Abstract
Data sourcing challenges in African nations have led many African urban infrastructure developments to be implemented with minimal scientific backing to support their success. In some cases this may directly impact a city’s ability to reach service delivery, economic growth and human development goals, let alone the city’s ability to protect ecosystem services upon which it relies. As an attempt to fill this gap, this paper describes an exploratory process used to determine city-level demographic, economic and resource flow data for African nations. The approach makes use of scaling and clustering techniques to form acceptable and utilizable representations of selected African cities. Variables that may serve as the strongest predictors for resource consumption intensity in African nations and cities were explored, in particular, the aspects of the Koppen Climate Zones, estimates of average urban income and GDP, and the influence of urban primacy. It is expected that the approach examined will provide a step towards estimating and understanding African cities and their resource profiles.
Highlights
Common consensus suggests that cities currently produce roughly 80% of the global Gross domestic product (GDP) and consume approximately 75% of global energy and materials
With a stated assertion that all non-extractive economic production takes place in the city, the percent of GDP derived from urban activities is stated as the total GDP minus the proportion of GDP from agriculture and mining activities, excluding those related to oil production
This paper presents an exploratory approach utilized as first step towards estimating resource consumption profiles in data scarce urban environments such as African cities
Summary
Recent studies of urban metabolism acknowledge the need for developing a comprehensive and standardized framework for metabolic flow analysis in the urban context, which includes increased data collection and some degree of consensus on parameters that should be part of basic level reporting [21] While this argument is put forward, major data challenges and limitations exist in most regions of the world and in relation to most cities. This may directly impact a city’s ability to reach service delivery, economic growth, and human development goals, as well as its ability to protect ecosystem services which support the city This is aggravated by the fact that governments in African cities are (necessarily) more focused on delivery of basic services than on environmental protection or resource efficiency agendas [23] and have yet to prepare for the expected increase in population of the second wave of urbanization. It can assist decision-makers in African cities in making informed decisions about future infrastructure development and configurations, in order to improve resource access and flows
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