biosphere assessment report 2009 - posiva · biosphere assessment report 2009 march 2010 thomas...

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POSIVA 2010 -03

Biosphere Assessment Report2009

March 2010

T h o m a s H j e r p eT h o m a s H j e r p eT h o m a s H j e r p eT h o m a s H j e r p eT h o m a s H j e r p e

A r i T . K . I k o n e nA r i T . K . I k o n e nA r i T . K . I k o n e nA r i T . K . I k o n e nA r i T . K . I k o n e n

R o b e r t B r o e dR o b e r t B r o e dR o b e r t B r o e dR o b e r t B r o e dR o b e r t B r o e d

POSIVA 2010-03

March 2010

POSIVA OY

O l k i l u o t o

F I - 27160 EURAJOK I , F INLAND

Phone (02 ) 8372 31 (na t . ) , ( +358 -2 - ) 8372 31 ( i n t . )

Fax (02 ) 8372 3709 (na t . ) , ( +358 -2 - ) 8372 3709 ( i n t . )

T h o m a s H j e r p eT h o m a s H j e r p eT h o m a s H j e r p eT h o m a s H j e r p eT h o m a s H j e r p e

Saan io & R iekko la Oy

A r i T . K . I k o n e nA r i T . K . I k o n e nA r i T . K . I k o n e nA r i T . K . I k o n e nA r i T . K . I k o n e n

Pos iva Oy

R o b e r t B r o e dR o b e r t B r o e dR o b e r t B r o e dR o b e r t B r o e dR o b e r t B r o e d

Fac i l i a AB

Biosphere Assessment Report2009

Background maps and images © National Land Survey (permissions 41/MML/09,696/MML/09, 13/ILMA/2009), Finnish Environment Institute.

ISBN 978-951 -652 -174 -2ISSN 1239-3096

Tekijä(t) – Author(s)

Thomas Hjerpe, Saanio & Riekkola Oy

Ari T.K. Ikonen, Posiva Oy

Robert Broed, Facilia AB

Toimeksiantaja(t) – Commissioned by

Posiva Oy

Nimeke – Title

BIOSPHERE ASSESSMENT REPORT 2009

Tiivistelmä – Abstract

Following the guidelines set forth by the Ministry of Trade and Industry (now Ministry of

Employment and Economy), Posiva is preparing to submit a construction license application for

the final disposal spent nuclear fuel at the Olkiluoto site, Finland, by the end of the year 2012.

Disposal will take place in a geological repository implemented according to the KBS-3 method.

The long-term safety section supporting the license application will be based on a safety case that,

according to the internationally adopted definition, will be a compilation of the evidence, analyses

and arguments that quantify and substantiate the safety and the level of expert confidence in the

safety of the planned repository. The present Biosphere Assessment Report represents a major

contribution to the development this safety case. The report has been compiled in accordance with

Posiva‟s current plan for preparing this safety case. A full safety case, and an updated Biosphere

Assessment Report, will be developed to support the Preliminary Safety Assessment Report

(PSAR) in 2012.

This report summarises the biosphere assessment for the planned repository addressing the

following components: the site understanding (biosphere description), development of terrain and

ecosystems within the next ten millennia, calculations of radionuclide transport in the biosphere

and radiological consequences analysis, i.e. dose assessments for humans and the other biota. It

also presents the main models used in the assessment and summarises the input data and its

quality. It discusses compliance with Finnish regulatory requirements for long-term safety of a

geological repository on the basis of the calculated annual effective doses to representative

members of the most exposed people and to the a larger group of exposed people and typical

absorbed dose rates to plants and animals. The other aspects of the compliance are addressed in

the interim Summary Report of the safety case.

Various repository calculation cases have been considered in which failure of a single spent fuel

canister gives radionuclide releases to the biosphere within the biosphere assessment time window

of ten millennia. It is shown that the resulting doses to humans and other species of flora and

fauna imply that any radiological consequences of these releases will be negligible. Plans are in

place to manage remaining issues and uncertainties, as given in the report TKS-2009 so that a

comprehensive safety case will be developed to support the licensing process.

Avainsanat - Keywords

safety case, safety assessment, KBS-3V, KBS-3H, spent fuel repository

ISBN

ISBN 978-951-652-174-2 ISSN

ISSN 1239-3096

Sivumäärä – Number of pages

Kieli – Language

Posiva-raportti – Posiva Report

Posiva Oy Olkiluoto FI-27160 EURAJOKI, FINLAND Puh. 02-8372 (31) – Int. Tel. +358 2 8372 (31)

Raportin tunnus – Report code

POSIVA 2010-03

Julkaisuaika – Date

March 2010

Tekijä(t) – Author(s)

Thomas Hjerpe, Saanio & Riekkola Oy

Ari T.K. Ikonen, Posiva Oy

Robert Broed, Facilia AB

Toimeksiantaja(t) – Commissioned by

Posiva Oy

Nimeke – Title

BIOSFÄÄRIARVIOINTIRAPORTTI 2009

Tiivistelmä – Abstract

Kauppa- ja teollisuusministeriön vuonna 2003 vahvistaman aikataulun mukaisesti Posiva on

valmistautumassa käytetyn ydinpolttoaineen loppusijoituslaitoksen rakentamislupahakemuksen

jättämiseen vuoden 2012 lopulla. Loppusijoituksen pitkäaikaisturvallisuus käsitellään lupaha-

kemuksessa ns. turvallisuusperusteluna (engl. safety case), jolla kansainvälisesti omaksutun

määritelmän mukaisesti tarkoitetaan kaikkea sitä teknis-tieteellistä aineistoa, analyysejä,

havaintoja, kokeita, testejä ja muita todisteita, joilla perustellaan loppusijoituksen turvallisuus ja

turvallisuudesta tehtyjen arvioiden luotettavuus. Vuonna 2008 Posiva esitti päivitetyn suun-

nitelman tuvallisuusperustelun muodostavasta aineistosta ja sen laatimisesta. Tämä raportti on

alustava versio Posiva Oy:n Olkiluotoon suunnitellusta KBS-3 ratkaisuun ja geologiseen loppu-

sijoitukseen perustuvasta käytetyn polttoaineen loppusijoituslaitoksen turvallisuusperustelun

biosfääriarviointiraportista. Täydellinen turvallisuusperustelu, mukaan lukien päivitetty biosfääri-

arviointi, laaditaan alustavaa turvallisuusselostetta (PSAR) varten 2012.

Tässä raportissa esitetään yhteenveto suunnitellun loppusijoituksen biosfääriarvioinnista: paikan

nykytilan kuvaus ja prosessiymmärrys, maaston ja ekosysteemin kehittyminen seuraavien

kymmenen vuosituhannen aikana, radionuklidien kulkeutumislaskelmat sekä radiologisten

seurausten analyysi, ts. ihmisille ja muille eliöille aiheutuvat säteilyannokset. Raportissa esitetään

myös arvioinnissa käytetyt keskeiset mallit sekä lähtötiedot ja niiden laatu. Lisäksi raportissa

arvioidaan viranomaisvaatimusten täyttymistä eniten altistuville ihmisille ja muille altistuville

ihmisille aiheutuvien keskimääräisen efektiivisten vuosiannosten sekä tyypillisten kasveihin ja

eläimiin absorboituvien annosnopeuksien osalta. Muilta osin pitkäaikaisturvallisuusvaatimusten

täyttymistä käsitellään turvallisuusperustelun yhteenvetoraportin alustavassa versiossa.

Yksittäisen kapselin rikkoutumisesta ensimmäisten kymmenentuhannen vuoden arviointiajan-

jaksolla aiheutuvat säteilyannokset ja niiden vaikutukset ovat vuositasolla merkityksettömän

pieniä sekä ihmisten että muiden eliölajien osalta. Vielä avoinna olevat epävarmuudet on eritelty

ja suunnitelmat niiden ratkaisemiseksi on esitetty TKS-2009 raportissa; näitä suunnitelmia

noudattamalla voidaan biosfääriarvioinnin osalta tuottaa kattava turvallisuusperustelu, jota

voidaan käyttää tukena lopullisessa loppusijoitusta koskevassa lupamenettelyssä.

Avainsanat - Keywords

turvallisuusperustelu, turvallisuusanalyysi, biosfääriarviointi, Olkiluoto

ISBN

ISBN 978-951-652-174-2 ISSN

ISSN 1239-3096

Sivumäärä – Number of pages

186 Kieli – Language

Englanti

Posiva-raportti – Posiva Report

Posiva Oy Olkiluoto FI-27160 EURAJOKI, FINLAND Puh. 02-8372 (31) – Int. Tel. +358 2 8372 (31)

Raportin tunnus – Report code

POSIVA 2010-03

Julkaisuaika – Date

Maaliskuu 2010

1

TABLE OF CONTENT

ABSTRACT

TIIVISTELMÄ

PREFACE ..................................................................................................................... 3 TERMS AND ABBREVIATIONS ................................................................................... 5 1 INTRODUCTION ................................................................................................... 7

1.1 Olkiluoto site ................................................................................................... 7 1.2 Safety case ................................................................................................... 10 1.3 This report .................................................................................................... 17

2 BIOSPHERE ASSESSMENT ............................................................................... 19

2.1 Scenarios and calculation cases ................................................................... 23 2.2 The graded approach ................................................................................... 35 2.3 Multiple lines of reasoning ............................................................................ 35 2.4 Selection of radionuclide sets considered ..................................................... 36

3 SURFACE ENVIRONMENT ................................................................................ 39

3.1 Present surface environment ........................................................................ 39 3.2 Long-term transport and accumulation processes......................................... 45 3.3 Key data produced for further use in the biosphere assessment ................... 48

4 FORECASTING ................................................................................................... 55

4.1 Surface and near-surface hydrological modelling ......................................... 55 4.2 Terrain and ecosystems development model ................................................ 56 4.3 Key data produced for further use in the biosphere assessment ................... 57

5 RADIONUCLIDE TRANSPORT MODELLING ..................................................... 59

5.1 Landscape model set-up............................................................................... 59 5.2 Screening evaluation .................................................................................... 66 5.3 Modules applied in biosphere objects ........................................................... 69 5.4 Safety indicators ........................................................................................... 72 5.5 Key data produced for further use in the biosphere assessment ................... 74

6 RADIOLOGICAL CONSEQUENCES ANALYSIS ................................................. 75

6.1 Assessing doses to humans ......................................................................... 75 6.2 Assessing doses to other biota ..................................................................... 81

7 MAIN FINDINGS .................................................................................................. 87

7.1 Terrain and ecosystem forecasts .................................................................. 87 7.2 Landscape model applied ............................................................................. 87 7.3 Radionuclide transport .................................................................................. 93 7.4 Radiological consequences analysis........................................................... 100

8 COMPLEMENTARY ASSESSMENT ................................................................. 125

8.1 Sensitivity calculation cases ....................................................................... 125 8.2 Comparison with previous Posiva assessments ......................................... 134 8.3 Classical physics approach ......................................................................... 138

9 KNOWLEDGE QUALITY ASSESSMENT .......................................................... 141

9.1 Biosphere description ................................................................................. 141

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9.2 Terrain and ecosystem development .......................................................... 145 9.3 Landscape modelling .................................................................................. 150 9.4 Screening models ....................................................................................... 153 9.5 Safety indicators ......................................................................................... 155 9.6 Radiological consequences analysis........................................................... 158

10 DISCUSSION AND CONCLUDING REMARKS ................................................. 165

10.1 Compliance assessment ............................................................................. 165 10.2 Significant development and resolved issues .............................................. 171 10.3 On-going work and remaining issues .......................................................... 172

REFERENCES ......................................................................................................... 177

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PREFACE This report has been written by Thomas Hjerpe (Saanio & Riekkola Oy) with contributions from Ari Ikonen (Posiva Oy). Robert Broed (Facilia AB) implemented the models and carried out the radionuclide transport calculations supported by Rodolfo Avila (Facilia AB). Boris Alfonso (Facilia AB) contributed with the dose assessment for the other biota, and Jani Helin (Posiva Oy) drew most of the maps. The terrain and ecosystems development simulations, for which Martin Gunia and others at Arbonaut Ltd. have developed the UNTAMO toolbox, were carried out by Ari Ikonen and Jani Helin. Tuomo Karvonen (WaterHope) carried out the surface and near-surface hydrological modelling. Päivikki Mäntylä helped in final editing of the report.

The authors thank the SAFCA group members Margit Snellman (Saanio & Riekkola Oy), Paul Smith (SAM Switzerland GmbH), Nuria Marcos (Saanio & Riekkola Oy), Pirjo Hellä (Pöyry Finland Oyj) and Barbara Pastina (Saanio & Riekkola Oy) for fruitful discussions and commenting, as well as the reviewers Mike Thorne (Mike Thorne and Associates Limited, UK), Graham Smith (GMS Abingdon Ltd, UK), Paul Gierszewski (Nuclear Waste Management Organization, Canada; Chapters 1-6) and Steve Sheppard (ECOMatters Inc, Canada; review of the background data reports).

The photograph copyrights of Hannu Vallas (Lentokuva Vallas Oy) to Figure 1-2 are also credited.

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TERMS AND ABBREVIATIONS BCC Biosphere calculation case – representing one set-up for how the surface

environments might evolve and perform over time, used to quantitatively evaluate a specific dose assessment scenario, see section 2.1.

BSA Biosphere assessment as an entirety either regarding the reporting of the assessment process (Figure 2-1) or the process itself. Specifically, BSA-2009 refers to the biosphere assessment of 2009.

BSD Biosphere description is the sub-process of analysing and integrating the site and regional data to the description of the present properties and transport processes of the site. Specifically, BSD-2006 refers to the report of Haapanen et al. (2007) and BSD-2009 to the report of Haapanen et al. (2009).

DCF Dose conversion factor EMCL Environmental media concentration limit, see sections 5.2 and 6.2. ERICA Environmental Risk from Ionising Contaminants: Assessment and

Management (EC 6th Framework Programme) FEP Feature, Event, Processes FET Forest extensive-level monitoring plot, a basic unit of a systematic 100 x 100

m² environmental monitoring grid at Olkiluoto FIP Forest intensive(-level) monitoring plot, a part of the environmental monitoring

network at Olkiluoto GIS Geographical information system LSM Landscape modelling, see sections 5.1 and 7.2 NRR Nominal release rates, see section 2.4 PSAR Preliminary safety analysis report RCA Radiological consequences analysis sub-process in the biosphere assessment RCC Repository calculation case – representing one set-up for how the repository

system might evolve and perform over time, used to quantitatively evaluate a specific repository assessment scenario, see section 2.1.

RNT Radionuclide transport modelling sub-process in the biosphere assessment RQ Risk quotient, see section 5.2 SDR Screening dose rate, see section 5.2 SNSH Surface and Near-Surface Hydrological model, described in section 4.1 STUK Radiation and Nuclear Safety Authority SVAT Soil-Vegetation-Atmosphere-Transfer model (section 5.1), used for computing

water and energy balance TESM Terrain and ecosystems development modelling as the sub-process.

Specifically TESM-2009 refers to the effort and reporting within BSA-2009 (mainly Ikonen et al. 2010b), and TESM-2006 to the model version of 2006 (Ikonen 2007b).

UNTAMO A GIS toolbox customised for Posiva for TESM, see section 2. YVL Radiation and Nuclear Safety Authority’s guides on nuclear safety

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1 INTRODUCTION Posiva Oy (Posiva) was established in 1995 by the two Finnish nuclear power companies, Teollisuuden Voima Oyj (TVO) and Fortum Power and Heat Oy (Fortum), to implement the final disposal programme for spent nuclear fuel and to carry out the related research, technical design and development (RTD, or TKS, in Finnish). Other nuclear wastes are handled and disposed of by the power companies themselves. The spent nuclear fuel is planned to be disposed of in a KBS-3 type of repository to be constructed at a depth of about 400 metres in the crystalline bedrock at the Olkiluoto site. Currently, two variants of the KBS-3 method are under consideration, KBS-3V and KBS-3H. In KBS-3V, the canisters are emplaced vertically in individual deposition holes constructed in the floors of deposition tunnels. In KBS-3H, several canisters are emplaced horizontally in a system of 100-300 m long deposition drifts. In both variants, the canisters are surrounded by a swelling clay buffer material that separates them from the bedrock and, in the case of KBS-3H, also separates the canisters one from another along the deposition drifts. The KBS-3V deposition tunnels and other underground openings in both variants are to be backfilled with a low permeability material.

In 2001, the Finnish Parliament ratified the Government’s favourable Decision in Principle on Posiva’s application to locate a repository at Olkiluoto. This decision represents the milestone prior to entering the phase of confirming site characterisation. Following the guidelines set forth by the Ministry of Trade and Industry (now the Ministry of Employment and Economy), Posiva is preparing for the next step of the nuclear licensing of the repository, which involves submitting the construction licence application for a spent fuel repository by the end of 2012. A safety case will be produced to support the licence application. This report presents the biosphere assessment performed for the interim safety case of 2009, and will be updated for the safety case of 2012.

1.1 Olkiluoto site Olkiluoto is a moderately sized island (currently an approximate area of 12 km2), on the coast of the Baltic Sea, separated from the mainland by a narrow strait (Figures 1-1 and 1-2). The Olkiluoto nuclear power plant, with two reactors in operation, and a repository for low- and intermediate-level waste are located on the western part of the island. The construction of a new reactor unit (OL3) is underway at the site. The repository for spent fuel will be constructed in the central-eastern parts of the island after the construction licence for the spent fuel repository has been obtained. The construction of an underground rock characterisation facility, called ONKALO, started in June 2004.

The areas considered in biosphere assessment are shown in Figure 1-3: the smaller purple rectangle, in which Olkiluoto Island is located, delineates the Model area considered in the safety assessment modelling, and the larger study area is the so-called Reference area, which is used for regional descriptions, especially for lakes and mires, which presently are scarce in the Model area. Monitoring and investigations to obtain terrestrial data have, however, been concentrated on Olkiluoto Island, and more specifically on the central parts of the island.

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Figure 1-1. An overview map of Olkiluoto. Topographic database by the National Land Survey of Finland, map layout by Jani Helin/Posiva Oy.

Figure 1-2. Olkiluoto Island and neighbouring mainland areas from the air on August 6, 2007 Photograph by Hannu Vallas/Lentokuva Vallas Oy.

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Figure 1-3. The full Reference area with locations of lakes and mires selected as reference objects. The Model area refers to the area included in the terrain and ecosystem development model, and the dependent radionuclide transport model. CORINE Land Cover 2000 classification by Finnish Environment Institute. Map layout by Jani Helin/Posiva Oy.

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The site is located in an area of significant continuing postglacial land uplift (currently the rate of uplift is approximately 6–6.8 mm/y; Eronen et al. 1995, Kahma et al. 2001, Löfman 1999). This leads to new land areas continuously emerging. The effects of this process are accentuated by a rather flat topography and anthropogenic eutrophication1

1.2 Safety case

of the Baltic Sea, which increases primary production, and consequently accumulation of organic matter especially in shallow bays. Common reed is a key organism in this process, producing detritus, decreasing water flows and increasing silting. In the archipelago area south-southwest of Olkiluoto, emergence of smaller-scale lake and river systems is expected within some centuries. Another important factor for the development of the landscape is the Eurajoki River that has its outlet northeast of the island. It is expected that this river will flow north of the planned repository after one or a few millennia.

Posiva is currently producing a safety case to support the construction licence application for a KBS-3 type of repository at the Olkiluoto site. A safety case is a synthesis of evidence, analyses and arguments that quantify and substantiate the long-term safety, and the level of expert confidence in the safety, of a geological disposal facility for radioactive waste (IAEA 2006, NEA 2004, NEA 2009). Posiva's plan for the safety case was initially prepared in 2004 (Vieno & Ikonen 2005), and has recently been revised (Posiva 2008). The first planning report introduced the Posiva safety case portfolio as the documentation management approach, facilitating a flexible and progressive development of the safety case; this approach is further developed in the current safety case plan.

1.2.1 Principles of the safety case A safety case includes a quantitative safety assessment, which is defined as the process of systematically analysing the ability of the disposal facility to provide the safety functions and to meet technical requirements, and evaluating the potential radiological hazards and compliance with the safety requirements (Posiva 2008).

The safety case broadens the scope of the safety assessment to include the compilation of a wide range of evidence and arguments that complement and support the reliability of the results of the quantitative analyses and demonstrate compliance with regulatory requirements. In concrete terms, a safety case includes all material presented by the repository implementer to the authorities and to other stakeholders in support of an application to site, construct, operate or close a disposal facility. The safety case is a key input to decision-making at several steps in the repository planning and implementation process. It becomes more comprehensive as the programme progresses.

1.2.2 Posiva safety case portfolio Posiva’s safety case will be developed according to the plan published in 2008 (Posiva 2008). The first safety case plan of 2005 introduced the Posiva safety case portfolio as the documentation management approach, facilitating a flexible and progressive development of the safety case; this approach was further developed in the 2008 safety

1 Increase in the concentration of chemical nutrients in an ecosystem to an extent that it increases the production of organic compounds of the ecosystem.

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case plan. The safety case will be documented in a report portfolio. The safety case report portfolio is structured as shown in Figure 1-4 and elaborated below.

The Safety case plan 2008, describes the methodology and the plan (Posiva 2008). The Description of the disposal system report summarises the information on the waste form, the engineered barrier system and the geosphere and surface environments at the Olkiluoto site. More detailed descriptions are given in technical and scientific reports on various components of the disposal system, including the site descriptive model of Olkiluoto and the description of biosphere conditions. Background analyses related to future climatic conditions will also be performed and reported. The features, events and processes (FEPs) affecting the evolution of the repository will be described in the Process report supported by a FEP database. The evolution of the disposal system and the scenarios for analysis in the safety assessment are described in the Formulation of scenarios report. The most important models and data, together with their underpinning assumptions are documented in the Models and data report. This serves as the main link between the safety case and the Olkiluoto site investigations and biosphere descriptions as well as between the safety case and the engineered barrier system (EBS) design and development. The quantitative assessment of the radiological consequences of scenarios leading to radionuclide releases is presented in the Analysis of scenarios report. The Complementary considerations report is carried over from the earlier Safety Case Plan 2005 (Vieno & Ikonen 2005), where it was called the Complementary evaluations report. This provides additional evidence and arguments for long-term safety to promote confidence in the arguments, models and data used in, and results derived from, the quantitative safety assessment. Finally, the main arguments and results of the safety case will be condensed in a Summary report. This report will provide the main input to the Preliminary Safety Analysis Report (PSAR) needed for the application for a repository construction licence.

The production of the safety case is divided into four main sub-processes. The Conceptualisation & methodology sub-process defines the framework for the assessment. The Data handling and modelling sub-process creates the main links between the safety case, the engineering design and planning of implementation processes, and the site characterisation process. The Assessment sub-process produces the Olkiluoto- and design-specific descriptions of the evolution of the disposal system in various scenarios, classified either as part of the expected evolution or as disruptive scenarios and analyses their potential consequences. The Compliance & confidence sub-process is responsible for the final evaluation of compliance of the assessment results with the regulatory criteria and for determining the overall confidence in the safety case.

A key contributor to the safety case is the biosphere assessment (BSA). In the present safety case plan (Posiva 2008), the biosphere assessment portfolio (as presented in Ikonen 2006) has been fully integrated into the main safety case portfolio and the safety case main sub-processes. However, the BSA component is retained as a distinct entity for practical reasons, and will be documented in detail in several modelling and other reports (see Section 1.2.4).

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Figure 1-4. Main reports of the safety case portfolio (in blue) and the main input from

supporting technical and scientific activities (in white). EBS: engineered barrier system.

1.2.3 Regulatory requirement and guidance for dose assessment

The basic regulatory requirements for the long-term safety of a geological repository in

Finland are set out in the Government Decree on the safety of disposal of nuclear waste

(GD 736/2008) and, in more detail, in the Radiation and Nuclear Safety Authority’s

(STUK) Guide YVL E.5 on disposal of nuclear waste. Guide YVL E.5 is expected to be

issued in 2010 by the Finnish regulator and will supersede the earlier YVL 8.4 issued in

2001 (STUK 2001). GD 736/2008 and Guide YVL E.5 cover all aspects of the disposal

of nuclear waste, including spent nuclear fuel. These aspects include radiation

protection during the operation of the disposal facility and long-term safety. In an

appendix to YVL E.5, guidance on regulatory expectations on the safety case will be

provided. Guide YVL E.5 is quoted throughout the present document, based on an

unofficial English translation of draft version 3 (STUK 2009). The GD 736/2008 sets

the criteria for the time window to be addressed in the biosphere assessment and the

criteria for protection of humans within this time window:

“In any assessment period, during which the radiation exposure of humans can be

assessed with sufficient reliability, and which shall extend at a minimum over

several millennia:

1) the annual dose2 to the most exposed people shall remain below the value of

0.1 mSv, and

2) the average annual doses to other people shall remain insignificantly low.”

2 annual dose refers to the sum of the effective dose arising from external radiation within the period of

one year, and the committed effective dose from the intake of radioactive substances within the same

period of time (GD 736/2008). In this report “dose” refers to effective dose, and “annual dose” refers to

the annual effective dose, unless otherwise explicitly stated.

SAFETY CASE PLAN 2008

Description of the Disposal System

Analysis of scenarios

Expected

Process Report

Formulation of Scenarios

Models and Data

Complementary considerations

Summary

EBS and Repository

Design

SITE (Geosphere and Biosphere)

EXTERNAL CONDITIONS(e.g. Climate)

CONCEPTUALISATION AND METHODOLOGY

VAHA RSC

SUBSYSTEMS

REPOSITORYENVIRONMENT

Critical data needs

ASSESSMENT

COMPLIANCE AND CONFIDENCE

Other

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Posiva’s interpretation of “assessment period” is presented in Chapter 2, while those of “most exposed” and “other” people are presented in Section 6.1. After that period, the quantitative regulatory requirements are based on constraints on the activity release of long-lived radionuclides from the geosphere into the biosphere (Guide YVL E.5). Consequently, the licence applicant does not have to present quantitative dose assessments for the period beyond which “the radiation exposure of humans can be assessed with sufficient reliability”; this period shall commence at the earliest after several millennia. However, biosphere FEPs may influence the assessed releases from the geosphere to the biosphere during the whole time frame considered in safety assessment.

Guide YVL E.5 (STUK 2009) identifies the potential exposure environments and pathways to be considered. The dose assessment in general may assume that types of climate, human habits, nutritional needs, and metabolism remain unchanged, but needs to take account of reasonably predictable environmental changes, such as those that “arise from changes in ground level in relation to sea”. At least the following exposure pathways shall be considered:

• Use of contaminated water as household water, as irrigation water and for watering animals,

• Use of contaminated natural or agricultural products originating from terrestrial and aquatic environments.

Based on these guidelines, the most exposed individuals are assumed to live in a self-sustaining family or small village community in the environs of the disposal site, where the highest radiation exposure arises via various pathways. In the living environment of this community, a small lake and shallow water well are assumed to exist. Larger groups of people for whom average doses are estimated are assumed to live by a regional lake or at a coastal site and are exposed to the radioactive substances transported into these watercourses. For the larger groups, no fixed dose constraint is set, but the acceptability of the doses depends on the number of exposed people, and they shall not exceed values from one hundredth to one tenth of the constraint for the most exposed individuals (STUK 2009).

The Guide YVL E.5 does not give any quantitative criteria for the protection of other living species. However, it is stated that:

• Disposal shall not affect detrimentally to species of flora and fauna, this shall be demonstrated by assessing typical radiation exposures of terrestrial and aquatic populations in the disposal site environments.

Consideration may be limited to the kinds of living populations currently found in the surface environment. No quantitative dose or exposure constraints are given for other living species. To demonstrate compliance with the regulatory criteria, the licence applicant shall assess the exposures and demonstrate that they are clearly below the levels which, on the basis of best available scientific knowledge, would cause decline in biodiversity or other significant detriment to any living population. In the compliance assessment part of the current assessment, Posiva has calculated typical absorbed dose

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rates and compared these with the screening values recommended by the PROTECT3

Finally, according to Guide YVL E.5, the regulator expects that a safety case shall include a description of the disposal system, including the natural environment at the disposal site.

project.

1.2.4 Biosphere assessment The overall aims of the biosphere assessment in the safety case are:

• to describe the future, present, and relevant past conditions at, and prevailing processes in, the surface environment of the Olkiluoto site;

• to model the transport and fate of radionuclides hypothetically released from the repository through the geosphere to the surface environment; and

• to assess possible radiological consequences to humans and other biota.

The surface environment will evolve significantly on a timescale comparable to that of variations in the radionuclide release from the geosphere. For example, areas that are currently sea bottom will develop into terrestrial areas and lakes will be formed over a period of a few millennia. Hence, a steady-state approach, based on the current conditions at the site or on stylised future steady state conditions, such as the use of drinking water or irrigation wells in different assumed steady-state climate conditions, is not sufficient to meet current assessment purposes. The main approach in the present biosphere assessment is to develop a fully dynamic model for the development of the surface environments, radionuclide transport and radiological consequences analysis.

Biosphere assessment has conceptually been implemented as a process divided into five main sub-processes. These are discussed in detail in section 2 and can briefly be summarised as follows.

• Biosphere description (BSD) sub-process – performing environmental studies and monitoring, and the compilation of a description of the present properties and on-going processes at the Olkiluoto site.

• Terrain and ecosystems development sub-process – predicting the development of the topography, overburden, and hydrology at the site. In the future, flora and fauna will also be included in the predictions. This is called forecasting and is carried out by terrain and ecosystems development modelling (TESM).

• Landscape model set-up sub-process – defining the landscape model (LSM), which is the state-of-the-art time-dependent and site-specific radionuclide transport model used in the next sub-process.

• Radionuclide transport (RNT) modelling sub-process – defining the ecosystem-specific radionuclide transport models underlying the landscape model, and

3 The EU EURATOM- funded PROTECT project (FI6R-036425) is evaluating the different approaches to protection of the environment from ionising radiation and comparing these with the approaches used for non-radioactive contaminants. This will provide a scientific justification on which to propose numerical targets or standards for protection of the environment from ionising radiation.

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analysing the fate of radionuclides released from the geosphere. A screening approach is first applied, to screen out radionuclides that have insignificant radiological consequences.

• Radionuclide consequences analysis (RCA) sub-process – assessing potential radiological consequences to humans and other biota and putting them in the context of regulatory requirements.

The work performed within the biosphere assessment will contribute to the safety case, often to more than one of the main safety case reports. To illustrate the relationship between the BSA and the safety case, Table 1.1 indicates where the five major sub-processes of the BSA significantly contribute to the main safety case reports.

Reporting the biosphere assessment The Biosphere Assessment Portfolio was introduced in the Safety case planning report (Vieno & Ikonen 2005) and revised in Ikonen (2006). This portfolio structure was followed in the reporting of the biosphere analysis included in the safety assessment of a preliminary design of a KBS-3H repository for spent nuclear fuel at the Olkiluoto site, the KBS-3H safety studies (Smith et al. 2007a). However, the KBS-3H biosphere analysis (Broed et al. 2007) was lacking some major components to be considered to be a full biosphere assessment, such as assessing average doses to a larger exposed group, as required by the GD 736/2008, and demonstrating the radiation protection of other living biota. As discussed above, the biosphere assessment is now conceptually fully integrated into the safety case, but the biosphere assessment component has been retained as a distinct entity for practical reasons. This means that the reporting of the biosphere assessment will continue to mainly follow the Biosphere Assessment Portfolio in Ikonen (2006), with a few modifications due to new features in the overall safety case portfolio (Posiva 2008). The biosphere assessment undertaken in 2009 is part of the interim safety case developed in 2009. The current biosphere assessment, which is the first considered to include all necessary components to be denoted an assessment, will produce four main reports, and several supporting reports, briefly described as follows.

Table 1-1. Main contributions from the five major sub-processes of the BSA to the main reports in the safety case. See main text for explanation of abbreviations.

BSA sub-process(a) BSD TESM LSM set-up RNT RCA Safety case main report Description of the disposal system X Process report X X Formulation of scenarios X Models and data X X X X X Analysis of scenarios X X X X Complementary considerations X Summary X X X X X

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Biosphere description report. The BSD-2009 report (Haapanen et al. 2009) provides a scientific synthesis of knowledge as to the current state of the surface environment and the main features of the past evolution at the site. Furthermore, it provides conceptual ecosystem models and assessment data to support the subsequent biosphere assessment sub-processes. Due to their extent, a large fraction of the data for the assessment was moved to a supplementary report (Ikonen et al. 2010a) The BSD-2009 is an update of Olkiluoto Biosphere description report 2006 (Haapanen et al. 2007), and will be further updated for the 2012 assessment.

Terrain and ecosystem development model report (TESM-2009). TESM-2009 (Ikonen et al. 2010b) provides a scientific synthesis of the expected development of the surface environments over the period for which the dose-based constraints apply. TESM-2009 is an update of TESM-2006 (Ikonen 2007b), and will be further updated for the 2012 assessment.

Radionuclide transport and dose modelling in biosphere assessment in 2009 (Hjerpe & Broed 2010). This report documents the conceptual and mathematical models and key data used in the landscape model set-up, radionuclide transport modelling, and radiological consequences analysis. The report also provides the basis for understanding the behaviour of the landscape model, by calculating results for stylised releases, such as pulse and long-term unit releases, into the biosphere, to investigate how the models respond in such cases. Key supporting reports are detailed model and modelling tool reports, such as Avila & Pröhl (2007), Avila & Bergström (2006) and Åstrand et al. (2005). The present report is also supported by a review report on concentration ratio and distribution coefficient data (Helin et al. 2010). The present report is an update, and extension of the similar report (Broed 2007a) produced for the KBS-3H safety assessment (Smith et al. 2007a), and will be further updated in 2012.

Biosphere assessment summary report (this report). This report (BSA-2009) presents the biosphere calculation cases and applies them to results from the relevant repository calculation cases presented in the recent radionuclide release and transport report for the KBS-3V design, the RNT-2008 report (Nykyri et al. 2008). The fate of any radionuclides potentially released from the repository in the scenarios considered in RNT-2008 is discussed in the present report, along with the radiological consequences to humans and other biota. In addition, this report summarises the three above-mentioned main biosphere assessment reports. The BSA-2009 report is the first biosphere assessment report produced within the development of the Posiva safety case. The methodology and models applied in the present biosphere assessment are an update and an extension of the methodology and models applied in the biosphere analysis in the KBS-3H safety assessment; and the BSA-2009 report has many similarities with that summary report (Broed et al. 2007). The BSA-2009 report will further be updated in 2012.

Biosphere assessment regarding operational safety and environmental impacts The biosphere assessment considers various aspects relevant to long-term safety, i.e., the performance of the repository, and fate and consequences of possible radionuclide releases from the emplaced disposal canisters in the time window from the emplacement of the first canister to several millennia in the future. However, the same characterisation activities, data and understanding of the ecosystems are useful also in

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considerations of environmental impacts of the entire disposal programme and in the assessment of operational safety, i.e. radiological safety of the staff and public during nuclear waste transport, encapsulation and final emplacement. These aspects are not, however, explicitly considered in this report.

1.3 This report This report is the final report in the biosphere assessment of 2009. The first aim of the report is to present and discuss the results from the radionuclide transport modelling and dose assessment conducted on the radionuclide releases from the geosphere for a KBS-3V repository. The second aim is to present the overall biosphere assessment methodology and the main findings from the three other main biosphere assessment reports (section 1.2.4). The report is structured as follows:

• Overview of the contents and outcome of the other three main BSA-2009 reports

- Biosphere description report (chapter 3), - Terrain and ecosystem development model report (chapter 4), and - Radionuclide transport and dose modelling report (chapters 5 and 6).

• Presentation of

- the biosphere assessment methodology (chapter 2), - the main findings of the biosphere assessment (chapter 7), - the main findings of the complementary analysis (chapter 8), and - a summary of the level of quality in the knowledge basis (chapter 9).

Finally, the conclusions from the present biosphere assessment are given in chapter 10.

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2 BIOSPHERE ASSESSMENT As mentioned in Chapter 1, the aims of the biosphere assessment in the safety case are to describe the present, future and relevant past conditions at, and prevailing processes in, the surface environments of the Olkiluoto site, to model the transport and fate of radionuclides hypothetically released from the repository through the geosphere to the surface environment, and to assess possible radiological consequences to humans and other biota. The time window adopted in the present assessment, which is the period over which the regulatory dose constraints are assumed to apply, starts at the year of the emplacement of the first canister and lasts for ten millennia. In the quantitative analysis in the biosphere assessment, the default time window is thus from the year 2 020 to the year 12 020 in the Common Era4

Performing a biosphere assessment can conceptually be described as a process (illustrated in

.

Figure 2-1); the biosphere assessment put into the context of the overall modelling process in the safety case is illustrated in Figure 2-2. The main activities in the five sub-processes, and their connections to each other, are described below.

The main activities in the Biosphere description sub-process are to conduct environmental studies and monitoring, and provide a description (including a functional analysis) of the biosphere component of the repository site, by means of scientific synthesis of the current state of the surface environment and the main features of the past evolution at the site. It also increases overall understanding of the surface environments at the site. In addition, this process supports the analysis of potential future evolution of the disposal system and the assessment of resulting radiological consequences by supporting the modelling of terrain and ecosystems development and the selection of site-specific parameter values and distributions in the analyses of transport of radionuclides.

Figure 2-1. Schematic illustration of the biosphere assessment process. The five major sub-process are marked in bold; the main activities (text under the components) are indicated by colours in the components. Selected key inputs and links are also included, especially regarding hydrological modelling.

4 Common Era (abbreviated as CE) is a designation for the world's most commonly used year-numbering system; the numbering of years is identical to the numbering used with Anno Domini (BC/AD) notation, 2010 being the current year. In the present report, all years, if not explicitly stated otherwise, are based on the Common Era system.

Radiological consequences

analysis

Radionuclide transport modelling

Landscapemodel set-up

Terrain & ecosystem

development

Biosphere description

Integration of site dataProcesses Forecasting Transport modelling Compliance assessment

Safety indicators

Outcome

BIOSPHEREASSESSMENT

CLIMATIC ENVELOPE

Surface and near-surface hydrological modelling

Groundwater flow modelling

Near-field modelling Geosphere modelling

Env. studies Monitoring

Simplifiedrelease pattern

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Figure 2-2. Models and information flows in the overall safety assessment. Radionuclide release and transport models and radiological consequences analysis are shown in white boxes. System descriptions are shown in light blue boxes, key supporting models in green boxes and their principal outputs in dark blue ovals. The boxes within the blue line are addressed in the biosphere assessment. The description of present conditions in the surface environment forms the basis for predicting the development of the topography, overburden, hydrology, flora and fauna at the site within the climate condition envelope applied in the overall safety case (see chapter 5 in Pastina & Hellä (2006)). This is called forecasting and is carried out by terrain and ecosystems development modelling (TESM). It is the main task in the Terrain and ecosystems development sub-process. For simulating land-uplift-driven changes and other changes in the biosphere until and beyond the time when the potential releases would reach it, a geographical information system (GIS) toolbox named UNTAMO has been developed (Ikonen et al. 2010b). Briefly, the toolbox consists of the following main components:

• Land uplift and delineation of the sea area, • Surface water bodies, • Terrestrial and aquatic erosion, • Accumulation of organic matter, • Terrestrial vegetation, • Aquatic vegetation, • Faunal habitats, • Human settlement and land use, and • Simulation control.

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The UNTAMO toolbox is used in the biosphere assessment together with the surface and near-surface hydrological model (SNSH), documented in Karvonen (2008, 2009a-c). The future terrain and ecosystems are forecast with UNTAMO and delivered as input data to the SNSH model to simulate groundwater flow and water table characteristics in detail, which in future assessments will be used as the groundwater head boundary condition in the deep groundwater flow modelling.

The forecasted conditions in the surface environment in the year 2020, which is the assumed emplacement time of the first canister, define, in this context, the initial state of the biosphere. This is the starting point for the landscape modelling. The forecast is based on the terrain and ecosystem modelling and surface and near-surface hydrology modelling. These, in turn, are based on the latest available site-specific data and models, such as the terrain (elevation) model (Pohjola et al. 2009), the land uplift model (Vuorela et al. 2009) and the ecosystem models describing the present surface environment (Haapanen et al. 2009). Using the forecasts, continuous and sufficiently homogeneous5

In the Radionuclide transport modelling process, the potential fate of radionuclides released to the biosphere is assessed. The main task of this process is to produce time-dependent radionuclide-specific spatial activity distributions in all biosphere objects. A graded approach based on three tiers has been applied (see also section

sub-areas of the modelled area that could potentially receive radionuclides released from the repository are identified (these are called biosphere objects). To identify the biosphere objects, the release pattern is determined. The release pattern is a stylised representation of the radionuclide release points from the geosphere to the biosphere, based on surface and near-surface hydrology modelling and on deep groundwater modelling. Each biosphere object is described by one, or more, ecosystem types and one set of data, and is associated with a corresponding radionuclide transport model. The connections between the objects are derived from terrain forecasts for the period from the present (initial state) to the end of the assumed time window when regulatory dose constraints apply. The combination of the connected biosphere objects and the release pattern is the landscape model. The landscape model is a state-of-the art site-specific and time-dependent radionuclide transport model. Defining the initial state for the landscape model and how it develops with time is the main task of the landscape model set-up sub-process.

2.2). Tier 1 and 2 involve conducting generic evaluations to screen out radionuclides that have insignificant radiological consequences, using two levels of inherent pessimism, and only Tier 3 is based on the landscape model. The deterministic ecosystem-specific radionuclide transport models used for the biosphere objects are called biosphere object modules and, in the present assessment, include: forest, wetland, cropland, lake, river, coast, and sea. A great improvement in the models applied now, compared with the versions used in the KBS-3H safety assessment (Broed 2007a), is that they are

5 Sufficient homogeneity requires firstly that within the sub-area, the variation in properties does not affect significantly the parameter values of the respective object(s) in the radionuclide transport modelling and in the radionuclide consequence analysis. Secondly, the size should not be large enough to allow the inherently heterogeneous distribution of radionuclide concentration within the object to become significant in the dose calculations; in smaller objects the behaviour of an individual averages over these variations in the cause of the exposure in accordance with the dose concept (Chapter 6).

