Quantifying changes in litter loads in urban stormwater run-off from Cape Town, South Africa, over the last two decades

To implement effective mitigation measures to stop the flow of litter from land-based sources into the sea, it is important to identify key pollution sources and to monitor litter trends over time. We sampled plastic and other anthropogenic debris in urban stormwater run-off in Cape Town, South Africa, from three catchment areas representing different land-use types: residential, industrial and a mixed commercial/residential area. Sampling was conducted in 2018–19 by placing nets over stormwater outlets during rain events. Organic matter constituted 79% of material by dry mass (industrial: 51 ± 22%, commercial/residential: 86 ± 4%, residential: 88 ± 13%). The nets caught 5–576 anthropogenic litter items·ha−1·day−1 (2–377 g·ha−1·day−1) with significantly higher densities in the industrial and commercial/residential areas than the residential area. Among anthropogenic litter items, 40–78% were made of plastic (52–64% by mass). Most plastic items were single-use packaging, but industrial pellets washed out of the industrial outlet during every rain event. Compared to a similar study conducted in 1996, the number of litter items decreased by ~20% in the industrial and residential areas but tripled in the commercial/residential area. The proportion of plastics in the litter stream was broadly similar to 1996. We extrapolate that some 60–570 t of plastic are released from Cape Town stormwater outlets annually, which is orders of magnitude less than predicted by global models. It is nevertheless clear that stormwater outlets are a significant source of litter into the sea. Intercepting this waste before it reaches the sea would greatly reduce litter loads in coastal waters around Cape Town. [Display omitted] •Litter loads highest in industrial and mixed commercial/residential catchments•Most common types of litter were single-use plastic and cigarette butts•Industrial pellets found in the industrial catchment during every rain event•Estimated output is 1–2 orders of magnitude lower than global model predictions