Predicting polycyclic aromatic hydrocarbon concentrations in resident aquatic organisms using passive samplers and partial least-squares calibration.

The current work sought to develop predictive models between time-weighted average polycyclic aromatic hydrocarbon (PAH) concentrations in the freely dissolved phase and those present in resident aquatic organisms. We deployed semipermeable membrane passive sampling devices (SPMDs) and collected resident crayfish (Pacifastacus leniusculus) at nine locations within and outside of the Portland Harbor Superfund Mega-site in Portland, OR. Study results show that crayfish and aqueous phase samples collected within the Mega-site had PAH profiles enriched in high molecular weight PAHs and that freely dissolved PAH profiles tended to be more populated by low molecular weight PAHs compared to crayfish tissues. Results also show that of several modeling approaches, a two-factor partial least-squares (PLS) calibration model using detection limit substitution provided the best predictive power for estimating PAH concentrations in crayfish, where the model explained ≥72% of the variation in the data set and provided predictions within ∼3× of measured values. Importantly, PLS calibration provided a means to estimate PAH concentrations in tissues when concentrations were below detection in the freely dissolved phase. The impact of measurements below detection limits is discussed.