A New Model Algorithm for Estimating the Inhalation Exposure Resulting from the Spraying of (Semi)-Volatile Binary...

Area of Science:

• Environmental Chemistry
• Occupational Health
• Chemical Engineering

Background:

• Spraying liquid mixtures in industrial settings can release hazardous aerosols and vapors.
• Accurate exposure assessment is crucial for regulatory risk evaluation of chemicals.

Purpose of the Study:

• To develop a mechanistic mass balance model for predicting exposure during spraying of multicomponent mixtures.
• To account for combined exposure routes including spray mist, droplet evaporation, surface evaporation, and non-ideal mixture behavior.

Main Methods:

• Developed a mass balance model incorporating an impaction module for wall-spraying scenarios.
• Approximated continuous spraying as sequential spray pulses and solved differential equations numerically.
• Included time-dependent concentration gradients and backpressure effects for complex mixtures.

Main Results:

• The model accurately calculates exposure to aerosols and vapors from sprayed substances.
• A case study on hydrogen peroxide (H2O2) showed aerosol exposure is highest during spraying, while surface evaporation persists longer.
• Backpressure effects significantly influence concentration curves, while activity coefficients have less impact.

Conclusions:

• The developed model, SprayEva, provides a plausible and predictive tool for assessing chemical exposure from spraying operations.
• The model is valuable for occupational and consumer risk assessments in regulatory contexts.
• Further validation with more measurement data is recommended.