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Weapons of Mass Destruction (WMD)

K.9.0 RESULTS

Uncertainty in the conclusions of the TWRS EIS is a consequence of uncertainty in two major areas: the descriptions of the alternatives, with their associated assumptions about tank waste inventories, composition, and remediation technologies; and the consequences analyses, which included assumptions about waste source and release terms, future land uses, environmental transport parameters, and relationships between exposure and risk. The purpose of Appendix K is to discuss the major sources of uncertainty in each of these areas. In addition, a less conservative human health risk analysis is presented to illustrate the implications of making fewer conservative assumptions than were made for the bounding case analyses in the EIS.

Uncertainty in risk analysis is a consequence of two factors: lack of data and natural variability. Lack of data is reflected in our limited knowledge either about the value of constants (e.g., distribution coefficients), or about the statistical parameters (e.g., distribution shape, mean, variance) of things that are inherently variable (e.g., inhalation rates or body weights). Uncertainty due to lack of data can be reduced in principle by more accurate measurements. Uncertainty due to natural variability cannot be reduced by more data, but can be better estimated by acquiring data to characterize statistical distributions of measured variables and by using computer programs to simulate the effect of such variability in the components of equations on calculated values, for example, risk estimates. These combined efforts can reduce systematic uncertainty in the EIS analyses and provide a more thorough understanding of the effects of the remaining uncertainty on the conclusions in the EIS.

K.9.1 UNCERTAINTIES IN THE ALTERNATIVES

There were many uncertainties associated with the alternatives for remediating the tank waste. These uncertainties involved the types of waste contained in the tanks, the effectiveness of the proposed retrieval techniques, waste separations, waste immobilization, and the costs of implementing the alternatives. These uncertainties existed because some of the technologies that may be implemented would be first-of-a-kind technologies, would not have previously been applied to the tank waste, or would not have been applied on a scale as large as would be required for the tank waste, and because only conceptual designs would be available for the alternatives.

K.9.1.1 Major Assumptions

The impact analyses in the EIS required assumptions be made regarding the technologies used for each of the alternatives. These assumptions were based on either the best information available, applications of a similar technology, or engineering judgement. By definition, when an assumption was made, there was some uncertainty associated that was expressed as a reasonable expected range for the assumed value. This section identifies the major assumptions used for the alternatives, describes uncertainties associated with the cost estimates, and presents the results of an uncertainty analysis for the Ex Situ Intermediate Separations alternative.

K.9.1.2 Continued Management and In Situ Alternatives

The following assumptions were made for the Long-Term Management and in situ alternatives. It was assumed that there would be no leaks from the SSTs or DSTs during the administrative control period for the No Action, Long-Term Management, and In Situ Fill and Cap alternatives. The SSTs and DSTs were assumed to maintain their structural integrity throughout the administrative control period for the No Action and Long-Term Management alternatives. The In Situ Vitrification, In Situ Fill and Cap, and the in situ portion of the Ex Situ/In Situ Combination 1 and 2 alternatives were assumed to require additional characterization data to evaluate the acceptability of in-place disposal and to address Resource Conservation and Recovery Act (RCRA) land disposal requirements. The in situ vitrification system was assumed to be capable of vitrifying each tank to the required depth, with no impact of variation in waste composition and inventory on the ability to produce an acceptable waste form. The concentrated liquid waste contained in the DSTs was assumed to be acceptable for gravel filling under the In Situ Fill and Cap alternative.

K.9.1.3 Ex Situ Alternatives

The impact analysis for ex situ alternatives required assumptions about waste retrieval efficiencies, waste loading and blending factors, separations efficiencies, canister sizes and types, and releases to the soil during retrieval. The efficiency of waste retrieval was assumed to be 99 percent. The volume of HLW produced was calculated using the waste inventory, conservative assumptions for waste loading and blending factors, and separations efficiencies. Assumptions about volumes released to the soil during retrieval were made, which directly affected the predictions of the risk consequences resulting from such releases.

K.9.1.4 Schedule

Schedules for construction, operation, and closure were developed for each of the alternatives within the constraints of the Tri-Party Agreement. Schedule constraints would affect the size of the treatment facilities required to process the waste. Following design and construction of a waste treatment facility, the major schedule uncertainty would be the operating duration. Each of the ex situ alternatives was developed using 60 percent overall operating efficiency except for Phase 2 of Phased Implementation, which used 70 percent overall operating efficiency. Operating at higher efficiencies would reduce the operating duration and lower operating efficiencies would increase the duration.

For the alternatives with multiple components, such as retrieval, pretreatment, HLW treatment, and LAW treatment, the overall operating schedule would depend on the efficiency of each component. Uncertainties in the operating schedule would be expected to result in longer operating durations. The operating duration for the ex situ alternatives would be sensitive to the rate at which waste could be retrieved from the SSTs. A low SST sludge retrieval rate could increase the operating duration by 50 percent.

K.9.1.5 Staffing

Staffing estimates were developed for each alternative in support of risk, accident, and socioeconomic impact analysis. These estimates were developed using conservative assumptions for both construction and operating staffing levels. The major uncertainty was associated with the operating schedule. Staffing requirements would be affected by operating efficiencies because efficiency changes would increase or decrease the operating duration and the overall staffing requirements.

K.9.1.6 Resources

The resources required to construct and operate waste treatment facilities were estimated for each alternative using a consistent methodology and common assumptions. The ex situ alternatives and the In Situ Vitrification alternative would have the largest uncertainty for estimated resources. The major uncertainties associated with the estimated resource requirements for the ex situ alternatives included the size and type of facilities required and the volume of LAW and HLW produced.

K.9.1.7 Cost

Cost uncertainties for the various tank waste treatment alternatives were evaluated using a range estimating model. The Ex Situ No Separations (Vitrification) alternative had the largest estimated cost range due to the disposal cost for the large number of HLW packages that would be produced. The In Situ Vitrification alternative had the highest cost range on a percentage basis due to the uncertainties associated with implementing this technology for remediation of the tank waste.

