Fracture Mineral Investigations in 2014 –Characteristics of Fillings Associated with

Black Pigment and Geochemical andIsotopic Modelling of Littorina Infiltration

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POSIVA OY

Olki luoto

FI-27160 EURAJOKI, F INLAND

Phone (02) 8372 31 (nat. ) , (+358-2-) 8372 31 ( int. )

Fax (02) 8372 3809 (nat. ) , (+358-2-) 8372 3809 ( int. )

March 2017

Working Report 2016-59

El ina Sahlstedt, Juha A. Karhu

March 2017

Working Reports contain information on work in progress

or pending completion.

El ina Sahlstedt, Juha A. Karhu

University of Helsinki , Department of Geosciences and Geography

Working Report 2016-59

Fracture Mineral Investigations in 2014 –Characteristics of Fillings Associated with

Black Pigment and Geochemical andIsotopic Modelling of Littorina Infiltration

ABSTRACT

Fracture fillings containing black pigment material were studied from seven samples. The black pigment may represent a precursor of pyrite which is formed in bacterial sulfate reduction (BSR). The calcite (±pyrite, clays) fillings associated with the fractures containing black pigment belonged to Groups 1, 3 and 5. The δ13C and δ18O values of the calcite fillings were -13.1 ‰ to +7.1 ‰ and -10.1 ‰ to -6.8 ‰, respectively, and within the ranges obtained in previous studies for the calcite fillings. The fracture surfaces were closely examined under binocular microscope, in thin sections and in electron microprobe, but the black pigment-material could not be identified. The samples did contain, however, very dark clays (chlorite) and graphite, which may contribute to the observation of black pigmented material in the fractures. Further, the fracture contained tiny pyrite crystals which could represent the end product of BSR.

Mass balance modeling was performed to investigate Littorina Sea infiltration. The modelling was based on the assumption that Littorina Sea water is first modified in the sea bottom sediments (BSR, ion exchange reactions) and then mixed in the bedrock with glacial and subglacial waters. Further, mixing of these three components and variable mineral (+CH4, organic matter) – water reactions resulted in the formation of the Littorina derived groundwaters in the bedrock. The results indicate that reactions occurring in the sea bottom sediments have a strong effect on the modelling results, especially concerning the sulfur and carbon cycling. The results highlight the uncertainty related to SO4

2- concentrations in the initial waters and suggest that Littorina Sea water was variably influenced by BSR in the sea bottom sediments prior to infiltration. The mass balance models indicated either consumption of CH4 or organic matter (CH2O) in BSR, together with the precipitation of pyrite and calcite. Models showing calcite and/or pyrite dissolution are considered less reliable based on other geochemical and mineralogical evidence from the site. The δ34S values of dissolved SO4

2- in Littorina derived groundwaters can be reasonably well explained by the modelled mixing and sulfate reduction reactions. The δ13C values of DIC calculated by the models were typically lower compared to the δ13C values of the groundwaters, except for models which showed calcite dissolution. Therefore, additional reactions or input from other carbon sources have affected the δ13C values of the groundwaters. In models showing calcite precipitation, the model calculated δ13C values for precipitating calcite are comparable to the δ13C values of late-stage calcite in the shallow bedrock (<50 m).

Keywords: fissure fillings, black pigment, calcite, stable isotopes, carbon isotopes, oxygen isotopes.

RAKOMINERAALITUTKIMUKSET VUODELTA 2014 - NK. MUSTAAN PIG-MENTTIIN LIITTYVÄT RAONTÄYTTEET SEKÄ LITORINA SUOTAUTU-MISEN GEOKEMIALLISIA JA ISOTOOPPIMALLINNUSTARKASTELUJA

TIIVISTELMÄ

Työssä tutkittiin rakomineralisaatioita, joissa on havaittu mustaa materiaalia tai pigmenttiä rakopinnalla. Tämän pigmenttimateriaalin uskotaan mahdollisesti liittyvän bakteerien katalysoimaan sulfaatin pelkistykseen ja edustavan sulfidimineralisaation varhaista vaihetta. Rakotäytteet koostuivat ryhmien 1, 3 ja 5 kalsiittista (±pyriitti, savi). Rakokalsiittien δ13C arvot vaihtelivat välillä -13.1 ‰…+7.1 ‰ ja δ18O arvot välillä -10.1 ‰…-6.8 ‰. Rakokalsiittien δ13C ja δ18O arvot eivät eroa aikaisemmissa tutkimuksissa kullekin ryhmälle saaduista arvoista. Rakopintoja tutkittiin stereo-mikroskoopilla, ohuthieistä ja elektronimikroprobilla, mutta mustaa pigmenttimäistä ainetta ei löydetty. Näytteissä oli sen sijaan hyvin tummia savipintoja (kloriitti) ja grafiittia, mikä saattaa vaikuttaa havaintoihin mustasta pigmenttimäisestä materiaalista. Osassa näytteitä oli myös pienikiteistä pyriittiä, joka saattaa edustaa sulfaatin pelkistyksen lopputuotetta.

Litorina merivaiheen infiltraatiota kallioperään mallinnettiin massa tasapainoreaktiona. Malli perustuu oletukseen, että ennen infiltraatiota kallioperään, Litorina vaiheen murtovesi reagoi merenpohjan sedimentissa (sulfaatin pelkistys, ioninvaihtoreaktiot) ja sekoittuu edelleen kallioperässä glasiaali ja subglasiaalivesien kanssa. Tämä sekoittu-minen ja vaihtelevat mineraali (+ metaani, orgaaninen aines)- vesi reaktiot ovat johtaneet niihin Litorina peräisiin pohjavesiin, joita kallioperässä tavataan nykyisin. Työssä saadut tulokset viittaavat siihen, että merenpohjan sedimenteissä tapahtuvilla reaktioilla on suuri vaikutus massatasapainomallien tuloksiin, erityisesti reaktioihin, jotka liittyvät rikin ja hiilen kiertoon kallioperässä. Erityisesti epävarmuus lähtövesien SO4

2--konsentraatioissa vaikuttaa mallinnustuloksiin ja viittaa siihen että Litorina vedet reagoivat vaihtelevalla tavalla sulfaatin pelkistyksen suhteen merenpohjan sedimen-teissä. Massatasapainolaskelmat osoittavat joko metaanin tai orgaanisen aineksen kulutusta reaktioissa ja pyriitin ja kalsiitin kiteytymistä. Mallit, joissa pyriittiä tai kalsiittia liukenee, ovat muiden mineralogisten ja geokemiallisten havaintojen perusteella vähemmän luotettavia. Massatasapanomallit kykenivät suhteellisen tarkasti toistaamaan sulfaatin reaktiot Litorina lähtöisissä pohjavesissä, perustuen lasken-nallisten ja mitattujen δ34S arvojen vertailuun. Malleista saadut laskennalliset liuenneen hiilen δ13C arvot olivat tyypillisesti alempia kuin pohjavesistä mitatut, lukuun ottamatta malleja, joissa kalsiittia liukenee. Tämän perusteella vaikuttaa siltä, että pohjavesien hiilen kierto on ollut monimutkaisempi massatasapainomalleihin verrattuna. Mallit, joissa kalsiittia kiteytyi, antoivat kiteytyvälle kalsiitille sellaisia laskennallisia δ13C arvoja, jotka vastaavat alle 50 m syvyydellä olevien kalsiittien δ13C arvoja.

Avainsanat: raontäyte, musta pigmentti, kalsiitti, stabiilit isotoopit, hiilen isotoopit, hapen isotoopit.

 

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TABLE OF CONTENTS

ABSTRACT TIIVISTELMÄ 1. INTRODUCTION ...................................................................................................... 3

1.1. Geological and hydrogeochemical setting .......................................................... 3 2. MATERIALS AND METHODS .................................................................................. 5 3. RESULTS ................................................................................................................. 7

3.1. Sample descriptions ........................................................................................... 7 3.2. Isotope composition ......................................................................................... 16

4. GEOCHEMICAL MODELING ................................................................................. 19 4.1. Materials and methods ..................................................................................... 19 4.2. Modelling scenario ........................................................................................... 19 4.3. Initial and final waters ....................................................................................... 20 4.4. Modelling parameters ....................................................................................... 23 4.5. Results ............................................................................................................. 24

4.5.1. Test models ............................................................................................... 24 4.5.2. Mass balance models ................................................................................ 26

5. DISCUSSION ......................................................................................................... 29 5.1. Mineralogy and isotopic composition of fracture fillings .................................... 29 5.2 Modelling results and implications to Littorina infiltration .................................... 32

5.2.1. Sulfate concentrations and implications to initial water compositions ......... 32 5.2.2. Mass balance models ................................................................................ 32 5.2.3. Sulfur isotopes ........................................................................................... 32 5.2.4. Carbon isotopes ......................................................................................... 36 5.2.5. Concluding remarks ................................................................................... 41

6. SUMMARY ............................................................................................................. 43 7. REFERENCES ....................................................................................................... 45

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1. INTRODUCTION

The study of fracture filling minerals aids in the determination of paleohydrogeological evolution of the Olkiluoto island. Information obtained from the fracture minerals (stable isotopes, chemical composition) can also be compared to the composition of the groundwaters to show possible changes in the geochemical environment. Recent studies have shown changes in the redox conditions of the shallow bedrock, recorded by the carbon isotope composition of the calcite fillings (Sahlstedt et al., 2009, 2010, 2014a, b, c). Detailed studies of the sulfur isotopes of fracture pyrite (Sahlstedt et al. 2013) and carbon isotopes of fracture calcite (Sahlstedt et al., 2016) have shown evidence of bacterial sulfate reduction (BSR) in the shallow bedrock and a distinct redox stratification in the upper ~100 m.

The aim of this study was two-fold. First, we will characterize fracture filling calcite associated with fracture containing so called “black pigment”. The black pigment is thought to represent possibly an early stage of sulfide mineralization associated with BSR in the fractures. BSR is an important process in the fractures which cycles sulfur and carbon. The early sulfide precipitates associated with BSR are often amorphous and/or cryptocrystalline precipitates, appear very dark in colour and are easily reoxidized. The second aim of this study is to model Littorina infiltration episode using the NETPATH mass balance modelling tool (Plummer et al. 1994). The aim of the modelling is to investigate the infiltration process and possible mixing and mineral-water reactions in the bedrock. The modelling results, which will include carbon and sulfur isotope data can be compared to the fracture fillings and current groundwater chemistry in order to examine the validity of the resulting models.

1.1. Geological and hydrogeochemical setting

Olkiluoto is located on the western coast of Finland ca. 15 km north of the town of Rauma. Geologically, the area belongs to the pelitic migmatite belt (PEMB, see Figure 4-3 in Posiva, 2013) of the southern Satakunta region. Overview of the geological evolution and bedrock of Olkiluoto can be found in Posiva (2013) and is briefly summarized here (for more details see Posiva 2013, and references therein). The bedrock of Olkiluoto is composed of high grade metamorphosed supracrustal rocks, which took part of or formed during the Svecofennian orogeny ca. 1.9-1.8 Ga. These rocks are divided into four major groups based on their mineralogy, texture and type of migmatitic structure as follows: migmatitic gneisses, tonalitic-granodioritic-granitic gneisses, other gneisses (mica, quartz and mafic gneisses) and pegmatitic granite. These rocks are cut by a few diabase veins. To the east of the area is located the Mesoproterozoic Laitila rapakivi batholith (1583±3 Ma, Vaasjoki, 1996) and the smaller Eurajoki rapakivi stock (1571±3 Ma to 1548±3 Ma, Vaasjoki, 1996). Satakunta sandstone formation is located on the eastern border of the Laitila batholith, continuing along its eastern and northern margin into the Baltic Sea. The sandstone and rapakivi granite are cut by Mesoproterozoic olivine diabase (1.27-1.26 Ga, Suominen, 1991).