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consistent at a conceptual level, meaning that the structure of compartments6

The resulting activity concentrations from the radionuclide transport modelling constitute the basis for assessing potential radiological consequences to humans and other biota. Assessing these consequences and putting them into the context of regulatory requirements are the main tasks of the Radionuclide consequences analysis sub-process. Radiological consequences to humans are assessed by a prospective deterministic dose assessment process, based on recommendations from the ICRP (International Commission on Radiological Protection) (ICRP 2000, 2007b). The assessment is based on site-specific conditions and present regional land use; e.g., the exposed population size is limited by site-specific constraints on food production and by the availability of drinking water. During the time window of biosphere assessment, the surface environment will undergo significant development and many generations may be exposed. This is taken into account by deriving the full dose distribution (the dose to each potentially exposed individual utilizing the contaminated area) for each generation. Radiological consequences to other biota are assessed by a deterministic prospective exposure assessment, in which typical absorbed dose rates to flora and fauna at the site are calculated. The guidance provided by the regulators on how to calculate typical absorbed dose rates to other biota is very sparse; the approach developed and implemented in this report is considered by Posiva to meet the requirements in the Guide YVL E.5 (STUK 2009). However, it is acknowledged that the approach lacks in maturity, compared with the approach for assessing doses to humans, and, if found necessary, further development may be undertaken. The approach to identify typical absorbed dose rates is firstly, to identify a group of species to include in the assessment, and secondly, for these to derive absorbed dose rates based on Tier 3 of the ERICA (Environmental Risk from Ionising Contaminants: Assessment and Management) methodology (Beresford et al. 2007). When selecting assessment species, the first step is to identify their trophic roles (the position that the species occupy in the food web). These have been identified (Haapanen et al. 2009, chapters 4-7, especially section 4.1.6 for terrestrial fauna

is very similar in each module. This facilitates the coupling between ecosystems existing at the same time, and the transition over time from one ecosystem type to another due to the development of the biosphere.

7

6 The ecosystem-specific radionuclide transport models are based on a compartmental approach, where the radionuclides are assumed to be well-mixed within each compartment.

but should be done similarly for other ecosystems in future versions of BSD) and then characteristic species have been selected to represent each trophic role. Here, ‘characteristic’ means most common within the limitations of the available data, since analogue data are needed anyway, The species selected are considered to matter less than the fact that the different roles in the ecosystem are covered and the range of data applied to the properties of the assessment species also cover the other species in the trophic compartment to a reasonable degree. With the process implemented to identify the assessment species, the results can be argued to be typical at least at the level of the trophic roles, implying that impacts on ecosystem functioning are evaluated for a typical representation.

7 This will be expanded to the other fauna in the future updates of the Biosphere description.

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2.1 Scenarios and calculation cases Each sub-process in Figure 2-1 includes sources of uncertainties. In order to assess the potential impact of key uncertainties on radiological consequences, dose assessment scenarios will be formulated, and subsequently quantitatively assessed by means of a set of calculation cases. This section describes the methodology to develop assessment scenarios (defined below), how it is applied here, and the calculation cases identified to assess the scenarios.

2.1.1 Methodology The evolution of the disposal system will be affected by features, events and processes (FEPs) both internal and external to the system. Uncertainties in the occurrence and timing FEPs lead to uncertainties in the potential future evolutions of the disposal system; these uncertainties give rise to multiple potential lines of evolution. All potential lines of evolution are evaluated and systematically grouped into a range of scenarios. The classification8

Climatic scenarios provide the framework within which the evolution of the disposal system can be described. The disposal system is taken to comprise the repository system, i.e. the system of engineered barriers and the surrounding bedrock, plus the overlying surface environment.

of scenarios adopted by Posiva for the purposes of the present safety assessment is as follows:

In the safety analyses described in the present report, the base scenario includes lines of evolution of the disposal system during which the canisters will isolate the waste and provide complete containment of radionuclides over at least a million year time frame (Posiva 2008).

Assessment scenarios include those lines of evolution of the disposal system that involve radionuclide release from the canister and hence contain the possibility of exposing humans and other biota to ionising radiation. They are developed by combining repository assessment scenarios and dose assessment scenarios. These categories of scenarios are each described separately, below.

Repository assessment scenarios are developed for lines of evolution of the repository system leading to canister failure and radionuclide release to the repository near-field. These generally have a low probability of occurrence, although in some cases the probabilities are not yet well defined.

Dose assessment scenarios are scenarios describing the potential fate of radionuclides in the surface environment. They include lines of evolution of the surface environment, which also form part of the base scenario, and lines of evolution as how humans and other biota inhabit and use the surface environment during the time window for quantitative dose assessment (at least several millennia), taking regulatory guidelines into account.

Dose assessment scenarios explore the consequences of the main uncertain features and processes that potentially could lead to alternative development and usage of the surface

8 The classification will be updated in the future based on guidance in STUK YVL E.5

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environment and migration paths for radionuclides into and within it. Potential radiological consequences to humans and other biota constitute the primary endpoints to consider when identifying the main uncertain features and processes. The dose assessment scenarios are driven primarily by the combination of climatic changes and land use. The shoreline position at Olkiluoto is time-dependent, and may be inferred from combining the land uplift rate and the possible effect on the sea level caused by climate changes (such as increased global sea levels due to reduction of Greenland or Antarctic ice sheets). Land use changes are mainly driven by anthropogenic influences, below denoted future human activities (FHA).

Other dose assessment scenarios could be driven by further external factors, such as meteorite impact, but these are not considered in Posiva’s dose assessment. Changes in available technology could potentially affect the land use. Changes in the fields of radiobiology and epidemiology (related to our understanding of radiation risks at low doses and dose rates) or medical science (related to our capability for treating cancer) could affect the dose assessment. These types of changes are not considered in the dose assessment, which is consistent with the Guide YVL E.5, where it is stated that human habits can be assumed to remain unchanged within the time window where dose constraints apply.

In addition to the scenarios mentioned above, the consideration of unintentional disturbance to, or intrusion into, the repository by humans subsequent to repository closure is a requirement in Finnish regulations. Uncertainties in the evolution of human society and of the state-of-the-art in science and technology are such that estimates of the consequences of human intrusion scenarios must be based on “stylised assumptions” that cannot be fully substantiated or evaluated in respect to conservativeness of radiological consequences. They are thus considered as a class of scenarios separate from repository and dose assessment scenarios.

2.1.2 Scenarios in BSA-2009 The methodology briefly described above has been applied in the present assessment to identify dose assessment scenarios, although only one of these has been analysed quantitatively by means of a set of calculation cases. Each scenario defines a general setting in which the system evolves, and is further characterised in terms of one or more calculation cases using a tree methodology, illustrating the impact of individual uncertainties, or uncertainties in combination. The key drivers for the scenarios are climatic changes and land use. The combinations of these key drivers give rise to alternative lines of evolution when formulating dose assessment scenarios. The key drivers, and the variants considered are presented in Table 2-1 and the key lines of evolution are presented in Table 2-2.

In addition to the key drivers for dose assessment scenarios, additional drivers may be used, see Table 2-3 for a few examples. The comprehensive identification of additional scenario drivers, and which variants to consider, is a work in progress that will be implemented in the 2012 assessment. In the present assessment, only one scenario has been formulated, and a few selected additional scenario drivers are addressed in the identification of calculation cases (section 2.1.3). The scenario analysed in the present assessment, the dose assessment base scenario is identified as follows:

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The dose assessment base scenario assumes that the present climate, land use and characteristics and habits of humans and other biota will remain

unchanged during the time window for biosphere assessment.

The scenario is assessed by analysing a set of biosphere calculation cases, further described below.

Table 2-1. Key drivers in the formulation of dose assessment scenarios and the variants under consideration.

Scenario driver

Descriptions and divisions into variants

Climate CL1: “Present climate” - Unchanged climatic conditions during dose assessment time window, - Sea level displacement caused by post-glacial land uplift, - Flora and fauna as currently present

CL2 “Warmer climate” - Increased temperatures during dose assessment time window, - Sea level displacement caused by post-glacial land uplift, and global

sea level changes consistent with a warmer climate, - Changes in flora and fauna

Land use LU1: “Present land use” - Present land use characteristics assumed (cultivation, forestry and

demography) - Unchanged land use during dose assessment time window

LU2: “Urbanisation” - The site is developed into an urban area within the dose assessment

time window LU3: “Wilderness” - The site is abandoned by humans within the dose assessment time

window and left in its natural state (unsettled and uncultivated)

Table 2-2. Key lines of evolution for the surface environment and land use; and how they are addressed in the biosphere assessment.

Line of evolution

Description and treatment in the biosphere assessment

CL1-LU1 Present climate and land use. This is the line of evolution applied when formulating the dose assessment base scenario

CL2-LU1 Warmer climate and present land use. Not considered in present assessment – will be addressed in the future

CL1-LU2 CL2-LU2

Present or warmer climate and urbanisation of the site. Not considered in present assessment – will be addressed in the future

CL1-LU3 CL2-LU3

Present or warmer climate and the site abandoned by humans (wilderness). Not considered in present assessment – will be addressed in the future

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Table 2-3. Selected additional drivers in the formulation of dose assessment scenarios.

Additional scenario driver

Comment Default approach in the formulation of scenarios

Habits (humans)

Especially diet and residence are of importance

Present characteristics – no changes

Habits (other biota)

For example, changes in types of flora and fauna present at the site and their habits


Other future human actions (FHAs)

There are numerous possibilities, e.g. changes in cultivation techniques, damming of a lake, intensive forest management, etc.


Natural (“sporadic”) events

This category includes isolated events that are likely to occur, such as forest fire, flooding, exceptional storms, etc.

No events addressed, will be addressed in the future

2.1.3 Calculation cases in the biosphere assessment The dose assessment base scenario is analysed by means of a set of calculations cases, denoted as biosphere calculation cases (BCC), in order to distinguish them from repository calculation cases (RCC). Repository calculation cases analyse the repository assessment scenarios; the main outcome is radionuclide fluxes from the geosphere, which is a key input when analysing the dose assessment scenarios. The radionuclide fluxes are only a function of time; information about the spatial distribution of releases at the boundary between the geosphere and the surface environment is given from the deep groundwater modelling (see section 5.1.2). The information on the spatial distribution of radionuclide releases from the geosphere will be improved in future assessments. Furthermore, not all RCCs are propagated to the biosphere assessment and analysed with BCCs; the approach as to how RCCs are treated in the biosphere assessment is presented below. Each BCC aims to quantitatively assess the impact of individual uncertainties, or uncertainties in combination, within the boundaries of the scenario. The cases are systematically arranged, following the biosphere assessment process in Figure 2-1, using a tree methodology. This approach aims to assure traceability of assumptions and data used in each calculation case, facilitates the evaluation of comprehensiveness and the classification of cases according to their level of conservatism9 and degree of realism10

Realistic biosphere calculation cases – refers to the cases considered to have an adequate

. The classification is rather similar to the classification of repository calculation cases in Nykyri et al. (2008), and can be summarised as follows:

11

9 Conservative means, in this context, overestimation of potential radiological consequences.

level of conservatism for the scenario under consideration. These cases are always analysed using radiological consequences endpoints.

10 It should be stressed that the degree of realism only concerns the dose assessment scenario, where the repository scenario is given, and is not a measure of the probability of a release from canisters and the geosphere. 11 An adequate level means here that the parameter values and assumptions used throughout the safety assessment are selected to ensure that the estimates of potential radiological consequences are cautious, but still plausible and hence not unduly pessimistic.

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Sensitivity biosphere calculation cases – address uncertainties in the knowledge of the state and behaviour of the system, or parts of it, that are reflected in the variability of the data used in the analyses. The assumptions made, and parameter values selected, are expected to be within the reasonably expected range of possibilities for the considered scenario. These cases are always analysed using radiological consequences endpoints.

“What if” biosphere calculation cases – address other, more speculative, uncertainties with low realism that could affect the outcome of the assessment. The assumptions made, and parameter values selected, may go beyond the reasonably expected range of possibilities of events, processes and possible values for the considered scenario. These cases may be analysed using other endpoints, such as radionuclide activity concentrations in environmental media, or with partial or simplified models and approaches.

Ideally, the radionuclide transport in the realistic cases should be modelled based on the likely/expected characteristics of the surface environment and a radiological consequence assessment based on reasonable and sustainable situations. In practice, parts of the radionuclide transport modelling relate to matters on which there are large uncertainties in the knowledge base, leading to the need for conceptual assumptions and simplified modelling. The approach, when making assumptions or simplifications is always, to increase the level of conservatism. The subsequent radiological consequences analysis, described in chapter 6, is considered to represent a cautious reasonable exposure situation.

Typically in the assessment of the radionuclide release and transport in the near-field and geosphere, a large number of repository calculation cases are identified and analysed in terms of radionuclide-specific near-field and geosphere release rates (Nykyri et al. 2008, Smith et al. 2007b, Vieno & Nordman 1999). In addition, the results from analysing the repository calculation cases are discussed in terms of safety indicators (section

Treatment of repository calculation cases

2.3), typically by deriving annual doses based on the stylised drinking water well scenario (section 5.4). The treatment of a repository calculation case in the analysis of dose assessment scenarios depends on the timing of geosphere release and the classification of the repository calculation case, and can be summarised as follows.

• All repository calculation cases with no geosphere release in the first 10 000 years are excluded, because they cannot lead to any radiological consequences within the time window when the regulatory dose constraints are assumed to apply.

• Only repository base cases are analysed with the full set of biosphere calculation cases.

• To avoid excessive conservatism in the outcome of the safety assessment, repository calculation cases classified as “what if” cases and considered to result in pessimistic estimates of radionuclide releases from the geosphere in the first 10 000 years are not analysed in the present report.

• Repository calculation cases with a geosphere release in the first 10 000 years, but with very low likelihood of occurring, are not analysed in the present report.

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Table 2-4. Treatment of repository calculation cases in the dose assessment. The sub-set specifies if repository calculation cases within the same case classification are treated differently in the biosphere assessment.

Assessment Case classification Sub-set Biosphere calculation cases applied

RNT-2008 Most realistic Base case All cases Most realistic Other Realistic cases Sensitivity All Realistic cases What if All None KBS-3H Base case - Realistic cases Variant cases Penalising(a) Realistic cases TILA-99 Most realistic(b) Base case Realistic cases

(a) Calculation case with annual dose nearest to the regulatory constraints in the KBS-3H safety assessment.

(b) This classification was not used in the TILA-99 study (Vieno & Nordman 1999); here the most realistic base case refers to the case most resembling the most realistic base case in RNT-2008.

In the present assessment, the approach presented in Table 2-4 is adopted. Although the focus of the dose assessment is on the repository assessment from RNT-2008 (Nykyri et al. 2008), a few cases from the previous assessments (the KBS-3H safety assessment reported in Smith et al. 2007b, and TILA-99 reported in Vieno & Nordman 1999) are also addressed, for comparison purposes and to enhance the confidence in the overall safety case. The repository cases from previous assessments are only analysed with realistic biosphere calculation cases.

Ideally, the hierarchic calculation case tree for the biosphere assessment would be derived by first identifying FEPs in each of the five sub-processes (

The biosphere calculation case tree

Figure 2-1) and possible couplings, identifying a number of possible model representations (mainly select which model parameter to vary, and the parameter values) for each, and then combining the different sub-processes. However, this approach is not feasible in practice, due to the large number of FEPs and their possible settings that would have to be considered; the tree would become unmanageable. A method of systematically identifying relevant FEPs, and the combinations of relevant FEPs, in order to derive and justify a complete set of BCCs to analyse is under development, and will be implemented by 2012. The simplified approach adopted is to treat each sub-process individually and:

1. identify key FEPs that from earlier experience have been shown to have a significant effect on the outcome the safety analysis, especially on dose endpoints, and other FEPs that possibly may have a significant effect, at least for results produced by a sub-process that are used later in the assessment (for example terrain forecasts, or the set-up of the landscape model),

2. determine the potential model representations (how many variants to analyse, and their parameter values) that could be used for each FEP,

3. combine the FEP lists for the sub-processes and select which “combinations”, i.e., which biosphere calculation cases, to analyse (the combinations not selected are argued to be bounded by the analysed cases),

4. classify the selected biosphere calculation cases.

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A concise list of FEPs is presented in Table 2-5 to Table 2-9. The tables also briefly describe how they are treated (BCC in present assessment, addressed in earlier assessment, ongoing research work, to be included future assessments, etc.). It should first be noted that these tables are far from being complete; the aim is to have a comprehensive list included in the 2012 assessment. Secondly, for the first sub-process, biosphere description, no key FEPs have been selected; in a future assessment the effect on the assessment outcome due to variability and uncertainty in site data will be included. The calculation cases addressed in the present assessment are summarised in Table 2-10 and illustrated in a simplified two-level hierarchy tree structure in Figure 2-3, with the realistic BCCs on the top level and sensitivity BCCs on the next level down; it should be noted that only the key FEPs leading to calculation cases are included in the tree.

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Table 2-5. Selected FEPs in the terrain and ecosystem development sub-process, and how they are addressed in the biosphere assessment. FEP Comment Treatment Erosion and sedimentation (aquatic)

The model for aquatic erosion/sedimentation needs to be improved.

Currently, a modified model (Ikonen 2006) based on the model by Brydsten (2004) to estimated sedimentation in lake basins can be used, but is considered to produce results with large uncertainties.

A wind fetch12

Realistic BCC. Cautious assumption that there is no sedimentation in lakes.

based physical model has only recently been developed and will require testing, thus it will not be used until the 2012 assessment.

Ongoing work. The fetch model will be subject to preliminary testing in 2009, and used in 2012.

Developing surface environment

The paths for ecosystem evolution (see section 5.1) are uncertain. One set of paths is considered to be more probable than the others. However, alternative evolutionary paths are considered.

Realistic BCC. Paths following the full lines in Figure 5-2 are allowed.

Ongoing work. Sensitivity or What if case(s) in 2012.

Terrain The terrain model is a statistical model. Thus, alternative topographies can be extracted.

Ongoing work. Sensitivity case(s) in 2012.

Post-glacial land uplift

Uncertainty in the magnitude, and spatial and temporal variability. This process is linked to the terrain model. Research is currently being performed regarding this issue (forthcoming PhD thesis).

Ongoing work. Sensitivity case(s) in 2012.

Overburden The impact of uncertainties in the overburden model will be evaluated. Data are currently being compiled.


Erosion and sedimentation (terrestrial)

Models handling terrestrial erosion processes in a more physical manner are available, but need testing before use in assessment.

Realistic BCC. Soil erosion in croplands considered as a constant flux in the radionuclide transport modelling.

Ongoing work: The model will be used in BSA-2012.

FHA Large lakes may be dammed or dried and used as croplands. The impact of such actions shall be assessed.

This has partly been addressed (Ikonen et al. 2008b), discussed in BSA-2009 and will be improved by 2012.

FHA Channelling of rivers, so they flow over the exit points or major hydraulic bedrock features.

What if case(s) in 2012 (requires a link to hydrological modelling).

12 Wind fetch is the unobstructed distance that wind can travel over water in a constant direction. Fetch is important, because the fetch affects the size of wind-generated waves. That, in turn, affects e.g. the shoreline and bottom erosion and sediment resuspension.

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Table 2-6. Selected FEPs in the landscape model set-up sub-process and how they are addressed in the biosphere assessment. FEP Comment Treatment Flooding This is an event currently addressed within the

landscape model set-up sub-process. This type of event might be addressed in the TESM in the future.

Uncontaminated areas might receive radionuclides if they are flooded.


Release paths in the geosphere

Distribution and timing of the release locations into the biosphere, here called the release pattern, is a key feature when building the landscape model and hence in the outcome of the dose assessment.

15 patterns evaluated in the present assessment (see also Table 5-1).

Realistic BCC. Three patterns, one for each considered repository panel.

Sensitivity BCCs. 12 additional patterns assessed.

What if cases, addressed in the KBS-3H analysis (Broed 2007a).


Analyses should be undertaken on to whether the assessment outcome is sensitive to the stage of the development the surface environment at which a geosphere release reaches the biosphere (this issue is also closely related to the TESM sub-process).

Sensitivity BCCs. Nominal releases (section 2.4) input to the landscape model at various times.

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Table 2-7. Selected FEPs in the radionuclide transport sub-process and how they are addressed in the biosphere assessment. FEP Comment Treatment Water balance The effect of a significant change in the flow rate

of a main river originating from a dry/wet year within the envelope consistent with the overall climate should be evaluated (see also Table 2-5)

Sensitivity cases in 2012.

Soil degassing Evaluate if this process has any significant role for carbon, iodine, chlorine and selenium

Sensitivity or What if case in 2012.

Forest fire Impact of forest fires should be evaluated. When the organic material is burnt, all radionuclides bound to biomass, litter and humus become concentrated in the ash or redistributed via the atmosphere.

What if cases in 2012.

Seasonal variations

Usually, mean annually data are used in long-term safety analysis. Appling monthly data would potentially reveal the effects of peak concentrations in runoff (during spring) and in soil (during wetter and/or growing season); possibly relevant to long-term accumulation processes.

What if case(s) in 2012.

Release paths in the biosphere

Releases are, in the model, directed to the water body in the aquatic objects to ensure conservatism in respect to doses to humans. For the derivation of doses to the other biota, the more conservative case might be, for some assessment species, to direct the release through the aquatic sediment

Sensitivity or What if case in 2012.

Table 2-8. Selected FEPs in the radiological consequences analysis sub-process and how they are addressed in the biosphere assessment. FEP Comment Treatment Habits (humans)

The dose assessment concept is based on a hypothetical person with reasonably cautious habits, regarding intake of food and water, relative to average habits on a national scale. Uncertainties arise from different habits, especially regarding intake of food and water, both due to individual and socio-regional variability.

Realistic BCCs. Annual intake of water and nutritional demand based on the ICRP Reference Man (ICRP 1975, 2002).

Sensitivity cases in 2012.

Habits (humans)

The irrigation practises vary substantially in reality between crops and between farms, even on a regional scale.

Realistic BCCs. All crops are cautiously assumed to be irrigated with contaminated water in croplands.

Sensitivity BCCs. No irrigation with contaminated water in croplands.

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Table 2-9. Selected FEPs external to the biosphere assessment process and how they are addressed in the biosphere assessment. FEP Comment Treatment Timing of geosphere releases

The starting year for the near-field and geosphere modelling is not given in calendar years, since no assumption is made when, during the operational period, the defective canister is actually emplaced. The uncertainty arising from when the defective canister in question is emplaced will be evaluated.

Realistic BCCs. Year 0 in RNT-2008 is 2 020 (expected emplacement of the first canister).

Sensitivity BCC. Year 0 in RNT-2008 is year 2 100 (approximate time of repository closure).

Table 2-10. Summary of the FEPs considered in the analysis of biosphere calculation cases in the present assessment and the identifier and aims of the cases. It should be noted that each BCC identified in the table will also get the suffix A, B or C in the analysis, since each case will be analysed for a realistic release pattern from the three repository panels considered (see section 5.1.2).

FEP BCC identifier

Aim

- Realistic The three cases considered to have an adequate level of conservatism for the considered scenario. See also discussion in Table 2-5 to Table 2-8, and the text in Figure 2-3.

Sensitivity cases (results presented in section 8.1)


Evo-stage1, Evo-stage2, Evo-stage3, Evo-stage4

Evaluating the impact of evolving conditions in the surface environment at the time when the geosphere release first reaches the biosphere.

Release paths in the geosphere

See Figure 2-3 and Table 5-1

Evaluating the impact of uncertainties in the distribution of release locations into the biosphere (caused by uncertainties in the initial location of the released radionuclides in the repository and in the release paths to the biosphere).

Timing of geosphere releases

Timing Evaluating the impact of uncertainty in the time at which the geosphere release enter the surface environment.

Habits (humans) NoIrr

Evaluating the impact of uncertainties in the way in which crops are irrigated.

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Figure 2-3. The biosphere calculation cases considered in the present assessment (c.f. Table 2-10). The four numbered assumptions in the top line represent the realistic BCCs, the downward arrows represent alternative assumptions leading to sensitivity BCCs, each having the rest of the assumptions as in the realistic BCCs.

Developing surface

environments

Release paths in the

geosphere

Timing of geosphere

release

Evo-stage1 Forest_focused-A

Forest_focused-B

Forest_focused-C

Forest_dispersed-A

Forest_dispersed-B

Forest_dispersed-C

Cropland_focused-A

Cropland_focused-B

Cropland_focused-C

Cropland_dispersed-A

Cropland_dispersed-B

Cropland_dispersed-C

Timing

1 2 3

Sensitivity BCCs

Habits (humans)

Realistic BCCs

NoIrr

4

4 Reasonable cautious habits

3 Representative timing of releases from the geosphere

2 Realistic release patterns for repository panels A, B and C

1 Most likely path of evolution

Evo-stage2

Evo-stage3

Evo-stage4

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2.2 The graded approach When conducting the biosphere assessment, two important goals are to ensure that

• the assessment is based on an appropriate level of understanding of the biosphere and its potential behaviour, and that

• the level of detail of the assessment is appropriate to the magnitude of the potential radiological consequences.

In the previous biosphere analysis (Broed et al. 2007) performed in the KBS-3H safety assessment (Smith et al. 2007a), the landscape modelling approach was applied directly to the release rates from the geosphere, thus including a large number of radionuclides. This was done even though it is well known that both the radioactivity and radiotoxicity fluxes span several orders of magnitude, and it is a small number of radionuclides that dominate the possible radiological effects on both humans and other biota. Furthermore, the landscape model is a complex system including many uncertain processes and parameters. In particular, the data gaps are often large for many of the radionuclides that are expected to have a very low impact on potential radiological consequences. Consequently, applying the landscape modelling approach alone does not fulfil the above-mentioned goals.

In the present biosphere assessment, a three-tiered graded approach is implemented to achieve the goals. The common denominator in tiered approaches is that the complexity and realism are greater for higher tiers compared with lower tiers. In the present approach, Tier 1 and Tier 2 are generic radionuclide screening evaluations, requiring a minimum of site-specific data. Tier 3, which uses the landscape model, is the most realistic. The models used for the screening evaluation are described in section 5.1.2, and the landscape model is addressed in sections 5.1.1 and 7.2.

The approach is to use the results from Tiers 1 and 2 to identify radionuclides that are highly confidently expected to have insignificant radiological consequences, and do not need to be considered in Tier 3. This allows the computationally demanding landscape model used in Tier 3 to focus on key radionuclides. The approach thus avoids the need to obtain Tier 3 data, and evaluate uncertainties in these data, for radionuclides to which the overall assessment results are not sensitive. It also facilitates and strengthens confidence in the biosphere assessment and strengthens the demonstration of compliance with regulatory criteria, especially by increasing the transparency of the biosphere assessment. Furthermore, it provides an instrument for analysing model uncertainties, and providing guidance for the development of the landscape model, and the associated environmental monitoring programme. This approach will be evaluated, and possibly revised, in order to reach maturity by 2012.

2.3 Multiple lines of reasoning The end results from the main assessment process described above are dose quantities directly used in the quantitative compliance assessment (sections 6.1 and 6.2). The conclusions made regarding compliance, based on these dose quantities, are further supported by using other lines of reasoning, here implemented by using a range of safety indicators. Safety indicators are used to support the safety case, by building understanding of, and confidence in, the outcome and conclusions of the safety

36

assessment. In the biosphere assessment, they include both doses derived from robust, stylised scenarios, and other quantities (such as activity concentrations in environmental media) illustrating the behaviour of the biosphere, either as a whole or in relation to individual system components. Here, a distinction is made between safety indicators and complementary safety indicators, where the former includes quantities comparable to regulatory constraints, and the latter all other quantities derived for confidence building. This approach is similar to that of the PAMINA project (Becker et al. 2009) regarding safety indicators and performance indicators. The important difference in the present assessment, compared with the general PAMINA concept, is that in Posiva’s terminology the doses used in the compliance assessment are, naturally, indicators of safety, but they are not classified as safety indicators. The term “safety indicator” is used for indicators that support the decision on compliance based on Tier 3 of the graded approach. The reason is to make a clear distinction between the quantities used in the quantitative compliance assessment and the quantities (Posiva’s safety indicators) used to support the conclusions regarding compliance, even though they all are expressed in the same dosimetric quantities.

In the present assessment two safety indicators, in the form of annual doses, are derived, based on indicative stylised well scenarios: one for a drinking water well and one for an agricultural well. The drinking water well is similar to the well scenario applied in previous safety assessments (Vieno 1994, 1997, Vieno & Nordman 1996, 1999, Broed et al. 2007, Nykyri et al. 2008). The definition of the agricultural well has been extended to also include watering cattle and irrigation of crops, and has earlier only been used in the KBS-3H safety analysis (Broed et al. 2007). These safety indicators are further discussed in section 5.4.

The two most important complementary safety indicators are the calculated activity concentrations in environmental media and the release rates from the geosphere expressed in number of atoms. Derived activity concentrations in environmental media are presented in Hjerpe & Broed (2010); these form the basis for the dose calculations. However, the activity concentrations themselves are useful when comparing with e.g. natural levels of radioactivity or the level of contamination in areas affected by accidents involving radioactive materials. The purpose of expressing release rates from the geosphere in terms of numbers of atoms (see section 8.3) is to put the radionuclide releases into a more classical physics perspective, avoiding the complex concept of annual effective dose, and illustrating the large differences in the release rates of different radionuclides from the geosphere.

2.4 Selection of radionuclide sets considered A novelty in the Posiva approach for the biosphere assessment is the implementation of a graded approach, aimed at reducing the number of radionuclides needed to be considered in Tier 3 (landscape modelling) of the graded approach described in section 2.2. The approach to selecting sets of nuclides to consider in the different modelling stages in the present assessment can be summarised as follows:

1. A full set of radionuclides is established, containing all radionuclides included in the calculated releases from the geosphere to the biosphere in the repository assessment for a KBS-3V repository (Nykyri et al. 2008), and KBS-3H

37

assessment13

2. A subset of the full set of radionuclides is derived as the key set of radionuclides. The key radionuclides are selected based on a screening evaluation of a preliminary set of repository assessment cases (see section

(Smith et al. 2007b). The full set of radionuclides is presented in Table 2-1 of Hjerpe & Broed (2010) and is used in the screening evaluation.

7.3.1). The key set of radionuclides comprises the only radionuclides expected to be relevant for long-term safety (either themselves or their progeny radionuclides) and is used in the landscape modelling and when deriving safety indicators and focusing the research. The set is presented in Table 2-11, where it is further divided into:

• top priority nuclides – either they or their progeny radionuclides are expected to dominate the dose in most biosphere calculation cases, especially the most realistic cases, and

• high priority nuclides – either they or their progeny radionuclides are expected to give a significant contribution to the doses in some biosphere calculation cases, or even dominate in one or more sensitivity biosphere calculation cases. These are, in turn, further divided into three priority groups; these groups are mainly used to prioritise the site investigation and research resources in respect of radionuclides most relevant to long-term safety.

All actinides and all radionuclides in the naturally occurring decay chains are excluded from the key set of radionuclides (Table 2-11) since the applied screening evaluation is only valid for the time window where the dose constraints are assumed to apply and for the analysed repository assessment scenario with a single defective canister. However, this does not mean that it is only these 11 radionuclides, and their progeny radionuclides, that are important for long-term safety. A similar screening evaluation carried out beyond the dose assessment time window, or for different scenarios, such as human intrusion, would most likely return another set of radionuclides; in this case, Ra-226 and Pa-231 would certainly be regarded as key radionuclides (see for example the rock shear cases in Nykyri et al. 2008).

Nominal release rate In the present assessment Nominal Release Rates (NRRs) are considered in addition to the modelled geosphere release rates. The NRR are assumed to be constant geosphere release rates for the key set of radionuclides. The NRRs are not estimates of the expected magnitude of the geosphere releases. Rather, they aim to capture a fairly realistic relationship between the geosphere release rate maxima for the key radionuclides in order to put the results in the context of well known differences in the magnitude of releases of different radionuclides. The selected NRRs are presented in Table 2-12, and are based on the modelled geosphere release rate maxima in a set of repository assessment cases from RNT-2008 (see Table 7-2). The NRR is used in the present report when deriving and comparing doses, such as doses from the stylised well scenarios, ecosystem-specific doses and doses from the full landscape. The purpose is to

13 The main scope for the present assessment concerns the recent KBS-3V RNT-2008 analysis; however, selected geosphere releases from the KBS-3H assessments and previous KBS-3V assessments are included for comparison.

38

improve the focus on implications for long-term safety when comparing safety-related quantities such as radiation doses. It is considered a more informative approach than using unit release rates for all radionuclides and deriving (scenario-, ecosystem- or landscape-specific) dose conversion factors.

Table 2-11. Key set of radionuclides included in the present biosphere assessment.

Key set of radionuclides

Comment

Top priority C-14 Cl-36 I-129

The nuclides not screened out in the “most realistic” repository calculation cases.

High priority (I) Mo-93(a) Nb-94

Cs-135

The additional nuclides not screened out in the sensitivity repository calculation cases, see also section 7.3.1. High priority (II) Ni-59

Se-79 Sr-90(a)

High priority (III) Pd-107 Sn-126(a)

(a) Radionuclides that decay to nuclides which are themselves radioactive. The activity build-ups of

the progeny are taken into account in the dose calculations, assuming secular and environmental equilibrium with the parent radionuclides.

Table 2-12. Nominal Release Rates (NRR) applied in the present assessment.

Radionuclide NRR [Bq/y]

C-14 100 Cl-36, I-129 10 Ni-59, Se-79, Cs-135 1 Sr-90, Mo-93, Nb-94, Pd-107, Sn-126 0.01

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3 SURFACE ENVIRONMENT

Figure 3-1. Detailed illustration of the biosphere description sub- process, focusing on the modelling. The first major component in the iterative BSA process is the biosphere description process, which describes the present properties and on-going processes at the site and provides the safety assessment with key data. An illustration of the modelling in the biosphere description process is presented in Figure 3-1. A brief summary is included in the present report. The full documentation can be found in the biosphere description report (Haapanen et al. 2009), in its supplement describing the full set of site/regional data (Ikonen et al. 2010a) and in underlying supporting reports.

3.1 Present surface environment Global and regional setting Olkiluoto is an island approximately 12 km² in size, located in Southwestern Finland, by the Bothnian Sea. Finland is located on a stable and old bedrock area (Fennoscandian Shield) and its relief is mainly determined by the bedrock. The bedrock of Southwestern Finland comprises Precambrian gneisses and migmatites of mostly supracrustal origin. These high-grade metamorphic rocks are crosscut and overlain by slightly younger Rapakivi granites, Jotnian sandstones and post-Jotnian diabases. The sediments, in turn, have mainly been formed during the Quaternary period, when continental ice sheets repeatedly covered northern Europe. In Southwestern Finland, the glacial till is sandy. Clay soil types form about one-third of the soils. Rock outcrops are also typical of the coastal landscape. The Baltic Sea and its gulfs occupy a depression in the Fennoscandian Shield. Thus, the bedrock and the landforms are very similar on both the sea bottom and the adjacent land. As a result of post-glacial land uplift, new areas emerge from the sea throughout coastal Finland due to a sea-level decrease rate of about 3–10 mm/y (in Olkiluoto 6–6.8 mm/y).

Regarding biomes, Finland belongs mainly to the boreal coniferous forest zone with cool-temperate, moist climate, short growing season and wintertime snow cover. In Southwestern Finland, annual mean temperatures range from 4 to over 6 oC and mean precipitation from 410 to 670 mm/y. Due to the climate, soil types and the low population pressure, the landscape is dominated by forests and mires. Southwestern Finland belongs also to the raised bog zone. Most of the mires initially formed on land


analysis



Terrain & ecosystem

development



Safety indicators

Outcome

BIOSPHEREASSESSMENT

CLIMATIC ENVELOPE






TESMAnalysis Transport

matrices(processes)

Analogue data

LiteratureSite data Ecosystem

models(mass balances)

Site/regional data for further

modelling

40

uplift shores (primary mire formation) and are in various stages of development into ombrotrophic conditions (in which all water and nutrients are received from precipitation).

After the last glaciation, the first inhabitants came to the current Finnish territory approximately 10 000 years ago. Southwestern Finland was occupied somewhat later. The population density has always been rather low and urbanisation started later than in Western Europe. However, due to silviculture, very little of Finland remains in a natural state.

Terrestrial ecosystems Generally, the terrestrial areas of Olkiluoto do not differ from other coastal locations in Southwestern Finland. Primary succession ends typically in grove-like or fresh Norway spruce forests. Other major climax types are dryish Scots pine forests, rock forests and ombrotrophic raised bogs.

The most common soil type on Olkiluoto Island is fine-textured and sandy till. Soils are on average acid, except for the alder stands growing near seashores on clayish soils. The base cation concentrations in the surface soils are high, but they are expected to decrease in the future due to surface soil weathering, leaching and removal of nutrients (podzolisation). Generally, there is quite a large variation in elemental concentrations in soils in Olkiluoto.

The forests in Olkiluoto are growing on slightly more fertile sites than are typical in Southwestern Finland. There is a greater amount of Norway spruce and deciduous species in Olkiluoto, mainly due to the higher fertility of the soils and the high proportion of coastline. Black alder typically forms a belt behind the treeless shore vegetation zones. Pine is more common in the younger age classes. There is a large, relatively untreated area of mature spruce forest (a conservation area, belonging also to the Natura 2000 network). However, the forests of Olkiluoto are on average younger than in Southwestern Finland as a whole, which is reflected in lower mean volume and higher growth rate of tree stands. The relative area of mires and the proportion of undrained mires in Olkiluoto are less than those found on average in Southwestern Finland. The peat layers are shallow, the hydrological conditions of drained mires are still changing, the mires are small, and the range of mire types is wide. Given the scarcity of current larger mire areas on Olkiluoto, mires of similar characteristics to the ones expected to evolve in future were searched for in the regional area, and three of them (Figure 1-3) were selected to be described in more detail based on a review of literature.

The field-layer vegetation of the conifer tree stands is generally dominated by bilberry and lingonberry. However, Scots pine-dominated forests on rock surfaces support drought-tolerant species adapted to nutrient-poor and sunny conditions, such as dwarf-shrubs with wax-covered leaves or lichens. Thus their field-layer differs clearly from other conifer tree stands. Deciduous forests are commonly characterised by tall grasses. The field layer of deciduous forests dominated by black alder consists of moisture and nutrient-demanding ferns and vascular species.

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Regarding land-based birds, Olkiluoto Island is a typical representative of South Finnish forested coastal areas; even though the number of species is high, the area is not important for the occurrence of rare species. During the last decade, species common in human-altered habitats have increased, whereas species typical of Norway spruce forests and deciduous swamps have slightly declined. The mammalian fauna on the island is very typical of coastal areas in Southwestern Finland. Olkiluoto is generally not very favourable for most amphibians and reptiles. Invertebrates captured on Olkiluoto represent rather common species in Southern Finland.

Littoral ecosystems Seashores around Olkiluoto show a great variation in environmental conditions due to their location between an almost open sea and the extremely sheltered river mouth area of Lapinjoki. Deep hard and soft sand bottoms, as well as shallow bottoms with mostly soft clay, mud and silt are found. Furthermore, land-uplift-driven and eutrophication-accelerated succession is ongoing. The aquatic flora in the Olkiluoto offshore ranges from algae-dominated hard bottom communities in the outer archipelago to vascular-plant-dominated soft-bottom communities in sheltered locations. Effects of eutrophication can be observed, especially in the area affected by the power plant cooling waters. The most distinctive littoral species, common reed, forms an almost continuous belt around the island in the upper hydrolittoral, being at its widest in the most sheltered locations. Low meadows are often, but not always, found between the reed zone and the black alder or sea buckthorn belt higher on the shore. The great variety of habitats near the shoreline, from aquatic conditions to mires or climax stage forests, also maintains a great variety of fauna species, waterfowl being the most distinctive group. For waterfowl, the most important area of Olkiluoto Island is the northern shoreline. During the last decade, populations of species typical of inner archipelago and more eutrophic waters have increased, while those of species typical of the outer archipelago have decreased.

There are two regionally major rivers, Eurajoki and Lapinjoki, which drain into the Bothnian Sea near Olkiluoto. These rivers flow through the intensively cultivated, flat field area. Clay, sand, silt and partly peaty soils are common in the catchments, making the riverbanks easily erodable. The flora and fauna of the littoral zones of the rivers Eurajoki and Lapinjoki have not been inventoried.

The lakes selected from the regional Reference area as representative of the future lakes on the site (see below), have shores that are till-dominated or sandy, but open cliffs and soft or paludified14 shores exist, as well. Due to shallowness of the lakes, the littoral zones are wide in proportion to the lake sizes. Wide helophyte15 zones exist, followed by nympheids16

14 Paludifiction; wetland expansion resulting from the gradual rising of the water table as accumulation of peat impedes water drainage.

, except on stony and hard shores. Sedge meadows or reed areas are typical of the lakes.

15 Biennial or herbaceous plants of which only the buds survive a harsh period, such as winter. 16 Floating-leaved plants.

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Limnic (freshwater) ecosystems The differences in soil type in the watersheds of the rivers Eurajoki and Lapinjoki are reflected in the water quality characteristics. The catchment of the larger river, Eurajoki, includes the largest lake in Southwestern Finland (Lake Säkylän Pyhäjärvi). The river is a medium-sized to large clay-region river, regulated by dams. About half of the nutrients in the river water originate from agriculture. Due to the compensating influence of the large lake basin, seasonal variations in upper course water quality are relatively minimal and the nutrient concentrations are at the same levels as in moderately eutrophic lakes. Toward the lower course, concentrations of nutrients and suspended solids as well as turbidity and electric conductivity are much higher and the water has on occasions been extremely acidic due to aluminium washed from the soil. In the lower reaches, the water quality shows seasonal variations in addition to considerable yearly variations. The amount of nutrient load varies depending on the discharge and weather conditions, especially precipitation. Fish species composition varies from place to place.

The River Lapinjoki is classified as a nationally medium-sized river running through mineral soil lands. The river is regulated by a dam. Furthermore, in dry seasons water can be drawn from the River Eurajoki to the River Lapinjoki. The water is brown and rich in humus and contains high levels of iron and organic matter. As a consequence of acid sulphate soils and peatlands in the catchment area, the pH of the water may occasionally be low. Nutrient transport in the River Lapinjoki is mainly caused by diffuse-source loading. In the middle part of the river, concentrations are comparable with those of slightly eutrophicated lakes. In the lower part of the river, concentrations are typical of slightly eutrophicated or eutrophicated lakes.

Descriptions of small water bodies, such as springs and brooks, are based on literature and regional data. The majority of the nearby spring water concentrations measured in the region have been found to correspond to the shallow groundwater tube and borehole monitoring data from Olkiluoto. Given the scarcity of current limnic (freshwater) systems at Olkiluoto, lakes of similar characteristics to the ones expected to evolve in future were searched for in the regional area (Figure 1-3). Four lake systems, representing expected future types at the Olkiluoto site, were chosen to be described based on literature:

• A system of two shallow, humic and mesotrophic lakes with slow water exchange.

