New developments to support decision-making in contaminated inhabited areas following incidents involving a release of radioactivity to the environment

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Journal of Environmental Radioactivity 99 (2008) 439e454 www.elsevier.com/locate/jenvrad

New developments to support decision-making in contaminated inhabited areas following incidents involving a release of radioactivity to the environment K.G. Andersson a,*, J. Brown b, K. Mortimer b, J.A. Jones b, T. Charnock b, S. Thykier-Nielsen a, J.C. Kaiser c, G. Proehl c, S.P. Nielsen a a

Risoe National Laboratory, P.O. Box 49, DK-4000 Roskilde, Denmark b Health Protection Agency, Chilton, Didcot OX11 0RQ, UK c GSF e National Research Center for Environment and Health, 85764 Neuherberg, Germany Received 15 October 2006; received in revised form 6 July 2007; accepted 9 August 2007 Available online 29 September 2007

Abstract The Chernobyl accident demonstrated that releases from nuclear installations can lead to significant contamination of large inhabited areas. A new generic European decision support handbook has been produced on the basis of lessons learned on the management of contaminated inhabited areas. The handbook comprises detailed descriptions of 59 countermeasures in a standardised datasheet format, which facilitates a comparison of features. It also contains guidance in the form of decision flowcharts, tables, check lists and text to support identification of optimised solutions for managing the recovery of inhabited areas within a framework consistent with ICRP recommendations. A new comprehensive inhabited-area dose model is also being developed for implementation in the ARGOS and RODOS decision support systems. Shortcomings of previous models are demonstrated. Decision support modelling in relation to malicious dispersion of radioactive matter in inhabited areas is also discussed. Here, the implications of, e.g., particle sizes and dispersion altitude are highlighted. Ó 2007 Elsevier Ltd. All rights reserved. Keywords: Inhabited area; Contamination; Decision support; Dose model; Dispersion; Countermeasure; Nuclear accident; Optimisation; Decision-maker; Recovery

1. Introduction Prior to the Chernobyl accident on the 26th of April 1986, it was in general not considered likely that any plausible incident leading to airborne dispersion of radioactive contaminants would significantly affect inhabited areas. However, the importance of inhabited areas when looking at accident consequences was explored shortly after the Chernobyl accident in a workshop (Kelly, 1987), and it soon became apparent that external exposure to radionuclides deposited on surfaces in inhabited areas would give a major contribution to the dose received by the inhabitants of * Corresponding author. Tel.: þ45 4677 4173; fax: þ45 4677 5330. E-mail address: [email protected] (K.G. Andersson). 0265-931X/$ - see front matter Ó 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.jenvrad.2007.08.013

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the contaminated areas in the Former Soviet Union (Balonov, 1997). The available knowledge was at that time not adequate to enable proper estimation of the radiological impact that the accident would have in inhabited areas over the following decades. Information on countermeasures that might be considered for mitigation of the problems in the contaminated inhabited areas was very sparse and in most cases not directly applicable. The countermeasures that were introduced in the late 1980s in contaminated settlements in Russia and Ukraine were therefore largely selected on a ‘hit-and-miss’ basis (Anisimova et al., 1994), and the outcome of the implementation was generally poor, as important pitfalls were overlooked (Roed et al., 1998). The Chernobyl accident, however, also provided a unique opportunity to study a wide variety of countermeasures for inhabited areas and test them in situ, and the decision-making knowledge base was thus improved considerably. The concept of systematically describing countermeasure features in a datasheet format was introduced in connection with the ECP4 project supported by the European Commission (Roed et al., 1995; Andersson, 1996). Standardised datasheets capturing the key information required to evaluate options are useful in providing a clear and consistent overview of a wide range of options, aiding the decision-making process and ensuring that potentially important issues are not overlooked. They also outline the requirements (e.g., equipment, consumables, and number of skilled workers) that are needed to carry out the countermeasures. Consequently, for the most practicable options within a given area, the required resources can be secured prior to any contaminating incident. Over the years various ‘generations’ of countermeasure datasheets have emerged, and the level of detail in descriptions has increased substantially, e.g., to recognise the need for data representing more diverse conditions and to look at a wider range of radiological hazards. Justification and optimisation of countermeasure strategies cannot be based solely on a balancing of technical features like direct intervention costs against the averted dose, but other, not easily quantifiable, factors must also enter the decision-matrix. According to the ICRP (1999), potential advantages of intervention include ‘the consequent reassurance gained by the population and the decrease in anxiety created by the situation’, whereas ‘disadvantages include costs, harm and social disruption associated with it’. Such considerations were first incorporated in countermeasure datasheets in connection with the European STRATEGY project (Howard et al., 2005; Andersson et al., 2003; Eged et al., 2003), introducing viewpoints from experts on social, ethical and economical sciences, and also considering observed reactions of the public and other participants in connection with countermeasure trials in the Former Soviet Union. In the ongoing European EURANOS project, the STRATEGY countermeasure database has been further developed and the format modified, primarily to make it more suitable for describing countermeasure features of specific relevance to inhabited areas. Also countermeasures for the pre-release and early emergency phase of an incident have been introduced (Brown et al., 2005). Further, whereas previous databases for inhabited areas focused solely on radiocaesium contamination, as this would be likely to govern the long-term doses after a major nuclear power plant accident, the EURANOS countermeasure compendium takes into account a wide range of radionuclides and subsequent hazards that may be important also in connection with other types of contaminating incidents. The countermeasure compendium forms an integral part of a new generic European handbook (Brown et al., 2007) which has been produced with the aim of assisting decision-makers in forming countermeasure strategies in the recovery phase following a radiological incident leading to airborne dispersion of radioactive material over an inhabited area. Guidance is given in the form of decision flowcharts, tables, check lists and text. A key requirement in ensuring an optimal outcome for intervention is a good model for estimating radiation doses (Brown et al., 2006). A comprehensive model describing the various contributions to doses to members of the public living in an inhabited area is also being developed under the EURANOS project, primarily based on investigations made over the first two decades following the Chernobyl accident. The model, which is developed for incorporation in the European standard decision support systems ARGOS and RODOS, is currently designed for assessing the doses arising from a radiological incident where contamination of the inhabited area arises from a radioactive plume with origin outside the inhabited area, e.g., from a nuclear power plant. The overall aim of this paper is to introduce some of the main features of the new European decision support tool for inhabited areas consisting of the generic EURANOS handbook with its countermeasure compendium and the associated dose model. The different requirements of a dose model to estimate the radiological consequences of a malicious dispersion event (so-called ‘dirty bomb’) are discussed. 2. The EURANOS decision support handbook for inhabited areas This new generic handbook has been written to assist the management of contaminated inhabited areas following a radiological incident during the recovery phase, i.e. it does not cover the initial emergency phase of an incident where urgent