The hydrogeochemcal conditions at Olkiluoto are described in Posiva (2013) and Pitkänen et al. (2004) and are shortly summarized here. Based on the distribution of major ions in groundwaters, stable isotope composition of water and salinities determined as the amount of total dissolved solids (TDS), the groundwater in the

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bedrock are divided in to four groups, which occur in roughly horizontal layers. The salinity of the groundwaters increase with depth. The shallow bedrock, from ground surface to depths of about 150 m, are characterized by fresh to brackish HCO3

--type groundwaters. These waters have the shortest residence times, because they are highly affected by modern water sources composed of meteoric water, Baltic Sea water and surface water (Korvesuo reservoir). In the brackish HCO3

--type waters, modern waters are mixed with Littorina Sea water. The groundwaters at the depth range of 150 m to approximately 300 m are characterized by high SO4

2--concentrations and formed by mixing of Littorina Sea water with older glacial and subglacial groundwater in the bedrock, based on the δ18O values of the groundwaters. Below the brackish SO4

2--type groundwaters are brackish Cl--type groundwaters (down to depths of ~400m) and saline groundwaters (>400 m). The brackish Cl-type groundwaters are diluted saline waters. Based on low δ18O values of the brackish Cl--type groundwaters, the dilution was caused by infiltration of old meteoric water of a colder time period. The residence time of the saline groundwaters are estimated to be over million years, and they may be related to ancient hydrothermal events.

 

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2. MATERIALS AND METHODS

Samples were selected from water conducting and calcite bearing fractures, which were associated or contained black pigment. These black pigmented areas on the fractures appeared as matte-black surfaces. The fracture surfaces typically contained clays, calcite and sulfide (pyrite). Polished thin sections were prepared from the samples, which cut the fracture perpendicular relative to the fracture plain and thus displayed cross section of the fracture filling. The fracture filling was studied using standard petrological microscope and electron microprobe.

Table 1. Description of the samples.

sample N:o

drill core/length (m) fracture transmissivity (m2/s)

Short description

7-1 OL-KR3/45.98-46.05 2.95E-10

Clay and calcite containing thin (<500 µm) fracture filling. Calcite is mostly covered by brownish clay.

7-2 OL-KR3/51.94-51.95 1.41E-9 Chloritized fracture surface with a thin calcite + pyrite filling

7-3 OL-KR3/60.43-60.46 6.31E-9 The fracture surface contains mixed layers of calcite, clay and pyrite. Dark areas on the surface appear to be very dark green chlorite, which forms spherical clusters. Calcite appears as clear, translucent layer between clay layers. Calcite on the fracture surface has a weathered appearance and shows signs of dissolution, most likely due to acid testing performed with drill core logging.

7-4 OL-KR45B/41.71-41.83 Fracture filling contains dusky calcite which follows the fracture surface closely. Parts of the surface is dusted with small pyrite grains. Cross section of the sample reveals that the calcite has interlayers of small grained silicate lenses and inclusions of larger pyrite crystals.

7-5 OL-KR47/105.84-105.91

1.54E-9 The sample contains a thick calcite and pyrite filling. The surface of the calcite is dusted with small pyrite grains which are slightly oxidized.

7-6 OL-KR47/116.86-116.90

3.41E-8 The sample contains an uneven fracture surface which is partly covered by platy calcite and pyrite.

7-7 OL-KR47/159.43-159.53

Thin (100-200 µm), nearly translucent calcite filling, appears partly white in parts where the calcite is partly detached from the surface. Comparing the fracture surfaces shows that the calcite filling was continuous in the fracture.

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The composition of the calcite was analysed at the University of Helsinki, with a Jeol JXA-8600 superprobe. The analysis spots were selected according to the back scattered electron images (BEI) obtained from the samples. The amounts of Ca, Mn, Mg, Fe and Sr were measured in wave dispersive mode (WDS) using an accelerating voltage of 15 kV, a 5 nA beam current and a 15 μm spot size. The following standards, mounted on MINM25-53 Serial BC standard mount (Astimex Scientific Limited) were used: calcite for Ca, dolomite for Mg, hematite for Fe, celestite (Sr sulfate) for Sr and Mn containing silicate for Mn. Oxygen concentrations were calculated from the cation stoichiometry and the rest was contributed to carbon. The results of WDS analyses are presented in Appendix 1.

Calcite subsamples were separated using a steel blade according to the structures of the fillings. Approximately ~100-150µg of calcite was reacted with concentrated phosphoric acid for at least 1 h at 70 °C. The evolved CO2 gas was analysed by a Thermo Finnigan Delta Advantage gas source mass spectrometer running in a continuous flow mode (Sahlstedt et al. 2009). The reproducibility was ±0.1 ‰ for δ13C values and ±0.2 ‰ for δ18O values (or better), determined from multiple analyses of a reference calcite sample. The results are reported using the δ-notation defined as:

δX = (Rsample / Rstandard – 1)×1000 ‰ (Eq. 1)

where X is either 13C or 18O and R is either 13C/12C or 18O/16O. The δ13C and δ18O values are reported with respect to the VPDB (Vienna Pee Dee Belemnite) standard.

 

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3. RESULTS

3.1. Sample descriptions

Sample 7-1: OL-KR3/45.98-46.05

The sample contains a fracture surface with a thin, discontinuous layer of grayish calcite and a more continuous layer of greenish clay (Figure 1). Calcite is mostly covered by a brownish layer of clay. Small amount of euhedral calcite crystals are found on the fracture surface. The calcite is contains minor amount of Mn, 0.3-0.5 wt% (Appendix 1). EDS analyses of the clay indicates that it is Fe and Mg rich, likely chlorite. Clay adjacent to the fracture surface is more Fe-rich (chamosite?) compared to the clay on the surface of the calcite. The δ13C value of the euhedral calcite is -11.2 ‰ and δ18O value is -8.9 ‰ (average of two analyses). The δ13C value of the clay covered calcite is 7.1 ‰ and the δ18O value is -8.6 ‰.

Sample 7-2: OL-KR3/51.94-51.95

The sample contains a discontinuous calcite and pyrite fracture filling (Figure 2). Below the calcite is a thinner, greenish layer of clay, which is also found partly covering the calcite layer. Structure of the filling suggest that precipitation of the calcite closed the fracture, which was later reopened. Small calcite crystals with euhedral character are found on places on top of the continuous calcite layer (Figure 2). The calcite contains Mn 1.7-2.1 w% and < 0.3 wt% of Mg and Fe (Appendix 1). The δ13C value of the clay covered calcite is -9.9 ‰ and the δ18O value is -8.4 ‰ (fracture at 51.94 m core depth). The amount of euhedral crystals were not sufficient for isotope analysis.

Sample 7-3: OL-KR3/60.43-60.46

The sample contains a fracture filling composed of clay, calcite and pyrite. The clay is dark to light green in colour. Calcite covering dark green chlorite layer is clear and anhedral. The weathered surface of the fracture fillings contains brownish calcite with dissolution marks (Figure 3). The dissolution marks are likely due to acid testing of the fracture surface for mineral identification purposes. The calcite contains minor amount of Mn, 0.4-0.6 wt% and Fe, ~0.1 wt% (Appendix 1). The δ13C and δ18O values of the clear, anhedral calcite are -10.4 and -9.1 ‰, respectively.

Sample 7-4: OL-KR45B/41.71.41.83

The sample contains a clear to white calcite filling covering a greenish clay + pyrite surface (Figure 4). Cross section of the filling reveals a series of interconnected veins filled with calcite and minor pyrite (Figure 4). The veins are separated by fine grained silicate (mainly quartz) sections. The calcite contains on average 0.7 wt% of Mn and 0.1 wt% of Fe. The δ13C and δ18O value of the calcite is -13.1 ‰ and -6.8 ‰, respectively.

Sample 7-5: OL-KR47/105.84-105.91

The sample contains a thick calcite and pyrite bearing filling (Figure 5). Small pyrite crystals are on top of the fracture filling. The calcite contains minor amounts of Mn,

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0.4-0.6 wt% and typically <0.1 wt% of Mg, Fe and Sr (Appendix 1). The δ13C and δ18O values of the calcite are -6.9 ‰ and -9.1 ‰, respectively (average of two analyses).

Sample 7-6: OL-KR47/116.86-116.90

The sample contains an uneven fracture surface with clay (chlorite), calcite and pyrite filling (Figure 6). Calcite and pyrite are found on two of the fracture surface plains. Small, euhedral crystals are on top of a more continuous, white layer of calcite. The calcite contains 0.4-0.6 wt% of Mn, 0.2-0.7 wt% of Fe, and typically < 0.1 wt% of Mg and Sr. The δ13C and δ18O value of the calcite anhedral calcite is 7.2 ‰ and -10.1 ‰, respectively.

Sample 7-7: OL-KR47/159.43-159.53

The sample contains a fracture surface with thin layer of nearly translucent calcite over greenish clay (Figure 7). The calcite contains minor omaounts of Mn, 0.2-0.8 wt%, and typically <0.1 wt5 of Mg, Fe and Sr (Appendix 1). The δ13C and δ18O values of the calcite are -4.4 ‰ and -7.6 ‰, respectively.

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Figure 1. Sample 7-1 (OL-KR3/45.98-46.06. a) Photograph of the fracture surface showing white calcite and greenish to gray clay. b) Microphotograph of the thin section showing calcite and greenish clay. c)-d) BE image showing the structure of the fracture filling. Numbers in the BE image refer to locations of the WDS analyses.

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Figure 2. Sample 7-2 (OL_KR3/51.94-51.95) a) Photograph of the sample showing grayish to white calcite covering parts of the sample. b) Microphotograph of the thin section, crossed polars. c) BE image of the fillings. Thin black crystals in the host rock are graphite. Numbers in the BE image refer to locations of the WDS analyses of calcite.

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Figure 3. Sample 7-3 (OL-KR3/60.43-60.46) a) Photograph of the fracture surface showing weathered calcite, green clay and pyrite. b) Thin section of the fracture surface, crossed polars. c) BE image of the filling showing homogenous calcite outlined by clay. Numbers in the BE image refer to locations of the WDS analyses.

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Figure 4. Sample 7-4 (OL-KR45B/41.71-41.83) a) Photograph of the fracture surface showing gray to white calcite filling covering parts of the fracture surface. b) Microphotograph showing the fracture filling, crossed polars. Calcite layers are intercepted by zones of fine grained feldspar and quartz. c) BE image of the filling showing calcite (light gray) and pyrite (white). Numbers in the BE image refer to locations of the WDS analyses.

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Figure 5. Sample 7-5 (OL-KR47/105.84-105.91) a) Photograph showing a thick white filling of calcite and pyrite. b) Thin section of the fracture filling. c)-d) BE image of the fracture filling with homogenous calcite (light gray) and pyrite (white). Numbers in the BE image refer to locations of the WDS analyses.