K.9.2 UNCERTAINTIES IN SOURCE AND RELEASE TERMS

Source terms refer to the inventory, which is the total quantity of the hazardous material within the tanks, and to the release term, which is the amount released to environmental media such as air, groundwater, surface water, and soil under normal or accident conditions. Uncertainties associated with source terms included the characteristics and composition of the waste in the tanks and the specific performance capabilities of waste retrieval and processing technologies. Information needed to more thoroughly determine the composition and characteristics of the tank waste currently is being obtained through waste characterization studies. DOE has identified 46 key radionuclides for tracking in development of a "best basis inventory" for Hanford Site tank wastes. These include the radionuclides that dominate the risk estimates in this EIS: C-14, I-129, Np-237, Pa-231, Se-79, Tc-99, and U isotopes. This information will be incorporated into any NEPA analysis of tank farm closure alternatives.

K.9.3 UNCERTAINTIES IN TRANSPORT

Uncertainties in the human health and ecological exposure assessments depend in part on the uncertainties of estimated transport of contaminants from sources through air, soil, groundwater, and surface water to potential receptors. The principal sources of uncertainty of soil and groundwater transport include the physical and chemical mechanisms of contaminant transport through the vadose zone to the groundwater, the rates of infiltration into natural soil and through a protective barrier cap, distribution coefficients (Kd) of contaminants, assumptions about future groundwater flow direction due to assumed decay of groundwater mounds onsite and to climate change, assumptions about future vadose zone thickness due to climate change, assumptions about vadose zone transport in one-dimensional flow and transport simulations, and estimates of releases during retrieval.

The primary sources of uncertainty in estimating surface water transport were associated with the rate of dilution of contaminants in groundwater entering the Columbia River. These sources were the groundwater flow rate and river flow rate, including seasonal and diurnal fluctuations ranging from 2,300 m3/s (81,000 ft3/s) to 7,100 m3/s (250,000 ft3/s); plus turbulence of river flow, which depends on velocity; irregularities in the stream channel, including bends; and width of the river. All of these factors ultimately would depend on the total flow in the river at the point(s) where contaminated groundwater is discharged.

Estimation of transport through air depends on air dispersion modeling. Various assumptions and other factors can introduce uncertainty to these estimates. These uncertainties can be broadly separated into uncertainty inherent in the models, uncertainty in the data used as model inputs, and uncertainty in interpretation of model outputs. Input assumptions included pollutant release characteristics (form, particle size distribution, emission rate, temperature, flow rate), meteorological conditions (ambient temperature, mixing height, stability, wind speed and direction, atmospheric temperature, wind speed profile), and pollutant transport behavior (dispersion, plume rise, interaction with terrain). Model output interpretation required converting 1-hour average values to 3-, 8-, and 24-hour average values using conversion factors. These factors involved an implied assumption regarding the persistence of the meteorological condition producing the highest 1-hour impact. For example, conservative meteorological conditions that produced the highest 1-hour concentration could be expected to persist for most of a 3-hour period, and to a lesser degree, over an 8- or 24-hour period. The midpoint conversion factor values of 0.9. 0.7, and 0.4, respectively, were considered appropriate for this study.

K.9.4 UNCERTAINTIES IN HUMAN EXPOSURE ASSESSMENT

Uncertainties in the human health exposure assessment were divided into two parts. The first part was associated with the exposure parameters used in the post remediation land use scenarios. The second part was associated with the accidental release scenarios. In both cases, Monte Carlo simulations were used to evaluate the uncertainty in the exposure assessment and to establish the parameters that contributed the most to the uncertainty in the exposure assessment (i.e., sensitivity analysis).

In the Monte Carlo approach, PDFs were used to represent the range of values of a given parameter. The effects of simultaneous variations over these ranges on the exposure assessment then were examined using a computer software package (Crystal Ball). These computations were repeated a large number of times to produce complete PDF of the output functions. Statistical summaries of the results then were plotted to help interpret the data.

K.9.4.1 Post-Remediation Land-Use Scenarios

The percentiles of the Monte Carlo-based PDFs were computed and compared to the fixed point estimates of the same function. Two important conclusions can be drawn from these results. First, as expected, the fixed point estimates in the exposure assessment generally lie at the high end of the PDF or approximately the 95th percentile. This is expected, because the fixed point estimate is intended to be an upper bound estimate. Second, the mean of the Monte Carlo-based PDF generally was approximately one order of magnitude lower than the fixed point estimate. This result suggests that the exposure estimates in the EIS were higher-than-expected values or best estimates by approximately an order of magnitude.

K.9.4.2 Accidental Release Scenarios

A Monte Carlo uncertainty and sensitivity analysis also was conducted on the parameters used to compute LCFs or the probability of contracting cancer from accidental releases associated with the remedial actions. The sensitivity analysis indicated that the parameters that contributed the most to the uncertainty in the LCF for the accidental release scenarios, as measured by rank correlation, were the ULD, atmospheric dispersion coefficient (Chi/Q), release volume, IR, and LCF conversion factor.

Comparing the mean and percentile estimates of the LCF distributions for the four accidental release scenarios with the fixed point estimates derived using the upper-bound values indicated that the LCFs based on the upper-bound values were in all cases greater than the 100th percentile of the LCF PDF. The means of the LCF PDFs were approximately one order of magnitude lower than the upper-bound fixed point estimates. These results suggest that the LCF estimates in the EIS are upper bound values. The true probability of contracting cancer or fatalities resulting from cancer actually could be much less than the predicted value.

K.9.5 UNCERTAINTIES IN HUMAN HEALTH RISK

The uncertainties associated with the TWRS EIS risk estimates included parameters used in the equations relating exposure to risk and the historical data on worker risks and accidents used in the evaluations of potential accident impacts. To estimate risk, information must be available on dose-response relationships, which would define the biological response from exposure to a contaminant. Although human epidemiological data were used for developing radiological and nonradiological chemical dose-response models, this information also was developed in laboratory tests using animals exposed to relatively high doses. Therefore, uncertainty is inherent in dose-response relationships, including extrapolating from effects in animals at high doses to potential effects in humans who most often are exposed at much lower doses.

