-------
OSWER Directive 9285.5-1
Slope Length, Meters
20 30 40 6O aOIOQ ISO ZOO 300 4OO 6OO 90O
40.0
20.0
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Slope Length, Feet
Figure 3-4. slope Effect Chart Apnllcable to Areas A-l 1n Washington,
Oregon, and Idaho,and All of A-3: See Figure 3-5
(USOA 1974)
NOTE: Dashed lines are extensions of IS formulae beyond values tested 1n
studies.
3-38
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OSWER Directive 9285.5-1
20.0
3.9 6.0
Slept Langth, Mtttrs
20 4O 60 IOO
200
4OO 6OO
(0
20
4O 60 100 200 400 6OO 1000 2000
Slop* Langth, Faซt
Figure 3-5. Slope Effect Chart for Areas Where Figure 3-5 Is Not
Applicable. (USOA 1974)
NOTE: The dashed lines represent estimates for slope dimensions beyond
the range of lengths and steepnesses, for which data are available.
3-39
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OSWER Directive 9285.5-1
OO 20Q MILES
Figure 3-6. Soil Moisture-Soil Temperature Regimes of the Western United
States. (USDA 1974)
3-40
-------
OSWER Directive 9285.5-1
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3-41
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0607E
OSWER Directive 9285.5-1
Table 3-6. "C" Values for Woodland
Stand condition
Well stocked
Medium stocked
Poorly stocked
Tree canopy
percent of
area3
100-75
70-40
35-20
Forest
litter
percent of
area5
100-90
85-75
70-40
Undergrowth0
Managed0*
Unmanaged^
Managed
Unmanaged
Managed
Unmanaged
"C" factor
0.001
0.003-0.011
0.002-0.004
0.01-0.04
0.003-0.009
0.02-0.096
Source: Wischmeier 1972
aWhen tree canopy is less than 20 percent, the area will be considered as grassland
or cropland for estimating.soil loss.
^Forest litter is assumed to be at least 2 in deep over tne percent ground surface
area covered.
cUndergrowth is defined as shrubs, weeds, grasses, vines, etc., on the surface area
not protected by forest litter. Usually found under canopy openings.
^Managed - grazing and fires are controlled.
Unmanaged - stands that are overgrazed or subjected to repeated burning.
eFor unmanaged woodland with litter cover of less than 75 percent, C values should
be derived by taking 0.7 of the appropriate values in Table 3-4. The factor
of 0.7 adjusts for much higher soil organic matter on permanent woodland.
3-42
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OSWER Directive 9285.5-1
(3 = soil bulk density, (g/cm3).
C] = total substance concentration, (kg/ha, Ib/acre).
A = contaminated area, (ha, acre).
This model assumes that only that contaminant in the top 1 cm of soil is
available for release via runoff.
The soil sorption partition coefficient for a given chemical can be
determined from known values of certain other physical/chemical
parameters, primarily the chemical's octanol-water partition coefficient,
solubility in water, or bioconcentraton factor. Lyman et al. (1982)
present regression equations that allow the analyst to determine sorption
coefficients for specified groups of chemicals (e.g., herbicides,
polynuclear aromatlcs). If parameter values required by the appropriate
equations are not available in chemical reference literature, they can be
estimated according to procedures described 1n Lyman et al. (1982).
Initially, the octanol-water partition coefficient can be estimated based
on the substance's molecular structure. If necessary, this value can be
used, 1n turn, to estimate either solubility In water or bioconcentration
factor.
After calculating the amount of sorbed and dissolved contaminant, the
loading to the receiving water body is calculated as follows (Haith 1980):
PX1 = [YE/100 6] Ss (3_28)
and
P(?1 ' CW Ds (3-29)
where
= sorbed substance loss per event, (kg, Ib).
- dissolved substance loss per event, (kg, Ib).
Qr - total storm runoff depth, (in, cm).
Rt * total storm rainfall, (in, cm).
and PQi can be converted to mass per volume terms for use in
estimating contaminant concentration In the receiving water body by
multiplying by the site area and dividing by the site storm runoff volume
(Vr, see Equation 3-23).
(2) Remedial action. Although remedial technologies implemented at
Superfund sites will be designed to preclude continuing contaminant
release over time, insofar as is possible, the likelihood of control
3-43
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OSWER Directive 9285.5-1
failure must still be evaluated. For example, under RCRA regulations,
run-on/run-off controls designed for a 25-year storm event are required.
However, it can be estimated that there is a 94 percent probability of
exceeding a 25-year storm event over a 70-year period.* From this
example it can be seen that the possibility of episodic releases at some
sites may be high and would, therefore, require careful evaluation. Such
evaluation can be considerably facilitated by the use of modeling
techniques appropriate for the remedial technologies under
consideration. USEPA (1985e) provides considerable guidance on the
application of numerical modeling in evaluating the expected degree of
effectiveness of remedial alternatives in controlling overland
runoff-related contaminant release from hazardous waste sites.
3.5.2 In-depth Analysis
(1) Baseline condition. Releases to surface water bodies at
uncontrolled hazardous waste sites can most accurately be quantified by
direct measurement (sampling and analysis) of the contaminant flow.
Alternatively, upcurrent and downcurrent sampling can be conducted to
determine the release level at the site that would be used to estimate
the ambient concentration (i.e., the difference between the upcurrent and
downcurrent concentrations). Either simple dispersion equations or
sophisticated computer modeling approaches (see Chapter 4) can be used to
"back up" the measured ambient concentration to the "virtual point
source."
(2) Remedial action. As stated above, the potential for episodic
releases during the 70-year (long-term) time frame must be evaluated on a
case-by-case basis.
3.5.3 Long-term and Short-term Release Calculation
For surface runoff releases, the long-term release value can be
calculated as follows:
Characterize an average storm event for the area in terms of
duration. This can best be accomplished by consulting local or
regional climatological experts, or the National Climatological
Data Center in Asheville, North Carolina. Then, using USDC
(1961), determine the amount of rainfall corresponding to the
selected duration rainfall event on a one year-return frequency
basis. Divide this amount into the mean annual rainfall for the
area to obtain the average number of average rainfall events per
year.
Information provided by Kevin Garrahan, Exposure Assessment Group,
Office of Research and Development, U.S. Environmental Protection Agency.
3-44
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OSWER Directive 9285.5-1
Use these data and the equations presented in this section to
calculate runoff contaminant release associated with each yearly
average storm.
Estimate potential total long-term release as follows for both
dissolved and sorbed runoff loss:*
EA1- BN (3-30)
where
= long-term release of contaminant i in runoff (mass/70
years).
B = dissolved or sorbed loss per storm event, (i.e., PX^ or
PQi; see Equations 3-29 and 3-30).
N = number of "average" storm events in 70 years.
Determine the total amount of soil that will erode from the site
over 70 years. This can be accomplished by applying the Universal
Soil Loss Equation (USLE, Wlschmeier and Smith 1978). This
equation, from which the MUSLE (see Equation 3-22) was developed,
estimates annual soil losses in runoff. The USLE takes the same
form as the MUSLE, except that the storm event-specific volume and
flow rate variables are replaced by a factor R, the rainfall
runoff factor. Therefore, the USLE is:
Y(S)A . RrKLSCP (3-31)
where
Y(S)/\ = Annual soil loss in runoff
Rr = Rainfall and runoff factor (dimensionless).
Other variables are as defined for Equation 3-22. Note that in
certain areas of the Pacific Northwest and central western states,
thaw and snowmelt may contribute the majority of the runoff
erosive force on an annual basis. In such cases, an additional
erosion factor, Rs, must be added to the rainfall and runoff
factor, R, to calculate the total R value for use in the USLE.
Limited field data have indicated that an approximate estimate of
Rs may be obtained by multiplying 1.5 times the local average
total rainfall (in inches) for the period December 1 through March
31 (Wischmeier and Smith 1978).
*This approach is overly conservative as it assumes that the
contaminant concentration in surface soil remains essentially the same
during the entire 70-year period.
3-45
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OSNER Directive 9285.5-1
Based on the average contaminant concentration in site soils,
calculate the mass of contaminant present in that amount of soil
estimated to be eroded over 70 years. This represents the maximum
amount of contaminant available for erosion losses over the
70-year period.
Compare the estimated potential contaminant runoff losses over 70
years with the mass of contaminant present in 70-year erodible
soils at the site. If the estimated total loss to runoff is less
than the amount available, divide the estimated total 70-year
losses by the total volume of stormwater runoff estimated, over 70
years to approximate the contaminant concentration in runoff (both
dissolved and sorbed).
If the total estimated contaminant runoff losses exceed the amount
of contaminant present in 70-year erodible site soils, divide the
total mass of contaminant present in such soils by the volume of
runoff estimated to leave the site over 70 years to develop
adsorbed and dissolved contaminant loss estimates in concentration
form. In either case, the associated steady-state runoff effluent
value needed to estimate contaminant transport and dispersion in
surface waterbodies can be estimated by dividing the total volume
of runoff estimated to leave the sHe over 70 years by the number
of seconds, minutes, etc.. in 70 years to estimate runoff volume
per unit time.
It is recognized that many factors influence the actual degree of
contaminant loss in given storm events. Because of the great variety in
such factors from locale to locale, no single method will guarantee
accurate estimates of short-term contaminant losses in runoff from all
sites. However, it is felt that the following approach should yield
reasonable approximations of the magnitude of such short-term loss.
While short duration, high intensity storm events (thunderstorms) clearly
cause significant erosion, the water quality effects of such storms are
considered to be too ephemeral to adequately reflect short-term releases
as defined herein (i.e., 10-90 days). Therefore, a storm event that will
generate contaminant releases adequate to affect water quality over a
time period approaching the ten-day lower bound of the short-term time
frame is needed. For this analysis, a 1-year, 24-hour storm event has
been selected. Data quantifying the amount of rainfall that corresponds
with the 1-year, 24-hour storm event (as well as similar data for other
storm return periods and durations) are provided in USDC (1961).
The user of this manual should note that, based on the work of Haith
et al. 1980, research is presently underway at Cornell University
*Contact Douglas A. Haith, Cornell University, Ithaca, N.Y.,
(607)256-2280.
3-46
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OSWER Directive 9285.5-1
to develop runoff loading factors for organic chemicals in soils. After
these are developed, the analyst will be able to obtain average loading
values based simply on a chemical's octanol/water partition coefficient
and the geographic location under study. This will greatly simplify
generation of long-term average release estimates. It is projected that
this data base, which will not address short-term extreme events, should
be developed by December 1986.
Note that in order to estimate long-term and short-term contaminant
concentrations in surface water, the long-term and short-term release
values are used along with average and minimum streamflow data as
described in Chapter 4, Environmental Fate Analysis.
3.6 Ground-water Contamination Analysis
Ground-water contamination at uncontrolled hazardous waste sites
results from leaching of toxics from contaminated surface or subsurface
soils, and from seepage of concentrated contaminants from lagoons and
ponds. Approaches exist for both direct and indirect evaluation of the
degree and extent of such contaminant release to ground water. This
section addresses these methods.
3.6.1 Simplified Procedures
(1) Baseline condition. A method has recently been published that
is designed to support rapid (within a 24-hour period) estimation of the
level of ground-water contamination attributable to toxic contamination
situations. Based on the critical site- and chemical-specific
characteristics listed in Table 3-7, this approach relies on the use of
tables and nomographs for the estimation of contaminant release and
loading to an aquifer. The method is specifically designed to analyze
abandoned hazardous waste sites
-------
0607E
OSWER Directive 9285.5-1
Table 3-7. Critical Compound and Site Characteristics
Critical Compound Characteristics
1. Contaminant identity and physical state
2. Extent of the contamination
3. Solubility
4. Adsorption
5. Degradation
6. Toxicity
7. Concentration and loading
8. Density, viscosity, and temperature
Critical Site Characteristics (Applicable to both the unsaturated and
saturated zones unless otherwise indicated)
1. Identity of subsurface medium
2. Age of site
3. Distances to wells, streams, property boundaries
4. Porosity
5. Infiltration, net recharge; and volumetric water content
(unsaturated zone only)
6. Bulk density
7. Hydraulic conductivity (saturated zone only)
8. Chemical characteristics of medium
9. Dispersion
10. Depth to ground water (unsaturated zone only)
11. Hydraulic gradient (saturated zone only)
12. Effective aquifer thickness (saturated zone only)
13. Structural and geologic features
Source: Donigian et al. 1983.
3-48
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OSWER Directive 9285.5-1
vary among potentially useful remediation technologies. For evaluation
of post-remediation control effectiveness, the analyst is referred to
USEPA (1985e) for a detailed discussion of both simplified methods and
numerical modeling approaches to such analysis.
3.6.2 In-depth Analysis
(1) Baseline condition. In-depth analytical approaches for
quantification of baseline contaminant release to ground water involve
use of computerized models. Refer to Chapter 4 of this manual for a
detailed discussion of the nature and applications of such modeling tools,
(2) During remediation. As stated above, well-designed remedial
alternatives would be expected to preclude the potential for remediation-
related ground-water contamination. The analyst is again referred to
USEPA <1985e) for a discussion of computerized modeling techniques useful
in assessing post-remediation contaminant release control effectiveness.
3.6.3 Long-term and Short-term Release Calculation
For toxic substance release to ground-water systems, directly
calculate the short-term (maximum) release values from the measured
surface and subsoil contaminant concentrations using the tools discussed
in this section. Obtain long-term (average) values by applying the
procedure previously outlined for particulate releases to air (see
Section 3.4.3).
3.7 Soil Contamination
Surface soils at uncontrolled hazardous waste sites may become
contaminated with toxic materials through intentional placement of wastes
on the ground (dumping, landfarming), as a result of spills, as a
consequence of lagoon failure (overland flow), or as a result of
contaminated site runoff. Leaching of toxics from a contaminated soil
surface can carry contaminants into subsurface layers. Generally, the
substances of concern at uncontrolled hazardous waste sites are non-polar
(Delos et al. 1983) and will bond (adsorb) strongly to organic soil
particles as a result of their hydrophobic properties.
3.7.1 Simplified Procedures
(1) Baseline condition. No estimation methods are presented for
surface soils, since site soils will be sampled directly and the degree
and extent of their contamination delineated during the Remedial
Investigation. For subsurface soils, sampling and analysis may also have
been conducted. However, in certain cases it may be desirable to project
subsurface contamination without conducting unsaturated zone sampling.
3-49
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OSWER Directive 9285.5-1
As discussed previously, Donigian et al. (1983) have recently published
an analytical method that is specifically designed for such evaluation.
This approach, based on the use of tables and nomographs developed to
allow rapid estimation of contaminant movement, provides quantitative
estimation of subsurface soil contamination.
(2) During remediation. Additional contamination of soils can
probably be avoided by well-engineered remedial alternatives. However,
in some circumstances, short-term ancillary soil contamination may be
unavoidable, as when toxics containment vessels rupture unexpectedly
during handling. Estimation of the level of additional remediation-
related soil contamination must be made on a case-by-case, best judgment
basis, considering the nature and condition of toxics placement at the
site and the engineering design of the remedial alternative(s) under
consideration.
3.7.2 In-depth Analysis
(1) Baseline condition. Surface soil monitoring, usually conducted
during the Remedial Investigation as mentioned above, constitutes
in-depth quantitative analysis. Subsurface (unsaturated zone) in-depth
analysis will usually Involve application of sampling and modeling
approaches. Sampling and analysis can provide a direct quantification of
the degree of contamination in subsurface soils. Alternatively, computer
models exist (e.g., SESOIL, see Bonazountas and Wagner 1981) that are
capable of projecting the level of unsaturated zone contamination ove*"
time from surface placement of toxics. Refer to Chapter 4 of this manual
for a detailed discussion of computer models that can be applied to
unsaturated zone contamination estimation.
(2) During remediation. Well engineered remedial alternatives would
be expected to correct rather than cause soil contamination on site.
However, as discussed above, short-term, remediation related soil
contamination may be unavoidable under certain circumstances. No
quantitative analysis method is presented for surface soil, however,
because remediation related contamination of the surface would have to be
estimated on a case-by-case basis from site conditions and engineering
design.
3.7.3 Long-term and Short-term Release Calculation
The potential for post-remediation long-term or short-term soil
contamination must be evaluated on a case-by-case basis. Such
contamination would be associated with failure of an on-site containment
remediation technology. Also, as discussed above, short-term soil
contamination may result from implementation of the remedial alternative
itself. The likelihood of this must also be evaluated on a case-by-case
basis in light of site conditions and the design of the selected remedial
alternative.
3-50
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OSWER Directive 9285.5-1
4.0 ENVIRONMENTAL FATE ANALYSIS
4.1 Introduction
Environmental fate analysis assesses the areas affected by, and
estimates the concentrations of, hazardous substances released to the
ambient environment. Qualitative release assessments, or quantitative
release rate estimates derived from the steps described in the preceding
chapter, provide the basis for this analysis. For each released
contaminant in each receiving medium, various environmental transport,
transformation, and removal mechanisms are considered or quantified. The
results of fate assessment subsequently support identifying populations
exposed to contaminants in the ambient environment, and assessing
exposure levels (Chapters 5 and 6).
This chapter provides decision networks and guidance for qualitative
screening of environmental fate pathways and an overview of applicable
quantitative techniques. Simplified algorithms for estimating ambient
contaminant concentrations based on the most important fate mechanisms
are presented, and annotated lists of more sophisticated methods and
computer-based models are presented for each environmental medium.
4.2 Environmental Fate Screening
Environmental fate screening provides an Initial qualitative
assessment of contaminant migration or transport in the environment and
of the likely ambient contaminant concentration ranges at affected
locations. The starting point of this assessment is the results of the
contaminant release screening assessment; the fate of each potential
release thus identified is systematically assessed in each environmental
medium.
In the following subsections, decision networks are presented as a
framework for environmental fate screening assessments. Each subsection
is keyed to points within the accompanying decision networks and provides
additional detail about individual steps.
In each of these networks, certain negative decisions result in the
elimination of a given fate pathway as resulting in potentially
significant ambient environmental concentrations. These are represented
in each case by a box containing the word "No." Such decisions indicate
that further assessment is unnecessary.
