microbiology of olkiluoto groundwater 2004 2006 · posiva 2008-02 microbiology of olkiluoto...
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P O S I V A O Y
O l k i l u o t o
F I N - 2 7 1 6 0 E U R A J O K I , F I N L A N D
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POSIVA 2008 -02
Microbiology of Olkiluoto Groundwater2004 – 2006
February 2008
Karsten Pedersen
POSIVA 2008-02
February 2008
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 . )
Karsten Pedersen
Mic rob i a l Ana l y t i cs Sweden AB
Microbiology of Olkiluoto Groundwater2004 – 2006
Base maps: ©National Land Survey, permission 41/MYY/08
ISBN 978-951 -652 -161 -2ISSN 1239-3096
The conc lus ions and v i ewpo in ts p resen ted i n the r epo r t a r e
those o f au tho r ( s ) and do no t necessa r i l y co inc ide
wi th those o f Pos i va .
Tekijä(t) – Author(s)
Karsten Pedersen, Microbial Analytics Sweden AB
Toimeksiantaja(t) – Commissioned by
Posiva Oy
Nimeke – Title
MICROBIOLOGY OF OLKILUOTO GROUNDWATER, 2004-2006
Tiivistelmä – Abstract
The microbiology of shallow and deep groundwater in Olkiluoto, Finland, was analysed for almost three years from 2004 to 2006. The extensive sampling and analysis programme produced a substantial database, including 60 analytical datasets on the microbiology of Olkiluoto groundwater, which is described and interpreted here. One part of this database comprises 39 complete analytical datasets on microbiology, chemistry, and dissolved gas composition assembled on four sampling campaigns from measurements from 16 shallow observation tubes and boreholes ranging in depth from 3.5 to 24.5 m. The second part of the database contains 21 datasets on microbiology and chemistry covering 13 deep boreholes ranging in depth from 35 to 450 m. In addition, the database contains 33 completed analyses of gas covering 14 deep boreholes ranging in depth from 40 to 742 m. Most of these analyses were completed before the onset of ONKALO construction, and the remaining samples were collected before ONKALO construction had extended below a depth of 100 m; therefore, this dataset captures the undisturbed conditions before the building of ONKALO.
Shallow groundwater in Olkiluoto contained dissolved oxygen at approximately 10% or less of saturation. The presence of aerobic and anaerobic microorganisms, including methane-oxidizing bacteria, has been documented. The data confirm earlier suggested processes of oxygen reduction in the shallow part of the bedrock. These microbial processes reduce intruding oxygen in the shallow groundwater using dissolved organic carbon and methane as the main electron donors. Microbiological and geochemical data strongly suggest that the anaerobic microbial oxidation of methane (ANME) is active at a depth down to approximately 300 m in Olkiluoto, as has been suggested previously, based on interpretations of geochemical data. However, proof of the presence and activity of ANME microorganisms is needed before the existence of active ANME processes in Olkiluoto groundwater can be accepted. It appears as though ANME is limited to the 0–300 m depth interval due to a lack of sulphate at depths below 300 m. This implies that the rate of sulphide production by ANME processes at depths of 300 m and above is limited by the rate of methane transport from deeper layers.
The construction of ONKALO will probably influence the ANME processes. These processes may, therefore, need detailed modelling when there are applicable data regarding how the ANME processes react to the construction of ONKALO. Future sampling and analysis will reveal whether ONKALO construction has influenced biogeochemical conditions in the surrounding groundwater. If such an influence is found, it will, hopefully, be possible to model the underlying reasons for this influence and to predict its continuation, based on the obtained data.
Avainsanat - Keywords
ATP, bacteria, dissolved gas, methanogens, microorganisms, oxygen, shallow groundwater, sulphate-reducing bacteria
ISBN
ISBN 978-951-652-161-2 ISSN
ISSN 1239-3096
Sivumäärä – Number of pages
156Kieli – Language
English
Posiva-raportti – Posiva Report
Posiva Oy OlkiluotoFI-27160 EURAJOKI, FINLAND Puh. 02-8372 (31) – Int. Tel. +358 2 8372 (31)
Raportin tunnus – Report code
POSIVA 2008-02
Julkaisuaika – Date
February 2008
Tekijä(t) – Author(s)
Karsten Pedersen, Microbial Analytics Sweden AB
Toimeksiantaja(t) – Commissioned by
Posiva Oy
Nimeke – Title
OLKILUODON POHJAVEDEN MIKROBIOLOGIA, 2004-2006
Tiivistelmä – Abstract
Olkiluodossa on tutkittu jo vuodesta 2004 alkaen matalien ja syvien pohjavesien mikrobiologiaa. Vuosien 2004-2006 laaja näytteenotto- ja analyysiohjelma on tuottanut huomattavan määrän tuloksia, joita käsitellään ja tulkitaan tässä raportissa. Ensimmäinen osa pitää sisällään 39 perinpohjaista mikro-biologista, kemiallista ja kaasuanalyysia, jotka ovat peräisin neljästä eri matalien kallioreikien ja pohjavesiputkien näytteenottokampanjasta. Kampanjat toteutettiin yhteensä 16:sta matalasta kallioreiästä sekä pohjavesiputkesta, joiden syvyydet vaihtelivat 3,5 - 24,5 m välillä. Toinen osa pitää sisällään 21 mikrobiologista ja kemiallista näytettä, 13:sta eri syvyisestä kairanreiästä, syvyysväliltä 35-450 m. Lisäksi kuvaillaan ja käsitellään 33 kaasuanalyysia, jotka on otettu 14:sta kairanreiästä syvyysväliltä 40-742 m. Suurin osa analyyseistä tehtiin ennen kuin ONKALOn rakentaminen alkoi ja loput ennen kuin ONKALO saavutti 100 m syvyyden, minkä johdosta tulokset edustavat Olkiluodon mikrobiologista luonnontilaa.
Matala pohjavesi Olkiluodossa sisältää liuennutta happea noin 10 %:a tai vähemmän. Lisäksi aerobisia ja anaerobisia mikro-organismeja (ml. metaania hapettavat bakteerit) on havaittu. Tämän tutkimuksen tulokset tukevat aiempaa käsitystä hapen kulumisesta aivan kallion yläosassa ja maaperässä. Raportissa käsitellyt mikrobiologiset prosessit pelkistävät happea käyttämällä liuennutta orgaanista hiiltä ja metaania pääasiallisena elektronien luovuttajina. Mikrobiologinen ja hydrogeokemiallinen data viittaa siihen, että metaanin anaerobinen mikrobinen hapettuminen (ANME) Olkiluodossa on aktiivista noin 300 m syvyyteen saakka. Tähän on viitattu myös aiemmin perustuen hydrogeokemiallisen datan tulkintaan. Ennen kuin ANME prosessien esiintyminen Olkiluodossa voidaan hyväksyä, tarvitaan todisteita ANME mikro-organismien olemassaolosta ja aktiivisuudesta. Tämän tutkimuksen perusteella voidaan sanoa, että ANME prosessit ovat rajoittuneet 0-300 m syvyysvälille, koska sulfaattia ei esiinny tarpeeksi -300 m alapuolella. Tämä viittaa siihen, että sulfidin tuottoa rajoittaa syvemmältä kallioperästä kulkeutuva metaanin määrä.
ONKALOn rakentaminen tulee todennäköisesti vaikuttamaan ANME prosesseihin. Nämä prosessit voivat tarvita yksityiskohtaista mallintamista. Tulevaisuuden näytteenotot ja analyysit selventävät, onko ONKALOn rakentaminen vaikuttanut ympäröivien pohjavesien biogeokemiallisiin olosuhteisiin. Jos muutoksia prosesseissa havaitaan, niiden syyt pyritään mallintamaan ja mahdollinen jatkuvuus ennustamaan olemassa olevan datan perusteella.
Avainsanat - Keywords
ATP, bakteerit, liuenneet kaasut, metanogeenit, mikro-organismit, happi, matala pohjavesi, sulfaattia pelkistävä bakteeri
ISBN
ISBN 978-951-652-161-2 ISSN
ISSN 1239-3096 Sivumäärä – Number of pages
156 Kieli – Language
Englanti
Posiva-raportti – Posiva Report
Posiva Oy OlkiluotoFI-27160 EURAJOKI, FINLAND Puh. 02-8372 (31) – Int. Tel. +358 2 8372 (31)
Raportin tunnus – Report code
POSIVA 2008-02
Julkaisuaika – Date
Helmikuu 2008
1
TABLE OF CONTENTS
ABSTRACT
TIIVISTELMÄ
PREFACE ................................................................................................................ 5
1 INTRODUCTION .................................................................................................. 7
1.1 Research, development, and technical design programme: TKS-2003.......... 71.1.1 TKS-2003 Geogases and microbes present at Olkiluoto .......................... 71.1.2 TKS-2006 Hydrogeochemistry ............................................................... 9
1.2 This work......................................................................................................... 91.3 Microbes – what are they?............................................................................ 10
1.3.1 Bacteria ................................................................................................... 111.3.2 Archaea................................................................................................... 121.3.3 Unicellular fungi....................................................................................... 131.3.4 Unicellular animals .................................................................................. 141.3.5 Unicellular photosynthetic organisms...................................................... 141.3.6 Viruses .................................................................................................... 18
1.4 Microbial processes ...................................................................................... 201.4.1 Closed systems....................................................................................... 211.4.2 Open systems ......................................................................................... 221.4.3 Microbial oxidation–reduction processes – “behind the scenes”............. 24
1.5 The microbe’s dilemma – death or survival .................................................. 26
2 MATERIALS AND METHODS............................................................................ 27
2.1 Sampling groundwater from shallow observation tubes and boreholes........ 272.1.1 Sampling point descriptions .................................................................... 272.1.2 Packer control tests with nitrogen ........................................................... 272.1.3 Sterilization of borehole pumps............................................................... 282.1.4 Test for reproducibility of groundwater chemistry and microbiology over
time ......................................................................................................... 292.1.5 Sample collection for microbiological analyses....................................... 29
2.2 Sampling groundwater from deep boreholes ................................................ 292.2.1 Packer-equipped deep boreholes sampled for microbiology .................. 302.2.2 Sampling, transport, and extraction of deep groundwater samples ........ 30
2.3 Physical parameters, chemistry, and gas content of the sampled groundwater .................................................................................................. 32
2.3.1 Field measurements of physical parameters in shallow boreholes and groundwater observation tubes............................................................... 32
2.3.2 Analysis of dissolved oxygen in shallow groundwater using Winkler titration .................................................................................................... 33
2.3.3 Chemical analyses of shallow and deep groundwater ............................ 332.3.4 Sampling and analysis of dissolved gas ................................................. 34
2.4 Microbiological analyses ............................................................................... 362.4.1 Determining total number of cells............................................................ 362.4.2 ATP analysis ........................................................................................... 362.4.3 Determining cultivable aerobic bacteria .................................................. 372.4.4 Preparing media for most probable numbers of cultivable anaerobic
microorganisms....................................................................................... 38
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2.4.5 Inoculations and analysis for anaerobic microorganisms........................ 382.4.6 Inoculations and analysis for aerobic methane-oxidizing bacteria .......... 392.4.7 Quality controls for the most probable number analysis ......................... 42
3 RESULTS ........................................................................................................... 43
3.1 Analysis of physical and chemical parameters ............................................. 433.1.1 Field measurements of physical parameters .......................................... 433.1.2 Chemical analyses of groundwater ......................................................... 44
3.2 Sampling, extraction, and analysis of gas..................................................... 493.2.1 Dissolved gas in shallow groundwater – comments on the methods...... 493.2.2 Dissolved gas in deep groundwater – comments on the methods.......... 493.2.3 Distribution of gases in Olkiluoto groundwater........................................ 51
3.3 Analysis of biological parameters ................................................................. 603.3.1 Sterilization of borehole pumps............................................................... 603.3.2 Comparison of sampling using the SOLINST sampler and using the
borehole pump ........................................................................................ 613.3.3 Test for reproducibility of groundwater microbiology over time............... 613.3.4 Tests for reproducibility of the pressure vessel method.......................... 613.3.5 Biomass determinations.......................................................................... 623.3.6 Cultivable heterotrophic aerobic bacteria................................................ 633.3.7 Most probable number of metabolic groups of bacteria .......................... 64
4 DISCUSSION...................................................................................................... 75
4.1 Sampling procedures for shallow groundwater ............................................. 754.1.1 Selection of sampled shallow groundwater boreholes ............................ 754.1.2 Sampling of shallow groundwater ........................................................... 764.1.3 The oxygen blockage packer test ........................................................... 774.1.4 Sterilization of borehole pumps............................................................... 774.1.5 Comparison of sampling using the SOLINST sampler and using the
borehole pump ........................................................................................ 774.2 Sampling procedures for deep groundwater microbiology............................ 784.3 Evaluating the analysis methods .................................................................. 79
4.3.1 Analysis of physical parameters.............................................................. 804.3.2 Chemical parameters .............................................................................. 804.3.3 Microbiological parameters ..................................................................... 81
4.4 Geochemical conditions of the investigated aquifers.................................... 864.4.1 Physical parameters................................................................................ 874.4.2 Chemistry dissolved solids................................................................... 884.4.3 Origins and amounts of dissolved gases in Olkiluoto groundwater......... 92
4.5 Specialists, generalists, opportunists, and antagonists in the world of microbes ....................................................................................................... 95
4.6 Microbial processes in shallow groundwater ................................................ 964.6.1 Aerobic processes................................................................................... 974.6.2 Anaerobic processes............................................................................... 98
4.7 Microbial processes in deep groundwater .................................................... 984.7.1 Aerobic processes................................................................................... 984.7.2 Anaerobic processes............................................................................. 100
4.8 Relevance of microbiological processes to ONKALO................................. 1044.8.1 Oxygen reduction and maintenance of anoxic and reduced conditions 1044.8.2 Bio-corrosion of construction materials ................................................. 1054.8.3 Bio-mobilization and bio-immobilization of radionuclides, and the effects
of microbial metabolism on radionuclide mobility.................................. 106
3
REFERENCES ........................................................................................................... 107
A. APPENDIX........................................................................................................ 115
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5
PREFACE
Many people have made important contributions to this report.
The first expedition to Olkiluoto, Finland, in April 2004 was a pioneering adventure involving a large group of Ph.D. students, post-doctoral fellows, and laboratory personnel. We learnt a lot about how investigations of shallow groundwater should be successfully performed. I am very happy to have done fieldwork in Olkiluoto in April 2004 with the following people: Ernest Chi Fru, Hallgerd Eydal, Annika Kalmus, and Sara Wikstrand from Göteborg University and Chris Kennedy and Rachel James from the University of Toronto, Canada. Johanna Arlinger, Jessica Johansson, and Marcus Olofsson contributed to the analytical work when we brought samples back to the laboratory in Göteborg. The work of these people ensured that the ensuing three expeditions went smoothly and produced an extensive amount of high-quality microbiology data.
In October 2005, all field and laboratory work was transferred from Göteborg University to Microbial Analytics Sweden AB. The personnel of this company contributed invaluably to the fieldwork and to the laboratory analyses. This report would not have been possible without the extensive work of Johanna Arlinger, Jessica Johansson, Anna Hallbeck, Lotta Hallbeck, and Sara Eriksson.
During our fieldwork campaigns in Olkiluoto, we were treated very well, receiving experienced, professional, and efficient support from the following people: Anne Lehtinen, Tero Jussila, Kari Kovanen, and Janne Laihonen. Mia Ylä-Mella played an important part in initiating and planning this work. Finally, behind-the-scenes personnel at the Teollisuuden Voima Oy (TVO) and other analytical laboratories capably supported us by performing high-quality chemical analyses. As well, we very much appreciated working in the new ONKALO laboratory during our field trips.
