IAEA-TECDOC-647

Modelling of resuspension, seasonality and losses during food processing

Firs! reporte th f o VAMP Terrestrial Working Group

Part of the IAEA/CEC Co-ordinated Research Programme on the Validation Environmentalof Model Predictions (VAMP)

INTERNATIONAL ATOMIC ENERGY AGENCY /A MODELLIN RESUSPENSIONF GO , SEASONALITY AND LOSSES DURING FOOD PROCESSING: FIRST REPORT OF THE VAMP TERRESTRIAL WORKING GROUP IAEA VIENNA, 1992 IAEA-TECDOC-647 ISSN 1011-4289

Printed by the IAEA in Austria May 1992 FOREWORD

Following the Chernobyl accident and on the recommendation of the International Nuclear Safety Advisory Group (IPSAG) in its Summary Report Post-Accidene th n o t Review MeetinChernobye th u ^ g l Accident (Safety Serie 75-INSAG-l. sNo , IAEA, Vienna, 1986) Agence ,th y establishea d Co-ordinated Research Programme on "rhe Validation of Models for the Transfe Radionuclidef ro Terrestrialn i s , Urba d Aquatinan c Environments Acquisitioe th d an Datf r thano fo at 'urpose" e programmTh . e e seekus o st the information on the environmental nehaviour of radionuclides which became availabl asuremenu n e a resul th s a ef t o t programme™, instituten i d the Soviet Union and in many European ".ountries after April 1986 for the purpos f testino e e reliabilitth g f o yssessmen t models. Such models find application in assessing the radiologi«- il impact of all parts of the nuclear fuel cycle. plannine ! The t usee yt ar d desiga d gan n stago t e predict the radiological impact of plan; ed nuclear facilities, in assessing the possible consequence accidentf so s '-volving release radioactivf so e material to the environment and in establishing criteria for the implementation of countermeasures. In tl c operational phase they are used together with the results of environmental monitoring to demonstrate compliance with regulatory requirements r*4arding release limitation.

The programme, which has the short title "Validation of Environmental Model Predictions" (VAMP) startes ,wa 1988n jointls i di t i ; y sponsorey b d e Divisioth Nucleaf no r Fuel Cycl d Wastan e « Managemen Divisioe th d f an tno Nuclear Safety and is also supported by the Commission of the European Communities. Ther e fouear r working groups withi programmee nth ; thee ar y the Terrestrial Working Group Urbae ,th n Wo-king Group Aquatie ,th c Working Group and the Multiple Pathways Working Gro*i,->. This is the first report of the Terrestrial Working Group. PLEAS AWARE EB E THAT ALL OF THE MISSING PAGES IN THIS DOCUMENT WERE ORIGINALLY BLANK EDITORIAL NOTE

In preparing this material for the press, staff of the International Atomic Energy Agency have mounted paginatedand originalthe manuscripts givenand some attention presentation.to The views expressed necessarilynot do reflect governmentsthoseshe of Memberthe of Statesor organizations under whose auspices the manuscripts were produced. thisin The bookuse of particular designations countriesof territoriesor does implynot any judgement by the publisher, the IAEA, as to the legal status of such countries or territories, of their authorities and institutions or of the delimitation of their boundaries. The mention of specific companies or of their products or brand names does not imply any endorsement recommendationor IAEA. partthe {he of on CONTENTS

CHAPTER I. INTRODUCTION ...... 7

CHAPTER 2. RESUSPENSION FOLLOWING CHERNOBYL ...... 9 J.A. Garland, N.J. Pattenden, K. Play ford 2.1. Introduction ...... 9 . 2.2. Definitions ...... ! Î . 2.3. Available estimate f resuspensioo s n ...... 2 1 . 2.4. Opportunities from Chemobyl ...... 14 2.5. Data following Chernobyl ...... 6 1 . 2.5.1. Time series resuspension data ...... 6 1 . 2.5.2. Traffic ...... 21 2.5.3. Scale length for resuspension ...... 21 2.5.4. Comparison with models ...... 22 2.5.5. Deposition of resuspended O7Cs ...... 22 2.6. Significance of resuspension ...... 24 2.6.1. Air concentration due to resuspended particles ...... 24 2.6.2. Depositio cropn no s ...... 6 2 . 2.7. Conclusions ...... 29 References ...... 31

CHAPTER 3. THE INFLUENCE OF FOOD PROCESSING AND CULINARY PREPARATIO RADIONUCL1DE TH N NO E CONTENF TO FOODSTUFFS REVIEA : AVAILABLF WO E DATA ...... 5 3 . Noordijk,H. J.M. Quinauh 3.1. Introduction ...... 35 3.1.1. Background ...... 35 3.1.2. Industria domestid an l c scale processing ...... 6 3 . 3.1.3. Data needed for radiological assessments ...... 36 3.1.4. Objectives and scope ...... 38 3.2. Definitions ...... 9 3 . 3.3. Effect f normao s l food processing ...... 2 4 . 3.3.1. Data analysis ...... 2 4 . 3.3.2. Data variation ...... 2 4 . 3.3.3. Dairy products ...... 3 4 . 3.3.4. Meat ...... 44 3.3.5. Vegetable d fruian st ...... 4 4 . 3.3.6. Root crops ...... 47 3.3.7. Cereals ...... 48 3.3.8. Drinks ...... 8 4 . 3.4. Decontamination ...... 49 3.4.1. Introduction ...... 9 4 . 3.4.2. Milk ...... 50 3.4.3. Meat ...... 50 344 Root crops 51 ^45 Vegetables 51 1 5 5 Conclusion 3 s 2 5 References

1 6 CHAP 4 SEASONALLR !E Y A Aarkrog 4 1 Introduction 61 411 Seasonably 61 4 1 2 Seasonal variability 62 4 2 Pre-Chernobyl data and models 65 4 2 1 Experimental studies 65 0 7 2 Model42 s 5 7 43 Post-Chernobyl datmodeld an a s 5 7 . 431 Observations 8 7 2 Model43 s 4 4 Need for model improvement 87 4 4 1 ECOSYS 87 442 FARMLAND 88 443 Summary 88 4 5 Conclusion and recommendations 90 1 9 Anne 1 x References 93

LIST OF TERRESTRIAL WORKING GROUP MEMBERS 7 9 ATTENDIN 199E GTH 0 i991 MEETINGS Chapter 1 INTRODUCTION

The Terrestrial Working Group of VAMP aims to examine, by means of expert review, the state-of-the-art in modelling the transfer of radionuclides from the terrestrial environment to man. An aim of the studies is to evaluate the lessons learned and to document the improvements in modelling capability as a result of post-Cheraobyl experience. The topic r reviefo s w were decided upon followin e firsth g t Working Group Meeting makinn I . g this choice, consideratio relative s giveth nwa o t n e importance of a given process as a potential contributor to radiation dose to man, the degree of uncertainty which exists in the area because of lack of knowledge and the possibilities presented by Chernobyl for improvement understandinf o processe th f go .

Reviews of three of the identified topics are presented in this report; they are:

Resuspension - the process in which surface deposits of particulate matter are re-entrained into the air by mechanisms such as wind disturbance and man-made activities.

s beeItha n demonstrate dy environments dr tha n i t , particlee b n ca s resuspended for many years after their initial deposition. In the case of radionuclides this could represent a long term pathway of radiation exposure, especiall thosr fo y e long lived radionuclides which present most hazard via the inhalation route. The validity of the resuspension models developed on the basis of the evidence from dry environments in other more vegetated and damper environments had never been adequately tested. The fall-out from the Chernobyl accident affected environments which are mostly in temperate regionn opportunita d san r testinfo y g resuspension models swa presented.

Food processing losseremovae th s- radionuclidef lo s frofood-chaie th m n to man as a result of food processing and culinary preparation.

The significance of the reductions in radionuclide contamination of foodstuffs which result from food processing and culinary preparation has been recognise manr fo dy years. However e informatio,th n available th n o e reduction factors achieve varioue th y b ds processea functio s a d f nso an radionuclide was scarce and poorly documented. The need for realistic dose assessments after the Chernobyl release made modelling deficiencies of this type apparen d stimulatean t areae w th wor ne .dn i k

Seasonalit varyine th - y g respons radioactivo et e contaminatio f fooo n d crop d othesan r environmental system e tim yeath f o eo st r whee nth contaminating event occurs.

The variation of the contamination of environmental materials with season has been most clearly demonstrated in grain crops. Early experiments showed that depending upostage th ngrowtf eo croa f po h when contaminated e leveth ,f radionuclido l e concentratio e finath n li n grain product can vary by more than a factor of 100. Because of the season of the year whe Chernobye th n l accident occurre becausd dan fall-oue th e t affected countries in different geographic latitudes, a significant variatio apparene th f no t degre f radionuclideo e transfe same th e o t cror p type with latitude was seen. This was due to seasonality effects. Pre-existing food-chain t represenmodelno d sdi seasonalite th t y effect very well, if at all. The Chernobyl experience has emphasised the need for e takeb o it nt into accoun predictivn i t e models.

e followinTh g reviews were prepare namee th dy db author havt d sbu e ha the benefi reviea f to w process which, involve membere e dth th f so Terrestrial Working Group of ¥AMP. The versions presented in this document have been revise tailso t d into accoun e commentth t s received froe th m Working Group. Publication was finally decided upon at a meeting of the full VAMP Research Co-ordination Meeting in March 1991, and after the approva VAMf o l P member y correspondence(b s Autumn )i n 1991. Chapter 2 RESUSPENS1ON FOLLOWING CHERNOBYI

J.A, Garland, N.J. Fallenden . PlavforK , d AIÎA Environmen d hnergyan t . Harwell Laboratory, Didcot, Oxfordshire, United Kingdom

2.1. Introduction

Resuspension comprise processee th s s whic y raishma e deposited material from the ground. It is thus related to, but in principle distinct from, suspension, where no previous airborne condition is implied, and entrainment, whic suspensios i h n winde causeth .y b d Howevere ,th resuspension mechanisms usually include the entrainment of particulate materia windn i l s passing over surfaces d thioccun ,an sca r ovey an r natural or artificial surface from which particles or droplets may be detache wine other th o d y db r disturbance. Therefore distinctioe ,th n between resuspension and suspension is often ignored. The material initially deposited may be changed in its physico-chemical characteristics during its contact with the surface. For example, it might become attached to other particles. In conditions of continuous emission from the primary difficule b source n ca mako t t ,i e quantitative measurementf so resuspended material, because of its similarity to its source material before deposition and the relative sizes of the concentrations of the material before depositio d aftenan r resuspension.

Resuspension has the potential to cause persistent air concentrations followin briega f release redistributo t d ,an e material depositee th n o d ground. Inhalation hazards, recontaminatio previouslf no y cleaned surfaces and contaminatio f cropno e possiblar s e consequences. Plan copinr fo s g with the aftermath of accidents that result in spills or airborne releases, and consequence assessment models, must make allowances for resuspension processes.

Despite many measurements, the prediction of resuspension remains uncertain. Many factors influence resuspension, including various facets weathere oth f surface ,th e structur naturcontaminane e th th f d eo an e t TABLE I

SOME FACTORS THAT MAY INFLUENCE SESÖSPENSION

Time since deposition Wind speed

Natur surfacef o e : vegetation, building etc.

Surface moisture

Soil chemistry and texture Size distribution of contaminant particles

Chemical propertie f contaminanso t

e depositioTh n process dryr o it win;we d speed, precipitation amount etc. Mechanical disturbanc y trafficb e , agriculture etc. Dept d methohan f cultivatioo d n Intensity and frequency of rain Snow cover or freezing of the surface

(see Tabl . ConsequentlyeI) , field measurements sho widwa e rangf o e oftes behavioui t ni difficuld ran associato t e changes with specific causes.

Data available from observation Americat sa n nuclear site weapod san n test sites have been summarise wide th e d rangy Sehmean db f ] eo [1 l information available on the topic has been described by Sehmel [2] and Nicholson [3]. Generally, arid or semi-desert areas predominate in the results, and a strong dependence on wind speed is apparent. Additional studies have used wind tunnel controller so d application f tracerso o t s outdoor surface investigato t s e individual resuspension mechanisms (e.g. Garland. Eesuspensio5] , [4 , trafficy nb , agricultur somd ean e other types of mechanical disturbanc bees eha n demonstrated summarises ,a Nicholsoy db n [3]. Experiments designe investigato t d e such factors have also demonstrated an important reduction in resuspension with time after deposition. Several models have been proposed to describe this effect (see Ref. [6]).

10 Results from wind tunnel experiments, mechanistic field investigations, and even monitoring results from contaminated areas within nuclear establishment weapor so n test sitese inappropriatb y ,ma r fo e application in some areas. They may represent too great or too small an are f contaminateo a d surface climateth r o e , surface roughnesse th r ,o density of traffic or other source of disturbance may differ. In principle the effect f theso s e parameters have been investigate a correctio d an d n coul attemptee b d r recognisefo d d differences t knowledg,bu incomplets i e e and uncertainties would be great. This is particularly true for the humid climate of Europe where there have been few investigations of resuspension.

The Chernobyl accident of 26 April 1986 provided a unique opportunity to observe resuspension from a brief event which caused widespread contamination in Europe. This paper attempts to draw together data from several laboratories that have reported measurements following Chernobyl, comparo t d e resultan th e s with expectation base previoun o d s experience.

2,2. Definitions

Three parameters have been use o describt d e resuspension [3]e .Th first is the resuspension factor:

, Concentration in air, C (Bq m— 3 ) = —————————————————a————— ) n d K ) (I — Surfac) e depositm q (B ,d

e advantagwhicth s hha e that both numerato d denominatoran directle rar y measurable. However, measurement of K may be complicated since the concentratio y includma r ai e n importani n t contributions from processes other than resuspension. In addition K is likely to be strongly dependent on such details of measurement technique as the height of air sampling above the surface. In evaluating d a decision must be made regarding the depth of surface to be included, and it is not straightforwar o decidt d e what dept f soi ho y contribut lma airborno t e e radioactivity n practiceI . predictior fo , resuspensiof no n fron a m accidental dispersion totae conveniens i th t ,li e amounus o t t initially deposited, without allowanc verticar fo e l mixingr intfo e soi th r oo l remova weatheringy lb .

drawbace th s ha k thaK must i t t variatioe depenth n d witdo f nho distance from the point of measurement. At locations with relatively low

11 deposit, transpor wine th d y b frot m area higf o s h deposi y dominatma t r ai e concentrations. Although ther s beeeha n some theoretical investigation relevan o thit t n appropriatsa problem, 8] , [7 ,e averaging d scal r fo e t beeno ns establishedha .

In principle, the difficulty of spatial variations in deposit is circumvented by the use of the resuspension rate:

Resuspension flux, R (Bq m s ) ————————————— —————————— — (2) ) m q (B d fractioe th Thus s i n,A remove seconr pe d y resuspensiondb . This quantit n ofteca y derive e b n d directl winn i y d tunnel measurementd an s laboratory studies. However, it can only be readily deduced from field observations in exceptional circumstances. In principle, A may be include atmospherin i d c transport model describo st movemene th e f o t contamination froe are anotheo on mt a y resuspensiorb d depositionnan s ,a well as to predict air concentrations (eg, Ref. [8]). Such models, with a knowledge of A, appear essential for predicting air concentrations at locations downwind of a contaminated area.

The use of the equivalent soil concentration

3 ) ( m~q (B ) C S (kg «f3) = ——————————— 8 —————————————————— ^ (3) Concentration in surface soil, C (Bq kg ) S

avoid neee decido th st d e what dept f soih o o include calculatiolt th n i e n allowt I . sK o fsurrogat e soil tracer usee b o estimat t do t s r ai e concentrations fro radioactiva m e contaminan hat t t beesoili n i t no 1 t n ,bu much used.

makA d allowanco e definitionn effecte an Th th S r , seK fo f so of the many environmental variables that may influence resuspension rates. Large variations must therefor e expecteb e d with wind speed, time after depositio witd othee nan th h r parameters liste Tabln i d . I e

2.3. Available Estimates of Resuspension

The resuspension factor, K, is the parameter that has been used most frequently to describe the results of previous studies, and for predicting the consequence contaminatioe th f so surfacesf no . Field measurements

12 0 001 ————— Lmsley (1978) [6]