4-1
-------
OSWER Directive 9285.5-1
When positive responses to successive decision points determine that
significant ambient concentrations are likely to result from a given
pathway, a qualitative screening assessment of human exposure and an
identification of exposed populations must be made. Procedures for
screening assessments of exposed populations are presented in Chapter 5,
Identification of Exposed Populations.
In cases where available site survey data include the results of
sampling and analysis of surrounding ambient environmental media, these
data may form the basis of environmental fate screening assessments or
may provide enough data in themselves so that no further assessment need
be undertaken. The media and locations sampled should be compared with
the expected extent of contaminant migration, and procedures outlined
below should be employed to fill data gaps and to project future trends.
4.2.1 Contaminant Environmental Fate Screening: Atmospheric Fate
The following numbered paragraphs are provided to facilitate
interpretation and application of the atmospheric fate decision network
presented as Figure 4-1. Each paragraph refers to a particular numbered
box in the figure.
1. Atmospheric fate of contaminants must be assessed whenever it is
determined that significant gaseous or airborne particulate contaminants
are released from the site. In addition, atmospheric fate of
contaminants released originally to other media, but eventually
partitioning to the atmosphere beyond site boundaries, must also be
assessed whenever this intermedia transfer is likely to be significant.
2. Predominant directions of contaminant movement will be determined by
relative directional frequencies of wind over the site (as reflected in
area-specific wind rose data). Off-site areas affected by ambient
concentrations of gaseous contaminants are determined by atmospheric
stability and wind speeds.. Usually, high stability and low wind speed
conditions result in higher atmospheric concentrations of gaseous
contaminants close to the site.- High stability and moderate wind speeds
result in moderate concentrations over a larger downwind area, while low
stability or high wind speed conditions cause greater dispersion and
dilution of contaminants, resulting in lower concentrations over greater
areas.
For particulate contaminants (including those adsorbed to dust or
soil particles), ambient concentrations in the atmosphere and areas
affected by airborne contaminants are determined by windspeed and
stability and also by particle size distribution. High winds result in
greater dispersion, and also cause particulars to remain airborne longer
(which may also increase release rates). Low winds and high stability
4-2
-------
OSWER Directive 9285.5-1
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4-3
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OSWER Directive 9285.5-1
will result in rapid settleout of particulates and in a more concentrated
contaminant plume closer to the site. Larger particles will settle
rapidly, decreasing the atmospheric concentrations with distance from the
site. Finer particles will remain airborne longer, and their behavior
will more closely approximate that of gaseous contaminants, as described
above.
3. Settleout and rainout are important mechanisms of contaminant
transfer from the atmospheric media to both surface soils and surface
waters. Rates of contaminant transfer due to these mechanisms are
difficult to assess qualitatively; however, they increase with increasing
soil adsorption coefficients, solubility (for particulate contaminants or
those adsorbed to particulates), particle size, and precipitation
frequency.
Areas affected by significant atmospheric concentrations of
contaminants exhibiting the above physical/chemical properties should
also be considered as potentially affected by contaminant rainout and
settleout to surface media. Contaminants dissolved in rain water may
percolate to ground water, run off or fall directly into surface waters,
and adsorb to unsaturated soils. Contaminants settling to the surface
through dry deposition may dissolve 1n or become suspended in surface
waters, or may be leached into unsaturated soils and ground water by
subsequent rainfall. Dry deposition may also result in formation of a
layer of relatively high contamination at the soil surface. When it is
determined that such intermedia transfers are likely, the fate of
contaminants in the receiving media should be" assessed.
4. If areas identified as likely to receive significant atmospheric
contaminant concentrations include areas supporting edible biota, the
bio-uptake of contaminants must be considered as a possible environmental
fate pathway. Direct biouptake from atmosphere is a potential fate
mechanism for lipophilic contaminants. Biouptake from soil or water
following transfer of contaminants to these media must also be considered
as part of the screening assessments of these media.
4.2.2 Contaminant Environmental Fate Screening: Surface Water Fate
The following numbered paragraphs are provided to facilitate
interpretation and application of the aquatic fate decision network
presented as Figure 4-2. Each paragraph refers to a particular numbered
box in the figure.
1. The aquatic fate of contaminants released from the CERCLA site as
well as those transferred to surface water from other media beyond site
boundaries must be considered.
4-4
-------
OSWER Directive 9285.5-1
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z
4-5
-------
OSWER Directive 9285.5-1
2. Direction of contaminant movement will usually only be clear for
contaminants introduced to rivers and streams. Currents, thermal
stratification or eddies, tidal pumping, and flushing in impoundments and
estuaries render qualitative screening assessment of contaminant
directional transport highly conjectural for these types of water
bodies. In most cases, entire water bodies receiving contaminants must
be considered potentially significant human exposure points. More
in-depth analyses or survey data may subsequently identify contaminated
and unaffected regions of these water bodies.
3. Similarly, contaminant concentrations in rivers or streams can be
roughly assessed based on rate of contaminant introduction and dilution
volumes. Estuary or impoundment concentration regimes are highly
dependent on the transport mechanisms enumerated above. Contaminants may
be localized and remain concentrated, or disperse rapidly and become
diluted to insignificant levels. Again, the conservative approach is to
schedule such water bodies receiving significant amounts of contaminants
for more in-depth assessment, and use model results or survey data as a
basis for determining contaminant concentration levels.
4. Important intermedia transfer mechanisms that must be considered
where significant surface water contamination is expected include:
transfers to ground water where hydrogeblogy of the area indicates
significant surface-water/ground-water, exchange; transfers to biota where
waters contaminated with lipophilic substances support edible biotic
species; and transfer to the atmosphere where surface water is
contaminated by volatile substances. High temperatures, high .
surface-area-to-volume ratios, high wind conditions, or turbulent stream
flow also enhance volatilization rates.
Contaminant transfer to bed sediments represents another significant.
transfer mechanism, especially in cases where contaminants are in the
form of suspended solids, or are dissolved, hydrophobic substances that
can adsorb to organic matter inched sediments. For the purposes of this
manual, sediments and water are considered part of a single system,
because of their complex inter-association. Surface water-bed sediment
transfer is reversible; bed sediments often act as temporary repositories
for contaminants, and gradually re-release contaminants to surface
waters. Sorbed or settled contaminants are frequently transported with
bed sediment migration or flow. Transfer of sorbed contaminants to
bottom-dwelling, edible biota represents a fate pathway potentially
resulting in human exposure. Where this transfer mechanism appears
likely, the biotic fate of contaminants should be assessed.
4-6
-------
OSWER Directive 9285.5-1
4.2.3 Contaminant Environmental Fate Screening: Soil and Ground-water
Fate
The following numbered paragraphs are provided to facilitate
interpretation and application of the soil and ground-water fate decision
network presented as Figure 4-3. Each paragraph refers to a particular
numbered box in the figure.
1. The fate of contaminants in the soil medium is assessed whenever the
contaminant release atmospheric or fate screening assessments result in
the determination that significant contamination of soils is likely.
2. Most significant contaminant movement in soils is a function of
liquid movement. Dry, soluble contaminants dissolved in precipitation,
run-on, or human-applied water will migrate through percolation into the
soil. Migration rates are a function of net water recharge rates and
contaminant solubility.
o
Liquid contaminants may percolate directly into soils. Organic
liquids may alter soil permeabilities or may be of lower viscosity and/or
higher density than water, resulting in percolation rates many times
greater than that of water. Contaminants with high soil adsorption
coefficients may bind to soils and become relatively immobile.
3. Important intermedia transfer mechanisms affecting soil contaminants
include volatilization or resuspension-to the atmosphere and biouptake by
plants and soil organisms. These, in turn, introduce contaminants to the
food chain.
4. The fate of contaminants in ground water is assessed whenever site
contaminant release screening analyses indicates direct introduction of
contaminants to ground water (e.g., through disposal wells, or fluid
releases to an aquifer near the ground surface), or whenever the
screening assessments of atmospheric, surface water, or soil contaminant
fates (as outlined above) indicate potential contaminant transfer to
ground water.
5. The qualitative assessments of ground-water flow is often based on
the assumption that subsurface hydrologic gradients (which determine flow
directions and rates) approximate surface topography. This approach is
unrellabile and should be used only in the absence of hydrogeologic
data. Ground-water flow is influenced by many factors including
hydraulic conductivity of soils, hydraulic gradient, presence of
subsurface impermeable barriers, presence of discharge areas (e.g.,
streams intercepting ground-water flow) and presence of fissures,
cavities, or macropores. Hydrogeologic survey data (where available)
provides a more reliable basis for contaminant transport assessment than
do surface topographs.
4-7
-------
OSWER Directive 9285.5-1
s a
3 1C
S E
X 3
h- a
ig
UJ
= 2
11
o g
H
S u
K a
! Q ฃ
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COULD CONTAMINANTS REACH
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^
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O
z
CONSIDER TRANSFER OF CONTAMINANTS
TO SURFACE WATER MEDIUM. ASSESS FATE
IN THIS MEDIUM (Sn Fipre 4-2)
4-8
-------
OSWER Directive 9285.5-1
6. Site and surrounding community survey data describing the location of
wells are compared with the expected subsurface contaminant plume ,
boundaries to identify locations of potential exposure points.
7. Important mechanisms of contaminant transfer from ground water to
other environmental media include contaminated water exchange between
surface waters and ground water and uptake of contaminants by edible
biota. The former mechanism must be considered whenever surface waters
are downgradient from the CERCLA site; it increases in likelihood with
closer proximity of these surface waters to the site. Available
hydrogeologic information for the site and surroundings should be
reviewed for any indication that the aquifer underlying the site is
connected to surface waters.
The second major intermedia transfer mechanism, biouptake, may occur
through two pathways: (1) direct exposure of plants and lower trophic
level animals to contaminated ground water in regions where the
ground-water level is close to or at the soil surface (e.g., marshy
areas, areas adjacent to aquifer discharge points) and (2) blotic
exposure to ground water due to human activities such as irrigation or
watering of livestock with well water.
4.2.4 Contaminant Environmental Fate Screening: Biotic Fate
The following numbered paragraphs are provided to facilitate
interpretation and application of the blotic fate decision network
presented as Figure 4-4. Each paragraph refers to a particular numbered
box in the figure.
1. A scraening environmental fate assessment for the biotic medium is
performed after the fate of contaminants in the atmosphere, surface
waters, or ground water has been assessed. Starting with the expected
distribution of contaminants 1n each of these media, potential points of
biotic contact with contaminated media and important affected biotic
species are Identified.
2. Important species are those used directly by man (game animals, sport
or commercial fish, crustaceans, and mollusks, agricultural crops and
livestock; naturally-occurring fruits, herbs, other edible vegetation),
and those that introduce contaminants to species used by man through the
food chain (e.g., livestock feed crops; or plants and lower trophic-level
animals consumed by any of the animal groups listed above).
3. Assessed mechanisms of transport in the biotic medium include
biomagnification through the food chain, natural animal migration, or
human commercial activity. Food chain biomagnification can result in
high concentrations of contaminants in the tissue of edible species not
4-9
-------
OSWER Directive 9285.5-1
AMBIENT CONTAMINANT CONCENTRATION
AND DISTRIBUTION ESTIMATES FROM
AIR, SURFACE WATER, GROUND WATER
SCREENING FATE ANALYSES
POTENTIAL BIOTIC
EXPOSURE TO
CONTAMINANTS
I
CONSIDER BIOTIC SPECIES WITHIN AREAS OF
ELEVATED AMBIENT HAZARDOUS SUBSTANCE
CONCENTRATIONS AS POTENTIAL VECTORS
OF HAZARDOUS SUBSTANCES
i
CONSIDER TRANSPORT OF HAZARDOUS MATERIAL
WITHIN BIOLOGIC MEDIUM
MAJOR MECHANISMS: HUMAN COMMERCIAL ACTIVITY,
ORGANISM MIGRATION, MOVEMENT OF HAZARDOUS
MATERIAL THROUGH FOOD CHAIN.
IDENTIFY EDIBLE BIOTIC SPECIES
AFFECTED INDIRECTLY THROUGH
FOOD CHAIN BIOMAGNIFICATION
ASSESS POTENTIAL EDIBLE TISSUE
CONCENTRATIONS, DISTRIBUTION OF
CONTAMINATED ORGANISMS
IDENTIFY
EXPOSED HUMAN POPULATIONS
(CHAPTER 5)
FIGURE 4-4. ENVIRONMENTAL FATE SCREENING ASSESSMENT DECISION NETWORK: FOOD CHAIN
4-10
-------
OSWER Directive 9285.5-1
In direct contact with contaminated air, water, or ground water. Human^
commercial transport and natural migratory behavior of contaminated
species can result in wide distribution of edible species or
tissue-containing contaminants.
4. Edible tissue concentrations are a function of the level and type of
biotic exposure to contaminants, the partitioning of contaminants between
organic tissue and substrate media, the biodegradability of contaminants,
organism-specific metabolic characteristics, and ecosystem
characteristics.
4.3 Quantitative Environmental Fate Analysis
The following subsections provide two forms of guidance for
quantitative environmental fate analyses. For each environmental medium,
simplified algorithms for calculating important environmental fate terms
(contaminant distribution and/or ambient concentrations) are first
presented. The discussion of these algorithms is followed by annotated
lists of 1n-depth environmental fate analysis methods and models.
Simplified environmental fate estimation procedures are based on the
predominant mechanisms of transport within each medium, and they
generally disregard transfer or transformation processes. They produce
conservative estimates (i.e., reasonable upper bounds) for final ambient
concentrations and the extent of hazardous substance migration. Because
the estimates obtained by these procedures serve as input to subsequent
identification of exposed populations and exposure estimations, it is
important to avoid underestimating or overlooking significant pathways
that Impact human health. Wherever the simplifying assumptions
incorporated into these estimation procedures could lead to
underestimation of ambient concentrations or movement of hazardous
substances 1n the environment, this is indicated in the discussion. In
general, it will be necessary to use more sophisticated, in-depth
analysis techniques (i.e., modeling/monitoring) in such cases.
When more in-depth analysis of environmental fate is required than
can be performed with simplified algorithms, the analyst must select the
modeling procedure that is most appropriate to the circumstances under
study. In general, the more sophisticated models are more data-, time-,
and resource-intensive. Models that produce results of greater
sophistication than is required for public health evaluation or is
supported by the reliability or availability of data should be avoided.
The following criteria should be considered when selecting an
in-depth environmental fate model or method.
Capability of the model to account for important transport,
transformation, and transfer mechanisms.
4-11
-------
OSWER Directive 9285.5-1
"Fit" of the model to site-specific and substance-specific
parameters.
Data requirements of the model, compared to availability and
reliability of site information.
Form and content of model output. Does it address important
questions regarding human exposure, environmental effects? Does
it provide all data required as input to further analysis?
As an aid in identifying the important fate processes affecting the
substance in question or operative at the site, information regarding the
major environmental processes that may affect the fate of hazardous
substances in each medium is provided. These processes include
transformation and intermedia transfer mechanisms, as well as the more
complex transport mechanisms that are not incorporated into the provided
estimation procedures.' By comparing the list of important processes
identified for the site with the tabular summary of model features
presented at the end of each section, a selection of the model best
suited to the requirements of the site can be made.
An excellent guide to the selection of computer-based contaminant
fate models can be found in Modeling Remedial Actions at Uncontrolled
Hazardous Waste Sites (USEPA. 1985e). This document goes beyond providing
detailed guidance on the matching of site parameters, data availability,
and data needs with model capabilities. It also provides guidance on
matching models to remedial alternatives being considered at a site.
Models listed in the following subsections cover a wide range in
complexity, capabilities, and resource requirements. The degree of
sophistication varies from the simplified algorithms to the highly
complex and detailed.
One particular set of computer models is highlighted in the
following sections because of its easy accessibility and use, and because
of its ability to produce sophisticated analyses of environmental fate.
This is the Graphical Exposure Modeling System (GEMS), prepared by the
EPA's Exposure Evaluation Division (EED), Office of Toxic Substances
(OTS).
GEMS consists of models capable of assessing contaminant fate in air,
surface water, ground water, and soil. These fate models are integrated
with pertinent data files (containing nationwide soil, land use, and
meteorological data, in addition to data on many major river systems,
lakes, and reservoirs), user-input data manipulation and storage
capabilities, statistical processing programs, and graphics capabilities
including presentation of results in map form.
4-12
-------
OSWER Directive 9285.5-1
GEMS is designed to be user-friendly. Although environmental fate
modeling experience is highly desirable, personnel with no computer
programming background can also use the system because of its progressive
menu and user prompting formats. At each decision point, the user is
presented with a list of possible selections. When specific data are
required for activation of a program, the system requests each type of
data needed and the units required. At any point in the procedure, the
user can request help from the system, whereupon a clear explanation of
the choices or steps facing the user is provided.
The GEMS host computer is a Vax-11/780, which is located at the EPA
National Computer System at Research Triangle Park, North Carolina.
The system can be accessed and used with the following terminal types:
DEC UT-100 series
Tektronix 4014 series
ASCII
Terminals must be capable of transmitting or receiving ASCII data in
full duplex mode, using even parity and seven bit data word'length, with
communication rates of 300 or 120Q bits per second. Most common acoustic
modems are compatible (GSC 1982).
4.3.1 Atmospheric Fate
(1) Simplified Procedures. The atmospheric fate of substances
released from uncontrolled hazardous waste sites can be estimated based
on the two predominant mechanisms affecting the movement of airborne
substances, advectlon and dispersion.
The following equation takes these two mechanisms Into account and
estimates ground-level atmospheric concentrations of pollutants at
selected points directly downwind from a ground-level source (Turner
1970): -
C(x) V (4-1)
ir a a u
y z
Contact personnel within the EED are Ms. Patricia Harrigan, Mr. Loren
Hall, or Mr. Russell Klnnerson. They can be reached at EPA, Washington,
DC., (202) 382-3931.
4-13
-------
OSWER Directive 9285.5-1
where
C(x) = concentration of substance at distance x from site
(mass/volume).
