Multimedia model for polycyclic aromatic hydrocarbons (PAHs) and nitro-PAHs in Lake Michigan

Area of Science:

• Environmental Chemistry
• Ecotoxicology
• Environmental Modeling

Background:

• Polycyclic aromatic hydrocarbons (PAHs) and their nitro-derivatives (NPAHs) are persistent environmental contaminants of concern in the Great Lakes.
• Current data on PAH/NPAH sources, distribution, and fate in Lake Michigan, especially for NPAHs, are limited.
• Understanding PAH/NPAH behavior is crucial for effective environmental management and risk assessment.

Purpose of the Study:

• To model the distribution and fate of 16 PAHs and five NPAHs in Lake Michigan.
• To estimate PAH and NPAH emission rates using fugacity, food web, and Monte Carlo models.
• To assess model performance against measured concentrations and identify data gaps.

Main Methods:

• Application of fugacity, food web, and Monte Carlo models to simulate PAH and NPAH behavior in Lake Michigan.
• Comparison of model predictions with available measured data for air, water, sediment, and lake trout.
• Derivation of historical and current PAH emission rates based on model outputs.

Main Results:

• Model accurately predicted PAH concentrations in air but under-predicted those in water and sediment.
• Food web model successfully matched heavier PAHs in lake trout but over-predicted lighter PAHs.
• Derived PAH emission rates peaked in the 1950s, now nearing mid-19th century levels, and significantly exceed inventory estimates.

Conclusions:

• Models provide valuable insights into PAH and NPAH behavior and emission trends in Lake Michigan.
• Discrepancies between predicted and measured concentrations suggest uncertainties in degradation rates, discharge data, or tributary inputs.
• Significant differences between derived and inventoried emission rates highlight the need for data reconciliation and uncertainty reduction.