Download - Evaluation and ranking of restoration strategies for radioactively contaminated sites

Journal of

Environmental Radioactivity 56 (2001) 33–50

Evaluation and ranking of restoration strategiesfor radioactively contaminated sites

Th. Zeevaerta,*, A. Bousherb, V. Brendlerc,P. Hedemann Jensend, S. Nordlindere

aSCK CEN, Boeretang 200, 2400 Mol, BelgiumbWestlakes Scientific Consulting, Moor Row, Cumbria CA24 3LN, UK

cForschungszentrum Rossendorf, Institut f .ur Radiochemie, 01314 Dresden, GermanydRisoe National Laboratory, Dpt. of Nuclear Safety Research, 4000 Roskilde, Denmark

eStudsvik Eco & Safety AB, 61182 Nyk .oping, Sweden

Received 28 February 2000; accepted 12 July 2000

Abstract

An international project, whose aim was the development of a transparent and robustmethod for evaluating and ranking restoration strategies for radioactively contaminated sites

(RESTRAT), was carried out under the Fourth Framework of the Nuclear Fission SafetyProgramme of the EU. The evaluation and ranking procedure used was based on theprinciples of justification and optimisation for radiation protection. A multi-attribute utility

analysis was applied to allow for the inclusion of radiological health effects, economic costsand social factors. Values of these attributes were converted into utility values by applyinglinear utility functions and weighting factors, derived from scaling constants and expertjudgement. The uncertainties and variabilities associated with these utility functions and

weighting factors were dealt with by a probabilistic approach which utilised a LatinHypercube Sampling technique. Potentially relevant restoration techniques were identified andtheir characteristics determined through a literature review. The methodology developed by

this project has been illustrated by application to representative examples of differentcategories of contaminated sites; a waste disposal site, a uranium tailing site and acontaminated freshwater river. # 2001 Elsevier Science Ltd. All rights reserved.

Keywords: Restoration; Radioactivity; Ranking; Evaluation; Optimisation

*Corresponding author. Tel.: +32-14-33-28-68; fax: +32-14-32-10-56.

E-mail address: [email protected] (T. Zeevaert).

0265-931X/01/$ - see front matter # 2001 Elsevier Science Ltd. All rights reserved.

PII: S 0 2 6 5 - 9 3 1 X ( 0 1 ) 0 0 0 4 6 - 7

1. Introduction

A number of nuclear facilities in Europe began operation in the 1950s and 1960sand, as a consequence, are now reaching the end of their life expectancy. The maintechnical part of the installations will be subject to a controlled decommissioning.However, the sites themselves may require restoration where the contamination hasbeen dispersed or where radioactive residues are contained by methods which may beunreliable for long-term storage.Restoration of such sites would appear necessary both for the sake of protecting

the public and for relieving otherwise costly control of the sites. However, clean-upby conventional techniques can be very expensive and may, therefore, not offer theoptimal solution based on cost-benefit evaluations. The US experience at formermilitary sites shows that the application of alternative techniques, e.g., in-siturestoration, is hampered by the lack of transparent risk assessments in consideringthe exposure of present and future populations and of restoration workers. Anothershortcoming is the lack of relevant data from on-site experiences.An international project partly funded by the EU under the Fourth Framework of

the Nuclear Fission Safety Programme has been addressing these problems. In thisproject, a transparent, generic decision-aiding methodology has been established,which is capable of evaluating and ranking restoration strategies for radioactivelycontaminated sites and their close surroundings (RESTRAT). The study has nowbeen concluded and a manual (Zeevaert, Bousher, Brendler, Nordlinder, &Hedemann, 1999a) has been produced to explain the methodology and to apply itto typical example cases. A summary of the progress made at the mid-term wasreported by Jackson et al. (1999). The final report for this project is also available(Zeevaert, Bousher, Brendler, Nordlinder, & Hedemann, 1999b).

2. Method

The method proposed for the ranking of restoration options is based on theradiation protection principles of justification and optimisation, as recommended inICRP 60 (International Commission on Radiological Protection, 1991). In ICRP 60recommendations, distinction is made between practices and interventions. Thisdistinction may not always be clear for clean-up of radioactively contaminated land.However, in cases where there is existing exposure of a population from sitescontaminated with the residues of past, or old, practices or work activities, theprinciples of protection for intervention are applicable, and dose limits do not apply.According to the justification principle, the intervention or restoration should domore good than harm, which means that the net benefit (benefit of the reduction inradiation detriment less the harm and costs of the restoration) should be positive.According to the optimisation principle, among the justified restoration options, thestrategy with the highest net benefit should be selected.Quantitative decision-aiding techniques for radiological optimisation analysis

purposes are available. The principal ones are described in detail in ICRP 55

T. Zeevaert et al. / J. Environ. Radioactivity 56 (2001) 33–5034

(International Commission on Radiological Protection, 1989) and by Stokell, Croft,Lochard, and Lombard (1991).Decisions in site restoration require multiple criteria to be taken into account. The

major attributes, to be considered, include:

* Health attributes;* Economic attributes;* Social attributes.

