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      QSDsan: an integrated platform for quantitative sustainable design of sanitation and resource recovery systems

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          Abstract

          QSDsan is an open-source platform that integrates the design, simulation, and sustainability characterization of sanitation and resource recovery systems.

          Abstract

          Sustainable sanitation and resource recovery technologies are needed to address rapid environmental ( e.g., climate change) and socioeconomic ( e.g., population growth, urbanization) 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 in Python for the quantitative sustainable design (QSD) of sanitation and resource recovery systems. As an integrated platform for system design, simulation, techno-economic analysis (TEA), and life cycle assessment (LCA), QSDsan can be used to enumerate and investigate the expansive landscape of 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 process modeling 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.

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          SciPy 1.0: fundamental algorithms for scientific computing in Python

          SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.
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            Matplotlib: A 2D Graphics Environment

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              Planetary boundaries: Guiding human development on a changing planet

              The planetary boundaries framework defines a safe operating space for humanity based on the intrinsic biophysical processes that regulate the stability of the Earth system. Here, we revise and update the planetary boundary framework, with a focus on the underpinning biophysical science, based on targeted input from expert research communities and on more general scientific advances over the past 5 years. Several of the boundaries now have a two-tier approach, reflecting the importance of cross-scale interactions and the regional-level heterogeneity of the processes that underpin the boundaries. Two core boundaries—climate change and biosphere integrity—have been identified, each of which has the potential on its own to drive the Earth system into a new state should they be substantially and persistently transgressed.
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                Author and article information

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                Journal
                ESWRAR
                Environmental Science: Water Research & Technology
                Environ. Sci.: Water Res. Technol.
                Royal Society of Chemistry (RSC)
                2053-1400
                2053-1419
                October 03 2022
                2022
                : 8
                : 10
                : 2289-2303
                Affiliations
                [1 ]Institute for Sustainability, Energy, and Environment, University of Illinois Urbana-Champaign, 1101 W. Peabody Drive, Urbana, IL 61801, USA
                [2 ]DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois Urbana-Champaign, 1206 W. Gregory Drive, Urbana, IL 61801, USA
                [3 ]Department of Civil and Environmental Engineering, 3221 Newmark Civil Engineering Laboratory, University of Illinois Urbana-Champaign, 205 N. Mathews Avenue, Urbana, IL 61801, USA
                [4 ]Department of Bioengineering, Stanford University, 129 Shriram Center, 443 Via Ortega, Stanford, California 94305, USA
                [5 ]Department of Civil and Environmental Engineering, Stanford University, 311 Y2E2, 473 Via Ortega, Stanford, California 94305, USA
                [6 ]Department of Chemical Engineering, Stanford University, 129 Shriram Center, 443 Via Ortega, Stanford, California 94305, USA
                Article
                10.1039/D2EW00455K
                184a25d0-b840-42de-99dc-c3aebed57198
                © 2022

                http://creativecommons.org/licenses/by/3.0/

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