Sun, 5/23: 1:00 PM - 5:00 PM
Professional Development Course
Room: Virtual 4
CM Credit Hours: 3.5
*All PDCs have an additional fee and require preregistration*
To register, please visit: https://www.aihceexp.org/2021/register-2021
This PDC provides an introduction to IH Mod 2.0, an Excel-based freeware modeling tool available on AIHA's website. IH Mod 2.0 is used for evaluating workplace and consumer inhalation exposures that include Monte Carlo Simulation. Participants will learn: a) about the IH Mod 2.0 exposure models and support files; b) to select the appropriate models and parameter inputs; and, c) whether predictions should be based on a deterministic or probabilistic approach. Case studies will illustrate these models: well-mixed room (box), two-zone (near field/far field), near-field plume, and turbulent eddy diffusion. The following topics will be presented: 1) characterizing exposure distributions using Monte Carlo simulation; 2) interpreting model outputs as concentration curves or time-weighted averages; and, 3) issues relating to data quality, model validation, and model limitations. A series of case studies/scenarios will demonstrate how to apply IH MOD 2.0 to IH exposures.
• Mathematical Modeling in Exposure and Risk Assessment
• Historical Evolution and Development of IH MOD
• IH Mod 2.0 – Addition of Advanced Monte Carlo Simulation Tool
• Variability and Uncertainty in Exposure Estimates
• Description of Deterministic Versus Probabilistic Approaches
• Overview of Exposure Models
• Key Input Parameters
• Case Study Examples
• Data Quality Issues and Model Limitations
• Future Directions
• Q & A Review
Upon completion, participants will be able to:
• Identify situations where exposure models may be useful.
• Demonstrate knowledge of the types of models covered in the PDC.
• Summarize the parameters required for each model and data sources.
• Select appropriate model(s) for different exposure scenarios.
• Determine whether to use a deterministic or probabilistic approach.
• Define input parameters for point estimates and exposure distributions.
• Apply models and interpret model results.
• Recognize data gaps and model limitations.
• Complete an uncertainty analysis of exposure estimates.
Participants should have a knowledge of Microsoft Excel, enabling macros and capability to install software prior to the course on a notebook/laptop.
Attendees will increase knowledge of: 1) exposure modeling tools; 2) model selection, characterizing distributions and input parameters; 3) exposure variability and uncertainty; and 4) data quality and model uncertainty.
Business Case/IH Value Statement
PDC will provide skills in exposure estimation, predictive modeling, and uncertainty analysis, to support risk decision-making.
Available as part of AIHce OnDemand
Hazard Recognition/Exposure Assessment
Risk Assessment and Management
Transfer of Knowledge
Hands-on demonstrations and practicum