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measures are required to protect individuals from short-term, relatively high risks (Brown et al., 2007). It is intended to be used by European decision-makers to clarify requirements and facilitate preparedness planning prior to a contaminating incident, and to assist in the identification and implementation of optimised countermeasure strategies in the event of a contaminating incident. The target user group is primarily the persons and organisations responsible for decisions to select, prioritise, optimise, organise and supervise strategies for mitigation. However, it is important that these key participants ensure that selected relevant parts of the information are made available, discussed and explained to all groups who have an interest in the recovery of the affected area after an incident at different levels and phases of the intervention process. For example, this may be to enable countermeasures to be carried out in prescribed ways, and to strengthen the basis for public dialogue. The organisations involved will be highly dependent on the way radiological preparedness is organised in a particular country or region. In many member states of the European Union, the responsibility for decision-making, including decisions related to implementation of countermeasures, rests within organisations at a national level. However, for instance in Sweden, such decisions are taken on a regional basis by district councils, which may seek guidance and advice from central government bodies. As the background knowledge of the user group may vary considerably, the handbook is equipped with separate text sections explaining general radiation protection principles and criteria, to clarify objectives. The scope of the EURANOS handbook is wider than an earlier handbook that was produced in Sweden (Andersson and Johnsson, 1999) and is consistent with a recently developed handbook in the UK (HPA-RPD, 2005). It contains information on a wide range of hazards that could be found after a radiological incident, considers how these contribute to doses and provides much supporting information on the issues to be considered and the types of assessment that will need to be carried out. Also, the EURANOS handbook is a generic European tool, taking into account essentially all the different countermeasures that might under some circumstances be recommended for some part of Europe. Since the generic handbook applies to the whole of Europe, its use may, to some extent, make decision-making across Europe more consistent, thus reducing the risk of making inconsistent or apparently conflicting decisions (particularly in border areas), which could be perceived as illogical and might possibly have a disruptive effect on society. Nevertheless, prior to its use in any specific community, the generic handbook will need to undergo a ‘customisation’ process, to extract and adapt the information of use to the particular country/area, as for instance not all countermeasures and waste management options will be relevant, practicable, acceptable and legal. Also some optimisation elements may well need modification for local contextualisation. An annex to the handbook gives information and guidance that may be useful in connection with ‘customisation’ of the material for a specific country or region. The first ‘prototype’ version of the EURANOS handbook has been developed jointly by HPA (UK) and Risoe (Denmark). It has been evaluated in ‘stakeholder’ networks consisting of key players in the decision-making process in Finland, France, Germany and the Slovak Republic, to determine its suitability from different perspectives in Europe, with respect to scope, format and content. On the basis of the received comments and suggestions, the handbook has been revised in an interactive process between the originators and the ‘stakeholder’ networks. It must be stressed that it is not the aim of the handbook to suggest a rigid framework for decision-making. Clearly, a number of politically driven factors that cannot be quantified on a generic scale will need to enter the decision-matrix in the event of any incident. These may comprise the value assigned to a unit of saved dose, and the impact of a countermeasure on personal or societal values, including the value of changes in the psychological well-being of affected people. However, such issues are very site-specific and need to be picked up in the customisation process for a particular area. This process will also determine the exact roles of the various local participants in the response process, and their routes of communication. Although the handbook does not explicitly address the early emergency phase of an incident, where urgent countermeasures may be introduced to protect people against comparatively high risks posed over short time, such countermeasures are described in the datasheet compendium (see Section 2.1). This is because their implementation could impinge on the choices of methods to reduce problems encountered in the medium and long-term (recovery) phases. A pdf-based interactive version of the handbook is being produced. In parallel, a generic European handbook for the management of contaminated food production systems is also being developed under the EURANOS project (Nisbet et al., 2006). Some of the main features of the handbook for inhabited areas are outlined below. 2.1. Countermeasure datasheets The datasheet template used to describe each countermeasure comprises a series of items that need consideration by decision-makers in evaluating the various countermeasure options. These items are grouped in the datasheet template under the following headings:

