Dose Rate Measurements and Action Levels in the Event of a Nuclear Accident: Variational Analysis.

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1 Reprint of IAEA Report With acceptance from IAEA Dose Rate Measurements and Action Levels in the Event of a Nuclear Accident: Variational Analysis. Bent Lauritzen Dept. of Nuclear Safety Research, Risø National Laboratory, DK-4000 Roskilde, Denmark and Ulf Bäverstam Swedish Radiation Protection Institute S Stockholm, Sweden Abstract Dose rate measurements are analysed as being early indicators of the range of avertable doses in the event of a nuclear accident. The extent to which dose rates and avertable doses are correlated is evaluated in a Monte Carlo study, using two years of cumulated meteorological data. The study is carried out for three different release scenarios from a nuclear power plant, and the avertable doses and dose rates are obtained in an atmospheric dispersion model calculation. It is shown that dose rate measurements carried out in the early phases after an accident may provide a valuable tool for decision support, and action levels of dose rates may be defined for the purpose of assisting a rapid emergency response. 1. Introduction This report is borne out of an ongoing Nordic Nuclear Safety Research (NKS) project, EKO-3.3, dealing with action levels as a decision aiding tool in the event of a nuclear accident. Action levels (AL s) are defined as the instrument readings of measurements carried out in the early phases of a nuclear accident, above which values protective actions aiming at dose reduction should be taken. For an effective protection of the public, countermeasures should in general be introduced at the earliest possible time, before the public is exposed to radiation. During the initial stage of a nuclear accident, the information available regarding the severity and the scale of the accident is often limited, but may be supplemented by measurements carried out as a part of a nuclear emergency preparedness programme. Apart from contributing to an assessment of the radiological consequences of the accident the measurements will also facilitate a rapid emergency response by invoking pre-determined AL s as site- and accidentspecific observable thresholds for the implementation of dose reducing protective actions.

2 In the present study, dose rate measurements are analysed as being early indicators of the forecasted radiation doses to the public, following a severe accident at a nuclear reactor. The accident is assumed to include core-melt, loss of coolant and, either a breach of containment followed by a rapid release of activity to the atmosphere, or a functioning containment with a more slow, filtered release to the atmosphere. In a Monte Carlo calculation, the joint probability distribution of dose rates and doses averted by means of protection is evaluated. From this probability distribution, the correlation between the measurable dose rates and the predicted avertable doses is assessed, and the implications for decision making based on dose rate measurements are discussed. 2. AL s in a nuclear emergency 2.1 Early measurements as decision support The decision on the introduction of protective intervention measures in a nuclear emergency should as a general principle be based on an estimate of the averted doses resulting from the intervention [1]. Any protective action is deemed to be justified if the averted dose resulting from the chosen course of action offsets the costs associated with the intervention measure. The costs include economic, social, psychological and possibly political costs by introducing the protective measure. As a guidance towards decision making, intervention levels (IL s) of averted doses may be predetermined, based upon an optimisation of the scale and duration of the intervention measures considered. Guidelines for IL s provided by ICRP [2], IAEA [3], NKS [4], as well as other international recommendations have been summarised in the NKS project BER-3 [4]. During the early stages of a nuclear accident however, the concept of avertable doses will not be an operational quantity with respect to decision making, because of the uncertainty associated with the forecasting of radiation doses to the public. The uncertainty has its origin both in the inherent variation associated with the stochastic processes of atmospheric transport and deposition and with the location-dependent effectiveness of dose reducing protective measures, as well as in the insufficient information regarding the source term. That is, an accurate estimate of the avertable doses requires a detailed knowledge of the type of accident and of the amount and the isotopic composition of released material, i.e. a level of information which supposedly will not be available during the early stages of a nuclear accident. In order to maximise the effectiveness of protective intervention measures, decision on the implementation of such measures should be taken at the earliest possible time, before the public is exposed to radiation stemming from the accident scene, and therefore, at a time when the available information about the accident is less than complete. Rather than relying on avertable doses forecasting, the decision making should be linked directly to the information at hand. The information available for decision makers at the early stages of an accident will most likely be restricted to include meteorological information (weather history and forecasts), information on the plant condition in conjunction with design safety analyses and/or measurement data from emergency preparedness units. Early measurements may provide information that is valuable as decision support, both in case that information on the plant conditions is available and, especially, when information about the origin and the scale of the nuclear accident is limited. The measurements considered are dose rate measurements by either mobile units or stationary measuring stations, or total activity concentrations in air obtained in a filter analysis. Measurements giving spec-