Professor Karsten Pedersen,
Microbial Analytics Sweden AB
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1 INTRODUCTION
The subsurface biosphere of Earth appears to be far more extensive and metabolically and phylogenetically complex than previously thought (Amend and Teske 2005). A diverse suite of subsurface environments has been reported to support microbial ecosystems, extending from a few meters below the surface to thousands of meters underground (Pedersen 2000a, 2001). The discovery of a deep biosphere (Pedersen 1993) will have several important implications for underground repositories for spent radioactive wastes (Pedersen 2002). The main effects of microorganisms in the context of a KBS-3 type repository (Anonymous 1983) for radioactive waste in the bedrock of Olkiluoto are:
Oxygen reduction and maintenance of anoxic and reduced conditions
Bio-corrosion of construction materials
Bio-mobilization and bio-immobilization of radionuclides, and the effects of microbial metabolism on radionuclide mobility
1.1 Research, development, and technical design programme: TKS-2003
Because of the potentially important effects of microorganisms, as listed above, microbiology research initiatives form part of both the Finnish and Swedish radioactive waste disposal programmes. The first comprehensive Swedish state-of-the-art report on microbiology in radioactive waste disposal was published in 1995 (Pedersen and Karlsson 1995). Sweden, unlike Finland, has not yet selected a disposal site, so the Swedish programme has mainly attempted to build our understanding of microbial processes in general. Relevant microbiology research in Finland, on the other hand, can now be more site related, because the disposal site, Olkiluoto, has been selected. The Finnish programme started extensive microbiological site-related investigations in Olkiluoto in 2004, with the aims set forth in the research (tutkimus), development (kehitys), and technical design (suunnittelu) (TKS) programme (Posiva Oy 2003). This programme summarized previous work and presented the current (as of 2003) model of microbiology and geogases in Olkiluoto groundwater. The TKS-2003 section of the programme, dealing with microbes and geogas, is briefly summarized below; this section initiated the microbiological investigations that are covered in the present report.
1.1.1 TKS-2003 Geogases and microbes present at Olkiluoto
TKS-2003 supplied the following background to the microbiological programme in Olkiluoto: Microbes were found in all groundwater studied in the Finnish site selection investigations performed from 1996 to 2000 at depths of between 60 and 900 m (Haveman et al. 1998, 2000). Sulphate-reducing bacteria (SRB) were the most abundant species found in the Olkiluoto groundwater (at depths of 200 m and below), and tended to be associated with groundwater at an intermediate depth range of approximately 250–330 m (Table 1-1). The deeper, saline groundwater (below 400 m) contained very small
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Table 1-1. Total number of cells (TNC) and the most probable number of metabolic groups of microorganisms in Olkiluoto groundwater sampled from 1996 to 2000. IRB = iron-reducing bacteria, SRB = sulphate-reducing bacteria, AA = autotrophic acetogens, HA = heterotrophic acetogens, AM = autotrophic methanogens, and HM = heterotrophic methanogens.
cells mL1Borehole Depth
(m)
TNC IRB SRB AA HA AM HM
OL-KR3 243–253 510000 1500 >16000 7.8 330 -a -
OL-KR8 302–310 280000 NTb 16000 - - - -
OL-KR10 324–332 650000 7 >16000 22 9200 0.45 0.45
OL-KR3 438–443 700000 460 420 - 930 - -
OL-KR9 470–475 150000 33 92 - 110 - -
OL-KR9 563–571 620000 NT 1.7 - - - -
OL-KR4 861–866 170000 - - - 4.9 - -
a Below detection limit (0.2 cells mL 1).b Not tested.
amounts of SRB and iron-reducing bacteria (IRB). The populations of SRB and IRB seemed to be high, particularly in the transition zone between sulphate-rich and sulphate-poor groundwater, in which Eh conditions changed from sulphidic to methanic.
Results of the earlier preliminary investigation phases at Olkiluoto indicated that the saline groundwater contained massive amounts of dissolved gases (despite the fact that the sampling techniques were not very representative). The amounts of dissolved gases, such as methane and hydrogen, were high, especially in the deep saline groundwater, and some of the saline groundwater samples contained methane close to the saturation limit (Gascoyne 2000). The total content of dissolved gases displayed a fairly coherent increasing trend with depth, indicating that the current gas sampling system was relatively reliable (Pitkänen et al. 2003). Large variations were also observable in single samples, for example, in the results for the deep samples from borehole KR4 at a depth of 860 m (900 and 1900 mL L 1), reflecting uncertainty in the quantitative results. The main reason for uncertainty was considered to be the variable amount of water recovered during sampling (Gascoyne 2000). Isotopic and chemical data suggested that bacterial, thermogenic, and abiogenic formation were all potential mechanisms for hydrocarbon (HC) formation (Pitkänen et al. 2003). Microbial analysis by Haveman et al. (1998, 2000) also suggested ongoing methanogenesis occurring below the sulphate-rich zone, as indicated by a few low 13CH4 values. Methane concentrations were several hundreds of mL L 1 in deep saline groundwater at Olkiluoto. Bacterial methane formation was evident deep in the bedrock, but insufficient isotopic data on dissolved
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inorganic carbon (DIC) and hydrocarbons impede detailed evaluation of the magnitude of methanogenesis and its effect on the carbonate system. The calculations suggested a level of few mL L 1 for bacterial methane production (Pitkänen et al. 2003). The hydrocarbon data indicated that the principal sources of methane and other hydrocarbons were thermal processes. However, it was unclear whether these hydrocarbons were formed by the thermal decomposition of organic matter or by hydrothermal reactions between carbonate or graphite and hydrogen.
1.1.2 TKS-2006 Hydrogeochemistry
The TKS report, TKS-2006 (Posiva Oy 2006), described the plans for continued microbiology research, and some of the findings of this work are reported here.
Microbial processes play important roles in aerobic respiration, methane formation, and sulphate reduction in Olkiluoto groundwater (Andersson et al. 2007b). The results of the microbiological studies carried out between 2004 and 2006 are presented in the present report. Microbiological analysis will continue as part of the sampling campaigns in selected deep boreholes, i.e., as part of the gas investigations. Samples will also be taken from shallow boreholes and groundwater observation tubes every second year starting in 2008, to check whether construction has caused any changes in microbe concentrations. One important aim of the research is to investigate whether construction at the ONKALO site has influenced the microbiological populations and their activity at depth. From the point of view of long-term safety, sulphate reduction could harm copper canisters, and it is particularly important to obtain information on the activity of sulphate reducers in groundwater close to the disposal depth.
The gas data have been further evaluated (Pitkänen and Partamies 2007), and the results suggest a need to obtain additional data using improved sampling techniques and analysis methods, especially from the repository depths and below. In particular, methane formation is an issue that must be evaluated. Gas will continue to be sampled as part of the ongoing monitoring programme and from new boreholes. Special attention will be paid to the quality of the gas analyses (e.g., by preventing contamination of the samples with air) and to the possibility of obtaining additional isotope data (e.g., regarding helium and hydrogen isotopes) from the gases.
1.2 This work
At Olkiluoto, investigations to establish the baselines for subsurface geochemical (Pitkänen et al. 2007) and microbial conditions were performed during the 1996–2000 site investigation period (Haveman et al. 1998, 1999, 2000; Haveman and Pedersen 2002a). Since then, a new series of deep groundwater samples has been collected from 21 sections distributed among 13 deep Olkiluoto boreholes, using the PAVE pressure sampling vessel according to the method of Haveman et al. (1999), and analysed. These new deep groundwater samples were collected over the two years from 10 October 2004 to 28 November 2006 from depths of 34 to 900 m. To fill gaps in our knowledge of the shallow groundwater environment, a series of investigations of shallow boreholes in Olkiluoto was performed concurrently with the new Olkiluoto deep groundwater
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investigations. Samples were collected on four different occasions from 16 shallow boreholes ranging in depth from 4 to 24.5 m. The sampling periods were 3 6 May 2004, 10 14 October 2005, 24 28 April 2006, and 9–13 October 2006. The results of the first two investigations were reported in Posiva working reports (Pedersen 2006, 2007). All the results obtained from the deep and shallow groundwater investigations from 2004 to 2006 have now been merged and interpreted, and the outcome is reported here.
As a guide for readers not so familiar with the science of microbiology, I will first briefly introduce the microbial world. The general textbook on microbiology, BrockBiology of Microorganisms (Madigan et al. 2006), is recommended for those who wish to deepen their knowledge of microorganisms.
1.3 Microbes – what are they?
A microbe is a living entity that contains all functions needed to perform a life cycle, such as feeding, growth, and reproduction, in a single cell. Microbe size varies significantly, ranging from approximately 0.2 m in diameter in the smallest bacterium to 1 mm or more in some unicellular animals and plants. The largest known bacterium is the sulphur-oxidizing microbe Thiomargarita namibiensis, which reaches a maximum diameter of 0.75 mm (Schulz et al. 1999).
The tree of life, based on analysis of the gene 16/18S rRNA, is depicted in Figure 1-1; it displays the phylogenetic relationships between the main known and characterized organism groups found on Earth. The organisms cluster in three major domains, viz. Bacteria, Archaea, and Eukarya. All organisms in the domains Bacteria and Archaeaare microbes, and most branches of the domain Eukarya are microbial as well. In fact, multicellular organisms are only represented in the three branches comprising animals, plants, and fungi. Microbes can be found virtually everywhere in the tree of life, accounting for most of the diversity of life on our planet. Much microbial diversity is biochemical, unlike multicellular life in which the diversity is largely morphological. The enormous biochemical diversity among the microbes explains their huge adaptability to almost any environment on the planet where temperature allows life. Microbes are usually divided into five different groups, based mainly on a mix of morphological, biochemical, and molecular criteria. The most important criteria for each of the five groups, and their relevance to a high-level radioactive waste (HLW) repository, are given below. Viruses constitute a sixth group of microbes that differ from the other five in their total dependence on a host for reproduction. They cannot be fitted into the molecular tree of life shown in Figure 1-1. Viruses display no signs of life outside their host cells.
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Figure 1-1. The phylogenetic relationships between all main organism groups on the planet can be revealed by comparing their 16S rDNA and 18S rDNA genes, coding for the ribosomes, which are the protein factories of the cell (Woese et al. 1990). Red represents microbes adapted to high temperatures (60–113 C), many of which utilize hydrogen as a source of energy. Yellow represents microbes that can live in saturated salt solutions (25–30% NaCl). Green represents the proteobacteria, the group that includes many microbes found in the Fennoscandian Shield aquifers. Methanogens living at low or intermediate temperatures (0–60 C) appear in light blue; these constitute an important group in most underground environments. The bulk of the domain Bacteria is indicated in blue while the domain Eukarya is indicated in light brown.
1.3.1 Bacteria
A typical bacterium is a very robust organism that generally survives extremely well in the niche for which it is adapted. It is isolated from its surrounding environment by a cell membrane (Figure 1-2) and a cell wall. The sack-like cell membrane contains various structures and chemicals that allow the bacterium to function. Key structures are the nucleotides and the genetic code (DNA), which store information needed for cell function, and the cytoplasm, which contains the machinery of cell growth and function. Bacteria are adapted to various conditions and, as a group, the bacteria can handle all possible combinations of environmental conditions. This is reflected in the species diversity of the domain Bacteria (Figure 1-1), which comprises many millions of
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species, as reflected by environmental ribosomal rDNA sequencing (Pace 1997). Approximately 10,000–15,000 of these microbes have been characterized (Dworkin et al. 2007); the rest remain molecular imprints on the environment of organisms, imprints that await exploration and characterization. This vast diversity of unknown species represents uncertainty with respect to unknown microbial processes that might be important for nuclear waste disposal. One obviously undesired species, for example, would be one that would, under repository conditions, produce large quantities of radionuclide-chelating agents. In contrast, anaerobic methane oxidisers would be very beneficial, as they would help keep the groundwater redox potential (Eh) at a low and negative value.
There appear to be several overriding characteristics that unify many of the main branches of the domain Bacteria (Figure 1-1). The ability to photosynthesize is a typical characteristic of green bacteria (cyanobacteria) and some proteobacteria; because of their need for light, these groups are not naturally represented in groundwater. Some other groups are also naturally absent, such as the pathogenic microbes (e.g., Chlamydia) and all obligate parasitic microbes (mostly among the proteobacteria) that generally require a multicellular host. Representatives of the remaining branches have been reported in various underground environments (e.g., Amend and Teske 2005). Fennoscandian Shield rocks are generally cold to moderately warm for the first 2 km of depth. The rock temperature at repository depths is some 15–20 C, so thermophilic (i.e., heat-loving) organisms will not be common there before waste disposal. It is uncertain to what extent thermophilic Bacteria and Archaea will invade and/or multiply in a repository area in which the temperature will fall from 80 C to 50 C over the first 3000 years. They certainly can be found active in all naturally occurring high-temperature groundwater. The consensus today is that thermophiles will appear in significant numbers in a warm repository.
1.3.2 Archaea
Microorganisms in the domain Archaea (Figure 1-1) were regarded as bacteria until molecular data revealed that they belong to a domain that differs completely from those of all bacteria and all plants, animals, and fungi. A unifying characteristic of organisms in this domain is their ability to adapt to what are called “extreme conditions”. Different species of Archaea are active under different conditions. Some Archaea like very hot conditions (Stetter 1996). For example, the optimum temperature for the growth of the genus Pyrolobus is 105 C and it survives in temperatures of up to 113 C. Remarkably, this species “freezes” to death when the temperature goes below below 90 C. Many other genera of Archaea grow best at approximately 100 C. The temperature of the HLW repository will consequently not exceed the temperature range within which life can exist. Some genera of Archaea are adapted to extreme pH levels, as low as 1 or up to 12, and some may even survive at more extreme pH levels (Pedersen et al. 2004). A group that is important for an HLW repository is the methanogens (Figure 1-3, Figure 1-4); these produce methane gas from hydrogen and carbon dioxide, or from short-chain organic carbon compounds, such as formate, methanol, or acetate.
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Figure 1-2. A cross-section of the bacterium Gallionella ferruginea (Hallbeck and Pedersen 2005) produced using a transmission electron microscope (TEM). This microbe is very common in groundwater seeps on the walls and floors and in ponds in the Äspö Hard Rock Laboratory (HRL) tunnel in Sweden (Anderson and Pedersen 2003). The cell wall gives the microbe its form and rigidity, while the cell membrane controls the transport of nutrients into and wastes out of the cell. The nucleic acid DNA constitutes much of the interior of the cell and carries information necessary for cell function and reproduction. This organism is a chemolithotroph that uses ferrous iron (Fe2+) as a source of energy. This energy is used to reduce carbon dioxide to cell carbon constituents, just as photosynthetic plants do, but using iron energy instead of solar energy. The visible structures in this cell do not look very different from those of a bacterium that uses organic carbon as a source of energy and for building cell constituents. The differences are almost completely on the molecular, biochemical scale, a scale that is not resolved by the TEM. The diameter of this cell is approximately 1 m (photograph: Lena Bågenholm and Lotta Hallbeck).
1.3.3 Unicellular fungi
The fungi belong to the domain Eukarya (Figure 1-1) and represent great morphological and biochemical diversity. There are data in the scientific literature that demonstrate fungi to be natural inhabitants of intra-terrestrial environments (Reitner et al. 2005). The unicellular fungi include yeast, which can commonly ferment many different organic compounds to form carbon dioxide, organic acids, alcohols, and hydrogen. Some of
14
these organic acids, for example, citric acid, are excellent chelating agents and are therefore undesired in a repository in the case of a canister failure. Mould is another group of fungi regarded as unicellular, despite their ability to form multicellular mycelia (i.e., networks of threads); each cell in a mycelium is capable of a complete life cycle and therefore falls into the microbe category. Some yeasts are capable of performing anaerobic metabolism (i.e., of living without oxygen) and are small, typically no bigger than a few m or more, which makes them suitable for life in the narrow aquifers of hard rock. Recent investigations of groundwater from the Äspö Hard Rock Laboratory (HRL) in Sweden (Ekendahl et al. 2003) identify yeast as a natural part of the subterranean biosphere in Fennoscandian Shield igneous rock aquifers (Figure 1-5). This finding introduces uncertainty regarding repository performance with respect to fungal chelating agents and their influence on radionuclide migration.
