Filling Ecotoxicity Data Gaps for Plasticizers via an Integrated Framework: Toxicity Prediction, Prioritization, and...

Area of Science:

• Environmental Chemistry
• Toxicology
• Polymer Science

Background:

• Plasticizers are essential polymer additives, but their environmental release poses ecological risks.
• The structural diversity of plasticizers complicates traditional toxicological assessments and data collection.
• A significant data gap exists regarding the environmental hazards of numerous plasticizers.

Purpose of the Study:

• To develop an integrated modeling framework for the hazard assessment and prioritization of plasticizers.
• To predict the toxicity of a wide range of plasticizers across different trophic levels.
• To identify high-priority plasticizers contributing to ecological risks in aquatic environments.

Main Methods:

• Development of species-specific quantitative structure-activity relationship (QSAR) models for six species.
• Toxicity prediction for 600 plasticizers using QSAR models.
• Integration of QSAR predictions with interspecies correlation estimation and species sensitivity distributions (SSD) to derive hazardous concentrations (HC5).

Main Results:

• Eighty-five plasticizers were identified as high-priority due to potent toxicity (LC50 < 10 μM).
• 54.1% of high-priority plasticizers are alternative types; many are used in PVC and bioplastics.
• Crustaceans were identified as the most sensitive taxa, with derived HC5 values ranging from 0.04-274 μg/L for high-priority plasticizers.

Conclusions:

• The integrated modeling framework effectively assesses and prioritizes plasticizer hazards.
• High-priority plasticizers, including alternative types, are present in common and "green" polymers, posing potential risks.
• Linking hazard prediction with polymer occurrence allows for systematic identification of concerning plasticizers and associated products.