3 troscopic information will not be considered here. In general, measurements will act to reduce the uncertainty in the avertable doses forecasted. The measurement data will both constrain the range of possible doses and provide information on the geographical and demographical distribution of doses. As a decision support, measurements may be quantified as being below or above an AL, above which level the implementation of dose-limiting protective actions are recommended. The introduction of AL s for decision support is sensible only to the extent that averted doses are correlated with the measurement data, such that the IL of averted dose translate into an AL. When the measurements provide either the only piece, or the most important piece of information regarding the severity of the accident there will be a desire for defining and using AL s for the purpose of decision support, even in cases where the correlation between measurement data and averted doses is more uncertain and the level of confidence in the averted doses estimate is small. The AL can be defined either for a single measurement such as a dose rate measurement, or for a measurement in combination with other relevant information, such as dose rate measurement combined with information regarding the nuclide composition of the released activity The information content of measurement data collected within a nuclear emergency preparedness programme, is given by the capability of the measurements in reducing the uncertainty of the forecasted doses. If the uncertainty by means of measurements can be reduced to a reasonable low level, the measurements qualify as being valuable for decision support. On the other hand, if the uncertainty in the avertable doses estimate remains large compared to the avertable doses themselves, the measurements clearly will be less useful as decision support. This may eventually lead to a reevaluation of the choice of instrumentation used in the emergency programme or to an adjustment of the measurement strategy in order to decrease the uncertainty in the avertable doses predictions. 2.2 Variability of forecasted doses I a nuclear emergency, several pieces of information may be available for decision support and the value attributed to measurement data collected within the nuclear emergency preparedness programme depends on their ability to constrain the range of possible averted doses resulting from a specific protective action. The variability of forecasted doses may be expressed in terms of the conditional probability distribution, P( E {measurements, plant condition,... }) which is the probability density, conditioned by the information available, of averting the dose E. Each choice of protective action has its own probability distribution P. From the probability distributions, all information about the magnitude of avertable doses may be derived and, in particular, the mean value and the variation in avertable dose can be obtained. The distribution P establishes the relation between IL s and AL s. The IL of avertable dose is evaluated on the basis of a cost-benefit optimisation, its value being determined by requiring the intervention measure to have zero total costs. When the costs are ascribed a probabilistic distribution, the costs should be replaced by their expectation value (the mean value) in defining the AL. Then, assuming a linear avertable dose - total cost relationship, the expectation value of the avertable dose links the AL to the IL. For instance, writing d AL

4 for the dose rate AL and E IL for the avertable dose IL, the defining equation for d AL becomes E IL = d( E ) P( E d AL ) E, i.e. the dose rate measurement value for which the mean avertable dose equals the IL. The avertable doses and the measurement values depend on time and location, thereby complicating the relationship between measurements and forecasted doses. Not all times and locations need to be considered however, as they are dictated by the actual measurement and intervention strategies. In nuclear emergency preparedness programmes, one will have contingency plans for dealing with a nuclear accident. Both the Danish and the Swedish nuclear emergency preparedness programmes operates with predetermined, fixed sets of measurement locations. Measurements at some fixed point may be followed by more intensive measurements, but here we only consider decisions taken on the basis of the first measurements. Each measurement point will be representative of an area or a geographical sector surrounding the measurement point, provided that the spatial variation of nuclide concentrations remains small over the distance between neighboring measurement points. Since the emergency response, if any, will trigger on the largest measurement value, this largest value must be used in determining an AL for the type of measurement. The procedure of averted dose calculation must be consistent with the philosophy underlying the choice of intervention level. If the IL is evaluated for a critical group of highly exposed individuals [6], the averted dose must be a conservatively estimated avoided dose representative of the geographical sector surrounding each measurement point. The critical avertable dose, (the dose to the critical group) is determined as the maximum avertable individual dose to be found within the sector. 3. Variational analysis 3.1 Model The conditional probability distribution P of avertable doses can be estimated, by running a series of atmospheric dispersion calculations using an accident consequence assessment code. The calculation assumes a probabilistic distribution in all parameters describing both the accident scenario and the atmospheric transport and deposition of radionuclides. From the atmospheric dispersion calculations a joint probability density is obtained, P( E, x), where x denote the measurement values, e.g. dose rate values. From this joint probability distribution, the conditional probability density is derived as P( E x) = P( E, x ) / d( E ) P( E, x). In a case study, the joint probability distribution of dose rates and avertable doses, P( E, d ), has been evaluated by using a modified version of the emergency preparedness system LENA 3.0, developed by SSI [5]. The atmospheric dispersion model of LENA 3.0 is a straight line Gaussian plume model, in which a continuous release of activity is dispersed downwind forming a Gaussian shaped plume. The modifications allow the meteorology (e.g. wind direction and speed) to change every hour, such that the total release is segmented into hourly releases, each forming a straight line Gaussian plume.

