The potential and scale of cities enable economic growth and the improvement of citizens’ access to jobs, education, healthcare, culture, public utilities and services. Solid waste management (SWM) is one of the key services provided by cities. Its operations are complex, very visible to the general public, and impacted by strong financial, societal, and political constraints. Performances in developing countries, however, are not positive. United Nations research shows urban collection services covering no more than 39% of the population in low-income countries. Why are many cities in developing countries not able to use their increasing wealth and scale for basic SWM services such as city cleaning, collection, and sustainable landfilling? This paper provides a review of literature on this question over the last decade. It shows that research is mostly on symptoms and has not led to a deeper diagnosis of causes. Lack of resources, infrastructure, awareness, and institutional strength are often pinpointed as causes but, in fact, they should be addressed as symptoms. These symptoms should be designated as dependent variables in a complex causal network with systemic feedbacks, hindering or neutralizing attempts to improve performances if not properly dealt with. Research should concentrate more on assessing the relations between urbanization, urban processes, and urban governance that shape the performance of urban solid waste management. System dynamics modeling may provide new approaches for this diagnosis.

Cities in developing countries struggle with providing good waste collection services to all their citizens. Daily practice mostly shows low service coverage, especially in the poorer parts of cities. Up until now, research has mainly dealt with the symptoms of poor performance. This article aims at designing a qualitative System Dynamics model of the urban system that may serve as a diagnostic tool to find the root causes and leverage points for interventions. The research presented here uses a broad literature review to draw up a complex causal loop diagram describing all relevant urban variables (demographic, economic, social, financial, technical and governance-related) and their relations. The diagram is analysed using qualitative methods, partly derived from graph theory. It results in an evaluation of all variables, paths, loops and branches of the model, and finally in a simplified model. This simplified model is helpful in diagnosing waste management problems in cities, in formulating interventions and their points of leverage and even in formulating a new taxonomy that classifies cities with regard to the effect and delay in their urban processes. When it comes to interventions, the model suggests that the root cause is in populations growing faster than their economies, and that the enabling circumstances are mainly in poor governance practices that are unable to secure that tax incomes keep pace with needed budgets for sound services.