ML20206M952

Preliminary Guidelines for Evaluating Dose Assessments in Support of Decommissioning

ML20206M952
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Issue date:	02/11/1999
From:	NRC
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References
REF-WM-3 PROC-990211, NUDOCS 9905170088
Download: ML20206M952 (32)

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. e b

t .

s Preliminary Guidelines for Evaluating Dose Assessments in Support of  ;

Decommissioning j l

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Introduction The purpose of this guideline is to provide a consistent approach for staff to evaluate dose l

assessments conducted to demonstrate compliance with the current license termination rule l

l (LTR). Staff is currently developing a standard review plan (SRP) for decommissioning that will include guidance on evaluating dose assessments used to demonstrate compliance with the l

l LTR. This interim guideline along with draft Regulatory Guide DG4006 issued August 1998 can be used by staff who are currently working on decommissioning case work involving dose assessments while the SRP is being developed. This preliminary guideline is designed to not ,

y only p'covide a consistent approach to reviewing dose assessments but also to ensure l j

cons;stency between staff reviews during the interim period and guidance likely to come out in the SRP. This guideline documents current approaches being considered by staff for l conducting dose assessments.

l Because staff is still working to resolve several significant issues such as an acceptable approach to moving from screening to site-specific analyses, an acceptable rationale for  ;

j changing land-use scenarios, and acceptable justification for modifying parameters and l

l selecting computer codes, this interim guideline will change as issues are resolved and l additional insights are gained through testing, interaction with industry, and comments from users. Accordingly, this guideline should be viewed as a "living" document.

NUREG-1549, cited in Regulatory Guide DG4006, lays out a process (Figure 1) for identifying l

l decommissioning options that consider potential doses a hypothetical future land user couM receive and the inherent uncertainty in estimating this potential long-term dose. The framework l

provides a process that balances the need for more data to reduce uncertainty with the need to l

l limit data collection costs (i.e., licensees can direct resources and expenditures to areas important to demonstrating compliance). Thus, the framework is consistent with the agency's overall goal of risk-informed regulation.

l t

l Recognizing that there is uncertainty in calculating future doses is an important consideration.

! Whether the dose assessment is a deterministic analysis (i.e., where a single resulting dose is determined) or a probablistic analysis (i.e., where a range of potential doses is determined), the l

analyst and reviewer need to recognize that the result from the analysis is not an absolute

' measure of the real dose that a specific individual is I;kely to receive. In other words, there is some uncertainty in the estimate in terms of the true likely dose.

Uncertainty refers to lack of knowledge about specific factors, parameters, or models. In a dose assessment, there are three sources of uncertainty; these are: model uncertainty, scenario uncertainty, and parameter uncertainty (Bonano et. al,1988 and Kozak et. al,1991). Because of difficulty with quantifying scenario and modeling uncertainty, ideally we would like to use

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conservative assumptions regarding the scenarios and conceptual model used in the analysis.

l Parameter uncertainty on the other hand can be quantified through the use of a probablistic analysis (NCRP,1996 and Maheras and Kozak,1990). Regardless of whether or not l uncertainty is quantified, it is important that both the analyst and reviewer need to be aware that there are inherent uncertainties in a dose assessment and these uncertainties need to be considered in interpreting the results.

! NUREG-1549 identifies the following six key components in dose assessments:

l e Determining the source inventory (Step 1) l

• Defining future land-use scenarios (Step 2) l

• Identifying exposure pathways (Step 2)

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• Developing conceptual models (Step 3) i e Calculating the dose (Step 4) e Evaluating uncertainty and sensitive parameters (Steps 8 and 9) p i

ideally, a computer code to perform the calculation is selected after the conceptual model has been developed; this helps to ensure that the selected computer code can embody the conceptual model of a given site. In this preliminary guideline, two computer codes will be j discussed, the DandD and RESRAD computer codes. Accordingly, the guideline primarily addresses reviewing assessments that involve the use of these two codes (i.e., soil or waste contamination). These codes are discussed because it is anticipated that most analyses will involve the use of one of these codes. The DandD code is based upon the methodology described in NUREG/CR-5512. DandD can be used for doing both screening and site-specific analyses in support of decommissioning (NUREG-1549). RESRAD, documented in Yu et. a l,  ;

1993', is widely used for dose assessments in support of decommissioning. Both codes are based on different conceptual models. The reviewer should ensure that the conceptual model embodied in the code used in the assessment is consistent with the conceptual features of the 2

site based upon what is known about the site. Also, because both codes are only designed for analyzing doses on site, these preliminary guidelines will only address analyses for on-site land use; that is, these guidelines will not cover off-site land-uses which need to be considered for restricted release. The final SRP is expected to provide more guidance on selecting computer codes.

Decon:missioning Dose Requirements The NRC's new license termination rule is contained in Subpart E of 10 CFR Part 20, Subpart E provides the regulatory basis for determining when a site is suitable for license termination.

' Updates on RESRAD can be found at: http:IIwww.ead. ant. gov /~resrad/reshstry.html.

' Appendix K of the RESRAD User's Manual describes an approach for using RESRAD to evaluate doses off site; however, staff is not prepared at this time to recommend this as an acceptable approach.

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Sections 20.1402 and 20.1403 of Subpart E include requirements for unrestricted and restricted use of facilities after license termination. In addition to specific dose limits, additional ,

requirements include demonstrating that residual radioactivity is as low as reasonably achievable (ALARA), financial assurance, and public participation for restricted use.

@ 20.1402 states that a site is considered acceptable for release for unrestricted use if the j

residual radioactivity that is distinguishable from background radiation results in a Total Effective Dose Equivalent (TEDE) to an average member of the critical group that does not exceed 25 mrem /yr, and the residual radioactivity has been reduced to levels that are as low as reasonably achievable (ALARA).