5 The model assumes total reflection of the plume at the ground surface and at the top of the atmospheric mixing layer. Dry deposition is modelled by source depletion, using a constant dry deposition velocity, while wet deposition is modelled by a precipitation ratedependent scavenging coefficient. Lena 3.0 has a library of 69 different radioactive nuclides, arranged into 9 different release groups according to the physical-chemical properties of the nuclides. Each nuclide group is ascribed a single release fraction, and the release is assumed to occur at a constant rate throughout the specified release period. The dispersion model parameters are drawn from an ensemble of meteorological data, consisting of two years meteorological time series collected by the Swedish Meteorological and Hydrological Institute at the at Sturup airport near the Barsebäck nuclear power plant. The data set provides hourly meteorological information, including wind direction and speed, atmospheric stability and precipitation rates. The reactor undergoing the accident is taken to be the Barsebäck nuclear power plant. Three accident scenarios are selected that could result from a severe core melt-down with a loss of coolant, and the joint probability density P( E, d ) is evaluated independently for each of the three scenarios. The accident parameters are given in Table 1. In the release scenarios A and B the containment is assumed to be functioning and the activity is only released through the filter system, causing the delay before release. In the scenario C, the containment is malfunctioning and a substantional release activity bypasses the filter. The accident scenarios are not treated fully probabilistic in the model; the timescales and the release fractions specifying each of scenarios are allowed to vary, while the relative probability of encountering the three scenarios remains unspecified. Table 1. Release fractions and release times of the source terms A, B and C. Release fractions ( except for the noble gases ) are allowed to vary ± 20 % around the mean values shown in the table. Source term A B C Release delay (h) Release duration (h) Noble gases Organic Iodine I Cs, Rb Co, Ru etc Sb, Te Zr, Nb etc Sr, Ba Trans-uranium The remaining model parameters describing the source term, the atmospheric dispersion and deposition, and the shielding factors applicable for sheltering and evacuation are shown in Table 2. The variable parameters, t r, t d, L PL, F, and the release fractions, are all ascribed flat probability distributions, i.e. probability distributions with equal weights to all parameter values within the specified interval. Dose rates and averted doses are calculated on a circle surrounding the power plant. The dose rate d is taken to be the maximum value among a number of fixed locations, the dis-

6 tance between the measuring locations given in Table 2, while the averted dose E is taken as the maximum value along the entire circle. The dose rates are effective dose rates measured outdoors due to external radiation from the plume and from the ground. The averted dose consists of the effective dose (averted) from external radiation and effective, committed dose (averted) from inhalation. Table 2. Model parameters used in the calculation. Parameter Symbol Value Source term Time from shutdown to release t r Table 1 begins. Release duration. t d Release fractions Release height h 50 m Atmospheric dispersion and Pasquill-Gifford stability classification 2 years cumulated meteorological data deposition Wind speed and direction u Mixing layer height z mix Precipitation J Wet deposition scavenging Λ 10-4 (J/(mm/h)) 0.8 s -1 coefficient organ. I : 10-6 (J/(mm/h)) 0.8 s -1 Shielding factors Dry deposition velocity v d 10-3 m/s organ. I : m/s Location factor, plume L PL Location factor, ground L GR = L PL / 2 Filtration factor F Measurement Distance from site of release x 5, 20 and 50 km (fixed values) Angular separation between measuring locations φ 0.26 radian 3.2 Results For each of the three accident scenarios a total of 10,000 dose rate and averted dose calculations were performed for the three distances x from the site of the accident, given in Table 2. For the sheltering option, the 24 hour period immediately following the beginning of the release were used to determine averted doses, while for the evacuation option, a one month period starting at 24 hours after the beginning of the release were used. The dose rates are determined as 1 hour averages as they would have been measured by a perfect instrument. In the Figs. 1-3 the joint probability densities for sheltering is shown for the three distances x = 5, 20, and 50 km, respectively. The three accident scenarios have been superimposed with an equal weight in the figures. In Figs. 4-6, the three accident scenarios are shown separately for the common distance of x = 20 km. In all cases the probability densities are shown in log(d ) - log( E ) plots.