• A system of three shallow, eutrophicated short-delay lakes with strong floods and humus-rich water.

• A small lake, which floods easily. Signs of eutrophication, mesotrophy and oligotrophy have been observed.

• A mesotrophic lake, having a small catchment area. Indications of eutrophy have also been observed. The fish community is more variable than in the other lakes.

Sea ecosystems around Olkiluoto The sea around Olkiluoto Island is shallow, except for a few areas where water depth reaches about 15 m. The Rauma Archipelago lies to the south, but to the west and north

43

the island is exposed and the wind strongly affects currents in the area. The sea bottom varies considerably, consisting of Precambrian rock and Jotnian sandstone, till, glacio-aquatic mixed sediment, glacial clay, Ancylus17

The two regionally large rivers described above discharge to the sea north and east of Olkiluoto, increasing the concentrations of nutrients and solids, especially at the river mouths. The cooling water intake and discharge by the nuclear power plant locally significantly affects the temperature and the currents. The effect of cooling water can be seen most clearly in winter, when an unfrozen water area of a few square kilometres in size forms. Other factors affecting the water quality and biological production in the Olkiluoto area are the general state of the coastal waters of the Bothnian Sea and the local wastewater load.

sulphate clay, Litorina clay/mud, sand and gravel, washed sand layers, recent mud and gaseous sediments (sediments with a high content of gas, likely organic in origin).

The oxygen levels are mainly good near the sea bottom. The nutrient concentrations in sea water around Olkiluoto are typical of the coastal waters of the Bothnian Sea and local variations in the nitrogen and phosphorus concentrations are relatively minor. Growing conditions (eutrophication, short and mild winters) affect the phytoplankton biomasses. The aquatic macrophytes range from algae-dominated hard bottom communities in the outer archipelago to vascular plant-dominated soft-bottom communities in sheltered locations. The number of aquatic plant species found has been 24 to 27. Due to eutrophication, the proportions of different species have changed. The annual variation in the bottom fauna biomasses is considerable, which shows the instability of the communities. However, some indicator species for polluted bottoms have clearly decreased during the last few years. The most common fish species are perch and roach.

Agriculture Due to the minor importance of agriculture on the present-day Olkiluoto Island, agriculture has been described at the level of the Eurajoki municipality, Southern Satakunta or the whole of Satakunta, depending on the availability of statistics and the aspect in question. The average farm size in Satakunta is slightly over 30 ha. The main production system of farms is similar in Eurajoki and in Southern Satakunta: cereals are produced on 75% of the cultivated area, barley and oats being the main species. Special plant cultivation includes production of malt barley, pea, potatoes, sugar beet and oil plants (turnip rape, rape, sunflower), and is the second largest sector at about 20% of the cultivated area. Milk production is generally important in the whole of Satakunta, but not in Eurajoki municipality.

Agricultural soils have usually been established on sediment soils that are fine in texture, free from stones and contain plenty of nutrients. Thus, fields are often located along the rivers. The soil thickness must be over half a metre to secure proper root growth and water availability for plants. In Southern Satakunta, almost half of the fields 17 As the Scandinavian ice sheet retreated from Central Sweden about 8 300 B.C. (10 300 years BP, the Danish Straits opened from the Baltic Sea basin to the ocean. Due to the isostatic land uplift, the straits closed up about 7 500 B.C. (9 500 BP) and the sea stage became the freshwater Ancylus Lake. The Ancylus Lake became the Litorina Sea about 5 500 B.C. (7 500 years BP) when the eustatically rising ocean levels broke through the Danish Straits.

44

are sandy and the proportion of clay soils is small. Agricultural soils have high nutrient contents derived from original minerals and organic matter, but also in some places from the annual applications of fertilisers and manure. About 20% of the fields are on organic soils. Since grass and cereals for feed production can be grown basically on all soils, animal production tends to use less fertile fields than special crops and horticulture. The majority of the fields have been subsurface drained.

Other land use Fields in the area around Olkiluoto are mainly concentrated on clayey soils in the valleys of the rivers Eurajoki and Lapinjoki. Settlement is located on hills, on the margins of open areas or by riversides. Eastern parts of the municipality of Eurajoki have a field-dominated landscape, whereas the coastal section is dominated by rock areas and forests, with fewer and scattered fields. A relatively small percentage of the area is built on. The nuclear power plant and related activities on Olkiluoto Island are by far the most significant industrial activities in the area.

Permanent settlement in Eurajoki originates from the turn of the 13th and 14th centuries. In the town of Rauma, about 10 km south of Olkiluoto, the first permanent settlement dates from the 11th century or earlier. The settlement acquired its general shape early. The riversides, river mouths and the shores of big inland lakes accessible from the sea were popular. Coastal areas were attractive as well, but not unsheltered shores. The focus of the population has, however, changed throughout the centuries and some distinct contiguous centres have formed on the lower and central reaches of the River Eurajoki.

Figure 3-2. Permanent population density around Olkiluoto Island (red square) according to the grid database of Statistics Finland (2006). Background map: topographic database by the National Land Survey of Finland. Map layout by Jani Helin/Posiva Oy.

45

In the late 1960s, new densely built areas with terrace houses and a few apartment buildings emerged in the centres of Eurajoki and Lapijoki. The old villages have regressed and the majority of inhabitants now live in the more densely populated centres (Figure 3-2), partly due to the building of a straighter national main road. Due to the proximity of the coast and the city of Rauma, the area has historically been more densely populated than the country on average. From the 1960s to the present day, the size of the population of Eurajoki municipality has varied between 5 200 and 6 100 and the average population density is 16.8 persons/km2. One significant feature in the settlement pattern at the coasts and islands is the growing number of summer cottages.

3.2 Long-term transport and accumulation processes The processes affecting transport and accumulation of matter in ecosystems, specifically carbon, in the long-term have been identified and quantified using mainly site data as far as possible. The ecosystems considered are terrestrial and aquatic, a combination of both, and a continuous shoreline system. The overall ecosystem structure and long-term transport processes related to the transport of matter, specifically the key radionuclides (section 2.4), are presented as transport matrices in Figure 3-3 to Figure 3-5 and the processes briefly explained, below. The processes in the matrices have been quantified with site and site-relevant data as far as possible for each sub-type of ecosystem (sub-types are shown along the top-left to bottom-right diagonals of the matrices). The use of matrices to analyse interactions among components of the system has been recommended by IAEA (2003); this approach contributes to transparency and traceability of decisions on FEPs. Figure 3-3 presents the overall transport matrix of terrestrial ecosystems, applicable to forests, mires and agriculture. As the sub-types of terrestrial systems vary by nature, some of the components and processes are not present or significant in all of the terrestrial ecosystems. Some of the less significant processes (listed in parentheses) might be of importance in some specific cases (e.g., for some specific radionuclides). The terrestrial system is connected to the external systems of Atmosphere, Shoreline and Bedrock by a number of processes. The connection to the Bedrock is of highest importance: it is the main route of possible contamination arriving with the groundwater from the deep repository. Atmosphere includes, in this context, both the region below the plant canopy and the region above it, as far as this is relevant in the different applications. The Shoreline system connects the terrestrial system to aquatic systems. The main component in the terrestrial matrix is the Soil, the unconsolidated mineral and organic material that provides water, nutrients, support and habitat to the flora and fauna. The Plants provide the primary production in the system. By senescence18

18 Biological changes taking place in organisms as they age; for plants this refers here to litterfall (especially trees) but also fall of branches and other parts of plant (especially in case of understorey).

and death, the plants form the Litter layer, into which freshly dead plant material and pollen and seeds have also been included. Animals in the matrix denote the wild fauna other than detrivores, living both on Soil and burrowing within it. Birds and other avian fauna are also included as they affect the mass fluxes in the terrestrial system. Livestock kept by Man is represented separately due to the different habitats and food sources. The compartment ‘Man’ includes not only the human as an organism, but also anthropogenic storage. Together with Livestock, Man forms a terrestrial sub-system, represented in the other ecosystems only by activities of Man.

46

Figure 3-3. Overall transport matrix in terrestrial ecosystems. Cells outside the boxes with green outlines are part of the systems external to the terrestrial ecosystems.

In Figure 3-4, the overall transport matrix for aquatic ecosystems is presented. The external components (Atmosphere, Shoreline system, Bedrock and Man) are defined similarly to the terrestrial matrix. The most significant processes giving rise to mass fluxes in water ecosystems are connected with the food web. The basic idea is that energy and nutrients flow from primary producers to species higher up in the food chains. The most important nutrients are carbon, phosphorus and nitrogen. The mass balances and fluxes in lakes are based on a food web similar to that of the coastal areas. River ecosystems are characterised by the flowing water. The rivers receive nutrients and other substances through leaching and often in waste effluents. The rapid changes in flow rates cause erosion and increase nutrient transfer from sediment to water.

Atmo- sphere

See Shoreline system matrix

Rainfall CO2 uptake

Deposition Rainfall

Gas exchange

Deposition Rainfall

Gas exchange(Inhalation) (Migration)

(Inhalation)(Deposition)

(Rainfall) (Inhalation) (Rainfall) (Inhalation)


Shoreline system

Irrigation (Sea spray)

Irrigation (Litterfall)

(Sea spray)

Terrestriali-sation

Irrigation (Sea spray)

(Migration) See Shoreline system matrix

See Shoreline system matrix (Drinking)

(Transpiration) (Respiration) (Litterfall) Plants Litterfall

Throughfall Root

exudation & channelling

Food source Food sourceFood source

(Other harvesting)

Food source

(Resusp.) (Gas

exchange)Litter

Bioturbation Mineralisation

Leaching (Degradation)

Intake (Inhalation) (Ingestion)

Resuspension Gas exchange Runoff Uptake Bioturbation Soil (see its

own matrix)Intake

(Inhalation)Ingestion

(Adhesion) (Infiltration)(Drinking) (Ingestion)

(Material use)

(Drinking) Ingestion

(Exhalation) Excretion Excretion Decom-posers Food source Food source (Food source)

(Migration) (Exhalation) (Migration) Excretion Excretion Food source Animals Food source

See Shoreline system matrix (Irrigation) (Irrigation)

GW discharge (Gas

discharge) (Irrigation)

Bedrock (Drinking) (Drinking)

(Exhalation) See Shoreline system matrix

Crop protection (Planting)

Soil preparation, Fertilisation

Man Feed

(Exhalation) Manure Manure (Use of wastes)

(Use of wastes) Food source Livestock

47

*) also processes Suspended and dissolved matter flow, and Mineralisation included in this cell. The sediment sub-matrix refers to the same as the soil sub-matrix in the terrestrial systems.

Figure 3-4. Overall transport matrix in aquatic ecosystems. Cells outside the box with blue outline are part of the systems external to the aquatic ecosystems. The Shoreline system matrix ties together the Terrestrial and Aquatic system matrices into a continuous system that can also be applied to represent the key connections at the level of landscape. The Shoreline system (Figure 3-5) includes the same processes and components as the other systems, but in a simplified form. The transport processes in the Shoreline system result from the interaction of wind, waves and currents with the water column, sediments, and biota. The Shoreline system is an area of high primary production because of its shallowness and because of nutrient input from local onshore catchments. Large parts of the Shoreline are covered by macrophytes. The water body is so shallow that the light reaches the bottom and enables the growth of vascular plants and attached macroalgae. The species composition is dependent on the bottom type. The phytal area19

is significant as a breeding and nursery ground for many pelagic fish (e.g. Baltic herring) and invertebrates.

19 The part of a lake, river or sea with water shallow enough to permit the growth of rooted plants.

Atmo- sphere


Deposition Rainfall CO2 uptake (Inhalation)

(Migration)(Deposition)

(Rainfall) (Inhalation)


Shoreline system

Water exch. Susp. and

diss. matter flow

R ff

Flotation (Migration) (Migration) (Migration) Runoff See Shoreline system matrix


(Gas exchange) (Sea spray)

Water exchange Susp. and

diss. matter fl

Water Uptake Intake (Inhalation)

(Intake) (Inhalation)

Intake (Inhalation)

Drinking (Intake)

Sedimentation Water

exchange ....more *)

(Infiltration)

Drinking Water usage (Ingestion) (Dredging)

(Respiration) Flotation (Degradation) Primary producers Food source Food source Food source Food source

Root exudation

Root channelling

(Food source)

(Migration) Excretion (Respiration)

Other fauna Food source Food source Food source Bioturbation (Food source)

Excretion (Left-overs)

(Respiration)(Food source) Detrivores

(benthic only) Food source Food source Bioturbation

(Migration) Excretion (Respiration) (Food source) Food source Fish Food source Bioturbation Food source

(Migration) (Exhalation) (Migration) Excretion (Food source) Mammals

and birds (Bioturbation) (Food source)

Water exch. Susp. and

diss. matter flow

T i li

Resuspension Bioturbation

(Gas exchange)

Uptake (Intake) (Adhesion)

(Adhesion) (Intake)

(Adhesion) (Intake)

Sediment (see its own

matrix)(Infiltration) (Dredging)

(Material use)


Groundwater discharge

(Gas discharge)


(Gas discharge)

Bedrock

(Exhalation) See Shoreline system matrix (Effluents) (Dumping) Man

48

*) also processes Suspended and dissolved matter flow, Root exudation, Root channelling/intrusion, and Mineralisation included to this cell.

Figure 3-5. Overall transport matrix for shoreline systems. Cells outside the box with purple outline are part of the systems external to the shoreline systems 3.3 Key data produced for further use in the biosphere assessment This section summarises the types of data where the biosphere description sub-process recommends values for further use in subsequent sub-processes (Haapanen et al. 2009). The summary is limited to key parameters and to the key nuclides with top priority (C-14, I-129 and Cl-36) for radionuclide-specific data. Site and region-specific data have been supplemented with values from site-relevant literature when needed, and considered sensible. Similar recommendations for use of site data for other parameters are presented in a background report (Ikonen et al. 2010a). The focus in the data description below is on values derived from site- and regional-specific data.

3.3.1 Data most relevant to terrain and ecosystem modelling The stratigraphical order is a major conceptual prerequisite for the overburden modelling. The interpreted standard stratification order presented in Posiva (2003) has been further developed, based on expert judgment and review of the relevant information.

Atmo- sphere

See Terrestrial

system matrix

(Inhalation) (Migration)

Deposition Rainfall

CO2 uptake

Deposition Rainfall

(Inhalation) (Migration)

Deposition Rainfall

CO2 uptake

Deposition Rainfall

(Deposition) (Rainfall)

See Aquatic system matrix

(Deposition) (Rainfall) (Inhalation)

See Terrestrial

system matrixTerrestrial (Migration) Runoff

(Litterfall) (Migration) Litterfall (Litterfall)See

Terrestrial system matrix

See Terrestrial

system matrix

(Exhalation) (Migration) (Migration) Fauna Bioturbation

Excretion(Migration)

(Food source) (Food source)

(Respiration) Food source Flora

Litterfall Decomp.

Root exudation

(Food source) (Food source)

Gas exchange Terrestriali-sation Food source Uptake Soil Runoff Runoff (Infiltration) (Ingestion)

(Dredging)

(Migration) (Exhalation) (Migration) (Food source)

(Migration) Fauna Excretion Bioturbation Excretion (Migration) Food source

(Respiration) (Food source) Food source FloraDecomp. Leaching/ detatch.

"Litterfall" Decomp.

Root exudation

Flotation (Food source)

(Gas exchange) (Sea spray)

(Sea spray) (Sea spray) (Drinking) (Sea spray) Flooding Food source

(Drinking) Uptake Water column

Sedimentation Water

exchange ....more *)

Water exchange

Drinking Water usage (Ingestion) (Dredging)

Terrestriali-sation Food source Uptake

Water exch. Resuspension Bioturbation

Sediment Runoff (Infiltration) (Dredging) (Material use)

See Aquatic system matrix (Migration) Flotation

Water exchange Susp. and

diss. matter f

Terres-trialisation Aquatic See Aquatic

matrixSee Aquatic

matrix

See Terrestrial

system matrix


(Gas discharge)


(Gas discharge)

See Aquatic matrix Bedrock

(Exhalation)See

Terrestrial system matrix

(Dumping) (Effluents) (Dumping) See Aquatic matrix Man

Geolittoral sub-matrix Hydrolittoral sub-matrix

49

The flow rates in future streams are modelled based on the present-day situation in the rivers Eurajoki and Lapinjoki and their catchments. Measured long-term precipitation (Ikonen 2002, 2005, 2007a, Haapanen 2008) and the annual discharge of the rivers are used to derive the value for the key parameter specific runoff (the amount of annual precipitation falling on the catchment that reaches the running water in the river). The precipitation measured at Olkiluoto is used for the entire large catchment of the rivers. The sediment balance (erosion and deposition of sediments) regulates the transport of radionuclides sorbed in solid matter. For modelling the source of suspended solids in the stream water, specific parameter values considered to be applicable to the Olkiluoto site are provided. Key parameters for the underwater erosion and sedimentation model are the wind statistics (speed and direction) and the critical shear stresses of sediment types that determine whether the material is eroded or whether the conditions are favourable for net sedimentation. Wind statistics are provided, calculated from Olkiluoto weather data (Ikonen 2002, 2005, 2007a, Haapanen 2008, 2009). Only single literature values applicable to the Olkiluoto site are available for the critical stresses. However, they are expected to be valid, since the description of the sediment type corresponds to the properties of surface sediments in offshore Olkiluoto observed in sediment cores in 2008 (Ilmarinen et al. 2009, and a report on offshore sediment cores pending the chemical analysis results).

Accumulation of organic material provides an important storage and, to some extent, a sink for organic-bound radionuclides. At Olkiluoto, accumulation has two main modes: accumulation during the aquatic phase, and peat formation. The recommended parameter values related to these processes are given in BSD-2009. The growth of vegetation is the main driver for radionuclides entering the biological cycle, and the vegetation biomass provides storage for radionuclides. In TESM, site classes for the vegetation are used, and their identification is mainly based on the soil type. The classes are given in BSD-2009 and have been derived by expert judgment. On the shorelines, the existence or lack of macrophyte vegetation (reed colonies) determines whether a gyttja20

3.3.2 Data most relevant to surface and near-surface hydrological modelling

layer accumulates or not. The reed colony model is based on assessing the fetch distance (degree of physical exposure) and assuming a maximum water depth and minimum flow rate for the vegetation to survive. Since the parameters are difficult to quantify in detail, the model is calibrated using data from a survey at the site (Haapanen & Lahdenperä 2009).

The most important temporally, and, to some extent, also spatially varying, data are meteorological data, such as precipitation, air temperature, radiation, relative humidity and, wind speed. These are collected and presented within the biosphere description sub-process.

The key vegetation parameters are those influencing interception and transpiration. Maximum stomatal conductance21

20 Fine-grained, nutrient-rich organic mud deposited in aquatic conditions.

(Karvonen 2009b), needed in the transpiration model, was calibrated using sap flow measurements from forest intensive monitoring

21 The speed at which water evaporates from pores in a plant.

50

plots (FIP) (Haapanen 2008, 2009). Rainfall and snowfall interception capacities were calibrated using the FIP data and other interception model parameters were taken from literature (Koivusalo & Kokkonen 2002).

Key hydraulic parameters in soils include saturated hydraulic conductivity and parameters of the soil water retention curve. Saturated hydraulic conductivity values were taken from the results of slug tests carried out on Olkiluoto Island (Tammisto et al. 2005) and complemented for the other soil types with literature data. Initial values for the soil water retention curve parameters were obtained from measured particle size distribution curves (Jauhiainen 2004) and calibration was used to find the final values used in the surface and near-surface hydrological model (Karvonen 2008, 2009a).

3.3.3 Data most relevant to radionuclide transport models The biosphere description provides data for direct use in the ecosystem-specific radionuclide transport models (section 5.3).

Key parameters provided by the BSD-2009 for the modelled elemental circulation in forests are the annual production, and average biomasses of wood, foliage and understorey, and concentration ratios (CR) from soil to understorey and foliage. However, not many site data are available as yet to derive CRs, and only values for iodine are provided.

For radionuclide transport in croplands, the irrigation rate (amount and frequency) and leaf area index (related to the capacity to capture contaminants from the irrigation water) are key parameters, for which average values for the most common crops in Finland are provided. The average leaf area index for the time of the irrigation event is estimated from the irrigation recommendations (Maatalouskeskusten liitto 1979), a review of current practise (Pajula & Triipponen 2003) and studies in which leaf area index development was documented (see Table 11-13 in Haapanen et al. 2009).

C-14 is modelled separately from the other radionuclides using a specific activity model (Avila & Pröhl 2007). Key parameters for which data are provided in the biosphere description sub-process are:

• Wind speed, which determines in the model, together with the mixing height, the mixing volume for the C-14 release from the soil to the air – the pathway for assimilation by plants in terrestrial systems.

• Net primary production.

• Sedimentation rate in lakes; sedimentation is a removal effect, mainly controlled by the sedimentation rate parameter. Sedimentation rates depend on winds, currents, upwelling and the productivity of system. In Lake Joutsijärvi, located in the Reference area, the sedimentation rate has been determined. The value for the most recent decade has been taken as the best estimate here, since the other values have been reported to be associated with changes in land use in the catchment area (Salonen et al. 2002).

51

3.3.4 Data most relevant to dose assessment models When deriving typical absorbed doses to other biota (section 6.2), the concentration ratios (Brown et al. 2009) and the sizes of the selected biota species or their surrogates form the essential data. The biosphere description (Haapanen et al. 2009) provides the selected assessment species for the Olkiluoto site (listed in section 6.2.2 of this report) together with their sizes. They are based on expert judgement, and partially on available data, and cover the significant trophic levels (roles) in the food webs of the ecosystems prevailing and expected at the site. The transfer factors are based on a literature review (Helin et al. 2010).

When deriving doses to humans (section 6.1), the annual food intake is presented in terms of demand for carbon. Key parameters when deriving food and radionuclide intakes are the production of foodstuffs and the radionuclide transport to them; the former is characterised by total productivity of edible components (edibles) in an ecosystem and the latter as the average aggregated concentration ratios22

Forests and wetlands

(CRagg) to the edibles. An aggregated concentration ratio is the ratio between the radionuclide concentration in the edibles (weighted by productivity) and the radionuclide concentration in the environmental media. Site-specific productivity estimates are given in BSD-2009 (Haapanen et al. 2009; details of derivation in Ikonen et al. 2010a), and details about aggregated concentration ratios in Helin et al. (2010).

The productivities of edibles from the forests are listed in Table 3-1, and the aggregated concentration ratios in Table 3-4. The productivity of edible fungi (mushrooms) was estimated based on Ohenoja (1978). Compared with recent values used by SKB (Löfgren 2008), the estimate of productivity for mushrooms seems rather high, i.e., pessimistic with respect to dose assessment. The productivity of game (moose and deer) at the Olkiluoto site has been evaluated on the basis of the average game bag in 2002–2007 (Ikonen et al. 2003, Oja & Oja 2006, Haapanen 2007, 2008) divided by the respective forest area (uniformly distributed game). The value for moose has been applied to deer.

The productivity of edibles in the mires (used in wetland objects) and aggregated concentration ratios are presented in Table 3-1 and Table 3-4, respectively. It should be noted that the game bag for the mires is based on data on the Olkiluoto site with very limited mire areas, and is likely an over-estimate.

Croplands The productivities of the crops considered in the assessment are presented in Table 3-2, and the aggregated concentration ratios in Table 3-4. The values are calculated according to the average yields in Satakunta in 2007 and 2008 (from www.matilda.fi). The table is limited to the crop type selected in the biosphere calculation base case (field vegetables).

22 CRagg is identical with the quantity aggregated transfer factor (TFagg) used in Haapanen et al (2009), which earlier has been used for example in Broed et al. (2007), Bergström et al. (2008).

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Aquatic ecosystems The productivities of edibles and aggregated concentration ratios for lakes, rivers and coastal areas are presented in Table 3-3 and Table 3-4, respectively. Different fish species are the only commonly used edibles from Finnish lakes, in addition to waterfowl. Crayfish are also captured from some lakes, but the overall amount is very small. The productivity of fish is based on a study of water quality, fishing efforts and fish yields in lakes (Table 2 in Ranta et al. 1992). There are few suitable data on hunting of birds from lakes or rivers. On the other hand, it is known that the catch almost solely consists of Anseriformes (e.g. ducks). Given the lack of data, the values derived for the coastal area were also used to represent lakes. Because of the lack of specific information on the rivers Eurajoki and Lapinjoki, data collected for lakes are currently used to also represent the future river systems.

The productivity of fish in the sea areas is based on the statistics for 2007 and 2008 for the Bothnian Sea from the Finnish Game and Fisheries Research Institute (www.rktl.fi). Losses from the ordinary cleaning of fish are taken into account. Given the lack of more specific quantified data, recreational fishing was taken into account by scaling with the species-specific value of the ratio between catch in commercial fishing and total catch (national average from; www.rktl.fi). The best estimate for waterfowl game in coastal areas was derived from the 2002–2007 game bag. The density was calculated by using the total area of waterfowl counting sectors (Yrjölä 1997, 2009). These data apply to the shore area, but not necessarily to the open sea. However, these are believed to result in overestimates of density and hence cautious dose estimates. Productivity of other edibles from the coastal areas is minor; for example, crustaceans and algae are not utilised in the Olkiluoto area.

Table 3-1. Productivity of edibles (kgC/m2/y) used in forest and wetland biosphere objects.

Rocky forest

Heath forest

Herb-rich heath forest

Wetland (mires)

Berries 2.5E-5 1.4E-4 1.6E-5 1.2E-4 Mushrooms 5.1E-4 5.1E-4 5.1E-4 2.6E-5 Moose and deer 4.1E-5 4.1E-5 4.1E-5 2.6E-5 Hare 7.7E-8 7.7E-8 7.7E-8 0 Birds 1.4E-8 1.4E-8 1.4E-8 1.4E-7

Table 3-2. Productivity of edibles (kgC/m2/y) in croplands; field vegetables is the crop type used as the base case in the assessment.

Crop type Productivity Grain (flour) 0.074 Potato 0.200 Pea 0.020 Sugar beet (15% sugar) 0.180 Field vegetables 0.148 Berries and fruit 0.020

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Table 3-3. Productivity of edibles in aquatic ecosystems (kgC/m2/y).

Lake River Coastal areas

Fish 5.3E-5 5.3E-5 8.5E-5 Waterfowl 1.4E-7 1.4E-7 1.4E-7

Table 3-4. Aggregated concentration ratios in terrestrial (Bq/kgC)/(Bq/kgdw,soil) and aquatic (Bq/kgC)/(Bq/m3) ecosystems. For croplands, the value is based on vegetable production only.

Forest Wetland Cropland Lake, river Coast Rocky Heath Herb-rich

heath Mire Vegetables

Cl 3.8E+1 3.6E+1 3.8E+1 3.2E+1 3.0E+1 6.7E-1 4.2E-4 I 4.4E+0 3.7E+0 4.4E+0 1.3E+0 5.5E-2 7.2E-1 5.4E-2 Mo 1.5E+0 2.3E+0 1.4E+0 4.9E+0 5.5E-1 1.7E-2 1.4E-2 Nb 1.4E+0 2.2E+0 1.3E+0 4.7E+0 1.0E-2 4.8E-1 3.9E-1 Cs 2.2E+2 1.8E+2 2.2E+2 4.3E+1 5.0E-2 3.7E+1 3.7E-1 Ni 1.6E+0 3.3E+0 1.4E+0 8.8E+0 1.0E-2 4.8E-1 3.9E-1 Se 1.4E+0 1.4E+0 1.4E+0 1.0E+0 1.7E+0 2.4E+1 5.4E+1 Sr 5.1E-1 1.2E+0 4.5E-1 3.7E+0 7.5E-1 2.2E+0 9.2E-2 Y 1.5E+0 2.3E+0 1.4E+0 4.9E+0 2.0E-3 4.8E-1 3.9E-1 Pd 1.6E+0 3.3E+0 1.4E+0 8.9E+0 1.0E-2 4.8E-1 3.9E-1 Sn 3.8E-2 3.6E-2 3.8E-2 3.0E-2 4.0E-2 1.3E+0 1.1E+0 Sb 3.8E-2 3.6E-2 3.8E-2 3.0E-2 2.4E-4 1.7E-1 1.3E-1

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4 FORECASTING

Figure 4-1. Detailed illustration of the TESM sub-process. The surface and near-surface hydrological model is linked to nearly all components of the sub-process. The assumed animal habitats are only preliminary in BSA-2009.

The second major sub-process in the iterative BSA process is the Terrain & ecosystems development, which predicts the development of the surface environments at the site given the climate scenarios envelope of possible conditions (as illustrated in Figure 4-1). This is documented in detail in the TESM-2009 report (Ikonen et al. 2010b), and in several underlying supporting reports. Below, a brief summary of the methodology for forecasting the surface environments during the biosphere assessment time window is presented. The surface and near-surface hydrological modelling, which is the main link between the deep groundwater flow modelling and the landscape model (see Figure 2-2), is first summarised (section 4.1). Secondly, the TESM methodology is described (section 4.2), and, finally, the key information provided to the next sub-processes is discussed (section 4.3).

4.1 Surface and near-surface hydrological modelling The radionuclide release and transport analysis RNT-2008 (Nykyri et al. 2008) considers the release of radionuclides from spent nuclear fuel and their subsequent transport to the interface between the bedrock and the overburden soils or sediments (termed the overburden-bedrock interface in the following). RNT-2008 results include around 39 000 computed flow paths that originate from different panels in the final repository area, and, for steady-state flow conditions, are predicted to exist 1 000 and 10 000 years in the future. These two flow fields calculated for these two times are sufficient for forecasting purposes because the difference in the upper boundary condition (groundwater pressure head) between the time points is very small; thus the resulting flow fields are nearly identical. The flow paths were simulated by particle tracking. The aim of the model described here was to compute the transport of radionuclides (in term of pathways) from the overburden-bedrock interface to surface waters or to the root zones in forest, agricultural or wetland areas. The end-points of the


analysis



Terrain & ecosystem

development



Safety indicators

Outcome

BIOSPHEREASSESSMENT

CLIMATIC ENVELOPE






LSM

/RN

T

BSD

Oth

er

la

nd u

se

Land

upl

ift

Aquatic ecosystems

Forest types Peat growth Croplands Erosion and sedimentationTerrestrial ecosystems

Surface and near-surface hydrological model

Ani

mal

ha

bita

tsStream network Lakes Reed beds Erosion & sedimentation

56

flow paths at the overburden-bedrock interface from the RNT-2008 groundwater flow modelling computations were used as the radionuclide release points in surface and near-surface hydrology modelling.

The water fluxes needed for determining the radionuclide pathways through the overburden were computed using the Olkiluoto surface and near-surface hydrological model (Karvonen 2008, 2009a-c). It is a 3-dimensional model that is used to study the water balance components at Olkiluoto. In the model, the overburden and the bedrock are combined into one single numerical solution and the overburden-bedrock interface can be seen as the layer where hydraulic properties change from soil values to bedrock values. The model links unsaturated and saturated soil water in the overburden and groundwater in bedrock into one continuous system, characterised by a pressure distribution. Horizontal and vertical water fluxes can be obtained as output values.

In the first step, steady-state recharge/discharge through the bedrock-overburden interface was computed for all grid points (pixels). In the second step, vertical and horizontal water fluxes were computed for a period of nine years (daily data) using precipitation, air temperature and potential evapotranspiration data for the present-day climate. Steady-state recharge/discharge through the bedrock-overburden interface, calculated in the first step, was used as the lower boundary condition of the model. Average seasonal fluxes were computed for all the pixels. The radionuclide pathways were calculated for a period of 2 000 years ahead starting from final points of the RNT-2008 computations and repeatedly using the seasonal average fluxes for each successive year (2 000 times corresponding to the 2 000 years).

The surface and near-surface hydrology model used raster files created in the TESM (section 4.2) as model input data. The computational grid was created automatically from the input rasters to produce soil surface elevation, thickness of overburden layers, bedrock elevation and soil type of the overburden layers. The boundary conditions needed in the model came also from the TESM: location of coastal areas, lakes and stream network. Soil water retention curve parameters were defined separately for overburden soils and for bedrock (Karvonen 2009a); each soil type was treated as isotropic and homogenous.

The results of the computations include the locations of the end-points of the flow paths, which may be watercourses (sea, lake, and river) or the root zones, and the time it takes for an unretarded solute to be transported to these locations (Karvonen 2009c).

4.2 Terrain and ecosystems development model The terrain and ecosystem development model report (TESM-2009; Ikonen et al. 2010b) provides an up-to-date, scientific synthesis of the expected evolution of the surface environments for the time period when the dose-based constraints apply. The TESM-2009 is an update of TESM-2006 (Ikonen 2007b), and will be further updated for the 2012 assessment. TESM is based on the latest available site-specific data and models, such as the terrain (topographical) model (Pohjola et al. 2009), and the land uplift model (Påsse 2001, revised by Vuorela et al. 2009).

Lakes, rivers and their catchment areas are identified using standard GIS processing tools. Terrestrial and aquatic erosion and sedimentation models have been recently

57

developed in this modelling environment but remain to be fully tested before their use in the biosphere assessment. For aquatic erosion and sedimentation, a fetch approach (physical exposure to wind-induced effects; e.g., Ekebom et al. 2003) is applied (Huttula 1994, Shore protection manual 2001, Seuna & Vehviläinen 1986), and for terrestrial erosion an application of a universal soil loss equation is used (Zaluski et al. 2004, www.iwr.msu.edu/rusle).

Accumulation of organic material is modelled for reed beds and wetlands. Peat growth is simulated with the model of Clymo (1984), based on productivity-driven accumulation constrained by the hydrology (summer droughts) and on decay in deeper layers. For lack of better data, deposition of gyttja in reed beds has been modelled as occurring at a constant rate. In addition to these modules, the thickness of the humus layer is predicted by the vegetation modules. In the simulation of the vegetation on upland soils, vegetation stand classes are formed based on the differences in fertility of different soil types (Haapanen et al. 2009).

Locations of croplands are identified based on the generic soil suitability for a given purpose and preferences in the region at present (Ikonen 2007b). In addition, the required thickness of the suitable soil type is taken into account. Another part of the Human settlement and land use module, the illustrative human settlement simulator, is based on correlations of various factors affecting house density around the Olkiluoto site (e.g. soil type and distances to the main road, nearest neighbour or a water body). The main road network is simulated by minimising the construction cost depending on the terrain type, using cost surface analysis. The cost surface is based on terrain slope classification and water body areas. In the present version of the model (see Ikonen et al. 2010b), the slope is assigned to one of five possible cost classes. The water body area (lakes, rivers, sea) is then superimposed on that using a constant cost value; building bridges becomes possible but costly, depending on the parameter values applied. Due to the unavoidably large uncertainties, the prediction of houses and roads is meant only for illustration and for carrying forward the present-day housing pattern to the future. Identification of the habitats of characteristic groups of animals is based on the identification of different ecosystems and their properties, and identifying preferred, suitable and unsuitable areas (Haapanen et al. 2009).

4.3 Key data produced for further use in the biosphere assessment The TESM provides key inputs to the surface and near-surface hydrology model: the terrain sub-model, overburden thickness, the surface ditch network, land use types, vegetation types and soil types.

The TESM model provides predicted conditions for the surface environment from year 2 020 to 12 520, in time steps of 500 years. This is the most important information for configuring the landscape model (section 5.1), since it determines the ecosystem types within each biosphere object and its geometrical properties.

The surface and near-surface hydrology model provides the landscape model with vertical water fluxes between the compartments within a biosphere object, at each time step and for each biosphere object. Furthermore, horizontal water fluxes between biosphere objects are provided, also at each time step.

59

5 RADIONUCLIDE TRANSPORT MODELLING

Figure 5-1. Detailed conceptual illustration of the radionuclide transport modelling sub-process (SNSH: surface and near-surface hydrological modelling).

This section presents an overview the radionuclide transport modelling part of the biosphere assessment, indicated by the red box in Figure 5-1. The main endpoint of this modelling is to produce time-dependent radionuclide-specific spatial activity distributions in all biosphere objects in the landscape model.

Firstly, the approach to the landscape model set-up is presented (section 5.1), based on the forecasts from terrain and ecosystems development modelling (TESM) and the connections between the modelled geosphere transport paths and the surface environment. Secondly, radionuclide transport modelling is summarised. This can be divided into three parts: the screening evaluation (Tier 1 and 2), the use of biosphere object modules in the landscape model (Tier 3), and the complementary models (in practice, the models used for deriving safety indicators). These are addressed in sections 5.2 to 5.4. A more detailed discussion of radionuclide transport modelling is found in Hjerpe & Broed (2010).

5.1 Landscape model set-up The predicted conditions for the surface environment at year 2 020, upon the emplacement of the first canister, define, in this context, the initial state of the biosphere. This is the starting point for the set-up of the landscape model. The biosphere objects are delineated, based on the forecasts from TESM. A biosphere object represents a continuous and sufficiently homogeneous sub-area within the modelled area that can potentially, directly or indirectly, receive radionuclides released from the repository. Each biosphere object is described by one, or more, ecosystem types and one set of data, and is associated with a corresponding radionuclide transport model (described in section 5.3). The connections between the objects are derived from terrain forecasts for the period from the initial state to the end of the assumed time window when regulatory dose constraints apply. When delineating the biosphere objects, it is sufficient to include areas of the surface environment that will potentially be contaminated, either by direct release of radionuclides from the geosphere or by horizontal transport of radionuclides


analysis



Terrain & ecosystem

development



Safety indicators

Outcome

BIOSPHEREASSESSMENT

CLIMATIC ENVELOPE






BSO modules

Tier 1 & 2

Annual release

Safety indicators

Dose assessmentComplianceassessmentLSM set-up

Release pattern

SNSH

TESM

60

within the surface environment during the biosphere assessment time window23

5.1.1

. The spatial and temporal distribution of possible radionuclide release paths to the biosphere, the release pattern, is needed in order to identify which biosphere objects to include in the landscape model. The combination of the connected biosphere objects and the release pattern is the landscape model. The landscape model is thus a state-of-the-art, time-dependent and site-specific radionuclide transport model. The initial state for the landscape model and its development is defined as part of the landscape model set-up process. This is discussed in detail in Hjerpe & Broed (2010) and summarised here. Firstly, the general properties of biosphere objects are discussed (section ), and then the derivation of the simplified release pattern is presented (section 5.1.2).

5.1.1 Biosphere objects In the present assessment, the following six main ecosystem types are included: lake, coast, river, forest, wetland and cropland. The transitions between ecosystem types due to the evolution of the biosphere (e.g. when new terrestrial ecosystems are formed from the sea due to land uplift) are also regulated in the landscape modelling, see Figure 5-2 for the allowed paths.

Delineation of biosphere objects A key issue when delineating the biosphere objects is to assure that links between the locations of possible radionuclide release points into the biosphere and to the biosphere objects in the landscape model can be established. The spatial distribution of possible radionuclide release points into the biosphere is based on the findings from the groundwater flow simulations in the bedrock, as are summarised in the RNT-2008 report (Nykyri et al. 2008). There, the steady-state release paths from six repository panels in the repository to the upper boundary of bedrock have been calculated for 1 000 and for 10 000 years in the future. As discussed above (section 4.1), the results are nearly identical and, for simplicity, only the results for 10 000 years in the future are used in the present assessment. Furthermore, the time window for the biosphere assessment is much less than the time window for radionuclide transport in the repository system presented in Nykyri et al. (2008). For this reason, radionuclide release paths with advective travel times of up to 15 000 years are included, and those with longer travel times are excluded from further consideration, as releases from the repository cannot reach the biosphere within the dose assessment time window along such paths.

The TESM was used to delineate the ecosystem types of these objects for the years 2 020 to 12 520 (in 500 year intervals). Nine different types of ecosystems were delineated for each time step. The six main types were: coast, lakes, mires, forests, croplands and rivers. Furthermore, lakes include, in addition to the open water part, reed areas, parts dried out and covered by forests, and parts formed into mires. Certain rules for the delineated objects were also applied in order not to underestimate doses to the most exposed people (Hjerpe & Broed 2010). The most important rules concern the areas of terrestrial objects; upper limits for the areas of individual forests and croplands were applied in order to avoid excessive numerical dispersion of radionuclides arising

23 The large areas of sea bottom that may be contaminated to a small degree (very low activity concentrations), will be addressed as what- if cases in future assessments, due to computational limits.

61

Figure 5-2. The allowed paths for ecosystem evolution in the landscape model. The dashed lines represent alternative paths. The directions of the paths may also be reversed, for example in the case of sea level rise.

from treating individual objects as laterally homogeneous. The resulting landscape model is presented and further discussed in section 7.2.

Computation of vertical and horizontal water fluxes in biosphere objects The location and maximum extent of terrestrial and surface water areas (lakes, rivers) that could potentially receive radionuclides from the repository were identified based on results from simulating the continuation of the radionuclide pathways from the geosphere through the overburden using surface and near-surface hydrology modelling (Karvonen 2009c).

In the first step of the analysis, vertical and horizontal fluxes were calculated on a 10x10 m2 grid using the Olkiluoto surface and near-surface hydrological model (Karvonen 2008, 2009a,c). Steady-state recharge to bedrock or discharge from bedrock was computed for all computational pixels and these results were used as the lower boundary condition of the model. Upper boundary conditions for the model were precipitation and potential evapotranspiration rates. Parameterization of the transpiration and interception processes were based on the results of the Soil-Vegetation-Atmosphere-Transfer (SVAT) model that was used for computing water and energy balance components of the forest intensive monitoring plots on Olkiluoto Island (Karvonen 2009b).

The second step included compilation of fluxes for each biosphere object, delineated as discussed above, at each time step. Vertical fluxes were averaged values from all pixels inside the delineated ecosystem types. Horizontal fluxes were computed by summing the horizontal inflows and outflows through the ecosystem boundaries. Moreover, soil water content and water amount in deep soil/deep sediment, intermediate soil/intermediate sediment, root zone/catotelm24/active sediment layer and humus/acrotelm25

5.1.2 Simplified release patterns

were computed.

The modelling of transport pathways for radionuclides released from the canister, through the near-field and geosphere was carried out separately from the transport modelling in the biosphere. Although multiple flow pathways are identified in deep

24 The permanently saturated peat layer. 25 The peat layer above the elevation of low water table.

lake (or river)coast wetland

forest

cropland

open sea

62

groundwater flow modelling, the transport of radionuclides through the geosphere was evaluated with a simplified model that considers only a single representative and non-dispersive pathway (Nykyri et al. 2008). Hence, the full information on spatial and temporal distribution of releases from the geosphere is not provided to the biosphere modelling in the present assessment; this will be improved by 2012. The connection between the geosphere transport modelling and the landscape model is achieved by deriving simplified release patterns (stylised representations of the radionuclide transport paths for the geosphere releases to the biosphere) based on surface and near-surface hydrology modelling and deep groundwater flow modelling. The derivation is summarised below, and presented in detail in Hjerpe & Broed (2010).