@ 20.1403 states that a site is considered acceptable for release with restriction on land use if the residual radioactivity that is distinguishable from background radiation results in a TEDE to an average member of the critical group that does not exceed 25 mrem /yr with the restrictions in place and the TEDE does not exceed 100 mrem /yr or 500 mrem /yr to the average member of the critical group if the land-use restrictions fail at some point. In addition, to these dose limits, @

20.1403 has additional requirements (such as ALARA financial assurance, and public participation). ,

The dose objective for both unrestricted and restricted use requires an assessment considering no land-use restrictions, which means that the average member of the critical group (a hypothetical future land user)is located on the site. An acceptable resident farmer scenario is described in NUREG-1549 for this purpose. The final SRP is expected to provide additional insights on how someone could justify changing or using an alternative scenario. The dose objective for restricted release also requires an assessment assuming that the land-use restrictions are effective; accordingly, this may necessitate analyzing potential doses to the average member of the critical group located off site or outside of the restricted area. Even with effective on-site restrictions, radionuclides can become mobilized and travel to areas where restrictions are not in place. Because the two computer codes addressed in this guideline cannot be used to analyze radionuclide transport away from the contaminated area, this interim guideline only addresses dose assessment for complying with unrestricted use of the site and restricted release assuming the restrictions have failed. Analyses involving transport of contaminants off site will have to be dealt with on a case-by-case basis, and may require the involvement of staff hydrogeologists. Again, the final SRP is expected to address dose assessment for both unrestricted and restricted release of decommissioning sites.

In addition, because it is covered in Regulatory Guide DG-4006, this interim guideline will not address ALARA demonstration.

Besides the dose limit and ALARA requirement, there are several other aspects of @ 20.1402 l

@20.1403 to consider from a dose assessment perspective. First, Subpart E establishes a 1000-year time frame for the assessment of soil contamination. This is important in not only establishing a time frame for the analysis, but means that parameters affecting the rate of radionuclide migration can become important in demonstrating compliance. For example, radionuclide adsorption (especially in the contaminated and unsaturated zones) can slow up C.\oost.WPDl FEBRUARY ll. 1999

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radionuclide migration sufficiently to prolong their contribution to the calculated dose beyond the ,

1000-year period. Accordingly, staff reviewers need to be especially cognizant of the likely importance of such parameters to demonstrating compliance. The time frame is also important in the types of future events and processes that need to be considered in the analysis. l i

Second, Subpart E excludes radon, instead demonstrating compliance with the LTR will be achieved by evaluating doses from radium (the principal precursor to radon). In particular, the background to the license termination rule states that radon is excluded bedause it is difficult to distinguish radon resulting from a site activity from background radon. In addition, it is difficult to predict design features of future building construction which will greatly affect doses that someone will receive. Therefore, the background to the LTR recommends that licensees with residual radioactivity that contains radium should evaluate the applicability of the EPA radon guidelines, including local building codes designed to minimize the impact of indoor radon levels.

The DandD code does not address radon. RESRAD does allow for evaluating effects from radon. Accordingly, for the purpose of this evaluation, the radon exposure pathway will have to be turned off in the analysis using RESRAD.

1 Analyses with DandD DandD is designed for two-levels of analyses, generic screening and limited site-specific analyses. Screening analyses with DandD relies on the use of default parameter values, predefined models, and predefined scenarios. The result is expected to provide a prudently ,

conservative estimate of the dose; that is, an overestimation of the actual dose that individuals i might receive. Site-specific analyses with DandD involve the use of some site-specific l parameter values with predefined models and scenarios. In following the approach outlined in Figure 1, an analyst is encouraged to start the assessment using the generic screening approach. If the generic screening approach shows nat the dose limit can be met, the analysis is done. The analyst would then move onto lookino m demonstrating ALARA (Step 6). If the l I

generic screening gives doses above the dose limit, trw analyst will need to do some type of sensitivity analysis (Step 8 and 9) to identify parameters where more site-specific data would be helpfulin refining the parameter and analysis. In going mrough the framework a second or l subsequent time, the analyst will then use DandD with the site-specific parameter value(s).

More details on going through the framework are provided in NUREG-1549.

DandD is designed to perform screening analyses using only the source inventory or concentration. The reviewer should ensure: 1) that the source inventory used is appropriate,2) that the default parameter values have not been changed, and 3) that there is no known existing ground-water contamination at the site or other features not appropriately represented by the DandD conceptual model. Because the source inventory is the only input parameter in a screening analysis, it is important that there be appropriate justification through the use3 of: 1) measured data,2) operational and burial records, or 3) possession limits in the license .

'For sites with old burials under 10 CFR 20.304, the maximum quantity that was allowed to be buried in trenches, should not be used to estimate the source inventory C ADOSE.WPDl FEBRUARY ll. I999 l

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Assuming that the staff reviewer has determined the acceptability of using DandD (in general, l DandD can be used for screening, with adjustments to the source term, unless the site is known j to have existing ground-water contamination or other important pathways not included in the j generic scenario), the primary consideration will be whether the licensee has appropriately l converted the source inventory (i.e., source activity) into concentrations and also whether the licensee has changed any of the default parameters. The scenario (i.e., a resident farmer) and conceptual model are already assumed as part of the code. Accordingly, an analyst following the NUREG-1549 framework would establish their source concentration (Step 1) and then move directly to calculating the dose (Step 5).

The DandD code requires that the source inventory (i.e., activities) be input as a source concentration (i.e., in pCi/g or Bq/g). Accordingly, the inventory must be averaged over some i volume. There are three acceptable approaches to calculating the source concentration.

These three approaches move from conservative to more realistic ways of dealing with the source concentration.

1. Mass Balance Assume that the source activity is distnbuted uniformly over a default volume of 360 m2 ' through the following relationshio:

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because NRC has identified instances where disposal limits have been exceeded.

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I-Activity (i)

(1)

Conc (i) = (p Ar

• T

• CF) where:

Conc (i)= concentration of radicnuclide I(pCiIg)

Activity (i)= total activity of radionuclide i(pCl) 2 2 Ar = cultivation area in DandD (m ) = 2400 m 3 3 p = waste density (kg / m ) = 1431 kg/ m in DandD CF = conversion factor (g / kg) = 1000 g / kg T = thickness of the contamination (m) = 0.15 m Activity (i)

Conc (i) = (5.15x10')

i This approach should be used if the thickness of the contaminated area is unknown3 and it can be safely assumed the volume of contamination is greater than and equal to 360 m Because of the small volume, it will always provide a conservative source concentration. The 360 m' volume is based on a 2400 m2 cultivation area multiplied by a contamination thickness of 0.15 ,

i m. The activity should be adjusted to account for radioactive decay since waste emplacement through the following relationship:

fat "A f 1' At=A# t * ^O @ (2)

O where:

A3 = activity (Ci)

AO = initial activity (Ci)

A = decay constant (year ~l)

= 0.693/T b

T

% = half-life (years) t = time (years) n = number of half-lives C:\oost.WPDj FEBRUARY l1,1999 l

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I DandD accounts for the ingrowth of some progeny by assuming that the parent and daughter radionuclides are at secular equilibnum when the progeny has a half-life less than nine hours and a half-life less than ten percent of the parent half-life. An analyst can also assume secular 1 equilibrium for an entire chain by selecting radiohuclides that have a "+C" designation.

