Computer Models to Estimate RealWorld Aggregate and Cumulative Exposures and Doses

1
Computer Models to Estimate Real-World Aggregate
and Cumulative Exposures and Doses Edwin J.
Furtaw, Jr. (NERL-Las Vegas), Valerie Zartarian
(NERL-R1), Fred Power (NERL-Las Vegas), Tom
McCurdy (NERL-RTP), Zhishi Guo (NRMRL-RTP), and
Chris Saint (NCER-DC) U.S. Environmental
Protection Agency, Office of Research and
Development
6
Future Directions
3A. Source-to-effects modeling ORD researchers
have developed a variety of computer models to
simulate how pollutants enter and move through
the environment, and how they contact, enter, and
move through exposed humans. For pesticides,
several models have been developed and are being
used for exposure and risk assessments. These
models span the source-to-effects continuum of
processes whereby chemicals are introduced into
the environment, move through multiple
environmental media, are contacted and absorbed
into humans, and have effects on biological
systems that can in turn lead to health effects.
Use of such models will enable risk assessors to
answer questions about the sources, pathways, and
factors that contribute to aggregate and
cumulative exposures and risk.
3F. Exposure-Related Dose-Estimating
(ERDEM) Models ORD scientists have developed the
Exposure-Related Dose-Estimating Model (ERDEM), a
physiologically-based pharmacokinetic (PBPK)
model to simulate the human organism and its
ability to absorb, distribute, metabolize, and
eliminate chemicals. ERDEM has been used to
simulate the reaction of multiple (cumulative)
pesticides and their metabolites with
cholinesterase enzymes in the nervous system, and
will be interfaced with SHEDS for enhanced dose
estimates.

• The development, improvement, and application of
  ORDs exposure-related models is an ongoing
  activity. Future research activities in this
  area include

• Linking environmental, exposure, dose, and
  effects models
• Developing improved methods for modeling
  variability and uncertainty
• Developing advanced computational models of
  organs and other biological systems
• Develop robust mass transfer models for pollutant
  emissions from aqueous solutions
• Evaluate existing sink models with experimental
  data and recommend practically useful sink models
  for use in exposure models
• Develop IAQX Version 2, which includes 8 to 9
  stand-alone simulation programs and supporting
  programs. We hope that, with minor
  modifications, some of these programs can be used
  as front-end modules for NERLs exposure models
• Continued SHEDS-Pesticides model evaluation will
  be conducted in-house on the dietary module and
  on the aggregate estimates of SHEDS-Pesticides
  version 2 (for chlorpyrifos) using available
  measurements data
• SHEDS-Pesticides version 3 will be applied to an
  aggregate exposure assessment case study,
  accounting for co-occurences in space and time
  for the pesticide permethrin (using outputs from
  the indoor residential fugacity model)
• SHEDS-Pesticides version 4 will be developed and
  applied to a cumulative exposure assessment case
  study, accounting for co-occurences in space and
  time for multiple pyrethroid chemicals

3D. Stochastic Human Exposure and Dose
(SHEDS) Models SHEDS inputs include air and
surface concentrations from the indoor fugacity
model, human activity data extracted from ORDs
Consolidated Human Activity Database (CHAD), and
other exposure factors data as compiled in the
EPA Exposure Factors Handbooks (see Moya et al.
poster) and collected through ORD measurement
studies (see Egeghy et al. poster). SHEDS
utilizes probabilistic modeling to estimate
distributions of multiple-pathway (aggregate)
exposure and absorbed dose for user-selected
segments of the population. The outputs from
SHEDS represent the inherent variabilities of
exposure and dose that result from varying
environmental conditions and human behavior, as
well as the uncertainty surrounding those
estimates. SHEDS has been applied for numerous
pollutants of interest to the USEPA, including
chlorpyrifos (Zartarian et al. 2000), arsenic and
chromium from Chromated Copper Arsenate-treated
wood products (Zartarian et al. 2003), air
toxics, and airborne Particulate Matter (PM).
Can computer models be developed and applied to
estimate the human exposure and dose of various
pollutants on humans exposed via multiple routes
and pathways (e.g., inhalation, dietary, dermal
contact)? What models are available to perform
these assessments?
Schematic Diagram of ERDEM
3B. Indoor Fugacity Model for
Pesticides Working with colleagues in academia,
ORD researchers have developed a model to
simulate the indoor fate and transport of
low-volatility pesticides (Bennett et al., 2002,
2004). This model uses the chemical principle of
fugacity to estimate the reversible movement of
pesticides between indoor air and household
surfaces such as carpets and vinyl, and
incorporates ventilation rates to show the
gradual exhausting of the chemicals to the
outdoors. The indoor fugacity model is being
linked to ORDs Stochastic Human Exposure and
Dose Simulation (SHEDS) model for pesticides.
This model is one of several indoor fate and
transport models that ORD has developed.