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Objectives of countermeasure e definition of the primary aim and other benefits. Countermeasure description e a brief description of how the countermeasure option works. Target e definition of the type of area or surface on which the countermeasure is to be implemented. Targeted radionuclides e some countermeasures only have significant effect on problems posed by specific radionuclides or types of hazard. Scale of application e indications of the size of the area for which it would be practicable and recommendable to implement the countermeasure. Timing of implementation e some countermeasures would only be effective or practicable if implemented within a limited time frame. Constraints on implementation e restrictions on use of the method may be of a technical, environmental or legal nature. Effectiveness e includes reduction in contamination level on target surface, reduction in dose rate contribution from target surface, reduction in resuspension, additional doses to implementers, and technical and social factors influencing the countermeasure effectiveness. Some indications of likely reduction in doses to members of the public are also given where possible. Requirements e information on the equipment, utilities, infrastructure, consumables, worker skills and safety precautions required to carry out the method. Waste e amount and type of waste (if any) produced by the countermeasure option per unit of area. Intervention costs e indications of the costs of the various requirements, including worker time, and indications of factors influencing the costs. Side effects/impact e other environmental or social impacts of implementation. Practical experience e some procedures have only been tested on a limited scale, whereas others are well established and documented. Key references e the key publications describing the countermeasure.

The 59 countermeasures listed in Table 1 are described in this standardised format. The techniques are here grouped according to time phase and target. As the countermeasures are relevant for, e.g., different time phases, target/area types, seasons and weather conditions, a number of these options may need to be considered as part of any preparedness planning, although some countermeasures can be seen as each other’s direct alternatives. For instance, in relation to public acceptability it is important to distinguish between ‘removal’ options that clean the surface of contaminants and ‘shielding’ options that may have equally good dose reductive effect, but leave the contamination in the area (e.g., buried under a shielding layer), often severely complicating future removal. Removal on the other hand implies waste management, which can be expensive and problematic. Decision trees have been provided in the handbook to assist in this selection (see Section 2.4). In addition to the described countermeasures, a number of other methods have, over the years, been suggested for management of contaminated inhabited areas. These have been omitted, since they are considered unrealistic, ineffective, insufficiently trialled or otherwise unsuitable for implementation within an inhabited area. It should always be kept in mind that it is a valid alternative to do nothing to actively improve the situation. Indeed the various other options should always be evaluated against this alternative. However, if it is considered not to introduce countermeasures, it should be recognised that there will still be a need to establish that the choice is justified, and thorough communication with the affected community will in any case be required to avoid social disruption. This option will also need to be supported by an agreed monitoring programme. Potential advantages and disadvantages of not implementing any countermeasures are described in the handbook. A number of the more simple countermeasures that do not require any specific experience to implement (e.g., lawn mowing, and digging) are considered potentially suitable for implementation by affected inhabitants themselves. This could for instance be beneficial in introducing an extra labour force in situations where large areas need to be treated over short time. The involvement of affected persons in actions to improve their own situation can be psychologically important and gives a better feeling of control of the situation, which also prevents undue anxiety. It should always be considered that people carrying out such ‘self-help’ options may be unfamiliar with the type of work, and all possible arrangements should be made to ensure that implementation does not lead to accidents or other harm. Also, people may not physically be fit for the scale of the work required. ‘Self-help’ countermeasures need to be conducted on a voluntary basis and careful and detailed communication with these individuals would be required, as some of the countermeasures could have irreversible negative outcomes if implemented wrongly.

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Table 1 List of countermeasures described in EURANOS inhabited areas handbook datasheets Pre-release and emergency phase countermeasures

Indoor surfaces of buildings

Sheltering Evacuation Stable iodine tablets

Vacuum cleaning Washing Other cleaning methods (scrubbing, shampoo, steam cleaning, etc.)

Wearing simple masks for respiratory protection Closing windows, doors and air ducts and controlling air exchange

Surface removal, e.g., paint, wallpaper, carpets, etc. Removal of furniture, soft furnishings and other objects

Using vacuum cleaners as air cleaners

Aggressive cleaning of indoor contaminated surfaces

Covering, storing or sealing personal/precious objects Recovery phase countermeasures: restrict access Temporary relocation from residential areas Permanent relocation from residential areas Prohibit access by public to non-residential areas Restrict access by workforce (time or personnel) to non-residential areas Recovery phase countermeasures: buildings (public, industrial and commercial buildings as well as residential homes)

Precious objects and personal items Storage, shielding/covering, gentle cleaning Recovery phase countermeasures: roads and paved areas (and other hard outdoor surfaces)

Additional options for gardens/small open spaces Rotovating (mechanical digging) Manual digging Cover grassed and soil surfaces (e.g., with asphalt) Triple digging Additional options for large open spaces (parks, countryside, etc.) Ploughing Deep ploughing Skim and burial ploughing Recovery phase countermeasures: all outside areas

Fire hosing

Peelable coatings

Vacuum sweeping

Snow removal

High pressure hosing

Recovery phase countermeasures: trees and shrubs

Surface removal (road planning) and replacement

Collection of leaves

Demolish buildings

Turning paving slabs

Tree and shrub pruning/removal

Fire hosing

Tie-down (fixing contamination to the surface)

Roof brushing

Recovery phase countermeasures: specialised surfaces (particularly metals)