2. Single Simulation A single simulation can be used by assuming that the contaminants are distributed uniformly over the volume of contaminated soil and interspersing clean soil, and assuming that the soil is l I

distributed over a surface to a depth of 0.15 m. Figure 2 shows a conceptualization of this alternative. The following relationship can be used to calculate the source concentration:

Activity (i)

Conci(i) = (3)

- SA

• T,

• 1.431x10*

where:

Conc.(i) = Concentration of raoionuciide i i

The equivalent cultivation area (A,) that should be used in DandD would be:

Ar, = SA

• T* -200 (4) 0.15 2

This assumes that the area of the hypothetical house is 200 m . It should be noted that the i average waste concentration can be used if concentration measurements have been made.

For this alternative, the hypothetical individual is assumed to be exposed through all pathways.

This second approach requires that the depth of contamination be known. This ap'proach should in general provide comparable results to the dual simulation approach (described below) especially if the ground watcr is expected to be an important environmental pathway. It should be noted that no credit is taken for an existing cover in order to evaluate the impacts from gamma exposure and because DandD assumes no cover over the contaminated area. This approach may not be appropriate for large contaminated areas, because the activity is diluted more as the area is increased. As a cut off, it is recommended that this approach not be used l 2

for contaminated areas larger than 2400 m 2 For burials larger than the 2400 m , the analyst should consider using some other method for calculating the source term. The surface area represents the area of contamination plus any interspersing clean soil.

3. Dual Simulation l Assume that the activity is uniformly distributed over the volume of contaminated soil and '

interspersing clean soil. Further assume that a volume equivalent to the size of the basement is C Aoost.WPDl FEBRUARY ll. I999

excavated and spread out over the land surface to a depth of 0.15 m. Figure 3 shows a ,

schematic conceptualization of the problem. Note that there will be two different i concentrations, Conc, and Conc 2 Conc, represents radionuclides mixed with the cover material  !

and spread out over the land. Conc 2 represents the concentration of the remaining radionuclides left in place (i.e., in the waste but not excavated). The two contaminated zones will not represent the same exposure to the hypothetical farmer. The farmer can be exposed through all pathways from the top zone (at concentration Conci); however, the farmer's l exposure to the second zone will be limited primarily through what is leached out and reaches the ground water. Because of the two concentrations and different exposure pathways associated with each, this conceptual problem will require two simulations with the DandD code.

The first simulation is used to evaluate exposure from contaminants spread out over the land surface. For this first simulation all exposure pathways are considered with the exception of drinking water and irrigation (these will be covered in the second simulation). To exclude the drinking water and irrigation pathways set the following parameters to zero: water ingestion, domestic use, infiltration rate, and irrigation rate. If the total activity within the waste area is known, the following approach can be used to calculate source concentrations for this first simulation:

If T; + T, > 3, Activity (i)(3 - T,)

Conc.(i) = 6 5A

• T,

• 4.293x10 .

1 IfT, + T < 3, (5)

Activity (i)

Conc,(i) = 0 SA

• 4.293x10 where:

Conc,(i) = concentration of material on the surface (pCi/ g) l 2

SA = surface area of contamination (m ) f T, = thickness of cap (m)

T, = thickness of contaminacion (m)

Derivation of the above equations is provided in Appendix A. In the above formulas, the cap i

and waste are both assumed to be represented by soil at a density of 1.431 g/cc (the DandD default). In addition, the basement height is assumed to be three meters. The surface area represent the area of contamination and any interspersing clean soil. The cultivation crea (Ar) 2 2 parameter in DandD should be set to 4000 m (i.e.,600 m divided by 0.15 m). The area of the 2

hypothetical house is assumed to be 200 m The second simulation is used to evaluate exposure from the remaining inventory, which could l leach into the ground water. Because we are primarily interested in exposure from contaminated ground water, several parameters will have to be set to zero in order to eliminate C:\oose.WPDl FEBRUARY ll, j999 w_-__

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or reduce the exposure from the other pathways (i.e., external, inhalation, plant ingestion, and resuspension) Accordingly, the following parameters will have to be set to zero for the second simulation: floor dust, resuspension factor, indoor dust, outdoor dust, gardening dust, indoor breathing, outdoor breathing, gardening breathing, time spent gardening, time spent outdoors, and soilingestion rate. In addition, the indoor shielding factor should be set to 1.0 and the plant '

mass loading factor should be set to 0.0011 (the smallest value allowed in DandD)', As with the first simulation, the surface area represents the area of contamination plus interspersing clean soil. The second simulation can be eliminated entirely if the licensee can demonstrate conclusively that the ground water will not be used at the site. Further, the second simulation can be eliminated if the contaminated volume is s600 m3 which represents excavation of the entire source term. If the second simulation is eliminated, then all pathways including drinking water and irrigation should be evaluated in assessing the material brought to the surface.

Source concentrations for the second simulation can be obtained using the following functional relationship:

Activity (i)

Conc,(i)

= # (6)

' $A

• T,

• 1431x10 where:

Conc 2(i) = concentration in waste area for second simulation (pCi/0 )

I For this second simulation, we do not account for the activity removed for the first simulation because irrigation and drinking water are excluded in the first simulation. Accordingly, the whole activity is used in evaluating impacts from exposure from these pathways in the second simulation. The cultivation area (Ar) parameter in DandD should be calculated as follows:

i Ar2 = SA - 200 (7) 2 Again, the area of the hypothetical house is assumed to be 200 m l The total dose can be obtained by summing the dose from the two simulations. If the peak doses for both simulations occur at roughly the same time, the reported doses from each simulation can be simply added together. However, if the two peaks occur at vastly different l times, some type of integration of the two dose curves will be needed. in any event, it will be always conservative to simply sum the two peak doses.

The activities for both equations (5) and (6) should be adjusted to account for radioactive decay since waste burial. This third approach (i.e., the dual simulation approach) also requires that the

! depth of contamination be known. In addition, it accounts for the presence of an existing cover

)

'It should be noted that even with this small mass loading factor, the agricultural pathway maybe a dominant pathway. Accordingly, it is recommended that the dose from )

the agricultural pathway be subtracted from the total dose for the second simulation.

