Lohman Hannah A C, Morgan Victoria L, Li Yalin, Zhang Xinyi, Rowles Lewis S, Cook Sherri M, Guest Jeremy S
Department of Civil and Environmental Engineering, 3221 Newmark Civil Engineering Laboratory, University of Illinois Urbana-Champaign, 205 N. Mathews Avenue, Urbana, Illinois 61801, United States.
Institute for Sustainability, Energy, and Environment, University of Illinois Urbana-Champaign, 1101 W. Peabody Drive, Urbana, Illinois 61801, United States.
ACS Environ Au. 2023 Mar 27;3(3):179-192. doi: 10.1021/acsenvironau.2c00067. eCollection 2023 May 17.
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.
在资源有限的环境中，传统卫生系统往往无法实现其目标，系统故障源于社区需求、限制因素和所采用技术之间的不匹配。尽管存在决策工具来帮助评估特定背景下传统卫生系统的适用性，但缺乏一个整体的决策框架来指导卫生技术的研究、开发和部署（RD&D）。在本研究中，我们引入了DMsan——一个开源的多标准决策分析Python包，它能使用户透明地比较卫生和资源回收方案，并描述早期技术的机会空间。基于文献中常用的方法选择，DMsan的核心结构包括五个标准（技术、资源回收、经济、环境和社会）、28个指标、标准权重情景以及针对250个国家/地区量身定制的指标权重情景，所有这些最终用户都可以进行调整。DMsan与开源Python包QSDsan（卫生和资源回收系统的定量可持续设计）集成，用于系统设计和模拟，以计算不确定性下的定量经济（通过技术经济分析）、环境（通过生命周期评估）和资源回收指标。在此，我们使用乌干达坎帕拉一个非正式定居点布瓦西的现有传统卫生系统以及两个提议的替代系统来说明DMsan的核心功能。这两个示例用例分别是：（i）供实施决策者使用，以提高决策透明度，并了解在利益相关者输入和技术能力不确定和/或变化的情况下卫生选择的稳健性；（ii）供技术开发者使用，以识别和扩大其技术的机会空间。通过这些示例，我们展示了DMsan在评估针对具体情况定制的卫生和资源回收系统以及提高技术评估、RD&D优先级确定和特定背景决策的透明度方面的效用。