Q = release rate of substance from site (mass/time).
ay = dispersion coefficient in the lateral (crosswind)
direction (distance).
az = dispersion coefficient in the vertical direction
(distance).
H = mean wind speed (distance/time).
* = the value pi =ป 3.141593.
The appropriate dispersion coefficients can be taken from Figures 4-5
and 4-6. These figures provide values for <*y and az,
respectively, as functions of downwind distance, x, and stability classes
A though F. These stability classes are based on the Pasquill stability
classification system, where Class A is very unstable and Class F is very
stable (see Pasquill 1961).
Values for wind speed, wind direction, and stability class can be
taken from Table 4-1 for estimating maximum ambient concentrations.
These values are only recommended if site-specific meteorological data
cannot be obtained for the site region; however, the use of site-specific
data is highly recommended. The values in Table 4-1 represent reasonable
worst-case assumptions for conditions likely to occur at a site for the
time periods specified and will therefore resu.lt in conservative
estimates of ambient concentrations. When using these values, multiply
the concentration value obtained from Equation 4-1 by the appropriate
percent value in the final column of Table 4-1 to Incorporate reasonable
worst-case assumptions regarding wind directional variability.
For estimation of long-term mean atmospheric concentrations, a wind
speed of 3 meters/second, stability Class D, and the assumption that the
wind blows towards the exposure point 30 percent of the time can be used
where necessary in lieu of site-specific data, or for very rough
conservative estimates.
More accurate estimates of long-term mean atmospheric concentrations
can be obtained through use of STAR (Stability Array) data specific to
the site. These data provide seasonal or annual joint frequencies for
each stability class, wind direction, and wind speed category. Assume an
annual average wind speed of 3 meters/second, and calculate the long-term
mean atmospheric concentration for each receptor by applying a weighted
average, based on the relative frequency of each stability class and of
wind flow toward selected exposure points. Equation 4-2 provides a rough
weighted average estimate:
4-14
-------
OSWER Directive 9285.5-1
10,000-
1,000-
u*
1
o
c x
100-
//
10'
0.1
1 10
DISTANCE DOWNWIND, km
100
FIGURE 4-5. HORIZONTAL DISPERSION COEFFICIENT AS A FUNCTION OF DOWNWIND DISTANCE
FROM THE SOURCE (From Turner, 1970)
LINES DESIGNATED A THROUGH F REPRESENT DISPERSION COEFFICIENT FUNCTIONS FOR ATMOSPHERIC STABILITY CLASSES
A THROUGH F. SEE TEXT FOR SOURCES OF ATMOSPHERIC STABILITY DATA .
4-15
-------
OSWER Directive 9285.5-1
1,000-
0>
N 100-
10-
D:
_j^
E-,
1.0-
0.1
1 10
DISTANCE DOWNWIND, km
100
FIGURE 4-6. VERTICAL DISPERSION COEFFICIENT AS A FUNCTION OF DOWNWIND DISTANCE
FROM THE SOURCE (From Turner, 1970)
'CURVES DESIGNATED A THROUGH F REPRESENT DISPERSION COEFFICIENT FUNCTIONS FOR
ATMOSPHERIC STABILITY CLASSES A THROUGH F. SEE TEXT FOR SOURCES OF ATMOSPHERIC
STABILITY DATA. _
-------
0603E OSWER Directive 9285.5-1
Table 4-1. Assumptions for Calculation of Short-term
Maximum Concentrations in Air*
Duration
1 hour
24 hour
7 days
Wind speed
1 m/sec
2 m/sec
3 m/sec
Stability
class
F
E
D
Percent
towards exposure point
100
50
30
* These assumptions are provided for general guidance only. For some
sites, such as deep valleys, these input assumptions may be
inappropriate and detailed site-specific data may be required.
4-17
-------
OSWER Directive 9285.5-1
C/\(x)= concentration at point x during stability class A (from <
Equation 4-1).
f/\ = relative annual frequency of stability class A for the
specified wind direction.
and subscripts B through F represent the various stability classes.
. Hi
Note that this estimate 1s a rough" approximation because 1t 1s
simplified by the assumption that the mean wind speed 1s 3 m/second for
all stability classes. A more sophisticated estimate can be made by
Incorporating site-specific wind speed frequency data, and performing
similar weighted average calculation of ambient concentrations. This 1s
a time-consuming procedure, however, and the use of computer based <
estimation procedures may be more cost-effective 1f sophisticated
estimates are required. STAR data are available for all U.S. locations
from the National Climate Center (NCC), Ashevllle, North Carolina
(phone: (704) 259-0205).
The area within which the ground-level concentration of a hazardous 1
substance 1s above a predetermined critical concentration (I.e., the
plume Isopleth) can be described using the following procedures.
Calculate the crosswlnd distance from any point along the plume
centerllne (I.e., perpendicular to the plume centerllne) to the Isopleth
boundary by Equation 4-3: ' ^
P/V\ \ ' ' ' / \
=|2in - ' i w- ' (4"3)
where
()
C(CL) = predetermined critical concentration level (mass/volume).
V(x) = perpendicular distance from point on plume centerllne
to the C(CL) Isopleth boundary (length units).
C(x) = concentration at plume centerllne, x distance from source
(mass/volume, as calculated by Equation 4-1).
-------
OSWER Directive 9285.5-1
increasing this value until the value for C(x) (obtained from
Equation 4-1) equals the predetermined critical concentration C(CL).
Values calculated for y describe the isopleth boundary on either side of
the plume centerline.
Estimate the area within a plume isopleth using Figure 4-7 (Hilsmeier
and Gifford 1962 as presented by Turner 1970), which plots the value
C(CL)M, (relative concentration times wind speed with nomenclature
Q
remaining as defined for Equations 4-1 and 4-3) versus isopleth area, for
each stability class A through F.
All of the preceding simplified equations provide atmospheric fate
estimates based on several simplifying assumptions, one of which requires
special mention. This is the assumption that the hazardous substance
released from a site is in a form that can remain airborne indefinitely
(i.e., either gaseous, or consisting of particles less than 20 microns in
diameter; Turner 1970).
In cases where fugitive dust blown from the site includes solid
hazardous substances (or soil- particulates carrying adsorbed hazardous
substance) of greater diameter than 20 microns, relatively rapid
gravitational settling of the larger particles occurs. Consequently,
much of the hazardous material reaches the ground before advection and
dispersion can transport and dilute the plume as described by the above
equations. Thus, areas close to the uncontrolled hazardous site may
experience significant soil contamination, and human exposure points
farther from the site may experience lower atmospheric concentrations
than estimated by these equations. Hanna and Hosker (1980) present a
procedure for estimating the gravitational settling rate, distance of
travel from the source, and deposition rate of airborne particulates.
All of the above simplified procedures incorporate the following
additional assumptions:
Steady state condition, i.e., windspeed is steady at rate u, and
the hazardous -substance release is continuous, at average rate Q.
Wind direction is also assumed to be steady; short-term
fluctuations are disregarded.
Longitudinal dispersion is negligible (substance travels at wind
velocity in the downwind direction).
The substance is conservative (all removal and decay processes are
disregarded).
The substance is distributed normally, or according to a Gaussian
distribution, both vertically and in the crosswind direction.
4-19
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OSWER Directive 9285.5-1
01
10a
10ฐ
10'
10C
10
10"
10J
E
D
C
B
A
10"
10"
,-4
10
C(CL)/i
10
,-3
FIGURE 4-7. AREA WITHIN ISOPLETHS FOR A GROUND-LEVEL SOURCE
(Hilsmeir and Gifford 1962, as presented by Turner, 1970)
* CURVES DESIGNATED A THROUGH F REPRESENT FUNCTIONS FOR ATMOSPHERIC STABILITY CLASSES
A THROUGH F. SEE TEXT FOR SOURCES OF ATMOSPHERIC STABILITY DATA.
10'
4-20
-------
OSWER Directive 9285.5-1
. The air environment is homogeneous; wind speeds and stability are
equal at all'heights above the ground, and no obstructions to wind
flow or dispersion exist other than at the ground. Complete
reflection occurs at the ground/air interface.
Releases are at ground level, with no initial vertical velocity or
heat capable of causing initial plume rise. . All vertical
transport Is a result of dispersion.
(2) In-Oepth Analysis. In cases where estimates of ambient
atmospheric concentrations of hazardous substances developed by the
preceding simplified procedures indicate that these concentrations pose
ootencial health hazards, more accurate, In-depth analysis of atmospheric
fata may be required. Numerous computer models are available for this
purpose. These models vary in sophistication and capability, and in
their ability to Incorporate expressions describing the effect of various
processes on the atmospheric fate of hazardous substances. The most
important of these processes are briefly described below. Consider the
Importance of each of these processes to the atmospheric fate of the
substances under analysis before selecting a computer model.
a. Intermedia transfer. The following are the most Important
processe's that affect the removal of hazardous substances from the air
medium and their transfer to other sectors of the environment.
" Dissolution. -This 1s the process whereby hazardous substances in
the gaseous state are dissolved into water droplets present in the
atmosphere. This process, followed by precipitation, distributes
the substance over the surface media, and percolation to ground
water may follow. Direct dissolution may also occur between
gaseous substances In the atmosphere and surface waters at the
air/water Interface. Dissolution Is a constant, reversible
process, the amount of hazardous substance In the aqueous phase is
determined by the partition coefficient of the substance between-
the gas and aqueous phases. This partition coefficient is in turn
a function of the vapor pressure and water solubility of the
substance, Its concentration In the air, and temperature. See
Lyman et al. (1982) or Hanna and Hosker (1980) for methods of
estimating this partition coefficient and atmospheric half-lives
due to d1ssolution/ra1'nout.
Adsorption. Through the process of adsorption, hazardous
substances in the vapor phase become attached to particulate
matter suspended In the air (aerosols), or onto soil particles at
the air/soil media Interfaced Suspended aerosols settle to
surface media, thereby removing adsorbed substances from the air
environment. The adsorption rate of a particular substance- is
4-21
-------
OSWER Directive 9285.5-1
principally a function of the number and surface area of aerosols
per volume of air, the molecular weight of the substance In
question, Its concentration in the air, and its saturation vapor
pressure. Cupltt (1980) provides a method for estimating
atmospheric contaminant removal rates due to adsorption to
particulates and settleout.
Gravitational settling. As stated earlier, this mechanism Is most
Important for partlculate hazardous substances, or hazardous
substances adsorbed onto suspended particulates, if the
partlculate matter Is more than 20 urn in diameter. These
particles settle to the surface media at a rate that is a function
of their density, shape, and diameter, and of wind speed (see
Hanna and Hosker 1980).
b. Intramedla transformation processes. Many hazardous substances
are subject to decay or transformation to other substances with new
properties while entrained 1n the air environment. The two most
Important of these processes are described .below. While the product of
such transformation processes will usually have different properties from
those of the original hazardous substance, it should be noted that the
new substance produced may also have hazardous properties. Cupltt (1980)
provides estimates of constants that determine the rate of each
transformation process below, as well as of the Importance and likely
products of these processes, for 46 hazardous materials. Hendry and
Kenley (1979) also provide rate constants and estimation procedures for
these processes.
Photolysis. This Is the breakdown of substances because of
photochemical reaction brought about by solar energy. Photolysis
can be direct, when the hazardous substance Is Itself affected by
solar radiation, or Indirect when the hazardous substance reacts
with other substances that have been raised to a reactive state by
solar radiation. Photolysis rates depend .on solar radiation
availability, the light absorption coefficient of the hazardous
substances, and a reaction yield constant (which describes the
efficiency of transformation of the hazardous substance with the
available sun energy).
Oxidation. The reaction of substances with oxidants in the
atmosphere can result In their transformation. The two most
Important atmospheric oxidants are ozone and the hydroxyl
radical. Reaction rate constants for oxidation are chemical
"specific; the overall rate of transformation of a hazardous
substance by oxidation depends on the concentration of the oxldant
and the reaction rate constant.
4-22
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OSWER Directive 9285.5-1
The effects of terrain. Features such as vegetation, large
buildings,'urban areas, rougji topography, hills, or mountains can
all profoundly affect the atmospheric fate of airborne substances,
principally by altering the laminar flow of transporting wind
currents. The effects of terrain on wind currents may include
Increased turbulence, downwash in the lee of large obstacles, or
localized alterations In the direction of flow. Because the
release of substances from hazardous waste sites usually occurs at
ground level, the fate of these substances Is especially
susceptible to the effects of terrain. Select a model capable of
accounting for these effects In any case where these listed
terrain features exist between the site and points of human
exposure.
(3) In-Depth Methods and Models. Tables 4-2, 4-3, and 4-4 provide
Information about computer-based models most appropriate to in-depth
analysis of the atmospheric fate of substances released from CERCLA
sites. Table 4-2 centalnsoresource requirements, references, and sources
for each model; Table 4-3 summarizes their features and capabilities; and
Table 4-4 discusses the data requirements of each. Through comparison of
the Information In these tables with Identified site features, site data
availability, final output requirements, and resource availability, a
selection of the most applicable and cost-effective model can be made.
The Atmospheric Transport Model (ATM) Is the most sophisticated of
the atmospheric fate models presently Integrated Into the GEMS system. A
detailed description of ATM Is provided below. Three other models
directly accessible through GEMS (ISC, PTDIS, and PTMAX) are described in
Tables 4-2, 4-3, and 4-4.
The ATM (Cylkowskl and Patterson 1976) Is a Gaussian dispersion
model, capable of estimating the concentration and deposltfon rates of
gaseous and particulate pollutants around a point, area, or line source.
Because It Is Integrated Into the GEMS system, 1t is especially useful
for the analysis of the atmospheric fate of hazardous substances. Based
on a user-Input release location (1n the form of latitude/longitude
coordinates or zip code), stored cllmatological data from the nearest
meteorological monitoring, stations are retrieved (GSC 1982).
The Integration of ATM with a population distribution model called
SECPOP gives It the capability of expressing atmospheric fate of
pollutants 1n terms of numbers of people affected at various
concentration levels (this capability Is discussed In more detail In
Chapter 5, Exposed Populations). The graphic capabilities of the GEMS
package can be used to display ambient concentration as a function of
distance or direction from the release site, 1n the form of bar charts,
scatter plots, or circle diagrams. Ground-level plume isopleths can also
be depicted In map form (GSC 1982; personal communication with Mr. Loren
Hall, EPA-EED).
The following information must be provided by the user of the ATM
model (GSC 1982):
4-23
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4-28
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OSWER Directive 9285.5-1
Source location (latitude/longitude coordinates or zip code)
Cover type surrounding the site (on a scale of 1 for grassland to
10 for dense forest)
Source strength or emission rate, in grams per second
Emission state (gaseous or particulate)
If particulate emission, particle size and density
Molecular weight of pollutant
Atmospheric half-life of pollutant (calculated on the basis of
loss rates due to transfer or transformation processes)
The ATM model can estimate the concentration of pollutants released
from point, area, or line sources. Area sources are simulated by use of
a virtual point, and line sources by a series of points. Short-term
(hourly) or long-term (monthly, seasonal, annual average) concentration
estimates can be developed, and gravitational settling,
dlssolution/rainout, and Intramedia transformation losses can be
simulated based on user-input half-life data (GSC 1982).
ATM can be executed on IBM, CDC, or VAX computers. The model is
implemented within GEMS on EPA's VAX 11/780 and can be accessed, with a
variety of user terminal types. (See Section 4.3 for access
Instructions.)
(4) Short- and Lonq-Term Concentration Calculations. Long-term
average ambient-air concentrations of hazardous substances at-human
exposure points are estimated using the long-term average release rate
over the time period of interest, and the weighted averaging algorithm
presented as Equations 4-1 and 4-3. Annual average climatological data,
or STAR data including long-term frequencies of all climatological
parameters, should be used as input to these equations.
Where site-specific data are unavailable, short-term concentration
levels are estimated using the maximum short-term release rate and
climatological assumptions presented in Table 4-1. When using
site-specific data, the most stable atmospheric conditions, lowest wind
speed, and greatest percent of wind flow towards the receptor should be
used as Input to Equation 4-1, along with maximum release rate estimates
for the duration of Interest. Usually, the receptor nearest the point or
area of a ground-level release experiences the highest short-term
exposure.
4-29
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OSWER Directive 9285.5-1
As Indicated In Table 4-2, several atmospheric fate models have the
capability of producing short-term maximum and long-term average ambient
concentration estimates where in-depth analysis is desirable.
4.3.2 Surface Water Fate Analysis
The environmental fate of hazardous materials entering surface water
bodies is highly dependent on the type of water body. The three major
classifications are rivers and streams, impoundments, and estuaries.
Methods for estimating contaminant concentrations in the first category
are provided below. Because of the diversity in reservoir and estuary
types, and the relative complexity of the methods necessary for
predicting hazardous material fate in these various environments,
approaches that conservatively estimate ambient hazardous material
concentrations are beyond the scope of this work. Refer to Mills et al.
(1982) for estimation methods covering impoundment and estuary fate
assessment.
(1) Simplified Procedures. The following equation (adapted from
Delos et al. 1984) provides a rough estimate of the concentration of a
substance downstream from a point source release Into a flowing water
body, after dilution of the substance by the receiving water body:
(4-4)
where
c -
ce -
Qt -
concentration of substance in stream (mass/volume).
concentration of substance in effluent (mass/volume)
effluent flow rate (volume/time).
combined effluent and stream flow rate (volume/time)
In cases where hazardous waste is introduced into a stream through
Intermedia transfer from air, soil, ground water, or from a nonpoint
source, or where the release rate is known in terms of mass per unit time
rather than per unit effluent volumes, in-stream concentrations can be
estimated by use of the following equation:
(4-5)
4-30
-------
OSWER Directive 9285.5-1
where
Tr = Intermedia transfer rate (mass/time).
Qt = stream flow rate (volume/time).
Assumptions Implicit 1n these equations are:
Mixing of the hazardous substance 1n the water 1s Instantaneous
and complete.
The hazardous material 1s conservative (I.e., all decay or removal
processes are disregarded).
Stream flow and rate of contaminant release to the stream are
constant (I.e., steady state conditions).