Radionuclide release paths When delineating the biosphere objects in the landscape model (section 5.1.1), the findings from the groundwater flow simulations in the bedrock from six repository panels (Nykyri et al. 2008) were used. When deriving the simplified release pattern, only results for three repository panels, which are those needed for spent fuel from the units currently in operation or under construction, were applied (the 2006 repository layout, Kirkkomäki 2007). The present radionuclide transport modelling addressed results from Panels 1, 2 and 5 in Nykyri et al. (2008); denoted as Panels A, B and C in this report, respectively.

The starting points for each individual flow path from the repository (origin points) are distributed in the repository panels (see Figure 5-3). The results from all realisations of the groundwater flow simulations in the bedrock (Löfman & Poteri 2008) are included in relation to the three panels considered. The distribution of advective travel times from the origin point to the biosphere is given in the dataset for each path. For example, the advective travel times from Panel C to the biosphere on the southern side range from about 10 to 27 000 years, and on the northern side from about 10 years to 6.4 million years. Figure 5-4 shows the spatial and temporal distribution of release paths into the biosphere with travel times up to 15 000 years. For the biosphere assessment, release paths with advective travel times longer than 15 000 years are excluded from further consideration, as they cannot mediate any releases to the biosphere within the dose assessment time window.

In geosphere transport modelling, which calculates the radionuclide release rates to be used in the biosphere assessment, the complex flow path system is represented as a single, representative and non-dispersive transport path, characterised by an integrated transport resistance (Nykyri et al. 2008, citing Poteri 2007). This simplification means that the flow paths are, in effect, treated as identical for geosphere transport modelling purposes. Thus, a full coupling between the calculated time-dependent activity release rates from a failed canister and the temporal and spatial distribution of possible radionuclide transport paths is not currently feasible. In reality, radionuclides released from a failed canister at a certain time will subsequently be dispersed in space and time, and will thus arrive at different locations in the biosphere and at different times. Here, a stylised coupling between the modelled release rates and the deep groundwater modelling has been established to facilitate the connection between the geosphere release points and the landscape model. The only temporal aspect considered is the advective travel time for the characteristic single pathway used in the geosphere

63

Figure 5-3. Origin points for flow paths from groundwater flow simulations presented in Nykyri et al. (2008), overlaid on the 2006 repository layout (Kirkkomäki 2007). The origin points from different model realisations are shown in the figure. Map layout by Ari Ikonen / Posiva Oy

Figure 5-4. Release into the biosphere from Panel C for six intervals of the advective transport time (to the biosphere) for the first 15 000 years, based on groundwater flow simulations presented in Nykyri et al. 2008 and on the 2006 repository layout (Kirkkomäki 2007). Map layout by Ari Ikonen / Posiva Oy.

64

transport modelling. Hence, the stylised coupling described below results in releases from the canister occurring at a certain time ending up at different locations in the biosphere, but at the same time. The derived spatial and temporal distribution of transport paths (see Figure 5-4) shows that the distribution of possible release paths to the biosphere does not vary greatly with time in the time window for biosphere assessment. Even though the number of possible pathways increases with time, the spatial pattern remains fairly constant. To simplify the implementation of a spatially distributed geosphere release, the pattern of release paths for each repository panel is treated as constant in time, and includes all pathways with travel times less than 15 000 years. Further, all pathways are assumed to have the same probability.

Formulation of simplified release patterns The next step is to link the locations of the release points (see e.g. Figure 5-4) with specific biosphere objects in the landscape model. This is done based on the type of ecosystem in the landscape model coinciding with the location of each release point to the biosphere. Basically, the release goes to the object coinciding with the release point. The final step is to select a small number of simplified release patterns for use in the assessment, conceptualised based on the analysis and detailed results above. These are all analysed by radionuclide transport modelling and doses are derived (presented in section 8.1.1) for nominal release rates. Two types of simplified release patterns are selected: realistic release patterns and alternative release patterns. The realistic release patterns are considered to have the highest likelihood and are to be used in the realistic biosphere calculation cases. In the alternative release patterns, considered to have lower likelihood, the releases are targeted towards selected types of objects, in order to assess the impact of the outcome of the assessment due to uncertainties in the selection of the release pattern (i.e., analysed as sensitivity calculation cases).

For each panel, a realistic release pattern, based on the degree of realism, is selected to underpin the realistic biosphere calculation cases (see section

Realistic release patterns

2.1.3). When formulating a realistic release pattern, a high degree of realism is considered to have been reached when it captures a majority of the geosphere release points.

By selecting just a few biosphere objects at least 97% of the geosphere release points, for releases from each repository panel, are captured by the landscape model. Distribution of the whole geosphere release between these few dominating objects can be done in several ways, since the distribution of releases between different release points in a release pattern is not well known. In the realistic release patterns, a simple approach is used: the release to each object is weighted by the relative number of release points due to releases from one repository panel. The formulation of the realistic patterns is presented below (Table 5-1). The realistic release patterns are all dominated by releases to aquatic objects (lakes). The high number of individually simulated release paths ending up in lakes suggests that water bodies do tend to draw groundwater flow, and thus releases, to them due to the hydraulic gradients.

65

Table 5-1. Simplified release pattern formulations, based on release from the three repository panels A, B or C. The percentages before the names of the biosphere objects specify the fraction of the geosphere release that is directed into the object.

Panel A Panel B Panel C

Realistic release patterns

Identifier Realistic-A (a) Realistic-B (a) Realistic-C (b) 75% Liiklanjärvi

14% Tankarienjärvi 8% Liiklanpelto 3% Mäntykarinjärvi

94% Tankarienjärvi 6% Mäntykarinjärvi

71% Tankarienjärvi 16% Mäntykarinjärvi 11% Liiklanjärvi 2% Susijärvi

Alternative release patterns

Identifier Forest_focused-A (c) Forest_focused-B (d) Forest_focused-C (e) Flutanmetsä W 100%

Telakka 100% Mäntykarinedus 100%

Identifier Forest_dispersed-A (f) Forest_ dispersed-B (g) Forest_ dispersed-C (h) 81% Flutanmetsä W

19% Flutanmetsä E

71% Telakka 11% Kiskarinsivu 11% Kiskarintaka 7% Satama

76% Mäntykarinedus 24% Kiskarintaka

Identifier Cropland_focused-A (i) Cropland_focused-B (j) Cropland_focused-C (k) 98% Liiklanpelto

2% Koskelonpelto

100% Marikari 100% Mäntykarinmaa

Identifier Cropland_dispersed-A (l) Cropland_ dispersed-B (m) Cropland_ dispersed-C (n) 91.3% Liiklanpelto

4.8% Tuomonjoki2 1.7% Koskelonpelto 1.7% Liiklanpellonjoki 0.5% Lepänmaa

73% Marikari 20% Mäntykarinmaa 7% Koivisto

53% Mäntykarinmaa 23.5% Kaunissaari W 23.5% Koivisto

(a) Captures 98% of all release points (b) Captures 97% of all release points (c) An over-estimation, captures only 0.24% of all release points (d) An over-estimation, captures only 1.1% of all release points (e) An over-estimation, captures only 0.7% of all release points (f) Still rather focused release, but no other forests available; captures 0.30% of all release points (g) Almost all forests receiving releases, capturing 1.6% of all points (h) Two most release-dominating forests, capturing 0.94% of all release points (i) Compromise between the most upstream and the dominating field, captures 7.7% of all release points (j) The release-dominating cropland capturing 0.15% of all release points, also located upstream (k) The release-dominating cropland capturing 0.3% of all release points (l) Only the southern croplands (northern croplands - total 1% of all release), captures 8.3% of all release

points (m) All croplands receiving releases, capturing 0.20% of all release points (n) All croplands receiving releases, capturing 0.55% of all release points

66

Even though the majority of geosphere release points may be linked to aquatic biosphere objects, points also exist that may be linked to terrestrial areas. Thus, routes direct to terrestrial objects cannot be totally ruled out, but may be considered to have a lower degree of realism. Consequently, alternative, less likely, release patterns may be formulated. The role of the alternative release patterns in the present assessment is to assess the sensitivity of the outcome of the assessment due to the selection of the release pattern.

Alternative patterns

Targeted releases to forests and croplands are selected as alternative patterns, primarily to assess the level of conservatism in the selected realistic patterns. The selection of forest and croplands is based on their characteristics regarding the food ingestion exposure pathway, which is expected to be most important; targeted releases to forest ecosystems are selected since forest objects resulted in the highest (biosphere object-specific) landscape dose maxima in the KBS-3H biosphere analysis (Broed 2007a). Thus, forest ecosystems may be the major contributor to the annual doses, at least to a few exposed persons, since forest objects generally can support only a few persons with food. Targeted releases to croplands are selected due to their high productivity of edibles (see section 3.3.4). Thus, cropland ecosystems have the potential to expose a larger population via food ingestion. Furthermore, lakes are well represented in the realistic case. In the alternative patterns, it is assumed that the release either is entirely captured by forest objects or cropland objects. These patterns are divided into two variants: focused and dispersed. In the focused variants, the whole release is directed into a small number of, mostly a single, forest or cropland objects. In the dispersed variants, the whole release is distributed to all forest or cropland objects with at least one release point. The weighting of the releases to several objects is done, as for the realistic patterns, according to the number of release paths ending in each object.

5.2 Screening evaluation This section describes the approach, and the models and data used in the screening evaluation (Tier 1 and Tier 2) in the graded approach (see section 2.2). The quantity of interest in both tiers is the Risk Quotient (RQ), which is the calculated nuclide-specific dose rate divided by pre-selected Screening Dose Rates (SDR). The approach must be sufficiently cautious so that there is a high degree of confidence that the potential radiological consequences are below the relevant regulatory requirements when the RQ is below 1. The SDR itself must be assigned a value substantially below regulatory dose constraints; how much lower depends on the desired degree of conservatism in the screening evaluation. The approach here is to select the SDR low enough to allow Tier 1 and 2 to screen out individual radionuclides for which the calculated RQ is less than or equal to 1. Two SDRs are used throughout the evaluation: 10nSv/y for humans, which is two orders of magnitudes below the lowest regulatory dose constraint, and 10 µGy/h for the other biota, which is the default generic screening absorbed dose rate in the ERICA Tier 1 (see below) and is also recommended by the PROTECT project (Andersson et al. 2008).

The procedure for the screening evaluation is similar to the one recommended in IAEA (2001) for use in assessing the impact of discharges of radioactive substances to the environment, and the models are in line with the recommendation by the ICRP (2000,

67

2007b) on how to conduct a dose assessment. In Tier 1, an extremely cautious approach is taken, in which it is assumed that a hypothetical individual receives the maximum exposure over one year to the whole integrated release from the geosphere. If the RQ calculated for a specific radionuclide in Tier 1 is greater than 1, then it is necessary to continue to Tier 2. In Tier 2, a screening model is applied that includes a higher degree of realism than the model used in Tier 1, but is still sufficiently cautious for screening purposes. The generic model includes two generic ecosystem-specific sub-models, one terrestrial and one aquatic, and a well sub-model. The screening model used in Tier 2 does not require site-specific parameters and therefore can be called “generic”. If the RQ calculated for a specific radionuclide in Tier 2 is greater than 1, then it is necessary to consider that radionuclide in the site-specific landscape modelling (Tier 3). The screening models are summarised in the following sections; see Hjerpe & Broed (2010) for more details and the data used. For clarity the applied radiological consequences analysis is described together with the radionuclide transport models.

5.2.1 Tier 1 The first tier is conceptually illustrated in Figure 5-5. It is designed to ensure extremely pessimistic RQs, by several orders of magnitude. Thus, radionuclides screened out at Tier 1 are indisputably insignificant for radiological consequences during the biosphere assessment time window. The evaluation regarding humans is carried out by assessing the doses due to each radionuclide in three exposure situations, where the whole integrated release from the geosphere is

• totally routed to one person for intake by ingestion, • totally routed to one person for intake by inhalation, and • transferred to the ground surface and exposes one person externally.

When assessing the dose due to external exposure, it is pessimistically assumed that the whole activity is transferred to one square meter of ground surface; then the external dose rate is, unrealistically, derived by multiplying the activity concentration in the contaminated surface by the dose coefficient for a source distributed over an infinite ground surface. Further, to derive the annual dose due to external exposure, it is assumed that the person is exposed to that dose rate over one year. The highest annual dose from the three exposure situations considered is then divided by the SDR, for humans, to obtain the RQhumans. Thus, Tier 1 is an extension of the integrated radiotoxicity flux that may be used as an indicator of safety (Becker et al. 2009).

The evaluation, regarding other biota, is implemented in a somewhat different fashion. Instead of calculating absorbed dose rates to compare with the selected SDR for other biota to obtain the RQbiota, the SDR is used to determine radionuclide-specific environmental media concentration limits (EMCL), based on the ERICA integrated approach (section 6.2). The most penalising EMCL for different solid media (soil or sediment) and liquid media (freshwater and marine water) are denoted as EMCLsolid and EMCLliquid, respectively.

68

Figure 5-5. Conceptual model of Tier 1. The environment box is shaded for the ingestion and inhalation pathways to emphasize that no environmental processes are considered – the source is directly inhaled/ingested (DCing, DCinh and DCext are the dose coefficients for ingestion, inhalation and external exposure, respectively).

Figure 5-6. Conceptual model of Tier 2 (DCing, DCinh and DCext are the dose coefficients for ingestion, inhalation and external exposure, respectively).

SOURCEIntegrated geosphere release – cautious time window

max

RQ

ENVIRONMENTNo processes considered

ENVIRONMENTPessimistic accumulation

ENVIRONMENTPessimistic accumulation

Humans Other biota

EMCLsolid EMCLliquid

RQbiotaRQhumans

IngestionDCing

InhalationDCinh

ExternalDCext

max SDRhumans

SDRbiota

SOURCEGeosphere release rate maxima – cautious time window

IngestionDCing

InhalationDCinh

ExternalDCext

max

ENVIRONMENTGeneric ecosystem-specific radionuclide transport models

(terrestrial, lake, well)

EMCLsolid/liquid

HABITSCautious assumptions

sum

Other biotaHumans

RQ

RQbiota

RQhumansSDRhumans

SDRbiota

69

Furthermore, it is pessimistically assumed that the habitat for the worst case reference organism has an activity concentration numerically equal to the total integrated activity, for each radionuclide, in the geosphere release. For example, if the integrated activity is 100 Bq and the worst case reference organism habitat is lake water, an activity concentration of 100 Bq/L in the lake water is assumed. The RQbiota is then determined as the highest ratio of the derived activity concentrations in solid media, or liquid media, and EMCLsolid, or EMCLliquid.

In addition, to be even more certain that the RQs are not underestimated, the integrated geosphere release rates used are not corrected for any radioactive decay, but include build-up of progeny radionuclides. This is, of course, a non-physical approach. However, this is deliberate, so that there is no potential for underestimating the contribution either from the parent or from its progeny. The integration takes places over a time window of 15 000 years (from year 2 020 to year 17 020), which is significantly longer than Posiva’s interpretation of the biosphere assessment time window where regulatory dose constraints apply. Thus, this means that one person, or one individual of the limiting reference organism for other biota, is exposed to everything released from the geosphere up to the year 17 020.

5.2.2 Tier 2 The second tier is illustrated in Figure 5-6, and is designed to ensure defensible and very cautious RQs. In contrast to Tier 1, Tier 2 takes transport in the biosphere into account, and thus the degree of realism is increased. The generic model applied is still sufficiently cautious for the screening purpose, and includes generic ecosystem-specific sub-models: a cropland, a lake, and an agricultural well. These three sub-models are evaluated in parallel, and the sub-model resulting in the highest exposure is then used for deriving the RQ, which may differ for different radionuclides.

Each sub-model applies cautious assumptions regarding transport and retention. For example, the geometrical properties of the lake and cropland are selected to support exactly one person with food, and the mixing capacity of the well is cautiously selected. The parameter values are also, to as great extent as possible, cautiously selected (see Hjerpe & Broed 2010 for more details and justifications for the selected data). For example, the selected solid-liquid distribution coefficients (Kd) in soil are the 95th percentiles of internationally recommended distributions (IAEA 2009), and intake rates are based on 95th percentiles derived from studies at a national population level (Smith & Jones 2003, Ershow & Cantor 1989). In addition, geosphere release rate maxima are used. Tier 2 is applied over the same time window as Tier 1, i.e., 15 000 years.

5.3 Modules applied in biosphere objects The biosphere object modules used in the landscape model each represent a typical ecosystem identified to exist during any time interval in the developing landscape. In the present assessment, the following types are applied: forest, wetland, cropland, lake, river, coast and sea. These modules are discussed in detail in Hjerpe & Broed (2010) and summarised in this section. The modules are consistent on a conceptual level, meaning that the structure of compartments is very similar in all models. This facilitates the coupling between ecosystems existing at the same time, and the transition between

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Figure 5-7. The conceptual radionuclide transport model for terrestrial ecosystems. The indices in the compartment names define for which ecosystem(s) they are valid, where: (F) is forest, (W) is wetland and (C) is cropland.

Figure 5-8. The conceptual radionuclide transport model for aquatic ecosystems (lake, river, coast and sea).

Deep soilFWC

Intermediate mineral soilFC

Rooted mineral soilFC CatotelmW

Green partsFW CropsC

AnimalsFWC FungiF

WoodF

Dead woodF LitterF

AirFWC

HumusF AcrotelmW

Radionuclide release rates from the geosphere

Net RN flux out from the system

RN flux between compartments

Equilibrium relationship

Compartment possibly receiving direct release of radionuclides

Air to ground interface

Deep sediment

Intermediate sediment

Active layer (bio-active sediment)

Green parts

Animals

Water

Radionuclide release rates from the geosphere

Net RN flux out from the system

RN flux between compartments

Equilibrium relationship

Compartment receiving direct release of radionuclides

Water to sediment interface

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ecosystem types due to landscape development (e.g. when new terrestrial ecosystems are formed from the sea due to land uplift). All included ecosystem-specific models could, in principle, be illustrated in one generic conceptual model. However, for clarity, two conceptual models are illustrated separately, one terrestrial and one aquatic; these are presented in Figure 5-7 and Figure 5-8.

Compartments receiving the releases directly from the geosphere To ensure that potential radiological consequences are not underestimated, at least for humans, the geosphere releases are directed straight to the compartments assumed to maximise the incorporation of radionuclides in the human food chain26

Applied data

. The approach can be summarised as follows: the releases to the biosphere enter the biosphere object modules in the rooted mineral soil layer for terrestrial objects, except in wetlands were they are directed to the acrotelm layer, or to the water column in aquatic objects. When an object receiving releases is partially under sea (or lake), all releases are targeted to the terrestrial part. If only sea (coast type) exists in the object, then the releases are directed to its water column.

All data used in this assessment are presented in background reports (Hjerpe & Broed 2010, Ikonen et al. 2010a,b, and Helin et al. 2010). A brief discussion of key sources of data that have been utilised is provided, below. Compared with earlier analyses (Broed et al. 2007, Broed 2007a,b), site and regional data have been used to a much greater extent in the present assessment. All fluxes of water between the compartments in the biosphere object modules, and also between objects, are based on site data, interpreted through the surface and near-surface hydrology model (Karvonen 2009c). Selected key parameters for those biosphere object modules for which site and regional data are used to derive values are briefly discussed below. The fate of C-14 is modelled using a specific activity model (Avila & Pröhl 2007); however, the C-14 model is integrated in the landscape model and is not treated separately.

• For forest objects, key parameters for which site and regional data are used are annual production of wood, tree foliage and above-ground parts of understorey vegetation, concentration ratios (CR) from soil layers to green parts, for the key radionuclides, biomasses of trees and other vegetation, transpiration, and intercepted fraction of precipitation by the canopy.

• For cropland objects, key parameters for which site and regional data are used are the irrigation amount and irrigation frequency, and the leaf area index.

• For aquatic objects, the key parameter for which site and regional data are used is the retention time in lakes and rivers.

Key C-14 model-specific parameters for which site and regional data are used are the net primary production for forest and the sedimentation rate in lakes.

26 This is a cautious assumption for most of the other biota, too, but not for all assessment species. Alternative release terms will be analysed in the 2012 assessment.

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5.4 Safety indicators In the previous biosphere analysis, the KBS-3H safety study, (Broed et al. 2007), two indicative stylised well scenarios were applied to derive safety indicators in terms of annual effective doses: one for a drinking water well and one for an agricultural well. The same concept is used in the present assessment, with only minor changes in models and applied parameter values. The drinking water well (WELL-2009) is similar to the well scenario applied in previous safety assessments (Vieno 1994, 1997, Vieno & Nordman 1996, 1999, Broed et al. 2007) and in the RNT-2008 report (Nykyri et al. 2008). The agricultural well (AgriWELL-2009) is an extension of this approach to also include watering of cattle and irrigation of crops, and is similar to the agricultural well scenario applied in the previous assessment (Broed et al. 2007). Both well scenarios are stylised indicative scenarios, based on wells with identical characteristics. The well scenarios are used to estimate indicative hypothetical annual doses received by a representative member of the most exposed people by deriving dose conversion factors (DCF), and multiplying these by the annual release rates from the geosphere. These safety indicators, the “well doses”, are used to support the decisions made in the compliance assessment regarding dose constraints, which are based on landscape doses (see section 6.1). Well doses are also used to obtain indicative annual effective doses beyond the time window of biosphere assessment, where the applicable regulatory constraints are based on activity fluxes from the geosphere; this is discussed in Nykyri et al. (2008). The radionuclide models and the applied data are presented in the following sections. For clarity, the radiological consequences analysis is presented together with the radionuclide transport models. In the present report, the well scenarios are used to derive doses for the nominal release rates (section 2.4).

Stylised well scenarios Conceptual models for the radionuclide transport and exposure pathways in the two scenarios WELL-2009 and AgriWELL-2009 are illustrated in Figure 5-9; see Hjerpe & Broed (2010) for the mathematical structure. The drinking water well (WELL) scenario was introduced in the Finnish assessment of deep repositories by Vieno (1994) and has been applied, with minor modifications, in safety assessments since 1996 (Vieno & Nordman 1996, Vieno 1997, Vieno & Nordman 1999, Broed et al. 2007, Smith et al. 2007b, Nykyri et al. 2008). The WELL scenario is very simple and robust; based only on an effective mixing capacity (the mixing of the annual releases from the geosphere with the water in a well), and an annual intake of water (an adult male satisfies his annual demand for drinking water entirely from water from the well). The agricultural well (AgriWELL) scenario is an extension of the WELL scenario, taking more pathways into account. The AgriWELL scenario was first used in the KBS-3H biosphere analysis (Broed et al. 2007). In AgriWELL, it is assumed that the yield of the well is sufficiently high for human consumption, watering of livestock, and for irrigation of crops. Additional exposure pathways (see Figure 5-9) are consumption of irrigated crops and of animal products. The radionuclides in irrigation water contaminate the crops, and thus also the animal fodder, both by direct uptake of surface deposited activity and by secondary uptake via the roots. The radionuclides in the well water also contaminate animal products due to the animals’ water consumption.

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Figure 5-9. Conceptual models for the radionuclide transport and exposure pathways to derive the dose conversion factors in the two well scenarios. AgriWELL utilises data for a fictive farm, with characteristics based on region-specific farm statistics (such as land-use, yields, and production). The AgriWELL scenario is applied to an adult male who satisfies his nutrient needs by eating and drinking products from the farm and drinking water from the WELL.

Applied data All data applied are presented and discussed in Hjerpe & Broed (2010). Below is a summary of some of the key data and data sets used.

• The assumed effective mixing capacity of the well is unchanged since previous assessments, (100 000 m3/y, based on the discussion in Vieno (1994) and supported by Kattilakoski & Suolanen (2000)).

• The annual intake of water has been selected to be 0.9 m3/y; based on high-consumer (95th percentile) intake of tap water (Ershow & Cantor 1989 cited in OEHHA 2000), which is a higher intake than that applied in all previous versions.

• The data for the fictive farm are based on average farm statistics for farms in the Satakunta region for the year 2004. The main source of information is the Yearbook of Farm Statistics 2005 (TIKE 2006). Irrigation practises are mainly based on regional data, derived from Pajula & Triipponen (2003).

• Swedish data for overall consumption (SJV 2006) and age-dependent consumption of different food groups (Karlsson & Aquilonius 2001) are used, as combined to derive average intakes of different foodstuffs for an adult male. The results are then fitted to the foodstuffs produced at the fictive regional farm, contaminated by irrigation water.

• Radionuclide transport data are taken from literature; key parameters and their main data sources are:

Irrigation

Ingestion (drinking)

Ingestion (eating)

Well water

BerriesGreenhouse Kitchen gardenOutdoors

Vegetables

Livestock

SheepsPoultry Pigs Cows

DCFAgriWELL

Potatoes Silage/green fodderWheat

Cereals/grass/tubers

Humans

DCFWELL

Humans

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o Solid-liquid distribution coefficients in soils (Kd) and translocation of intakes from diet to animal products (Ff, Fm): IAEA (2009),

o Soil to plant concentrations ratios (CR): Karlsson & Bergström (2000, 2002), OPG (2002, 2004), US DOE (2004) and Uchida et al. (2007), and

o Translocation factors for root crops: Karlsson & Bergström (2002).

5.5 Key data produced for further use in the biosphere assessment The main outputs of the radionuclide transport modelling sub-process for further use in the biosphere assessment modelling are radionuclide concentrations. These provide key input data for dose assessment, both for humans and for other biota. They are derived for key radionuclides in all compartments in all biosphere objects in the landscape model, at each time -step (from year 2 020 to year 12 520, in time steps of 50 years).

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6 RADIOLOGICAL CONSEQUENCES ANALYSIS

Figure 6-1. Detailed illustration of the radiological consequences analysis sub-process (RNT: radionuclide transport modelling).

This section gives an overview of the radiological consequences analysis (RCA) in the biosphere assessment restricted to the part within the red box in Figure 6-1. This section addresses the last main sub-process in the biosphere assessment process, radiological consequences analysis (RCA) (Figure 6-1). The models and concepts presented here are used to estimate potential consequences to humans and other biota due to the spatially distributed, time-dependent radionuclide-specific activity concentrations in each environmental medium in each biosphere object in the landscape model, as calculated by radionuclide transport modelling. The focus is here on the main (dose) quantities to be used in assessing compliance with regulatory criteria and constraints related to radiation protection.

6.1 Assessing doses to humans The main objective of the assessment of doses to humans is to determine compliance with the regulatory dose constraints. The regulatory guideline includes constraints on the annual dose to the most exposed people and to other people. As mentioned in section 1.2.3 (see footnote 2), the quantity used for measuring “dose” to humans is the effective dose. The effective dose is the tissue-weighted sum of the equivalent doses in all specified tissues and organs of the body, where the tissue weighting factor represents the relative contribution of that tissue or organ to the total health detriment27

resulting from uniform irradiation of the body. The equivalent doses are mean absorbed doses in each tissue or organ, weighted by a factor that depends on the radiation type (ICRP 2007a). Thus, effective dose is a quantity designed to reflect the amount of health detriment likely to result from the dose, based on current radiobiological, epidemiological and medical expertise.

27 A concept used to quantify the harmful health effects of radiation exposure in different parts of the body; defined as a function of several factors, including incidence of radiation-related cancer or heritable effects, lethality of these conditions, quality of life, and years of life lost owing to these conditions (ICRP 2007a).


analysis



Terrain & ecosystem

development



Safety indicators

Outcome

BIOSPHEREASSESSMENT

CLIMATIC ENVELOPE






Geosphere releases

Safety indicators

Dose calculationsComplianceassessmentR

NT

Dose identification

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Doses to the public cannot be measured directly and we are in any case concerned with doses that may occur in the future. Therefore, for the purpose of protection of the public, it is necessary to characterise an individual, either hypothetical or specific, whose dose can be used for determining compliance with the relevant dose constraint. The ICRP has provided guidance (ICRP 2007b) on how to assess dose to the individual for the purposes of establishing compliance with the ICRP recommendations (ICRP 2007a). However, ICRP states (ICRP 2007b) that the guidance for the protection of future individuals in the case of disposal of long-lived radioactive waste as provided in (ICRP 2000) remains valid. ICRP (2000) recommends, in the context of assessing doses to those most likely to receive the highest doses, that exposures should be assessed on the basis of the mean annual doses received by the critical group28

The concept adopted in this report for assessing annual doses for the purpose of determining compliance with the regulatory dose criteria is based on the guidance in (ICRP 2007b) on how to assess the dose to the ‘representative person’ This is considered to be consistent with the ICRP (2000), since the ‘representative person’ is considered to be equivalent to an ‘average member of the critical group’ (ICRP 2007b, paragraph (i)) and the dose to the ‘representative person’ is considered to be the equivalent to the mean dose in the ‘critical group’ (ICRP 2007b, paragraph (25)). The dose assessment process is described in detail in (Hjerpe & Broed 2010). A brief summary of the concept is given below.

. Further, ICRP (2000) states that it is reasonable to calculate the annual dose averaged over the lifetime of the individuals, which means that it is not necessary to calculate doses to different age groups; this average can be adequately represented by the annual dose to an adult. This is valid in the cases in which radioactive contamination of the biosphere remains relatively constant over periods that are considerably longer than the human life span, as is expected to be the case for contamination due to releases from a geological repository.

6.1.1 Dose assessment in the present assessment The dose assessment used is a refinement of the approach developed and applied in Broed et al. (2007), and extended to a comprehensive dose assessment. The extension has especially focused on:

• harmonising the dose assessment with international recommendations,

• ensuring an adequate level of conservatism, and

• broadening the assessment to address all regulatory dose constraints.

The dose assessment follows the general process for converting results from radionuclide transport modelling into suitable quantities to be used in the compliance assessment with annual effective dose constraints, as illustrated by Figure 6-2.

28 A group of people representative of those individuals in the population expected to receive the highest annual dose, which is a small enough group to be relatively homogeneous with respect to age distribution, diet, and those aspects of behaviour that affect the annual doses received.

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Figure 6-2. General process for assessing the doses to humans. Each step is described in section 6.1.1. Environmental information The key information regarding the environment is obtained from landscape modelling, namely the geometric properties of the landscape model and the time-dependent and radionuclide-specific radioactivity concentrations in environmental media. In addition, information such as production rates of individual food products, to derive the total productivity of edibles, and aggregated concentration ratios of radionuclides from environmental media to edible food products, are needed.

The productivity of edibles is calculated by summing over all plant parts and animal products normally consumed by man. The original data, mostly in terms of fresh weight, from BSD-2009 are converted to kilograms of carbon. The carbon content is calculated based on the contents of proteins, carbohydrates and lipids (fat), as reported in the FINELI database of the National Institute for Health and Welfare (www.fineli.fi).

The aggregated concentration ratios are radionuclide- and ecosystem-specific, and derived as the productivity-weighted average of the soil-to-edible concentration ratios for all edibles produced in the ecosystem in question. The concentration ratios for each type of edible are based on site and literature data (see section 3.3.4). The aggregated concentration ratio also uses the carbon content in edibles, which is derived in the same way as described above for productivity. This approach to deriving aggregated concentration ratios describes, if there is no preference as to what humans eat, the average transport of radionuclides from the soil to the foodstuffs consumed. Thus, it gives a reasonable measure of the ingestion of radionuclides in foodstuffs by people who satisfy their full annual demand of food from one biosphere object, without making assumptions regarding the details of their diets. The only assumption needed is whether to include an item or not in the list of edibles from each ecosystem.

Exposure characteristics A specific set of individual characteristics29

29 The term ‘exposure characteristics’ is equivalent to the ICRP (2007) ‘exposure scenario’. This terminology is selected to avoid confusion with the term dose assessment scenario used in the present assessment.

is selected, including, among others, food and water intake rates. In general, diet, residence, and other information needed to estimate exposure can be referred to as ‘habit data’ (ICRP 2007b). When assigning the exposure characteristics, care has been exercised to prevent excessive conservatism. The

Environmental information

Exposure characteristics

Dose calculation

Dose identification

Compliance assessment

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key features in the selected exposure characteristics, and the selection of habit data, can be summarised as follows:

• the exposure characteristics aim at being reasonable and sustainable, in line with the concept of assessing doses to the representative person (ICRP 2007b),

• four exposure pathways are considered: ingestion of food, ingestion of water, inhalation and external exposure,

• the number of exposed persons is limited by the capability of the biosphere objects to produce food and drinking water, by the size of suitable residential areas from a present-day perspective, and by present demography,

• average present-day intake rates are assumed for the representative person,

• cautious assumptions are made for residence data (e.g., time spent outdoors),

• a very cautious assumption is made for usage of local resources (i.e., all foodstuffs and water originate from contaminated areas), and

• individuals have no preferences regarding food. Dose calculation The dose calculation method applied follows the deterministic concept described in Avila & Bergström (2006). The calculations are based on values of food energy intake (carbon) and water intake given by the ICRP for Reference Man (ICRP 1975, 2002). The doses arising from intake of contaminated water and food, inhalation of contaminated air, and external exposure from contaminated areas are calculated by using dose coefficients30. The dose coefficients for ingestion and inhalation are based on the values recommended by the International Commission on Radiological Protection (ICRP 1996) for adults. Dose coefficients for external radiation from radionuclides uniformly distributed to an infinite depth, and an effectively infinite lateral extent of the contamination, in soil are used (based on Table III.7 in EPA 1993, extracted using the software Radiological Toolbox31

• Landscape dose (EL) – the pathway-, radionuclide- and biosphere object-specific annual effective dose to an individual.

). The present assessment applies the above discussed environmental information and exposure characteristics discussed above to calculate landscape doses. The landscape dose is defined as follows:

In the dose calculation, the two exposure pathways inhalation and external exposure are combined into the same dose quantity (EL,IE), whereas doses due to food ingestion (EL,F) and water consumption (EL,W) are kept separate. The reason for this is that the exposures from external and inhalation pathways occur simultaneously at the same location, whereas it is not always the case that the consumed food and water originate

30 A synonym for dose per unit intake, but also used to describe other coefficients linking quantities or concentrations of activity to doses or dose rates, such as the external dose rate at a specified distance above a surface with a deposit of a specified activity per unit area of a radionuclide (IAEA 2007). 31 U.S. Nuclear Regulatory Commission Radiological Toolbox, (version 2.0.0, August 2006) (www.nrc.gov/about-nrc/regulatory/research/radiological-toolbox.html)

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from the same location. This approach gives the possibility to calculate the dose to a person who, for example, e.g. lives in a forest, drinks water from a nearby lake and eats food produced on a nearby cropland.

For the biosphere objects in the landscape model, landscape doses are calculated for the different pathways as follows:

• Landscape dose from food ingestion (EL,F) is the product of the annual intake of a radionuclide from food ingestion and the corresponding dose coefficient for ingestion.

• Landscape dose from water consumption (EL,W) is the product of the annual intake of a radionuclide from water consumption and the corresponding dose coefficient for ingestion. This dose is only calculated for lake and river objects.

• Landscape dose from inhalation and external exposure (EL,IE). This dose is the sum of doses due to inhalation and external exposure from terrestrial32

It should be noted that, when calculating EL,F and EL,W, the situation will occur that there is not enough available food or water in a biosphere object to satisfy one person’s annual demand. Then, the remaining part of this demand is obtained from another object. The implementation aspect is addressed below in dose identification.

objects (forest, wetland and cropland). The contribution from inhalation is the product of the annual intake of a radionuclide and the corresponding dose coefficient for inhalation. The contribution from external exposure is the product of the activity concentration in the soil and the corresponding dose coefficient for external exposure.

Dose identification Here, the pathway-specific dose contributions are combined to obtain the “total” dose to each person in the whole exposed population. The approach to identifying the all-pathway dose, denoted below as the annual landscape dose, EALD, to a person is to identify the dose maxima from each pathway, and combine them. Thus, the dose to the most exposed person is the sum of the doses from ingestion of the most contaminated food, ingestion of the most contaminated water, and the dose from inhalation and external exposure arising from living in the biosphere object giving the highest dose. When deriving EALD, it is also required that the annual consumption of food and water originate from the exposed area to as full an extent as possible. Thus, the dose may be a sum of contributions from different biosphere objects (or even from different biosphere object types). For example, if a forest is the object capable of producing food with highest “dose rate”, but not enough food to satisfy one person’s annual food demand, it is then assumed that this person eats everything produced from this forest; and the rest of the food the person needs is taken from the biosphere object producing food with the second highest “dose rate”.

In the current assessment, the approach is to derive EALD to each exposed individual. The distribution of annual landscape doses between the different individuals of an

32 The potential contributions to the dose from inhalation and external exposure from aquatic objects are considered negligible for the radionuclides and activity levels of interest.

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exposed population is referred to below as the dose distribution; the underlying assumptions and the procedure for deriving this distribution are briefly explained below, and described in detail in Hjerpe & Broed (2010). The doses to each exposed person are derived, but information about the exposed population is also needed. The highest numbers of people that can satisfy their annual food demand, drinking water demand, and demand regarding residential areas, by utilising contaminated food, water and land are referred to as maximum sustainable populations; these are derived for each exposure pathway. For food ingestion, the carbon content in all contaminated edibles produced during one year divided by the average annual carbon demand is the maximum sustainable population. For water intake, the population is derived as the available drinking water (from all contaminated surface water bodies) divided by the average annual water intake, and multiplied by a usage factor taking into account that not all available water is utilised as drinking water. Finally, for inhalation and external exposure, the population is derived by dividing the total suitable residential area by an assumed population density. Here, only forest objects are included and the population density is cautiously selected as the highest present urban density in Finland (Helsinki).

The derivation of the dose distribution is performed iteratively, starting by deriving the annual landscape dose to the most exposed person, and then subtracting what caused that person’s exposure from the landscape model (one person’s annual demand of food or water, or the size of the residential area). Then, the annual landscape dose to the second most exposed person is derived, taking into account what the most exposed person has “used” from the landscape. This procedure is repeated until all three pathways have been the dominating pathway in the annual landscape dose at least once, or until a pre-selected upper limit on the size of the exposed group is reached. This approach to derive the dose distribution ensures that no potentially highly exposed groups are excluded. For example, if the potential residential areas (forest objects) are small, the maximum population living in the close vicinity of the site may be a small number. However, other contaminated objects may still be capable of producing food and water for a larger population, which is then accounted for in the dose distribution. Or, in other words, when food or water intake is the dominating pathway, no assumption is made regarding where the exposed person lives.

The dose distribution is used as the basis for identifying annual landscape doses to Identifying the dose to a representative person

• a representative person from the most exposed group, which is the sub-group of the above identified exposed population that receives the highest doses, and

• a representative person for the other people in the exposed population.

ICRP (2007b) recommends using the 95th dose percentile as the basis for selection of the most exposed group. Further, ICRP recommends that in the case when relevant dose constraints might be exceeded by a few tens of people or more, the characteristics of these people need to be explored (ICRP 2007b). These recommendations are appropriate for probabilistic assessments, whereas the present dose assessment is deterministic. However, since a distribution of doses is derived, a similar approach for selecting the most exposed group is applied here. The most exposed group is defined as consisting of the smallest of: 1) the 5% most exposed persons in the dose distribution,

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and 2) a few tens of people, here selected as the 50 most exposed persons. As the final step, the annual landscape doses to the two representative persons are identified as follows:

• the annual landscape dose to a representative person within the most exposed group, Egroup, is the average EALD for all persons in the most exposed group.

• the annual landscape dose to a representative person among the other individuals in the exposed population, Epop, is the average EALD in the exposed population, excluding the most exposed group.

6.1.2 Compliance assessment - humans In order to assess compliance with the regulatory dose constraints for humans, the whole assessment time window needs to be considered. This is done by deriving, for each generation, the dose distribution and identifying the doses to representative persons. Then,

• the highest value, over all generations, of Egroup is used to determine compliance with the regulatory dose constraints to the most exposed people, and

• the highest value, over all generations, of Epop is used to determine compliance with the regulatory dose constraints to other people.

6.2 Assessing doses to other biota The assessment by Posiva of consequences to other biota is not as mature as for humans. This is also true internationally. In the current assessment, typical absorbed dose rates to flora and fauna of the types currently present at the site are estimated, mainly based on the ERICA integrated approach, summarised below.

6.2.1 ERICA approach The ERICA project (Beresford et al. 2007) was conducted under the EC 6th Framework Program. It aimed at providing an integrated approach to scientific, managerial and societal issues concerning the environmental effects of contaminants emitting ionising radiation, with emphasis on biota and ecosystems. For utilisation within the impact assessment process, each (ERICA) reference organism has been assigned default attributes relating to radioecology and dosimetry in order to derive dose conversion factors; these are equilibrium concentration ratios, occupancy factors, and ellipsoidal geometries. The ERICA Tool, which is a piece of software, has a structure based upon the ERICA tiered approach to assessing the radiological risk to other biota. The tiers can be summarised as (modified from Brown et al. 2008):

• Tier 1 assessments are based on environmental media concentrations, and use pre-determined environmental media concentration limits (EMCL) to estimate risk quotients (RQ).

• Tier 2 calculates absorbed dose rates, but allows examination and editing of most of the parameters used, including concentration ratios, distribution

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coefficients, percentage dry weight soil or sediment, dose conversion coefficients, radiation weighting factors and occupancy factors.

• Tier 3 offers the same flexibility as Tier 2, but allows the option of running the assessment probabilistically if the underling parameter probability distribution functions are defined.

The EMCLs used in Tier 1 of the ERICA approach are utilised in the screening evaluation (section 5.1.2), and Tier 3 forms the basis for the current approach to deriving typical absorbed dose rates to the other biota (below). 6.2.2 Approach in Posiva’s biosphere assessment To assess the consequences to other biota, typical absorbed dose rates to flora and fauna of the types currently present at the site are derived. The general approach is presented in Figure 6-3. One major difference regarding the other biota, compared with assessing doses to humans, is the wide variety of taxa. Consequently, the first task to carry out is to identify a group of assessment species (reference organisms; reference animals and plants, or RAPs). Then, as for humans, the assessment is a multistage process, and can be summarised as follows:

• Obtain information about the environment, specifically the estimated activity concentrations of radionuclides in environmental media, and identify assessment species and their specific geometrical data.

• Derive the internal concentrations in the biota to be assessed, by application of concentration ratios. Ingestion and inhalation are described through the use of aggregated concentration ratios.