7 For the calculations performed at a fixed distance using one of the three release scenarios, Figs. 4-6, the joint probability density approximate a correlated log-normal distribution. This is seen in Figs. 7-8, where the projected distributions P(d ) and P( E ) are shown for the distance x = 20 km, using release scenario B, along with the log-normal distributions determined from the mean values and the variances. The variation in the calculated dose rates and averted doses is a result of the variations in the parameters specified. Hence the total spread in the averted dose by sheltering is given by the combined effect of the spread in the source term parameters, the meteorological data/parameters, and the shielding factors, while the spread in dose rates is sensitive to the distance between the plume centerline and the measuring location. With the accident scenario B being dominated by the release of noble gases, the parameter variations act as independent, random factors, resulting in the observed log-normal probability distribution. For the case of 24 hours sheltering, dose rate measurements are seen to provide a reasonable constraint on the forecasted avertable doses. In Fig. 9, the conditional probability distribution P( E d ), evaluated at a distance of 20 km from the site of the accident, is shown for three values of the dose rate. The distributions are based on the joint probability shown in Fig. 2, giving equal weights to the three accident scenarios. The joint probability distributions shown in the Figs for the distances x = 5, 20 and 50 km, respectively, are evaluated for one month of evacuation. In each of the figures, the three scenarios that have been used are clearly visible as three distinct contributions to the joint probability distributions. It is immediately obvious from the figures, that dose rate measurements alone constitute a poor constraint on the averted dose from evacuation, when the isotopic composition of the release is otherwise unknown. When considering the evacuation option, knowledge on the isotopic composition of the released activity seems as useful for decision support than information from dose rate measurements performed shortly after the accident. In the calculations however, only little uncertainty was given to the release fractions in the accident scenarios, a precision which is of course not realistic in a true accident situation. Finally, in Fig. 13 the conditional probability distribution P( E d ) is shown for evacuation (cf. Fig. 9). The log-normal distributions indicated represent a poor approximation to the observed distributions, but one should be aware that the three accident scenarios are varied independently. Nevertheless, dose rate measurements clearly represent less useful information when considering evacuation than for sheltering, the prime reason being the longer timescale of the evacuation protective measure. 4. Conclusion The model calculations presented show the variability of forecasted avertable doses following a release of activity from a nuclear installation. The variability has its origin partly in the insufficient information characterising the source term and the atmospheric transport of radionuclides (accident specific parameters), and partly in the variation of shielding factors and other factors that determine the effectiveness of dose reducing protective actions (location specific parameters). Dose rate measurements, or dose rate measurements in combination with information about the isotopic composition of the released activity, limit the range of forecasted doses

8 and reduce the uncertainty in the estimate of avertable doses. The constraints imposed by measurements are more effective for short time prognosis than for long time predictions. Based on a Monte Carlo calculation using 2 years of meteorological data, the uncertainty in the dose averted by 24 hours sheltering can be reduced to one order of magnitude by applying an appropriate measuring strategy. For comparison, dose rate measurements alone will reduce the uncertainty in the dose avertable by one month of evacuation to not less than two orders of magnitude. An action level for dose rate measurements may be defined for any protective action as the instrument reading of the measurement for which the mean avertable dose is equal to the intervention level for the protective action considered. The level of confidence one may associate with the action level however, decreases with the duration of the protective action and only for short time intervention measures the action level will constitute a valuable tool for decision support. References 1. International Commission on Radiological Protection, 1990 Recommendations of the International Commission on Radiological Protection, Publication 60 (Pergamon Press, 1991). 2. International Commission on Radiological Protection, Principles for Intervention for Protection of the Public in a Radiological Emergency, Publication 63 (Pergamon Press, 1993). 3. International Atomic Energy Agency, Generic Intervention Levels for Protecting the Public in the Event of a Nuclear Accident or Radiological Emergency, IAEA Safety Series No. 109 (Vienna, 1994). 4. Intervention Principles and Levels in the Event of a Nuclear Accident, Final Report of the Nordic Nuclear Safety Research Project BER-3 (NKS, ed. O.Walmod-Larsen, TemaNord, 1995). 5. U. Bäverstam, Lena 3.0 Users Manual, Statens Strålskyddsinstitut (SSI) (Stockholm, 1996). 6. The term critical group is here used in the context of intervention rather than its traditional use in the context of continuing practices.