Computational fluid dynamics (CFD) modeling techniques can be used to examine contaminant transport and to estimate personal exposure. This work proposes to use CFD to investigate particle aspiration in low velocity environments, typical of the occupational environment. The long-term objective of this work is to provide guidance to the development of an international performance criterion for inhalable particle samplers when used indoors with little air movement. The existing criterion was developed from experiments in larger windspeeds, which may overestimate the amount of particles that are inhaled by a worker in an indoor setting. CFD methods allow the simulation of uniform particle concentration fields, allowing us to avoid the experimental difficulties associated with uniform suspension of large particles. Initial research has developed, validated, and verified a computer representation of a single humanoid form to investigate particle aspiration using the standard k-epsilon turbulence model in the facing-the-wind orientation. This research will: (1) examine the sensitivity of aspiration efficiency estimates to facial feature dimensions, turbulence equations, and bounce parameters to quantify uncertainty in aspiration efficiency estimates;(2) investigate particle aspiration at orientations other than facing-the-wind to understand the influences of orientation and velocity parameters on particle aspiration for a humaniod form;(3) to propose a low velocity aspiration efficiency curve for use in the development of an inhalable particle sampler criterion. This work supports the Exposure Assessment Methods NORA priority research area. There is current concern that occupational exposure samples collected using the existing high-velocity IPM criterion collects particles at efficiencies greater than what can be inhaled by workers. If so, mass-based exposure estimates will overestimate the true exposures of individuals. Once health effects studies are applied to these exposure estimates, risk estimates will be based on overestimated exposures. This will result in risk assessments that actually underestimate the risk of exposure to workers. This research will identify whether the sampling criterion to assess exposures to large particles in workplaces requires adjustment to improve exposure and risk estimates.