1.3.4 Unicellular animals
Unicellular animals belong to the domain Eukarya. They are found in all taxonomic branches except the fungi and plant branches (Figure 1-1). Their natural presence in deep groundwater remains to be established. Some unicellular animals, particularly the flagellates, are so small (a few m) that they are difficult to distinguish from large bacteria and yeasts. Their obvious function in deep groundwater ecosystems would be as grazers of other microbes (Figure 1-6). Many unicellular animals feed on organisms of the domains Bacteria and Archaea.
1.3.5 Unicellular photosynthetic organisms
Unicellular photosynthetic microbes are found in several branches of the domain Bacteria and also in the plant branch of the domain Eukarya (Figure 1-1). The domain Archaea does not contain any known true photosynthetic organisms. The process of photosynthesis requires light (Figure 1-6), which is not available underground, except in artificially illuminated vaults and tunnels. Mosses, cyanobacteria, and some other photosynthetic organisms have been observed in the Äspö HRL tunnel and will certainly occur where there is light in a repository during the open phase. These organisms fix carbon dioxide as organic carbon and therefore add some organic substances to the repository environment. Their activity in open deposition tunnels, however, is not foreseen to interfere with the long-term performance of the HLW repository.
15
0 10 20 30 40 50 60
Incubation temperature (°C)
0
0.05
0.10
0.15
0.20
Gro
wth
ra
te (
h-1
)
A
Figure 1-3. Methanobacteriumsubterraneum is a genus of Archaeaisolated from the Äspö HRL aquifers and characterized (Kotelnikova et al. 1998). Its temperature (A), pH (B), and salt (C) requirements include values of these parameters typical in the repository. This species is thus likely to be an important inhabitant of the repository when the temperature is below 50 C.
0 0.25 0.50 0.75 1.00 1.25 1.5
NaCl (M)
0
0.05
0.10
0.15
0.20
0.25
Gro
wth
ra
te (
h-1
)
C
6 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10
pH
0
0.10
0.20
0.30
0.40
0.50
Gro
wth
ra
te (
h-1
)
_ B
Figure 1-4. Autofluorescent image of Methanobacterium subterraneum. Methanogens contain a unique molecule, coenzyme F420, that takes part in methane formation. The more active the methanogenesis of the cells, the more F420 is present. This molecule fluoresces turquoise when irradiated with ultraviolet light. The methanogens on the image were consequently very active in the pure culture from which this specimen came.
16
Figure 1-5. Scanning electron micrographs of yeast strains isolated from Äspö HRL (Ekendahl et al. 2003). Using sterile syringes and needles, groundwater was sampled directly from fractures and boreholes and placed in appropriate culturing media. Growth of yeast and fungi occurred frequently. The isolated yeasts depicted were unique, representing new species having growth demands that correlated with the environmental conditions in groundwater at the repository depth of 500 m. The strains shown are: a) strain J1 (enlargement 8000 , bar = 2 m), b) strain J2 (9000 , bar = 2
m), c) J3 (enlargement 8000 , bar = 2 m), d) strain C (9000 , bar = 1 m, arrow shows typical bud scar), and e) strain 5e (6750 , bar = 2 m; the arrow indicates exopolymeric material). Images are reproduced from Ekendahl et al. (2003).
17
Figure 1-6. Unicellular plants and animals are also microbes. All functions they need in order to live are contained in a single cell. The yellow-brown diatom in the image makes dextrose out of light, water, and carbon dioxide. The cell is not entirely watertight, and some of the sugar leaks out between the shell halves. Bacteria sense this and gather around the diatom to consume the crumbs from the algal “dining table”. The little round object in the top left corner is a small, unicellular animal with two flagella with which it swims. It swims fast and hunts bacteria to eat them. The big blob in the bottom left is an amoeba. An amoeba is an unicellular animal with a cell membrane but no definite shape. It flows over surfaces as would a sack of potatoes; the “potatoes” push in the direction the amoeba wants to move, thereby rolling the whole sack in the desired direction. It typically engulfs bacteria, which it ingests (From: Pedersen 2004).
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1.3.6 Viruses
A virus is a non-cellular genetic element that uses living cells for its own reproduction. Viruses can be found in one of several different states. Outside cells, a virus is a submicroscopic particle that contains a nucleic acid surrounded by a shell of proteins called a capsid. In this state, the virus is lifeless and does not carry out any biochemical reactions. The main function of the capsid is to carry the genetic material, the nucleic acids, from one host cell to another. When the genetic material enters a new host cell, viral reproduction occurs. The genetic material of the virus takes over the cell machinery and produces many new copies of the virus. When a virus enters and infects a bacterium the result is usually disastrous for the bacterium. When the virus has multiplied, what is left of the cell lyses and breaks up and many new viruses are ready to search for a new host to infect and kill. This is called a lytic infection. Sometimes, the genetic material of the virus can be incorporated into the genetic material of the host cell. When the host cell multiplies, so does the genetic material of the virus. This process is called a lysogenic infection.
Viruses that infect microorganisms have been found around the world, including in some of the most extreme environments on Earth, such as hot spring water (Rachel et al. 2002), Antarctic lakes (Lisle and Priscu 2004), and deep-sea hydrothermal vent systems (Ortmann and Suttle 2005). The presence of prokaryotes in deep intra-terrestrial and sub-seafloor environments to a depth of at least 3.3 km has been established (Amend and Teske 2005; Lin et al. 2006), but viruses have so far not been reported. Previous studies (Pedersen 2001) of groundwater from deep granitic aquifers revealed microorganisms in numbers of 104 to 106 cells mL–1, which is at or above the lower limit for the replication of prokaryotic viruses (Wiggins and Alexander 1985). An abundant diversity of viruses has recently been discovered in granitic groundwater from depths of 69 to 455 m in the Äspö HRL, Sweden. Fluorescent microscopy counts were in the range of 108 to 1010 virus-like particles L–1 groundwater; these counts generally exceeded the microbial counts by a factor of 10, which is a ratio typical of ecosystems containing active viruses and microorganisms in surface environments (Maranger and Bird 1996; Suttle 2005). At concentrations of 1010 virus-like particles L–1 groundwater, viruses contribute significantly to the pool of colloids. This effect has previously been overlooked, because of our ignorance of the presence of viruses in deep groundwater. Using transmission electron microscopy, four distinct main viral morphologies were found in Äspö HRL groundwater encompassing polyhedral, tailed, filamentous, and pleomorphic forms that could be further divided into 12 distinct morphological sub-groups, in accordance with recent assessments of prokaryotic virus diversity (Ackermann 2007). In addition, a tailed virus that infects the indigenous sulphate-reducing bacterium Desulfovibrio aespoeensis (Motamedi and Pedersen 1998) was isolated and subsequently detected in significant numbers in some groundwater samples (Figure 1-7). The presence of active lytic viruses in deep groundwater is a direct indicator of virus–microbe, predator–prey interactions in intra-terrestrial ecosystems. The infection of microorganisms by viruses may contribute to the transfer of DNA between host cells, implying that viral transduction is important for the diversification of intra-terrestrial microorganisms.
19
Figure 1-7. The morphologies of viruses, isolated from deep groundwater, that were lytic for Desulfovibrio aespoeensis (Motamedi and Pedersen 1998) growing in a medium for sulphate-reducing bacteria, shown in transmission electron micrographs aand b. Images c and d show viruses (indicated by arrows) at the surface of a bacterium. Images were taken using 70,000 magnification in a c and 45,000 magnification in d.Images a and b are of a virus isolate denoted E, c of isolate D, and d of isolate B. The scale bar represents 100 nm in a c and 500 nm in d. (Photograph: Hallgerd Eydal).
The lack of large microbial biomass in intra-terrestrial environments has usually been taken as evidence that any microorganisms present there are inactive or metabolizing extremely slowly (Kerr 2002). The new results regarding virus presence at the Äspö HRL offer an alternative explanation of what viruses control active microbial populations in deep intra-terrestrial environments. Viruses encounter the cell walls of their hosts by chance, and attach to them before infection. The infection rate thus depends on the numbers of both viruses and available hosts. As the number of hosts decreases in response to lysis, the number of potential host cells also decreases, as will virus replication and abundance. If the rate of microorganism growth equals the rate of infection and lysis, the overall number of microorganisms will remain within a range defined by the infectivity of the viruses.
Viruses are completely dependent on active and growing host microorganisms for their reproduction. The number of viruses has been demonstrated to be significantly related to bacterial turnover in samples from deep Mediterranean sediments (Danovaro et al. 2002), to bacterial activity in sediments from Nivå Bay in Denmark (Middelboe et al. 2003), and to the number of host cells in the Adriatic Sea aquatic system (Corinaldesi et al. 2003). High ratios of viral to bacterial numbers have been observed at the Äspö HRL and are indicative of viruses actively infecting microorganisms that must be metabolically active. It confirms previously obtained energy source assimilation data (Pedersen and Ekendahl 1992a) and recent ATP analysis data (Eydal and Pedersen
20
2007), both of which suggested that the investigated microorganisms were in a state of active growth. Predator–prey relationships may be present in deep groundwater containing active and growing microorganisms, just as they are in many surface environments. However, as many intra-terrestrial environments are stagnant with low or no advective flow of water, intra-terrestrial microorganisms may be growth limited due to low access to energy over time. The observed metabolic rates may thus be much slower than in surface water, but the low numbers could be a result of predation rather than of starvation.
1.4 Microbial processes
Microbiological decomposition and the production of organic material depend on the energy sources and electron acceptors present (Madigan and Martinko 2006). Organic carbon and methane and reduced inorganic molecules, including hydrogen, are possible energy sources in the repository environment. During the microbial oxidation of these energy sources, microbes preferentially use electron acceptors in a particular order (as depicted in Figure 1-8): first oxygen, and thereafter nitrate, manganese, iron, sulphate, sulphur, and carbon dioxide are utilized. Simultaneously, fermentative processes supply the metabolizing microorganisms with, for example, hydrogen and short-chain organic acids. As the solubility of oxygen in water is low, and because oxygen is the preferred electron acceptor of many bacteria that utilize organic compounds in shallow groundwater, anaerobic environments and processes usually dominate at depth in the subterranean environment.
The reduction of microbial electron acceptors may significantly alter the chemistry of groundwater. Dissolved nitrate is reduced to gaseous nitrogen, solid manganese and iron oxides are reduced to dissolved species, and the sulphur in sulphate is reduced to sulphide (Figure 1-8). In addition, the metabolic processes of some microorganisms produce organic carbon, such as acetate, from the inorganic gases carbon dioxide and hydrogen, while other microorganisms produce methane from these gases; all these processes generally lower the redox potential, Eh. Most of these microbiologically mediated reactions will not occur in a lifeless groundwater environment lacking the cascade of biochemical reactions going on inside the cell membranes (Figure 1-2) of microorganisms. The mere presence of sulphide in a low-temperature granitic groundwater provides indisputable evidence of microbiological sulphate reduction. However, concentrations of reduced electron acceptors alone will not reveal when, where, and at what rate the individual microbial processes take place. Hence, robust, sound, and reproducible methods for estimating the rate at which microbial processes occur have had to be applied. Methods for analysing microbial process rates have been developed and tested under open and closed in situ conditions in the Äspö HRL situated 450 m underground. Groundwater that contained microorganisms, coming from a fracture adjacent to the laboratory, was circulated under in situ pressure and chemistry via flow cells that mimicked the conditions of fractured rock. The focus was determining the rate of the reduction of sulphate to sulphide and the rate of the production of acetate from hydrogen and carbon dioxide. Changing from an open to a closed system resulted in significant changes in the biogeochemistry (Hallbeck and Pedersen 2008). The conceptual difference between closed and open systems, which explains this change, is presented next.
21
Monomers
Hyd
roly
sis
Hydrolysis
CO2
CH4
2H2 + CO2
Acetate
H2 + CO2
O2 H2O
NO 3 N2
Mn4+ Mn2+
Fe3+ Fe2+
SO42 S2
S0 S2
Sulphate-reducing bacteria
Sulphur-reducing bacteria
Methanogens
Acetogenic bacteria
Manganese-reducingbacteria
Denitrifyingbacteria
Aerobic bacteria
Iron-reducing bacteria
Organic polymers
Oligo- and monomers
Organic acids, alcohols
Syntrophic bacteria
Acetate
Fermentative bacteria
CO2
CO2
CO2
CO2
CO2
Figure 1-8. Possible pathways for the flow of carbon in the subterranean environment. Organic carbon is respired with oxygen, if present, or else fermentation and anaerobic respiration occur with an array of different electron acceptors.
1.4.1 Closed systems
The usual way to culture microorganisms in the laboratory is by using batch cultures. A culture vessel is supplied with all constituents necessary for growth, and is inoculated with the microbe of interest. A typical batch growth curve can be registered (Figure 1-9). First, there is an adaptation phase during which the cells adjust to the conditions in the culture vessel. Then the cells start to divide and grow exponentially to high counts, doubling their number over constant time intervals. Finally, growth is arrested when some limiting component is used up, or when a toxic component is formed and accumulates to too high a concentration (e.g., alcohol, in fermentation cultures). Figure 1-9 indicates that the cells are basically active only during the exponential growth phase. The batch culture represents a closed system with no input or output of components. It is a superb tool for many research purposes in the laboratory, but it does not mimic the life of microbes in natural environments. The environment generally consists of a huge number of open systems with continuous input and output of matter between them. Models of microbial processes in the repository should therefore be based on continuous culture conditions, as described below, rather than on batch culture conditions.
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Living cells
per ml
10 000 000
1 000 000
100 000
10 000
1 000
100
10
1
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0
Relative activity
per cell
Stationary phase
Lo
gp
hase
Declin
ation
phase
Time
Figure 1-9. A schematic representation of microbial growth in a closed batch culture. The microbes are basically active only during the exponential growth phase, when they double in number within specific time periods. The doubling time can be as short as 15 min for some easily cultivated microbes or may be many hours for more recalcitrant microbes.
1.4.2 Open systems
Hard rock aquifers can be considered open systems. A particular fracture will contain water of a composition that reflects the origin of the water and the various reactions between the solid and liquid phases occurring along the flow path. A new composition may be the result of two fractures meeting and their waters mixing. Though these processes may be slow, there is a continuum of varying geochemical conditions in hard rock aquifers at repository depth, and the repository, with all the alien substances added by construction, will add variance to these conditions. Microbes are experts at utilizing any energy in the environment that becomes thermodynamically available for biochemical reactions. A slow but steady flow of organic carbon from the surface or a flow of reduced gases, such as hydrogen and methane from the interior of the planet or hydrogen from iron corrosion processes, will ultimately be the driving forces of the active life of deep aquifer microbes in and around an HLW repository.
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Living cells
per ml
10 000 000
1 000 000
100 000
10 000
1 000
100
10
1
1
0
Relative activity
per cell
Time
Energy availability
over time increases
Energy availability
over time decreases
Figure 1-10. The graph is a schematic representation of microbial growth in an open, continuous culture system. The microbes are continuously active at a constant level, except for periods when there is a decrease in energy availability over time. The doubling time of the population can be very long and, if growth is counteracted by viral predation, the numbers observed will remain relatively constant.
