Assessment of the economic and social impacts of new technologies regarding collection and transportation of recyclable waste in smart cities

Abstract

The objective of this thesis is to assess the economic and social impacts of implementing new technologies for the collection and transportation of recyclable Municipal Solid Waste (MSW) in the context of Smart Cities (SCs), especially in low/middle-income countries. The research is composed of three interconnected articles. The first one presents a systematic and bibliometric literature review, which revealed that most international scientific output in the field prioritizes environmental efficiency and cost reduction. Social aspects, such as the inclusion of vulnerable communities or labor rights of informal waste pickers, are largely underrepresented. This suggests a significant imbalance in how MSW management is approached in smart city discussions. The second chapter addresses this gap by proposing and applying a route optimization model in the municipality of Aracruz, Brazil. Using Vehicle Routing Problem (VRP) and Simulated Annealing (SA) metaheuristic, the model simulates multiple vehicle trips and scenarios that include Indigenous communities historically excluded from public waste collection services. The results show that it is possible to reach all districts, urban and rural, without increasing operational costs. This reinforces the potential of data-driven tools in supporting more equitable and efficient MSW systems, provided they are informed by local context and planning sensitivity. The third chapter expands the discussion by proposing a set of social performance indicators for evaluating MSW systems based on the Social Life Cycle Assessment (S-LCA) methodology. These indicators were adapted to realities commonly found in low/middle-income countries and tested in the same case study. The analysis revealed structural social vulnerabilities in MSW management, such as lack of social protection for waste workers, poor stakeholder participation, and gender related disparities. In summary, the integration of route optimization models and social performance indicators provides a more comprehensive decision-support framework for municipalities aiming to implement inclusive smart waste strategies. Rather than focusing solely on cost or efficiency, MSW systems must also address social equity and institutional resilience as central pillars for sustainable urban development.