0 0001 r--- ___. ______Anspaugh (1975) [10]

~~~----.„ —————— USAEC (1974) [9j 'E 1E-05 ~~~~~---.^ """"^^ — — — USAEC (1975) [11] o o IC-06 _0 —Garlan — ^ ~- — — d (1982 \ —] X —(5 ) ——-~-^_^ v - ^ c o 1E-07 ui c o Cl 1E-06 l/l ; "^^^^^ ^ in ^^^"^^ci. ^*v a 1E-09 CL Nf -->-._^ IE- 10 ^-^

1F-1 1 ii iiiii««' i t i i i ( i 1 1 n i i t i i n n ! a 1 i i a n i n 1 i « ï i i i ! i } 10 100 1.00010.000 100.000 Time (doys) l Resuspensio G FI n factor measure) (K s Europn di e (hatched area) compared with models 'Iho model relationships are- Linsley K = lO"* exp(0.01 t) + KT9; Anspaugh K = 10'4 exp(-0 15 l1'2) + 10 y,

USAEC (1974 = !0' 5K ) exp(-0013 + !

(e.g. Ref. [1]) suggest that soon after deposition K is of the order of ovet bu perioa r, yearsf m o d 0 ,declineK 1 1 - o t 4 o - st 0 1 -6 approximately 10- 9 m- 1 . A number of empirical models represent this behaviour (see Fig. 1). One model [9] allows K to vary with particle size, ascribing a value to each of several size intervals and setting K inversely proportiona depositioo t l n velocity.

The last mode] listed in Fig. 1 is based on wind-tunnel studies . Thes5] , e[4 studies wer agreemenn i e t with field experience than ,i tK increased strongly with wind spee d decreasean d d with time following deposition. K also increased with particle diameter in the range from about 1 to 5 urn. The decrease with time was represented by an inverse-time relationship.

Informatio lonK n gno after depositio gleanee b n nca d fron measurement nucleaf so r weapon test debris concentrationr Ai . grount sa d level have always been subject to some input from the stratospheric reservoir, so that only upper limits on K can be deduced. Data for over Unitee ai th r n i d s KingdoC m show that year3 ,1 s after peak deposition m less and wa 0 s 1 , ,K tha aftex nyears2 2 2 r , less —9 —1 than 5 x 10~ m~ . Consideration of radionuclide ratios and trace element concentration soid bees an lha r n ai use refinn o si t d e limits

13 further, and Garland [4] and Cambray et al. [12] argue that K cannot - l1}1 —10 —1 have been greater than 7 x 10 or 2 x 10 m , 15 or 18 years after deposition, respectively.

The effect of countermeasures on «suspension is indicated by observations at Palomares, In 1966 two nuclear weapons were destroyed by fire followin accidenn a gaire e bombth Th .n si t burne n impaco d t with the ground causing plutonium contamination over an area of a few km . Subsequently, continuous measurements of plutonium in air were made at four sampling station e contaminateth n i s d zone [131. Using estimatef o s the initial level of deposition and the air concentration data, the mean firse . Sooth m ntr yeafo value 0 K 1 r f x rangso 2 o et fro2 m0. -9 -1 after the accident top soil was removed from the worst affected areas, and in other areas surface concentrations were alleviate deey b d p ploughing. Presumably these actions account for the low values of K. During the following four years, air concentrations declined rather erratically at all stations about five-fold. At two stations where measurements continued concentrationr ai e ,th s remained roughly constan e reduceth t a td level for a further seven years, but rose again in 1977 when cultivation bega previousla r nc y unused, contaminated area. These data applo t y rather arid conditions in southeast Spain.

2,4. Opportunities from Chemobyl

In the following, the observations after Chemobyl will be examined in terms of K. Generally, only long term mean concentrations are available, parameter responsthe manthe to of yK and hiddeTablof ein sare I ein n values which are appropriate to the climate, rather than the short term weather.

e ChemobyTh l accident yielde a drar e opportunit e studth f o yr fo y resuspension, sinc providet i e d what coul e considereb d a larg s a d e single pulse of radionuclides of limited duration. This pulse was fairly rapidly dispersed over a large part of Europe. Deposition continued over a few s essentiallweekswa d an ,Junef o d y. en complet Howevere th y b e , data give y Cambra. nb [14 al ]t e y shows tha cenr t pe ovet 0 occurre9 r d mi y db May.

The main contaminated air mass arrived at locations experiencing considerably different climatic regimes, where, for example, in some cases spring was well advanced! and in others was in the early stages. Continental, maritime and mediterranean situations all received a signal from Chernobyl. This brings the possibility of observing the transfer of radionuclides throug e environmentth h , includin e resuspensioth g n process, unde a varietr f conditionso y e comparisoTh . f suco n h observationy ma s enable the relative significance of the various conditions to be established.

Data obtained following Cbernobyl permit direct estimation of resuspensio mann i n y area d extenan se informatioth d n availabln o e resuspension to climates not previously represented« However, these observations have limitations. They give information on only one radioélémen - caesiumt e depositioTh . s vernwa y variabl n somi e e areas, and even where numerous measurements of the amount deposited have been made their representativenes doubtn i e b . y Thersma soms ei e questioo t s a n whether local resuspensio e onlth ys i nsourc materiaf eo l measuree th n i d air: contributions due to transport by the wind of resuspended material from more heavily contaminated areas may be significant.

Cs and Cs were the most widely distributed long lived radionuclides from Chernobyl, The ratio between these radionuclides varied within a narrow range about Cs/ Cs = 1.6 [14] and this ratio has been used as evidence that the persistent radiocaesium in the atmosphere did derive from Chernobyl. However, the shorter half-life and smaller quantitrelease Cs accidenthe in of minodyof t Cs makr interese t in assessing resuspension.

Informatio n otheo n r radioéléments significanf woulo e db t interest. Resuspension may be influenced by the physico-chemical behaviour of radionuclides in soil and other environmental compartments. For example, Garlan] observe5 , [4 dn increas a d n resuspensioi e n with particle size. Many other radionuclides were observe n Europi d e soon afte e accidentth r . However, they were mostly short lived or wore present in small quantities d gavan e little opportunit r observinfo y g resuspension.

Garger et al. [15] observed the resuspension rates of14 4 Cs,13 7" Cs and 95Zr/N exclusion bIo withi0 3 e n nth zone around Chernobyl. Some differences in resuspension rates were observed but there was not a consistent pattern n somO . e occasion e resuspensiosth s C n ratr fo e 144 95 exceeded that for Ce and for Zr/Nb, while in other cases the reverse was true.

15 The limited data suggest that any differences between radionuclides are much smaller than the two or three orders of magnitude variability between measurements on different occasions. However, these results apply nearelease th r e point, where large fuel particles probably dominated deposition for the radionuclides measured, and a different behaviour might apply in other circumstances.

2.5. Data Following Chernobyl 2.5.1. Time series resuspension data

Experimental result monthlr fo s y averag concentrations C e n i s near-groun havr ai de been obtaine 4 station1 r fo d s across Europe. Typically measuremente ,th s used high volum samplersr eai , operatint a g 3 sampling rates of 1 to 10 m per minute and using high efficiency filters.

In all cases, measurements of the direct deposit from the Chernobyl accident were available y eithe,b r direct deposition (we d drytan )soir o l 134 sampling, where the Chernobyl contribution was estimated from the Cs concentration. This has enabled the air concentrations to be converted to restispension factors n thiI .s review Chernobye ,th l direct deposis tha bee e deposin th assume e b to t dmeasure d betwee e acciden th date f nth o e t Jun0 3 ed 1986an . After this timdeposie th e bees tha n e du assume e b o t d to indirect mechanisms, such as resuspension. Thus, the resuspension factor at time T was calculated by dividing the measured air concentration amoune atth timy tb depositeeT d soon afte accidente rth , wito hn correction for gains due to deposition after 30 June 1986, or removal by resuspension or by dispersal or transport within the soil.

Example variatioe th f so f resuspensiono n factors with time showar e n in Fig. 2. Each data set has been fitted by an exponential function which is also shown in the figures. A summary of the parameters is given in Table II.

2 For the 14 sites, the initial deposit varied from 52 to 43700 Bq/m . In all cases the resuspension factor, K, decreased with time over the observation e exponentiaperiodth d ,an l functio nexp(-BtA ) gava e reasonable fit to the data. Values of the parameter A, corresponding to K in mid-June, 1986, were in the range (3.6 - 49) x 10— 9 m— 1 , and values parametee ofth whic, rB h specifie exponentiae th d l declinn i e resuspension, were in the range 0.026 - 0.124 per month.

16 49e-00371

K.m'1 10

K,m

69 12 3 69 12 369 12 36 6 9 12 3 6 9 12 3 69 1986 1987 I9B6 1989 Dote 1986 1387 19f£ Dote CHILTO • N'"C s RESUSPENSION FACTOR Im"') NEUHERBER 1J• G 'Cs RESUSPENSIOU7„ N FACTO' Im R

Fig. 2. Examples of data for resuspension of 137Cs from Chernobyl. TABLE II

137Cs RESUSFENSIOH FACTOR (K)

Air concentration («•) (Bq m ) K(t) (m"1) =- Surface) deposi~ m q (B t

Time dependence fitte y exponentiab d l function: exp(-BtA = Ktim = t n monthi ( e) s after mid-June 1986)

Initial A B Deposit Period of Location (Bq m~2) Observation (m~1X10~9) (month"1) Reference

Klagenfurt, Austria 43700 1/87-12/89 3.6 0.049 16,17,18,19 Neuherberg, Germany 19700 7/86-12/88 7.4 0.090 20,21 Biegenz, Austria 13200 1/87- 8/89 5.3 0.061 16,17,18,19 Ispra, Italy 11900 7/86- 6/88 5.9 0.026 22,23,24,25 Nurmijärvi, Finland 7100 7/86-12/89 10.0 0.063 26,27,28,29 Vienna, Austria 4000 1/87- 8/89 12.8 0.053 16,17,18,19 Warsaw, Poland 3200 7/86-10/89 15.0 0.062 30, 31 Braunschweig, Germany 2700 7/86-12/88 28 0.124 32, 33 EskmealsK ,U 2500 7/86- 6/89 16.0 0.085 23 , 34 Berlin, Germany 2300 7/86-12/88 35 0.093 93 , 32 Rise, Denmark 800 7/86-12/88 31 8 3 0.10 , 6 37 , 36 1mo Bo,mh Denmark 620 7/86-12/88 31 0.082 36, 37, 38 Skibotn, Norway 195 7/86-12/88 35 0.060 32, 33 CM 1 ton, UK 52 7/86- 6/89 49 0.037 39,40,41

Thernegativa s i e e correlation betwee e initianth l deposi. A d an t The Spearman rank correlation coefficient is -0.96 which is significant at the >99.9X level, (see Fig . However3) . o systemati,n c variatio witB f ho n initial deposit is apparent.

The variation of K with deposit has been confirmed in a larger data set in Table III, which includes some stations for which the data were unsuitable for the time trend analysis of Table II. Table III also shows that the dependence of K on deposit has persisted over two years. Moreover, Bjurman et al. [42] observed resuspension at four sites in

18 50 c- es

T's3 10

c o

20 100 1000 10000 Deposition Apri Junl- e 2 1986m" q ,B

Fig. 3. Variation of the resuspension factor in mid-June 1986 with the amount deposited during April-June 1986.

Sweden. At Gavle, the deposit was 30 to 50 times larger than at the other Swedish sites K average d ,an d over Jul Decembeo t y0 time 1 o t sr p u 198 s 6wa smaller.

The correlation between A and the initial deposit shows that, although the concentration of Cs in air soon after deposition increases with the amount initially deposited, the rate of increase is significantly less than proportional to the deposit. Two possible explanations for this difference have been considered. Generally, different deposition mechanisms operated for large and small deposits, the large deposits being t depositiocausewe y b d heavn i n y rain whil smale th e l deposits were du e mainly to dry deposition. A real difference in resuspension factors, consistent with the observations, might be due to a greater availability for resuspension of material deposited dry than for wet deposited material. However, a 'memory' of a year or more of the circumstances of deposition woul requirede db d thi,an s seems improbable e seconTh . d explanation involves long range transport of resuspended material. This would increas observee eth d concentratio depositw arean lo ni f so t ,bu reducarean i higt f sei o h deposit d produc,an apparenn ea t variation ni

19 TABLE III

137Cs AIR CONCENTRATIONS AMD MEAN RESÖSPKNSION FACTORS

Initial Mear nai Resuspension Deposit concentration factor Site (Bq m-2) (pBq nr3) (10~9 HT1)

7/86-6/87 7/87-6/88 7/86-6/87 7/87-6/88

Neuherberg, Germany 19700 96 27 4.9 1.4 Ispra, Italy 11900 69 54 5.8 4.5 Hurmijïrvi, Finland 7100 68 23 9.6 3.2 Lerwick, UK 4600 2.7 1.4 0.6 0.3 Warsaw, Poland 3200 39 14.5 12 4.5 Braunschweig, Germany 2700 46 9.9 17 3.7 Eskmeals, UK 2500 37 7.8 15 3.1 Berlin, Germany 2300 57 19.6 25 8.5 ConligK ,U 2200 6.7 2.6 3.0 1.2 EskdalemuirK ,U 820 9.5 3.3 12 4.0 Ris«S, Denmark 800 18.5 3.6 23 4.5 Bomholm, Denmark 620 14.4 4.4 23 7.1 SMbotn, Norway 195 6,3* 3.3 32 17 Tromso, Norway 175 2.6 1.7 15 9.7 OrfordnessK ,U 110 10.3 4.0 94 36 Compton, UK 105 29 3.0 280 29 CM 1 ton, UK 52 3.1 2.7 60 52 Harwell FC, UK 52 3.8 1.8 73 35 Harwell CM, UK 52 69 6.2 1300 120 Milford Haven, UK 18 1.5 0.7 80 40 month1 1 * s data

Data sources as for Table II and Garland and Cambray [43] for additional UK stations.

resuspension factor. Very simple modellin transpore th f go t process suggests that such an explanation is plausible.

Chiltoe th case th f eo n I data set, e correspondinth f o e on o gt smallest deposits, ther soms i e e evidence, albeit inconclusive sprina f ,o g peak in the air concentration. A spring peak is characteristically

20 observed In the effects of debris from past nuclear weapon tests, and is explained by the return of material from a stratospheric reservoir. Thus there is a suggestion that a small fraction of the Chernobyl release was injected into the stratosphere, (Aoyama, [A4], reported similar observations in Japan.) The Chernobyl material returned from the stratosphere woul e difficulb d o identift t t locationa y s whic d receivehha d large deposits because of the relatively large contribution from local resuspension. Hence, there would be more chance of observing a stratospheric effect at Chilton than at most other sites. Stratospheric return would also reduce the differences in air concentration between sampling sites mighd ,an t contribut lace proportionalitf th ko o t e y between air concentratio d depositan n .

2.5.2. Traffic

t Rls«a r J ai (AarkrogMeasurement n i . [36] s al C t ,e ) f shoso w a pronounced weekly cycle during July and August 1986. Concentrations were high during weekdays and low at weekends. Later this pattern disappeared. The weekly periodicity was attributed to resuspension by traffic of Chernobyl deposit on nearby roads, which were busy on working days but quiet at weekends. After August, the Chernobyl deposit had presumably been removed from road e roa r fixeth o longeso n d o s t surfacd wa r d availablean e for resuspension.

A comparison between two sites at Harwell Laboratory also suggested that traffic is important. One sampling site (Harwell CM, in Table III) is located in a car park and the second (Harwell FC), a kilometre away, in a field wit o roadwahn y withi hundrew fe na d metres 20-folA . d differencn i e air concentratio s observenwa d durin yeae th gr July 198 6Jun- e 1987d an , the difference persisted, though somewhat diminished e followinth n i , g twelve month sampling period .neighbourine th Althoug parr d ca kan e hth g o hourtw roadsr o buse eac onlr e ar sfo y hyon dayhighese th , t post-Chernobyl resuspension factors were observe thit a d s locality.

2.5.3. Scale length for resuspension

Large differences between neighbouring sites show that variationn i s air concentrations occur on a scale not exceeding some tens of kilometres. Indeed, where local variation traffin i s c occur, concentration vary sma y substantiall kilometra n . i y Furtheso r eo r indication lengte th f ho s

21 scale for resuspension are found in the data for selected sites. Weekly 137 e islanth t f Bornhola o d r ai d Ris n measurementan mi e s werC " e r fo s compared (Aarkrog et al. J37]) with the frequency of wind speed and direction t botA . h sites, a positivther s wa e e correlatior ai f o n concentration with winds from the east, and negative correlations with westerly winds. Both site e coastaar s l wit e eashd wate th lanan to o t t rd the west, and the correlations support the view that the source of resuspensio dominantls i n y nearby land areas, withi a rangn m f abouk o e 0 2 t (the distance across Bomholm) o correlationN . s with wind speed were revealed.

Low resuspension factors were found at Lerwick (Table III) which is near the east coast of a strip of land only 5 km wide on the island of Shetland.

2.5.4. Comparison with models

e exponentia e rangth Th f o e l functions i e valuefitte th K o f t o ds show n Figi n , alon.1 g with models previously use o providt d a descriptioe n of resuspension. The models show a wide divergence over the time interval occupied "be data yth o somT . e extent thi s determinei s e differenth y b d t circumstance d usean s s intendee modelsth e Chernobyr Th fo .d l data teno t d support the models predicting lower rather than higher concentrations, but the limited time range of the Chernobyl data currently available must be kep mindn i tn additionI . e dat, th mosa f o sett s reflect conditions where disturbanc d vehiclean n ma s slighti sy b e . People workinf dooro e t ar sou g liable to generate dust locally and to be exposed to higher concentrations in consequence, and Linsley [6] suggested that an increase of an order of magnitude in predicted concentrations may be appropriate.

2.5.5. Deposition of resuspended Cs

Garland and Cambray [43, 45] noted two unexpected features of deposition measurements following Chernobyl. Total apparent deposition velocities (i.e. the flux to a deposition collector funnel divided by the —1 137 air concentrations C amoune th f d o t an , ) rangeabouo t s p 3m tu d collected during July 1986 to June 1987 at some sites was comparable to that deposited in May-June 1986. In comparison, Aarkrog [37] noted that at Rise and Bornholm the amount deposited in 1987 was just 2.1 per cent of the initial deposit.

