Evaluating Enforcement Strategies for Curbing Illegal Waste Dumping: A Case Study of King Sabata Dalindyebo Local Municipality, South Africa

Abstract

Illegal dumping of waste can be classified as a considerable risk to the sustainability of the environment and the well-being of the people in the urban local area, including the King Sabata Dalindyebo Municipality (KSDM) in South Africa. In spite of the intervention of regulatory regimes to alleviate this, cases of illegal dumping still occur, wherein low-income neighborhoods are over-represented. The current mixed-methods study evaluates the success of the use of municipal interventions to reduce the incidence of illegal dumping within the KSDM communities. A multi-dimensional approach, which consisted of a set of semi-structured interviews with the municipality officials and community representatives, as well as closed-ended questionnaires used to examine 80 selected residential citizens in four localities, was applied. The results of the SPSS analysis based on quantitative data provided a descriptive statistic of community perceptions, and the thematic analysis of qualitative responses allowed producing the categories of their descriptive characteristics. The ArcGIS mapping and proximity analysis were deployed to rate the spatial location of the dumping sites; bins known as skipper and notice boards. The results obtained show that enforcement methods are significantly effective in areas with high incomes, Southridge and Southernwood, where compliance with waste-management rules is consistent and, in these regions, the municipal waste services are not disrupted. In comparison, the lower-income regions, especially Mandela Park and Ngangelizwe have limited resources which inhibit compliance and further frustrate dumping. The research concludes that the current regulatory responses are likely to focus on symptomatic, rather than structural causes of illegal dumping, and therefore make long-term effectiveness a challenge. In this respect, a more combined resource-sensitive model is advised to enhance enforcement across the socio-economic lines.