Predicting bioconcentration factors (BCFs) for per- and polyfluoroalkyl substances (PFAS)

Area of Science:

• Environmental Chemistry
• Ecotoxicology
• Computational Chemistry

Background:

• Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants of growing concern.
• Limited bioaccumulation data exists for most PFAS, hindering risk assessment.
• The bioconcentration factor (BCF) is crucial for understanding contaminant uptake in aquatic organisms.

Purpose of the Study:

• To develop a quantitative structure-property relationship (QSPR) model for predicting the BCF in fish.
• To assess the bioaccumulation potential of a large dataset of PFAS compounds.
• To identify key molecular properties influencing PFAS bioconcentration.

Main Methods:

• Developed a QSPR model using experimental BCF data for 33 PFAS representatives.
• Applied the QSPR model to predict log BCF for an external dataset of 2209 PFAS.
• Validated model predictions by comparing laboratory and field study data for 13 PFAS.

Main Results:

• The QSPR model achieved high correlation (R² = 0.844) between predicted and observed log BCFs.
• Out of 2209 PFAS, 1045 were predicted as non-bioaccumulative, 208 as bioaccumulative, and 956 as very bioaccumulative.
• PFAS bioconcentration is influenced by molecular size (chain length) and atomic distribution.

Conclusions:

• Predicting fish BCF for diverse fluorinated compounds is feasible using QSPR modeling.
• The developed model aids in estimating PFAS environmental behavior and bioaccumulation risk.
• Long-chain PFAS generally exhibit higher bioconcentration potential than short-chain variants.