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University Partnership Agreements

Dr. Daniel A. Vallero, EPA Principal Investigator (919) 541-3306
Email: Vallero.Daniel@epa.gov

Interagency Agreement DW 8993 0582

Lawrence Berkeley National Laboratory, Environmental Energy Technologies Division
Indoor Environment Department, Exit EPA Disclaimer Exposure and Risk Assessment Group
Thomas E. McKone, Principal Investigator

Cooperative Agreement CCR 831 625

Environmental and Occupational Health Sciences Institute (EOHSI)
Paul J. Lioy and Panos G. Georgopoulos, Co-Principal Investigators Exit EPA Disclaimer
Exposure Measurement and Assessment Division and Computational Chemodynamics Laboratory

Both Agreements teams are associated with universities (LBNL with University of California, Berkeley and Stanford University in Stanford, California and EOHSI with Robert B. Wood Johnson Medical School and Rutgers University) resulting in two consortia which collectively possesses world-class experience in human exposure modeling and risk assessment. Collaboration of several EPA scientists with the University Partners contributes to the Research Program at EPA aimed at:

Reducing Uncertainty in Human Health Risk Assessment by  Characterizing Multipathway Human Exposure and Source-to-Dose Relationships Using State-of-the-Art Modeling Methods

Objective: The primary goal of this comprehensive research program is to develop a scientifically-robust, complete multimedia, multipathway Human Exposure Source-to-Dose Modeling Framework software program that can:

Rationale: The overall EPA Exposure and Dose Research Branch needs to have a sound, scientifically-based research approach for understanding how people are actually exposed to pollutants and the factors and pathways influencing exposure and dose. This research program, centered around these two University Partnerships, addresses the need to integrate and incorporate human exposure measurements, models, and methods from all aspects into a comprehensive, scientifically-sound framework for evaluating human exposures.

Benefits: The modeling framework software and its various components and modules and other analytical tools developed through these UPAs will be of great value to researchers engaged in the development, refinement, and interpretation of human exposure modeling techniques.

In addition, the risk assessment community will have a set of useful modeling software packages to enable multimedia, multipathway exposures to be estimated - with explicitly quantified variability and uncertainty - for a wide variety of subpopulations and environmental contaminants. This capability will also provide EPA Program Offices with the analytical software tools and algorithms needed to support the prioritization of pollutants and pollutant source categories in support of future mitigation strategies to evaluate human exposure and risk implications of pollutants in air, soil, food and water.

In designing future measurement studies, this capability will aid in determining which areas in the source-to-dose human exposure process are associated with the greatest uncertainties.

Progress to Date: Research has focused on the development of the conceptual components for a source-to-dose human exposure modeling framework and software system. Initial testing has been done on the framework for exposures and dosimetry using the Stochastic Human Exposure and Dose System (SHEDS) models. Significant progress has been made in the development and refinement of important framework components such as an improved understanding of phase, spatial, and temporal distributional characteristics for various pollutants of interest and the prediction of variability and uncertainty in modeling outputs.

Selected Publications:

Burke, J. M., Zufall, M. J. and Ozkaynak, H. "A Population Exposure Model for Particulate Matter: Case Study Results for PM2.5 in Philadelphia, PA," Journal of Exposure Analysis & Environmental Epidemiology (2001) 11(6), 470-489.

Zartarian, V.G., H. Ozkaynak, J.M. Burke, M.J. Zufall, M.L. Rigas, and E.J. Furtaw, Jr. "A modeling framework for estimating children's residential exposure and dose to chlorpyrifos via dermal residue contact and nondietary ingestion." Environ. Health Perspect. 108, 6: 505-514 (2000).

Klepeis, N. E., W. C. Nelson, W. R. Ott, J. P. Robinson, A. M. Tsang, P. Switzer, J. V. Behar, S. C. Hern and W. H. Engelmann, "The National Human Activity Pattern Survey (NHAPS): A Resource for Assessing Exposure to Environmental Pollutants," J. Exposure Analysis & Environmental Epidemiology (2001), 11(3), 231-252.

Ozkaynak, H., Evans, G. F., Pahl, D. A., and Graham, J. A. Overview of EPA's human exposure and source-to-dose modeling program: HEADSUP. ISEA 2000 Exposure Analysis in the 21st Century: Integrating Science, Policy, and Quality of Life, Monterey Peninsula, CA, October 24-27, 2000.

Bennett, D. H., T. E. McKone, and W. E. Kastenberg, "Evaluating Chemical Persistence in a Multimedia Environment: A CART Analysis," J. Environmental Toxicology and Chemistry (2000), 19, 32-46.

Bennett, D. H., T. E. McKone, and W. E. Kastenberg, "CART Screening Level Analysis of Characteristic Time - A Case Study," Presented at Special Session on Persistent Organic Pollutants, 217th ACS National Meeting and Exposition, March 21-25, 1999, Anaheim, CA. Published in Persistent, Bioaccumulative and Toxic Chemicals, ACS Symposium Series, 2001, No. 773, R. L. Lipnick (ed.), 29-41.

Maddalena, R. L., T. E. McKone, D. P. H. Hsieh, and S. Geng, "Influential Input Classification in Probabilistic Multimedia Models," Stochastic Environmental Research and Risk Assessment (2001), 15, 1-17.

Bennett, D. H., M. Scheringer, T. E. McKone, and K. Hungerbuhler, "Predicting Long-Range Transport: A Systematic Evaluation of Two Multimedia Transport Models," Environmental Science & Technology (2001), 35, 1181-1189.

Switzer, P. and W. R. Ott, "Theory of Exposure Models: Derivation of an Indoor-Outdoor Averaging Time Model from the Mass Balance Equation," Department of Statistics, Stanford University, Stanford, CA, Technical Report No. 2001-22, September 2001, 67 pp.

Human Exposure and Atmospheric Sciences

Research & Development | National Exposure Research Laboratory

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