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Figure 6. Sample 7-6 (OL-KR47/116.86-116.90). a) Photograph showing the uneven fracture surface of the sample. Calcite (white) and pyrite (yellowish spots) form a thin filling on parts of the surface. b) Thin section of the sample showing thin calcite+clay layer (dark band on the surface). c) BE image of the filling showing layers of calcite (light gray) and silicate (patchy coloring). Numbers in the BE image refer to locations of the WDS analyses.

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Figure 7. Sample 7-7 (OL-KR47/159.43-159.53) a) Photograph of the fracture surface showing white to nearly translucent (dark due to host rock) calcite. White calcite parts are partly detached from the surface. b) Thin section of the fracture surface. Black crystals in the host rock and on fracture surface are graphite. c) BE image of the filling. Numbers in the BE image refer to locations of the WDS analyses of calcite.

 

 

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3.2. Isotope composition

The results of the carbon and oxygen isotope analyses are presented in Table 2 and Figures 8 and 9. The δ13C values of calcite in this study varied from -13.1 ‰ to +7.1 ‰ (Table 1, Figure 9) and the δ18O values ranged from -10.1 ‰ to -6.8 ‰ (Table 1, Figure 8). The samples are from the depth range of 0-150 m and fall in to the range of the previous results (Figures 8-9).

Table 2. Isotopic composition of the fracture fillings.

Sample #  Drill core/length  depth  13C (‰, PDB)  18O (‰, PDB)  group  note 

 7‐1  OL‐KR3/45.98‐46.05 

‐35.5  ‐11.56 ‐8.7 1 translucent euhedral crystals

  ‐10.92 ‐9.13 1 murky euhedral crystals

  7.05 ‐8.62 3 continuous calcite layer

 7‐2  OL‐KR3/51.94‐51.95 

‐40.99  ‐9.92 ‐8.4 3 clay containing calcite at 51.95

  ‐4.38 ‐8.28 3 clay containing calcite at 51.94

 7‐3  OL‐KR3/60.43‐60.46 

‐48.82  ‐10.43 ‐9.11 3 translucent calcite on clay

 7‐4  OL‐KR45B/41.71‐41.83 

‐41.7  ‐13.08 ‐6.8 3 compact calcite layer

 7‐5  OL‐KR47/105.84‐105.91 

‐85.2  ‐6.93 ‐9.1 5 massive calcite

 7‐6  OL‐KR47/116.86‐116.90 

‐94.2  ‐7.2 ‐10.08 3? translucent calcite

 7‐7  OL‐KR47/159.43‐159.53 

‐129  ‐4.44 ‐7.62 3 thin calcite layer

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Figure 8. Oxygen isotope composition of the fracture filling calcite at Olkiluoto. Larger symbols show the results obtained in this study, smaller symbols show the data obtained in previous studies (Sahlstedt et al. 2009, 2010, 2014a, b, c). Different groundwater types are named in the approximate depth range they appear.

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Figure 9. Carbon isotope composition of the fracture filling calcite at Olkiluoto. Larger symbols show the results obtained in this study, smaller symbols show the data obtained in previous studies (Sahlstedt et al. 2009, 2010, 2014a, b, c). Different groundwater types are named in the approximate depth range they appear.

 

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4. GEOCHEMICAL MODELING

The aim of this modeling exercise is to study the Littorina infiltration event at Olkiluoto. The Littorina Sea infiltration occurred during the brackish stage of the Baltic Sea ca. 6.5-3 ka (Widerlund and Andersson, 2011) when the more saline water of Littorina Sea replaced the less saline glacial mixtures in the bedrock to depths of approximately 300 m in a so called density turnover (Posiva, 2013). The geochemical evolution of the infiltrating Littorina Sea water was schematically described by Pitkänen et al. (1999). The evolution model (Fig. 8.3., Pitkänen et al., 1999) is extended here and includes examination of the carbon and sulfur isotope effects of different reactions included in the mixing process and mineral-water reactions.

4.1. Materials and methods

The waters used in the modeling are obtained from the OIVA database (Pitkänen et al. 2007) and the end member water compositions presented for Littorina Sea and Glacial water in Pitkänen et al. (1999, 2004). Subglacial end member was derived from the data presented in Pitkänen et al. (1999), but with the Cl--concentration modified to the level of 3000 mg/L (Hellä et al., 2014). The modeling was conducted using the PHREEQC and NETPATH-WIN programs (El-Kadi et al. 2011). PHREEQC program was used to equilibrate initial waters (calcite equilibrium) and NETPATH-WIN was used in mass balance calculations.

4.2. Modelling scenario

The first scenario was build according to the model suggested by Pitkänen et al. (1999) for Littorina infiltration and schematically represented in Figure 10. First step of the model includes the calculation of preliminary sulfate reduction step occurring in the sea bottom sediments, accompanied by ion exchange reactions (Na, K and Mg for Ca and Fe). This step is thought to result in minor decrease in SO4

2- concentration by bacterial sulfate reduction (BSR), estimated to be approximately 110 mg/L (Pitkänen et al., 1999), which will introduce a 5 ‰ increase in the δ34S value of SO4

2- by Rayleigh fractionation (fractionation factor -45 ‰). The evolution of sulfur isotopes of SO4

2- means that the system is closed with respect to sulfate and will maintain the SO4

2- concentration and the δ34S value of sulfate until further reactions such as mixing and BSR occurring in the bedrock.

This sediment modified Littorina end member (Littorina sediment) is used in mass balance calculations. The calculations will consider mixing with end member water types pre-existing in the bedrock prior to Littorina infiltration, i.e. subglacial and glacial water types (e.g. Pitkänen et al., 1999, 2004, Posiva 2013), and further mineral-water reactions, which will transfer species between solid and liquid phases in order to fill the mass balance calculations defined as:

Initial water(s) +"Reactant phases"= Final water+ "Product phases"

 

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Figure 10. Conceptual image of Littorina Sea water infiltration at Olkiluoto. The principles depicted in the diagram are used as a basis of the modelling (modified after Pitkänen et al., 1999).

4.3. Initial and final waters

Littorina Sea water reacts in the overburden before infiltration to the bedrock fractures (Fig. 10, Pitkänen et al., 1999). The main reaction in the sediment is sulfate reduction and associated degradation of organic matter. This reaction will decrease SO4

2- concentration, increase DIC concentration and modify the δ13CDIC and δ34SSO4 values of the Littorina Sea water. The reaction occurs according to the following equation:

SO42- + 2CH2O HS- + 2HCO3

- (Eq. 2)

where organic matter is identified as the simplified form CH2O. The effect of this is to consume 110 mg/L of SO4

2- and increase the DIC concentration by adding HCO3- in to

the water. Furthermore, the reaction will increase the δ34SSO4 value by 5 ‰ (Rayleigh

effect) and decrease the δ13CDIC value from -1 ‰ to -12 ‰ due to the input of 13C depleted carbon from organic matter. The Ca and Fe concentrations will increase by exchange reactions with Na, K and Mg. Following procedure was used to build this water type: First, the increase in alkalinity and decrease in SO4

2--concentration was calculated prior to equilibration of the water with calcite in PHREEQC. Second, the isotope effects were checked using NETPATH (Littorina water to “Littorina sediment” water). The water type is presented in Table 3.

Subglacial water was build using the data from Pitkänen et al. (1999) and adjusting the Cl-concentration to 3000 mg/L (Hellä et al. 2014). Note that the subglacial composition

21  

has been later re-evaluated, e.g. the δ18O value of the water is estimated to be closer to -12 ‰ (e.g. Posiva 2013). The water type was then allowed to form equilibrium with calcite using PhreeqC and the resulting composition is presented in Table 3. Glacial water type is derived from Pitkänen et al. (2004), Table 3-1 and also presented in Table 3.

Final waters were selected from the OIVA database (Pitkänen et al. 2007) and includes the Littorina derived brackish SO4

2--type waters designated as baseline waters. Furthermore, only samples containing both δ13C and δ34S data of DIC and SO4

2-, respectively, and alkalinity were used in modelling. The water samples fulfilling these requirements are: KR4_T132_2, KR6_135_1, KR7_282_1, KR8_302_1, KR19_110_1, KR20_186_1, KR23_192_1, KR27_124_1 and KR27_247_1. Temperatures were calculated according to the equation presented in Ahokas et al. (2008):

T = (313 - Z) / 67 (Eq. 3)

Where z is the elevation in m (a.s.l.).

 

22  

 

Table 3. Composition of the initial and final waters used in the modelling (dissolved solids in mg/l, tritiumin TU, δ-values in ‰).

well name Glacial  Sublaglacial  Litorina 

sediment  KR20_186_1#  KR19_110_1  KR4_T132_2  KR6_135_1  KR7_282_1  KR8_302_1  KR23_192_1  KR27_124_1  KR27_247_1 

temp  1  10  11  6.7¤  6.2¤  6.5¤  6.2¤  8.5¤  8.6¤  7¤  6.1¤  7.6¤ 

pH  5.8  9.3  7.2  7.9  7.6  7.5  7.8  7.6  7.8  7.6  7.9  7.6 

O2  7.2  0  0  0  0.003  0.001  0.003 

Alkalinity  0.16  43.9  197  42.5  146  92.1  148.5  95.2  44.5  135  127  140 

Tritium  0  0  0  0.2  2.5  0  4.1  1.6  10  0.94  1.9  1.66 

H2S  0  0.02  0.03  0  0.17  0.02  0  0  0 

Ca2+  0.13  13.69  506  260  770  700  517  390  1020  590  370  510 

Mg2+  0.1  1.28  402  34  120  260  130  92  130  210  89  190 

Na+  0.15  1829  3306  1360  1390  1870  1050  1200  2030  1480  888  1410 

K+  0.15  6.29  119  7.7  21  20  17  8.4  7  31  6.9  20 

Cl‐  0.7  3000  6500  2540  2850  4500  2850  2630  4770  3400  2050  3400 

SO42‐  0.05  1.76  780  240  410  510  352  320  470  440  250  400 

F‐  0  1.39  0.49  0.4  0.4  0.61  0.34  0.41  0.7  0.4  0.9  0.6 

SiO2  0.01  8.48  1.84  7  11  12.3  12.4  12  5.1  12  11  12 

Br‐  0.001  0  22.2  9.6  10  18  4.1  9.2  16  13  7.6  15 

B  1.2  0.51  0.54  0.5  0.8  0.8  0.39  0.4  0.39 

Ba2+  0.01  0.02  0  0.034  0.02  0.03 

Li+  0  0.05  0.07  0.07  0.09  0.08  0.05  0.076 

Sr2+  0.0001  0  2.68  3.1  4.3  6.7  5.1  2.4  8.7  5.4  4.1  5.7 

Fe  0.0001  0.13  55.8  0.08  0.71  0.32  0.73  0.12  0.02  1.121  0.26  0.63 

Mn  0  0.13  0  0.11  1.2  1.1  0.32  0.48  1.7  0.42  1 

DOC  2.15  0  0  3.6  8.6  5.2  1.6  0  0  0 

δ13CTDIC  ‐25  ‐20.9  ‐17  ‐24.3  ‐13.6  ‐12.1  ‐16.3  ‐18.2  ‐16.4  ‐14.3  ‐18.8  ‐16.1 

δ34SSO4  0  0 26.07  27.32  21.82  26.93  22.59  24.79  26.69  25.23  27.87  26.14 

δD  ‐166  ‐80.81  ‐37.8  ‐107.7  ‐75.8  ‐72.4  ‐80  ‐75.5  ‐79.7  ‐73.9  ‐94.8  ‐72.2 

δ18O  ‐22  ‐10.35  ‐5  ‐14.64  ‐9.97  ‐9.5  ‐9.9  ‐9.9  ‐9.6  ‐9.81  ‐13.04  ‐9.99 

bold = initial waters,  #) same as Littorina high 34S, but with H2S set to 0 and temperature to 12°C (measured from sample), ¤) temperature calculated according to Eq. 3   

23  

4.4. Modelling parameters

The modeling parameters are presented in Table 4. Initial modelling concept used a simplified model in order to examine the extent of isotope effects caused by bacterial sulfate reduction and different carbon sources on the δ34S values of sulfate and pyrite and δ13C values of DIC and calcite (Sahlstedt et al., 20xx). The results of the simplified models could be used to observe the range of variation in the C- and S-isotope compositions of dissolved and precipitating species. However, it is difficult to estimate the true composition of the initial and final waters in the extreme cases of reactions (i.e. nearly all sulfate consumed) because groundwaters which took part in these reactions have not been preserved. In the following, a more realistic picture of the changes in chemical and isotopic compositions is obtained by using more realistic compositions for initial waters and measured compositions of Littorina derived groundwaters as final waters. Reacting mineral phases include calcite, pyrite, feldspar and clay minerals as well as organic matter (CH2O), methane and ion exchange.