The assumption of complete mixing of a hazardous substance 1n a
flowing water body 1s not valid within a mixing zone downstream from the
point or reach of substance Introduction. Under certain conditions, this
mixing zone can extend downstream for a considerable distance, and
concentrations can be considerably higher within the mixing zone than
those estimated by the foregoing dilution equations.
The length of the mixing zone 1s estimated by the following equation
(adapted from Fischer et al. 1979, L1u 1977, Neely 1982):
HZ = 0.4 w2u (4-6)
0.6d ~
where
MZ * mixing zone length (length units).
w = width of water body (length units).
u = stream velocity (length/time).
d = stream depth (length units).
s = slope of the stream channel (length/length).
g = acceleration due to gravity (32 ft/sec2).
In addition, these equations provide 1n-stream contaminant
concentrations resulting from site releases only. If total 1n-stream
contaminant concentrations are desired, these should be estimated by
adding background (I.e., upstream from the site) 1n-stream contaminant
concentrations to those estimated by Equations 4-4 and 4-5.
If the hazardous substance 1s Introduced Into a flowing water body
over a length of that body, rather than from a point source, assume that
4-31
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OSWER Directive 9285.5-1
the mixing zone begins at the downstream end of the reach over which
Introduction takes place. Neely (1982) presents an estimation procedure
for hazardous substance concentration at exposure points within a mixing
zone that Incorporates an expression for dispersion.
The above dilution equations (4-4, 4-5) and the procedure presented
by Neely (1982) assume that the Introduced hazardous substance 1s
conservative. Therefore, they predict an estimated stream/river
concentration that remains constant from the downstream end of the mixing
zone throughout the remaining length of the stream, or decreases only
with further dilution due to additional stream flow from tributaries.
This 1s useful as a basic model for the fate of conservative hazardous
substances; for nonconservatlve substances, 1t provides a useful
worst-case estimate. If the released substance 1s found through this
estimation procedure to be diluted to concentrations below a
predetermined level of concern, and no Important exposure points exist
.within the mixing zone, the fate of the substance 1n this medium may need
no further analysis. However, where the concentration after dilution of
a nonconservatlve substance 1s still above a predetermined critical
level, 1t may be useful to estimate the distance downstream where the
concentration will remain above this level, as well as the concentration
of the substance at selected exposure points downstream.
This type of estimation can be performed through using an overall
decay coefficient, which represents a .combination of all decay and loss
rates affecting the removal of a substance from a water body. The
concentration of a nonconservatlve substance at a selected point
downstream from the release point and beTow the mixing zone; (complete
mixing 1s assumed) can be estimated by the following equation (from Delos
et al. 1984), which employs the concept of an overall decay coefficient:
-K*
W (x) = W(0)e U (4-7)
The overall decay coefficient can also be used to estimate the
distance downstream over which a nonconservatlve substance remains above
a predetermined critical concentration level W(CL). This 1s estimated by
substituting W(CL) for W(x) 1n Equation 4-7, and solving this equation
for x, as follows:
u f
K \
in rWCDI \ (4-8)
in [W(0)] I
Nomenclature for both equations 1s as follows:
4-32
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OSWER Directive 9285.5-1
W(CL) = predetermined critical concentration level (mass/volume)
W(x) = concentration at downstream distance x (mass/volume).
W(0) = concentration immediately below point of introduction
(from dilution Equations 4-4, 4-5).
e = exponential function.
K = overall decay coefficient (time)"1.
u = stream velocity (length/time).
x = distance downstream from point of introduction (length
units).
This equation incorporates the following assumptions:
Complete mixing.
Steady-state conditions.
Longitudinal dispersion is negligible; substance transports
downstream at stream velocity.
All decay and transfer processes can be described as first-order
coefficients (I.e., decay rates are a direct function of hazardous
substance concentration).
Values for K can be derived empirically where monitoring data are1
available, or can be estimated based on decay rate constants available
for many hazardous substances in the technical literature.
Concentration data from Immediately below the point of substance
release Into a stream, and from at least one point downstream of the
mixing zone are required for the empirical estimation of K. Note that
overall decay coefficients are substance- and site-specific and can vary
with climatic and hydrologlc conditions. Care must be taken in
calibrating the coefficient empirically. Data covering seasonal
fluctuations must be used, and seasonal values for K corresponding to the
various observed conditions, or a worst-case K value (I.e., lowest
reasonable value) for the purpose of conservative estimation should be
developed.
For estimation of K through the summation of published decay rate
constants, the most Important removal process affecting the compound of
concern In the receiving water body must be known. For this information,
see the discussion below (Section 4.4.2), or see Callahan et al. (1979),
or Mabey et al. (1982). Additional references that provide decay rate
constant values for a wide variety of compounds include: Verschueren
(1979), Dawson, English, and Petty (1980), and USCG (1974).
Reliable values for K, which have been developed for a given water
body and hazardous substance under no-action (i.e., during remedial
investigation) conditions, can be used to estimate the fate of this same
substance resulting from the release rates projected after implementation
of various remedial action alternatives.
4-33
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OSWER Directive 9285.5-1
(2) In-Depth Analysis. When aquatic concentration estimates
developed by the above simplified methods (or methods covering estuaries
or impoundments provided by Mills et al. 1982) indicate that these
concentrations pose a potential human health hazard at one or more
exposure points, more accurate estimates of short-term and long-term
concentrations of the hazardous substance may be required. A large
number of in-depth methods and computer models exist for assessing the
fate of substances in the aquatic environment. Each of these models
differs in the number and types of aquatic fate processes that it
incorporates. The most important of these aquatic processes are
described below, and information is provided to allow identification of
those processes most likely to be significant at the site, and for the
hazardous substances under analysis.
a. Intermedia transfers. The major processes by which hazardous
substances can be transferred from surface water to other environmental
media are as follows:
Volatilization. Volatilization of a substance from water is
dependent upon physiochemical properties of the substance and
characteristics of the water body and body of air involved.
Volatilization increases in importance for substances with higher
vapor pressure, and for water bodies with higher surface
area-to-volume ratios and higher turbulence (Deles et al. 1984).
The importance of volatilization as a route of intermedia transfer
for 129 priority pollutants is given by Callahan et al. (1979).
If volatilization is considered an important process for the
substance being studied, or if the importance of volatilization is
unknown, rate of volatilization can be estimated by the method
provided by Mills et al. (1982) for quiescent water bodies, or by
Delos et al. (1984) for turbulent bodies. Lyman et al. (1982)
also provide methods for estimating volatilization rates from
water.
Sedimentation. Hazardous substances released to a surface water
body in the solid, particulate form will settle out over time and
become mixed into the bottom sediment. In addition, liquid
hazardous substances with high affinities for adsorption to
suspended particulates will settle out of surface waters with
these particulates. The rate of sedimentation is governed by the
difference between settling velocity and resuspension velocity.
The former increases with mean particle size and density and with
water temperature, and can be estimated by the procedure presented
by Delos et al. (1984). Resuspension velocity is a function of
bottom shear stress. Delos et al. (1984) also provide a procedure
for estimation of this rate. Where sedimentation is considered to
4-34
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OSWER Directive 9285.5-1
be an important process, use a surface water fate model that has
the capability of accounting for bed-water exchange and sediment
load transport.
Sorption. Substances dissolved in surface waters can sorb onto
solids suspended in the water, or onto bed sediments. This
process, in effect, transfers the substances from the water to the
sediment medium, and proceeds until an equilibrium point is
reached. This equilibrium point (and the resulting water and
sediment concentrations of the substance) is determined by the
soil-water partition coefficient, a parameter that is a function
of sediment type, water pH, cation exchange capacity, and organic
content of sediment, and the physicochemical properties of the
hazardous substance. In general, metals and hydrophobic,
non-polar organic compounds have a high tendency to sorb onto
entrained or bottom sediment. See Lyman et al. (1982) for methods
of estimating sediment adsorption of waterborne contaminants.
b. Intramedia transformation processes. The following is a brief
description of the important intramedia transformation processes that may
be significant for the surface water fate of hazardous substances.
Rate-controlling factors are stated for each. Callahan et al. (1979),
Mabey and Mills (1982), Verschueren (1984), and Sax (1984) provide rate
constants for these processes for numerous compounds.
Photolysis. Chemical transformation due to photolysis utilizes
energy from sunlight and for some chemicals can occur by several
processes. Direct photolysis rates are a function of photon
availability, light absorption coefficients for the chemical in
question, and a reaction yield constant (i.e., the efficiency of
substance transformation with the available solar energyX.
Indirect photolysis occurs through the action of intermediate
substances naturally occurring in the medium. These intermediates
absorb light energy by various processes, and in this energized
state react with the hazardous substance. Indirect photolysis is
a function of photon availability, concentration and light
absorption coefficient of the intermediate, and a rate constant
for the reaction between the energized intermediate and the
hazardous material.
Oxidation. This is the reaction of substances with oxidant
species. Oxidation rates are a function of the concentrations of
the substance in question, concentration of the oxidant, and a
rate constant for reaction between them.
4-35
-------
OSWER Directive 9285.5-1
Hydrolysis. Hydrolysis refers to the introduction of a hydroxyl
group into a compound, usually either as an addition or as a
substitution for another group. Hydrolysis of most compounds is
highly dependent on the pH of the water body medium, and can be
promoted by both acid and base conditions. The rate of hydrolysis
is a function of the concentration of the hazardous substance, and
the rate constants for the acid- and base-promoted processes at
each pH value.
Biodegradation. This is the breakdown of substances through the
enzymatic action of biota present in the water. Mos.t
biodegradation is carried out by microbial biota. It is a
function of the metabolic rates and characteristics and the
population density of the biotic agents, which are in part
functions of the availability of other nutrients, pH and
temperature of the medium, and sunlight availability among other
factors.
(3) In-Depth Methods and Models. Tables 4-5, 4-6, and 4-7 summarize
the features, data requirements, resource requirements, and references or
contacts for selected computer-based models appropriate to the in-depth
analysis of the aquatic fate of hazardous releases from Superfund sites.
The surface water model presently integrated into the EPA GEMS system
1s EXAMS. This model 1s comprehensive in the transport and
transformation processes that it Incorporates and is versatile in its
ability to simulate streams, rivers, ponds, and lakes. It cannot
estimate fate in estuaries or tidal systems, and it is limited only to
the modeling of the fate of organic compounds.
Because of Its relative complexity, EXAMS is data intensive. It
requires Information on climatic, biological, hydrological, and sediment
characteristics; physicochemical properties of the substance, such as
molecular weight, solubility, partition coefficients, hydrolysis rate
constants, biodegradation rates, etc; and release strength and stream
flow rate data.
A data set of average or typical values for water body-specific data
Is presently being developed by Battelle Northwest Laboratories, under
contract to EPA. This data file will contain parameter values for a
number of major U.S. river systems, reverine lakes, and reservoirs, and
will be integrated with the EXAMS program. These values will therefore
be accessible for fate modeling of the water bodies included (General
Software Corp. 1982).
4-36
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OSWER Directive 9285.5-1
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OSWER Directive 9285.5-1
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OSWER Directive 9285.5-1
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OSWER Directive 9285.5-1
4-43
-------
OSNER Directive 9285.5-1
(4) Short- and Long-term Concentration Calculations. Long-term
average ambient water concentrations should be calculated using: (1) the
average release rate (from Chapter 3) projected for the time period of
interest and (2) the annual average stream flow rate as input to the
above estimation procedures.
Short-term concentration levels are obtained through use of the
short-term release rate developed during contaminant release analysis and
the lowest reasonable 24-hour flow rate, or the 7-day, 10-year (7-Q-10)
low flow rate for the period of record, as presented in the above
estimation procedures.
Table 4-6 indicates several aquatic fate models capable of estimating
both short- or long-term ambient water concentrations that are
appropriate to in-depth analysis of the aquatic fate of contaminants
released from Superfund sites.
4.3.3 Ground-Water Fate Analysis
(1) Simplified Procedures. The fate of hazardous substances in the
soil (unsaturated zone) and in the ground water (saturated zone) after
release to these media from an uncontrolled hazardous waste site is .
determined by many, mainly site specific factors. The two estimation
procedures provided below for pollutant transport .in these zones
incorporate simplifying assumptions for hazardous substance properties as
well as the hydrogeology underlying the site. It must be emphasized,
however, that certain soil, geological, and hydrological features render
these assumptions nonconservative and the presented algorithms
inapplicable. These features, highlighted in the discussion of
assumptions implicit in these equations, are described in further detail
in Subsection 4.3.3(2) below.
The following procedures provide estimates of the rate of contaminant
travel and approximate boundaries of the contaminant plume as a function
of time elapsed since release. These procedures assume that, after
release from a site, contaminants travel vertically downward through the
unsaturated zone, dissolve into the ground water underlying the site, and
then travel with the advective flow of this ground water. They further
assume that contaminants are completely soluble in water and travel at
the velocity of leachate or ground water in the unsaturated and saturated
zones, respectively.
a. Unsaturated Zone. The following equation is used to estimate the
mean rate of downward travel of a hazardous material spread on or just
beneath the surface of soils (or deposited by wind, or by water
erosion/deposition). It provides the velocity of interstitial pore water
downward through the unsaturated zone, and therefore gives the assumed
velocity of hazardous substance movement through this zone. This
velocity is given by the following algorithm (Enfield et al. 1982):
4-44
-------
OSWER Directive 9285.5-1
(4-9)
where
Vpw = interstitial pore water velocity (length per unit time).
q = average percolation or recharge rate (depth per unit time).
9 = volumetric water content of unsaturated zone (decimal .
fraction, representing volume of water per volume of soil).
Records of estimated percolation rates for the site locality and
during the time period in question (or annual average percolation rate
estimates) are often available from local climate or soil authorities,
including regional U.S. Geological Survey (USGS) and U.S. Department of
Agriculture offices.
An estimation procedure can be used for evaluating percolation rates
(q) at sites where the sources listed above cannot provide them
directly. This estimation procedure requires data for precipitation,
evaporation, and runoff rates are available. In addition to the above
two sources, the National Weather Service, Forest Service offices,
National Oceanic and Atmospheric Administration (NOAA) gauging stations,
or other first order weather stations (e.g., at local airports) are
possible sources for these three types of data.
The following equation provides an estimate of the term q:
q = HL + Pr - ET - Qr
where
(4-10)
HL = hydraulic loading from manmade
Pr = precipitation, (depth per unit
ET = evapotranspiration, (depth per
Qr = runoff, (depth per unit time).
sources, (depth per unit time)
time).
unit time).
"The term HL, representing hydraulic loading from manmade sources, is
not significant or quantifiable at many sites. This term is generally
only used for sites at which liquids were applied to the site surface
(e.g., land application sites), and the volumes and general time periods
of application are on record. For such sites, HL is calculated by
dividing the volumes of liquid applied by the area of application, and
dividing the resultant depth value by the time periods during which the
liquid was applied. This HL value is added to other terms in Equation
4-10 only for those time increments during which the liquid application
took, place. For time increments during which no known or quantifiable
liquid application took place, and at sites where HL cannot be quantified
at all, the value for HL is zero.
4-45
-------
OSWER Directive 9285.5-1
Note that the term HL and Equation 4-10 are not applicable to sites
where high-volume releases resulted in saturated conditions or where
ponding are known to have occurred.
The average precipitation rate per unit time (Pr) for the study
period can be obtained from various local weather authorities such as
those 1isted above.
ET is estimated by using measured Class A pan evaporation rates (a
measure of local evaporation rates under standardized conditions,
available from the nearest NOAA gauging station) in the equation:
ET = EVAP x Cet x C
veg
(4-11)
where
EVAP
cet
region-specific or site-specific measured evaporation rates,
(depth per unit time).
correction factor for converting measured pan evaporation
rates to evapotranspiration rates froro turf grass, (unitless).
correction factor for converting evapotranspiration from turf
grass to evapotranspiration from other vegetative cover types,
(unitless).
Values for Cet are taken from Table 4-8,
and pan descriptive information.
which requires climatological
The term Cveg is available mainly for agricultural
with the
crops (see
Table 4-9), and varies with the thickness, depth, and characteristics of
vegetative cover. Typical values are 0.87 for shorter broadleaf plants
(alfalfa) to 0.6 for taller broadleaf plants (potatoes, sugar beets) and
0.6 for taller grains and grasses. Where crop-specific data is
unavailable, a conservative default value for this term is the smallest
reasonable value, or 0.6.
Qr, or the average runoff over the study period, is estimated by the
method presented in Section 3.5 of this manual, or through other
appropriate methods (e.g., Donigian et al . 1983). A more reliable value
for this term may be obtained from local USGS. gauging stations. For
relatively level sites, a reasonable conservative default value for the
purposes of this estimation procedure is that Qr = 0, where site-specific
data are unavailable or cannot be estimated.
The second independent variable in Equation 4-9, the volumetric water
content of the site soil (e) may be quantified during site
investigation through soil sampling and gravimetric analysis. The value
for e obtained in this manner, however, may reflect conditions only at
the time of the site investigation, and may not provide a value for 9
that is appropriate for the entire period of study.
4-46
-------
OSWER Directive 9285.5-1
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4-47
-------
0616E
OSWER Directive 9285.5-1
Table 4-9. Crop Coefficients for Estimating
Evapotranspi rat i on
Crop
Alfalfa
Potatoes
Small grains
Sugar beets
April
May 10
April
April
Period
1 - October 10
- September 15
1 - July 20
10 - October 15
Coefficient
(CVeg)
0.87
0.65
0.6
0.6
Source: Jensen 1973, as presented by Enfield et al. 1982.
4-48
-------
OSWER Directive 9285.5-1
The volumetric water content 1n the unsaturated zone for the five
period of concern may be estimated using the following equation adapted
from Clapp and Hornberger (1978):
e = e
1
2b+3
(4-12)
where
6 = volumetric water content 1n unsaturated zone (volume/volume
or unltless).
es = volumetric water content of soil under saturated conditions
(volume/volume, or unltless).
q = percolation rate (calculated by Equation 4-10; assumed to be
equal to the unsaturated hydraulic conductivity term 1n
ithe original Clapp and Hornberger equation; depth per unit
time).
