With the growth of industry’s sustainability and product stewardship programs, traditional industrial hygiene practices may increasingly extend beyond the workplace environment. The same approaches for assessing risk and identifying risk management options may also apply to downstream users of chemicals and products.  The maturation of industrial hygiene practice can support this shift in focus. When AIHA launched the Product Stewardship Society in 2012, 15 percent of hygienists reported that their work scopes included product stewardship. Within the Product Stewardship Society’s community of practice, product exposure assessment models are considered a core competency necessary to perform risk-based product evaluations. This article explores the appropriate place at the table for industrial hygiene participation in product stewardship, with a focus on developing a technical aptitude for modeling. THE AIHA EXPOSURE MODEL REVIEW  Thomas W. Armstrong’s article “Downstream Modeling: Considerations for Exposure Assessment of Consumer Products” in the September 2017 Synergist focused on the extension of models for airborne chemical concentrations in occupational settings to nonworker populations. The objective of any model is to reasonably bound or narrow the probable solutions from the possible. Common to occupational and nonoccupational models are the conditions and durations of the generation or release of the chemicals. The models differ regarding target populations and subpopulations (for example, nonoccupational models typically incorporate the infirm, the elderly, and children), routes of exposure (with dermal and oral much more important for nonoccupational models), and “vetted data sources” unique to product classifications (such as cosmetics or sunscreens). During the Product Stewardship Society’s 2018 conference, members of AIHA’s Product Exposure Assessment Modeling Team presented “Product Exposure Modeling Workshop: What’s in the Toolbox?” Led by 3M’s Josie Walton, the team addressed the vision and objective of the project: to review occupational models that are also helpful for product exposure assessment modeling. Audience polling indicated that most practitioners found it difficult to locate appropriate models, many were familiar with two to five different models, and that most product assessors did not avail themselves of a community of practice to gain and share experiences in modeling. In the months after the conference, exposure scientists have made further progress in promoting mathematical modeling. PRODUCT EXPOSURE MODELING TOOLBOX After three years of effort, a Product Exposure Modeling Toolbox is now available in Catalyst, the home for AIHA’s online communities. To access the toolbox, AIHA members must first join the “Modeling Tools” community, which is managed by AIHA’s Exposure Assessment Strategies Committee and Stewardship and Sustainability Committee. An option to join the Modeling Tools community is available on the "All Communities" page in Catalyst (AIHA membership is required). Among the files available to members of the community is a spreadsheet with information about several models. The spreadsheet identifies the organization that developed or promotes a given model, whether the model is deterministic or probabilistic, the target populations to which the model may be applied, and general comments on the model’s ease of use.  HOW TO LEARN ANY MODEL Everyone who first approaches modeling feels intimidated. The procedure below presents a sure-fire way to move from intimidated to competent and comfortable, using EPA’s Exposure and Fate Assessment Screening Tool version 2.0 as an example. E-FAST contains a family of models, one of which, called the Consumer Exposure Model or CEM, is used to assess exposures to chemical substances in consumer products. CEM was developed for use in assessments performed under the Toxic Substances Control Act.  The following steps use E-FAST as an example to explain how to self-validate any model—that is, how to demonstrate that a newly-introduced model works as it’s supposed to: Step 1: Download the software and manual. The E-FAST software and user’s guide can be downloaded from EPA's website. (With some networks, administrator privileges or assistance from IT might be required to install models.) Step 2: Click through the screens and prompts. Get a feel for the workflow of the model and the kinds of input values needed to run it. Step 3: Read the manual. We don’t mean front to back—read it interactively while exploring the model. Take note of declared and underlying assumptions in the model. For transparency, when you deploy a model you should declare all assumptions. Step 4: “Exercise” the model. This is best accomplished using values from an existing exposure scenario. Fortunately, several example scenarios with input values and resulting outputs already exist for CEM. These examples are found in EPA’s consumer products risk assessment for trichloroethylene.  Step 5: Run your own scenario. This step converts a narrative description of an exposure scenario, source, pathway, or receptor into input values. Inputs of chemical properties and exposure factors can be pulled from existing databases. The user’s guide may have suggestions for  obtaining model inputs. This is a good time to adopt (if provided) or create an “inputs table” for preparing and capturing all inputs. Look at the results and see if they “make sense”—that they’re justifiable and practical. Use a sensitivity analysis to see how stable the model results are with changing input values.