Social factors are difficult to quantify. Therefore, a multi-attribute utility (MAU)analysis is the obvious technique to be applied for optimisation. In order to carry outthe evaluations in this way a hierarchy of attributes must be set up. Themajor attributes are divided into sub-attributes according to the scheme as shownin Fig. 1.The values for the attributes of each option are determined and converted into

utility values through the use of utility functions. Each attribute is assigned aweighting factor, expressing the relative importance of that attribute with respect tothe other attributes of the same group. Each alternative strategy can then be assigneda score which is equal to the sum of the products of utility values and weightingfactors for all its attributes. The option with the highest score is considered to beoptimal.Utility functions can be linear, concave or convex. They can either be of an

increasing type or of a decreasing type. Risk-neutral, risk-averse and risk-proneutility functions of the decreasing type are shown in Fig. 2.In this study, risk-neutral, linear utility functions are applied. These are expressed

as

UðxÞ ¼ 100 1þxmin � x

xmax � xmin

� �;

where (xmin; xmax) is the value range of the attribute considered.The restoration option which does best for a particular attribute is assigned a

utility value of 100, and the option which does worst a utility value of zero. Otheralternatives are assigned intermediate utility values according to the utility functionshown above.Determination of the weighting factors of the attributes is a subjective task; each

decision-maker may well come up with a different set of weighting factors.Therefore, a simple scaling method has been proposed to establish conversionconstants between the weighting factors for attributes of the same hierarchy level.For the major attributes, health attributes, economic costs and social factors, these

constants can be expressed as

weconomic

whealth¼ C1;

wsocial

whealth¼ C2

and the sum of the weighting factors should be equal to one, i.e.

weconomic þ wsocial þ whealth ¼ 1:

T. Zeevaert et al. / J. Environ. Radioactivity 56 (2001) 33–50 35

This would determine the weighting factors as

whealth ¼1

1þ C1 þ C2; weconomic ¼

C1

1þ C1 þ C2; wsocial ¼

C2

1þ C1 þ C2:

The value of C1 can be determined as the ratio of the ranges of economic costs to theranges of collective doses, multiplied by the monetary value of the man. Sievert(taken here as 100,000 EUR man Sv�1) (Nordic Radiation Protection Authorities,1991).The ratio C2 is much more difficult to quantify. Intuitively, it would be expected to

be less than one and, for non-accidental situations such as restoration ofcontaminated sites with small exposures, significantly less than one. In this study avalue of 0.25 has been proposed.The weighting factors for the sub-attributes of a same group have been determined

in a similar manner to that described above. For sub-attributes, expressed in thesame units, conversion constants have been taken equal to the ratios of the ranges ofthe values of the sub-attributes. For the social sub-attributes, reassurance is given ahigher weight (5–7 times higher) than disturbance because of its more permanentnature. However, further research studies are needed before the weighting factors for

Fig. 1. Attibute hierarchy for restoration of a contaminated site.


social sub-attributes can be properly quantified. Further details may be found inHedemann Jensen (1999).

3. Assessment of attributes

3.1. Radiological health

The radiological impact was assessed in terms of effective doses to the public andto the restoration workers. Collective dose was considered as a measure for theradiological health detriment. For the public, the collective doses have beentruncated at 100 and 500 years, in accordance with international recommendations(Barraclough, Robb, Robinson, Smith, & Cooper, 1996; United Nations ScientificCommittee on the Effects of Atomic Radiation, 1982). The doses are calculated bothwith and without the restoration measures implemented, so that the doses avertedthrough those measures could be determined.Maximum annual individual doses to the critical group (before restoration) have

been assessed for the sake of comparison with the recommendations of ICRP(International Commission on Radiological Protection, 1998) and of IAEA(International Atomic Energy Agency, 1997) on the clean-up of contaminated land.For restoration workers, doses can be readily calculated from the contamination

levels at the site and the labour volumes required. Exposure will only take placethrough external irradiation and inhalation on the site.For the public, a more complicated impact assessment model is needed for

assessing the doses. Ingestion of contaminated food and water and exposure off-site(through use of contaminated water for irrigation purposes for instance) must alsobe taken into account. Therefore, a compartmental type of model has been applied.This is based on the BIOPATH model developed by Studsvik (Bergstr .om, Edlund,Evans, & R .ojder, 1982), which has been validated and verified in severalinternational studies such as PSACOIN (Klos et al., 1993). The compartmentalscheme applied has been adapted to each of the major categories of contaminatedsites considered. Fig. 3 shows its application to a contaminated fresh water river(Molse Nete).

