
The shift toward a low-carbon circular economy requires transforming conventional wastewater and solid waste treatment systems into integrated biorefineries capable of recovering value-added products. Participatory approaches address the complexity of this transition by leveraging stakeholder expertise to guide the selection of feedstocks, technologies, and products suitable for integration into biorefinery systems. This study proposes a novel conceptual biorefinery design developed through participatory workshops and the collaborative process mapping of 33 Brazilian research initiatives focused on agro-industrial and urban-source wastewater and waste streams. The analysis reveals a multi-product landscape dominated by low-value energy outputs, primarily generating biogas, methane, hydrogen, and syngas, followed by medium-value-added products, including volatile fatty acids, fertilizers, and biochar. Conversely, high-value bioproducts (polyhydroxyalkanoates, lactic acid, acetic acid, γ-valerolactone, mycelium-based materials) were identified less frequently. Based on this analysis, seven conceptual integrated biorefinery scenarios originating from local agro-industrial sectors and urban environmental services were proposed by combining: (i) feedstock-based integration, clustering by-products originating from the same production chain and functionally similar wastes from different sources within defined sectors; (ii) technological integration, emphasizing mass/energy integration and process intensification; and (iii) product integration, utilizing a value-oriented cascading logic and zero-waste principles. Finally, although no quantitative Life Cycle Assessment (LCA) was performed, the study presents preliminary LCA modeling for a multifunctional scenario, with decision-support criteria and thresholds for constructing integrated biorefinery scenarios, providing practical guidelines for future multi-product life cycle modeling of these conceptual configurations through a scenario-based application of a five-step LCA decision framework.