Uncertainty associated with the derivation of toxicity values also affects the level of confidence in human health risk estimates. Sources of uncertainty associated with published toxicity values include the following:

  • Use of dose-response information from effects observed at high doses to predict effects at low levels expected in the environment;
  • Use of data from short-term exposure studies to extrapolate to long-term exposure or vice versa;
  • Use of data from animal studies to predict human effects; and
  • Use of data from homogeneous animal populations or healthy human populations to predict effects on the general population.

The summation of cancer risk across pathways or for multiple pathways makes the total cancer risk more conservative. This is because each slope factor for each chemical carcinogen is an upper 95th percentile estimate, and such probability distributions are not strictly additive. The risk values calculated for the post-remediation scenario in the TWRS EIS were a conservative bounding estimate. The uncertainty in the risk values for certain receptors increases as the time to the future increases. Less uncertainty was associated with the risk values at 300 years than the risk estimates at 500, 2,500, 5,000, and 10,000 years.

By far the greatest uncertainty in the routine remediation risk was associated with the source data, which were based on the estimated inventory and source terms (i.e., the amount of chemicals and radionuclides released to the environment). Other contributors to the routine risk uncertainty were airborne transport of the released chemicals and radionuclides; accumulation of contaminants in food products; production and distribution of food products; lifestyle and diet of specific individuals; food consumption rates; and dose conversion factors.

The risk estimates for the post-remediation and intruder scenarios were associated with more uncertainty than facility routine operation risk because they involved uncertainties associated with the future land use and intrusion into residual waste, in addition to modeling. Finally, the MEI risk estimates generally involved a greater level of uncertainty than population risk estimates. The greatest uncertainty in calculating the post-remediation intruder risk was associated with the source data. Source terms were based on the estimated inventory and an average tank within the eight aggregated tank farms of the 200 Areas (Volume Two, Appendix A). Additional information regarding the source term would decrease the uncertainty in the risk estimate. The relative uncertainties associated with the dose conversion factors were not as important as the source data, source terms, and exposure pathway parameters.

K.9.5.1 Uncertainties in Ecological Risk

The ERA for this EIS used a screening level methodology to estimate potential radiological and chemical hazards to a suite of representative terrestrial receptors: the Great Basin pocket mouse, coyote, mule deer, red-tailed hawk, and loggerhead shrike. Pathways considered for the No Action alternative were food and water ingestion (all receptors except the mouse, which was assumed to obtain all water from metabolic sources), incidental soil ingestion (mouse and mule deer, coincident with consumption of vegetation), inhalation of routine releases (all), and direct external exposure (mouse, while in a burrow). Potential hazards to aquatic organisms were evaluated using the CRITRII program developed at the Pacific Northwest National Laboratory.

Overall, the parameters of the equations used to estimate ecological risks would need to vary or be in error by several orders of magnitude to affect the conclusions of the ERA by themselves. Simultaneous variability in multiple parameters in the same direction could do so. For example, increasing both water ingestion rates and the fraction of water obtained from a contaminated source by 10-fold would increase receptors estimated contaminant intake by a factor of 100. Such simultaneous variability is possible and would contribute to the overall uncertainty in the risk estimates. Nonetheless, because the ecological risk estimates in this EIS were so different for the various scenarios considered (very high for direct contact with stored wastes and very low for routine releases associated with either the No Action or various remedial alternatives) more detailed analysis was not considered likely to alter those distinctions. Conversely, more detailed analysis was unlikely to permit clear distinctions among the remedial alternatives based on potential radiological risks of routine releases, because these latter values were both low and similar to each other. The primary distinction in ecological risks thus remains between the No Action (assuming direct contact with the stored wastes at some future point) and remediation alternatives collectively.

K.9.6 CONCLUSIONS

The scope of the tank waste disposal action and alternatives analyzed in the TWRS EIS was such that a number of components of actions and analyses contributed varying degrees of uncertainty to the assessment of impacts as discussed above. Some of the components were well characterized and the uncertainties were well known and documented. Other components were better characterized as estimates and the uncertainties were not known or were also estimated. However, the major sources of uncertainty were associated with a few major components of the proposed action and alternatives. Following is a brief discussion of those major components of uncertainty and DOE or other actions which would be expected, in time, to reduce the level or range of uncertainty for that component.

K.9.6.1 Engineering

Uncertainties related to engineering included facility, process, and equipment design, and performance. The flowsheets and facility designs for the TWRS alternatives were preconceptual, based on design information and performance criteria that are in the early planning stages and involve considerable engineering judgement. Engineering design uncertainties will be reduced or better defined as investigations are completed, disposal decisions are made, and engineering design proceeds to preliminary and ultimately definitive design. These efforts would include pilot-scale testing and process demonstration on the tank waste before full scale implementation.

K.9.6.2 Waste Inventory

Uncertainties regarding waste inventory relate to the waste type, form, and quantity of tank waste constituents. These uncertainties contributed in turn to the uncertainty of source terms, release rates and transport estimates (Figure K.1.0.1). The waste inventory data used in developing the alternatives and their associated impacts were derived from model predictions and sample analyses performed to date. DOE has an ongoing waste characterization program in place to better define the quantity, content, form, and characteristics of the tank waste that will ultimately reduce the inventory-related uncertainties. DOE has identified key radionuclides for tracking in developing a "best basis inventory" for Hanford Site tank waste. These include the radionuclides that dominate the risk estimates in this EIS: C-14, I-129, Np-237, Pa-231, Se-79, Tc-99, and U isotopes. This information will be incorporated into any NEPA analysis of tank closure alternatives. As part of this program, DOE is currently developing the HTI program that will provide information on the characteristics of the tank residuals and the capability of retrieval systems to deal with difficult-to-remove SST wastes. This program, which will reduce the uncertainties associated with residual waste, includes demonstrations of capabilities to quantify residual waste volume and technologies for sampling and characterizing the residual waste.