• The development of models for use in exposure and
  risk assessments serves several purposes
• Improve our understanding of the sources,
  environmental fate and transport, human exposure
  and dose, and health effects of environmental
  pollutants
• Understand the various factors that affect the
  above processes so that researchers can
  prioritize those factors that most need
  additional study
• Provide tools for exposure and risk assessors to
  give a better mechanistic understanding of the
  pathways of exposure and the effects of pollutant
  doses
• Enable risk managers to make better-informed
  decisions on the appropriate uses of chemicals
  and levels that can prevent environmental and
  human health problems.

Compartments in the Indoor Fugacity Model for
Pesticides
3G. Model Development by Grantees In addition to
these ORD-developed models, other
exposure-related models have been developed by
academic researchers working under Science To
Achieve Results (STAR) grants from ORDs National
Center for Environmental Research (NCER).
Examples include
Bennett, D.H. and Furtaw, E.J.Jr. (2004).
Fugacity-Based Indoor Residential Pesticide Fate
Model. Environ. Sci. Technol. 38(7) 2142 -
2152. Bennett, D.H., Furtaw, E.J.Jr., and McKone,
T.E. (2002). A fugacity-based indoor residential
pesticide fate model. Proceedings Indoor Air
2002, July 2002, Monterey, CA. Guo, Z. (2002).
Review of indoor emission source models part 1.
overview. Environmental Pollution, Vol. 120, pp
533-549. Guo, Z. and Roache, N. F. (2003).
Overall mass transfer coefficient for pollutant
emissions from small water pools under simulated
indoor environmental conditions. The Annals of
Occupational Hygiene, Vol. 47, pp
279-286. Sparks, L. E., Tichenor, B. A., Chang,
J., and Guo, Z (1996). Gas-phase mass transfer
model for predicting volatile organic compound
(VOC) emission rates from indoor pollutant
sources. Indoor Air, Vol. 6, pp 31-40. US EPA
(1996). IAQ Model for Windows, RISK Version 1.0,
User Manual, U.S. Environmental Protection
Agency, National Risk Management Research
Laboratory, Research Triangle Park, NC,
EPA-600/R-96-037 (NTIS PB96-501929), March 1996.
(The most recent version 1.9 is available at
EPA website http//www.epa.gov/appcdwww/iemb/risk.
htm). US EPA (2000). Simulation Tool Kit for
Indoor Air Quality and Inhalation Exposure (IAQX)
Version 1.0 Users Guide, U.S. Environmental
Protection Agency, National Risk Management
Research Laboratory, Research Triangle Park, NC,
Report No. EPA-600/R-00-094 (NTIS PB2001-101221),
76 pp. U.S. EPA (2002). Exposure Related Dose
Estimating Model (ERDEM) for Assessing Human
Exposure and Dose. EPA/600/X-04/060. US EPA
(2005). Program PARAMS Users Guide, National
Risk Management Research Laboratory, Research
Triangle Park, NC 49 pp. (In press). McCurdy, T.
and Graham, S. (2003). Using human activity data
in exposure models Analysis of discriminating
factors. J. Exp. Anal. Env. Epi. 13
294-317. McCurdy, T. and Xue, Z. (submitted).
Meta-analysis of Physical Activity Level (PAL)
data for US children and adolescents. J.
Childrens Health. Xue, J., McCurdy, T.,
Spengler, J. and Özkaynak, H. (2004).
Understanding variability in time spent in
selected locations for 7-12-year old children. J.
Exp. Anal. Env. Epi. 14 222-233. Zartarian,
V.G., Özkaynak H., Burke J.M., Zufall M.J., Rigas
M.L., Furtaw Jr. E.J., (2000), A Modeling
Framework For Estimating Children's Residential
Exposure and Dose to Chlorpyrifos Via Dermal
Residue Contact and Non-Dietary Ingestion,
Environmental Health Perspectives, 108(6)
505-514. Zartarian, V.G., Xue J., Özkaynak H.,
Dang W., Glen G., Smith L., Stallings C. (2003),
Pro-babilistic Exposure Assessment for Children
Who Contact CCA-Treated Playsets and Decks Using
the Stochastic Human Exposure and Dose Simulation
Model for the Wood Preservative Exposure Scenario
(SHEDS-Wood), Draft Preliminary Report, prepared
for EPA Office of Pesticide Programs FIFRA
(Federal Insecticide, Fungicide, Rodenticide Act)
Science Advisory Panel (SAP) meeting, December
3-5, 2003.