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, 10 over ine burial. If there is no cover over the burial area, the formulations are still valid, the analyst only has to set T, to zero. Although less conservative than the mass balance and single simulation approaches, the dual simulation approach should be appropriate in most cases because it is consistent with the assumed resident farmer scenario. That is, the resident farmer scenario assumes that an individual's activities take place over the whole area and is not limited to exposures from isolated spots; thus, the concentration contacted over time is best represented by a spatially averaged concentration. However, for large areas this approach is not appropriate because the activity becomes more diluted as the surface area gets larger. As a cut off, it is recommended that this approach not be used for contaminated areas larger than the 2400 m2 area assumed in DandD. For burials larger than this, the analyst will need to consider using some other method to devise the source term. Staff is currently working on a method that can be used for these cases.

The above formulas can be used if the analyst knows the total activity in the waste area. If concentration measurements have been made, the average concentration can be used. For the ,

first simulation, the average concentration can be used in the following relationship:

If T, + T, > 3, Conc (i)(3 - T.)

Conc (i) =

3 If T, + T, < 3, (8)

Conc,(i) = Conc (i)

• T"'

3 where:

Conc (i) = average concentration of rationuclide i )

from measurements (pCi / g)

For the second simulation, the arithmetic average concentration from the measurements can be used directly in the analysis.

For all three of these approaches, it is assumed that the activity is uniformly distributed over some defined volume. In using either of the last two approaches it is important to assess the appropriateness of assuming that the activity is uniformly distributed over the waste volume.

This assumption may not be' appropriate for situations where the waste is very heterogeneous or if there are isolated large areas of elevated concentrations. Demonstrating the appropriateness of assuming an uniform distribution should be based on an evaluation of the dose from assuming a non-uniform distribution.:

No credit is assumed to be taken for any waste containers (e.g., metal drums or boxes); that is, containers are assumed to have failed or decayed. In general, this assumption should be appropriate because of the expected lifespan of most waste containers are expected to be short C Acost.WPDl FteRUARY ll. I999

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relative to the time frame of the dose assessment. The equations described in these three approaches can be easily evaluated, especially for a large number of radionuclides, in a I

spreadsheet.

After evaluating the source concentration, the staff reviewer should evaluate the licensee's DandD output report. Any changes to default parameters are echoed in the output.

Accordingly, it is important that staff reviewer regeest a copy of the licensee's output report.

l Staff can also determine that the default parameter set has not been altered by running DandD using the licensee's source concentration as input. A copy of the DandD code can be downloaded at: http://techconf.llnl. gov /radcriljava.html, under " dose assessment" and

" decontamination and decommissioning software " The installation instruction file "readme.txt' can also be downloaded. A user's manual for DandD is still under development.

l Staff is still developin'g an acceptable approach for reviewing dose assessments involving DandD where one or more of the default parameters have been changed. The approach used l* to select the default parameter set for DandD is designed to ensure a specific confidence level for generic screening. Although this approach is appealing by providing additionalinsights on the confidence level of the screening analysis, it has a significant drawback in that the confidence level is maintained if one or more of the default parameters are changed only by re-sampling all of the other parameters and changing them as well. In other words, changing one or more of the default parameters and leaving the others unchanged may not give the same confidence level. One clear way to maintain this confidence levelis to re-sample all the parameters each time any one parameter is changed. Accordingly, staff is currently pursuing the development of a Monte Carlo version of DandD that will be capable of such analyses. It is envisioned that the Monte Carlo version of DandD will be developed so that the Monte Carlo features are fairly transparent to users not familiar with probablistic analyses in general, staff believes that changing a suite of parameters associated with a single exposure pathway will not greatly effect the confidence level. Accordingly, in the interim, staff can use the following approach to evaluating site-specific assessments using the DandD code:

e Initially perform a screening analysis with all default parameters.

e identify the key radionuclide(s) and exposure pathways (i.e., those contributing the greatest fraction to the total dose). This can be read directly from the printout.

e Rerun DandD with the site-specific parameter values. Site-specific parameters should be changed as a group as described in Appendix C of NUREG-1549. If the dominant exposure pathway does not change, it is probably appropriate to change a group of default parameters without re-sampling for all parameters. If the dominant exposure pathway changes, it is probably not appropriate to change a subset of the default parameter set without considering the influence of the other parameters.

e The licensee will need to provide justification, as it relates directly to their l

particular site, for all parameter values where defaults are not used. In general, l

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the behavioral and metabolic parameters listed in Table 1 should not be altered. '

Values for these parameters were selected specifically for the screening (critical) group assumed in the assessment. However, the following four behavioral parameters may be changed, if justified, to modify the screening group assumptions: ingestion rate of vegetables, fruits, and grain (Uv), ingestion rate of beef, poultry, milk, and eggs (Ua), ingestion rate of fish (Uf), and ingestion rate of drinking water (Uw).

Staff reviewers are encouraged to read Appendices A and C of NUREG-1549 for additional guidance on changing the critical group and modifying parameters.

Analyses with RESRAD RESRAD is a computer code developed by Argonne National Laboratory (ANL) for the Department of Energy (DOE) to calculate site-specific residual radiation guidelines and radiation dose to future hypothetical on-site individuals at sites contaminated with residual radioactive material. The RESRAD code was adopted by DOE in Crder 5400.5 for derivation of soil cleanup criteria and dose calculations, and it is widely used by DOE, other federal agencies, and industry. Because it is so widely used and willlikely be used by NRC licensees, it is being specifically addressed in this interim guideline. Staff plans to develop more guidance in the SRP on suitable criteria for accepting computer codes.

The RESRAD code is continuously updated. The latest version is 5.82. Staff reviewers will need to ensure that the latest version has been used in assessments that they are reviewing. If an earlier version has been used, the analyst should be required to document that the earlier version is not expected to give significantly different results from the latest version. The RESRAD web site (http://www.ead anl aov/~resrad/reshstry.html) provides information on all the updates from one version to another.

RESRAD, like DandD, has an assumed coneptual model(see Figure 1.1 of Yu et. al,1993),

therefore, the analyst only has to determine if 01e assumed conceptual model is appropriate for the problem. However, unlike DandD, RESRAD does not have prescribed land-use scenarios.

The analyst must develop the land-use scenario by switching on or off various exposure scenarios. For the standard resident farmer scenario used by the NRC, all of the exposure pathways should be switched on with the exception of the radon pathway. The staff reviewer should request that the analyst provide justification for excluding any of the other pathways. For example, if it can be shown that the ground water at the site cannot be used because of either widespread ambient contamination (e.g., salinity) or low yields, it should be justifiable to exclude the ground-water pathway. A finding that the ground water is unsuitable is typically made in coordination with State agencies. Staff plans to develop additional guidance on appropriate rationale for excluding pathways, in the interim such rationale will have to be looked at on a case-specific basis.

