PM infiltrating into the indoor environment. REPORT NO:NWU/2015/Eskom01 48

80 CHAPTER 5. THE UNDERTAKING OF DISPERSION MODELING Theo Fischer, Michael Weston, Mogesh Naidoo and Rebecca Garland 5.1 Overview The aim of the dispersion modelling is to model household emissions for a baseline scenario before interventions are implemented and to then run scenarios for various interventions. The reason this is needed is that the houses selected for intervention are too few to register a change in ambient monitoring, whereas the pilot project is interested in mass roll out of an intervention, which can be simulated in the model. While the modelling may not represent measured ambient data exactly, it does represent the percentage decrease in ambient concentration between baseline and intervention scenarios. This in turn is used to calculate the health effect and the potential improvement in health. For the purposes of dispersion modelling the CALPUFF suite of models was employed (Figure 5-1). CALPUFF is an EPA approved model and a recommended model in the draft Guideline to Air Dispersion Modelling for Air Quality Management in South Africa. The CALPUFF model is a non-steady state with capabilities of modelling regional or high resolution scenarios. It provides for source input in various forms, whether point, area or volume and allows for time varying emissions, as will be required for household fuel use. Dispersion modelling was conducted using emissions inventories of; Household emissions (derived from survey data) and Eskom emissions (supplied by Eskom) The household survey data represents the baseline emissions scenario from households before interventions in fuel use were applied. During the intervention phase sample houses were selected for the energy weighing campaign in order to measure in quantitative change in fuel use per intervention type. These results were compared to a control baseline group. CALPUFF requires meteorological input which is processed using CALMET, a micro scale, diagnostic meteorological model. CALMET is initiated with either observed data or meso scale meteorological data. We suggest the latter methodology and will present the methodology here for all dispersion modelling here below. REPORT NO:NWU/2015/Eskom01 49

81 Figure 5-1. Flow diagram of modelling process. The household emissions inventory was modeled for different model set up scenarios, in other words the emissions inventory stays the same but the way emissions behave is changed in the model (Table 5-1). This included altering the diurnal cycle of burning based on measured temperature data on stove chimneys and including observed wind speed data to better capture calm conditions at night. Table 5-1. Model setup scenarios that were tested. Emissions Inventory Meteorological input Diurnal cycle of emissions Baseline Household emissions WRF only WRF and observed WRF and observed Based on observed ambient data Based on observed ambient data i-button temperature cycle REPORT NO:NWU/2015/Eskom01 50

82 5.2 Baseline Emissions Inventory Emissions from combustion of household fuel are estimated as follows: E ij =EF ij * A j * HH s (Eq 1) E ij denotes the total of emissions of the pollutant i (i.e. PM10, SO2) from the fuel j (i.e. wood, coal). EF is the emission factor per type of fuel (Table 5-2), A specifies the average amount of fuel j used per household in the area of study (Table 4), and HHs the number of households in the area. Emission factors were derived from previous studies of fuel use on the Highveld of South Africa (CSIR Environmentek, 2005) (Table 5-2). These were applied to the fuel use results from activity 5 to calculate total emissions of each pollutant. The undertaken household emissions quantification is based upon the information contained in the StatsSA 2011 Census (household count per subplace) and the household surveys conducted under activity 5 in this project. Figure 5-2 presents the location of each census sub place. For each census subplace the percent of houses that use coal was calculated from survey results and Census 2011 results and showed that the survey results presented much higher coal use than the census results (Table 5-3). KwaZamokuhle results varied from % houses using coal from survey results compared to 2-39 % in the census data. This significantly alters the dispersion modelling results, with the census data underestimating the emissions. The major fuel use reported is coal with winter use ranging from about kg per household per winter month (Table 5-4). The net result is that tons of PM10 are emitted in the year from households in KwaZamokuhle compared to tons/annum from the census data. REPORT NO:NWU/2015/Eskom01 51

83 Table 5-2. Emission factors for household fuel use applied in (Eq 1). Grey cells are derived from literature. Pink figures are derived making certain assumptions. Coal (g/kg fuel) Wood (g/kg fuel) PM PM SO CO NOx VOCs Figure 5-2. Census sub places of the KwaZamokuhle according to the Census 2011 delineation. REPORT NO:NWU/2015/Eskom01 52

84 Table 5-3. Percentage of houses using fuel as per Census data and the survey data. Survey data reports much higher fuel use. HH Count Data Percentage Using Coal SP_Name TotalHH_Census TotalHH_NOVA (1.5%Inc) UsingCoal Census (%) UsingCoal NOVA(%) Mafred Emaskopasini Tycoon Mapehla KwaZamokuhle SP Hendrina SP Table 5-4. Estimated fuel use per summer and winter month based on census 2011 and survey data. Summer Coal Usage per HH (using coal) Winter Coal Usage Per HH (using coal) Subplace Name Coal Census (kg/summer month/hh) Coal NOVA (kg/summer month/hh) Coal_Census (kg/winter month/hh) Coal_NOVA (kg/winter month/hh) Mafred Emaskopasini Tycoon Mapehla KwaZamokuhle SP Hendrina SP KwaZamokuhle Total REPORT NO:NWU/2015/Eskom01 53

85 (a) (b) (c) (d) Figure 5-3. Household fuel emission rates for a.) summer PM10, b.) summer SO2, c.) winter PM10 and d.) winter SO2. REPORT NO:NWU/2015/Eskom01 54

86 Eskom emissions were supplied by Eskom based on monthly production at Arnot, Camden, Duvha, Grootvlei, Hendrina, Kendal, Komati, Kriel, Majuba, Matimba, Matla and Tutuka. 5.3 Preparation for Dispersion Modelling Diurnal and Seasonal Cycles Household emissions vary through the day typically with a peak in the morning and a peak in the evening. This variation need to be included in the dispersion model and initially the cycle was determined by calculating the hourly average PM10 ambient concentrations from the ambient monitoring (Figure 5-4). The potential risk with this approach is that the ambient monitoring will include sources other than the household emissions, however, even when the i-button data was later implemented for the diurnal cycle is showed similar morning and evening peaks as well as use during the day between peaks. Summer and winter have peaks at the same time but the magnitude in summer is between % of the winter peaks. To determine which months to model as summer and winter we calculated the monthly average temperatures from the ambient monitoring. Summer and winter was split in 8 months and 4 months with September-April as summer and May-August as winter. Figure 5-4. Diurnal cycle applied to emissions from household fuel use. REPORT NO:NWU/2015/Eskom01 55

87 After the i-button data became available it was possible to identify when fires were ignited. The i-button is a temperature sensor that was placed on the chimneys of selected houses where the different interventions were introduced. Interventions were based on fuel type and the retrofit applied to the house where: Coal Basic: No energy subsidy. Ceiling insulated. Coal Full: No energy subsidy. Ceiling insulated and walls insulated. Electricity-Basic: Electricity subsidy. Ceiling insulated Electricity Full: Electricity subsidy. Ceiling insulated and walls insulated. Control: No subsidy or insulation. Results showed that the morning fires correlated with the morning peak ambient PM10 emissions, while the afternoon fires were started earlier than the peak ambient concentration (Figure 5-4). This lag is most likely due to a change in meteorological conditions, where a surface inversion is present later in the evening. However, this does indicate that emissions start earlier in the evening than originally input in the baseline modelling (Figure 5-5). To account for this earlier peak the model diurnal cycle was adjusted so that the timing of the model peaks coincided with the timing of emissions from the control group (Figure 5-6). Figure 5-5. Diurnal cycle i-button chimney data and ambient PM10. REPORT NO:NWU/2015/Eskom01 56

88 Figure 5-6. Adjusted model diurnal cycle (button profile) compared to ambient PM10 and the diurnal burning cycle from the control household group. 5.4 Model domain The model domain for household emissions centred on KwaZamokuhle and included the power stations of Hendrina, Arnot and Komati (domain was roughly 50km by 50km). The model resolution was 300m and made use of discrete receptors for a buffer around KwaZamokuhle. A regional domain with a 2m resolution was used to model the contribution from the remaining Eskom power stations to ambient air. Both are shown in Figure 5-7. REPORT NO:NWU/2015/Eskom01 57

89 (a) (b) Figure 5-7. a) Model domain and b) discrete receptors used in the model domain. REPORT NO:NWU/2015/Eskom01 58

90 5.5 Ambient data at the site Meteorological data The observed wind speed indicates a high frequency of low wind speed at KwaZamokuhle (Figure 5-8 and Figure 5-9). This is significant for dispersion of emissions, especially at night when the calm conditions occur in conjunction with low level nocturnal inversion layers resulting in high concentrations. At low wind speeds the wind direction is spurious and should be ignored. Rather, the dominant wind directions are north-easterly, north-westerly and south-westerly. The meteorological modelling captures these wind directions as the most frequent, but overestimates the wind speed during calm conditions. Thus, the model is expected to cause efficient dispersion at night when calm conditions occur and is evident in the dispersion model results presented later in this report. Figure 5-8. Windroses from May and June 2015 at KwaZamokuhle for Observed data. REPORT NO:NWU/2015/Eskom01 59

91 Figure 5-9. Windroses from May and June 2015 at KwaZamokuhle for CALMET model Local source of emissions KwaZamokuhle is located adjacent to the town of Hendrina where the Department of Environmental Affairs has a long standing ambient monitoring station. This station is located about 3 km south west of ambient monitoring at KwaZamokuhle (Figure 5-10). This means that both stations should be affected equally by regional sources (e.g. Eskom) and should show the same signal in concentration peaks for regional sources. This means that any signal present at one station but not the other is most likely a local source and not a regional source. From the diurnal cycle of PM10 it is clear that there is a morning and evening peak at KwaZamokuhle that is not evident at Hendrina which is indicative of local domestic burning (Figure 5-11). However, also surprising is the evening peak in SO2 at KwaZamokuhle which indicates a local source unique to KwaZamokuhle and is most likely domestic fuel combustion (Figure 5-12). The midday peaks in SO2 evident at both ambient stations is indicative of tall stack emissions. This means that a decrease in domestic fuel combustion will have a combined improvement on ambient PM10 and SO2, and not just PM10 as expected. REPORT NO:NWU/2015/Eskom01 60

92 Figure Ambient monitoring station location at KwaZamokuhle and Hendrina. Figure Diurnal cycles of ambient PM10 at KwaZamokuhle and Hendrina monitoring stations. REPORT NO:NWU/2015/Eskom01 61

93 Figure Diurnal cycles of ambient SO2 at KwaZamokuhle and Hendrina monitoring stations. 5.6 Chemical air quality modeling The focus of task has shifted somewhat from what was in the original proposal to Eskom. The original intent of air quality modeling using CAMx was not only to evaluate the extent (both spatial and magnitude) of Eskom s contribution to sulfate aerosol over the Highveld, but also to estimate changes in general air quality over the Highveld due to theoretically scaled emission changes around the community brought about by the interventions. The current focus for the chemical modeling is now to only answer the former, i.e. what is Eskom s contribution to sulfate aerosol over the Highveld? This change in scope was requested by Eskom and was discussed on the 22 April 2015 meeting with Eskom, and confirmed with follow-up discussions with Dr Langerman from Eskom on and over the phone. This focus will support better Eskom s large scale offset plan. The air quality model used for the chemical air quality modelling is the US-EPA approved regional air quality model CAMx ( The first step was to develop a regional emissions inventory for input into CAMx. The inventory should cover the following sources: 1. Eskom 2. Sasol 3. Residential fuel use 4. Vehicles 5. Biogenic 6. Biomass burning 7. Agriculture 8. Other industry (i.e. excluding Sasol and Eskom) CSIR developed the emissions inventory for biogenic emissions. Eskom provided emissions for Eskom power stations (received on 27/05/2015), and liaised with REPORT NO:NWU/2015/Eskom01 62

94 Sasol to provide emissions information for Secunda (received on 12/08/2015). The version of the draft emissions inventory from EScience that we are using and incorporating into CAMx is the version updated on 25/09/2015. Currently, emissions from other industry sources are still outstanding. At the request of Eskom for any initial estimate of Eskom secondary aerosol (through sulfate) a preliminary methodology was formulated since the regional emissions inventory was not ready in time. This was used to inform the first draft of Eskom s large-scale offsets plan and initial results were presented during the meeting of 02 September 2015, and data files have since been sent to Eskom for their internal use. It is recognized however that those results are only a preliminary estimate, and the more detailed modeling that was proposed will still be done. Table 11 below highlights the key differences between the model set-up and inputs for Plan B and the Final Assessment. In addition, in the Final Assessment run(s), the team will attempt to use the Plume in Grid (PIG) functionality in CAMx for Eskom power stations. PIG allows individual point sources to be treated in a semi- Langrangian way. The limiting factor of the CSIR being able to use PIG will be the computing power needed for PSAT (which tracks Eskom SO2 and sulfate aerosols) and PIG to be run simultaneously. CAMx is run on the CHPC Table 5-5. Comparison of model set-up and inputs for Preliminary B versus Final Assessment model. Item Preliminary Final assessment Resolution 12km 4km Number of cells 150 x 135 x x 110 x 18 (x, y, z) Coverage National Regional (Highveld) Period 2006 (2014 Eskom) 2014 (2006 other industry ) Met fields CCAM WRF Initial and boundary conditions Chemistry in CAMx Tracking of Eskom emissions Cape Point GAW site monitored data CBIV PSAT MOZART Global modelled output CB05 (newer code) PSAT In order to complete this task, the regional emissions inventory needs to be finalised. To date the Other industry sources are outstanding. In order to be able to include this source category in the emissions inventory, we will use the current regional emissions inventory that covers sources 1-7, and supplement the Other Industrial sources with an older dataset (i.e. that used within the preliminary exercise). The Other Industry emissions in this older dataset will be for 2006, and were calculated using a top-down approach. In order to use the Other Industry emissions from the older dataset in the new CAMx run, the inventory will be regridded from the 12km resolution of the older dataset to the 4 km resolution of the updated CAMx run. REPORT NO:NWU/2015/Eskom01 63

95 The CSIR team is currently working through the emission data that have been sent through from EScience and Sasol (QA/QC, VOC/PM speciation, temporal profiles, regridding and formatting for CAMx), and will begin work on regridding the Other Industry for use in the new 4 km CAMx runs. The preliminary model runs have been used in the methodology testing (work package 2), however, the final assessment output will be used to work towards answering what is Eskom s contribution to sulfate aerosol over the Highveld? 5.7 Dispersion Model results Temporal distribution Dispersion modelling of PM10 compared favorably to ambient concentrations when compared to average diurnal concentration in winter months (May June 2015). Initially the model under estimated evening concentrations due to the difference in wind speed between the model and observed wind speed (Figure 5-13). The model over estimated wind speed which resulted in more efficient dispersion. When observed wind speed was included in the model the calm conditions were assimilated and the evening model concentrations increased accordingly. Figure Diurnal cycle on observed and modelled PM10 at KwaZamokuhle. For SO2 emissions the results from the households were added to the results from Eskom as described in Table 5-6. Modelled results captured the midday and evening peak as shown in Figure 12. The inclusion of regional SO2 significantly increased the evening peak SO2 which is essentially due to its role as background SO2 relative to household emissions. Household contributed about 75% of the evening peak SO2 concentration while regional sources contributed about 25%. Interestingly, the observed data does not have a matching morning peak in SO2 as seen in the observed PM10. This is most likely due to some reaction of SO2 in the morning related to higher relative humidity that results in the removal of ambient SO2. The alternative explanation would be to suggest that the sources of PM10 and SO2 are independent; however there is no evidence at this stage to support this. REPORT NO:NWU/2015/Eskom01 64

96 Overall, the model slightly under predicts PM10 (due to lower evening peaks) and over predicts SO2 (due to higher morning peaks) for the baseline emissions modelling (Table 5-7). The mean bias indicates the direction (over or under) of the error while the root mean square error indicates the magnitude of modelled concentrations. Table 5-6. CALPUFF model scenarios for combining household and Eskom SO2 emissions Source Scenario SO 2.hh Households (300m) Eskom (300m) Hendrina +Arnot +Komati Eskom (2km) Incl Hendrina +Arnot +Komati Eskom (2km) Excl Hendrina +Arnot +Komati SO 2.eskom_hh SO 2.eskom_regional.hh SO 2.eskom.300m.regional. HH Figure Diurnal cycle on observed and modelled SO2 at KwaZamokuhle. These model results are a combination of regional and near field model domains where observed meteorological data was not included. REPORT NO:NWU/2015/Eskom01 65

97 Table 5-7. Statistical performance of CALPUFF PM10 and SO2 at KwaZamokuhle. Pollutant Averaging Period Sources MB RMSE (ug/m3) PM10 24hr Households PM10 1hr SO2 24hr Eskom 300m Eskom 2km SO2 1hr Hosueholds Spatial distribution The spatial distribution of modelled concentrations of PM10 and SO2 captures the gradient in concentration seen in the observed data between KwaZamokuhle and Hendrina ambient monitoring stations (Figure 5-15 a and b). Concentrations are highest, and exceed the ambient limits, over the south of KwaZamokuhle for the baseline modelling without observed meteorological data. However, when the calm conditions are included in the modelling by assimilating the observed wind speeds, the area of exceedance extends to the whole of KwaZamokuhle for PM10 and to about half of KwaZamokuhle for SO2 (Figure 5-15 c and d). The annual average of modelled SO2 from Hendrina, Arnot and Komati power stations ranges between 5-6 ug/m3 (Figure 5-16a) while the remaining power stations annual average ranges between ug/m3 (Figure 5-18). This is in line with the diurnal model results that indicate the regional modelling as a source of background SO2 to KwaZamokuhle that can contribute to evening peaks. However, although exceedance of the 1 hour SO2 limit of 350 ug/m3 occurred in the model, it did not occur more than 1% of the time (i.e. within the limit of 88 occurrences in the year) (Figure 5-17). REPORT NO:NWU/2015/Eskom01 66

98 a) b) c) d) Figure Maximum 24-hour model concentration during winter (May-June 2015) from household emissions for a) PM10 baseline, b) SO2 baseline, c) PM10 baseline with observed meteorology and d) SO2 baseline with observed meteorology. Exceedance of the ambient limit. REPORT NO:NWU/2015/Eskom01 67

99 a) b) Figure Annual average of SO2 from the three power stations closest to KwaZamokuhle, Hendrina, Arnot and Komati for a.) the model domain and b.) zoomed into KwaZamokuhle. a) b) Figure Maximum 1 hour SO2 concentration from CALPUFF for the three power stations closest to KwaZamokuhle, Hendrina, Arnot and Komati for a.) concentration and b.) number of exceedances. REPORT NO:NWU/2015/Eskom01 68

100 Figure Annual average of SO2 for all power stations excluding Hendrina, Arnot and Komati. 5.9 Summary and Conclusions The development of emissions from the household survey results combined with emission factors from a literature review provided an adequate, if not exceptional emissions inventory for household emissions modelling. This information alone provided morning and evening peaks of the same magnitude as the observed data. Further refinement of the meteorological data and timing of emissions achieved even better results than the baseline modelling. This emissions inventory is deemed adequate for the task of assessing sensitivity of household emissions to interventions applied and the resultant change in ambient concentrations. REPORT NO:NWU/2015/Eskom01 69

101 CHAPTER 6. THE COMPLETION OF HOUSEHOLD SURVEYS Christiaan Pauw and Alex Howard 6.1 HEALTH ASPECTS The levels of emissions from power stations are required to comply with the Minimum Emission Standards (MES), which came into effect in terms of section 21 of the National Environmental Management: Air Quality Act (Act No. 39 of 2004) (NEM:AQA) on 1 April Many of Eskom s power stations are unable to comply with the required emission levels within the compliance timeframes; some will not be able to comply within their remaining lifespans. Eskom has therefore applied for postponement of the date on which they have to comply with the MES. Offset projects are considered to be a method to improve ambient air quality in the immediate vicinity of power stations in support of Eskom s application for postponement. The end result is envisaged to achieve a greater improvement in ambient air quality than what would have been achieved by emission retrofits. During Eskom s pre-feasibility study, household emission interventions were identified as being the most promising offset project. Household fuel emissions are an issue, especially in low and middle income countries. It was estimated that in 2012, about 3 billion people were relying on household fuel as energy carrier for cooking and heating globally, and that it resulted in some 4.3 million premature deaths worldwide, as well as being responsible for nearly 5% of the global disease burden (expressed as disability-adjusted life-years (DALYs)), causing it to be the single most important environmental risk (WHO, 2014a). The emissions from indoor household fuel burning of course also contribute to emissions into outdoor (ambient) air and the World Health Organization (WHO) estimated that these emissions were responsible for around 0.4 million deaths (12% of the total from ambient air pollution) in 2012 (WHO, 2014a). One activity in developing and implementing an offset project is a household survey to obtain baseline information on energy usage and domestic sources of air pollution, as well as on the quality of life of the sample community. The results of such a community survey will then allow for the estimation of the impact of domestic air pollution caused by domestic sources and the impacts of interventions on the quality of life of households and the local economy. This document reports on the results of the community study as a baseline prior to implementation of any interventions Aims and objectives of the community survey study The main aim of the community study was to provide baseline information that will be used in management and planning of the offset project. The objectives of this section of the study were: To carry out a household survey in about 1000 households in the community of concern To perform an epidemiological analysis of associations between health outcomes/diseases and environmental risk factors (exposures) REPORT NO:NWU/2015/Eskom01 70

102 To understand the relationship between human health and environmental factors using results of the epidemiological study To determine the baseline human health status through data at household level and existing disease status at individual level. Methods Introduction and rationale Many communities in South Africa are faced with a multitude of hazards in different environments, which may be of a natural, social or economic nature. Such hazards emanate from dynamic pressures such as energy production, which in turn are driven by forces such as economic, demographic and political processes within society. As a result, it has been recognised that exposure to multiple stresses and hazards is a real concern, particularly in developing countries given the co-existence of issues such as the existing disease burden (e.g. HIV/AIDS), air pollution, water insecurity, food insecurity and others. It therefore follows that such communities may face challenges that may enhance their vulnerability and undermine their coping capacity in the event of exposure to environmental pollution. Such exposure may in turn influence not only their quality of life but also their health. Why several factors, seemingly not directly linked to air pollution, must be measured in the community study? The community study, with the aim of informing the health status of the community, therefore determined not only the prevalence of illnesses and conditions, but also the status of socio-economic factors that are known to have an influence on health, as well as risk factors for illnesses. These are factors that can make people more vulnerable to a specific issue (in this instance air pollution ) or help them to cope better with the issue. For example, children, the aged, people with existing diseases (such as HIV/AIDS), and people with inadequate nutrition can be more susceptible to the effects of air pollution. On the other hand, factors such as access to health care or services can help people cope better with, and therefore to be less vulnerable to, air pollution. If people s level of education is low, they will more easily be unemployed. If they are employed, it will mostly not be in the formal sector. Thus, they will have a lack of income and a lack of means to cope with environmental stressors, for example, to provide enough healthy food to be resistant to diseases. When people cannot afford proper housing and have to live in overcrowded conditions, it may lead to unhygienic conditions and the transmission of communicable diseases such as tuberculosis (TB), which in turn make them more susceptible to the effects of air pollution. A study in Nigeria (Fakunle, 2011) found that the prevalence of acute respiratory infections in children under 5 years old was influenced, among others, by household size, number of bedrooms, ventilation and the population density in the area. People s activities also have an influence on their exposure to air pollution and therefore on their health. For example, when people burn waste it causes air pollution, and when waste is dumped anywhere it forms an ideal breeding source REPORT NO:NWU/2015/Eskom01 71

103 for vectors of diseases such as rats, mice and flies. When waste is not regularly removed, people may tend to increase dumping and/or burning waste. Study methods The community study was conducted in five areas within Kwazamokuhle, namely Emaskopasini, Kwazamokuhle SP, Manfred, Mapela and Tycoon. Kwazamokuhle is situated about 2 km north-east of the town of Hendrina in the Steve Tshwete Local Municipality in the Mpumalanga province (Figure 6-1). Figure 6-2 shows the location of the study area in relation to nearby towns. The study area lies about 55 km south-east of emalahleni and 40 km west of Carolina. A total of six field workers were recruited in each study area and then trained over a five day period. Street blocks in each area were randomly selected after which structured interviews were held with heads of households or caregivers. A total of 919 households with 3070 individuals were included in the survey, of which 117 households were in Emaskopasini, 523 in Kwazamokuhle SP, 82 in Manfred, 53 in Mapela and 144 in Tycoon. Responses on the questionnaires, that were piloted beforehand, were captured electronically using cell phones. The head of the household or caregiver answered the questions on behalf of all members of the household. A quality control process entailed re-interviewing a sample (10%) of the study participants telephonically. In the quality control process, questionnaires were evaluated in two ways. Firstly, the reported data were evaluated to determine whether the interview did in fact take place and secondly, accuracy in capturing the data was evaluated by following a set of criteria, including re-asking some questions. No field worker fraud was detected and no systematic deviations identified. REPORT NO:NWU/2015/Eskom01 72

104 Figure 6-1. Kwazamokuhle where the ESKOM community survey was conducted. Figure 6-2. Location of study area in relation to nearby towns. Univariate analysis Univariate analysis is one of the most uncomplicated forms of analysing data with one variable. Univariate analysis does not prove causality but finds patterns in the data. Data were analysed using STATA release 13 (StataCorp LP). Questionnaire data were mostly categorical (numeral/ordinal) in nature and were summarised by means of frequencies, percentages and cross-tabulations. Associations between outcome variables (respiratory variables) and various risk factors were assessed using Pearson s chi-squared test or, when applicable (cell frequency of five or less), Fisher s exact test. The crude odds ratios (ORs) along with their 95% confidence intervals (CI) were also recorded to indicate direction and strength or significance of the association (in terms of p-value). The CI is a range of possible values consistent with the odds or risk estimate. A precise CI is narrow and does not include the figure Only statistically significant associations (p 0.05) are reported. It must be noted that a statistical significant association does not imply causality. The OR is a relative measure of risk, describing the odds of someone who is exposed to the factor under investigation, developing the outcome as compared to someone who is not exposed. Some epidemiologists are of the opinion that an OR above 1.2 indicates a risk while others consider less than 1.5 a weak association (Craun and Calderon, 2005). An OR below 1 indicates protection, although some epidemiologists consider a decreased risk of 0.70 to 0.99 (thus less than 30% decreased risk) as a weak association (Craun and Calderon, 2005). It must be kept in mind that random error or chance can never be completely ruled out as the explanation for an observed association (Craun and Calderon, 2005). REPORT NO:NWU/2015/Eskom01 73

105 Multivariate analysis The associations of upper respiratory illnesses (URI) and lower respiratory illnesses (LRI) with risk factors were assessed by univariate analysis and those factors significant at the 0.1 level of significance were used in the multivariate analysis. It consisted of stepwise logistic regression during which the most likely variables were selected (which included significant p-values), followed by logistic regression to determine the final factors. Multivariate analysis allows for multiple independent variables and multiple dependent variables (outcomes) to be analysed simultaneously. While univariate analysis considers each variable in isolation, multivariate analysis considers the way that variables may interact with on one another Results of the community survey: statistical analyses Descriptive statistics Descriptive statistics for all variables were calculated using, among others, maximum, minimum, percentiles, and frequency counts. Socio-demographics Table 6-1 provides information on age, gender, employment and income of the different areas in this survey. The total study area can be considered as a lowincome community with the majority of households (about 60%) living below the poverty line with a total income of <R400 per month. The different areas were comparable in terms of their socio-demographic profile. At individual level there were more females (53.6%) than males (46.4%) in the study population. Tycoon had the highest number of females (56.2%). The overall mean age was 26.8 years. Kwazamokuhle SP had the youngest population (mean age 25.5 years). As much as 40% of the population may be classified as vulnerable to hazards including air pollution, due to their age (below 15 years or above 65 years). The unemployment rate of individuals between the ages of 20 and 59 years, who were looking for work at the time, ranged between 20.3% in Emaskopasini and 42.3% in Maphela. The unemployment rate in four of the five areas was above the rate of 24.1 % for South Africa as in December 2013 (StatsSA, 2014). The highest full-time employment rate of those between 20 and 59 years was recorded in Maphela (34.6%) and the lowest in Kwazamokuhle SP (19.6%). Mapela thus showed a large inequality because it had the highest percentage of economically active people who were unemployed and the highest percentage that were full-time employed. Most households (about 96%) had some form of income. Overall 3.5% of households had no income at all, of which the most (9%) were from Manfred. Income was largely confined to social grants: someone in the household earning a salary (about 59.5%), someone in the household receiving a pension (about 23.0%), someone in the household receiving a disability grant (about 2.3%) and someone in the household receiving a child grant (about 29.9%). Tycoon had the highest percentage (38.7%) of households where someone in the household earned a pension and Kwazamokuhle SP the highest percentage (34.6%) of households where someone received a child grant. REPORT NO:NWU/2015/Eskom01 74