Recovery phase countermeasures: soil and grassed areas

Sandblasting (walls)

Grass cutting

High pressure hosing (walls and roofs)

Plant and shrub removal

Roof cleaning with pressurised hot water Roof replacement

Turf harvesting Top soil and turf removal (mechanical)

Treatment of walls with ammonium nitrate

Top soil and turf removal (manual)

Mechanical abrasion of wooden walls

Cover with clean soil

Tie-down (fixing contamination to the surface)

Tie-down (fixing contamination to the surface)

Ultrasound treatment with chemical decontamination Cleaning of contaminated ventilation systems Filter removal Chemical cleaning of metal surfaces Chemical cleaning of plastic and coated surfaces Application of detachable polymer paste on metal surfaces Electrochemical cleaning of metal surfaces

A section of the handbook deals with the protection of workers implementing countermeasures, both in relation to radiological and other types of hazards, and outlining international recommendations on this topic. It should be recognised that skilled workers (e.g., plough or bulldozer operators) are not, by default, familiar with the specific objectives of implementation in contaminated areas and should also be carefully supervised.

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2.2. Waste management methods The contaminated waste generated by some of the described countermeasures needs to be managed in a safe, yet cost-effective way. Any decision to undertake clean-up that generates contaminated waste should be supported by an assessment of the impact that the generated waste will have on the public, workers and the environment. As outlined in the handbook, questions decision-makers should ask themselves in this context include:          

Is the management scheme acceptable to all involved parties? Can waste processing and/or disposal be carried out locally to minimise transport costs? Is local geology/topography appropriate for the waste management option being considered? Are required working materials available? Are required transport vehicles and routes available? Is the required monitoring equipment available? Are workers with required skills available? Are workers adequately protected? Does the management scheme provide adequate safety to the population? Does the management scheme impose restrictions on future land/property use?

The waste can originate from many different types of operations and may be solid and/or liquid and contain a variety of different types of substances. Sections in the handbook give recommendations on processes to treat or minimise contaminated wastes as well as the types of disposal options that should be considered. It is not appropriate for the handbook to recommend or specify disposal options as these will be specific to individual countries and their legislation. Fig. 1 shows a decision flowchart from the handbook for the overall selection of countermeasure waste management schemes. The handbook also contains sections dealing with the management of contaminated refuse and goods and the management of contaminated water arising from the incident (rainwater and run-off water as well as that from decontamination). 2.3. Social and ethical considerations Considerations of social and ethical nature can be crucial elements in the establishment of an acceptable and optimised countermeasure strategy. These issues are dealt within the handbook in a generic way as it is recognised that these factors will vary across countries in Europe and also may not become apparent until an incident occurs. Social issues may include the following:  The potential impact of a given countermeasure strategy in creating reassurance or anxiety in the local society is very important to evaluate and consider.  It is important to give high priority to problems related to critical facilities and infrastructure, which can be of vital societal importance.  Treatment of places frequently used by children (e.g., kindergartens, schools, and sandpits) is likely to be a high priority, reflecting public demand and the perception that children are at more risk.  Tourism and general perception of the area by people living outside it can be strongly affected by the way problems are dealt within the area. This could result in severe economical repercussions to the area. There will therefore be a great pressure to demonstrate that people can live and work in the area without severe constraints.  Specific radioactive substances may lead to enhanced fear. Also, incidents involving deliberate contamination may be perceived differently by the public, and this may affect the demands for clean-up.  It should be recognised that the political agenda at all levels may come to play an important role in the way problems are dealt with.  Different societal groups are likely to respond differently to the implementation of countermeasures (Salt et al., 1999), which emphasizes the importance of developing an effective strategy for public dialogue.  Due to adverse side effects of countermeasures it may be necessary to rank the importance of different societal aspects potentially affected by an intervention. Experiments to assess public opinion in this context have been

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Fig. 1. Suggested management schemes for different countermeasure wastes. It is assumed that the various types of wastes contain high levels of long-lived contaminants and thus require special management (illustration from the handbook).

conducted in different parts of Europe, where people were asked to rank the importance of factors like scenic landscape, animal welfare, water, disruption and heritage (Howard et al., 2005). A problem with such studies is however that the results are highly case-specific and cannot be expected to reflect the local public opinion in a real crisis situation.

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Previous work has identified a number of important general ethics questions (Oughton et al., 2003), which are listed in the handbook for reference only. No specific guidance is given on the management of ethical issues. Some examples of issues that may need to be considered are as follows:    

Is the distribution of costs and benefits equitable? Does the action carry a risk of serious environmental damage? Are any associated risks imposed or voluntary? Have the public and other stakeholders been involved in the decision-making process?