RESRAD, like DandD, requires that the radioactive inventory be input as a source C.\oosE,WPDl FEBRUARY Ii.I999

.i3-concentration. Because RESRAD is designed for conduc'ing d' -specific analyses, it is expected that for most analyses, the analyst will have data on radionuclide concentrations at the site5. Given that we are assuming a resident farmer scenario, it should be appropriate to use the arithmetic average of the radionuclide concentration in the analysis (note this also includes any interspersing clean soil). RESRAD allows the user to input information on the area and thickness of the contaminated zone (i.e., these are not fixed, although defaults are provided).

For surface contamination (s0.9 m, the default rooting depth in RESRAD), the site-specific mean concentration, area of contamination, and thickness of the contamination can be used directly in the code. For deeper contamination or if the contaminated area is capped (such as with burials) some assumptions must be made about how much waste will be brought to the surface and how it will be mixed with uncontaminated soil. In general, the schematic in Figure 3 should apply.

Analyzing this conceptual model, as with DandD, requires two simulations. During the first simulation it is assumed that a small volume of waste (600 m') is brought to the surface and spread out over an area to a depth of 0.9 m. For the first simulation, we are interested in the dose from exposure to the material brought to the surface, such as, direct gamma radiation, inhalation, soil ingestion, and plant ingestion (excluding irrigation with contaminated water). j Exposure.from ground water, irrigation, and aquatic use will be considered in the second simulation. Accordingly, the drinking water and aqJatic pathways should be switched off for the first simulation. In addition, the irrigation rate should be set to zero. The source concentration for this first simulation would be derived using equation (8) as previously defined. l The concentrations should be adjusted to account for radioactive decay. The area that should  !

be used in the first simulation should be 700 m2 (i.e.,600 m) divided by 0.9 m). The assumed contaminated thickness would be 0.9 m (note: T that should be used in the above formulation represents the true contaminated zone thickness in its current configuration). The second simulation looks at effects from exposure from the remaining waste. The primary environmental transport pathway for this remaining waste will be ground water. For the second simulation the external gamma, inhalation, and soilingestion pathways should be switched off. In addition, the mass loading for foliar deposition parameter should be set to zero. Further, if the contaminated zone is presently capped, the contaminated zone can be assumed to be covered for the second simulation, unless there are reasons to believe that the cover will be removed (e.g., through a high soil erosion rate). The source concentration for the second simulation should be the mean concentration for the waste area. This includes interspersing clean soil. The contaminated area and thickness used in the second simulation would be based upon the true existing waste zone configuration. Accordingly, to use this approach the analyst will have to know something about the waste zone configuration.

An alternative to using the dual simulation approach is to simply assume that the waste is uniformly distributed over the source volume, taking no credit for the cover (i.e., by assuming

'RESRAD is primarily designed to look at radioactively contr ninated soils; therefore, for analyses involving other types of wastes, the analyst will have to make some assumptions about the waste form and how the radionuclides will be released from this waste form. These assumptions should be clearly laid out.

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that tc,c cap is not present). This should provide comparable, but conservative results to the l

' dual simulation approach especially if the ground water is an important pathway. Using this simpler approach, the analyst would use the mean concentration as the source concentration.

In using either of these approaches it is important for the staff reviewer to assess the appropriateness of assuming that the activity is uniformly distributed over the waste volume.

This assumption may not be appropriate for situations where the waste is very heterogeneous or if there are isolated large areas of elevated concentrations.

If all that is known is the source inventory (activities), such as at some old burial sites, the source concentration can be calculated with equations (5) and (6). It should be noted that the density for the contaminated zone should be set to 1.431 or the concentration should be calculated with the same density assumed in the analysis.

Because RESRAD is designed for site-specific analyses, a single default parameter set has not

'* been established for performing generic screening analyses. Although RESRAD has default parameters, these parameters may or may not be suitable or provide a conservative estimate of l the dose for any given site. The same can also be said about the parameter values recommended in PG-8-08 (U.S. NRC,1994). As an example, Kamboj et. al (1996) found three site-specific parameters (distnbution coefficient, contamination zone thickness, and contamination area) caused residual soil cleanup guidelines calculated by RESRAD to vary by as much as a factor of 40 at 17 Formerly Utilized Sites Remedial Program (FUSRAP) sites. To l ensure consistency between the critical group used in DandD analyses, analysts are

encouraged to use the parameters listed in Table 2. In addition, analysts are encouraged to use site or regional data to the extent possible to establish site-specific parameter values for other parameters. For example, regional climatic data (such as precipitation) can be obtained at

l htt p://www4. n cd c. noa a .g ov/cgi-win /wwcgi. dll?wwnolo s-Produ ct-P B-016# TABLE S .

1

' Given the large number of parameters in RESRAD it is not practical and may not be necessary for an analyst to justify all of their selected parameter values. The important thing is for there to be appropriate justification for those parameters that have the greatest influence on the calculated dose. This is consistent with the philosophy inherent in the NUREG-1549 framework.

To identify key parameters that possibly should be justified, the following approach is recommended:

1. Run RESRAD using as much site or regional data as possible to define physical I parameters, along with the behavioral parameters listed in Table 2 and the source concentration as previously described. It is also recommended that the mass balance approach be used for the ground water pathway for contaminated areas that are s1000 m2 The mass balance ground-water modelis more consistent with the assumed exposure scenario.

2. Identify the key exposure pathways (i.e., those contributing the greatest percentages to the dose). As an example, Kamboj et. al (1996) found in general for the 17 FUSRAP sites, that:

l c Aoost.weol r'teauany ii. 1999

A. for radionuclides with large distribution coefficients (>100 cm3/g) associated with a thick source zone, the plant ingestion pathway was important.

1 B. for radionuclides with small distribution coefficients, the water dependent pathways were important.

C. for radionuclides with intermediate distribution coefficients (between 40-100 cm'/g) associated with a shallow source zone, the dust inhalation and external gamma pathways were important.

D. for radionuclides with intermediate distribution coefficients associated with a thick source zone, the plant ingestion pathway was important.

