A New Model for Discarded Municipal Waste Composition in the US

Jon Powell

Yale University,

Jon is a researcher and environmental engineer with wide-ranging interests across the spectrum of waste materials management. His research career began with operating and optimizing full-scale landfills, with a focus on in-situ aeration of the waste and the mechanisms underlying gas production and emissions changes.  In subsequent years, his research portfolio expanded to include assessing the beneficial use of non-hazardous waste materials (e.g., industrial and construction wastes), waste management policy interventions, municipal landfill mining, and life-cycle assessment.  In recent years, he has worked to bring informatics to the waste sector by using contemporary analytical tools to create large-scale data sets across multiple dimensions of waste management to inform current management outcomes (e.g., the efficiency of landfill gas capture), highlight emergent issues (e.g., the scale of disposal sites reaching the end of the aftercare period), and pinpoint areas where intervention strategies - such as diversion - should take place based on spatially- and temporally-resolved analytical models.  Jon holds a Bachelor's degree and Master's degree in Environmental Engineering Sciences from the University of Florida, is a registered professional engineer in Florida, Connecticut, and Puerto Rico, and is completing his doctorate in Chemical & Environmental Engineering at Yale University.


The US EPA has published national-level estimates of MSW management approximately annually since the 1990s. These data are heavily relied upon by researchers, state environmental agencies, local planners, and researchers... [ view full abstract ]


  1. Jon Powell (Yale University,)

Topic Areas

• Open source data, big data, data mining and industrial ecology , • Management and technology for sustainable and resilient energy, water, food, materials, , • Decision support methods and tools


ThS-15 » Special session: "Waste Informatics and Data Quality in Industrial Ecology" (11:30 - Thursday, 29th June, Room F)

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