Ranking of potential hazards from engineered nanoparticles and micro/nano-plastics in food systems.

Engineered nanoparticles (ENPs) and micro- and nanoplastics are increasingly detected in agri-food systems, yet approaches for prioritising particles relevant to oral exposure remain limited and fragmented. A semi-quantitative probability-impact framework was developed to rank potential human health hazards associated with dietary exposure. Six probability-related factors: annual production, application sectors, predicted environmental concentrations (PECs), dissolution ratio, first-order decay rate (k), and zeta potential; and four impact-related factors: Predicted No-Effect Concentrations (PNEC), half maximal Effective Concentration (EC50), Reference Dose (RfD), and minimum of No-Observed-Adverse-Effect Level (NOAEL) and Lowest-Observed-Adverse-Effect Level (LOAEL) values were integrated within a probability (P)-impact (I) matrix. Literature-derived inputs were parameterised using appropriate distributions, transformed into percentile-based dimensionless scores and aggregated under a baseline equal-weight scenario and two alternative weighting scenarios based on the Entropy Weight Method (EWM) and Analytical Hierarchy Process (AHP). Monte Carlo simulation (100,000 iterations) and Spearman rank-order coefficients were used to quantify uncertainty and identify dominant drivers. Across scenarios, Ag, TiO2, ZnO, CNTs, CeO2, and CuO consistently formed the high-priority group, whereas SiO2, Al2O3, microplastics, nanoplastics, fullerene, Au, and Fe2O3 generally occupied intermediate positions. PEC and production were the most recurrent positive drivers of ranking variability. This framework provided an updateable screening-level prioritisation tool to support targeted monitoring, refined exposure assessment, and focused toxicological evaluation of higher-priority particles.