EPA/600/A-94/252


      Exposure  Assessment Methodologies for  Humans and  Ecosystems
                              Daniel A. Vallero
                   Human Exposure and Field Research Division
              Atmospheric Research and Exposure Assessmen Laboratory
                      U.S. Environmental Protection Aeency
                       Research Trianele Park. NC. USA "
Disclaimer:

This paper has been reviewed in accordance with the United  States
Environmental  Protection  Agency's peer  and administrative review policies
and approved for presentation and publication.  Mention of trade names or
commercial products does  not  constitute  endorsement or recommendation  for
use.
                                ABSTRACT

Health scientists and risk assessment experts are developing approaches to
estimate exposure of human populations and ecosystems to environmental
contaminants. Ecological scientists are exploring methodologies for estimating
the exposure of ecosystems, or subdivisions within an ecosystem, to
environmental stresses, while human health scientists are investigating
approaches for estimating exposures to contaminants that can affect human
health.  Exposure assessment methods vary significantly, depending upon
factors, such  as the scale of the exposure, the measurement focus, and level of
biological organization.  The paper discusses the elements of ecological and
human exposure assessment methodologies. Examples of multiple pathway
exposure assessments are provided to illustrate human exposure concepts,  and
how thev mav also applv to ecosvstem exposure assessments. Ecosvstem and
        -     «•      I I ^       -        A                       -
human exposure assessment paradigms are compared and contrasted with  regard
to the level of biological organization, source-receptor relationships, biomarkers,
dose, pollutant characteristics,  and modeling.

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Exposure  Assessment  Methodologies for Humans and Ecosystems
Daniel A. Vallero
Hi-.man Exposure and Field Research Division (MD-56)
Atmospheric Research and Exposure Assessment Laboratory
U.S. Environmental Protection Aeency
Research Triangle Park. NC 27711
USA
Introduction

       Human exposure is the contact between a "contaminant and the human body"
(Sexton and Ryan, 1988).  By extension, ecological exposure is the contact between the
contaminant and an ecosystem or its components (e.g., communities, species, or individual
organisms). The principal elements of exposure are the magnitude of the pollutant
concentration, the duration of the exposure, and the frequency of the exposure.  Human
exposure assessments of these three elements include measuring pollutant concentrations,
in the ambient environment, as well as in microenvironments (including outdoor, indoor,
transitory, occupational, and personal).  Assessments also need  to characterize personal
exposure scenarios, by describing activity patterns and uptake rates. Ecological exposure
is the expression of the magnitude, duration, and frequency of contact between an
ecological resource and a "stressor," i.e., a physical, chemical, or biological entity that can
induce an  adverse response" (Risk Assessment Forum, 1992).
       Risk assessors and other scientists are developing approaches to estimate exposure.
Ecological scientists are exploring methodologies tor estimating the exposure of
ecosystems and their subdivisions to environmental stresses, while human risk assessment
analysts are investigating approaches for estimating exposures to contaminants that could
affect human health.  Exposure assessment methods vary with the spatial and temporal
scale of the exposure, the  measurement focus,  and the level of biological organization.
This paper compares ecological and human exposure assessment methodologies concerning
the types and scales of monitoring and sampling designs, the availability of models to
simulate and estimate exposure, and the components necessary  to calculate exposure.  The
National Research Council of the National Academy of Sciences < 1983) developed a risk
assessment paradigm with four separate steps: hazard identification; dose-response
assessment; exposure assessment; and risk characterization.  Regulatory agencies, like the
U.S. Environmental Protection Agency (EPA), ha%'e applied this paradigm to human  health
risks. Each of the four steps has been subdivided further. For exposure assessment. EPA

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applies the steps shown in Figure 1:  source characterization: transport, transformation, and
fate; pathwav.;; environment.) i oncentrations: and exposure measurements.
       Lipt,/n et al (1993) ha\e questioned the appropriateness of applying the NAS
paradigm to i^ological risk assessment, since several "intrinsic distinctions" can be drawn
between human health and eer-iogical risk assessments. Ecological target receptors may be
unknown or ambiguous and the level of biological organization is variable. Exposure
assessment, however, is similar for ecological and human risk assessments (Figure 2).
                          Exposure Assessment
         Source
      Characterization
Environmental
  Pathways
                Environmental
                Concentrations
                  Transport,
             Transformation* Fate
                                              Measurements
                                               of Exposure
Internal Dose
                                                             Effects
                                      Effects Assessment
Figure 1:  Simplified Exposure Assessment Paradigm.
Exposure Assessment  Methodologies
       Routes, magnitude, duration, and frequency of exposure are important
considerations for both human and ecosystem exposure assessments. While both
paradigms include measurements of pollutant concentration, the major difference rests in
measurements of behavior. For humans, exposure is a function of concentration, activity
pattern, and uptake (ventilation, consumption, and absorption!. For ecosystems, exposure
is a function of pollutant concentration in the abiotic and biotic environment, and ecological
function and structure (e.g., species migration, bioaccumuiation and sequestration rates,
bioenergetics. succession, and nutrient cycling).  Ecological exposure assessments can be
complicated because changes in function and structure are expressions of both exposure
and effect; i.e.. functions and structures change as a result of the exposure.  All pathways,
e.g., ingestion. dermal, or inhalation, must be included to express exposure fully. A