106 Table 6-1. areas. Data on gender, age, employment and income of the different Factor Emaskopasini Kwaz. SP Manfred Maphela Tycoon Individual level Ave. age in years Age <15 y 23.2% 29.9% 28.7% 30.9% 24.2% Age >65 y 9.3% 11.2% 8.5% 7.8% 12.8% Female 52.3% 54.2% 45.1% 56.0% 56.2% Male 47.7% 45.8% 54.9% 44.0% 43.8% Employment level (20-59y) Unemployed-looking for work 20.3% 32.4% 24.5% 42.3% 26.9% Full-time employed 33.0% 19.6% 32.2% 34.6% 24.1% Disabled-cannot work 2.2% 1.6% 0.7% 1.0% 3.2% Household level Household with no income at all 3.3% 3.4%% 9.09% 2.38% 0.9% Income from a salary 71.4% 58.6% 50% 64.3% 56.8% Income from a pension 18.7% 19.1% 25.8% 21.4% 38.7% Income from a disability grant 4.4% 1.6% 4.5% 0.0% 2.7% Income from a child grant 27.5% 34.6% 18.2% 31.0% 22.5% Living conditions Table 6-2 provides information on the housing and assets of households in the five areas included in this survey. In order to have healthy housing it is assumed that the following elements are adequately addressed: shelter, water supply, sanitation, solid waste, wastewater, overcrowding (supports the distribution of infectious diseases), indoor air pollution, food safety, vectors of diseases as well as aspects related to transport and shopping facilities (WHO 1997). Information on living conditions is therefore important to bear in mind when considering health impacts of exposure to air pollution, because it may be risk factors for these illnesses and may render people more vulnerable to the effects of air pollution. Housing Most of the households (ranging from 88% to 97%) had only one structure in the yard, (Table 6-2). Structures were mostly (79.3%) formal (built from brick), while 18.1% were built from corrugated iron and thus considered informal. The most informal structures (29.3%) were in Kwazamokuhle SP. Households where more than four individuals shared a bedroom were considered to be overcrowded in this study. The WHO considers more than 2.5 persons per room of the dwelling as being overcrowded (WHO, 2015). Given this definition, it was evident most individuals (about 95%) did not live in overcrowding conditions. The highest number of households where more than four people shared a bedroom was recorded for Maphela. In another study in South Africa recently conducted by the CSIR, and of which the results have not been published yet, overcrowding was found to be a risk factor for upper respiratory conditions. REPORT NO:NWU/2015/Eskom01 75

107 Most of the structures had two bedrooms. This ranged from 51% to 69% of the structures. Only Manfred had structures (1.5%) with no bedrooms. Asset ownership Most households had access to information in the form of a television (ranging from 72% to 100%). The fact that between 34% and 83% of households possessed a fridge is an indication that most households were able to store food in a safe way. Not many households had their own private transport. Tycoon had the most households (36%) with a car or a truck and Kwazamokuhle the fewest (13%). Table 6-2. Data on housing and assets of the different areas. Factor Emaskopasin Kwaz. SP Manfred Maphela Tycoon i Household level Housing Brick structures 92.3% 67.5% 92.4% 92.9% 96.4 Corrugated iron structures 4.4% 29.3% 7.6% 2.4% 2.7 One structure in yard 94.5% 95.8% 98.5% 88.1% 97.3% Two structures in yard 3.3% 1.83% 1.5% 9.5% 1.8% Over crowding 1.1% 3.4% 3.0% 9.5% 2.7% > 4 sharing a bedroom Assets Anyone in hh possesses 20.0% 13.0% 32.0% 29.0% 36% car/truck Anyone in hh possesses a 95.6% 72.0% 95.5% 92.9% 100% TV Anyone in hh possesses a fridge 34.0% 36.0% 83.0% 64.0% 53.0% Access to services Information on access to services is important to consider when analysing health impacts of exposure to air pollution because infectious diseases may be reduced through measures such as infection control, but these measures often rely on basic standards of hygiene, including the provision of safe drinking water and sanitation. Water Table 6-3 provides information on individuals access to water and sanitation as a function of area. The 2013 South African Health Review reported that 91.2% of households in South Africa had access to piped water. In this survey, 85.8% of households had access to piped water either inside the dwelling (35.1%) or inside the yard (50.7%). It is assumed that households that rely solely on piped water from municipal water sources, which are treated, will be at a lower risk of waterborne diseases. Kwazamokuhle SP had the lowest number of households (76.3%) with access to piped water; while Tycoon had the highest percentage of households (100%) who had access to piped water. The provision of water was interrupted between one and 14 days for many households in all of the areas during the 90 days before the survey. On average, about 26% of households did not experience any interruptions (Tycoon was the best off with 40%), while about 19% of households had interruptions for four or more days during that time. REPORT NO:NWU/2015/Eskom01 76

108 Most households (between 90% and 100%) had cleaned the containers they use for water during the week before the survey. The minority of households treated water before use. This ranged between 2% in Manfred and 10% in Maphela. It is understandable, that people do not treat water as most had access to piped water. Sanitation The majority of households (93.3%) in the areas surveyed indicated they had access to a flush toilet, which is better than the national figure according to the WHO 2013 statistics report, where it was stated that the number for South Africa was 74% in Some households had more than one toilet in the yard. This figure ranged from 5.2% in Kwazamokuhle SP to 26.2% in Maphela. However, about 12.4% of households had no access to a toilet. This number ranged from 0% in Manfred and Tycoon, 2.4% in Maphela, and 3.3% in Emaskopasini to 21.5% in Kwazamokuhle SP. The 2013 South African Health Review reported that about 7% of households in South Africa did not have access to a toilet. Only one area (Kwazamokuhle SP) was thus worse off than the South African average. In the current survey, the most households (4.4%) where more than 10 people had to share a toilet was in Kwazamokuhle SP. Overall, about 83% of households had their waste collected and disposed of by the municipality. The 2013 South African Health Review stated that 63.6% of households in South Africa had this service. However, 2.2% of households in Emaskopasini, 6.1% in Manfred and 30.1% in Kwazamokuhle SP, had no access to refuse removal. Despite of access to waste removal, disposal of waste is an issue in some areas. A total of 56 households in the five areas indicated that they burn their waste. This practice may expose individuals to harmful emissions, including dioxins and furans, of which some are known to cause cancer (WHO, 2014b). Even in Maphela, where all households indicated that they do have access to refuse removal, 20 households reported that they burn their waste. In another study, recently conducted by the CSIR, of which the results have not been published yet, burning of waste was found to be a risk factor for upper respiratory conditions. REPORT NO:NWU/2015/Eskom01 77

109 Table 6-3. Percentage of households with access to water and sanitation in the five areas. Factor Emaskopasini Kwaz. SP Manfred Maphela Tycoon Household level Access to services Water Piped into dwelling 47.7% 18.2% 30.7% 57.5% 76.6% Piped in yard 47.4% 58.1% 64.6% 41.5% 23.4% No interruptions in last 90 days 23.1% 27.5% 7.6% 11.9% 38.7% Store water Cleaned container past week 100% 96.4% 100% 100% 90% Treat water 4.4% 5.2% 1.5% 9.5% 3.6% Sanitation Toilet No toilet 3.3% 21.5% 0% 2.4% 0% One toilet in yard 81.3% 73.3% 86.4% 71.4% 76.6% > 1 toilet in yard 15.4% 5.2% 13.6% 26.2% 23.4% Flush toilet 97.8% 89.6% 93.6% 100% 99.1% Flush sometimes not working 4.5% 1.5% 0% 0% 0.9% Hh >10 people/toilet 0% 4.4% 1.5% 2.4% 1.8% Waste Waste removal 1X/w 97.8% 69.9% 93.9% 100% 100% No waste removal 2.2% 30.1% 6.1% 0% 0% Burn waste in yard (n) Burn waste outside yard (n) Energy use It is evident from Table 6-4 the main energy carrier used for cooking and heating was not electricity, as fewer than 50% of households used electricity for cooking (47%) and heating (35%). Emaskopasini and Tycoon were the two areas where most households (about 65% and 70%, respectively) used electricity for cooking and heating. However, it was still below national average of 76% of households that used mainly electricity for cooking in 2012 (DoE, 2012). In the current survey, more than 50% of households in Kwazamokuhle SP, Manfred and Maphela used coal or wood for cooking, and more than 60% of households in the same areas used these fuels for heating. In 2011, about 15% of households in South Africa were using solid fuels for cooking and heating (WHO, 2013), thus well below the current study. REPORT NO:NWU/2015/Eskom01 78

110 Table 6-4. areas. Main energy carriers used for cooking and heating in the different Factor Emaskopasini Kwaz. SP Manfred Maphela Tycoon Household level Energy carriers Mainly electricity for cooking 64.8% 36.6% 47% 42.9% 71.2% Mainly coal/wood for cooking 34.1% 58.4% 51.5% 57.1% 26.1% Mainly electricity for heating 49.5% 26.7% 31.8% 28.6% 55% Mainly coal/wood for heating 45.1% 66.5% 65.2% 66.7% 42.3% Lifestyle Lifestyle plays an important role in a household s nutritional status and acquired illnesses and conditions. Good nutritional status helps the immune system to fight against diseases and lifestyle diseases such as diabetes, high cholesterol and high blood pressure render people more susceptible, even to effects from air pollution. Nutrition Only about 40% of the households ate fruit and vegetables at least three times a week, and about 8% ate protein at least three times a week. It is evident from Table 6-5 that Manfred had the highest percentage of households that ate fruit and vegetables (62%) and protein (20%) on a regular (at least 3 times a week) basis, followed by Kwazamokuhle SP, then Emaskopasini, Tycoon and lastly Maphela. The number of children who were getting food at school ranged between 30 in Manfred and 285 in Kwazamokuhle SP. Substance use According to the 2013 South African Health Review, the prevalence of smoking in South Africa (amongst those 15 years and older) was 16.2%. In the current study the overall (individual) prevalence of smoking was 16.8%, which is about the same as for South Africa. The prevalence ranged between 15% at Kwazamokuhle SP and 21.7% at Maphela. Due to the relatively high prevalence of smoking in Maphela it is understandable that it was indicated about 18% of individuals in this area are exposed to passive smoke. REPORT NO:NWU/2015/Eskom01 79

111 Table 6-5. Statistics on nutrition and substance use in the different areas. Factor Emaskopasini Kwaz. SP Manfred Maphela Tycoon Household level Nutrition Veg. & Fr. At least 3x/w 45.1% 40.9% 62.1% 35.7% 33.3% Prot. At least 3x/w 2.2% 8.1% 19.7% 0% 7.2% Number of children getting food at school (N) Individual level Substance use Smoking 18.3% 15.0% 18.1% 21.7%% 18.8% Exp. to passive smoke 13.8% 15.6% 1.8% 18.1% 13.1% Prevalence of health outcomes (illnesses or conditions) The prevalence of health outcomes amongst individuals were evaluated per community. As mentioned in the Section 3.2 (methodology), the head of the household or the caretaker with whom the interview was conducted, answered on behalf of the household members. The fieldworkers were able to speak the preferred languages of the area and were trained in explaining the diseases to the head of the household or caretaker should that be necessary. Prevalence of disease is a measure that indicates how much of a certain disease or condition occurs in a population at a particular point in time. It is calculated by dividing the number of cases (disease cases) by the number of individuals evaluated at a particular point in time, and is expressed as a percentage. Appendix A provides a detailed list of prevalence rates for all health outcomes evaluated in this study; the main ones are discussed here. A minority of households (5.3%) had access to a medical aid. This ranged from 2% in Kwazamokuhle SP to 14% in Emaskopasini. According to the 2013 South African Health Review, about 17% of individuals in the country had access to a medical aid. Fortunately there is a clinic in the study area. The 2011 South African General Household Survey states that about 40% of individuals in the country live within 15 minutes walk or 5 minutes drive from the nearest health facility, while another 40% live within one hour s walk or 12 minutes drive from the nearest facility. The South African General Household Survey of 2011 found that more than 90% of people went to their nearest clinic when they need medical attention. Those who indicated that they did not make use of the closest facility mostly did so because they went to a private health facility. Nearly half (47%) of the population in South Africa walked to the health facility (in some population groups up to 55% did so), therefore it is important for them to be close to such a facility. The minority of the population (about 30%) made use of public transport, while about 20% used their own transport. About 40% of the study population had never been examined by a doctor or nurse (35.2% in Emaskopasini, 41.6% in Kwazamokuhle SP, 52.3% in Manfred, 24.4% in Maphela and 39.3% in Tycoon). This raises the question whether individuals may prefer not to go to a health professional when they are ill or injured. However, the 2011 South African General Household Survey found that the majority (78%) of the population surveyed had consulted a doctor or nurse when they were ill and those REPORT NO:NWU/2015/Eskom01 80

112 who did not, were mostly young adults and the reason was that it was either not serious enough or they used self-medication. The 2011 South African General Household Survey found nearly 10% of the population surveyed at national level were ill or injured during the month before the survey. More females reported being ill or injured than males; the elderly (65 years and older) more than younger individuals; the white population group more than other groups, and those living in the Northern Cape more than those from other provinces. In the current survey 8.2% of individuals had some or other ailment during the 30 days preceding the study. It was evident from the current data that the chronic disease which most individuals were under treatment for was high blood pressure (213) followed by asthma (63), diabetes (53) and TB (32). The 2013 South African Health Review reported that about 41% of individuals above the age of 25 years had high blood pressure, 10% of those above 15 years had diabetes and 0.8% of the population had TB. The prevalence of TB was from the WHO 2013 statistics report. Overall the most prevalent acute illnesses people were diagnosed with in this study were sinusitis (6.2%), bronchitis (5.4%) and hay fever (3.5%). The 2013 South African Health Review stated that 94% of children below the age of one year had been immunised. In this survey the majority of children under the age of 16 years (99.2%) had been immunised. Emaskopasini, Maphela and Tycoon had 100% immunisation, Kwazamokuhle SP 99.6% and Manfred, 94.1%. Acute health outcomes The prevalence of acute health outcomes the individuals were diagnosed with during the month preceding the survey are presented in Table 6-6. All of these prevalences were below 10% except for hay fever in Maphela which was 12%. The prevalence rate of bronchitis was in the same order (around 6%) for Emaskopasini, Kwazamokuhle SP and Manfred, while it was much lower (4%) for Tycoon and Maphela (no cases). The highest prevalence of bronchitis and diarrhoea was recorded for Manfred, while the highest prevalence of ear infection was recorded for Maphela, and the highest prevalence of sinusitis for Kwazamokuhle SP and Tycoon. The short-term prevalence of diarrhoea for South Africa was 4% during the 2011 South African General Household Survey, thus higher than the overall prevalence of 1.8% in the current study. REPORT NO:NWU/2015/Eskom01 81

113 Table 6-6. Prevalence of diagnosed acute (month preceding study) health outcomes in the five areas. Factor Emaskopasini Kwaz. SP Manfred Maphela Tycoon Individual level Acute Past month diagnosed with Bronchitis 6.3% 5.9% 6.8% 0.0% 4.2% Diarrhoea 0.0% 0.9% 9.1% 0.0% 0.8% Ear infection 1.3% 2.7% 0.0% 4.8% 2.5% Hay fever 6.3% 2.4% 0.0% 11.9% 4.2% Sinusitis 0.0% 7.4% 6.8% 2.4% 7.6% Chronic health outcomes The prevalence of chronic diseases were also determined in the current survey by asking different questions, including the question whether an individual had ever been diagnosed with a specific illness or condition. In addition, the number of individuals under treatment for a specific disease or condition was also determined. The results of these questions on chronic conditions and treatment are presented in Table 6-7 for each of the five study areas together with the national statistics. In general, Maphela had the highest prevalence for the most number (4) of chronic illnesses or conditions (mostly lifestyle related), followed by Kwazamokuhle SP and Tycoon (2 each). Emaskopasini and Manfred each had the highest prevalence for one chronic illness only. Kwazamokuhle SP had the largest number (176) of individuals under treatment for one or more chronic illnesses. For lung illnesses, the prevalence of chronic bronchitis, asthma and tuberculosis (TB) were determined. Maphela had the highest prevalence of chronic bronchitis (1.4%), Tycoon and Kwazamokuhle SP the highest prevalence of asthma (5.4% and 5.1%, respectively) and Tycoon the highest of TB (2.9%). No prevalence for chronic bronchitis could be found for South Africa in the literature surveyed. The 2011 South African General Household Survey found the asthma prevalence in South Africa to be 2.3%, with Asian/Indian people having the highest prevalence (4.8%), followed by whites (3.1%). The prevalence among black Africans (the majority group of the current study) was lower at 1.9%. The same household survey found the prevalence of TB in South Africa to be 0.8% in The prevalence of chronic illnesses and conditions are often related to lifestyle, such as high blood pressure, diabetes and high cholesterol were also determined. Tycoon had the highest prevalence of high blood pressure (19.9%) and Maphela the highest of diabetes (5.6%) and cholesterol (0.7%). The 2013 South African Health Review reported the prevalence of high blood pressure in South Africa as 40.6% in those older than 25 years, that of diabetes as 9.5% in those older than 15 years, and that of high cholesterol as 28.1% among females and 18.0% among males. The same report stated that the Indian/Asian population group had the highest prevalence of diagnosed diabetes, while the lowest was among black Africans (4.0%). In the 2013 South African National Health and Nutrition Examination Survey (Shisana et al, 2013), results of clinical examinations were analysed. According to these examinations, high blood pressure increased with age and it was found to be REPORT NO:NWU/2015/Eskom01 82

114 the highest among the white and coloured population groups. About 66% of those with high blood pressure were also overweight or obese. The cholesterol tests showed the highest prevalence of high cholesterol was found in formal areas. The clinical tests further showed that diabetes was mostly found in urban formal and rural informal areas. The prevalence of diabetes was highest amongst Asians (11% to 30%), followed by the coloured population group (11% to 13%) and it also increased with age (Shisana et al, 2013). In a study on high blood pressure in South Africa, Kandala et al., (2013) found a noticeable difference between provinces, with the highest in the North-west and lowest in Limpopo and Mpumalanga provinces. Among the risk factors they identified were smoking, drinking, having diabetes or high cholesterol and having had a heart attack or stroke during the 12 months preceding the survey. REPORT NO:NWU/2015/Eskom01 83

115 Table 6-7. Prevalence of diagnosed chronic illnesses and number of individuals under treatment. Factor Emaskopasini Kwaz. SP Manfred Maphela Tycoon SA Individual level Chronic: Ever diagnosed with Chr. bronchitis 0.5% 0.3% 0.0% 1.4% 0.0% Arthritis 2.4% 1.9% 1.5% 0.0% 1.1% 4.2% *** Individuals under treatment for arthritis (n) Asthma 3.8% 5.1% 3.8% 4.9% 5.4% 2.3% *** Individuals under treatment for asthma (n) Cancer % 0.1% 0.0% 0.7% 0.0% 0.5% *** >25 Individuals under treatment for cancer (n) Depression 0.0% 0.8% 1.5% 0.7% 1.1% 2.0% *** Individuals under treatment for depression (n) Diabetes % 2.5% 3.1% 5.6% 5.1% Individuals under treatment for diabetes (n) Epilepsy 3.1% 0.5% 0.7% 2.1% 1.3% High blood pressure 17.2% 11.5% 18.3% 10.4% 19.9% 40.6% Individuals under treatment for high blood pressure (n) High cholesterol % 0.2% 0.0% 0.7% 0.0% 9.5 >15 >25 y F28.1% M18 % Individuals under treatment for cholesterol HIV 1.0% 1.8% 1.5% 0.7% 0.7% 10.00% Individuals under treatment for HIV (n) Tuberculosis 1.4% 1.9% 2.3% 0.0% 2.9% 0.8% ** Individuals under treatment for TB (n) ** WHO stats *** 2011 SA General Household Survey SA Health Review 2013/14 REPORT NO:NWU/2015/Eskom01 84

116 The prevalence of a number of notifiable diseases was also determined in the current study, by asking whether a person had been diagnosed with such an illness or condition during the twelve months preceding the study (Table 6-8). This was done, because existing illnesses or conditions may render a person more vulnerable to the effects of air pollution. These illnesses or conditions included the notifiable diseases bilharzia and malaria, and the non-communicable illness, pneumonia. The highest prevalence of bilharzia (1.3%) was found in Maphela, while the highest prevalence for malaria (0.2%) was found in Kwazamokuhle SP. No case of pneumonia was reported in any of the areas during the year preceding the study. Table 6-8. Prevalence of notifiable diseases and pneumonia diagnosed in the 12 months preceding the study. Factor Emaskopasini Kwaz. SP Manfred Maphela Tycoon Individual level Past year diagnosed with: Bilharzia 0.0% 0.0% 0.0% 1.3% 0.0% Malaria 0.0% 0.2% 0.0% 0.0% 0.0% Pneumonia 0% 0% 0% 0% 0% Symptoms In addition to diagnosed illnesses and conditions experienced during the year preceding the study, the prevalence of symptoms of certain illnesses and conditions for the same time period (12 months preceding the study) was also determined. These symptoms are presented in Table 9. This was done as an indication of possible existing illnesses and conditions among individuals, because not all individuals go to a health professional if symptoms are not severe enough. The prevalence of these symptoms were all below 3%. The condition that most people in all the areas had symptoms of was heartburn. In general, the highest prevalence of symptoms experienced by individuals during the 12 months preceding the study survey was recorded in Emaskopasini. These symptoms ranged from burning urine, skin conditions (itchy skin and or skin rash) to injury. REPORT NO:NWU/2015/Eskom01 85

117 Table 6-9. Symptoms experienced in the five areas during the 12 months preceding the survey. Factor Emasko Kwaz. SP Manfred Maphela Tycoon pasini Individual level Symptoms during past 12 months Burning urine 0.3% 0.3% 0.0% 0.0% 0.2% Runny nose with body ache 0.3% 0.3% 0.0% 0.0% 0.4% Runny nose without body ache 0.0% 0.1% 0.0% 0.5% 0.0% Puss from ear 0.0% 0.1% 0.0% 0.0% 0.0% Coughing (no fever, night sweats) 0.0% 0.4% 0.0% 0.0% 0.0% Severe headache 0.0% 0.2% 0.0% 0.0% 0.0% Jaundice 0.6% 0.1% 0.0% 0.0% 0.0% Heartburn 1.8% 0.4% 0.4% 2.1% 1.1% Mouth sores 0.6% 0.4% 0.0% 0.0% 0.2% Skin rash 0.3% 0.1% 0.0% 0.0% 0.0% Bad tooth 1.2% 0.9% 0.0% 0.5% 0.2% Itchy skin 1.8% 0.6% 0.4% 0.5% 0.9% Sore glands 0.3% 0.3% 0.0% 0.5% 0.4% Epilepsy 3.1% 0.5% 0.7% 2.1% 1.3% Injury 0.6% 0.1% 0.0% 0.0% 0.2% Statistical analysis of risk factors associated with relevant health outcomes Univariate analysis Risk factors were identified for relevant health outcomes (illnesses or conditions) (Appendix B) by determining crude odds ratios though univariate analysis. These health outcomes were grouped into different categories, namely those related to illnesses or conditions of the lung (bronchitis, asthma and tuberculosis) and those related to the upper respiratory system (ear infection, hay fever and sinusitis). All significant (up to 0.10 level) associations between health outcomes and risk factors were used to screen variables to be included in the next step of statistical analyses; multivariate analysis, (Section 4.2.2). However, only risk factors statistically significant (p equal or smaller than 0.05) are reported here. Risk factors associated with upper respiratory illnesses or conditions (Appendix B) Hay fever Three risk factors were statistically significant associated with the upper respiratory health outcome hay fever. These were: electricity supply being interrupted for one or more days over a period of 90 days. This is probably an indication that they then use household fuels which may be associated with the hay fever. Using electricity as one of the energy carriers for cooking was another risk factor, but this factor had a wide CI, indicating an unreliable result. The odds of having hay fever were almost three times higher when an individual was below the age of 15 years, which indicated that age group is more sensitive to the condition. No exposure factors were identified as being protective of hay fever. REPORT NO:NWU/2015/Eskom01 86

118 Sinusitis Risk factors for sinusitis were: using wood as one of the energy carriers for cooking, using dung as one of the energy carriers for heating, using wood as one of the energy carriers for heating and having had influenza during the past year. The latter risk had a wide confidence interval, indicating that the results may not be reliable. All of these risk factors are biologically plausible and the latter risk did probably coincide with the sinusitis. Factors that were statistically significantly protective of sinusitis were: spending more than 11 hours per day indoors, children getting food at school, and having high blood pressure. It is possible that children who get food at school have a better immune system and that may be why this was identified as being protective. It is uncertain why high blood pressure was protective of sinusitis. It can be speculated that those individuals are most probably on medication for the condition and that there could be an association between the medication and protection of sinusitis. A protective association between upper respiratory illness and having high blood pressure was also found in another study by the CSIR (unpublished data). Combining hay fever, sinusitis and ear infection as URI (Appendix B). Risk factors were also determined for a combination of diagnosed upper respiratory illnesses or conditions (hay fever, sinusitis, and ear infection). Risk factors statistically significant associated with this combination had to do with energy usage (using wood as one of the energy carriers for cooking, using wood as one of the energy carriers for heating, using dung as one of the energy carriers for heating), sanitation (failure to collect refuse regularly (at least once a month and dispose of waste inside the yard), having a level of education higher than no schooling (people may be more aware of URI and therefore reported it at a higher rate and they may also be seeking medical help more easily than unschooled people) and being below 15 years of age, which is an age where individuals respiratory systems are physiologically still developing. Another risk factor identified for URI, although not biologically plausible, and which may be a confounding factor, was preferred to go to a faith healer. Factors also identified as statistically significant protective of URI, were being above 15 years of age, which is biologically plausible and spending more than 17 hours per day indoors. Risk factors associated with the lower respiratory illnesses bronchitis, tuberculosis (TB) and asthma (Appendix B) Bronchitis Eight risk factors were identified as being statistically significant associated with having been diagnosed with bronchitis. These were the following: i. having been diagnosed with anaemia (OR 58.8) or epilepsy (OR 17.9) ii. owing a business (OR 4.1) (not biologically plausible) iii. have heartburn (OR 7.6) REPORT NO:NWU/2015/Eskom01 87

