PDC 604: Introduction to IH Mod 2.0 – Exposure Modeling With Monte Carlo Simulation

Alan Rossner, PhD, CIH, FAIHA Lead Instructor
Clarkson University
Potsdam, NY 
United States of America
Thomas Armstrong, PhD, CIH, FAIHA Instructor
TWA8HR Occupational Hygiene Consulting,
Branchburg, NJ 
United States of America
Dr. Pamela Williams, MS, ScD, CIH Instructor
E Risk Sciences, LLP
Boulder, CO 
United States of America
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.

Course Outline

• 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 

Learning Outcomes

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.  

Value Added

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.  

Course Level


Learning Aids



Available as part of AIHce OnDemand
Chemical Hazards
Hazard Recognition/Exposure Assessment
Risk Assessment and Management

Transfer of Knowledge

Group activities
Hands-on demonstrations and practicum
Practice exercises
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