Ks = saturated hydraulic conductivity (depth per unit time).
b = soil-specific exponential parameter (unltless).
The saturated volumetric water content (es), saturated hydraulic
conductivity (Ks), and the exponential function (b) are all related to
soil properties. The most reliable values for these parameters are
empirical values (1f available) measured during site Investigation.
Where empirical values are unavailable, values 1n Tables 4-10, 4-11,
4-12, and 4T13, provide guides for the rough estimation of es, Ks,
and the term 1 . Representative values from two different sources are
2b+3
presented for Ks (Tables 4-11 and 4-12) and es (Tables 4-10 and
4-13), 1n order to demonstrate the variability 1n estimates for these
values.
Note that the value e cannot exceed es, the saturated soil
moisture content. When e calculated by Equation 4-12 equals or exceeds
es, 1t must be assumed that saturated conditions exist. In such
cases, use es as the upper bound for the value e 1n Equation 4-9.
Similarly, the minimum value for e that 1s applicable to Equation
4-9 1s the field capacity of the soil. This value represents the
volumetric moisture content remaining 1n the soil following complete
gravity drainage, and 1s the moisture content below which downward flow
of water due to gravity through unsaturated soil ceases. Field capacity
1s a function of soil type; the most reliable values for the study site
are those measured empirically during site Investigation (1f this
parameter was evaluated). Where empirical values are not available,
4-49
-------
0603E OSWER Directive 9285.5-1
Table 4-10. Representative Values of Hydraulic Parameters
(Standard Deviation in Parentheses)
Soi 1 texture
Sand
Loamy sand
Sandy loam
Silt loam
Loam
Sandy clay loam
Silt clay loam
Clay loam
Sandy clay
Silt clay
Clay
No. of
soils3
13
30
204
384
125
80
147
262
19
441
140
1
bb 2b+3
4.
4.
4.
5.
5.
7.
7.
8.
10.
10.
11.
05
38
90
30
39
12
75
52
40
40
40
(1
(1
(1
(1
(1
(2
(2
(3
(1
(4
(3
.78)
.47)
.75)
.87)
.87)
.43)
.77)
.44)
.64)
.45)
.70)
0
0
0
0
0
0
0
0
0
0
0
.090
.085
.080
.074
.073
.058
.054
.050
.042
.042
.039
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
Q
395
410
435
485
451
420
477
476
426
492
482
c
s
(0
(0
(0
(0
(0
(0
(0
i
(0
(0
(0
(0
.056)
.068)
.086)
.059)
.078)
.059)
.057)
.053)
.057)
.064)
.050)
a Number of individual soil samples included in data compiled by Clapp and
Hornberger (1978).
b Empirical parameter relating soil matric potential and moisture content;
shown to be strongly dependent on soil texture.
c Volumetric soil moisture content (volume of water per volume of soil).
Source: Adapted from Clapp and Hornberger, 1978.
4-50
-------
0616E
OSWER Directive 9285.5-1
Table 4-11. Representative Values of Saturated
Hydraulic Conductivity
Hydraulic conductivity
Soil texture Number of soils3 (Ks; cm/sec)b
Sand
Loamy sand
Sandy loam
Loam
Silt loam
Sandy clay loam
Silt clay loam
Clay loam
Sandy clay
Silt clay
Clay
762
338
666
383
1,206
498
366
689
45
127
291
_3
5.8 x 10
-3
1.7 x 10
-4
7.2 x 10
_4
3.7 x 10
_4
1.9 x 10
-4
1.2 x 10
_5
4.2 x 10
-5
6.4 x 10
-5
3.3 x 10
-5
2.5 x 10
_5
1.7 x 10
a Number of individual soil samples included in data compiled by Rawls
et al. (1982).
b Predicted values based on compiled soil properties.
Source: Adapted from Rawls et al. 1982.
4-51
-------
0616E
OSWER Directive 9285.5-1
Table 4-12. Saturated Hydraulic Conductivity Ranges for
Selected Rock and Soil Types
Soils
Saturated Hydraulic
Conductivity (cm/sec)
Unweathered marine clay 5 x 10 10
-10 -4
Glacial till 10 10
Silt, loess 10~7 10"3
Silty sand 10~ 10~
-4
Clean sand 10 1
-1 2
Grave? 10 10
Rocks
Unfractured metamorphic
-2 -8
and igneous rock .10 10
Shale 5 x lo"12 10~?
-8 -4
Sandstone 10 5 x 10
-8 -4
Limestone and dolomite 5 x 10 5 x 10
Fractored igneous and
-6 -2
metamorphic rock 10 10
Permeable basalt 10
-4
Karst limestone 10
Adapted from Freeze and Cherry, 1979.
4-52
-------
0603E OSWER Directive 9285.5-1
Table 4-13. Representative Values for Saturated Moisture Contents and
Field Capacities of Various Soil Types
Saturated Moisture Content Field capacity
(6s)a (on3/cm3)b
Number of Soils Mean + 1 standard deviation Mean + 1 standard deviation
Sand
Loamy sand
Sandy loan
Loam
Silt loam
Sandy clay loam
Clay loam
Silty clay loam
Sandy clay
Silty clay
Clay
762
338
666
383
1,206
498
366
689
45
127
291
0
0
0
0
0
0
0
0
0
0
0
.437
.437
.453
.463
.501
.398
.464
.471
.430
.479
.475
0.347
0.368
0.351
0.375
0.420
0.332
0.409
0.418
0.370
0.425
0.427
- 0.
- 0.
- 0.
- 0.
- 0.
- 0.
- 0.
- 0.
- 0.
- 0.
- 0.
500
506
555
551
582
464
519
524
490
533
523
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
091
125
207
270
330
255
318
366
339
387
396
0.018
0.060
0.126
0.195
0.258
0.186
0.250
0.304
0.245
0.332
0.326
- 0.
- 0.
- 0.
- 0.
- 0.
- 0.
- 0.
- 0.
- 0.
- 0.
- 0.
164
190
288
345
402
324
386
428
433
442
466
aFrom total soil porosity measurements compiled by Rawls et al. (1982) from numerous sources.
''Water retained at -0.33 bar tension; values predicted based on compiled soil property
measurements.
Source: Rawls et al. 1982.
4-53
-------
OSWER Directive 9285.5-1
default values may be taken from Table 4-13. Wherever Equation 4-12
results in a value for e which is less than the specific retention of
the soil, it should be assumed that no downward movement of moisture (and
dissolved contaminants) occurred for the associated time increment, and
VpW was equal to zero.
Note also that the percolation rate (i.e., the term q) cannot exceed
the saturated hydraulic conductivity (Ks> for the site soil. Whenever
q _> Ks (and therefore e as calculated by equation 4-12 >_ es) for
the duration of the study period, it must be assumed that saturated
conditions exist and that saturated flow prevails. Equation 4-13 in the
following subsection provides a means of estimating saturated flow
velocities.
Assumptions implicit in equations 4-9 and 4-10 include the following:
Dispersion and capillary flow in all directions are negligible in
relation to the downward velocity of pore water and dissolved
contaminants due to gravity.
Contaminants present at the site dissolve into infiltrating water,
without significantly changing the viscosity of the water.
. Contaminants are conservative; degradation and soil adsorption
effects are negligible.
Soils underlying the site are homogeneous and isotropic;
macropores resulting in rapid flow do not exist at the site.
The effects of surface or pore water freezing are negligible.
The site is located in a region of net precipitation (i.e.,
HL + Pr > ET) for the majority of time increments considered
The introduction of water from manmade sources is intermittent and
in low-volume increments, rather than as high-volume spill
events. These equations are not applicable to situations
involving significant ponding of liquids at the site or the
establishment of saturated soil conditions.
A more detailed discussion of some of these assumptions and their
implications is provided below in section 4.3.3(2).
The mean-estimated velocity value, VpW, when multiplied by the time
period of concern during a Superfund investigation, provides a
conservative estimate of the depth to which contaminants from the site
4-54
-------
OSWER Directive 9285.5-1
have penetrated or will penetrate. This depth estimate should be
compared with data for the depth to the underlying aquifer. Where such a
comparison suggests that contaminants may have reached or will reach the
aquifer, the following saturated zone calculation procedures
(Subsection 4.3.3(l)(b), below) should be followed in order to estimate
contaminant plume dimensions within.the aquifer.
In cases where this procedure indicates the possibility of human
exposure to contaminants via ground water, estimates of contaminant
concentration in ground water at potential exposure points will be
required. Such estimates require as input the rate of contaminant flux
through the unsaturated zone and introduction to the aquifer. A rough
estimate of the likely upper bounds of contaminant flux to ground water
can be developed by multiplying the percolation rate, q, with the area of
soil surface contamination, resulting in a volume per unit time influx of
moisture. If the soil moisture content is assumed to remain constant,
this same volume per unit time represents the water flux from the
unsaturated zone to the aquifer. The upper bound for contaminant
concentration in this water flux is the solubility of the contaminants in
water (assuming no chelating compounds or dissolution agents are
present). Thus, contaminant flux to ground water roughly equals
contaminant solubility in water multiplied by the volumetric water flux
through the unsaturated zone.
Estimates developed by this method must be regarded as preliminary
and of low reliability. For an additional, more reliable method of
estimating contaminant flux through the unsaturated zone to ground water,
the analyst is referred to the estimation procedure presented by Donigian
et al. (1983).
b. Saturated Zone. In cases where contaminants are contained in a
lagoon or pond, soils below the site are saturated, the unsaturated zone
is insignificant or nonexistent, or when the results of the foregoing
unsaturated zone fate estimation procedures indicate that contaminants
have penetrated the unsaturated zone and reached the ground water, the
rate of contaminant migration in the saturated zone is estimated. It is
assumed for the purpose of the following estimation that the hazardous
contaminants are dissolved into the pond liquid or ground water and-
travel at the rate of ground-water flow, or as a saturated flow.
For many sites, the ground-water flow rate may have been determined
empirically during site investigations. Where measurement data are
unavailable, the rate of ground-water or saturated flow can be estimated
by Darcy's Law, as summarized by the following equation:
4-55
-------
OSWER Directive 9285.5-1
pw
(4-13)
where
V
pw
K?
N
e -
average linear pore water velocity of ground water and
contaminant (distance/time).
saturated hydraulic conductivity of the soil (distance/time)
hydraulic gradient (distance/distance).
effective porosity of the soil (%).
Again, each of the input parameters for Equation 4-13 may have been
evaluated empirically during site investigation. If this is not the
case, rough estimates for saturated hydraulic conductivity can be taken
from the mean values for this parameter presented in Table 4-11, or
median values of ranges shown i_n Table 4-12, based on the general soil or
rock type underlying the site. " The range values presented in these two
tables provide an indication of the uncertainty of using assumed values
rather than site data.
Preferably, the hydraulic gradient (the change in the elevation of
the water table over distance from the site) should also be taken from
field data developed during site investigation. Alternatively, values
for this parameter-may be available through several sources including
hydrogeological reports from the U.S. Geological Survey, state or local
agencies, or nearby university geology or hydrogeology departments.
Water levels in existing nearby wells can also provide an indication of
hydraulic gradient. Table 4-10 provides values for saturated moisture
content, (which is roughly equal to the effective porosity, or Ne) for
several soil types.
It must be emphasized that site-specific data are highly preferable
to regional data, or data obtained from any of the above referenced
tables. Use of estimated values can be expected to yield very rough
approximation of the velocity of contaminant movement through the
unsaturated and saturated zones, and the incorporation of a wide margin
for error is necessary in order to ensure the desired conservative
results.
Equations 4-9 and 4-13, in combination with the time elapsed since
release, provide a means of determining whether hazardous substances have
potentially reached the ground water underlying the site, and if so,
whether they have traveled with ground-water flow to predetermined
receptor sites. They also permit estimation of the likelihood of
hazardous substances reaching a receptor point within a time frame of
future remedial alternative planning. They incorporate many conservative
4-56
-------
OSWER Directive 9285.5-1
assumptions (enumerated in the discussion of ground-water fate mechanisms
in Section (2) below) regarding contaminant properties and migration, and
as such provide worst-case estimates.
The use of these procedures for predicting the effect of remedial
actions on ground water contamination is highly dependent on the
assessment of the situation before remedial action and the type of
remedial action under evaluation. Where preliminary determinations
indicate that contaminants have not reached the ground water, remedial
actions that eliminate or reduce percolation at the site can be expected
to arrest or greatly retard contaminant movement. The effect of this
type of remedial action may be estimated through modification of the
percolation term (q) in Equation 4-9. If it is determined, however, that
hazardous substances have reached ground water, the reduction of
percolation or leachate release to ground water will usually result in a
plug-type flow of the contaminant plume already in the ground water
before the remedial action began. This plug of contaminated water will
usually continue to migrate downgradient at the rate determined by
Equation 4-13.
If, through the application of these estimation procedures, it is
determined that the contaminant will reach receptor sites either as a
plume or plug flow, ground-water concentrations of hazardous substances
must be estimated at the affected receptor sites.
To provide useful estimates, quantitative procedures for ground-water
contaminant concentrations must account for several complex fate
mechanisms and therefore require lengthly calculations (see for example
the procedure presented by Wilson and Miller 1978) beyond the scope of
this manual. The analyst is referred to two documents for simplified
approaches to these estimation procedures. The first is the article by
Kelly (1982) which presents a code for the Texas Instruments model 58 or
59 programmable calculators. This code performs the calculations
required for the estimation procedure presented by Wilson and Miller
(1978) and greatly reduces the time required for ground-water
concentration estimation. The second document is that by Donigian et al.
(1983) which presents the same basic estimation procedure in nomographic
form, eliminating the need for lengthy calculations.
(2) In-depth Analysis. The assumptions that form the basis of
Equations 4-9 and 4-13, and the estimation procedures for ground-water
concentration presented by Donigian et al. (1983) and Kelly (1982) limit
the application and reliability of these methods. These assumptions are
detailed below. The analyst should especially be able to identify
situations where ground-water concentrations may be greater than those
predicted by the estimation procedures, or where estimation of
contaminant flow and ground-water concentrations indicate that the
concentration of hazardous substances in ground water may present a
hazard to human receptors.
4-57
-------
OSNER Directive 9285.5-1
The following is a discussion of the fate mechanisms that must be
considered during the planning of an in-depth analysis or the selection
of a ground-water fate model. The assumptions and limitations of the
foregoing estimation procedures with respect to these fate mechanisms are
also discussed.
(a) Dispersion. This process is brought about by velocity
variations in individual pore spaces and by diffusion of hazardous
substances over a concentration gradient. Dispersion causes the
"spreading" of a contaminant plume as it moves farther from a point of
release, and occurs in three dimensions unless a barrier prevents this'
process in one or more directions (see Aquitards, below). While
dispersion affects the rate of movement of a plume boundary, this effect
is disregarded by Equations 4-9 and 4-12. The estimates of
one-dimensional flow obtained by these equations is nevertheless valid
for the development of conservative or worst-case estimates of
contaminant migration. The estimation procedures presented by Kelly and
Donigian et al. do take into account dispersion in the estimation of
contaminant concentrations in ground water.
(b) Hydrogeologic Characteristics Affecting Fate. The following
hydrogeologic characteristics determine the rate and direction of
contaminant transport. The assumptions concerning these characteristics
incorporated into the foregoing estimation procedures are stated in each
case.
Permeability. The above estimation procedures assume isotropy and
homogeneity of the subsurface medium through which the leachate or
ground water travels. Isotrophy refers to a uniform hydraulic
conductivity irrespective of the direction of water movement
(e.g., horizontal conductivity is equal to vertical
conductivity). Homogeneity refers to uniform hydraulic
conductivity characteristics at all points within the soil (i.e.,
no impermeable layers or strata with different conductivity
characteristics). In actuality, this is rarely the case; most
soils are heterogeneous and anisotrophic (Kufs et al. 1983).
Permeability of a soil can vary widely from one area to another or
with depth. Often, soil grain size fluctuates gradually with
depth or unpredictably in multilayered media (Kufs et al. 1983).
If such variation exists and can be reliably quantified, average
permeability values can be used as input to provide estimates of
ground-water fate. Computer models with routines accounting for
various levels of permeability can be used for more accurate
predictions.
Aquitards. Aquitards are zones of relative impermeability, which
act as barriers to movement of ground water. Aquitards can be
above, on either side of, or below an aquifer, confining its shape
and therefore the movement of contaminants. The estimation
4-58
-------
OSWER Directive 9285.5-1
procedures provided above assume that contaminants move vertically
through the unsaturated soil zone and horizontally in the ground
water. As such, these procedures do not account for directional
flow diversions caused by aquitards, and the effects of such
diversions are often difficult to model even with computer-based
procedures. The foregoing estimation procedures do assume, .
however, that there is an aquitard below the aquifer, which limits
mixing and transport downward (Donigian et al. 1983, Wilson and
Miller 1978). Absence of such an aquitard, resulting in unlimited
dispersion downward, therefore, renders these procedures
unreliable, as they may overestimate ground-water concentrations
of hazardous substances at shallow wells, and underestimate those
at deep withdrawal points. A more sophisticated model accounting
for this feature should be used in such situations.
Fissures in an aquitard further complicate prediction of plume
migration, unless these leaky aquitards can be described reliably
(Kufs et al. 1983). When such features are known to exist, but
cannot be accurately described or quantified, only the monitoring
of ground water can provide accurate information regarding
hazardous material concentrations at exposure points.
Solution cavities, fractures. The rock material that underlies,
confines, or is itself a medium of ground-water flow in many cases
contains irregular fractures, or cavities, formed by dissolution
of the rock material by water. Ground-water flow rate through
these fissures can be extremely rapid compared to that in
surrounding material (Kufs et al. 1983). Because of irregularity
in size, shape, and direction of fissures, attempts to model
ground-water flow in areas exhibiting these features are
unreliable. Contaminated liquids can flow through fractures and
cavities largely unimpeded and undiluted by retardation or
dispersion processes. When these conditions exist, the only
reliable method of determining concentrations at wells or springs
is monitoring. Predictions-as to whether a particular point in
the aquifer may be affected by plume migration can often only be
made through tracer studies.