119 iv. using gas (OR 30.2) or paraffin (OR 12.1) as one of the energy carriers for cooking v. using a paraffin stove (OR 13.6) and vi) being exposed to passive smoke (OR 14.1). Although the odds of being diagnosed with bronchitis was almost 60 times higher when an individual had been diagnosed with anaemia, the CI was wide ( ) indicating an unreliable result. The same was true for been diagnosed with epilepsy (CI ), as well as using gas as one of the energy carriers for cooking (CI ), using paraffin as one of the energy carriers for cooking (CI ) or using a paraffin stove (CI ). All of these results (risk factors for bronchitis) are considered not reliable due to large CIs. Some factors were protective of having been diagnosed with bronchitis. These were: i) waste collected regularly, ii) 4 people use water from communal tap/source. The association between waste removal and lower respiratory illness was also found in a previous study done by the CSIR (results not published). It is possible that if waste is not collected it may be a breeding source for microbiological organisms able to cause bronchitis. The fact that 4 people use water from communal tap/source is protective cannot be explained. Asthma The risk factors that were statistically significant associated with asthma, were nearly all related to the use of energy. Using wood, paraffin or gas as an energy carrier for cooking or heating was associated with a 3 to 6 times higher odds of having asthma. The use of a gas stove in the house was associated with a 5 times higher odds and the use of a paraffin stove with nearly a 4 times higher odds of having asthma compared with individuals from households that do not use these appliances. However, all risk factors associated with paraffin as well as the use of a gas stove had wide CiIs, thus indicating unreliable results. Living in a household that receives a child grant was associated with double the odds of having asthma. This finding is not biologically plausible, but probably a confounding factor for an elevated prevalence of asthma among children. No protective factors were found for asthma. Combining bronchitis, tuberculosis and asthma as LRI (Appendix B) Lower respiratory illness was considered as positive if being diagnosed over past 12 months with either bronchitis, TB or asthma. Risk factors statistically significant associated with a combination of the three illnesses as LRI were mostly associated with energy use, but also with sanitation (fail to collect waste at least once a month, dumping of waste anywhere and feeding waste to animals and water supply being interrupted >5 days over a period of 90 days). However, all the risks factors associated with paraffin had wide CIs and can therefore be considered unreliable. As mentioned previously, the fact that receiving a child grant was associated with LRI can be explained as that children are more sensitive to LRI and the child grant is just proxy for being a child. Spending more than 17 hours indoors per day was REPORT NO:NWU/2015/Eskom01 88

120 also identified as being a risk. A possible explanation is the longer time of exposure to indoor pollution as well as the fact that those who do spend more time indoors are the very young and the aged, who are physiologically more sensitive. Other risk factors not biologically plausible but also statistically significant associated with ever being diagnosed with chronic bronchitis, TB or asthma, was earning a salary, using a small container for coal and prefer to visit a traditional healer or prefer to visit a faith healer. It can be speculated that those who earn a salary possibly also belong to a medical aid and will therefore more easily visit a health professional when having one of these illnesses or conditions and get diagnosed. Using a small container (bag) for coal cannot be explained as a risk factor other than it being an indication of coal use. Factors found to be statistically significant protective, were also related to hygiene (cleaning water containers with soap and having waste collected regularly). In addition, if people did not recycle any waste, it was protective. A possible explanation is that if people do recycle waste, they tend to pile it up and that could be a breeding source for microorganisms Multivariate analysis Demographic, as well as environmental risk factors found to be statistically significant for URI and LRI during univariate analysis were subsequently assessed by means of multivariate analysis. The multivariate stepwise regression process identified the factors which were the most significantly associated with the URI and LRI. The following risk factor was identified for Upper Respiratory Illnesses (URI) (hay fever, sinusitis, ear infection): The practice of using wood as one of the energy carriers for heating (OR 2.23; p-value 0.012; CI ) The only protective factors related to URI was never failing to remove waste (OR 0.29; p-value 0.012; CI ) and spending more than 17 hours per day indoors (OR 0.35; p-value <0.0001; CI Risk factors identified for bronchitis, tuberculosis and asthma as LRI were: Water supply being interrupted for more than 5 days during past 90 days (OR 3.78; p-value 0.002; CI ) Using a small bag for coal (OR 2.60; p-value 0.001; CI ) It must be noted that the use of a small bag for coal is believed to be an indication of coal use, as most of the households that did use coal, used the small bags, most probably because they are cheaper. Never or very rarely failed to remove waste were the two factors identified as being protective against lower respiratory illnesses. For never failing, the statistics were as follows: OR 0.25; p-value 0.022; CI For rarely failing of removing waste, it was OR 0.20; p-value 0.002; CI REPORT NO:NWU/2015/Eskom01 89

121 6.1.6 Strengths and Limitations of the study Strengths: In a cross-sectional study design, as was used in this study, many exposures and many outcomes can simultaneously be investigated Households in the different areas were randomly selected Questionnaires were administered through face to face interviews Misclassification of health outcomes was limited as the interviewer was able to clarify concepts in a language the interviewee could understand There was an intensive quality control process as described in Section 3.2. Limitations: The head of the household or caretaker answered questions on behalf of the other members of the household The number of households that could be included in the survey was dependent on the budget Concluding remarks Study in general Despite the generally low socio-economic conditions that people live in, the prevalence of illnesses (both diagnosed and self-diagnosed) in all the areas were relatively low, for example for the respiratory illnesses it was below 10%, except for hay fever in Maphela (12%). About 40% of people in the different areas (ranging from 24% in Maphela to 52% in Manfred) had never been examined by a health practitioner. Kwazamokuhle SP The socio-economic conditions in Kwazamokuhle SP were in many aspects worse than in the other four communities. The lowest percentage with access to a medical aid was from Kwazamokuhle SP. The area also had the lowest education level (about 10% with no schooling), which may be the reason why this area had the lowest percentage of economically active people who were full time employed. Furthermore this area had the highest proportion of households with no access to piped water, waste removal or a toilet, and the highest where more than 10 individuals have to share a toilet. In addition, the area had the lowest use of electricity for cooking and heating, as most households used wood and or coal for cooking and heating. Indoor pollution is thus expected to be highest in this area. The highest proportion of vulnerable people by age (<15 and >65 years) is also from Kwazamokuhle SP. As far as illnesses and conditions are concerned it was evident that this area had the highest prevalence of the acute illness sinusitis (together with Tycoon), and the chronic illness asthma (also together with Tycoon). The most individuals under treatment of asthma, high blood pressure, diabetes and HIV were from this area as well. REPORT NO:NWU/2015/Eskom01 90

122 Tycoon Tycoon was better off in many socio-economic aspects than the other areas. For example Tycoon had the highest level of education, the largest proportion of households with access to electricity, a toilet and piped water and they also had the least interruptions in water supply. However, the area had the lowest consumption of fruit and vegetables on a regular (at least three times a week) basis. As far as illnesses and conditions are concerned it was evident that Tycoon had the highest prevalence of asthma and sinusitis (both together with Kwazamokuhle), diabetes (together with Maphela) and high blood pressure. Manfred In Manfred access to services was acceptable in some aspects (all households had access to a toilet) but in others not (most interruptions in water supply). The consumption of fruit, vegetables and protein was the best in this area and probably the reason why about 50% of individuals had never been examined by a health professional. However, the area had the highest prevalence of bronchitis and diarrhoea. Maphela Maphela had the highest unemployment rate amongst the economically active group (20 to 59 years), which could be the reason why they had the lowest consumption rate of fruit, vegetables and protein as they may not be able to afford healthy food. However, certain activities by the residents of the area were increasing their exposure to air pollution. For example in addition to having the highest prevalence of smokers and highest prevalence of individuals being exposed to second hand smoke, residents also burn waste, despite having access to regular waste removal. Maphela seems to have the worst overall health status of the five areas, as the lowest percentage (25%) of people who have never been examined by a health professional is from Maphela. The area showed the highest prevalence of ear infection, hay fever, chronic bronchitis, diabetes and cholesterol and had the highest number of individuals under treatment for TB. Emaskopasini Emaskopasini showed the lowest unemployment rate which was probably the reason why the area had the highest access to a medical aid of the five areas. The area also had the lowest proportion of vulnerable individuals in terms of age (<15 and >65 years). Access to services in this area was considered acceptable as 95% of households had access to piped water either inside the dwelling or the yard, 98% had regular waste removal, 81% of households had a toilet in the yard and no toilet in the area had to be shared by 10 or more individuals. Although Emaskopasini did not have the highest prevalence of any of the diagnosed illnesses or conditions, it showed the highest prevalence for seven selfdiagnosed symptoms, including mouth sores, skin rash and bad teeth, feeling sad and being injured. REPORT NO:NWU/2015/Eskom01 91

123 Univariate analysis The risk factors for upper respiratory illnesses were mostly related to energy use, age, existing illness and sanitation/hygiene. For example the odds of having an upper respiratory illness when an individual was below 15 years of age, was almost double that of a person older than 15 years. Using wood as an energy carrier was associated with double the odds of having an URI and when dung was used the odds was almost three times higher than when dung was not used for heating in a household. The odds of having an URI was about five times higher if the household did dispose of their waste inside the yard. However, this risk factor showed a wide CI and is therefore not reliable. The risk factors for LRI were also mostly related to energy use and sanitation. The use of coal was only a risk factor when used as an energy carrier for heating. Here the odds of having a LRI when using coal as one of the energy carriers for heating, was three times higher. Using paraffin for cooking and heating was associated with a five to six times higher odds of having LRI and using wood for cooking and heating with double the odds of LRI compared to when wood is not used for cooking or heating. It must be noted that all risk factors associated with paraffin had wide Cis, thus are not reliable. Having had some existing illnesses and conditions (anaemia, epilepsy and heartburn) were also associated with higher odds of having LRI. However, the confidence intervals for all of these were wide, indicating that the results are not reliable. Sanitation/hygiene was once again (as in previous unpublished studies) associated with higher odds (two to three times higher) of having lower respiratory illnesses. Spending more than 17 hours per day indoors was protective against URI (OR 0.51) but was a risk factor for LRI (OR 1.79). The reason for this is not clear. It can be speculated that those who spent the most time indoors are very young children (probably below 2 years of age) and old people as well as those who are ill. These individuals are all susceptible to diseases and thus the risk that indicated those who spent more than 17 hours indoors per day had a 1.7 higher odds of having LRI. It can also be speculated that those individuals were exposed to indoor pollution for longer time periods and keeping in mind that most households in the area use domestic fuel and there were smokers, that the indoor air was polluted. However, this does not explain why the same factor was protective against URI. Another risk factor that is difficult to explain is the three times higher odds of having LRI when the household is using small bags for coal. However, the most logical explanation is that it is just an indication of coal use as it was found most households using coal did in fact buy the small bags. Multivariate analysis The final risk factors maintained during multivariate analysis showed that the odds of having URI was double when wood was used as one of the energy carriers for heating compared to when wood was not used Factors identified as protective against URI, namely a 70% lower odds (OR 0.29) of having URI when waste was removed at least once a month over a period of 90 days and never failed to do so. REPORT NO:NWU/2015/Eskom01 92

124 The final risk factors maintained for LRI showed the odds of having LRI was almost four times higher if water supply was interrupted for more than five days over a period of 90 days and the odds was almost three times higher when a small container (bag) was used for coal (as mentioned, an indication of coal use). Factors about 75% to 80% protective against LRI were never or very rarely failing to remove waste over a period of three months. 6.2 Quality of Life Quality of Life status 2014 per indicator Demographics There are no significant differences between study communities regarding the reported number of persons per household with a mean of 4.1 members per household in all surveyed communities; the highest number of 4.6 household members was reported in Maphela and the lowest number of 3.59 in Emaskopasini (Table 6-10). The mean of 4.1 persons per household is slightly higher than the Census 2011 figure of 3.48 persons per household for Kwazamokuhle SP. There might be a possibility of an undercount of single member households in the GHS Definition The mean and median number of members 4 per household 5. Rationale Persons per household are a widely used demographic indicator that relates to population density, dependency ratio and economic development. This indicator can be used in combination with other indicators to calculate a number of important statistics, for example total population, dependency ratio, square metre per household member, per capita income, etc. Credibility The number of persons per household is validated by also recording the name, age, sex and other particulars for each household member 6. Calculation The sum of persons per household is determined for a single household by adding the individual members per household. The mean number of persons per household is calculated as the sum of household members divided by the number 3 This survey is referred to as the General Household Survey (GHS) Apply Census 2011 definition for household member: A person that resides with a household for at least four nights a week. Note that domestic workers are excluded unless they are paid in kind. 5 Apply Census 2011 definition of household: A household is a group of persons who live together and provide themselves jointly with food or other essentials for living, or a single person who lives alone. Note that a household is not necessarily the same as a family. 6 Note that the number of persons per household is also recorded by STATSSA in the National Census. REPORT NO:NWU/2015/Eskom01 93

125 of households. The median number of persons per household is calculated by placing the number of household members for every household interviewed in value order and identifying the middle number 7 as median. Table Number of persons per household. INDICATOR DESCRIPTION All MEAN 4.1 MEDIAN 4 (95% CI) (3.94, 4.27) (NA, NA) KwaSP (95% CI) (3.9, 4.36) (NA, NA) Emas (95% CI) (3.22, 3.97) (NA, NA) Maph (95% CI) (3.83, 5.36) (NA, NA) Tyco (95% CI) (3.78, 4.61) (NA, NA) Manf (95% CI) (3.64, 4.76) (NA, NA) Number of households per stand The median number of households per stand is one (Table 6-11). The mean number of households per stand is highest in Maphela at It is notable that Maphela was also the community with the highest number of persons per household (compare A.1.) In densely populated areas the negative effects of service delivery failure can be amplified because more people are exposed to, for example, uncollected waste. However, it does not seem from the service and infrastructure indicators that Maphela are notably worse off than any of the other communities. Definition The mean and median number of households per stand 8. Rationale Households per stand relates particularly to population density. Information on the population density is important for various reasons including the planning and delivery of infrastructure as well as the rendering of various services such as education, safety and security, health and recreation. This indicator can be used in combination with other indicators to calculate the population of the study area. Credibility Do triangulation to determine if household members on same stand but from different households answer this question the same. Calculation The number of households per stand is calculated by adding the households on a stand. The mean number of households per stand is calculated as the sum of households divided by the number of stands. The median number of households 7 In case where the total number of households amounts to an even number, the middle pair of numbers is identified and divided by two to determine the median. 8 A stand is considered to also be an erf as defined by Census 2011: The site, stand, yard, or plot described by cadastre on a map; physically, it may be defined by any material marking the perimeter of the property, e.g. fence, hedge, brick wall, etc. The cadastre can, however, be an imaginary lineand therefore may not be physically observable. REPORT NO:NWU/2015/Eskom01 94

126 per stand is calculated by placing the number of households for every stand in value order and identifying the middle number as median. Table Number of households per stand INDICATOR (95% (95% (95% (95% (95% All KwaSP Emas Maph Tyco Manf DESCRIPTION CI) CI) CI) CI) CI) (1.05, (1.05, (1.01, (0.92, (0.99, MEAN ) 1.17) 1.15) 1.61) 1.08) MEDIAN (95% CI) (0.98, 1.05) Age of persons in the study communities The median and average ages of people in Manfred (median 26; average 28.47) and Tycoon (median 25.5; average 29.98) are slightly higher than the average age of persons in the other communities. Definition The interval of time between the day, month and year of birth and the day and year of occurrence of the event expressed in the largest completed unit of solar time such as years for adults and children and months for infants under one year of age 9. Rationale Age is a widely used demographic indicator that can be used in combination with other indicators to calculate statistics such as health conditions per age group, education per age group and employment per age group, etc. Credibility This indicator is applicable to all persons. The indicator is validated by also asking the date of birth per person 10. Where age in years and birth dates are inconsistent, date of birth is accepted. Calculation The age of an individual is calculated as the sum of his or her completed life years from date of birth. Mean age is calculated as the sum of life years divided by the number of people. The median age for a sample population is calculated by placing the age of every person in value order and identifying the middle number as median. The working age percentage for a sample population is calculated by the sum of the number of people from the ages of 15 to 64 divided by the total number of people multiplied by Similar to definition of STATSSA 2011, except in case of infants, where STATSSA allows for months, weeks, days, hours or minutes of life, as appropriate, for infants under one year of age. 10 Some people find it easier to remember the date of birth than to calculate their age and, in some instances, it helps to eliminate the problem of people rounding off their age to the nearest five or ten years. REPORT NO:NWU/2015/Eskom01 95

127 Table Age of the population in the areas studied. INDICATOR DESCRIPTION All MEAN (95% CI) (26.13, 27.51) KwaSP (95% CI) (24.58, 26.37) Emas (95% CI) (25.79, 29.63) Maph (95% CI) (23.69, 28.96) Tyco (95% CI) (28.09, 31.88) MEDIAN % working age (15-64) (63.99, 67.47) (61.74, 66.46) (67.4, 77.04) (57.8, 71.16) (62.78, 71.28) Manf (95% CI) (26.19, 30.74) (59.56, 70.7) Sex of persons in the study communities A number of health related behaviors and conditions can be linked to the sex of persons in the study communities: More men smoke than women (32% vs 4%) and more men are also exposed to passive smoke (21% vs 8%). More men have never seen a doctor (45% vs 35%). Women are more likely to have been diagnosed with diabetes but differences are small in absolute terms (5% women vs. 1% men). Women are more likely to have experienced ulcers in the 12 months before the interview, but absolute differences are small (4% women vs. 2% men). Results summarized in Table For other conditions and symptoms such as: high blood pressure, any kind of symptom in the past 12 months, painful and stiff joint, heartburn or stomach burn, severe and long lasting headaches, general morbidity in the 30 days before the interview there is no difference between the sexes. Definition The biological distinction between males and females 11. Rationale Sex is a widely used demographic indicator that can be used in combination with other indicators to calculate statistics where sex is of importance, for example assessing the relation between sex and various health conditions, patterns of crime, safety and vulnerability, sex in the workplace, etc. Credibility The sex of each household member is specifically asked and not assumed. Calculation The percentage of women is calculated by the sum of the women in the sample divided by the total number of persons in the sample multiplied by Sex is a biological category and therefore a person is classified as either male or female solely on biological characteristics regardless of gender preferences REPORT NO:NWU/2015/Eskom01 96

128 Table Sex of persons in the study communities. INDICATOR DESCRIPTION All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (95% CI) Tyco (95% CI) Manf (95% CI) % female (51.71, 55.38) (51.74, 56.65) (46.88, 57.65) (48.91, 62.78) (51.69, 60.66) (39.37, 51.01) Orphans in the study communities The total number of maternal orphans (8.01%) is higher in the study area than the national (5.81%) and provincial figures for Mpumalanga (6.39%) as reported by the 2011 Census (Table 6-14). The lowest number of orphans was reported in Maphela (3.08%) and the highest number in Manfred (12.94%)(Table 6-15). The survey results indicate that large numbers of children in the sample area are vulnerable as a result of poverty, regardless if they are orphans or not. The vulnerability of children can best be understood looking at multiple standard of living indicators and it is concluded that high vulnerability exists in the study communities and is a matter of concern. A high number of 5.88% of households in Manfred were reported to be double orphaned households. The double orphan figures of 3.94% in Tycoon and 3.88% of in Kwazamokuhle SP are both higher than the 2.91% (SA national) and 3.01% (Mpumalanga) figures as reported by the 2011 Census. Definition A maternal orphan is a child under the age of 16 whose biological mother is no longer alive 12. A double orphan is a child under the age of 16 who has lost 13 both his/her biological mother and father. Rationale The number of orphans is a pointer to the prevalence of vulnerability in children and is linked to other indicators such as mortality in young adults. It is important to determine if the number of orphans in a community increases or decreases over time. Providing a decent quality of life to double orphans places an additional responsibility on society since the parents of these children can no longer contribute in person to their care. It is important to monitor the number of double orphans in order to determine the extent of this additional responsibility. A sudden increase in the number of orphans could be a pointer to calamities or illness befalling a society. 12 Note that this definition does not include children who do not live with their biological mothers even though they are still alive. In many instances where children do not live with their biological mothers they might be vulnerable, although not formally classified as maternal orphans. 13 Has lost means they are no longer alive REPORT NO:NWU/2015/Eskom01 97

129 Credibility Both the questions Is this child s biological mother still alive? and Is the child s biological father still alive? are asked for every child under the age of 16 included in the survey 14. A child is identified as a double orphan where both questions are answered in the negative for the same child. The option exists to answer I don t know. Such respondents are not counted as orphans. Calculation The percentage of maternal orphans is calculated by the sum of children under the age of 16 whose biological mother is no longer alive divided by the total number of children under the age of 16 in the sample multiplied by 100. The percentage of double orphans is calculated by the sum of children under the age of 16 who has lost both his/her biological mother and father divided by the total number of children under the age of 16 multiplied by 100. Table Maternal orphans in the study communities. INDICATOR DESCRIPTION % maternal All 8.01 (95% KwaSP CI) (6.42, 9.96) 7.21 (95% Emas CI) (5.32, 9.7) 7.53 (95% Maph CI) (3.69, 14.73) 3.08 (95% Tyco CI) (0.85, 10.54) (95% Manf CI) (6.68, 17.65) (95% CI) (7.38, 21.7) Table Maternal and paternal orphans in the study communities INDICATOR DESCRIPTION % double All 3.73 (95% KwaSP CI) (2.68, 5.17) 3.88 (95% Emas CI) (2.55, 5.86) 2.15 (95% Maph CI) (0.59, 7.51) 1.54 (95% Tyco CI) (0.08, 8.21) 3.94 (95% Manf CI) (1.69, 8.89) 5.88 (95% CI) (2.54, 13.04) Dominant language in the study communities isizulu is the language most frequently used in the study area (Table 6-16). Maphela has a fairly large isindebele group (28.42%) and therefore the isizulu speaking group are a smaller portion of the total population in this community. The proportion of isizulu speakers in this study is significantly higher for all communities taken together compared to the Census 2011 figures for Kwazamokuhle 15. Definition The language most often spoken by a particular person in his/her household is considered to be his/her dominant language Stepmothers/fathers or mothers/fathers by adoption or aunts/uncles or grandmothers/grandfathers are not biological mothers/fathers and are therefore excluded 15 Note that the Census 2011 question (P-06), which asked from respondents to indicate the two languages spoken most at home per person could be the cause of the difference between the two set of figures. 16 Compare the Census 2011 definition: The language most often used by the individuals at home, whether or not they consider it their mother tongue. REPORT NO:NWU/2015/Eskom01 98

130 Rationale Language is a widely used demographic indicator that reflects something of the culture and identify of people. Knowing the dominant language of a particular area is important for communication. Language relates to many aspects of quality of life for example the quality of education. Credibility The question Which language does this person speak most often in this household is asked for every person in the study. Calculation The percentage of speakers per language is determined by the sum of people speaking the language divided by the total number of people multiplied with 100. Table Dominant language in the study communities. INDICATOR DESCRIPTION All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (95% CI) Tyco (95% CI) Manf (95% CI) % main language isizulu (73.67, 76.92) (76.27, 80.43) 73.5 (68.38, 78.06) (50.68, 64.84) (71.11, 79.13) (66.39, 77.13) 6.3 Health and wellbeing Satisfaction life-as-whole (scale 0-10) The satisfaction with life-as-a-whole in Manfred is reported to be significantly lower than in the other study communities (Table 6-17). When compared with statistics from the Gallup World Poll 18 it seems that the Manfred scores (below 5) are closer to average South African scores and that the satisfaction scores in the other communities are above average for South Africa 19. Definition Satisfaction with life-as-a-whole (scale 0-10) is a well-being indicator that assesses how a person perceives his or her own satisfaction with life-as-a-whole, all things taken into consideration, by rating it on an 11 point numeric scale where 0 means complete dissatisfaction and 10 means complete satisfaction. 17 In this category three indicators measured perception with an 11 point numerical scale: B1, B2 and B12. Perception indicators always have to be taken with caution because of the complexities involved in the assessment of perceptions. Many factors can influence results including cultural and lingual factors but also household or fieldworker bias. In this particular study, there might be a possible data quality issue pertaining to fieldworker bias confined to the indicators that apply the 11 point numerical scales. 18 Website: 19 These types of comparisons should be done with caution since there are nuance differences not only in the way in which questions are asked but also in the way in which surveys are conducted. REPORT NO:NWU/2015/Eskom01 99

131 Rationale Both life circumstances and perceived well-being are important in order to assess the quality of life of households. In recent years, there has been a growing debate about the question to what extent purely consumption-based GDP alone can measure progress. A growing number of researchers and policy makers believe that measuring progress should include a combination of GDP and measures of sustainable development, the environment and quality of life. Perceived wellbeing is an important component of quality of life 20. It is valuable in larger samples to relate various indicators to life-as-a-whole satisfaction in order to determine which indicators are most strongly related to satisfaction with life-as-a-whole. Credibility This indicator is used by several surveys world-wide e.g. World Values Survey. Fieldworkers are trained to apply the method based on the Cantril Self-Anchoring Striving Scale to explain the numeric scale to respondents if necessary 21. Respondents are asked to imagine an eleven-rung ladder where the bottom represents complete dissatisfaction and the top 10 represents complete satisfaction with life-as-a-whole. The question is then asked: On which step of the ladder do you feel you personally stand at the present time? Note that this question is only answered by the respondent and not by all household members included in the survey. Table Satisfaction life-as-whole (scale 0-10) for the study communities. INDICATOR DESCRIPTION MEAN All 5.94 (95% KwaSP CI) (5.8, 6.08) 5.91 (95% Emas CI) (5.74, 6.08) 6.17 (95% Maph CI) (5.73, 6.61) 6.1 (95% Tyco CI) (5.51, 6.68) 6.34 (95% Manf CI) (6.01, 6.67) 4.71 (95% CI) (4.05, 5.37) Satisfaction work (scale 0-10) in the study communities. There are no significant differences between the reported work satisfactions in the surveyed communities (Table 6-18). The results on the domain work should be interpreted with caution since both a broad definition of work (tasks in and around the household), as well as a narrow definition (formal work for an income) are included in the study. Definition Satisfaction with work (scale 0-10) is a well-being indicator that assesses how a person perceives his or her work by rating it on an 11 point numeric scale where 0 means complete dissatisfaction and 10 means complete satisfaction. Note that 20 Compare: OECD (2009), Society at a Glance 2009: OECD Social Indicators, Brussels 21 Also used by the Gallup World Poll but with a slight nuance difference: the Gallup questionnaire asks about the worst possible life for you and the best possible life for you REPORT NO:NWU/2015/Eskom01 100

132 work in this definition includes tasks performed without receiving payment thus, a broader definition than employment 22. Rationale Work is one of the core daily activities that persons of working age do or should be able to do daily. The ability to work is related to other standard of living aspects such as earning an income. Work satisfaction can be related and can influence satisfaction with life-as-a-whole. Credibility The fact that a broad definition of work is used means that linking this answer to satisfaction with employment should be done with caution. When interviews are done mainly during working hours on weekdays this has to be taken into consideration as a possible research bias. During working hours it can be expected that people who are full-time employed will mostly not be at home. Calculation The mean satisfaction with work score for a population is calculated by the sum of the respondent scores divided by the number of respondents. Table Satisfaction work (scale 0-10) in the study communities. INDICATOR DESCRIPTION MEAN All 6.39 (95% KwaSP CI) (6.27, 6.51) 6.17 (95% Emas CI) (6.01, 6.32) 6.79 (95% (95% Maph CI) CI) Tyco (6.52, 7.06) 6.43 (6, 6.86) 6.82 (95% Manf CI) (6.52, 7.12) 6.48 (95% CI) (5.98, 6.98) Employment in the study communities Kwazamokuhle SP (16.96%) has the least and Maphele (29.6%) the highest number of full time employed persons of all communities surveyed. Interestingly Maphele also has the most unemployed persons looking for work (36.8%) and the most persons that will accept a job (39.2%) (). The proportion of the unemployed who are not actively looking but will accept a job can serve as an indicator of the number of people who have given up hope of finding a job. The national (40.00%) and provincial (42.00%) proportions of such people are higher than in the study areas (34.17%), meaning that there are still slightly more people in the study communities that still do have the hope to find employment. Definition An employed person (full time or part time) is someone of working age (15-64) who is working for pay, profit or family gain and has some form of paid work to return to 23. An unemployed person is someone who is not employed. 22 Compare Census 2011 definition of employment: work for pay, profit or family gain for at least one hour in the seven days prior to the interview or who were absent from work during these seven days, but did have some form of paid work to return to. REPORT NO:NWU/2015/Eskom01 101