• Calculate internal and external exposures. Following the methodology recently adopted internationally, a simplified (ellipsoidal, see Figure 6-4) geometry representative of the dimensions of the main body of the organism is assumed in the derivation of dose conversion coefficients. Species-specific occupancies are also considered.

• Sum the contributions from external and internal exposure.

• Lastly, identify typical absorbed dose rates for reference organisms to be used in the compliance assessment.

Assessment species The selected assessment species for the Olkiluoto site are listed in Table 6-1 to Table 6-3, and discussed in detail in Haapanen et al. (2009). The selected species are typical of the Olkiluoto terrestrial area, sea area or in the lakes in the Reference area (Figure 1-3); they are based on expert judgement, and partially on available data, and cover the significant trophic levels (roles) in the food webs of the ecosystems prevailing and expected at the site. The names of the respective reference organisms in the ERICA approach are given in the table for comparison. The assessment species “tree” has been divided into the stem below the crown and the crown including the upper part of the stem.

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Figure 6-3. General process for dose assessment for the other biota; for further explanations, see section 6.2.2.

Figure 6-4. Illustrative picture of the applied simplified geometry and the exposure pathways considered (external radiation; combined ingestion and inhalation); drawing by Ari Ikonen/Posiva Oy.

Environmental radioactivity

concentrations (soil, sediment, water)

Total ecosystem exposure

Typical absorbed dose rates

Internal concentrations

External exposure

Internal exposure

Simplified geometry (ellipsoid)

Transfer factors (agg.)Concentration ratios

Occupancy habits Simplified geometry (ellipsoid)

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Table 6-1. Site-relevant data for terrestrial assessment species for Olkiluoto site and the respective ERICA reference organisms (Beresford et al. 2007).

Assessment species ERICA reference organism Herbivorous invertebrate, Ringlet flying insect Herbivorous bird, Hazel grouse bird Herbivorous rodent, Bank vole mammal (rat) Herbivorous mammal, Mountain hare mammal (rat) Large herbivorous mammal, Moose mammal (deer) Omnivorous invertebrate, Ant - Omnivorous reptile/amphibian, Common frog amphibian Insectivorous/omnivorous bird, Hooded crow bird Omnivorous mammal, Red fox mammal (rat) Large omnivorous mammal, Brown bear (a) mammal (deer) Carnivorous invertebrate, Carabid beetle - Carnivorous reptile/amphibian, Viper reptile Carnivorous bird, Tawny owl bird Carnivorous mammal, American mink mammal (rat) Decomposer, Earthworm soil invertebrate Moss, Red-stemmed feather-moss, bryophyte Lichen, Reindeer lichen lichen Herb (b), May lily herb Herb (b), Bracken herb Grass, Wavy hair-grass grass Shrub, Bilberry shrub Tree/stem of tree below crown tree Tree/crown of tree tree

(a) Specific case due to the hibernation; spends a large part of the year in the soil. Not currently present at Olkiluoto, but the site is peripheral to the present area of distribution.

(b) For herbs, two assessment species are given to cover the variability.

Table 6-2. Site-relevant data for freshwater assessment species for Olkiluoto site and the respective ERICA reference organisms (Beresford et al. 2007).

Assessment species ERICA reference organism Phytoplankton, Anabaena flos-aquae phytoplankton Phytoplankton, Anabaena lemmermannii phytoplankton Phytoplankton, Tabellaria fenestrata phytoplankton Phytoplankton, Gonyostomum semen phytoplankton Vascular plant, Common reed vascular plant Zooplankton, Cladocera sp. zooplankton Insect larvae, Chironomus plumosus insect larvae Bivalve mollusc, Anodonta sp. bivalve mollusc Gastropod, a snail, Lymnaea peregra gastropod Gastropod, a snail, Planorbis planorbis gastropod Crustacean, Crayfish crustacean Benthic fish, Ruffe (benthic) fish Pelagic fish, Vendace (pelagic) fish Amphibian, Common frog amphibian Reptile, Grass snake reptile Bird, Mallard bird Mammal, Otter mammal

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Table 6-3. Site-relevant data for marine assessment species for Olkiluoto site and the respective ERICA reference organisms (Beresford et al. 2007).

Assessment species ERICA reference organism Phytoplankton, Chaetoceros wighamii phytoplankton Phytoplankton, Aphanizomenon sp. phytoplankton Macroalgae, Cladophora glomerata macroalgae Vascular plant, Common reed vascular plant Zooplankton Cladocera sp. zooplankton Benthic mollusc, Blue mussel benthic mollusc Benthic mollusc, Baltic macoma benthic mollusc Crustacean, Baltic prawn crustacean Benthic fish, Flounder (benthic) fish Pelagic fish, Baltic herring (pelagic) fish Polychaete worm, a ragworm polychaete worm Bird, Oystercatcher (wading) bird Mammal, Grey seal mammal

6.2.3 Compliance assessment - other biota Guide YVL E.5 (STUK 2009) requires that typical radiation exposures to terrestrial and aquatic population shall be derived, and further states that:

“the assessed exposures shall remain clearly below the levels which, on the basis of best available scientific knowledge, would cause decline in biodiversity or other significant detriment to any living population.”

The approach adopted in the present report is to assess the exposures to other living species in terms of the typical absorbed dose rates to identified assessment species. The approach to demonstrating that the environment is adequately protected and to assessing compliance with regulatory criteria is to compare the typical absorbed dose rates with internationally proposed screening values for the protection of biota against radiation in the environment. The screening values are used to screen out situations of no regulatory concern. Thus, if none of the typical absorbed dose rates that are calculated exceed the screening values, it can be stated, with a high degree of confidence, that any releases from the repository do not affect species of flora and fauna detrimentally. If derived typical absorbed dose rates do exceed the screening values, this means only that detrimental effects cannot be ruled out, and the assessment has to continue by performing a more detailed analysis to assess the level, and nature, of possible detrimental effects.

The screening levels applied in the present assessment are the organism group-specific screening values recommended by the PROTECT project (Andersson et al. 2008). In that project, screening values were derived for three broad groups of organisms, recognising that each group contains organisms that are likely to have a range of radiosensitivities. The estimated screening values, in the form of absorbed dose rates, applied in the present assessment are as follows:

• 2 μGy/h for vertebrates, • 70 μGy/h for plants, and • 200 μGy/h for invertebrates.

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7 MAIN FINDINGS The previous chapters have presented the methodology used in the biosphere assessment and a summary of the present properties and on-going processes at the Olkiluoto site. This chapter presents the main results from the terrain and ecosystem development modelling (section 7.1), landscape modelling (sections 7.2 and 7.3), and the assessment of radiological consequences (section 7.4). The results presented in this chapter address only the realistic biosphere calculation cases (section 2.1.3); results from the analysis of sensitivity biosphere calculation cases are presented in chapter 8. It should be stressed that neither the landscape model, the biosphere object modules, nor the code for the dose assessment process for humans have yet been fully verified. These models and codes will be verified for the 2012 assessment.

7.1 Terrain and ecosystem forecasts During the biosphere assessment time window (from year 2 020 to 12 020), the coastline will be displaced away from the Olkiluoto site (Figure 7-1) due to continuing land uplift even if global average sea level rises as a result of warmer climate, although in this case the apparent land uplift would be slower than indicated in Figure 7-1. As a result, the surface environment will change and the increased freshwater infiltration, together with the corresponding decreased contribution from seawater, will change the groundwater composition. No great change in the biota present at the site is expected, although anthropogenic warming may introduce some new species from further south, and also lead to an increase in the length of the growing season. In the longer term, peatlands will become abundant both by primary mire formation and by overgrowth of shallow water bodies, unless future land use disturbs the natural vegetation succession.

7.2 Landscape model applied The applied landscape model is fully documented in Hjerpe & Broed (2010) and summarised in this section.

7.2.1 Biosphere objects The landscape model is comprised of biosphere objects, delineation of which is based on the forecasts from TESM. As discussed in section 5.1.1 a biosphere object is described by one ecosystem type, or more than one if the object is divided into sub-objects, where each object is associated with a corresponding radionuclide transport model (biosphere object modules, described in section 5.3). Each biosphere object has an exchange of radionuclides during the assessment time window due to the fact that they together occupy the same modelled area, and that the individual ecosystem types inside the object often change over time due to the terrain development. For example, an area characterised by a forest might have been developed from sea bottom sediment, and consequently, inherited the activity inventory that existed in the sediment. Table 7-1 presents the time-dependent ecosystem evolution for selected biosphere objects. This inheritance of activity inventory from one shrinking ecosystem to a growing ecosystem was implemented by taking the areal rate of change divided by the area of the shrinking object.

88

Figure 7-1. Predicted evolution of the sea level, croplands and surface water bodies at four time steps, with the present coastline as a grey line. Map layout by Jani Helin/ Posiva Oy.

89

On the basis of the nine types of delineated ecosystems, each biosphere object consists of one or more of the following types: lake, river, coast, forest, cropland, wetland (with two possible types of vegetation: mire and reed). In addition to these ecosystem types, a separate system was implemented in the landscape model for the atmospheric air part, shared by all terrestrial ecosystems. This air system is only used when modelling the plant-air gaseous exchange, a process specific for the C-14 model.

When constructing biosphere objects in the landscape model, all sub-objects that will occur during the assessment time window were implemented and connected as a sequential chain with respect to any incoming flux of radionuclides. Consequently, all sub-objects within a biosphere object may not exist at all times. Each individual sub-object has a mechanism that instantaneously passes through any incoming flux of radionuclides when it does not exist (not yet formed or has been developed into another ecosystem type) and takes up incoming radionuclides if the ecosystem does exist. The incoming flux of radionuclides could either originate from an upstream biosphere object, from a direct release of radionuclides, or a mix of both. Using this approach it is possible to describe the ecosystem development in time for all biosphere objects in the model.

7.2.1 Landscape model structure The landscape model is presented in detail in Hjerpe & Broed (2010), and summarised here. Figure 7-2 schematically shows the landscape model at the end of the biosphere assessment time window (year 12 020). The present-day coastline is shown as a grey line and it can be seen from the figure that most of the objects are currently under sea. Figure 7-3 shows the landscape model, also at year 12 020, with the three realistic release patterns (Table 5-1) included. The total number of biosphere objects in the landscape model is 70, and the total number of interconnected sub-objects is 166; the distribution of ecosystem types of the sub-objects is as follows:

• Forest 24 sub-objects • Wetland 19 sub-objects • Cropland 15 sub-objects • Lake 11 sub-objects • River 29 sub-objects • Coast 68 sub-objects

Due to the complexity and scope of the model, the model has been split into smaller “sub-models”. The whole landscape model was first split into two main water flow paths, one representing the water flow on the northern and the other the southern part of the present-day Olkiluoto Island. A third western part was also identified, taking the sum of the northern and southern water flow paths as influx. Splitting the model in three parts is possible, under the assumption that any releases to the northern route would not affect the southern, and vice versa. By using this approach, the model became numerically stable, and it significantly reduced the overall required simulation time.

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Table 7-1. Ecosystem evolution paths for selected biosphere objects. (B) Baltic coast, (C) Cropland, (F) Forest, (R) River, (L) Lake, (BC) Baltic coast and cropland, (BF) Baltic coast and forest, (BR) Baltic coast and river, (Lf) Lake, partly dried into forest, (Lfw) Lake, partly overgrown by vegetation into forest and wetland.

Object Yea

r20

20

2520

3020

3520

4020

4520

5020

5520

6020

6520

7020

… 1252

0

Marikari BC BC BC C C C C C C C C C CMäntykarinmaa B B BC C C C C C C C C C CKoskelonpelto B BC C C C C C C C C C C CLepänmaa B B BC C C C C C C C C C CLiiklanpelto B BC BC C C C C C C C C C CRoopenmaa 3 B B B B B B B B B BC C C CTelakka BF BF BF F F F F F F F F F FSatama BF F F F F F F F F F F F FKiskarinsivu B BF F F F F F F F F F F FKiskarintaka B F F F F F F F F F F F FMäntykarinedus B B BF F F F F F F F F F FFlutanmetsä BF F F F F F F F F F F F FLapinjoki S B R R R R R R R R R R R RLapinjoki N B BR R R R R R R R R R R REurajoki E B B B R R R R R R R R R REurajoki W B B B R R R R R R R R R RSusijoki B B B BR R R R R R R R R RKallanjoki B B B B BR R R R R R R R RTuomonjoki B R R R R R R R R R R R RKaunisjoki B B B BR BR R R R R R R R RTankarienjärvi B B B L L L L L L L L L LMäntykarinjärvi B B B L Lf Lfw Lfw Lfw Lfw Lfw Lfw Lfw LfwSusijärvi B B B B L L L L L L L L LLiiklanjärvi B B B L L L L L L L L L LLiponjärvi B B B L Lf Lf Lf Lf Lfw Lfw Lfw Lfw Lfw

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Figure 7-2. Schematic figure of the landscape model at year 12 020 (grey line shows present coastline). Map by Jani Helin/Posiva Oy.

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Figure 7-3. Schematic figure of the three realistic release patterns applied in the landscape modelling (grey line shows present coastline). The size of the circles represents the fraction of the releases directed to the biosphere object in question. Map layout by Jani Helin/Posiva Oy and Thomas Hjerpe/S&R Oy Table 7-2. Set of repository calculation cases included in the biosphere assessment.

Case name Case type Origin Sh1 Base case RNT-2008 Sh1-EPR Base case variant RNT-2008 Sh1-VVER Base case variant RNT-2008 PD-BC Base case KBS-3H SH-sal50 Base case (a) TILA-99 Sh1 Fd Sensitivity case RNT-2008 Sh1 Irf Sensitivity case RNT-2008 Sh1 Q Sensitivity case RNT-2008 Sh1 Sal Sensitivity case RNT-2008 Sh4 Sensitivity case RNT-2008 Sh4 Q Sensitivity case RNT-2008 PD-EXPELL Variant case KBS-3H

(a) This classification was not used in TILA-99 (Vieno & Nordman 1999); here the case most resembling Sh1 is selected.

Realistic-A

Realistic-B

Realistic-C

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7.3 Radionuclide transport This section presents the main findings from the screening evaluation and the landscape modelling, applied to the repository calculation cases. Following the discussion of treatment of repository calculation cases in section 2.1.3, the list of cases addressed in the current assessment contains 12 cases (Table 7-2). All cases addressed here have their origin in the same type of repository scenario, assuming releases from a single canister with an initial penetrating defect at the time of emplacement. The full descriptions of the cases are presented in Nykyri et al. (2008), Smith et al. (2007) and Vieno & Nordman (1999), for the RNT-2008, KBS-3H and TILA-99 cases, respectively. The main assumptions and differences between the repository cases addressed in the present report are summarised in Table 7-3.

It should be emphasised that the PD-EXPELL case is included in the screening evaluation, which was the case with release of several radionuclides resulting in highest33

Table 2-4

annual effective doses to most exposed persons in the KBS-3H safety studies (Broed et al. 2007). The reason for including this case is to better identify key radionuclides for a KBS-3 repository, regardless of design alternative. The assumptions underpinning the PD-EXPELL case (gas-induced displacement of radionuclide-contaminated water from the canister interior through the defect) are highly hypothetical when assessing a KBS-3V repository (Nykyri et al. 2008). Nonetheless, even though the likelihood of releases caused by this process is very small, a repository calculation case of this type (denoted GASexW) is included as a “what if” case for a KBS-3V repository (Nykyri et al. 2008). Consequently, following the logic in , the GASexW case is excluded from the dose assessment in the present assessment, addressing a KBS-3V repository.

Screening results concerning cases originating from other sources than RNT-2008 are considered as a main finding in the present assessment and are included in this chapter. However, the estimated radiological consequences from these cases are derived primarily to assess the impact on the outcome of the assessment due to differences between the landscape model and dose assessment processes applied in the present assessment and the ones used in previous analyses (addressed in section 8.2).

7.3.1 Screening evaluation The screening models have been applied to the repository calculation cases in Table 7-2 to screen out the radionuclides considered to be insignificant for the biosphere assessment, from a radiological consequences point of view. Results from the screening evaluation are presented in detail in Hjerpe & Broed (2010). Of the 35 radionuclides included in the full set of radionuclides in the repository calculation cases, 11 are screened out at Tier 1, and a further 13 at Tier 2. The remaining 11 radionuclides (the key set of radionuclides) and their resulting Tier 2 RQs are summarised in Table 7-4 and Table 7-5. It is notable that all actinides and radionuclides in the naturally occurring

33 PD-VOL1 resulted in slightly higher dose maximum in the KBS-3H biosphere analysis. This case contains only a release of C-14, and, since C-14 is a key radionuclide also in many other cases, it is excluded from the screening analysis.

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Table 7-3. Brief descriptions of the repository calculation cases addressed in the biosphere assessment.

Case name Brief description Sh1 General assumptions

- The base case (most realistic) in the defective canister scenario (DCS-II) - A hole with 1 mm diameter in the copper overpack reaching the insert is

assumed - The defect time (the time when water enters a canister through a defect

and the dissolution of fuel matrix starts) is 0 (a) years - Default value used for groundwater flow (near-field flow rates and the

far-field transport resistances that are selected as base values from the results of the EPM and DFN modelling

- Solubility limits and distribution coefficients (Kd) for buffer and backfill correspond to dilute/brackish groundwater

- The reference spent fuel is based on BWR fuel from the Olkiluoto 1-2 reactor units

Key differences compared with Sh1 Sh1-EPR - The reference spent fuel applied is based on EPR fuel from the

Olkiluoto 3 reactor unit Sh1-VVER - The reference spent fuel applied is based on VVER fuel from the

Loviisa 1-2 reactor units Sh1 Fd - A ten times higher fuel degradation rate is assumed Sh1 Irf - Only the radionuclides in the instant release fraction (b) are released Sh1 Q - Higher flow rates in all release routes are assumed Sh1 Sal - Saline groundwater assumed Sh4 - A hole with 4 mm diameter in the copper canister is assumed Sh4 Q - A hole with 4 mm diameter in the copper canister in conjunction with

higher flow rates for all release routes is assumed, PD-BC - Calculation case for a KBS-3H repository

- It is assumed to take 1000 years for contact of water with the fuel/metallic parts to take place and for transport pathways to be established.

PD-EXPELL - Calculation case for a KBS-3H repository - Gas generated inside a defective canister has an impact on radionuclide

transport - The gas-driven water pulse begins 2 800 years after deposition

(year 4 820) and lasts for 1 300 years. SH-sal50 - A ‘pinpoint’ hole with 5 mm2 area in the copper overpack

- Saline groundwater (a) Assumed to correspond to year 2020 in the present assessment, the emplacement time of the first

canister (b) Following canister failure and contact of the fuel with water, there will be a relatively rapid release to

solution of the radionuclide inventory at grain boundaries and in gaps; this part of the radionuclide inventory is termed the instant release fraction

95

Table 7-4. RQs exceeding 1 in the screening evaluation for the analysed repository calculation cases (base cases and base case variants).

Base cases and base case variants Case name Assessment

Sh1 KBS-3V

Sh1-EPR KBS-3V

Sh1-VVER KBS-3V

PD-BC KBS-3H

SH-sal50 TILA-99

I-129 580 700 620 77 000 8 600 Cl-36 120 130 130 18 000 810

Cs-135 - - - - 46 Se-79 - - - - 170

Sn-126+d - - - - 2 400 C-14 11 11 12 250 32

Sr-90+d - - - - 140

Table 7-5. RQs exceeding 1 in the screening evaluation for the analysed repository calculation cases (sensitivity and variant cases).

Sensitivity cases and variant cases Case name Assessment

Sh1 Fd KBS-3V

Sh1 Irf KBS-3V

Sh1 Q KBS-3V

Sh1 Sal KBS-3V

Sh4 KBS-3V

Sh4 Q KBS-3V

PD-EXPELL KBS-3H

Mo-93+d - - - - - - 1 028 000 I-129 800 570 610 580 3 600 3 700 655 000 Cl-36 170 12 140 130 780 870 160 000

Cs-135 - - 5 700 - - 78 500 -

Se-79 - - - 29 - - 2 600 Sn-126+d - - - - - - 880

C-14 15 - 16 11 130 200 16 200 Sr-90+d - - 3 2 - 44 -

Pd-107 - - - - - - 100 Nb-94 - - 2 - - 29 - Ni-59 - - - - - 8 -

decay chains are screened out. Further, it should also be noted that the generic screening absorbed dose rate for other biota is a factor of five higher than the lowest screening absorbed dose rate used in the compliance assessment (section 6.2.3); this will be taken into account in the future. However, the set of key radionuclides would have been the same if the environmental media concentration limits (EMCL), see section 5.2, had been a factor five lower in the screening evaluation (Hjerpe & Broed 2010).

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7.3.2 Landscape modelling The landscape model presented above (section 7.2) contains 166 connected sub-objects in 70 biosphere objects. Further, each biosphere object module (see section 5.3) is represented by a multi-compartment transport model. Consequently, when running the model, thousands of radionuclide-specific activity concentrations are produced. These results are then the key input when calculating radiation doses, both for humans and other biota.

This section presents only a few selected results from the realistic biosphere calculation case with releases from panel A for the repository base case Sh1. Figure 7-4 to Figure 7-6, show the activity concentrations for the top priority radionuclides (C-14, Cl-36 and I-129) in the key compartments for the dose calculations, for the biosphere objects Mäntykarinjärvi, Liiklanpelto and Kaunisjoki. These objects are selected on the basis that they are important for the resulting annual dose maxima (see Table 7-9 and Table 7-10). The key compartments for the dose calculations are (c.f. Figure 5-7 and Figure 5-8): the rooted mineral soil layer for forests and croplands, the acrotelm for wetlands, and the active layer and the water column for aquatic objects.

There is a gap between the years 3 020 and 3 520 in the activity concentrations in Mäntykarinjärvi (Figure 7-4). The reason for this is how the inheritance of activity is treated when a coast object develops into a lake object. The coast is modelled to cease to exist at year 3 020 and the lake starts to exist at year 3 520. In the time in between, the residual activity and the geosphere releases entering the model in Mäntykarinjärvi are transferred to the biosphere object downstream.

For the two other biosphere objects, Kaunisjoki and Liiklanpelto, the situation is slightly different from Mäntykarinjärvi. The transition from coast object to their final ecosystem types (river for Kaunisjoki and cropland for Liiklanpelto) is modelled by two co-existing ecosystems in the same object. For example, at year 2 020 (see Figure 7-6 and Table 7-1) is Liiklanpelto a coast object and at year 3 520 it has developed into a cropland. In the time interval in between, two sub-objects, a coast and a cropland object co-exist in the Liiklanpelto object. The area of the cropland object is increasing as the area of the coast object is decreasing. During this time period of co-existing sub-objects, activity concentrations will be non-zero for both its sub-objects.

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Figure 7-4. Activity concentrations of C-14 (top), Cl-36 (middle) and I-129 (below) in Mäntykarinjärvi (results from the realistic biosphere calculation case with releases from panel A for the repository base case Sh1).

1.E-15

1.E-13

1.E-11

1.E-09

1.E-07

1.E-05

1.E-03

1.E-01

2020 4020 6020 8020 10020 12020

Year

Wetland acrotelm [Bq/kg]

Forest soil [Bq/kg]

Wetland reed [Bq/kg]

Lake sediment [Bq/kg]

Coast sediment [Bq/kg]

Lake water [Bq/m3]

Coast water [Bq/m3]

1.E-13

1.E-11

1.E-09

1.E-07

1.E-05

1.E-03

1.E-01

2020 4020 6020 8020 10020 12020

Year



Forest soil [Bq/kg]



Lake water [Bq/m3]

Coast water [Bq/m3]

1.E-16

1.E-14

1.E-12

1.E-10

1.E-08

1.E-06

1.E-04

1.E-02

2020 4020 6020 8020 10020 12020

Year



Forest soil [Bq/kg]



Lake water [Bq/m3]

Coast water [Bq/m3]

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Figure 7-5. Activity concentrations of C-14 (top), Cl-36 (middle) and I-129 (below) in Kaunisjoki (results from the realistic biosphere calculation case with releases from panel A for the repository base case Sh1).

1.E-11

1.E-09

1.E-07

1.E-05

1.E-03

1.E-01

1.E+01

2020 4020 6020 8020 10020 12020

Year



Lake water [Bq/m3]

Coast water [Bq/m3]

1.E-15

1.E-13

1.E-11

1.E-09

1.E-07

1.E-05

1.E-03

1.E-01

2020 4020 6020 8020 10020 12020

Year



Lake water [Bq/m3]

Coast water [Bq/m3]

1.E-15

1.E-13

1.E-11

1.E-09

1.E-07

1.E-05

1.E-03

1.E-01

2020 4020 6020 8020 10020 12020

Year



Lake water [Bq/m3]

Coast water [Bq/m3]

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Figure 7-6. Activity concentrations of C-14 (top), Cl-36 (middle) and I-129 (below) in Liiklanpelto (results from the realistic biosphere calculation case with releases from panel A for the repository base case Sh1).

1.E-13

1.E-11

1.E-09

1.E-07

1.E-05

1.E-03

2020 4020 6020 8020 10020 12020

Year

Cropland soil [Bq/kg]


Coast water [Bq/m3]

1.E-11

1.E-09

1.E-07

1.E-05

1.E-03

2020 4020 6020 8020 10020 12020

Year



Coast water [Bq/m3]

1.E-15

1.E-13

1.E-11

1.E-09

1.E-07

1.E-05

1.E-03

1.E-01

2020 4020 6020 8020 10020 12020

Year



Coast water [Bq/m3]

100

7.4 Radiological consequences analysis The main results from the radiological consequences analysis following the methodologies presented in chapter 6 are summarised in this section. Annual doses to humans are addressed in section 7.4.1, and typical absorbed dose rates to other biota in section 7.4.2.

7.4.1 Annual doses to humans The geometrical properties of the landscape model (section 7.2), the resulting activity concentrations (section 7.3.2) and ecosystem-specific productivities and aggregated concentration ratios (section 3.3.4) are the key input, resulting from the three preceding sub-processes in the biosphere assessment process, when deriving annual doses to humans. This section summarises the annual landscape doses, based on the methodology in section 6.1.1, for the realistic biosphere calculation cases (section 2.1.3) applied on the nine repository calculation cases for a KBS-3V repository (cases origin from RNT-2008 in Table 7-2). Further, the safety indicators, the “well doses”, are presented at the end of this section.

Annual landscape doses The annual landscape dose maxima to representative persons for the most exposed group and other exposed people, Egroup and Epop, are summarised in Table 7-6 for the 27 realistic biosphere calculation cases resulting from the 9 repository calculation cases. The annual landscape dose maximum to a representative person for the most exposed group, Egroup, ranges from about 5x10-7 to 3x10-5 mSv. The annual landscape dose maximum to a representative person for other people, Epop, ranges from about 1x10-8 to 5x10-6 mSv. The repository calculation case resulting in the highest doses is the same, Sh4 Q, for both Egroup and Epop. However, the highest dose for Egroup is caused by releases from panel C (Table 7-7) and the highest dose for Epop is caused by releases from panel A (Table 7-8). More details for the realistic biosphere calculation cases resulting from the repository base cases (Sh1) and the repository case resulting in highest doses (Sh4 Q) are presented in the following Tables and Figures:

• Table 7-7 and Table 7-8 present the pathway- and radionuclide-specific contributions to Egroup and Epop maxima,

• Table 7-9 and Table 7-10 present the dominating biosphere objects in Egroup and Epop maxima,

• Figure 7-7 and Figure 7-8, show Egroup and Epop over the whole biosphere assessment time window,

• Figure 7-9 and Figure 7-10 show the dose distribution for the 2001 most exposed individuals in four selected cases (Sh1 and Sh4 Q analysed with a realistic biosphere calculation case with releases from panels A and C),

• Figure 7-11 and Figure 7-12 show the relative contributions to Egroup and Epop from the exposure pathways considered, for the repository base case Sh1, analysed with the realistic biosphere calculation cases with releases from all three repository panels, and

• Figure 7-13 to Figure 7-16 show both the total and radionuclide-specific annual landscape doses for Egroup and Epop for the repository cases Sh1 and Sh4 Q,

101

analysed with the realistic biosphere calculation cases with releases from all three repository panels.

A few selected observations regarding the results presented in this section are made below:

• The Egroup maxima occur generally at the end of the biosphere assessment time window (see Table 7-6). This is mainly due to the behaviour of the geosphere release rates of the dominating radionuclides (C-14, Cl-36 and I-129); in most repository calculation cases addressed in this report, the geosphere release rates increase during the biosphere assessment time window, and have release rate maxima beyond year 12 020. One exception is the Sh4 Q case (assuming radionuclide release from panel A), where the maximum is around year 6 600. The reason for this is that the C-14 release from the geosphere is more prominent than in other cases. The C-14 geosphere release rate maxima occur around year 5 000 (Nykyri et al. 2008), leading to Egroup having a first period of higher doses due to the C-14 release (about between years 3 000 to 6 000), then decreasing, then starting to increase again due to the increased geosphere releases of Cl-36 and I-129 (see for example Figure 7-14).

• The Epop maxima occur often in the time period between year 3 500 and 4 000 (see Table 7-6). This is due to Epop being in general dominated by C-14. Thus the dose maxima occur in the period of higher doses between about years 3 000 to 6 000 mentioned above. However, for Epop, the maxima are often in the early part of this period. The reason for this is that the landscape dose from water consumption (EL,W) plays a significant role for Epop. For the cases with Epop maxima around year 3 500, the EL,W is due to the rivers Kaunisjoki or Susijoki (Table 7-10), which are the first rivers downstream from the objects receiving geosphere release. They are developed around year 3 520, and are shortest when first developed. This leads to activity concentrations, and thus EL,W, that are highest when they have just developed.

• Egroup is dominated by the food ingestion exposure pathway in the major part of the time window (see Table 7-7 and Figure 7-11). Radionuclide releases from panels B and C have a time period, between years 3 520 and 4 520, during which the water ingestion pathway dominates the annual landscape doses (EALD). From the beginning, up to year 3 520, EALD is generally very low (see Figure 7-4), and is dominated by the landscape dose from food ingestion (EL,F) since the landscape dose from water ingestion (EL,W) is zero (no lakes have been developed, and the few existing rivers do not get contaminated). Later, beyond year 3 520, the three lakes Tankarienjärvi, Mäntykarinjärvi and Liiklanjärvi will be developed and almost all geosphere releases (originating from panels B and C) are routed into them, resulting in EL,W dominating. Further, at year 4 020 the forest Mäntykarinjärvi develops from areas of the lake Mäntykarinjärvi that are dried out. This forest then receives direct geosphere releases, and produces a EL,F greater than the highest EL,W during the rest of the time window. Radionuclide release from Panel A results in a slightly different behaviour, EL,W contributes less to EALD during the whole time window. The reason is that the object Liiklanpelto

102

receives 8% of the geosphere releases, and Liiklanpelto will be developed from coast to cropland already around year 2 520.

• Following the formation of Lake Mäntykarinjärvi, part of the lake dries out and develops into a forest part (as mentioned above) and a wetland part. These terrestrial sub-objects of Mäntykarinjärvi dominate the dose to most individuals in the most exposed group, at the time of dose maxima, for five of the six cases presented in Table 7-9. For the remaining case (Sh4 Q – releases from panel A), the first cropland downstream (Roopenmaa 3) from lake Liiklanjärvi (the main receptor of geosphere releases) dominates the dose.

• The exposure pathway has a more significant role for Epop than for Egroup maxima (compare Table 7-7 and Table 7-8). This is a consequence of the most exposed group consuming a large part of the contaminated edibles, and in some cases even everything.

• Before year 3 520 are time periods when Epop is zero (see for example Figure 7-12 and Figure 7-15). The reason for this is that the exposed population is small, just a few tens of people. It is considered that they all are members of the most exposed group, thus the number of individuals in the group for ‘other people’ is zero.

• The radionuclides totally dominating the annual landscape doses in all biosphere calculation cases applied to Sh1 and Sh4 Q are I-129, C-14 and Cl-36 (see Table 7-7, Table 7-8). These are the same three as are nominated as top priority radionuclides (section 2.4) based on the screening evaluation. The same three radionuclides dominate also in all other analysed cases, though for the sake of clarity the results are not explicitly included in the present report.

103

Table 7-6. Annual landscape dose maxima to a representative person for the most exposed group, (Egroup) and other people (Epop) derived with the realistic biosphere calculation cases, the year the maxima occur and the number of exposed individuals in the groups.

Case Egroup [mSv]

Year

Ngroup Epop [mSv]

Year

Npop

Panel A Sh1 7.9 x 10-7 11 920 50 1.2 x 10-7 3 970 3 269 Sh1-EPR 1.1 x 10-6 11 920 50 1.7 x 10-7 3 970 3 269 Sh1-VVER 8.6 x 10-7 11 920 50 1.4 x 10-7 3 970 3 269 Sh1 Fd 8.3 x 10-7 11 920 50 1.2 x 10-7 3 970 3 269 Sh1 Irf 4.8 x 10-7 11 970 50 3.4 x 10-8 4 420 3 596 Sh1 Q 1.1 x 10-6 6 570 50 3.9 x 10-7 12 020 3 203 Sh1 Sal 7.9 x 10-7 11 920 50 3.4 x 10-7 3 970 3 269 Sh4 6.9 x 10-6 8 520 50 1.5 x 10-6 3 970 3 269 Sh4 Q 1.4 x 10-5 6 570 50 4.7 x 10-6 3 970 3 269

Panel B

Sh1 1.6 x 10-6 11 870 50 2.0 x 10-8 12 020 5 309 Sh1-EPR 2.1 x 10-6 11 870 50 3.7 x 10-8 3 570 3 299 Sh1-VVER 1.7 x 10-6 11 870 50 3.3 x 10-8 3 570 3 299 Sh1 Fd 1.6 x 10-6 11 920 50 3.1 x 10-8 3 570 3 299 Sh1 Irf 1.0 x 10-6 11 970 50 9.7 x 10-9 3 620 3 295 Sh1 Q 2.0 x 10-6 11 820 50 5.7 x 10-8 3 570 3 299 Sh1 Sal 1.6 x 10-6 11 870 50 3.1 x 10-8 3 570 3 299 Sh4 9.7 x 10-6 11 870 50 1.3 x 10-7 12 020 5 309 Sh4 Q 1.2 x 10-5 11 820 50 2.0 x 10-7 3 570 3 299

Panel C

Sh1 3.9 x 10-6 11 870 50 2.9 x 10-8 3 570 3 299 Sh1-EPR 5.3 x 10-6 11 870 50 3.6 x 10-8 12 020 5 309 Sh1-VVER 4.2 x 10-6 11 870 50 3.1 x 10-8 3 570 3 299 Sh1 Fd 4.1 x 10-6 11 920 50 2.9 x 10-8 3 570 3 299 Sh1 Irf 2.5 x 10-6 11 970 50 1.3 x 10-8 12 020 5 309 Sh1 Q 5.0 x 10-6 11 820 50 1.3 x 10-7 12 020 5 309 Sh1 Sal 3.9 x 10-6 11 870 50 9.8 x 10-8 12 020 5 309 Sh4 2.5 x 10-5 11 870 50 1.1 x 10-6 12 020 5 309 Sh4 Q 3.1 x 10-5 11 820 50 4.5 x 10-7 3 920 3 272

104

Table 7-7. Annual landscape dose maxima to a representative person for the most exposed group, (Egroup) derived with the realistic biosphere calculation cases, the year the maxima occur, the contribution to the dose maxima from different exposure pathways, and contributions from dominating radionuclides (>0.1%), for the repository base case (Sh1) and the case resulting in the highest landscape dose maxima (Sh4 Q).

Case Egroup [mSv]

Year

FI (a) [%]

WI (b) [%]

I-EE (c) [%]

RN-specific [mSv]

[%]

Panel A Sh1 7.9 x 10-7 11 920 93.8 6.2 0.0 I-129 4.3 x 10-7 54.2 Cl-36 3.6 x 10-7 45.6 C-14 1.3 x 10-9 0.2 Sh4 Q 1.4 x 10-5 6 570 96.4 3.6 0.0 C-14 1.4 x 10-5 99.3 Cl-36 5.4 x 10-8 0.4 I-129 4.0 x 10-8 0.3 Panel B Sh1 1.6 x 10-6 11 870 99.1 0.9 0.0 I-129 9.0 x 10-7 57.7 Cl-36 6.6 x 10-7 42.3 Sh4 Q 1.2 x 10-5 11 820 99.0 1.0 0.0 I-129 6.6 x 10-6 53.2 Cl-36 5.7 x 10-6 46.5 C-14 7.5 x 10-9 0.1 Panel C Sh1 3.9 x 10-6 11 870 99.7 0.3 0.0 I-129 2.3 x 10-6 58.9 Cl-36 1.6 x 10-6 41.1 Sh4 Q 3.1 x 10-5 11 820 99.7 0.3 0.0 I-129 1.7 x 10-5 54.5 Cl-36 1.4 x 10-5 45.2 Cs-135 6.5 x 10-8 0.2

(a) FI – contribution to the dose maxima from food ingestion, (b) WI – contribution to the dose maxima from water ingestion (c) I-EE – contribution to the dose maxima from inhalation and external exposure

105

Table 7-8. Annual landscape dose maxima to a representative person for other people, (Epop) derived with the realistic biosphere calculation cases, the year the maxima occur, the contribution to the dose maxima from different exposure pathways, and contributions from dominating radionuclides (>0.1%), for the repository base case (Sh1) and the case resulting in the highest landscape dose maxima (Sh4 Q).

Case Epop [mSv]

Year

FI (a) [%]

WI (b) [%]

I-EE (c) [%]

RN-specific [mSv]

[%]

Panel A Sh1 1.2 x 10-7 3 970 33.3 66.7 0.0 C-14 1.0 x 10-7 84.1 I-129 1.7 x 10-8 13.8 Cl-36 2.7 x 10-9 2.2 Sh4 Q 4.7 x 10-6 3 970 31.6 68.4 0.0 C-14 4.4 x 10-6 93.6 I-129 2.6 x 10-7 5.5 Cl-36 4.3 x 10-8 0.9 Panel B Sh1 2.0 x 10-8 12 020 30.7 69.3 0.0 Cl-36 1.6 x 10-8 77.1 I-129 4.2 x 10-9 20.8 C-14 4.1 x 10-10 2.0 Sh4 Q 2.0 x 10-7 3 570 0.0 100 0.0 I-129 2.0 x 10-7 99.2 Cl-36 1.5 x 10-9 0.8 Panel C Sh1 2.9 x 10-8 3 570 0.0 100 0.0 C-14 2.9 x 10-8 99.7 Cl-36 9.2 x 10-11 0.3 Sh4 Q 4.5 x 10-7 3 920 0.0 100 0.0 C-14 4.3 x 10-7 95.2 I-129 1.6 x 10-8 3.5 Cl-36 5.9 x 10-9 1.3

(a) FI – contribution to the dose maxima from food ingestion (b) WI – contribution to the dose maxima from water ingestion (c) I-EE – contribution to the dose maxima from inhalation and external exposure

106

Table 7-9. The biosphere objects and ecosystem types dominating the pathway-specific doses in the annual landscape dose maxima to a representative person for the most exposed group, (Egroup), for the repository base case (Sh1) and the case resulting in the highest landscape dose maxima (Sh4 Q).

Case Food ingestion Water ingestion Inhalation and external exposure

Biosphere object Ecosystem type Biosphere object Ecosystem type Biosphere object Ecosystem type Panel A Sh1 Mäntykarinjärvi (a)

Liiklanjärvi (a) Mäntykarinjärvi (a) Mäntykarinjärvi

Wetland (b) Lake Lake (reed) Forest (b)

Liiklanjärvi Lake Mäntykarinjärvi Wetland (b)

Sh4 Q Mäntykarinjärvi (a)

Roopenmaa 3 Wetland (b) Cropland

Kaunisjoki River Mäntykarinjärvi Wetland (b)

Panel B Sh1 and Sh4 Q Mäntykarinjärvi (a)

Mäntykarinjärvi (a) Tankarinjärvi (a) Mäntykarinjärvi

Wetland (b) Lake (reed) Lake Forest (b)

Tankarinjärvi

Lake Mäntykarinjärvi Wetland (b)

Panel C Sh1 and Sh4 Q Mäntykarinjärvi (a)

Mäntykarinjärvi (a) Mäntykarinjärvi

Wetland (b) Lake (reed) Forest (b)

Tankarinjärvi

Lake Mäntykarinjärvi Wetland (b)

(a) Produces less edibles than one person’s annual demand (b) These wetlands and forests have developed from areas of the lake that have been overgrown by vegetation

107

Table 7-10. The biosphere objects and ecosystem types dominating the pathway-specific doses in the annual landscape dose maxima to a representative person for the other people, (Epop), for the repository base case (Sh1) and the case resulting in the highest landscape dose maxima (Sh4 Q).

Case Food ingestion Water ingestion Inhalation and external exposure

Biosphere object Ecosystem type Biosphere object Ecosystem type Biosphere object Ecosystem type Panel A Sh1

Liiklanpelto Cropland Kaunisjoki River Liiklanpelto Cropland

Sh4 Q Liiklanpelto Cropland Kaunisjoki River Liiklanpelto Cropland

Panel B Sh1 Mäntykarinjärvi (a) Forest Tankarinjärvi Lake Mäntykarinjärvi

Mäntykarinjärvi Wetland (a) Forest (a)

Sh4 Q - (b) Susijoki River - (c)

Panel C Sh1 - (b) Susijoki River - (c) Sh4 Q - (b) Kaunisjoki River - (c)

(a) These wetlands and forests have been developed from areas of the lake that have been overgrown by vegetation

(b) All contaminated edibles produced consumed by the most exposed group (c) No contaminated terrestrial objects

108

Figure 7-7. Annual landscape doses to a representative person for the most exposed group (Egroup) for the repository base case Sh1 and Sh4 Q (case resulting in highest landscape dose maxima), analysed with the realistic biosphere calculation cases with releases from panels A, B and C.

Figure 7-8. Annual landscape doses to a representative person for other people (Epop) for the repository base case Sh1 and Sh4 Q (case resulting in highest landscape dose maxima), analysed with the realistic biosphere calculation cases with releases from panels A, B and C.

