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Model Report

Modeling Environment for Total Risk-4M

Last Revision Date: 07/11/2011 View as PDF
General Information Back to Top
Model Abbreviated Name:

MENTOR-4M
Model Extended Name:

Modeling Environment for Total Risk-4M
Model Overview/Abstract:
MENTOR-4M uses an integrated, mechanistically consistent, source-to-dose modeling framework to quantify simultaneous exposures and doses of individuals and populations to multiple contaminants. It is an implementation of the MENTOR system for exposures to Multiple contaminants from Multiple media, Multiple routes, and Multiple pathways (4M). MENTOR-4M uses, as one of the options, the USEPA’s Stochastic Human Exposure and Dose Simulation approach.

MENTOR-4M combines microenvironmental and human activities characterization to assess the relative contribution of (1) media (e.g., water, food, dust), (2) pathways (e.g., drinking water, diet, hand-to-mouth) and (3) routes (e.g., oral, inhalation, dermal) to (4) multiple contaminant (e.g. VOCs and heavy metals) exposures for individuals or populations. It addresses aggregate and cumulative exposures to co-occurring pollutants in a consistent manner, and provides the ability to focus on mechanism-relevant time scales and subpopulations of interest. It uses two dimensional Monte-Carlo methodology to quantify variability and uncertainty in model inputs and outputs.

MENTOR-1A can be used for both “Individual Based Exposure Modeling” (IBEM) and “Population Based Exposure Modeling” (PBEM) approaches. Both these approaches employ a “Person Oriented Modeling” (POM) formulation, i.e. they are driven by the attributes and activities of the exposed “real” and/or “virtual” individual(s). While IBEM implementations utilize the information relevant to “actual” individuals (and produce exposure and dose estimates specific to each one of them), the PBEM implementations focus on the statistical characterization of the exposures and doses of selected populations (at the census tract, county, or state etc. level). Thus, the questions posed by any particular environmental health problem can be tailored to small sets of individuals potentially at risk or to larger populations or subpopulations of interest.

To date, demonstration applications of the model have focused on simulating aggregate/cumulative exposures to arsenic, copper, mercury/methylmercury, and trichloroethylene (TCE); populations studied have included NHEXAS-V study subjects and residents in Oswego county, NY.

Keywords: Modeling ENvironment for TOtal Risk studies (MENTOR) for Multiple co-occurring contaminants and Multimedia, Multipathway, Multiroute exposures (4M)
Model Technical Contact Information:
Agency Contact
Dan Vallero
USEPA, NERL
Vallero.Daniel@epamail.epa.gov
919-541-3306

Developer Contact
Dr. Panos Georgopoulos
panosg@fidelio.rutgers.edu
732-445-0159

Dr. Shengwei Wang
shengwei@fidelio.rutgers.edu
732-445-0393

Dr. Sastry Isukapalli
sastry@fidelio.rutgers.edu
732-445-0171

Computational Chemodynamics Laboratory
www.ccl.rutgers.edu
EOHSI
A Joint Institute of UMDNJ - R.W. Johnson Medical School and Rutgers University
170 Frelinghuysen Rd.
Piscataway, NJ 08854

Model Homepage: http://www.ccl.rutgers.edu/mentor/ Exiting the EPA Site
Substantive Changes from Prior Version: Incorporation of modules for characterizing long-term (e.g., month to year long) dietary exposures
Plans for further model development: Refinements in the treatment of interindividual and intraindividual metabolic variability that arises due to genetic factors.

User Information Back to Top
Technical Requirements
Computer Hardware
Operational on multiple, alternative hardware platforms: Intel/AMD based PCs, Sun Workstations (e.g. Sparc), Linux servers or clusters, and Apple Macintosh computers. Minimum requirements: 10 GB free hard drive space, 512 MB RAM, and 500 MHz CPU processor.
Compatible Operating Systems
Any of the following: Windows NT/2000/XP, Linux, Solaris, Mac OS X.
Other Software Required to Run the Model
Matlab version 6.5 or higher for Windows/Linux/Solaris/Mac OS X (Matlab statistical toolbox needed). Local or remote installation of Access or MySQL databases are needed. Depending on the application, SAS 8.0, C, or Fortran compilers may be needed. ArcGIS 8 is required for visualization.
Download Information
http://www.ccl.rutgers.edu/mentor/exit EPA
Using the Model
Basic Model Inputs
  • Demographic characteristics of the population under study.
  • Multimedia concentrations of contaminants (e.g. air, water, soil/dust, dietary).
  • U.S. EPA's Consolidated Human Activity Database (CHAD) time-location-activity diaries, other activity pattern information (e.g. METS values, frequency of hand-to-mouth contact.).
  • Other exposure factors (e.g. dermal transfer coefficients, dermal absorption rates, food consumption rates, drinking water consumption rates).
Basic Model Outputs
Output options include individual/population temporal exposure and dose profiles, summary statistics tables, contributions by route and pathway, cumulative internal doses of the contaminants (and their metabolites), distributions in target organs, model sensitivity and uncertainty analysis through HDMR (High Dimensional Model Representation) and SRSM (Stochastic Response Surface Method).
User Support
User's Guide Available?
Not currently available.

