Is our evidence contaminated? Tracing the ways in which proof is validated in the context of Cape Town's marine effluent outfalls - Zackon, Melissa Amy (Department of Medicine, 2021)
The effects on seawater quality from Cape Town's marine outfalls and their use for sewage disposal has been a concern for local residents for over a century. This dissertation explores the production of scientific evidence that contrasts public experience and independent science. Beginning with the 2015 application by the City of Cape Town (CoCT) for a permit renewal to continue discharging 38 million cubic meters of sewage daily off the city's Atlantic coast, the study considers the arguments of concerned citizens, photographers and independent scientists who warned that the outfalls are responsible for poor seawater quality. This dissertation begins by tracing the contemporary experiences of concerned citizens as they discovered that the outfall was polluting the ocean and then considers the evidence utilised by the CoCT in their responses to these concerns and in their permit application. The study finds that the CoCT's commissioned CSIR report and the use of tourism-orientated Blue Flag criteria are not compatible with the public interest and independent findings, and further finds that a managerialist approach to scientific data has confused the fulfilment of departmental mandates with the public interest, though they are not the same thing. Through the signing of international treaties, its constitution and various legislations, South Africa prescribes to the precautionary principle, but the author argues that this principle has not been applied in this scenario and that retrospective attitudes towards beach management and seawater quality concerns have been applied instead. Consequently, the implementation of a proactive and forward-looking procedure is recommended, and transparency, ocean modelling and the precautionary principle should be applied to the management of Cape Town's marine outfalls and to concerns over its water quality and attendant data.