  Sustainable sanitation and resource recovery technologies are needed to
address rapid environmental and socioeconomic changes. Research prioritization
is critical to expedite the development and deployment of such technologies
across their vast system space (e.g., technology choices, design and operating
decisions). In this study, we introduce QSDsan - an open-source tool written in
Python (under the object-oriented programming paradigm) and developed for the
quantitative sustainable design (QSD) of sanitation and resource recovery
systems. As an integrated platform for system design, process modeling and
simulation, techno-economic analysis (TEA), and life cycle assessment (LCA),
QSDsan can be used to enumerate and investigate the opportunity space for
emerging technologies under uncertainty, while considering contextual
parameters that are critical to technology deployment. We illustrate the core
capabilities of QSDsan through two distinct examples: (i) evaluation of a
complete sanitation value chain that compares three alternative systems; and
(ii) dynamic simulation of the wastewater treatment plant described in the
benchmark simulation model no. 1 (BSM1). Through these examples, we show the
utility of QSDsan to automate design, enable flexible process modeling, achieve
rapid and reproducible simulations, and to perform advanced statistical
analyses with integrated visualization. We strive to make QSDsan a
community-led platform with online documentation, tutorials (explanatory notes,
executable scripts, and video demonstrations), and a growing ecosystem of
supporting packages (e.g., DMsan for decision-making). This platform can be
freely accessed, used, and expanded by researchers, practitioners, and the
public alike, ultimately contributing to the advancement of safe and affordable
sanitation technologies around the globe.
