QSAR Model Development for the Environmental Risk Limits and High-Risk List Identification of Phenylurea Herbicides in Aquatic Environments.

Due to the extensive residues of phenylurea herbicides (PUHs) in the environment, it is important for the ecological risk assessment of PUHs to determine their environmental risk limits and identify the high-risk PUHs. This study derived the environmental risk limit (HC₅) of PUHs based on the species sensitivity distribution method and obtained the molecular descriptors using the ORCA and Dragon software. Based on the derived HC₅ and the molecular descriptors, quantitative structure-activity relationship (QSAR) models were developed to predict the HC₅ values using multiple linear regression (MLR) and machine learning (ML) methods. Then, the ecological risk assessment was carried out based on the monitored environmental concentration and the predicted HC₅, and a list of high-risk PUHs was proposed. The results indicated that the derived HC₅ concentrations of 36 PUHs vary greatly, ranging from 0.0000084963 to 5.1512 mg/L. The performance of both the developed QSAR models by the MLR and RF methods met the OECD requirements. Comparatively, the RF model showed a better predictive performance, with a higher correlation coefficient between the experimental HC₅ and predicted HC₅ (R² = 0.90) than the MLR model (R² = 0.86). The developed QASR models also provided insights into the influence of the molecular descriptors on toxicity that the spatial structural descriptors, electronic descriptors, and hydrophobicity descriptors are key descriptors affecting the toxicity of PUHs. The high-risk PUH list from the ecological risk assessment demonstrated that the risk quotient of 10 PUHs (diuron, rimsulfuron, thifensulfuron-methyl, metsulfuron-methyl, metsulfuron, isoproturon, pyrazosulfuron, bensulfuron, tribenuron-methyl, and tebuthiuron) ranged from 4.39 to 2977.68, which are high-risk PUHs that should be given more attention. The obtained results can provide important basis for the ecological risk assessment of PUHs.