• Development of a Physiologically-Based
  Pharmacokinetic/Pharmacodynamic Model to
  Quantitate Biomarkers of Exposure for
  Organophosphate Insecticides, Charles Timchalk,
  Battelle Memorial Institute (STAR Grantee -
  R828608)
• Biomarkers of Human Exposure to Pesticides
  Utilizing a New PBPK/PD Model and Kinetic Data on
  Pesticide Metabolism in Humans, James Olson and
  James Knaak, SUNY Buffalo (STAR Grantee -
  R830683)
• Measurements and Models of Longitudinal Dietary
  Intake of Pyrethroid and Organophosphate
  Insecticides by Children, Barry Ryan, Emory
  University (STAR Grantee R829396)
• Lumped Chemical Approach for Fate and Transport
  Modeling of Organic Pollutant Mixtures, Kenneth
  Reardon, Colorado State University (STAR Grantee
  R829355)

3C. NRMRLs Indoor Air Quality Modeling
Research ORDs National Risk Management Research
Laboratory (NRMRL) has unique research facilities
for characterizing indoor pollution sources and
other indoor air related problems such as
pollutant penetration and surface
adsorption/desorption. The facilities include a
small chamber lab, a room-sized well-mixed
chamber, a plug-flow chamber for particulate
matter, a dual-chamber system for pollutant
penetration, and a well-equipped research house.
Data generated from these facilities have been
used to develop source models and indoor air
quality (IAQ) and exposure models. Over 50
indoor source models have been developed by
researchers worldwide. Ten of them were developed
by NRMRL researchers (Guo, 2002). NRMRL is also
actively involved in developing dynamic sink
models, which describe pollutants adsorption and
desorption from interior surfaces. The Langmuir
sink model developed by NRMRL is the most widely
used sink model in IAQ simulation. In the area
of IAQ modeling, NRMRL has developed two
Windows-based IAQ simulation software packages
RISK and IAQX. Both are available to the
public. Initially published in 1996 (Sparks,
1996), RISK has undergone several revisions. The
current version (v 1.9) is a multiple-pollutant
IAQ model developed by using the experimental
data from test chambers and research house. It
takes into consideration building features,
indoor-outdoor air exchange, heating and
air-conditioning system, indoor sources, outdoor
sources, indoor sinks, and air filtration and
cleaning, and computes indoor pollutant
concentration over time, inhalation exposure, and
individual health risks. Simulation package
IAQX (Guo, US EPA, 2000) consists of 5
stand-alone simulation programs a
general-purpose IAQX simulation program and four
special-purpose programs for applications such as
petroleum-based interior paint or building
materials. The two packages combined have more
than 500 registered users in over 20 countries.
These programs have been used by indoor air
professionals for risk management and IAQ
investigation, by emergency response personnel
for emergency planning, by manufacturers for
product stewardship, and by universities for
teaching IAQ courses. One of the major
difficulties in developing physically based
exposure models is to develop methods for
estimating model parameters independently. NRMRL
has been developing such methods to support ORDs
development of exposure and risk models.
Examples of such research outputs include the
development of a method for estimating the
gas-phase mass-transfer coefficient for the
indoor environment (Sparks et al., 1996), and a
method for estimating the overall mass-transfer
coefficient for pollutant emissions from aqueous
solutions applied to interior surfaces (Guo and
Roache, 2003). As part of this effort, NRMRL is
also involved in developing modeling tools. A
recent product in this area is a Windows-based
computer program, PARAMS 1.0, that implements 30
existing methods for parameter estimation.
Exposure Pathways Considered in SHEDS
3E. Consolidated Human Activity Database
(CHAD) ORDs National Exposure Research
Laboratory (NERL) is making a concerted effort to
develop and evaluate human activity data used in
its SHEDS model, and in program office exposure
models, such as APEX and HAPEM. Among other
things, NERL is exploring how representative are
the data in CHAD with respect to literature from
the exercise physiology and clinical nutrition
disciplines. One recent investigation evaluated
age/gender differences in Physical Activity Level
(PAL) obtained in children and adolescents, a
factor found in McCurdy Graham (2003) to be
highly correlated with the time spent outdoors by
that population subgroup. In another analysis,
NERL staff investigated how many days of activity
data were required from an individual over a year
time period in order to be reasonably assured
that their time spent in important locations of
interest from an exposure assessment viewpoint
was well-characterized (Xue et al., 2004). Using
the criterion of reducing the reciprocal of the
intraclass correlation coefficienta metric that
incorporates both intra- and inter-individual
variabilityto a reasonable level, requires that
around 27 days of data for each person be
obtained. These projects are examples of work
being done by NERL staff relating to the
understanding and evaluation of human activity
data used in its exposure models, and eventually
trying to incorporate this knowledge into updates
of the CHAD database.
ORDs human exposure and dose models serve
multiple purposes. In the research field, they
help scientists understand the transport and fate
of chemicals both in various environmental media
and within humans, and the relative importance of
various factors in contributing to exposure,
dose, and risk. The improved understanding from
the use of the models helps to prioritize
additional research. In the regulatory arena,
the models provide risk assessors and managers
with tools for helping to understand the effects
of the pollutants on health risks, the need for
regulatory controls on the use of chemicals, and
the likely effectiveness of various possible
regulatory actions.
ORDs exposure and dose models have been used by
EPAs Office of Pesticide Programs (e.g.,
exposure of children to chromated copper
arsenate-treated wood playsets use of malathion
for head-lice treatment) and by its National
Center for Environmental Assessment (e.g., dose
assessments for several volatile organic
compounds) to conduct exposure and dose
assessments that contribute important scientific
information to risk assessments that in turn
inform risk-management decisions.
2005Feb HH Program Review (Modeling) Poster
EFurtaw.PPT