Fig. 2. Examples of utility functions of the decreasing type : risk-neutral (linear), risk-averse and risk-

prone utility functions.


In the impact assessment model, two parts can be distinguished:

* the transport model (the proper compartmental part),* the exposure model.

The transport model describes the exchange or transfer of the contaminants(radionuclides) between biosphere compartments. Processes that are responsible forthose transfers can be identified. They may be caused by man, such as dredging ofsediment, irrigation, or they may be of a natural origin, such as water flow,advection, diffusion, sedimentation, bioturbation, etc. Mathematically, thesetransfers are expressed by a set of first-order differential equations with constantor time-varying transfer coefficients (rate constants, expressing the number ofturnovers per unit of time). The application of restoration techniques are modelledeither by adapting the transfer coefficient values for the processes that are influencedor, by adapting the value of the source term in the cases where sources are removed(with or without subsequent separation).The exposure model is the part of the assessment model, which converts

radionuclide (contaminant) concentrations, in the relevant biosphere media, intodose values to the exposed population. Exposure pathways to the population mustfirst be identified. They may include:

* external irradiation: on contaminated fields or river banks,* inhalation due to resuspension,* ingestion of contaminated drinking water,* ingestion of fish from contaminated surface water,* ingestion of food crops, contaminated through irrigation, or grown on soil

contaminated through application of amendments,

Fig. 3. Compartmental scheme for a freshwater river (Molse Nete).


* ingestion of milk, meat contaminated through the watering of cattle, or throughcattle grazing on contaminated pasture.

Uncertainty and sensitivity analyses were also carried out with respect tothe collective doses, using the PRISM program (Gardner, R .ojder, & Bergstr .om,1983). This is a general tool for addressing the uncertainties in any modelarising from the uncertainty or variability in parameter values. The uncertainty isevaluated by generating random parameter values applying a systematicLatin Hypercube sampling method, and executing the model for each set ofinput parameter values. The joint set of model parameters and results are thenstatistically evaluated by considering means, percentiles, standard deviations. Forthe sensitivity analysis, correlations between model parameters and model resultsare examined, using the simple Pearson and the Spearman rank correlationcoefficients.An important issue recognized in the RESTRAT project has been the influence of

physico-chemical phenomena, or processes, on the source term evolution and on themigration of radionuclides in the environment. Relevant physico-chemical phenom-ena have been identified from a literature review and the parameters, for describingthe processes in a quantitative way, have been determined.Distribution coefficients (Kd) play a very important role in this respect. In

common with most impact assessment models, the BIOPATH model also uses singleKd values taken from the literature. This concept is, however, too simplistic. Manydifferent basic physico-chemical phenomena (hydrolysis and complexations, redoxreactions, mineral precipitation and dissolution, adsorption and ion exchange)determine the Kd value and even small changes in the physico-chemical parameters,Eh, pH, concentrations, mineral composition, temperature, etc, can influence itsvalue. This assigns very large uncertainties to Kd values which constitute importantsources of uncertainty to the dose results.A better strategy than using single Kd values is to unfold the Kd into a parameter

vector; decomposing the Kd into its underlying basic processes. This introduces manynew parameters but these can be determined more easily and more precisely.An overview of geochemical speciation modelling software was elaborated in

order to find an appropriate model that can allow for an unfolding of the Kd and beintegrated into the risk assessment code. Two software packages have been selected:the EQ3/6 program (Wolery, 1992) and MINTEQA2 (Allison, Brown, & Nova-Gradac, 1991). These cover the whole range of chemical reactions in homogeneousaqueous solutions and have source codes which are readily available. The maindifferences between them are, that EQ3/6 is capable of dealing with kinetic rate laws,while MINTEQA2 incorporates surface complexation models. Because surfacecomplexation is considered to be the dominant process, and because its database ismore extensive than the one for kinetic parameters, MINTEQA2 has been appliedprimarily in this project.Software has been created to organize data input and transfer to the PRISM/

BIOPATH package and also to incorporate the speciation model into the riskassessment software. The manner of incorporation has been made flexible enough so


that substituting the present speciation modules by another program would require acomparatively small amount of effort.

3.2. Economic costs

Economic costs constitute one of the major attributes in the optimisation analysisfor the ranking of restoration options. Important cost categories include:

* pure restoration costs;* waste disposal costs;* survey and monitoring costs.

Pure restoration costs consist of two important components:

* capital costs, generally incurred once;* operation and maintenance cost, mainly including labour and consumable costs

and usually evaluated on an annual basis.

