The health and economic benefits of interventions to reduce residential solid fuel burning on the Highveld

MSc (Geography and Environmental Management), North-West University, Potchefstroom CampusDue to its complicated history, South Africa faces air quality problems associated with both developed and developing countries. On the one hand, industrial activities and high numbers of private vehicle ownership are significant sources of emissions, whilst on the other, solid fuel burning by large numbers of the population and a strong agricultural sector also contribute significantly to air quality problems. This complex mix of sources pose a challenge for air quality management (AQM) in South Africa. The legacy of apartheid policies that created extreme inequality and inequity for over four decades still affects all aspects of South African society, including public health. The environments and quality of housing where people live is one of the strongest determinants of public health. Despite efforts by government, many residents of low-income settlements are still living in conditions of extreme poverty, with less access to quality basic services like healthcare, sanitation, electricity and education. These households often cannot afford to use electricity as their only energy source and supplement their energy needs by burning solid fuels for cooking and/or heating purposes. Low socio-economic status also increases vulnerability to the adverse health impacts of air pollution. In many parts of the developing world, including South Africa, residential solid fuel burning is widespread enough to contribute significantly to ambient air pollution levels and can have impacts on health far from the original source. The Department of Environmental Affairs’ recently published air quality offset guidelines mention residential solid fuel burning as a source that could be addressed in offset programmes. Several community scale pilot offset programmes have been implemented in densely populated low-income areas on the Highveld, but quantifying their true impact remains a challenge. More information is needed in order to identify the most suitable interventions for large-scale roll-out in the area. A need thus exists to quantify the impact of individual pilot offset projects on a larger scale. Health impact Assessment (HIA) could be a useful tool to quantify the health and associated economic benefits of air pollution interventions and provide a more comprehensive understanding of their true impact. This study takes a predictive approach, as it aims to assess the future health impact of a specific intervention measure. This approach required making assumptions about future trends involving the study population, health outcomes, the time required to achieve decrease pollutant levels as well when health outcomes will occur. These assumptions introduce uncertainties in any HIA. Air quality data from monitoring stations in the study area were used to quantify the spatial variation of average annual PM2.5 concentrations by using the enumeration area (EA) dataset of the 2011 census. This scale of analysis was chosen to better represent the high spatial variability of factors that influence pollution concentrations and exposure to household emissions in densely populated low-income communities. In order to most accurately represent the context of this study, the findings from a pilot air quality offset programme implemented at the community scale was used as the control scenario. To create the post-intervention air quality dataset, the control value (a 4 μgm3 reduction in mean PM2.5) was applied to EAs where more than 10% of households reported using dirty fuels as an energy source and the HIA was conducted in only these identified communities. This approach was aimed at reducing uncertainty by using spatially refined estimates of site specific air quality, population and mortality data for each EA. The economic value of avoided mortality estimates was calculated by applying the value of a statistical life calculated for South Africa as valuation measure. Results were aggregated at the local municipality level for easier reporting. Our analysis estimated that the modelled improvements in air quality over the Highveld could avoid 143 premature mortalities over 20 years, with an associated economic benefit of ZAR (2011) 371.4 million. Even though existing models use significant assumptions to link air quality with health outcomes, these results could provide valuable insight into the true impact of improved air quality in low-income settlements on the Highveld. Attaching a monetary value to improved health outcomes could further inform decision making regarding the suitability of this offset for the private sector and government alike, despite the limitations involved in the calculation of cost estimates.Master