Filling Ecotoxicity Data Gaps for Plasticizers via an Integrated Framework: Toxicity Prediction, Prioritization, and Hazardous Concentration Derivation.
Abstract
Plasticizers are widely used polymer additives whose release into aquatic environments poses ecological risks, while their structural diversity challenges conventional toxicological assessment. To address this data gap, an integrated modeling framework was established for hazard assessment and prioritization of plasticizers. Species-specific QSAR models were developed for six species across three trophic levels, enabling accurate toxicity prediction for 600 plasticizers. Eighty-five plasticizers were identified as high-priority due to potent toxicity (LC50 < 10 μM) across trophic levels, 54.1% of which are alternative plasticizers. Approximately half of these high-priority plasticizers are widely used in polyvinyl chloride plastics, and 21.2% occur in bioplastics, indicating their potential contribution to the chemical risk of conventional plastics and "green" polymers. Across multiple taxa, predicted toxicity differences among plasticizer subclasses were linked to structural features captured by 2D descriptors. By integrating QSAR predictions with interspecies correlation estimation, the hazardous concentrations for 5% of species (HC5: 0.04-274 μg/L) were derived for high-priority plasticizers using species sensitivity distributions, with crustaceans identified as the most sensitive taxa. Linking hazard prediction and prioritization with polymer occurrence enables the systematic identification of high-priority plasticizers and highlights polymers that contain plasticizers of potential concern.