About 12% of the about 300 million tons of trash generated by Americans is converted into energy by waste-to-energy plants. Though recycling and composting have increased, the majority of the waste produced goes into landfills, the most inexpensive option. Researchers now aim to develop a new AI to make waste-to-energy plants a more attractive option by making it more effective and thus less cost intensive.
The technology the team is working on is designed to provide rapid, in-situ characterization of MSW feedstock, providing critical characterization and chemical analysis data in minutes for feed-forward process control of downstream biofuel production processes. The project includes the development of both hardware and software elements that, together, will be capable of improving MSW characterization throughput over baseline methods by at least 25%. The approach could make it possible to process waste material in minutes, instead of hours.
This project could lead to a process that is both easier and less costly, making waste-to-energy a more attractive alternative to the landfill, and moving the U.S. closer to a waste-processing approach that is sustainable. The proposed project supports BETO’s goal of innovation to accelerate feedstock technologies that would propel a bio-economy, by allowing real-time characterization of MSW feedstock for feed-forward process control of downstream biofuel production processes.
Source: Waste Management World
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