133 Rationale Employment status is an indicator that relates to numerous aspects important in the measurement of the quality of life of individuals and societies. This indicator can be used in combination with other indicators to calculate several statistics important to policy and decision. Credibility In the GHS-2013 the worked for at least one hour in the last seven days criterion is not included in the question itself as is the case with Census The question What does this person do? is asked and a list of options are provided to the respondent. The assumption is that people generally do have an accurate perception of their working status and that it is not necessary to provide a definition in the question for an accurate result. However, the extent of the possible deviation because of the difference in phrasing of this question in GHS-2013 and Census 2011 has not been quantified. Calculation The proportion of persons of the working age (15-64) employed full-time is calculated by the sum of full-time employed persons of working age divided by the total number of persons of working age multiplied by 100. Table Employment in the study communities. INDICATOR DESCRIPTION All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (95% CI) Tyco (95% CI) Manf (95% CI) % full time (19.13, (14.78, (22.53, (22.3, (16.35, (22.63, employed WP ) ) ) ) ) ) % part time employed WP % unemployed, looking WP % unemployed, will accept WP (11.55, 14.59) (23.17, 27.09) (31.04, 37.57) (10.63, 14.7) (24.47, 29.94) (33.55, 42.85) (10.45, 19.38) 5.6 (12.28, 21.7) 36.8 (16.48, 32.38) 39.2 (2.74, 11.11) (28.86, 45.53) (29.68, 52.35) (12.05, 20.09) (18.39, 27.64) (21.81, 36.16) (10, 20.22) (15.7, 27.5) (24.77, 46.47) Total income of household (all sources) in study communities Maphela has the highest mean household income of R3160 per month and Kwazamokuhle SP the lowest of R1557 per month (Table 6-20). Not even calculating inflation, this is much lower than the mean national household income of R and provincial household income of R as reported by Census This means that the average household in Kwazmokuhle has to survive on R51.19 per day. Taking the average number of persons per household into calculation it means the per capita income in Kwazamokuhle SP is R377 per person 23 Derived from Census 2011 definition. Note further that Census 2011 considers commercial farms as businesses, but small family farms or small areas in the yard/plot cultivated for household food not to be businesses. Other examples of businesses include spaza shops, renting rooms, fetching water/firewood for sale, stalls by roadside selling items such as sweets, chips, etc. REPORT NO:NWU/2015/Eskom01 102

134 per month or R12.39 per person per day. Relative to other communities Manfred has a relative low total income in spite of the fact that the full and part time employment (compare B3) is fairly high in comparison to the other communities. Definition Total monthly household income is the sum of all financial receipts per month of a household. The GHS differs from the census in so far as the census includes payments in kind as well 24. In the GHS-2013 this includes all financial receipts by all members of a household in exchange for employment, or in return for capital investment, or receipts obtained from other sources for example government grants. Rationale Household income is an indicator that relates to numerous aspects important in the measurement of the quality of life of individuals and societies. This indicator can be used in combination with other indicators to calculate several statistics important to policy and decision makers such as the economic ability of an area or the per capita income. A low per capita income could be a strong indicator of vulnerability. Credibility Disclosing income can be a sensitive issue. In the GHS-2013 respondents were given the option not to disclose the income of their family. More than 85% of respondents revealed their household income. It is difficult to verify the accuracy of disclosed information per household 25. Calculation The mean household income per month is calculated as the sum of monthly household incomes divided by the number of households. The median monthly household income is calculated by placing the monthly incomes per household in value order and identifying the middle number as median. Table Total income of household (all sources) in study communities. INDICATOR DESCRIPTION MEAN monthly 1965 MEDIAN monthly All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (95% CI) Tyco (95% CI) Manf (95% CI) ( , ) 1557 ( , ) 2459 ( , ) 3160 ( , ) 2715 ( , ) 1631 ( , ) (NA, NA) 2000 (NA, NA) 1500 (NA, NA) 1400 (NA, NA) 24 Compare Census 2011: All receipts by all members of a household, in cash and in kind, in exchange for employment, or in return for capital 25 In the study a number of households reported their total monthly income as R0 per month. This result was validated by comparison to sources of income and inconsistent results were discarded. REPORT NO:NWU/2015/Eskom01 103

135 6.3.5 Lower bound poverty line of the study communities The dire situation in the surveyed communities should be evident taken into consideration that around than 90% of households in Kwazamokuhle SP and Manfred, more than 70% in Tycoon and Emaskopasini and Maphela live below the Lower Bound Poverty Line (). Table Lower bound poverty line of the study communities Error! Not a valid link.a point estimate together with the 95% confidence interval of the number of persons falling in each of the poverty categories are shown in Table This gives an indication of the scale of poverty in Kwazamokuhle. In 2012, Statistics South Africa published a set of three national poverty lines the food poverty line (FPL), lower-bound poverty line (LBPL) and upper-bound poverty line (UBPL) to be used for poverty measurement in the country. The FPL is the level of consumption below which individuals are unable to purchase sufficient food to provide them with an adequate diet. Those below this line are either consuming insufficient calories for their nourishment, or must change their consumption patterns from those preferred by low income households. The LBPL includes nonfood items, but requires that individuals sacrifice food in order to obtain these, while individuals at the UBPL can purchase both adequate food and non-food items. The Rand value of each line is updated annually using CPI price data. The poverty gap is used as an indicator to measure the depth of poverty. The gap measures the average distance of the population from the poverty line and is expressed as a percentage of the poverty 26. The National Planning Commission (NPC) adopted the use of the lower-bound poverty line (R443 in 2011 prices) with regard to its poverty targets outlined in the NDP. They have set the ambitious target of eliminating all poverty below this line by As of 2011, 32,3% of the population or roughly 16,3 million people were living below this poverty line. According to the poverty gap, roughly R31,7 billion per annum would be needed to eliminate poverty at this level 27. South Africa's social assistance system has expanded tremendously since 2000, growing from around 3 million grants to 15 million by Growth in grants has been primarily driven by the expansion of child support grants which increased from roughly recipients in 2000 to over 10 million in The coverage of this grant has successively been extended to children in older years, reaching those between the ages of 15 and 16 in 2010 and thus increasing its ability and reach to improve the lives of those living below the poverty line 28. In our opinion these high levels of dependency make low income households vulnerable to adverse economic conditions which pose a risk that has to be assessed and managed also by industry. 26 Poverty Trends in South Africa, An examination of absolute poverty between 2006 and Statistics South Africa, Report No ; Web reference: p Ibid., p Ibid., p. 20. REPORT NO:NWU/2015/Eskom01 104

136 Definition 29 A poverty line is a line drawn at a particular level of income or consumption; households/individuals whose incomes fall below a given level of the poverty line or whose consumption level is valued at less than the value of the poverty line are classified as poor. The LBPL includes non-food items, but requires that individuals sacrifice food in order to obtain these, while individuals at the UBPL can purchase both adequate food and non-food items. The Rand value of each line is updated annually using CPI prices data. In this study the LBPL for October 2014 is calculated at R Rationale The National Planning Commission (NPC) adopted the use of the lower-bound poverty line (originally calculated at R443 for 2011 prices) with regard to its poverty targets outlined in the NDP. They have set the ambitious target of eliminating all poverty below this line by Credibility Disclosing income can be a sensitive issue. In the GHS-2013 respondents were given the option not to disclose the income of their family. More than 85% of respondents revealed their household income. It is difficult to verify the accuracy of disclosed information per household. Calculation % persons less than R per capita income per month is calculated as the number of persons having a capital income of less than R divided by total number of persons multiplied by 100. Per capita income per month is calculated as the total income of household per month divided by the number of household members. R is calculated as follows: i. Recalculated 2011 LBPL value = R517 for Mpumalanga (Reference: Methodological report on rebasing of national poverty lines and development of pilot provincial poverty line, Technical Report, No , Statistics South Africa, by Pali Lehohla, Statistics General, ii. Original 2011 LBPL value = R443 (2011) (Reference: Poverty Trends in South Africa, Statistics South Africa, 2012) iii. LBPL 2014 = R544 (Reference: Statistics South Africa, 2014) 29 Compare Poverty Trends in South Africa: In 2012, Statistics South Africa published a set of three national poverty lines the food poverty line (FPL), lower-bound poverty line (LBPL) and upper-bound poverty line (UBPL) to be used for poverty measurement in the country. The FPL is the level of consumption below which individuals are unable to purchase sufficient food to provide them with an adequate diet. Those below this line are either consuming insufficient calories for their nourishment, or must change their consumption patterns from those preferred by low income households. REPORT NO:NWU/2015/Eskom01 105

137 Following i, ii and iii: R517/R443*R544 = R Table Number of persons in each poverty category in KwaZamokuhle. Place poverty.income.cat PointEst Lower Upper Emaskopasini Food poverty One twentyfive $ Lower bound poverty line Upper bound poverty line Minimum wage/ Kwazamokuhle SP Food poverty One twentyfive $ Lower bound poverty line Upper bound poverty line Minimum wage/ Manfred Food poverty One twentyfive $ Lower bound poverty line Upper bound poverty line Minimum wage/ Maphela Food poverty One twentyfive $ Lower bound poverty line Upper bound poverty line Minimum wage/ Tycoon Food poverty One twentyfive $ Lower bound poverty line Upper bound poverty line Minimum wage/ Perceived good health of household in the study communities Interestingly perceived good health is the highest in the two communities with the highest number of persons living below the LBPL namely Kwazamokuhle SP (74.9%) and Tycoon (76.58%) (). This phenomenon, namely, that people from low-income areas can score high on health satisfaction is known in literature. Compare for example the observation of Deaton: countries with high rates of HIV prevalence do not systematically report poorer health satisfaction, a finding that is in line with earlier reports that selfreported health measures are often better in places where people are sicker, and presumably more used to being sick (Sen, 2002; Murray & Chen, 1992) Deaton, A. 2008: Income, Health, and Well-Being Around the World: Evidence From the Gallup World Poll, Journal of Economic Perspectives Volume 22, Number 2 Spring 2008 ( REPORT NO:NWU/2015/Eskom01 106

138 The satisfaction in Manfred and Maphela is reportedly significantly lower than in the other communities surveyed. However, there might be a possible data quality issue pertaining to fieldworker bias and we therefore recommend that the above result be interpreted with caution. Definition Percentage of respondents that perceive the health of their household to be good. Rationale The way in which people perceive their health is important since it generally has an impact on health seeking behaviour. Getting timely treatment can drastically improve particular treatment outcomes. Credibility There is an association between perception of health of the household and reported symptoms perceived of household members. Calculation The sum of respondents that perceives the health of their household to be good divided by the total number of respondents times 100. Table Perceived good health of household in the study communities. INDICATOR DESCRIPTION All % positive (95% CI) (72.28, 78.66) KwaSP (95% CI) (70.36, 79.01) Emas (95% CI) (42.59, 62.68) Maph (95% CI) (33.36, 62.28) Tyco (95% CI) (67.89, 83.48) Manf (95% CI) (34.02, 57.38) Immunisation (children under 15) in study communities. Almost all children are reported to having been immunised, except in Manfred with only 94.12% of children. In the whole of South Africa an estimated children are not fully immunised each year 31. Definition Proportion of children under 15 who have received childhood vaccination as prescribed by the SA Government against diseases such as measles, diarrhoea, pneumonia, meningitis and other life threatening conditions. Rationale Childhood immunisation is essential to the prevention of diseases that cause death and disability. 15% of deaths in children under five years of age are due to diarrhoea and 9% are due to pneumonia, both to a certain extent vaccine 31 REPORT NO:NWU/2015/Eskom01 107

139 preventable diseases of childhood. Immunisation is one of the most successful and cost-effective public health interventions. Increasing access of children and mothers in deprived districts to high impact immunisation services is crucial if maternal and child mortality trends in South Africa are to be reversed. 32 Credibility The question is asked if a particular child has ever been immunized against polio, measles, etc. The question does not ask if a child has undergone a complete immunisation programme. Thus, the indicator might include children that are only partially immunized. It might further happen that a particular respondent is not certain if a child has ever been immunised. In such an instance respondents are encouraged to find out from other household members where possible. Calculation The sum of children under 15 that have been immunised divided by the total number of children under 15 times 100. Table Immunisation (children under 15) in study communities. INDICATOR DESCRIPTION % immunised All (95% CI) KwaSP (98.42, 99.63) (95% CI) (98.66, 99.9) Emas 100 (95% CI) (96.03, 100) Maph 100 (95% CI) (94.42, 100) Tyco 100 (95% CI) (97.06, 100) Manf (95% CI) (86.96, 97.46) Never been to a medical professional A very high 52.35% of persons in Manfred have never been to a medical professional. In Kwazamokuhle SP the figure is also high at 41.68%. Of the communities surveyed the community who seems to have the greatest access to medical services is Maphela where only 24.35% of persons have never been to a medical professional (Table 6-25). South Africa comprises almost 17% of the world s population living with HIV/AIDS. The country has the largest antiretroviral treatment programme in the world, yet only 40% of eligible adults are receiving treatment. 33 It is assumed that if 52.35% of people in Manfred and 41.68% in Kwazamokuhle have not been examined by a doctor or nurse, there also must be a significant number of people living with HIV/AIDS that are still not receiving proper medical care. These percentages point to some discrepancies between people s perceived well-being and the situation as deducted from other indicators such as reported HIV/AIDS prevalence rates. More men have never seen a doctor than women (45% men vs. 35% women) 32 Statement by Aida Girma from Unicef: 33 S. Benatar The challenges of health disparities in South Africa. Editorial, in SAMJ Vol 103, No 3. REPORT NO:NWU/2015/Eskom01 108

140 Definition If a person has never been examined by a medical doctor or professional nursing sister he/she is considered to have never been to a medical professional. Rationale Access to professional medical care is an important indicator for quality of life. Being able to access medical care could in many instances make a significant difference in the outcome of a particular illness or condition. In extreme cases lack of care could result in premature death. Credibility The question is asked: When last has this household member been examined by a doctor or nursing sister? Respondents has the option to choose between last 30 days, last year, more than a year ago, never been examined by doctor or nursing sister. It might happen that a particular respondent is not certain if a household member has ever been examined by a doctor or nursing sister. In such an instance respondents are encouraged to inquire from other household members where possible. It is not expected that this will cause a significant bias. Calculation The sum of persons never been examined by a doctor or nursing sister divided by the total number of persons times 100. Table Never been to a medical professional. INDICATOR DESCRIPTION % of population All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (95% CI) Tyco (95% CI) Manf (95% CI) 40.4 (38.61, 42.22) (39.28, 44.13) (30.19, 40.49) (18.84, 30.87) (34.94, 43.77) (46.47, 58.16) Symptoms in last 12 months (self-reported) 34 It is interesting that the least health complaints were received in the town in Manfred where 95.67% of households report no complaints, taking into consideration that Manfred is the town with the second lowest per capita income (). The following can be deducted from the results in terms of the relationship between sex and health conditions: Fewer men have ever been diagnosed with arthritis, but the difference is not large (0.06% men vs. 0.24% women) No difference between sexes w.r.t high blood pressure No difference between sexes w.r.t high depression 34 The Maphele results had to be discarded because of a data quality issue. REPORT NO:NWU/2015/Eskom01 109

141 Women are more likely to have been diagnosed with diabetes but differences are small in absolute terms (5% women vs. 1% men) No differences between sexes w.r.t. any kind of symptom in the past 12 months No differences between sexes w.r.t. painful and stiff joints Women are more likely to have experienced ulcers in the 12 months before the interview, but absolute differences are small (4% women vs. 2% men) No difference in the sexes w.r.t. heartburn or stomach burn No difference in the sexes w.r.t. severe and long lasting headaches No difference in the sexes w.r.t. general morbidity in the 30 days before the interview Definition A symptom is an observable change in the body or mind which could be a sign of a disease or bodily disorder 35. Certain symptoms can be perceived and described by the subject that experiences these symptoms or it can be observed by another person such as a fellow household member or a medical professional. Selfreported-symptoms here means a respondent reporting on his/her own symptoms of disease and/or the symptoms of disease of his/her household members without professional medical consultation at the time of the interview. The period specified for these self-reported-symptoms is 12 calendar months, meaning that only the symptoms experienced in the specified time period are reported. No-complains means that not one of the items on the list of common health problems is experienced. Bronchitis-like symptoms mean that the person is reported to have experienced coughing sputum but no weight loss or fever or night sweats. Asthma-like symptoms means that the person is reported to have experienced wheezing and a tight chest at night or after exercise. Diarrhoea means that the person is reported to have experienced three or more loose stools per day for longer than a day. Rationale Gathering information on specific symptoms prevalent in a particular community over time is important to better understand the factors that influence the health of a community. A sudden upsurge or a high level of particular symptoms in a particular area could be an indicator of a health risk in a community e.g. where contaminated water results in an increased number of diarrhoea cases or where people close to an emitting industry have significantly more symptoms of the respiratory system than people living further away from the emitting source. Credibility The respondent is only required to report on symptoms experienced by members of the household and not to make a diagnosis. The symptom descriptions were formulated in consultation with an experienced medical professional. Both 35 Compare REPORT NO:NWU/2015/Eskom01 110

142 diagnostic factors and comprehensibility were taken into account. It does appear from the results that there might be slight under-reporting of symptoms in other household members. In other words, respondents tend to be more aware of their own symptoms, than those of other household members. Calculation The percentage of people having a particular symptom (or no complaints) is calculated by the sum of persons having the symptom divided by the total number of persons times 100. Table Symptoms in last 12 months (self-reported). INDICATOR DESCRIPTION % no complaints % bronchitislike symptoms % asthma like symptoms All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph % diarrhoea 2.18 (89.52, 91.66) (1.55, 2.59) (0.04, 0.31) (1.7, 2.78) (89.78, 92.56) (1.12, 2.4) (0.06, 0.56) (1.65, 3.14) (83.09, 90.36) (0.31, 2.66) (95% CI) (74.7, 85.76) (7.23, 16.06) (0, 1.16) (0, 1.95) (2.11, (0.28, 6.3) 3.7) Tyco (95% CI) Manf (89.25, 94.18) (0.73, 3.07) (0, 0.82) (0.59, 2.78) (95% CI) (92.58, 97.5) (0, 1.37) (0, 1.37) (1, 4.64) Restricted activity days working population (sickness & hh care) Restricted activity days are reportedly the highest in Maphela. As is the case in B.9 we suspect a possible data quality issue in the case of this particular result in Maphela and we therefore propose that this particular result (restricted activity days working population in Maphela) be taken with caution. The number of restricted activity days in all communities does not seem to be very high in comparison to claims made by other studies, for example the 2004 Fridge report. 36 Definition The mean days per person over a six month period in which a person of working age (from 15 to 64 years) has been absent from day to day activities (work, homework, schoolwork or studies 37 ) due to sickness 38 and/or caring for other sick household members The FRIDGE report in 2004 estimated through simulations that air pollution caused a total of ca restricted activity days in the urban and industrial areas of South Africa, representing 67.2 days per potentially economically active person (i.e. persons 20 to 65 years of age. The Study to Examine the Potential Socio- Economic Impact of Measures to Reduce Air Pollution From Combustion. Final Report 2004: The study included a number of South African cities (Johannesburg, Ekurhuleni (greater East Rand), Tshwane, Cape Town, Ethekwini (greater Durban), Mpumalanga Highveld and Vaal Triangle), under the heading Health Risk Impacts due to Current Fuel Combustion Practices. 37 When an individual is forced to significantly limit normal activity due to illness or injury it is considered as being absent from day to day activities. 38 Sickness in the above definition includes injury. 39 This definition could be considered as a broad definition of restricted activity days, as opposed to a narrow definition that only focuses on absence from formal work or the work place. REPORT NO:NWU/2015/Eskom01 111

143 Rationale This indicator links functional well-being of the community to productivity. This could be used as an indicator with which the cost-effectiveness of a project to improve the quality of life in the community can be calculated. A broad and narrow definition is possible. In the narrow definition the direct cost to industry can be calculated, but a broad definition comes closer to the actual cost, since healthy people of working age even if they are not formally employed may also be involved in valuable activities at home or in the informal economy. We regard this as a major restricted activity day. For this reason the term absent is used. Credibility Improve question to read absent or unable to perform... Calculation The indicator here is calculated as the sum of work days lost by people of working age (from 15 to 64) divided by the total number of work days in the six months preceding the study multiplied by 100. Table Restricted activity days working population (sickness & hh care) INDICATOR DESCRIPTION MEAN days per working person per six months All 0.48 (95% CI) (0.45, 0.51) KwaSP 0.25 (95% CI) (0.22, 0.28) Emas 0.74 (95% CI) (0.66, 0.84) Maph 2.88 (95% CI) (2.64, 3.14) Tyco 0.3 (95% CI) (0.25, 0.36) Manf 0.09 (95% CI) (0.06, 0.14) Active smoking in study communities There is no significant difference in the number of adult smokers in the surveyed communities. The average percentage of smoking adults for all communities is 16.78% (Table 6-28). The quantitative analysis shows that smoking and the sex of the smoker are associated: Men smoke more than women (32% vs 4%) and it is reported that more men are exposed to passive smoke (21% vs 8%). Definition Active smokers are persons who smoke tobacco products themselves, compared to passive smokers who are persons who do not smoke, but are exposed to the smoke from an active smoker and as a result inhales their smoke involuntarily. Rationale Smoking is generally regarded as having a negative impact on health. Data on the levels of active smoking makes it possible to assess the effects of smoking on health and productivity. In areas where ambient air quality is substandard and could possibly impact on the health of residents this indicator makes it possible to REPORT NO:NWU/2015/Eskom01 112

144 study the health of smokers, passive smokers and non-smokers in order to better understand the impacts of various exposures on health. Credibility It is possible that there may a slight underreporting because some people may hide their smoking. Calculation The indicator is calculated as the sum of active smokers in the adult population (all persons above 18 years) divided by the total adult population multiplied by 100. Table Active smoking in study communities. INDICATOR DESCRIPTION % adults All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (95% CI) Tyco (15.26, 18.42) (13.05, 17.13) (14.11, 23.45) (15.71, 29.12) (95% CI) (15.1, 23.13) Manf (95% CI) (13.56, 23.83) Satisfaction with food (scale 0-10) in the study communities There are no significant differences between the different communities regarding reported satisfaction with food (Table 6-29). Definition Satisfaction with food (scale 0-10) is a well-being indicator that assesses how a person perceives his or her food by rating it on an 11 point numeric scale where 0 means complete dissatisfaction and 10 means complete satisfaction. Rationale Human beings need food as means of survival, but it is also important to consume healthy foods, to have a variety of foods, to have foods that taste good and to sometimes share food in order to achieve and maintain a good quality of life. Perceived satisfaction with food is an indicator of how satisfied people generally are with their food. Credibility Statistical analysis shows that in the study communities this indicator is closely related to the other household domain satisfaction indicators. This indicator is associated with the indicator B1 Satisfaction with life-as-a-whole. Calculation The mean satisfaction with food score for a population is calculated by the sum of the individual scores divided by the number of individuals. Table Satisfaction with food (scale 0-10) in the study communities. REPORT NO:NWU/2015/Eskom01 113

145 INDICATOR DESCRIPTION All MEAN 5.44 (95% CI) (5.31, 5.58) KwaSP 5.14 (95% CI) (4.95, 5.32) Emas 5.6 (95% CI) (5.25, 5.95) Maph 6.24 (95% CI) (5.82, 6.66) Tyco 5.91 (95% CI) (5.6, 6.22) Manf 5.58 (95% CI) (5.13, 6.03) Frequency of fruit and/or vegetable intake in study communities The frequency of daily fruit and vegetable intake is very low in the surveyed communities and only 24.71% of households report that they take in either fruit or vegetables every day (Table 6-30). The situation in Tycoon is statistically significantly better than in the other surveyed communities with 45.32% of households that report they do eat fruit or vegetables every day. Definition This indicator measures the regularity of fruit and/or vegetable 40 consumption per person expressed as intake or lack of intake of fruits and vegetables over the period of a week. Rationale Fruit and vegetables are low energy-dense foods relatively rich in vitamins, minerals and other bioactive compounds as well as being good sources of fibre. It is widely accepted that fruit and vegetables are important components of a healthy diet and that their consumption could help prevent a wide range of diseases. 41 Credibility In the measurement of fruit and vegetable intake both the frequency of intake and the size of the portion consumed per person are relevant in order to make an accurate estimate of the nutritional benefits achieved. Some experts recommend a daily intake of 400g. However, it can be unpractical to gather detailed nutritional information in a general household survey mainly because of time constraints. It takes too long to gather food diaries where respondents report on all foods consumed for a specific period and in some instances even weighing their food. It is also very time consuming to present a structured list of various types of fruits and vegetables to respondents to indicate frequency of consumption. The current indicator was therefore chosen for its practicality in spite of the limitation that detailed analysis of the quality and quantity of fruit and vegetable intake cannot be deduced from this indicator 42. Calculation The sum of persons who eat fruit and vegetables every day divided by the total number of persons multiplied by Note that the definitions of the terms fruits and vegetables can differ and have to be explained to respondents. It is explicitly mentioned in the question posed to respondents that potatoes and sweet-potatoes do not count as vegetables. 41 See Angudo, A Measuring intake of fruit and vegetables. Background paper for the joint FAO/WHO Workshop on fruit and vegetables for health, 1-3 September 2004, Kobe, Japan. World Health Organisation. 42 Keep in mind also that the respondent, with whom the interview is conducted, indicates the fruit & vegetable and protein intake frequency per household member. REPORT NO:NWU/2015/Eskom01 114

146 Table Frequency of fruit and/or vegetable intake in study communities. INDICATOR DESCRIPTION % daily All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (95% CI) Tyco (95% CI) Manf (95% CI) (23.15, 26.35) (19.04, 23.08) (17.81, 26.81) (18.67, 30.77) (40.82, 49.89) (11.23, 19.67) Frequency of protein intake in study communities. Residents of Manfred report significantly less protein intake than the other communities with only 73.72% of households reporting that they take in protein daily (Table 6-31). Definition The indicator measures the regularity of consumption of foods that include proteins (such as eggs, meat, fish, lentils, peas, beans, milk, cheese, peanuts and/or peanut butter) per person expressed as intake or lack of intake of proteins over the period of a week. Rationale Every cell in the human body contains protein. It is a major part of the skin, muscles, organs, and glands. Humans need protein in their diet to help the body repair cells and make new ones. Protein is also important for growth and development during childhood, adolescence, and pregnancy 43. The Institute of Medicine recommends that adults get a minimum of 0.8 grams of protein for every kilogram of body weight per day (or 8 grams of protein for every 20 pounds of body weight). 44 Credibility The current indicator was chosen for its practicality in spite of the limitation that detailed analysis of the quality and quantity of protein intake cannot be deducted from this indicator. 45 Calculation The sum of persons who eat proteins every day divided by the total number of persons multiplied by 100. Table Frequency of protein intake in study communities. 43 Medline Plus: 44 Compare: Institute of Medicine, Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids (Macronutrients). 2005, National Academies Press: Washington, DC, and also 45 Please compare the motivation for the credibility of indicator B13: Fruit and vegetable intake. REPORT NO:NWU/2015/Eskom01 115