The continuous growth of microbes can be studied in the laboratory using a chemostat, in which the culture vessel is continuously supplied with energy via a slow inflow of nutrients. The inflow is balanced by an outflow that removes waste products and some cells. Though the number of microbe cells will therefore remain constant in the chemostat, the microbes that remain will be active (Figure 1-10). Unlike a batch system, a chemostat system is open, as it incorporates both an influx and outflow of matter. The continuous culture conditions of the chemostat are applicable to any hard rock aquifer experiencing a flux of matter through the continuous mixing of groundwater of varying compositions. Though the flows may be very slow in such aquifers, they will be significant over geological time scales.
The open, continuous culture system concept can be used when interpreting microbiology data for groundwater, such as the number of cells in a chosen groundwater measured at various times. If we apply the batch concept (Figure 1-9), we would conclude that the microbes are not growing and are inactive because we do not register any increase in cell numbers over time. In contrast, with the continuous culture concept (Figure 1-10), it can be predicted that the microbes will be active and growing slowly under constant environmental conditions over the time period studied. This prediction requires the existence of processes that counteract an increase in cell numbers due to
24
growth. Viruses that attack and infect microbes (1.3.6) may neutralize cell growth. Their activity results in the lysis of infected cells and in the production of new viruses. This process, which occurs in most surface environments, has recently been found in the deep aquifers of the Äspö HRL (1.3.6).
A special case is the possible occurrence of microbes that grow attached to aquifer surfaces, a phenomenon repeatedly observed in groundwater from deep hard rock aquifers (Ekendahl and Pedersen 1994). Such biofilms will increase their cell numbers until they reach steady state, as previously described for the continuous growth of unattached microbes. A comparison of the hypothetical cell numbers and activities of attached versus unattached bacteria in a 0.1-mm wide fracture was previously done (see Table 4.5 in Pedersen 2001). It demonstrated the potential importance of attached versus unattached microorganisms in underground environments. The studied microorganisms attached to artificial surfaces generally exhibited greater activity per cell than did the unattached microorganisms. Taken together with the cell numbers, there were up to five orders of magnitude more activity on the surfaces than in the groundwater. It is still an open question whether attached bacteria are common and active on aquifer rock surfaces under pristine conditions.
1.4.3 Microbial oxidation–reduction processes – “behind the scenes”
The biological oxidation–reduction processes presented in Figure 1-8 are commonly represented by general stoichiometric summary reactions. However, the actual biochemical reaction pathways are always much more complicated, often including a cascade of biochemical enzyme-catalysed reactions inside the living cells that are strictly controlled by the genetic code (i.e., DNA) of the individual cells. In addition, feedback and substrate-level control mechanisms may also be active. It is important to understand the biochemistry underlying summary reactions, otherwise the output of biological process models may be wrong. The reduction of the sulphur in sulphate to sulphide is used below to demonstrate the difference between a summary reaction and the full biochemical process.
Consider the summary equation for sulphate reduction with lactate as the electron donor:
2CH3CHOHCOO + SO42 2CH3COO + 2CO2 + 2H2O + S2 (Eq. 1-1)
The reaction would seem to indicate that lactate reacts directly with sulphate resulting in the formation of acetate, carbon dioxide, and sulphide. This, however, is very far from what actually happens. In fact, lactate and sulphate never make contact, but rather are dealt with by the bacterium in two separate biochemical pathways inside the cell (Figure 1-11). Lactate is split into acetate and formate via pyruvate, and the formate is then oxidized to carbon dioxide. This process involves three enzymes (i.e., lactate dehydrogenase, pyruvate formate lyase, and formate hydrogenolyase) and an oxidized proton–electron transport molecule denoted nicotinamid adenine nucleotide (NAD+). The electrons released are used as electron donors in reducing sulphate via a membrane-bound respiration chain. Consequently, the oxidation of the organic carbon is not
25
Sulphate-reducing
bacterium
4H2H2-ase
Cyt c3
Hmc
8H+
FeSprotein
LDH
Lactate
Pyruvate Acetate + Formate
CO2 + H2
SO42
ATP
SO32
H2S
6e
2e
H+
ADP
ATP
e APS
Cell membrane
8e
ATP-ase H+
ATP-sulfurylase
Sulphite-reductase
(excreted)
insideoutside
SO42
H2S
X
Lactate
X
Genetic control
DNA
Figure 1-11. Electron transport and energy conservation in sulphate-reducing bacteria. In addition to external hydrogen (H2), H2 originating from the catabolism of organic compounds such as lactate and pyruvate can fuel hydrogenase with electrons via enzymes such as lactate dehydrogenase (LDH). The protons released by the hydrogenase feed the proton gradient across the cell membrane, and this gradient changes ADP to ATP via ATP-ase. The enzymes hydrogenase (H2-ase), cytochrome c3
(cyt c3), and a cytochrome complex (Hmc) are periplasmic proteins located between the outer and inner membranes of the cell. A separate protein functions to shuttle electrons across the cytoplasmic cell membrane to a cytoplasmic iron-sulphur protein (FeS) that supplies the adenosine 5´-phosphosulphate (APS) reductase (forming SO3
2 ) and sulphite reductase (forming H2S). The process of sulphate reduction is controlled by the genetic code (i.e., DNA) of the bacterium. Environmental conditions are scanned by bacterial sensors that send messages to the DNA, which turns the sulphate reduction on and off under favourable and unfavourable conditions, respectively.
directly connected to the reduction of the sulphate. This is an important point valid for all processes depicted in Figure 1-8. Sulphate reduction will occur only when the cell needs to get rid of electrons that have generated a proton gradient across the cell membrane. From this, it should be clear that the rate of sulphate reduction cannot be determined solely from concentrations of sulphate and lactate. Rather, the needs of the cell are what determines whether sulphate reduction will occur and at what rate. If, for example, the cell lacks a crucial element needed to synthesize an enzyme involved in sulphate reduction, the process will not proceed at all, even if there is plentiful lactate and sulphate in the environment around the cell.
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Turning to other processes, such as iron, manganese, and nitrate reduction, acetate formation, and methanogenesis, will reveal other biochemical pathways, each of which is unique to the respective process. An endless array of more or less intricately linked processes can be found by anyone looking into a microbiology textbook, such as Brock Biology of Microorganisms (Madigan and Martinko. 2006). A full understanding of microbial oxidation–reduction processes is thus very complex. It becomes necessary to develop model approximations and simplifications that do not violate the rules of microbial biochemistry, otherwise the model output may be wrong. Later in the present report (4.7), the problems of understanding microbial biochemistry in groundwater will be brought up in relation to the obtained results.
1.5 The microbe’s dilemma – death or survival
In periods of inactivity due to lack of energy and necessary nutrients, or due to other environmental constraints, such as desiccation or slowly decreasing water activity, microbes can do one of two things: die or enter one of many possible dormancy states. Different species have different ways of addressing the problem of unfavourable conditions for active life. The most resistant form of survival is the endospore formed by certain gram-positive and sulphate-reducing bacteria. An endospore displays no measurable signs of life yet, after many years of inactivity, it can germinate into an actively growing cell within hours. It resists desiccation, radiation, heat, and aggressive chemicals far better than does the living cell.
The endospore is the most resistant survival states of any known life form, but there are many other survival strategies among the microbes, strategies more or less resistant to environmental constraints. Transforming into morphologically specific survival states is an advantage when the environment changes. However, in response to mere nutrient and energy deficiency, many microbes simply shut down their metabolism to an absolute minimum level at which they may survive for many years. Most such responses result in the shrinkage of the cell to a fraction of its volume under optimal growth conditions. What all these survival strategies share is that the cell is active at an absolutely minimal level – or displays no activity at all. It is thus possible that certain microbes may survive initially harsh conditions in a repository, including radiation, desiccation, heat, and high pH, until conditions for growth again become favourable. However, if the conditions are so difficult that all survival forms die off, and if the pore size of the environment does not allow for transport of microbes, as in highly compacted bentonite, then it is possible that specific environments in the repository may remain free of microbes once the original microbe population has disappeared. It is at present uncertain whether this will indeed be the case.
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2 MATERIALS AND METHODS
2.1 Sampling groundwater from shallow observation tubes and boreholes
Samples were collected on four different occasions from 16 shallow boreholes ranging in depth from 4 to 24.5 m (Table A-1). The sampling periods were 3 6 May 2004, 10 14 October 2005, 24 28 April 2006, and 9–13 October 2006. Descriptions of the first two rounds of sampling and associated investigations have been published as Posiva working reports (Pedersen 2006, 2007). All sampling sites were pumped out using an immersed borehole pump for at least 1.5 h prior to any field measurements or sample retrieval (Table A-1). The pump and tubing assembly was sterilized for approximately 2 h in an 11-ppm chlorine dioxide solution (FreeBact 20; XINIX, Märsta, Sweden) in a 100-L plastic barrel. The pumps were soaked in the chlorine dioxide solution and the solution was also pumped through the tubing.
2.1.1 Sampling point descriptions
The sites sampled at Olkiluoto (PVP1, PVP3A, PVP3B, PVP4A, PVP4B, PVP13, PVP14, PVP20, PR1, PP2, PP3, PP7, PP8, PP9, PP36, and PP39) penetrated groundwater, which was present in either the overburden (PVP) or water-conducting fractures in the bedrock (PR, PP) (Figure 2-1, Table A-1). Several of the boreholes and tubes selected for the 2004 sampling campaign turned out to be problematic due to bad packers, collapsing rock, similar or little water (PVP3A, PVP3B, PVP4B, PP3, PP7, and PP8). These were abandoned and new sampling points were selected for the three subsequent field campaigns. Overburden extended down to a depth of approximately 13 m and is composed of sand and silt with an organic soil layer approximately 0.8 m thick. Bedrock groundwater samples extended to a depth of 24.5 m. The local bedrock at Olkiluoto is Precambrian, composed of metamorphic rocks (predominantly migmatitic mica gneisses) and intruded by igneous rocks (granodiorites, coarse-grained granites, and granitic pegmatites). Local land use above the aquifers ranges from undisturbed forest to open areas cleared for repository construction. Further details can be found in the Posiva 2006 site description report (Andersson et al. 2007a).
2.1.2 Packer control tests with nitrogen
In the spring 2004 field week (Pedersen 2006), oxygen was detected in all boreholes. It was impossible to determine whether the sampling procedure had introduced this oxygen, or whether it was actually present in the groundwater that entered the boreholes. Therefore, an inflatable packer that allowed passage of sampling tubes and the wire for the pump was constructed and tested in the fall 2005 field week. Nitrogen was flushed, starting before the pumping, through half the number of boreholes that were being sampled at a rate of approximately 1 L of nitrogen gas per minute. In that way, the gas above the water level was replaced with nitrogen while the groundwater
28
Figure 2-1. Map showing the sampling points for shallow boreholes. Boreholes marked with blue squares were only sampled in 2004. See text for details.
level was being lowered due by the pumping (Table A-1). This prevented oxygen from entering the sampled groundwater from the atmosphere in the borehole.
2.1.3 Sterilization of borehole pumps
The procedure for sterilizing the pumps and tubing was tested by pumping sterile water through the equipment after a completed sterilization. The pumps were first soaked in a chlorine dioxide solution for 2 h as described above. The barrel was then washed with 500 mL of analytical grade water (AGW) (MilliQ-unit in the ONKALO laboratory). The adapter used for microbiology sampling was installed on the orifice of the pump tube. Two L of AGW water was then pumped through the system. Thereafter, 10 L of AGW water was added to the barrel and pumped (1 L min 1) out through the sampling adapter. The adapter was removed after 2 min and the remaining 8 L of water were pumped out (8 L min 1). This procedure simulated the pumping out of a borehole before starting sampling (See Table A-1). The adapter was flushed with 1 L of sterile AGW water and was then remounted. Finally, 5 L of sterile AGW water was pumped through the tubing, after which a full sampling for microbiology was performed according to the procedures used in the field.
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2.1.4 Test for reproducibility of groundwater chemistry and microbiology over time
Pumping out a borehole results transports water from the surrounding aquifers out through the borehole. It was deemed important to test for sensitivity in the data obtained from prolonged pumping. The borehole PVP4A had a yield of approximately 4 L min 1,and this borehole was selected for a reproducibility test in April 2006. It was sampled twice within a 6-h interval, which allowed 1440 L of groundwater to be pumped out of the borehole between the sampling occasions (Table A-1).
2.1.5 Sample collection for microbiological analyses
Groundwater was collected in the spring 2004 and fall 2005 field weeks using a Solinst Model 425 Discrete Interval Sampler (Solinst Ltd., Georgetown, ON, Canada) immediately after the pumping period was finished and the pump was hoisted out of the borehole (Figure 2-2). The sampling depth coincided with the depth of the borehole pump (Table A-1). Two different diameter samplers (26 mm and 51 mm) were used, depending on the diameter of the observation tube or borehole used. Prior to sampling, all exterior and interior fittings of the Solinst sampler were sterilized with a 20-ppm chlorine dioxide solution (FreeBact 20, XINIX) and then rinsed with sterile, autoclaved AGW water to prevent microbial contamination of the groundwater. To collect in situ groundwater from the required depth interval, the sampler was kept pressurized to 2 bars with N2 gas until it was at depth; then it was de-gassed (i.e., vented to the surface) allowing the ambient water in, and finally re-pressurized once the sampler was full prior to surface retrieval. Water from the sampler was then dispensed to the various containers for the analyses described below. Pressurizing the sampler to a pressure at least double that of the highest water pressure experienced by the sampler ensured that it remained closed until reaching the sampling depth.
While taking samples from the overburden holes (PVP) in the fall 2005 field campaign, it was noted that the water sampled using the Solinst sampler was in some cases slightly more turbid than that sampled using the borehole pump. This effect was not observed in the bedrock holes (PR, PP). It was assumed that the hoisting of the pump and the lowering of the Solinst sampler may have caused some hydrodynamic disturbance that increased the concentration of suspended material in the borehole. Microorganisms attach to particles, which could create some uncontrolled variability in the data. Therefore, in fall 2005 a comparison was made in the PVP20 borehole in which water was sampled twice for microbiology, first using the with the borehole pump and then the Solinst sampler. The assumed effect was confirmed. Therefore, groundwater was taken directly from the pump to sample tubes and bottles in the 2006 spring and fall sampling campaigns.
2.2 Sampling groundwater from deep boreholes
Deep groundwater was sampled for the analysis of chemistry, microbiology, and gas, as described below, using the PAVE system.
30
2.2.1 Packer-equipped deep boreholes sampled for microbiology
A total of 21 samples for microbiological analysis were taken between October 2004 and November 2006 (Table 2-1) from 13 boreholes (Figure 2-3). The depth range of the boreholes was from 34.6 m down to 449.6 m.
2.2.2 Sampling, transport, and extraction of deep groundwater samples
The groundwater was sampled using the PAVE system. The procedures for microbiological analysis using PAVE have been evaluated with the appropriate quality controls (Haveman et al. 1999). Before sampling groundwater from a deep borehole
Figure 2-2. Groundwater from PP36 is transferred from the SOLINST sampler to various microbiology analysis tubes by the team from Microbial Analytics Sweden AB.
section, the PAVE pressure vessel’s lower compartment was filled with argon or nitrogen and the movable piston was moved to the top of the pressure vessel. The gas pressure was set to approximately 5 bars. The borehole section to be sampled was packed off with inflatable rubber packers. The PAVE system, consisting of a membrane pump and one or several sterile, evacuated, closed pressure vessels connected in a series, was lowered into the borehole. Groundwater was pumped from the packed-off zone, past the closed pressure vessels, and out of the borehole. Groundwater parameters (i.e., pH, Eh, conductivity, O2, temperature, and the drill-water marker uranine) were monitored on-line until they stabilized. The uranine tracer had to indicate that drill-water contamination was below 2.5% before sampling could start. At that point, samples for field and laboratory analysis for hydrogeochemical characterization were
31
collected (Table A-2) and analysed (Table A-3). After this phase, the pressure valve of the PAVE system was opened; groundwater pressure then pushed down the piston in the sampler to fill the sampler with groundwater. The valve was left open for several hours to allow water to flow through the sampler, after which the pressure vessel was closed again and raised out of the borehole. The pressure vessels were shipped cold and arrived at the laboratory in Göteborg the morning after sampling (within 24 h of sample collection). At the laboratory, the vessel was opened and the groundwater removed. Fifteen numbered, sealable, sterilized anaerobic glass tubes (no. 2048-00150; Bellco Glass, Vineland, NJ, USA), sealed with butyl rubber stoppers (no. 2048-117800) and sealed with aluminium crimp seals (no. 2048-11020, Bellco Glass), were each filled with 10 12 mL of sampled groundwater. Media inoculation started immediately after removing the groundwater from the sampler, and work with each sample was complete within 2–4 h of removal of groundwater from the pressure vessel.