K.9.6.3 Waste Transport

Uncertainties regarding waste transport include source terms (type, quantity, form, composition, concentration, solubility), and release rates for tank residuals and LAW, vadose zone characteristics, groundwater flow characteristics, transport mechanisms, and rates. Recent observations of relatively immobile contaminants at depths of up to 38 m (125 ft) below the tanks are not fully explained with interstitial flow and may indicate there are other transport mechanisms in effect. These observations are currently the focus of a DOE program. The initial phase of the program is to determine if the observations are representative of extensive vadose zone contamination beneath the tanks or if they are related to other phenomena such as borehole cross contamination. DOE is also currently developing criteria and technologies to identify leaks and limit releases during retrieval.

K.9.6.4 Exposure Scenarios

The TWRS EIS has assessed an extensive and well defined suite of potential human exposure scenarios including an array of potential remediation and post remediation receptors. The scenarios included a variety of Hanford land uses (farming, industry, recreation, Native American subsistence), a variety of receptors (resident, worker, farmer, recreational user, intruder) and a variety of pathways. Uncertainties related to exposure scenarios include the degree to which Hanford land or groundwater would be accessible or restricted, the location, timing, and duration of exposures to contaminants, and the density of user populations. DOE has an ongoing program to determine future land uses for the Hanford Site including preparation of a Comprehensive Land Use Plan. These efforts, in combination with those described in Sections K.9.1 through K.9.3, will both reduce the total uncertainty in the TWRS risk analyses and better characterize that which remains.

ATTACHMENT 1

Explanation of Input Distributions Used in the Monte Carlo Methodology

This attachment explains the information sources and rationale used in deriving the input distributions used in the Monte Carlo uncertainty and sensitivity exposure analysis. This attachment is ordered by exposure scenario (e.g., industrial, residential) with input distribution explanations given for the exposure route which resulted in the greatest risk for each particular exposure scenario.

Industrial Exposure Scenario

The industrial exposure scenario is based on worker exposure over a 20-year duration. The scenario involves mainly indoor activities, although outdoor activities (e.g., soil contact) are also included. The air inhalation rate is 20 m3 per day for a worker and external exposure occurs 8 hours per day. Inhalation of contaminants occurs 250 days per year and external exposure occurs for 146 days per year.

EF (exposure frequency)

Units: days per year
Distribution used: triangular (likeliest 245, maximum 307, minimum 156)
Source: EPA 1989

This input represents the number of days per year that a typical worker would spend in the workplace. The likeliest value for EF was established using the rationale that the worker works two weekends per year and takes two weeks' vacation and two weeks' sick leave. The minimum value for EF was established by assuming that the worker is part-time and only at the site approximately 60 percent of the time. The maximum value for EF was based on a person taking two weeks' vacation, two weeks' sick leave, and working all but 15 weekends per year.

ED (exposure duration)

Units: years
Distribution: lognormal (mean 7.3, standard deviation 8.7)
Source: Department of Labor 1992

This input represents the number of years that the individual being modeled will spend at a particular job location within the contaminated area. After considering the information in the EPAs Exposure Factors Handbook (EPA 1989) and after considering various factors that could impact ED, it was determined that the input would be characterized using the data from a study conducted by the Department of Labor completed in 1992. The distribution used for ED is a lognormal distribution based on a mean standard deviation presented by the Department of Labor report. The maximum value is 30 years, which is the upper bound time specified by the report for a worker at any one given job, and which is also the value specified by the EPA.

IR (inhalation rate)

Units: cubic meters per day
Distribution: triangular (likeliest 18.9, maximum 32.0, minimum 6.0)
Source: EPA 1985

This input represents the amount of air that is breathed in during a typical day at work by an adult under an industrial exposure scenario. Layton (Layton 1993) has shown that inhalation rates vary with body weight and the type of activity (i.e., light, medium, or heavy). For this evaluation, a triangular distribution was used based on adults working at light activity levels.

Residential Exposure Scenario

The residential scenario is based on exposures over 30 years duration to an individual residing onsite. The individual is assumed to be exposed to contaminated soil, air, surface water, and groundwater, and homegrown fruits and vegetables 365 days per year. The exposed individual was assumed to ingest 2 L (0.5 gal) of contaminated water per day, 365 days per year for 30 years.

EF (exposure frequency)

Units: days per year
Distribution used: triangular (likeliest 345, maximum 365, minimum 180)
Source: Smith 1994

This input represents the number of days per year that the typical behavior being used to characterize risk to the target population takes place. Providing an example of a nontypical day that would be excluded from consideration when generating an EF input may be helpful in understanding the purpose of the input. Days taken during the year as vacation, where the person is away from work, would not be considered typical since exposure parameters are likely to differ from those associated with a typical day in that persons life.

The likeliest value for EF was established using the rationale that two weeks spent away from home was a plausible likeliest value for EF. The minimum value for EF assumes that a person spends 50 percent of his or her time at home and the rest away from home. The maximum value for EF assumes that the person spends all of his or her time at home.

ED (exposure duration)

Units: years
Distribution: lognormal (mean 11.4, standard deviation 13.7)
Source: Department of Labor 1992

This input represents the number of years that the individual being modeled will reside at a residence located within the contaminated area. After considering the information in the EPAs Exposure Factors Handbook (EPA 1989) and after considering various factors that could impact ED, it was determined that the input would be characterized using the data from a study conducted by the Department of Labor completed in 1992. The distribution used for ED is a lognormal distribution based on the mean and standard deviation presented by this report. The maximum value is the upper bound time specified by the report for a worker at any one given job.

IR (drinking water ingestion rate)

Units: liters per day
Distribution: lognormal (mean 1.12, standard deviation 1.63)
Source: Rosenberry-Burmaster 1992

Direct ingestion of radionuclides in tap water is an important exposure pathway that often dictates groundwater remediation at contaminated sites. The IR input represents the amount of drinking water ingested during a typical day by an adult under a residential exposure scenario.

