Systematic model reduction for efficient multimedia/multipathway exposure and dose assessments

S.W. Wang, M. Ouyang, P.G. Georgopoulos (EOHSI, UMDNJ-R.W. Johnson Medical School and Rutgers University)

Traditional methods of modeling exposure and internal dose typically use simplified (and conservative) algebraic equations to calculate these quantities from environmental concentrations. The estimates obtained through these methods usually provide an upper bound of the exposures and doses that actually occur, since they do not account for dynamic concentration variations in microenvironments and have to assume steady-state processes for physiological uptake by the human body. A more accurate approach for calculating exposures and doses requires the combined solution of the differential mass balance equations that govern the microenvironmental and biological concentration levels (physically and physiologically based modeling). However, the computing time and resource requirements for implementing this approach are often prohibitive. The objective of the present study is to demonstrate a method for deriving adjusted exposure factors, which can better reflect the detailed exposure and human intake processes, while allowing the use of simple algebraic relations. The systematic construction of the adjusted exposure factors is performed via the High Dimensional Model Representation (HDMR) approach. In the case study presented here HDMR is used to parameterize the coupled microenvironmental/pharmacokinetic model of the MENTOR (Modeling Environment for Total Risk Studies) framework. As an example, adjusted exposure factors are constructed for modeling the exposures and associated internal doses for waterborne contaminants within a residence. The coupled microenvironmental/pharmacokinetic model considers the properties of the contaminant, three exposure routes (ingestion, inhalation, and dermal absorption), release of the contaminant from water into the air within different rooms in the home, the activities of individuals and the physiological uptake processes. By parameterizing this modeling system through the HDMR technique, adjusted exposure factors are developed for different exposure scenarios involving the contaminant water concentration, activity patterns, house characteristics, and individual physiological attributes.

Acknowledgments: This work has been funded in part by the US Environmental Protection Agency under Cooperative Agreement # EPAR-827033 to the Environmental and Occupational Health Sciences Institute; and by a grant to the Institute for Responsible Management, Consortium for Risk Evaluation with Stakeholder Participation from the US Department of Energy, Instrument DE-FG2600NT 40938. The viewpoints expressed in this work are solely the responsibility of the authors and do not necessarily reflect the views of the US Department of Energy, the US Environmental Protection Agency, or their contractors.