DMsan: A Multi-Criteria Decision Analysis Framework and Package to Characterize Contextualized Sustainability of Sanitation and Resource Recovery Technologies.

In resource-limited settings, conventional sanitation systems often fail to meet their goals-with system failures stemming from a mismatch among community needs, constraints, and deployed technologies. Although decision-making tools exist to help assess the appropriateness of conventional sanitation systems in a specific context, there is a lack of a holistic decision-making framework to guide sanitation research, development, and deployment (RD&D) of technologies. In this study, we introduce DMsan-an open-source multi-criteria decision analysis Python package that enables users to transparently compare sanitation and resource recovery alternatives and characterize the opportunity space for early-stage technologies. Informed by the methodological choices frequently used in literature, the core structure of DMsan includes five criteria (technical, resource recovery, economic, environmental, and social), 28 indicators, criteria weight scenarios, and indicator weight scenarios tailored to 250 countries/territories, all of which can be adapted by end-users. DMsan integrates with the open-source Python package QSDsan (quantitative sustainable design for sanitation and resource recovery systems) for system design and simulation to calculate quantitative economic (via techno-economic analysis), environmental (via life cycle assessment), and resource recovery indicators under uncertainty. Here, we illustrate the core capabilities of DMsan using an existing, conventional sanitation system and two proposed alternative systems for Bwaise, an informal settlement in Kampala, Uganda. The two example use cases are (i) use by implementation decision makers to enhance decision-making transparency and understand the robustness of sanitation choices given uncertain and/or varying stakeholder input and technology ability and (ii) use by technology developers seeking to identify and expand the opportunity space for their technologies. Through these examples, we demonstrate the utility of DMsan to evaluate sanitation and resource recovery systems tailored to individual contexts and increase transparency in technology evaluations, RD&D prioritization, and context-specific decision making.