3. Identify the parameters associated with that pathway from Table 3 (Yu et. al,1993b).

4. Perform sensitivky analyses on those parameters to determine which ones have the greatest influence on the calculated dose. There are several ways to evaluate parameter sensitivity. The simplistic approach is to calculate partial derivatives where the change in the dose is evaluated with respect to the change in each parameter while holding the other parameters constant. For example, SD AD D, - D.

(9)

S(j) = SP(j) AP(j) P(j)2 - P(j),

where:

9(j)= sensitivity of parameter P(j) ,

i D = dose i l

~ P = input parameterj Differences in magnitude of parameters can make direct comparison of their sensitivity ,

difficult. Therefore, for comparison purposes it is best to normalize the sensitivity l through some type of relationship as follows:

P(j) ' AD '

S(j)= (10)

F(P(j)) YAP (j);

Where:

F'(J) = mean or baseline value for parameter P(j)  ;

F(P(j)) = dose when all baseline or mean parameters are used C.\Dost.WF Dl FCBRUARY Ii. 1999

The partial derivative approach can be easily implemented in RESRAD. RESRAD ,

allows the user to perform sensitivity analyses on specified parameters. These l sensitivity analyses look at each parameter individually. The effects of the sensitivity are provided in plots. Information for equation (10) can be read directly off these plots.

Because the relative sensitivity of a given parameter may change as a function of the simulation time, it is recommended that the maximum change in the dose be used to evaluate the sensitivity. One potentially significant drawback to using the partial derivative approach is that it does not allow consideration of potential correlation between parameters (i.e., parameters are assumed to be independent of each other).

An alternative to the partial derivative approach is to use some type of probablistic approach (such as a Monte Carlo analysis) that allows the simultaneous variation of multiple parameters at once. To easily assess the relative effects of any one parameter on the dose, the probablistic approach is used in conjunction with some type of statistical analysis (such as regression or correlation analysis). There is a probablistic version of RESRAD 5.82 which could be used for such analyses; however, the current version is somewhat limited only allowing a maximum of 17 parameters to be treated as uncertain, and 100 samples of each of the uncertain parameter. In addition, the user is limited to choosing from among only five different statistical distnbutions; namely, normal, lognormal, uniform, loguniform, and triangular. Because of the limitation in the number of parameters and realizations that can handled at one time, it may be necessary to l

perform multiple analyses to cover all of the parameters that may have to be treated as uncertain. This limits the viability of considering multiple parameters at the same time.

Accordingly, no attempt should be made at interpreting the uncertainty results as a true measure of the uncertainty in the dose estimate.

Two potential drawbacks to the use of the probablistic approach are that it requires )

information on the probability density function (pdf) of each parameter that is assumed to vary and it requires information on the degree of correlation between parameters.

Analysts will have to use their best professional judgement in selecting appropriate probability density functions. It is best to avoid making strong assumptions about distribution types; instead, the widest distribution consistent with the state of knowledge should be selected. The analyst can also use the maximum entropy theory (Buckley, 1985) as a basis for selecting distribution functions. Table 4 shows distributions that would be used based upon the maximum entropy theory. In general, analysts should use broad ranges of parameter values to represent the large uncertainty.

i Staff is still developing guidance on how to perform sensitivity and uncertainty analyses.

It is anticipated that additional guidance will be developed on how to develop pdf's.  ;

5. Request licensees to provide additional site-specific information on the most sensitive parameters.

References C:\oost.WPDl FEBRUARY ll. l999 l

l L

.' 17 i

Buckley, J.J., " Entropy Principles in Decision Making Under Risk," Risk Analysis, Vol. 5, No. 4, pp. 303-313,1985.

Bonano, E.J., F.A. Davis, and R.M. Cranwell, "A Review of Uncertainties Relevant in Performance Assessment of High-Level Radioactive Waste Repositories," U.S. Nuclear Regulatory Commission NUREG/CR-5211, September 1988.

! Kamboj, S., M. Nimmagadda, E. Faillace, C. Yu, and W.A. Williams, "Effect of Distribution Coefficient, Contaminated Area, and the Depth Contamination of the Guidelines for Uranium Residual Radioactive Material in Soils," Health Physics, Vol. 70, Suppl. 6, p. 64b,1996.

l Kozak, M.W., N.E. Olague, D.P. Gallegos, and R.R. Rao, " Treatment of Uncertainty in Low-Level Waste Performance Assessment," 13* Annual DOE Low-Level Waste Conference, November 19-21,1991.

? Maheras, S.J. and M.R. Kotecki, " Guidelines for Sensitivity and Uncertainty Analyses of i

Performance Assessment Computer Codes," National Low Level Waste Management Program:

DOE /LLW-100, September 1990.

NCRP,"A Guideline for Uncertainty Analysis in Dose and Risk Assessments Related to Environmental Contamination," National Council on Radiation Protection and Measurements:

NCRP Commentary No.14, May 10,1996.

U.S. Nuclear Regulatory Commission, " Policy and Guidance Directive PG-8-08, Scenarios for Assessing Potential Doses Associated with Residual Radioactivity," Division of Waste l Management, Office of Nuclear Material Safety and Safeguards, May 1994.

U.S. Nuclear Regulatory Commission," Decision Methods for Dose Assessment to Comply with Radiological Criteria for License Termination - Draft Report for Comment," U.S. Nuclear Regulatory Commission:NUREG-1549, July 1998.

Yu, C. et. al, " Manual for Implernenting Residual Radioactive Material Guidelines Using RESRAD, Version 5.0," Argonne National Laboratory, September 1993.

Yu, C. et. al, " Data Collection Handbook to Support Modeling the impacts of Radioactive Materialin Soil," Argonne National Laboratory:ANL/EAIS-8, April 1993(b).

C:\oost.WPDl FEBRUARY I 1, 1999 l

l

.ig.

l .

l Table 1. Behavioral and Metabolic Parameters in DandD.

