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11

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Abstract

The development of two new probabilistic acQdent consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the risks presented by nuclear installations based on postulated frequencies and magnitudes of potential accidents. In 1991, the US Nuclear Regulatory Commission (NRC) and the Commission of the European Communities (CEC) began a joint uncertainty analysis bf the two codes. The ultimate objective of the joint effort was to develop credible and traceable uncertainty distributions for the input variables of the codes. As a first step, a feasibility study was conducted to determine the efficacy of evaluating a limited phenomenological area bf consequence calculations (atmospheric dispersion and deposition parameters) and to determine whether the technology exists to develop credible uncertainty distributions on the input variables for the codes. Expert elicitation was identified as the best technology available for developing a library of uncertainty distributions for the selected consequence parameters.

The study was formulated jointly and was limited to the current code models and to physical quantities that could be measured in experiments. The elicitation procedure was devised from previous US and EC studies with refinements based on recent experience. Elicitation questions were developed, tested, and clarified. Sixteen internationally recognized experts from nine countries were selected using a common set of selection criteria. Probability training exercises were conducted to establish ground rules and set the initial boundary conditions. Experts developed their distributions independently. Results were pro- cessed with an equal weighting aggregation method, and the aggregated distributions were processed into code input variables.

To validate the distributions generated for the wet deposition input variables, samples were taken from these distributions and

propagated through the wet deposition code model. Resulting distributions closely replicated the aggregated elicited wet depo- sition distributions. To validate the distributions generated for the dispersion code input variables, samples were taken from the distributions and propagat d through the Gaussian plume model (GPM) implemented in the MACCS and COSYMA

GPM assumptions.

codes. Resulting distributions &,ere found to well replicate aggregated elicited dispersion distributions consistent with the

Valuable information was obtained from the elicitation exercise. Project teams from the NRC and CEC cooperated success- fully to develop and implement a unified process for the elaboration of uncertainty distributions on consequence code input parameters. Formal expert judgment elicitation proved valuable for synthesizing the best available information. Distributions on measurable atmospheric dispersion and deposition parameters were successfully elicited from experts involved in the many phenomenological areas of consequence analysis.

... 111 NUREGKR-

NuREG/CR-6244 iv

NUREGICR-6244 vi

Preface

This volume is the second of a three-volume document that summarizes a joint project conducted by the US Nuclear Regula-

tory Commission and the Commission of European Communities to assess uncertainties in the MACCS and COSYMA proba- bilistic accident consequence codes. These codes were,developed primarily for making estimates of the risks presented by nuclear reactors based on postulated frequencies and magnitudes of potential accidents. This three-volume document reports on an ongoing project intended to assess uncertainty in the MACCS and COSYMA offsite radiological consequence calcula- tions for hypothetical nuclear power plant accidents. A panel of 16 experts was formed to compile credible and traceable uncertainty distributions for the dispersion and deposition code input variables that affect offsite radiological consequence cal- culations. The expert judgment elicitation procedure and its outcomes are described in these volumes.

Volume 11 contains two appendices. Appendix A contains (1) the rationales for the dispersion and deposition data provided by

the 16 experts who participated in the elicitation process and (2) the tabulated elicited information from the experts. Appendix

B contains short biographies of the I 16 experts.

Volume I of this document includes a complete description of the joint consequence uncertainty study. Volume 111 contains six appendices that describe in greater detail the specific methodologies used by the atmospheric dispersion and deposition panels.

vii NUREGKR-

Acknowledgments

The authors would like to acknowledge all the participants in the expert judgment elicitation process, in particular the disper- sion and deposition expert panels. While we wrote and edited the report, organized the process, and processed the results, the experts provided the technical content that is the foundation of this report. Dr. Detlof von Winterfeldt is acknowledged for his contribution as elicitor in several expert sessions.

The authors would also like to express their thanks for the support and fruitful remarks from Dr. 'G. N, Kelly (CECDG XII),

Dr. R. Serro (CECDG XI), and Dr. J. Glynn (USNRC).