147 INDICATOR DESCRIPTION % daily All (95% CI) KwaSP (88.18, 90.46) (95% CI) (86.7, 89.88) Emas (95% CI) Maph (95% CI) Tyco (95% CI) Manf (95% CI) (95.19, 98.74) (97.08, 99.97) (89.33, 94.28) (68.21, 78.58) 6.4 Services and infrastructure Satisfaction with water (scale 0-10) in study communities There is no significant difference in the reported satisfaction with water between the surveyed communities (). Definition Satisfaction with water (scale 0-10) is a well-being indicator that assesses how a person perceives his or her water by rating it on an 11 point numeric scale where 0 means complete dissatisfaction and 10 means complete satisfaction. Rationale Human beings need clean, safe water to drink as prerequisite to survive. But there are more aspects related to water that influences satisfaction with this element such as finding the taste of water likable, having affordable water, having warm water to bath in or cold water to drink. Perceived satisfaction with water is an indicator of people s overall general satisfaction with the water they have. Credibility Statistical analysis shows that in the study communities this indicator is strongly related to the other household domain satisfaction indicators. Calculation The mean satisfaction with water score for a population is calculated by the sum of the individual scores divided by the number of individuals. Table Satisfaction with water (scale 0-10) in study communities. 46 In this category four indicators measured perception with an 11 point numerical scale: C1, C4, C9 and C13. Perception indicators always have to be taken with caution because of the complexities involved in the assessment of perceptions. Many factors can influence results including cultural and lingual factors but also household or fieldworker bias. In this particular study, there might be a possible data quality issue pertaining to fieldworker bias confined to the indicators that apply the 11 point numerical scales. REPORT NO:NWU/2015/Eskom01 116

148 INDICATOR DESCRIPTION All MEAN 6.06 (95% CI) (5.92, 6.21) KwaSP 5.89 (95% CI) (5.7, 6.08) Emas 6.72 (95% CI) (6.45, 6.98) Maph 5.52 (95% CI) (4.96, 6.08) Tyco 6.88 (95% CI) (6.55, 7.21) Manf 5.32 (95% CI) (4.73, 5.92) Main source of water supply in study communities Only 70.5% of households in Kwazamokuhle have a tap or borehole in the yard and this is significantly lower than the rest of the surveyed communities. A further challenge in terms of service delivery is that only 17.23% of households in Kwazamokuhle have piped water in their houses. In both Emaskopasini (45.05%) and Manfred (28.79%) less than half of the surveyed households have piped water in their homes. Tycoon is the best off in terms of water service delivery where 72.97% of households have piped water in the house and a full 100% of households report that they have a tap or borehole in the yard (Table 6-33) Definitions Main source of water supply refers to the primary or most important source of water supply used for household purposes. 47 Piped water into the house means water that is piped into the house or dwelling itself, whereas tap or borehole in yard refers to access to water on the stand. Rationale Piped water on the stand is usually associated with higher quality access to water as opposed to for example having to obtain water from a communal tap or borehole a distance away. Two categories of piped water onto the stand are differentiated: in the dwelling itself or only on the stand. This distinction makes it possible to monitor over time if shifting of peoples perceptions or expectations occur. Both the quality and the accessibility of water are necessary for a good quality of life: dirty water is associated with a number of diseases and lack of water is associated with unhygienic conditions and poor sanitation. Credibility Respondents are asked what the main source of water supply for the members of the household is. Where Statistics SA distinguishes between access to piped water and source of water supply 48 the current indicator combines the two questions. The only nuance that cannot be picked up by the single question would be in a case where households pipe water from other than municipal sources for example from boreholes into their own dwelling. Comparisons with Statistics SA results do not indicate that this is a significant factor that jeopardises the credibility of the indicator. 47 Similar to the Census 2011 definition the question excludes water used for non-domestic purposes, e.g.. 48 water used for gardens or cattle REPORT NO:NWU/2015/Eskom01 117

149 Calculation The sum of households with piped water into the house, divided by the total number of households, multiplied by 100. The sum of households with a tap or borehole in the yard divided by the total number of households multiplied by 100. Table Main source of water supply in study communities. INDICATOR DESCRIPTION % hh piped water into house % hh tap or borehole in yard All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (95% CI) Tyco (95% CI) Manf (95% CI) (29.78, 36.78) (79.23, 84.92) 70.5 (13.78, 21.34) (65.74, 74.84) 95.6 (35.24, 55.27) (89.24, 98.28) (39.95, 68.78) (84.21, 98.68) 100 (64.05, 80.36) (96.65, 100) (19.27, 40.64) (85.43, 97.62) Water supply unavailable in last 30 days in study communities Service delivery failure is quite high in the reported community where water was unavailable for almost two and a half days in the last 90 days. There is no community where unavailability was reported to be statistically significantly higher than in the other surveyed communities. Definition The number of days in the previous 90 days that water supply was unavailable. Rationale This indicator gives an indication of the reliability of water supply in the recent past namely in the last 90 days. Piped water can only be accessed by residents if the service is available. Credibility This indicator differs somewhat from the water reliability indicator used by Census Census 2011 asks if the household had any interruptions in water supply in the last 12 months and further how many interruptions lasted for more than 2 days. The advantage of taking a longer period is that it could render more information in terms of the longer term stability of supply. The disadvantage is that it might be difficult for a respondent to recall all events over a year long period, particularly in cases where many interruptions occurred. A further disadvantage of the Census 2011 indicator is that if there were 5 interruptions in 12 months each lasting one full day, it will not be picked up by the indicator since only interruptions of 2 days and longer are recorded. Table Water supply unavailable in last 30 days in study communities. REPORT NO:NWU/2015/Eskom01 118

150 INDICATOR DESCRIPTION MEAN days unavailable per hh All 2.46 (95% CI) (2.26, 2.67) KwaSP 2.83 (95% CI) (2.51, 3.14) Emas 1.92 (95% CI) (1.39, 2.45) Maph 2.62 (95% CI) (2.17, 3.06) Tyco 1.65 (95% CI) (1.29, 2.01) Manf 2.38 (95% CI) (1.77, 2.98) Satisfaction getting rid of waste (scale 0-10) in study communities Satisfaction with waste removal is reportedly the lowest in Kwazamokuhle SP and Maphela (). Definition Satisfaction with ability to get rid of waste (scale 0-10) is a well-being indicator that assesses how a person perceives his or her ability to get rid of waste by rating it on an 11 point numeric scale where 0 means complete dissatisfaction and 10 means complete satisfaction. 49 Rationale There is a strong relation between waste removal and quality of life, especially with respect to aspects such as health, dignity, comfort and an attractive environment. Credibility Statistical analysis shows that in the study communities this indicator is associated with access and reliability of waste removal services, as well as to well-being indicators such as satisfaction with life-as-a-whole and other household domain satisfaction indicators. Calculation The mean satisfaction-with-ability-to-get-rid-of-waste score for a population is calculated by the sum of the individual scores divided by the number of individuals. Table Satisfaction getting rid of waste (scale 0-10) in study communities. INDICATOR DESCRIPTION All 5.66 (95% CI) (5.52, 5.79) KwaSP 5.32 (95% CI) (5.13, 5.51) Emas 5.85 (95% CI) (5.59, 6.11) Maph 5.4 (95% CI) (5.11, 5.7) Tyco 6.37 (95% CI) (6.07, 6.67) Manf 6.81 (95% CI) (6.22, 7.39) 49 The question to the respondent explicitly mentions that an overall opinion considering bodily and domestic waste is required REPORT NO:NWU/2015/Eskom01 119

151 6.4.5 Access to piped or flush system in yard in study communities All residents of Maphela and Tycoon have access to a flush toilet system in their yards, but in the other communities there are still a minority of persons who do not have access to such a system. In Kwazamokuhle only 91.83% of households have a piped or flush system in the yard and in Manfred only 93.94% (Table 6-36). The proportion of households with access to flush toilets in all communities is significantly higher than the national (60.11%) and provincial (43.80%) proportions (2011 Census figures). Definition Access to piped or flush system means access to a flush toilet connected to a sewerage system or access to a flush toilet connected to a septic tank. Rationale Accessibility to good sanitation is a fundamental prerequisite for a good quality of life and human dignity. The Water Services Act and Regulations states that everyone has a right of access to basic water supply and basic sanitation. 50 Credibility A similar question is included in Census Fieldworkers are trained to know the difference between various kinds of toilets in order to explain the difference to respondents if necessary. It is suggested that the question for this indicator be changed to: What kind of toilet is mostly used by the member(s) of this household? Calculation The sum of households with piped or flush toilets in the yard divided by the total number of households multiplied by Note also: On 28 July 2010, through Resolution 64/292, the United Nations General Assembly explicitly recognized the human right to water and sanitation and acknowledged that clean drinking water and sanitation are essential to the realisation of all human rights to human dignity. In 2014, the South African Human Rights Commission issued a report on the state of water and sanitation titled: Report on the Right to Access Sufficient Water and Decent Sanitation in South Africa: 2014 Water is Life. Sanitation is Dignity. REPORT NO:NWU/2015/Eskom01 120

152 Table Access to piped or flush system in yard in study communities. INDICATOR DESCRIPTION % households All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (92.72, 96.13) (88.57, 94.21) (92.26, 99.39) 100 (95% CI) (91.62, 100) Tyco 100 (95% CI) (96.65, 100) Manf (95% CI) (85.43, 97.62) Flushing system failure report in study communities The flushing system failure is reported to be slightly higher in Emaskopasini than in the other communities surveyed. It is reported that only 87.64% of flush toilets in Emaskopasini are always working (Table 6-37). Definition When a toilet fails to properly function for example when it fails to flush because it is defunct, blocked or because there is no water it is considered to be a flushing system failure report and it is not considered as a flush toilet that is in working condition. Rationale A toilet that does not flush is for all practical purposes the same, or worse, than having no toilet in your yard. It causes a decrease in quality of life related to health, bad smell and inconvenience. Therefore it is important to not only measure the access to sanitation services but also the proper functioning of these services. Credibility This indicator cannot be compared to Census 2011 since it was not included in the census questionnaire. The question was posed in the present: Is this flushing system working? Thus, it measures the status quo on the date of the questionnaire. It could have also measured failure reports for a particular period for example asking for how many days in the last 12 months or the last 30 days where your toilet not working? It is suggested that the question for this indicator should be: Have your flushing system been out of order or not functioning in the last 90 days? If yes: for how many days in the last 90 days have your flushing system not been working? Calculation The sum of households with a flush toilet who report that the flush mechanism is currently working divided by the total number of households multiplied by 100. Table Flushing system failure report in study communities. INDICATOR DESCRIPTION % flush toilets always working All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (95% CI) Tyco (95% CI) Manf (95% CI) (93.23, 96.58) (92.45, 97.07) (79.21, 92.96) (87.68, 99.88) 98.2 (93.67, 99.5) (91.41, 99.92) REPORT NO:NWU/2015/Eskom01 121

153 6.4.7 Access to waste collection service in study communities In Maphela and Tycoon all households have access to waste collection services. The waste collection service delivery challenge is the largest in Kwazamokuhle SP, where only 69.97% of households have a waste collection service. This is significantly lower than in any other community surveyed. In Manfred only 93.94% of households have a waste collection service (Table 6-38). Definition Waste is collected by a local authority or private company. Rationale There is a strong relation between waste removal and quality of life, especially with respect to aspects such as health, dignity, comfort and an attractive environment. Access to a waste removal service gives an indication of the services that are provided in this respect by government, or when it is not provided, whether any alternative service exists, such as a recycling service that is done by the private sector, either on a profit or a non-profit basis. Credibility The indicator considers a household to have a waste removal service if the respondent reports that the waste of their household is collected. Note there is a slight difference in the formulation used by this indicator and the similar indicator used by Census Calculation The sum of households having their waste collected divided by the total number of households multiplied by 100. Table Access to waste collection service in study communities. INDICATOR DESCRIPTION % once a week collected All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (95% CI) Tyco (95% CI) Manf (95% CI) (79.54, 85.18) (65.2, 74.35) 97.8 (92.34, 99.4) 100 (91.62, 100) 100 (96.65, 100) (85.43, 97.62) Waste collection failure in study communities It seems as if there are reasonable waste removal services in all communities. Only in Kwazamokuhle a very small minority of 0.78% of households report waste collection service delivery failure more than once a month (Table 6-39). Definition This indicator measures the proportion of the sample population that reports the waste collection failure to occur on average more than once a month. REPORT NO:NWU/2015/Eskom01 122

154 Rationale Waste collection failure can be particularly disruptive and cause a decrease in quality of life related to health, bad smell and inconvenience. Therefore it is important to not only measure the access to waste collection services but also the proper functioning of these services. Credibility This indicator assesses the perception of the respondent regarding the frequency of waste collection failure. The question asked is: How often do the people who are supposed to collect your waste fail to do so? and the options are: more than once a month, once a month or less, very rarely, never. The options are posed in such a manner that more than once a month points to regular waste collection failure. Calculation The sum of people who have municipal waste collection services who report collection failure more than once a month divided by the total number of people who have municipal waste collection services, multiplied by 100. Table Waste collection failure in study communities. INDICATOR DESCRIPTION % more than once a month All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (95% CI) Tyco (95% CI) Manf (95% CI) 0.43 (0.15, 1.26) 0.78 (0.27, 2.28) 0 (0, 4.05) 0 (0, 8.38) 0 (0, 3.35) 0 (0, 5.5) Satisfaction with "air you breathe" (scale 0-10) Satisfaction with the air you breathe is reportedly the lowest in Manfred (). Definition Satisfaction with air breathed (scale 0-10) is a well-being indicator that assesses how a person perceives the air he or she breathes by rating it on an 11 point numeric scale where 0 means complete dissatisfaction and 10 means complete satisfaction. Rationale Human beings need clean air to breathe in order to sustainably maintain their good health. Clean air and air pollution are directly linked to several aspects of quality of life, such as health, comfort, and aesthetics. Small children who are with their mothers cooking with dirty fuels can incur serious health effects at a crucial period of their lives. Credibility The question: How satisfied are you these days with the air you breathe? probes the personal experience of the respondent of air and air pollution in his or her living environment. As can be expected the indicator is strongly related to place and satisfaction with terrain, which points to its credibility. REPORT NO:NWU/2015/Eskom01 123

155 Calculation The mean satisfaction score with air breathed for a population is calculated by the sum of the individual satisfaction scores divided by the number of individuals. Table Satisfaction with "air you breathe" (scale 0-10). INDICATOR DESCRIPTION MEAN 5.45 All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (95% CI) Tyco (95% CI) Manf (95% CI) (5.32, 5.57) 5.33 (5.17, 5.5) 5.34 (4.99, 5.69) Dirty energy carrier for cooking in study communities (5.39, 5.99) 6.3 (6, 6.6) 4.35 Many people in all the surveyed communities use dirty energy carriers for cooking with an overall average in all surveyed communities of 67.1% (Table 6-41). The Census 2011 figure for dirty energy carriers for cooking in Kwazamokuhle is much lower at 34.48%. The difference between this study and Census 2011 can be explained by the fact that the Census only asks about the primary energy carrier. Several people use electricity to cook, but during the winter they use coal because it heats up the house and cooks at the same time. Definition An energy carrier used for domestic cooking that contributes to air pollution for example coal, paraffin and biomass (such as dung, charcoal, wood, or crop residues). Rationale This indicator is important to measure the extent to which domestic cooking contributes to ambient and indoor pollution. Cooking with dirty energy carriers could lead to exposure to health-damaging pollutants such as respirable particulates and carbon monoxide and it is therefore important to monitor that indoor air pollution exposures do not exceed national standards and international guidelines. Credibility In order to determine the extent to which dirty energy carriers for cooking are used, it is necessary to ask about all energy carriers used for cooking. Census 2011 only asks: What type of energy/fuel does this household MAINLY use for cooking This leads to gross underreporting of dirty energy carriers, since several households use more than one energy carrier or changes energy carriers per season. Thus, this indicator is in our view more credible than the Census 2011 indicator for determining the extent of dirty fuel use in a community. (3.76, 4.95) 51 For more information on energy usage patterns, please refer to Chapter 9 of this report. REPORT NO:NWU/2015/Eskom01 124

156 Calculation Sum of households using a dirty energy carrier for cooking divided by the total number of households multiplied by 100. Table Dirty energy carrier for cooking in study communities. INDICATOR DESCRIPTION % households cooking All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (95% CI) Tyco (95% CI) Manf (95% CI) 67.1 (63.52, 70.5) (69, 77.79) (46.89, 66.82) (61.47, 86.52) (43.92, 62.17) (48.55, 71.5) Total tons of coal burned at home per annum in study communities The total annual per household in each community that was studied is given in Definition Weight in tons of coal burned for domestic energy purposes per annum. Rationale Where coal is readily available and affordable in comparison to other energy carriers it remains an option as domestic energy source particularly for low-income households. It is important to measure the amount of coal used for domestic purposes in order to monitor and manage the negative effects caused by the increase in ambient and indoor air pollution as a result of this combustion. Credibility This indicator is based on the cumulative result of individual household estimations of the amount of coal used. Respondents are probed on the units in which their household buy coal (e.g. big bag, small bag, tin, large drum, etc.) as well as the price per unit and the number of units used in winter months and summer months 52. From the result the total weight and cost of coal can be calculated. Calculation Sum of kilograms of coal burned by all household divided by Table Total tons of coal burned at home per annum in study communities. INDICATOR DESCRIPTION tons per town per year All (95% CI) KwaSP Total tons of coal burned at homes per annum tons per town per year (95% CI) Emas (95% CI) Maph (95% CI) Tyco (95% CI) Manf (95% CI) 52 May to August are considered to be winter months and September to April are considered to be summer months. REPORT NO:NWU/2015/Eskom01 125

157 Satisfaction with house (scale 0-10) of study communities The house satisfaction scores are quite low in comparison to other household elements (Table 6-43). Looking at the association with other variables and at the relatively low satisfaction scores, improving people s houses could be a possible area of intervention that could also improve the perception of overall quality of life 53. Definition Satisfaction with house 54 (scale 0-10) is a well-being indicator that assesses how a person perceives the house he or she lives in by rating it on an 11 point numeric scale where 0 means complete dissatisfaction and 10 means complete satisfaction. Rationale A house is closely linked to fundamental needs such as protection against elements, it is a place where various family activities take place and it is a place where people can express their identity and creativity. Credibility The question: How satisfied are you these days with the house you live in? probes the perception of the respondent regarding his or her residence. The importance of this indicator can be deducted from the list of variables dependent on it that includes the general quality of life indicators, such as overall life satisfaction, happiness and meaning. Calculation The mean satisfaction score with house for a population is calculated by the sum of the individual satisfaction scores divided by the number of individuals. Table Satisfaction with house (scale 0-10) of study communities. INDICATOR DESCRIPTION MEAN 5.08 All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (95% CI) Tyco (95% CI) Manf (95% CI) (4.93, 5.24) 4.86 (4.65, 5.06) 5.04 (4.61, 5.47) 5.67 (5.14, 6.19) 5.75 (5.39, 6.1) 4.77 (4.12, 5.43) 53 In a recent study in communities comparable to the communities surveyed in this study, the following was found regarding a house in terms of its meaning to its residents: (i) Beauty: People want their homes to be attractive to others (ii) Finances: A house is an investment that one should protect also expensive things in the house (iii) Comfort: You want to stay well in your house (iv) Cleanliness: The house must be fresh and neat (v) Self-respect: You clean the house because you love yourself (vi) Ownership: The house is your place, people who did not get their house through their own strength will not care for it (vii) Education: It depends on what you saw in your parents house (viii) Gender roles: Some see caring for the house as the woman s role, others disagree (ix) Financial means: some said, if you have money, you will take care of your house; others say, even if you are poor, your house can be clean and neat. 54 The term house refers to the structure that people live in, including formal and informal dwellings. It is more neutral than the word home, which suggests safety, happiness, and where you can be yourself. REPORT NO:NWU/2015/Eskom01 126

158 Housing in study communities Kwazamokuhle SP (31.15%) has significantly more informal houses than the other communities surveyed (Table 6-44). This also explains the challenges regarding services and infrastructure as indicated by the service infrastructure indicator set as a whole. The absolute number of RDP houses in each community as well as the absolute number of informal houses in each place is of particular importance to this project. The point estimates together with the upper and lower bound of the 95% confidence interval are in REPORT NO:NWU/2015/Eskom01 127

159 Table 6-45 and Table Definition A formal dwelling is a structure built according to approved plans, i.e. a house on a separate stand, flat or apartment, townhouse, room in a backyard or rooms or flatlet elsewhere 55. An informal dwelling (also informal structure) is a makeshift structure not approved by a local authority. Typically built with corrugated iron (or other materials) and contrasted with formal dwelling and traditional dwelling. Rationale It is important to measure the number of informal structures in a particular community. Not only does this give policy and decision makers an indication of the housing backlog, it also helps to quantify the challenges in other living standard categories such as water, sanitation, waste removal and electricity services. A sudden increase in informal structures could be the result of various factors and is important to monitor since it has to be managed carefully in order to avoid social unrest. Ceilings can contribute to enhanced protection against elements such as temperature fluctuations and dust. Credibility Fieldworkers are trained to distinguish between the various types of dwellings and to check for ceilings if necessary. Calculation The sum of informal structures (dwellings) divided by the total number of dwellings multiplied by 100. For ceilings: The sum of dwellings with a ceiling in at least one room divided by the total number of dwellings multiplied by 100. Table Housing in study communities. INDICATOR DESCRIPTION % informal of all structures All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (95% CI) Tyco (95% CI) Manf (95% CI) (26.98, 33.13) (26.71, 35.96) 4.4 (1.72, 10.76) 7.14 (2.46, 19.01) 2.7 (0.92, 7.65) 7.58 (3.28, 16.54) 55 Compare Census 2011 REPORT NO:NWU/2015/Eskom01 128

160 Table Number of RDP and non-rdp houses in KwaZamokuhle. Place RDP? PointEst Lower Upper Emaskopasini Not RDP RDP Kwazamokuhle SP Not RDP RDP Manfred Not RDP RDP Maphela Not RDP RDP Tycoon Not RDP RDP Table Number of formal and informal houses in KwaZamokuhle. Place House Type PointEst Lower Upper Emaskopasini Formal Informal Kwazamokuhle SP Formal Informal Manfred Formal Informal Maphela Formal Informal Tycoon Formal Informal Education Satisfaction with education (scale 0-10) in study communities The satisfaction with education scores are very low in all communities surveyed in comparison to the rest of the household domain satisfaction scores (Table 6-47). Definition Satisfaction with education (scale 0-10) is a well-being indicator that assesses how a person perceives his/her education by rating it on an 11 point numeric scale where 0 means complete dissatisfaction and 10 means complete satisfaction. 56 In this category one indicator, D1, measured perception with an 11 point numerical scale. Perception indicators always have to be taken with caution because of the complexities involved in the assessment of perceptions. Many factors can influence results including cultural and lingual factors but also household or fieldworker bias. In this particular study, there might be a possible data quality issue pertaining to fieldworker bias confined to the indicators that apply the 11 point numerical scales. REPORT NO:NWU/2015/Eskom01 129

161 Rationale Education is a fundamental human right and essential for the exercise of all other human rights. It promotes individual freedom and empowerment and yields important development benefits 57. The relationship between education and poverty appears strong as the poverty measures reflect, the lower the level of education attained, the more likely adults are to be poor and experience more intense levels of poverty 58. Credibility The question: How satisfied are you these days with your education? probes the overall personal perception an individual has about his/her education. The importance of this indicator is supported by the list of variables dependent on it, for example the perception that life is meaningful or worthwhile, satisfaction with the self and overall-life-satisfaction. Calculation The mean satisfaction score with education for a population is calculated by the sum of the individual satisfaction scores divided by the number of individuals. Table Satisfaction with education (scale 0-10) in study communities. INDICATOR DESCRIPTION MEAN 4.44 All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (95% CI) Tyco (95% CI) Manf (95% CI) (4.29, 4.58) 4.29 (4.11, 4.48) 4.38 (3.97, 4.79) Adult illiteracy level in study communities 5.12 (4.64, 5.6) 4.76 (4.38, 5.14) The adult illiteracy level does not differ significantly between communities (Table 6-48). The percentage of persons 20 years and older without schooling in all communities is 13.84%, which is close to the Mpumalanga provincial figure of 14.00% and somewhat higher than the national figure of 8.60% (Census 2011). Definition Adult illiteracy refers to the percentage of the population 20 years and older who cannot, with understanding, read and write a simple statement about their everyday life (3.37, 4.76) 57 Quoted from UNESCO webpage: 58 Poverty trends report, p Compare the World bank definition: Compare also the UNESCO definition: The ability to identify, understand, interpret, create, communicate and compute, using printed and written materials associated with varying contexts. Literacy involves a continuum of learning in enabling individuals to achieve their goals, to develop their knowledge and potential, and to participate fully in their community and wider society in The Plurality of Literacy and its implications for Policies and Programs, UNESCO Education Sector Position Paper: REPORT NO:NWU/2015/Eskom01 130

162 Rationale Literacy encompasses a complex set of abilities to understand and use the dominant symbol systems of a culture for personal and community development. Literacy levels can be a pointer to particular aspects of human capital in a population, for example, it gives an indication of the number of people that could qualify for certain skills development programmes and higher education. Credibility The question used to determine this indicator is the same as the question used by Census 2011: it asks what the highest level of school education is for every person included in the sample 60. Calculation The sum of persons 15 years and older with no school education completed divided by the total number of persons. Table Adult illiteracy level in study communities. INDICATOR DESCRIPTION % 20y+ without schooling All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (95% CI) Tyco (95% CI) Manf (95% CI) (12.39, 15.43) (12.45, 16.67) (8.71, 16.94) (7.12, 18.17) (9.39, 16.37) (12, 22.47) Adult population (20y+) with grade 12 competed in study communities (D3) Only about a third of the working population above 20 years of age in all communities have completed grade 12 (). Tycoon (43.13%) has somewhat more adult residents that have completed grade 12 than the other communities. Definition Persons 20 years and older who have successfully passed Grade 12 school education 61. Rationale The number of people in a particular community who have completed their school education is a pointer to particular aspects of human capital in an area such as the people that could qualify for certain skills development programmes and higher education. In South Africa graduates are more likely to be employed in the formal sector Compare Census 2011: P20_EDULEVEL 61 Successfully passed means that it has been certified that the persons has complied with all set criteria to pass grade Compare REPORT NO:NWU/2015/Eskom01 131

163 Credibility The question used to determine this indicator is the same as the question used by Census 2011: it asks what the highest level of school education is for every person included in the sample. The decision to include all persons 20 years and older is to enable comparison with Census 2011 percentages. Calculation The sum of persons 20 years and older who have successfully completed grade 12 divided by the total number of persons 20 years and older. Table Adult population (20y+) with grade 12 competed in study communities. INDICATOR DESCRIPTION % working population All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (95% CI) Tyco (95% CI) Manf (95% CI) (30.95, 35.21) (27.91, 33.58) (28.43, 40.43) 29.6 (22.3, 38.11) (37.76, 48.67) (23.64, 36.86) 6.6 Safety and Security in study communities (indicator E) Safety perception (E1) People in Kwazamokuhle SP feel significantly less safe than residents of the other communities surveyed: only 55.09% of households in this community reported that they think the area is safe (Table 6-50). Definition The respondent s perception regarding the safety of the area where he/she lives. 63 Rationale Surveys such as the Victims of crime survey by Statistics SA cannot replace police statistics but it can be a rich source of information which will assist in the planning of crime prevention as well as providing a more holistic picture of crime in South Africa: The data can be used for the development of policies and strategies, as well as for crime prevention and public education programmes. 64 Similarly this indicator provides an indication of perception of safety which will make it possible to see if the safety perception changes over time in the study communities. Credibility This indicator asks for an overall impression and does not distinguish between perceptions of safety during night and day times. It also does not specify a specific place or activity, such as being at home or walking. The advantage of a general perception is that it gives an overall impression and the disadvantage is that it can 63 Note that neither the geographic borders of the area nor the specific definition of safety are provided to the respondent 64 STATSSA, Victims of Crime Survey 2011, P0341, p. 1. REPORT NO:NWU/2015/Eskom01 132

