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.