Solid waste management and selection of a solid waste disposal site in the Mankweng Cluster, Polokwane Local Municipality, South Africa

Abstract

Solid waste management (SWM) has become a major concern due to its rapid generation rate, especially in developing countries. It is projected that the quantity of waste generated will keep on rising with an increase in population. The solid waste (SW) generation rate is relatively influenced by various factors associated with population growth, urbanisation, and economic growth. This includes South Africa as most of its big cities are experiencing intense poor waste management (WM) and lack of landfill space. Therefore, accurate planning of a region's SWM system requires knowledge of the waste quantity, generation rate, and composition. Most studies on SWM have been focused on big cities whilst neglecting rural towns and villages, thus creating information and knowledge gap. Consequently, this current study aims to investigate the management of SW in the Mankweng cluster and find a potentially suitable area for a solid waste disposal site. The objectives of the study were to (i) to evaluate household solid waste management practices and perceptions, (ii) forecast the municipal solid waste generation and (iii) identify a potentially suitable landfill site using a Geographic Information System (GIS) and Analytical Hierarchy Process (AHP) in Mankweng Cluster. The study adopted a mixed-method approach whereby both qualitative and quantitative methods were explored. A total of 240 households in ward 25 (urban) and ward 27 (rural) participated in this study. The data was collected using semi-structured questionnaires, field observations, and waste-weighing measurements. Furthermore, complementary data was obtained from secondary data sources such as government documents, and internet sources for forecasting and identification of a location for a suitable landfill site. Qualitative data was analysed using the thematic approach and quantitative data was analysed using statistical methods such as descriptive statistics, correlation, regression (i.e., forecasting) and GIS-based AHP. The results of the study show that majority of the SW produced was organic food waste (53% and 61%) based on their weight in ward 25 and ward 27, respectively. An estimated SW generation rate of 0.27kg/cap/day and 0.13kg/cap/day was observed for ward 25 and ward 27, respectively. Respondents from both wards indicated that improper WM practices lead to, amongst to other things, illegal dumping. Furthermore, the respondents stated that illegal dumping occurs because of ignorance, lack of knowledge and unavailable waste collection services. They recommended that the municipality should build recycling facilities, install disposal bins on hotspots for illegal dumping, and promote good SWM practices. The results further showed that the multiple linear regression model used for forecasting waste generation rate in Polokwane Local Municipality yielded coefficient of determination (R2) of 0.88, with RMSE of 50690.2 ton/year and P<0.000. The model was significant (P≤0.05) and was then used to forecast future solid waste generation rate. The model showed that in future the amount of municipal SW is set to increase leading to the need for construction of a new landfill. In addition, the results for site selection for a new landfill estimated that roughly 67% of the area in Mankweng cluster is suitable for the construction of a disposal site. However, the outcome of the study demonstrated the effectiveness of integrating GIS-based multicriteria decision analysis and community perceptions in the selection of suitable landfill site. In conclusion the study emphasises the value of waste separation, collection, recycling, and awareness in achieving a sustainable SWM.