Parameter Type Description Value Units l DIET B Fraction of annual diet derived from home-grown foods 1 l TTR B Total time in exposure period 365.26 d TCA(1) B Food consumption period for beef 365.25 d TCA(2) B Food consumption period for poultry 365.25 d TCA(3) B Food consumption period for milk 365.25 d

! TCA(4) B Food consumption period for eggs 365.25 d TCV(1) B Food consumption period for leafy vegetables 365.25 d TCV(2) B Food consumption period for other vegetables 365.25 d TCV(3) B Food consumption period for fruits 365.25 d TCV(4) B Food consumption period for grain 365.25 d TD B Drinking water consumption period 365.25 d TF B Fish consumption period 365.25 d THA(1) B Holdup period for beef 20 d THA(2) B Ho.ldup period for poultry 1d THA(3) B Holdup period for milk 1d THV(1) B Holdup period for leafy vegetables 1d THV(2) B Holdup period for other vegetables 14 d i THV(3) B Holdup period for fruits 14 d THV(4) B Holdup period for grains 14 d f TTG B Total time in gardening period 90 d XF(1) B Fraction of contaminated beef cattle forage 1 XF(2) B Fraction of contaminated poultry forage 1

]

XF(3) B Fraction of contaminated milk cow forage 1 I XF(4) B Fraction of contaminated hen forage 1 XG(1) B Fraction of contaminated beef cattle grain 1 XG(2) B Fraction of contaminated poultry grain 1 XG(3) B Fraction of contaminated milk cow grain 1 XG(4) B Fraction of contaminated hen grain 1 XH(1) B Fraction of contaminated beef cattle hay 1 XH(2) B Fraction of contaminated poultry hay 1 XH(3) B Fraction of contaminated milk cow hay 1 ,

XH(4) B Fraction of contaminated hen hay 1 1 XW(1) B Fraction of contaminated beef cattle water 1 XW(2) B Fraction of contaminated poultry water 1 XW(3) B Fraction of contaminated milk cow water 1 C;\oost.WPDl FEBRUARY ll, l999

l-. ..

I s

f 19 l

XW(4) B Fraction of contaminated hen water 1 j Ar B Area of land cultivated 2400 m 2 ti B Exposure period indoors 240 d/y tx B Exposure period outdoors 40.2 d/y tg B Exposure period gardening 2.92 d/y l SFi B Indoor shielding factor 0.5512 GR B Soilingestion transfer rate 0.05 g/d IR B Irrigation rate 1.29 L/m2*d

j. Vdr B Volume of water removed from aquifer for domestic use 118000 L Uv B Ingestion rate of vegetables, fruits, and grain 80.4 kgly Ua B Ingestion rate of beef, poultry, milk, and eggs 317.2 kg/y Uf B Ingestion rate of fish 20.6 kgly Uw B Ingestion rate of drinking water 1,31 L/d I l,

Vr M Volumetric breathing rate indoors 0.9 m /h Vx M Volumetric breathing rate outdoors 1.4 m /h Vg M Volumetric breathing rate gardening 1.7 m'/h l

l

• C:\oosE.WPDl FEBRUARY lI, !999

• 20-Table 2. Initial Parameters for RESRAD Parameter Value Units Inhalation rate 1.16ge+04 m'/y Mass loading for inhalation 3.14e-06 g/m' Shielding factor for extemal gamma radiation 0.5512 Fraction of time spent indoors 0.6571 Fraction of time spent outdoors 0.1101 Fruits, vegetables, and grain consumption 112 kg/y Leafy vegetable consumption 21.4 kg/y Milk consumption 233 Uy

. 3 Meat and poultry consumption 65.1 kgly Fish consumption 20.6 kg/y Soil ingestion 18.26 g/y Drinking water intake 478.5 Uy Contamination fraction of dnnking water 1 Contamination fraction of livestock water 1 Contamination fraction of irrigation water 1 Contamination fraction of aquatic food 1 Contamination fraction of plant food 1 Contamination fraction of meat 1 Contamination fraction of milk 1 Livestock fodder intake for meat 27.1 kg/d Livestock fodder intake for milk 63.25 kg/d Livestock water intake for meat 50 Ud Livestock water intake for milk 60 Ud Growing season for non-leafy vegetables 0 25 y Growing season for leafy vegetables 0.123 y Growing season for fodder - 0.15 y Storage time for fruits, non-leafy veg , and grain 14 d Storage time for leafy vegetables 1 d C:\oost.WPDl FEenuAny i I , t c .. .a

I i l

l0 l 4

Storage time for milk i d Storage time for meat and poultry 20 d Storage time for livestock fodder 0 d Fraction of grain in beef cattle feed 0.0743 ,

1 Fraction of grain in milk cow feed 0.0308 Well pumping rate 118 m2/y Irrigation rate 0.5 m/y l

l l

l l

l l

i l

l l

l l

l I

r C.\oosE.WPDl FEBRUARY ll, i999 1

E

a w-l l

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02 deust1X

/ / / / /

SZ 0aus!1A l 02 dojos!h / / / / / / / /

nZ dojos!h / /^ / / / l SZ dojos!h - / / / / /

02 BH' dojos!4 / / / / / / / /

/ / / / / l nZ 3# dolos!h -

I SZ 3#' dojosih / / / / / i 02 H/p' ooup' / / / / / / / /

nZ hap ooup- / / / / /  !

l SZ Hhp' Ooup' / / / / /

djao!dile)!ou / / / / / / / /

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BL ooaH' / / / / / / / /

oz q-deJewalaJ / / / / / / _/ /

nz q-deJewalaJ / / / / /

sZ q-deJewalaJ / / .

/ / /

02 ajos!ou Jela / / / / / / / /

HAp 6Jep!aul / / / / /

/ / / / /

lau61y I ebnpaJ melaJsyap ejae / / / / /

gelejleqla pJod / / / / /

/ / / / /

galipad14 nzty!oMuass / / / / /

ovaosar3aajassunysA ii*leec

o Area of CZ / / / / / / / /

Kd's / / / / / / / /

Fractions of Annular areas /

Leach rate / / / / / / / /

Shielding factor for inhalation /

Depth of roots / / /

Thickness of CZ / / / / / / / /

Dilution length for airborne dust / / / /

Seafood consumption /

Shape factor /

Mass loading for foliar deposition / / /

Depth of soil mixing layer / / /

CZ = contaminated zone UZ = unsaturated zone SZ = saturated zone C:\oosr..WPD j FEBRUARY Ii, I999

• l 24-l Table 4. Probably density functions based upon the maximum entropy theory. l State of Knowledge Probability Density Function no constraint uniform distribution mean exponential distribution  !

1 mean, variance 4-parameter lognormal, beta l

l 1

l i

C;\ DOSE WPDj FEBRUARY l 1, 1999

6 25-O AssimilationofExistingData andinformation l

U 0 ScenarioDefinitioni PathwayIdentificaden I ReviseModelAssumptions, 0 System Conceptualization ParameterValues,& Pathways andEvaluateResults Dose A sessment y

0 Irnplement Preferred 0ption 0

Can Defhe Site Characterization, N

Site be Released?