22 10,000 30,000 100,000

1,000 S.OOO 10,000 30,000 100.000

30 100 300 1,000 3,000 11.000 30.000 100,000 Depositio 1S8n 6Ju (Chemobyl• n nJa J m q )B

Fig. 4. The amount of resuspended material deposited during (i) July 1986-June 1987; (ii) July 1987-June 1988; (iii) July 1988-June 1989.

23 e depositioTh f «suspendeo n s oveC a perior d f threo d e yearst ,a several cite Europen i s s displayeI , A decreasn Figi d . .4 e with tims i e apparent s alswide i th os e ,a variabilit e amoun e ratith th o tt n oi y originally deposited. There is no apparent trend in this ratio with the amount initially deposited e width et scatte,bu e result th n y havi r sma e obscured such a trend.

It seems probable that the observed deposition involves material resuspended very locally, as a result of rain splash, wind or mechanical disturbance. Particle t leasa f to s several ten micronf so s diameter would explain the high apparent deposition velocities. Air samplers are prone to undersample such large particle d theisan r sedimentation velocitf o s i y order tens of centimetres per second. The explanation of apparent deposition velocities of order 1ms probably involves an exaggeration of the true deposition velocity as a result of biased measurement of the air concentration. The very variable deposition velocities and fractions re-deposited suggest that local characteristics of surface condition and vegetation cover have a marked effect on the suspension rate, or that the amount collecte strongle b y ma d y influence e size d heighth th ean d y db an t exposure of the deposition collector.

2.6. Significance of Resuspension

2.6.1. Air concentration due to resuspended particles

Models which describe resuspension in terms of the resuspension factor y readilma , ,useK e yb comparo t d predictee eto d inhalation dose du e to resuspended material with the dose caused by the passage of the plume resulting directly fro releasma airbornf eo e material. This section sets out the results of such a comparison for the resuspension models introduced earlie ralsd (Figan o ) 1 consider. correspondine sth g comparison derived from field measurements following Chernobyl.

It is convenient to make these comparisons by calculating the ratio A /A , where KD lT dosr ai e integrae e th (thath , s f concentratioi tis o l A_ r ai n i n K over time) due to resuspended material and A- is the air dose dudue< to the initial passage of the cloud of airborne material.

24 If V is the total deposition velocity due to dry and wet deposition processes e quantit,th y deposited durin e initiath g l passage clouth df o e subsequene th d an is tV givef D concentratioo t s na e du r ai n i n resuspension will be DjV_K(t) where K(t) is the resuspension factor at time t following the initial passage of the cloud.

Thus, for each resuspension factor model, the ratio

A T J--(TJ rT TV 2 )=

give measurs a e relativth f eo e importanc f resuspensioeo n durine th g

comparison i ? T perioo t n. T dwit initiae th h l passagcloude th f .eo

T withi d calculatee range an e b rati y valuth nI Th y T ean oma f r eo fo d of validity of the models listed in Fig. 1, while the measured air concentrations following Chernobyl can be used to calculate A /A K Tl directl timesr fo y exceedin, ,T g abou monthst2 e appropriatTh . e valuf eo V_ for this comparison requires some consideration. Following Chernobyl, V ranged from ~0.1 min s- 1 in areas where dry deposition occurred to 1 _i ~0.1 m s in areas where heavy rain coincided with the arrival of the plume. For the calculations, a value of 0.01 m s~ has been used as a representative value shoult I . e remembereb d d that larger value, ¥_ f so y occuma r both where heavy rain enhances deposition wherr ,o e very large

particle presente ar s d tha,an t proportionas Ai R/A . Tabl V V o I et l

show valuee sth Af /Aso calculate resuspensioe th r fo d n model timer sfo s

T D M J. up to 50 years, probably an upper limit of the time for which the model can be considered valid. The table also includes corresponding ratios determined from measurements of Cs in air for a number of locations where sufficient dat availabls i a . determino SomA t e d e an eA T D K X caution is advised in applying these ratios for radiological assessment purposes, since the size distributions and behaviour on inhalation of the initia d resuspendelan d aerosols diffey ,ma r substantially.

e valueTh se tablshowth en ni emphasis e largth e e differences between the various models. Some predict resuspension doses similar to or greater than the dose due to the original cloud, while others predict resuspension doses whic quite har e insiptiiflean n thii t s comparison measuremente Th . s generally indicate thalattee th t r resuspension model e closee th sar o t r truth valueratiw e Lo th . of s o wer e observed even where rain resulten i d high deposition.

25 TABLE IV

E RATITH F RESUSPENDEO O DIRECR DOSR T D_ AI FO DOSR A E TAI A E T K l FIVE K-MQDELS AND DETERMINED DIRECTLY FROM MEASUREMENTS FOLLOWING CHERNOBYL

AU/AJ for time intervals Mode r o l —————————— Locationd 5 42 o t 00 6 to 36 5a d0 5 o t 0 d 0 79 o t 5 42

Anspaugh 8 5.3. 9 6 7. 0.84

USAEC 1974 0.61 0.64 0.27 0.002

USAEC 1975 2.3 4.7 2.1 1.0

Linsley 0.083 0.10 0.045 0.0025

Garland 0.006 0.010 0.0021 0.00064

Observations :

Lerwick, UK 0.1 0.005

Milford HavenK ,U 0.01 0.005

EskdalemuirK ,U 0.002 0.0007

ComptonK ,U 0.026 0.003

OrfordnessK ,U 0.002 0.0008

Tromso, Norway 0.002 0.001

Chilton, UK 0.003 0.003

Harwell CM, UK 0.06 0.005

2.6.2. Deposition on crops

It is well established that a fraction of material deposited from the atmosphere is retained on the leaves and other aerial parts of plants (Chamberlain and Garland, [46]): thus direct contamination of pasture grass d leafan vegetables results whenever toxi r radioactivo c e substancee ar s deposited. Here commonly used models are applied to estimate the possible effec f resuspendeo t d materia n contaminatinli g crops.

26 e fractionTh materiaf o , f , l intercepte e croth p y e b dcanopb n ca y approximated by f = 1 - exp(-pB), (5) (Chamberlain, [47]), where B is the dry weight of the above-ground portion of the crop per unit area of ground and p. is an empirical parameter, which may be a function of the physico-chemical properties of the material deposited, the mode of deposition, the structure of the crop canopy and the weather.

Observed values of u range from 0.2 to 4 m2 kg- 1 (Chamberlain and Garland, [46]). There is some evidence that p decreases with increasing particl ee inferenc sizeth f I . correcs ei t thadepositioe th t n of resuspended particle dominates i s y largdb e particles, then valuef o s e probablar g yk applicablem 0 1. o t e rang .th 2 n e0. pi . 2 —1

conveniens Ii t noto t e B <0.3u that r ,fo , exp(-uB )= (1-jjB o )s that (5) may be simplified to

f = uB. (6)

Then the fraction .ntercepted per unit dry weight of crop is

f/B = u. (7)

Material retaine lose leaven b o dprocessey tb y sma s suc wash-ofs ha y fb rain, erosion of leaf cuticle, blow-off and die back of older leaves. Several observations have shown that the consequence is an exponential decrease of contaminant from crop surfaces:

M/M = exp(-t/t), (8) quantitiee th e ar M s d retainewher an croe th eM p n initiallo d d an y n empiricaa aftes i t r ld timean tim , t ,e constant. Durin growine th g g season, t ~15 days.

It is possible to use the simple models represented in equations (7) and (8) to estimate the ratio, d /d , of the ingestion dose due to K X resuspensio ingestioe th initiae o nt th o nt l dos e contaminatioedu n event. Tiie e contaminatiotiminth f o g n even n relatioi t developmene th o nt d an t harves e cro crucials th i p f to . Henc considee ew exampleso tw r .

27 First, conside hypotheticaa r l crop whic harvestes i h d consumean d t a d a constant rate over an extended growing season for T days after the initial deposition. Then the dose ratio will be approximately:

(9)

assuming that T is several times t_. M

d an defines a ) e parametere (8 equationar B I Th dd T an d ) an i (5 ssy resuspendee e suffixerefeI th th d o t ran sE d materia d initiallan l y deposited material, respectively. Because of the particle size considerations mentione e similad b r les o abovey o sma t r _ tha; ,ji np

. p ] 0„ = _ u d wean consider u = p r

R is the fraction of deposited material that is resuspended and deposited again each day. Durin yeae gth r from July 198 Jun6o t e 198e 7th s frofractioC m Chernoby f o n l thas re-deposite range twa th en i s wa d 0.03 to -1.0. Then R ma1 y- b e3 - of order 1 04 - to 3 x 10 d , perhaps 1 _ A _ with a most probable value of about 3 x 10 d

Usin valuee gth s indicate parametere d th abov r fo e equation i s ) (9 n the ratio d /d for growing season of 100 days is expected to be about 10- 2 with a possible range of about 10- 3 to 10-1

dose Thith e s si rati o that would result durin e firsth g t growing season after deposition, assuming that the growing season continued for 0 day10 s after initial deposition. Deposition dose th e d ratioe ,an th n i , second growing season migh severae b t l times smaller (see woul d Figan d.) 4 ad smala d l, fractiod / d o nt

In an alternative scenario, initial deposition occurs T days before harves seasonaa f to l crop. Various loss processes deplet fractioe th e f o n the initial deposit that remains on the crop at harvest to p exp(-T /t-), whil accumulatioe eth d los nan resuspendef so d material throughoue th t growing season results in a contribution u_ R t{l-exp(-T /T )}.

In this case

dg= UR T R{l-exp(-TyTR^ RU-exp(-Tc/Tp)R>)J (1Q) d "IT

28 r shorFo T td thi / d s , rati„ T > o approximateT r fo T /|i d R ,an _ u s i KC CKKi C approaches u T R/u exp(-T /T ). If Tc is as long as 100 days this ratio 1 C 4 I K K T masubstantialle b y y greater than unity attenuatioe a resul th s ,a f o t f o n the initial deposit.

These sample calculations suggest that resuspensio y causnma modesa e t increas totae th ln I eingestio n dose through crop contamination. Resuspensio y sustainma n concentration croa n psI which would have been cleansed by field loss processes and may necessitate countermeasures over extended period f timso e afte e initiath r l contamination event.

It Is Important to appreciate that the calculations have used models beyond their usual range of application, and the results must be regarded as tentative.

2.7. Conclusions

measuremente Th s reviewed here have demonstrated that resuspensioy nma result in measurable concentrations in air for a period of at least three years following deposition in climates common in Europe. The resuspension factor ) derive(K s d from measurement differenn i s t region Europf so l al e show a reduction with time after the initial deposit. 1'he deposits varied byfactoa 800f ro . However siteo ,tw witsr exceptioe o wher th he on e f no traffi agriculturr o c e cause substantial disturbance shortly after deposit, . Thera Ks m ei varie viz, facto a 0 14 y .db .1 f ro ) (3.49 6- 9 —J strong negative correlation betwee direce nth t Chernobyl deposi. K d an t A possible explanation relates to the transport of resuspended airborne activity from area higf so h deposi o thost lowef eo r deposite Th . reductio e fittenb wit n dhca wittimK f exponentian ho ea l function, with the decay time constant within the range 0.03 - 0.12 per month. With few exception similas wa s K site t ra s with similar deposit contrastinn i s g climatic regions.

There is evidence that the source of the resuspended material is mainly the area around the sampling site. In the first months after the accident, mechanical disturbance of the deposit in this area, e.g. by road traffic, could provid largea e additional contributio resuspensione th o nt . At a site which received a low direct deposit, there is inconclusive evidence of a small contribution to the air concentration from material returned frostratospheree mth .

29 The air dose due to resuspension has been compared to the air dose due to the initial contaminating event at a number of measuring sites. In all cases the air dose due to resuspension during the first two years after the accident was less than 10 percent (and at most sites no more than about 1 percent) of the initial air dose.

The deposition of resuspended material has also been considered. The fraction of the deposited material that was resuspended and deposited again durin e firsth g t year afte e initiath r l contaminating event ranged from 0.0 1.0o t 1potentiae .Th contaminatinr fo l g crop uncontaminated an s d surfaces may be significant.

ACKNOWLEDGEMENTS

The authors thank the Central Electricity Generating Board (now Nuclear Electric) and the Department of the Environment of the UK for financial support. The views expressed in the paper are those of the authors and do not necessarily represent those of the funding bodies, nor UK Government Policy.

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[44] AOYAMA, M., Evidence of stratospheric fallout of caesium isotopes froChernobye th m l accident, Geophys. Res. Lett (19885 1 . ) 327-330. [45] GARLAND, J.A., CAMBRAY, R.S., 'Deposition resuspensioe th d nan long-term variatio f airbornno e activity from Chernobyl", Impact des Accidents d'Origine Nucléaire sur l'Environnement, (4e Symp. Int Radioécologie d . Cadarachee ed , 1988) Tom CEN/Cadarach, 1 e e (1988). [46] CHAMBERLAIN, A.C., GARLAND, J.A., Interception of Radioactive Fallou Vegetationy tb , AERE R-13826, HMSO, London (1991).

[47] CHAMBERLAIN, A.C., Interception and retention of radioactive aerosol vegetationy sb , Atmos. Environ (1970, .4 ) 57-58. Oia |»l er 3 INFLUENCF I!I F FOOlE« » PROCESSIN l LINARt' D GAN \ PREPARATION ON THE KADIONIJCIJDL CONTENT OF FOODSTLFFS: A REVIEW OF AVAILABLE DATA

H, Noordijk National Institute of Public Hcalih, Bilthovcn. Netherlands J.M. Quinault Cuinniissariiii à I"énergit e atomique, Centic d "etudes nuck'iiiies dc Cadarachc. Saint-Paul-le?-Duiance, h ranee

J.I. Introduction

3.1.1. Background

Radioactive contaminatio e environmenth f no e y resulth tma n i t increased radiation exposure of human beings due to their ingestion of radionuclides in food. In the chain of transfer processes which leads from e depositioth f radionuclideo n o soilt d plann san o s t surface o theit s r presenc e dietth n ,i e food processin d culinargan y preparatio e lasth t e ar n processes which can effect the radionuclide content of foodstuffs. In the years before the Chernobyl accident the effects of food processing and culinary preparation on the radionuclide content of foodstuffs received comparatively little attention although for some food products the reductions can be substantial. Studies and investigations in this field have instead focussed e processemainlth n o y f transfeso f radionuclideo r s componente ith n humae th nf o sfoo d chain.

Knowledge of the effects of food and processing and culinary preparatio needes i n d when assessin e radiatioth g n froe ma dos th mo t e ingestion of contaminated foodstuffs. Appropriate allowances have to be e reductionth madr fo e s produce y foob d d processing n ordei * r that doses t systematicallno e ar y overestimated A knowledg. e effectth f f o eo s special food processing or decontamination techniques is needed in order to estimate their effectivenes s possibla s e countermeasure r reducinfo s e th g

*In the remainder of this paper 'food processing' is used as a general term to include industrial processing and domestic food preparation.

35 dose to man following the contamination of the food chain with radionuclides in the aftermath of an accident.

Measurements of the transfer of radionuclides during food processing are comparatively scarce. Most tneasureoients date back to the sixties and w attemptonlfe a y s have been mad o reviet e w this literature [1-6]. These reviews are often limited to selected food classes. Also, the comparability of data is hindered by the variety of definitions used to define changes in radionuclide content of the food. Since the Chernobyl acciden n 198 I tw dat 6ne a have become available especiall behavioue th n o y r of radiocaesium.

3.1.2. Industrial and domestic scale processing

Food processing methods vary considerably from foodstuff to foodstuff d alsan o betwee e industria th ndomestie th d an lc scal eA foo (Fig d. 1) . product may be processed quite differently when grown locally in a garden d consumes familgrowean e hi th s d compare a y ran db d wit large hth e scale commercial productio same th e f o nfoo d product followe y factordb y processing e icsultin.Th significantle caseb o tw y g sma e losse th n i s y different. In the case of milk, modern processing techniques provide several alternative products each of which may contain different concentrations of the contaminating radionuclide (Fig. 2). This may be contrasted wick the small scale consumption of whole milk.

3.1.3. Data neede radiologicar fo d l assessments

Depending upo e radiologicanature th nth f o e l assessment, different type f informatioso needee nar n fooo d d processing losses assessmentr Fo . s of dose to identified groups of individuals living at particular locations, the ideal approach would be to obtain local information on food processing losses specific to the foods consumed by the group. This approach would minimise the predictive error associated with the food processing component of the dose calculation. However, this is rarely feasible and national or regional compilations of the type contained in this report are usually used. Nevertheless potentiae ,f tabulateth o e us le derro th processinn i r g loss factor reducee b n sy checkinca b d g thasourcee th t f informatioso n no which the loss factor is based are relevant to the circumstances of the dose assessment, for example, whether the food is locally grown and prepared or is subject to industrial processing.

36 NA I LI Rl 1S ICBA MAIL RIAIS

HA< \'\ ' IllJIj 1,' HIHIMvi f/l MM i M AIM III hin Q

loon PROOFSSINu twti DIRECT USir MAHK! i dftffit, - . —™ Cul I N AH Y f ••RL PARAT ION uousi t^toO INGESTION C| MAN P