Technical documents on the formulation and applications of MENTOR/SHEDS-4M are available, click here.exit EPA

Other User Documents
Selected publications describing the system and applications:

Isukapalli, S.S. and Georgopoulos, P.G. (2001). Computational Methods for Sensitivity and Uncertainty Analysis for Environmental and Biological Models (EPA/600/R-01-068). Research Triangle Park, NC. US EPA, National Exposure Research Laboratory (145 pp.)

Wang, S.W., Georgopoulos, P.G., Li, G. and Rabitz, H. (2003). RS-HDMR with Nonuniformly Distributed Variables: Application to an Integrated Multimedia/Multipathway Exposure and Dose Model for Trichloroethylene. Journal of Physical Chemistry A 107: 4707-4716

Wang S.W., Georgopoulos P.G., Li G. and Rabitz H. (2005). Characterizing uncertainties in human exposure modeling through the Random Sampling - High Dimensional Model Representation (RS-HDMR) methodology. International Journal of Risk Assessment and Management (IJRAM) 5: 387-406.

Hore P., Zartarian V., Xue J., Özkaynak H., Wang S.-W., Yang Y.-C., Chu P.-L., Sheldon L., Robson M., Needham L., Barr D., Freeman N., Georgopoulos P. and Lioy P.J. (2006) Children’s residential exposure to chlorpyrifos: Application of CPPAES field measurements of chlorpyrifos and TCPy within MENTOR/SHEDs pesticides model. Science of the Total Environment 366(2-3):525-537.

Georgopoulos P.G., Wang S.W., Lioy P.J., Georgopoulos I.G. and Yononne-Lioy M.J. (2006). Assessment of human exposure to copper: A case study using the NHEXAS database. Journal of Exposure Science and Environmental Epidemiology 16: 397-409.

(continued below)

Availability of User Support
Additional Publications include:

Georgopoulos P.G. and Lioy P.J. (2006). From theoretical aspects of human exposure and dose assessment to computational model implementation: The modeling environment for total risk studies (MENTOR). Journal of Toxicology and Environmental Health - Part B, Critical Reviews 9(6): 457-483.

Cohen M., Sunderland E., Georgopoulos P.G., Wang S.W., Isukapalli S., Yang Y.C., Sasso A., Tong S., Xue J., McCurdy T., Zhang M., Sheldon L. and International Air Quality Advisory Board (2006). Development of a multicompartment mercury model for Lake Ontario: Tracking mercury from sources, deposition, and dispersion to fish to accumulation in humans. In Priorities 2005 - Priorities and Progress Under the Great Lakes Water Quality Agreement. Windsor, Ontario, Canada, International Joint Commission (IJC): pp.39-69

Georgopoulos P.G., Wang S.-W., Yang Y.-C., Xue J., Zartarian V.G., McCurdy T. and Ozkaynak H. (2008). Biologically based modeling of multimedia, multipathway, multiroute population exposures to arsenic. Journal of Exposure Science and Environmental Epidemiology 18(5): 462-476

Georgopoulos P. (2008). A multiscale approach for assessing the interactions of environmental and biological systems in a holistic health risk assessment framework. Water, Air, and Soil Pollution: Focus 8(1): 3-21.

Georgopoulos P.G., Krishnan K. and Isukapalli S. (2009-in press). Exposure modeling – with emphasis on multiple source and multiple routes. In Quantitative Modeling in Toxicology. Krishnan, K. and Andersen, M. E. (eds.), John Wiley

User Qualifications
Bachelor’s degree in Environmental Science/Engineering, Chemical Engineering, Exposure Science, Meteorology, or related fields.

Model Science Back to Top
Problem Identification
There is a need for reducing uncertainty in Human Health Risk Assessment, and for interpreting exposure/dose information relevant to human health studies. This requires development and application of computational models that are capable of representing these relationships at spatial scales ranging from geographic regions to personal and residential microenvironments.

The MENTOR toolbox is an open and “flexible” system that provides components for performing either simple (screening) or detailed (comprehensive) simulations at various scales and levels of detail. MENTOR-4M provides modules for assessing simultaneous exposures and doses of individuals and populations to multimedia contaminants.