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 single-species exposure assessment (e.g., for an endangered species) can be very similar 10
 the multipathway. human exposure assessment described or> rije left side of Figure 2.
       Multiple pathway field studies are designed to measure concentrations of pollutants
in various environmental media.  Temporal and spatial distributions of these measurements
give an indication of the frequency, magnitude and duration or the exposure. The level of
temporal  (continuous, hourly, 12-hour. 24 hour, monthly, annual average) and spacial
precision of these measurements varies depending upon the field study objectives and
methods.
     COMPARISON OF EXPOSURE ASSESSMENT PARADIGMS
                 Human
      1 Source identification. Characterization
            & Apportionment
      1 Transport/ Transformation/
            Interaction/Fate
      • Environmental Concentration
      1 Exposure Measurements (Potential Dose)
                 t
      Actual Dose
      « Applied Dose
      • Internal Dose
      « Delivered Dose
      » Biologically Effective Dose
       » Biomarkers
                                       Ecological
                               • Source Identification, Characterization
                                     Sc Apportionment
                               1 Transport/Transformation/
                                     Interaction / Fa te
                               1 Deposition
                               1 Physical/Chemical Measurements of
                                     Srressor in Ecosystem
                                                Phys/Chem/Bio
                                                  Degradation
                                * Accumulation into Abiotic and Biotic
                                      Components of Ecosystem
                                                « Biomarkers
 Figure 2:
Exposure components of risk paradigms are similar for humans and ecosystems.
        EPA developed the Total Exposure Assessment Methodology (Wallace, 1987) to
 estimate total human exposure using personal exposure monitors. Results from these
 TEAM studies indicate that a person's activities and behavior greatly affect one's actual
 exposure. Even when ambient concentrations are similar, activity variables, e.g., cleaning.
 cooking, smoking (active and passive exposure), time spent indoors versus  outdoors, and
 transportation, can introduce considerable variability for most contaminants.

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       The U.S. EPA's (1990) Non-Occupational Pesticide Exposure Study (MOPES)
illustrates the necessary methods to measure and estimate total exposure irom the air
pathways. MOPES was a i.iulti-season study of pesticides commonly used in and around
the home. The study households were selected from stratified random population samples
in two urbanized areas. An embedded nine-home pilot study conducted in Jacksonville.
Florida found that household dust may be a significant pathway for exposure to previously
used pesticides ; e.g., Chlopyrifos, Propoxur. and Chlordane.  NOPES extended the
findings of other research which found indoor environmental exposures of certain
pollutants to be considerably higher than outdoor exposures. Other pathways, such as diet
and drinking water, can also be significant pathways for other pesticides. NOPES was
successful in estimating exposure levels for populations of two urban areas of the United
States, assessing the relative importance of each exposure pathway to the overall level of
exposure; characterizing the components of variability in the observed exposure levels.
and, in beginning to model the relationships between exposure levels, rates of use. activity
patterns, and other factors that could contribute to variation in exposure levels.  These
results demonstrated that the multi-pathway approach can be applied to nonoccupational
exposures through inhalation. The study's probability-sampling design also allowed for
inferences about the distribution of exposures for populations.
       The objectives tracked well with the approaches recommended by the NAS (1991)
for assessing human exposure to airborne pollutants (Figure 3), illustrating the need for
data from direct measurements (personal and biomarker monitoring)  and from indirect data
gathering methods, such as diaries and questionnaires (especially to gain knowledge about
activities).  NOPES characterized exposure, including seasonal variations, by monitoring
and comparing outdoor, indoor, and personal air concentrations.  The study  also
demonstrated that questionnaire-based models may be practical for particular analytes: e.g.,
certain termiticide concentrations were related to use and  application history, age of home,
and household inventory of the pesticides.

Scale  of Exposure

       Exposure studies can range from  subcellular exposure to  global.  Methods for
assessing exposure  for an individual organism (e.g., one human  being; differ from
methods used to assess population exposure. Likewise, estimating exposures for a  single
ecosystem component: e.g., a lake or wetland, will be different from a large-scale exposure
assessment of region or biome.