1.E-09

1.E-08

1.E-07

1.E-06

1.E-05

1.E-04

2020 4020 6020 8020 10020 12020

Ann

ual l

ands

cape

dos

e [m

Sv]

Year

Sh4 Q (Panel A)

Sh1 (Panel A)

Sh4 Q (Panel C)

Sh1 (Panel B)

Sh4 Q (Panel B)

Sh1 (Panel C)

1.E-19

1.E-14

1.E-09

2020 3020 4020

1.E-10

1.E-09

1.E-08

1.E-07

1.E-06

1.E-05

2020 4020 6020 8020 10020 12020

Ann

ual l

ands

cape

dos

e [m

Sv]

Year

Sh1 (Panel A)

Sh4 Q (Panel C)

Sh1 (Panel B)

Sh4 Q (Panel B)

Sh1 (Panel C)

Sh4 Q (Panel A)

1.E-20

1.E-15

1.E-10

2020 3020 4020

109

Figure 7-9. The dose distributions for the repository base case Sh1 (top) and Sh4 Q (below), analysed with the realistic biosphere calculation cases with releases from panel A.

Ann

ual l

ands

cape

dos

e [m

Sv]

10-14

10-4

10-6

10-8

10-12

10-10

Ann

ual l

ands

cape

dos

e [m

Sv]

10-14

10-4

10-6

10-8

10-12

10-10

110

Figure 7-10. The dose distributions for the repository base case Sh1 (top) and Sh4 Q (below), analysed with the realistic biosphere calculation cases with releases from panel C.

Ann

ual l

ands

cape

dos

e [m

Sv]

10-13

10-3

10-5

10-7

10-11

10-9

Ann

ual l

ands

cape

dos

e [m

Sv]

10-13

10-3

10-5

10-7

10-11

10-9

111

Figure 7-11. Relative contributions to Egroup from inhalation and external exposure (Inh+Ext), ingestion of water (water), and ingestion of food (Food) for the repository base case Sh1 analysed with the realistic biosphere calculation cases with releases from panel A (top), B (middle) and C (below).

0%

20%

40%

60%

80%

100%

2020 3020 4020 5020 6020 7020 8020 9020 10020 11020 12020Year

Inh+Ext Water Food

0%

20%

40%

60%

80%

100%

2020 3020 4020 5020 6020 7020 8020 9020 10020 11020 12020Year

Inh+Ext Water Food

0%

20%

40%

60%

80%

100%

2020 3020 4020 5020 6020 7020 8020 9020 10020 11020 12020Year

Inh+Ext Water Food

112

Figure 7-12. Relative contributions to Epop from inhalation and external exposure (Inh+Ext), ingestion of water (water), and ingestion of food (Food) for the repository base case Sh1 analysed with the realistic biosphere calculation cases with releases from panel A (top), B (middle) and C (below).

0%

20%

40%

60%

80%

100%

2020 3020 4020 5020 6020 7020 8020 9020 10020 11020 12020Year

Inh+Ext Water Food

0%

20%

40%

60%

80%

100%

2020 3020 4020 5020 6020 7020 8020 9020 10020 11020 12020Year

Inh+Ext Water Food

0%

20%

40%

60%

80%

100%

2020 3020 4020 5020 6020 7020 8020 9020 10020 11020 12020Year

Inh+Ext Water Food

113

Figure 7-13. Total (Egroup) and radionuclide-specific annual landscape doses to a representative person for the most exposed group, for the repository base case Sh1 analysed with the realistic biosphere calculation cases with releases from panels A (top), B (middle) and C (below).

1.E-20

1.E-18

1.E-16

1.E-14

1.E-12

1.E-10

1.E-08

2020 4520 7020 9520 12020

Ann

ual l

ands

cape

dos

e [S

v]

Year

Egroup

C-14

Cl-36

I-129

Mo-93

Se-79

1.E-20

1.E-18

1.E-16

1.E-14

1.E-12

1.E-10

1.E-08

2020 4520 7020 9520 12020

Ann

ual l

ands

cape

dos

e [S

v]

Year

Egroup

C-14

Cl-36

I-129

Mo-93

Se-79

1.E-20

1.E-18

1.E-16

1.E-14

1.E-12

1.E-10

1.E-08

2020 4520 7020 9520 12020

Ann

ual l

ands

cape

dos

e [S

v]

Year

Egroup

C-14

Cl-36

I-129

Mo-93

Se-79

114

Figure 7-14. Total (Egroup) and radionuclide-specific annual landscape doses to a representative person for the most exposed group, for the repository case Sh4 Q, analysed with the realistic biosphere calculation cases with releases from panels A (top), B (middle) and C (below).

1.E-19

1.E-17

1.E-15

1.E-13

1.E-11

1.E-09

1.E-07

2020 4520 7020 9520 12020

Ann

ual l

ands

cape

dos

e [S

v]

Year

Egroup

C-14

Cl-36

Cs-135

I-129

Mo-93

Nb-94

Ni-59

Se-79

Sr-90

1.E-19

1.E-17

1.E-15

1.E-13

1.E-11

1.E-09

1.E-07

2020 4520 7020 9520 12020

Ann

ual l

ands

cape

dos

e [S

v]

Year

Egroup

C-14

Cl-36

Cs-135

I-129

Mo-93

Nb-94

Ni-59

Se-79

Sr-90

1.E-19

1.E-17

1.E-15

1.E-13

1.E-11

1.E-09

1.E-07

2020 4520 7020 9520 12020

Ann

ual l

ands

cape

dos

e [S

v]

Year

Egroup

C-14

Cl-36

Cs-135

I-129

Mo-93

Nb-94

Ni-59

Se-79

Sr-90

115

Figure 7-15. Total (Epop) and radionuclide-specific annual landscape doses to a representative person for other people, for the repository base case Sh1, analysed with the realistic biosphere calculation cases with releases from panels A (top), B (middle) and C (below).

1.E-22

1.E-20

1.E-18

1.E-16

1.E-14

1.E-12

1.E-10

1.E-08

2020 4520 7020 9520 12020

Ann

ual l

ands

cape

dos

e [S

v]

Year

Epop

C-14

Cl-36

I-129

Mo-93

Se-79

Sn-126

1.E-22

1.E-20

1.E-18

1.E-16

1.E-14

1.E-12

1.E-10

1.E-08

2020 4520 7020 9520 12020

Ann

ual l

ands

cape

dos

e [S

v]

Year

Epop

C-14

Cl-36

I-129

Mo-93

Se-79

1.E-22

1.E-20

1.E-18

1.E-16

1.E-14

1.E-12

1.E-10

1.E-08

2020 4520 7020 9520 12020

Ann

ual l

ands

cape

dos

e [S

v]

Year

Epop

C-14

Cl-36

I-129

Mo-93

Se-79

116

Figure 7-16. Total (Epop) and radionuclide-specific annual landscape doses to a representative person for other people, for the repository case Sh4 Q, analysed with the realistic biosphere calculation cases with releases from panels A (top), B (middle) and C (below).

1.E-19

1.E-17

1.E-15

1.E-13

1.E-11

1.E-09

1.E-07

2020 4520 7020 9520 12020

Ann

ual l

ands

cape

dos

e [S

v]

Year

Epop

C-14

Cl-36

Cs-135

I-129

Mo-93

Nb-94

Ni-59

Se-79

Sn-126

Sr-90

1.E-19

1.E-17

1.E-15

1.E-13

1.E-11

1.E-09

1.E-07

2020 4520 7020 9520 12020

Ann

ual l

ands

cape

dos

e [S

v]

Year

Epop

C-14

Cl-36

Cs-135

I-129

Mo-93

Nb-94

Ni-59

Se-79

Sr-90

1.E-19

1.E-17

1.E-15

1.E-13

1.E-11

1.E-09

1.E-07

2020 4520 7020 9520 12020

Ann

ual l

ands

cape

dos

e [S

v]

Year

Epop

C-14

Cl-36

Cs-135

I-129

Mo-93

Nb-94

Ni-59

Se-79

Sr-90

117

Safety indicators The two well scenarios (AgriWELL-2009 and WELL-2009) described in section 5.4 have been applied to derive safety indicators, using the geosphere releases in the set of repository calculation cases listed in Table 7-2. Only releases within the biosphere assessment time window have been considered; thus the time of dose maxima may deviate from the times in Nykyri et al. (2008). The maxima of the safety indicators (in terms of annual doses) are presented in Table 7-11 and Table 7-12. The safety indicators, during the whole time window, for the repository base case and the case resulting in the highest dose maxima in Nykyri et al. (2008) are plotted in Figure 7-17. The doses from the AgriWELL scenario are about 50% higher than the doses only taking the exposure pathway ingestion of drinking water into account. The annual dose maxima based on the well scenarios are about 10 times lower than the corresponding maxima for Egroup (see Table 7-6).

This is an expected result – assuming that the reasoning behind the effective mixing volume can be summarised as follows:

• In the documentation of the well scenarios, the detailed assumptions behind the applied effective mixing volume are not explicitly given. However, in earlier reports (for example Vieno & Nordman 1999, page 85) it is stated that the assumed value (called effective dilution volume) is obtained, for example, if 1% of the total releases from the repository into the biosphere end up in a well and the dilution of the well (well capacity) is 1 000 m3/y.

• Effective mixing volume can be seen as the well capacity, divided by the number of pathways for the radionuclide release to reach the well water, multiplied by the total number of pathways for the release to take through the geosphere.

• The number of pathways for the radionuclide release to reach the well water, dived by the total number of pathways is then the simplified release pattern for the well (as discussed in section 5.1.2 for the landscape model)

• Consequently , the well scenario applied in the present assessment, as well as in earlier assessments, can be considered to apply a "simplified release pattern", defined as 1% of the geosphere releases ending up in a well with a capacity of 1 000 m3/y.

Thus, compared with the landscape model, it may be considered that the well scenario is less cautious; since the simplified release pattern in the landscape model accounts for the whole release. This assumption, regarding the treatment of geosphere releases in the well scenarios, is a plausible explanation why the annual dose maxima based on the well scenarios are about 10 times lower than the corresponding maxima for Egroup.

A well with the capacity mentioned above is a reasonably sized well, appropriate to sustain a family with drinking water and supply water for irrigating a garden plot. However, a larger well would be needed to supply irrigation water also to crops and water animals, assuming a farm of the size assumed in the AgriWELL scenario. Then, changing the assumption to “100% of the geosphere release ends up in a well with the capacity of 100 000 m3/y” would result in the same effective mixing volume.

118

Table 7-11. Indicative annual dose maxima, during the time window of biosphere assessment, arising from the AgriWELL-2009 scenario, doses from dominating radionuclides and their relative contribution to the annual dose from drinking of water (WI) and intake of food (FI).

Case Annual dose [mSv]

Year

RN-specific dose [mSv]

WI FI

Base cases Sh1 2.4 x 10-7 9 920 C-14

I-129 Cl-36

1.1 x 10-7 1.1 x 10-7 1.6 x 10-8

32% 31%

2%

16% 16%

3%

Sh1-EPR 3.2 x 10-7 5 170 C-14 I-129 Cl-36

1.6 x 10-7 1.5 x 10-7 1.5 x 10-8

32% 31%

2%

16% 16% 3%

Sh1-VVER 2.6 x 10-7 9 870 C-14 I-129 Cl-36

1.2 x 10-7 1.2 x 10-7 1.2 x 10-8

32% 31%

2%

16% 16%

3%

Sensitivity cases Sh1 Fd 2.5 x 10-7 11 470 I-129

C-14 Cl-36

1.3 x 10-7 1.1 x 10-7 1.4 x 10-8

34% 28%

2%

17% 14% 4%

Sh1 Irf 1.2 x 10-7 12 020 I-129 C-14

Cl-36

1.2 x 10-7 5.5 x 10-9

1.7 x 10-9

63% 3%

-

32% 2% 1%

Sh1 Q 3.0 x 10-7 5 820 C-14 I-129 Cl-36

1.7 x 10-7 1.2 x 10-7 7.9 x 10-9

38% 27%

1%

19% 13% 2%

Sh1 Sal 2.4 x 10-7 9 920 C-14 I-129 Cl-36

1.1 x 10-7 1.1 x 10-7 1.1 x 10-8

32% 31%

1%

16% 16% 3%

Sh4 2.2 x 10-6 8 570 C-14 I-129 Cl-36

1.4 x 10-6 6.6 x 10-7 5.7 x 10-8

44% 20%

1%

22% 10% 2%

Sh4 Q 3.0 x 10-6 5 170 C-14 I-129 Cl-36

2.2 x 10-6 7.6 x 10-7 4.3 x 10-8

49% 17%

-

25% 8%

1%

It should be kept in mind that the aim safety indicators in the present assessment is to support the safety case by building understanding of, and confidence in, the outcome and conclusions of the safety assessment, in terms of indicative hypothetical annual doses received by a representative member of the most exposed people. Furthermore, “well doses” are used to obtain indicative annual effective doses beyond the time window of biosphere assessment. Thus, it would be preferable if the level of conservatism in safety indicators were to be higher than for the primary quantities used in the compliance assessment; this is further addressed in section 10.3.

119

Table 7-12. Indicative annual dose maxima, during the time window of biosphere assessment, arising from the WELL-2009 scenario, and doses from dominating radionuclides


Year


Base cases Sh1 1.5 x 10-7 9 870 C-14

I-129 Cl-36

7.5 x 10-8 7.3 x 10-8 3.6 x 10-9

49% 48%

2%

Sh1-EPR 2.1 x 10-7 9 870 C-14 I-129 Cl-36

1.0 x 10-7 1.0 x 10-7 5.0 x 10-9

49% 48%

2%

Sh1-VVER 1.7 x 10-7 9 870 C-14 I-129 Cl-36

8.2 x 10-8 8.1 x 10-8 3.9 x 10-9

49% 48%

2%

Sensitivity cases Sh1 Fd 1.6 x 10-7 11 470 I-129

C-14 Cl-36

8.6 x 10-8 7.1 x 10-8 4.5 x 10-9

53% 44%

3%

Sh1 Irf 8.0 x 10-8 12 020 I-129 C-14

Cl-36

7.6 x 10-8 3.8 x 10-9

5.5 x 10-10

95% 5% 1%

Sh1 Q 2.0 x 10-7 5 820 C-14 I-129 Cl-36

1.1 x 10-7 8.1 x 10-8 2.5 x 10-9

58% 41%

1%

Sh1 Sal 1.5 x 10-7 9 870 C-14 I-129 Cl-36

7.5 x 10-8 7.3 x 10-8 3.6 x 10-9

49% 48%

2%

Sh4 Q 2.0 x 10-6 5 170 C-14 1-129 Cl-36

1.5 x 10-6 5.0 x 10-7 1.4 x 10-8

74% 26%

1%

120

Figure 7-17. Annual doses from the two well scenarios, for the base case (Sh1) and the case resulting in highest dose maxima (Sh4 Q) from Nykyri et al. (2008). 7.4.2 Typical absorbed dose rates to other biota The geometrical properties of the assessment species (presented in Hjerpe & Broed (2010), based on Table 11-23 in Haapanen et al. (2009)), the resulting activity concentrations (section 7.3.2) and concentration ratios (Hosseini et al. 2008, Beresford et al. 2008) are the key data input when deriving typical absorbed dose rates to other biota. In this section the typical absorbed dose rate maxima are presented, for the realistic biosphere calculation cases applied to the repository calculation cases Sh1 and Sh4 Q.

Table 7-13 and Table 7-14 present the typical absorbed dose rate maxima for assessment species in terrestrial, freshwater and Baltic coast objects derived with the realistic biosphere calculation cases for the repository base case Sh1. Table 7-15 and Table 7-16 present the typical absorbed dose rate maxima for assessment species in terrestrial, freshwater and Baltic coast objects derived with the realistic biosphere calculation cases for the repository base case Sh4 Q.

The terrestrial species with the highest dose rate maxima are, for both repository calculation cases, American mink, Bank vole, Common frog, Hazel grouse, Hooded crow, Moose, Mountain hare, Red fox, Tawny owl and Viper. For species in freshwater, the highest dose rate maximum is estimated for Grass snakes, and for marine species, the highest dose rate maximum is estimated for Gray seal and Oystercatcher.

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ual d

ose [

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Table 7-13. Typical absorbed dose rate maxima for terrestrial assessment species derived with the realistic biosphere calculation cases for the repository base calculation case (Sh1).

Assessment species Typical absorbed dose rate [µGy/h]

Terrestrial Panel A (a) Panel B (a) Panel C (a) Carnivorous mammal: American mink 1.8 x 10-5 3.8 x 10-5 9.5 x 10-5 Herbivorous rodent: Bank vole 1.8 x 10-5 3.8 x 10-5 9.5 x 10-5 Shrub: Bilberry 1.2 x 10-5 2.5 x 10-5 6.2 x 10-5 Herb: Bracken 1.2 x 10-5 2.5 x 10-5 6.3 x 10-5 Carnivorous invertebrate: Carabid beetle 5.6 x 10-6 1.2 x 10-5 3.0 x 10-5 Omnivorous reptile/amphibian: Common frog 1.8 x 10-5 3.8 x 10-5 9.5 x 10-5 Decomposer: Earthworm 5.6 x 10-6 1.2 x 10-5 3.0 x 10-5 Herbivorous bird: Hazel grouse 1.8 x 10-5 3.8 x 10-5 9.5 x 10-5 Insectivorous/omnivorous bird: Hooded crow 1.8 x 10-5 3.8 x 10-5 9.5 x 10-5 Herb: May lily 1.2 x 10-5 2.5 x 10-5 6.2 x 10-5 Large herbivorous mammal: Moose 1.8 x 10-5 3.8 x 10-5 9.5 x 10-5 Herbivorous mammal: Mountain hare 1.8 x 10-5 3.8 x 10-5 9.5 x 10-5 Omnivorous mammal: Red fox 1.8 x 10-5 3.8 x 10-5 9.5 x 10-5 Herbivorous invertebrate: Ringlet 5.6 x 10-6 1.2 x 10-5 3.0 x 10-5 Carnivorous bird: Tawny owl 1.8 x 10-5 3.8 x 10-5 9.5 x 10-5 Tree/crown of tree 1.7 x 10-5 3.7 x 10-5 9.2 x 10-5 Tree/stem of tree below crown 1.7 x 10-5 3.7 x 10-5 9.2 x 10-5 Carnivorous reptile/amphibian: Viper 1.8 x 10-5 3.8 x 10-5 9.5 x 10-5 Grass: Wavy hair-grass 1.2 x 10-5 2.5 x 10-5 6.3 x 10-5

(a) All dose rate maxima occur at the same year (12 020), in the same biosphere object (Mäntykarinjärvi) and ecosystem type (wetland) for all three repository panels.

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Table 7-14. Typical absorbed dose rate maxima for assessment species in freshwater and Baltic coast objects derived with the realistic biosphere calculation case for the repository base calculation case (Sh1).


Freshwater Panel A (a) Panel B (b) Panel C (c) Phytoplankton: Anabaena flos-aquae 5.9 x 10-6 4.7 x 10-7 2.7 x 10-6 Phytoplankton: Anabaena lemmermannii 6.9 x 10-6 5.5 x 10-7 3.1 x 10-6 Bivalve mollusc: Anodonta sp. 3.9 x 10-5 3.1 x 10-6 1.8 x 10-5 Insect larvae: Chironomus plumosus 3.8 x 10-5 3.1 x 10-6 1.7 x 10-5 Zooplankton: Cladocera sp. 2.0 x 10-5 1.6 x 10-6 9.3 x 10-6 Amphibian: Common frog 3.9 x 10-5 3.1 x 10-6 1.8 x 10-5 Vascular plant: Common reed 2.5 x 10-5 2.0 x 10-6 1.1 x 10-5 Crustacean: Crayfish 3.9 x 10-5 3.1 x 10-6 1.8 x 10-5 Phytoplankton: Gonyostomum semen 8.3 x 10-6 6.7 x 10-7 3.8 x 10-6 Reptile: Grass snake 9.0 x 10-5 7.2 x 10-6 4.1 x 10-5 Gastropod: a snail: Lymnaea peregra 3.9 x 10-5 3.1 x 10-6 1.8 x 10-5 Bird: Mallard 3.9 x 10-5 3.1 x 10-6 1.8 x 10-5 Mammal: Otter 3.9 x 10-5 3.1 x 10-6 1.8 x 10-5 Gastropod: a snail: Planorbis planorbis 3.5 x 10-5 2.8 x 10-6 1.6 x 10-5 Benthic fish: Ruffe 2.4 x 10-5 2.0 x 10-6 1.1 x 10-5 Phytoplankton: Tabellaria fenestrata 6.0 x 10-6 4.8 x 10-7 2.7 x 10-6 Pelagic fish: Vendace 2.4 x 10-5 2.0 x 10-6 1.1 x 10-5

Baltic coast Panel A (d) Panel B (d) Panel C ( d) Phytoplankton: Aphanizomenon sp. 2.3 x 10-9 1.3 x 10-8 1.2 x 10-8 Pelagic fish: Baltic herring 7.9 x 10-9 4.6 x 10-8 4.1 x 10-8 Benthic mollusc: Baltic macoma 6.5 x 10-9 3.8 x 10-8 3.4 x 10-8 Crustacean: Baltic prawn 6.5 x 10-9 3.8 x 10-8 3.4 x 10-8 Benthic mollusc: Blue mussel 6.5 x 10-9 3.8 x 10-8 3.4 x 10-8 Phytoplankton: Chaetoceros wighamii 3.1 x 10-9 1.8 x 10-8 1.6 x 10-8 Zooplankton Cladocera sp. 6.5 x 10-9 3.8 x 10-8 3.4 x 10-8 Macroalgae: Cladophora glomerata 5.2 x 10-9 3.0 x 10-8 2.7 x 10-8 Vascular plant: Common reed 5.3 x 10-9 3.1 x 10-8 2.8 x 10-8 Benthic fish: Flounder 7.9 x 10-9 4.6 x 10-8 4.1 x 10-8 Mammal: Grey seal (female) 1.1 x 10-8 6.6 x 10-8 5.9 x 10-8 Mammal: Grey seal (male) 1.1 x 10-8 6.6 x 10-8 5.9 x 10-8 Bird: Oystercatcher 1.1 x 10-8 6.6 x 10-8 5.8 x 10-8 Polychaete worm: Nereis diversicolor 6.5 x 10-9 3.8 x 10-8 3.4 x 10-8

(a) All dose rate maxima occur at the same year (3 910), in the same biosphere object (Kaunisjoki) and ecosystem type (river)

(b) All dose rate maxima occur at the same year (3 710), in the same biosphere object (Susijoki) and ecosystem type (river)

(c) All dose rate maxima occur at the same year (3 570), in the same biosphere object (Susijoki) and ecosystem type (river)

(d) All dose rate maxima occur at the same year (3 520), in the same biosphere object (Janijärvi) and ecosystem type (coast)

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Table 7-15. Typical absorbed dose rate maxima for terrestrial assessment species derived with the realistic biosphere calculation cases for the repository calculation case (Sh4 Q).


Year

Terrestrial Panel A (a) Panel B

(a) Panel C

(a)

Carnivorous mammal: American mink 3.1 x 10-4 6.6 x 10-4 1.7 x 10-3 11 940 Herbivorous rodent: Bank vole 3.1 x 10-4 6.6 x 10-4 1.7 x 10-3 11 940 Shrub: Bilberry 2.1 x 10-4 4.4 x 10-4 1.1 x 10-3 12 020 Herb: Bracken 2.1 x 10-4 4.4 x 10-4 1.1 x 10-3 12 020 Carnivorous invertebrate: Carabid beetle 9.9 x 10-5 2.1 x 10-4 5.3 x 10-4 12 020 Omnivorous reptile/amphibian: Common frog 3.1 x 10-4 6.6 x 10-4 1.7 x 10-3 11 940 Decomposer: Earthworm 9.9 x 10-5 2.1 x 10-4 5.3 x 10-4 12 020 Herbivorous bird: Hazel grouse 3.1 x 10-4 6.6 x 10-4 1.7 x 10-3 11 940 Insectivorous/omnivorous bird: Hooded crow 3.1 x 10-4 6.6 x 10-4 1.7 x 10-3 11 940 Herb: May lily 2.1 x 10-4 4.4 x 10-4 1.1 x 10-3 12 020 Large herbivorous mammal: Moose 3.1 x 10-4 6.6 x 10-4 1.7 x 10-3 11 940 Herbivorous mammal: Mountain hare 3.1 x 10-4 6.6 x 10-4 1.7 x 10-3 11 940 Omnivorous mammal: Red fox 3.1 x 10-4 6.6 x 10-4 1.7 x 10-3 11 940 Herbivorous invertebrate: Ringlet 9.8 x 10-5 2.1 x 10-4 5.2 x 10-4 12 020 Carnivorous bird: Tawny owl 3.1 x 10-4 6.6 x 10-4 1.7 x 10-3 11 940 Tree/crown of tree 3.0 x 10-4 6.4 x 10-4 1.6 x 10-3 11 970 Tree/stem of tree below crown 3.0 x 10-4 6.4 x 10-4 1.6 x 10-3 11 990 Carnivorous reptile/amphibian: Viper 3.1 x 10-4 6.6 x 10-4 1.7 x 10-3 11 940 Grass: Wavy hair-grass 2.1 x 10-4 4.4 x 10-4 1.1 x 10-3 12 020

(a) All dose rate maxima occur in the same biosphere object (Mäntykarinjärvi) and ecosystem type (wetland).

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Table 7-16. Typical absorbed dose rate maxima for assessment species in freshwater and Baltic coast objects, derived with the realistic biosphere calculation case for the repository calculation case (Sh4 Q).


Freshwater Panel A (a) Panel B (b) Panel C (c) Phytoplankton: Anabaena flos-aquae 2.7 x 10-4 1.9 x 10-5 1.3 x 10-4 Phytoplankton: Anabaena lemmermannii 3.2 x 10-4 2.3 x 10-5 1.5 x 10-4 Bivalve mollusc: Anodonta sp. 1.8 x 10-3 1.3 x 10-4 8.6 x 10-4 Insect larvae: Chironomus plumosus 1.8 x 10-3 1.2 x 10-4 8.5 x 10-4 Zooplankton: Cladocera sp. 9.5 x 10-4 6.6 x 10-5 4.5 x 10-4 Amphibian: Common frog 1.8 x 10-3 1.3 x 10-4 8.6 x 10-4 Vascular plant: Common reed 1.1 x 10-3 8.0 x 10-5 5.4 x 10-4 Crustacean: Crayfish 1.8 x 10-3 1.3 x 10-4 8.6 x 10-4 Phytoplankton: Gonyostomum semen 3.9 x 10-4 2.7 x 10-5 1.8 x 10-4 Reptile: Grass snake 4.2 x 10-3 3.0 x 10-4 2.0 x 10-3 Gastropod: a snail: Lymnaea peregra 1.8 x 10-3 1.3 x 10-4 8.6 x 10-4 Bird: Mallard 1.8 x 10-3 1.3 x 10-4 8.6 x 10-4 Mammal: Otter 1.8 x 10-3 1.3 x 10-4 8.6 x 10-4 Gastropod: a snail: Planorbis planorbis 1.6 x 10-3 1.1 x 10-4 7.7 x 10-4 Benthic fish: Ruffe 1.1 x 10-3 8.0 x 10-5 5.4 x 10-4 Phytoplankton: Tabellaria fenestrata 2.8 x 10-4 1.9 x 10-5 1.3 x 10-4 Pelagic fish: Vendace 1.1 x 10-3 8.0 x 10-5 5.4 x 10-4

Baltic coast Panel A (d) Panel B (d) Panel C ( d) Phytoplankton: Aphanizomenon sp. 1.1 x 10-7 6.5 x 10-7 5.8 x 10-7 Pelagic fish: Baltic herring 3.8 x 10-7 2.2 x 10-6 2.0 x 10-6 Benthic mollusc: Baltic macoma 3.2 x 10-7 1.9 x 10-6 1.7 x 10-6 Crustacean: Baltic prawn 3.2 x 10-7 1.9 x 10-6 1.7 x 10-6 Benthic mollusc: Blue mussel 3.2 x 10-7 1.9 x 10-6 1.7 x 10-6 Phytoplankton: Chaetoceros wighamii 1.5 x 10-7 8.7 x 10-7 7.8 x 10-7 Zooplankton Cladocera sp. 3.2 x 10-7 1.9 x 10-6 1.7 x 10-6 Macroalgae: Cladophora glomerata 2.5 x 10-7 1.5 x 10-6 1.3 x 10-6 Vascular plant: Common reed 2.5 x 10-7 1.5 x 10-6 1.3 x 10-6 Benthic fish: Flounder 3.8 x 10-7 2.2 x 10-6 2.0 x 10-6 Mammal: Grey seal (female) 5.4 x 10-7 3.2 x 10-6 2.8 x 10-6 Mammal: Grey seal (male) 5.4 x 10-7 3.2 x 10-6 2.8 x 10-6 Bird: Oystercatcher 5.4 x 10-7 3.2 x 10-6 2.8 x 10-6 Polychaete worm: Nereis diversicolor 3.2 x 10-7 1.9 x 10-6 1.7 x 10-6

(a) All dose rate maxima occur at the same year (3 910), in the same biosphere object (Kaunisjoki) and ecosystem type (river)

(b) All dose rate maxima occur at the same year (3 550), in the same biosphere object (Susijoki) and ecosystem type (river)

(c) All dose rate maxima occur at the same year (12 020), in the same biosphere object (Susijoki) and ecosystem type (lake)

(d) All dose rate maxima occur at the same year (3 520), in the same biosphere object (Janijärvi) and ecosystem type (coast)

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8 COMPLEMENTARY ASSESSMENT In the previous chapter, the main findings from the assessment based on the realistic biosphere calculation cases are presented and discussed. This chapter presents the results from the biosphere sensitivity calculation cases (section 8.1). Section 8.2 compares selected results in the present assessment with results from previous Posiva assessments, and also results from analysing calculation cases from previous assessment with the current landscape model and dose assessment approach. Finally, in section 8.3, the release rates from the geosphere are examined from a more classical physics perspective, namely by expressing the activity releases in terms of numbers of atoms.

8.1 Sensitivity calculation cases Sensitivity calculation cases aim to evaluate uncertainties in the knowledge of the state and behaviour of the system, or parts of it, that are reflected in the variability of the data used in the analyses. The assumptions made, and parameter values selected, are expected to be within the reasonably expected range of possibilities for the considered scenario. This section presents and discusses the assumptions used and the findings from the sensitivity biosphere calculation cases defined in section 2.1.3.

8.1.1 Release paths in the geosphere The uncertainties in the initial location of the radionuclides released from the repository (which canister position) and the paths through the geosphere by which the radionuclides are transported up to the surface environment leads to uncertainties in the spatial distribution of the release locations into the biosphere. The methodology to handle this issue in the current assessment is by defining and evaluating simplified release patterns; this has been discussed in detail in section 5.1.2. The resulting annual doses maxima (for Egroup and Epop) due to nominal release rates introduced into the landscape model are presented in Table 8-1, and the annual doses during the whole time window are plotted in Figure 8-1 and Figure 8-2.

Targeted releases to one or a few forest objects result in higher doses to the most exposed group. Egroup ranges from 4 to 30 times higher for the release patterns with targeted release to forest objects, compared with the realistic release patterns. However, since the forest objects receiving the releases have low productivities of edibles, they generally cannot support all individuals in the most exposed group with food (which is the exposure pathway dominating the all-pathway dose). Hence, there is no corresponding effect on the doses to other people. Epop is about the same for release patterns with targeted releases to forest objects as for the realistic release pattern.

Targeted releases to one or a few cropland objects result in similar doses to the most exposed group as the realistic release patterns. Cropland objects can support a large group of people, in the range of 30 to 600 persons, depending on the size of the cropland object. This has the consequence that the doses to other people are higher when the releases are targeted to cropland objects, compared with both the realistic release pattern and targeted releases to forest objects. Epop ranges from 2 to 6 times higher for the release patterns with targeted release to cropland objects, compared with the realistic release patterns.

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Table 8-1. Annual landscape dose maxima for the representative persons for the most exposed group (Egroup) and for the other people (Epop) for the cases investigating effects of uncertainties in the release paths (c.f. Table 5-1).

Case Egroup [mSv]

Year

Ngroup Epop [mSv]

Year

Npop

Realistic-A 6.9 x 10-8 11 870 50 9.8 x 10-9 4 220 3 589 Realistic-B 1.4 x 10-7 11 870 50 3.1 x 10-9 3 670 3 291 Realistic-C 3.6 x 10-7 11 870 50 2.8 x 10-9 3 670 3 291

Forest_focused-A 2.1 x 10-6 2 470 50 4.0 x 10-8 4 220 3 589 Forest_focused-B 6.0 x 10-7 4 470 50 3.1 x 10-9 3 670 3 291 Forest_focused-C 1.4 x 10-6 12 020 50 2.4 x 10-9 3 620 3 295

Forest_dispersed-A 2.0 x 10-6 12 020 50 3.9 x 10-8 4 220 3 589 Forest_dispersed-B 7.6 x 10-7 12 020 50 4.3 x 10-10 12 020 5 309 Forest_dispersed-C 1.5 x 10-6 12 020 50 3.7 x 10-10 12 020 5 309

Cropland_focused-A 9.5 x 10-8 4 220 50 5.7 x 10-8 4 220 3 589 Cropland_focused-B 3.8 x 10-7 2 670 50 5.7 x 10-9 3 570 3 299 Cropland_focused-C 4.5 x 10-7 3 320 50 5.8 x 10-9 3 570 3 299

Cropland_dispersed-A 9.0 x 10-8 4 220 50 5.3 x 10-8 4 220 3 589 Cropland_dispersed-B 3.0 x 10-7 3 070 50 7.0 x 10-9 3 570 3 299 Cropland_dispersed-C 2.4 x 10-7 3 320 50 1.4 x 10-8 11 620 5 395

The results (Table 8-1) and discussion illustrate that the selection of the three realistic release patterns to underpin the realistic biosphere calculation case is not the most cautious choice for potential radiological consequences. However, the level of conservatism in the realistic release patterns is considered adequate for the assessment (following the discussion in section 5.1.2). If releases targeted to small croplands or forest areas were to be selected for the realistic biosphere calculation cases, it would be considered that the outcome of the assessment would have an unnecessary high conservatism. This because it is considered that it would be pessimistic to assume that the release ends up in the most conservative (highest doses) areas in the surface environment in conjunction with the cautious assumptions used for exposure characteristics (all foodstuffs and water originate from contaminated areas) and dose identification (each individual satisfying their annual nutrition demand from the most contaminated areas). In other words, for example, assuming that the whole geosphere release is routed into a small forest and the most exposed persons eat nothing else but what that forest can produce is considered to result in unduly pessimistic dose estimates.

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Figure 8-1. Annual landscape doses for the representative persons for the most exposed group, Egroup, for the simplified release patterns; results from panel A (top), panel B (middle) and panel C (below).

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Figure 8-2. Annual landscape doses for the representative persons for other people, Epop, for the simplified release patterns; results from panel A (top), panel B (middle) and panel C (below).

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8.1.2 Developing surface environment Up to the end of the biosphere assessment time window in year 12 020, the surface environment will undergo large changes; in particular during the first half of the time window, where a large part of the area considered in the landscape model will develop from coastal areas to terrestrial ecosystems or lakes. In the second half of the time window, from about year 7 000 onwards, the landscape model is more static and contains only a few changes between ecosystem types.

Due to the development of the surface environment many biosphere objects in the landscape model will change ecosystem type with time, once or twice, especially in the first 1 000 years. The cases analysed here aim at evaluating if the assessment outcome is sensitive to the stage of the surface environment development when geosphere releases reach the biosphere. This is evaluated by deriving annual landscape doses (Egroup and Epop) for nominal release rates introduced into the landscape model from different starting years. The simulation time is always 10 000 years from the starting year, thus the end of the simulation period will differ. Doses are derived for the three realistic release patterns (section 8.1.1). In order to enable modelling beyond the normal ending of the biosphere assessment time window it is assumed that the surface environments do not develop further for at least 10 000 years more (i.e., static configuration of the landscape model between the years 12 020 and 20 020). The cases are presented in Table 8-2, and the results in Table 8-3.

The results show that the assessment outcome is relatively insensitive to the further development of the surface environment, when the geosphere releases enters the biosphere after the three lakes Liiklanjärvi, Tankarienjärvi and Mäntykarinjärvi have been developed at year 3 520. The reason is that these three lakes receive a large part of the direct geosphere releases (see Table 5-1) and the doses are dominated by biosphere objects in the vicinity of these lakes. The further development of the surface environment occurs mainly in the western parts and the biosphere objects located there are generally less significant to the doses. As a consequence, the dose curves for the cases with a starting year at 3 500 or later, Evo-stage2, Evo-stage3 and Evo-stage4, look rather similar (see Figure 8-3) and the resulting dose maxima do not differ much.

For geosphere releases that enter the biosphere earlier, the situation is significantly different. As long as the three lakes mentioned above are still coastal objects (up to year 3 520) a significant part of the activity is mixed in the large water volumes and also transported to the outer sea. Consequently, activity concentrations are low in the water (and in the edibles from the coastal objects). Furthermore, the coastal objects do not give any doses from water ingestion (salty water) and the productivity of edibles is low. Thus, the resulting doses are significantly lower (see Figure 8-3) than for the case when the geosphere releases enter the lakes. Moreover, the total number of persons in the exposed group is small, generally only a few tens of persons. The most pronounced differences between “early” (Realistic and Evo-stage1) and “late” (Evo-stage2, Evo-stage3 and Evo-stage4) starting times for the releases are for Epop. The shape of the curves for Epop for the “early” cases is similar to the corresponding curves for Sh1 (c.f. Figure 7-8). The reason is that the dose maxima occurring in the early parts of the time window are the same for the cases based on NRR as for the cases based on Sh1: Epop is dominated by the C-14 landscape dose from water consumption from the rivers Kaunisjoki or Susijoki (see also the discussion in section 7.4.1).

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Table 8-2. The sensitivity biosphere calculation cases assessing the impact on the assessment outcome due to the developing surface environment.

Case Time window for NRR Comment

Realistic-A,B,C 2 020 – 12 020 This is the assumed starting and ending years used in the realistic BCCs

Evo-stage1-A,B,C 2 520 – 12 520 The starting year is the time step when many Coastal objects have just been developed to Forest or Cropland objects

Evo-stage2-A,B,C 3 520 – 13 520 The starting year is the time step when many Coastal objects have just been developed to Forest or Cropland objects, and the first time-step with the River Eurajoki and Lake objects.

Evo-stage3-A,B,C 7 020 – 17 020 The starting year is the time step when all Cropland objects have been formed

Evo-stage4-A,B,C 10 020 – 20 020

Table 8-3. Annual landscape dose maxima for the representative persons for the most exposed group (Egroup) and for the other people (Epop) in the calculation cases assessing the impact on the assessment outcome due to the dynamics in the development of the surface environment; nominal release rates are applied.

Case Egroup [mSv]

Year

Epop [mSv]

Year

Panel A Realistic 6.9 x 10-8 11 870 9.8 x 10-9 4 220 Evo-stage1 6.9 x 10-8 11 870 5.9 x 10-9 4 220 Evo-stage2 1.5 x 10-7 13 520 8.1 x 10-8 13 520 Evo-stage3 1.5 x 10-7 17 020 8.2 x 10-8 17 020 Evo-stage4 1.5 x 10-7 20 020 8.2 x 10-8 20 020 Panel B Realistic 1.4 x 10-7 11 870 3.1 x 10-9 3 670 Evo-stage1 1.4 x 10-7 11 870 3.1 x 10-9 3 670 Evo-stage2 1.4 x 10-7 11 870 3.1 x 10-9 3 670 Evo-stage3 1.4 x 10-7 17 020 1.2 x 10-9 17 020 Evo-stage4 1.4 x 10-7 20 020 1.2 x 10-9 20 020 Panel C Realistic 3.6 x 10-7 11 870 2.8 x 10-9 3 670 Evo-stage1 3.6 x 10-7 11 870 2.8 x 10-9 3 670 Evo-stage2 3.7 x 10-7 11 870 1.3 x 10-8 13 520 Evo-stage3 3.6 x 10-7 17 020 1.3 x 10-8 17 020 Evo-stage4 3.6 x 10-7 20 020 1.3 x 10-8 20 020

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Figure 8-3. Egroup (top) and Epop (below), for release from panel A, in the calculation cases assessing the impact on the assessment outcome due to the dynamics in the development of the surface environment; nominal release rates are applied.

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Realistic Evo-stage1 Evo-stage2 Evo-stage3 Evo-stage4

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8.1.3 Timing of geosphere releases The starting year for the near-field and geosphere modelling is not given in calendar years; the resulting geosphere release rates do not correspond to a canister emplaced in the repository at a certain time. The repository operating time is estimated to be from 2 020 to 2 120. Thus, the time-dependent geosphere release rates given by the near-field and geosphere modelling may, in principle, have the starting year anytime within this 100-year interval. The assumption made in the realistic BCCs is that the canister that fails and release radionuclides is emplaced at the beginning of the operational phase, i.e., assuming that year zero in the near-field and geosphere modelling corresponds to calendar year 2 020. The potential impact on the dose assessment due to the uncertainty arising from the timing of the geosphere release is evaluated here.

In the sensitivity BCC it is assumed that the failed canister is one of the last emplaced, thus assuming that year zero in the near-field and geosphere modelling corresponds to calendar year 2 120. The effect of the uncertainty as to when the failed canister is emplaced in the repository is evaluated by deriving annual doses (Egroup and Epop) for the Sh1 RCC, using the three realistic release patterns (see also section 8.1.1). The results are presented in Table 8-4, and show that the impact on the assessment outcome due to uncertainties in the timing of the geosphere release is small for Egroup, but rather significant for Epop.

The results for panel B shows that the dose maxima increases 50% and also occurs in the beginning of the time window for the Timing case, compared with the Realistic cases. The reason for this is that Epop is, in the period around year 3 570, dominated by the C-14 dose from water ingestion, where the water originates from River Susijoki (see Figure 8-4).

Table 8-4. Annual landscape dose maxima for the representative persons for the most exposed group (Egroup) and for the other people (Epop) in the calculation cases assessing the impact on the assessment outcome due to uncertainties in timing of the geosphere releases; all cases apply the geosphere releases in the RCC Sh1.

BCC Egroup [mSv]

Year

Epop [mSv]

Year

Panel A Realistic 7.9 x 10-7 11 920 1.2 x 10-7 3 970 Timing 7.8 x 10-7 11 920 1.1 x 10-7 11 920 Panel B Realistic 1.6 x 10-6 11 870 2.0 x 10-8 12 020 Timing 1.5 x 10-6 11 920 3.0 x 10-8 3 570 Panel C Realistic 3.9 x 10-6 11 870 2.9 x 10-8 3 570 Timing 3.8 x 10-6 11 870 2.8 x 10-8 3 570

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Figure 8-4. Annual landscape dose for the representative persons for the other people (Epop) for the Realistic and Timing cases (Panel B), and the C-14 landscape doses for water ingestion (EL,W) for River Susijoki. 8.1.4 Irrigation practises The soil in croplands may be contaminated either by direct release of radionuclides from the geosphere or by secondary contamination when the fields are irrigated by contaminated water from a near-by lake or river. In the realistic BCCs are vegetables the only crop type included when deriving the CFagg for croplands. The reasons for this are that vegetables are a common crop type in the region and vegetables are generally, but not always, irrigated.