Native American Scenario

The Native American scenarios are intended to include a wide range of activities from reserved rights related to traditional lifestyles and preservation of natural and cultural resources to those specifically delineated in the Treaties. Specific activities include hunting, gathering, collecting, fishing and processing of the catch along the shoreline, and pasturing of livestock, as well as ceremonial, educational, seasonal, social, and trade activities.

EF (exposure frequency)

Units: days per year
Distribution used: triangular (likeliest 345, maximum 365, minimum 180)
Source: Smith 1994

This input is the number of days per year that the typical behavior being used to characterize risk to the target population takes place. An example of a nontypical day that would be excluded from consideration when generating an EF input may be helpful in understanding the purpose of the EF input. Days taken during the year as vacation, where the person is away from work, would not be considered typical since exposure parameters are likely to differ from those associated with a typical day in that persons life.

The likeliest value for EF was established using the rationale that two weeks spent away from home seemed a plausible likeliest value for EF. The minimum value was based on a scenario in which a person spends 50 percent of his or her time at home and the rest away from home. The maximum value was based on a person spending 100 percent of their time at home.

ED (exposure duration)

Units: years
Distribution: lognormal (mean 11.4, standard deviation 13.7)
Source: Israeli-Nelson 1992

This input is the number of years that the individual being modeled will reside at a residence located within the contaminated area. After considering the information in the EPAs Exposure Factors Handbook (EPA 1989) and various factors that could impact ED, it was determined that the input would be characterized using the data from a study conducted by the Department of Labor in 1992. The lognormal distribution used for ED is based on that report. The maximum value is 70 years, which is the upper bound time specified in the Native American scenario.

IR (fish ingestion rate)

Units: grams per day
Distribution used: triangular (likeliest 140, maximum 1,080, minimum 30.0)
Source: DOE 1996 and EPA 1989

Consumption rates for recreationally caught fish from large bodies of water have a 50th percentile average of 30 g/day and a 90th percentile average of 140 g/day (EPA 1989). Therefore, for purposes of this scenario, the fish ingestion PDF was approximated by a triangular distribution.

VF (volatilization factor)

Units: liters per cubic meter
Distribution: triangular (likeliest 0.1, maximum 0.3, minimum 0)
Source: Andelman 1990

For groundwater, an upper bound volatilization factor (VF) based on uses of household water (e.g., showering, laundering, dish washing) was used. A VF of 0.1 L/m3 was used for household activities. The transfer of contaminants from water to a Native American in a sweat lodge was also estimated using a VF similar to that proposed by EPA (Andelman 1990). The steam in the sweat lodge is generated by pouring water onto heated rocks. A VF of 0.3 L/m3 is used for all nonvolatile contaminants, a factor of 2.5 is used for all VOCs, and a factor of 0.5 is used for radon. Therefore, for the Native American scenario, the VF probability density function was modeled as a triangular PDF with a most likely value of 0.1 L/m3, maximum value of 0.3 L/m3, and minimum value of zero.

Total Health Impacts for Hanford Site Users

The total adverse health impacts to a hypothetical future resident of the Hanford Site is expressed as the total cancer fatalities over a 10,000-year period. The cancer fatalities are calculated by first computing the total cancer risk for a given population and then dividing by the dose to risk conversion factor for cancer incidence and cancer fatalities (ICRP 1991). The parameters driving the uncertainty are the population density and the length of time for a life span or generation.

P (population density)

Units: persons per square kilometer
Distribution used: triangular (likeliest 3, maximum 5, minimum 1)
Source: professional judgment and WSDFM (1994)

The population density describes the number of people in a given area that will live at some hypothetical time in the future at the Hanford site. The current estimates of the farming population density surrounding the site give a value of approximate 5 persons/km2. The triangular distribution for population density was chosen in order to estimate the uncertainty in the cancer fatalities at a population density of as low as 1 person/km2.

D (Duration of each generation)

Units: years
Distribution: normal distribution (mean 75 years, standard deviation 7.5 years)
Source: EPA 1989

This input is used to represent the life expectancy for the each generation. Although 70 years has been widely used in the past, current data suggest that 75 years would now be a more appropriate average value.

Intruder Scenario

The post drilling scenario has three exposure pathways: exposure to airborne contamination via inhalation, external exposure to penetrating radiation, and consumption of contaminated produce. For the post drilling scenario, 0.35 m3 of waste are distributed throughout a 15-cm-deep plow layer in a garden that is 2,500 m2 in area. The individual is assumed to spend 4,380 hr/year residing at home (indoors), 1,700 hr/year outdoors, and 100 hr/year outdoors in gardening activities on the Site. The sensitivity analysis for the intruder scenario indicated that the intruder effective dose is most dependent in order of rank upon soil concentration, external exposure time, depth to the contamination, and the soil density.

Soil Concentration

Units: picocuries per gram
Distribution used: triangular (likeliest 9.9 E+05 maximum 1.7 E+06 minimum 4.4 E+05)
Source: professional judgment and Rittman 1994

The concentration of the contaminant in soil is a function of the diameter of the well, the thickness of the waste layer, the garden surface area, and the soil density. The thickness of the waste layer is assumed to be a constant 5 m (16 ft), although some uncertainty is associated with this parameter. The uncertainty associated with the surface area of the garden and the soil density are treated separately below. The diameter of the well excavated at the site was assumed to vary as a triangular distribution. The maximum value was assumed to be the point estimate of 30 cm (12 in.) and the most probable and minimum values were selected to be 22.5 cm (9 in.) and 15 cm (6 in.), respectively. The rationale for this assumption is that the well diameter could conceivably be three-fourths or one-half the point estimate. The corresponding triangular distribution for the soil contaminants concentration had the values stated above.

