Target and Suspect Screening Integrated with Machine Learning to Discover Per- and Polyfluoroalkyl Substance Source
Nayantara T Joseph1, Trever Schwichtenberg2, Dunping Cao2
1School of Civil and Environmental Engineering, Cornell University, Ithaca, New York 14853, United States.
This study identifies unique chemical fingerprints for per- and polyfluoroalkyl substances (PFAS) from various sources like firefighting foam, landfills, and industrial wastewater. These PFAS profiles help pinpoint contamination origins for better environmental management.
Area of Science:
- Environmental Chemistry
- Analytical Chemistry
- Environmental Science
Background:
- Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants originating from diverse sources.
- Identifying specific PFAS sources is crucial for effective remediation and regulatory strategies.
- Existing methods for PFAS source attribution often lack comprehensive chemical profiling.
Purpose of the Study:
- To establish distinct per- and polyfluoroalkyl substance (PFAS) "fingerprints" for various environmental sources.
- To identify specific PFAS compounds (target and suspect) that are characteristic of each source type.
- To enable accurate source allocation of PFAS contamination in the environment.
Main Methods:
- Collected 92 environmental samples from sources including firefighting foam-impacted groundwater, landfill leachate, and industrial wastewater.
- Utilized high-resolution mass spectrometry to quantify 50 target PFASs and screen over 2,000 suspect PFASs.
- Employed machine learning classifiers to analyze PFAS data and identify source-specific diagnostic compounds.
Main Results:
- Aqueous film-forming foam impacted groundwater (AFFF-GW) showed unique fingerprints with specific short-chain perfluoroalkyl acids.
- Landfill leachate was characterized by fluorotelomer carboxylic acids and sulfonamido acetic acids.
- Biosolids leachates shared characteristics with landfill leachates, with specific sulfonamido acetic acids aiding classification.
- Municipal wastewater treatment plant (WWTP) effluent contained few target PFASs, but the insecticide fipronil was a key indicator.
Conclusions:
- The study successfully generated "fingerprints" for various PFAS sources, aiding in their identification.
- Specific target and suspect PFAS compounds were identified as reliable markers for source allocation.
- These findings provide valuable tools for environmental scientists and regulators to trace PFAS contamination back to its origin.
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