Hydrologic fluctuations. Percolation and hydrologic head
gradients, and therefore ground-water flow rates and directions,
can fluctuate significantly with seasonal or long-term fluctuation
in precipitation, snow melt, evapotranspiration, surface runoff,
and flooding (Kufs et al. 1983). The estimation procedures
provided assume a constant or average flow rate, and a consistent
= or average direction of flow. For conservative estimates of
ground-water contaminant concentrations whenever wide hydrologic
fluctuation occurs, use low flow rates as inputs to the
ground-water concentration estimation procedures of Donigian et
al. (1983) or Kelly (1982).
4-59
-------
OSWER Directive 9285.5-1
c. Transfer and Transformation Processes. The following are the
most significant processes that remove hazardous substances from ground
water through transfer to other media, or through degradation of the
substance. The Darcy's Law estimation procedure disregards these
processes, and thereby provides worst-case estimates of ground-water
contaminant migration. If such worst-case estimates indicate potential
human hazard and estimation of contaminant concentration in ground water
is required, the concentration estimation procedures of Kelly (1982) and
Donigian et al. (1983) do allow the incorporation of an overall decay
coefficient.
The coefficient represents the combined removal action of all of the
processes that are active at a site and for the contaminant in question.
It is developed through summation of the individual decay rates of each
process. Appropriate individual decay rates or overall decay
coefficients have been developed for numerous substances, and are
available in the technical literature. Sources for such data'include:
Callahan et al. (1979); Dawson, English, and Petty (1980); Mabey et al.
(1982); Sax (1979); U.S.C.G. (1974); and Verschueren (1984). Methods of
estimating decay coefficients are presented by Lyman et al. (1982).
Volatilization. This mechanism can be important if the hazardous
substance in question has a high vapor pressure or is insoluble
and less dense-than water. If the aquifer.has a large surface
area near the soil surface, or if the unsaturated soil layer is
especial '"y porous or thin, volatilization rates can also be
enhanced. Transport rates of the hazardous substance in the
gaseous phase through the unsaturated soil zone and through the
air away from the soil-air interface are important determinants of
the rate of volatilization.
Hydrolysis. This is a pH-dependent process for most substances.
Hydrolysis rates are chemical specific and dependent on the
presence of available hydroxyl or hydronium ions in the
ground-water medium.
Biodegradation. Enzymatic action of biota present in the
unsaturated soil and ground water results in the biodegradation of
some hazardous substances. Biodegradation is a function of the
population and metabolic characteristics and rates of the biotic
agents in question.
(d) Retardation. The rate of movement of hazardous substances
through the aquifer is usually not the same as that of the gr.ound water
itself, because of the action of the following mechanisms of
retardation. These mechanisms are not accounted for by Equation 4-9 or
4-60
-------
OSWER Directive 9285.5-1
the Darcy's Law equation. The procedures presented by Oonigian et al.
(1983) and Kelly (1982) account for sorption, but not for the effects of
viscosity, filtration or entrapment. Results of these estimation
procedures, then, are rendered less reliable in situations where these
latter three retardation factors exist, and may predict ground-water
concentrations significantly lower than actual levels. Use in-depth
analysis techniques or models that incorporate these factors whenever
they may be important.
Filtration. Hazardous substances in suspended particulate form,
or that are converted to suspended solid form from solution as the
result of precipitation or flocculation, can be filtered out of
the ground-water medium. The rate of filtration depends on the
relationship between average soil pore size and average size of
the suspended particulate hazardous substance. Because
precipitation and flocculation are reversible processes that are
dependent on the concentration of the hazardous substance in
ground water, filtration tends to slow but not arrest movement of
most hazardous substances within this medium.
Sorption. This term encompasses several processes by which
substances in ground water or the unsaturated soil zone are
attached to soil particles. Sorption rates are a function of the
ionic exchange capacity, the organic carbon content of the soil,
and properties of the hazardous substance. Soil/water partition
coefficients have been developed for many contaminants of
importance (see Callahan et al. 1979, and Mabey et al. 1982), and
estimation procedures are provided by Delos et al. (1984),
Donigian et al. (1983), and Lyman et al. (1982). Sorption is also
a reversible process and tends, therefore, to retard rather than
/stop hazardous substance migration within ground water.
Entrapment. Because of minor eddies in ground water, portions of
hazardous substances dissolved or suspended can disperse into and
become temporarily trapped in dead-end pores or fractures in the
medium. This process occurs at a rate that is a function of the
porosity and interconnectedness of pore spaces in the soil medium.
Viscosity. High concentrations of hazardous substances dissolved
in ground water can significantly raise the viscosity of the
solution. Hazardous substances released into the medium in liquid
form are often significantly more viscous than water. The
effective permeability of soil decreases with increasing viscosity
of the solution passing through it, and viscous solutions are
therefore transported through the subsurface soil medium at a
slower rate than that predicted for water or dilute solutions of
4-61
-------
OSWER Directive 9285.5-1
contaminant. This results in more gradual downward movement of
the contaminant through the unsaturated zone, plume boundaries
closer to the site than predicted by Equations 4-9 and 4-13, and
higher concentrations within the plume than predicted by the
method presented by Donigian et al.
e. Immiscible contaminants and multi-phase flow. All of the
foregoing estimation procedures incorporate the assumption that the
contaminants under study dissolve almost entirely in ground water, and
that their movement can be approximated through minor modification of or
direct comparison to ground-water flow. However, the contaminant
compounds likely to be encountered at Superfund sites vary widely in
solubility; many are immiscible with water. These compounds, upon
release to soils or ground water, tend to migrate as discrete non-aqueous
phases (Mackay et al. 1985). Such immiscible compounds that are denser
than water are most likely to concentrate at the bottom of an aquifer,
just above the underlying aquitard, while compounds less dense than water
are most likely to "float" at the uppper surface of the zone of
saturation. Non-aqueous phases commonly have distinct migration
properties and may flow at different velocities and in different
directions than water in both the unsaturated and saturated zones.
Velocities of immiscible contaminants through the unsaturated or
saturated zones can- be several times that of water.
(3) In-Depth Methods and Models. Several references are available
that provide detailed derivations and outline the application of more
sophisticated equations for the analysis of contaminant migration in the
saturated and unsaturated zones. The analyst is referred to the
following documents for these useful compilations of in-depth methods:
USEPA 1985d; Van Geunchten and Alves 1982, Walton 1984, and Javendel et'
al. 1984.
Tables 4-14, 4-15, and 4-16 provide information regarding several
modeling procedures for the in-depth -assessment of the ground-water fate
of hazardous substances. Two of the models in Tables 4-14, 4-15, and
4-16 are part of GEMS: SESOIL and AT123D. The latter is described in
greater detail below because it is more versatile and is applicable to a
wide range of fate analysis situations.
AT123D (Analytical Transient 1-. 2-. or 3-D1mensiona1 Simulation
Model) is capable of simulating the transport and fate of hazardous
material under 300 different user-selected situations (Yeh 1981). The
model handles two types of waste pertinent to uncontrolled hazardous
waste sites, radioactive and chemical. One of eight source
configurations can be selected: a point source; line sources aligned in
one of three different ways with respect to ground-water flow; area
4-62
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OSWER Directive 9285.5-1
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OSWER Directive 9285.5-1
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4-68
-------
OSWER Directive 9285.5-1
sources, also aligned in one of three different configurations; or a
volume source (existing plume). Release types can be instantaneous,
longer term but finite, or constant. Aquitard locations can be specified
below or on both sides of the aquifer in any configuration, or the
aquifer can be treated as infinite in all directions. Advection and
dispersion transports are simulated. Losses due to volatilization,
degradation, and adsorption are modeled. The model predicts contaminant
movement in one, two, or three dimensions (Yeh 1981).
Use of AT123D requires the following information: dispersion
coefficients in horizontal, vertical, and longitudinal direction;
geometry of the aquifer, especially regarding configuration of aquitards;
soil properties, including bulk density, effective porosity, hydraulic
conductivity (permeability); source type; and release duration and
strength, soil-waste stream partition coefficient, hydraulic gradients,
and an overall decay constant (or soil half-life figures) for the
substance studied (Yeh 1981).
The model determines contaminant concentration at any point, at a
downstream and lateral distance and depth specified by the user, as a
function of time from the beginning of source release.
AT123D can be accessed through the GEMS system (see Section 4.1
above). It is written in FORTRAN and can be installed on a wide range of
computer types.
(3) Short- and Long-term Concentration Calculations. Long-term
average ground-water concentrations of contaminants at receptor points
are a function of the concentration profile over the time period of
study, which are in turn a function of hydrologic fluctuations, release
rate fluctuations, and the effectiveness of remedial actions. Average
concentration values are obtained from the methods of Kel'ly or Donigian
et al. through input of time-weighted average values for the above
parameters. Several of the in-depth analysis models tabulated in Section
4.5.2 accept time-weighted input data, and provide long-term average
concentrations as well as the concentration profile as a function of
time.
Short-term concentrations at receptor points are obtained by
examination of the ground-water concentration profile at the selected
exposure point over time, and identification of the period of maximum
concentration.
4-69
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OSWER Directive 9285.5-1
4.3.4 Biotic Pathways
(1) Estimation Procedures. An assessment of the fate of hazardous
material in biotic populations is conducted after the fate of this
material in the air, water, and ground water has been estimated. Using
the ambient concentration data developed for each of these media, a
determination is made whether any biotic populations that can potentially
serve as pathways for human exposure to hazardous materials (i.e., vector
organisms) are within zones of elevated hazardous material
concentrations. Such vector populations may include agricultural crops;
agricultural livestock; fish, shellfish, or crustaceans that are
important commercial or sport species; and game populations in hunting
areas.
In assessing the biological fate of hazardous, materials, the
following processes, which determine the rate of introduction of
hazardous material to and the final concentration of hazardous material
within vector organisms, should be considered:
The concentration of hazardous material in environmental media
containing or supporting vector organisms.
The metabolic rate of the vector organisms. Metabolic rates are
functions of several environmental parameters including
temperature and the availability of sunlight, oxygen, nutrients,
and water or other factors.
Substance bioavailabi1ity; the affinity of each hazardous
substance for partitioning into the organic phase or its
availability for other forms of uptake. The bioavailability of
each substance differs as does that of various chemical species of
an individual substance; the octanol/water partition coefficient
is an indication of this parameter. Bioavailabi1ity of a given
substance can vary with environmental conditions. Factors that
influence the physicochemical speciation of substances, and thus
their bioavailabi1ity include salinity, pH, Eh, organic carbon
concentration and temperature.
Characteristics of species metabolic processes. These
characteristics differ among species and include feeding habits
and ability'to metabolically degrade, store, and eliminate the
substance. Bioconcentration factors (or BCFs, the ratios of
organism tissue concentration to ambient environmental
concentration) for many species and hazardous substances have been
empirically determined and are discussed below.
Consider the following transport mechanisms in assessing the
distribution of hazardous substances within the biologic medium and
identifying the potential points of human exposure:
4-70
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OSWER Directive 9285.5-1
Transport and distribution of vector organisms as a result of
human commercial or sport activity.
Migration of organisms, or movement of these organisms with
advective flow of environmental substrate media.
Movement of contaminants through the food chain. This mechanism
often results in very high concentrations of hazardous materials
in the tissue of higher trophic level organisms within and without
contaminated areas.
General theoretical relationships between the above factors and
concentrations of hazardous substances at human exposure points are not
available. This is because such relationships are highly specific to
individual ecologies, biotic species, hazardous substances, and human
activities associated with involved biotic species.
For this reason, the assessment of biotic concentrations of hazardous
substances at human exposure points is limited to the qualitative
identification of major pathways, and the rough quantification of
exposure levels wherever some means of relating ambient soil, water, or
air concentrations to edible tissue concentrations are available.
The available methods of estimating tissue concentrations in aquatic
animals, terrestrial animals, and terrestrial plants are:
(1) Aquatic animals. Because aquatic animals are immersed in the
contaminated water medium to which they are exposed, it is commonly
assumed that tissue contaminant concentrations are a function of
contaminant equilibrium partitioning between water and organic tissue,
and are therefore directly related to contaminant ambient water
concentration. This assumption closely represents the behavior of many
water-borne contaminants, although recent studies suggest that for many
hazardous substance tissue concentration is not very strongly related to
water column concentration. The bioconcentration factor (BCF) represents
the ratio of aquatic animal tissue concentration to water concentration.
This ratio is highly contaminant-specific and is also dependent on the
aquatic species and on site parameters.
The most reliable source of aquatic animal BCF values is monitoring
data about the site. Wherever water concentrations and biotic tissue
concentrations have been surveyed simultaneously, a site-specific BCF can
be calculated for the species and substance involved (assuming water
column concentration values represent relatively steady concentrations
over at least the previous several weeks, and not short-term high or low
concentrations). This BCF can be used to project changes in tissue
concentrations resulting from projected changes in ambient water
concentrations of the involved hazardous substance.
4-71
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OSWER Directive 9285.5-1
In cases where site monitoring data are insufficient for development
of a BCF, BCF values reported in technical literature can be used. A
substantial amount of research is available regarding the
bioconcentration of hazardous substances, especially in aquatic organisms
(see USEPA Office of Water Regulations and Standards: Ambient Water
Quality Criteria documents, for a review of research current to 1980, or
Verschueren 1984, Dawson, English, and Petty 1980, Mabey at al. 1982,
Callahan et al. 1979, for BCF factors). Exercise care to match
contaminants, species, and site conditions (e.g., temperature, pH, water
salinity) for which reported BCF values were measured with conditions at
the site. BCF values for different species or contaminants or those
measured under dissimilar conditions may not be applicable.
A third alternative for derivation of BCF values is to calculate
these values based on the structure or physiochemical properties of the
hazardous substance. See Lyman et al. (1982), Kenaga and Goring (1980),
Veith et al. (1980) for instructions for BCF estimation procedures.
(2) Terrestrial animals. Very few data are available allowing the
quantification of contaminant concentrations in edible terrestrial animal
tissue based on ambient environmental concentrations. Kenaga (1980)
compiled and studied data comparing dietary concentrations of several
organic compounds with the concentration of these compounds in the fat of
beef cattle and found that the fat/diet BCF for these compounds correlate
reasonably well with the water solubility (negative correlation) and
octanol-water partition coefficient (positive correlation) of these
compounds. BCFs could only be predicted within 3- to 4-orders of
magnitude, however. Hence, this method of tissue concentration
estimation must be considered semiquantltative at best.
Human exposure to contaminants via the terrestrial animal pathway can
only be reliably determined through identification of potential vector
organisms and exposure points, and through a sampling and analysis
program for determining tissue concentrations at these exposure points.
(3) Terrestrial plants. Plant adsorption of environmental
contaminants has been studied by various researchers, and some data are
available regarding the uptake of pesticides and other contaminants by
edible crops. These data cover specific crop uptake of specific
contaminants (see CDHS 1985 for a review of pesticide research), however,
and no relationships allowing reliable extrapolation of soil/plant tissue
concentration ratios are presently available. Where plant/soil BCF data
are available in the technical literature for the specific plant species,
contaminant, soil type, and tissue type of concern in a Superfund
exposure assessment, these BCF data can be used for a semi-quantitative
estimation of edible tissue concentrations.
4-72
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OSWER Directive 9285.5-1
As is the case with terrestrial animals, the most reliable technique
for assessing contaminant concentrations at points of human exposure to
plant tissue is the identification of potential vector organisms and
exposure points, and the surveying of tissue contaminant concentration in
these organisms.
4-73
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OSWER Directive 9285.5-1
5.0 QUANTITATIVE ANALYSIS OF EXPOSED POPULATIONS
5.1 Introduction
The results of contaminant release and fate analyses provide the
basis for assessing exposed populations. In this assessment,
environmental contamination data are compared with populations data to
determine the likelihood of human contact with contaminants of concern.
As with other evaluations, exposed populations analysis begins with a
screening assessment which identifies exposure pathways that are
incomplete, i.e., those situations where contaminants are released and
migrate from a site, but do not contact human populations. Such
situations require no further analysis. At the same time, exposed
populations screening also points out those exposure pathways that are
complete and that will require quantitative analysis to estimate the
extent of human exposure.
Data needed to quantify potentially exposed populations are readily
available. In essence, all quantitative exposed populations evaluations
can be considered in-depth analyses. For each population segment
identified in this portion of the exposure assessment process, exposures
are quantified and integrated as described in Chapter 6.
5.2 Exposed Populations Screening
Consistent with the preceding analyses, exposed populations screening
is primarily qualitative. This evaluation draws on the results of
contaminant fate analysis (presented in Chapter 4) to determine the
liklihood and extent of human population contact with contaminants.
Exposed populations screening is guided by the decision network
provided in Figure 5-1. The following numbered paragraphs are provided
to facilitate interpretation and application of the exposed populations
decision network presented as Figure 5-1. Each paragraph refers to a
particular numbered box in the figure.
1. Human exposure via inhalation should be evaluated for contaminants
that have migrated or may, in the future, migrate from the site into air
(either directly or indirectly via intermediate transfer). The
assessment should consider contaminated dust as well as volatile
compounds. For screening purposes, comparison of contaminant
concentration isopleths with maps of the local area will identify the
potential for such human population inhalation exposure. However, the
user should realize that such exposure can occur in recreational areas as
well as in residential, commercial, or industrial areas and therefore
should interpret local area maps accordingly.
5-1
-------
OSWER Directive 9285.5-1
JI
1 = 3
111
135
5-2
-------
OSWER Directive 9285.5-1
2. In cases where surface water bodies have been contaminated by toxics
migrating from a site, the water's potential commercial use as a fish or
shellfish source should be evaluated. If the subject waters are
commercially fished, the potential for worker exposure, via dermal
contact with contaminated water, can also be considered, although such
exposure will generally be overshadowed by other exposure mechanisms.
3. In cases where recreationally or commercially caught fish/shellfish
are taken from contaminated waters, significant exposure to persons
consuming the catch may result. For chemicals that tend to
bioaccumulate, consumers may be exposed to contaminant concentrations in
fish/shellfish tissue that are many times greater than those present in
the water column. In exposed population screening, the analyst need only
determine whether waters identified in the environmental fate analysis as
receiving contaminants from the hazardous waste site are used
commercially or recreationally.