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       In the case of the small-scale assessment (residential, occupational, farms), a
researcher may be able to determine signals of exposure ibr a wide array of contaminants.
and pro/ide detailed and specific information about a subject s activity patterns. Often.
however, scientists are asked to estimate exposure of entire populations or target groups.
wherein gathering detailed and specific information about the exposure of each individual in
a population is scientifically and economically infeasible. Moreover, in the case of
ecosystems, detailed information about individuals may have less importance than the
interrelationships and diversity of a larger ecological community; true to the adage, "not
seeing the forest for the trees." The hypothesis or study objective determines the scale of
an exposure assessment.
                           Exposure Analysis
                             Approaches
Biological
Markers


Environmental
Monitoring
1

PharmacoKinetic &
Pharmacodvnamtc Models
 Figure3    Possible approaches for analysis of air contaminant exposures (National
           Academy of Sciences, 1991). Aythor s Xote: 'Exposure Models" are inputs to
           'Pharmacokinetic and Pharrnacodynamic Models.  50 a line should connect
           them.

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Focus of Exposure  Measurements

       Human and ecosystem expo .ure measurement and assessment methods vary.  Studies
may be conducted to estimate the exposure of one type of receptor to a single pollutant: e.g.,
blood lead levels in children.  A sinr.ie pollutant exposure assessment can be conducted for a
number of receptors; e.g., bone-lead concentrations in urban and rural school-aged children,
lead concentrations in lawns bordering highways, and translocated lead in leafy vegetables
downwind from an industrial  source. The process is  far more complex when a number of
pollutants and receptors are included in risk assessment; e.g., ecological and human exposure
to dioxins and toxic metals near potential agricultural, industrial, and transportation sources.
       The measurement focus varies considerably among exposure assessments. Ambient
outdoor, indoor, and personal exposures are directly measured or input into models.  "Direct"
measurements are usually used to make spatial and temporal inferences about pollutant
concentrations, since the measurement is a value at one  point for one time period.  Stationary
monitoring devices provide outdoor and indoor measurements. Passive (diffusion) and active
(constant flow) sampling devices are used for personal and microenvironmental measurements.
Recently, researchers have deployed these devices to  enhance ambient monitoring data and to
provide average environmental exposure estimates for ecosystems, especially for forest stands.

Source-Receptor  Assessment

       Determining source characteristics and the transport and transformation of
pollutants is similar for human and ecological exposure assessments.  Various methods for
identifying and apportioning the sources are available, including emission inventories.
source-receptor models, and actual measurements (e.g., stack tests, remote sensing, and
continuous emission monitoring). Emission inventories are often derived from calculations
of fuel or feedstock and the manufacturing processes taken from emission forms completed
by the operator; e.g., incinerator operators provide information about the type of fuel;
amount and type of feedstock; a description of the combustion processes: and the  types of
stacks and vents at the facility, which is used to generate the emission inventory.  This
information can be highly uncertain and is not sufficiently specific to characterize potential
pollutant sources.
       Stack tests, such as dilution samplers, are much more reliable than emission
inventories, but are cosily and require on-site access. Actual measurements of stack
emissions are necessary to apportion the sources of pollutants to which a receptor is
exposed (Figure 3).  Temporally and spatially precise measurements are needed at the

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source (i.e.. for "source signatures") to be coupled with ambient measurements of chemical
species that are "mancers" of particular sources.  For example, the U.S. EPA's chemical
mass balance model (CMB 7.0), developed by Watson et al (1990) is used by the Agency
to "identity and the presence ot and to quantity source contributions to receptor
concentrations."  Dispersion models are also useful exposure tools which require emi->sion
rates be estimated and combined with meteorology, and transformation algorithms to
estimate the relative contribution of sources to measurements of pollutant concentrations at
a receptor.  If variability and uncertainty are high for emissions, as is common for source
information derived from inventories, the dispersion model-derived source-receptor
relationship is also highly uncertain and variable.
                              Exposure Assessment
                                               *  Transport and
                                                 Transformation,
                                                 Interactions. & Fate
                                               *  Source/Receptor Models
                                                 link sources with
                                                 concentrations found in
                                                 environment
                                               •  Models are evolving/
                                                 improving.
                               Airshed
Figure 4:   After emissions are released, they undergo physical and chemical transformation
           before being deposited.  Receptors can be human or ecological. The level of
           biological organization can be subcellular to regional.  Human exposure assessments
           are often conducted at the population or subpopulation level (e.g., cancer risk per
           million in the United States). Ecological exposure assessments are conducted at
           many different levels, but regulatory and natural resources agencies often are
           interested in community level risk (e.g., loss of biological diversity in forest stands
           or wetlands).
       Some promising chemical markers and their associated source categories are shown
in Table 1. The total, upper-bound contribution of the potential source on the measured
ambient concentration can be obtained by multiplying the measured ambient concentration
of the marker species by the characteristic factor (i.e.. the reciprocal of the marker's per
cent abundance in the source's emission (i.e.. listed in "Source Profiles," such as the U.S.
EPA's VOC/Particulate Matter Speciation Data System, Version 1.4.). For example.
acetylene is one of the common volatile organic compounds (VOCs) found in motor vehicle
tailpipe emissions. On average, acetylene represents 4 ± 2 % of total VOCs in exhaust in