Cost values used in this study were derived from the unit cost data, collected froma literature survey. Values of capital costs of restoration techniques reported in theliterature may be widely applicable, however, labour and consumable costs are verysite-specific and may vary to a large extent and give rise to significant uncertainties.Waste disposal costs are very important when the disposal of large quantities of

contaminated material is necessary. Contaminated waste will arise from allrestoration options. However, the quantities and associated costs will be onlyimportant for cases where source removal is involved (with or without thesubsequent separation of contaminants). These costs were also derived from unitcost data collected from the literature. A distinction must be made between the lowerunit costs for bulk removal of sources, such as contaminated soil, and the higher unitcosts for the disposal of the residue that remains after separation. However, thelarger quantities of low-level waste without separation often give rise to higher costsfor disposal than the lower quantities of the residue after separation.Survey and monitoring costs are in general reduced after the restoration of a

contaminated site. However, the gain will not be directly proportional to averteddoses or fractions of activity removed from the site. Normally, it is also lower thanthe costs of restoration and/or waste disposal. Survey and monitoring costs cannotbe derived from literature data. They are very site-specific and have to be derivedfrom site-specific data at each example site.

3.3. Social factors

Social factors belong to a group of non-radiological protection factors which areconsidered in an optimisation analysis. Whereas radiological protection factors,such as economic costs and averted dose, are related to the level of radiologicalprotection achieved, non-radiological protection factors are defined as thosewhich are not. Social factors may include public perception of the hazard posedby the radiation at the site, anxiety caused by implementation of measures, losses


of income etc. Most of these factors are not easily quantifiable and will varymarkedly between countries. They also may have opposing influences on the choicesof intervention levels.Important social factors that have been considered in this study are:

* reassurance provided by the implementation of remedial measures;* disturbance caused by the implementation of measures.

In order to overcome the difficulties of quantifying these attributes, they have beenlinked, in this study, to quantifiable factors which underlie these attributes.Reassurance has been linked to the residual dose and fraction of activity remainingon the site after the remedial measure has been implemented; these were consideredto be factors which strongly influence reassurance. Disturbance has been linked tothe volume of waste to be transported to the waste disposal site; which is one of themain causes of this disturbance.For the purposes of this study, the values for reassurance assigned to the options

have been taken to be inversely proportional to the residual dose and the fraction ofthe activity remaining on the site. In addition, the values for disturbance assigned tothe options have been taken to be directly proportional to the volumes of wasteremoved from the site.

4. Characterisation of restoration techniques

A comprehensive literature review (187 literature sources) was undertaken toidentify and charactise potentially relevant restoration techniques. The techniquesconsidered by this study were those which had been reported as having beenapplied to remediate radionuclide contamination on medium-sized sites and whichhave been documented with adequate data to allow a comprehensive characteri-sation.The restoration technologies identified fell into four major categories:

* Removal of sources: excavation or elimination of contaminated soil, sediment orwater.

* Separation of contaminated fractions from less contaminated fractions.* Containment: providing barriers between contaminated and uncontaminated

medium.* Immobilisation: adding material or agents to the contaminated medium in order

to bind the contaminants.

These categories may be further divided into physical, chemical or biologicaltechniques, that can be carried out in-situ or ex-situ (Table 1).Characteristics, recognised to play a role in the methodology for ranking and

selecting the restoration techniques, were determined. These were:

* Applicability: the contaminants and media they are suited for, and the meansrequired for their application;


Table 1

Categories of restoration techniques for contaminated sites

Technology Performance indicator Cost (EUR/m�3) Workforce exposure

(man hm�3)

Removal of source (B) Decontamination factor Extraction Disposal and transport

Soil excavation 1–20 50–150 450–800 0.2–1

Physical separation (C) Decontamination

factor

Waste

reduction

Excavation &

separation

Disposal and transport

of residue

Soil washing (C1) 1–10 50–98% 200–650 2000–3000 0.25–1.5

Decontamination

factor

Separation from liquid

Filtration (C2) 2–>100 0.1–3.8 2000–3000 0.4–1.4

Chemical separation Excavation and

separation

Chemical solubilisation (D1) 1–20 180–820 2000–3000 1.2–3.5

Separation from liquid

Ion exchange (D2) 3–100(U), 20–100(Cs) 1.3–2.5 2000–3000 0.4–1.4

Biological separation

Biosorption (D3) 2.5–>100 1–3 2000–3000 0.4–1.4

Containment (E) Permeability (m s�1) Total (per m2 surface

area)

(per m2 surface

area)

Capping (E1+E2) 1� 10�12–1� 10�9 30–45 0.03–0.3

Subsurface barrier (E3+E4)

(a) slurry walls 1� 10�12–1� 10�8 510–710 0.06–0.4

(b) ground curtains 1� 10�12–1� 10�8 310–420 0.06–0.4

Immobilisation Mobility reduction factor Total

Cement-based solidification (F)

(a) ex-situ (F1) 5–25 75–300 0.25–1.5

(b) in-situ (F2) 5–25 50–310 0.06–0.4

Chemical immobilisation (G)

(a) ex-situ (G1) 5–50 110–570 0.25–1.5

(b) in-situ (G2) 5–50 60–420 0.06–0.4

T.Zeeva

ertetal./J.Enviro

n.Radioactivity

56(2001)33–50

42

* Performance: the effectiveness against contaminants, which may be expressed as:* a decontamination factor (removal of sources, separation) with

– a reduction factor in waste volumes (separation only);* a change in hydraulic permeability (containment);* a reduction of the contaminant mobility (immobilisation techniques);

* Costs: proper restoration costs (capital, operational and maintenance costs) andcosts of waste disposal.