Table 4. The parameters used in the modelling.

Initial wells:   CONSTRAINTS (11): 

 PHASES (12): 

1  Glacial   Carbon         CALCITE  

2  Litorina sediment   Sulfur        +CH4 GAS 

3  Subglacial   Calcium        PYRITE   

   Magnesiumc    CH2O 

Final wells:   Sodiumc    EXCHANGE 

(Ca/Na) 

  Litorina ref. high 34Sa)   Potassiumc      FeII‐Na  

  KR4_T132_2   Chloride      +ANORTHc 

  KR6_135_1   Silicac       +ALBITEc 

  KR7_282_1   Iron           KAOLINITc  

  KR8_302_1   Redox          Mg/Na EXc  

  KR19_110_1b)   Sulfur‐34      CHLORITEc 

  KR20_186_1     ILLITEc 

  KR23_192_1   

KR27_124_1   

KR27_247_1    a) Modified KR20_186_1; H2S set to 0, temperature 12°C b) Littorina low δ34S, temperature 12°C c) excluded from the simplified test model 

 

 

24  

4.5. Results

4.5.1. Test models

The model was tested first in a simplified form by selecting the waters with the highest and lowest δ34S values as the final water in the model. The groundwater samples had corresponding, low SO4

2--concentration (high δ34S) or high SO42--concentration (low

δ34S). A mass balance reaction model could be computed for the high δ34S value sample, but not for the low δ34S sample. All the other final waters were tested similarly and two other final wells, KR23_192_1 and KR27_124_1, could not produce a mass balance models with the specified parameters. The effect of uncertainty in the SO4 concentration was tested by adding NaSO4 to reacting phases in cases where the test modelling parameters did not produce mass balance model. Addition of NaSO4 to reacting phases produced a mass balance model for these final waters (KR19_110_1 i.e. Littorina low 34S, KR23_192_1 and KR27_124_1) but required the addition of large amount of SO4

2- (80-190 mg/kg of H2O) by dissolution of NaSO4. The results are presented in Table 5.

The mixing ratios indicated by the models show that Littorina sediment water and glacial water are the major contributors in most cases, except for final water KR8_302_1. Contribution from Littorina sediment water varies between 32-67 %, glacial water between 12-59 % and subglacial water between 1-27 % (Table 5). The model calculated carbon isotope compositions of final waters are modified by CH4 consumption (all test models) and calcite precipitation or dissolution. A δ13C value of -10 ‰ was given for the calcite phase in the model. Therefore, the calculated δ13CDIC values are higher in the models where calcite dissolves and lower in the case of calcite precipitation. Model calculated δ34S values of SO4

2- were determined by initial mixing and slightly modified by pyrite precipitation or dissolution. The calculated values were close to the measured δ34S values, with <1.5 ‰ difference.

25  

Table 5. Results of the test model. Phase exchanges are given in mmol/kg of water. Initial waters; init 1 = glacial, inti 2 = Littorina sediment, init 3 = subglacial, appreviatios; Calc = calculated, meas = measured, prec =precipitating, cc= calcite, py=pyrite.

Test model  Test model + NaSO4 

final well  final well 

reacting phase Litorina ref. high d34S  KR20_186_1  KR4_T132_2  KR8_302_1  KR27_247_1  KR6_135_1  KR7_282_1  reacting phase  KR19_110_1  KR23_192_1  KR27_124_1 

Init 1  0.52  0.52  0.28  0.12  0.47  0.54  0.59  Init 1  0.48  0.41  0.65 

Init 2  0.32  0.32  0.67  0.61  0.51  0.42  0.40  Init 2  0.37  0.46  0.29 

Init 3  0.16  0.16  0.06  0.27  0.02  0.05  0.01  Init 3  0.14  0.13  0.06 

CALCITE  ‐0.661  ‐0.657  ‐0.790  ‐1.635  0.488  1.508  0.427  CALCITE  0.383  ‐0.257  0.463 

CH4 GAS  0.105  0.105  0.264  0.117  0.056  0.173  0.201  CH4 GAS  0.673  0.810  0.567 

PYRITE  ‐0.035  ‐0.035  ‐0.050  ‐0.034  ‐0.003  0.139  0.049  PYRITE  ‐0.361  ‐0.443  ‐0.285 

CH2O  0  0  0  0  0  0  0  CH2O  0  0  0 

EXCHANGE  ‐3.108  ‐3.103  ‐9.852  ‐19.351  ‐5.763  ‐6.140  ‐4.272  EXCHANGE  ‐14.129  ‐9.107  ‐5.111 

FeII‐Na  0.281  0.281  0.613  0.579  0.501  0.545  0.447  Na2SO4  1.970  1.712  0.826 

isotopes  mg_SO4/kgw  189.3  164.5  79.3 

Carbon‐13 (calc)  ‐22.4  ‐22.5  ‐22.5  ‐23.7  ‐16.4  ‐15.6  ‐18.8 

DIC C‐13 (calc)  ‐22.4  ‐22.5  ‐22.1  ‐23.5  ‐16.4  ‐12.9  ‐17.2 

Sulfur‐34 (calc)  27.3  28.7  27.9  27.4  26.1  22.6  24.7 

Carbon‐13 (meas)  ‐24.3  ‐24.3  ‐14.14#  ‐17.72#  ‐16.1  ‐18.25#  ‐19.63# 

DIC C‐13 (meas)  ‐24.3  ‐24.3  ‐12.1  ‐16.4  ‐16.1  ‐16.3  ‐18.2 

Sulfur‐34 (meas)  27.32  27.31  26.92  26.68  26.14  22.59  24.71 

prec CC (average)  ‐17.49  ‐17.42  ‐15.01  ‐16.39  ‐  ‐  ‐ 

prec CH4 (average)  ‐  ‐  ‐  ‐  ‐  ‐  ‐ 

prec PY (average)  ‐19.53  ‐25.4&  ‐25.8&  ‐25.2&  ‐20.07  ‐  ‐ 

     

#) Samples contain DOC (designated 13Corg=‐25 ‰), which is included in the carbon‐13 value 

&) approximate values for precipitating pyrite recalculated according to Plummer et al. 1994 

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4.5.2. Mass balance models

Models obtained using the parameters presented in Table 4 can be divided into two general groups: 1) CH4 consuming group and 2) organic matter (CH2O) consuming group (Table 6). Between 10 and 16 models can be calculated for a single final well with different mineral-water and ion exchange reactions. All possible solutions for Littorina high δ34S reference water are presented in Table 6. It can be seen from the results that between the models the transfers of calcite, CH4 (CH4 consuming type) or organic matter (CH2O consuming type), pyrite, Fe2+-Na exchange and illite remain same, but transfers of plagioclase, kaolinite, Mg/Na exchange and chlorite are variable. Similar results were obtained also for the rest of the final wells, summarized in Table (7). In Table 7 the transfers of calcite, CH4, CH2O and pyrite, which affect the isotope compositions of carbon and sulfur in the final wells, are presented. The transfers of calcite, CH4, CH2O and pyrite remained the same for CH4 consuming models and for CH2O consuming models (cf. Table 6).

Mixing ratios, the amount of calcite precipitating (or dissolving) and consumption of CH4 or CH2O all affect the carbon isotope composition calculated for the final wells. CH4 consuming models obtain lowest δ13CDIC values, and calcite dissolving models the highest δ13CDIC values (Tables 6-7). The δ34SSO4 values of final wells are determined by the mixing ratios of initial wells, and the precipitation/dissolution of pyrite. The isotope evolution of final wells are further studied in the following discussion.

27  

Table 6. Results of mass balance models obtained for Littorina high δ34S water (see Table 3, KR20_186_1). The models can be divided into two general groups: CH4 consuming and organic matter consuming. Phase transfers are given in mmol/kg of water cc= calcite and py=pyrite, init 1 = glacial, init 2 = Littorina sediment, init 3 = subglacial.

Final well: Littorina high δ34S                       methane consuming              organic matter (CH2O) consuming   model #  #1  #2  #3  #4  #5  #6  #7  #8  #9  #10  #11  #12  #13  #14  #15  #16   Init 1  0.52  0.52  0.52  0.52  0.52  0.52  0.52  0.52  0.52  0.52  0.52  0.52  0.52  0.52  0.52  0.52 

Init 2  0.32  0.32  0.32  0.32  0.32  0.32  0.32  0.32  0.32  0.32  0.32  0.32  0.32  0.32  0.32  0.32 

Init 3  0.16  0.16  0.16  0.16  0.16  0.16  0.16  0.16  0.16  0.16  0.16  0.16  0.16  0.16  0.16  0.16 

CALCITE  ‐0.66  ‐0.66  ‐0.66  ‐0.66  ‐0.66  ‐0.66  ‐0.66  ‐0.66  ‐0.66  ‐0.66  ‐0.66  ‐0.77  ‐0.77  ‐0.77  ‐0.77  ‐0.77 

CH4 GAS  0.11  0.11  0.11  0.11  0.11  0.11  0.11  0.11  0.11  0.11  0.11 PYRITE  ‐0.03  ‐0.03  ‐0.03  ‐0.03  ‐0.03  ‐0.03  ‐0.03  ‐0.03  ‐0.03  ‐0.03  ‐0.03  ‐0.03  ‐0.03  ‐0.03  ‐0.03  ‐0.03 

CH2O  0.21  0.21  0.21  0.21  0.21 EXCHANGE  0.13  0.40  ‐3.11  0.04  ‐3.11  0.13  ‐3.11  0.09  ‐3.21  0.13  ‐3.21 

FeII‐Na  0.28  0.28  0.28  0.28  0.28  0.28  0.28  0.28  0.28  0.28  0.28  0.28  0.28  0.28  0.28  0.28 