2.4. Decision framework An important part of the EURANOS handbook for inhabited areas is the framework of decision trees designed to guide the user through some of the different aspects of selecting a countermeasure strategy for a specific purpose. An example of a branch of such a decision tree from the handbook is given in Fig. 2 for the elimination of countermeasure options for contaminated building surfaces. The handbook is also equipped with illustrative worked examples of use of the entire handbook for different types of contaminating incidents, featuring choices made according to the decision trees to aid familiarisation and training. A further part provides support for planning and customisation of the generic handbook for use in different countries and by different users and guidance on how this process forms part of planning for response after a radiological incident. Information is given on the topics, issues and questions that need to be addressed as part of these planning and customisation activities. 3. Dose modelling for countermeasure decision support Although the EURANOS handbook for inhabited areas contains a system of tables for crude estimation of doses, it is stressed that this is only intended to give the user an approximate idea of the levels of dose that would be received after a radiological incident affecting inhabited areas for defining the scope of the likely scale of countermeasures needed. To get a better idea of the likely doses that could be received in a particular inhabited area, more detailed and accurate estimates are required. The ARGOS and RODOS decision support systems are intended to assist decision-makers in planning remediation strategies after contaminating incidents and contain models for estimating doses in inhabited areas. It should be recognised, however, that this type of model should not be used in isolation and should be flexible enough to make use of monitoring data as they become available. To facilitate the support provided by RODOS and ARGOS in this area, a software tool is being developed within EURANOS. This so-called Inhabited Areas Monitoring Module (IAMM) uses the wealth of monitoring data, which is gathered immediately after an accident, to produce high-resolution maps of the surface contamination in densely populated areas. One such map would define an initial condition as the starting point for a dose calculation (Kaiser et al., 2006). It should be noted that there are some shortcomings in the models that have been used to estimate external doses in the past, including those used in RODOS and ARGOS. Some key examples of these are as follows:  In for instance RODOS, external dose rate is calculated by multiplying an estimate of the external dose rate at a given height above an open, plane reference soil surface by a ‘location factor’ (relationship between a likely ‘average’ dose rate received by people in the area and the dose rate at the reference location). The ‘location factors’ used are time-invariant. This means that changes to dose rate with time are only considered through allowing for the downward migration of the radioactive matter in soil. In reality, the natural weathering and migration of radioactive matter on different surfaces vary widely, as the governing processes are specific to the different surfaces. Dose estimates made with models ignoring this could in some cases be in error by an order of magnitude or more.  Another frequent problem in previous approaches is that the models do not distinguish between different contaminant aerosol sizes. The Chernobyl accident demonstrated that the radionuclides transported far from the power plant site could be divided into two groups: a ‘volatile’ group of condensation particles with an AMAD (Activity Median Aerodynamic Diameter) of typically slightly less than 1 mm, and a ‘refractory’ group

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Fig. 2. Branch of decision tree to aid option elimination for buildings (illustration from the handbook).

with an AMAD of the order of 4 mm. Deposition velocities of these two groups of aerosols on surfaces in inhabited areas differ widely (Roed, 1990; Roed, 1987; Schwartz, 1986).  The data and concept behind previous dose models for inhabited areas date back to the early years after the Chernobyl accident, when little knowledge was available on the long-term behaviour of contaminants on the

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different surfaces. Later measurements have demonstrated that both the equations and parameter values used are inadequate. Long-term processes have often been shown to be more complex than anticipated from early assessments. An example is illustrated in Fig. 3, which shows the results of measurements made on asbestos roof sheets exposed to wind and weather for years after having been contaminated by the Chernobyl accident. The curve shows the predicted decline in contamination level on the surface, by simple extrapolation (halflife of w2.3 years) from the values measured over the first two years (Andersson et al., 1995). However, when the contamination level on the roof sheets was reassessed after more than 14 years, the data point to the very right in the figure was obtained. All the data points represent average values of a large series of measurements on individual sheets from the same roof, and since these measurements showed very little variation (within about 10%), uncertainties cannot explain the position of the latest point. Actually, the rather slow longterm decline, which was also observed for other roofing materials (Andersson et al., 2002), is not surprising, since it is known that most urban construction materials contain certain minerals that retain caesium and over some years fix it very strongly (Andersson et al., 2002; De Preter, 1990; Shrivastava and Shrivastava, 1998; Ma et al., 1996). It is clear that a long-term external dose estimate over a period of 70 years, based on the curve shown in Fig. 3 would be very far off. A new model has now been developed to address these shortcomings and is described below. 3.1. The EURANOS dose model for inhabited areas Recent detailed calculations of doses received over the first two decades after a nuclear power plant accident have demonstrated that a number of different contributions to dose in inhabited areas may be significant and important to consider (Andersson and Roed, 2006). Excluding doses from ingestion, as much or all of the food is likely to have been produced elsewhere, these may include external doses from contamination deposited on soil/grassed areas, trees and other vegetation, paved horizontal surfaces, outdoor building surfaces (external walls, roofs), and indoor building surfaces, as well as doses from inhalation of contaminants. Contrary to previous models, the EURANOS dose assessment tool, ERMIN (EuRopean Model for INhabited areas) (Jones et al., 2006), is capable of modelling all these different types of dose contributions in detail on the basis of state-of-the-art knowledge. ERMIN focuses on doses received in the intermediate to late phase of an incident, thus omitting dose contributions received entirely during the plume passage or over the following few days.

Fig. 3. Measured decline in 137Cs contamination level (relative to initial 137Cs contamination level on a grassed reference surface) on an asbestos sheet roof contaminated by the Chernobyl accident (data points). The curve shows a simple extrapolation based on the first six measurement points.