Values for performance characteristics and unit values (per unit volume ofcontaminated medium or unit size area) of costs and exposure times of restorationworkers have been collected from the literature. The ranges of the values observedare also indicated in Table 1. These ranges were considered to represent theuncertainties of these characteristics for all example sites, applying triangular or log-triangular pdfs (probability density functions) with the same minimum andmaximum values for all sites. The choice of the values of the modes for each ofthe example sites, has been a matter of judgement, depending upon factors such asaccessibility of the site, nature of the contamination and local conditions. Additionaldetails can be found in Zeevaert and Bousher (1999).

5. Results and discussion

The ranking methodology for restoration options has been applied to some majorcategories of contaminated sites. This includes uranium mine tailings, represented bythe Ranstad tailing site (Sweden), low-level radioactive waste disposal sites,represented by the Drigg disposal site (United Kingdom), and contaminatedfreshwater rivers, represented by the Molse Nete river (Belgium).At Ranstad, industrial facilities for uranium mining and milling were in operation

between 1969 and 1984. In the mill tailing area, about 106m3 of tailings weredeposited, covering an area of 250 m2. Restoration has been carried out. Thisconsisted of covering the mill tailings area with a multi-layer system.The Drigg site has been used for the disposal of low-level radioactive waste since

1959. Disposals of radioactive waste into trenches at Drigg have taken place in thenorth-western part of the 120 km site. It is now operated by British Nuclear Fuel plc.(BNFL) for the shallow burial of solid waste. For the purposes of this study, the siteas it was prior to remediation of the trenches was used as the illustrative example.The Molse Nete is a small river (average flow rate 1m3 s�1 and average width 5m)

in the north eastern part of Belgium. Since 1956 controlled releases of low-levelradioactive effluents have been made into the river (through a waste treatmentfacility) by the nuclear activities in the region of Mol.The radiological impact (doses) for the various restoration options considered at

the example sites have been assessed, applying the characteristics of the site andliterature-based Kd values. Collective effective committed doses to the general public,truncated at 100 and 500 y, have been assessed Tables 2–4). They are the result ofvery conservative assumptions concerning actual and future exposures and are not


meant to be accurate dose assessments for the specific sites. They are only adoptedfor illustrative purposes.Annual individual effective committed doses over the first year, to the critical

group have also been calculated under the same conservative assumptions as thecollective doses. Critical groups considered in this study mainly consist of ‘‘self-sustaining’’ farmers or fishermen living in the contaminated area. The individualdoses to the critical group were calculated to amount to 0.4 and 0.6mSv/yr for theDrigg site and the Molse Nete river and to be an order of magnitude lower for theRanstad tailing site (only 238U intake).Uncertainties (5–95% confidence intervals) due to the parameter uncertainty have

been estimated for the collective doses. For the Molse Nete river and the Drigg site,

Table 2

Evaluation of attributes at the Molse Nete river

Restoration

strategy

Collective dose

to population

(manSv)

Collective

dose to

workers

(manSv)

Monetary costs of restoration

(kECU)

Fraction

of activity

left

on-site

Waste

volume

(m3)

100

(yr)

500

(yr)

Reme-

diation

Monito-

ring

Waste

disposal

A 16 51 0 0 3200 0 1 0

B 1.6 5.1 6.1� 10�4 3570 1000 19,580 0.1 26,520

C1 4.5 14 1.8� 10�3 12,870 2000 13,260 0.3 5300

D1 1.6 5.1 1.6� 10�3 13,970 2000 13,260 0.1 10,600

E1 negli. negli. 2.6� 10�3 4250 3200 0 1 0

F1 negli. negli. 6.7� 10�3 6220 3200 0 1 0

F2 negli. negli. 1.8� 10�3 5810 3200 0 1 0

G1 negli. negli. 6.7� 10�3 8340 3200 0 1 0

G2 negli. negli. 1.8� 10�3 5810 3200 0 1 0

Table 3

Evaluation of attributes at the Ranstad tailings site

Restoration

strategy

Collective dose

to population

(manSv)

Monetary costs

of restoration

(kECU)

Fraction of

activity left

on-site

Waste volume

(m3)

100 (yr) 500 (yr) Remediation Waste

disposal

A 0.59 24 0 0 1 0

C1 0.23 9.4 640,000 38,000 0.4 4.5� 105

D1 0.13 5.5 730,000 38,000 0.2 1.5� 105

E1 0.37 15 9500 0 1 0

E2 0.19 8.1 16,000 0 1 0

F2 0.051 1.8 23,000 0 1 0

G2 0.034 1.1 32,000 0 1 0


the 5th percentiles were situated 1–2 orders of magnitude lower than the mean, andthe 95th percentiles a factor of 3–5 higher than the mean, respectively. For theRanstad site, the uncertainties were very restricted (only 238U intake considered).

