Parameter uncertainty in modeling bioaccumulation factors of fish

Area of Science:

• Ecotoxicology
• Environmental Chemistry
• Quantitative Biology

Background:

• Bioaccumulation factors (BAFs) are critical for assessing persistent organic pollutant (POP) risks in aquatic organisms.
• Quantifying uncertainty in BAF estimations is essential for reliable ecological risk assessments.
• Biota-related parameters significantly influence BAF variability, necessitating detailed investigation.

Purpose of the Study:

• To quantify the uncertainty in estimated bioaccumulation factors (BAFs) for fish due to biota-related parameters.
• To identify the key biota parameters contributing most to BAF uncertainty.
• To improve the accuracy of bioaccumulation modeling for persistent organic pollutants.

Main Methods:

• Utilized Monte Carlo simulations to estimate uncertainty in BAFs.
• Employed the OMEGA (Optimal Modeling for EcotoxicoloGical Applications) model, parameterized using literature data, allometric analysis, and maximum likelihood estimation.
• Included uncertain parameters such as lipid content, assimilation fractions, allometric exponent, and mass transfer resistances.

Main Results:

• Biota-related parameters introduced a factor of 10 uncertainty in estimated fish BAFs.
• Uncertainty in fish lipid content was the primary driver (>50%) for chemicals with K(OW) 10^3 to 10^6.
• For high K(OW) chemicals (≥10^7), assimilation fractions and partial resistances also significantly contributed (up to 60%) to BAF uncertainty.

Conclusions:

• Lipid content is a dominant factor in BAF uncertainty for many persistent organic pollutants in fish.
• Understanding and accurately parameterizing biota-related factors are crucial for reducing uncertainty in bioaccumulation modeling.
• The OMEGA model provides a framework for assessing parameter uncertainty in ecotoxicological risk assessments.