External Exposure Time

Units: hours
Distribution used: triangular (likeliest 1,800, maximum 3,260, minimum 676)
Source: professional judgment and EPA 1989

For estimating external exposure from the soil contamination, the house was assumed to reduced the dose rate to one-third the direct dose rate. Therefore, the average time exposed at the unshielded dose rate is:

(1,800 hr/year)*1 + (4,380 hr/year)*(1/3) = 3,260 hr/year

For the purposes of the Monte Carlo assessment, the minimum external exposure time was based on EPAs analysis of activity patterns in United States households (EPA 1989). The most likely value was chosen to represent 100 percent shielding of the receptor by the house.

Depth to Contamination

Units: centimeters
Distribution used: triangular (likeliest 15.0, maximum 22.5, minimum 7.5)
Source: EPA 1989 and Rittman 1994

The likeliest depth to the contaminants was chosen to be 15 cm or the tilling depth (Rittman 1994). However, due to leaching and other factors, surface soil was considered to extend to 22.5 cm or to be as shallow as 7.5 cm.

Soil Density

Units: grams per cubic centimeter
Distribution used: uniform (maximum 1.50, minimum 0.50)
Source: Rittman 1994 and DOE 1996

Published soil densities for the Hanford Site range from 0.5 g/cm3 (DOE 1996) to 1.5 g/cm3 (Rittman 1994). Therefore, the soil density distribution was assumed to be uniform with likeliest value 1.0.

Total Health Impacts Along the Columbia River

This scenario is used to estimate the dose to a population exposed to contamination from the Columbia River. The contamination enters the Columbia River as a result of groundwater flow into the river. Different contaminants will enter the groundwater and reach the Columbia River at varying times in the future.

Total cancer fatalities are calculated using factors that relate the number of fatal cancers to the curies of each contaminant released to the river. These factors were calculated using a computer program which estimates the time integral of collective dose over a period of up to 10,000 years for time variant radionuclide release to surface waters, such as rivers (DOE 1987).

The dose estimates for the Columbia River scenario indicate that of the three principal routes of exposure (i.e., external, ingestion, and inhalation), ingestion is the principal route, followed by inhalation and external exposure. A Monte Carlo sensitivity analysis indicated that the parameters which most affect the equivalent dose are in rank order: soil to plant transfer factor, root ingestion rate, Columbia River flow rate, total population exposed, months per year of irrigation, and soil area density.

Root Ingestion Rate

Units: kilogram per year
Distribution used: triangular (likeliest 55.7, maximum 73.0, minimum 0.0)
Source: DOE 1996 and Rittman 1994

The root ingestion rate is the quantity of rooted vegetables consumed on a yearly basis by a resident along the Columbia River. For nonleafy vegetables, this value is approximately 55.7 kg/year (Rittman 1994). A more recent publication which deals directly with potential impacts to the Columbia River by contaminants from the Hanford Site states a value of 200 g/day or approximately 73 kg/year (DOE 1996).

Columbia River Flow Rate

Units: cubic feet per second
Distribution used: triangular (likeliest 8.1E+04, maximum 2.5E+05 minimum 3.6E+04)
Source: Volume One

The flow rate of the Columbia River is important in that it is used to estimate the amount of dilution that a contaminant would undergo once groundwater discharges to the river. Flows through the Reach fluctuate significantly and are controlled by operations at Priest Rapids Dam. Daily average flows range from 3.6E+04 ft3/sec to 2.5E+05 ft3/sec.

Months Per Year of Irrigation

Units: months per year
Distribution used: triangular (likeliest 6.0, maximum 7.0, minimum 5.0)
Source: Rittman 1994 and professional judgment

This parameter is the number of months per year that plants are irrigated with contaminated Columbia River water. A default value of six months per year has been assumed for the Hanford Site (Rittman 1994). However, in order to place some uncertainty on this value, irrigation has been assumed to occur for six months plus or minus 1 month to account for dry and wet years.

Soil Area Density

Soil area density is the product of soil density and the depth to the contamination. The same distributions used in the Monte Carlo approach for the intruder scenario for these distributions were used in the present scenario.

Soil to Plant Transfer Factor (root)

Units: curie per kilogram dry weight of vegetable to curie per kilogram of soil
Distribution: lognormal (mean 0.50, standard deviation 0.25)
Source: professional judgment

The soil to plant transfer factor accounts for the amount of contaminant that will be taken up from the soil through the roots of a plant. The most recent published value for this factor is 1.0 (Rittman 1994) for Np which is two orders of magnitude larger than the last published value (PNL 1986). However, examination of the most recent published values for this factor for other radionuclides (Rittman 1994) indicates that in general, the soil to plant transfer factor is between 0.01 and 1.0. Therefore, the distribution used for the Monte Carlo analysis was a lognormal with a mean value of 0.50 and standard deviation of 0.25. Examination of this probability distribution reveals that the selected distribution captures the range of values between 0.01 and 1.0.

REFERENCES

Aaberg-Kennedy 1990. Aaberg, R.L. and W.E. Kennedy, Jr. Definition of Intrusion Scenarios and Example Concentration Ranges for the Disposal of Near-Surface Waste at the Hanford Site. PNL-6312. Pacific Northwest National Laboratory. Richland, Washington. October 1990.

Andelman 1990. Andelman, J.B. Total Exposure to Volatile Organic Compounds in Potable Water. Significance and Treatment of Volatile Organic Compounds in Water Supplies, Ram, N.M. Christian, R.F., and Cantor, K.P. eds. Lewis Publishers. 1990

Brodeur 1995. Brodeur, J.R. Vadose Zone Characterization Project at the Hanford Tank Farms Tank Summary Data Report for Tank SX-101. GJ-HAN-5 Tank SX-101. U.S. Department of Energy. Richland, Washington. September 1995.

Caggiano 1996. Caggiano, J.A. Groundwater Water Quality Assessment Monitoring Plan for Single-Shell Tank Waste Management Area S-SX. WHC-SD-EN-AP-191, Rev. 0. Westinghouse Hanford Company. Richland, Washington. 1996.

