Researchers at North Carolina State University developed a user-friendly tool that uses multiple computational models to help solid refuse systems achieve their environmental goals the most cost-efficiently possible.
Waste management systems do much more than just dump solid waste into landfills. These systems must not only safely store and recycle solid waste but also minimize health risks, reduce environmental risks, and minimize the emission of greenhouse gases (GHGs), that can be generated when solid waste is processed.
James Levis, coauthor of the paper and research assistant professor of civil construction and environmental engineering at NCState, says, “The problem is that there are many things waste management systems could do to achieve these goals.” “And many of these actions have trade-offs in the form of cost, environmental impacts, technical challenges, etc.
“To address this, we created an open-source tool called Solid Waste Optimization Life-cycle (SwolfPy) that allows users to evaluate all of these options from one place. This tool can help users decide the best course for each situation. Open-source means that the solid waste community can continue to develop new features to make the tool more useful in decision-making.
“SwolfPy can be dynamic,” Mojtaba Sardarmehni (corresponding author and NCState Ph.D student), said. “For example, if someone creates a better model of one of its components, the platform will allow users update SwolfPy.”
The SwolfPy framework has a set of process models and a user interface that allows users input data relevant for their situation. SwolfPy will then run the numbers, and do two things. It provides a quick snapshot of the current operations and how it impacts their environmental and cost goals. SwolfPy also helps users to determine the best combination of processes that will allow them meet their targets for cost and GHG emissions.
However, users don’t need to use the default SwolfPy models. Users can choose to create process models specific to their projects and connect them with SwolfPy. Users can also use a combination or all of the standard models and customized ones. SwolfPy allows users the ability to input their target numbers into the interface. SwolfPy will tell them which combination will bring them closer to their goals.
Sardarmehni states, “To be clear there isn’t always a best solution.” “For example there may be one option that is the most cost-effective and another option that does a better job at reducing GHG emissions. SwolfPy helps users identify the best options based on their priorities.
Levis states that SwolfPy is a useful tool for waste management companies and government decision makers dealing with solid waste issues, as well as state policymakers and researchers.
SwolfPy is available online already on Github.
Levis says, “We’re open for people in the solid-waste community who have questions or ideas about how SwolfPy could be used, and what can be done to keep it as a practical tool.”
The paper is published in Journal of Industrial Ecology.
Mojtaba Sardarmehni et. al. Solid waste optimization framework in Python (SwolfPy). Journal of Industrial Ecology (2022). DOI: 10.1111/jiec.13236
New tool to assist solid-waste systems in achieving their environmental and cost goals (2022, Jan 20)
Retrieved 20 January 2022
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