An improved method to predict polycyclic aromatic hydrocarbons in surface freshwater by reducing the input parameters

Predicting the concentration of polycyclic aromatic hydrocarbons (PAHs) in surface freshwater are critical for understanding their spatio-temporal distribution, regulation effectiveness, and the subsequent health risks. In this study, by exploring the correlation of PAHs concentrations in surface freshwater (CPAHs) in China reported in the past twenty years with their emission (EPAHs), a novel relationship of CPAHs with EPAHs and PAHs properties (i. e., logK(ow) and S-w) was established. For PAHs individual, percent sample deviation between the measured concentrations and the calculated concentrations are in the range of 18% to 48%, suggesting that the calculated concentrations of PAHs are well consistent with the measured PAHs concentration in surface freshwater. Moreover, spatial distribution of predicted PAHs concentrations in surface freshwater of China is also matched well with measured ones. Compared with other environmental models, the established relationships in this work can reduce the number of model parameters fromdozens to three, as well as decrease percent sample deviation fromseveral orders of magnitude to less than 50%. The established relationship of PAHs concentrations in surface freshwater with EPAHs, Sw, and logKow of PAHs, are valuable to facilitate the prediction of PAHs concentrations in surface freshwater by reducing monitoring costs. (c) 2021 Published by Elsevier B.V.

Automated summary

A novel relationship between polycyclic aromatic hydrocarbons (PAHs) concentrations and their emission and properties was established, and the predicted concentrations matched well with the measured values. The findings are valuable for reducing monitoring costs.