Optional: Reproduce your calculations. While not feasible for every complex model, reproducing model calculations by hand or using a spreadsheet can lead to a deeper understanding of the model and the material in the user’s guide. In cases where it’s not possible to exercise the model with a worked-out example, the self-validation process involves reproducing model results by hand. Note that some models are tedious to set up accurately in another calculation environment.  PROMOTION OF COMPETENCY IN MODELING  To promote the use of the product exposure modeling toolbox, the Product Exposure Modeling Team invites AIHA members to join the Modeling Tools community on Catalyst. Community members may post questions about how to select models and how to arrive at inputs, and solicit other professionals’ experiences in model performance. Members of the Modeling Team plan to produce short recordings of “self-validation exercises” in which they present their efforts at learning model performance by following case studies of inputs to validate that they are using the model correctly. All community members are encouraged to ask questions, test models, and share the results.  ENGAGING THE COMMUNITY OF PRACTICE The culture of industrial hygiene has greatly expanded beyond the technical sampling of chemical and physical hazards that permeated advanced degree programs 30 years ago. However, modeling remains mysterious to many people. The Product Exposure Modeling Team hopes to engage practitioners across the breadth of exposure science and product stewardship. One way practitioners can help promote modeling is to challenge a colleague to model an aspect of an actual work project prior to monitoring and to communicate the results to the community of practice. Did you pick the best model for the application? Did you successfully locate reference information to inform the input variables? Did you get through the effort deliberately enough to do it more quickly next time, or to show someone else the ropes? Have you discovered a valuable model that has not been addressed with the existing toolbox? The Modeling Team encourages you to help us answer these and many other questions.  PRIORITIZING PRODUCT EXPOSURE MODELING Every five years, AIHA conducts an environmental scan of trends affecting the practice of industrial hygiene and their implications for workers. Based on the most recent scan, AIHA has updated its content priorities, which include three of significance to product exposure modeling: Total Worker Health, occupational exposure banding, and Big Data. Total Worker Health encompasses all hazards and exposure profiles across a 24 hours-a-day, 7 days-a-week, 365 days-per-year exposure without the constraints of the workplace. As a result, product exposure modeling, which was previously of concern only to the product stewardship community, now has bearing on the workplace. (For example, consider a worker who is exposed to formaldehyde both at work from job tasks and at home due to off-gassing from building materials.) Occupational exposure banding will be useful for the development of exposure ranges for contaminants that don’t have a published concentration limit. Classification of product emissions resulting from OEB processes can simplify product exposure assessment. The most prevalent tool for creating occupational exposure bands is available from NIOSH.  As for Big Data, AIHA and NIOSH plan to establish minimal data elements around exposures, create a vetted data dictionary for those elements, and examine the utility of a data repository for everything from field-collected traditional air sampling information to exposure bands. The data repository could include standard exposure scenarios from the IH Exposure Scenario Tool and certain assessments conducted with the NIOSH OEB eTool. (The IH Exposure Scenario Tool, available from AIHA's website is a spreadsheet that allows IHs to record the variables from an exposure event. This information can be useful in retrospectively comparing model performance against real data collected later.) Clearly, the shift from the field-anchored industrial hygienist to the modeling expert will provide greater capacity and capability to AIHA members.   STEVEN JAHN, CIH, is a technical advisor for Savannah River Nuclear Solutions, LLC in Aiken, S.C. JOHN A. LOWE, CIH, is principal technologist at Jacobs. Send feedback to The Synergist.