Inhalation dosimetry plays a key role in determining the link between environmental exposure to airborne contaminants and observed human health effects. Due to the limited availability of human experimental data and the complex nature of exposure-dose-response scenarios, mathematical modeling is an important tool in studying the mechanisms which dictate the inhaled "dose." Numerous factors affect the inhaled dose, and available computational models must include an extensive amount of information regarding physiological and anatomical parameters.
A Matlab-based inhalation module was developed at the Computational Chemodynamics Laboratory (CCL) as part of the Modeling ENvironment for TOtal Risk (MENTOR) system. A flexible design allows for adaptation to a variety of exposure conditions and scenarios. This semi-empirical model accounts for variation in inhalation rate and delivered dose across individuals and populations due to differences in factors such as age, gender, and level of physical activity. Capturing the inter- and intra-individual variability of input parameters is accomplished primarily through the interaction of the module with databases of anatomical and physiological parameters.
Predictions from existing models are compared to one another and to available experimental data. Results indicate that the variation in human airway anatomy and respiration physiology among individuals of different ages and genders affects the inhaled dose of particulates. Results also suggest that the level of physical activity is an important factor in nanoparticle deposition, and that available models often underpredict the effects of exercise.