164 only be compared to a similar question in other surveys that also focus on a general impression. Calculation The sum of respondents who perceive their area to be safe divided by the total number of respondents times 100. Table Safety perception in the study communities. INDICATOR DESCRIPTION % that think area is safe All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (95% CI) Tyco (95% CI) 67.1 (63.52, 70.5) (50.08, 60) (74.57, 89.75) (69.4, 91.68) (73.8, 88.02) Victim of crime in last 12 months in the study communities (E2) Interestingly there is no statistically significant difference between the communities surveyed ( REPORT NO:NWU/2015/Eskom01 133

165 Table 6-51). As indicator, safety perception is strongly correlated to being a victim of crime in as far as people who have been a victim of crime are more prone to feel unsafe. However, although there are significant differences in safety perceptions between towns, the results do not show a significant difference between towns in terms of being a victim of crime in the last 12 month reports. In other words, even though significantly more people in Kwazamokuhle perceive their area to be unsafe, the reported victim of crime rates in the last 12 months are not significantly higher than in the other sampled communities. Definition A victim of crime is a person who has been the victim of a crime in the 12 calendar months preceding the survey. Rationale See Section Calculation The count of households that had become a victim of crime, divided by the total number of households, multiplied by 100. The count of households where a member has been a victim of a specific crime (street robbery, home burglary, home robbery) divided by the total number of households multiplied by 100. REPORT NO:NWU/2015/Eskom01 134

166 Table Victim of crime in last 12 months in the study communities. INDICATOR DESCRIPTION All (95% CI) KwaSP (95% CI) Emas (95% CI) Maph (95% CI) Tyco (95% CI) % hh victim of crime (8.2, 12.73) 10.7 (7.99, 14.2) 6.59 (3.06, 13.65) 7.14 (2.46, 19.01) 9.01 (4.97, 15.79) % hh street robbery 3.32 (2.22, 4.93) 1.83 (0.89, 3.72) 2.2 (0.6, 7.66) 0 (0, 8.38) 3.6 (1.41, 8.9) % hh home burglary 0 (0, 0.55) 0 (0, 0.99) 0 (0, 4.05) 0 (0, 8.38) 0 (0, 3.35) % hh home robbery 6.06 (4.51, 8.09) 8.09 (5.76, 11.26) 2.2 (0.6, 7.66) 7.14 (2.46, 19.01) 4.5 (1.94, 10.11) 6.7 Energy Aspects of Community Solid fuel use Definition Solid fuel users are households that use solid fuels (e.g. coal, wood, dung, charcoal, or crop residues) as an energy carrier for domestic cooking or heating. Solid fuel use is assessed by considering the following aspects: i. % households using solid fuel in winter ii. iii. iv. % households using coal in winter % households using wood in winter average quantity of coal used per winter month (in kg) v. average quantity of wood used per winter month (in kg) vi. vii. viii. % households using solid fuel in summer % households using coal in summer % households using wood in summer Rationale Particularly in areas where solid fuels are readily available and affordable in comparison to other energy carriers it remains an option as domestic energy source for low-income households. Both the proportion and the number of solid fuel using households should be monitored for trends in domestic solid fuel combustion and resulting emissions: a declining proportion of solid fuel users indicates a transition of households away from solid fuels and translates to decreased emissions Household solid fuel use characteristics In Figure 6-3 the percentages of households that use solid fuels in winter are compared among the seven different intervention types. On the left side of the graph, the starting point of each ribbon indicates (with a 95 % confidence interval) REPORT NO:NWU/2015/Eskom01 135

167 the percentage of households from that particular intervention type that used solid fuels during winter before intervention; on the right side of the graph, the ending point of each ribbon indicates (with a 95 % confidence interval) the percentage of households from that specific intervention type that are still using solid fuels in winter after the intervention. When two ribbons overlap, the differences between them cannot be considered statistically significant. As can be expected, no statistically significant differences were evident among the different intervention groups prior to the intervention. Post-intervention, however, the LPG households reported markedly less winter solid fuel use than the other five intervention groups. This can mainly be ascribed to the fact that the coal stoves of the former group were physically replaced by LPG stoves during the intervention; hence, the households no longer had stoves in which they could use solid fuels. The small amount of solid fuel use that was, however, still reported by some of the LPG households post-intervention can probably be ascribed mainly to the occasional bundle of wood and bucket of coal used for making an outside social fire. The other five intervention groups did not report significantly less solid fuel use during winter months after the intervention (their ribbons overlap). There seems to be a slight decrease in winter solid fuel use among the elec-full houses, but due to the fact that its ribbon still overlaps with those of the other four groups, the decrease cannot be said to be statistically significant. Together with this, the ribbon for the elec-full households widens towards the right, indicating an increased degree of variance in post-intervention winter solid fuel use among the elec-full households. The reported changes are all mainly due to parallel changes in coal use, not wood use, as can be seen in Figure 6-4. Figure 6-3. Percentage of households using solid fuel in winter, pre- and postintervention. REPORT NO:NWU/2015/Eskom01 136

168 a) b) Figure 6-4. Percentage of households using coal (a) and wood (b) in winter, preand post-intervention Summer solid fuel use varies greatly within and among the different intervention groups (Figure 6-5). The great variance within the groups is indicated by the breadth of the ribbons and is present both pre- and post-intervention. They do, however, all narrow down a bit towards the right, pointing to the influence of a converging factor(s). REPORT NO:NWU/2015/Eskom01 137

169 Variance among the groups were not statistically significant prior to intervention, but a distinct post-intervention difference can be noted between the LPG households and the other intervention groups, excluding the elec-full households (Figure 6-6). As was the case with winter solid fuel use above, the LPG households reported markedly less summer solid fuel use than most of the other groups. It is only the elec-full group that slightly overlaps with the LPG groups. No statistically significant difference can be detected in summer solid fuel use among the coal-basic, coal-full, elec-basic and control groups after intervention. Once again, the noted changes can mainly be ascribed to parallel changes in summer coal use, not wood use. Figure 6-5. Percentage of households using solid fuel in summer, pre- and postintervention. REPORT NO:NWU/2015/Eskom01 138

170 a) b) Figure 6-6. % of households using coal (a) and wood (b) in summer, pre- and post-intervention Household fire ignition patterns Definition Fire ignition patterns are assessed in the following categories: i. proportion of fires made per hour of day during a winter month ii. iii. iv. average number of fire ignitions per winter month proportion of fires made per hour of day during a spring month average number of fire ignitions per spring month Rationale The time of day at which a fire is made generally conveys a great deal of information about the purpose of the fire: early morning fires are mostly made for space heating when bathing; daytime fires are mostly made for cleaning purposes, and to a lesser extent for cooking and bathing; late afternoon and early evening REPORT NO:NWU/2015/Eskom01 139

171 fires are primarily made for cooking, but also for space heating, bathing and socialising purposes; and late evening fires again mostly for space heating. In the light of the above, a decline in the proportion of early morning fires translates to a decreased need for space heating in the mornings; it also translates to a decrease in solid fuel use in the morning. The same applies to a decline in the proportion of late evening fires. One would hope that the fewer purposes there are to make a fire, the fewer fires will be made, resulting in a reduction in solid fuel use and, hence, emissions Characteristics if fire ignition patterns The study found a notable decline in the proportion of early morning fires both during winter and spring among the majority of the households that received a retrofit, especially those that received the full retrofit, while the control group made 37.4% of their winter fires in the hours between 5 and 8 am, the coal-full, elec-full and coal-basic groups only made between 5.6 and 14.1 % of their winter fires during that time of the day. The elec-basic group, however, performed worse than all the other groups including the control group making 38.9 % of their fires in the early morning (Figure 6-7). During spring months, the control group still made 26.7 % of their fires between 5 and 8 am, while the full retrofit households only made % of their fires in the morning and the basic retrofit households between % during the same hours. With regards to evening fires during winter times, the control group made 22.2 % of their fires between 4 and 8 pm, while the coal-full, elec-full and coal-basic groups made between 32.7 and 38.3 % of their fires during those hours. The majority of the control group s winter fires were thus made for space heating purposes, with a morning-evening fire ratio of 1.7:1 (i.e. seventeen morning/bathing fires for every ten evening/cooking fires); the coal-basic, coal-full and elec-full households, on the other hand, maintained morning-evening fire ratios of 1:5 to 2:5 (i.e. only two to four morning/bathing fires for every ten evening/cooking fires). During spring times, the morning-evening fire ratios for the full retrofit households followed roughly the same pattern with only one to two morning fires made for every 10 evening fires; coal-basic averaged a 7:10 morning-evening ratio, while elecbasic a ratio of 15:10 and the control group a ratio of 16:10. Once again, the elecbasic group performed worse in spring time than all five other intervention groups, performing only marginally better than the control group. REPORT NO:NWU/2015/Eskom01 140

172 a) b) Figure 6-7. Proportion of fire ignitions per hour of day during (a) winter and (b) spring. The black line follows the contour of the control group s graph as point of reference REPORT NO:NWU/2015/Eskom01 141

173 The above tendencies correlate with the higher degree of overall thermal comfort attributed by the retrofit interventions that was both reported in the DES and recorded in the i-buttons measurements (Figure 6-8). Figure 6-8. Improved thermal comfort reported in DES and recorded by i- buttons. At 5 am on a winter morning the full retrofit houses averaged 5.5 to 6.8 degrees warmer than the control houses, while the basic retrofit houses outperformed the latter with between 3.2 and 4.8 degrees. On an average spring morning none of the retrofit houses whether basic or full dropped below a comfortable 20.6 C, while the control houses only averaged 17.5 C. In the light of this, it remains unclear why the elec-full group made so many morning fires. Unfortunately, the reduced space-heating need on winter mornings did not, in most groups, lead to a significant overall reduction in the number of winter fire ignitions. It did, however, seem to have an effect in the spring season. Figure 6-9 a and b summarise the average number of monthly fire ignitions across the seven groups, during the winter and spring seasons respectively. REPORT NO:NWU/2015/Eskom01 142

174 a) b) Figure 6-9. Average number of fire ignitions per month during (a) winter and (b) summer. REPORT NO:NWU/2015/Eskom01 143

175 In conclusion, the estimated values of stove-related coal and wood use per energy type during winter months are given in Table 6-52 and Table 6-53 (in increasing order). LPG groups have not been included due to their lack of access to solid-fuel using stoves. Table Winter monthly coal use per type (kg). Energy intervention Insulation intervention Data source Value coal full ibuttons coal basic ibuttons control none ibuttons elec full ibuttons elec basic ibuttons Table Winter monthly wood use per type (kg). Energy intervention Insulation intervention Data source Value coal basic ibuttons coal full ibuttons elec basic ibuttons control none ibuttons elec full ibuttons REPORT NO:NWU/2015/Eskom01 144

176 CHAPTER 7. THE CREATION OF A ROLL-OUT PLAN Hendrik Snyman and Henry Murray 7.1 Introduction Rationale The success of the project depends on a proper roll-out plan particularly where interventions are made in the private domain of peoples households Activity objective The objectives of this activity was to: Obtain the understanding and support of the broader community and participating households Determine design criteria for each intervention Design intervention prototypes Map the study area taking into account participant privacy Perform in-use testing and monitoring of prototypes Obtain the understanding and support of the broader community and participating households 2.1. Local stakeholder communication (LSRG) Nova engages communities through their representatives. These representatives should be from a wide spectrum in order to not benefit just one set of representatives (e.g. only elected political leaders. The following are key stakeholder representatives when conducting community communication: All households through elected leadership and community structures Households participating in the current project Political leadership councillors, ward committees, community associations etc. Social leadership religious leaders, traditional leaders, educators etc. Government district and local South African Police Service Any relevant local NGOs The project implementer and its partners/subcontractors The project sponsor (if applicable) The Kwazamokuhle community has a typical community structure found throughout South African townships. The groups listed above are all active in the community and do represent a wide spectrum of people. The Nova project coordinator compiled a list of contacts from each of the above sectors by visiting the relevant offices, officials and/or known persons. REPORT NO:NWU/2015/Eskom01 145

177 The first communication meeting took place on 24 July 2014 at the Old Age Room, Senzokuhle Advice Centre, 291 Ackerman Street, Kwazamokuhle. Please see Attachment 1 for the invitation. Where possible, the project coordinator sent invitations by and confirmed receipt. In cases where was unavailable, the coordinator delivered invitation personally. The agenda contained the following main discussion points: Opening and Welcome Introduction of attendants Apologies Additional items The purpose of the LSRG Background to the emission offset study The planned offset study interventions The choice of participating households Implementation team and recruitment Timeline What happens after the pilot study? Discussion Next meeting, contacts and closure Nova compiled elaborate content under the above points and attempted to communicate in a manner which ensured understanding from all representatives. The entire content was scripted and the verbatim discussion was added to the script. This script was then circulated to all invitees to ensure that those who could not attend had as much information as possible to disseminate to their groups. Please see Attachment 2 for the meeting script. Nova allowed two weeks for responses to the communication. Nova received no negative comments or concerns regarding its plans for implementation and therefore proceeded as planned. 7.2 Selection and recruiting households for in-use evaluation Primary qualification criteria Nova formulated the following primary qualification criteria for participating households: Households are chosen at random from the general interview The household indicated at the interview that it will be interested to participate The household uses solid fuel for space and water heating and cooking at least in winter Ownership can be explicitly determined REPORT NO:NWU/2015/Eskom01 146

178 The specific RDP house is suitable for one of the retrofit interventions. As such, the house o o o o o o o Was built by a governmental program, irrespective of time period Is rectangular in shape Has walls constructed of clay or cement bricks Has a corrugated iron or asbestos roof Does not exceed 50m2 in floor size Has no extensions Has none other than a lean-to shacks to one façade which is not north o Requires no open electrical wiring in to remain in ceiling cavity or along boards (conduit allowed) The household complies with at least one set of the detailed intervention/control group intervention criteria House owner is satisfied with the specific intervention terms and conditions and signs the agreement Recruitment of participating households After sampling the project coordinator visited the households on the selection lists in order of their listing. At each visit she introduced the project, described the aims and discussed the details of the implementation and contract. All the information and sample documents were contained in a brochure which she left at the household for their consideration. Please see Attachment 3 for an example. She returned to each household after a few days and received their decision on participation. The coordinator assessed the following secondary selection criteria where applicable to household selection: A Hi-efficiency stove selection criteria Satisfied with the replacement stove design and performance A high efficiency and low smoke stove will be sourced, tested and demonstrated to households to ensure satisfaction as a replacement Temporary/permanent exchange with the existing stove accepted This acceptance is required to test eventual chance to permanently replace the stove with a high efficiency stove. This will form part of the contract. Agree to solid fuel usage logging Agree to indoor air quality measurement if chosen Agree to personal air quality monitoring if chosen REPORT NO:NWU/2015/Eskom01 147

179 B C LPG intervention selection criteria Removal and storage of existing coal stove accepted Agree to attend the LPG safety training session Is satisfied with the LPG cylinder logistics and vouchers Agree to indoor air quality measurement if chosen Agree to personal air quality monitoring if chosen Pre-paid subsidy selection criteria Has a standard pre-paid meter fitted Is prepared to use electricity for space heating Is satisfied with the electric heater and pre-paid vouchers Is prepared to keep log of the study requirements regarding power outages and heater usage Agree to attend the safety training session Agree to solid fuel usage logging Agree to indoor air quality measurement if chosen Agree to personal air quality monitoring if chosen The project coordinator repeated this process for each intervention category until a full sample was realised. Nova contracted participating households after consultation with them concluded, they made a positive decision regarding their involvement and all relevant selection criteria were satisfied The design criteria for each intervention Intervention description For the purpose of this part of the report intervention refers to the intervention intended in the participating household s cooking and heating practice. It does not refer to the type of insulation installed in the house but rather to the replacement of coal stoves with an efficient biomass stove, the replacement of coal stoves with LPG devices, or the provision of an electricity vouchers in order to assess the impact thereof on solid fuel use. Process to derive design criteria Please refer to Attachment 4 for the full Process and selection criteria to contract 140 households. What follows is a summary of the selection criteria derived from the process. Nova conducted two focus group sessions and a third session with all participating households with the following aims: REPORT NO:NWU/2015/Eskom01 148

180 The aim of the first session on 18 November 2014 was to understand all user requirements. What do respondents need, in detail, regarding four usage areas and their priorities The aim of the second session on 11 December 2014 was to understand the user requirements/design specification for the specific technologies The aim of the third consultation was to introduce sampled households to the draft intervention designs, assess their willingness to participate by offering a contract, and finalise the designs after a demonstration/training session with each group End-user perceptions and preferences for artefacts A number of energy usage patterns emerged: The fast, modern pattern where people use electricity. They want to be off to work quickly in the morning, in the evening they cannot spend a lot of time to cook and they heat up their bedroom with an electrical heater for only an hour before going to bed. They do not do washing by hand like it was done in the past because washing machines are faster:...their hands can t manage anymore so the machine is right or...our hands are no longer strong; we can t use our hands anymore. The second pattern is slower and is related to coal: it may be a mother or grandmother with children who are at home and want the whole house to be warm with food on the stove and warm water for all when needed. Sometimes they cook traditional types of food (beans, samp, cow heels and head meat ) which take a long time. The stove is called the black man mama. However, coal is perceived as dirty and it pollutes the air Pragmatic combination of modern and traditional patterns: this could happen where for example more food has to be cooked over a weekend, or where people that normally heat water for bathing with an electrical kettle decide to heat the water on the coal stove when it is used either to heat the house or to cook traditional food Patterns related to energy poverty: households that uses pre-paid electricity might find that no cash is available to reload electricity but there might be some coal or wood available for cooking or space heating Patterns related to service delivery failure: when there are power outages, households have to revert to other energy carriers in order to fulfil their immediate energy needs Prominent views on energy carriers and artefacts Coal is popular because of its multiple usages Electricity is expensive and unreliable Gas and paraffin are perceived as dangerous and unwanted. The conversation about LPG did not develop as respondents were not familiar with its usage REPORT NO:NWU/2015/Eskom01 149

181 The image of solar energy is positive In summer the electric stove is preferred over a coal stove as the latter is too hot In winter the coal stove is preferred over an electric stove: In winter what we use a lot is the coal because not all of us can afford to use electricity. That is why so people prefer to use the coal stove. Because with the coal stove, they can cook, and the kids get warm and they can also do their household chores. In the winter the best thing is the coal stove because there is always hot water there For warm water the preference is seasonally dependent. For winter: The coal stove, as it has these water boilers, if we light it in the evening, and leave the water boiler filled with water when we go to sleep, when we wake up, we get warm water for bathing. For bathing that is the easy way. We use the kettle to boil water for tea. In summer: Kettle (rather than any stove), it is faster. You cannot use electric stove for warm water Intervention specific requirements resulting from group discussions Improved coal stove The group discussions yielded the following specific requirement relating to coal stoves: The stove should be big with 4-6 plates It should have an oven and a boiler for hot water A small stove is seen as unstable and dangerous: the children may upturn it or if it low, try to jump over it and tip it over A coal stove can be combined with a ceiling Electrical heater The group discussions yielded the following specific requirement relating to coal stoves: For long periods of heating, some prefer a cement heater / asbestos heater For short periods a spiral heater with two or three bars that get red because it is fast and can, for example, heat up the bedroom quickly before they go to bed. Certain respondents feel it is dangerous for the kids and prefer the electric oil heater Intervention prototypes design Technical description of the equipment and potential air quality improvement Key functional performance factors After determining the design criteria for each intervention, Nova formulated the following key functional performance factors per intervention: REPORT NO:NWU/2015/Eskom01 150

182 Interventions should not require substantial change in current household energy use practice Interventions should replace or enhance current device functionality Interventions should be injury risk aversive Interventions should be robust Interventions should be serviceable by local resources Interventions should cause no harm in the target community Requirements per intervention The functional performance factors enabled Nova to set the following requirements per intervention: Efficient biomass stove Ability to efficiently burn locally used coal Heating time similar or better than common stoves Sufficient cooking space and surface to accommodate commonly used crockery An oven for baking Robust design allowing for mobility if necessary Safety features similar or better than current stoves Construction allowing for part replacement LPG appliances Easily understandable and manageable safety features Straight-forward operation Sufficient cooking space and surface to accommodate commonly used crockery An oven for baking Robust design allowing for mobility if necessary Heating and cooking ability similar to current devices without exceeding current energy costs Replacement parts readily available at local retail outlets Electricity subsidy The subsidy should be sufficient enough to replace the heating performance provided by solid fuel stoves The subsidy should be in voucher format and not cash REPORT NO:NWU/2015/Eskom01 151

183 Identification of suitable intervention options Nova could only identify one suitable, scalable option in South Africa as a high efficiency stove replacement, namely the Kitchen King stove (Figure 7-1). The stove is the only option satisfying all requirements raised during the group discussions, including size, water warming capacity, oven capacity, durability and aesthetics: Figure 7-1. The Kitchen King. Entry level LPG stoves and heaters are fairly similar in function and standard Nova identified Totai Gas Appliances as a leading manufacturer supplying the local market (Figure 7-2). They supply stove with ovens which are suitable to replace existing coal stoves, as well as suitable space heaters: REPORT NO:NWU/2015/Eskom01 152

184 Figure 7-2. Entry-level LPG stoves and heaters. Electricity vouchers would be bought at the local municipal offices and distributed to participating households on a monthly basis. Laboratory results or certification for required parameters The Kitchen King stove supplier could only provide laboratory testing results dated in???. The stove was not certified by any authority. The project team decided to conduct emissions testing on the stove at the North West University s facility. All Totai LPG appliances are verified against the South African National Standard (SANS) and approved by the LPG Safety Association of South Africa (please see Attachment 4). Field tests per implementation Nova purchased two Kitchen King stoves and two LPG stove/heater combinations and conducted the following field tests. Field tests focused on practical operation and were conducted by Nova staff at the warehousing facility and in two households from the sample groups. The field test results confirmed that the interventions complied with the intervention requirements (see above). REPORT NO:NWU/2015/Eskom01 153

185 Obtain emission factors for stove and LPG Discuss old stove test results Nova obtained LPG emission factors from the US EPA AP42 (Table 7-1) as follows, unless indicated otherwise: Table 7-1. LPG emission factors. Pollutant g/kg PM PM SO CO 0.9 NOx 1.56 CO N 2O CH Hg N/A VOCs Description of the potential quality of life impacts of the intervention In order to ascertain the impact of intervention on households quality of life, Nova developed the Particular Impact on Quality of Life (Piqola) survey approach. The Piqola survey combines open-ended and semi-structured questions in order to gain the maximum amount of relevant information with minimum chances of research bias. A Piqola questionnaire is composed with the Piqola questorming chart. The potential QoL impacts per intervention (PIQOLA questorming matrix) The Piqola questorming chart could be described as an exercise in structured lateral question generation. The hermeneutic instrument assists in attaining a comprehensive pre-understanding of the possible impact an intervention could have on the quality of life of household residents. This is attained through the fusion of the following horizons: Understanding of the information contained in the hermeneutic multidimensional need/element database Understanding of the particular impact to be assessed, and Capability to use the questorming technique focused on anticipating relevant impact Note that when the above steps are done, the researcher is still on the level of preunderstanding. The aim is to enter into a dialogue with the intended study subjects to attain a better understanding of their horizons. 65 Escience projected from???? 66 Escience projected from???? REPORT NO:NWU/2015/Eskom01 154

186 The questorming chart was filled in as follows: Step 1: Spontaneous list First Nova researchers made a spontaneous list of all relevant questions of which the answers could shed light on the impact of retrofitting RDP houses and intervening in the cooking/heating practice on the QoL of the households in the focused community. Step 2: Fusion of horizons into questorming chart The next step was to populate the need-element interfaces of an unpopulated multidimensional need/element matrix through the fusion of horizons process. This requires competency from every researcher participating in the composition of the chart since it presupposed: Acquaintance with the contents of the hermeneutic multi-dimensional need/element database Familiarity with the retrofitting of RDP houses, and Proficiency in the application of the questorming technique The completed Piqola questorming chart could consist of hundreds of questions that the researchers think can shed light on the impact of retrofitting houses in the focused community on the quality of life of the residents. The 250 need-element interfaces are used to brainstorm on the possible impact and the questions were listed during this exercise in the form of a completed intervention multi-dimensional need/element matrix. The objective of the questorming exercise is not to come up with one best question per interface, but rather to generate a list of questions relevant for an enhanced understanding of the possible impact of the intervention at hand on quality of life. Step 3: Condense questions The third step is to condense the broad list of questions into a shorter list containing the most relevant questions. This shortened version is used in the survey as the customised Piqola questionnaire. It is important to note that the goal of any customised Piqola questionnaire is not to enforce a rigid framework onto a respondent that could influence or enforce a particular response. It is exactly the opposite: during the practical execution of any investigation the first goal is to get open feedback from any respondent before influencing the respondent with the semi-structured or structured questions. Ultimately we constantly remind ourselves of the fact that we are influenced by our presuppositions, biases and contexts and therefore we consciously want to remain as open as possible for the encounter with the respondent by first listening to what he/she wants to say before being too directive even in a semi-structured manner with the questions we intend to ask. In other words, the questions generated through this process should not be seen as a thought experiment or hypothesis. The aim of this chart is not to reason from causes to effects but it is rather an attempt to think as widely as possible about REPORT NO:NWU/2015/Eskom01 155

187 what the researcher does not know and about what could possibly be important to consider when thinking about the impact of an intervention on quality of life. In other words, as hermeneutic instrument the Piqola questioning chart is a question generator much rather than an answer generator. PIQOLA post-implementation survey design After condensing the questions flowing from the questorming chart, the research team programmed them into an electronically delivered questionnaire. The questionnaire also contained unique identification and state of the installed technology questions, and were recorded for accurate rendering. Please find the complete questionnaire in Attachment 5. The research team produced a sample of 12 houses in the control group and 6 houses in each of the 6 intervention combination groups. Target households were randomly selected and only qualified if temperature- and energy use measurements were done in the house. Evaluation of the interventions against Quality of Life indicators The completed Piqola questorming chart consisted of close to a thousand questions that could shed light on the possible impacts of the intended interventions on quality of life (QoL). These questions are generated in the matrix with 250 QoL interfaces which function as heuristic QoL parameters or indicators against which the possible impact of interventions can be evaluated. The evaluation results in a condensed customised Piqola questionnaire which accesses the QoL impacts of the interventions Formulate integrated monitoring regime per intervention Installation quality control Nova drafted the a quality control procedures for the installations which is given in Table 7-2, Table 7-3 and Table 7-4. REPORT NO:NWU/2015/Eskom01 156

188 Table 7-2. Quality control procedure for installation of ceilings. REPORT NO:NWU/2015/Eskom01 157

189 Table 7-3. Quality control procedure: exterior cladding, trombe panel. Table 7-4. Quality control procedure: stove replacement Safety aspects Each participating household would be contractually obliged to attend a safety training session before any installation is completed. The training sessions would be conducted by qualified supplier experts and trained Nova staff Energy use Nova has drafted a energy use monitoring regime which is summarized in Table 7-5. REPORT NO:NWU/2015/Eskom01 158

190 Table 7-5. Monitoring regime. REPORT NO:NWU/2015/Eskom01 159

191 CHAPTER 8. THE INTERVENTION ROLL-OUT Hendrik Snyman and Henry Murray 8.1 Introduction This part of the report structure closely follows that of the Work Breakdown Structure (WBS) of Activity 7 contained in the project proposal and budget Rationale In order to find the most promising household emission offset interventions and to determine the associated emission reductions, improvement in air quality, and acceptability to households it is important to test the feasibility of these interventions in actual in-house conditions Activity objective To test all aspects related to the implementation process per intervention in order to access the effectiveness of each intervention in actual in-house conditions and in order to select the most promising intervention(s) for the purposes of offsetting Establish teams Formulation of selection criteria per intervention Each intervention can be divided in two elements, namely household insulation/retrofit and stove replacement. The household insulation/retrofit primarily demands building work while the stove replacement primarily demands mechanical fitting. Prospective applicants for the household insulation would benefit from physical conditioning that could meet the demand of construction work and previous building experience. Prospective applicants for the stove replacement would benefit from similar physical conditioning and previous mechanical fitment experience. Based on previous project outcomes Nova foresee no gender constraints and men and women would compete on equal basis. During planning Nova calculated that the implementation needed the following contractor compliment: 10 construction teams consisting of a team leader and two members 1 stove replacement team consisting of a team leader and three members A small number of reserves to replace fall-out contractors 1 driver stock control officers REPORT NO:NWU/2015/Eskom01 160