ANORTH  3.24  3.51  3.11  3.11  3.11  3.14  3.24  3.11  3.30  3.35  3.21 

ALBITE  0.26  0.21  0.19  1.82  1.82  0.21  0.09  1.80  1.80  0.13 

KAOLINIT  0.19  2.46  ‐0.07  0.28  0.19  0.09 

Mg/Na EX  ‐0.27  3.24  0.03  0.13  2.33  2.33  0.03  2.45  2.45  0.07 

CHLORITE  ‐0.70  ‐0.76  ‐0.06  ‐0.70  ‐0.70  ‐0.68  ‐0.70  ‐0.24  ‐0.70  ‐0.24  ‐0.70  ‐0.70  ‐0.21  ‐0.70  ‐0.21  ‐0.69 

ILLITE  ‐1.33  ‐1.33  ‐1.33  ‐1.33  ‐1.33  ‐1.33  ‐1.33  ‐1.33  ‐1.33  ‐1.33  ‐1.33  ‐1.33  ‐1.33  ‐1.33  ‐1.33  ‐1.33 

computed  observed 

Carbon‐13  ‐22.4  ‐22.4  ‐22.4  ‐22.4  ‐22.4  ‐22.4  ‐22.4  ‐22.4  ‐22.4  ‐22.4  ‐22.4  ‐20.7  ‐20.7  ‐20.7  ‐20.7  ‐20.7  ‐24.3 

DIC C‐13  ‐22.4  ‐22.4  ‐22.4  ‐22.4  ‐22.4  ‐22.4  ‐22.4  ‐22.4  ‐22.4  ‐22.4  ‐22.4  ‐20.7  ‐20.7  ‐20.7  ‐20.7  ‐20.7  ‐24.3 

Sulfur‐34  27.3  27.3  27.3  27.3  27.3  27.3  27.3  27.3  27.3  27.3  27.3  27.3  27.3  27.3  27.3  27.3  27.32 

δ13C(cc)  ‐17.5  ‐17.5  ‐17.5  ‐17.5  ‐17.5  ‐17.5  ‐17.5  ‐17.5  ‐17.5  ‐17.5  ‐17.5  ‐16.7  ‐16.7  ‐16.7  ‐16.7  ‐16.7 

δ34S(py)  ‐19.5  ‐19.5  ‐19.5  ‐19.5  ‐19.5  ‐19.5  ‐19.5  ‐19.5  ‐19.5  ‐19.5  ‐19.5  ‐19.5  ‐19.5  ‐19.5  ‐19.5  ‐19.5 

28  

Table 7. Summary of the results of mass balance modeling for final wells KR20_186_1, KR4_T132_2, KR8_302_1, KR27_247_1, KR6_135_1 and KR7_282_1. The table shows only the transfers of calcite, CH4, CH2O and pyrite, which affect the isotope compositions of carbon and sulfur in the final wells. Modelling parameters are presented in Table 4. The models can be divided into two general groups: CH4 consuming and organic matter (CH2O) consuming. Phase transfers are given in mmol/kg of water (cf. Table 6). Mixing ratios for initial waters are same for both CH4 and CH2O consuming models. Init 1 = glacial, init 2=Littorina sediment, init 3 = subglacial, cc = calcite (average δ13C of precipitating calcite), py = pyrite (average δ34S of precipitating pyrite).

 

KR20_186_1  KR4_T132_2  KR8_302_1  KR27_247_1  KR6_135_1  KR7_282_1 

(no. of models)  (16)  (11)  (15)  (10)  (10)  (14) 

mixing 

Init 1  0.52  0.28  0.12  0.47  0.54  0.59 

Init 2  0.32  0.67  0.61  0.51  0.42  0.40 

Init 3  0.16  0.06  0.27  0.02  0.05  0.01 

methane consuming 

CALCITE  ‐0.66  ‐0.79  ‐1.63  0.49  1.51  0.43 

CH4 GAS  0.11  0.26  0.12  0.06  0.17  0.20 

PYRITE  ‐0.03  ‐0.05  ‐0.03  ‐0.003  0.14  0.05 

δ13Ctot  ‐22.5  ‐22.5  ‐23.7  ‐16.4  ‐15.6  ‐18.8 

δ13CDIC  ‐22.5  ‐22.1  ‐23.5  ‐16.4  ‐12.9  ‐17.2 

δ34S  28.7  27.9  27.4  26.1  22.6  24.7 

cc  ‐17.4  ‐15.0  ‐16.4 

py   ‐25.4&  ‐25.8&  ‐25.2&  ‐20.1 

organic consuming 

CALCITE  ‐0.76  ‐1.05  ‐1.75  0.43  1.33  0.23 

PYRITE  ‐0.03  ‐0.05  ‐0.03  ‐0.003  0.14  0.05 

"CH2O"  0.21  0.53  0.23  0.11  0.35  0.40 

δ13Ctot  ‐20.7  ‐20.9  ‐22.5  ‐16.2  ‐15.0  ‐17.9 

δ13CDIC  ‐20.7  ‐20.1  ‐22.1  ‐16.2  ‐12.2  ‐16.0 

δ34S  28.7  27.9  27.4  26.1  22.6  24.7 

cc  ‐16.6  ‐14.2  ‐15.9 

py   ‐25.4&  ‐25.8&  ‐25.2&  ‐20.1 

measured δ13Ctot  ‐24.3  ‐14.1  ‐17.7  ‐16.1  ‐18.2  ‐19.6 

δ13CDIC  ‐24.3  ‐12.1  ‐16.4  ‐16.1  ‐16.3  ‐18.2 

δ34S  27.3  26.9  26.7  26.1  22.6  24.7 

&) approximate values for precipitating pyrite recalculated according to Plummer et al. 1994 

29  

5. DISCUSSION

5.1. Mineralogy and isotopic composition of fracture fillings

The studied fracture fillings were divided into calcite Groups 1 to 5 (Sahlstedt et al., 2009). Group 5 and 4 fillings represent old hydrothermal circulation at the site, Group 3 calcite are possibly related to a Paleozoic event (Sahlstedt et al. 2013) and Group 1 and 2 calcite represent the latest precipitation event at the site. The isotopic composition of the studied fillings are within the range of δ13C and δ18O values obtained in the previous studies for each calcite group (Sahlstedt et al., 2009, 2014 a,b,c).

The studied samples did not contain, on closer examination, any noticeable areas of black pigment material. The darker colored, nearly black precipitates on the surface were usually clays, typically chlorite. Several on the fillings did contain, however, tiny pyrite crystals (Figures 11-12). The studied samples did contain graphite (5 out of 7 samples). One thin section shows graphite from the host rock reaching the fracture surface (Figure 7). Graphite, together with the presence of very dark colored clays, could contribute to the black pigment observation.

The morphology of late-stage pyrite shows they have formed by periodical growth from the solution where older pyrite nucleus have, in many cases, acted as precipitation centers (Sahlstedt et al., 2013). Sulfur isotope trends in the grains support the morphological observations, and indicate sequential growth from solution having varying δ34SSO4 (Sahlstedt et al., 2013). For example, small pyrite crystals observed on the fracture surfaces may act as similar precipitation centers (Figures 11-12). Formation of pyrite from potential precursor mineral phases such as mackinawite and greigite is a complex and the small sizes of the precipitates are prone to oxidation when exposed to air (Rickard and Morse, 2005). Detection of these phases from the drill core material (exposed to oxidizing conditions) is therefore challenging. It is likely that majority of the sulfate reduction products which formed in the bedrock is preserved only as pyrite in the drill core material. A more detailed study conducted on the fracture surfaces with visually observably (by naked eye) black pigment material is presented by Gehör in prep.

30  

Figure 11. a) Microphotograph of the fracture surface of sample 7-3. The image shows the occurrence of dark green clay (chlorite) with calcite on a weathered fracture surface. Calcite shows signs of dissolution due to acid testing of the fracture surface. b) Microphotograph of the surface of sample 7-4. In the image, white calcite filling is partly covered by tiny pyrite crystals. c) Microphotograph of the surface of sample 7-5. The image shows white calcite filling partly covered by tiny pyrite crystals.

31  

Figure 12. BE images of the fracture surfaces. a) BE image of sample 7-3, showing calcite and clay (chlorite) b) close up of the surface shown in a). The clay forms spherical cluster on the fracture surface. c) Be image of sample 7-4 surface. d) Close up of the surface in c). Note the tiny pyrite crystals on the surface. e) BE image of sample 7-5 surface and a close up f) of the same surface, where pyrite occurs as tiny euhedral crystals.

32  

5.2 Modelling results and implications to Littorina infiltration

5.2.1. Sulfate concentrations and implications to initial water compositions

All of the final wells used in the modeling did not produce a mass balance model. The uncertainty in SO4

2- concentrations were tested by adding NaSO4 in to the reacting phases in cases where mass balance model could not be found (Table 5). As a results, a mass balance model could be found for these final wells (KR19_110_1 i.e. Littorina low 34S, KR23_192_1 and KR27_124_1) but required a significant contribution from dissolving NaSO4, corresponding to 80-190 mg of SO4

2- per kg of water. The high SO42-

input from an artificial source (NaSO4 or other sulfate minerals do not occur in Olkiluoto) suggest that contribution from an additional initial water source or that the SO4

2- in one of the initial waters was higher than predicted in some cases. For example the low δ34S values (close to +20 ‰) in some Littorina derived groundwaters suggest only very minor modification of the sulfate in BSR and thus the SO4

2- concentrations in the infiltrating waters likely have varied.

Addition of SO42- source was also tested for final wells: Littorina high δ34S,

KR4_T132_2, KR8_302_1 and KR7_282_1 for which a mass balance model could be found without adding NaSO4 in to the reacting phases. The results indicated either significant input of SO4

2- (up to 174 mg/kg of H2O) or relatively minor decrease in SO4

2- (12-17 mg/kg of H2O). The results reflect uncertainty in assigning initial waters and the extent of BSR reactions in the sediment. Mixing reactions between variably altered Littorina water in the upper parts of the bedrock are possible, which could be mixed with glacial and subglacial waters deeper in the bedrock.

5.2.2. Mass balance models

Overall, reasonable mass balance models are obtained for the studied case of Littorina infiltration, given the uncertainties of the reactions in the sediments and compositions of the initial waters. The results obtained for the Littorina high δ34S reference waters (Table 6) indicates both pyrite and calcite precipitation. Significant amount of calcite or pyrite dissolution is not predicted to occur below shallow depths in the bedrock based on mineralogical evidence (Posiva, 2013). Therefore, models showing calcite and/or pyrite dissolution (final wells KR27_247_1, KR6_135_1 and KR7_282_1, Table 7) are suspect. The true evolution of the final waters in cases where mass balance models indicate calcite and/or pyrite dissolution may be more complex compared to the modelling premises used in this study. Overall, the calculated isotope compositions (δ13CDIC and δ34SSO4) are relatively close to the values observed in the final wells, with more variation in the δ13C values compared to the δ34S values. Different aspects related to the carbon and sulfur isotope compositions in mixing and mineral reactions as outlined by the mass balance models are discussed in the following.