Figure 2-3. Map showing the deep boreholes sampled. Red squares indicate the sampled boreholes listed in Table 2-1.
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Table 2-1. Identification information for the deep boreholes sampled for micro-biological analyses.
Borehole Posiva no. Sampled
section
(m)
Mid elevation,
z
(m)
Sample
date
OL-KR-2 KR2-329-1 328.5–330.5 306.2 2004-12-20
OL-KR-6 KR6-98-8 98.5–100.5 73.7 2006-10-16
OL-KR-6 KR6-125-6 125–130 94.1 2006-06-26
OL-KR-6 KR6-135-8 135–137 101.8 2006-08-22
OL-KR-6 KR6-422-5 422–425 328.4 2006-05-11
OL-KR-7 KR7-275-1 275.5–289.5 249.4 2005-03-01
OL-KR-8 KR8-77-1 77.0–84.0 57.3 2005-10-25
OL-KR-8 KR8-302-2 302.0–310.0 260.7 2006-06-06
OL-KR-10 KR10-326-2 326.0–328.0 316.0 2006-06-19
OL-KR-10 KR10-115-1 115.5–118.5 106.0 2005-02-21
OL-KR-13 KR13-362-2 362.0–365.0 294.0 2004-10-12
OL-KR-13 KR13-362-3 362.0–365.0 294.0 2006-03-14
OL-KR-19 KR19-526-1 525.5–539.5 449.6 2004-11-08
OL-KR-27 KR27-247-1 247.0–264.0 193.5 2004-11-09
OL-KR-27 KR27-503-1 503.0–506.0 391.7 2005-01-17
OL-KR-31 KR31-143-1 143.0–146.0 122.4 2006-10-24
OL-KR-32 KR32-50-1 50.0–52.0 34.6 2006-01-10
OL-KR-33 KR33-95-1 95.0–107.0 70.6 2006-01-24
OL-KR-37 KR37-166-1 166–176 111.6 2006-11-28
OL-KR-39 KR39-108-1 108.0–110.0 88.2 2006-05-30
OL-KR-39 KR39-403-1 403.0–406.0 344.8 2006-04-03
2.3 Physical parameters, chemistry, and gas content of the sampled groundwater
2.3.1 Field measurements of physical parameters in shallow boreholes and groundwater observation tubes
Field measurements were made in a 1-L container at the surface while groundwater was being pumped to the surface. The measurements and sampling for chemistry were done at the end of the pumping period (Table A-1). The temperature of the groundwater was
33
measured using a pIONeer 10 portable pH meter equipped with a pHC5977 cartrode combined pH electrode (pH range 0–14, ± 0.5 at zero; temperature range –10 to 110°C, ± 0.3°C) (Radiometer, Labora, Stockholm, Sweden). Redox was measured using the same pH meter, but equipped with a MC3187Pt combined platinum electrode with an Ag/AgCl reference system, range –2000 to 2000 mV (± 0.01% of reading) (Radiometer). The dissolved oxygen concentration was measured using two different meters and electrodes: 1) a pIONeer 20 portable oxygen meter equipped with a DOX20T-T oxygen probe with a concentration range of 1–20 mg/L (0–200% ± 1%) (Radiometer), and 2) an HQ10 Hach Portable LDO™ Dissolved Oxygen Meter, Cat No. 51815-00 (Hach, Stockholm, Sweden). The probes were calibrated in situ per the manufacturer’s instructions. The dissolved oxygen was measured in a series of five measurements made over one year to analyse for seasonal variations; the sampling months were October 2005 and April, May, July, and October 2006.
2.3.2 Analysis of dissolved oxygen in shallow groundwater using Winkler titration
Oxygen was analysed in the laboratory using a modified Winkler method as described in detail in Carritt and Carpenter (1966). Briefly stated, three approximately 115-mL, glass-stoppered Winkler bottles (Figure 2-4) were flushed with at least three volumes of groundwater from the pump to remove all oxygen from atmospheric sources. Then manganese ions were precipitated directly in the field in an alkaline medium, forming manganous hydroxide. This hydroxide was oxidized by present dissolved oxygen in the sample according to:
2Mn(OH)2 + O2 2MnO(OH)2 (Eq. 2-1)
The manganese hydroxide was dissolved in the laboratory with acid and reduced by iodine ions (Figure 2-4), as follows:
MnO(OH)2 + 4H3O+ + 3I Mn2+ + I3 + 7H2O (Eq. 2-2)
Finally, the I3 ions produced were determined by titration, with thiosulphate ions and soluble starch used as the titration indicator, as follows:
2S2O32 + I3 S4O6
2 + 3I (Eq. 2-3)
2.3.3 Chemical analyses of shallow and deep groundwater
Water samples were transferred from the investigation site to the Teollisuuden Voima Oy (TVO) laboratory directly after sampling. The chemical analyses were performed by TVO according to their protocols, or were subcontracted to external laboratories.
Groundwater samples for laboratory analysis were collected during pumping before stopping the pump (Table A-1) in a 5-L plastic canister (for testing for Br , Cl , F ,SO4
2 , Stot, pH, and conductivity), 1-L glass bottles (for testing for alkalinity, acidity,
34
Figure 2-4. Winkler bottles with acid-dissolved precipitations. The samples from PP39 were free of oxygen. For comparison, oxygen-containing tap water is shown to the right.
DIC/DOC), and 1-L nitric acid-washed glass bottles (for testing for metals). Groundwater samples for sulphide analysis were collected in three 100-mL Winkler bottles. All the water chemistry samples were partly filtered with a membrane filter (0.45 µm), bottled, and preserving chemicals were added to part of the samples according to Table A-2. Analysis methods, detection limits, and uncertainties of the measurements are presented in Table A-3.
2.3.4 Sampling and analysis of dissolved gas
Shallow groundwater was sampled in triplicate in nitrogen-flushed 120-mL glass bottles equipped with butyl rubber stoppers (no. 2048-117800; Bellco Glass) and sealed with aluminium crimp seals (no. 2048-11020). The vacuum pressure in the bottles was set to 10 2 mBar 2–4 h before sampling. Water from the pump was led via poly-ether-ether-keton (PEEK) tubing through a syringe into the bottles, which were filled with approximately 100 mL of groundwater. In the laboratory, the bottles were attached to the extraction unit (Figure A-1) and the samples were transferred to the extraction unit cylinder. The transfer time was approximately 20–30 min. Thereafter analysis was
35
Table 2-2. List of deep packer-equipped boreholes sampled for analysis of dissolved gas; -N2 and -Ar appearing after the borehole code indicate the gas used in the pressure compartment.
Borehole Sampled
section
(m)
Mid elevation,
z
(m)
Sampling
date
Analysis
date
OL-KR-2-N2 596.5–609.5 560 2006-02-28 2006-03-07
OL-KR-6-N2 422–425 328 2005-08-02 2005-08-24
OL-KR-6-N2 135–137 116 2006-08-22 2006-08-28
OL-KR-6-N2 135–137 102 2005-09-27 2005-09-27
OL-KR-6-N2 125–130 94 2006-06-26 2006-07-02
OL-KR-6-N2 120–125 90 2005-11-02 2005-12-12
OL-KR-6-N2 98.5–100.5 74 2006-10-16 2006-10-24
OL-KR-6-N2 98.5–100.5 73 2005-12-27 2006-01-13
OL-KR-7-N2 284–288 257 2006-04-25 2006-05-11
OL-KR-7-Ar 220–230 197 2005-04-25 2005-08-22
OL-KR-7-N2 220–230 197 2005-04-25 2005-08-23
OL-KR-8-N2 302–310 261 2006-06-06 2006-06-09
OL-KR-8-N2 77–84 57 2005-10-25 2005-12-12
OL-KR-8-N2 77–84 57 2006-08-15 2006-08-28
OL-KR-8-N2 556.5–561 490 2006-04-27 2006-05-11
OL-KR-10-N2 326–328 316 2006-06-19 2006-06-21
OL-KR-10-N2 259–262 249 2005-04-04 2005-06-26
OL-KR-10-Ar 326.5–328.5 316 2005-04-04 2005-08-23
OL-KR-10-N2 326.5–328.5 316 2005-04-04 2005-08-23
OL-KR-13-N2 362–365 294 2006-03-14 2006-03-27
OL-KR-19-N2 110–131 101 2005-09-05 2005-10-05
OL-KR-19-N2 455–468 433 2005-10-31 2005-12-12
OL-KR-22-N2 390–394 320 2006-03-01 2006-03-07
OL-KR-22-N2 147–152 116 2005-12-13 2006-01-13
OL-KR-22-N2 147–152 102 2006-08-17 2006-08-28
OL-KR-29-N2 320–340 293 2005-06-06 2005-08-23
OL-KR-29-N2 800–800 742 2005-04-16 2005-08-23
OL-KR-30-N2 50–54 40 2005-08-04 2005-08-24
OL-KR-31-N2 143–146 122 2006-10-24 2006-10-26
OL-KR-33-N2 95–107 71 2006-01-24 2006-01-26
OL-KR-37-N2 166–176 112 2006-11-28 2006-11-30
OL-KR-39-N2 403–406 345 2006-04-03 2006-04-06 OL-KR-39-N2 108–110 88 2006-05-30 2006-06-09
36
performed as described in the Appendix (page 149). Water samples from all boreholes and observation tubes sampled in spring and fall 2006 were analysed for dissolved gas (Table A-1).
Deep groundwater (Table 2-2) was sampled using the PAVE sample vessel, which was attached to the extraction unit in the lab. Groundwater transfer typically took 5 min. Thereafter analysis was performed as described in the Appendix (page 149).
2.4 Microbiological analyses
2.4.1 Determining total number of cells
The total number of cells (TNC) was determined using the acridine orange direct count (AODC) method as devised by Hobbie et al. (1977) and modified by Pedersen and Ekendahl (1990). All solutions used were filtered through sterilized 32-mm-diameter, 0.2-µm-pore-size Minisart CA syringe filters (Sartorius, GTF, Göteborg, Sweden). Stainless steel analytical filter holders, 13 mm in diameter (no. XX3001240; Millipore, Billerica, MA, USA), were rinsed with sterile, filtered, AGW (Millipore Elix 3; Millipore, Solna, Sweden). Samples of 1 mL were suction filtered ( 20 kPa) onto 0.22-µm-pore-size Sudan black-stained polycarbonate isopore filters, 13 mm in diameter (GTBP011300, Millipore, Solna, Sweden). The filtered cells were stained for 5 min with 200 µL of an acridine orange (AO) solution (SigmaAldrich, Stockholm, Sweden). The AO solution was prepared by dissolving 10 mg of AO in 1 L of a 6.6 mM sodium potassium phosphate buffer, pH 6.7 (Pedersen and Ekendahl 1990). The filters were mounted between microscope slides and cover slips using fluorescence-free immersion oil (Olympus, Göteborg, Sweden). The number of cells was counted under blue light (390–490 nm) and using a band-pass filter for orange light (530 nm), in an epifluorescence microscope (Nikon DIPHOT 300; Tekno-Optik, Göteborg, Sweden). Between 400 and 600 cells, or a minimum of 30 microscopic fields (1 field = 0.01 mm2), were counted on each filter.
2.4.2 ATP analysis
The ATP Biomass Kit HS for determining total ATP in living cells was used (no. 266-311; BioThema, Handen, Sweden). This analysis kit was developed based on the results of Lundin et al. (1986) and Lundin (2000). Sterile and “PCR clean” epTIPS with filters (GTF, Göteborg, Sweden) were used in transferring all solutions and samples to prevent ATP contamination of pipettes and solutions. Light may cause delayed fluorescence of materials and solutions, so all procedures described below were performed in a dark room and all plastic material, solutions, and pipettes were stored in the dark. A new 4.0-mL, 12-mm-diameter polypropylene tube (no. 68.752; Sarstedt, Landskrona, Sweden) was filled with 400 µL of the ATP kit reagent HS (BioThema, Handen, Sweden) and inserted into an FB12 tube luminometer (Sirius Berthold, Pforzheim, Germany). The quick measurement FB12/Sirius software, version 1.4 (Berthold Detection Systems, Pforzheim, Germany), was used to calculate light emission as relative light units per
37
second (RLU s 1). Light emission was measured for three 5-s intervals with a 5-s delay before each interval, and the average of three readings was registered as a single measurement. The background light emission (Ibkg) from the reagent HS and the tube was monitored and allowed to decrease to a value below 50 RLU s 1 prior to registering a measurement. ATP was extracted from 100-µL aliquots of sample within 1 h of collection, by mixing for 5 s with 100 µL of B/S extractant from the ATP kit in a separate 4.0-mL polypropylene tube. Immediately after mixing, 100 µL of the obtained ATP extract mixture was added to the reagent HS tube in the FB12 tube luminometer, and the sample light emission (Ismp) was measured. Subsequently, 10 µL of an internal ATP standard was added to the reactant tube, and the standard light emission (Istd) was measured. The concentration of the ATP standard was to 10 7 M. Samples with ATP concentrations close to or higher than that of the ATP standard were diluted with B/S extractant to a concentration of approximately 1/10 that of the ATP standard. Mixtures of reagent HS and B/S extractant were measured at regular intervals to control for possible ATP contamination. Values of 1600 ± 500 amol ATP mL 1 (n = 10) were obtained with clean solutions, while solutions displaying values above 1600 amol ATP mL 1 were disposed of.
The ATP concentration of the analysed samples was calculated as follows:
amol ATP mL 1 = (Ismp Ibkg) / ((I smp + std I bkg ) – (I smp – I bkg)) 109 / sample volume
where I represents the light intensity measured as RLU s 1, smp represents sample, bkg represents the background value of the reagent HS, and std represents the standard (referring to a 10 7 M ATP standard).
This ATP biomass method has been evaluated for use with Fennoscandian groundwater, including Olkiluoto groundwater, and the results were recently published (Eydal and Pedersen 2007).
2.4.3 Determining cultivable aerobic bacteria
Petri dishes containing agar with nutrients were prepared for determining the numbers of cultivable heterotrophic aerobic bacteria (CHAB) in groundwater samples. This agar contained 0.5 g L 1 of peptone (Merck), 0.5 g L 1 of yeast extract (Merck), 0.25 g L 1 of sodium acetate (Merck), 0.25 g L 1 of soluble starch (Merck), 0.1 g L 1 of K2HPO4, 0.2 g L 1 of CaCl2 (Merck), 10 g L 1 of NaCl (Merck), 1 mL L–1 of trace element solution (see Table 2-3 D), and 15 g L 1 of agar (Merck) (Pedersen and Ekendahl 1990). The medium was sterilized in 1-L batches by autoclaving at 121°C for 20 min, cooled to approximately 50 C in a water bath, and finally distributed in 15-mL portions in 9-cm-diameter plastic Petri dishes (GTF, Göteborg, Sweden). Ten-times dilution series of culture samples were made in sterile analytical grade water (AGW) with 0.9 g L 1 of NaCl; 0.1-mL portions of each dilution were spread with a sterile glass rod on the plates in triplicate. The plates were incubated for between 7 and 9 d at 20°C, after which the number of colony forming units (CFU) was counted; plates with between 10 and 300 colonies were counted.