DOE 1996. Human Scenarios for the Screening Assessment - Columbia River Comprehensive Impact Assessment. DOE/RL-96-16-A. U.S. Department of Energy. Richland, Washington. 1996.

DOE 1994j. Occupational Injury and Property Damage Summary, January - December 1993. DOE/EH/01570-H5. U.S. Department of Energy. Washington, D.C. 1994.

DOE 1988. Radioactive Waste Management. DOE Order 5820.0A. U.S. Department of Energy. Washington, D.C. September 26, 1988.

DOE 1987. Final Environmental Impact Statement. Disposal of Hanford Defense High-Level, Transuranic and Tank Wastes Hanford Site Richland, Washington. DOE/EIS-0113. U.S. Department of Energy. Washington, D.C. 1987.

Ecology et al. 1994. Hanford Federal Facility Agreement and Consent Order, as amended. Washington State Department of Ecology, U.S. Environmental Protection Agency, and U.S. Department of Energy. Olympia, Washington. January 1994.

EPA 1989. Exposure Factors Handbook. U.S. Environmental Protection Agency, Office of Health and Environmental Assessment. Washington, D.C. 1989.

EPA 1988. Recommendations for and Documentation of Biological Values for Use in Risk Assessment. EPA/600/6-87/008. EPA Environmental Criteria and Assessment Office. Cincinnati, Ohio. 1988.

EPA 1985. Guideline for Determination of Good Engineering Practice Stack Height Technical Support Document for the Stack Height Regulations Revised. PB85-225241. U.S. Environmental Protection Agency. Research Triangle Park, North Carolina. 1985.

EPA 1985a. Development of Statistical Distributions or Ranges of Standard Factors Used in Exposure Assessments. U.S. Environmental Protection Agency, Office of Health and Environmental Assessment. Washington, D.C. 1985.

Fecht-Weekes 1996. Fecht, K.R. and D.C. Weekes. Geologic Field Inspection of the Sedimentary Sequence at the Environmental Restoration Disposal Facility. BHI-00230. Bechtel Hanford, Inc. Richland, Washington. April 1996.

Finley et al. 1994. Finley, B., D. Proctor, P. Scott, N. Harrington, D. Paustenbach, and P. Price Recommended Distributions for Exposure Factors Frequently Used in Health Risk Assessment. Risk Analysis 14, 533-553. 1994.

Freeman-Pollard 1994. Engineering Evaluation of the GAO-RCED-89-157, Tank 241-T-106 Vadose Zone Investigation. U.S. Department of Energy. Richland, Washington. September 1994.

Gee et al. 1992. Gee, G.W., M.L. Rockhold, M.J. Fayer, and M.D. Campbell. Variations in Recharge at the Hanford Site. Northwest Science, Vol. 66, No. 4. 1992.

Hanlon 1995. Hanlon, B.M. Waste Tank Summary for the Month Ending December 31, 1994. WHC-EP-0182. Westinghouse Hanford Company, Richland, Washington. February 1995.

Hill 1992. Hill, J.W. Chemistry for Changing Times. Macmillan Publishing Company. New York, New York. 1992.

IAEA 1992. Effects of Ionizing Radiation on Plants and Animals at Levels Implied by Current Radiation Protection Standards. Technical Report Series No. 332. International Atomic Energy Agency. Vienna, Austria. 1992.

ICRP 1991. 1990 Recommendations of the International Commission on Radiological Protection. ICRP Publication 60. International Commission on Radiological Protection. Pergamon Press. New York. 1991.

ICRP 1986. The Metabolism of Plutonium and Related Elements. ICRP Publication 48. International Commission on Radiological Protection. Pergamon Press. New York, New York. 1986.

ICRP 1979-1982. Limits for Intakes of Radionuclides by Workers. ICRP Publication 30. International Commission on Radiological Protection. Pergamon Press. New York, New York. 1982.

ICRP 1977. 1977 Recommendations of the International Commission on Radiological Protection. ICRP Publication 26. International Commission on Radiological Protection. Pergamon Press. New York, New York. 1977.

ICRP 1975. Report of the Task Group on Reference Man, Report No. 23. International Commission on Radiological Protection. Elmsford, New York. 1975.

Israeli-Nelson 1992. Israeli, M. and C.B. Nelson. Distribution and Expected Time of Residence for U.S. Households. Risk Analysis 12, 65. 1992.

Jacobs 1996. Engineering Calculations for the Tank Waste Remediation System Environmental Impact Statement. Jacobs Engineering Group Inc. Kennewick, Washington. August 1995.

Kaplan et al. 1994. Kaplan, D.I., R.J. Serne, and M.G. Piepho. Geochemical Factors Affecting Radionuclide Transport Through Near and Far Fields at a Low-Level Waste Disposal Site. Pacific Northwest National Laboratory. Richland, Washington. December 1994.

Kennedy-Strenge 1992. Kennedy, W.E. and D.L. Strenge. Residual Radioactive Contamination From Decommissioning--Technical Basis for Translating Contamination Levels to Annual Total Effective Dose Equivalent. Pacific Northwest National Laboratory. Richland, Washington. 1992.

Kincaid et al. 1995. Kincaid, C.T., J.W. Shade, G.A. Whyatt, M.G. Piepho, K. Rhoads, J.A. Voogd, J.H. Westsik, Jr., M.D. Freshley, K.A. Blanchard, and B.G. Lauzon. Performance Assessment of Grouted Double-Shell Tank Waste Disposal at Hanford. WHC-SD-WM-EE-004, Rev. 1. Westinghouse Hanford Company. Richland, Washington. May 1995.

Kochner 1981. Dose-Rate Conversion Factors for External Exposure to Photons and Electrons. NUREG/CR-1918, prepared by Oak Ridge National Laboratory for the U.S. Nuclear Regulatory Commission. Washington, D.C. 1981.

Layton 1993. Layton, D.W. Metabolically Consistent Breathing Rates for Use in Dose Assessment. Health Phys. 64(1), 23-26. 1993.

