First Place Award: An Analysis of the Use of Mathematical Models to Predict Chemical Inhalation Exposures versus Traditional Air Sampling

First Place Award: An Analysis of the Use of Mathematical Models to Predict Chemical Inhalation Exposures versus Traditional Air Sampling
Keith M. Mullen; University of Minnesota Duluth

Mathematical modeling can be a very effective tool to better assign risk to potential chemical inhalation exposures. Furthermore, modeling has been shown to be effectively used for a preoperational hazard analysis, litigation purposes, epidemiological studies, and past historical exposures. Mathematical chemical inhalation exposure modeling combined with risk assessment can be a more cost effective tool to better prioritize chemical inhalation hazards in the workplace. The paper presents results of a literature review on the use of modeling as a valid risk assessment tool in high technology industries and evaluates the general accuracy associated with each model by side-byside comparison of the models against actual air sampling results. The primary conclusion of the analysis was that simple models will likely overestimate exposures. These overestimates of modeling uncertainty are due to the uncertainty of the modeling inputs. The result of the analysis further promotes the use of mathematical exposure modeling as a risk assessment tool. Based on the results of the literature review and comparison of mathematical chemical inhalation modeling, the high technology industry could save time, money, and resources by using these techniques to prioritize air sampling.