5.2.3. Sulfur isotopes

The δ34S value of the reacting initial water is first modified by mixing between Littorina, subglacial and glacial water. The δ34S values of subglacial and glacial waters are unknown and assumed to 0 ‰ by the program. This could result in some uncertainty

33  

in the modelling results. The effect of mixing can be examined by plotting a three component mixing diagram using SO4

2--concentrations and the associated δ34S values. This type of diagram was plotted in Figure 13 for the initial waters used in the mass balance models. The δ34SSO4 values of subglacial and glacial waters were assumed to be +10 ‰ and 0 ‰, mainly because it allows better separation of these component in Figure 13. All admixtures following from mixing between these three components are located within the area outlined by mixing lines between the separate components (Figure 13). Figure 13 clearly shows that the δ34S value of Littorina Sea water dominates in the mixing due to its comparably high SO4

2--concentration (Table 3). Only in cases where subglacial or glacial water dominates (fraction of either component >0.9), the δ34SSO4 value of these end members could have a small effect on the δ34SSO4 of the admixture. None of the models indicated such large fractions of these end members in the resulting admixtures (Tables 6-7). Therefore, the uncertainty in the δ34S values of subglacial or glacial water has a negligible effect on the δ34SSO4 value of the resulting admixture. Instead, the δ34SSO4 value of the admixture is determined by the δ34SSO4 value of the Littorina end member (“Littorina sediment”, Table 3).

Second process affecting the sulfur isotope composition of SO42- is mineral reactions

along the flow path. Because sulfate minerals are absent from Olkiluoto, precipitation (or dissolution) or sulfide minerals may affect the δ34S values of SO4

2-. The sulfide mineral considered in the models is pyrite, which is ubiquitous in the fractures (e.g. Sahlstedt et al., 2013). The mass balance models indicated either precipitation of small amount of pyrite (<0.05 mmol/kg) or dissolution of pyrite (0.14-0.05 mmol/kg) (Tables 6-7). Dissolution of pyrite is not supported by other geochemical evidence (e.g. Posiva, 2013). However, if minor amount of pyrite dissolution does occur in some flow paths, it could affect the isotope composition of the SO4

2- in solution.

Sulfur fractionation during pyrite dissolution is considered negligible in NETPATH, which is in line with experimental results (e.g. Balci et al., 2007 and references therein). However, biogenic pyrite oxidation may result in small fractionation, which is typically found to result in ca. 5‰ depletion in 34S for product sulfate (e.g. Toran and Harris, 1989). The δ34S values of pyrite in Olkiluoto is highly variable, but generally tend to be positive, clustering widely around the δ34S value of +10 ‰ (Sahlstedt et al., 2013). Based on these data, input from pyrite dissolution would slightly decrease the δ34S value of SO4

2- from the marine value of +20 ‰. For example, mass balance models for final wells KR6_135_1 and KR7_282_1 indicate pyrite dissolution. For these wells, NETPATH calculated dissolution of 0.14 and 0.05 mmol of pyrite, respectively. Due to pyrite dissolution (pyrite having δ34S of -20 ‰) the δ34S values of SO4

2- in the admixture decreased 3.5 ‰ (KR6) and 1.4 ‰ (KR7). The mass balance model for well KR7_282_1 was recalculated with pyrite δ34S value of +10 ‰, which indicated slightly different mixing ratios of initial waters (difference in contributions <5%) and increase in pyrite dissolution (0.09 mmol) in order to obtain the measured δ34S value of SO4

2-. Pyrite dissolution is not, however, supported mineralogical or geochemical data (e.g. Posiva, 2013).

Mass balance models indicated small amount of pyrite precipitation (<0.05 mmol/kg). Because the SO4

2--concentration of the reacting water (admixture of three components, cf. Figure 13) is high, the effect pyrite precipitation has on the δ34SSO4 is minor (Tables 6-7). Due to these reasons, the selection of fractionation factor has negligible effect on

34  

the δ34SSO4 value and a significant effect on the δ34S value of the precipitating pyrite. In the mass balance calculations, fractionation calculations are based on the enrichment factor, defined as pyr-soln= 34SH2S - 34ST in NETPATH (Plummer et al., 1994), where δ34ST is the δ34S value of total sulfur (in this case ST ~ SSO4) in solution. A value of -45 ‰ was chosen in cases where final wells did not contain all the variables needed for the program to calculate fractionation factors. In nature, the kinetic fractionation associated with bacterial sulfate reduction is highly variable and may range from near 0 to ca. 75 ‰ separation between SO4

2- and sulfide (see summary by Sim et al. 2011). The extent of the sulfur isotope effect associated with BSR has been connected to the rate of sulfate reduction by experimental and modelling data, which show that the fractionation effect increases with decreasing reduction rates (e.g. Brunner and Bernasconi, 2005; Canfield, 2001; Sim et al., 2011). The selected value of -45 ‰ fractionation is in the middle range of the variation observed in BSR. The effect of the selection of pyr-soln was examined by testing different values, from -15 to -70 ‰ (final well is Littorina high δ34S-reference water OL-KR20_186_1, Figure 14). Figure 14 illustrates how changes in thepyr-soln have only a small impact on the δ34S value of SO4

2- (variation <1.6 ‰) but a large effect on the δ34S value of pyrite. The results suggest that pyrite precipitating in this case would most likely have negative δ34S values, but the exact value is strongly dependent on the selection of the kinetic fractionation factor. Problematically, in cases where the program calculated the εpyr-soln value based on the analytical data, unreasonable high fractionation between precipitating pyrite and solution was indicated (ca. 96 ‰ depletion in 34S). The fractionation factor was recalculated according to the procedure outlined in Plummer et al. (1994), and a more reasonable value of ca. -51 ‰ was obtained, which was used to recalculate the δ34S value of pyrite in Tables 5-6 (Rayleigh effect was not taken in to account due to the small amount of pyrite precipitation).

In summary, mixing affects only the SO42- concentration of the admixture, and due to

the low SO42- concentration of glacial and subglacial waters, the δ34S value of the

admixture is determined by the Littorina end member. In evaluating the mass balance models, results showing pyrite precipitation are preferred over pyrite dissolution based on mineralogical evidence from the site (Posiva 2013, Sahlstedt et al., 2013). The mass balance models indicated pyrite precipitation in four out of six cases (Table 7). Precipitation of pyrite has only a small effect on the δ34S value of SO4

2- in the final well, but the selection of fractionation factors strongly affects the δ34S value of the precipitating pyrite. It is likely that the precipitating pyrite will have negative δ34S values in these cases, but the exact value depends on the extent of kinetic fractionation in BSR. The δ34S values of late-stage pyrite are highly variable, showing considerable changes even within single grains. The changes in δ34S values of pyrite are much larger than the variation expected from the modelling results presented here (cf. Figure 14). The high variation in the δ34S values of late-stage pyrite indicates a more complex SO4

2-

-cycling system compared to the models presented here. Nevertheless, a fraction of the pyrite may have precipitated according to the scenario presented by the mass balance models.

35  

 

Figure 13. Three component mixing diagram showing the sulfur isotope composition and SO4

2- concentration resulting in from the mixing of Littorina water, glacial water and subglacial water. The δ34SSO4 of glacial water is set as 0 ‰ and subglacial +10 ‰ in order to have better separation between these end members in the diagram. Sulfur isotopic composition of water resulting from mixing between these components will have SO4

2--concentration and δ34S value within the area defined by the mixing lines between the three components. The diagram shows that the δ34SSO4 value of the admixture will be defined by the Littorina end member due to its high SO4

2--concentration.

0

5

10

15

20

25

30

0 1 2 3 4 5 6 7 8 9

34S S

O4mix

SO42‐ (mmol/kg)

34SSO4 in three component mixing

glacial

subglacial

Littorina (sediment)

36  

 

Figure 14. The dependence of the δ34S value of SO42- (secondary y-axis) and the δ34S

values of precipitating pyrite (primary y-axis) on the extent of kinetic fractionation between pyrite and solution. Mass balance model used to build this diagram uses the parameters outlined in Table 4, for the final well “Littorina high δ34S” (OL-KR20_186_1). Kinetic fractionation is defined as εpyr‐soln= δ34SH2S - δ34ST and was given values between -15 ‰ to -70 ‰. The diagram shows that the selection of fractionation factor has little effect on the δ34S of sulfate but strongly affects the δ34S value of precipitating pyrite.

5.2.4. Carbon isotopes

Similar to the sulfur isotope system, also the δ13C value of DIC is first defined by mixing between the three initial waters. Figure 15 is a three component mixing diagram showing the evolution of DIC concentration and δ13C values in mixing of Littorina, glacial and subglacial waters. The diagram shows also the isotopic compositions of the admixtures calculated from the mixing fractions provided by the mass balance models (Tables 6-7). Most of the modelled admixtures are close to the Littorina-glacial mixing line. However, due to the low DIC concentration of the glacial water, the δ13C values is defined by the Littorina and the subglacial components, with the Littorina component dominating.

Reactions between calcite and water and CH4 or CH2O consumption further modify the δ13CDIC value of the final water (Tables 6-7). In these reactions, CH4 and CH2O consumption will decrease the δ13C value of DIC due to the low δ13C values of CH4 and CH2O (-50 ‰ and -25 ‰, respectively). Calcite precipitation will slightly decrease the δ13C value of DIC, because 13C is preferably precipitated with CaCO3. How calcite dissolution affects the δ13CDIC value depends on the δ13C of calcite, but because the δ13C of calcite is typically higher compared to the δ13CDIC, dissolution reaction will increase the δ13CDIC. Models which indicate CH4 consumption and calcite precipitation, the δ13C values in final waters are app. -22 ‰ to -23 ‰ (Table 6-7). Although this value is not unreasonably low, the δ13C value measured from Littorina derived groundwaters are typically higher, ranging between -24 ‰ to -12 ‰ (Table 3). In models where CH2O is consumed and calcite precipitates, the calculated δ13CDIC is ca. -21 ‰ to -22 ‰. Overall, the effect of CH4 or CH2O consumption will overshadow the effect of calcite

‐80 ‐70 ‐60 ‐50 ‐40 ‐30 ‐20 ‐10 0

26

26,5

27

27,5

28

28,5

‐50

‐40

‐30

‐20

‐10

0

10

20

‐80 ‐70 ‐60 ‐50 ‐40 ‐30 ‐20 ‐10 0

Effect of fractination factor (~H2S‐SO4) on SO4(solution) and pyrite (precipitate)

py py initial py final Sulfur‐34

37  

precipitation because of the bulk transfer of carbon from CH4 and CH2O into the groundwater, whereas the effect of calcite precipitation is governed by the small fractionation factor between DIC (large fraction of DIC occurs as HCO3

-) and calcite.

Additionally, the carbon isotope evolution in the models starts with the selection of the δ13C value of the Littorina derived water, which in this exercise was -17 ‰, reflecting BRS in the sediment. (Fig. 10). It is likely that the δ13C of the Littorina derived water has varied, due to differencies in e.g. (bio)geochemical processes in the sediment, and may have been higher than the selected δ13C. Selection of a higher δ13C value would have been reflected as higher δ13C values in the final waters.

Some of the models (final waters KR27_247_1, KR6_135_1 and KR7_282_1) indicated calcite dissolution (Table 7). Mineralogical observations do not support calcite dissolution deep in the bedrock. Calcite dissolution is thought to be restricted to the overburden and shallow depths of the bedrock where carbonate minerals first react with infiltrating waters (Posiva 2013). In the deep bedrock methanogenesis could increase in the δ13CDIC value (cf. Sahlstedt et al., 2010). However, microbial methanogenesis in the modelled waters is inhibited by the high SO4

2- concentrations, and therefore, cannot explain the discrepancy between the measured and calculated δ13CDIC values. Calcite dissolution could, although not a preferred reaction in the deep bedrock, increase the δ13C values of DIC, because calcite in the fractures is generally more enriched in 13C compared to DIC. Therefore, the influence of calcite dissolution was further investigated and is illustrated in figures 16-17. The influence of calcite dissolution together with consumption of CH4 or organic matter was calculated for the mass balance model obtained for final water KR27_247_1, which shows dissolution of 0.49 mmol of calcite (per kg of water).