192 Obtaining CVs Nova continued with the call for CVs process agreed upon at the LSRG during the survey recruitment phase of late Nova sent a call for CVs to all invitees to the LSRG meeting, and posted the call at the following locations: Skills Development Center: 129 Ackerman Street Kwazamokuhle Dutch Reformed Church: 233 Nkosi Street Kwazamokuhle Saint John Church: 3722 extension 6 Kwazamokuhle Steve Tshwete Municipality offices: 33 Mouton Street Hendrina SAPS: 44 Mountons Street Hendrina Library: 33 Mouton Street Hendrina Hendrina Clinic: 38 Mounton Sstreet Hendrina As per advice from the councillors, secure collection boxes were placed in each ward at the following locations: Ward 1: Thabo Tuck Shop, 2173 Thwala Street, emaskopasini Ward 2: Tololo shop, Stand 301 Ward 3: Malfred Tuck Shop, 1750 Mbokane Street Nova coordinators collected the CVs on regular basis. Nova received 164 CVs in total. After applying the selection criteria, Nova invited 59 persons for interviews. Candidate interviews Nova conducted interviews by means of a panel consisting of the Project Coordinator, the Construction Manager and the Assistant Construction Manager. The panel assessed candidates understanding of the position they are applying for, their experience and skills in the light of the selection criteria and their English language skills. After completing 59 interviews, Nova appointed the following contractors: 11 team leaders 28 team members 1 driver 1 stock control officer 1 stock control assistant Worker contracts Nova contracted successful applicants by means of a standard fixed term contract. The contract makes provision for general employment conditions as well as specific work- and payment descriptions. Please see Appendix 1 for a contract example. REPORT NO:NWU/2015/Eskom01 161

193 Develop training material and organise training logistics During previous iteration of retrofit feasibility projects, Nova transported contractors to Gauteng for training at the material supplier s venue. This is however a costly exercise and the actual benefit is not clear. For the current project Nova decided to set up training cubicles (Figure 8-1) at its store facilities and manage to secure participation of a technical team from the supplier. Figure 8-1. A training cubicle. REPORT NO:NWU/2015/Eskom01 162

194 Training material was procured from the supplier. All team leaders had to attend and successfully complete training in order to start work. Train teams and evaluate teams Training was divided into training at the store facility (3 days) and training in inhouse conditions for as long as necessary to ascertain good quality work (Figure 8-2 and Figure 8-3) Figure 8-2. Training at store facility. Figure 8-3. Training in in-house conditions. REPORT NO:NWU/2015/Eskom01 163

195 The operational manager, construction manager and assistant construction manager supervised and evaluated the teams in terms of adherence to design specifications, neatness and material preservation/prevention of wastage. The total time needed to ensure acceptable quality of work was 7 days. All team leaders successfully completed the training course, including the stove replacement team leader (as reserve). Issue equipment Nova procured equipment needed and issued it to each team. Equipment included safety gear such as uniforms, safety goggles and protective gloves. All equipment fitted into tool boxes suitable for transport and the responsibility to maintain the inventory was given to the team leader. Allocate houses to teams The project coordinator divided the target houses equally between teams. She made appointments with each household and requested them to prepare their houses before the teams arrived (e.g. to move out furniture). At first the stove replacement team had to remove and replace stoves where applicable. After that the construction teams could install the insulation. Teams worked over the entire Kwazamokuhle area and not confined to a particular sub-place Manage materials Formulate inventory per intervention Nova formulated the following elements relating to the inventory needed: Ceilings/Basic retrofit EPS 24FR 50mm ceiling boards, to be affixed along roof pitch (not horizontal hanging installation) Joining strips consisting of aluminium top- and PVC bottom sections Galvanized steel wall angles EPS cornices with adhesive and mechanical fixings White non-acrylic painting Assessing of particular requirements on a case to case basis in houses where poor interior building present challenges Full retrofit Insulative ceiling as above EPS X-Grade sheeting, fixed by adhesive and mechanical means Cement-based, fibre-reinforced base plaster including fibre-mesh reinforcing Polymer SBR Latex modified, flexible, cementitious external coating with pigmentation (white, grey, apricot, brown) Door insulation consisting of EPS sheeting and steel panel covering REPORT NO:NWU/2015/Eskom01 164

196 Passive solar device (Trombe panel) on northern facade, consisting of treated wooden frame, polycarbonate sheeting and black painting of wall Efficient stove intervention Kitchen King LPG intervention Totai 4 plate stove with oven Totai LPG space heater Totai bullnose regulator for stove Two standard 9kg LPG cylinders Electricity subsidy intervention Electricity vouchers of R (two hundred rand) sampled households for five months For a full inventory description including construction tools please see Attachment Identify suppliers and obtain quotes Procure Nova conducted a full analysis of possible material suppliers during a preceding iteration of the retrofit design test. Saint-Gobain Construction Products is a market leader in terms of insulation and protective renderings and had been participating in the evolvement of the retrofit application since its inception. Nova decided to continue the relationship and utilise Saint-Gobain as the main supplier of insulation materials. The Kitchen King stove was the only suitable option Nova identified and as there is only one supplier in South Africa they were chosen by default. Entry-level LPG stoves and heaters are fairly similar in function and standard. Nova identified Totai Gas Appliances as a leading manufacturer supplying the local market. They supply stove with ovens which are suitable to replace existing coal stoves, as well as suitable space heaters. All appliances are SABS approved. The construction team procured as much material as possible at the onset of the implementation phase to mitigate the risk of extended lead times on orders. Quantities relating to insulation products were derived from previous retrofit tests. The Kitchen King stoves and LPG appliances were bought in one batch. Total Gas supplied cylinders via a local distributor Receive and store Kwazamokuhle had no suitable options and the team was forced to rent expensive storage facilities in Hendrina. The facilities had to be of sufficient size to accommodate all the swopped-out stoves and the entire material complement. The project budget for storage proved insufficient. REPORT NO:NWU/2015/Eskom01 165

197 8.1.8 Distribute to teams Because the main storage was located in Hendrina (6km away from Kwazamokuhle s entrance) the team encountered a significant logistic challenge. The only viable solution was to rent a 4-ton truck and appoint a driver to act as the main supply vehicle. This truck would be loaded every morning and visited each team in succession to deliver needed material. Two 1-ton pickups complimented the main supply vehicle and ensured delivery of smaller item during the work day Material QC and issue management Nova appointed a stock control officer and assistant to manage material issuance. The following system was followed: Team leaders report to the main storage facility at the start of each work day They order material from the stock control officer The stock control assistant oversees the issuance of the material The team leader and stock control officer sign a issuance form The stock control officer inputs the order into the central database where material quantities are being monitored The material is transported to the target house If additional material is needed during the day, the drivers of the smaller vehicles will take the team leader to the main storage facility for issuance and transport The operational manager analysed issued material averages to identify and investigate possible discrepancies between teams. 8.2 Installation Schedule The projected time required for installation is summarized in Table 8-1. Table 8-1. Installation time requirements. Number of installatio ns Work days required (one team) Total work days required for installations Total work Number of Installation days teams Ceilings Cladding Stove replacement Draft proofing Trombe walls Concurrent with ceiling installations Concurrent with cladding Concurrent with cladding Nova scheduled the implementation activities for April to May 2015, leaving June as a contingency month. REPORT NO:NWU/2015/Eskom01 166

198 8.2.2 Installation by teams Insulation: challenges and mitigation/reactive measures From the onset of installations, the construction teams encountered the following major challenges: Timeous material supply. Before construction started the project team experienced challenges relating to two divisions of Saint-Gobain not adhering to delivery schedules. This resulted in material being delivered a week late and a delay in the installation start. The responsibility for timeous material supply is often an issue and should be placed entirely on the supplier in any subsequent phases Poor construction of houses. Although poor construction is common in RDP-type housing, some of the houses in the test group produced worse than anticipated construction. After initial analysis the construction team identified an owner-builder principal as origin of the shoddy work: when some of the RDP houses were given to the new owners, they had no inner walls and the construction of these walls was left to the inhabitants. Being financially challenged in the first place this obviously led to them either doing the work themselves or trying to get it completed for as little money as possible. Examples of challenges pertaining to the installation of ceilings included weak/sandy plastering, weak paint pulling away from walls, grossly uneven/skew walls and protruding steel frames utilised in the construction of the outer walls Roof design. A number of houses had a peculiar roof design where the highest part of the roof was made up of a concave corrugated iron section with no roof beam at the top of the roof. This made the anchoring of ceiling boards at the highest point impossible High variety in installation methods required. Because of the above principals, very few houses were the same and team had to develop a keen sense of adjustment to the particular demands of each house. Because of the non- standard installations required, quality control became very complex Water damage to ceilings. In approximately one-third of households water damage to ceiling boards became apparent quite rapidly. Water damage poses low structural risk to EPS ceiling boards (unlike gypsum boards for example) but it does results in brown discolouring and stains. The maintenance of roofs and fixing of water leaks is a contractual obligation of the home owner. Owners are repeatedly reminded of this obligation before and after installation, made aware of any (potential) leaks observed and prompted to fix leaks where necessary. However, the reality is that leaks are not always detected/ anticipated as they might be small, or that owners do not always do the required maintenance. The construction management team implemented the following mitigation/reactive measures: Choose quality over quantity and use the available contingency time rather that force the pace and risk less robust installations REPORT NO:NWU/2015/Eskom01 167

199 Due to particular construction challenges outlined above, the training period was extended to ensure that team leaders are fully equipped to produce quality installations Houses were sorted in order of least- to the most complicated. The most complicated houses were left to the latter part of the installation period in order to give teams time to gain the most possible experience Where shoddy construction work made it impossible to fit ceilings properly, the construction team decided on and tested mitigation measures including: o o o fixing plywood to uneven walls to provide a stable adhesive surface extensive use of polyurethane foam to fill gaps more/longer mechanical fixings o installing beams at the pitch of roofs where they were absent The stove replacement team were trained and supported to become a Jackof-all-trades team which would divide their time between swopping stoves and preparing complicated houses for ceiling teams to do installations at later stages Nova removed some of the water-damaged ceiling boards for analysis and it was apparent that water accumulates at roof beams. This is probably due to small leaks at roof fixings/screws which in most cases do not have proper seals installed. Nova sealed two roofs where damage occurred at each fixing and installed new boards, and monitored one roof which the owner himself sealed. Damage did not appear or re-appear in these cases. During analysis Nova investigated the possibility of condensation occurring in the ceiling cavity resulting in or exacerbating water damage. Although possible, the investigation was inconclusive as no explanation could be given for the seizure of damage after fixings were sealed off in the three cases mention above. However, for feature implementations the drilling of ventilation holes in the ceiling cavity would be a low-cost conservative measure well worth the effort Stove replacement: challenges and mitigation/reactive measures From the onset of stove replacement the team encountered the following challenge: Household contract breach. At 11 of the 80 houses (14%) where stoves were scheduled to be replaced, the households resisted the replacement after the insulation was installed. Some out-rightly said that they do not wish to swop their stoves anymore, while other had all sorts of excuses ranging from ownership to hiding the stoves from teams. These household refused despite the project coordinator fully explaining the extent of the test and the implications of the contract they signed. The fact that these households waited until the insulation was installed to refuse further participation suggests at least some measure of premeditation The project coordinator countered this challenge as follows: REPORT NO:NWU/2015/Eskom01 168

200 8.2.4 Progress Thorough consultation with the household to explain that they are breaching the contract and to confirm that their stoves will be returned at the end of the 3 month testing period should they choose so As the electricity group was last to be contracted, 5 of households who still resisted the stove swop was transferred to that group One household was removed from the test altogether. Stove swopping started, continued and finished according to schedule. The challenges described above resulted in a slower than planned start to the insulation installations. However, as soon as the construction management team implemented the mitigation/reactive measures the progress sped up and took place at the pace originally planned for. The contingency period was used in full. Installations concluded for the most part on 26 June 2015, which only a small number of Trombe panels installed during the first week of July Some images of the progress and completed houses are given in Figure 8-4, Figure 8-5 Figure 8-4. Some progress and completion images. REPORT NO:NWU/2015/Eskom01 169

201 Figure 8-5. Progress and completion images QC on installations, corrective action and sign off Nova employed a construction manager and assistant construction manager. They were both full-time employed. Their main assignment was to assure quality installations by managing logistics and assessing/signing off on work completed. Teams would only be paid if installations were inspected and approved at two stages, firstly after insulation was installed (ceiling boards, exterior insulation boards) and secondly after finishing. The first inspection assured that the material was installed as per specification (e.g. filling of gaps, sufficient mechanical fitting, robust fixings). If necessary, the construction team had to take corrective action. The second inspection assured an acceptable, completed product. Teams were remunerated after the second inspection yielded positive results Household training on use of equipment The contract signed between Nova and the household representative contained the following stipulation: 2.11 The Owner agrees to attend a safety and usage training session facilitated by Nova. The Owner agrees to train all household members on safe use of installed devices as per training provided to him or her. Nova facilitated training sessions for both the Kitchen King and LPG interventions. Nova scheduled several sessions of each and installation only commenced once a representative attended the relevant training session. REPORT NO:NWU/2015/Eskom01 170

202 Kitchen King training The supplier of the Kitchen King stove supplied a user manual and trained Nova staff on the Kitchen King s usage. Training focused on the working/efficiency of the Kitchen King, the correct lightning procedure and safety relating amongst others the water heater (Figure 8-6). The staff in turn conducted Kitchen King training sessions with household representatives (Figure 8-7). Figure 8-6. Kitchen King training for Nova staff. Figure 8-7. Kitchen King training for household representatives. REPORT NO:NWU/2015/Eskom01 171

203 LPG appliance training Nova contracted the LPG Safety Association of South Africa (LPGSAS) to provide safety training on the intervention appliances. A LPGSAS representative provided training to household representatives in Hendrina over two days (four occasions to accommodate households). Despite providing several opportunities and logistical support to attend, some households could not attend the LPG training sessions. The LPGSAS representative decided to train two Nova members who assisted during his sessions in order to enable them to provide training to the few who could not attend. Given the unfamiliarity with LPG use in the target community, Nova decided to add to the training by employing a LPG safety officer (Figure 8-8). This officer was tasked with visiting households who participated in the LPG appliance testing on at least a two-weekly/fortnight basis for the duration of the test period. The safety officer conducted a structured interview with representatives in order to re-affirm safe LPG use principles, assure that representatives understood reactive steps in case of perceived danger, and enquire about any safety incidents which might have occurred. Please see Appendix 3 for a copy of the interview employed. Figure 8-8. LPG training for household representatives. By the end of the testing period on 30 September 2015, the safety officer recorded 286 attempts at a LPG safety interview with participating households. Of these attempts, 216 resulted in interviews. The following outcomes are significant: Households reported safety incidents in 5 interviews (2.3%). On 4 occasions it pertained to stove knobs/valves left open without flame ignition. On 1 REPORT NO:NWU/2015/Eskom01 172

204 occasion a user suffered what appeared to be minor burning as there was indication of medical treatment sought Respondents indicated in 201 interviews that they ventilate their households during heating (93%) Respondents indicated in 215 interviews that they shut the cylinder valve after using the LPG appliance (99.5%) When prompted to name the three steps to be taken in case gas is smelled (no ignition, ventilate, shut main valves), respondents were able to name all three in 210 interviews (97.7%) 8.3 Set local up LPG distribution for duration of project Nova took the responsibility to distribute LPG to households for the duration of the test. Households telephonically informed the project coordinator that they wished to purchase a refill after which Nova purchased the refill and recovered costs after delivery. 8.4 Manage and distribute electricity subsidies After concluding contract agreements with the electricity voucher test group, the local project coordinator conduct interviews with each household. During this interview she explained the main intention behind supplying vouchers, namely to motivate households to use less coal. The coordinator encouraged the household representatives to try their best to substitute coal usage with electricity. The installation team planned to obtain the electricity meter numbers from all the households and purchase vouchers. However, this did not succeed as the municipality wanted households electricity cards present at purchase. This resulted in a complicated process of collecting cards, buying credit and returning the cards to the households all within a time suitable to the household as they would have no electricity during this time. In addition to this, the installation team learned that if the household have outstanding water rate bills the municipality refused to sell them electricity before the bill was settled. Households often refused to pay the outstanding bills which forced Nova to pay them and deduct the amount from the voucher. This meant that households sometimes did not get the full R subsidy. REPORT NO:NWU/2015/Eskom01 173

205 CHAPTER 9. MACROECONOMIC IMPACT ASSESSMENT AND SOCIAL COST BENEFIT ANALYSIS Jackie Crafford, Nuveshen Naidoo and Wean Visser 9.1 Objectives The main objective of the Eskom Offset Pilot project is to test the effectiveness of the most promising household emission offset interventions identified during Eskom s pre-feasibility study. In Work Stream 8, in terms of the socio-economic analysis to be conducted to assess the costs and benefits associated with the project, the following objectives have been outlined: 1. Health impact and health costs: a. Changes in health expenditure b. Increased economic activity as a result of the decreased health burden 2. Full time equivalent employment job creation, specifically: a. Direct Jobs b. Indirect Jobs c. Induced Jobs 3. Direct and indirect GDP contributions 4. Greenhouse Gas Emissions: a. Changes on fuel consumption behaviour b. Reductions/increases in power generation 5. Social cost benefit analysis: a. Negative and positive impacts b. Costs and benefits of intervention implementation c. Use of shadow prices and other economic techniques aimed at converting costs and benefits into monetary terms d. A thorough technical and financial analysis of the pilot study REPORT NO:NWU/2015/Eskom01 174

206 9.2 Introduction The purpose of this deliverable is to perform a number of resource economic studies that culminate in a social cost-benefit analysis (CBA), and that provide a range of salient financial and macro-economic indicators which may be used to evaluate the project and possible project scenarios. Our approach to work stream 8 was: To apply appropriate techno-economic, resource-economic and macroeconomic analysis techniques To conduct the analysis through the development of single integrated model which may be used by the project team and Eskom staff to evaluate different project options, potential offset scenarios, and to conduct sensitivity analysis where appropriate To apply international best practice in the analysis. In particular we will employ best practice CBA practice as specified by the World Bank and the project evaluation guidelines set out by the World Business Council for Sustainable Development (WBCSD) of which Eskom is a member. Work Stream 8 is a macroeconomic impact assessment and social cost benefit analysis of the data collected in preceding work streams. The assessment and analysis are conducted using data inputs from previous work streams, model relevant indicators and factors in an integrated model and report on results in the outputs specified in the project terms of reference. An overview of the process is presented in Error! Reference source not found.. Considering the data intensive nature of the work stream and dependencies on preceding components of the study, there are many limitations due to the absence of some data sources to date. These include: Ambient Air Quality data will be produced by E-science Indoor Air Quality data will be produced by North-West University Health outcomes will be finalised in consultation with the CSIR and Eskom More detailed information on interventions will be provided by the Nova Institute Household fuel use date pre- and post-intervention from the Nova Institute In the absence of this information, alternative or preliminary inputs have been used to demonstrate the effectiveness of the model and estimate the broad impact of interventions. The integrated modelling provides outputs aligned with the objectives listed in Section 2 as outlined in the project terms of reference. REPORT NO:NWU/2015/Eskom01 175

207 Figure 9-1. Components of the integrated model, their relationship to data requirements from other Work Streams, and outputs in which the results will be reported. 9.3 Health Impact And Health Costs A health impact and cost analysis was performed to estimate the externalities of air pollution. The health impact and cost model was developed using best practices specified by the World Bank and the World Health Organization. The health cost model uses inputs from other parts of the study enabling the quantification of the positive impacts of reducing air pollutant emissions on human health. The outputs of this model feed into the Social Cost Benefits Analysis described in Section 8. The health cost model integrates the following components: Exposed population: This is the population within the study area that is exposed to the indicators of air pollution. This population is affected by the health endpoints associated with the indicator pollutants Air quality data: The baseline concentrations of indicator pollutants that the population is exposed to is used in conjunction with the modelled concentrations to determine the relative changes in air quality due to the interventions Exposure-response functions: Epidemiological evidence of the relationship between exposure to pollutant indicators and health endpoints experienced by the exposed population. These relationships are sourced from epidemiological studies. Health costs: The costs associated with treating, as well as other costs associated with health endpoints, is estimated REPORT NO:NWU/2015/Eskom01 176

208 9.3.1 Exposure Indicator Selection Quantifying the effects of air pollution requires suitable indicator pollutants as anthropogenic air pollution is a complex mixture of many toxic components (Figure 9-2). Common components include: sulphur dioxide (SO2), oxides of nitrogen (NOx), suspended particulate matter (PM) and others. The ambient concentration of these pollutants is highly correlated, and thus summing the health effects associated with each pollutant can lead to an overestimation of the total health effects. Thus, often a single indicator pollutant, which the majority of effects are correlated to, can be used. The WHO and other organisations guideline methodologies for the assessment of health impacts due to air pollution are based on epidemiological studies conducted around the world. Thus they use relationships between emission concentrations and various types of health outcomes. A suitable indicator pollutant needs to be measurable, with sufficient data from which to create exposure concentration estimates and linkages to health outcomes. Figure 9-2. Effects of Air Pollution (EPA, 2003). Particulate Matter (PM) as an indicator pollutant Particulate matter affects more people than any other pollutant. The major components of PM are sulphate, nitrates, ammonia, sodium chloride, black carbon, mineral dust and water. It consists of a complex mixture of solid and liquid particles of organic and inorganic substances suspended in the air. The most healthdamaging particles are those with a diameter of 10 microns or less, ( PM10), which can penetrate and lodge deep inside the lungs. Chronic exposure to particles contributes to the risk of developing cardiovascular and respiratory diseases, as well as lung cancer. REPORT NO:NWU/2015/Eskom01 177

209 Air quality measurements are typically reported in terms of daily or annual mean concentrations of PM10 particles per cubic meter of air volume (m3). Routine air quality measurements typically describe such PM concentrations in terms of micrograms per cubic meter (μg/m3). When sufficiently sensitive measurement tools are available, concentrations of fine particles (PM2.5 or smaller) are also reported. There is a close, quantitative relationship between exposure to high concentrations of small particulates (PM10 and PM2.5) and increased mortality or morbidity, both daily and over time. Conversely, when concentrations of small and fine particulates are reduced related mortality will also go down presuming other factors remain the same. This allows policymakers to project the population health improvements that could be expected if particulate air pollution is reduced. Nitrogen Oxides (NOx) as an indicator pollutant The public health effects of nitrogen oxides (NOx) as an indicator pollutant are well known. NOx share common sources and formation routes with other harmful reaction products such as O3 and PM in the atmosphere, as well as yielding NO2. NOx is the generic term for a group of highly reactive gases all of which contain nitrogen and oxygen in varying amounts. For example, it reacts with hydrocarbons in the presence of sunlight to form harmful ozone and photochemical smog. NOx is mostly formed when fuel is burned at high temperatures and many of them are colourless and odourless. Furthermore, nitrogen dioxide (NO2) is one common pollutant with particles that can often be seen as a reddish-brown layer in the air over many urban areas. NOx can also be formed naturally. Sulphur dioxide (SO2) as an indicator pollutant Sulphur dioxide (SO2) is emitted when fuels containing sulphur are combusted. Sulphur dioxide is a pollutant that contributes to acid deposition. As a secondary particulate matter precursor SO2 also contributes to the formation of particulate aerosols in the atmosphere. Particulate matter is an important air pollutant due to its adverse impacts on human health, and SO2 is therefore also indirectly linked to effects on human health. 9.4 Exposed Population The exposed population is the population within the study area that is exposed to the indicators of air pollution (Figure 9-3). This population is affected by the health endpoints associated with the indicator pollutants. The model uses the borders of KwaZamokuhle (main place) in the Nkangala District Municipality as the project boundary. KwaZamokuhle has a population of distributed amongst households (Statssa, 2011). These figures are considered to describe the exposed population. REPORT NO:NWU/2015/Eskom01 178

210 Figure 9-3. KwaZamokuhle is used as the boundary for the exposed population in the preliminary model. KwaZamokuhle falls within the Highveld Priority Area, an airshed that experiences high levels of air pollution. In preceding work streams ambient levels of indicator pollutants were modelled and used for the cost benefits analysis. However, personal exposure to poor air quality is affected very much by indoor air pollution. The Highveld Priority Area Air Quality Management Plan (2011) highlights the impacts of domestic fuel consumption as having a potentially greater impact on exposure in rural and informal settlements. To this end personal exposure is calculated by combining the exposure to ambient and indoor air pollutants Exposure-Response Functions Epidemiology plays an important role on human health endpoints. One of the objectives of epidemiological studies is to assess the effects of inhaled air pollutants on human health. Most of the epidemiological studies have linked air pollution with increased mortality as well as morbidity, such as chronic and acute bronchitis, asthma symptoms, increases in hospital admissions and emergency-room visits, and restricted activity days (Jalaludin et al., 2009). Exposure-response functions estimate the change in a health endpoint of interest for a given change exposure to an indicator pollutants. While many different exposure-response functions for different health endpoints, indicator pollutants and populations exist, the specific functions used in this study are narrowed down according to European Union guidelines on health impact assessments (Figure 9-4) (IEHIAS, 2015). REPORT NO:NWU/2015/Eskom01 179

211 Figure 9-4. Checklist for deriving an exposure-response function (IEHIAS, 2015). Typical exposure-response functions have three requirements: (1) the size of the potentially affected population; (2) the estimated change in the relevant pollutant concentration; (3) a baseline incidence rate for the health effect. The standard format for exposure-response functions are those of Relative Risk (RR). RR is defined as the increase in the probability of occurrence of the adverse effect on health associated with a given change in exposure level (US EPA, 1999), where P1 and P0 are the prevalence of health endpoints at given higher or lower exposure respectively: RR = P 1 P 0 (Eq 9.1) According to WHO guidelines (WHO, 2000) exposure-response functions may be reported as a slope of a regression line with the health response as the dependent variable and the stressor as the independent variable. Alternatively an exposureresponse function may be reported as a relative risk (RR) of a certain health response for a given change in exposure. As such, a relative risk reported for a health outcome in response to exposure to an indicator pollutant can be represented in a simple X-Y graph relating the magnitude of a stressor (concentration of a pollutant) to the response of the receptor (population) (Figure 9-5). REPORT NO:NWU/2015/Eskom01 180

212 Figure 9-5. Relationship between the incidence of health outcomes and exposure to pollutants as described by an exposure-response function (ERF). Where: The y-axis represents the incidence or prevalence of a health outcome/ response The x-axis represents the exposure to the indicator pollutant X0 is the baseline (current) exposure, X1 is the exposure after intervention Y0 is the baseline incidence, Y1 is the incidence after intervention The line ERF is the linear relationship between exposure and response. When annotated as y=mx+c, the slope (m) is the relative risk c is the intercept and represents the background incidence The prevalence of health outcomes was estimated using this methodology, the results of which were used to determine the healthcare cost implications of different interventions (Table 9-1). Table 9-1. Preliminary exposure-response functions for selected health outcomes attributable to PM10 exposure. REPORT NO:NWU/2015/Eskom01 181

