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The Pollutant Fate and Transport Processes and Geochemistry Laboratory (PFTPG) conducts researches combining laboratory experimentation, field scale testing, data analysis, and model development and assessment. Essentially, the PFTPG Lab seeks to answer two questions: How can the sustainability of civil infrastructure and the environment be improved effectively? The research topics include 1) the innovation of smart geomaterials for waste containment, 2) remote sensing and artificial intelligence in geoenvironmental engineering, and 3) the design of infrastructures with nature-based resilience in a complex environment.
Feature Project 1: AI-Powered Detection of Battery-Containing Items in Residential Recycling
Developing an AI-based image recognition framework to detect battery-containing items in residential recycling streams by integrating field-collected imagery, curated e-waste datasets, and convolutional neural network models, supporting safer recycling operations and reduced contamination at transfer stations.
Feature Project 2: Improve the Operation and Design of Radioactive Waste Disposal Facilities
Integrating field observations and numerical modeling to evaluate water movement, infiltration, and moisture dynamics in radioactive waste disposal facilities, supporting long-term performance assessment under realistic hydrological conditions.
Feature Project 3: Fate and Transport of Contaminants in Waste Management
Designing waste containment facilities based on the fate/transport of the contaminants using advanced modeling and experimental approaches.
Feature Project 4: Recycling Behavior and Clean Recyclables
Address the nation's need for economical and environmentally friendly recycling, and reduce contamination from recyclables.
Feature Project 5: Functional Stability for Post-Closure Care Assessment
To develop a detailed performance-based framework to evaluate the level of functional stability in coal combustion product landfills.
Feature Project 6: Remote Sensing and Digital Twin for Waste Management
Advanced remote sensing for landfill geometry, emission, and odor survey. Creating the first ever landfill digital twin to aid the operation. The funded projects featured the UCF Smart City Initiatives.
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