Table 4

Evaluation of attributes at the Drigg disposal site

Restoration

strategy

Collective dose

to population

(man Sv)

Collective dose

to workers

(manSv)

Monetary costs of restoration

(kECU)

Fraction of

activity left

on-site

Waste

volume

(m3)

100

(yr)

500

(yr)

Remedi-

ation

Moni-

toring

Waste

disposal

A 49 120 0 0 75,000 0 1 0

C2 0.93 3.3 1.5� 10�9 380,000 750 31,000 0.01 12,500

D1 9.9 33 1.7� 10�9 300,000 7500 100,000 0.1 41,000

D2 16 51 3.7� 10�10 1,000,000 15,000 31,000 0.2 12,500

D3 13 42 7.1� 10�10 1,300,000 7500 31,000 0.1 12,500

E1 0.43 1.9 5.5� 10�12 3500 75,000 0 1 0

E3 2.9 11 6.9� 10�10 6300 75,000 0 1 0

F1 4.2 10 2.8� 10�9 55,000 75,000 0 1 0

F2 4.2 10 1.4� 10�9 190,000 75,000 0 1 0

G1 2.9 7.2 1.9� 10�9 130,000 75,000 0 1 0

G2 2.9 7.2 9.4� 10�10 55,000 75,000 0 1 0

Table 5

Distribution coefficients from literature and from site-specific calculations (m3/kg)

Site and nuclide Literature data Site-specific data

Mean Low High Mean Log Mean Std of log

River Molse Nete60Co 20 5 100 0.41 �0.38 0.18239Pu 250 100 1000 17 1.23 0.12241Am 1000 100 2000 310 2.49 0.09

Drigg238U, drain 0.1 0.01 1 3.63 0.56 0.33238U, stream 10 1 100 17 1.23 0.48239Pu, drain 2 0.01 100 87 1.94 0.12239Pu, stream 100 1 600 240 2.38 0.19241Am, drain 6 0.001 50 26 1.42 0.30241Am, stream 100 1 600 32 1.49 0.26

Ranstad tailing, 238U

Tailing layer 0.015* 0.002 0.1 0.034 �1.47 0.35

Moraine layer 0.015* 0.002 0.1 0.29 �0.54 0.26

Limestone layer 0.015* 0.002 0.1 0.0023 �2.63 0.31

Storage pond 2 0.2 20 59 1.77 0.19

*One single parameter was used.


The influential parameters contributing most to the uncertainty were shown to be:

* distribution coefficients Kd in soil and sediment (especially for plutonium andamericium doses at all sites);

* soil-to-plant concentration factors (especially for root crops and tubers) for theMolse Nete river;

* concentration factors to fish, for the Ranstad site;* water flow rates, for the Drigg and Ranstad sites.

With MINTEQA2, site-specific values of the distribution coefficients have beencalculated for a number of compartments and for the major radionuclides of thespecific example cases. They are compared with the literature-based values in Table5. The uncertainty and sensitivity analysis carried out on the computed Kd valuesshowed uncertainty ranges that were considerably lower than those of the literaturevalues. The most sensitive parameter is in many cases the solid concentration,reflecting the uncertainty of the effective rock porosity. Additional details are givenby Brendler (1999).Collective doses over 100 y have been assessed with the calculated, site-specific Kd

values for the three example sites for the no restoration option and compared withthe doses, assessed with the literature-based Kd values in Fig. 4.The sensitivity analysis on the results with the site-specific Kd values shows a

considerable reduction in the contribution of the Kd values to the overall uncertaintyof the doses with respect to the results with the literature-based Kd values. For theDrigg site, the contribution of the Kd in the drain was reduced from 69% and 64% to3% and 15% respectively for 239Pu and 241Am. For the Ranstad site, thecontribution of the Kd in soil was reduced from 80% to 27% (238U). Additionalinformation may be found in Stiglund and Nordlinder (1999).

Fig. 4. Collective dose (man Sv) to the public at Molse Nete river (M), Drigg (D) and Ranstad tailing (R).


