Solid waste management entails more than treatment and recycling, as processors must also minimize health risks associated with the waste and mitigate environmental risks associated with air or water pollution. A life-cycle optimization framework was developed at North Carolina State University to economically and efficiently address these varied facets of solid waste and sustainable materials management.

The open-source Solid Waste Optimization Life-cycle in Python (SwolfPy) tool includes an array of processSource: North Carolina State UniversitySource: North Carolina State University models and a user-interface that allows users to plug in data relevant to site-specific circumstances. SwolfPy provides users a concise snapshot of their current overall operations and implications for cost and environmental goals. Combinations of processes will help operators meet their target numbers for cost, greenhouse gas emissions and other facility targets and considerations.

The framework described in the Journal of Industrial Ecology includes life-cycle models for landfills, mass burn waste-to-energy, gasification, centralized composting, home composting, anaerobic digestion, material recovery facilities and more. Users can also develop process models tailored to specific projects and connect those models to SwolfPy.

SwolfPy can be accessed on Github.

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