Fig. I. Different types of food processing.

Milk Milk

Milk powder Cream Skim milk

Butter Butter milk

Butte t fa r Butter whey

Mil r Skiko m milk Milk or Skim milk

Cheese Whey Casein Casein whey

- ~ deskimme ^ d whey whey cream whey deproteinized proteins whey

* rennet or acid may be used to start the coagulation procedure.

e fractionatioTh Fig . 2 . milf o n k into product d by-productan s s in the dairy industry.

37 In more generic dose assessments suc s thosa h e use planninn i d g studies where dose hypotheticao t s l critical group e beinar s g predictedr o , in the evaluation of collective dose, regional or nationally averaged values of the loss factor may be appropriate. In one approach to collective dos e necessareb evaluatiot no o identify yt ma t i ne expose th y d population grou merelt bu p o assumt y e thal fooal t d producea n i d particular area is consumed. In this case an overall food processing loss factor could, in principle, be used. This is an averaged factor representing the total loss between the activity in the raw food product and that in the consumed material. However, in practice, the available information tends to be at the process level and is in the form of several separate loss factors between the raw product and consumption by man.

3.1.4. Objectives and scope f thio m s ai pape e preseno t th r s Ii t e informatiosurvea t th f yo n available on radionuclide behaviour during food processing. It expands on an earlier study supported by the Commission of the European Communities (CEC) [1] and takes into account new data. Most of these were presented at the Semina n "Radioactivito r y Transfer during Food Processin d Culinaran g y Preparation" organise Commissariae th y b d l'Energià t e Atomique (CEAd )an the CEC at Cadarache, France, in 1989. In addition, the paper takes into accoun commente VAMe th t th P f Terrestriao s l Working Group e datTh .a presente e reportear d n termsingla i d f o s e definitio e e changth th n f i eno radionuclide conten resula f foo o ts a dprocessingf o t A distinctio. s i n made between normal food processing procedures and special decontamination procedures which mighf importanco e b t emergencn i e y situations.

If not stated otherwise, all data presented in this review are based n experimento s which reflect contaminatio n fooi n d product tima t ea s after an accident, when contamination has been to some extent relocated and is no longer predominantly external. Thus, the data on plant contamination used n thii s repor e generallar t y derived from root uptake experiments, while thos n fooeo d from animal origi derivee ar n d fro vivn i m o studies. Shortly after an accident the contamination will be predominantly on the exterior parts of the product. For vegetables and fruit, separate values are available for contamination which is predominantly on external parts. These data have rather large ranges. Data which refer to the situation shortly after an accident are not available for other classes of food. However, the use of data, which refer to internal contamination, will lead,

38 case Ith nf frese o h contamination o underestimatio,t e th f no decontaminating effect of food processing since newly deposited external contamination wil easiee b l o removt r e than aged relocatean d d contamination.

3.2, Definitions

Several definition e literatur th usee n sar i d defino t e e changen si the radionuclide content of food due to processing. Most definitions are equal to or closely related to one of the three definitions presented here,

e changTh radionuclidn i e ) (A e contenfooo t de processintdu e b n ca g defined by the food processing retention factor, F , which is the total amount of a radionuclide In processed food divided by the total amount of this radionuclide in the original raw food (Bq processed per Bq raw). Thus, F is the fraction of the quantity of the radionuclide which remains in the food after processing datl Al .a presente thin i d s revie basee ar wn thi o d s definition.

(B) The effect of food processing on the radionuclide content of food may also be quantified by the ratio of radionuclide concentrations, measure d fres an fresn i dhw hra processe d food. (Bq/kg fresh processe Bq/kr pe d g fresh raw).

e thirTh d typ) definitiof (C eo bases ratia ni n radionuclidf o do e concentrations, measured in dried raw and dried processed food. (Bq/kg processed dried per Bq/kg raw dried).

The F value is considered to be the best way to define changes in radionuclide conten foof to thin i d s review becaus considerabla ) (a e e amount of literature data is already defined in this way, and (b) conversio F value o nt s appear possible b o t snearlr fo el collecte al y d literature data which is not the case for the other definitions.

orden I avoio t r d misinterpretations definitioe ,th illustrates i ) (A n d boiles C r dfo mea4 F valu 0. e t f Th eo wit. Sr h referencd an s C o t e indicates that only 40% of the Cs present in raw meat is retained after boiling, 60% is removed in the boiling liquid (Table I). In the case of dairy product syiele (Tabl th eacf do ) heII produc importants i t e th n I .

39 i ABI E i

Under-lined denote best estimates

Hethof o d Raw Material process 8^9 Sr Cs I IB u Pe

Meaf o t Boilin J 0.4-0.QJ g 9«eat 3 0. P_,4 0.2-6 0. .07 0.7 •anma 1 s Soiling bone 0.999 0.2-0 .Ï 0.98 0.7 1.0 (cow, pig Frying8 0. , roasting 0.5-0 .8 0.4-0.7 sheep, deer or gri 1 1 ing meat rabbit) Muncing meat 0.4 Microwave baking 0.4-0 .5 0.4-0.7 Pick! i ng wet 0.1-0 .1 0.9 dry 0.8 Marinât ing 0.1-0 .6 Sausage production 0,4-1 .0

s Bire S O. Boiling meat Baking meat 0.7-0 .8

Fish 9 0. Boiling meat 0-1 0.2-.09 0.5-0.9 Frying meat 0.8-0.9 0.7-0.8

References: [3, 6, 29, 42-58]

tables yiele ,th presentes I d d unde "processine th r g efficiencyg (k "P prepared product/k material)w gra exampler Fo . F valu n , a 0.6 f o e r 1fo goan i tr S chees removes econversioe i indicateth r S y db e th nf so tha% 39 t of goat milk to cheese, but, due to the 121 yield of cheese, the concentratio goan i tr S chees f no 0.61/0.1s i e time5 2concentratioe = th s n goan i tr o S fmilk .

It mus stressee tb dF value thal al t s referrin extractioo t g n procedures such as cooking, frying, etc., are only valid when the extraction liquid is removed and not used for other culinary purposes. The same applie fractionatioo t s n processes which daire takth ey. placeg n i e industr durinr o y milline th g f cerealso g moss A . t fraction usee r sar fo d human consumptionF value f o e s us shoul e ,th supportee db d witha thorough knowledg destinatioe th f differene o th f no t fractionsr Fo . example, the by-product of cheese-making, whey, was formerly regarded as waste or used to feed animals. Nowadays, a large part of the produced whey i sadditivn a use s a d foor humansr fo efo d . Similarly l fraction,al f so the milling proces usualle sar y use produco t d e food thesn I . e casesn ,a shoul0 F valu1. usede f db eo , r 40 ÎA81E U

UndeH inecä daïa denote best estimates

r S Product

Cream 0.07 04-0. Û 5 .2 0.05 0.03-0 .16 0.06-0 .19 0.08 0 .03- 0.24 S k i mm i Ik 0.93 0.75-0.96 0.95 0.85-0 .99 0.81-0 .94 0.92 0 .76- 0.97

Butter 0.006 0.002V0.012 0.01 0.003- 0.02 0.035- 0.01 0.04 0 .01- 0.05 Butter-mk I i 0.06 O.CB-0,07 0.05 0.02-0 .13 0.05-0 .13 0.04 0 .03- 0.14 Bulterfat o. ooi-o. ooa 0.00 0.00-0 .00 0.02 0.04 0 .04- 0.04

Milk powder 1.00 1.00 1.00 0.12

Cheese * goat 0.61 0.07-0.15 0.08-0.H 0.12 0.08-0.17 co« rennet 0.025-0.80 OUJ7 0.05-0.23 0.20 0.11-0.53 0^12 0.08-0.18 COM acid 0.04-0.08 0.11-0.12 0.22-0.27 0.10 0.08-0.12 Cottage cheese rennet 0.07-0.17 0.01-0.05 Cottage cheese acid 0.22

Yogurt 0.34

Whey * rennet 0.20-0.80 0.73-0.96 0.47-0.89 0.90 0.70-0.94 acid 0.70-0.90 0,75-0.90 0.60-0.73 0.82

Casein * rennet 0.10-0.85 0.01-0.08 0.02-0.12 0.03-0.06 acid 0.05-0.08 0.01-0.04 0.03-0.04 0.01-0.06

Casern whey* rennet 0.08-0.16 0.77-0.83 0.69-0.82 0.76 0.73-0.79 acid 0.67-0.86 0.83-0.34 0.78-0.80 0.76 0.75-0.79

* * Milk io n1 0. exchange 0.011 0.

COMMENTS * Separate values are given for the rennet and acid coagulation procedures "Decontaminatio n exchang io f milo n y b kn commercia o e l scale

References: [3-5, 7-41]

41 3.3. Effects of Normal Food Processing

3.3.1. Data analysis

The quality and reliability of all data on radionuclide behaviour during food processing was checked to the extent possible before they were incorporate e surveyth n i d. Firstly s requirei t i , d that experimentar o l test procedures should produc n artificiaa e l contaminatio e footh d f no products which is comparable to the contamination which would occur followin n accidentaa g l releas f radionuclideso e . Special atte/- s .iowa n given to speciation and to the spatial distribution of the radionuclides in food. Also, simulated processing procedure realistia se b nee o t d c reflection of the procedures normally applied to food before it is consumed. Informatio modifien no d procedures may, however relevane ,b n i t order to know the effectiveness of a planned decontamination method. Special decontamination procedure includee survee ar s th n yi d only when (a) they result in a lower contamination of the processed food than in the case of normal food processing and (b) when the food retains its nutritiona unacceptablt no l s valui d ean y change n tasti dd appearancean e .

The data was converted to F values and ordered on the basis of the r type of food, the method of processing and the type of radionuclide studied e largTh . e amoun informatiof o t n from more tha hundrena d articles and reports required a grouping of the different processing modes in order to presen usefue a dat th n ti a l forma subsequenr fo t t applicationse Th . tables present ranges of F values for different foods and processing techniques. Where possible, processing efficiencie alse ar o includedsP .

3.3.2. Data variation

In general, the data within each separate combination of product, procedure and radionuclide show a large variation. This variation may have different causes. Variatio e causeb y differencey b dnma yielde th n i ,s P . For example, the first row of data in Table I show the range in F values of Sr for cream. Th's range in F values is nearly identical to th e. Observe rangP n i e d concentration crean i close r ar mS o t ef so milkw thosra n ,i e wit h much less variatio then i n m F valuetha e nth n i s Table I suggest. For dairy products and cereals the differences in yield arn importanea t caus variationf eo . VariatioF value e e th th f so n ni other products, however, seem to be mainly caused by differences in the application of particular food preparation methods. In fact, the way in

42 which people prepare their food is a very important and specific part of their cultural background. Some ol the most important aspects of the preparation are the temperature, the additives used, the time spent on each step in the procedure and the mechanical treatments such as removal of inedible parts, peeling, slicing, etc. Also industrial processe y varsma y from country to country, leading to more or less refined products. For external contamination time th ,e between contaminatio d harvesnan t will cause variation in F values. In this case, climatological conditions or agricultural techniques, such as the addition of water by spraying rather tha y irrigationnb y als,ma o influenc F values e th e .

Best givee estimatar n P wheneve d ean valuee dat e F th r ar af o s r e adequat o permit e t these judgements e mosTh .t important feature e thaar st many data from different regions are available, that the range in the vast majorit e dat mucs th i a f ho y smaller thae totath n l range observed and, that extreme t typicano r certaie fo ar sl n regions. Regardin e largth g e P value f o o convere t so us t e F tth , F d variatioan P n i n concentration ratiot recommendeno s i s r extremfo d e values. Howeverr fo , best estimates or mean values the use of P will give a good indication of expected concentration ratios.

3.3.3. Dairy products

A considerable amoun f date o availablt ar ae behaviou th e n th o e f o r nuclides Sr, Cs and I during milk processing (Table II) (Figure 2). In this case F represents the fraction of the radionuclides which remains e processeth n i d food. However undes a , r normal circumstances nearll al y by-product e useother ar sfo d r food product - eveswhee f cheesth no y e production is used nowadays for beverages and other foodstuffs - only a small amoun f radioactivito t y wil e removeb l d froe die y milth mb t k processing. Following an accident, however, milk processing may be modified deliberately so as to reduce intakes.

The distribution of the radionuclides over the various products is influenced by the yield of each product. For example, a higher yield of cream will a proportionalllea o t d y highe F r value r creath fo ef i m increase in the yield does not affect the concentration of the radionuclide e creamith n .

e coagulatioTh n process appear havo t s a considerable e e effecth n o t transfer of Sr to cheese. F values for Sr are quite unpredictable in

43 the case of rennet coagulation, but often a large transfer to cheese is observed. Coagulatio n acidifyina y b n g procedure appear muca o lea t so ht d lowe r transfeS r nuclidesl cheeseo t al r r To e variatio.th , F n i n value r cheesfo s e production acid coagulatio s smallei n r tha y rennenb t coagulation.

TABLE III

FOOD PROCESSING RETENTION FACTOR F AMD THE PROCESSING EFFICIENCY P FOR r e LOWE A ORGANISMSSE R

Organism Method of processing F values

crevette cooking Ra:0.04-0.5 Pb:0.0-0.4 0.35 Po:0.04-0.8

mussels Washin d removagan l Ra:0.01 Pb:0.5 Po:0.02 0.25 of flesh

algues alginate production Tc:0.00.0h R , 7 Ru Sr:0.2 6 0.04 satiagum productio Rh:0.0, Ru 4n Co:0.04 0.08

References: [59-61]

3.3.4. Meat

Tables I and III give data on meat, fish and other marine derived food sources. Dat mean ao t processin t appeae influenceb no o o gd t r y animab d l type. Radionuclides in fish might behave somewhat differently when compare mammalso t d , althoug datw available fe ar a o hto n fiseo h processing to dra y firwan m conclusions.

3.3.5. Vegetable d fruian s t

F values for vegetables and fruit appear to depend highly on the typ methoe producf eo th processinf d o d an t g (Table IV) e variabilit.Th y

44 TABLE IV

FOOD PROCESSING RFIENTIO E PROCESSINTH N D FACTOAN r F GR EFFICIENCC P Y R VEGETABLEFO D FRUIAN S T

Date base ar an tota o d l contaminâtio e planth f to n

Plant Metho f processino d g Sr s C Other Nucl C ideP s

Spi nach Wasg n hi 0.4-1.0 0.6 1 0 Uashing & blanching 0.4-1.0 0.5-0.6 0.8 Cooking & rinsing 0.9 1.0 Co 0.9 0.7 Canning 0.5 0.2 0.7 Freezing 1.0 0 7 lettuce Removing inedible parts 0.5 0.7 Blanching 0.3-0.9 0.1-0.6 0.5

Cabbage Man nat ing 5 0. u R 9 0. 0.9 Uashing 0.3 0.9 1.0 Washin blanchin& g g 0.4-1.0 0.1-1.0 1.0 Cookin & rinsing g 0.8 0.7 Freezing 0.2-0.9 0.7 0.7 Canni ng 0.4 0.2 0 7

Cau louef li r Peeling 0.5 0.7

Beans Uashing 0.1 1. 0 B l anchi ng 0.3-1.0 0.6-0.9 0.9 Canni ng 0.3-0.8 0.4-1.0 Froth flotation 0.4-0.6 1.0 Brine grading 0.6 1.0

Tomatoes Uashing 07 1. 0 Peeling & slicing 0.7 0.9 Canni ng 0.8 Frying 0.5 0..5

Onions Peelin + washing + bolting g 0.5

Mushrooms Boi 1 ing 0.7-0.9 O.J-0.5 0..6 Boi ling in 2X NaCl 0.2 0.2 Canni ng 0.5 0.5 Parboi ling 0.1-0.4 Soakin f drieo g d mushrooms 0.1-0.2 Parboiling -* salting + soaking 0.00

Cucumbers Pickling 0.15 Canni ng 0 35 0.06

Peaches Peel i ng 0 5 0.9 Canni ng 0.5 Lye peel ing 0.09 0.03

Strawberries Rl nsi ng 0.7 0.6 1 .0

Bern es Making Puree 0.6-0.8 0.6-0.8 R insi ng 0.8

References [4, 29, 61-863

45 l«EV lE

FOOD PROCESSÜG RETENTION FACTOR F r AND 1HE PROCESSING EfFICiEHCY PC FOR ¥EGETABLES AND FRUIT

Data are based on external contamination only

Plant Method of Sr Cs 1 Other pe Processing s de 1 1 c My

2 0. Spinach Washing 0.2-0.9 0.07-0.8 Ry;0.4-0.8 1.0 Washin7 0. 4 blanchin* g0. g 0.2-0.9 0.6-0.7 Ru;0.5-0.8 0.8 Cooking + rinsing 0.4 0.7

Lettuce Uashi ng 0.2-1.0 0.1-0.5 Ru:0.2 1 .0 Removing inedible parts 0.1-0.4 0.1-0.4 Ru:O.Q1-0.3 0.7

Cabbage Removing inedible parts 0.9 5 0. Ru:0. 7-1.0 0.8 Washing 0.070.09 0.4 1,0 Washing + blanching 0.3 0.2-0.7 0.7 Cooking + rinsing 0,2-0.5 0.7

Cauliflower Peeling 0.05-0.2 0.03 Ru:0.02 0,7

Beans Washing 0.7 1 .0 Blanching 0.3 0.3 0.2 0.9 Frot4 0. h flotation 0.4 4 0. Brine grading 0.4

Tomatoes Washing 0.5 1.0 lini Bo g 0.2 0.7

Onions Removing inedible parts 0.2 2 0. Ru:0.2 0.9 Washing 0.3 0.2 1.0

Mushrooms d Na Boilin X 2 n i g 0.3

Berries Rinsing 0.8-0.9 Ru:0. 8-1.0 Making purée Ry:0.7 0.6-«

lini Bo g 0.3-0.5 0.2 Te:0.3-0.7 Ba:0.6-0.9 Zr:1.0

References: [29, 61-86] a resul e b differencef date o ty o th fama processinn i s g timd an e temperature, in other specific aspects of the processing, and in the rigidity of the cellular structure of the vegetable product, etc. For example muc,a h more efficient remova observes lwa severan o d l productr fo s steam blanching when compared to water blanching [78]. The high Sr removal from beans by washing might be due to large amounts of soil attached to the product, but no explanation was given in the relevant report [76].

46 Data on externally contaminated plants are presented separately (Table V), The scatter in these data is even higher when compared to internally contaminated plants.

I ABIE VI

FOOD PROCESSING RETENTION fACIOIR If r AND HUE PROCESSING EFFICIENCY f>e FOR ROOI CPOPS

w materiaRa s lC methoOthe r < Si processino rd radionuce P g l ides

Pot aï o Bo» 1 ing with peel 0 1 • 1 . 9 . 0 0.8-0.9 Po:0.4-0.7 0.9 Peeg lm 0,5-0.9 0.6-0.8 Po:0.3-0. Am:0, 5Pu . 1-1.0 0.8 Peel ing £ hol l ing 0.7-0.8 0.6 0.8 Frying 0,6 0.6 Hscrouave boiling unpeeled 0.8 0.8 Microwave boiling peelfd 1.0 0.6 Canning 0,7 1.0 0.6 uecon lamina t ion 0.5 0.05-0.2 Ru:0.5

Carrot Scraping + washing * boiling 0.8 0.8 Peeling , Ara4 Pu 0.:0. 7 5 0. 0.8 Cooking unpeeled 0.5-0,8 0.8-0.9 Microwave cooking unpeeled 0.7 0.8 Hicroyave cooking peeled 0.5 0.7

Beetroot Peeling 0.8 0.4-0. Am:0.4, Pu 7 5 0.8 Cooking unpeeled 0.3-0.7 0.9 Cooking + peeling 0.3 o.e Microwave cooking unpeeled 0.4 0.75 Microwave cooking peeled 0.3 0.7

Parsnip Peel ing 0.7 0.6 Pu:0.3