The economic costs were derived from the unit costs of the literature review,except for the monitoring costs, which were estimated on a site-specific basis.The ‘reassurance’ and ‘disturbance’ social factors were evaluated from the activity

left on-site and residual dose after the implementation of the restoration techniqueconcerned, and the volume of waste to be transported to the waste disposal, asexplained before.The restoration options considered in the example cases and the relevant data for

the evaluations of the attributes have been indicated in Tables 2–4. From these data,utility values for the attributes and weighting values of the attributes are derivedaccording to the procedure described above.Uncertainties were determined by applying the Latin Hypercube sampling

technique with a number of trials of 10,000. The weighting factors were sampledfrom a triangular distribution between 1.5�1 and 1.5 times the most probable valuegiven in Tables 2–4. Similarly, the utility values were determined from the utilityfunctions in which the values of the attributes were sampled from a triangulardistribution between 1.5�1 and 1.5 times the central values of the attributes. Negativecorrelation between collective doses and restoration costs was applied with acorrelation coefficient of �0.8.The overall scores of the restoration options, determined from the weighted sum

of utilities for each of the attributes considered, are shown in Figs. 5–7. The figureson the left-hand side give the results for the integration of the collective dose over100 years; the figures on the right-hand side, the results for the integration of thecollective dose over 500 years. For the Drigg site (Fig. 7) both results are similar. Theerror bars represent the confidence intervals between the 5th and 95th percentiles ofthe distribution of the total scores.For the Molse Nete river (integration of collective dose over 500 y) and for the

Drigg site, capping seems to be the optimal solution. For the Molse Nete river(integration of collective dose over 100 years) and for the Ranstad site, the no-restoration option seems to be the optimal one.However, these results are only valid for the best-estimate values of the scores.

When the uncertainty ranges are taken into account, there is no significant difference

Fig. 5. Total scores for restoration options at the Molse Nete river.


between the no-restoration, the containment and (most of) the immobilisationoptions. The results reflect the importance of the large economic costs, in particularthe costs for waste disposal, which cause the removal and separation techniques to benever the optimal solution.We have also to bear in mind that the results were obtained with subjective

estimations of the utilities and weighting factors of the social attributes, that theeconomic costs were largely derived from generic data and that the radiologicalhealth attributes have been based on very conservative assumptions.Comparison of the maximum annual dose to the critical group (before restoration)

with the IAEA criteria on contaminated land (International Atomic Energy Agency,1997) is shown in Table 6. This shows that the need for restoration varies from‘‘sometimes’’ (with constraint) or ‘‘rarely needed’’ (without constraint) for theRanstad site. to ‘‘almost always’’ (with constraint) or ‘‘usually needed’’ (withoutconstraint) for the Drigg site.

Fig. 6. Total scores for restoration options at the Ranstad tailings site.

Fig. 7. Total scores for restoration options at the Drigg disposal site.


6. Conclusions

A methodology for the ranking of restoration options for contaminated sites hasbeen established, based on the optimisation and justification principles ofradiological protection and taking into account radiological health, economic andsocial criteria. Its usefulness has been demonstrated through the application to someexamples of major categories of contaminated sites. For the radiological healthassessments, the importance of a rigorous, site-specific approach for the determina-tion of Kd has been shown, and of the assessment model coupled with a geochemicalmodel for this purpose.Social attributes have been determined in a subjective way and economic

attributes in a generic way. In fact, the intention of the study has not been to comeup with some ‘‘universal’’ results but to deliver a method which allows all attributesinfluencing the ranking of the restoration options to be included in a clear andsystematic manner, taking into account the uncertainty associated with theirevaluation.Such a method can be of use for all groups of stakeholders concerned in the

decision-aiding process with respect to the restoration of contaminated sites. Itallows the introduction of attributes and attribute values according to theirviewpoints and leads to results which will reflect their concerns.

Acknowledgements

Thanks are extended to the Commission of the European Community (NuclearFission Safety Programme) and to the partners to the project, SCKCEN (co-ordinating the work programme), the Institute of Radiochemistry (FZR), RisoeNational Laboratory and to British Nuclear Fuels plc (BNFL) and the SwedishNational Institute of Radiation Protection (SSI) for partly funding this project

Table 6

Summary of results

Site Compliance with IAEA criteria Optimised strategy

Molse Nete river Remediation usually needed (constraint)

or sometimes needed (no constraint)

‘No remediation’ (100 yr);

Capping soil and sediment

(500 yr);

Drigg Remediation almost always needed

(constraint) or usually needed (no constraint)

Capping

Ravenglass estuary Remediation almost always needed

(constraint) or usually needed (no constraint)

‘No remediation’

Ranstad tailing site Remediation sometimes needed

(constraint) or rarely needed (no constraint)


Lake Traneb.arssj .on Remediation sometimes needed

(constraint) or rarely needed (no constraint)



References

Allison, J. D., Brown, D. S., & Novo-Gradac, K. J. (1991). MINTEQA2/PRODEFA2, a geochemicalassessment model for environmental systems: Version 3.0 user’s manual. US Environmental ProtectionAgency, Environmental Research Laboratory, EPA/600/3-91/021.