213 The results of this exercise were used to estimate the health costs savings due to the interventions Health Costs For the health cost valuation the model follows the costs of illness methodology developed by Rice et al. (1985). The methodology represents the financial burden on society of the morbidity and premature mortality associated with a particular illness (Rice et al., 1985). The cost of illness methodology consists of direct costs, indirect costs, and intangible costs. However, the present study only monetises the direct and indirect costs, with any intangible costs identified being presented in a suitable manner determined by the nature of the costs. Direct costs arise from the health care services used in the prevention, diagnosis and treatment of the disease. For example, acute (short-term) and chronic (longterm) human exposures to fuel combustion products can result in a range of health effects classifiable in the following major categories (FRIDGE 2004): chronic obstructive lung disease (COD) heart diseases cancer, particularly lung and nasopharynx cancer acute respiratory infections low birth weights upper respiratory tract illnesses (URI) and symptoms Such health effects are associated with hospitalisation for respiratory or cardiovascular diseases and exacerbation of respiratory diseases, such as asthma. In order to monetise yearly air pollution related costs, the health endpoint incidence estimates will be applied to health costs obtained from South African Health Review (2007; 2011), commissioned by the Health Systems Trust. Indirect costs are caused by loss of productivity resulting from absenteeism, temporary or permanent disability and premature mortality. Hence, this study only looked at absenteeism resulting from: Days when a person needs to stay in bed Days when a person stays off work but doesn t need to stay in bed Less serious restrictions on normal activity The costs associated with restricted activity days are estimated using employment and production data from preceding work streams. The total health costs per household, saved due to interventions are presented in Table 9-2. Table 9-2. Direct and indirect health cost savings attributable to interventions. REPORT NO:NWU/2015/Eskom01 182

214 The total health costs per household, saved due to interventions were then incorporated into the Social CBA GDP Contributions An input-output model (represented in Table 9-3) (IO) was used to determine the GDP contribution of interventions as it represents all of the flows of all of the economic transactions that take place within an economy. IO s are regularly used as a matrix representation of the National Accounts of a given country. The IO provides information on interactions between production activities (by sectors), factors of production (capital and labour), institutions (households by occupations, local government), capital accounts and the rest of the world (imports, exports). The core components of an IO are arranged in a square as in the highlighted grey section in the figure below. Each row of the IO gives receipts of an account while the column gives the expenditure. An entry in row i and column j represents the receipts of account i from account j. The total of each row is supposed to be equal to the total of each corresponding column. Table 9-3. Basic structure of a input-output model. An IO is able to generate: Total Output: Estimate of the revenue flows within economic sectors identified in the value chain analysis. It generates the change in total output generated by a certain stimulus, e.g. a development project, and is a useful measure for small business development. REPORT NO:NWU/2015/Eskom01 183

215 Gross Domestic Product (GDP): GDP is a measure of all of the goods and services produced by a nation/region within a given year. The Income Approach is utilized in this project which calculates GDP by summing up factor payments including: Compensation of employees Rent and the income of property owners Interest income for supplying capital (borrowing/lending) Proprietors income and corporate profits, the income/profits derived from businesses, paid out to shareholders Economic impacts can be broken down to direct and indirect impacts where: Direct impacts refer to value added by industries which are impacted directly by the intervention, e.g. the building improvements on a house will impact the construction industry directly affecting the industry s total output, value added (GDP) and other economic indicators Indirect impacts refer to the knock-on or spill-over economic impact that is created in all the sectors in the economy, e.g. the construction sector (which was directly affected) will require inputs like cement, water, etc. from a whole array of other industries. Because of this inter relationship the impact in one sector in the economy is not an event in isolation but rather an initial (direct) impact that ripples through the entire economy. All the sectors that are affected in this manner constitute the indirect effect. The total direct and indirect GDP contributions in relationship to the intervention costs are presented in Table 9-4 Table 9-4. GDP impacts of different interventions. 9.5 Job Creation Job creation is an important component of the intervention benefits to society. The impacts of the intervention on job creation were derived from the I-O model results (Table 9-5). This allowed the calculation of: Direct effects: The direct economic or employment impact is the change in economic activity or employment directly related to intervention roll out Indirect effects: Indirect effects are changes in inter-industry purchases in response to the change in demand from the sectors directly affected by the intervention roll out. The indirect economic impact seeks to capture the knockon benefits to the host economy. These indirect impacts, also known as the multiplier effects, include the re-spending within the local economy REPORT NO:NWU/2015/Eskom01 184

216 Induced effects: Induced effects are changes from household spending due to changes in income that are caused by production changes Table 9-5. The impacts of interventions on employment. The direct effect is the increase in employment that arose from the interventions spending in the specific economic sectors (see the direct effect discussion of GDP for an example). The principle idea is that an increase in demand for the various sectors output means that these sectors have to increase their inputs to meet this new output, where inputs include labour. Hence to be able to meet the new demand, employment in these sectors need to increase. The total effect captures the employment that is created through the total economic impact from the intervention; this means the direct effect as well as any indirect effects that the intervention might have caused. Similarly, an increase in economic activity in a sector means an increase in labour demand by that sector and therefore all the sectors that are directly and indirectly affected will demand higher labour which is captured by the total effect on job creation. The total effect minus direct effect is disaggregated to the indirect effects and induced effects to illustrate the impacts as discussed above. 9.6 Greenhouse Gas Emissions The change in greenhouse gas (GHG) emissions attributable to each intervention can be estimated within the integrated model. The model considers the different interventions in relation to the control in terms of GHGs derived from the use of different energy carriers. The model utilizes emission factors per energy carrier (fuel type) from international and national standards. The broad methodology is presented in Figure 9-6. REPORT NO:NWU/2015/Eskom01 185

217 Figure 9-6. Greenhouse Gas Reduction Benefits Model. Data collected during the household survey was used to generate average fuel consumption per household and the impacts of the interventions (Table 9-6). Table 9-6. The GHG emission reductions are reported on in terms of carbon dioxide equivalents (CO2e). The change in GHG emissions is also monetized in the social cost benefit analysis (Section 7) using carbon pricing proposed by the South African Revenue Services, amongst others. 9.7 Social Cost Benefit Analysis The World Bank defines a Social CBA as an extension of a financial analysis. In extending the financial analysis all relevant economic costs and benefits are quantified and analysed. The CBA pulls together the component analyses of the study to assess the overall impact for a set of scenario options. The objective of the CBA is to determine whether a particular investment, amongst a suite of possible investments, is the best use of available resources. The CBA achieves this end by identifying and monetizing every direct impact and predicting the timing thereof over the same horizon as the projects economic lifetime (National Treasury, 2013). REPORT NO:NWU/2015/Eskom01 186

218 The National Treasury stipulates the categories of consideration that are a required as a precursor to capital projects. The guidelines state that while every project must address all the elements, the detail and rigor applied at a particular stage will be dependent upon the size and complexity of the project. This systematic process of consideration is necessary to identify the specific impacts to be subjected to analysis in the CBA. A value chain was developed to segment and analyse, in technical and financial details, all aspects of the project (Table 9-7). It includes an analysis of the supply chain, the implementation requirements and the externalities associated with the value chain. The key externalities are health impacts and carbon emissions. In this step we used the integrated model which quantifies in physical terms the project components and impacts in their forward and backward linkages and externalities. Table 9-7. Value chain identifying the different sectors affected by intervention scenarios. In the preceding methodological steps, the different impacts from interventions, direct and indirect, were quantified. However, the nature of the parameters investigated were not directly comparable especially considering that the interventions have different implementation costs. In order to provide Eskom with an objective measure of the different interventions a Social CBA was incorporated into the integrated model to allow direct comparison. The Social CBA allows intervention scenarios to be compared according to: Health Impacts and Health Costs Job Creation GDP Contribution Greenhouse Gas Emissions A summary of these results are presented in Table 9-8. Table 9-8. The benefits to cost ratio of the different interventions. REPORT NO:NWU/2015/Eskom01 187

219 Due to the preliminary nature of these results, no recommendations on the suitability of each intervention can be made. 9.8 Way Forward The first deliverable reported on Work Stream 8: Macro-economic impact assessment and social cost benefit analysis progress as of October 2014, and served as an Inception Report and description of the Integrated Economic Model architecture for the Eskom Offset Pilot Project. The report served as a description of linkages to and dependencies upon the preceding work streams, a review of international best practice in cost benefit analysis and description of the methodology to be employed to meet the outputs of this work stream. The second deliverable submitted in February 2015 was a preliminary model that demonstrated the application of the proposed study. The third deliverable is the current preliminary final report and incorporates some of the outstanding data with the refined model to report on the following effects of the interventions: Health impacts and health costs Job creation GDP contribution Greenhouse gas emissions The interventions are compared to each other and the baseline in the Social Cost Benefits Analysis. Due to the preliminary nature of these results, no recommendations on the suitability of each intervention can be made. This report and the model it reports on will be updated as further information is made available. REPORT NO:NWU/2015/Eskom01 188

220 CHAPTER 10. ASSESSMENT OF THE FEASIBILITY OF THE INTERVENTIONS 10.1 Introduction People need to eat, to stay thermally comfortable, to be clean, to communicate and to relax. All these human needs can only be actualised if people have energy. The energy mix of every household is a combination of choice, capability, access, availability and affordability. Choices are influenced by world view as well as by pragmatic decisions, for example to quickly finish a task. Capabilities can be inherently there but if people lack the knowledge about the advantages or applications of a certain clean energy technology, they will not use it. Furthermore it is only possible to sustainably use for example an LPG stove if it is accessible, available and affordable. Domestic air pollution has to be interpreted against this background: while poverty impairs the choices, capabilities, access, availability and affordability of clean energy options it does not remove the essential requirements people have to cook their food, to warm their homes, to bath and clean the household environment, to reload their mobile phones and to listen to music or watch television. Thus, several factors could be considered as drivers for domestic pollution and poverty has to be singled out as the largest single factor Objectives The large scale roll-out of interventions should only proceed once the feasibility of the interventions has been demonstrated. The objective of activity 9 is to evaluate the feasibility of the pilot interventions by assessing: Potential improvement in air quality Emission reduction capacity Quality of life and economic impacts Desirability to end-users Air quality impact of interventions when implemented on largescale The pilot project results make it possible to: Rate the different interventions and identify the most suitable option for large scale implementation Estimate the impact of the interventions when implemented on a largescale 10.3 Rating the different interventions During the pre-feasibility study preceding this pilot study, the Analytic Hierarchy Process (AHP) was used in consultation with a broad group of relevant stakeholders to determine criteria to apply when evaluating the suitability of offset interventions. Potential emission offsets projects were evaluated based on the following criteria: REPORT NO:NWU/2015/Eskom01 189

221 Reduced human exposure to ambient PM10 Reduced human exposure to ambient SO2 Cost attractiveness of intervention Success probability of intervention Government and Eskom Board acceptance of intervention Sustainability of intervention Household acceptance of intervention Indirect impact of implementation (long & short term) Household acceptance of the proposed offset projects was identified as the most important criterion that would determine the success of the offset projects, followed by acceptance by licencing authorities and the Eskom Board (Figure 10-1 and REPORT NO:NWU/2015/Eskom01 190

222 Table 10-1). Figure Weighting of the criteria used to evaluate proposed offset (relative % weight on y axis per criterion). REPORT NO:NWU/2015/Eskom01 191

223 Table Stakeholder acceptance figures. The ranking of the tested interventions in terms of their suitability for community offset programme implementation are - starting from the most to the least suitable: 1. Full LPG (30.5%) 2. Basic LPG (22.6%) 3. Full Kitchen King (15.1%) 4. Full Electricity (13.5%) 5. Basic Kitchen King (11.6%) 6. Basic Electricity (6.7%) The ranking of the tested interventions can be illustrated in the summary comparison shown in Figure 10-2 and Table REPORT NO:NWU/2015/Eskom01 192

224 Figure Table Ranking in order of suitability for air quality offset implementation. Consistency REPORT NO:NWU/2015/Eskom01 193

225 10.4 User Desirability Introduction The aim of this section of the report is to give an interpretation of the way in which 37 RDP households in Kwazamokuhle have experience the impact of a number of specific interventions in their domestic energy usage patterns, based on individual interviews with end-users. A Control group of 12 households, who received no interventions, also took part in the project to help determine a baseline. This report does not provide quantitative measurements. The focus is on the desirability of each intervention as evaluated by the users, in order to be able to determine which interventions residents would use and maintain. Most residents use an energy mix of burning solid fuels and using electric appliances. In this project, two additional variables were added: domestic energy efficiency in the form of insulation, and LPG. These variables make new energy mixes possible, and this report is part of a process to determine, with households, what the best energy mixes are for different types of households. The following houses, with different types of interventions, were interviewed: Full retrofit with electricity: 6 Basic retrofit with electricity: 6 Full retrofit with Kitchen King: 6 Basic retrofit with Kitchen King: 6 Full retrofit with LPG: 6 Basic retrofit with LPG: 7 Control group: 12 The Control Group received no interventions. This group gives an indication of the way residents experienced the situation before the interventions were implemented. This picture is made more complete when residents of the households where the interventions have been implemented compare their present experiences with the way it was before Experience of life of low-income households in KwaZamokuhle The descriptions of daily life of the Control group are clearly different from those of the houses with interventions. The interventions have made a marked difference. Most people seem quite happy, they do not complain much and they do not feel very insecure or afraid. However, some experience severe cold, so that they may not allow their children to get out of bed until 9 am, or they may not be able to continue normal tasks in the house. The heat can make people lazy or even dizzy, and houses get dirty because of smoke and dust. To keep warm they have to burn a lot of coal that they can ill afford, but sometimes there is not enough money for that. One gets an impression of how tough life is for some if you note that people REPORT NO:NWU/2015/Eskom01 194

226 would buy electricity in quantities as small as R10 or R20, or that people have to go to bed because they cannot afford to heat the house. Most answers indicate that people understand what air pollution is, and that it is harmful to them. It is important to take note of a variety of perceptions on air pollution when efforts are made to educate residents about air pollution, or to involve them in combating air pollution and maintaining the interventions that were made. In Kwazamokuhle, which is far from a big industry, no sources external to the community are mentioned, but several sources inside the community are mentioned. Apart from the smoke from the households that burn coal and wood, a variety of other materials are mentioned: the burning of shoes was mentioned at least five times, other substances include plastics ( there are other types of plastics that produce smoke that chokes ), bones, tires, cow dung, oil (if you light and you add oil, you could smell the oil. And the oil affects our lungs), dirt, old clothes, cars, diesel and garbage. There is a general feeling of powerlessness, of being unable to improve or extend your house. However, a relatively large group that are unable to improve their house in a more substantial way feel they can fix smaller things in the house. This may be important for involving residents in maintaining the interventions in future. The residents who received interventions do not show the same level of powerlessness as the Control group,, which means that the interventions did increase peoples feeling that they can do something to improve their own conditions. This seems to be primarily an external influence rather than an internal change, or in other words, a change in attitude that is caused by something being done for you rather than something being done by you, an external rather than an internal source of motivation. The social impact of the interventions is important: neighbours and friends make positive remarks on residents houses, and relations in the family can also improve, e.g.: The intervention has changed the way we socialise as a family. We stay together most of the time, especially when it is cold. Before, when it was cold, everyone would go to their own bedrooms, but now we can sit together and chat. One of the implications for such an external source of motivation is that it must be kept alive by some community programme, rather than to depend on each individual s own initiative and motivation. Possible ways of involving communities must be considered Some usage patterns Artefacts must become part of a usage pattern, before it can be used in households. Two usage patterns are considered in this section. The impact on the way people bath The standard way of bathing is to warm up the water with a kettle, two per person, and to bath in a dish twice a day (one said only twice a day). If people have better sources of heat they may bath in more water. REPORT NO:NWU/2015/Eskom01 195

227 The interventions have made a huge difference to the way people bath, in two ways: Many people describe how difficult it was to bath when the house was very cold; they often had to keep some of their clothes on while washing themselves. The insulation has provided a warmer interior, so that they can bath comfortably. That is one improvement in the quality of life of residents that generated many comments, such as: It was cold in that other room where we bath during winter but now after there is a ceiling, it is warm, you can feel that it is warm. It does make me happy, like now I just boil water so I don t make fire, it is too warm and there is a huge difference The boiler of the Kitchen King stove makes it possible to have enough warm water. After bathing, the water is mostly thrown in the toilet. Women bath more than men. One said: Because I am a man, I bath once. Another said: I am only bathing when I am around, I don t know about these children, the girls bath a lot The choice of an energy carrier The choice of an energy carrier(s) is the function of a combination of factors, such as: Cost and functionality have to do with pragmatic behaviour. It mostly has to do with the fact that, when it is cold, a coal stove can provide space heating and warm water while it cooks the food. Electricity, on the other hand, is more functional when time is of the essence, and it can be used with many different appliances Identity and preferred lifestyle patterns have to do with what people want. If cost and functionality were not an issue, the energy mix would be determined by identity and preferred lifestyle patterns. Coal is associated with a more traditional identity, e.g. of a grandmother at home, with the children around, the whole family together in the warmth of the kitchen with traditional food that cooks slowly. Electricity is associated with a more modern identity, where you have to eat something quickly before going off to work and where you want to relax before the TV when you come home. Hardly any household exhibits one of these identities in a pure form. That is, almost every household has some combination of these two All these factors combine in different ways to produce different energy mixes. The prevailing pattern has been some combination of coal and electricity, since one energy carrier alone does not serve all purposes. The result is mostly an imperfect match. This can be improved by adding more variables (in this case: domestic energy efficiency in the form of insulation, and LPG) and a proper consultation process with residents Results of the interventions Since all interventions were made in combination with others, the impact of a specific intervention on the thermal efficiency of the house has mostly to be REPORT NO:NWU/2015/Eskom01 196

228 determined by indirect evidence. That is difficult to do in this project, because of the positive impact of the ceiling that was implemented in all the households, excluding the Control group. Some impacts are not significantly influenced by the combination of interventions. The following trends have been observed from the qualitative interviews: There is a marked improvement in the way residents who received an intervention experienced their homes, if compared with those in the Control group who received none The electricity subsidy means more cash in peoples pockets, but it does not bring about a substantial shift away from coal to electricity The usage pattern, that you use only electricity when it is hot, but light the coal stove when it is cold, was found in all five groups that had a coal stove: before we were forced to make fire not because we wanted to cook, but to make the house warm. But now we can just stay without making fire Electricity is seen as unreliable, so that another energy carrier to fall back on, such as coal or LPG, is often required The ceiling is the one intervention that makes the biggest difference over a wide front: it not only improves the thermal conditions in the house during hot and cold weather, it also keeps dust, smoke and rats out, it decreases noise and it makes the house beautiful All houses have received a ceiling, half with wall cladding and half without it. There is not a marked contrast between the experiences of these two groups The ceiling makes such an impact that it overshadows the other interventions from a resident perception point of view. Residents tend to ascribe the improvement in indoor thermal conditions to the ceiling rather than to the wall cladding While the Kitchen King has brought many improvements, some adjustments to its design are recommended. The critical question is how long it will take before it also becomes old and begins to show the same dysfunctionality as the stoves that were replaced The LPG stove, and to some extend the LPG heater, is experienced in a very positive way, although LPG is seen as dangerous, and some adjustments to the design of the stove are recommended. It is, for example, seen as too weak to take a full load, and the oven is not functioning well Houses with roofs that are leaking may become a major problem for the long term sustainability of ceilings The gas stove, more than the electric stove, has the tendency to heat up the house, so that people may switch from gas to electricity when it is hot: When you light the gas stove it gets warmer so if we light the gas stove when it is hot, it becomes hotter, so that is why we use the electricity stove and we become all right REPORT NO:NWU/2015/Eskom01 197

229 10.6 The way forward It is important to involve the community as far as possible. The improvements will only be sustainable if the residents take ownership of the improvements and sustain it themselves. This project has shown that a combination of insulation (either basic or full insulation) and an LPG stove and heater may make it possible that a good majority of people may move away from coal completely. That would require attention to a number of essential success factors: A better design of the LPG stove Proper training in the safe use of LPG Ensuring that LPG is always available Creating a community movement or trend, where the improvements that are introduced from outside the community are continued in a communal process that would motivate and involve people to be active in improving their quality of life even beyond the use of energy. Such a communal movement is important for maintaining the improvements in air quality NOTE: The feeling of many is well expressed by this remark: It has changed. It is now warm. Before it was cold, then they installed that thing and now it is warm. Ai, it became nice, it became a home Estimating the impact of the interventions on a largescale Solid fuel use reduction The solid fuel reduction that can be brought about by each intervention is the product of the average reduction in solid fuel and the number of households who are expected to eventually take up the intervention. It is also useful to express the reduction in solid fuel use as a fraction of the total solid fuel use. In combination with results of the source apportionment this yields an estimate of the fraction of the total air pollution problem that can be addressed with a specific intervention. The baseline coal consumption per town was estimated from the household survey results. Because there are a number of variables, it is best to present this as a range of possibilities. Bootstrapping was used to achieve such an estimate as Monte Carlo simulation is not suited to modelling dependent variables. The mean, standard deviations and densities are shown in Table 10-3 and Figure Table Results of bootstrapped estimate of winter coal use per month (in tonnes). Emaskopasini Kwazamokuhle SP Manfred Maphela Tycoon All Mean 114 t 726 t 111 t 78 t 170 t 1198 t Std. dev 11 t 28 t 12 t 9 t 16 t 38t REPORT NO:NWU/2015/Eskom01 198

230 Figure Density of the estimation of total fuel use in kg based on a bootstrapping sample of The most reliable of all the methods for estimating the mass of coal used in each intervention group is the fire classification from chimney temperature readings that has been calibrated with the fuel use per fire cycle from the coal logs. Data for winter months are availible and is shown below in Table 10-4 and Table 10-5 for coal and wood respectively. Some assumptions will have to be made for the summer months. Table Monthly winter coal consumption per intervention type. Winter monthly coal use per type (kg) Energy carrier Insulation type Mean Improved coal stove Full Improved coal stove Basic Control None Electricity subsidy Full Electricity subsidy Basic LPG Full 0 LPG Basic 0 Table Monthly wood use per intervention type Winter monthly wood use per type (kg) Energy carrier Insulation type Mean Improved coal stove Full 22,04 Improved coal stove Basic 29,45 Control None 36,04 Electricity subsidy Full 41,25 Electricity subsidy Basic 43,45 LPG Full 0 LPG Basic 0 REPORT NO:NWU/2015/Eskom01 199

231 Eligible households The number of eligible households is estimated from the results of the household survey (Table 10-6, Table 10-7 and Table 10-8). Table Estimate of the number of formal and informal structures per subplace with upper and lower bound of the 95% confidence interval per sub-place. Subplace House type PointEst Lower Upper Emaskopasini Formal Informal Kwazamokuhle SP Formal Informal Manfred Formal Informal Maphela Formal Informal Tycoon Formal Informal Table Estimate of number of households who use coal for heating with upper and lower bound of the 95% confidence interval per subplace. Subplace Coal use for heating PointEst Lower Upper Emaskopasini No Kwazamokuhle SP Yes No Yes Manfred No Yes Maphela No Yes Tycoon No Yes REPORT NO:NWU/2015/Eskom01 200

232 Table Estimate of the number of RDP houses per subplace with the upper and lower bound of the 95% confidence interval per sub-place. Subplace RDP PointEst Lower Upper Emaskopasini Not RDP RDP Kwazamokuhle SP Not RDP RDP Manfred Not RDP RDP Maphela Not RDP RDP Tycoon Not RDP RDP In the whole of Kwazamokuhle, there are an estimated 3035 households (aggregated 95% confidence interval between 2577 and 3489) who use fuel and have an RDP house. The breakdown per sub-place is shown in Table Number of solid fuel users among RDP house owners in KwaZamokuhle. Subplace Fuel use and house PointEst Lower Upper Emaskopasini Use fuel, has RDP Kwazamokuhle SP Use fuel, has RDP Manfred Use fuel, has RDP Maphela Use fuel, has RDP Tycoon Use fuel, has RDP Evaluation of interventions No intervention In the no intervention scenario, current solid fuel use trends are expected to continue or even increase due to increasing electricity prices Basic retrofit and electricity With current results, the implementation of the electricity subsidy is expected to lead to an increase in solid fuel consumption, likely due to the income effect of the subsidy. This disqualifies the basic retrofit and electricity subsidy as a viable intervention. Exact quantification of the increase in solid fuels is of little practical use Full retrofit and electricity Just as with the basic retrofit and electricity subsidy, the full retrofit and electricity subsidy is expected to lead to an increase in solid fuel consumption although the REPORT NO:NWU/2015/Eskom01 201

233 increase is expected to be smaller than that due to the basic retrofit and electricity subsidy Basic retrofit and Kitchen King The mechanism through which the two improved stove interventions are expected to work is not necessarily a reduction in fuel consumption but more complete combustion of the fuel and therefore a lower emission factor for particulate matter, i.e. less smoke. The mean monthly coal consumption for a winter month of kg/month and the wood consumption of kg/month are nominally but not significantly lower than that of the control group. The total volume of solid fuel burned in the town after a large scale implementation of the improved stove will therefore likely be the same for all practical purposes but the air quality may improve depending on the improvement in the emission factor. Over time the improvement in the emission factor could decrease as wear and tear of the stove takes place Full retrofit and Kitchen King As in the case of the electricity subsidy, the mean fuel consumption for the basic retrofit and Kitchen king is slightly higher that that of the same stove combined with the full retrofit. Once again, the apparent slight decrease in coal use may be of little practical significance compared to the expected improvement in the emission factor Basic retrofit and LPG In contrast to electricity subsidy and the improved stove, the reduction in solid fuel use due to the use of LPG is dramatic because the coal stove is exchanged for an LPG stove. At least initially, solid fuel use drops to zero. This makes the LPG interventions very attractive. Two uncertainties remain in terms of the long term effect if this intervention is taken to scale, namely what the uptake of the offer to exchange a coal stove for LPG and an insulation retrofit will be, and what the rate of fallback to solid fuel will be. A key question in this regard will be the applicability of the intevention in informal houses, since households living in informal houses make up a large part of the coal using population Full retrofit and LPG From the experience during the pilot, the rate of uptake does not differ between the basic retrofit with LPG and the full retrofit with LPG. One may however expect a lower fallback rate because of the better thermal performance of the full retrofit. Because coal use drops to zero initially, the expected proportion of solid fuel to be saved is simply the uptake proportion of the intervention. If an uptake of 70% of eligible users is assumed and the intevention is offered to every RDP owner who use coal (of whom there are an estimated 3035), then approximalty 2124 households out of the appriximately 4714 coal using households in Kwazamokuhle (i.e. ~45%) will at least initially stop using coal. One expects the pollution attributible to domestic coal use to decrease by the same proportion. AIT range improvement REPORT NO:NWU/2015/Eskom01 202

234 All the interventions improve indoor temperature but the improvement of indoor temperature and the time that people spend in an acceptable indoor temperature range, are greater for the full retrofit compared to the basic retrofit. In the control group, indoor temperatures were below 10 degrees for more than 25% of the time during which indoor temperature was measured. The full retrofit narrows the temperature range and effectively eliminates very low temperatures (Figure 10-4). Figure Indoor temperature by intervention typoe as measured at Kwazamakhule Energy poverty alleviation Of all measures, the full retrofit makes the greatest contribution to curbing energy poverty because it provides a high level of utility (prevention of extreme cold temperatures) sustainably at basically zero cost to the end user Notes on poverty and sustainability A reduction in air pollution will only be sustainable if it removes or replaces the current usage patterns causing pollution. If it introduces new patterns that do not take into consideration the choices and capabilities of households, as well as the accessibility, availability and affordability to households, it will not be sustainable. The poverty gap in these communities taken together is currently R That means R. is needed annually to get these communities to the target that the South African Government set themselves in the National Development Plan for This state of affairs means that the underlying drivers of domestic air pollution will not disappear spontaneously. Furthermore, if an intervention does not sustainably impact on energy poverty, people will revert back to unsustainable practices the moment there is a change in circumstances that makes it more affordable to REPORT NO:NWU/2015/Eskom01 203