38
2.4.4 Preparing media for most probable numbers of cultivable anaerobic microorganisms
Media for determining the most probable number of microorganisms (MPN) in groundwater were formulated based on previously measured chemical data from Olkiluoto. This allowed the formulation of artificial media that most closely mimicked in situ groundwater chemistry for optimal microbial cultivation (Haveman and Pedersen 2002a). Media for the nitrate-reducing bacteria (NRB), iron-reducing bacteria (IRB), manganese-reducing bacteria (MRB), sulphate-reducing bacteria (SRB), autotrophic acetogen (AA), heterotrophic acetogen (HA), autotrophic methanogen (AM), and heterotrophic methanogen (HM) metabolic groups were autoclaved and anaerobically dispensed, according to the formulations outlined in Table 2-3, into 27-mL, sealable anaerobic glass tubes (no. 2048-00150; Bellco Glass), sealed with butyl rubber stoppers (no. 2048-117800), and sealed with aluminium crimp seals (no. 2048-11020).
All culture tubes were flushed with 80/20% N2/CO2 gas and then filled with 9 mL of the appropriate media. For IRB, 1 mL of hydrous ferric oxide (HFO), prepared from FeCl3,was added to each culture tube. The final concentration of the iron solution was 0.44 M. For MRB, 2 mL of 135 mM MnO2 solution (Lovley and Phillips 1988) was added. The HM media also contained 20 mL L 1 of 100 g L 1 NaCOO, 3 mL L 1 of 6470 mM trimethylamine, 4 mL L 1 of methanol, and 20 mL L 1 of a 20 g L 1 solution of NaCH3COO. The HA medium also contained 20 mL L 1 of 100 g/L NaCOO, 3 mL L 1
of 6470 mM trimethylamine, and 4 mL L 1 of methanol. The final pH was adjusted to between 6.5 and 7.5 with 1 M HCl or 1 M NaOH.
2.4.5 Inoculations and analysis for anaerobic microorganisms
Inoculations for NRB, IRB, MRB, SRB, AA, HA, AM, and HM were performed in the laboratory less than 2 h after sampling for shallow groundwater and the next morning for deep groundwater samples. After inoculating, the headspaces of only the AA and AM cultures were filled with H2 to an overpressure of 2 bars; all MPN tubes were incubated in the dark at 20°C for 8 13 weeks. After incubation, the MPN tubes were analysed by testing for metabolic products or substrate consumption. Nitrate consumption was determined using a DR/2500 spectrophotometer (HACH, Loveland, CO, USA) with the chromotropic acid method (HACH method no. 10020) for water and wastewater (0.2–30 mg/L NO3 -N). The production of ferrous iron by IRB was determined using the 1,10 phenanthroline method (HACH, method no. 8146). HACH method no. 8034, based on periodate oxidation, was used in a similar way to determine Mn2+ concentrations in MPN tubes for MRB. SRB were detected by measuring sulphide production using the CuSO4 method according to Widdel and Bak (1992) on a UV visible spectrophotometer (Genesys10UV, VWR, Stockholm, Sweden). Methanogens were detected by measuring the production of methane in the culture tube headspace. The methane was analysed using a Star 3400CX gas chromatograph (Varian, Stockholm, Sweden) using a flame ionization detector (FID) at an oven temperature of 65°C and a detector temperature of 200°C. The methane gas was separated using a Porapak-Q column (2 m 1/8 inch diameter; Agilent Technologies, Varian, Stockholm, Sweden) and analysed on the FID with nitrogen as the carrier gas (confer Appendix,
39
page 149). Acetogens were detected by means of acetate production using an enzymatic UV method (Enzymatic Bioanalysis Kit no. 10 139 084 035; Boehringer Mannheim/R-Biopharm, Food Diagnostics, Göteborg, Sweden) with a UV visible spectrophotometer (per SRB detection). Product formation at a concentration twice or above that of the uninoculated control tubes was taken as positive for all MPN analyses except nitrate, for which a 50% reduction in nitrate concentration, compared with that of uninoculated controls, was taken as a positive result.
The MPN procedures resulted in protocols with tubes that scored positive or negative for growth. The results of the analyses were rated positive or negative compared with control levels. Three dilutions with five parallel tubes were used to calculate the MPN of each group, according to the calculations found in Greenberg et al. (1992).
2.4.6 Inoculations and analysis for aerobic methane-oxidizing bacteria
Sets of MPN tubes were prepared for samples using a nitrate mineral salts (NMS) medium (Whittenbury et al. 1970) prepared as follows: 1.0 g L 1 of KNO3, 1 g L 1 of MgSO4 7 H2O, 0.2 g L 1 of CaCl2 2 H2O, 1 mg L 1 of CuCl2 2H2O, 7 g L 1 of NaCl, 1 mL L 1 of an iron solution made of 0.5 g of ferric (III) chloride in 1000 mL of AGW, 1 mL L 1 of a trace element solution according to Table 2-3D and 2 mL L 1 of a phosphate buffer solution made of 3.6 g Na2HPO4, and 1.4 g NaH2PO4 in 100 mL of AGW. The pH was adjusted to 6.8–7.0. Cultural conditions were optimized to support the growth of both types I and II methane-oxidizing bacteria (MOB) by adding 1 mg L 1
of copper chloride dihydrate. This is because the soluble and particulate methane monooxygenase (s/pMMO) common to all known MOB is controlled by a copper-inducible regulatory pathway.
MPN inoculations were completed at the ONKALO laboratory within 2 h of sample collection for all shallow borehole samples. Five parallel dilution tubes were used for each dilution. All transfers were performed aseptically using new sterile syringes and needles. After each transfer, the tubes were vortexed to achieve homogeneity. Control tubes contained nitrate minimal salt medium and 1 mL of filtered groundwater. After inoculation, filter-sterilized (using 0.2-µm Millipore filters) methane was injected into the headspace of each tube to 1 Bar overpressure. The tubes were then incubated horizontally in the dark at 20 C. Growth of cells was detected after between 2 and 4 weeks, as judged by turbidity compared with that of negative controls and the concomitant production of CO2 via methane oxidation in turbid tubes. MPN calculations were made using a combination of positive tubes in a 3-tube dilution series (i.e., 15 tubes) according to Greenberg et al. (1992). The detection limit was <0.2 cells mL 1.
40
Table 2-3. A-G. Compositions of anaerobic media used for MPN cultivation of different metabolic groups of anaerobic microorganisms. All components were anoxic.
A) Ready medium Metabolic groupa
Component (mL/L) NRB IRB & MRB SRB AA & HA AM & HM
Basal medium (Table B) 925 940 860 860 890
Trace elements (Table C) - - 10 10 10
Trace elements (Table D) 1.0 1.0 - - -
Vitamins (Table E) 1.0 1.0 - - -
Vitamins (Table F) - - 10 10 10
Thiamine stock (Table G) 1.0 1.0 1.0 1.0 1.0
Vitamin B12 stock (Table G) 1.0 1.0 1.0 1.0 1.0
Fe stock (Table G) - - 5.0 5.0 5.0
Resazurin (Table G) - - 2.0 2.0 2.0
Cysteine hydrochloride (Table G) - - 10 10 10
NaHCO3 (Table G) 30 30 60 60 60
Yeast extract (Table G) 1.0 1.0 10 10 10
NaCH3COO (Table G) 25 25 - - -
Lactate (Table G) 5.0 - 5.0 - -
KNO3 (G) 10 - - - -
Sodium sulphide (0.2 M) - - 7.5 10 10
a NRB = nitrate-reducing bacteria, IRB = iron-reducing bacteria, MRB = manganese-reducing bacteria, AA = autotrophic acetogens, HA = heterotrophic acetogens, AM = autotrophic methanogens, HM = heterotrophic methanogens
B) Basal medium Metabolic groupa
Component (g) NRB, IRB, & MRB SRB AA & HA AM & HM
AGW 1000 1000 1000 1000
NaCl 7 7 7 7
CaCl2*2H2O 1.0 1.0 1.0 0.28
KCl 0.1 0.67 0.67 0.67
NH4Cl 1.5 1.0 1.0 1.0
KH2PO4 0.2 0.15 0.15 0.15
MgCl2*6H2O 0.1 0.5 0.5 0.5
MgSO4*7H2O 0.1 3.0 - -
MnCl2*4H2O 0.005 - - -
Na2MoO4*2H2O 0.001 - - -
a NRB = nitrate-reducing bacteria, IRB = iron-reducing bacteria, MRB = manganese-reducing bacteria, AA = autotrophic acetogens, HA = heterotrophic acetogens, AM = autotrophic methanogens, HM = heterotrophic methanogens
41
Table 2-3. Continued. C) Trace element solution
Component Amount
AGW 1000 mL
Nitrilotriacetic acid 1500 mg
Fe(NH4)2(SO4)2*6H2O 200 mg
Na2SeO3 200 mg
CoCl2*6H2O 100 mg
MnCl2*4H2O 100 mg
Na2MoO4*2H2O 100 mg
Na2WO4*2H2O 100 mg
ZnSO4*7H2O 100 mg
AlCl3 40 mg
NiCl2*6H2O 25 mg
H3BO3 10 mg
CuCl2*2H2O 10 mg
D) Non-chelated trace elements
Component Amount
AGW 987 mL
HCl (25% = 7.7 M) 12.5 mL
FeSO4*7H2O 2.1 g
H3BO3 30 mg
MnCl2*4H2O 100 mg
CoCl2*6H2O 190 mg
NiCl2*6H2O 24 mg
CuCl2*2H2O 2 mg
ZnSO4*7H2O 144 mg
Na2MoO4*2H2O 36 mg
E) Vitamin mixture for NRB, IRB, and MRB
Component Amount
Sodium phosphate buffer 10 mM pH 7.1
100 mL
4-Aminobenzoic acid 4 mg
D(+)-biotin 1 mg
Nicotinic acid 10 mg
Pyridoxine dihydrochloride 15 mg
Calcium D(+) pantothenate 5 mg
F) Vitamin mixture for SRB, AA, HA, AM, and
HM
Component Amount
Sodium phosphate buffer 10 mMpH 7.1
1000 mL
p-Aminobenzoic acid 10 mg
Nicotinic acid 10 mg
Calcium D(+) pantothenate 10 mg
Pyridoxine dihydrochloride 10 mg
Riboflavin 10 mg
D(+)-biotin 5 mg
Folic acid 5 mg
DL-6-8-thiotic acid 5 mg
G) Stock solutions
Component Amount
NaHCO3 84 g L 1
Thiamine chloride dihydrochloride in a 25 mM sodium phosphate buffer, pH 3.4
100 mg L 1
Cyanocobalamin (B12) 50 mg L 1
KNO3 100 g L 1
NaCH3COO 100g L 1
Yeast extract 50 g L 1
Fe(NH4)2(SO4)2*6H2O,initially dissolved in 0.1 mL of concentrated HCl
2 g L 1
Resazurin 500 mg L 1
Cysteine-HCl 50 g L 1
Sodium lactate solution 50%
42
2.4.7 Quality controls for the most probable number analysis
The reproducibility of the sampling and analysis procedures was tested using the Swedish PAVE analogue, the PVB pressure vessel. The 353.5–360.0-m section of the Forsmark site investigation borehole KFM06A was sampled on 14 March 2005 using two PVB samplers installed at the same time. It was also deemed important to test reproducibility over time in borehole sections that were expected to harbour stable and reproducible populations. This was done in two boreholes at the MICROBE site (Pedersen 2005a) in the Äspö HRL tunnel, denoted KJ0052F01 and KJ0052F03. Groundwater from the borehole sections was sampled using PVB samplers on two occasions, 26 October 2004 and 9 February 2005. The PVB samplers were attached to the flows from each borehole section, and groundwater was circulated overnight under in situ pressure, temperature, and chemistry conditions. Early in the morning, the samplers were closed, detached, and transported to the laboratory in Göteborg; analysis started the same afternoon, before 14.00. All parts of this procedure resembled the sampling of sections in the Olkiluoto deep boreholes, except that in this case the samplers were not operated remotely from the ground surface; instead, personnel standing next to the PVB samplers in the tunnel manually operated the samplers using adjustable spanners.
43
3 RESULTS
3.1 Analysis of physical and chemical parameters
The results of all field and laboratory measurements of physical and chemical parameters are presented in Appendix A, Table A-4. All references to specific physical and chemical data in this results section refer to this table. For some parameters, such as the analysis of oxygen and Eh using the HACH field instruments, results were only obtained for the shallow groundwater samples. The shift from sampling shallow groundwater using the SOLINST sampler and the pump to sampling deep groundwater using the PAVE system partly meant applying different sampling methods. For example, shallow groundwater gas was analysed from samples in glass bottles while the deep groundwater was analysed in samples from the PAVE pressure vessel. However, the differences between sampling procedures do not imply biased data, and shallow and deep groundwater data are presented and interpreted together. All available data for each analysed parameter in both shallow and deep groundwater are presented in the following figures.
3.1.1 Field measurements of physical parameters
The pH ranged from 4.8 to 8.2. All values below pH 6 were found in groundwater from a depth of less than 10 m (Figure 3-1), except for samples from borehole PP36 (12.1 m), which had a stable pH of 5.8 over all sampling periods. Most of the shallow groundwater samples had pH values from 6.5 to 7.5, while the deep groundwater had pH values from 7 to 8.2.
The conductivity ranged from 10 to 10000 mS m 1 (Figure 3-2), with the exception of groundwater from boreholes PR1 (sampled 2006-10-11) and PP39 (sampled 2006-04-24), which were diluted to below and at the detection limit, respectively. The conductivity increased exponentially with depth within a range of approximately plus–minus five times the observed average value for each depth.
Oxygen was found in several shallow groundwater samples (Figure 3-3) but was absent from deep groundwater (see section 3.2). Two different methods were used to analyse oxygen in shallow groundwater, one electrochemical and one wet chemistry method. The HQ10 HACH Portable LDO™ dissolved oxygen meter was used in the field starting in fall 2005. The data from spring 2004 were obtained using a membrane electrode that is more difficult to operate than the LDO electrode is. The membrane electrode needs frequent calibrations that can be difficult to perform in the field, while the LDO electrode is calibrated once per year and is very stable. On-line electrodes were used to analyse oxygen in deep groundwater (data not presented). The oxygen values obtained in shallow groundwater in spring 2004 were generally higher than those obtained in the remaining three field campaigns. Although the membrane electrode was carefully calibrated, some caution should be used when comparing 2004 oxygen data with oxygen data from 2005 and onwards, as the different types of electrodes used may have introduced a bias. Titrating oxygen using the Winkler method was introduced in spring 2006. The LDO electrode results correlated well with the Winkler data (Figure 3-4).
44
The LDO electrode results were very well correlated with the Winkler results at high oxygen concentrations. The exception was for borehole PP9 (sampled 2006-04-27), but on this occasion there was an unusual gap of approximately 4 h in sampling time between the LDO electrode measurement (1st) and the Winkler sample (2nd), due to problems with heavy turbidity from a dissolving bentonite packer; this delay may have introduced more oxygen. Therefore, the Winkler data (4.24 mg O2 L 1) were much higher than the LDO data (2.35 mg O2 L
1) on this occasion. Otherwise, all LDO data were similar to or somewhat higher than the Winkler data. The LDO electrode is less precise at values below 0.5 mg O2 mL 1, and those data should be taken as approximations. The Winkler analysis is reliable over a large range, extending from the detection limit of 0.05 mg of O2 mL 1 to oversaturated samples. In conclusion, both the electrode and the Winkler analyses revealed rapidly decreasing oxygen values with increasing depth. Small amounts of oxygen remained in the groundwater below 10 m (Figure 3-3), except for the problematic PP9 sample mentioned above.
