The U.S. Department of Energy (DOE) recently announced it has awarded $27.5 million for 16 water infrastructure projects. The goal of all these projects is to reduce energy use and carbon emissions in our aging water infrastructure, particularly in wastewater treatment.
For one of the projects, which was awarded $2 million over three years, DOE’s Argonne National Laboratory, along with lead organizations University of Chicago, Northwestern University, and other partners, will be developing an artificial intelligence-assisted system for recovery of energy, nutrients, and freshwater from municipal wastewater.
“This project is an important step forward in realizing Argonne’s strategic plan to enhance our leadership in water-related science through pioneering research, discoveries and innovations using artificial intelligence,” said Junhong Chen, the Crown Family Professor of Molecular Engineering at the Pritzker School of Molecular Engineering (PME) at the University of Chicago.
The project’s approach will combine artificial intelligence and machine learning for online learning of system dynamics, mathematical modeling for optimizing energy and nutrient recovery, and life-cycle analysis and modeling with respect to both the science and economics to guide system design. It will also involve the development of novel materials for efficient solar steam generation and wireless sensors for real-time water quality monitoring.
The resulting resource recovery system would benefit the water supply in underserved communities on Chicago’s South Side as well as the Great Lakes region in general, including Milwaukee and Detroit.
The ultimate goal of the project is to transform the existing U.S. treatment system for municipal wastewater into an intelligent water resource recovery system that will dramatically reduce energy consumption and become energy positive at a national scale.