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the U.S.  If ambient acetylene is measured to be 3 |ig/mj. then the upper bound estimate =
3 u.g/m-> (25 ± 12V;  '5 ± 36 Iig/sn3. Therefore, if total ambient VOCs = 150 uam->, the
greatest possible motor vehicle contribution is about one-half (75/150) of all VOC sources
at this ambient site.
Aerosols
Na. CI
K (soil-corrected), Cl. 14C
Al. Si, K, Ca, Ti, Fe
Zn. Pb. Sn. Sb, Cl
V
Gases
CO, various VOCs
xvlene
ethane, propane
isoprene, a-pinene, b-pinene. ^Q
Dominant Source
Marine
Wood Combustion
Soil
Incinerators
Electric Utilitv Oil Combustion

Motor Vehicles
Industrial Solvents
Natural Gas
Bioeenic Emissions
Table 1:   Selected examples of presently available chemical marker species. The dominant
          source is airshed dependent; i.e., in addition to indicating a dominant source,
          measurements of marker concentrations in ambient air may represent products of
          transformation or  background concentrations. For example, Na and Cl-rich particles
          not near marine water bodies may be indicators of extraction or transportation
          activities that emit salt. High concentrations of Fe and Al may  not be re-entrained
          dust, but may be indications of smelting activities. Therefore, an inventory of source
          types in the airshed should complement the receptor modeling.

        The physical and chemical characteristic must also be considered when determining
potential sources of measured ambient contaminant concentrations.  Figure 5 illustrates
three different idealized bimodal distributions for panicles.  The distributions can provide
weight-of-evidence for whether the particles are anthropogenic or natural in origin.
"Routine screening of certain indicators" in ecosystems provides an estimate of "the actual
threats to the condition" of those ecosystems (Messer, 1990"). Such screening for the
presence of pollutants can be an indication of ecosystem exposure; however, the chemical
and physical characteristics of a contaminant can ultimately determine actual exposure.  For
example, outdoor concentrations of fine particles  near a home can be similar to fine particle
concentrations inside the home, but ozone (03) concentrations may be  much lower inside.
because 03 readily absorbs on surfaces. Aerosol acidity may be lower indoors due to
higher concentrations of ammonia that buffer the acid.

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       Physical characterization techniques, sucii ,is scanrmig electron microscopy and X-
ray fluorescence, can help to verify linkages to source categones because particles emitted
by different types of combustion display unique r.iorphologies (e.g., spheres, chains, and
clusters). Analyzed together, chemical composition and physical characterization can
provide weight-of-evidence for linking source emissions to measured ambient
concentrations.
       IDEALIZED MASS/SIZE DISTRIBUTION FOR
       URBAN AEROSOLS:VARIES BY CITY FOR
       MASS. SIZE DISTRIBUTION. AND CHEMICAL
       COMPOSITION
Cut Co«« *ucn M P
      ce.M*
   <*nt to torn ait tf*et
  a $
  t 
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estimate of exposure: i.e.. the concentration of a contaminant around an organism. For
airborne contaminants. D^ is a function of concentration, lime, and ventilation. It is
difficult or impossible to measure Dgg directly, so D^, Dj and Dp are most ot(en expressed
by biomarkers. i.e.. "indicators of changes or events in human biological systems" (MAS.
1991).  Biomarkers may either be the contaminant itself or metabolites indicating exposure
to the contaminant; e.g., increased concentration of cotinine (a metabolite of nicotine)in
blood resulting from exposure to tobacco smoke. Similarly, biomarkers in ecosystems are
"biochemical, physiological, or histological indicators of either exposure to or effects of
xenobiotic chemicals at the suborganismal or organismal level" (Huggett, et al, 1992).
             Microenvironment
           re Bounda
                                                 Biomarkers
                                                -Blood Lead
                                                -Carboxyhemoglobin
                                                -Urine Nicotine
                                                -Enzvmes
Exchange/Absorption Bamer
                                                   BE
                                                Target'Organ
Figure 6:  U.S. Environmental Protection Agency s Schematic ot Dose and Exposure for Airborne
           Substances (Modified by McCurdy. Draft in Processj.  Biomarkers can be substances to
           which the organism is exposed or metabolites te.g., enzymes! indicating exposure.
        Biomarkers can also apply to ecological exposure, although they are not often
classified as measures of dose i"biotic and abiotic accumulation" in Figure 21.  For

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example. Hunsaker, et al (1990) suggested measuring cholinesterase levels and porphyrin
accumulation to indicate the level of ecosystem exposure.

