Evaluating microplastic particles as vectors of exposure for plastic additive chemicals using a food web model

Microplastic particles (MPs) represent potential hazards for humans and wildlife, including as vectors for chemical exposure (e.g. plastic additives and pollutants sorbed from the surrounding environment). The leaching of chemicals from MPs has been identified as a potential exposure pathway but the relative magnitude of this pathway under environmentally relevant conditions remains unclear. Here, we describe a modification of the ACC-HUMANSTEADY bioaccumulation model to include dietary exposure to MPs containing either accumulated chemicals from the surrounding environment or embedded plastic additive chemicals (PACs). Chemical transfer to humans and wildlife is described using two-film resistance concepts assuming spheroidal particles of different sizes. The relative contribution of MPs and environmental media to the estimated daily chemical intake in humans was assessed in various exposure scenarios, for a range of hypothetical chemicals with varying octanol-water and air-water partition coefficients (KOW and KAW, respectively; i.e. 0 < log KOW <8 and − 5 < log KAW < 3). Results imply that MPs could act as sources of exposure to chemical additives when the ingestion rate of 1 μm MPs is ≥ 10 mg d− 1, and the concentration of hydrophobic plastic additive is ≥ 5% wt wt− 1. The contribution made by MPs as vectors of exposure decreased with increasing particle size and decreasing ingestion rates of MPs. Human health risks were evaluated for four specific PACs to illustrate the application of the model for risk assessment. Risks were negligible when the ingestion rate of MPs was < 100 μg d− 1. Uncertainties are high regarding the characterization and quantification of ingestion of MPs by humans and wildlife, including particle sizes and polymer composition, as well as on the presence of PACs in MPs. These data gaps need to be addressed if the issue of MPs as vectors of chemical exposure is to be fully understood. The work illustrates that mechanistic models, which account for all major exposure pathways, can be used to identify the importance of different exposure pathways, help prioritize research needs and support decision making.