Swede Peeling 0.65 0.6 Pu:0.7

1 88 , 87 , 86 , 84 , 83 , 82 , 77 , 76 , References73 , 72 , 69 :, 63 [29 , ,62

3.3.6. Root crops

e effectTh f fooo s d processin generalle ar g y smal r roofo lt crops with e exceptioth beetroof o n t (Table VI). Peelinvere b y gma efficien n i t removing actinides ,e remova probablth o t soif o le lydu particles attached to the peel combined with the extremely low uptake of actinides from the soi plantsy lb .

47 3.3.7. Cereals

F value miller fo s d cereal e generallar s y lower tha5 0. n (Table VII). The values depend on the yield of the product, as observed with milk products. The conclusion which has sometimes been drawn that transfer of Cs and Sr to "dark' wheat flour is lower than transfer to "white flour" is not justified. Concentrations of Cs and Sr in 'dark' flour are higher than concentrations in "white' flour, but the yield P of 'dark seconr o '- d qualit - flouy mucs i r h lowe thesn i r e experiments. Remova f actlnideo l y millinsb alss i g o high.

3.3.8. Drinks

e limiteTh d dat Tabln i a e VIII indicate that normal treatmend an t processin f beverageo g onls ha sy modest effect n reducinso e th g

TABLI VI E

FOOD PROCESSING RETENTION FAC10K F|r »ND THE PROCESSING EFFICIENCY Pp FOR CEREALS

w MateriaRa l Method or fSi Processing m A , Pu Cs pe

Wheat grain H i 1 1 i ng to white flour 0.09-0.5 0.2-0.6 0.1-0.2 0.7 g n i 1 1 i M to dark: flour 0.1-0.2 0.05-0.1 0.05-0 ,1 g n i H Mi to semolina 0.15-0.5 0.2-0. 3 H i 1 1 i ng to bran 0.6-0.9 0.5-0.6 0.1-0. 2 Cooking wheat sprouts 0.9 1.8 Shreddin r puffino g g wheat 0.1-0.15 0.9-0. 95

Durum Wheat grain HI 1 i ing to flour 0.1-0.6 0.08-0 .8 Milling to groat + groatdust 0.3-0.4 0.6-0. 7 Hilling to bran 0.4-0.5 0.2 e graiRy n g n i 1 1 i H to white t lour 0.6 0.3-0.6 0.2 0.6-0. & H i 1 1 i ng to dark flour 0.2 0.1 Hilling to bran 0.35-0.7 0.15-0.4 Cookin ge sproutry s 0.8-0.9 1.9-2. 4

Barley graig n ni 1 1 i M to 5 whit0. e flour 0.2-0.6 0.1-0.2 0.6-0. 8 M i 1 1 i ng to seiuol i na 0.35 0.1 Milling to bran 0.4 0.4

Osts grain Milling to white flour 0.3 0.4 0.4

Pasta Cooking 2.2

References: [16, 29. 62, 67, 86, 89-99J

48 TABLE VIïI

FOOD PROCESSING RETENTIO PROCESSINE NTH D FACTOAN F RG EFFICIENCr P Y e FOR DRIHKS

Raw material Method of processing Sr Cs Other radionuclides

Surface water Conventional treatment watep tta o r 7 0. 1.0 Ru:0.3 Co:0.4 1:0.8

Tea Brewin minuteg2 s 0.4 Brewin minuteg8 s 0.6

Hera te b Brewing 0.04-0.6

Berries Pressing to juice 0.8-0.9 0.8-0.9 Steaming to juice 0.2-0.6 0.3-0.7

References :100-1048 6 [29 , ,61 ]

radionuclide content, although it is recognized that special drinking water treatment vere b yn sca effectiv somr fo ee elements.

3.4. Decontamination

3.4.1. Introduction

In cases of extensive contamination of the environment with radionuclides, processes for the decontamination of foodstuffs may be considere countenneasura s da orden ei reduco rt epopulation e doseth o st . Although food processing takes househol e plac th industryn i n ei d an d , change householn si d food preparation methods should onl e recommendeyb n i d

49 very extreme situations becaus f possiblo e e public reactions, social consequence e possibilit th e lac th f o k d san controo t y e implicationth l f o s such advice. However, changes in industrial food processing methods may be feasible and lead to a lower transfer of radionuclides to the population.

In general some decreas transfee th n i ef radionuclide ro e th o t s population may be obtained by applying selective processing to certain types of products. In some cases, optimised decontamination procedures may decrease food contamination considerably. The feasibility of changes in food processing methods will depend strongly on the product and food technology.

The success of efforts to decontaminate food is, in general, related to the rigidity of the cellular structure. Consequently, decontamination is more efficien r foodfo t f animaso l origin thavegetablr fo n e products, and the results for liquids such as milk are rather successful.

3.4.2. Milk For the decontamination of milk without losses in nutritional value and deterioratio e tasteth n exchangf no io , mose th appear te b o st promising method [14] F value e .Th s presented here refe milo t r k decontamination on a commercial scale (Table II). Better results have been reported from research on a laboratory scale especially for caesium. Other methods, based on coprecipitation or electrodialysis led to a serious deterioration of the taste of milk. Recently, a method based on complexatio f caesiuno modifiey mb d Prussian Bludevelopes ewa o t d decontaminate commerciawhea n yo knowt lye nt scalno s ei [104t I ]. whether this method will have adverse effect tasten so , appearancr o e nutritiona daire l milk th e valu yth n I .industrf eo alss i ot i ypossibl e to shift production towards products whic contaminatee har a lesse o t d r exten y radionuclidesb t . However, consideratio e givee th b o o t nt s nha economic by-products e valuth f eo . Butter production, sometimes suggested, would lead to contaminated buttermilk, which has an important economic value A bette. r strateg yproductioe woulth e b d certaif no n typef so chees refiner o e d products suc s caséineha e remaininTh . gf les o whe s i y economi regardee b n c ca valuwastes a dd ean .

3.4.3. Meat

Several decontamination procedures have been applied to meat, often resultin poon i g r decontamination combined with quite unfavourable

50 consequences for the taste and appearance of the meat. Certain ways of picklin marinatinr o g g may, however, resul contamination i t n levels C f so whic e reducear h y aboub d n ordea t magnitudef o r , whil e tastth e e remains good [50, 56].

3.4.4. Soot crops

e casI th nf rooe o t crops decontamination proceduren a y lea o ma st d F valuluee of about 0.1 or even lowelow«r for Cs [63] but the effects of decontaminatio e limiteS nar r fo d

3.4.5. Vegetables

For vegetables, a mush er of decontamination procedures have been applied, most often based on immersion in a decontamination liquid. The results are, however, not promising and consequences for taste and appearance not favourable. Unexpected effects were observed, such as a decreasing permeability of the cellular structure at higher temperature, leading to lower decontamination [88]. However, some efforts were successful; mushrooms can be decontaminated effectively by a combination of salting and cooking [75].

No important result e knowar s decontamination no cerealsf no , other drinks than wine or of sea organisms.

3.5. Conclusions

The effects of processing on the behaviour of radionuclides depend on the radionuclide methoe e typth th f producf processingn o e o do n o ,d an t . In general, food processing may halve the amount of radionuclides present e foodith n . Processing effect e rathear s r smal r roolfo t crops whereas milling cereal grain o flout s r will often remove th ef o abou % 70 t radioactivity. Although attempts to apply decontamination procedures were often not successful, several procedures have been developed which may remov e radioactivit eth r mor o abouf o e% 90 t certair yfo n combinationf o s radionuclide processine d products th an scase f th eo n I milkf .o g , meat and potatoes, available data allow a rather detailed insight into the effects of processing. The effects of processing on vegetables and fruits are rather unpredictable, especially when the radionuclides are adsorbed on the surfacplantse th f o e .

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[90S ARAPIS MARTI, ,G. , J.M., KOUSKOUTOPQULÖ KARANDINOS, SA. , ,M. IRANZO, E., 'Low radioactivity contribution of cereals to diet due to their specific composition and processing". Radioactivity Transfer during Food Processing and Culinary Preparation (Proc. Sein. Cadarache, 1989), Commissio Europeae th f o n n Communities, Luxembourg (1989).

[91] BUNZL, K., KRACKE, W., Soil to plant transfer of 239 + 240Pu, 238Pu> 24iAmj 137Cs and 90Sr from global fallout in flour and bran from wheat, rye, barley and oats, as obtained by field measurements, Sei. Total Environ. M (1987) 111-124.

[92] BiraZL KRACKE, ,K. Transfe, ,W. 137f 90o rd CS flouro sran t , bran and straw from wheat, rye, barley and oats during the years 1982, 1986 (reactor acciden Chernobylt ta 198d ) an fieln 7i d measurements, Z. Lebensmitt.-Untersuch, (in press).

[93] LIU, D.J., ROBBIHS, G.S., POHERAMZ Compositio, ,Y. utilizatiod nan n of milled barley products, Cereal Chem. 51 (1974) 309-316.

[94] LOFTI, M., HOTARO, M., AZIMI-GARAKAHI, D., PIERMATTEI, S., TOMMASIKO, L,, Loss of radioactivity in cooked spaghetti, Sei. Total Environ. 79 (1989) 291-293.

[95] MUELLER Radioaktivitäts-Kontaninatio, ,H. Brotgetreidn nvo e nach Tschernobyl, Mühle-Mischfuttertech. 123 (1986) 392-393.

[96] OHMOMO, Y., SUMIYA, M., 0CHIDA, S., MURAMATSU, Y., YOKOSUKA, S., OBATA, H., YAMAGUCHI, S., "Transfer of radioiodine into rice grains', Impac Accidents de t s d'Origine Nucléairr su e l'Environnement, (4e Symp. Int. de Radioécologie de Cadarache, 1988) Tom CEN/Cadarach, e1 e (1988).

[97] PFEIFER, V.F., PEPLIHSKI, A.J., HUBBARD, J.E., Strontium-9 plann 0i t parts and milling fractions from a 1963 Illinois wheat, Radiol. Health Data Rep. 5 (1964) 283-284.

[98] RIVERA, J., Sr-90 in U.S. wheat and flour produced in 1962 and predictions of levels in the 1963 crop, Fallout Program Quarterly Summary Report HASL-140, Offic Technicaf o e l Services, Departmenf to Commerce, Washington, D.C. (1964) 276-282.

[99] VOIGT, G., MUELLER, H., PROEHL, G., PARETZKE, H.G., 'Cesium activity distribution in cereals after milling processes', Radioactivity Transfer during Food Processin Culinard gan y Preparation (Proc. Sem.

58 Cadarache, 1989), Commission of the European Communities, Luxembourg (1989) 351-360.

[100] CASTRO, J,, SANCHO, A., VEIGA, E., DIAS YUBERO, J., MURIAS, B.S.F., "Transfert de Cs-134 et Cs-137 dans les infusions d'herboristerie', Radioactivity Transfer during Food Processing and Culinary Preparation" (Proc. Sera. Cadarache, 1989), Commission of the European Communities, Luxembourg (1989) 205-218.

[101] GEDIKQGLU SIPAHI, ,A. , B.L., OSKAY KURÜGLU, ,T. , Chernoby,M. l radioactivit Turkeyn i y , Radioactivity Transfer during Food Processing and Culinary Preparation (Proc. Sem. Cadarache, 1989), Commission of the European Communities, Luxembourg (1989) 193-204.

[102] MÂSSCHELEIN, W.J., 'Elimination d'isotopes radioactifs par les filières conventionnelle e traitemensd eaus de tx potables', Radioactivity Transfer during Food Processing and Culinary Preparation (Proc. Sem. Cadarache, 1989), Commission of the European Communities, Luxembourg (1989) 167-192.

[103] MIRIBEL , DELMAS,J. , 'Utilisatio,J. traceure nd s activables pour 1' étud devenie ed a contaminatiol e rd n radioactiv a u courl a e e sd vinification', Radioactivity Transfer during Food Processind an g Culinary Preparation (Proc. Sem. Cadarache, 1989), Commissiof no the European Communities, Luxembourg (1989) 219-227.

[104] GIESE, W., SCHIMANSKY, K., KLUGE, K., ROINER, F., Radiocesium transfer to whey and whey products: whey decontamination on an industrial scale, Radioactivity Transfer during Food Processind an g Culinary Preparation (Proc. Sem. Cadarache, 1989), Commissioe th f no European Communities, Luxembourg (1989) 295-308.

59 Chapter 4 SEASON ALIT Y

A. Aarkrog Rise Naîional Laboratory, Roskilde, Denmark

4.1. Introduction

4.1.1. Seasonality

The impact of environmental releases of radionuclides on the human food chain depends, among other yea e things th time r f th wheo e e n ,o nth release occurs e terTh .m seasonality uses ,a thin i d s report, meane sth varying response to radioactive contamination of environmental samples according to the time of the year, when the contamination occurs. Seasonality effect maskede b y sma , enhance confuser o d othey db r seasonal changeassiso t d clarification i tsan nseasonalita y facto introduceds i r . e seasonalitTh y factor , ,allowS s seasonalit quantifiede b o t y s i t i ; define Annen i d seasonalit0 . Whex1 > nS o n presens i y, 0 whe d = an tnS seasonality is observed. Annex 1 also contains an example of the applicatio seasonalito t S f no agriculturan i y l crops.

Agricultural ecosystems

The most obvious effects of seasonality are seen in relation to direct deposition on the surface of crops. When the contamination has reached the ground, and indirect contamination (root uptake) becomes the dominant pathway, seasonality is usually no longer relevant. Seasonality is of special importance in connection with the contamination of cereals. saie b generan dI y thama t depositiota li n event during winter, whee nth fields lie fallow and the domestic animals are stabled, will result in a significantly lower radiological impact similathaa f ni r contamination wer tako t e e summee placth n ri e before harvest. Seasonalit generalls i y y of greater importance in temperate regions than in the subtropics where cultivatee soilb y sma d throughou yeare tth .

Seminatural ecosystems

Natural and seminatural ecosystems e.g. forests may also show seasonality. Decidious trees contaminated durin wintee gth r will retain

61 less activity tha simmea casn i nf o e r contamination, whee leaveth n s will retai nactivite th mor f eo y froe airth m . Henc e foresth e t wil mose b l t contaminate contaminatioe th f i d n summere occurth n i s. Howeve e effecth r t on the forest floor will be delayed until leaf fall, which is not the case for a contamination during the winter. Coniferous trees will show less seasonality than décidions trees. But a delay of the contamination of the forest floor will also be seen here.

Aquatic ecosystems

In general, seasonality has not been considered in the context of aquatic pathways. However e cas th f freshwatee o n i , r fish livina n i g frozen lake whe contaminatioe nth n occurs, there wildelayea e lb d dan lesser response to the contamination compared with an ice-free lake. There might also be some influence due to plankton. If it is assumed that the contamination occurs during a plankton bloom, then much of the activity may capturee b d ente e an food-chaid th r fishe th .f no Howevere th f ,i radioactive debris is not captured by plankton, it will reach the bottom sediments becoming more or less unavailable to the biota in the lake and the infinite time integra f activito l e fisth hn i wily lowee lb r than i n the case where therplanktoa s i e n bloom. Contaminatio drinkinf no g water derived from groundwater will show no seasonality. However, drinking water coming from surface water may (as discussed above for fish) show a seasonality e eithe,du planktoo t r n blooo icet r .mo Radioactivitn i y drinking water may also be influenced by snow melting. In this case, when the snow melts, contamination of a snow-covered area may affect drinking water derived fro rivea m r receivin meltwatere th g . Contamination with long lived radionuclides durin summee th g r would probably have fewer implications because the activity then would more easily be retained by the soil.

4.1.2. Seasonal variability

Seasonality confusee shoulb t dno d with "seasonal variability". Foodproducts produced throughou yeare tth , e.g.- milk shoy ,ma w seasonal variability which occurs even though the radioactive deposition is evenly distributed throughou yeare tth . Thusconcentrations C , seee b ny sma to be significantly higher in summer milk than winter milk, if the cows are grazing in summer, but fed with beets during winter (Fig. 1). Permanent pasture alsy sma o sho seasonawa l variatio thein ni r radionuclide

62 YEARS **-* MONTHS *•** LOCATIONS ***

1 5 «5 ' "

1 0 - 1 0 - -

05 - 05 J _ 1 il l i ! i 1 50 65 70 5 7 MJJASONOJFMA HjaJ VKJ Ode Nak Ârh Abe Rm variatioe Th Cs-13i Fig. pC 1 .K)-g f 7( no Danisn 1i h dried milk collected monthl drie7 t ya d milk factories from May 1959 to April 1976. The bars indicate the levels relativ grane th t da o t e1 mea K)~g = ( ( n l i 18.pC 5 the relative scales) [41]. concentration variationo t e uptake sdu th d los n ean f radionuclidei s so s throughou growine th t g e seasoncasth e n wherI . e only seasonal variability is present wit seasonalityo hn e seasonalit,th y factor zeros i ,S .

Agricultural practice

Agricultural practic havy ema e seasonal aspects. Ploughing, harrowing or harvesting giving rise to resuspension may, for example, contaminate neighbouring fields n evenln casa I .f e o y distributed fallout rate throughout the year this resuspension will enhance the contamination of crops in neighbouring fields. Variations in crop contamination from this phenomenon belong seasonao st l variability depositioe th f e I .th f no activit unevenls i y y distribute e resuspensioth f i n tim i d ean n from treatment of neighbouring fields occurs prior to the contamination only a minor additional effect from resuspension wil seene l b howeve f I . e th r treatment of the fields takes place after the contamination event a more pronounced additional contamination is expected. The seasonality effect is then either diminished (if contamination took place in winter season) or enhanced (if the contamination occurs in summer). This illustrates how seasonal variability may influence seasonality.

Seminatural ecosystems

Karlen et al.[l] have shown seasonal variability in the """"C137, s content of roe-deer in Sweden. A peak is observed in August-September due to a high consumption of mushrooms in these months by the roe-deer.

63 Year Quarter uocation 30 j- 1967-1904 of Ihe R Rmghals - yeaKlinK r! S Sordal B BarsebatK

LeUr ! l H

00 Ln___ n nfl! 67 70 75 8B 0 S K R t. 3 2

Fig. 2. Time variation of Tc-99 in Fucus in the Danish Straits 1967-1984 [42].

i « Yeai r

-200

-100

1 7 9 S 7 6 13 Year

Fig. 3. Activity concentration of Tc-99 in Fucus at the west coast of Sweden (56.76°N, 12.63°E) during 1967-84. In the upper part of the figure the Tc-99/(Cs-137/K-40) ratio is given [43].

64 Marine environment

