Description:

MENTOR-1A uses an integrated, mechanistically consistent source-to-dose modeling framework to quantify inhalation exposure and dose for individuals and/or populations due to co-occurring air pollutants. It uses the "One Atmosphere" concept to characterize simultaneous exposures to multiple atmospheric contaminants taking into account their physical and chemical interactions. MENTOR-1A uses, as one of the options, the USEPA’s Stochastic Human Exposure and Dose Simulation (SHEDS) approach.
MENTOR-1A characterizes cumulative exposures to co-occurring air pollutants, and calculates exposure and dose profiles, while providing the ability to focus on mechanism-relevant time scales and subpopulations of interest. This is achieved by combining information, as per the needs of a specific application, on: demographic characteristics of the population under study, outdoor concentration distributions, indoor/outdoor air exchange rates, indoor sources, time-activity diaries, and biologically based dosimetry. It uses the 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.
MENTOR-1A has been applied to date to simulate (a) regional potential population exposures and (b) urban population exposures and doses to co-occurring gas phase pollutants and particulate matter. Specifically it has been applied to criteria pollutants such as ozone, and PM2.5, and to air toxics such as benzene, formaldehyde and xylene. Additionally, MENTOR-1A has been applied to simulate longer term (year long) exposures to reactive and relatively inert air pollutants, and has also been applied to estimate study-specific exposures and doses to selected air toxics in multiple cities.

Record Details:

Model Detail:

Peer reviewed journal publications and technical reports presenting the application of MENTOR-1A are available.

Model URL :http://www.ccl.rutgers.edu/mentor/

Model Guidance Documents :Not currently available.

Technical documents on the formulation and applications of MENTOR/SHEDS-1A are available, click here.

Model Decision Documents :Selected publications describing the system and applications:

• Foley, G., Georgopoulos, P.G. and Lioy, P.J. (2003). "Examining Accountability for Changes in Population Exposures to 8-Hour Ozone Standard with Implementation of Different Control Strategies." Environmental Science and Technology 37(21):302A-309A.

• Georgopoulos, P.G., Wang, S.W., Vyas, V.M., Sun, Q., Burke, J., Vedantham, R., McCurdy, T. and Ozkaynak, H. (2004). "A Source-To-Dose Assessment of Population Exposures to Fine PM And Ozone in Philadelphia, PA, During a Summer 1999 Episode." Journal of Exposure Analysis and Environmental Epidemiology (accepted for publication).

• Georgopoulos, P.G., Wang, S.W., Vyas, V.M., Sun, Q., Chandrasekar, A., Shade, P., Vedantham, R., Burke, J., McCurdy, T. and Ozkaynak, H. (2004). A Source-to-Dose Assessment of Population Exposures to Fine PM, Ozone and Air Toxics in Philadelphia, PA, During a 1999 Summer Episode. Technical Report CERM:2003-01. Prepared for USEPA (Revised draft submitted for agency review).

• 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.).

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 Inputs :

• Environmental concentrations of pollutants: these are typically obtained via spatio-temporal interpolation of either the outputs from models such as Models-3 CMAQ (Community Multiscale Air Quality), or measurements at monitoring sites.
• Demographic characteristics of the population of interest.
• Time-location-activity diaries, other activity information (e.g. METS values) from the US EPA's Consolidated Human Activity Database (CHAD),
• Indoor/outdoor air exchange rates, uptake and deposition coefficients.
  
  Model Outputs :Output options include individual/subpopulation temporal exposure and dose profiles (for relevant time scales), summary statistics tables, cumulative internal doses of the contaminants, sensitivity and uncertainty analysis for calculated exposures and doses.
  
  otheruserdocs :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.)

  Foley, G., Georgopoulos, P.G. and Lioy, P.J. (2003). Examining Accountability for Changes in Population Exposures to 8-Hour Ozone Standard with Implementation of Different Control Strategies. Environmental Science and Technology 37(21): 302A-309A

  Georgopoulos P.G., Wang S.W., Vyas V.M., Sun Q., Burke J., Vedantham R., McCurdy T. and Ozkaynak H. (2005). A source-to-dose assessment of population exposures to fine PM and ozone in Philadelphia, PA, during a summer 1999 episode. Journal of Exposure Analysis and Environmental Epidemiology 15: 439−457.

  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. (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.

  Zhu X., Fan Z., Wu X., Meng Q., Wang S.-W., Tang X., Ohman-Strickland P., Georgopoulos P., Zhang J., Bonanno L., Held J. and Lioy P. (2008). Spatial variation of volatile organic compounds in a "Hot Spot" for air pollution. Atmospheric Environment 42 (32): 7329-7338.

  Wang S.-W., Tang X., Fan Z., Lioy P.J. and Georgopoulos P.G. (2009). Modeling personal exposures from ambient air toxics in Camden, New Jersey: An evaluation study. Journal of the Air and Waste Management Association 59: 733-746.
  
  

  Model Computer Requirements:

  Model Operating Systems Needs :Any of the following: Windows 2000/XP/Vista, Linux, Solaris, Mac OS X.
  
  Model Hardware Needs :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 processor.
  
  Model Programming Language(s) :Matlab version 6.5 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.
  
  other_req :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.