Comparison  «;f  Human and Ecological  Assessments

       A major difference between human and ecological exposure paradigms is their level
of biological organization; i.e., population exposure for one species (human) versus
community (several species), association, and population exposure for ecological risk
assessments. Human risk assessments express the likelihood that an adverse outcome will
result from a given hazard; e.g., 10"6 chance of ovarian cancer in a population exposed to a
particular pollutant.  Ecological risk assessments are also expressions of the likelihood of
an adverse outcome, but the expression depends upon the "environmental value" of
concern; e.g., biological diversity, sustainability, and aesthetics (Environmental Monitoring
and Assessment Program, 1993). Scientists are currently debating the usefulness of
ecological risk assessments, with many instead favoring ecological benefits assessments.
That is, benefits, can be gained or lost, depending on regulatory, management, and other
decisions. Both risk and benefit assessments, however,  require exposure assessments.
       A number of similarities exist between human and ecological exposure assessments.
Both are often  concerned with sensitive sufapopulations. many pollutants are both human and
ecological stressors, and ambient measurements for some pollutants can be indicators of both
human and ecosystem exposure (e.g., ozone).
       Passive monitors may improve useful data for both human and ecosystem exposure
assessments, since they provide an  inexpensive means of gaining coverage over large areas
with reasonable accuracy for several gaseous pollutants (± 20% for nitric oxide, ozone, and
sulfur dioxide). The use of passive devices may even provide greater potential for ecosystems
than for human exposure, since the need for more temporal precision may often be less for
ecosystems than for human; i.e.. if accumulation and degradation of a contaminant are the
major areas of concern, a weekly average may be sufficient, whereas, hourly averages may be
critical for human exposure assessments.
       Both assessments can benefit from the use of models, although modeling ecosystem
exposure pathways can be highly complex and includes  much uncertainty.  However, an
increased understanding of fluxes and cycling of nutrients and contaminants, bioenergetics.
and bioaccumulation will improve the application of ecosystem models.

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Human  Microenvironmental Exposure  Models

       Exposure models vary by scale (personal, microcnvironmental. indoor, site-specific,
regional), and type. Table 2 compares 20 hiiuian exposure models insofar as they incorporate
ventilation ruies, outdoor and indoor microer.vironmental concentrations, and human activity
patterns.  Presently, new models are being used for carbon monoxide, oxides of nitrogen,
ozone, lead, paniculate matter, sulfur dioxide, and hazardous pollutants. The table illustrates
that many have not yet been validated, or have been validated for limited rnicroenvironments;
e.g., within an automobile. However, the application of human exposure models is expanding
rapidly and their reliability is being improved.

Conclusions

       Exposure assessment can be similar for humans and ecosystems, although the level of
biological organization is often different for the two types of receptors. Data gathered from the
field may be used for both human and ecosystem exposure assessments. This seems to
indicate a likelihood for an increase in the number of combined human/ecosystem exposure
studies. The information about both receptor types would be enhanced, and the understanding
of the interrelationships between humans and ecosystems may be better understood.  Data and
assessments may become more interchangeable insofar as they are used to interpret to protect
both public health and the environment.
       New methods for measuring, modeling, and assessing exposure are presently being
developed. Passive monitors may prove to be valuable for ecosystem exposure estimates.
beyond their uses in human mieroenvironmental monitoring, since even large averaging times
may sufficient for many ecosystem exposure scenarios. The body of knowledge is growing
beyond simple ambient measurements to personal and indoor monitoring. Although the
science has emerged relatively recently, models are increasingly providing more reliable
exposure information for a greater  number of microenvironments. This trend may lead to
greater certainty in characterizing and predicting exposures.
       Enhancements in exposure assessment should lead to improved, scientifically-based
mechanisms and programs to reduce exposures of humans and ecosystems to harmful
substances and other stresses.

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Acknowledgments

       Several persons in EPA's Atmospneric Research and Exposure Assessment
Laboratory provided invaluable information and advice to the author when preparing this
report:  Gerald Akland (biomarkers and riuiiipathway methods); Tom McCurdy (models);
Charles Lewis, Shaibal Mukerjee and Robert Stevens (source apportionment); Larry
Purdue and Robert Burton (panicles and ozone); Jim Mulik (personal monitors); Deborah
Mangis (ecosystem receptors), and Andy Bond (multimedia exposure studies).

