Background: Silicone personal samplers are increasingly being used to measure chemical exposures, but many of these studies do not attempt to calculate environmental concentrations.
Objective: Using measurements of silicone wristband uptake of organic chemicals from atmospheric exposure, create log Ksa and ke predictive models based on empirical data to help develop air equivalency calculations for both volatile and semi-volatile organic compounds.
Methods: An atmospheric vapor generator and a custom exposure chamber were used to measure the uptake of organic chemicals into silicone wristbands under simulated indoor conditions. Log Ksa models were evaluated using repeated k-fold cross-validation. Air equivalency was compared between best-performing models.
Results: Log Ksa and log ke estimates calculated from uptake data were used to build predictive models from boiling point (BP) and other parameters (all models: R2 = 0.70-0.94). The log Ksa models were combined with published data and refined to create comprehensive and effective predictive models (R2: 0.95-0.97). Final estimates of air equivalency using novel BP models correlated well over an example dataset (Spearman r = 0.984) across 5-orders of magnitude (<0.05 to >5000 ng/L).
Significance: Data from silicone samplers can be translated into air equivalent concentrations that better characterize environmental concentrations associated with personal exposures and allow direct comparisons to regulatory levels.
© 2021. The Author(s).