We would also like to acknowledge several institutes that facilitated the collection of unpublished experimental information used in the probabilistic training and evaluation of the dispersion and deposition experts. The authors want to thank Dr. T. Mikkelsen and coworkers at Riso and the Danish Center for Atmospheric Research, Denmark; Dr. R. Brown at British Gas,

UK; Dr. B. Jolliffe at NPL Teddington, UK; Dr. G. Deville-Cavelin at IPSNKadarache, France; Dr. P. Berne at IPSN/Greno-

ble, France; Dr. Y. Belot at IPSNBontenay-aux-Roses, France; Dr. J. Duyzer at TNODelft, The Netherlands; and Dr. J. Slan-

ina at ECNRetten, The Netherlands.

The authors also greatly appreciate the technical assistance of Ms. Ina Bos of Delft University of Technology, The Nether-

lands; the support of Ms. Darla Tyree and Ms. Judy Jones of Sandia National Laboratories, USA.; and the extensive assistance

and guidance provided by Tim Peterson of Tech Reps, Inc., in the preparation of this report.

This report is written under the following contracts:

Contract NO. L2294, United States Nuclear Regulatory Commission, Office of Nuclear Regulatory Research, Division of

Safety Issue Resolution.

Contract No. F13P-Ct92-0023, Commission of European Communities, Directorate-General for Science, Research and Devel- opment, XU^ Radiation Research.

Contract No. 93-ET-00 1, Commission of European Communities, Directorate-General of Environment, Nuclear Safety and

Civil Protection, XI-A- 1 Radiation Protection.

ix NUREGKR-

NUREGICR-6244 X

Appendix A

A. 1 Expert Rationales, Unprocessed Deposition Data

The Case Structures for the deposition expert panel are presented in Volume ID Appendix F of this document.

Expert A

Introduction

The deposition velocity is the mass transfer boundary

condition at the air-surface interface in atmospheric diffusion and transport models. The dry deposition velocity idea is assumed applicable to describe rates of gas and particle removal to all surfaces, rough or smooth, and vertical or horizontal. Chamberlain and Chadwick4 defined

the deposition velocity as the ratio of the deposition flux

divided by the airborne pollutant concentration per unit volume at some height above the deposition surface. The deposition velocity is often reported in units of either cm/s or d s. The maximum range of reported deposition velocities is about five orders of magnitude from lo5 to 1 d s , or io3 to 10’ c d s (Seh~nel).*~”

Expressed here is the author’s rationale for opinions of deposition velocities for large area surfaces. The NRC/CEC Program considers the dry deposition velocity, vd, as the ratio of the rate of deposition of radioactivity to the ground

[ B q / ( s m2)] to the air concentration at one meter height

(Bq/m3), and has units of m / s. The program requests

opinions on the median, 0.05 quantile, and 0.95 quantile for

dry deposition velocities, and the 0 and 100% bounds of the

distributions.

It is emphasized that it stretches and exceeds predictive capabilities to predict accurately the median. Uncertainties

to be meaningful in the 0.05 and 0.95 quantile and the 0

and 100 percent bounds also stretch and exceed predictive capabilities based on experimental results.

The agreed upon constraints for the rationale with the

Sandia program manager (Fred Harper) are 1) rationale are

to be,based upon data known to the author, and 2) new

theories or ideas are not to be developed for the rationale. Since the program is based on current knowledge, the rationale for estimates is based on prior publications by the author.

Dewsition Parameters to be Addressed

The Joint NRC/CEC Consequence Uncertainty Program (program) requests opinions on eliditation questions for dry deposition velocities for general and specific surface types (the case structure and elicitation variable) and particle and gas properties.

Generic Surfaces for Elicitation Ouestions

Generic surface types are urban, meadow, forest and human skin. The urban surface type consists of buildings and concrete. The meadow surface type includes bare soil,

freshly cut grass, pasture, and crops such as harvestable

corn. The forest surface type includes any type of trees

including deciduous and evergreen varieties. Human skin refers to skin that might be exposed to a passing plume.