 

38  

 

Figure 15. Three component mixing diagram showing the region of possible δ13CDIC values and DIC concentrations of admixtures resulting from mixing of Littorina (sediment), glacial and subglacial waters (Table 1). The admixtures calculated by the models (Table 7) are shown highlighted in the figure. The figure shows that the model calculated mixing ratios are close to the Littorina-glacial water mixing line. The δ13CDIC value is determined by the Littorina and subglacial component due to the high DIC concentrations of these end members.   

Figure 16 shows the influence of the δ13C value of dissolving calcite on the isotopic composition of DIC for models consuming CH4 (δ13CCH4=-50‰) or organic matter (δ13CorgC = -25‰). The results from the mass balance models show that in these models dissolution of calcite with a δ13C value of ca. -10 ‰ to -8 ‰ would result in δ13CDIC value measured from the groundwater. The diagram highlights the strong effect the isotopic composition of calcite would have on the isotopic composition of DIC if calcite dissolves in the system. Also, the effect of the isotopic compositions of CH4 was investigated. Figure 17 shows the effect of the δ13C value of CH4 on DIC as a function of the δ13C value of dissolving calcite. The δ13C value of CH4 can be considered to vary from about -60 ‰ to -20 ‰ in Olkiluoto (Partamies and Pitkänen, 2007). Figure 17

‐27

‐25

‐23

‐21

‐19

‐17

‐15

0 0,5 1 1,5 2 2,5 3 3,5

13CDICmix

DIC (mmol/kg)

13CDIC values of three component mixing

Littorina‐glacial Littorina‐subglacial glacial‐subglacial

KR27_247_1 Litorina high d34S KR4_T132_2

KR8_302_1 KR6_135_1 KR7_282_1

subglacial

Littorina (sediment)

glacial

39  

demonstrates that changes in the δ13CCH4 have a relatively small effect, about 1 ‰, on the δ13C values of DIC. Overall, calcite dissolution could explain the some of the discrepancy between the measured and modelled δ13CDIC values, but other geochemical and mineralogical data do not support calcite dissolution deep in the bedrock (Pitkänen et al., 2004; Posiva, 2013). It is possible that in some flow paths, calcite dissolution occurred in the upper parts of the bedrock. Other possibility is that some amount of calcite recrystallization has occurred in the fractures, which has affected the isotope composition of DIC without changing the DIC concentrations (Plummer et al., 1994).

The δ13C values of CH4 measured in Olkiluoto suggests that the CH4 source in the bedrock fractures has been heterogeneous and may have changed during the geological history of the site (Partamies and Pitkänen, 2007). Also, the δ13C value of organic matter may vary, but likely within a narrow limit of about -30 ‰ to -25 ‰ (cf. Clark and Fritz, 1997). Data compiled to Table 8 shows the effect of changes the isotopic composition of CH4 or CH2O on model calculated δ13C values of DIC and precipitating calcite. In mass balance models where CH4 is consumed (and calcite precipitates) the calculated δ13C of DIC range from about -19 ‰ to -24 ‰ (Table 8). In models where CH2O is consumed (calcite precipitates) δ13CDIC range from about -20 ‰ to -23 ‰ (Table 8). The measured δ13CDIC is comparable to the model calculated value in one groundwater sample.

The models predict a range of about -17 ‰ to -14 ‰ for the precipitating calcite (for both CH4 and CH2O consumption). This range in the calculated δ13C values of calcite corresponds with the δ13C values of late-stage calcite in the shallow bedrock (<50 m b.s.l, e.g. Sahlstedt et al. 2016). At greater depths, the δ13C values of late-stage calcite tend to be >-15 ‰ or even positive (Sahlstedt et al., 2009, 2010, 2014 a,b,c, 2016). Based on these data it is possible that the mixing and mineral-water reactions occurred in the upper parts of the bedrock and relatively little changes in groundwater chemistry occurred to the infiltrating waters as they settled to their current depths of about 100-260 m (b.s.l.). Incidentally, late-stage fracture minerals indicate that biogenic processes consuming SO4

2- and organic matter have been the active at shallow depths of the bedrock (Sahlstedt et al., 2013, Sahlstedt et al., 2016.). Based on the δ13C values of late-stage calcite, methanotrophic oxidation of CH4 occurred at the depth range of 34-54 m (Sahlstedt et al. 2016).

40  

 

Figure 16. The effect of the carbon isotopic composition of dissolving calcite on the δ13CDIC value. The figure shows the calculation for the CH4 and CH2O consuming models. The modelled final water was KR27_247_1. The figure shows that δ13C value selected for the calcite has a strong impact on the resulting δ13CDIC value in models which show calcite dissolution. Horizontal line indicates the δ13CDIC value measured from KR27_247_1.

 

Figure 17. The impact of the carbon isotopic composition of CH4 on the modelled δ13CDIC values. The modelled final water was KR27_247_1. The figure shows that 40 ‰ variation in the δ13C value of CH4 has a maximum effect of ca. 1 ‰ on the isotopic composition of DIC.

‐19

‐18

‐17

‐16

‐15

‐14

‐13

‐25 ‐20 ‐15 ‐10 ‐5 0 5 10

13C of DIC

13C of (dissolving) calcite

The influence of 13Ccalcite on DIC (cc dissolves)

CH4 model CH2O model measured DIC

‐20

‐19

‐18

‐17

‐16

‐15

‐14

‐13

‐12

‐25 ‐20 ‐15 ‐10 ‐5 0 5 10

13C DIC

13Ccc (cc dissolves)

The influence of 13CCH4 and 13Ccc on DIC (cc and CH4

dissolves)

CH4 ‐20 CH4 ‐40 CH4 ‐50 CH4 ‐60 measured DIC

41  

Table 8. Impact of the δ13C value of CH4 or CH2O on the carbon isotopic composition of DIC and precipitating calcite for different mass balance models. The δ13C value of dissolving calcite (last three models) is -10 ‰.

final well 13C (CH4/CH2O)  parameter  KR20_186_1  KR4_T132_2  KR8_302_1  KR27_247_1  KR6_135_1  KR7_282_1 

CALCITE  ‐0.657  ‐0.790  ‐1.635  0.488  1.508  0.427 

CH4 GAS  0.105  0.264  0.117  0.056  0.173  0.201 

‐30  13CDIC  ‐20.4  ‐19.3  ‐21.7  ‐15.9  ‐11.5  ‐14.7 

‐50  13CDIC  ‐22.5  ‐22.1  ‐23.5  ‐16.4  ‐12.9  ‐17.2 

‐60  13CDIC  ‐23.5  ‐23.5  ‐24.4  ‐16.6  ‐13.6  ‐18.4 

‐30  cc#  ‐16.5  ‐13.9  ‐15.8  ‐  ‐  ‐ 

‐50  cc#  ‐17.4  ‐15.0  ‐16.4  ‐  ‐  ‐ 

‐60  cc#  ‐17.9  ‐15.6  ‐16.7  ‐  ‐  ‐ 

CALCITE  ‐0.763  ‐1.054  ‐1.752  0.431  1.335  0.226 

"CH2O"  0.211  0.528  0.234  0.113  0.346  0.403 

‐25  13CDIC  ‐20.7  ‐20.1  ‐22.1  ‐16.2  ‐12.2  ‐16.0 

‐30  13CDIC  ‐21.7  ‐21.4  ‐22.9  ‐16.4  ‐12.9  ‐17.2 

‐25  cc#  ‐17.1  ‐14.8  ‐16.2  ‐  ‐  ‐ 

‐30  cc#  ‐16.6  ‐14.2  ‐15.9  ‐  ‐  ‐ 

measured  13CDIC  ‐24.3  ‐12.1  ‐16.4  ‐16.1  ‐16.3  ‐18.2 

# the average 13C value of precipitating calcite  

5.2.5. Concluding remarks

The Littorina infiltration scenario presented in Pitkänen et al. (1999) can explain the chemical composition of some of the Littorina derived groundwaters at Olkiluoto. In cases where a mass balance model could not be found (i.e. final wells KR19_110_1, KR23_192_1 and KR27_124_1), test calculations indicated significant uncertainty in SO4

2--concentrations. This uncertainty was observed as high input of NaSO4 by dissolution, corresponding to SO4

2--concentrations of 80-190 mg/kg. Therefore, it is possible that some of the Littorina derived groundwaters were less affected by BSR in the sediments. The δ34SSO4 values of Littorina derived groundwaters are as low as 21.8 ‰ (compared to marine δ34SSO4 value of +20 ‰), which indicates a relatively minor influence from BSR.

The mass balance models indicated either consumption of CH4 or organic matter (CH2O) together with the precipitation of pyrite and calcite. Models showing calcite and/or pyrite dissolution are considered less reliable based on other geochemical and mineralogical evidence. However, calcite dissolution could explain some of the variation observed in the δ13C values of DIC in Littorina derived groundwaters. Based on the examination of sulfur and carbon isotope evolution in the mixing and mineral-water reactions, following observations are made:

42  

1) The sulfur isotope composition of the Littorina derived groundwaters are highly dependent on the reactions occurring in the sediments prior to infiltration, due to the low SO4

2- concentrations of the glacial and subglacial groundwaters.

2) The mass balance models indicate that a minor amount of pyrite precipitation occurred in the bedrock. Therefore, the selection of kinetic fractionation factors in BSR have a small effect on the δ34S of the residual SO4

2-, but a large effect on the δ34S of precipitating pyrite. In the modelled cases, the δ34S of precipitating pyrite was likely negative but the actual value depends on the selection of kinetic fractionation factor, which cannot be constrained by the available data.

3) The δ13C value of DIC is first influenced by mixing of the Littorina water with glacial and subglacial groundwaters and secondly by the consumption of either CH4 or organic matter (CH2O). Dissolution of calcite could have a large effect on the δ13C value of DIC but this is an unlikely process to have occurred in the deep bedrock. The input from CH4/CH2O lowers the δ13C value of DIC and the calcite precipitating from these groundwater will have δ13C values <-14 ‰. The δ13C values obtained from the mass balance model calculations corresponds to late-stage calcite in the shallow bedrock (<50 m).

 

43  

6. SUMMARY

Fracture fillings containing black pigment material were studied. The calcite (±pyrite, clays) fillings associated with the fractures containing black pigment belonged to Groups 1, 3 and 5. The δ13C and δ18O values of the calcite fillings were within the ranges obtained in previous studies for each calcite group. Close examination of the fracture surfaces under binocular microscope, in thin sections and in electron microprobe, the black pigment-material could not be identified. Instead, the samples contained very dark clays (chlorite), graphite and fine grained pyrite crystals.

