Reliable prediction of sensory irritation threshold values of organic compounds using new models based on linear free energy relationships and GCxGC retention parameters

The human sensory irritation threshold (SIT) is an important biochemical parameter for the exposure assessment of organic air pollutants. First, we recalibrated the Abraham solvation models (ASMs) for 9 SIT endpoints by curating 720 individual experimental SIT values to find an accurate and parsimonious ASM variant, which exhibited root mean square error (RMSE) = 0.174-0.473 log unit. Second, we report linear free energy re-lationships - henceforth called partition models (PMs) - which exploit the correlations of 9 SIT endpoints with the linear combinations of partition coefficients for octanol-water and air-water systems showing RMSE = 0.221-0.591 log unit. These PMs can easily be integrated into widely used EPI-SuiteTM screening tool. The explanatory and predictive performance of PMs were like parameter-intensive ASMs. Third, we present GC x GC models that are based on the retention times of the nonpolar analytes on the comprehensive two-dimensional gas chromatography (GC x GC), which successfully described the SIT variance (R2 = 0.959 -0.996) and depicted a strong predictive power (RMSE = 0.359-0.660 log unit) for an independent set of nonpolar analytes. Taken together, PMs allow easy SIT screening of organic chemicals compared to ASMs. Unlike ASMs, our GC x GC models can be applied to estimate SIT of complex nonpolar mixtures.

Automated summary

This study recalibrates the Abraham solvation models (ASMs) and introduces partition models (PMs) to accurately assess the sensory irritation threshold (SIT) of organic air pollutants. Additionally, GC x GC models are used to predict the SIT of nonpolar analytes in complex mixtures. PMs provide a more convenient screening tool for SIT compared to ASMs, and the GC x GC models offer estimation for nonpolar mixtures.