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Name Maintain
of
Model
Tir-c
Series?
Account Outdoor Indoor
for
VE?
ue
Human
us Activity/ Validated
Cone. Cone. Vg
CARBON
Convolution
CO/Reeression
SHAPE
pNEM/CG

No
No
No
Yes

No
No
No
Yes

3
3
3
2.

5
5
5
3 7

B
A
B
F

Model?
MONOXIDE
No
No
Limited
Limited

User
Friendly

No
Yes
No
No


? Citations i

Duanil989)
Schwab ( 1989)
Ott(1984)
Johnson, et al
( 1992)
NITROGEN DIOXIDE
SIMSYS
REHEX

NO2/Regression

No
No

No

No
Yes

No

3
2

3

5
6

5

B
D

A

No
No

No

No
No

Yes

Ryan (1986)
Lurmann. et al
(1989)
Drye, el al
(19*89)
OZONE
SAI/NEM

REHEX

pNEM/O3

EPEM

Yes

No

Yes

No

Yes

Yes

Yes

Yes

1

2

2

2

7

7

7

.

D

D

D

D

No

No

Limited

No

No

No

No

No

Haves, et al
(1984)
Lurmann. et al
(1989)
Johnson, et al
(1993)
Johnson, et al
(1992)
LEAD
Pb-NEM
EUBK

No
No

No
No

4
4

6
6

A
A

RESPIRABLE
THEM
Yes
No
2
7
C
SULFUR
SO2-NEM

No

Yes

1

.

A

HAZARDOUS
HEM
HAPEM
AERAM

SHEAR


BEAM

No
No
No

No


No

No
No
Yes

No


Yes

4
2
4

4


1

6
6
.

.


6

A
C





.

No
No

PARTICULATES
No
DIOXIDE
No

POLLUTANTS
No
No
No

No


No

No
Yes


No

No


Yes
No
No

No


Yes

OAQPS(1989)
Lead Work-
group (1994)

Klepeis(1994)

Billeretal
(1986)

Radian ( 1985)
Johnson i 1992)
Hschenroder
et al(l 985)
Anderson
& Lundbere
( 1983)
Behar et al
(1994)
Table  2:  Attributes of selected air exposure models (After McCurdy Draft in Process i.
          Notes: OUTDOOR (ie:  1 = Use fixed site values as a surrogate.  2 = Use "adjusted" fixed site
          (ic values.  3 = Monitor outdoor ne concentrations,  4 = Model outdoor ue concentrations.
          INDOOR (ie: 5 = Measure indoor |ie concentrations. 6 = Use indoor/outdoor ratios + indoor
          sources i if any).  7 = Use mass-balance model that includes indoor sources (if any). 8 = Use
          regression equations developed from indoor ue measurements. HUMAN ACTIVITY/
          VENTILATION: A = Use of aggregate data and/or Vg.  B = Simulate transitions: ignore V"£
          C = Sample from activity data: ignore V£.  D = Sample from joint activity/;Vg data.