Mass balance modeling was performed to investigate Littorina Sea infiltration. The modelling is based on the assumption that Littorina Sea water is first modified in the sea bottom sediments by BSR and ion exchange reactions and then mixed in the bedrock with glacial and subglacial waters (Pitkänen et al., 1999). The results show that reactions occurring in the sea bottom sediments (i.e. the selection the composition of the intitial water) have a strong effect on the modelling results, especially concerning the sulfur and carbon cycling. The reason for this is the comparably high concentrations of dissolved species in Littorina water (and Littorina derived groundwaters) compared to the more dilute glacial and subglacial waters. The results highlight the uncertainty related to SO4

2- concentrations in the initial waters and indicate that Littorina Sea water was variably influenced by BSR in the sea bottom sediments prior to infiltration. The groundwaters were affected by mineral-water reactions in the bedrock and the mass balance models indicated either consumption of CH4 or organic matter (CH2O) together with the precipitation of pyrite and calcite. Models showing calcite and/or pyrite dissolution are considered less reliable based on other geochemical and mineralogical evidence from the site. The mass balance models indicate a minor amount of pyrite precipitation in the bedrock resulting in pyrite with negative δ34S values. Precipitation of pyrite (BSR) has a small effect on the δ34S value of SO4

2- in groundwaters. The associated consumption of either CH4 or organic matter (CH2O) slightly decreases the δ13C value of DIC and the calcite precipitating from these groundwater will have δ13C values < -14 ‰. The δ13C values obtained from the mass balance model calculations corresponds to late-stage calcite in the shallow bedrock (<50 m). The δ13CDIC values of Littorina derived groundwaters at Olkiluoto are typically higher compared to the model calculated δ13CDIC values, suggesting that these waters are affected by additional processes such as calcite dissolution in shallow bedrock. Additionally, the composition of the initial Littorina derived may have varied, which would have also altered the modelling results. Especially, the effects of infiltration on SO4

2- and DIC concentrations and δ13CDIC and the effect of these variations on modeling results could be examined in detail in future work.

 

 

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45  

7. REFERENCES

Ahokas, H., Tammisto, E. and Lehtimäki, T. 2008. Baseline head at Olkiluoto. Posiva Working Report 2008-69, Posiva Oy Olkiluoto, 191 p.

Balci, N., Shanks, W.C. III, Mayer, B. and Mandernack, K.W. 2007. Oxygen and sulphur isotope systematics of sulfate produced by bacterial and abiotic oxidation of pyrite. Geochimica et Cosmochimica Acta, 71, p. 3796-3811.

Brunner, B. and Bernasconi, S.M. 2005. A revised isotope fractionation model for dissimilatory sulfate reduction in sulfate reducing bacteria. Geochimica et Cosmochimica Acta, 69, p. 4759-4771.

Canfield, D.E. 2001. Isotope fractionation by natural populations of sulfate-reducing bacteria. Geochimica et Cosmochimica Acta, 65, p. 1117-1124.

El-Kadi, A.I., Plummer, N.L. and Aggarval, P. NETPATH-WIN: An interactive user version of the mass-balance model, NETPATH. Groundwater 49 (4), p. 593-599.

Gehör, in prep

Hellä, P., Pitkänen, P., Löfman, J., Partamies, S., Vuorinen, U. and Wersin, P. 2014. Safety Case for the Disposal of Spent Nuclear Fuel at Olkiluoto, Definition of Reference and Bounding Groundwaters, Buffer and Backfill Porewaters. Posiva Report 2014-04, Posiva Oy Olkiluoto, 164 p.

Pitkänen, P., Luukkonen, A., Ruotsalainen, P., Leino-Forsman, H. & Vuorinen, U. 1999. Geochemical modelling of groundwater evolution and residence time at the Olkiluoto site. Posiva Report 98-10. Posiva Oy, Helsinki, Finland, 169 p.

Pitkänen, P., Partamies, S. & Luukkonen, A. 2004. Hydrogeochemical interpretation of baseline groundwater conditions at the Olkiluoto site. Posiva Report 2003-07, Posiva Oy, Olkiluoto, 159 p.

Pitkänen, P., Ylä-Mella, M., Partamies, S., Snellman, M. & Hellä, P. 2007a. Quality review of hydrochemical baseline data from the Olkiluoto site. Posiva Oy, POSIVA 2007-05.

Plummer, L.N., Prestemon, E.C. and Parkhurst, D.L., 1994. An interactive code (NETPATH) for modelling net geochemical reactions along a flow path version 2.0. U.S. Geological Survey, Water Resources Investigations Report 94-4169, Reston, Virginia, 130 p.

Posiva 2013. Olkiluoto Site Description 2011, Posiva Report 2011-02, Posiva Oy, Olkiluoto, 1101 p.

Rickard, D. and Morse, J.W. 2005. Acid volatile sulphide (AVS). Marine Chemistry, 97, p. 141-197.

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Sahlstedt, E. Karhu, J. and Rinne, K.2009. Paleohydrogeological implications from fracture calcites and sulfides in a major hydrogeological zone HZ19 at Olkiluoto. Posiva Working Report 2009-54, 95 p.

Sahlstedt, E., Karhu, J.A. and Pitkänen P. 2010. Indications for the past redox environments in deep groundwaters from the isotopic composition of carbon and oxygen in fracture calcite, Olkiluoto, SW Finland. Isotopes in Environmental and Health Studies, 46, p. 370-391.

Sahlstedt, E. Karhu, J. and Rinne, K. 2014a. Fracture mineral study of the hydraulic feature HZ20 and implications to paleohydrogeology: a report of investigations in 2009. Posiva Working Report 2012-93.

Sahlstedt, E., Rinne, K. and Karhu, J. 2014b. Fracture mineral investigations at Olkiluoto in 2010: Implications to paleohydrogeology. Posiva Working Report 2012-94

Sahlstedt, E. and Karhu, J. 2014c. Paleohydrogeological implications from fracture calcites in fissures of low transmissivity: a report of investigations in 2011. Posiva Working Report 2012-XX

Sahlstedt, E., Karhu, J., Pitkänen, P. and Whitehouse, M. 2013. Implications of sulfur isotope fractionation in fracture-filling sulfides in crystalline bedrock, Olkiluoto, Finland. Applied Geochemistry 32, p. 52-69.

Sahlstedt, E. and Karhu, J. 2015. Mineralogical, stable isotope and fluid inclusion studies of fracture filling calcite at Hästholmen, Syyry and Olkiluoto. Posiva Working Report 2015-XX.

Sahlstedt E., Karhu, J. and Pitkänen, P. 2016. Biogenic processes in crystalline bedrock fractures indicated by carbon isotope signatures of secondary calcite. Applied Geochemistry 67, 30-41.

Suominen, V. 1991. The chronostratigraphy of south-western Finland with special reference to Postjotnian and Subjotnian diabases. Geological Survey of Finland Bulletin 356, 100 p.

Vaasjoki, M. 1996. The Laitila rapakivi batholith revisited: new, more precise radiometric ages. In: Haapala, I., Rämö, O.T. and Kosunen, P. (eds.) The Seventh International Symposium on Rapakivi Granites and Related Rocks, Wednesday 24 – Friday 26 July, 1996, University of Helsinki, Helsinki – Finland: abstract volume. Helsinki University Press, p. 82.

Toran, L. and Harris, R.F. 1989. Interpretation of sulphur and oxygen isotopes in biological and abiological sulphide oxidation. Geochmica et Cosmochimica Acta, 53, p. 2341-2348.

Widerlund, A. and Andersson, P.S. 2011. Late Holocene freshanin of the Baltic Sea derived from high-resolution strontium isotope analyses of mollusk shells. Geology, 39. p. 187-190.

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APPENDIX 1. RESULTS OF THE WDS ANALYSES.

7-1 W%(C ) W%(O ) W%(Mg) W%(Ca) W%(Mn) W%(Fe) W%(Sr) point #

13.0 49.5 0.0 37.1 0.3 0.0 0.0 1

12.7 49.1 0.0 37.5 0.5 0.0 0.1 2

12.6 48.9 0.0 37.8 0.5 0.0 0.0 3

7-2 W%(C ) W%(O ) W%(Mg) W%(Ca) W%(Mn) W%(Fe) W%(Sr) point #

12.6 48.8 0.0 36.3 2.1 0.1 0.0 1

12.7 48.9 0.0 36.6 1.7 0.1 0.0 2

12.7 48.9 0.2 36.1 1.9 0.3 0.0 3

12.6 48.8 0.0 36.4 2.0 0.1 0.1 4

13.4 50.1 0.1 34.5 1.7 0.1 0.0 5

13.0 49.4 0.1 35.7 1.8 0.1 0.0 6

7-3 W%(C ) W%(O ) W%(Mg) W%(Ca) W%(Mn) W%(Fe) W%(Sr) point #

13.5 50.4 0.0 35.3 0.6 0.1 0.1 1

12.3 48.4 0.0 38.5 0.5 0.1 0.1 1

12.7 49.1 0.0 37.6 0.4 0.1 0.0 1

12.6 48.8 0.0 38.0 0.5 0.1 0.0 1

13.2 49.9 0.0 36.3 0.5 0.1 0.0 1

7-4 W%(C ) W%(O ) W%(Mg) W%(Ca) W%(Mn) W%(Fe) W%(Sr) point #

13.1 49.6 0.0 36.2 1.0 0.1 0.0 1

12.7 49.0 0.1 37.1 0.8 0.2 0.1 2

13.2 49.9 0.0 36.1 0.8 0.0 0.0 3

13.2 49.9 1.3 32.6 0.8 2.2 0.0 4*)

12.5 48.7 0.0 37.8 0.8 0.1 0.0 5

12.7 49.0 0.0 38.0 0.3 0.0 0.1 6

11.9 47.7 0.0 39.5 0.8 0.1 0.0 7

12.9 49.3 0.0 37.1 0.7 0.0 0.1 8

13.2 49.8 0.0 36.2 0.7 0.1 0.1 9

12.9 49.4 0.0 37.0 0.7 0.1 0.0 10

13.0 49.6 0.1 36.3 0.7 0.3 0.0 11

*) silicate contamination

7-5 W%(C ) W%(O ) W%(Mg) W%(Ca) W%(Mn) W%(Fe) W%(Sr) point #

12.0 47.9 0.0 39.7 0.4 0.0 0.0 1

11.7 47.5 0.0 40.2 0.5 0.1 0.1 2

11.8 47.5 0.0 40.0 0.6 0.1 0.0 3

12.6 48.9 0.0 38.0 0.4 0.0 0.0 4

12.1 48.1 0.0 39.2 0.5 0.0 0.0 5

13.5 50.3 0.0 35.7 0.5 0.0 0.1 6

7-6 W%(C ) W%(O ) W%(Mg) W%(Ca) W%(Mn) W%(Fe) W%(Sr) point #

13.2 49.9 0.0 36.2 0.6 0.2 0.0 1

13.1 49.6 0.0 36.5 0.4 0.3 0.0 2

13.7 50.6 0.0 34.9 0.4 0.3 0.1 3

13.4 50.1 0.2 35.1 0.5 0.7 0.0 4

7-3? W%(C ) W%(O ) W%(Mg) W%(Ca) W%(Mn) W%(Fe) W%(Sr) point #

11.6 47.2 0.1 40.5 0.2 0.4 0.0 1

11.8 47.6 0.1 40.3 0.2 0.0 0.1 2

12.6 48.9 0.0 37.7 0.7 0.0 0.0 3

11.9 47.8 0.0 39.7 0.5 0.0 0.1 4

11.6 47.3 0.0 40.3 0.8 0.1 0.0 5

48  

 

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