\*: > Remedation,and no Restricteduse0ptions I I Y'8 le Analyze 0ptionsinterms ofCost Preferred 0 -

ALARA Requiremerts ummmmme andlikelihoodofSuccess Opdon U

License Maintained LicenseTe inationand SiteRelease Figure 1 NUREG-1549 Decision Framework.

l C Aoost.WPDl FEBRUARY ll. l999

1 Tc s( Cap ON*e;*NNNN*;*NN;**N:*NN*****ee*e*e*ee'e*e

,e ee e YC"'

seeeeeeeeeaeaea T* *e*e'e'e'e'e'e'e'e*e*e*e'e'e'e*

nee e

e e a e e*e a e*e eo*e*s

>*e*e*e*e*o*e*o*e

• e e*a s e

- ,oseeeeeeeeeees

,e x Contaminated

'e',e,e,e,e'e'e'e'e'e'e'e*e'

,e,e ,e ,e,e ,e,e,e,e,G e zone

• • e'e'e'e?e?o*e*e*o*e*e?e*e'e soee?e

• e e' HOUSE Uncontaminated soil /

Conc 3 Contaminated material ] /

0.1b m ,e de ,* ,* ,* ,,

,* * * ,* ,* ,* ,* ,* ,* ,* ,* ,*f2 ,* ,*,,*

Figure 2. Alternative conceptual disposal.

C:\oost.WPDl FEBRUARY ll. l999

b u

Tc G=0-0 Cap e,w,w*w,w, wwwwww k aeesee w"au,e,e,e,e,e,e,w,w,e ee eeaeeaeeeeeeeee T.;e:e:e:e:*e:e:e:*e,e:e:e,e,e:e,e:*e e e e 3*e e'e e'e'e*e'e'e' e*e*e*e*e*e*e*e*e*e*e*e e

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e a e e e a e a e a e*e **

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\

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n e'e e

• s'e'e'e's"e'e *e*ee'e'see eeeeeeeeee eae e,e,e,e e,e,e,e,e,e e,e,e,e C, *s*e*e*e' * *o*e*e*e* e**

e****

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C.\oost.WPDl FceauARY lI, I999

? -28 Appendix A Derivation of Equations 4-8 Equation 4:

For DandD the cultivation area needs to be equivalent to the area of contaminaiton. Therefore for the single simulation approach, the size of the area of contamination is an equivalent volume of the waste limited to a depth of 15 cm.

An' V l '"'"

O.15 where:

2 Ar; = cultivation area for DandD (m )

3 Vol ,.,., = volume of contamination (m )

= SA*T, 2

SA = sur face area of contamination (m )

T, = thickness of contaminated zone (m)

We subtract out the area taken up by the house; therefore, the equivalent cultivation area is:

Ar, = SA T* -200 O.15 s

C.\oost.WPDl FEBRUARY ll, l999

~

b .

f Equation 5:

The initial concentration in the waste or contamination zone can be derived as follows:

Activity (i)

Conc,(i) =

VoL,.,

• p.,,,, " CF where:

Conco (i)= initial concentration of radionuclide iin the waste or or contamination zone (pCi /g) 3 Vol ,,,, = volume of waste (m ) = SA

• T, 2

SA = surface area of waste or contamination (m )

T, = thickness of waste or contamination (m)

p. ,.,2 = denssy of waste = 1431 kg /m5 (Danc0 defauh )

CF = conversion factor = 1000 g /kg Activity (i)

Concm(i)

" =

SA

• T "1431x10" Th cc cer.tlation in the material brought to the surface, for the first simulation will depend upon how much of the basement extends into the waste or contamination zone. This concentration can be represented as a fraction of the volume of material excavated to the total volume of material in the basement.

l l

l l

l C:\Dost WPDl FEBRUARY ll, l999 l

l l

t

o s Conci (i) = Conc3 (i)

• Fraction i 1 where:

Conc 3(i) = concentration of radionuclide i in the material brought to the surface (PCi/ g)

Voi '

Fraction. =

Vol.,

3 Vol, = volume excavated (m )

= A,(T., - T; ) T < T. + T,

= A

• T, T., > T + T, where:

A, = area of house (m")

T, = thickness of the baser: ent (m) l T. = thickness of the cap (m)

T, = thickness of contamination (m)

Vol = vo:ume of the basement (m')

= A *T.

If we assume a basement thickness of 3 meters, i

Vol. = A,(3 - T. ) 3 < T. + T,

= A

• r, 3 > T. + T, A,(3 - T. )

Conc.(i) = Con::(i) 3 < T. + T, n_ ,3

)

= Conc -(i)

A.,*3 A"

• T 3 > T. + T ~

Canceuing terms and substituting in Concg (i):

Activity (i)(3 - T. ) 3 e ,i . + T*

Conc,(i) =

S A

• T,

• 4.293x10*

Activity (i)

= - 3 > T. + T*

S A

• 4.293x10" C:\oost.WPDl FrenuAny 11 1999 l

l l

I i

,, w f

P Equation 6:

For the second simulation, we are not concerned about the impacts from gamma radiation or plant uptake; therefore, the 0.15 m contaminated zone thickness is not important. Therefore, concentrations can be determined based upon the existing geometry of the contamination zone.

The concentration in the waste or contamination zone is simply:

Activity (i)

Conc,(i)

=

VOLee'Pog,'CF where:

Conc2 (i) = concentration of radionuchde iin waste or contamination zone (pCi / g)

Activity (i) = total activity of raaionuclide i in waste or contamination zone (pCi)

VoLc, = volume of waste (m') = Ti

• SA T, = thickness of contamination zcre (m)

SA = surface area of contaminat;on zare (m-)

p,,g, = waste density = 1431 kg / m' CF = convers on factor = 1000 gIke Activity (i)

Conc2 (i) =

S A

• T,

• 1431<10" l

Equation 7:

The cultivation area should be equivalent to the area of contamination The default cultivation area cannot be used if the contamination is assumed to spread out over an area different than the default of 2400 m2 . In this case, the size of the area of contamination is SA. In addition, we need to subtract the assumed area of the house; accordingly, Ar2 = SA- 200 Equation 8:

Derivation of equation 8 is the same as equation 5; however, the initial concentration (Conce (i))

l C;\oost.WPD( FEE)RUARY ll, I999

F' l

l ..

l G

,- o 1

l is assumed to be the average from the measurements. -

l l

l C:\ DOSE.WPD\ FEBRUARY I1, I999