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Essentially, the modelling of external dose requires knowledge of the initial contamination level, subsequent contaminant migration due to natural or ‘everyday’ processes, conversion factors from surface contamination level to dose rate contribution at given representative locations in different types of environment, and an estimate of the likely fractions of time spent by people in the various locations. In ERMIN, the initial contamination level on the various surfaces is expressed relative to the level on a recently mown (shortly cut) grassed reference surface. As mentioned above, the deposition velocity of particles, and thereby the initial contamination level on a surface, will depend on the aerosol size. ERMIN therefore groups potentially important particulate radionuclides in two aerosol size categories, according to the likely processes of aerosol formation. Also the deposition of elemental iodine is covered, due to its high deposition velocity (e.g., compared with methyl iodide) to the different surfaces. For each of the two aerosol groups as well as for elemental iodine gas, ERMIN is equipped with a data library that, on the basis of measurements made after the Chernobyl accident and other experimental work, provides factors representing the likely initial contamination on the different types of outdoor surface relative to that on the grassed reference surface. Factors are given for three different weather categories at the time of deposition: dry deposition, deposition in heavy rain and deposition with light rain. Factors for deposition in snow and dry deposition onto a snow covered area have been identified, but are currently not implemented in ERMIN. If outdoor ground level concentrations of contaminants in air are not depleted by precipitation, indoor contamination can also be significant. It is somewhat more complex to relate the contamination level on an indoor surface to that on the outdoor reference surface, as it depends on dwelling parameters such as the size, construction and furnishings of the building. If Io is the time-integrated outdoor air concentration over the total period of elevated outdoor air concentrations, the corresponding time-integrated indoor air concentration, Ii, is given by (Roed and Cannell, 1987) Ii ¼ Io f lv =ðlv þ ld Þ;

ð1Þ

where f is the dwelling filtering factor, lv is the rate coefficient of ventilation (assumed to be time-invariant), and ld is the rate coefficient of deposition. If V is the total volume of a room, the total amount of deposited contaminants in the room would be equal to IildV. Most of this contamination would be likely to deposit on the floor and other horizontal surfaces (Lange, 1995). The floor area would not be likely to differ greatly from the total horizontal surface area, A, in the room. The average deposition, Di, per unit area in the room can thus be found as Di ¼ Ii ld V=AwIi ld AH=A ¼ Ii ld H;

ð2Þ

where H is the height of the room. Inserting Eq. (1) into Eq. (2) gives: Di ¼ Io f Hld lv =ðlv þ ld Þ:

ð3Þ

On the outdoor reference surface, the dry deposition per unit area, Dro, will be Iovrd, where vrd is the deposition velocity to the reference surface. Together with Eq. (3) this gives:
Di =Dro ¼ 1=vrd f Hld lv =ðlv þ ld Þ: ð4Þ This model is not explicitly implemented in ERMIN; rather the indoor ratios are precalculated using the model and are held in the data library. ERMIN contains estimates of the likely statistical distributions of the parameters in Eq. (4), based on values recorded in different regions of Europe (e.g., Roed and Cannell, 1987; Roed, 1990; Hiemstra et al., 1997; Malanca, 1993; Lange, 1995). It should, however, be noted that they are currently not used. The redistribution of the contaminants deposited in the environment, due to ‘naturally’ occurring processes, is represented in ERMIN for many of the surfaces by sets of empirical equations based on a review of time-series observations (Jones et al., 2006). For instance, the average reduction with time, t, in contamination level, C(t), on paved areas has been found to be adequately expressed by the following equation (Andersson and Roed, 2006):       ln 2 ln 2 ln 2 CðtÞ ¼ Cð0Þexp  t þ 0:3 exp  t ; t 0:7 exp  T1=2 120 days 3 years