Seasonal variability is also observed in the marine environment, 7 13 99 wher (Figs brown C i e ) ne.g.3 d algac (FigT .an ) e2 . (Fucus vesiculosus) froBaltie th m c area show marked seasonal variationse Th . winter values for 99Tc are 2-3 times higher than in the summer, however, for C^, the summer values are 1.5 times higher than those in the winter. These seasonal variations are primarily influenced by physiological factors, but seasonal variations in the océanographie condition y alssma o pla rolea y .

Global fallout

Environmental contaminatio globao t e lndu fallout from nuclear weapons testinatmosphere th n i g s showeha pronouncena d seasonal variation with relativel w falloulo y t rates during autum winted falloua nan d an r t peak in spring (Fig. 4). This seasonal pattern influences the levels in environmental samples and thus gives rise to seasonality. However, natural wels a anthropogenis a l c factor bees sha n t may i show s ,a n above, superimpos thin eo s seasonality.

4.2. Pre-Chernobyl DatModeld an a s

4.2.1. Experimental studies

Middletons experiments

The first studies on seasonality were carried out by Middleton [2] in the late fifties. He studied the direct contamination of wheat, potato, cabbage and sugar beet after the application of 89 Sr and 137 Cs in a fine spra different ya t plantsgrowte e stageth th f n e founho i H s. d (Tables I-III) thas concentrateextene wa th t whics o C t e th h n i d 89 edible tissues greatly exceeded that of Sr. Usually the concentration of 89 Sr or 137Cs in each crop varied by less than an order of magnitude irrespective of the state of growth of the crop at the time of contamination. The 89Sr content of wheat grain-, however, was considerably lower when the plants were contaminated before the ears emerged laten I . r experiments, Middleto d Squir nan ] observe[3 e d thae th t go 137 maximum concentrations of Sr and Cs in the cabbage hearts and 137Cs in potato tubers were observed after contamination occurred in the middle of the season. 65 O) O)

""" ""* U) t/J 1 m RELATIVE UNITS Ir? . s CT i u - r j c J K Jb- . 3 S 0 O O * 4 ' W O O W ' rjpoco^ïoo g - •1 1,'•> M' s _____ r^ T i | i pi ai s ~* s 0 1— ta S n M H- H 13 3 n y a o v o e r o ——— s § B> fa 0 (-M ro S - s. I-" B r> -J Oo « 0 l B 1 1 B Î • • (B M O 8 ei a M o B 0 3 s b •~> ui rf >« g 3 • C, (0 - - 0 i^ ^000^01-- -0 ft ô •— s uj » wi c. (» tn ÛJ do 4. w io oi 10 iv» do ? i 5 c C;i i3 u'a ws g ,ï § ï fcî3 s- 2 n O i» li- r c M " • * ~ > M M- M S s <—< HI O (B S " 1i« 3 > • « P a < B E. * s s g . P B ( f f MW - a 0 B H " ^B * o » " o m 1 » l/l ! Ul Ch IvJ UJ |O O O O t^J io *=> --N r° tf M * r S3" * r P ° 2 S t i t i ' it0 ^ ^ I I T I | It g 1 % M O * H !( bi o tfl ö m 0 << î* t •4 I I I I S S ï ils " (- B M» S 3 H O. M <4 TI _^ •o 1» B t - H t r 9e O-t 'S 3 i i- 0 o ro t Z ^ o . . u u i c o t.j»w o o i 4 *> a . 4 3 n s £, > CT\ |vj oc fe i f» f H- o * i ~- o t- o o i o n ^ 3 s B « B ( f r f r 0 ! O - -P J t, 3 -J » t- M *°" § L_ n o ET p^ (B O. ft —1 3 3 i_ (B fl> M- X s- s rf » O > W çp >< oo a" f> a in , n (B H (B O ff- y M g WO •z. ö a> p &i H* M» o sk îûO i > ol* * u U *o 4* -oO t iv \O z rf Q. i-^ H Ôi — • -04 W Ô - 8L 8 0 * O v 0 ^ 1 > 10 lJ 1 | C OQ (O 00 O 00 4- =f W v O 1 1 " h ,—————— 1- 1 — ^-^„_^i 1 ———— a •< !-l 5 ra l 1 § oJ vD 3 o v> a. -c 1 3 o "~* C» Oi ^i OO »=

Experimental data Extrapolatio o rleit n d conditions

Irunal retention on Davs from 1 Content of heart as j foliage Final content in neart plantin l percentag o gt e initial i————————————— contamination ' retention by plant > 7 ; ixC/kg y vi fur „ wi y j u « drv wt.

(a) "5r 1937 32 0-33 81 3,000 0 27 0-84 4 -0 1 8 8 36 688 0-89 2-82 1 Sig. diff. M.S. 1958 58 0-18 ) 2,18-< 5 3 0 0-15 0-27 72 0-34 296 3,072±2 3 0-99 1-83 87 0-16 300 1,119±4 9 0-50 0-91 99 0-1 1 231:: 16 1,227 0-31 0-56 Sig. din. 0- 1 5

(4) '"Cs '• i I 1957 32 0-91 42 1.720 0-4 1 3 38 L-51 37 617 1-3 4-3 ! S.g. diff. N.S. ! 1958 58 1-15 141 ±26 2.830 ! 1 6 3-6 1-02 i 72 6-93 231-20 2,754 19-5 43-4 1-80 37 4-92 309±36 1,240 , 15-2 33 / 7-52 99 , 3-92 2SO±44 1,143 10-7 23-8 . 1-611 Sig. din. 0-28 I ,

The final concentration in the heart as a percentage of the amount initially retained by the plant was experimentally determined; the values for mmal retention and final content of the heart under field conditions after a deposition of 1 millicunc per square metre have been calculated. Final sampling 120 and 113 days after planting in 1957 and 1958 respectively. Where a logarithmic transformation was necessary far statistical analysis the transformed valueitalicsn i e sar . Significant difference cenr pe t 5 showlevel e e ar sth .t na

Aarkrog's grain studies

In the sixties and early seventies, Aarkrog [4-7] studied the direct contaminatio f cereao n l grain (rye, barley, whea d oatsan t ) applying d C , Na , Be , Ru , Sb , Pb , Hg , Zn , Co , Fe , Cr , Ce , radioisotopeMn , Cs , Sr f o s and Ba as a fine spray during different stages in the growth of the crops. The results of these studies with respect to seasonality were summarized in a number of heuristic models [8] (Figs. 5 and 6).

It appears that two important factors influence the contamination of grain: initial retention and translocation from the vegetative parts of the plante seedsth o t s. Initial retentio s fairli n y independen whicf o t h radionuclid s involvedi e , whereas translocation depends strongle th n o y radioélément.

67 TABLE III. FOLIAR CONTAMINATIO POTATF NO O WITH D | CSs(2 AN r 137 89

Experimental data Extrapolation to field conditions Initial retention Final contanm t Days from Content ot" tuber as foliage tubers plantino gt percentage initial contamination retentio n plano n t uorrr ."c'lt« *="•" £± drv wt

(a) "Sr 1957 55 0046 0 48 9,604 009 0 2 2 0 69 0033 0 65 8,666 5 02 0-tl Sig diff. N 5 1953 47 0 14 0 27 2,570 0-38 0'13 74 0-03 320 4 2,6003 0 2 6 009 97 002 0 58 4,461 012 0-041 <5ig. diff N. S.

(b) a:Cs 5 5 1957 25 480 6 760 120 -19 69 29 520 6753 151 62 ? diffS' . N S 7 4 195S 40 240 2.400 108 32 1 Öj 74 14 0 45 3,435 63 19 1 00 ' 97 2t 390 4 193 32 24 / .'2 g dif3i F 0 IS

e finaTh l concentratio e tube percentaga th s n a ni r e amounth t o e t initially retainey db e plan s experimentallth wa t y determine valuee th initiar d fo s l retentio d finaan n l content 0 i tubeoth f r under field conditions afte depositioa r ! milhcun f no r squarpe e e metre have DAYS BEFORE HARVEST been calculated. Fina dav9 12 l a samplin d aftean rS plantin12 g n 195 gi d 1957an 8 respectively. Fig. 5. Percentage of radiostrontium, applied Wher logarithmiea c transformatio necessars nwa statisticar yfo l analysi transformee sth d at variou s^ barle m date1 o yt s field, values are s^.own in italics. Significant differences are shown at the 5 per cent level. f maturrecovereo g k er graipe d t a n harvest assuming no radioactive decay. Number of determinations and 1 S,B, are shown (unless S.E. is less than the radius e circle)oth f . Curve calculated from 2 2 u(t)=4.Sxicr e-°.ooo9s(t-2) 10 0 50 100 50 TOO DAYS BEFORE HARVEST DAYS BEFORE HARVEST , FigPercentag6 . f radlocaesiumeo , appliet a d Fig. 7. Percentage of initial uptake in whole variou sbarlem date1 o yt s field, crops (above-ground parts) when a barley recovere2 d per kg of mature grain at fiel variout a d s date contaminates i s d harvest assumin o radioactivn g e decay. y radionuclidesb e totaTh . l crop yield (Numbe determinationf o r S.E1 d . an s at harvests in 0.8 kg dry matter m~2; are shown.) Curve calculated from datbasee ar a d upon measurements with u(t)=9.8xl(T- 2 n Z , Sb , Mn , radioisotopeCo , Cs , Sr f so e numbe; Fe determinationf d ro an d san 1 S.E. are indicated. Curve calculated O) fro initia% m l uptak e-°'6 3 e= 2(t-30)j 8 [ CO OOQ5 z e percentagTh f initiao e l uptak month3 e s before harves abous i t % 5 t activite oth f y deposited ove a fielr d with barley cropsmont1 d h,an before harves reachet i fiele t th s i df maximusa I % (Fig36 . f .o m7) contaminated withmonth3 examplr , fo ,Cs s before e harvesq kB 131 7( t contaminatioe th mature f th i , ; e} m grai g k n S nC contain q B 2 s occurs 1 month before harvest,1 - 100 Bq7 13 Cs kg is found in the mature grain (Fig. 6). In the case of90 Sr, the corresponding concentrations 1 — —1 respectively, g k q B 0 2 woul, d demonstratindan hav g ek beeq B n0 g translocates i s C tha tmuca o ht d greater extent r tha(FigS n. .5)

e highesTh t level grain i s e expectenar d whecontaminatioe th n n takes place in the final month before harvest. The lowest levels will be seen if the fields are contaminated before sprouting.

Delmass' fruitstudies

] hav[9 e Delma . studieal t e s d experimentall contaminatioe yth f no orange fruits with Sr and Cs. For the same initial direct contamination with the two radionuclides during the flowering of the orange s contaminatioC trees e e frui,th th f t no orden a fles f s o r hwa magnitude higher than that of 90Sr. The difference was due to the higher e contaminatioe fleshth th f o I .translocatiot r S s thaC nf no f no wer havo t e e occurred just e orangprioth o t er harvest difference ,th e would have been far less.

4.2.2. Models

C seminaCE A a tDublin i r e transfe198n i nth 3n o radioactivf o r e materials in the terrestrial environment subsequent to an accidental release to the atmosphere, a number of papers dealt with seasonality viz [10-14]. The consequence seasonalitf so y were illustrate modey b d l calculations.

Simmonds' model

e papeTh Simmondy b r s [13] concluded thagreer fo t n vegetabled an s meat from sheep, season of the year has little effect, but for grain mild (Tablan k ) (Figmear eIV o t) .8 fro m cattl elarge b ther n eca e variation concentrationn si . Such variation greatee sar r short-livefo r d raradionuclided longer-livee th thaI sr nfo sucd (Figs C an s ha ) d9 . 90„Sr. The variations in the total activity in the diet following

70 Concentration in m? Ik . Bq 1 per 8q m ^

0 0 O 0 I ! 1 1 o r- Fig 8. Theconcentratio ofCs-137 inmilk — * w - * I JFMAMJ JASONDJFMAMJJA 1 Cows gonleave t pastureo t i times ofyear[13]. accidental releaseattw o different as &functionoftimefollowin g an ? l\ ' t 1DeposiJani—I i \ ^' 'Deposit 1May(--l \ \ \ \ l i ^~~~~~ —^^Ls 1 3U T '0 Fig. 9Integratedconcentration s CD I "45 S £ 30 a a. £ 01 05 25 i S 20 1 0 iO 50 60 20 80 30 70 10 0 1 j ^i i i i i i i ; /v-s ; ! ——i —— —— —— —— l —— r~ JFMAM jASOND A M J J A S 0 / IODINE-131! Time ofyear.vhendepositoccur s 1 / i- l i l \ of theyear[13] . and1-131 atvariou s time a singledeposi t ofCs-137 in milkandmeatfollowin g ——— Meal| - Milk' i l - 1 1 " 1 1 1 - TABLE IV. TIME INTEGRAL OF CONCENTRATION IN GRAIN PRODUCTS FOLLOWIN GSINGLA E DEPOSI VARIOUT TA S TIMES BEFORE HARVEST (i3|

""•\Time of deposit Time integra f rar.centratioo l n ^\before ^\harves) m q tB r pe ' g k y q (8

Nue li de ^-^ 7d 30d 60d 90d Winter^

5 Sr-90 1.7 !0~2 1.6 lu"2 4.5 IO"3 2.0 " IO"o i 4 3 . :

R'j-106 1.7 I0~3 8 IO"6. 4 3.0 IO" i 4 ia~?. " 1.2 !0~4

i-131 4.8 IO"4 2.5 IO"4 1.1 IO"5 2.8 10"' 0.0

Cs-134 2.3 10"2 8.5 ID"2 4.8 iO"2 1.6 IO"2 3.1 IO"5

Cs-137 2.8 IO"2 1.0 10"' 5.9 10"2 2.0 10"' 4.4 10"4

Notes a) The integral of concentration in processed grain, integrated ovel timeal r . ) b Deposition occurs whee fieldth n e falloar s w before ploughing and seeding.

TABL . TOTAEV L INTAKE FOOA SVI D FOLLOWINGA SINGLE DEPOSI VARIOUT TA SYEAE TIMETH RF S[13O ]

"\-Time of 3 ^~"\deposit Tota) lm q intakB r a food*vi epe q (B ' Nuctide ^~^\^ January April August October

1-131 0.17 0.42 1.7 1.6

Cs-137 4.8 9.9 27 7.9

Sr-90 4.9 5.3 7.5 5.0

Note a) The total intake of activity from all food at a critical group intake rate integrated over all time deposits at different times of the year are generally smaller than for individua le agaifoodsar t n I thar longer-livebu greate, fo n r fo r d radionuclides (Table V).

Müller's model

Müller et al. [10] shows in a model calculation (Fig. 10) that a contaminatio n Germany(i y Ma )n i resultn n s integratea C wit n i hs 137d intake from food whic f tha o abous i ht% a similasee60 t f i n r contamination wer o takt e e plac 5 timen June i et bu s, highe re contaminatio th tha f i n n wer o occut e winten i r r (November-March).

72 2 1 s C - S Y S O EC

/-/-/-/Ä-J-J»/»/»/-/-

Fig.. Integra10 l intak activitf eo n ove year0 ma 5 ry b ys after deposition of 1 Ci/km2 of Cs-137 as function of month of release. The total intake ("sum") is spli intp differene u t th o t foodstuffs [10].

AGRID

IFinnisna h model stud founs ywa dt [15 i tha]expectee th t d values of collective 30-year doses in the case of dormant season and growing season seem to differ by a factor on the order of 10. In the first-year doses e differenc,th e woul e largerb d ,a facto abouf o r te Finnis 100Th . h AGRID model includes seasonal effect y considerinb s g growing seasod nan dormant season separately. But the model makes no seasonal distinctions withi e growinth n g season. Tabl I showeV variatioe sth dosee th sn i n accordin AGRIe th Do t gmodel .

PATHWAY

The PATHWAY model [16-18] was developed to estimate radionuclide ingestion by humans exposed to fallout originating at the Nevada Test Site (NTS) during the 1950s. As NTS is an arid region PATHWAY does r.ot consider wet deposition. The model considers seasonal changes in the biowass of vegetatio d animanan l diets wels ,a s specifia l c plowin d croan g p harvest dates; thus the integrated radionuclide intakes by humans are dependent on the seasonal timing of deposition. The model does not consider translocation. Tabl showI PATHWAVI e sth Y model calculation selecter fo s d

73 TABL I ECONDITIONAV L EXPECTED VALUEE TH F SO COLLECTIVE EFFECTIVE DOSEO T E S (maDU ) nSv FK-E TH ? RELEASE CATEGORY [15]

Release dunng averagn a n O e growine dormane Th Th g t dunne gth season season whole -.ear

Plume i I 7 IO2 Fallout 7 1 IO 8 I Inhalation 2 IO 1 2 Milk 9 8- IO3 8 0- IO2 3 3 10J Meat 26- IO3 4 7- IO2 1 1 10' Vegetables I 0- IO3 5 8-10' 2 IO 1 2 2 Gram 40- IO3 1 8 IO2 8 1 IO Roots 0 5 10' 4 1 10' 43 10' Nutrition total I 7- 10' 1 5 10' [54 <03]

Total 75 10'

TABL I INTEGRATEEVI D INTAK ADULY EB T MALES VARIOUF O S RADIONUCLIDES FROM

ALL FOODS PER UNIT FALLOUT DEPOSITIO8 N VERSUS SELECTED FALLOUT DATES [17] (units are Bq per Bq m~2)

Radio- 1 Mar 17 Mar 25 Apr 19 May 24 Jun 24 Jul 31 Aug 7 Oct nuclide (Tesla) (Annie) (Simon) (Harry) (Priscilla) (Kepler) (Smoky) (Morgan) lll0Ba 1.6 x 10-= 1.6 x 10-' 2.2 x 10— 2.6 x 10— 4.5 x 10— 2.7 x 10~' 1 .5 x 10— 1 .0 x 10-'

1I(3Ce 1.1 x 10-' 4.2 x 10— 1.0 x 10-' 1.5 x 10"' 2.4 x 10-' 2.4 x 10— x 10~ 2 1. ' 6.2 x 10— '"Ve 3.7 x 10— 5.5 x 10~' 1.5 x— 10 x - 0 2. 5.3 x 10-' 5.5 x 10-' 4. x 210- ' 4.3 x 10—

136Cs 1.0 x 10-' 1.1 x 10-' 1.2 x 10"' 1.4 x 10-' 1.9 x 10"' 1.6 x— 1010 —x 1 1. 1. x 210" ' 137CS 2.0 2.0 3.0 2.6 3-3 4 1. 1.6 2.4 I3ij 2.1 x 10— 2.0 x 10— 3-3 x 10— 4. x 9IQ" ' 9.1 x 10- 'x 10- 0 1. ' 5. x 10"5 ' 3.7 x 10-' I33j 4.2 x 10— 1.5 x 10— 3-7 x 10— 1.1 x 10-' 2. x 010" ' 2.9 x 10— 1.5 x 10~' 7.5 x 10— I35j 6 7.8 x 10— 2.6 x io- 6.9 x — 10-10 'x 5 1. 2.6 x 10— 3.4 x — 1010 — x 8 1. 8.7 x 10"'

"MO 3.7 x 10-'x 9 1. 10— 3.9 x 10— 5.5 x 10-' 9.2 x 10-' 1.0 x 10— 5.3 x 10-' 3.0 x 10-'

1"7Nd 1.3 x 10— 1.3 x ID- 1.8 x 10— 2.0 x— 10 10 —x 4 3. 2.0 x 10"' 1 .2 x 10"' 7.3 x ID"1

239Np 2.7 x 10- 1.1 x 10— 2.6 x 10— 3.1 x ID" x 10-' 1 '5. 5.2 x 10-' 2.7 x ID"' 1.1x— 10 ?39Pu 4.0 X 10— 6.0 x 10-= 2.1 x 10-' 2.9 x 10-' 8.1 x 10-' 6.0 X 10~' 4.7 x 10— 4.9 x 10-' 105Rh 1.3 x 10— 4.8 x ID- 1.2 x 10"' 1. x 710" ' 2.7 x— 10-10 x ' 8 2. 1.4 x 10-' 7.2 x 10— 103Ru 6.1 x ID- 7.1 x 10— 8.2 x 10— 9.0 x 10 —x 10" 6 '1. 5.9 x 10-' 5. x 210- ' 6. x 10"9 ' 106Ru 1.5 x 10-' 1.8 x 10-' 2.6 x 10— 3.1 x 10"' 6.8 x TO"' 1. x 10"4 ' 1.6 x 10~' 2. x 310- ' 2 89Sr 5.8 x io- 6.6 x 10-' x 1 . 10-' 1.3 x 10-' 2. x 410- ' 1. x 0ID" ' 6.5 x— 1010 —x 1 6. 90Sr 2.5 x ID- 2.4 x 10-' 6.0 x 10-' 6.0 x 10-' 1 .1 2.0 x 10"' 1.6 x 10"' 1.8 x 10~' 5 9'sr 1.5 x 10— 1.6 x io- 4.0 x— 10 —x 9 6. — TO X 1 1. 1.2 x 10— 6.0 x ID"' 3.0 x 10— 13?Te 1.5 x 10— 2.4 x 10- 4.6 x 10— 5.7 x 10-' 9.0 x— 10 10~ X '1 8. 4.5 x ID"' 2.6 x 10-* 97 zr 2 6 x ID- 9.1 x 10— 2.3 x TO"" 3.7 x 10— 5.8 x 10-"- ID 6. x 0 3.0 x 10— 1.5 x 10~"

1 Values for adult females average 35% less than males

74 fallou s IntakC t datese e variee Th .th n si e.g 3 factoa 2. y . b f o r period March-October, whil varier S factoa e y sb 9nearlf 0o r . 7 y

4.3. Post-Chernobyl Data and Models

4.3.1. Observations

In general, the Chernobyl accident confirmed qualitatively the assumption seasonalitn so y mad eaccidente prioth o t r .

European I and Cs data

In the case of milk (Fig. 11), it was thus seen, as expected, that e radioiodinth e concentration northern si wer w lo e n Europe where th e grazing season was just at its beginning, while they were significantly highe southern i r n Europe wher cowe beed eth s ha n grazin monthsr fo g . This latitudinal effect, which is due to seasonality, was also seen for Cs as show UNSCEAy nb R [19] e effec. Th moss wa tt eviden grair fo t n (Fig) .12 anticipateds wa s a .

Denmarn I krelative (Figth concentrations C ) 13 .e e th f o s grain species (rye, barley, wheat, oats) were compared with those observe yeare th sn e i Chernobydprio th o t r l accident t appeareI . d that the rye levels were an order of magnitude higher than those seen in the other species afte Chernobye th r l accident. This observation reflects

lO-i Milk Leafy veqetaoies

0 1-

0 01 0 7 0 6 0 5 0 4 0 3 20 20 30 «O 50 70 LATITUDE (°H) LATITUDE (°N) Fig. 11. Integrated concentrations of 1-131 in milk and leafy vegetable unir spe t 1-131 deposition density [19].

75 lOO-i

"1

0 1 0 6 0 5 0 4 0 3 ZC 20 30 iO 50 60 70 LATITUDE '°H) LATITUDE (°N)

1001 Leafy vegetables Viqeublei/Fruic

« 10-

0.1 0.1 0 5 0 4 0 3 0 2 60 70 30 «0 50 60 70 LATITUDE » t" 'LATITUDE (°N)

100 1

20 30 40 SO0 6 S O0 5 0 4 0 3 20 LATITUDE <°K) LATITUDE (°K) . FigIntegrate12 . d concentration Cs-13f so foodn 7i d tota san l dien i t the first year afte accidene rth unir tpe t Cs-137 deposition density [19]

76 ChernoDyi

JTl Pl

2 - Global fallout"

r 1 1 1 1 i nnn 1 0 • —— - ————————— 0 W B R

FOUE ITH N R GRAIN SPECIES [Normalize somo dt e mean) Fig. 13. Relative Cs-137 concentrations in Danish grain, globae normalizeTh l . mea 1 a fallouf o no t d t sample basee sar n observation o d perioe th n dsi 1962-1974 meae Th .n concentratio Danisn ni h grain in 1962-1974 was 7x1 Bq Cs-137 kg"1. In 198Cs-13meaq e B th 6n3 7leve3x kg"s lwa 1. R = rye, B = barley, W = wheat and 0 = oats [44]