To evaluate the impact on the outcome of the dose assessment of the cautious assumption that all vegetables produced in croplands are irrigated, a sensitivity BCC (NoIrr) is evaluated in which irrigation is excluded as a transport pathway for radionuclides. The importance of irrigation as a contributor to the derived annual doses is evaluated by deriving annual doses (Egroup and Epop) for the RCC Sh1, using the three realistic release patterns (see also section 8.1.1). The results are presented in Table 8-5.

The resulting dose maxima are only affected by excluding irrigation when the release originates from panel A. This is consistent with the results in Table 7-9 and Table 7-10, where it is only for releases from Panel A that a cropland dominates Egroup (Roopenmaa3) and Epop (Liiklanpelto).

Further, when excluding irrigation, the results show that croplands give insignificantly low doses, even if geosphere releases are routed direct into the deep soil layer of a cropland object. For geosphere releases from Panel A, 8% are directed into Liiklanpelto (Table 5-1). Nevertheless, the landscape dose, EL, from Liiklanpelto is insignificant. This suggests that sub-horizontal loss in interflow from the deep soil layer is high enough to remove almost all activity.

1E-12

1E-11

1E-10

1E-09

1E-08

1E-07

2020 4020 6020 8020 10020 12020

Ann

ual d

ose

[mSv

]

Year

EL,W (C-14, Susijoki, Timing)

EL,W (C-14, Susijoki, Realistic)

Epop (Timing)

Epop (Realistic)

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Table 8-5. Annual landscape dose maxima for the representative persons for the most exposed group (Egroup) and for the other people (Epop) in the calculation cases assessing the impact on the assessment outcome due uncertainties in the use of irrigation water; all cases apply the geosphere releases in RCC Sh1.

BCC Egroup [mSv]

Year

Epop [mSv]

Year

Panel A Realistic 7.9 x 10-7 11 920 1.2 x 10-7 3 970 NoIrr 7.8 x 10-7 11 920 7.4 x 10-8 3 970 Panel B Realistic 1.6 x 10-6 11 870 2.0 x 10-8 12 020 NoIrr 1.6 x 10-6 11 870 2.0 x 10-8 12 020 Panel C Realistic 3.9 x 10-6 11 870 2.9 x 10-8 3 570 NoIrr 3.9 x 10-6 11 870 2.9 x 10-8 3 570

8.2 Comparison with previous Posiva assessments In order to increase confidence in the assessment outcome, especially in the models and derived annual doses, selected results from the present assessment are compared with results from previous Posiva assessments. Further, a few calculation cases from previous assessments have been re-analysed with the landscape model and dose assessment approach applied in the present assessment. For this comparison, results are presented based on repository base calculation cases from the three latest safety assessments: Sh1 from present assessment, PD-BC from the KBS-3H safety assessment, and Sh-sal50 from the TILA-99 assessment. Average annual doses to other members of the public are excluded from the comparison, since the present assessment is the first in which they have been derived.

8.2.1 Annual landscape doses The landscape model approach has been applied in two assessments by Posiva, in the present assessment and in the KBS-3H safety analysis (Broed et al. 2007). In TILA-99 (Vieno & Nordman 1999), the compliance assessment was primarily based on doses from the drinking water well scenario.

Table 8-6 summarises the annual landscape dose maxima to representative persons for the most exposed group, Egroup, and the data are plotted in Figure 8-5. Based on the results, some observations can been made as follows:

• The annual dose maximum to a representative person of the most exposed group in the present base case (Sh1) is about 10 times lower than in the previous base case for a KBS-3V assessment (SH-sal50)

• The annual dose maximum to a representative person of the most exposed group in the present base case (Sh1) is about 50 times lower than in the base case for the KBS-3H analysis (PD-BC)

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These differences in dose maxima are due to differences in the geosphere release rates, thus reflecting the assumptions made when defining the repository calculation cases. Furthermore:

• The annual dose maxima to a representative person of the most exposed group is about 7-8 times higher applying the KBS-3H dose calculation approach compared with the approach applied in the present assessment for Sh1 and SH-sal50 (model 2009/2007 compared with model 2009/2009 in Table 8-6). For PD-BC, the corresponding difference is about a factor 2,

• Annual dose maxima to a representative person from the most exposed group is about 5-10 times lower applying the present landscape model and dose assessment process for PD-BC, compared with applying the KBS-3H models for PD-BC and SH-sal50 (model 2009/2009 compared with model 2007/2007 in Table 8-6). The reduction in dose is both due to a different dose assessment approach and differences in the landscape model,

• For SH-sal50, it may be noted that the dose maximum occurred in the beginning of the time window in the KBS-3H analysis (illustrated in Figure 8-6) and at the end in the present assessment. The reason for this is that the first releases into non-coastal objects occur at year 3 570 in the 2009 landscape model (for the realistic simplified release pattern with releases from repository panel C), and releases into the sea give generally low doses. In the 2007 version of the landscape model, releases into forest objects already occurred at the beginning of the time window (see Figure 3.10 in Broed 2007b). Moreover, at the year of dose maxima, one forest (denoted “N1”) received about 30-40% of the releases, and had an area corresponding to a production of edibles to support one person with food. This difference in the release patterns, and the fact that a small forest received a large fraction of the release in the 2007 landscape model, is clearly reflected in the shape of the annual landscape dose curve (Figure 8-6).

8.2.2 Safety indicators The two well scenarios described in section 5.4 (AgriWELL-2009 and WELL-2009) have been applied to derive safety indicators, using the geosphere releases in the repository calculation cases listed in Table 7-2. Only releases within the biosphere assessment time window have been considered; thus the time of dose maxima may deviate from the times in Nykyri et al. (2008), where the whole assessment time frame up to one million years is considered. The maxima of the safety indicators (in terms of annual doses) are presented in Table 8-7 and Table 8-8 for the repository base calculation cases from the three latest safety assessments: Sh1 from the present assessment, PD-BC from the KBS-3H safety studies, and Sh-sal50 from the TILA-99 assessment. The difference in the dose maxima between the assessment base cases shows similar behaviour as for the annual landscape doses above (section 8.2.1):

• The annual dose maximum in the present base case (Sh1) is about 10 times lower than in the previous base case for a KBS-3V assessment (SH-sal50)

• The annual dose maximum in the present base case (Sh1) is about 50 times lower than in the base case for the KBS-3H analysis (PD-BC)

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As for the landscape doses, these differences are due to differences in the geosphere release rates, thus reflecting the assumptions made when defining the repository calculation cases.

Figure 8-5. Egroup maxima for three repository base calculation cases in the three most recent Posiva safety assessments. Doses derived in the present report are denoted (2009), dose based on the present landscape model in conjunction with the dose assessment process applied in the KBS-3H biosphere analysis are denoted (2009/2007), and the doses presented in the KBS-3H biosphere analysis are denoted (2007).

Figure 8-6. Resulting annual landscape doses to most exposed persons for SH-sal50 analysed with the realistic biosphere calculation cases.

1.E-07 1.E-06 1.E-05 1.E-04 1.E-03

Sh1 (2009)

PD-BC (2009)

SH-sal50 (2009)

Sh1 (2009/2007)

PD-BC (2009/2007)

SH-sal50 (2009/2007)

PD-BC (2007)

SH-sal50 (2007)

Egroup maxima over all generations[mSv]

KBS-3HPanel APanel BPanel C

1.0E-14

1.0E-12

1.0E-10

1.0E-08

1.0E-06

1.0E-04

2020 4020 6020 8020 10020 12020

Ann

ual l

ands

cape

dos

e [m

Sv]

Year

SH sal50 (2007 models)

SH sal50 (2009 models - Panel C)

SH sal50 (2009 models - Panel B)

SH sal50 (2009 models - Panel A)

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Table 8-6. Annual landscape dose maxima (Egroup) derived with the landscape model and dose assessment process applied in this report, compared with results based on the landscape model and dose calculation approach used in the KBS-3H analysis.

Model Case Panel Value [mSv]

Year

2009/2009 (a) Sh1 A 7.9 x 10-7 11 920 B 1.6 x 10-6 11 870 C 3.9 x 10-6 11 870

PD-BC A 3.5 x 10-5 12 020 B 7.3 x 10-5 12 020 C 1.8 x 10-4 12 020

SH-sal50 A 9.2 x 10-6 11 870 B 1.9 x 10-5 11 870 C 4.6 x 10-5 11 870 2009/2007 (b) Sh1 A 6.4 x 10-6 11 720 B 1.2 x 10-5 11 720 C 3.0 x 10-5 11 720

PD-BC A 8.3 x 10-5 12 020 B 1.5 x 10-4 12 020 C 3.8 x 10-4 12 020

SH-sal50 A 6.9 x 10-5 11 720 B 1.3 x 10-4 11 670 C 3.3 x 10-4 11 670 2007/2007 (c) PD-BC - 4.6 x 10-4 12 020

SH-sal50 - 2.6 x 10-4 2 470 (a) The present assessment results (b) The present landscape model (LSM-2009) results analysed with the dose assessment

process applied in the KBS-3H safety studies (Broed et al. 2007), thus identifying the annual landscape dose to the most exposed individual

(c) The results presented in the KBS-3H biosphere analysis (Broed et al. 2007), assuming that year 0 in that report corresponds to year 2020, as used in this report.

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Table 8-7. Indicative annual dose maxima, during the time window of biosphere assessment, from the AgriWELL-2009 scenario, doses from dominating radionuclides and their relative contribution to the total dose from drinking of water and intake of food.


Year


Contribution from Water Food

Sh1 2.4 x 10-7 9 920 C-14 I-129 Cl-36

1.1 x 10-7 1.1 x 10-7 1.6 x 10-8

32% 31%

2%

16% 16%

3%

PD-BC 2.3 x 10-5 12 460 I-129 Cl-36 C-14

1.8 x 10-5 2.8 x 10-6 2.6 x 10-6

51% 4% 8%

26% 8%

4%

SH-sal50 2.1 x 10-6 11 455 I-129 C-14

Cl-36 Sn-126+d

1.6 x 10-6 2.8 x 10-7 1.1 x 10-7

5.5 x 10-8

52% 9% 2% 2%

26% 5% 4% 1%

Table 8-8. Indicative annual dose maxima, during the time window of biosphere assessment, from the WELL-2009 scenario, doses from dominating radionuclides and their relative contribution to the total dose.


Year


Sh1 1.5 x 10-7 9 870 C-14 I-129 Cl-36

7.5 x 10-8 7.3 x 10-8 3.6 x 10-9

49% 48%

2%

PD-BC 1.4 x 10-5 12 460 I-129 C-14

Cl-36

1.2 x 10-5 1.7 x 10-6 8.8 x 10-7

82% 12%

6%

SH-sal50 1.3 x 10-6 11 455 I-129 C-14

Cl-36

1.1 x 10-6 1.9 x 10-7 3.6 x 10-8

81% 14%

3%

8.3 Classical physics approach The quantity used in the dose assessment for humans, the annual effective dose, is not a straight-forward physical quantity (see section 6.1). It is a quantity used to estimate the radiation induced stochastic effects caused by exposure to ionizing radiation. Effective dose is intended for use as a radiation protection quantity; one of the main uses is when demonstrating compliance with regulatory dose limits, or constraints. To put the radionuclide releases into a more classical physics perspective, the number of atoms of the radionuclides in the geosphere releases has been derived. Table 8-9 presents the total number of atoms in the geosphere release for the repository calculation cases with the highest risk quotients for each radionuclide and in the case Sh1. The time window applied is the same as in the screening evaluation (years 2 020 to 17 020). The results clearly underline the huge differences between the different radionuclides in the geosphere release, and that the key radionuclides (Table 2-11) dominate the release.

139

Table 8-9. The highest total number of atoms on the geosphere release between years 2 020 and 17 020 for all repository calculation cases considered, the case resulting in the highest integrated release, and for radionuclides with a release of more than one atom in the case Sh1. Radionuclides in the key set of radionuclides, and their progeny, are marked in bold.

Radionuclide Number of atoms Highest Case Sh1

I-129 9 x 1022 PD-EXPELL 7 x 1020 Cl-36 2 x 1022 PD-EXPELL 8 x 1019

Pd-107 1 x 1022 PD-EXPELL 9 x 1014 Cs-135 1 x 1021 Sh4 Q 3 x 104 Mo-93 8 x 1020 PD-EXPELL 1 x 1012

C-14 4 x 1020 Sh4 Q 2 x 1019 Sn-126 5 x 1019 SHsal50 2 x 1012

Se-79 2 x 1019 PD-EXPELL 1 x 1013 Nb-94 7 x 1018 Sh4 Q 1 x 109 Ni-59 6 x 1018 Sh4 Q 3 x 101

Nb-93m 4 x 1018 PD-EXPELL 5 x 109 Pa-231 6 x 1013 Sh4 Q -

Zr-93 3 x 1013 Sh4 Q - U-238 2 x 1013 Sh4 Q - Tc-99 8 x 1012 Sh4 Q - Sr-90 4 x 1012 SHsal50 -

Sb-126 2 x 1012 SHsal50 7 x 104 Ra-226 5 x 1011 Sh4 Q - U-235 2 x 1011 Sh4 Q - U-236 9 x 1010 Sh4 Q -

Am-243 5 x 1010 Sh4 Q - U-233 2 x 1010 Sh4 Q -

Pu-239 1 x 1010 Sh4 Q - Pb-210 7 x 109 Sh4 Q - U-234 6 x 109 Sh4 Q -

Np-237 4 x 109 Sh4 Q - Pu-242 3 x 109 Sh4 Q -

Y-90 1 x 109 SHsal50 - Th-230 1 x 109 Sh4 Q - Pu-240 7 x 108 Sh4 Q -

Cm-245 7 x 108 Sh4 Q - Th-229 3 x 108 Sh4 Q - Po-210 1 x 108 Sh4 Q -

Am-241 4 x 107 Sh4 Q - Cm-246 2 x 107 Sh4 Q - Th-232 6 x 106 Sh4 Q -

Ni-63 4 x 103 Sh4 Q - Cs-137 2 x 103 Sh4 1 x 102

Sm-151 3 x 101 Sh4 Q -

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9 KNOWLEDGE QUALITY ASSESSMENT This chapter summarises the most important outcomes of the Knowledge quality assessment (KQA) performed as a part of the biosphere assessment process. The full KQA is documented in the main report for each biosphere assessment sub-process (Haapanen et al. 2009, Ikonen et al. 2010b and Hjerpe & Broed 2010). At the end of this section, a statement is given concerning the overall knowledge quality in the whole biosphere assessment process. The KQA is an iterative process that spans all activities in the Biosphere assessment and in the broader safety case. Its aim is to foster communication of assumptions and uncertainties throughout the assessment chain in a systematic and comprehensive manner. The different aspects covered by the KQA, developed on the basis of Ikonen (2006), Hjerpe (2006), Broed (2007), Broed et al. (2007) are as follows:

• Applied (and available) data: sources and subsequent handling of data, where the data are used, are they fit for the purpose, how the data quality is assured and checked, what the impact of using available but not used data would have been, why such data have not been used.

• Main assumptions, their impact, potential for alternative interpretations.

• Main uncertainties in the input data and those produced during the interpretation or modelling process, their cause, whether the uncertainty has been assessed, means to resolve and whether this would help in a further assessment.

• Sensitivity assessment and data quality: how sensitive the models are to the input data, confidence in an adequately high quality of the data and underlying process understanding.

• Overall consistency within the biosphere assessment, with previous versions, corresponding other models, assessments, and science in general.

• Overall knowledge quality. Overall statements regarding the confidence in applied models and data, level of conservatism, and the total uncertainty propagated to the next sub-process in the biosphere assessment (or next process in the overall safety case).

9.1 Biosphere description The KQA of the information in the biosphere description report (Haapanen et al. 2009) are summed up here. The KQA has been performed on two parts of the biosphere description: the site descriptive part and the recommended data for further use in the biosphere assessment modelling part. Generally, the knowledge quality provided by the biosphere description to the subsequent modelling, and more broadly to the overall biosphere assessment and the safety case, is good: there are uncertainties and data gaps, but they have been identified, as well as the major assumptions.

Applied data A large number of data sets are used in the biosphere description, especially for developing site understanding. The main data applied in the site descriptive part feeding to the ecosystem modelling, terrain and ecosystem development modelling, and especially the data recommendations to the radionuclide transport and dose assessment

142

are listed in Table 12-1 in Haapanen et al. (2009). The key data include data sets such as:

• meteorological observations, snow and ground frost measurements, and wet deposition monitoring,

• water quality monitoring results,

• overburden characteristics,

• soil survey results,

• acoustic-seismic sounding of sea bottom sediments,

• sea bottom surface sediment sampling,

• stratigraphy, geochemistry and hydrogeochemistry of mires,

• vegetation coverage, biomass measurements,

• fine root investigation results,

• inventories (e.g., forest, vegetation, terrestrial flora, littoral flora),

• fauna surveys (e.g., game, birds, fish, small mammals, bats, herpetofauna, invertebrates, and zooplankton),

• primary production of lakes and rivers,

• agricultural practices data (crop production and animal products), and

• irrigation practises survey.

Main assumptions The main assumptions in the descriptive part of the work are related to the post-processing of the direct measurements and survey results; thus closely related to the applied data discussed above.

The main assumptions underlying the data recommended for further use in the biosphere assessment are listed in Table 12-5 in Haapanen et al. (2009). For recommended data that are element-specific, the focus is on radionuclides with top priority (C-14, I-129, Cl-36). Almost two thirds of the main assumptions result in data within the range of possibilities, but without the possibility to currently evaluate the likelihood. About one third is conceptualisations as to the likely, or expected, characteristics of the system. Only a few assumptions were classified to the other types, most important of which are the stylised conceptualisations (i.e., coarse simplifications) of the system characteristics and evolution. These were related to the assumptions made in the models to which the data are provided: flow accumulation, formation of suspended matter flow by erosion and accumulation rate of gyttja in the terrain and ecosystem forecasts, and ellipsoidal geometry of assessment species.

Main uncertainties The main uncertainties related to the field data used in the biosphere description are listed in Table 12-3 in Haapanen et al. (2009) and in Table 12-6 for the main uncertainties related to data recommended in the biosphere description for further use in

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the biosphere assessment. Main uncertainties arise from the lack of directly site-relevant data, and some of the data gaps shall be filled with literature data later in the biosphere assessment and by additional field studies. Generally, site data are lacking on:

• concentration ratios for key elements, especially for I and Cl,

• distribution coefficients for the identified key elements,

• productivity of edibles for humans in various ecosystems, especially aquatic systems,

• dimensions and weights of assessment species, where the information density generally is low but on the other hand the effect on the doses are small − these data make the distinction between the assessment species, though,

• sedimentation rates in lakes,

• parameters in the peat growth model, such as consistent peat profiles, and

• parameters in the C-14 radionuclide transport model, such as mixing height, net primary production and dissolved carbon concentration in lakes, and decomposition rate of exposed sediment.

Sensitivity assessment and data quality The sensitivity of the assessment models to changes in the value of an input parameter are explored by sensitivity analysis (e.g., Ekström & Broed 2006). This is done in the biosphere assessment in the modelling processes following the biosphere description. Sensitivity analysis is a method applied to capture a quantitative dimension of the total uncertainty.

The quality of the data recommended for the further assessment has been evaluated with a quantified measure, the data quality index, which aims to capture the qualitative dimensions of the total uncertainty. The data quality index method is a further development from that of Broed (2007) and Broed et al. (2007), and can be considered to be a simplified pedigree analysis (e.g., Ellis et al. 2000, Jeroen et al. 2002). The results of the data quality index evaluation repeat the pattern of uncertainties and lack of data discussed already earlier, but provide a more systematic measure than the non-quantified lists.

To illustrate the applicability in the overall assessment, Figure 9-1 presents a plot of the data quality index against the respective sensitivity measure in the case of the C-14 transport model (Avila & Pröhl 2007). For each parameter given a site-relevant value, the corresponding Spearman rank correlation coefficient (SRCC) was taken from (Avila & Pröhl 2007). In the lower right corner of the figure, the data quality has been evaluated low and at the same time the model is relatively sensitive to small changes in the parameter value; parameters situated here would require immediate improvement. The further the individual parameters locate to the upper left corner on the plot, the higher the confidence in the model output is.

144

Figure 9-1. Data Quality Index for key data related to the C-14 transport model against the sensitivity of the transport model to the parameter expressed by the Spearman Rank Correlation Coefficient (NPP: net primary production).

Overall consistency Taken as a whole, comparing with the previous work undertaken as part of the Biosphere description process (Haapanen et al. 2007), the understanding over conventional disciplines of environmental studies and monitoring has increased, especially through ecosystem-specific and -linking transfer process descriptions and mass balance and flux estimates that reveal the data gaps and poorly compatible datasets, further contributing to the implementation of the future research programme. The descriptions of fauna, and littoral and agricultural ecosystems based on local and regional site data have been the main improvements in respect to the study disciplines, and also the description of the locally important rivers has been significantly improved.

Also, a significant conceptual improvement has been made by selecting lakes and mires analogous to those expected to form at the Olkiluoto site in the future, to compensate the lack of such ecosystems at the present site. The literature data on the ecosystems of the selected seven lakes (four lake systems) and three mires have been summarised. Also, the present description is supported by a large set of generic geographical information datasets, and related processing, on the larger Reference area covering most of the Satakunta and Varsinais-Suomi provinces. In some cases the regional GIS data have been used to fill data gaps. In respect to improvements within individual datasets, in general the time series of monitoring data are longer than in 2006. This is especially the case with water quality monitoring and the forest monitoring on Olkiluoto Island. No conflicts to the generic knowledge have been identified, but especially the study on fine root elongation and longevity at Olkiluoto is the first one using minirhizotrones in Southern Finland, and the first study on Scots pine and birch fine roots in the whole of Fennoscandia.

145

Overall knowledge quality As a conclusion, it can be stated that there has been a significant improvement in data and site understanding since the previous Biosphere description report, and that the knowledge quality of the site part of the biosphere assessment is at a good level. There are still major data gaps to be filled, but the overall understanding of the ecosystems and their relationships is better than adequate to fill the needs of the existing biosphere assessment models that will be further developed, in their turn, in iterations within the assessment process.

9.2 Terrain and ecosystem development This section summarises the KQA of the TESM-2009 modelling (Ikonen et al. 2010b). There the KQA has been performed regarding the modelling process itself and on the produced data delivered further to the landscape modelling. The input data has been addressed separately by the producing sub-process, i.e. the biosphere description (Haapanen et al. 2009) and its supplementary report on other than key data (Ikonen et al. 2010a), summarised in section 9.1 above. Generally, TESM-2009 produces rather realistic forecasts of the future ecosystems at the Olkiluoto site, although some identified uncertainties and data gaps remain.

In this section, also the KQA of the related surface and near-surface hydrological modelling (SNSH; Karvonen 2009c) is briefly evaluated as an integral part of the TESM-2009. The SNSH gives rather realistic results on the release paths in the overburden and on the water balance of biosphere objects based on the given release points from the geosphere and the biosphere set-up from TESM-2009.

Applied data The key data applied in the TESM-2009 and related SNSH modelling includes data sets on (Haapanen et al. 2009, Ikonen et al. 2010b):

• topographical and bathymetric data (digital terrain model),

• land uplift model parameters,

• present top soil and sediment types,

• hydraulic conductivity of soil and sediment types,

• climatic data (especially precipitation and temperature),

• runoff formation and discharge of the rivers draining at present to the western end of the model area (the Eurajoki and Lapinjoki Rivers),

• accumulation and decay rates of organic matter in the catotelm of peat bogs,

• threshold height of the groundwater table supporting peat-forming vegetation (location of peat bogs),

• accumulation rate of gyttja in reed beds,

• calibration dataset on reed bed extent, and

• site classification for forest vegetation (link of soil properties to vegetation type).

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Furthermore, (Haapanen et al. 2009) provide data for aspects not yet fully implemented in TESM-2009:

• fluxes of suspended matter in the rivers for calibrating the sediment balance in the model, and

• wind statistics and critical shear stresses of bottom sediments for the underwater erosion and sedimentation model.

For all the data, information is available from the site or from the Reference area. The largest data gaps resulting from the considerations that:

• the spatial distribution of dating information on past sea levels around the Olkiluoto site is very irregular,

• the accumulation and decay data for peat include an unnecessarily wide variation of bog types around Finland,

• data on gyttja accumulation are determined indirectly from a single formation (Olkiluodonjärvi mire at the site),

and, regarding the data not directly used in the TESM-2009 modelling:

• only single data values were available on critical shear stresses of bottom sediments.

Main assumptions The main assumptions in the input data to the TESM-2009 modelling have been listed in Table 12-5 of (Haapanen et al. 2009): About one third of the main assumptions were classified to be within the range of possibilities, but without the possibility of to currently evaluate the likelihood of these. Another third of the main assumptions were related to conceptual assumptions that correspond to the likely or expected characteristics and development paths, and the rest were stylised conceptualisations of the properties and behaviour of the system, such as assuming a constant accumulation rate of gyttja. Some of these assumptions in the input data arise from the characteristics of the model that they are used in.

Assumptions made within the TESM-2009 modelling (Ikonen et al. 2010b) as a whole are numerous, but considering their impacts on the radionuclide transport modelling and dose assessment, the central assumptions made are that:

• the future land uplift follows the arctangent functions fitted to the observations of past development (model of Påsse 2001),

• dimensions of river channels are based on hydraulic radius (cross-section area) where the width of the channel is related to the discharge and the depth is calculated,

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• sedimentation and erosion in water bodies has not been considered in the base case and in a variant case a model having only the water volume as the basin controlling the overall sedimentation rate has been employed as a more suitable model based on estimating the physical exposure on the bottom has been developed but not yet sufficiently tested for the assessment use,

• erosion on land has been assumed insignificantly small (not included in the model),

• peat formations are raised bogs with a size determined by the balance between peat production and decay and by the hydraulic constraint on lateral expansion,

• peat bog locations are based on the estimated groundwater table being close enough to the surface and the groundwater table is estimated only as a function of elevation,

• formation of reed vegetation is constrained by physical exposure, water depth and magnitude of underwater currents, bottom type is ignored, and same parameters are used for both sea and lakes,

• accumulation of gyttja occurs only under reed beds and with constant accumulation rate,

• forest vegetation types depend only on the soil type (and thickness),

• all and only clay and gyttja soils of sufficient thickness have been taken into cultivation (croplands).

All the main assumptions listed above are related either to availability of data or to computational limitations (several modules need to be run iteratively for a large modelling area over the 10 000-year assessment time window for each case), or both. However, the modelling as a whole is reasonably realistic and produces plausible results in comparison with similar ecosystems at present.

Regarding the surface and near-surface hydrological modelling (SNSH; Karvonen 2009c), the main assumptions related to the computation of the release paths in overburden are that:

• influence of recharge through the bedrock-overburden interface was computed using a two-step process (1. steady-state recharge/discharge through the bedrock-overburden interface for all grid points, 2. vertical and horizontal water fluxes for a period of nine years with the steady-state recharge/discharge through the bedrock interface as the lower boundary condition),

• each soil type was treated as isotropic and homogenous,

• the threshold value for stream delineation (smallest catchment area forming a stream) was assumed to be 5 ha,

• average seasonal fluxes (four seasons) were computed and the release paths were calculated for 2 000 years using the seasonal average fluxes over and over again34

34 The impact of long periods of dry or wet conditions will be studied for the 2012 assessment.

,

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• random components were not included in the particle tracking algorithm (deterministic transport based on the computed velocity field was used).

Furthermore, related to the computation water balance and flux components of biosphere objects with the SNSH model the main assumptions are that:

• downward and upward vertical fluxes were calculated area-averaged values from all pixels inside the delineated ecosystem without taking into account the possible effect of flow channeling along more permeable sub-areas of the object,

• horizontal fluxes were computed by summing separately inflow and outflow fluxes through the outer boundaries of each biosphere object and possible effect of preferential bypass routes had not yet been taken into account,

• influence of lateral flow to subsurface drainage in agricultural areas was taken into account by adding a horizontal flux to drains and by assuming that water from agricultural areas can flow only to the nearest watercourse,

• for each biosphere object homogenous vegetation was assumed (one of the types of pine, spruce or deciduous forest), and transpiration and interception model parameters were taken from the existing SVAT-model (Karvonen 2009b)35

.

Main uncertainties The main uncertainties in the input data to the terrain and ecosystems development modelling have been presented in Table 12-6 of (Haapanen et al. 2009). They are related directly to the data gaps mentioned above - an issue of low information density. In addition, the topographical model has been made statistical, i.e. for all points also an uncertainty estimate is given (5th and 95th percentiles) and the auxiliary data produced include a full probability distribution. However, connecting these uncertainties to the uncertainties in the end product is an area needing further effort, as well as estimating and propagating the uncertainties in the land uplift model and its parameters.

Correspondingly the main uncertainties of the end products created in the modelling process are related to the uncertainties of the input data and the uncertainties in the model, best illustrated by the list of main assumptions (see above). As systematic uncertainty analysis of the overall terrain and ecosystems development modelling process is still pending (see below), a balanced account of the impact of the several sources of uncertainties is not currently feasible.

In the surface and near-surface hydrological modelling, the main uncertainties (Karvonen 2009c) are related to the low data density on thickness of soils and sediments, to the difficulty of estimating the hydraulic conductivity at the bedrock-overburden interface, to the variability of vegetation types and evapotranspiration and to the inevitable uncertainty in the density of ditching in the future. The overburden model is being improved both conceptually and with more site data and the effect of the other

35 For the 2012 assessment the modelling process will be developed to propagate the full dataset, including also the vegetation biomass needed for the SVAT sub-model, to all relevant models.

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uncertainties will be studied further for the 2012 assessment, so that necessary calculation cases can be defined to sufficiently cover the overall uncertainty.

Sensitivity assessment and data quality As forecasting of the development of the terrain and ecosystems in a rather large modelling area is a wide and also computationally demanding task, no systematic sensitivity or uncertainty assessment has been performed on this part of the biosphere assessment. However, it can be deduced that the factors affecting most the radionuclide transport modelling and the dose assessment are dominated by the uncertainties in the topography and in the land uplift model: the highest doses arise from food produced in terrestrial objects and thus whether a specific spot in the model will be terrestrial or aquatic defines at least the magnitude of the higher end of the doses, and this is further regulated by the topography and in respect to the timing of the landscape evolution by the land uplift36

In respect of quantitative results, the effects of the parameters of the peat bog model, the thickness and extent of the peat layer, have been studied by means of algebraic and sensitivity analyses in (Ikonen et al. 2010b) to demonstrate the methodology in the case of rather simple sub-model. Also, the impact of sedimentation in lake basins has been explored by employing an alternative, though stylised, model in a variant case instead of ignoring the process. The full analysis of effects of data and model uncertainties on the forecasts will be a combination of uncertainty and sensitivity analyses and scenario methodology (calculation cases), and it will be formulated and presented in the 2012 biosphere assessment.

. A project is ongoing to study the overall uncertainties in the topographical and land uplift models and their combined role in the forecast simulations - the results are expected to be available for the 2012 biosphere assessment.

For the surface and near-surface hydrological modelling, a sensitivity and uncertainty analysis was made by simulating a number of variant cases (chapter 4 of Karvonen 2009c): drainage density, hydraulic conductivities, distribution of precipitation to water fluxes within the canopy, groundwater discharge rate from bedrock, and thickness of overburden. The main uncertainties listed above were identified, but in view of a lack of probabilistic simulations the quantification of the model sensitivity and overall uncertainty is difficult - improvements will be made for the 2012 assessment.

Overall consistency The terrain and ecosystems development modelling (TESM) with the present version of the UNTAMO toolbox produces similar results to earlier TESM campaigns (e.g. Broed 2007b, Ikonen 2007b, Ikonen et al. 2005, 2008a) being also similar to somewhat independent approaches (Mäkiaho 2005, Rautio et al. 2005, Ojala et al. 2006) even though the input data and models have been greatly improved recently. It can be argued that as a whole the main development lines of the biosphere at Olkiluoto site are well known and the ecosystem types and their properties at least at a coarse level have been identified. The conceptual picture of retreating sea, enlarging present islands,

36 The land uplift may affect also to water level in lakes and at coastline or to the location of streams (rivers) as the spatially distributed rate results in crustal tilting. So far in the simulations, these effects have been minor.

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continuation of the main rivers and appearance of lakes around the site has remained the same.

The surface and near-surface hydrological model has been verified against analytical solutions where possible and its results have been compared to independent monitoring data from the site (Karvonen 2008, 2009a-c). The model results agree well with the site observations.

Overall knowledge quality Taken as a whole, the terrain and ecosystems development modelling (TESM) produces plausible forecasts of the biosphere with rather realistic models, and based on the surface and near-surface hydrological modelling producing plausible paths of the releases in overburden and water balances of biosphere objects that correspond well with corresponding site measurements. However, the role of many uncertainties and assumptions remains to be explored in the future assessments. The probable main lines of propagation of uncertainties have been identified, though, and the further development by 2012 is focused on them. The TESM process produces similar results to a number of earlier studies, and at least the main features of the biosphere can be reliably identified; the remaining work is in the details.

9.3 Landscape modelling This section summarises the KQA of the landscape model applied in the present assessment (Hjerpe & Broed 2010). The KQA has been performed on the two parts of landscape modelling, the biosphere object modules and the landscape model set-up, and these are treated separately below.

9.3.1 Biosphere object modules The biosphere object modules themselves are conventional compartment models with rather simple transport functions, as described in detail in (Hjerpe & Broed 2010).

Applied data The radionuclide transport modelling (the landscape model) includes hundreds of parameters; in addition to the most important data set, the radionuclide release rates from the geosphere, some of the key data sets applied are as follows:

• Physical data, such as radionuclide half lives (Hjerpe & Broed 2010), and densities and porosities of soils and sediments (Ikonen et al. 2010a),

• radioecological data (Helin et al. 2010), such as:

o distribution coefficients in soils and sediments,

o bioconcentration factors from water to biota, and

o concentration ratios from soils to crops,

• ecological parameters, such as production of biomass, standing biomass, and sedimentation and resuspension rates (Haapanen et al. 2009, Ikonen et al. 2010a).

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Main assumptions The assumptions underpinning the individual modules are addressed in Hjerpe & Broed (2010); the key assumptions are as follows:

• The radionuclides are fully mixed within each compartment in the model within each modelled time step (standard approach in the modelling of the transport and fate of radionuclides in the environment),

• the geosphere releases are directed straight to the compartments assumed to maximise the incorporation of radionuclides in the human food chain (to the rooted mineral soil layer for forest objects, to the acrotelm layer for wetlands, or to the water column in aquatic objects),

• C-14 releases are fully mixed with the stable carbon, the excess C-14/C-12 ratio is not affected by the other C-14 than released from the repository, and the C-14 release is readily transformed into bioavailable forms by microbial activity (Avila & Pröhl 2008).

Main uncertainties Solving transport modelling problems with compartment modelling is a common approach; as the compartments have been defined with care, the largest uncertainties are arising from the parameter values aggregating a number of real-life processes into simplistic transfer factors necessitated by the computational demands.

In respect to the input data to the radionuclide transport modelling of the biosphere, largest gaps of site data are on concentration ratios and on distribution coefficient (Kd). For concentration ratios to forest and aquatic plants some site data exist readily and many more are becoming available for the 2012 assessment, then including also data on transport to animals. The literature values for both concentration ratios and for Kd exist (collection of a database was initiated by Helin et al. 2010), but interpretation of their appropriateness to the Olkiluoto site often remains questionable. This is mainly due to inadequately reported sampling or experimental conditions, or that the data in compendia many times being merely aggregated bulk values covering all possible conditions leaving the actual data to the original publications often hard to obtain, and certainly laborious to review to collect the relevant information on the sampling or experimental conditions once again.

Sensitivity assessment and data quality The confidence to the present data has been evaluated using data quality index (see section 9.1). Based on the data quality index, the best founded data at the moment are related to the forest and agricultural ecosystems, whereas data on lakes, coastal areas and especially rivers need improvement. These have been acknowledged readily in the biosphere description work (Haapanen et al. 2009, Ikonen et al. 2010a) to be addressed in the following version for the 2012 assessment.

Overall knowledge quality At the present, unlike with the other modules, the confidence in the model underlying the radionuclide transport from irrigation water to crops has not been assessed; since

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this model is originally developed for steady-state conditions, an evaluation of its fitness to the more dynamic landscape modelling shall be done by 2012.

9.3.2 Landscape model set-up The KQA performed on the delineation of biosphere and the process of connecting them into a landscape model is discussed in detail in Broed & Hjerpe (2010) and summarised here.

Applied data Main data input is the forecast of the terrain and ecosystems development model and the results from the surface and near-surface hydrological modelling, containing data sets such as:

• Forecast data, such as ecosystem-types and geometrical properties (areas and thicknesses) of the compartments in the biosphere objects, which results from the terrain and ecosystem modelling (see above),

• all fluxes of water between the compartments in the biosphere object modules, and also between objects, are based on site data, interpreted through the surface and near-surface hydrology model (Karvonen 2009c) - for its KQA see section 9.2.

Main assumptions The main assumptions made in the landscape model set-up are as follows:

• The areas of individual forests and croplands were not allowed to be larger than a certain limit, in order to avoid excess numerical dispersion of radionuclides arising from treating individual objects as laterally homogeneous,

• all terrestrial areas with suitable soil (clay or gyttja/mud soils) of a thickness of at least 0.5 m are modelled as croplands,

• when an identified biosphere object, receiving direct releases from the geosphere, consists of both aquatic and terrestrial ecosystems are the releases targeted to the terrestrial part,

• inheritance of activity inventory from one shrinking ecosystem to a growing ecosystem is the areal rate of change divided by the area of the shrinking object, and

• the landscape model contains two main flow paths of surface water, representing the northern and southern part of the present-day Olkiluoto Island respectively, and radionuclide releases to the one route do not affect the other.

Main uncertainties The main uncertainties made in the landscape model set-up are as follows:

• The spatial and temporal distribution of radionuclide pathways from the geosphere through the overburden (the simplified release pattern) - this issue is

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dependent also on how the releases in the geosphere are modelled, and improvements will be made for the 2012 assessment,

• the development path of the ecosystem, i.e. the succession paths of "natural" ecosystems and how they are affected e.g. by clearing croplands or by rising water levels - this is handled by scenario approach and will be further developed for the 2012 assessment.

Overall knowledge quality Generally, configuring the landscape model set-up is a rather robust step after the input data (terrain and ecosystem forecasts, surface and near-surface hydrological simulations and the release pattern from the geosphere) are available and well specified. There are a number of alternative development paths, which need to be handled by scenario approach, but producing adequate data basis, the calculation cases need to be propagated through the relevant other modelling steps - the overall uncertainties arise from the interplay of the various data sets more than from the landscape model set-up as such, even though some issues of discretisation always remain in compartment modelling.

9.4 Screening models The purpose of applying screening models is primarily to ensure that the level of detail of the assessment, especially the landscape modelling, is appropriate to the magnitude of the potential radiological consequences. The key considerations to ensure a high knowledge quality regarding the screening models is to apply models that are fit for the purpose in conjunction with assumptions and parameter values producing results that, with a high degree of confidence, undoubtedly overestimate potential radiological consequences. The numerical uncertainties in the results from the screening evaluation are of less importance, as long as, taking uncertainties into account, the results are undoubtedly overestimates of potential radiological consequences. Hence the KQA for the screening models focuses on applied data, main assumptions and overall consistency with the landscape modelling and internationally used models for screening purposes.

Applied data The main approach to select parameter value data is to select cautious values from generic sources. Further, all applied data are compared to values selected in the landscape model and in previous biosphere analyses, in order to ensure that more cautious values are not applied elsewhere. For only one parameter used, the effective mixing capacity of the well in Tier 2, are site properties used as a basis. The key data, listed in detail in Hjerpe & Broed (2010), include data and data sets such as:

• screening dose rates for humans, cautiously selected such that there is a high degree of confidence that the potential radiological consequences are substantially, at least two orders of magnitude, below the regulatory dose constraints,

• screening dose rates for other biota, selected to be internationally applied dose rates recommended for screening purposes,

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• dose coefficients for ingestion, inhalation and external exposure. The coefficients used for external radiation are selected under the geometrical assumption that radionuclides are distributed on the ground surface, which is the most cautious choice,

• EMCL (Environmental Media Concentration Limit) for each radionuclide-reference organism combination, derived by back-calculating from the selected screening dose rate,

• distribution coefficients (Kd) in soil, selected as the highest 95th percentile values, for any soil type, of the values/distributions reported in IAEA (2009) and Karlsson & Bergström (2002),

• bioconcentration factors for lakes and aggregated concentration ratios for forest,

• productivity of edibles for lake and agricultural land,

• cautious exposure characteristics, (intake rates of food, water and air).

Main assumptions The screening model for humans, in the first tier, contains only a few, and extremely pessimistic, assumptions. The screening model for other biota, in the first tier, also contains very few, and extremely pessimistic, assumptions. The main assumptions, listed in detail in Hjerpe & Broed (2010), are as follows:

• the whole integrated release, during an extended biosphere assessment time window, from the geosphere is routed to one person either via ingestion or inhalation, or is transferred to the ground surface and exposes one person externally,

• the most radiosensitive reference organism (lowest EMCL) gets exposed,

• the habitat for the most radiosensitive reference organism has an activity concentration numerically equal to the total integrated activity in the geosphere release, for each radionuclide, applying an extended biosphere assessment time window, and

• all exposure situations are evaluated in parallel, and the situation resulting in the highest exposure is then the basis for the screening decision, which may differ for different radionuclides.

The Tier 2 screening model has a higher degree of realism by taking transport in the biosphere into account. This is done by applying three generic ecosystem-specific models. The main assumptions, listed in details in Hjerpe & Broed (2010), are as follows:

• the whole geosphere release, during an extended biosphere assessment time window, is routed to one ecosystem (a cropland, a lake, or an agricultural well),

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• the geometrical properties of the cropland and lake are selected so that the cropland and lake can support exactly one person with food (maximizes the dose to one individual),

• all ecosystem-specific models are evaluated in parallel, and the situation resulting in the highest exposure is then the basis for the screening decision, which may differ for different radionuclides,

• cautious exposure characteristics, (intake rates of food, water and air).