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References

Anaerson. G,E. and Lundberg, G.W. • '983).  ' Ver'j Manual for SHEAR. Research Triangle
    Park: U.S. Environmental Protection Agency.
Behar. J.V..  Thomas, J.. Pandian. M. and Tsang. A. (1994). "National Benzene Exposure
    Study Using Benzene Exposure Assessment Model (BEAM)."  Paper presented at the
    Fourth Conference for Exposure Analysis: September.
Biller. W. B. (1986).  Analysis of Short-term SO-> Population Exposures in the Vicinity of
    Power Plants. Durham: U.S. Environmental Protection Agency.
Drye, E., Ozkaynak, H.,  Burbank, R., Billick, I.H.,  Spengler.'J.D.,  Ryan,  P.B.. Baker,
    P.E., and Humble, C. (1989).  "Development of models for predicting the distribution of
    nitrogen dioxide concentrations." J. Air Poll. Cont.Assoc,.  39: 1169-1177.
Duan, N. (1989).  "Estimation of microenvironmental concentration distributions using
    integrated exposure measurements,'*, pp.  15-1 to 15-14 in: T. Starks (ed.), Proceedings of
    the  Research Planning Conference on Human Activity  Patterns. Las  Vegas:   U.S.
    Environmental Protection Agency,
Environmental Monitoring and Assessment Program (1993).  Environmental Monitoring and
    Assessment Program: Master Glossary.  EPA/62Q/R-93/013. Research Triangle Park.
    NC:  U.S. Environmental Protection Aeency, Office of Research and Development.
Eschenroeder, A.Q., Magil, G.C.. and Woodruff, C.R. (1985). Assessing  the Health Risks
    of Airborne Carcinogens. Palo Alto: Electric Power Research Institute.
Hayes, S.R..  Seigneur. C..  and Lundberg, G.W. (1984).  Numerical  Modeling of Ozone
    Population Exposure: Application to a Comparison of Alternative Ozone Standards. San
    Rafael: Systems Applications, Inc.
Hidy, G.M. (1975). Summary of the California Aerosol Characterization Experiment. J. Air
    Poll. Com. Assoc. 25: 1106-1114.
Huggett, R.J., Kimerle. R.A.. Mehrle. Jr.. P.M.. and Bergman, H.L. eds. 1992.
      Biomarkers-Biochemical Physiological, and Histological Markers of Anthropogenic
      Stress. Boca Raton. LA:  Lewis Publishers.
Hunsaker. C.T., MacCarthy, J.F., Shugart. L.R., and O'Neill, R.V. (1990).   Indicators
    Relevant to Multiple Resource Categories. In Ecological Indicators for the Environmental
    Monitoring and Assessment Program., eds. C.T. Hunsaker and D.E. Carpenter. 2-1-2-
    18.  EPA 600/3-90/060.  Research Triangle Park. NC:  U.S. Environmental Protection
    Agency. Office of Research and Development.
Johnson. T..  Paul. R.A.. and Capel. J.E. 11992). Application of the Hazardous Air Pollutant
    Exposure Model (HAPEM) to Mobile Source Pollutants.  Durham: IT Technology.
Johnson. T.R.,  Capel, J. and  McCoy.  M. il993).   Estimation of Ozone Exposures
    Experienced by  Urban Residents  Using  a Probabilistic  Version of NEM and  1990
    Population Data.  Durham: FT Technology.
Johnson. T.R.,  Capel. J..   Olaguar, E.. and Wijnberg. L. (1992).  Estimation of Ozone
    Exposures Experienced by  Urban Residents Using a Probabilistic Version of NEM.
    Research Triangle Park:  U.S. Environmental Protection Agency.
Johnson. T.R.,  Capel. J..   Paul. R..  and  Wijnberg,  L.  11992).  Estimates  of Carbon
    Monoxide Exposures and Associated Carboxyhemoglobin Levels  in Denver Residents
    Using a Probabilistic Version of NEM. Research Trianele Park:
Klepeis. N.E.. Ott, W.R., and Switzer. P. f 1994).  "A Total human exposure model (THEM)
    for  respirable suspended particulates."  Paper 94-WA75A.03 presented at the Annual
    Meeting of the Air & Waste Management Association: June.
Lead Working Group U994).  Guidance Manual for the Integrated Exposure  Uptake Biokinetic
    Model for  Lead  in Children.   ;The  IEUBK  Model.)  Washington.  DC:  U.S.
    Environmental Protection Agency (EPA-450/R-93-081).
Lipton. J.. Galbraith, H.. Burger^., and Wartenberg, D. (1993).  A Paradigm for Ecological
    Risk Assessment. Environmental Management. Vol. 17. No. 1. 1-5.