the precosity of rye compared with the other species, resulting in a higher retention of Cs by the more developed rye crops when the fallout from Chernoby depositeds lwa . UHSCEAR [19] calculatee th d varioun i ) sm s C q W3 r pe transfe g k a s rC factor q (B s 137 —1 137 2 diets afte e Chernobyth r l accident appearet I . d thae factorth t s were usually lower than those observed previously for global fallout 137Cs, especially for northern Europe. One reason for this was seasonality, which in particular influences the levels for grain and for which the transfer factors post-Chernobyl were 1-2 orders of magnitude lower than those observe globar fo d l fallout. Another reason coullowea e b dr 137 availability of the Chernobyl Cs than of that from global fallout with respect to contamination of crops. But seasonality seems to be the most important factor.

Fruit seasonality

Berrie nutd san s showed relatively high radiocesium concentrations after the Chernobyl accident. It has been shown experimentally that radiocesium deposited on the leaves of fruit bushes is translocated to the

77 berries and the content of radlocacsium in the berries generally increases with time. In an experiment: carried out by Kopp et al. [20], it was found 134 that in red currants 0,6% of the deposited Cs activity was transported unripe tth o e ripe frui th d 3.4e o an tberriest % ; only minute amountf so 8 5d beeSrha n transferre e ediblth o t ed parts, howeve bilberrien I . r s 134 the corresponding figures for Cs were 0.7% (unripe) and 1.8% (ripe) gooseberrier anfo d s 4.4% (unripe 3.7d )an % (ripe).

4.3.2. Models

The principal terrestrial foodchain models known to consider seasonalit ECOSYe ar yd FARMLAND an S .

ECOSYS

ECOSYS (Fig ) [21 s .develope14 ]rapiwa e th dr predictiofo d f o n radiation exposure after single release f radionuclideso e th o t s atmosphere. In order to accomplish this for vegetation, the model takes morphological and physiological changes of the plants during their growing period into consideration.

modelline th r Fo f seasonalito g planf yo t contaminatione ,th processes deposition, interception, translocation, growth dilution and weatherin t depositio e consideredwe ar gd an modellee y nar Dr . d separately. e amounTh f activito t y retaine e plan th characterizes i ty b d e leath f y b d area index (Fig. 15). This indesuitabla s xi e paramete modellinr fo r g becaus e leat th eboundare we f th r are fo wels s a i as la y dr laye r fo r

RADIOACTIVITY IN AIR AND PRECIPITATION

, [pj__ANTsk—————————— J sn]D '\~J^^^ f~ \ [A N I M A L S f \„ ^^" inha lation PROCESSED ternal exposure PROQUCTS 1 external exposure i n o i t s e ng ___J 1 _ i^ l l i | EXPOSURE OF MAN 1

Fig. 14. Structure of the dynamic model ECOSYS [21],

78 <0 o

«J <0

April August Developmen f sprino t g wheat Fig. 15, Leaf area index of spring wheat durin e growinth g g s perioit d an d stages of development [21]. deposited radionuclides from the atmosphere. Data on the leaf area index are available from investigations on the growth characteristics of agricultural crops [22-26]. For the interception of wet deposition the amoun rainfalf o t anothes li r very important parameter [21,27] (Fig. 21).

The modelling of translocation is based on data from Middleton [2,3], Aarkro -7]4 [ g ,. [28 Voig Ludwieal d ]t an e t g [29] (Fig. 16).

For pasture grass growth dilution is modelled as a season-dependent process. The overall field loss of activity due to growth dilution and weathering variemort no e y sb tha 5 nbetweed a factoOctober 1. an f y o r nMa .

e versioTh ECOSYf no S whic s availablhwa e immediately aftee th r Chernobyl acciden s abl tpredicwa o t e contaminatioe th t f foodstuffno s quite well starting from the initial retention-on plants. There were sonie discrepancies concernin activite th g differenn i y t varietie graif so n (winter and spring wheat, rye, winter and spring barley, oats) because no differentiation between species was taken into account. The differences in the morphological and physiological status of winter and spring varieties are very pronounced at beginning of May. Whereas winter varieties are

79 100 50 Days before harvest Fig. 16. Translocation of caesium from foliage todependencs it grai perioe d th nan n edo between depositio harvesd nan t [21].

0.20

0.15 acsr

= 0.10

• £ 0.05 «

0.00

Fig. 17. Integrated Cs-137 activity concentration of spring wheat and its dependence on the month of deposition (dashed part: contributio roof no t uptake) [21]. normally well developed at this time, spring varieties have only recently emerged and the plants are still relatively small at the beginning of May. This leads to substantial differences in the intercepted activity and to different fractions being translocated fro foliage e grainth mth o t .e

At later times of deposition (e.g. 1st June or 1st July) these differences would not have been as pronounced as they are at the beginning of May.

80 -5 °-05 —

er 0.04 CO • £ 0.03-

o i < 0.0?* v 0 « 0.01 I £ o.oo

Fig. 18. Integrated Sr-90 activity concentration of spring wheat and its dependence on the month of deposition [27].

A4 i =XT ' "^ I NT [NT EXT i PLANT ! —— * ——— PLANT GRAIN GRAIN i i

1 XS " A2 Notes Tne concentratio n graii n s ootainei n y summinb d e th g contributions from external and internal grain compartments. ^ represenr a ran , t interceptio e deposie wholth th f y eo nb t plant ana by the grain respectively. They have values of 3.3 and 0.012 respectivel elementsl al r fo y . c represenA a Aan ? t o weatherinlosset e du s g froe wholth m e pïant ana the grain respectively. ^ = ^-95 '0~2 d~' and 1 z elements l 4.8= al 6 A 2r 10"fo . d" e obtainear g A y fittin b d an o ^ t gA , e value\3 Th f o s exDer'menta e elemeniar cald an at aepenaent e valueTh r . fo s strontiu o caesiuan m m are:-

iransrer Strontium \ Caesium \ setficient a'1 ! a i

2 Z X3 3.7 10" 3.4 1Q" •M 9 10~6. 2 6.4 10"2

2 ^5 4.5 10"' 5.2 \0~

Fig. 19. Revised model for the deposition of radionuclides onto grain plants [13]

81 .AESiUM

for key-see 3 0 in-2I

D CTl C

^ 0-31 a

Aarkrog|1969) Aarkrog 11975 I Middle ton (1957, 1958l

10 C 'O 20 30 40 50 60 70 80 Time T aoys that deposit OCCJTS berore narves' Fig. 20. Compariso f modeo n d experimentaan l l results for single deposits of caesium and strontiu grain mo n plant t varioua s s times before harvest [13].

FARMLAND

The National Radiological Protection Board's (NRPB) foodchain model FARMLAND [30-32] has been developed over a number of years and it includes seasonality (Fig. parametes 19) it modee .Th d an l r values were derived from global fallout observations as well as from experimental measurements, notably Middleton [2], Middleton and Squire [3] and Aarkrog [4-8] (Fig. 20). Furthermore compilations of data, notably those of Ng [33] and International Unio Radioecologistf no s (IUR) [34] have been applied.

From a seasonal viewpoint FARMLAND predicted the transfer of radionuclide fooo st d following Chernobyl reasonably well particularn I . ,

82 FARMLAND'S predictions of a decline in cow's milk concentrations following the deposit followed by an increase when the animals were fed on stored feed was observed following Chernobyl. However, the release occurred at a single time of year and data on the stage of growth of crops from locations other than that on which the model is based are difficult to obtain. Therefore, the testing of the seasonal aspects of the model has, so far, not bee s rigorouna desirables i s sa .

In testing the validity of FARMLAND with Chernobyl data some discrepancies were noted with results for particular farms in the united Kingdom .mainle du Thi differenceo s t ys wa s betwee generae nth l assumptions regarding agricultural practices adopted in FARMLAND and the actual practice individuae th t sa l farms. Also there were differencen i s some cases when the deposition occurred in rainfall as FARMLAND does not take accounrainfale th f to l rate, neither doe distinguist si h betweet nwe and dry deposition.

RissJ-models

The curves shown in Fig. 20 are to some extent similar to those in Figs. 5 and 6. These models were made from least squares fitting of the normal distributio nexperimentae curvth o t e l data [8] s e modeC . Th r fo l s applieChernobye wa (Figth ) o 6 t .d l observation 198n si Denmarn 6i y kb Aarkrog [35]. The model predicted 4.2 Bq Cs kg~ grain but the 137 -1 observed level was 0.3 Bq Cs kg . One reason for this discrepancy was a more rapid field loss of the Chernobyl 137Cs than that found during the experiments because intense rain in Denmark removed a good deal of the initially deposited Chernobyl debris. This effect has been shown by Müller and Pröhl [27] (see Fig. 21) who found that the interception factor can vary from nearl hundree on y d dowpercentw onlo fe nt a y .

A simpler empirical model for the contamination of grain in Denmark has been based on global fallout data collected since 1959 (Table VIII). This model assume s depositioC s thae May-Augusth tn i n decisivs i t e contaminatioe th r fo graie th harves t nf a no t tim August-Septembern i e . e modeTh l gave good prediction sChernobye prioth o t r l accidente th t ;bu prediction 198n i s Danisr 6fo h grai 2 ordern 1- cam magnitudt f so eou e higher than those actually observed. The reason for this was that the empirical model Tabln si e VIII assume thafalloue th t evenls i t y distributed over the period May-August, but the majority of the Chernobyl

83 1 On

M U

c o ~CL i) foc £ 02-

102 051 l § io 20 Precipitation (mm) Fig. 21. Interception factor for wet deposition of caesium on grass with different leaf area indices (LAI) as used in ECOSYS [27],

TABLE VIII PREDICTION MODELS FOR Cs !N CEREAL GRAIN [41] 137 (unit for radioeco/agical sensitivity pCi 137Cs kg~'a per mCi <17Cs km 2)

*ia Sdmole *rea Period Cs-ac^lvlty, pCl

1 Rye Denmark 1962-76 79d!KMay-Aug1 _1- . ). <-S Öd! . 17 0 999l"" 46 9957««« - ' - 2 8Sdl

4 52dWheat 23 0 9857-" ' " " i(Ma * y-^uq" ' ) 9 «.. 5 Oats 0d 0 9S2 - ' ' ' U«ay-Aug, ^

debri s depositeswa Mayn i d , wher e initiaeth l retentio sparsele th y nb y developed crops was low. Hence, although these empirical grain models have considered seasonality they were not sophisticated enough for dealing with the Chernobyl input.

OSCAAR-CHRONIC

Matsuzuru [36] has also proposed models that take seasonality into account A foodchai. n mode incorporates i l computee th n i d r code system OSCAAR-CHRONIC which evaluates chronic exposure due to radionuclides remaining in a Japanese environment after a reactor accident. The model is extension a methodologe th f no U.Se y th use .n CRAi d C code [37]. Four kinds of important Japanese crops are selected: leafy vegetables, cereals,

84 mont( h) 2 ! ! l 0 1 9 3 7 6 5 i 3

Pasture unaer under growing w grazeco y b d grass growing 1 Cereais dormant under growing harvestedj dormant

under Root crop bar d harvested growing

Leafy under h d harvested vegetaoles growing

Non- leaty under harvested dormant u , Fruit8 g sve growing .-- Fig. 22. The Model of Agricultural Practice [36]. rootcrop d fruitsan s (including non-leafy vegetables) assumes i t I .d that the year can be divided into 3 and 4 periods for the various crops as shown ind tim Figan e2 .2 dependen t function postulatee sar e intak th r f o efo d radionuclide for the various periods. Translocation is not included in the model, henc modee th e l seem underpredico t s s intakC te from cereals 137 (Table IX). The parameter values employed in the model are Japanese as far as productivity densit grass/cropsf o y , growing period d consumptiosan n rat f foodstuffeo concernede sar . Foreign datothee appliee th ar a r fo d parameters suc s interceptioha n factors, transfer rates, time delao t y consumption and so on. Most of the values are those used in the CRAG code d otheran takee sar n from NRPB data sets.

Figures 23 and 24 show the results of the model calculations for mil d cerealskan , respectively Japanesr ,fo e conditions e modelTh . s were

TABLE IX. RATIOS OF PREDICTED-TO-OBSERvED CONCENTRATIONS OF 137Cs IN WINTER GRAIN (w) AND SPRING GRAIN (s) BASED ON GEOMETRIC MEANS OF ALL MEASUREMENTS 138] (GM: geometric mean, GSD: geometric standard deviation)

T r S C H N L MODEL ROSK3LDE ROSKILDE GEEL TO KAI TRANVK MUNICH LovnsA LOVUSA GM GSD (Wl 15) IS) (w) (w) (w) (w) (S)

DETRA 8.0 7J 15 77 1.0 SIRATEC 0.26 OJ2 02 0.029 0.14 0.33 0.13 0.18 0 18 2.4 FARMLAND 5.3 21 3.8 1.6 065 3 ! 36 ECOSYS- 1.3 0 13 0.087 0.055 0.63 0% 0.03 0.20 40 SPADE 2 3.7 6.6 0.13 8.7 4.9 9.7 0014 1_5 127 TERFOC 0.029 0.027 049 0.0052 0.17 0.019 0.013 0.036 4 7 CHRONIC 0.029 0026 0.49 00059 0.17 0.019 0.015 0036 46 RAGTIME 7.1 0.91 22 6.7 1.8 2.3 2.4 CHERPAC 0.34 0.85 4.1 73E-6 7.96 0.028 000033 0049 176

' Calculations for ECOSYS are grain specific: listed are P/0 ratios for wheat.

85 98

TOTHL INIRK R UNIPE E T DEPOSITIO R CI/n««2PE I IC N )

3 45S7Ü9.1Q" 2 ' 3 Q 4Sfi7ß3.10~ Z ' 3 -156783,10610S ' 4 ï lu 9 ' 3 2 ° ______i I———1——' ' ' • ' I ______l ' . l r l l l I______l l——I——I j [ ( I £——————t————1——I——l t l l t

08

M

H O

3 rr SB

O 3

TQTflL INTflK R UNIPE E T DEPOSITIO R CI/H«.*2PE l (C N )

1Ü'' ? 3 < 56709,10'' ? 3 456709,10'' g 3 4 5 67^9,1 0° 2 3 4S67B9 1 0*

H O

3 fT 0> It

i-J O

0 fH M m Cl developed befor e Chernobyth e l accident BIOMOVe th n I S. stud modee th y l was applied to the Chernobyl scenario for I and Cs.

BIOMOVS international model validation study

e BIOMOVTh S group [38] compare numbea d modef ro l predictionf o s Cs in grain with the actual concentrations found after the Chernobyl acciden 198n i t6 (Table IX). model e Threth f seo have been described above (ECOSYS, FARMLAND and CHRONIC). None of the model predictions were close to observed values for all locations tested and there was considerable variabilit modee th ln i ypredictions r thiFo .s scenario BIOMOVe th , S group did not attempt to analyze the reasons for predictive variations and discrepancies because of the generally poor quality of the information available from the sites tested.

e BIOMOVTh S study conclude sdifficuls i tha t i t o fint d reasonr fo s the discrepancies betwee modee nth l prediction observationse th d san . However, it concluded that they may be associated with a strong seasonal absence factoth d sitf eo an r e specific informatio state th f eo n n o maturatio e accident plante e th tim th th f o et f sna o .

4.4. NeeModer fo d l Improvement

4.4.1. ECOSYS

Afte Chernobye th r l acciden ECOSYe th t S mode s improvelwa n i d various ways. Dry and wet deposition is now modelled separately, the leaf area index during the growing period of each plant species is considered an differentiatioa d n betweex majosi rl nal cerea l species cultivaten i d Europ mades i e .

Furthermore, realistic consideration of animal diets especially for beed dairan f y cattle bees ,ha n introduce e radionuclidd Th [39]. e content of anima mentiones la fee, is d d earlier, subjec seasonao t l variability (Section 4.1.2.) due to the differing growth intensities of pasture grass during the growing season. The supply of fresh pasture grass is highest at the start of the growing period and decreases towards the end of the growing period. This means that increasing amounts of fresh pasture have substitutee tb o y othedb r feedstuffs suc maizes ha , beet, beet leaves etc. reliabla Alsr ofo e predictio activite th f e no miln th mead i y kn an i t winter followin depositione th g e rea,th l site-specific feeding regimes

87 e takehavb o t en into account s alsi ot I necessary. a realisti r ,fo c predictio activite th f n o winte n i y r fodder havo t , e information aboue th t period when hay and silage are prepared, which may vary for climatic reasons.

4.4.2. FARMLAND

With regard to FARMLAND, this model has, according to NRPB, not been modifie tako t "fine-tunedr o dey accounwa Chernobye y th an f o tn i " l data. However, some particular parameter valuealteree e lighb th y f o n tsma i d data obtained after Chernobyl, although car s require i eplaco t o t to e no d much relianc singla n o e e sourc dataf o e compariso Th . FARMLANf o n D predictions with post-Chernobyl measurements generally strengthens NRPB's generin i validite beliee modee us th c th r n radiologica i ff lfo o y l assessments s intendedwhicr wa fo t hi e thir us Fo .se reaso,th n somf o e the detailed site specific modifications, such as can be incorporated into the ECOSYS t includedmodelno e ,ar . However recognises i t ,i d that further development of FARMLAND is desirable to enable the effect of deposition in y conditiondr varyind takee an b t o st ngwe into accoun morr fo te detailed applications.

4.4.3. Summary

The Chernobyl accident, which was a major short time input of radionuclides intbiospheree th o , demonstrated tha o existintn g modelt (a s the time of the accident) were able adequately to predict the effect of seasonality numbeA . modelf o r s have considere e importancth d e leath f f o e area index and translocations (as described by Prb'hl et al. [21]), but as shown by Müller and Prb'hl [27] the meteorological conditions m precipitation(m )significana als d oha t interceptioe impacth n o t n factor. Furthermore meteorologicae th , l condition e timth e n si afte e th r depositio e n effecfiela th d dn no tha loss, i.e. rat decreasf o ee th f o e activit plantse th n i y. Field los s influencei s weatheriny b d g processes, e.g. washoff, and also by plant growth dilution. All these elements have e includeb o t modeln i dyielo t thef e i sd yar reliable model predictions r singlfo e event radioactive contamination orde" In describo .t r e th e seasonality process adequately, models have to be site specific.

At any particular time of the year the stage of plant development in different regionworle th df s o yaries widely e tim harvesTh f .eo alss i t o variable. (Mülle Pröhd ran l [27] (Fig. 25)). Bot thesf ho e factorn sca

88 0«nmark Franc« G«rmany Italy N«lht<-lan

* USA

3 V777T, Brazil 12A w//, Uruguay ZSI3 r~T7S L W/M/À } irrfw E2SZ Irak i-

Japan

Syria Turttty r V/A Algwia

South -Africa Turvcsra V/M7h Egypt CZ32Î323 Australia 23 CEZ New Zealand '//S/A ~\ J FMAMJJASONO Month Fig. 25. Times of wheat harvest in some countries [45]