The measurement of Eh in shallow groundwater should be regarded as a relative analysis and the Eh values obtained should not be directly compared with Eh values obtained in deep groundwater as other electrodes and measurement conditions were valid there. The Eh values over depth in shallow groundwater were very scattered, displaying only a very weak decreasing trend with increasing depth (Figure 3-5).
The four field campaigns were performed in April and October. The concentration of dissolved oxygen was expected to vary seasonally, and when dissolved oxygen was repeatedly analysed in summer 2006 this could be confirmed (Figure 3-6). The concentration of oxygen decreased in summer and increased in fall and spring.
3.1.2 Chemical analyses of groundwater
The general trend was for dissolved solids to increase with depth (Table A-4), as reflected by the conductivity measurements (Figure 3-2). The concentration of dissolved organic carbon (DOC) is of special interest for microbiological interpretations, as DOC can be expected to relate to microbiology. When analysed, no correlation was found between DOC and depth (Figure 3-7). Instead, the DOC values were scattered from below the detection limit of 1.8 mg DOC mL 1 up to 39 mg DOC mL 1. One sample displayed an exceptionally high DOC value of 196 mg DOC mL 1. This was from the shallow PVP1 observation tube that was completely flooded by snow meltwater until the day before sampling (2006-04-27). This was not persistent contamination, as the DOC value was less than a tenth of that six months later (2006-10-12). The concentrations of ferrous iron and sulphide displayed inversely related trends, with decreasing ferrous iron and increasing sulphide values with depth (Figure 3-8). The ferrous iron concentration was up to ten times higher in shallow than in deep groundwater. The dissolved sulphide concentration was at or below the detection limit down to a depth of 70 m and peaked at a depth of approximately 300 m.
45
4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5
pH
1
10
100
1000
Dep
th (
m)
Figure 3-1. The pH in groundwater samples from Olkiluoto against depth.
0.1 1.0 10.0 100.0 1000.0 10000.0
Conductivity (mS m-1)
1
10
100
1000
Depth
(m
)
Figure 3-2. The electrical conductivity in groundwater samples from Olkiluoto over depth.
46
O2 HACH O2 Winkler
0 1 2 3 4 5 6 7
O2 (mg L 1)
0
5
10
15
20
Depth
(m
)
Figure 3-3. The concentration of dissolved oxygen in shallow groundwater analysed using the HQ10 HACH Portable LDO™ dissolved oxygen meter and by means of Winkler titration in the laboratory (the average values of three titrations are shown).
0.0 0.1 1.0 10.0
O2 LDO electrode (mg L 1)
0.0
0.1
1.0
10.0
O2
Win
kle
r (m
g L
1)
Figure 3-4. The correlation between oxygen as measured using the DOX20T-T membrane electrode (2004) or the HQ10 HACH Portable LDO™ dissolved oxygen meter and by means of Winkler titration in the laboratory (the average values of three titrations are shown). The line denotes identical values.
47
-200 -100 0 100 200 300 400 500
Eh HACH-electrode (mV)
0
2
4
6
8
10
12
14
16
18
Depth
(m
)
Figure 3-5. The relationship between Eh , as analysed using the pIONeer 10 portable pH-Eh , meter and depth.
PR1 PP2 PP9 PP36 PP39 PVP1 PVP4A PVP13 PVP14 PVP201 2 3 4 5 6 7 8 9 10 11 12
Time (months)
0
1
2
3
4
5
6
O2 (
mg L
1)
10 - 14th
October 2005
24 - 28th
April 2006
18 - 23rd
May 2006
7 - 12th
July 2006
9 - 13th
October 2006
Figure 3-6. The seasonal variation of dissolved oxygen in shallow Olkiluoto groundwater analysed using the HQ10 HACH Portable LDO™ dissolved oxygen meter.
48
1 10 100
DOC (mg L 1)
1
10
100
1000
Depth
(m
)
Figure 3-7. The concentrations of dissolved organic carbon (DOC) in groundwater samples from Olkiluoto over depth.
S2
Fe20.01 0.10 1.00 10.00
(mg L 1)
1
10
100
1000
Depth
(m
)
Figure 3-8. The concentrations of dissolved ferrous iron and sulphide in groundwater samples from Olkiluoto over depth.
49
3.2 Sampling, extraction, and analysis of gas
The total amount of extractable gas per L of Olkiluoto groundwater is shown in Figure 3-9. This total gas is equal to the sum of the amounts of several gases analysed separately. The amount of each analysed gas extracted per L of Olkiluoto groundwater is produced by dividing the total extracted gas per L by the ppm values shown in Table A-5 and Table A-6, resulting in µL of gas per L of groundwater. The ppm values in Table A-5 and Table A-6 thus indicate the proportions of each gas per L of extracted gas, while the scatter plots of gas versus depth (Figure 3-14 to Figure 3-20) indicate the amounts of each gas per L of groundwater. Please note this distinction, as it is very important for understanding how the gas analysis results are reported and interpreted.
3.2.1 Dissolved gas in shallow groundwater – comments on the methods
In the sampling procedure, 120-mL glass bottles were used, typically to collect approximately 100 mL of groundwater from which gas was extracted (Table A-5). The amount of extractable gas ranged from 2.3 mL L 1 in borehole PVP4A-1 (2006-04-27) to 7.2 mL L 1 in borehole PP39 (2006-10-11), which is a relatively small amount compared with what could be extracted from deeper groundwater using the PAVE pressure vessel (Table A-6). The precision of repeated extractions is reflected by the standard deviations, which were in the 11–87% range. Although these standard deviations are high, the results must still be regarded as good, given that the gas volumes extracted were quite small. Using the PAVE vessel for deep gas samples, which contained more water and gas than did the shallow samples, increased the precision to 10% as judged from the reproducibility tests made at the Äspö HRL (Table A-12).
The oxygen present in shallow groundwater samples could have two different origins. It could be dissolved oxygen present in the groundwater at the time of sampling, or it could be oxygen that entered the sample during the extraction procedure. The transfer of a 100-mL groundwater sample from the sample bottle to the gas extractor (Figure A-1) took 20–30 min, and during this time small amounts of oxygen may have entered the sample. If the oxygen results obtained using the gas extractor are compared with data obtained using the very reliable Winkler method (Figure 3-10), it is clear that some oxygen did enter the samples during extraction. The oxygen values obtained using gas chromatography, presented in Table A-5, are thus artefacts that in most cases should not be taken into consideration. Therefore, the values in Table A-4 should be used for dissolved oxygen.
3.2.2 Dissolved gas in deep groundwater – comments on the methods
The analysis of gas sampled using the PAVE pressure vessel and reported here is a methodology under continuous development at Microbial Analytics Sweden AB. The equipment was technically improved and the sampling, extraction, and analysis procedures were adjusted in 2005. The precision and reliability of the analyses were thus better in 2006 than in 2005. The analysis procedures must be further developed and such development may include constructing a new version of the PAVE pressure vessel.
50
However, the data obtained so far are still very valuable if interpretations and conclusions take the following method comments into consideration.
The PAVE pressure vessel has a piston that separates the groundwater sample from the lower compartment filled with argon or nitrogen gas. This gas will balance the pressure of the groundwater when sampled, which reduces large shifts in pressure in the sample that would result in degassing. There have occasionally been some problems with leakage of pressure gas into the sample, which elevates the argon or nitrogen concentration of the sample. This effect is difficult to track. The best way to judge a sample result is to evaluate it in relation to several other results for samples from similar depths. A large discrepancy between a particular sample result and the average result for samples from the same depth region indicates a sampling artefact. One obvious such case is that of the OL-KR22 sample from a depth of 320 m sampled on 2006-03-01 (Table A-6). This sample contains much more nitrogen than do all other samples from below a depth of 300 m (Figure 3-11), and the amount of extracted gas exceeds that in all other samples from adjacent depths by 3 to 4 times. It is obvious that this sample was heavily contaminated with nitrogen from the lower compartment. As a result, all other gases in this sample were diluted, so the results underestimate the actual values of all other gases by approximately 3 to 4 times. The reproducibility of the PAVE sampling and analysis method was tested twice using two samples from boreholes OL-KR7 (2005-04-25) and OL-KR10 (2005-04-04) (Table A-6). The reproducibility was not very good for unknown reasons. It appears as though the PAVE samplers collect different amounts of gas, possibly due to differences in the volumes of sample and their positions in the borehole sampling equipment. This problem is being studied on an ongoing basis. As of summer 2007, however, there were still no satisfactory explanations of or solutions to this problem. More extensive discussion of the problems with sampling and analysing gas using the PAVE system, and of the representativity of the gas results obtained with it, can be found elsewhere (Gascoyne 2000; Pitkänen and Partamies 2007).
The time from sampling to extraction and analysis should preferably be as short as possible. Technical problems in the laboratory made it impossible to extract samples from April to August 2005. The current standard is to have the sample extracted within a week of the sampling day and this goal was, with some exceptions, achieved in 2006. If samples are kept for long periods in the PAVE system, there is a risk that gas diffusion processes may change the gas composition; moreover, microbial activity inside the sample may also have a significant effect on results by producing and consuming hydrogen, methane, and carbon dioxide. To minimize microbial impact on the samples, they are kept refrigerated until analysis, which reduces the rate of microbial processes. Finally, anaerobic corrosion of the stainless steel in the PAVE container may generate hydrogen, which will of course distort the hydrogen values. This may explain the unexpectedly high hydrogen values in some of the samples from boreholes OL-KR6 and OL-KR8 (Table A-6). Alternately, the anomalously high hydrogen data may be due to incomplete filling of the sample vessels, as suggested by Pitkänen and Partamies (2007).
During the extraction process, there were problems with air entering the sample, which was detected as the presence of oxygen. As deep groundwater generally contain ferrous iron and sometimes sulphide (Table A-4), oxygen should not be present, because these
51
two ions are not stable in oxygenated water. Such air leakage was considerable in 2005, and most of the leakage was tracked to the unit used to connect the sampler to the gas extractor. A new type of connector unit was developed in late 2005, and the air contamination was immediately reduced ten-fold from approximately 10% to 1% (Table A-6). The remaining 1% has been more difficult to handle. In 2007, approximately half of the samples analysed were free of detectable air, analysed as the presence of oxygen. All deep groundwater samples are back calculated to the gas concentrations the samples had before air contamination.
The sum of all analysed gases in ppm should theoretically be 1,000,000 ppm, representing 100%. The results shown in Table A-6 indicate that this was achieved mostly within the 2% range. This indicates that the gases selected and analysed for were actually the dominant gases. If a major gas had not been analysed for, the sum of all gases would be less than 100%. The sum of the analysed gases was compared with the amount of extracted gas; these two values were also comparable, as reflected in the total percentage of gas.
3.2.3 Distribution of gases in Olkiluoto groundwater
The extracted gas was composed of five major and five minor gases. The distribution of the major gases nitrogen, methane, carbon dioxide, and helium is shown in Figure 3-11; argon concentrations were very scattered (Table A-6) and are omitted from these figures. There were three distinct gas composition profiles that could be related to different depth layers. The shallow gas down to a depth of approximately 20 m was composed mainly of nitrogen and a smaller but still significant amount of carbon dioxide. Intermediate-depth gas from depths of approximately 20 to 300 m was dominated by nitrogen. At depths below 300 m, methane concentrations increased significantly, making it the dominant gas in most deep samples. The results for a depth of 320 m in borehole OL-KR-22 were distorted by a leaking PAVE cylinder piston, and the methane concentration was most likely higher in the groundwater than the results suggest. The proportions of the minor gases hydrogen and carbon monoxide were not particularly correlated with depth; the exception was the minor gas carbon monoxide, the content of which was higher in the shallow and intermediate-depth groundwater than in the deep groundwater below a depth of 300 m (Figure 3-12). All two-carbon hydrocarbons were absent from the shallow groundwater, except for that from boreholes PVP1 and PVA1 (Table A5). The hydrocarbon gases analysed for appeared in the intermediate-depth groundwater and the proportion of ethane increased significantly in the deep groundwater (Figure 3-13).
The average total amount of dissolved gas increased exponentially with depth (Figure 3-9). In the shallow groundwater, volumes of 25–70 mL of gas L 1 groundwater 1 were found. The amounts then increased up to a maximum of 1380 mL of gas L 1
groundwater 1 in the deepest groundwater sample from borehole OL-KR29, at a depth of 742 m.
The concentration of dissolved nitrogen per L of groundwater increased with depth, but its concentration range was narrow compared with those of other gases. Nitrogen concentration increased approximately 20-fold with depth, rising from 15 to 250 mL of
52
nitrogen L 1 groundwater 1 (Figure 3-14). In comparison, the noble gas helium increased approximately 1000-fold over the depth range analysed, rising from 30 to 20000 µL of gas L 1 groundwater 1. The trend was for average helium concentrations to increase exponentially over most of the depth range analysed, except in the deepest sample (Figure 3-15). Methane displayed a two-layer profile with values between 1 and 1000 µL of gas L 1 groundwater 1 down to a depth of 300 m (Figure 3-16). At this depth, there was a distinct 100-fold increase in the methane concentration to 100,000 µL of gas L 1 groundwater 1; the methane concentration then increased ten-fold by a depth of 742 m, the depth of the deepest sample analysed. Overall, the concentrations of methane were distributed over a ten-million-times range. The concentration of the last of the major gases analysed, carbon dioxide, decreased approximately ten-fold from the shallow groundwater samples to a depth of approximately 20 m (Figure 3-17). Thereafter, the average concentration decreased slightly, except in the deepest sample, which had a high concentration relative to the other deep (300–560 m) groundwater samples. The average concentration of dissolved hydrogen per L of groundwater displayed a weak increasing trend with depth, but the data points were very scattered (Figure 3-18). Carbon monoxide concentrations did not change with depth, but were, as with hydrogen, scattered (Figure 3-19). However, average ethane concentrations increased exponentially with depth (Figure 3-20).
53
10 100 1000 10000
Gas (mL L 1 groundwater 1)
0
100
200
300
400
500
600
700
800
De
pth
(m
)
Figure 3-9. The total amount of extractable dissolved gas in Olkiluoto groundwater.
0 1 2 3 4 5
Winkler O2 (mg L 1
0
2
4
6
8
10
12
GC
O2 (
mL L
1)
Figure 3-10. The relationship between oxygen concentrations in groundwater samples as analysed using gas chromatography (GC) and using Winkler titration. The dotted bands denote 95% confidence intervals.
54
Methane Carbon dioxide Helium
Nitrogen
0 200 400 600 800 1000
Major gas components (mL L 1 gas 1)
KR29 - 742KR2 - 560KR8 - 490
KR19 - 433KR39 - 345
KR6 - 328KR22 - 320KR10 - 316KR10 - 316KR10 - 316KR13 - 294KR29 - 293
KR8 - 261KR7 - 257
KR10 - 249KR7 - 197KR7 - 197
KR31 - 122KR6 - 116
KR22 - 116KR37 - 112KR22 - 102
KR6 - 102KR19 - 101
KR6 - 94KR6 - 90
KR39 - 88KR6 - 74KR6 - 73
KR33 - 71KR8 - 57KR8 - 57
KR30 - 40PVA1 - 20PVA1 - 20
PP2 - 14PP2 - 14PP9 - 15PP9 - 15
PP39 - 14PP39 - 14
PVP20 - 13PP36 - 11PP36 - 11
PVP4A - 10PVP4A - 10PVP4A - 10
PVP14 - 9PVP14 - 9
PR 1 - 6PR1 - 6
PVP13 - 6PVP13 - 6
PVP1 - 4PVP1 - 4
De
pth
(m
)
Figure 3-11. Stacked values of the major components of the extractable gas from shallow and deep Olkiluoto groundwater. Blue borehole designations indicate cases in which analysis was done twice, once with argon (1st bar) and once with nitrogen (2nd
bar) in the pressure vessel.
