Conception et évaluation d’un système de gestion des déchets urbains

Thesis Abstract

Rapid urbanization coupled with increasing volumes of municipal solid waste poses significant environmental, public health, and economic challenges for mid-sized cities in Francophone regions. Despite progressive policies, many urban areas struggle with fragmented waste collection, limited recycling rates, and inefficient processing, leading to externalities such as litter, illegal dumping, and greenhouse gas emissions. This study advances the design, implementation, and evaluation of an integrated urban waste management system that aligns with circular economy principles and leverages digital decision-support tools to optimize collection routes, sorting, and treatment pathways. The aim is to develop a context-responsive model that improves service efficiency, reduces environmental footprint, and enhances population engagement in waste practices. Specific objectives address (i) assessment of current waste streams, infrastructure gaps, and stakeholder needs; (ii) development of an integrated system architecture combining municipal collection, material recovery facilities, and energy recovery options; (iii) design of a decision-support platform incorporating route optimization, capacity planning, and real-time monitoring; (iv) pilot implementation in the City of Douville, with delineation of process, cost, and performance metrics; and (v) evaluation of environmental, economic, and social outcomes through pre/post analysis. A mixed-methods design is employed. The population comprises municipal waste management stakeholders, including city authorities, waste collection operators, facility managers, and residents. A stratified random sample of 300 households will be surveyed to quantify waste generation patterns, recycling behavior, and acceptance of new separation schemes. In-depth interviews will be conducted with 40 stakeholders across municipal departments, private partners, and community organizations to capture governance dynamics and operational constraints. The study will implement a 6-month pilot of the integrated system in a representative district, supported by 15 municipal staff and 5 technical consultants. Data collection instruments include structured household questionnaires, semi-structured interview guides, facility performance checklists, and system telemetry logs from the decision-support platform. Validity and reliability will be ensured through pilot testing, Cronbach’s alpha for multi-item scales (target >0.7), and triangulation across data sources. The analytical approach encompasses descriptive statistics, regression analysis to identify determinants of recycling participation (control for income, education, and dwelling type), time-series analysis of waste generation and diversion rates, and cost-benefit analysis to assess economic feasibility. Thematic analysis will be applied to interview transcripts, guided by the Theory of Planned Behavior and the Diffusion of Innovations to illuminate behavioral and organizational adoption processes. A structural equation model will test relationships among perceived usefulness, ease of use, stakeholder engagement, and system performance. The conceptual framework also integrates the Circular Economy Indicators framework to quantify material recovery efficiency, greenhouse gas reductions, and resource circularity. Expected findings include (i) quantifiable improvements in recycling rates and waste diversion, (ii) measurable reductions in collection costs per ton via route optimization and dynamic scheduling, (iii) enhanced data transparency and accountability through the platform, (iv) positive shifts in resident attitudes toward waste separation, and (v) a scalable governance model outlining roles, responsibilities, and financing mechanisms. The study contributes to knowledge by operationalizing a hybrid design–implementation–evaluation approach for urban waste systems in emergent economies, empirically validating the applicability of digital decision-support tools in municipal settings, and refining theoretical linkages between behavioral theories and system performance in the context of waste management. The expected conclusion emphasizes that integrated, data-driven waste systems can achieve substantial environmental and economic gains while fostering citizen participation, provided governance structures, financing arrangements, and capacity-building initiatives are coherently aligned. Policy recommendations include adopting modular system architecture, establishing performance-based contracts with private operators, implementing mandatory separation at source accompanied by public education campaigns, and creating a transparent monitoring dashboard to sustain long-term improvements. The study also proposes avenues for further research on integrating anaerobic digestion, advanced sorting technologies, and city-level financing models for scalable replication.