The approach of MENTOR has been to develop, apply and evaluate state-of-the-art modeling methods for a wide range of environmental applications, that utilize existing models, when available, or provide new approaches to “fill gaps” in the source-to-dose sequence. MENTOR links state-of-the art predictive models of environmental fate/transport and of human exposure and dose; these models are coupled with up-to-date national, regional, and local databases of environmental, microenvironmental, biological, physiological, demographic, etc. parameters. Thus MENTOR is not a “new model”; it is an evolving open computational toolbox, containing both “pre-existing” and new tools, intended to facilitate consistent multiscale source-to-dose modeling of exposures to multiple contaminants, for individuals and populations

Summary of Model Structure and Methods
MENTOR (Modeling ENvironment for TOtal Risk) is a modular "modeling support system" that can be described as an expandable computational toolbox. It facilitates consistent multiscale source-to-dose modeling of exposures to contaminants for individuals and populations. It includes state-of-the-art models for environmental, microenvironmental, and biological processes and of human activities. The MENTOR system enables application and evaluation of models in the source-to-dose sequence either in a "stand-alone" mode, or within an integrated, mechanistically consistent, framework.

MENTOR/SHEDS-4M is an implementation of the MENTOR system that employs the SHEDS (Stochastic Human Exposure and Dose Simulation) approach for multiroute, multimedia, multipathway, multicontaminant exposures.

The consistency achieved with MENTOR/SHEDS improves upon the "traditional" approach, where different exposure factors and activity patterns could have been used in assessing exposures to different co-occurring pollutants.

Model Evaluation
Three case studies were conducted using the Population Based Modeling (PBM) option of MENTOR/SHEDS to characterize population exposures to arsenic in Pima County, AZ and Hunterdon County, NJ; and co-occurring exposures to arsenic and trichloroethylene in Franklin County, OH. The first two case studies above considered the exposure routes of inhalation and drinking water consumption only, while the third study (Franklin County, OH) took into account the additional exposure routes of food intake and non-dietary ingestion. In the Franklin County case study, the model results were evaluated by comparing predicted distributions of (a) total arsenic amounts in urine and of (b) TCE blood concentrations for the population studied with those measured in the National Human Exposure Assessment Survey (NHEXAS) Region-V study. The agreement of distributions of biomarker levels calculated from MENTOR/SHEDS-4M and measured in the NHEXAS-Region V study was satisfactory. Ongoing work focuses on improving the treatment of interindividual and intraindividual metabolic variability and on the impact of regional and local factor issues.

Key Limitations to Model Scope
The temporal extent of MENTOR-4M ranges from a day to up to a year. Though it can be applied to longer-term simulations, the underlying data needs (e.g. residue data, food and water intake distributions, etc.) can become prohibitive. The spatial resolution is currently up to a county, and the extent can be up to the entire United States. However, with higher resolution data sets, or study-specific information, the system can be applied for up to a single household.

Case Studies
Georgopoulos P.G., Wang S.W., Yang Y.C., Xue J., Zartarian V, McCurdy T. and Özkaynak H. (2007). Biologically-based modeling of multimedia, multipathway, multiroute population exposures to arsenic (Submitted for publication).

Georgopoulos P.G. and Lioy P.J. (2006). From theoretical aspects of human exposure and dose assessment to computational model implementation: The modeling environment for total risk studies (MENTOR). Journal of Toxicology and Environmental Health - Part B, Critical Reviews 9(6): 457-483.

Georgopoulos P.G., Wang S.W., Lioy P.J., Georgopoulos I.G. and Yononne-Lioy M.J. (2006). Assessment of human exposure to copper: A case study using the NHEXAS database. Journal of Exposure Science and Environmental Epidemiology 16: 397-409.

Hore P., Zartarian V., Xue J., Özkaynak H., Wang S.-W., Yang Y.-C., Chu P.-L., Sheldon L., Robson M., Needham L., Barr D., Freeman N., Georgopoulos P. and Lioy P.J. (2006) Children’s residential exposure to chlorpyrifos: Application of CPPAES field measurements of chlorpyrifos and TCPy within MENTOR/SHEDs pesticides model. Science of the Total Environment 366(2-3):525-537.

Wang S.W., Georgopoulos P.G., Li G. and Rabitz H. (2005). Characterizing uncertainties in human exposure modeling through the Random Sampling - High Dimensional Model Representation (RS-HDMR) methodology. International Journal of Risk Assessment and Management (IJRAM) 5: 387-406.

Georgopoulos P.G., Wang S.W., Yang Y.C., Xue J., Zartarian V, McCurdy T. and Özkaynak H. (2003). Assessing Multimedia/Multipathway Exposures to Arsenic Using a Mechanistic Source-to-Dose Modeling Framework. Technical Report CERM:2003-02 Prepared for USEPA (Revised Draft submitted for agency review)

(more case studies on previous page)


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