The only initial condition is the average wind speed. Wind

speeds are 2 and 5 m l s at 10 m height.

For general surface types, the program requests opinions on hourly average dry deposition velocities as the airborne plume traverses across general surface types. The program requests dry deposition velocities for elemental iodine,

methyl iodide, and particles in indicated diameter ranges.

Table A-1 shows the diameters of interest for estimating dry deposition velocities. A program constraint is that particle size corresponds to spherical particles of unit density ( g/cm3).

Table A-1. Particle diameters of interest

for general surfaces

Indicated Particle Range Assumed for Diameter Indicated Particle ( P I Diameter (pi)

0.1 0.05 to 0.

0.3 0.2 to 0.

1 .o 0.5 to 2.

3 .O 2.0 to 5.

10.0 5.0 to 15.

Specific Surfaces for Elicitation Ouestions

Dry deposition velocities for specific surface types are under the general heading of meadow: moorland/peatland, heather and grass, and grassland. The program considers two specific surfaces.

A- 1 NUREGlCR-

Appendix A

The first surface is moorlandpeatland with vegetation

consisting of 40 cm high tussocks and old dry grass partly

filling the spaces between the tussocks and underlain by a

wet peat layer. The wind speed is 5 m/s at 5 m height.

Surface roughness is 5 f 1 cm. Particle sizes are 0.55, 0.7,

0.9, 1.2, and 1.6 pn.

The second surface is heather and green grass, with

vegetation only partly covering the soil. The wind speed is 5 m/s at 5 m height. Surface roughness is 4.5 * 1.5 cm.

Particle sizes are 0.55, 0.7, 0.9, 1.2, 1.6, 2.32, 3.2, and 4.

CLm.

General Caveats for Rationale

Deposition velocities requested by the Joint USNRC/CEC Uncertainty program are not conventional values reported in the literature, but grouped values. The program requests opinions from panel members for dry deposition velocities that might apply to the generic surface types considered by the program.

The uncertainties in predicting dry deposition velocities are large. Further refinements in averaging deposition velocities for surface variations within one mile increments (in

transport models used by the program) are considered a

second order effect compared to uncertainties in predicting

dry deposition velocities.

There is no general correlation to predict 9 deposition velocities based on field measurements of dry deposition velocities. The author prefers measurements of dry deposition velocities, not dry deposition velocities inferred by application of diffusion and transport models to interpret field results. The author cautions the use of inferred dry deposition velocities that depend on the diffusion and

transport model used. There is not an obvious way to apply

deposition velocities inferred from one transport and diffusion model to different transport and diffusion models.

The rationale emphasizes the prediction of dry deposition

velocities as a function of particle diameter (and iodine) as

requested of the panel members. Rationale considers the empirical predictive model developed by Sehmel and Hodg~on.’~.’~The model is dased on experimental evaluation of surface mass transfer within the P cm above deposition surfaces in wind tunnel dry deposition experiments. Diffusion equations are used to adjust the concentration reference height from 1 cm to 1 m.

Assuming surface variation and dry deposition velocities can be calculated for an area average surface, the grouped dry deposition values, vGrouped,are hourly averages that

I

might be estimated by the expression

where

4 = surface within area of type i

v , = dry deposition velocity of species j over deposition surface i.

An assumption is that variation caused by changes in airflow between different surfaces can be neglected.

For a surface type i, the dry deposition velocity, vdj, is dependent on the particle size distribution and airborne

concentrations, Cj. For an aerosol with a polydispersed

particle size distribution (real aerosols), the average dry deposition velocity to surface i is

where Kj = dry deposition velocity for a monodispersed

particle of size j

Cj = airborne concentration of particle size j.