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Lurmann, F.W., Weiner, A.M., and Colome, S.D. ( 1989).  'Development of a new regional
    human exposure model (REHEX) and its application to the California South Coast Air
    Basin." Paper presented at the Annual Meeting  of the Air Pollution Control Association;
    June.
McCurdy, T, {Draft in Process). Modeling the "Dose Profile" in Human Exposure
    Assessments:  Ozone as an Example. Research Triangle Park. MC: U.S. Environmental
    Protection Agency, Office of Research and Development.
Messer, J.J. (1990). EMAP Indicator Concepts. In Ecological Indicators for the
    Environmental Monitoring and Assessment Program., eds. C.T. Hunsaker and D.E.
    Carpenter, 2-1 -2-18. EPA 600/3-90/060. Research Triangle Park. NC: U.S.
    Environmental Protection Agency, Office of Research and Development.
National Academy of Sciences, National Research Council (1983). Human Exposure
    Assessment for Airbone Pollutants: Advances and Opportunities.   Washington, DC:
    National Academy Press.
National Academy of Sciences, National Research Council (1991). Risk Assessment in the
    Federal Government: Managing the Process.  Washington, DC: National Academy
    Press,
OAQPS Staff (1989). Review of the National Ambient Air Quality Standards for Lead:
    Exposure Analysis Methodology and Validation. Research Triangle Park: U.S.
    Environmental Protection  Agency (EPA-450/2-89-011).
Ott, W.R. (1984).  "Exposure estimates based on computer generated activity patterns." CJin,
            21: 97-128.
Radian Corporation (1985). A Study of Feasible Modeling  Alternatives for Simulating
    Human Exposure and Risk Resulting from Airborne Pollutants. Research Triangle Park:
    Radian.
Risk Assessment Forum (1992).  Framework for Ecological Risk Assessment, EPA/600/R-
    92/001.  Washington, DC: U.S. Environmental Protection Agency Office of Research
    and Development.
Ryan, P.B.,  Spengler, J.D., and Letz, R. (1986). "Estimating personal exposures to NOo."
    Environ. Inter. 12: 394-400.
Schwab, M. (1989).  "The influence of  daily activity patterns on differential exposure to
    carbon  monoxide  among  social groups. "pp.  18-1  to  18-21  in  T.H.  Starks (ed.),
    Proceedings of the Research Planning Conference on Human Activity Patterns.  Las
    Vegas: U.S. Environmental Protection Agency,
Sexton. K. and Ryan. P.B. ( 1988). Assessment of Human Exposure to Air Pollution:
    Methods. Measurements, and Models. In Air Pollution, the Automobile, and Public
    Health.. 208.  Washington. DC:  Health Effects Institute. National  Academy Press.
U.S. Environmental Protection Aaency ( 1990). ,\'onoccupational Pesticide Exposure Study
    (NOPESl EPA/600/3-90/003.  Washington. DC: U.S. Environmental Protection
    Agency Office of Research and Development.
U.S. Environmental Protection Asency ( 1992). Federal Register.  Guidelines for Exposure
    Assessment.  Vol.57.  No.  K)4."FRL-4 129-5.
    U.S. Environmental Protection Agency.
Wallace, L.A. (1987).  The Total Exposure Assessment Methodology { TEAM) Study:
    Summary and Analysis, Vol. 1. EPA/600/6-87/002a. Washington. DC:  U.S.
    Environmental Protection Agency Office of Research and Development.
Watson, J.G, Robinson, N.F., Chow. J.C., Henry, R.C..  Kim. B.M.. Pace, T.G.. Meyer.
    E.L., and Nguyen. Q. (1990). "The USEPA/DRI Chemical Mass Balance Receptor
    Model. CMB 7.0" Environ. Software.

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                                TECHNICAL  REPORT  DATA
  1. REPORT NO.
    EPA/600/A-94/252
  4. TITLE AND SUBTITLE

  Exposure Assessment Methodologies for Humans and
  Ecosystems
                            5.REPORT DATE
                                                           6. PERFORMING ORGANIZATION CODE
  7. AUTHORfS)
  Daniel A. Vallero,  HEFRD/AREAL   (MD-56)
                            8,PERFORMING ORGANIZATION REPORT
                            NO,
  9. PERFORMING ORGANIZATION NAME AND ADDRESS

  U.S. Environmental•Protection Agency
  Research Triangle Park, North Carolina
                            IO.PROGRAM ELEMENT NO.
                                                           11. CONTRACT/GRANT NO.
  12. SPONSORING AGENCY NAME AND ADDRESS

  U.S. Environmental  Protection Agency
  Research Triangle Park,  North Carolina
                            I3.TYPE OF REPORT AND PERIOD COVERED

                            Presentation
                                                           14. SPONSORING AGENCY CODE
  15. SUPPLEMENTARY NOTES
  16. ABSTRACT

  Scientists and  risk assessment experts are  developing approaches to  estimate
  exposure of human populations and ecosystems  to environmental contaminants.
  Ecological scientists are exploring methodologies for estimating the exposure of
  ecosystems and  their subdivisions to environmental stresses, while risk analysts
  are investigating approaches for estimating exposures to contaminants which could
  affect human health.   Exposure assessment methods vary significantly, .depending
  upon factors, such as the scale of the exposure,  the measurement focus,  and whether
  the measurements  are actual expressions of  exposure or part of an algorithm to
  indicate exposure.   The paper discusses the elements of ecological and human
  exposure assessment methodologies.  The Nonoccupational pesticide Exposure Study
  provides an example of multiple pathway exposure assessment.  Ecosystem and human
  exposure assessment paradigms are compared  and contrasted with regard to the level
  of biological organization, source-receptor relationships, biomarkers,  dose,
  pollutant characteristics,  and modeling.	  	
  17.
KEY WORDS AND DOCUMENT ANALYSIS
                   DESCRIPTORS
                b.IDENTIFIERS/OPEN ENDED
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                                                                          c.COSATI
  18. DISTRIBUTION STATEMENT
                19. SECURITY CLASS (Mi Report)
                                                                          21.NO. OF PAGES
                                                20. SECURITY CLASS (Ms Page)
                                           22. PRICE
file: x:\*brtr»ct\exp-«M«.d«v

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