Performance of the partition-limited model on predicting ryegrass uptake of polycyclic aromatic hydrocarbons

Abstract

Accurate modeling of the uptake and accumulation behavior of organic contaminants like polycyclic aromatic hydrocarbons (PAHs) in plants is essential to assess crop contamination and subsequent human exposure. In this study, the performance of a partition-limited model on predicting ryegrass uptake of PAHs (acenaphthene, fluorene, phenanthrene and pyrene) from water was evaluated and the major factors were examined. It was found that model predictions of PAH concentrations in roots and shoots of ryegrass were all within an order of magnitude of the observed values with the differences between estimated and measured concentrations less than 42.1% for roots and 78.4% for shoots. Since the model considered soil/water–plant pathway only, it was inevitable that simulated concentrations in shoots suffered a bigger error than those in roots due to the influence of foliar uptake, the other important pathway for PAHs. If the impact of foliar uptake was excluded, the accuracy of simulated shoot concentrations would be greatly enhanced, with the maximum prediction error reduced from 78.4% to 47.1% for pyrene. Other factors aside from foliar uptake were also examined, including aqueous PAH concentrations, uptake time, plant composition and chemical properties. These factors were found to influence the model performance generally through acting on the quasi-equilibrium factor ( α pt). Results from this study substantiated the utility of this partition-limited model for vegetation-uptake assessment, and then provided some testimony valuable for the modification of a model with a better performance.