OMB Individually Reported
Inference of PFAS precursor compositions
Low riskExact public inventory row
Description
This approach will allow for better identification of PFAS source zones and materials, and will enable better estimation of transport processes
Detailed example
Tabular data of predicted PFAS precursor compositions.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
Improved understanding of PFAS compositions, sources, and transport mechanisms will improve mitigation strategies. These improvements have the potential to reduce mitigation costs while improving overall outcomes.
Controls / human review
ATO: No; PIA: N/A