Barraclough, I., Robb, J. D., Robinson, C. A., Smith, K. R., & Cooper, J. R. (1996). The use of estimatesof collective dose to the public. Journal of Radiology and Protection, 16(2), 73–80.

Bergstr .om, U., Edlund, O., Evans, S., & R .ojder, B. (1982). BIOPATH} A computer code for calculationof turnover of nuclides in the biosphere and resulting doses to man. Studsvik AB, STUDSVIK/NW-82/261, Nyk .oping, Sweden.

Brendler, V. (1999). Physico-chemical phenomena governing the behaviour of radioactive substances. site-specific characteristics. RESTRAT } TD 5.Forsschungszentrum Rossendorf, Dresden, Germany.

Gardner, R. H., R .ojder, B., & Bergstr .om, U. (1983). PRISM} A systematic method for determining theeffect of parameter uncertainty on model predictions. Studsvik AB, STUDSVIK/NW-83/555, Nyk .oping,Sweden.

Hedemann Jensen, P. (1999). Methodology for ranking restoration options. RESTRAT } TD 8.Ris�National Laboratory, Ris�-R-1121(EN), Roskilde, Denmark.

International Atomic Energy Agency (IAEA) (1997). Application of radiation protection principles to theclean-up of contaminated areas. International Atomic Energy Agency, IAEA – TECDOC – 987,Vienna, Austria.

International Commission on Radiological Protection (ICRP) (1991). 1990 Recommendations of theInternational Commission on Radiological Protection. International Commission on RadiologicalProtection, ICRP Publication 60, Oxford : Pergamon Press, Annals of ICRP, 21(1–3), 28 and 49–52.

International Commission on Radiological Protection (ICRP) (1989). Optimisation and decision-making inradiological protection. International Commission on Radiological Protection, ICRP Publication 55,Oxford : Pergamon Press, Annals of ICRP, 20 (1), 20–35.

International Commission on Radiological Protection (ICRP) (1998). Protection of the public in situationsof chronic exposure to radiation. International Commission on Radiological Protection, Draft reportof task group.

Jackson, D., Wragg, S., Bousher, A., Zeevaert, Th., Stiglund, Y., Brendler, V., Hedemann Jensen, P., &Nordlinder, S. (1999). Establishing a method for assessing and ranking restoration strategies forradioactively contaminated sites and their immediate surroundings. Nuclear Energy, 38(4), 223–231.

Klos, R., et al. (1993). PSACOIN level 1B intercomparison. An international code intercomparisonexercise on a hypothetical safety assessment case study for radioactive waste disposal system. OECD/NEA, Paris.

Nordic Radiation Protection Authorities. (1991). The monetary value of collective dose reduction (a-value).Statement from the meeting at Reykjavik, 14 June, 1991. Swedish Radiation Protection Institute,Str.alskyddsnytt 4/91, Stockholm, Sweden.

Stiglund, Y., & Nordlinder, S. (1999). Dose Assessment Model for use in Site Restoration. GeneralMethodology and Site-specific Aspects. RESTRAT } TD 6. Studsvik AB, STUDSVIK/ES-99/18,Nyk .oping, Sweden.

Stokell, P. J., Croft, J. R., Lochard, J., & Lombard, J. (1991). Alara. From theory towards practice.Commission of the European Communities, EUR 13796EN, Luxembourg.

United Nations Scientific Committee on the Effects of Atomic Radiation. Ionising radiation : sources andbiological effects. (1982). United Nations, UNSCEAR 1982 Report; New York.

Wolery, T. J. (1992). EQ3/6, a software package for the geochemical modelling of aqueous systems.Lawrence Livermore National Laboratory, UCRL-MA-110662Part I.

Zeevaert, Th. & Bousher, A. (1999). Restoration techniques: characteristics and performances. RESTRAT- TD 3+4. SCK �CEN, BLG-816, Mol, Belgium, or Westlakes S.C., 980132/01, Cumbria, UK

Zeevaert, Th., Bousher, A., Brendler, V., Nordlinder, S., & Hedemann Jensen, P. (1999a). RESTRATManual. RESTRAT: Restoration Strategies for radioactively contaminated sites and their closesurroundings. SCK �CEN, BLG-819, Mol, Belgium.

Zeevaert, Th., Bousher, A., Brendler, V., Nordlinder, S., & Hedemann Jensen, P. (1999b). RESTRATFinal Report. RESTRAT: Restoration Strategies for radioactively contaminated sites and their closesurroundings. SCK �CEN, BLG-822, Mol, Belgium.


Download - Evaluation and ranking of restoration strategies for radioactively contaminated sites

Top Related