Using dispersion models as a regulatory tool in South Africa

Abstract

Assessment of exposure to air pollution within densely populated low-income townships (intra-urban) is a priority area for research, due to urban air-sheds being heterogeneous with concentrations varying significantly temporally and spatially. Often assessment of exposure in developing countries is limited to sparse measurements due to costs associated with setting up monitoring networks. Therefore, the application of dispersion models can improve the accuracy of assessments which can advance understanding of the exposure at the receptors and enhances the evaluation. Until 2014, dispersion modelling practices in South Africa have been operating in the absence of a standardised regulatory approach leaving room for inconsistencies in assessment studies. Until now, the Code of Practice has uncertainties regarding modelling intra-urban environments. Therefore, a need exists to provide an assessment of the application of dispersion models in South African intra-urban environments. This research aims to evaluate the use of dispersion models as regulatory tools in modelling emissions within low-income settlements to better understand the contributions of local sources in intra-urban environments. To realise the aim, the study will identify, characterise and estimate emissions from local sources within Zamdela and Wedela (South Africa), evaluate the impact of the identified sources on ambient air of the townships using dispersion modelling, and evaluate the performance of the model against monitored particulates. Solid fuel burning, waste burning, fugitive dust, vehicle emissions and biomass burning were identified as potential sources within the study areas. These sources are usually overlooked yet their impact is immediate as they are at the breathing level. Emissions from sources were estimated using the product of emission factors and activity rates and it was observed that fugitive dust contribution is significant, yet usually ignored in research due to their complexities. The type of fuel used is mainly dependant on the quality of life and accessibility as shown by the difference in energy use between Zamdela and Wedela, hence the impact of solid fuel-burning is mostly endured by the poor. Vehicles also showed significant contribution followed by biomass burning then waste combustion. AERMOD was run for 2018 to 2020 as this period aligned with the measured data. PM2.5 and PM10 were modelled, and the results were compared against measured data from sites within the townships for validation purposes. Maximum concentrations over Zamdela were predicted in the core of the township while Wedela projected highs in areas downwind of the mine tailings. Monitored and modelled data compared relatively well temporally and spatially, suggesting that the modelled sources are possibly the major contributors to the measured data. Therefore, it can be concluded that with proper inputs and procedures dispersion modelling can aid as a regulatory tool in managing air quality.