ð5Þ

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where T1/2 is the physical half-life of the radionuclide. It should be stressed that a very large part of the information available for parameterisation, both for this and for other surfaces in the inhabited area, comes from studies of the behaviour of radiocaesium, which would also be likely to be the main contaminant governing the various total time-integrated external dose contributions received in an inhabited environment contaminated after a major nuclear power plant accident. Over the earliest few years after the Chernobyl accident, the migration of other radionuclides has also been observed to some extent, and here, differences in retention rates of different radionuclides were not found to be very large (Roed and Cannell, 1987; Roed, 1990). On some surfaces, this may reflect the attachment of the very small initial contaminant particles originating from a power plant accident to dust particles in the environment (Andersson, 1991), which would be likely to be weathered away at a constant rate. Due to the presence in many construction materials of minerals capable of selectively and efficiently retaining radiocaesium, it would in the long term generally be expected to be more efficiently bound to surfaces in the inhabited environment than would other contaminants. This would make long-term dose estimates for other radionuclides somewhat conservative, if based on the same migration data. The vertical migration of contaminants in soil is described in ERMIN by a one-dimensional, convectiveedispersive, local equilibrium, mass transport model, as suggested by Bunzl et al. (2000). This gives the contaminant concentration as a function of depth and time, thus facilitating multiplication at different times of contamination level values at different depths by appropriate dose rate conversion factors. The decisive parameters in the convectiveedispersive model are Ds and vs, which are defined as, respectively, Ds ¼ D=ð1 þ Kd ðr=3ÞÞ and vs ¼ vw =ð1 þ Kd ðr=3ÞÞ, where D is the dispersion coefficient, vw is the mean pore water velocity, Kd is the distribution coefficient of the contaminant in the soil, r is the bulk soil density, and 3 is the soil porosity. The parameterisation in ERMIN of Ds and vs is based on practical assessments in different types of soil areas in Europe (e.g., Szerbin et al., 1999; Krstic et al., 2004; Bunzl et al., 2000; Schuller et al., 1997). As well as external doses, inhalation doses from resuspension of deposited radioactive matter are also modelled dynamically in ERMIN, both for outdoor and indoor contaminants. For inhalation dose contributions, dose conversion factors are available from the publications of the ICRP (1995), whereas for external gamma dose contributions, a library of factors obtained through detailed Monte Carlo calculations of photon transport in various types of inhabited environments has been generated. The environments are characterised by the amounts, dimensions and locations of different surfaces, and their material characteristics (material type, density, and thickness). There are seven inhabited environment types with different features, ranging from detached single-family house areas to densely populated urban centres with multi-storey buildings, and also industrial buildings. For each of these, factors have been calculated giving the dose rate contribution in representative outdoor or indoor locations per unit contamination level on each type of surface in the environment (Meckbach et al., 1988; Meckbach, 1997; Jones et al., 2006). However, not all contamination remains on or near the surface, and this must also be built into the model. The effect of the vertical distribution of radionuclides in soil on dose rate at different locations indoors and outdoors in the environment has been taken into account, either directly in the Monte Carlo calculation setup or by using ‘location modification factors’ calculated for the particular environment types (Meckbach, 1997). Based on population studies, ERMIN then assumes a given fraction of the time spent in each of the modelled ‘target’ locations, for the calculation of ‘average’ dose rate contributions from each type of contaminated surface in an environment. Also, calculation of external beta dose contributions from contaminated surfaces is enabled in ERMIN, primarily on the basis of dose rate conversion factors reported by Holford (1989). Implementation of practically any foreseeable combination of the countermeasures described in the EURANOS inhabited-areas handbook, each countermeasure initiated at any chosen time, can be modelled in ERMIN. It is assumed in ERMIN that the implementation of each countermeasure occurs over a period of time, as would be the case in reality. By comparison with other ERMIN model runs where no countermeasures are assumed to be implemented, saved doses can be estimated, and extra doses to remediation workers can also be estimated by setting appropriate exposure times and locations. It should be noted that ERMIN, when implemented in the decision support systems ARGOS and RODOS, will use the IAMM modules for incorporation of measurement data, as they become available after a radiological incident. This data assimilation process will continuously improve model prognoses, thereby improving consequence assessment in relation to the specific situation. 3.2. Considerations on the modelling of doses from a ‘dirty bomb’ Currently, the ERMIN model is designed for decision support in connection with contaminant releases to the atmosphere from nuclear power plant accidents located some distance from the inhabited area. However, in recent years,

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the possibility of a malicious attack involving dispersion of radioactive matter, especially through the detonation of a so-called ‘dirty bomb’, has attracted increasing attention. Inhabited areas could be seen as likely targets for such incidents, as this is where most people could be affected. The use of dose models like ERMIN in connection with ‘dirty bombs’ would probably be very limited in the immediate vicinity of the detonation site, as this restricted area would be likely to be subject to very extensive monitoring determining the consequences in great detail. Also, the formation of large contaminated shrapnel would here make reliable estimation of the deposition pattern virtually impossible. However, a ‘dirty bomb’ would also be likely to produce a plume of more finely dispersed material that can travel beyond the immediate zone and potentially contaminate a large inhabited area (Sohier and Hardeman, 2006). Preliminary calculations made outside the EURANOS project have indicated that dispersion of strong sources might in this way lead to significant radiological problems over an inhabited area (Andersson, 2005). To predict and assess the extent and radiological impact of such contamination as well as the outcome of countermeasures, a consequence assessment tool essentially based on the same concepts as ERMIN would be valuable. However, it is important to note that the contaminants and their behaviour would differ significantly from what would be observed after a nuclear power plant accident. Therefore, for example, the ratios between deposition on the reference surface and deposition on the other urban surfaces currently in the ERMIN data libraries can be expected to be very different from those appropriate for a ‘dirty bomb’. For instance, a ‘dirty bomb’ might only contain a pure beta-emitter (e.g., 90Sr). In a calculation scenario with a ‘dirty bomb’ dispersing a 90Sr source, the most important dose contributions have been estimated to be (in decreasing order): the dose from inhalation during plume passage, the external dose from contamination on human skin, the external dose from contamination on outdoor surfaces, and the external dose from contamination on indoor surfaces (Andersson, 2005). Doses from inhalation during plume passage and from contamination on humans are beyond the current scope of ERMIN, as they are received over hours or days in the earliest phase of a contaminating incident. An important factor in determining the distribution of the dispersed contaminants in the environment is the size distribution of the contaminant particles generated by the blast. The information available from the open literature to describe this particle size distribution is very limited, and generally not directly related to ‘dirty bombs’. However, in January 1968, when an aeroplane carrying four nuclear weapons exploded about 12 km away from Thule Air Base in Greenland, the process of dispersion of radioactive material was essentially consistent with that of a ‘dirty bomb’. Particle size distributions were reported to be lognormal with a mean of 2 mm and a log standard deviation of one (Danish Atomic Energy Commission, 1970). This means that only 1.3% of the particles were larger than w18 mm, but these carried nearly 80% of the activity (Eriksson, 2002). This size distribution pattern is in line with dust observations made in connection with detonation of high explosives in/on various soils (Pinnick et al., 1983). Investigations of particle size distributions (as reported by differential mass) here revealed a distinct peak at a mean particle radius of w7 mm, but a more limited number of particles in the w100 mm range were also observed. The tests were conducted in areas of soils with very different textural features, ranging from desert sand to clay soil. However, no obvious connection was observed between soil particle size distributions and dust distributions. The limited number of large hot particles in the 100 mm range generated by the blast would, due to strong gravitational settling, not travel far. By contrast, smaller particles, on which gravity would have considerably less influence, would remain airborne over much longer periods of time and could reach much greater distances from the release point. The distribution on the various surfaces of an inhabited area of deposited particles in the 10e20 mm range would be very different from those of the particles currently considered in ERMIN (Andersson et al., 2004). A new deposition parameterisation for the relevant particle sizes is thus required. If the large contaminating particles are not readily soluble, the contaminants would also be weathered away much more rapidly from impermeable surfaces in the environment than would contaminants associated with smaller particles. This is illustrated by the very high decontamination factor of 50, obtained by Clark and Cobbin (1964) when hosing water on a street contaminated by particles in the 44e100 mm range. Thus the ERMIN functions describing the post-deposition migration in the environment would need revision. It would also be problematic to use the current dispersion modules in RODOS and ARGOS alone to estimate the contaminant dispersion after a ‘dirty bomb’ detonation. In mesoscale dispersion models, such as ATSTEP (Pa¨slerSauer, 1997) and RIMPUFF (Mikkelsen et al., 1984), inhabited areas are simply modelled as areas with enhanced surface roughness and different deposition rates compared with open areas. A ‘dirty bomb’ would be likely to result in dispersion at much lower altitude than would be seen following a large nuclear power plant accident. In an inhabited area, this means that the initial plume interaction with buildings and other obstacles and dispersion through street canyons can be important factors in determining the plume shape and dispersion pattern. Therefore, high-resolution puff