Napier et al. 1996. Napier, B.A., B.L. Harper, N.K. Lane, D.L. Strenge, and R.B. Spivey. Human Scenarios for the Screening Assessment, Columbia River Comprehensive Impact Assessment. DOE/RL-96-16-a, Rev. 0. U.S. Department of Energy. Richland, Washington. March 1996.

Napier et al. 1988. Napier, B.A., R.E. Peloquin, D.L. Strenge, and J.V. Ramsdall. GENII - The Hanford Environmental Radiation Dosimetry Software System. PNL 6584. Pacific Northwest National Laboratory. Richland, Washington. 1988.

National Research Council 1995. Technical Bases for Yucca Mountain Standards. National Research Council. National Academy Press. Washington, D.C. 1995.

NCRP 1995. Principles and Application of Collective Dose in Radiation Protection. NCRP Report No. 121. National Council on Radiation Protection and Measurements. Bethesda, Maryland. 1995.

NCRP 1991. Effects of Ionizing Radiation on Aquatic Organisms. NCRP Report No. 109. National Council on Radiation Protection. Bethesda, Maryland. 1991.

Neuhauser-Kanipe 1992. Neuhauser, K.S. and F.L. Kanipe. RADTRAN 4: Volume 3 - User Guide SAND89-2370. Sandia National Laboratories. Albuquerque, New Mexico. 1992.

NRC 1994. Branch Technical Position on Performance Assessment for Low-Level Waste Disposal Facilities (Draft). Low-Level Waste Management Branch. U.S. Nuclear Regulatory Commission. Washington D.C. January 1994.

NRC 1982. Atmospheric Dispersion Models for Potential Accident Consequences Assessment at Nuclear Power Plants. NUREG-1.145. U.S. Nuclear Regulatory Commission. Washington D.C. November 1982.

ORNL 1981. RSIC Data Laboratory Collection - DRALIST, Radioactive Decay Data for Application to Radiation Dosimetry and Radiological Assessments. DLC-80. Oak Ridge Laboratory. Oak Ridge, Tennessee. 1981.

PNL 1986. DITTY - A Computer Program for Calculating Population Dose Integrated Over Ten Thousand Years. PNL-4456. Pacific Northwest Laboratory. Richland, Washington. March 1986.

Rao et al. 1982. Rao, R.K., et al. Non-Radiological Impacts of Transporting Radioactive Material. SAND81-1703. Sandia National Laboratories. Albuquerque, New Mexico. 1982.

Rittman 1994. Rittman, P.D. Dose Estimates for the Solid Waste Performance Assessment. WHC-SD-WM-TI-616. Westinghouse Hanford Company. Richland, Washington. 1994.

Rosenberry-Burnmaster 1992. Rosenberry, A.M. and D.E. Burnmaster. Lognormal Distributions for Water Intake by Children and Adults. Risk Analysis 12, 53-63. 1992.

Serne-Wood 1990. Serne, R. J., and M. I. Wood. Hanford Waste-Form Release and Sediment Interaction: A Status Report with Rationale and Recommendations for Additional Studies. PNL-7927. Pacific Northwest National Laboratory. Richland, Washington. May 1990.

Shade et al. 1995. Shade, J.W., J.M. Conner, D.W. Hendrickson, W.J. Powell, and R.A. Watrous. Preliminary Low-Level Waste Feed Definition Guidance Low-Level Waste Pretreatment Interface. WHC-SD-WM-RD-052, Rev. 0. Westinghouse Hanford Company. February 1995.

Shire et al. 1995. Shire, P.R., W.L. Cowely, B.H. Gilbert, D.A. Smith, and G.L. Smith. Potential Accidents with Radiological and Toxicological Source Terms for Hanford Tank Waste Remediation System Environmental Impact Statement. WHC-SD-WM-ANAL-041, Rev. 0. Westinghouse Hanford Company. Richland, Washington. May 1995.

Smith 1994. Smith, R.L. Use of Monte Carlo Simulation for Human Exposure Assessment at a Superfund Site. Risk Analysis 14, 433-439. 1994.

Thompson et al. 1992. Thompson, K.M., D.E. Burnmaster, and E.A. Crouch. Monte Carlo Techniques for Quantitative Uncertainty Analysis in Public Health Risk Assessment. Risk Analysis 12 (1), 53-63. 1992.

USDL 1992. Employee Tenure and Occupational Mobility in the Early 1990's. U.S. Department of Labor, Bureau of Labor Statistics. USDL 92-386. Washington, D.C. 1992.

WHC 1995c. No Separations Data Package for the Tank Waste Remediation System Environmental Impact Statement. WHC-SD-WM-EV-103, Rev. 0. Westinghouse Hanford Company. Richland, Washington. July 1995.

WHC 1995j. Tri-Party Agreement Alternative Engineering Data Package for the Tank Waste Remediation System Environmental Impact Statement. WHC-SD-WM-EV-104, Rev. 0. Westinghouse Hanford Company. Richland, Washington. July 1995.

Wood et al. 1995. Wood, M.I., R.K. Khaleel, P.D. Rittman, A.H. Lu, S. Finfrock, R.J. Serne, and K.J. Cantrell. Performance Assessment for the Disposal of Low-Level Waste in the 200 West Area Burial Grounds. WHC-EP-0645. Westinghouse Hanford Company. Richland, Washington. June 1995.

WSDFM 1994. Annual Population Projections. Complied by the Tri-City Industrial Development Council. Kennewick, Washington. 1994.

WSDT 1993. Washington State Highway Accident Report 1993. Washington State Department of Transportation. Planning and Programming, Service Center Transportation Data Office. Olympia, Washington. 1993.

Wurstner-Devary 1993. Wurstner, S.K. and J.L. Devary. Hanford Site Ground-Water Model: Geographic Information System Linkages and Model Enhancements, FY 1993. PNL-8991. Pacific Northwest National Laboratory. Richland, Washington. December 1993.



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