You are here:
The Human Exposure Model (HEM): A Tool to Support Rapid Assessment of Human Health Impacts from Near-Field Consumer Product Exposures
Citation:
Price, P., D. Vallero, J. Bare, S. Csiszar, D. Meyer, K. Dionisio, AND P. Egeghy. The Human Exposure Model (HEM): A Tool to Support Rapid Assessment of Human Health Impacts from Near-Field Consumer Product Exposures. LCA XVI, Charleston, SC, September 26 - 29, 2016.
Impact/Purpose:
Present ongoing work to develop the HEM model and demonstrate how it will contribute to rapid LCA.
Description:
The US EPA is developing an open and publically available software program called the Human Exposure Model (HEM) to provide near-field exposure information for Life Cycle Impact Assessments (LCIAs). Historically, LCIAs have often omitted impacts from near-field sources of exposure. The use of consumer products often results in near-field exposures (exposures that occur directly from the use of a product) that are larger than environmentally mediated exposures (i.e. far-field sources)1,2. Failure to consider near-field exposures could result in biases in LCIA-based determinations of the relative sustainability of consumer products. HEM is designed to provide this information.Characterizing near-field sources of chemical exposures present a challenge to LCIA practitioners. Unlike far-field sources, where multimedia mass balance models have been used to determine human exposure, near-field sources require product-specific models of human exposure and considerable information on product use and product composition. Such information is difficult and time-consuming to gather and curate. The HEM software will characterize the distribution of doses and product intake fractions2 across populations of product users and bystanders, allowing for differentiation by various demographic characteristics. The tool incorporates a newly developed database of the composition of more than 17,000 products, data on physical and chemical properties for more than 2,000 chemicals, and models of exposure for more than 200 categories of consumer products. Product use patterns in HEM will be simulated using agent-based models developed by integrating existing habits and practices and human activity data.HEM is part of a larger program to produce tools that support rapid LCIAs of consumer products. HEM will provide exposure information for each substance known to be used in a product. In addition, the software will determine the combined chemical exposures for products containing multiple chemicals. Finally, the HEM will determine background exposures of chemicals from other consumer products. As a result, HEM will provide the information on near-field sources required to perform LCIA-based comparisons of consumer products.