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dispersion models like UDM (‘Urban Dispersion Model’) (Hall et al., 2002) are here needed to handle short-distance dispersion more accurately. This model can take into account both the ‘trapping’ of parts of the plume behind single obstacles, their subsequent spreading around these obstacles, and their later movement for instance in street canyons. Calculations have shown significant differences between UDM and RIMPUFF in the plume dispersion and shaping over the first few 100 m from the detonation point (Astrup et al., 2005). In order to enhance the modelling capacity of ARGOS beyond the scope of the EURANOS project, a highresolution dispersion model for inhabited areas, including data libraries for handling deposition of particles relevant to dirty bombs, is currently being developed at Risoe. 4. Conclusions A generic European handbook for decision support in relation to incidents leading to airborne dispersion of radioactive matter over inhabited areas has been created under the CEC-EURANOS project. The handbook focuses on the recovery (intermediate to late) phase of an incident, but also contains countermeasure descriptions in a standardised datasheet format for the pre-release phase and the earliest phase after the contaminated plume has emerged, as decisions made in these early phases may influence later choices on implementation of countermeasures. The datasheets contain information on a large number of aspects of the implementation of each countermeasure, facilitating method comparison and development of holistic cost-effective mitigation strategies. The decision support handbook for inhabited areas also comprises a framework of information, structured with the aim of guiding decision-makers through considerations needed to select and implement an optimised countermeasure strategy. This framework includes decision flow diagrams, tables, check lists and text sections. Reliable dose modelling is an essential part of the process of countermeasure strategy optimisation. Within the CEC-EURANOS project, the model system ERMIN has also been developed, which can be used for detailed estimation of doses to people in an inhabited area following a major airborne release of radioactive matter from a nuclear power plant accident. This new model, based on state-of-the-art knowledge, is called for since models previously available for estimating external doses to members of the public in inhabited areas, including those used in RODOS and ARGOS, have a number of shortcomings. The type of model developed is also considered potentially useful for decision support in relation to other types of contaminating incidents. However, it is demonstrated that substantial parametric revision would be required for ERMIN to be applicable to ‘dirty bomb’ malicious radioactivity dispersion incidents. Disclaimer The views expressed in this paper are those of the authors and do not necessarily reflect those of the EURANOS project. Acknowledgments The work described in this paper has been carried out with support from, inter alia, the European Commission under the EURATOM Research and Training Programme on Nuclear Energy (2002e2006), EURANOS project, contract no. FI6R-CT-2004-508843. The authors gratefully acknowledge contributions to the described EURANOS deliverables by W. Raskob (Forschungszentrum Karlsruhe, Germany), S. Hoe (Danish Emergency Management Agency, Denmark), L.H. Jacobsen and L. Schou-Jensen (PDC A/S, Denmark), F. Gallay (IRSN, France), G. Kirchner and F. Gering (Bundesamt fu¨r Strahlenschutz, Germany), V. Bertsch (University of Karlsruhe, Germany), T. Ika¨heimonen and R. Ha¨nninen ˇ u´ranova and A. Mrsˇkova (VUJE, Slovak Republic), M. Morrey and L. Singer (Health Protection (STUK, Finland), T. D Agency, UK), H. Mu¨ller (GSF, Germany), P. Astrup and T. Mikkelsen (Risoe National Laboratory, Denmark) and J. Roed (previously of Risoe National Laboratory, Denmark). References Andersson, K.G., 1991. Contamination and Decontamination of Urban Areas. Ph.D. thesis, Risø National Laboratory, Denmark. Andersson, K.G., 1996. Evaluation of Early Phase Nuclear Accident Clean-up Procedures for Nordic Residential Areas. NKS Report NKS/EKO5(96)18, ISBN: 87-550-2250-2.

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