4. Persons who swim in contaminated waters can experience dermal
exposure to toxics over their entire body. Therefore, the existing or
potential degree to which the local population uses contaminated water
bodies (fresh or marine) for swimming should be evaluated during
screeni ng.
5. If contaminated ground or surface waters are used as sources of
potable water, the population served may experience considerable drinking
water-related ingestion exposure. Similarly, the population may also be
exposed to toxics via both dermal absorption and inhalation (for
volatiles only) while showering or bathing. For screening analysis, it
is only necessary to determine which residences or commercial/
institutional establishments are likely to obtain their potable water
from contaminated water sources.
6. If contaminants migrate to off-site soils, persons contacting such
soil may be exposed. Persons who grow their own fruit or vegetables at
home may experience additional exposure from ingestion of fcod grown in
contaminated soils. Again, screening analysis should strive to correlate
areas of human habitation with areas of contaminated soil as defined in
the environmental fate analysis.
7. Similarly, if direct access to the site is possible, children may be
attracted to the location and may come in contact with any remaining
debris. Such activity may result in inhalation or dermal exposure. For
screening purposes, the proximity of residential areas to the site should
indicate the potential for direct access by children.
5-3
-------
OSWER Directive 9285.5-1
5.3 Quantitative Exposed Populations Analysis
Quantitative analyses of potentially exposed human populations
comprises three distinct steps, which are illustrated in Figure 5-2.
First, the results of environmental analysis are compared with data
identifying and enumerating nearby human populations to bound and
quantify the pop-ulation(s) potentially or actually coming into contact
with contaminated air, water, and soil. Populations consuming
contaminated food (home grown vegetables, fish) can similarly be
identified once the areal extent of contamination is known.
Population characterization, the second step, involves determining
those groups within the exposed population that, because of the specific
health effects of some pollutants, would experience a higher risk than
the average population as a result of a given level of exposure. Indeed,
the health effects of the contaminants under evaluation will often
dictate the need for population characterization. High risk groups could
include women of childbearing age, the chronically 111, infants/children,
and the elderly. While most Superfund studies will -consider only the
exposed population as a whole and not disaggregate discrete
subpopulations, in certain cases such detailed population analysis may be
warranted for in-depth studies. For example, if a chemical substance is
determined to be teratogenic, enumeration of women of- childbearing age
may be required.
Age and sex influence the average ventilation rate, the rate of food
and water intake, the body area subject to dermal exposure, and the types
of food consumed, all of which can affect the level of exposure actually
experienced. Some quantitative assessments may require the
characterization of populations-and use of age- and sex-specific exposure
factors.
The third step is activity analysis. Once population identification
and characterization have answered the question "Who may be exposed?",
activity analysis further refines the evaluation by addressing the
.question "How and to what level are component portions of this population
exposed?". This involves determining the exposed population's mix of
activities. Comprehensive, highly detailed analysis can encompass the
range of indoor, outdoor, and in-car subject population activities.
However, for Superfund Feasibility Studies, average value's for
activity-related considerations usually suffice.
5.4 Identification and Enumeration of Exposed Human Populations
The major population data base that can be accessed to determine the
size, distribution, and demographic characteristics of a
geographically-defined population is the Census of Population.
5-4
-------
OSWER Directive 9285.5-1
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OSWER Directive 9285.5-1
The data collected in the Census are organized according to
geographic areas, and within these, according to Census-defined
statistical areas and government units. Population data, therefore, are
available within Standard Metropolitan Statistical Areas (SMSAs) down to
the level of the "block" and in non-SMSAs to the level of the Enumeration
District (ED).
These data are especially useful in quantifying and characterizing
populations exposed as a result of their presence in a specific locale
(e.g., those exposed to toxics in ambient air or soil). An isopleth map
of varying concentrations around a source can be overlaid with Census
maps. Such maps are available for areas within Standard Metropolitan
Statistical Areas (SMSAs) and can be purchased from the Bureau of the
Census. Also, Census Tracts (Series PHC80-2) contains detailed
characteristics of the population (e.g., age, sex, race, education)
within each tract, a division of an SMSA containing 4,000 residents
each. Census Tracts is currently available on microfiche by SMSA and on
computer tape.
Many Superfund sites are not within SMSAs. Census data for non-SMSA
areas are not available on maps but can be transcribed from Census
publications.
The most useful Census publications for this type of data are Number
of Inhabitants (Series PC80-1-A) and General Population Characteristics
(Series PC80-1-B). Each series is currently available and consists of a
separate volume for each state, together with a national summary volume.
Number of Inhabitants provides only population counts, with no
demographic data. It provides data down to the level of county
subdivision and incorporated town. 'General Population Characteristics
provides population counts by age, sex, and other demographic data and
contains data down to the level of small towns (1,000 or more
inhabitants).
All printed Census Information is available for purchase through the
Government Printing Office (GPO); all series issued on microfiche, maps,
computer tapes, and technical documentation are available directly from
the Ci/stomer Services Branch at the Bureau of the Census, Department of
Commerce, Washington, D.C., and can be ordered by calling (202) 763-4100.
Alternatively, 1t may be more convenient to contact one of the Census
Bureau regional offices. Cities where such offices are located and phone
numbers for the public information service within each regional office
are listed in Table 5-1.
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OSWER Directive 9285.5-1
Table 5-1. Regional Census Bureau Offices
Atlanta, GA
Boston, HA
Charlotte, NC
Chicago, IL
Dallas, TX
Denver, CO
Detroit, HI
Kansas City, KS
Los Angeles, CA
New York, NY
Philadelphia, PA
Seattle, MA
404/881-2274
617/223-0226
704/371-6144
312/353-0980
214/767-0625
303/234-5825
313/226-4675
913/236-3731
213/209-6612
212/264-4730
215/597-8313
206/442-7080
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OSWER Directive 9285.5-1
5.4.1 Populations Exposed via Air
An especially convenient means of accessing quantitative population
data for a specific area impacted by air contaminants is to directly link
environmental fate and exposed populations analysis via use of an
integrated computer-based fate model and population data retrieval
program called ATM-SECPOP. Developed by the EPA Office of Toxic
Substances, Exposure Evaluation Division (OTS-EED), this model primarily
analyzes point source emissions, but can also be adapted to area or line
source analyses. ATM-SECPOP integrates the output of a concentration
prediction model (ATM) (Patterson et al. 1982); a population distribution
data base (the proprietary 1980 Census Master Area Reference File (MARF))
which is accessed via a population distribution model called SECPOP; and
graphic and mapping information displays. The integration affords a
rapid and efficient means of generating and presenting exposure data
relating to the airborne release of chemical substances. The graphic
display functions can be used to illustrate the relationship of variables
such as the distribution of exposure or concentration versus distance for
any or all directions around a facility. Graphic displays may be in the
form of bar charts, scatter plots, rose diagrams, or maps. Because of
the proprietary nature of the data contained in MARF, ATM-SECPOP's use is
restricted to personnel and contractors of EPA-OTS. Special arrangements
can be made for others to use the data. Inquiries should be directed to
the Chemical Fate Branch Modeling Team of EPA-OTS in Washington, D.C. A
detailed discussion of ATM is presented in Chapter 4 of this manual.
Where sites are accessible, the potential for children entering and
exploring or playing on the site should be evaluated. On-site, children
may experience inhalation exposure to contaminated dust, volatiles, or
both. Accurate estimation of the potentially exposed population in such
a case is difficult; it can be assumed that each household with children
in the immediate vicinity of the site has one child who may find the site
inviting. This should provide an upper bound estimate on the actual
number of children who may enter the site. The Bureau of the Census
(1985) reports that in 1983, 50.2 percent of all U.S. households included
children. This percentage can be applied to the total number of local
households to enumerate those in the area with children. The analyst
must decide which households are close enough to the site to be
Considered.
Similarly, workers conducting activities at the site may also
experience inhalation exposure. Local authorities (Zoning Board, etc.)
may be able to supply information on the liklihood of on-site
work-related activities that can be used to estimate the number of
workers who may become exposed. Remediation workers are not included in
this estimated exposed population.
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OSWER Directive 9285.5-1
5.4.2 Populations Exposed via Surface Water or Ground Water
Geographically-defined sources of aquatic, recreational dermal
exposure, such as river reaches downstream of an uncontrolled hazardous
waste site, can be identified through an examination of Environmental
Fate Analysis results. The exposed population comprises swimmers in
those specific contaminated waters. The local government agency
concerned with recreation should be able to provide estimates of the
populations swimming in local waters; this will usually be the state,
city, or county Department of Parks or Recreation. Alternatively, the
following national average value from the Bureau of Outdoor Recreation
(USDOI 1973) can be used: 34 percent of the total population swims
outdoors in natural surface water bodies (including oceans, lakes,
creeks, and rivers).
All persons in the service area of a water supply system that draws
water from a contaminated water source must be considered as potentially
exposed through ingestion and dermal exposure while bathing. Information
concerning local surface drinking water Sources and populations served
can be obtained from the local Department of Public Works, Planning
Department, or Health Department. Information on public departments or
private drinking water treatment companies that use ground water as their
raw water supply, and also the number of households drawing water from
private wells, will generally be available from these sources.
5.4.3 Populations Exposed via Food
Exposure to contaminated food will usually be associated with fruit
and vegetables grown in home gardens, or with game residing in or
utilizing contaminated areas. In order to identify the number of persons
consuming contaminated home grown fruit and vegetables, first consult
General Population Characteristics, Series PC80-1-B, to identify the
total number of households 1n a given geographic area. Then the data
presented in Table 5-2, which,provides estimates of the percent of
households in urban and rural areas that have fruit and vegetable gardens
and the average number of persons per household, can be applied to the
local population data to estimate the number of persons likely to consume
contaminated home grown produce.
The USDA Food Consumption of Households report series can be
consulted to estimate the local population using a given food item for
urban, rural non-farm, and rural farm locales. These reports present
seasonal food use survey data on the following bases: Northeast (USDA
1983a), North Central (USDA 1983b), South (USDA 1983O, and West (USDA
1983d). More aggregated data are also provided for the entire United
States in a companion report (USDA 1983e). The percent of households
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OSWER Directive 9285.5-1
Table 5-2. U.S. Home Fruit and Vegetable
Garden Use, 1977 (USEPA 1980b)
Percent of
Households
Urbanization with Gardens
Household
Size
(No. of Persons)
Percent of
Total U.S.
Population
Urban 43
Rural non-farm 41
Rural farm 84
3.17
3.44
3.86
32
9
3
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OSWER Directive 9285.5-1
using a given food item can be obtained from these reports. The product
of this value and the total resident population of an area is an estimate
of the local exposed population. Similar national level data are also
provided on the basis of age and sex in Food and Nutrient Intakes of
Individuals in 1 Day in the United States (USDA 1980). In addition, the
U.S. Food and Drug Administration (FDA) can be contacted for data
concerning daily intakes of various food items. Such data have been
compiled for the FDA Total Diet Study (Pennington 1983).
Monitoring data may indicate whether fish and game are contaminated
in the subject area. One can estimate the fishing population by
contacting the local agency responsible for issuing fishing licenses;
this may be the state fish and game commission or the state department of
natural resources. Since there are 2.71 persons in the average household
(Bureau of the Census 1985), one can estimate the actual exposed
population by multiplying 2.71 by the number of licensed hunters or
fishermen in the area.
5.4.4 Populations Exposed via Soil
Exposure to contaminated soil constitutes a potential exposure route
for Workers or children playing outdoors. Neighborhood children playing
at the site can be exposed to high lev-els of contaminants. Soil-related
exposure in such cases would be via direct dermal contact with the
contaminated soil. Another potentially significant, but infrequently
encountered, exposure mechanism involves children who eat dirt; this
eating behavior, known as pica, may lead to their actually ingesting
contaminated soil. For any site located in the vicinity of residential
areas,, the degree of access to children should be considered. Bureau of
the Census data can be used as described in Section 5.4.1 to estimate the
number of local children who may access the site.
In addition, workers conducting activities at the site (other than
remediation) may have direct dermal contact with contaminated soils.
Section 5.4.1 also provides general guidance for the identification and
enumeration of exposed worker populations.
5.5 Population Characterization
After exposed populations have been identified and enumerated, they
can be characterized by age and sex factors. The physiological
parameters' that determine dose received per a given level of exposure
(e.g., breathing rate, skin surface area, and ingestion rate) are often
age- or sex-specific. Also, from a toxicity standpoint, subpopulations
defined by age or sex, such as the elderly or women of childbearing age,
may be especially susceptible to a chemical substance. Average values
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OSWER Directive 9285.5-1
will generally be used for Superfund studies, but characterization of
exposed populations also permits the determination of exposure
distributions within the population at large and the delineation of
specific high risk subpopulations.
The Census Publication series General Population Characteristics
(PC80-1-B) provides figures for the age and sex structure of the
population residing in a specific area. Separate volumes for each state
contain age and sex breakdowns at the level of county subdivisions and
small towns. If more detail is required, the Census Bureau provides a
series of microfiche containing this information at the Census tract
level (only available by SMSAs).
In the case of exposure via ingestion of food, the food consumption
surveys of the USDA (1983a-e) record age and sex data for the sampled
population. These data are contained in five separate regional reports;
the appropriate one should be consulted.
In lieu of obtaining site-specific data, one can use the population
characteristics of the U.S. as a whole, provided in the yearly
Statistical Abstract of the United States (for example, see Bureau of the
Census 1985), to approximate the population distribution in the area of
concern.
5.6 Activity Analysis
Activities engaged in by members of a given population or
subpopulation can dramatically affect the level of human exposure to
environmental contaminants. For example, persons whose lifestyle or
employment involves frequent strenuous activity will inhale larger
volumes of air per unit time than will those living a less strenuous
life, and will, therefore, experience a higher level of exposure to
airborne contaminants.
Activity analysis allows refinement of certain parameters used in the
calculation of exposure:
Inhalation rate
Frequency of exposure
Duration of exposure
The procedure for integrating activity-related inhalation, frequency, and
duration data into the exposure assessment process is detailed in the
following chapter.
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OSWER Directive 9285.5-1
6.0 EXPOSURE CALCULATION AND INTEGRATION
Integrated exposure analysis is conducted for only those contaminants
determined to have complete exposure pathways, that is, those
contaminants that are released and migrate from the site and that do
contact receptor human populations. Therefore, no screening evaluation
is included in the exposure integration process. Calculation of exposure
incurred is traditionally the final step in the quantitative exposure
assessment process. However, it can also be viewed as a component of
public health evaluation. Therefore, the material detailed in this
chapter is also discussed in the Superfund Public Health Evaluation
Manual (USEPA 1985d).
Exposure is defined as the amount of pollutant contacting body
boundaries (skin, lungs, or gastrointestinal tract). Exposure
calculation considers how often receptors come into contact with
contaminants in specific environmental media, the mode of such contact,
and the amount of contaminated medium that contacts internal or external
body surface during each exposure event. The goal of this analysis is 'to
quantify the amount of contaminant contacted within a given time interval.
Short-term and Vbng-term exposures are calculated in the same
manner. First, for each exposure scenario under consideration, an
exposure per event is developed. This exposure value quantifies the
amount of contaminant contacted during each exposure event, with "event"
being defined differently depending on the nature of the scenario under
consideration (e.g., each day spent swimming in a contaminated river is a
single swimming exposure event, each day's inhalation of contaminated air
constitutes an inhalation exposure event). Event-based exposure
estimates take into account the concentration of contaminant in the
medium via which exposure occurs, the rate of contact with such media
(inhalation rate, ingestion rate, etc.), and the duration of each event.
The assessor can convert event-based exposure values to-final
exposure values by multiplying the exposure per event by the frequency of
exposure events over the time frame being considered. Short-term
exposure is based on the number of exposure events that occur during the
short-term time frame (10 to 90 days), while long-term exposures are
based on the number of events that occur within an assumed 70-year
lifetime.
Exposure estimates are expressed in terms of mass of contaminant/unit
of body mass/day by dividing daily exposure by the value for total body
mass of an average individual in the receptor population. For Superfund
studies, an average adult body mass of 70 kg will usually be adequate for
this conversion. However, in cases where exposure to specified
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OSWER Directive 9285.5-1
I
subpopulations must be evaluated, values for other than average adults
may be required. Consult Anderson et al. (1984) to obtain alternate body
mass values. Similarly, average values for activity-related parameters
(e.g., inhalation rate) generally will suffice for Superfund site
evaluations. For special situations and detailed exposure analysis, .,
assessors can refer to the discussion of activity data in Freed et al.
(1985).
The following sections address the exposure calculation process
specific to each exposure mechanism. Data management sheets designed to
facilitate the organization and tabulation of data in the exposure
calculation process are presented in Appendix C.
6.1 Inhalation Exposures
Inhalation exposure per event is estimated based on the hours per
event, the inhalation rate of the exposed individual during the event,
and the concentration of contaminant in the air breathed. The formula <
for calculating event-based exposure is:
IEX . D x I x C (6-1)
where
IEX = estimated Inhalation exposure per event (mass of contaminant
per event)
D = duration of an exposure event (hours per event)
I = average inhalation rate of exposed persons (cubic meters per
hour)
C = contaminant air concentration throughout the exposure period
(milligrams per cubic meter of contaminated air).
Short-term exposure is calculated using the short-term contaminant air
concentration, and long-term exposure is based on the long-term
concentration.
Inhalation exposures are keyed to geographic locations delineated
during the Environmental Fate Analysis. Ambient concentration is
generally assumed to be homogeneous throughout a limited area or sector
(within an isopleth). This assumption is not'always well-founded,
however. Numerous studies have shown that there can be marked
differences in indoor and outdoor concentrations of pollutants (Budiansky
1980; Moschandreas et al. 1978) or among microenvironments in the same
area (Ott 1981). To account for these differences when calculating
exposure, several investigations have coined the term "microenvironment,"
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OSWER Directive 9285.5-1
which refers to a type of physical setting where concentrations of
pollutants can be expected to be similar. For Superfund studies,
however, it is usually unnecessary to disaggregate analysis on a
microenvironment basis. Instead, it can generally be assumed that
contaminants have been present long enough for indoor to outdoor
concentrations to have reached equilibrium.