strongly influence the radionuclide content of crops; other factors, such harvestins a g method alsy sma o hav n influencea e .

BIOMOVe Th S study [38 s show]ha n thamore th te complex dynamic models do not necessarily give more reliable predictions than simple models. Howeve . shora e cas th f eo tn i rtim e inpu f radionuclideo t s into the environment, simple steady- state models for predicting the contaminatio cerealf no s wil t sufficlno dynamid ean c model e requiredsar . e contaminatioIth f s "chronicni " bee(e.gs case globar ha th nfo es .a l fallout )simpla e model will probabl complee juse yb th goos a ts a dx one. The Riso model shown in Table 8 has thus proved to produce very reliable predictions throughou yeare th tglobaf so lDanisn i fallou s C h t cereals.

89 4.5. Conclusion and Recommendations

Seasonalit y havyma strona e g influenc e radiologicath n o e l impact of environmental radioactive contamination. Seasonalit s influencei y a y b d number of environmental factors. In the terrestrial soil-to-plant-animal system the ratio between direct and indirect (root uptake) contamination of the plants is of major importance. Seasonality is pronounced if direct contamination is the dominating pathway. The degree of translocation of radionuclides to the fruit bodies of plants also influences Seasonality. High translocation normally reduces Seasonality. Contaminatio f cereao n l showI ' graingrsa pronounce ad an s s witC dh Seasonality, whereas 90„ Sr in root crops shows little or no Seasonality.

In aquatic ecosystems ice cover, plankton bloom and runoff during snow melting may influence Seasonality. Natural and seminatural ecosystems show generally lower seasonality than agricultural systems. Temperate Eones show higner seasonality than subtropical and tropical regions.

There is a need for a better understanding of the processes that influence seasonality, especially those connected to meteorology, e.g., washoff. The physicochemical behaviour of contaminants with respect to initial uptake and translocation in crops needs further study. Information seasonalitn o connection i y n with frui vegetabld an t e contaminatios i n particularly sparse. Seasonality effects also require further investigation in connection with aquatic pathways (e.g., fish, drinking water). Finally, natura d seminaturalan l ecosystems shoul furthee b d r examined with respect to seasonality.

n ordeI obtaio t r n reliable prediction radiologicae th f o s l consequence f shorso t term contaminatio f cropsno modee th , l applied should be site specific and be capable of taking account of changes in interception characteristics with plant growth effecte th , f so translocation, of rain intensity and of the physicochemical characteristics of the contaminant.

90 Definitio Seasonallte th f o n y Factor.S

The seasonality factor S is the coefficient of variation (CV) of the monthly infinite time integral concentrations of a given radionuclide in a given sample observed throughout twelve month yeara f so .

_2 A monthly deposition of l Bq m in month (i) of radionuclide (p) results in an infinite time concentration integral in sample item (a) of

'laKgq B p" lyr-

The variation of I.la p between the 12 months of the year is a measur degree th seasonalityf f eo eo . This variatio quantifies ni e th s da coefficient of variation CV, i.e. the relative standard deviation of the twelve I. values, which have an annual mean of I . Hence lap m E12 \ S = CV = (12 - 1)

seasonalit0 > o seasonalitIV n fC 0 presents - i yV C s i yf I . observed.

Application of S

Pröhl [40] has calculated a variety of I. values (see e.g. Figs. 17 and 18) based on a time dependent simulation model SINK, which is closely related to the ECOSYS model (Pröhl et al. [21]). These I. lap values are site specific for the average conditions in southern Germany and should thus be considered only as examples.

Below are summarized some S values calculated from Pröhl [40]

Sr-90 1-131 Cs-137

8 0. 1 1. 4 0. MILK 9 1. 6 2. 5 0. WHEAT 2 1. - ROOT 0 VEGETABLES LEAF VEGETABLES 0.4 0.2 0.5

91 It is evident (Figs. 17 and 18) that the degree of seasonality depends strongly on the ratio between root uptake and direct contamination of the crops e seasonalitthif I th . s w ratilo s hig s i od i vicy an h e versa. However, other factors, e.g. translocation of certain radionuclides play an important role particulan i , e cas th f fruit o en i d rcereals an s .

It should furthe e noticerb d thar certaifo t n sample types, e.g. cereal grain ,evee b ther ny monthlema y seasonality variationr fo t ,bu practical reasons the definition of the seasonality factor has teen based on monthly data.

92 KKFEREHCES

] [1 KARLEN JOHAHSON, ,G. J ,K. BERGSTROE , 'SeasonaK. M l variatioe th n i n activity concentratio !f no 3'C sSwedisn i h roe-dee d theian r r daily intake Environ. J ,» Vol58 .. Radioact (19914 .,1 ) 91-103. ] [2 MIDDLETQN, L.J., Radioactive strontiu e ediblcesiud th an m n i em parts of crop plants after foliar contamination, Radiât. IntJ . . Biol.,4 (1959) 387-402.

] [3 MIDDLETON, L.J., SQUIRE, H.H., Further studie radioactivf so e strontiu d cesiuman n agriculturai m l crops after direct contamination, Radiât. IntJ . . Biol (19636 . ) 549-558.

] [4 direce AARKROGth n tO contaminatio. ,A. ryef no , barley, whead an t oats with 85Sr, 134Cs, 54Mn and 141Ce, Radiât. Bot. 9 (1969) 357-366. ] [5 AARKROG LIPPERT, ,A. Direc, .J. t contaminatio barlef no y with 51Cr, 59Fe, 58Co, 65Zn, 203 210d HPbgan , Radiât. (1971l BotI . ) 463-472. ] [6 AARKROG Direc, ,A. t contaminatio barlef no y with 7Be, 22Na,

115d, IC5sbs Ba,an.d Aspects of Research at Risd.

C

134 133 A collectio2 n of papers dedicated to Professor T. Bjerge on his seventieth birthday. Ris«5 Repor . 256tNo , Ris«S National Laboratory, Roskilde (1972) 163-175.

[7] AARKROG, A., Radionuclide levels in mature grain related to radiostrontium conten d tim direcan tf o e t contamination, Health Pnys. 28 (1975) 557-562.

] [8 AARKROG Translocatio, ,A. f radionuclideno cerean i s l crops. Ecological Aspect Radionuclidf so e Release. Special Publication Series of the British Ecological Society No. 3, Blackwell Scientific Publications, Oxford (1983) 81-90.

] [9 DELMAS BOVARD, ,J. GRAUBY, ,P. DISDIER, ,A. BLONDEL, ,R. , ,L. GUENNELO , 'ContaminatioNR. n directe expérimental e l'orangeed r rpa le 90sr et je 137cs', Radloecology Applied to the Protection of Environmens hi d an n tMa (Proc. Symp. Rome, 1971), Commissioe th f no European Communities, Luxembourg (1972).

[10] MUELLER, H., EISFELD, K., MATTHIES, M., PROEHL, G., 'Contamination of crop y irrigatiosb n with radioactively contaminated water'e ,Th Transfe Radioactivf o r e Material Terrestriae th n i s l Environment Subsequen Accidentan a o t l Releas Atmosphero t e e (Proc. Sem. Dublin, 1983), Commissio Europeae th f no n Communities, Luxembourg (1983).

[11] sensitivitA " RAIR , ,S. y stud f ingestioyo n population dose following hypotheticaa l atmospheric release fro nucleaa m r power station'e ,Th Transfe Radioactivf ro e Material Terrestriae th n i s l Environment Subsequent to an Accidental Release to" Atmosphere (Proc. Sem. Dublin, 1983), Commission of the European Communities, Luxembourg (1983). [12] ROBERTS, J.A., 'Terrestrial pathways mode NUCRAr fo l e SAI'C- Th , Transfe Radioactivf ro e Material Terrestriae th n i s l Environment Subsequent to an Accidental Release to Atmosphere (Proc. Sem. Dublin, 1983), Commissio Europeae th f no n Communities, Luxembourg (1983).

93 [13] SIMMONDS, J.R., 'The influence of the season of the year on the agricultural consequence f accidentao s l release f radionuclideo s o t s the atmosphere', The Transfer of Radioactive Materials in the Terrestrial Environment Subsequent to an Accidental Release to Atmosphere (Proc. Sera. Dublin, 1983), Commissio Europeae th f no n Communities, Luxembourg (1983).

[14] GOVAERTS , KRETZSCHMAR,P. , J.G., MERTENS , 'Applicatio,I. e th f no "DOSDIM"-model to assess doses due to deposited materials subsequent n accidentata o l atmospheric release' e Transfe,Th Radioactivf o r e Materials in the Terrestrial Environment Subsequent to an Accidental Releas Atmosphero t e e (Proc. Sem. Dublin, 1983), Commissioe th f no European Communities, Luxembourg (1983).

[15] PARTANEN, J.P., SAVOLAINEN, I., Significance of contaminated food in collective dose afte a rsever e reactor accident, Health Phys. .50 (1986) 209-216. [16] KIRCHNER, T.B., WHICKER, F.W., Validatio PATHWAYf no simulatio,a n model of the transport of radionuclides through agroecosystems, Ecol. Modelling 22 (1984) 21-44.

[17] WHICKER, F.W., KIRCHNER, T.B., PATHWAY: A dynamic food-chain model to predict radionuclide ingestion after fallout deposition, Health Phys. 52 (1987) 717-737.

[18] BRESHEARS, D.D., KIRCHNER, T.B., OTIS, M.D., WHICKER, F.W., Uncertainty in predictions of fallout radionuclides in foods and of subsequent ingestion, Health Phys (19897 .5 ) 943-95. 3 [19] UNITED NATIONS, Sources, effects and risks of ionizing radiation, Scientific Committee on the Effects of Atomic Radiation (UNSCEAR), YorUNw ,Ne k . (1988pp 8 )64

[20] KOPP GOERLICH, ,P. BURKAET, ,W. ZEHNDER, ,W. , H.J., Foliar Uptakf eo Radionuclides and their Distribution in Plant (personal communication) (1989). [21] PROEHL MUELLER, ,G. JACOB, ,H. PARETZKE, ,P. , H.G., 'The dynamic radioecological model managemene ECOSYth A toor S- fo l nucleaf o t r accidents' consequences' (4e Symp. Int. de Radioécologie de Cadarache, 1988) Tome l, CEN/Cadarache (1988). [22] al.t PETRe , ,,J. Ertragsbildun landwirtschaftlichei gbe n Kulturpflanzen, Deutsch. Landwirtschaftsverlag, Berlin (1986).

[23] GEISLER, G., Ertragsphysiologie von Kulturarten des gemässigten Klimas, Verlag Paul Parey, Berli Hamburd nun g (1983).

[24] NOESBERGER, J., Die Analyse der Ertragsbildung von Pflanzen, Schweizer Landwirtschaftliche Monatshefte (1970. ,48 ) 325-345.

[25] NOESBERGER Einflus. ,J Bestandesdichtr sde Ertagsbildune di f eau g bei Mais Acker-Pflanzenba. ,2 (19713 u13 ) 215-232.

[26] FRIEDRICH NEUMANN, ,G. VOGL, , D. Physiologi . ,M Obstgehölzer ede , Akademie Verlag Berlin (1986).

[27] MUELLER PROEHL, ,H. , 'Th,G. e rol seasonalf eo , climatid can meteorological conditions in modifying nuclear accidents

94 consequences' e Influenc,Th Seasonaf eo l Conditione th n o s Radiological Consequences of a Nuclear Accident (Proc. NEA Workshop, Paris, 1989) OECD/NEA, Paris (1989).

[28] VOIGT, G., PROEHL, G., MUELLER, H. Experiments on the seasonality of the caesium translocation in cereals, potatoes and vegetables, Radiât. Environ. Biophys 0 (1991)3 . , 295-303.

[29] LUDWIEG, F.Z., Die Aufnahme von Cs-137 durch Kartoffelblätter, Z. Pflanzenernaehr. Bodenk. 99 (1962) 109-194.

[30] SIMMONDS, J.R., LINSLEY, G.S., JONES, J.A., A general model for the transfer of radioactive materials in terrestrial foodchains, Harwell, NRPB-R89, HMSO, London (1979).

[31] SIMMONDS, J.R,, CRICK, M.J., Transfer parameters for use in terrestrial foodchain models, Chilton, NRPB-M63, HMSO, London (1982). [32] SIMMONBS, J.R., The influence of season of the year on the transfer of radionuclides to terrestrial foods following an accidental releas atmosphereo t e , Chilton, NKPB-M121, HMSO, London (1985).

[33] BOONE, F.W., NG, Y.C., PALMS, J.M., Terrestrial pathways of radionuclide parMculates, Health Phys (19811 .4 ) 735-747.

[34] INTERNATIONAL UNIO RADIOECOLOGISTSF NO workgroue reporh th ,5t f o t p on soil-to-plant transfer factors. RIVM, Bilthoven (1987).

[35] AARKROG, A., et al., Environmental radioactivity in Denmark in 1986, Ris«5-R-549, Risrf National Laboratory, Koskilde (1988).

[36] MATSUZURU, H., VAMP-Terrestrial Working Group, Questionnaire No. 1 (1989).

[37] NUCLEAR REGULATORY COMMISSION, Calculatio Reactof no r Accident Consequences, WASH-1400, NUREG 75/014, USNRC Washington, D.C. (1975).

[38] KOEHLER, H. PETERSON, S.-R., HUFFMAN, F.O. (Eds.), Multiple model testing using Chernobyl fallout dat 1-13f o aforagn i 1 d mild an e an k Cs-137 in forage, milk, beef and grain, BIOMOVS Technical Report Scenario A4, National Institute of Radiation Protection, Stockholm (1991).

[39] KIRCHGESSNER Tierernaehrung, ,M. , DLG-Verlag, Frankfurt/Main (1987).

[40] PROEHL , Modellierun,G. Radionuklidausbreitunr gde n i g Nahrungsketten nach Deposition von Strontium-90, Cäsium-137 und Jod-131 auf landwirtschaftliche genutzte Flächen, GSF-Bericht 29/90, Gesellschaf Strahlen-unr fü t d Umweltforschung, Neuherberg (1990).

[41] AARKROG, A., Environmental studies on radioecological sensitivity and variability with special emphasis on'the fall-out nuclides 90Sr and 137Cs, DSc. Thesis, University of Copenhagen, Risd-R-437 (1979), Risrf National Laboratory, Roskilde (1979).

[42] AARKROG (Ed.). ,A , Bioindicator studie Nordin si c waters, Nordic Liaison Committe Atomir fo e c Energy, Rise National Laboratory, DK-4000 Roskilde, Denmark (1985) 22.

95 [43] HOLM, E., RIOSECO, J., MATTSSON S., 'Technetium-99 in the Baltic Sea', Technetium in the Environment, (DESMET, G., HYTTENAERE, C., Eds.) Elsevier, London, Hew York (1986) 61.

[44] AARKROGe radiologicaTh , ,A. l Chernobye impacth f o t l debris compared with that from nuclear weapons fallout Environ. ,J . Radioact (19886 . ) 151-162. [45] FRANKE, G., Nutzpflanzen der Tropen und Subtropen, Vol. II, S. Hirzel Verlag, Leipzig (1984).

96 LIST OF TERRESTRIAL WORKING GROUP MEMBERS ATTENDING THE 1990-1991 MEETINGS

Aarkrog. A , Risid National Laboratory 9 4 x Bo . 0 . P DK-4000 Koskilde Denmark Barchudarov, R. Institute of Biophysics Ministr Publif yo c Health Zhivopisnaya, 46 123182 Moscow Russian Federation Benes, P. Technical University of Prague Brehova 7 115 19 Prague 1 Czechoslovakia Bergman, R. National Defence Researh Institute ABC Research Department FOA ABC - skydd S-901 82 Umea Sweden

Bilo, M. Institut für Radioagronomie Forschungszentrum Julien GMBH Postfach 1913 D-5170 Jülichl Germany

Chamberlain, A. l Fifth Road Berkshire RG1N 46D United Kingdom

Colgan. ,T Nuclear Energy Board Clonskeag3 h Square Dublin 14 Ireland

Desmet. ,G Commissio Europeae th f no n Communities XII/F/1 Rue de la Loi, 200 B-1049 Brussels Belgium

Dovlete, C. Institute of Environmental Research and Engineering Environmental Radioactivity Laboratory Postal 11, C.P. 11-2 Bucharest Romania

Eriksson, A. Swedish Universit Agriculturef yo , Sciences, Department of Radloecology Box 7031 S-750 07 Uppsala Sweden

97 Erlandsson, B. Department of Nuclear Physics university of Lurid Sölvegata4 1 n S-22362 Lund Sweden Ettenhuber, E. Institu r Umweltüberwarhunfü t s de g Staatlichen Amtes für Atomsicherheit und Strahlenschutz Waldowallee 117 1157 Berlin Germany Firsakova, S. All-Union Institut Agriculturaf o e l Radioecology 246020 Gomel Barykina 305 E Russian Federation Frissel. ,M Torenlaan 3 6866 BS Heelsum Netherlands Fujimoto. ,K Divisio Hucleaf no r Safety International Atomic Energy Agency Wagramerstrase 5, P. 0. Box 100 A-1400 Vienna Austria Fulker, M. British Nuclear Fuels pic Building B433 Sellafield Seascale Cumbria CA 20 1PG United Kingdom Fülop. ,N National Research Institute Radiobiology and Radiohygiene P. 0. Box 101 H-1775 Budapest Hungary Garland, J.A. AEA Environment and Energy Harwell Laboratory Didcot Oxfordshire 0X11 ORA United Kingdom Gerzabek, M. Austrian Research Centre Seibersdorf A-2444 Seibersdorf Austria Giess, P. Imperial College of Science and Technology Reactor Centre Silwood Park Buckhurst Road Ascot, Berkshire SL5 7PY United Kingdom Henrich. ,E BALUF (Federal Food Control and Research Institute Radiation Protection Department Berggass1 e1 A-1090 Vienna Austria

98 Holm, E. Departmen Radiatiof o t n Physics Lund University Lasarettet S-22 Lun5 18 d Sweden Howard, B. Institut Terrestriaf eo l Ecology Merlewood Research Station Grange-over-Sands, Cumbria LA11 6JU United Kingdom Létourneau, C. Atomic Energy Control Board P. 0. Box 1046. Station "B" Ottawa9 5S P ,KI Canada Linsley, G. Division of Nuclear Fuel Cycle and (Scientific Secretary) Waste Management Internatinal Atomic Energy Agency 0 Wagramerstrass10 x Bo . 0 . P , e5 A-1400 Vienna, Austria Myttenaere, C. International Union of Radioecologists (Chairman) Plac4 ed CroiSu u xd B-1348 Louvain-la-Neuve Belgium Noordijk, H. National Institute of Public Health (RIVM) Laborator Radiatior fo y n Research P. 0. Box l NL-3720 BilthoveA ,B n Netherlands Pietrzak-Flis. ,Z Central Laboratorr fo y Radiological Protection Departmen Radiatiof o t n Hygiene Ul. Konwaliowa 7 Warsaw 03-194 Poland Prister, B.S. Ukrainian Branch of the All-Union Institute of Agricultural Radioecology 7 Mashinostroiletnaya St. Chabany, Kiev Ukraine Pröhl, G. Gesellschaf Strahler fü t d nun Umweltforschung Institut Strahlenschutr fü e z Ingolstädter Landstrasse l D-8042 Neuherberg Germany Quinault, J.M. CEA France CEN Cadarache 13108 Saint Paul lez Durance Cedex France Rantavaara. ,A Finnish Centr Radiatior fo e d nan Nuclear Safety P. 0. Box 268 SF-00101 Helsinki Finland

99 Eauret, G. Laboratori de Radiologia Arobiental Universitä e Barcelond t a Avda. Diagonal 647 Barcelona 08028 CatalTinya Spain Sansone. ,U ENEA/DISP Via Vitaliano Brancat8 4 i 1-00144 Rome Italy Schell, W.R. University of Pittsburgh Departmen Environmentaf o t d an l Occupational Health Graduate School of Public Health Pittsburgh, Pennsylvania 15261 United States of America Shaw, G. Imperial College Reactor The Reactor Centre Silwood Park, Ascot, SL5 7PY United Kingdom Sobotovich, E. Institut Geochemistrf eo d an y Physics of Minerals Academy of Sciences of Ukraine Palladin av. 34 Kiev 252680 Ukraine Strand, P. National Institut Radiatiof eo n Hygiene 134, 55 5x OsteraBo . 0 s. P Norway Thompson, L. Ministry of Agriculture, Fisheries and Food Ergon House c/o Nobel House 17 Smith Square London, SW1R P3J United Kingdom Vetrov, V. Division of Nuclear Techniques in Food and Agriculture International Atomic Energy Agency 0 Wagramerstrass10 x Bo . 0 . P , e5 A-1400 Vienna Austria Wirth, E. Institute of Radiation Hygiene Federal Health OfficeA ,EG Ingolstädter Landstrasse l D-8044 Neuherberg Germany Zombori, P. Hungarian Academy of Sciences Central Research Intitut Physicr fo e s Health Physics Department Budapes, 49 x Bo t . 0 . P Hungary

100