Overall consistency The aim of the screening models is to produce very conservative (i.e. overestimated) estimates of the magnitude of the doses from a given release. The approach selected for the screening evaluation is similar to the approach recommended in IAEA (2001) for use in assessing the impact of discharges of radioactive substances to the environment, and the models are in line with the recommendation by the ICRP (2000, 2007b) on how to conduct a dose assessment. The data have been selected from generic sources for the purpose, and will be revisited for each assessment to ensure an adequate level of conservatism.

Overall knowledge quality The three-tiered graded approach, which includes the screening evaluation, has been recently developed and has been applied for the first time in the present assessment. The methodology will be evaluated, and possibly revised, in order to reach maturity by 2012. For Tier 1, the confidence is very high that the outcome of the screening evaluation is fit for purpose. Considering the results from the BSA-2009 biosphere assessment, the selection of models and data for Tier 2 is considered to result in a screening model that meet the intended goal; at least for the radionuclide release scenarios considered.

9.5 Safety indicators Safety indicators are used to support the safety case, by building understanding of, and confidence in, the outcome and conclusions of the safety assessment. In the present assessment two safety indicators, in the form of annual doses, are derived, based on indicative stylised well scenarios: one for a drinking water well and one for an agricultural well. The aim of the well scenarios, in the present assessment, are to estimate indicative hypothetical annual doses received by a representative member of the most exposed group of people.

Applied data Three principles underpin the strategy when selecting data for the well scenarios:

1. The parameter values should reflect the aim of the well scenario; since the safety indicators are expressed as annual doses to a representative member of the most exposed group, a similar level of conservatism as in the landscape modelling is strived for.

2. The well scenarios, especially the agricultural well, are intended to be regional-specific.

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3. Since the well scenarios are used as an alternative line of reasoning to the main line of reasoning (the landscape modelling approach), care is taken to avoid applying data from the same sources as used in the landscape modelling, especially for key parameters.

The input data for the models can be divided into hydrological, radioecological and exposure data. Based on the three principles above, the approach for data selection can be summarised as follows for the three types of input data.

The hydrological data consists only of selecting a proper mixing volume for the well; currently selected to value representing a well with adequate conservatism regarding the present aim of the well scenario.

The approach for selection of parameter values for radioecological parameters, such as soil-to-plant concentration ratios, distribution coefficients and transfer factors, is to use generic data. This makes the outcome more independent from the outcome of the landscape modelling, thus in line with the third principle mentioned above. The parameter values applied are, to a large degree based on the most recent published data compendia intended to be used in generic dose assessment. This category of data suffers from rather large data gaps, especially for transfer factors other than for beef and soil-to-plant concentration ratios.

The last category, exposure characteristics, contains data sets regarding farm statistics, irrigation practices and dietary profiles both for humans and cattle. The approach for selecting values for describing the exposure characteristics is to apply regional and national data. In the present version of the model for the agricultural well, most of the data are based on regional information. Land use, crop production, and animal products, are based on average properties for the region, mainly taken from the Yearbook of Farm Statistics 2005 (TIKE 2006), using average values for the year 2004. Also irrigation characteristics, such as what types of crops are irrigated, irrigation amounts and frequencies, are based on regional data, derived from Pajula & Triipponen (2003). However, a significant fraction of the data is based on generic data (dietary profiles for cattle) and national data published in other countries (dietary profiles for humans based on Swedish data).

Main assumptions The main assumptions, listed in detail in Hjerpe & Broed (2010), are as follows:

• the yield of the well is sufficiently high for human consumption, watering of livestock, and for irrigation of crops,

• the selected effective mixing volume of the well is a representative expectation value adequate for cautious assessments,

• the production of the farm in the agricultural well scenario of crops and animal products corresponds to the arithmetic means of regional farm statistics,

• animals consume only contaminated feedstuffs,

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• the exposed individuals satisfy their nutrient needs by drinking water from the well (both well scenarios), and eating and drinking products from the farm (agricultural well scenario),

• every irrigation event fills the storage capacity of the plants, and 100% of the irrigation water passes through into the soil,

• annual intake of water corresponds to a high-consumer (based on the reported 95th percentile of intake of tap water),

• annual total consumption of food (meat, vegetables, cereals, milk products, potatoes, eggs, fruits and berries) corresponds to an average adult male consumer.

Main uncertainties The uncertainty in an annual dose estimated for a well scenario is dominated by uncertainties in the applied radionuclide-specific releases from the geosphere and uncertainties in the derived radionuclide-specific dose conversion factors. Further, the uncertainties in the dose conversion factors are dominated by the uncertainty in the assumed effective mixing volume of the well.

Other main uncertainties, but with less significance compared with the two above-mentioned, relate to the representativeness of the derived farm statistics and the dietary profile used for humans.

Sensitivity assessment and data quality No formal quantitative sensitivity analysis has yet been performed on the whole model used in the agricultural well scenario, and it is not necessary to perform one on the extremely simple expression used in the drinking water well scenario. Nevertheless, the obvious key parameter affecting the outcome (in terms of dose conversion factors) is the effective mixing capacity of the well37

The activity concentration in crops is dominated by uptake of activity through the roots due to irrigation water that has passed through into the soil. The model for root uptake is based on Bergström & Barkefors (2004), in which a sensitivity analysis was performed on the expression used for obtaining migration rates. The results show that for strongly sorbing nuclides (high distribution coefficient) bioturbation contributes more to migration than does the advection. When the distribution coefficient decreases, the advection contributes as well and the distribution coefficient and runoff begin to matter. Soil depth, porosity and density are the parameters for which the results are most sensitive. For nuclides with high mobility (low distribution coefficient), the outcome is most sensitive to parameters that affect the water turnover; such as runoff and soil depth.

. This parameter has a direct impact on the dose due to ingestion of drinking water, and also a direct impact on the activity concentration in the irrigation water, which is the key parameter for the resulting activity concentration in crops and animal products, and thus also for the outcome.

37 This is consistent with previous analysis of a range of deep disposal assessments (Pinedo et al. 1998) which formed the basis for the recommendation to study and understand better the geosphere-biosphere interface zone.

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Overall consistency The aim of the well scenarios in the present assessment is to derive safety indicators, which are estimates of indicative hypothetical annual doses received by a representative member of the most exposed group. This is consistent with how the well scenario has been applied in earlier Posiva assessments (for example in Smith et al. 2007b and Vieno & Nordman 1999). Prior to the development of the landscape modelling concept, these “well-doses” were been the primary quantity used in demonstrating compliance with regulatory dose constraints. In the present assessment, and in future ones, the main purpose of safety indicators has been shifted, and now constitutes an alternative line of reasoning. Thus, it may be grounds to revise the aim of the safety indicators, especially regarding the level of conservatism. It would be more consistent with how stylised well scenarios are applied internationally if the derived safety indicators were a more cautious (representing an upper bound) estimate of the potential annual doses received by a representative member of the most exposed group.

Overall knowledge quality Generally, regarding the present aim of safety indicators, the overall knowledge quality is high. For plain drinking water, the model is very simple and only a single exposure pathway is considered. For the agricultural well, the exposure pathways form a more complicated system but their modelling is conventional in the dose assessments, and the adequacy of included pathways and transport of the radionuclides in the system is still relatively easy to check and justify. There are still some data gaps, especially for element-specific data, to be filled; and furthermore, the data basis underlying the exposure characteristics will be improved by 2012.

9.6 Radiological consequences analysis The KQA regarding the dose assessment processes for humans and other biota is presented in Hjerpe & Broed (2010) and summarised here. The KQA has been performed for humans and other biota separately. Generally, the knowledge quality underpinning the radiological consequences analysis for humans is good. The areas to focus on are to strengthen the data basis for environmental information (productivity of edibles and aggregated concentration ratios) and exposure characteristics (implementing ranges of dietary profiles). The knowledge quality for the radiological consequences analysis for other biota has not yet reached the same level as for humans. This is as expected, since the radiation protection system for other biota is not yet as mature internationally as for humans. The approach to assess radiological consequences to other biota applied in the present assessment is considered to be in a fairly early maturity stage; the approach will be revised for the 2012 assessment.

9.6.1 Doses to humans This section summarises the KQA regarding the dose assessment processes for humans, presented in detail in Hjerpe & Broed (2010).

Applied and available data The main data sets used, and their sources, in the dose assessment for humans are:

• geometric properties of the landscape model (outcome of TESM),

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• radionuclide-specific radioactivity concentrations in environmental media (e.g., soil, sediment and water) – outcome of the landscape modelling sub-process,

• productivity of edibles – data recommended from the biosphere description sub-process,

• aggregated concentration ratios – data recommended from the biosphere description sub-process,

• exposure parameters:

o food intake rate – based on ICRP Reference Man (ICRP 1975, 2002), o water intake rate – based on ICRP Reference Man (ICRP 1975, 2002), o dose coefficients for ingestion and inhalation – based on the values

recommended by ICRP for adults (ICRP 1996), o dose coefficients for external radiation from radionuclides uniformly

distributed to an infinite depth - Table III.7 in EPA (1993).

Main assumptions The main assumptions in the dose assessment for humans are:

• exposure pathways other than ingestion of food, ingestion of water, inhalation and external exposure are of minor importance,

• each individual in the exposed population consumes only foodstuffs and water that are locally produced and contaminated,

• individuals in the exposed population have no food preferences,

• external exposure and inhalation of contaminated air occur only outdoors,

• dose calculations are based on food energy (carbon) intake,

• all individuals have average intake rates of food and water,

• the annual landscape dose is the sum of dose maxima from each exposure pathway, and

• the most exposed group is the 5% of most exposed persons in the dose distribution, with a maximum of 50 persons.

Main uncertainties The overall uncertainty in the landscape doses is mainly due to the uncertainty in the estimated activity concentrations in environmental media from the foregoing landscape modelling sub-process. However, the radiological consequences analysis itself naturally also introduces uncertainties, but these are likely less dominant than the uncertainties in activity concentrations. In the present assessment, a few uncertainties in need of reduction have been identified; these are as follows:

• the estimates of productivity of edibles are derived from site or analogue site data, and larger uncertainties were found in quantification of the yield per unit area of berries, mushrooms and game, and

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• the aggregated concentration ratios bear the uncertainties of the productivity estimates and, more strongly, the uncertainties in the concentration ratio values for the various edibles. The concentration ratios are derived from few actual data, as described in more detail in (Helin et al. 2010).

Sensitivity assessment and data quality The dose assessment process applied, especially the novel dose identification procedure, has been recently developed and is implemented here for the first time. A comprehensive sensitivity assessment has not yet been performed; this will be done for the 2012 assessment.

The quality of the underlying data is generally good. Exposure parameters are based on high-quality data from ICRP and EPA, and the important geometrical properties of the landscape model are derived from plausible forecasts in the TESM sub-process. The main parameters identified for which there is a need to strengthen the data basis, and thus the quality, are productivity of edibles and aggregated concentration ratios.

Overall consistency The dose assessment process applied is based on the one used in the KBS-3H analysis (see Broed et al 2007). In the present assessment, the process has been refined to be more consistent with how dose assessments are commonly applied internationally. However, the concept of landscape doses is fairly new and has not been applied in many safety assessments internationally. In the development of the dose assessment approach, emphasis has been put on harmonising the dose assessment with international recommendations and to ensure that the outcome has an adequate level of conservatism.

Overall knowledge quality Calculating doses to individual humans from a given environmental concentration by an exposure pathway is a rather straightforward task and conventional models are used, shifting the question of level of confidence to the input data. However, as the spatial distribution of the contamination in various areas and consumables needs to be taken into account in the context of the site and the present way in which people use the area, the task becomes somewhat more complicated, i.e. how to define the exposed groups. The approach used does not aim to be realistic in the permutations of possible exposures, but assumes the highest plausible exposure from the remaining contamination after contaminations giving the highest exposurehas been utilised by more exposed persons. In future assessments the reasonability of the dose distributions will be further discussed.

There is an identified need to strengthen the data basis for environmental information (productivity of edibles and aggregated concentration ratios) and exposure characteristics. For berries and mushrooms, a site study has been initiated to improve the estimates of productivity of edibles, and for game a more rigorous approach will be included in the next Olkiluoto biosphere description by 2012. The concentration ratio values for the various edibles are, as said above, derived from only a few actual data. A wider literature review and analyses of samples acquired from the site will be included in the 2012 assessment. The exposure parameters are on one hand based on the ICRP Reference Man (intake rates and dose coefficients) and on the other on the regional

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population statistics. It is purposed to use national statistics, as well as regional information, for intake rates to define ranges of dietary profiles for the 2012 assessment, which is commonly used in many other dose assessments.

9.6.2 Doses to other biota This section summarises the KQA regarding the dose assessment processes for the other biota, presented in detail in Hjerpe & Broed (2010).

Applied and available data The main data sets used, and their sources, in the dose assessment for other biota are:

• radionuclide-specific radioactivity concentrations in environmental media (e.g., soil, sediment and water) – outcome of the landscape modelling sub-process,

• selection of assessment species (Table 6-1Table 6-3) representing the diversity of biota at the site – made by expert judgement on the basis of site understanding in Haapanen et al. (2009),

• size and weight of the assessment species as simplified to the ellipsoidal geometry assumed by the model – a mixture of site-specific measurement, literature data and expert judgement, as presented in Haapanen et al. (2009) and complemented in Hjerpe & Broed (2010),

• occupancy factors, i.e. fraction of time the assessment species spends in air, on soil, in soil, on water surface, in water column, on sediment surface or in sediment – default values from the ERICA assessment tool (Beresford et al. 2007) with some adjustments based on knowledge on the site (listed in Hjerpe & Broed 2010), such as instead of assuming the default value that a wading bird spends 100% of time in water using an estimate of 50% of time in water and 50% on water surface, and

• concentration ratios for the assessment species – default values from the ERICA assessment tool (Beresford et al. 2007) are needed; these are justified in (Beresford et al. 2008, Hosseini et al. 2008) with the exception of concentration ratios to terrestrial plants derived as a combination of site and literature data provided in Helin et al. 2010.

Main assumptions The main assumptions in the dose assessment for the other biota are:

• all assessment species are represented by an ellipsoid – this is considered to be a suitable assumption for animals, but is acknowledged to be problematic for plants; alternative approaches will be considered for the 2012 assessment,

• exposure pathways include external exposure from the surrounding media (soil, sediment and water) and internal exposure from the radionuclides transported from the media inside the organism (modelled using the concentration ratios, thus also an equilibrium is assumed), but external exposure from other individuals of

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the same or other assessment species is not included38

• internal radioactivity is evenly distributed in the (ellipsoidal) body of the organism – it is known that this is not totally valid especially to certain elements like iodine that accumulate in specific organs but the present assessment methodology lacks this level of detail; alternative approaches will be considered for the 2012 assessment,

(alternative approaches will be considered for the 2012 assessment),

• occupancy in the compartments of habitat is handled in a stylised manner and conservative position in respect to the source of external exposure is assumed,

• all individuals of assessment species are located in a biosphere object where they remain full time, i.e.

o presence of a species does not prohibit the presence of any other species in the same object – in reality this is hardly the case due to competition and predator-prey relationships,

o individuals of assessment species stay full time in one ecosystem type (or, technically, in the same biosphere object) – it has not been considered that some species live in both aquatic and terrestrial habitats (e.g. birds) and in some cases the type of habitat changes during the life cycle (e.g. in early development frogs live solely in the aquatic environment, whereas adult frogs live on the interface of terrestrial and aquatic environments or in wetter terrestrial environments),

o size of home range with respect to the area of the biosphere object in question has not been considered, e.g. moose may have a home range of tens of square kilometres but get the assumed exposure resulting from full-time presence in an object of half a hectare,

o seasonal migration is not considered – in reality, for example, many birds migrate away for winter and moose wander between summer and winter ranges,

• different life stages of assessment species have not been considered (all have been assumed to be in the fully developed stage), but it is acknowledged that in some specific cases earlier development stages may be more sensitive to the radiation as such or associated with higher accumulation of contaminants – this will be improved for the 2012 assessment,

• assessment species have been considered as the whole organism, even though it is acknowledged that specific parts may accumulate more radioactivity, be more sensitive to radiation or be crucial for the welfare of the whole organism (e.g. plant roots) – the approach will be improved for the 2012 assessment, and

• the ensemble of the selected assessment species cover the essential exposure situations and ranges of dose to fully developed entire organisms, within the limitations of the model, and the results thus provide estimates on "typical

38 Individuals of a species hardly ever are in isolation from the other biota as at least plants are present and get contaminated from the same releases as the individual that is considered to be exposed. However, the geometry of the full setting is generally complex and stylised approaches seem unavoidable.

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radiation exposures of terrestrial and aquatic populations" per the regulatory requirements (STUK 2009).

Main uncertainties The main uncertainties in the dose assessment for the other biota, taken that the assessment methodology is appropriate (see discussion below), are:

• concentration ratios – the data is from a generic compendium full of data gaps, though it is the best available, and does not fully match the selected species and the conditions at the Olkiluoto site (some improvement especially for terrestrial and aquatic plants is expected for the 2012 assessment as more site studies are completed), and

• sizes and weights of assessment species – the data are partly from scientific literature, but also to a large extent from popular nature books lacking reliable peer review, and a number of data gaps have been filled by expert judgement (improvement is expected for the 2012 assessment resulting from several ongoing and planned site studies).

Sensitivity assessment and data quality The process of estimating the typical absorbed doses to the other biota has been recently developed and is implemented here for the first time. A comprehensive sensitivity assessment has not yet been performed; it will be done for the 2012 assessment.

However, the sensitivity of the dose assessment for the other biota has been studied in a project within the BIOPROTA framework (www.bioprota.com). Based on preliminary results that include also a case incorporating Olkiluoto data (based on activity concentrations predicted in Broed et al. 2007), in almost all cases the uncertainty in the concentration ratio has the largest affect on the doses, but in some specific cases of small organisms and nuclides of certain range of radiation energy also the dose conversion coefficient, i.e. the size and weight of the assessment species, is central. A number of experts also performed a pedigree analysis within the BIOPROTA project; low scores were given to the quality of process understanding and/or data reflects the assumptions and uncertainties discussed above. However, to make final conclusions on Posiva's biosphere assessment, both the sensitivity and pedigree analyses need to be performed on the actual models and data used in the assessment in contrast to the more generic context of the BIOPROTA project.

As reflected above, the quality of the underlying data varies rather much, but will be improved for the 2012 assessment as a number of site studies are completed and deliver suitable data.

Overall consistency The dose assessment for the other biota applied here is based on the ERICA integrated approach (Beresford et al. 2007) and on the test case of Smith & Robinson (2006). In the present assessment, the assessment process has been refined, but essentially it is

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similar than the earlier development and the main line of approaches applied internationally.

Overall knowledge quality The doses to the other biota can be stated to be uncertain, but almost certainly overestimated to the assessment species adopted. This is due to the fact that several conservative assumptions are combined. However, as reflected above, the issues of sensitive life stages or parts of organisms and detail differences in inter-/intra-species exposure geometry may produce less favourable dose/effect estimates. However, the assessment of doses to the other biota is in line with the recommendations of the international ERICA (Beresford et al. 2007) and PROTECT (Andersson et al. 2008) projects. The assessment methodology is still developing internationally.

Regarding the input data to the modelling, mainly the selection of the assessment species, their geometry, and concentration ratios from the environmental media to the organisms, the quality corresponds to recent international compendia. Mostly the data, especially the concentration ratios, are generic in nature, but improvements are expected for the 2012 assessment as ongoing and planned site studies provide a wider basis of site-specific data.

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10 DISCUSSION AND CONCLUDING REMARKS The biosphere assessment conducted for the interim safety case of 2009 has been presented in this report. There has been significant development, since the biosphere analysis conducted for the KBS-3H safety assessment, especially in the methodology of how to conduct the biosphere assessment, and in the underlying knowledge basis. Currently, no unresolved key issues for the long-term safety have been identified for the biosphere assessment. However, there are issues that need to be addressed in order to enhance the confidence that a fully balanced and comprehensive biosphere assessment is carried out in the safety case.

Firstly, in section 10.1, the biosphere assessment process is discussed in relation to the regulatory context and compliance with the regulatory requirements. Secondly, areas where major developments have been made, and issues that have been addressed and resolved (or considered to have reached a sufficient stage of maturity) in the present biosphere assessment are discussed in section 10.2. These issues originate from the discussion in the KBS-3H biosphere analysis report (Broed et al. 2007), the regulatory reviews of TKS-2006 (STUK’s letter “Olkiluodon ja Loviisan voimalaitosten ydinjätehuollon tutkimus- ja kehitystyön sekä teknisen suunnittelun ohjelma 2007-2009”, “The 2007-2009 programme for the research and development work and technical design of the nuclear waste management of the Olkiluoto and Loviisa power plants” and its attachment Y811/123) and the KBS-3H safety studies (STUK’s review letter H221/4, H221/14, H221/15 “Posivan KBS-3H-turvallisuusperustelun arviointi” and its attachments), or arose when conducting the 2009 biosphere assessment. Thirdly, areas needing significant development and issues needed to be further addressed are discussed in 10.3, together with the on-going and planned work.

10.1 Compliance assessment This section discusses compliance, limited to the aspects covered by the biosphere assessment in the safety case, with the guidance on the long-term safety of geological disposal of spent fuel, as set out in the Government Decree on the safety of disposal of nuclear waste (GD 736/2008) and the regulatory Guide YVL E.5 (STUK 2009). Guide YVL E.5 states that compliance with the long-term radiation protection requirements shall be demonstrated by means of a safety case. Further, detailed requirements for the content of the safety case are given in Appendix 1 of the Guide YVL E.5. First, the resulting doses are discussed in relation to the regulatory context and compliance with the regulatory constraints relating to radiation protection assessed, then the paragraphs of Appendix 1 in Guide YVL E.5 that directly concern the biosphere assessment are addressed.

Protection of humans The annual dose to most exposed people shall remain below a value of 0.1 mSv and the average annual doses to a larger group (denoted other people in this report) shall remain insignificantly low. There is no fixed dose constraint set for other people, but the doses shall not exceed values from one hundredth to one tenth of the constraint for the most exposed individuals. Thus, when assessing compliance, a constraint band for the average annual dose to other people from 0.001 to 0.01 mSv is used. Figure 10-1 shows the annual landscape dose maxima, over all generations, to the representative person for

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Figure 10-1. Annual landscape dose maxima, over all generations, to the representative person for the most exposed group (Egroup), for the repository calculation case geosphere release rates from the KBS-3V assessment RNT-2008 analysed with the realistic biosphere calculation cases. The red line corresponds to the regulatory annual dose constraint for the most exposed people.

Figure 10-2. Annual landscape dose maxima, over all generations, to the representative person for other people (Epop), for the repository calculation cases geosphere release rates from the KBS-3V assessment RNT-2008 analysed with the realistic biosphere calculation cases. The graded red box corresponds to the regulatory average annual dose constraint band for other people.

1.E-07 1.E-06 1.E-05 1.E-04 1.E-03 1.E-02 1.E-01

Sh1

Sh1-EPR

Sh1-VVER

Sh1 Fd

Sh1 Irf

Sh1 Q

Sh1 Sal

Sh4

Sh4 Q

Egroup maxima over all generations[mSv]

Panel A

Panel B

Panel C

1.E-09 1.E-08 1.E-07 1.E-06 1.E-05 1.E-04 1.E-03 1.E-02

Sh1

Sh1-EPR

Sh1-VVER

Sh1 Fd

Sh1 Irf

Sh1 Q

Sh1 Sal

Sh4

Sh4 Q

Epop maxima over all generations [mSv]

Panel A

Panel B

Panel C

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the most exposed group (Egroup) for the nine repository calculation cases analysed with the three realistic biosphere calculation cases. The highest doses are from case Sh4 Q, and are more than three orders of magnitude below the regulatory annual dose constraint. Figure 10-2 shows the annual dose maxima, over all generations, to the representative person for the larger group (Epop) for the same nine repository calculation cases analysed with the three realistic biosphere calculation cases. The highest doses are again from case Sh4 Q, and are more than two orders of magnitude below the lower limit of the regulatory annual dose constraint band.

Protection of other biota The Guide YVL E.5 states that the disposal shall not detrimentally affect species of flora and fauna. The recommendation is made that typical radiation exposures of terrestrial and aquatic populations in the disposal site environment should be determined and compliance assessed by comparing the results with the exposure levels which, on the basis of best available scientific knowledge, would cause a decline in biodiversity or other significant detriment to any living population.

Typical absorbed dose rates to identified assessment species have been derived in the present assessment. These dose rates are compared with internationally proposed screening values for the protection of biota against radiation in the environment, selected as the organism group-specific screening values recommended by the PROTECT project (Andersson et al. 2008). They are, in the form of absorbed dose rates, 2 μGy/h for vertebrates 70 μGy/h for plants, and 200 μGy/h for invertebrates.

The highest estimated typical absorbed dose rates for each identified assessment species are shown in Figure 10-3 to Figure 10-5. The results show that the assessed typical absorbed dose rates are clearly below all the proposed screening values, thus it is considered, with a high degree of confidence, that any releases from the repository will not affect species of flora and fauna detrimentally.

Other requirements In addition to dose and release criteria, Appendix 1 in YVL E.5 provides detailed requirements for the content of the safety cases; the paragraphs directly concerning the biosphere assessment part of the safety cases are addressed below.

According to the YVL E.5:

Paragraph A.1.2 – “The safety case shall include a description of the disposal system: quantities of radioactive materials … and the natural environment at the disposal site.”

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Figure 10-3. Typical absorbed dose rate maxima for terrestrial assessment species, for the calculation cases analysed. All maxima occur for the repository base case Sh4 Q with releases from repository panel C. The red lines correspond to the applied screening values (2 μGy/h for vertebrates, 70 μGy/h for plants and 200 μGy/h for invertebrates).

Figure 10-4. Typical absorbed dose rate maxima for assessment species in freshwater, for the calculation cases analysed. All maxima occur for the repository base case Sh4 Q with releases from repository panel A. The red lines correspond to the applied screening values (2 μGy/h for vertebrates, 70 μGy/h for plants and 200 μGy/h for invertebrates).

1.E-07 1.E-05 1.E-03 1.E-01 1.E+01 1.E+03

Large herbivorous mammal: Moose Omnivorous mammal: Red fox

Herbivorous mammal: Mountain hare Carnivorous mammal: American mink

Insectivorous/omnivorous bird: Hooded crow Carnivorous bird: Tawny owl

Herbivorous bird: Hazel grouse Carnivorous reptile/amphibian: Viper

Omnivorous reptile/amphibian: Common frog Herbivorous rodent: Bank vole

Tree/crown of treeTree/stem of tree below crown

Herb: BrackenGrass: Wavy hair-grass

Shrub: BilberryHerb: May lily

Decomposer: EarthwormCarnivorous invertebrate: Carabid beetle

Herbivorous invertebrate: Ringlet

Typical absorbed dose rate maxima [µGy/h]

1E-07 1E-05 1E-03 1E-01 1E+01 1E+03

Reptile: Grass snake Mammal: OtterBird: Mallard

Bivalve mollusc: Anodonta sp.Amphibian: Common frog

Crustacean: Crayfish Gastropod: a snail: Lymnaea peregra Insect larvae: Chironomus plumosus

Gastropod: a snail: Planorbis planorbis Vascular plant: Common reed

Pelagic fish: Vendace Benthic fish: Ruffe

Zooplankton: Cladocera sp.Phytoplankton: Gonyostomum semen

Phytoplankton: Anabaena lemmermanniiPhytoplankton: Tabellaria fenestrataPhytoplankton: Anabaena flos-aquae


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Figure 10-5. Typical absorbed dose rate maxima for assessment species in water of the Baltic coast, for the calculation cases analysed. All maxima occur for the repository base case Sh4 Q with releases from repository panel A. The red lines correspond to the applied screening values (2 μGy/h for vertebrates, 70 μGy/h for plants and 200 μGy/h for invertebrates). In Posiva’s terminology, the term “scenario formulation” is used in preference to “scenario analysis”. This is to avoid confusion with the term “analysis of scenarios”, which refers to the analysis of radionuclide release and transport in, and the radiological consequences of, scenarios involving radionuclide release from the repository. The scenario formulation in the biosphere assessment is conducted by defining dose assessment scenarios (section 2.1.2). The key drivers for the dose assessment scenarios are considered to be the external factors climatic changes and land use. The scenario formulation in the biosphere assessment part of the safety case is currently at an early phase with only one dose assessment scenario formulated; this is under development and is expected to reach maturity for the 2012 assessment.

Paragraph A.1.7 – “Modelling and determination of input data shall be based on high-quality scientific knowledge and expert judgement obtained through laboratory experiments, site investigations and evidences from natural analogues. The models and input data shall be consistent with the scenario, assessment period and disposal system.”

For the present assessment, the applied models and the input data used have been considerably improved. Especially the BSD-2009 (Haapanen et al. 2009) has strengthened the link between the biosphere description and the subsequent biosphere assessment sub-processes by providing parameter values recommended for safety assessment modelling based on site-specific data obtained through field or laboratory sample measurements, or appropriate literature. Further, the introduction of the surface and near-surface hydrological model (Karvonen 2009a-c) has provided an important link between the deep groundwater flow modelling and the forecast of the surface environment and the succeeding landscape model.

1E-07 1E-05 1E-03 1E-01 1E+01 1E+03

Mammal: Grey seal (male)Mammal: Grey seal (female)

Bird: Oystercatcher Benthic fish: Flounder

Pelagic fish: Baltic herringBenthic mollusc: Blue mussel

Crustacean: Baltic prawn Zooplankton Cladocera sp.

Benthic mollusc: Baltic macomaPolychaete worm: Nereis diversicolor

Vascular plant: Common reed Macroalgae: Cladophora glomerata

Phytoplankton: Chaetoceros wighamii Phytoplankton: Aphanizomenon sp.


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Paragraph A.1.8 – “Selection of the computational methods and input data should be based on the principle that the actual radiation exposure shall with a high degree of certainty be lower than those obtained through safety analyses...”

The fundamental principle applied when selecting models and data is to ensure that the outcome of the assessment is conservative. Conservative means, in this context, overestimation of potential radiological consequences, especially annual doses to humans. In particular, care has been taken to ensure that the outcome of Tier 3 (dose assessment based on landscape modelling) has an adequate level of conservatism, meaning that the parameter values and assumptions used throughout the safety assessment are selected to ensure that the estimates of potential radiological consequences are conservative, but still plausible and hence not unduly pessimistic.

Paragraph A.1.8 – “...The uncertainties included in the safety analysis shall be assessed by means of appropriate methods, e.g. by sensitivity analyses or probabilistic methods...”

In the recent assessment, reducing uncertainties has been in focus. Effort has been made on the selection of high-quality data appropriate for the Olkiluoto site. A main goal that was achieved in the BSD-2009 (Haapanen et al. 2009) was to give recommendations for site-specific values for key parameters in the safety analysis. The models for radionuclide transport and dose assessment will be subject to a comprehensive sensitivity analysis for the 2012 assessment.

Paragraph A.1.10 – The safety case shall be documented carefully. The documentation shall aim at transparency, implying that each part of the safety, the basic assumptions, used methods, obtained results and coupling to wholeness case are evident. Another goal shall be traceability, implying that the justifications for the used assumptions, input data and models shall be easily found in the documentation.

The biosphere assessment portfolio was revised in 2006 so as to among other reasons, satisfy these requirements for both transparency and traceability. In particular, the biosphere assessment report (this report) is intended to present the evidence, arguments and analyses of the biosphere assessment, with clear links to the other main reports in the biosphere assessment portfolio (Haapanen et al 2009, Ikonen et al. 2010b and Hjerpe & Broed 2010) and to the overall safety case portfolio, in a manner that favours transparency. Traceability is also facilitated by further documenting the knowledge basis in detail in supplementary reports (e.g., Ikonen 2010a, Helin et al. 2010 and Hjerpe & Broed 2010). Furthermore, the biosphere assessment database has technically been finalised and used throughout the radionuclide transport modelling and dose assessment modelling in the current assessment. In the next assessment, the database will be used throughout the whole biosphere assessment process and in addition act as the main tool for verifying that all data used in the safety analysis have been properly quality checked.

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10.2 Significant development and resolved issues There has been a significant development in all parts of the biosphere assessment process since the biosphere analysis conducted for the KBS-3H safety studies (mainly documented in Haapanen et al. 2007, Ikonen 2007b, Broed 2007a and Broed et al. 2007). Below, the key issues in the biosphere assessment in general and in the separate sub-process are summarised.

Biosphere assessment in general Graded approach to radionuclide transport modelling A major improvement of transparency and robustness of the biosphere assessment has been the development and implementation of the three-tiered graded approach to radionuclide transport modelling. The approach consists of preceding the landscape modelling (Tier 3) with a screening evaluation (Tiers 1 and 2), where the screening evaluation is used to identify radionuclides that are highly confidently expected to have insignificant radiological consequences.

Traceability The traceability of data and assumptions has been improved in the present assessment. The knowledge basis of the biosphere assessment is well documented in the main reports of the biosphere assessment portfolio (this report, Haapanen et al 2009, Ikonen et al. 2010b and Hjerpe & Broed 2010) and in supplementary reports by (e.g., Ikonen 2010a, Helin et al. 2010 and Hjerpe & Broed 2010), and the biosphere assessment database has been taken into use (see end of section 10.1). Further, the key model knowledge basis is summarised at the safety case level in the Models and Data report.

Biosphere description Site-specific data A main goal with the BSD-2009 (Haapanen et al. 2009) was to strengthen the link between the biosphere description and the subsequent biosphere assessment sub-processes, especially radionuclide transport modelling. This goal has been achieved, parameter values are recommended in (Haapanen et al 2009) for further use in safety assessment modelling; the recommended data are based on site-specific data obtained through field or laboratory sample measurements, or appropriate literature. However, even though the main goal has been achieved, more work is needed in the future to increase the site-specific data basis in order to improve the management of uncertainties, especially regarding key parameters and key radionuclides.

Terrain and ecosystem development Surface and near-surface hydrological modelling The need for improving the hydrological modelling of overburden and upper bedrock had earlier been identified (e.g., in Broed et al. 2007). The present assessment has a three-dimensional hydrological model that calculates the overall and object-specific water balances for the surface and near-surface of Olkiluoto Island (Karvonen 2008, 2009a-c). The model was used when describing the present-day conditions, when forecasting the hydrological development of the surface environments and in the landscape modelling.

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Forecasting The most important improvements in the applied forecasts of the surface environments (Ikonen et al. 2010) are the full use of the GIS toolbox UNTAMO, the use of a new statistical high-resolution elevation model and an update of the existing land uplift model. UNTAMO was used to forecast relevant properties of the future biosphere, such as changes in the topography (land uplift, crust tilting, sea level changes, physical and biological sedimentation, and erosion), to identify surface water bodies and to estimate runoff, as well as to estimate vegetation types.

Landscape modelling and radionuclide transport models Delineation of biosphere objects In the present assessment the biosphere objects have still been delineated by expert judgement supported by topographical and surface hydrological data, but unlike earlier the input data for each object in the landscape model is automatically extracted from the forecasts into a format that is readily transferrable to the overall parameter database. This removes human error and a large amount of manual work and enables wider use of time-dependent properties of the objects.

Biosphere object modules The used biosphere object modules (forest, wetland, cropland, lake, river and coast) has been revised and are now consistent at a conceptual level, meaning that the structure of compartments is very similar in all models.

Radiological consequences analysis Assessing doses to humans The dose assessment used is a refinement of the concept developed and applied in Broed et al. (2007) and has been extended to a comprehensive dose assessment. The extension has especially focused on harmonising the dose assessment with international recommendations, ensuring an adequate level of conservatism, and extending the assessment to address all regulatory dose constraints. Thus, the regulatory dose constraints to other people as well as most exposed people are addressed.

Doses to other biota The present assessment is the first assessment by Posiva where potential radiological consequences to other biota have been quantified. A methodology mainly based on the ERICA integrated approach has been developed and implemented. Typical absorbed dose rates to flora and fauna of the types currently present at the site are estimated and compared with the organism group-specific screening values recommended by the PROTECT project (Andersson et al. 2008).

10.3 On-going work and remaining issues As discussed above, significant development has been made to the present assessment since the KBS-3H safety studies in 2006-2007. However, some issues remain to be further developed as outlined in the TKS-2009 programme (Posiva 2009), summarised and complemented in the following.

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Transparency, traceability and robustness Even though significant progress has been made to the current assessment, there is still a need to continue to address this topic with high priority. This includes, among other tasks, continued improvement of the documentation of modelling work and the flow of information; especially the combination of various literature data with each other and with the site data has been problematic to handle due to the extensiveness of data and the large number of conversions and assumptions needed (Helin et al. 2010) − the workflow and its tracking will be improved for the 2012 assessment. In addition, the redundancy in the biosphere modelling capability will be strengthened. The primary focus is on building an additional capability to perform radionuclide transport modelling as a complement to the modelling tool currently used, initially at least concerning the most important parts of the assessment (e.g., Kyllönen & Keto 2010). The purpose of building an additional modelling capability is two-fold: first, it will increase the confidence in the outcome of the more complex landscape modelling by performing verifying calculations, and second, it will decrease the risk of losing the ability to perform a sufficient biosphere assessment in the case of losses of key resources, especially key persons.

Management of uncertainties The biosphere assessment will continue to focus on deriving site-specific data, and identifying suitable literature data, to use in the sub-processes of radionuclide transport modelling and radiological consequences analysis. The work of deriving site-specific parameter values for key parameters, such as concentration ratios, will be performed for more radionuclides. Bayesian updating of literature data with site-specific data (Helin et al. 2010) will be improved by expanding the literature review and introducing the new site data as they become available. Also, the ongoing project to acquire suitable sorption data by site sampling (Lusa et al. 2009), experiments and literature review will greatly contribute to the improved reliability of modelling results. To better quantify the probability density functions for the site -specific data, appropriate statistical methods will be used within the biosphere description sub-process.

Formulation of scenarios and calculation cases The classification of scenarios adopted for the purposes of the recent safety assessments will be updated for the PSAR 2012 based on guidance in YVL E.5. This issue is closely related to the management of uncertainties. The approach presented in the current report to formulating dose assessment scenarios and deriving biosphere calculation cases will be further developed and implemented. Due to vast diversity of potential calculation cases in the biosphere, compared with the near-field and geosphere systems, not all possible paths of evolution and parameter uncertainties will be explored with specific calculation cases. The approach in the biosphere assessment will likely focus on identifying key targets for the calculation cases to be assessed, in order to ensure that the main uncertainties have been bounded justifiably.

In addition to the dose assessment scenarios, two stylised well scenarios have been applied to derive safety indicators (indicative annual doses received by a representative member of the most exposed people). The formulation of well scenarios will be updated for the 2012 assessment, to better harmonise with the purpose of safety indicators as being a support to the safety case, by building understanding of, and confidence in, the outcome and conclusions of the safety assessment. Especially the level of conservatism

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in the well scenarios needs to be audited against the level applied in the graded approach to radionuclide transport modelling; it would be preferable if the level of conservatism for safety indicators were higher than for the primary quantities used in the compliance assessment. Further, the conceptual and mathematical models used when analysing well scenarios will be implemented so that they can be used either for deriving safety indicators or, with minor adjustments, directly used as biosphere objects in the landscape model.

Consistency between geosphere and biosphere assessment models In the radionuclide transport modelling, the transition from bedrock groundwater to biosphere should take place without gaps between the top of bedrock and the ecosystem. The coupling between the bedrock flow model and the surface hydrology model will be improved by initially transferring the top boundary condition of the bedrock flow model from the simulations with the surface hydrology model (Posiva 2009). The transport modelling in the biosphere assessment will in the future be closer integrated with the geosphere flow and transport modelling. The model interface in the transport modelling will be based on this coupling and on the interface between the surface and bedrock flow models, and on the continuation of the radionuclide release paths from the bedrock through the overburden to rooting zone and surface water bodies. The first implementation of the interface, although only in the geosphere-to-biosphere direction, was used in BSA-2009 and will be further improved for the 2012 assessment, including the top boundary condition to the bedrock groundwater flow modelling from the surface and near-surface hydrological model, further based on the terrain and ecosystem forecasts.

Assessing doses to other biota In the current assessment, typical absorbed dose rates to flora and fauna of the types currently present at the site are estimated, mainly based on the ERICA integrated approach. This approach is not as mature as the corresponding dose assessment process for humans, but is widely accepted internationally. Further developments will be followed and implemented in the biosphere assessment where reasonable. Also, use will be made of the results from the EU PROTECT project (Andersson et al. 2008) and of the BIOPROTA projects on the assessment for the other biota (www.bioprota.com). An important matter to address is that justification of the ellipsoidal geometry, especially for plants, has been found difficult. Thus, alternative approaches will be considered for the 2012 assessment.

Ecosystem models versus transfer factor approach in radionuclide transport modelling In the present assessment, as in earlier assessments, the radionuclide transport modelling is based on the transfer factor approach. It is acknowledged that using quantitative ecosystem models instead is a valuable goal, due to their mechanistic and site-derived nature. However, reaching that goal would require an exhaustive scientific study and site characterisation that cannot be hastened without jeopardising a thorough analysis of the data. It should also be noted that with the unavoidable uncertainties in the ecosystem models, they would not necessarily result in more accurate predictions of radionuclide concentrations than the transfer factor models.

The main role of ecosystem modelling, for the moment, is to support the transfer factor based assessment modelling (radionuclide transport and dose assessment modelling).

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This includes ensuring that the significant features and processes are included and represented properly in assessment models and analysing the site and regional data to derive high-quality input data for assessment modelling. The biosphere object modules (section 5.3) have been updated to better correspond to the features and processes of the site. The iteration with the biosphere description sub-process will be continued, but no major changes are expected.

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LIST OF REPORTS

POSIVA-REPORTS 2010

_______________________________________________________________________________________

POSIVA 2010-01 Models and Data Report 2010

Barbara Pastina, Saanio & Riekkola Oy

Pirjo Hellä, Pöyry Oyj

ISBN 978-951-652-172-8

March 2010

POSIVA 2010-02 Interim Summary Report of the Safety Case 2009

Posiva Oy

ISBN 978-951-652-173-5

March 2010

POSIVA 2010-03 Biosphere Assessment Report 2009

Hjerpe Thomas, Saanio & Riekkola Oy

Ikonen Ari T. K., Posiva Oy

Broed Robert, Facilia AB

ISBN 978-951-652-174-2

March 2010

biosphere assessment report 2009 - posiva · biosphere assessment report 2009 march 2010 thomas...

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