The proliferation of electronic goods manufacturing and the subsequent rise in electronic waste (e-waste) generation necessitate the establishment of efficient Waste of Electrical and Electronic Equipment (WEEE) reverse logistics systems, fostering collaborative efforts among manufacturers, retailers, and government agencies. Given its importance, this theme has received considerable attention in recent literature. This study focused on investigating the relationships between socio-spatial characteristics and the distribution of WEEE collection points in the city of São Paulo, Brazil. To this end, data mining (DM) techniques were applied to generate rules representing knowledge that explains the relationship among the considered variables. The results achieved (accuracy 81.25% and Kappa statistic 74.71%), indicating consistent patterns, demonstrate the potential of the proposed approach to aid WEEE reverse chain management. From a practical point of view, the knowledge produced is an important support for decision-making on the installation of new collection points, considering the socio-spatial characteristics of the target locations. In addition, this research contributes to the responsible management of solid waste recommended by the Brazilian National Solid Waste Policy (NSWP), as well as to the advancement of the United Nations’ Sustainable Development Goals (UN SDGs), particularly SDG 11 (Sustainable Cities and Communities) and SDG 12 (Responsible Consumption and Production), by fostering sustainable practices in waste management and resource utilization within urban contexts.

Objective: This study aimed to conduct an emergy assessment for the depollution of the Charles de Gaulle stream in Brazil. Methodology: A case study approach was employed, utilizing interviews and participant observation for data collection. The emergy assessment was applied to the gathered data, yielding significant results. Originality: This study addresses a critical research gap, as no literature specifically applies emergy assessment to urban stream depollution. It provides a comprehensive evaluation of the stream’s revitalization and monitoring impacts, contributing to the United Nations Sustainable Development Goal 6 (SDG 6) on clean water and sanitation. Results: Emergy indicators, analyzed through sensitivity analysis, reveal improvements in ecosystem services, resource optimization, and water quality. A decrease in the stream's total emergy indicates clear environmental restoration and societal reintegration into the ecosystem. Contributions: This research demonstrates the feasibility of applying emergy assessment in urban water revitalization. The reduction in total emergy signifies environmental restoration and supports practical actions toward achieving SDG 6 focused on clean water and sanitation.