A multi-tiered approach for human health risk assessment of pesticide residues in green peppers using Monte Carlo simulation.

Exposure to pesticide residues in vegetables remains a major concern for human health. This study proposes a robust, multi-tiered human health risk assessment framework to support food safety decision-making, using sweet green peppers as a case study. The approach integrates regulatory compliance assessment (Tier 1), deterministic evaluation (Tier 2), and probabilistic modelling (Tier 3). Pesticide residues from 80 samples were quantified using a QuEChERS UPLC-MS/MS method validated according to SANTE/11312/2021 guidelines. Residues were detected in 37.5% of samples, with 13 active substances quantified above the limit of quantification, and only 3.75% exceeding EU maximum residue limits, indicating high compliance. The deterministic assessment (Tier 2), based on a conservative intake-to-body weight ratio and mean concentrations of quantified residues, resulted in cumulative hazard index (HI) values of 0.044 for adults and 0.046 for children/adolescents. The inclusion of non-quantified compounds using the Middle-Bound approach (LOQ/2) increased the cumulative HI values to 0.067 for adults and 0.071 for children/adolescents. In contrast, the probabilistic risk assessment (Tier 3), based on fitted distributions of residue concentrations and dietary intake, yielded cumulative risk estimates at upper exposure percentiles (p90-p99), ranging from 0.0006 to 0.0045 for adults and from 0.0011 to 0.0057 for children/adolescents. These findings highlight the added value of probabilistic approaches for characterising dietary risk by incorporating exposure variability and reducing uncertainty. In particular, Tier 3 enables a more realistic estimation of exposure based on limited quantitative data and allows the integration and interpretation of values below the LOQ, thereby contributing to a more robust risk assessment.