An investigation of the imbalance of a fast-growing consumer culture and insufficient waste management infrastructure across a number of sub-Saharan Africa cities
Africa is developing at a fast pace in the 21st century and this is accompanied by continuing urbanization. The economic growth rate, measured in terms of growth in gross domestic product (GDP), has been of the order of 4-5% p.a. for much of the past decade, well above the global average. With these increases in economic wealth and urbanization, people are becoming more affluent and demanding more consumer goods. This implies not just growth in the volumes of materials entering and leaving cities, but also a qualitative shift in what is increasingly called ‘the metabolism’ of the cities where this consumption is taking place, a trend expressing itself by a shift in provisioning from the traditional market to the supermarket. It stands to reason that with these changes in consumption comes an increase in the quantity and variety of waste generated. Past studies already show under-capacity waste management infrastructure and insufficient investment in urban waste management in Africa. The objectives of this dissertation are to 1) Develop and present models of the food material flow profile for a traditional market and supermarket consumer from production to disposal and develop waste flow profiles for both the traditional market and supermarket consumer; 2) Analyse the effect of change in food provisioning on the waste generated ; and 3) Describe the impact of this effect given the current waste management capacity and structure in African cities. To better inform waste management planning in African cities undergoing such a metabolic transition, metabolic flow models have been developed to describe the acquisition of food from a traditional market vs. a supermarket. Consumer food flows are formulated based on cultural profiling and quantified via the daily nutritional and energy requirements of a healthy person. The associated waste profiles of these food items are then obtained by reading from packaging and processing data sets.
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