$295 Member/$345 Non-Member

Recorded in June 2020, this PDC provides a comprehensive introduction to IH Mod 2.0, an Excel-based modeling tool available on AIHA's website for evaluating workplace and consumer inhalation exposures with a stochastic model for addressing variability and uncertainty in exposure estimates. The session will discuss: a) the IH Mod 2.0 suite of exposure models; b) how to select the models and parameter inputs for a given exposure scenario; c) whether modeled predictions should be based on a deterministic or probabilistic approach; d) the interpretation of model outputs, which can be expressed as concentration curves or time-weighted averages; e) validation efforts comparing modeled and measured results; and f) issues related to data quality, model validation, and model limitations. Case studies will illustrate the application of the following models in different settings: 1) well-mixed room (box) model, 2) two-zone (near field/far field) model, 3) near-field plume model, and 4) turbulent eddy diffusion model. Special emphasis will be placed on characterizing the distribution of exposures using Monte Carlo simulation techniques.

Course outline

  • Introduction to Mathematical Modeling in Exposure and Risk Assessment
  • IH Mod 1.0 – Historical Evolution and Development
  • IH Mod 2.0 – Addition of Advanced Monte Carlo Simulation Tool
  • Accounting for Variability and Uncertainty in Exposure Estimates
  • Description of Deterministic Versus Probabilistic Approaches
  • Exposure Models (Well-mixed Room, Two-zone Model, Near, and Mid-field Plume Model, Turbulent Eddy Diffusion Model)
  • Key Input Parameters (e.g., Emission Rate, Ventilation Rate, Near Field Geometry, Random Air Speed)
  • Case Study Examples
  • Data Quality Issues and Model Limitations
  • Future Directions
  • Q & A Review

Course outcomes

  • Upon completion, the learner will be able to:
  • Identify situations where exposure models may be useful.
  • Demonstrate knowledge of the different types of models covered.
  • Summarize the key parameters required for each model and sources of data.
  • Select appropriate model(s) for different exposure scenarios.
  • Determine whether to adopt a deterministic or probabilistic approach.
  • Characterize input parameters for point estimates and exposure distributions.
  • Apply and interpret model results.
  • Recognize data gaps and model limitations.
  • Complete a simple uncertainty analysis of model exposure estimates.

Who will benefit

Those looking to enhance their exposure estimation skills, predictive modeling, quantitative uncertainty analysis, and risk-based decision making.


Attendees should have knowledge of Microsoft Excel and enabling macros. Attendees should bring a laptop/notebook PC capable of installing this software before the course.

Time to complete

Participants will have 90 days from the date of purchase to view the session recordings and submit the online evaluation for credit.


Have questions or need additional information? Contact us.


Thomas Armstrong, PhD, CIH, FAIHA

Dr. Thomas Armstrong is the Principal Investigator at his sole proprietor consulting company, TWA8HR Occupational Hygiene Consulting, LLC, established in 2008. Tom has his Bachelor of Science in Chemistry, Master of Science in Environmental Health, and Ph.D. in Environmental Engineering, all from Drexel University, Philadelphia, PA. He is certified in the comprehensive practice of industrial hygiene (CIH) and is a Fellow of the American Industrial Hygiene Association. His career spans over 40 years in multiple industries. His ongoing activities include exposure assessment for epidemiology studies, mathematical methods to estimate exposures to chemicals, quantitative risk assessments for Legionella and Legionnaires’ disease, and risk assessments for other hazards. He has over 30 peer-reviewed publications and has published chapters on exposure assessment strategies, mathematical modeling to estimate exposures, and risk assessment approaches.

Alan Rossner, PhD, CIH

Dr. Rossner is Director of Environmental Health Science and Environmental Science & Policy undergraduate programs at Clarkson University. He is also Associate Director of Clarkson’s Institute for a Sustainable Environment. His teaching and research interests are in human exposure to hazardous chemicals and agents. Before coming to Clarkson, he spent 10 years working in the industrial sector as an environmental, health, and safety professional, performing exposure assessments, safety and health audits, and implementing control systems. He worked for OSHA as a compliance officer and assistant manager in the mid-1980s, as a Corporate EHS person for The Boeing Company, and as an EHS consultant until 1995 when he came to Clarkson University. Over the last decade, he has taught and researched at Clarkson University in Industrial Hygiene, Environmental Health and Risk Analysis. He has taught several PDCs over the past decade, including the Intro to Risk Assessment and Whole Air sampling.

Pamela Williams, MS, ScD, CIH

Dr. Pamela Williams is a Principal at E Risk Sciences, LLP, an independent scientific consulting firm that provides sound analyses and tools to support risk-based decision-making related to human health and the environment. She is also a Clinical Assistant Professor in the Department of Environmental and Occupational Health at the Colorado School of Public Health and a Fellow with the non-profit organization Toxicology Excellence for Risk Assessment (TERA). Dr. Williams has an MS and ScD in Public Health from Harvard University. She is also a certified industrial hygienist (CIH). Dr. Williams specializes in assessing human exposures and health risks in environmental, community, and occupational settings. Her expertise includes human health risk assessment, exposure science, exposure modeling, and uncertainty analysis. She has published over 100 papers, book chapters, and presentation abstracts on various exposure and risk-related topics. Dr. Williams is past President of the Society for Risk Analysis (SRA) and past Chair of AIHA’s Risk Committee.