Uncertainties in grouped dry deposition values might be

comparable to uncertainties in transport and diffusion codes

to predict accurately airborne concentrations. Neither describe the effects of non-uniform surfaces on dry deposition velocities and airborne concentration.

Experimental Drv Deposition Velocities

The rationale is based on field data for iodine and particle

deposition, and predictions of particle deposition as a

function of particle size made from an empirical model based on dry deposition velocities measured in wind tunnel

experiments. Literature values from field experiments of

dry deposition velocities for iodine and particles were

summarized by Sehme1.8s9~10,”Predictions of dry deposition

velocities of particles as a function of particle size are based

on Sehme1.’4*’5+

NUREGiCR4244 A-

Appendix A

3 - GREEN PASTURE, STABLE ATM.

62 -GRASS, UPPER L I M I T 24 - GRASS RANGE 24 - GRASS, AVG. D A M P 3 - PASTURE, FRESHLY MOWN

3 - PASTURE, FRESHLY MOWN

24 - CLOVER 3 -GRASS, GROWING

12 - GRASS

8 - GRASS 3 - GRASS-DRY, UNSTABLE ATM. 3 - GRASS-DRY, UNSTABLE ATM. 24 - GRASS, AVG. DRY 39 - ROUTINE HANFORD 23 -GRASS 5 - S O I L + GRASS 35 - FIELD 3 - GRASS-GROWING, UNSTABLE ATM. 3 - GRASS-GROWING, NEUTRAL ATM. 5 - PAPER LEAVES 8 - GRASS 5 -LEAVES 1 -WATER 32 - GRASS 22 -GRASS 5 -PAPER I N D I S H 12 - STICKY PAPER 3,33,63- CHARCOAL, LAPSE ATM. 59 - GRASS 3 - GRASS-GROW1 NG 3 - GRASS-GROWING 9 -GRASS 3 -GRASS, DUSTY-DRY 3 - GRASS, FRESHLY MOW 3 - SNOW, NEUTRAL ATM. 3 -GRASS, GREEN 3,33,63 - CHARCOAL, INVERS I ON 55 -ENGLAND, WINDSCALE

I

20 - SL-1 A C C l DENT 63 - GRASS 3 - GRASS, DUSTY-DRY

REFERENCE

r

X X o----o I

li m

OH

I I , I , I t (^) I I 1 1 I L I I I I I I I l l

lo-L 10- 1 10

DEPOSITION VELOCITY RANGE, cm/sec

0 GRASS

X WATER

V SNOW

0 OTHER

Figure A-1. Deposition velocities for i d i e.

NUREG/CR-6244 A-

DN Deposition Velocities Measured in Wind Tunnel

Experiments

Sehmel and H o d g s ~ n ' s ' ~ " ~empirical model to predict

particle dry deposition velocities is based on wind tunnel

measurements of dry deposition velocities for monodispersed particles (single sized particles) onto five different surfaces. Table A-3 shows the ranges of experimental conditions in these wind tunnel experiments. Particle density was 1.5 s/cm3- A 1 1 experiments were for

near isothermal conditions, about 70°F (20°C).

Appendix A

Airborne concentrations were measured at a height of 1 cm above the deposition surface in order to define the dry

deposition velocity at 1 cm height (this allows evaluation of

the surface mass transfer resistance below a height of 1

cm). The deposition velocity, K, is defined as

Kl = --^ N C'

(3)

In this case, the concentration, C, is for monodispersed

particles, with concentration measured 1 cm above the deposition surface.

Table A-2. Dry deposition velocities for methyl iodide

Deposition Surface Deposition Velocity ( c d s l Reference

Pasture grass 1.4 104 to 2.4 10-3 Atkins et al.'

Activated charcoal 0. fallout plate

Bunch

Mixed pasture grass 10-4 to 10-2 Bunch Grass 0.9 per cent Heinemann et a1. of that for molecular iodine

Mixed pasture grass less than^ 0.05^ per cent

of that for molecular iodine

Zimbrick and , ~oilleque"

A-5 NUREGlCR-