To calculate exposure duration, the analyst considers the amount of
time exposed persons actually spend in the contaminated area. For
example, if a site is in a residential area, conservative estimates of
exposure can be developed by assuming that all residents spend the entire
day within the contaminated zone. In this case, a duration value of 24
hours per day would be used. However, if a site is located in an
industrialized area, it may be more appropriate to base duration on an
8-hour workday, if it can reasonably be assumed that workers do not also
live in the immediate industrialized area. Such factors must be
evaluated on a case-by-case basis. For inhalation exposure, frequency is
assumed to be daily.
In general application, an average adult value for inhalation rate
can be used. An example of an adult average derived from experimental
results (USEPA 1981) is an inhalation rate of 1 m3/hour. This value
can be used to conservatively estimate exposure regardless of
microenvironments or activity.
A more precise estimate of inhalation rate can be derived by
generating time-weighted average inhalation rates. The basis for this
calculation is microenvironment-related data and activity stress
levels/ventilation rates associated with the individual
microenvironment. If this level of detail is warranted, inhalation rates
presented in Table 6-1 can be used. Direction for developing
time-weighted average inhalation rates is provided in Freed et al. (1985).
For ambient inhalation exposure calculation, contaminant air
concentration values should be obtained from the results of the
environmental fate analysis. However, in one case, concentration values
will have to be calculated in the exposure integration stage of the
exposure assessment. As previously mentioned, persons showering or
bathing in potable water contaminated with toxics may be exposed through
inhalation if the contaminants are volatile. This is especially true of
showering, since the high turbulance in combination with the elevated
temperature of shower water can result in significant release of volatile
components.
Various approaches exist for estimating contaminant concentrations
indoors, which depend on a number of factors, including the room air
volume, air exchange and mixing factors, contaminant concentration
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OSWER Directive 9285.5-1
Table 6-1. Su/nmary of Human Inhalation Rates for Men, Women,
and Children by Activity Level (m3/hour)a
Adult male
Adult female
Average adu1tf
Child, age 6
Child, age 10
Resting15
0.6
0.6
0.6
0.4
0.4
Light0
1.3
1.3
1.3
1.4
1.7
Moderated
2.8
2.4
2.6
2.1
3.3
Heavy6
7.1
4.9
6.0
2.4
4.2
aValues of inhalation rates for males, females, and children presented
in this table represent the midpoint of ranges of values reported for
each activity level in Anderson et al. (1984).
''includes watching television, reading, and sleeping.
clncludes most domestic work, attending to personal needs and care,
hobbies, and conducting minor indoor repairs and home improvements.
^Includes heavy indoor cleanup, performance of major indoor repairs
and alterations, and climbing stairs.
elncludes vigorous physical exercise and climbing stairs carrying a
load.
^Derived by taking the mean of the adult male and adult female values
ฐ for each activity level. A representative 24-hour breathing rate for
an average adult is 1.1. This value is based on the assumption that
the average adult spends 93.2 percent of the time at the light/resting
level of activity, 5.8 percent at a moderate level of activity, and 0.9
percent at a heavy level of activity. Values for the percent of time
spent at each activity level are from Methods for Assessing Exposure to
Chemical Substances in the Ambient Environment. Volume 2 of Methods for
Assessing Exposure to Chemical Substances.
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OSWER Directive 9285.5-1
in the water, the amount of water used, and the manner in which a
contaminant is released into room air (instantaneously, continuously,
time-dependent). If showering/bathing exposure estimation is required
for a Superfund exposure assessment, the analyst is referred to Versar
(1984) for a detailed discussion of indoor air contaminant concentration
estimation techniques. For both showers and baths, the assessor should
assume a continuous contaminant release during the bathing/showering
period. Values for the other varible factors mentioned above can be
obtained from Versar (1985).
6.2 Dermal Exposure
Dermal exposure is determined by the concentration of hazardous
substance in a contaminated medium that is contacted, the extent of
contact (i.e., the body surface area contacted), and the duration of such
contact. For exposure to contaminated water, dermal exposure per event
is caTculated as follows:
DEX = D x A x C x Flux (6-2)
where
DEX = estimated dermal exposure per event (mass of contaminant per
event
D = duration of an exposure event (hours per event)
A = skin surface area available for contact (cm^)
C = contaminant concentration in water (weight fraction)
Flux = flux rate of water across skin (mass/cm^/hr).
Short-term dermal exposure per event is calculated using the short-term
contaminant concentrations in water or soil, and long-term exposure is
based on the long-term contaminant concentrations.
It is important to note that dermal exposure to contaminants in water
presents special problems. Such exposure scenarios involve the body's
external surface being brought into contact with an ever-replenished
supply of contaminant (i.e., the water in which one swims or bathes is
turbulent; thus, contaminants adjacent to the skin are replaced as water
containing the full complement of contaminants displaces that from which
contaminants have been removed by absorption). For example, to assess
dermal exposure to an individual swimming in contaminated waters, one
must know what mass of contaminant contacts the body. Since exposure to
the entire mass of contaminant in the area of the water body does not
occur., exposure must be calculated somewhat differently for the dermal
route than for other exposure mechanisms. A simplified approach to this
problem assumes that contaminants are carried through the skin as a
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OSWER Directive 9285.5-1
solute in water which is absorbed (rather than being preferentially
absorbed independently of the water) and that the contaminant
concentration in the water being absorbed is equal to the ambient
concentration. Thus, the flux rate of water across the skin boundary is
assumed to be the factor controlling the contaminant absorption rate.
According to Scheuplein and Blank (1971) (as reported in USEPA 1979b),
the flux rate of water through human skin ranges from 0.2 to 0.5
mg/cm2/hr. It is recommended that, for Superfund Feasibility Study
analyses, the higher value be used so as to generate a conservative,
worst-case estimate. In this special case, exposure essentially equates
with dose; this is unavoidable because of the exposure mechanism
involved. In all other exposure cases, contaminant dose is evaluated
separately as part of the public health evaluation (see USEPA 1985c).
The local recreation department may have detailed data quantifying
the duration and frequency of water use for swimming. When such
locale-specific data are not available, the following national average
figures, based on data from the Bureau of Outdoor Recreation (USDOI
1973), can be applied:
Frequency of exposure = 7 days/year
Duration of exposure = 2.6 hours/day.
Dermal absorption of waterborne contaminants may constitute an
exposure route of very significant magnitude. The factors that influence
dermal absorption of chemicals are the nature of the compound (molecular
weight, 1ipophilicity), the presence of other compounds that might
facilitate passage of a chemical though the skin (e.g., chelating or
complexing agents), and the permeability of the skin. Generally only
1ipid-soluble, non-ionized compounds are absorbed significantly through
the skin. Also, the skin is normally permeable only to compounds whose
molecular weights are less than 500 Daltons. The permeability of the
skin to larger molecular weight compounds and to less 1ipophilie
compounds can'be increased significantly in the presence of corrosive
agents such as acids or by means of abrasion of the skin (Klaasen 1975).
For waterborne chemicals, exposure through the skin is almost directly
proportional to concentration.
Brown, Bishop, and Rowan (1984) recently reported that when compared
with ingestion, dermal absorption of volatile organic contaminants in
drinking water accounted for from 29 to 91 percent of the total dose
incurred, with the average being approximately 64 percent. The
importance of the dermal exposure route is especially pertinent when
organic contaminants are present in very dilute aqueous solution, as may
often be the case at Superfund sites. In certain cases, then, dermal
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OSWER Directive 9285.5-1
exposure to contaminants contained in ground or surface water may
actually overshadow ingestion exposure.
In situations where persons are likely to become exposed to
contaminants in drinking water, the dermal exposure associated with
bathing or showering should also be considered. Bathing/showering
exposure can be assessed in the same manner as has been discussed for
swimming. Generally, an average frequency of one bath or shower per day
can be assumed and the duration of each event can be estimated at 20
minutes.
For swimming or bathing exposure, the surface area available for
dermal exposure is assumed to equal the total amount of human skin
surface area. Average availability values are given below for adults and
children. If the exposed population will not be disaggregated by age
groups, it is recommended that both availability values be used to
represent a general range of exposure for the total swimming or bathing
population. Both availability figures cited below are from Anderson et
al. (1984):
Average adult (male and female, 20-30 yrs) = 18,150 cm2
Average child (male and female, 3-12 yrs) = 9,400 cm2
Direct dermal contact with contaminants present in soil is calculated
per event as follows:
DEX = WF x A x DA (6-3)
where
DEX - dermal exposure (mg/event)
WF ป weight fraction of chemical substance in soil (unitless)
AV = skin surface area exposed per event (cm2/event)
DA =- dust adherence
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OSWER Directive 9285.5-1
Data on dust adherence to skin (DA) are limited, although the
following experimental values for (soil-related) dust adherence were
reported by the Toxic Substances Control Commission of the State of
Michigan (Harger 1979):
Commercial potting soil adheres to hands at 1.45 mg/cm2.
Dust of the clay mineral kaolin adheres to hands at 2.77 mg/cm2.
The degree to which these values represent dust adherence at any given
site is uncertain, as such adherence will depend on a variety of
site-specific factors. Therefore, instead of selecting one of the above
values to estimate direct dermal exposure, it is suggested that the
analyst use both values and generate an exposure range. The lifetime
frequency of direct dermal exposure will also vary considerably and will
depend on the nature of the site, its ease of access, and a variety of
other factors. Therefore, contact frequency should be estimated on a
case-by-case basis, based on knowledge of the site and its environs.
6.3 Ingestion Exposure
6.3.1 Food
Food ingestion exposure is estimated as the product of contaminant
concentration in the food consumed and the amount of food consumed per
day. Frequency is daily for foods that are a regular part of the diet.
For recreationally caught fish, frequency can be estimated based on the
seasonal nature of fishing involved, if appropriate.
USDA source materials listed in Section 5.2.3 are also useful in
quantifying the amount of contaminated food ingested. The Food
Consumptions of Households report series provides data quantifying the
amount of various food categories consumed by households on a seasonal
basis. Similar data are presented in Food and Nutrient Intakes of
Individuals in 1 Day in the United States. The first source can be used
to derive estimates of the amount of various foods consumed by the
overall exposed population by applying seasonal percentage use values to
local population Census data. The second source is used in subpopulation
analyses by applying sex- and age-specific consumption values to Census
data for the exposed population.
Consumption of fish caught in contaminated waters constitutes an
ingestion route of special significance, since certain contaminants of
concern tend to biomagnify in the food chain. This phenomenon results in
predator fish exhibiting tissue concentrations of contaminants at levels
greatly in excess of the ambient concentration in the water body. An
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average daily fish ingestion rate for the U.S. population has been
estimated as 6.5 grams per day (USEPA 1980c). It has been estimated that
persons for whom fish constitutes a major portion of the overall diet
consume up to 124 grams per day (USDA 1980). A West Coast study of
consumption of fish caught in contaminated waters by sport fishermen
(Puffer et al. 1979) reports a median fish ingestion rate of 37
grams/day. This report also lists a maximum rate of 225 grams/day.
Ingestion exposure estimates are calculated in the same manner
regardless of the type of food ingested. Multiplication of the
contaminant concentration in the ingested food by the amount of
contaminated food ingested per day yields exposure per day.
6.3.2 Water
Event-based water ingestion exposure equals the daily total amount of
contaminant Ingested from either surface or ground waters affected by the
Superfund site. This Is determined by the contaminant concentration in
the water and the amount of water ingested per day. On average, an adult
Ingestion coefficient of 2.0 liters per day (USEPA 1980d) can be used for
Superfund site analyses. Frequency of drinking water exposure is daily.
6.4 Exposure Integration
The final step 1n the exposure assessment process for uncontrolled
hazardous waste s-ites is the integration of all exposures experienced by
Individual receptor populations. This simply involves organizing the
results of the previous analyses to total all exposures to a given
hazardous substance experienced by each population segment. Because
different chemicals exhibit different toxicological properties, exposures
to each contaminant of concern are considered separately. Note, however,
that In some cases Individual populations may be exposed to a given
chemical in a particular medium via more than one exposure scenario. For
example, persons who swim in contaminated waters may obtain their
drinking water from the same contaminated water body. In such cases, the
dermal exposure experienced while swimming can be added to that
experienced during bathing or showering to generate an overall dermal
exposure value for that population segment. The data management forms
supplied in Appendix C are designed to facilitate organization of the
results of exposure calculation and integration.
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OSWER Directive 9285.5-1
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saturation. Draft final report. Versar, Inc. Chicago IL: U.S.
Environmental Protection Agency. Contract No. 68-01-6438.
Versar. 1984. Methods for estimating concentrations of chemicals in
indoor air". Draft final report. Versar, Inc. Washington, DC: Prepared
for the Exposure Assessment Branch, Exposure Evaluation Division, Office
of Toxic Substances, U.S. Environmental Protection Agency. March 30,
1984.
Versar. 1985. Exposure assessment for perchloroethylene. Revised draft
report. Versar, Inc. Exposure Assessment Branch, Exposure .Evaluation
Division, Office of Toxic Substances, U.S. Environmental Protection
Agency. September 30, 1985.
Weast WC. 1971. Handbook of chemistry and physics.
Chemical Rubber Company.
Cleveland, OH: The
Williams JR. 1975. Sediment-yield prediction with the universal
equation using runoff energy factor. In Present and prospective
technology for predicting sediment yields and sources. U.S. Department
of Agriculture. ARS-S-40.
Wilson JL, Miller PJ. 1978. Two-dimensional plume in uniform
ground-water flow. Journal of the Hydraulics Division, ASCE 104(4):
503-514.
Wischmeier WH. 1972. Estimating the cover and management factor on
undisturbed areas. U.S. Department of Agriculture. Oxford, MS:
Proceedings of the USDA Sediment Yield Workshop.
Wischmeier WH, Smith DD. 1978. Predicting rainfall erosion losses - a
guide to conservation planning. Washington, DC: U.S. Department of
Agriculture. Agriculture Handbook No. 537.
7-13
-------
OSWER Directive 9285.5-1
Yeh GT, Ward DS. 1981. FEMWASTE: A finite-element model of waste
transport through saturated-unsaturated porous media. Oak. Ridge National
Laboratory, Environmental Services Division: Publication No. 1462,
ORNL-5602. 137 p. As reviewed in: Versar Inc. 1983. Theoretical
evaluation of sites located in the zone of saturation. Draft final
report. Chicago, IL: U.S. Environmental Protection Agency. Contract
No. 68-01-6438.
Yeh GT. 1981. AT123D. Analytical transient one-, two-, and
three-dimensional simulation of waste transport in the aquifer system.
Oak Ridge, TN: Oak Ridge National Laboratory, Environmental Sciences
Division Publication No. 1439. ORNL-5601.
ten GT. 1982. CHNTRN: a chemical transport model for simulating
sediment and chemical distribution in a stream/river network.
Washington, DC: Office of Pesticides and Toxic Substances, U.S.
Environmental Protection Agency. Contract No. W-7405-eng-26. As
reviewed in: Versar 1983. Methodology for assessing exposures to
chemical substances via the ingestion of drinking water. Washington,
DC: U.S. Environmental Protection Agency. Contract No. 68-01-6271.
7-14
-------
OSNER Directive 9285.5-1
APPENDIX A
INDEX TO VARIABLE TERMS
-------
OSWER Directive 9285.5-1
Ol
(J
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OSWER Directive 9285.5-1
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OSWER Directive 9285.5-1
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OSWER Directive 9285.5-1
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OSWER Directive 9285.5-1
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OSWER Directive 9285.5-1
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OSWER Directive 9285.5-1
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OSWER Directive 9285.5-1
LU
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APPENDIX 8
Suggested Outline for Exposure Assessment
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OSWER Directive 9285.5-1
Suggested Outline for Exposure Assessment
Section of the Remedial Investigation Report
1. Summary
1.1 Purpose and scope
1.2 Significant release mechanisms
1.3 Impact on potential receptors
1.4 Organization of the report
2. Contaminant Release Analysis
2.1 Site contaminants
- Contaminants present at the site
- Contaminants selected for analysis (from health assessment
report)
2.2 On-sUe sources of hazardous substance release
2.3 Estimation of substance-specific release rates
- Short-term
- Long-term
3. Exposure Pathways and Environmental Fate
3.1 Contaminant Transport and Transformation
3.2 Identification of Principal Pathways of Exposure
3.3 Estimates of Environmental Concentrations
4. Exposed Populations Analysis
4.1 Exposed population identification
- Individual exposure points
4.2 Exposed population enumeration
- Individual exposure points
4.3 Exposed population characterization
- General population
- Sensitive subpopulations
5. Exposure Calculation and Integration
5ฐ. 1 Development of medium-specific exposure estimates for
each hazardous substance and for each exposed population
segment
5.2 Exposure Integration
6. Uncertainty in the Assessment
7. References
8. Appendices
A. Completed data management forms
B-2
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OSWER Directive 9285.5-1
APPENDIX C
Data Management Forms
-------
OSWER Directive 9285.5-1
This appendix presents master copies of data management forms
designed for use when applying the various analyses described in this
manual. The forms are intended to provide easy,, consistent organization
of the results of each analysis component in the human exposure
assessment process (qualitative analysis, quantitative contaminant
release analysis, etc.) for ready use in subsequent analytical
components. In addition, these forms will also organize exposure
assessment output in a form most useful for conducting a risk assessment
(executed following and based on the results of the exposure assessment)
as well as the development of a site Endangerment Assessment for
enforcement purposes.
These forms are included as master copies, that should be photocopied
for use in a given site investigation. In many cases, a number of copies
of certain forms will be required to tabulate all results of the exposure
assessments. For example, Form No. 7: Exposure Integration requires
that the exposed population segment be logged-into the upper left corner
of L'he form, and exposure information for that population segment be
entered into the remaining columns for each chemical to which the
population is exposed. If four distinct exposed population segments are
affected at the site, four copies of the form will be required.
C-2
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Chicago, Illinois 60604
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