55
Carbon monoxide
Hydrogen
0 50 100 150 650 700
Minor gas components (µL L 1 gas 1)
KR29 - 742KR2 - 560KR8 - 490
KR19 - 433KR39 - 345
KR6 - 328KR22 - 320KR10 - 316KR10 - 316KR10 - 316KR13 - 294KR29 - 293
KR8 - 261KR7 - 257
KR10 - 249KR7 - 197KR7 - 197
KR31 - 122KR6 - 116
KR22 - 116KR37 - 112KR22 - 102
KR6 - 102KR19 - 101
KR6 - 94KR6 - 90
KR39 - 88KR6 - 74KR6 - 73
KR33 - 71KR8 - 57KR8 - 57
KR30 - 40PVA1 - 20PVA1 - 20
PP2 - 14PP2 - 14PP9 - 15PP9 - 15
PP39 - 14PP39 - 14
PVP20 - 13PP36 - 11PP36 - 11
PVP4A - 10PVP4A - 10PVP4A - 10
PVP14 - 9PVP14 - 9
PR 1 - 6PR1 - 6
PVP13 - 6PVP13 - 6
PVP1 - 4PVP1 - 4
De
pth
(m
)
Figure 3-12. Stacked values of the minor gas components carbon monoxide and hydrogen in the extractable gas from shallow and deep Olkiluoto groundwater. Blue borehole designations indicate cases in which analysis was done twice, once with argon (1st bar) and once with nitrogen (2nd bar) in the pressure vessel.
56
Ethane Ethene + Ethylene
1 10 100 1000 10000
Minor gas components (µl L 1 gas 1)
KR29 - 742KR2 - 560KR8 - 490
KR19 - 433KR39 - 345
KR6 - 328KR22 - 320KR10 - 316KR10 - 316KR10 - 316KR13 - 294KR29 - 293
KR8 - 261KR7 - 257
KR10 - 249KR7 - 197KR7 - 197
KR31 - 122KR6 - 116
KR22 - 116KR37 - 112KR22 - 102
KR6 - 102KR19 - 101
KR6 - 94KR6 - 90
KR39 - 88KR6 - 74KR6 - 73
KR33 - 71KR8 - 57KR8 - 57
KR30 - 40PVA1 - 20PVA1 - 20
PP2 - 14PP2 - 14PP9 - 15PP9 - 15
PP39 - 14PP39 - 14
PVP20 - 13PP36 - 11PP36 - 11
PVP4A - 10PVP4A - 10PVP4A - 10
PVP14 - 9PVP14 - 9
PR 1 - 6PR1 - 6
PVP13 - 6PVP13 - 6
PVP1 - 4PVP1 - 4
Depth
(m
)
Figure 3-13. Stacked values of ethane and of ethane plus ethylene in the extractable gas from shallow and deep Olkiluoto groundwater. Note that the scale is exponential due to the very large concentration range. Blue borehole designations indicate cases in which analysis was done twice, once with argon (1st bar) and once with nitrogen (2nd bar) in the pressure vessel.
57
10 100 1000 10000
Nitrogen (mL L groundwater )
0
100
200
300
400
500
600
700
800
De
pth
(m
)
Figure 3-14. The amount of extractable dissolved nitrogen gas in Olkiluoto groundwater.
10 100 1000 10000 100000
Helium (µL L 1 groundwater 1)
0
100
200
300
400
500
600
700
800
Dep
th (
m)
Figure 3-15. The amount of extractable dissolved helium gas in Olkiluoto groundwater.
58
1 10 100 1000 10000 100000 1000000
CH4 (µL L 1 groundwater 1)
0
100
200
300
400
500
600
700
800
De
pth
(m
)
Figure 3-16. The amount of extractable dissolved methane gas in Olkiluoto groundwater.
1 10 100 1000 10000 100000 1000000
CO2 (µL L 1 groundwater 1)
0
100
200
300
400
500
600
700
800
De
pth
(m
)
Figure 3-17. The amount of extractable dissolved carbon dioxide gas in Olkiluoto groundwater.
59
0.1 1.0 10.0 100.0
Hydrogen (µL L 1 groundwater 1)
0
100
200
300
400
500
600
700
800
De
pth
(m
)
Figure 3-18. The amount of extractable dissolved hydrogen gas in Olkiluoto groundwater.
0.1 1.0 10.0 100.0
CO (µL L 1 groundwater 1)
0
100
200
300
400
500
600
700
800
De
pth
(m
)
Figure 3-19. The amount of extractable dissolved carbon monoxide gas in Olkiluoto groundwater.
60
0.01 0.10 1.00 10.00 100.00 1000.00 10000.00
C2H6 (µL L 1 groundwater 1)
0
100
200
300
400
500
600
700
800
De
pth
(m
)
Figure 3-20. The amount of extractable dissolved ethane gas in Olkiluoto groundwater.
3.3 Analysis of biological parameters
Consecutive tests were performed in the 2004, 2005, and 2006 field seasons to develop and test the quality of the sampling procedures. The procedures for sterilizing the pump and samplers were analysed and the data obtained using the SOLINST tube sampler and using the pump were compared. The influence of pumping time on the results was also studied.
3.3.1 Sterilization of borehole pumps
Testing the AGW water in the ONKALO laboratory revealed TNC counts that were significantly different from zero (Table 3-1). ATP readings confirmed that there was some biomass in this water-producing unit, which was expected, as such systems are not sterile. However, by using proper cleaning procedures and a UV lamp in the water tank, the bacterial numbers in AGW systems can be kept very low. AGW water sterilized in an autoclave had TNC and CHAB readings that were not significantly different from zero. An extremely small amount of ATP was detected but, at such a low concentration level, the ATP analysis was very sensitive to even the smallest contamination. The sterilized pump came directly from the field and had been in use for several years. Even so, the sterilization testing produced very good results, with values just above zero, significantly lower than had been found in the ONKALO laboratory’s AGW system. It can thus be safely concluded that the sterilization procedures worked properly and that the sampling pump systems did not cross-contaminate the sampled boreholes or samples.
61
Table 3-1. Results of the sterilization tests of the borehole pump and the analysis of the AGW water.
Measurementa
AGW water
produced in the
Onkalo laboratory
Sterile AGW water
for washing pumps
and samplers
Sterile AGW water
after pumping and
sampling
TNC (cells mL 1) 12000 (2200)b 110 (120) 7000 (3700)
ATP (amol mL 1) 9725 (3209) 472 (214) 3351 (86)
CHAB (cells mL 1) -d 3 (6) 43 (15)
NRB (cells mL 1) - - 0.4 (0.1–1.7)c
IRB (cells mL 1) - - <0.2
MRB (cells mL 1) - - <0.2
SRB (cells mL 1) - - <0.2
AA (cells mL 1) - - <0.2
HA (cells mL 1) - - <0.2
AM (cells mL 1) - - <0.2
HM (cells mL 1) - - <0.2
MOB (cells mL 1) - - -
a TNC = total number of cells, ATP = adenosine-tri-phosphate, CHAB = cultivable heterotrophic aerobic bacteria, NRB = nitrate-reducing bacteria, IRB = iron-reducing bacteria, MRB = manganese-reducing bacteria, SRB = sulphate-reducing bacteria, AA = autotrophic acetogens, HA = heterotrophic acetogens, AM = autotrophic methanogens, HM = heterotrophic methanogens, and MOB = methane-oxidizing bacteria. b Standard deviation, n = 6. c Lower and upper 95% confidence limits. d Not analysed.
3.3.2 Comparison of sampling using the SOLINST sampler and using the borehole pump
On 13 October 2005, sampling with the SOLINST sampler (sample PVP20-S) was compared with sampling directly from the borehole pump (sample PVP20-P) in the overburden borehole PVP20. Most microbiology results, except in the case of MOB, were lower in samples made with the borehole pump than in those made with the SOLINST sampler (Table 3-2). The largest differences were found in the case of NRB and AA.
3.3.3 Test for reproducibility of groundwater microbiology over time
The largest effect of pumping PVP4A (2006-04-27) 6 h was found for the CHAB value that decreased approximately 10-fold and the value for ATP that was decreased approximately 50% (Table A-7, Table A-8). All remaining values were not significantly different, as the standard deviations of all MPN values overlapped (indicated in blue in Table A-7 and Table A-8).
3.3.4 Tests for reproducibility of the pressure vessel method
The results of the MPN analyses of groundwater samples taken simultaneously in the Forsmark section in borehole KFM06A at a depth of 357 m reproduced very well (Table 3-3). The lower and upper 95% confidence intervals for the MPN method applied to five parallel tubes equalled approximately 1/3 and 3 times the obtained values,
62
respectively (Greenberg et al. 1992). There was a small bias towards higher numbers in the PVB sampler denoted 1. The maximum discrepancy between the samples was observed for SRB and equalled a factor of two, well within the 95% confidence intervals of the MPN analysis. The TNC determinations and ATP analysis also displayed good reproducibility; this included the sampling procedure, transportation logistics, and MPN inoculation, cultivation, and analysis for each physiological group of microorganisms, i.e., TNC, CHAB, and ATP. The second test explored the reproducibility of two different analytical rounds on groundwater from two different borehole sections and of repeated sampling over time. This test also included the effects of different personnel involved and different preparations of chemicals and media. In general, groundwater from the two borehole sections had very different result profiles that reproduced well (Table 3-4). The MPNs of MRB, SRB and AM differed most between the sampling times, while the MPNs of AA and HM were highly reproducible.
Table 3-2. Comparison of groundwater from the shallow overburden borehole PVP20 as sampled using the SOLINST borehole sampler (S) and directly from the pump (P).
Measurementa PVP20-S PVP20-P PVP20S /
PVP20P
Depth (m) 12.80 12.80 -
TNC 104 (cells L 1) 32 (4.3)b 15 (7.6) 2.1
ATP 104 (amol L 1) 10.6 (0.77) 7.61 (0.39) 1.4
CHAB 104 (cells L 1) 0.22 (0.042) 0.20 (0.023) 1.1
CHAB of TNC (%) 0.68 1.33 0.5
NRB (cells mL 1) 130 (50–390)c 2 (0.9–8.6) 65.0
IRB (cells mL 1) 2.2 (0.9–5.6) 0.4 (0.1–1.7) 5.5
MRB (cells mL 1) 8.0 (3–25) 2.3 (0.9–8.6) 3.5
SRB (cells mL 1) 5 (2–15) 3 (1–12) 1.7
AA (cells mL 1) 1600 (600–5300) 170 (70–480) 9.4
HA (cells mL 1) 30 (10–130) 30 (10–120) 1.0
AM (cells mL 1) <0.2 <0.2 -
HM (cells mL 1) <0.2 <0.2 -
MOB (cells mL 1) 2.3 (0.9–8.6) 24 (10–94) 0.1
MPN of TNC (%) 0.56 0.15 3.7
a TNC = total number of cells, ATP = adenosine-tri-phosphate, CHAB = cultivable heterotrophic aerobic bacteria, IRB = iron-reducing bacteria, MRB = manganese-reducing bacteria, SRB = sulphate-reducing bacteria, AA = autotrophic acetogens, HA = heterotrophic acetogens, AM = autotrophic methanogens, HM = heterotrophic methanogens, and MOB = methane-oxidizing bacteria. b Standard deviation, n = 6. c
Lower and upper 95% confidence limits.
3.3.5 Biomass determinations
The TNC ranged from 8 103 to 2.5 106 cells mL 1 in the shallow groundwater (Figure 3-21) and the overall average was 3.9 105 cells mL 1. There were fewer cells in the deep groundwater, which had a maximum of 1.5 105 cells mL 1 at a depth of
63
450 m in groundwater from borehole OL-KR19 (Table A-10). The overall average TNC over depth in deep groundwater was 5.7 104 cells mL 1, which was almost ten times lower than the average TNC over depth in shallow groundwater. The average TNC over depth in deep groundwater did not display any trend with depth.
Table 3-3. The total numbers of cells, ATP, and most probable numbers of various physiological groups of microorganisms in groundwater sampled using two different PVB samplers, taken simultaneously on 14 March 2005 at the same location in borehole KFM06A, section 353.5 360.0 m.
SampleAnalysisa and
physiological group KFM06A:1 KFM06A:2 KFM06A:1/KFM06A:2
TNC 104 (cells mL 1) 7.2 (1.7)b 5.2 (1.7) 1.4
ATP 104 (amol mL 1) 1.51 (0.07) 0,95 (0.05) 1.6
IRB (cells mL 1) 30 (10–120)c 23 (9–86) 1.3
MRB (cells mL 1) 13 (5–39) 30 (10–130) 0.44
SRB (cells mL 1) 0.8 (0.3–2.4) 0.4 (0.1–1.7) 2.0
AA (cells mL 1) 30 (10–130) 24 (10–94) 1.3
HA (cells mL 1) 24 (10–94) 24 (10–94) 1.0
AM (cells mL 1) <0.2 0.2 (0.1–1.1) <1.0
HM (cells mL 1) 0.2 (0.1–1.1) 0.4 (0.1–1.7) 0.5
a TNC = total number of cells, ATP = adenosine-tri-phosphate, CHAB = cultivable heterotrophic aerobic bacteria, IRB = iron-reducing bacteria, MRB = manganese-reducing bacteria, SRB = sulphate-reducing bacteria, AA = autotrophic acetogens, HA = heterotrophic acetogens, AM = autotrophic methanogens, HM = heterotrophic methanogens, and MOB = methane-oxidizing bacteria. b Standard deviation, n = 6. c
Lower and upper 95% confidence limits.
The concentration of ATP in the sampled groundwater ranged over approximately four orders of magnitude if the highest ATP value of 107 amol mL 1, obtained from borehole PVP1, was included (Table A-7). This was, however, an extreme value from spring 2006, when the borehole had been completely flooded by meltwater until the day before sampling. The remaining data ranged over three orders of magnitude (Figure 3-22). There were two peaks in the ATP values over depth: the first was found in the shallow groundwater, and the second appeared between depths of 300 and 400 m. The range of the ATP values in shallow versus deep groundwater did not differ markedly.
3.3.6 Cultivable heterotrophic aerobic bacteria
The numbers of CHAB in shallow groundwater were scattered, displaying no recognizable trend over depth (Figure 3-23). The overall average number of CHAB in shallow groundwater was 3.2 103 cells mL 1. Deep groundwater had a narrower range of CHAB values than did shallow groundwater (Figure 3-24). The overall average number of CHAB in deep groundwater, i.e., 3.1 103 cells mL 1, was similar to the number in shallow groundwater. CHAB analysis was not done from the start of the sampling programme, only having been introduced in 2005.
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3.3.7 Most probable number of metabolic groups of bacteria
The stacked number profiles of MPN values in shallow groundwater (Table A-8 and Table A-9) remained similar from season to season and were borehole specific in the case of groundwater from several boreholes (Figure 3-25). The spring 2004 values are excluded from the stacked MPN figures, as most of these values refer to boreholes that were not analysed again. Groundwater from boreholes PP2 and PP9 had low MPN values in all three seasons while samples from boreholes PR1 and PP39 had the highest stacked MPN values in all shallow groundwater samples. The spring 2006 value for borehole PVP1 groundwater was much higher than in the other two seasons, due to the above-mentioned flooding event. There was no clear difference in the stacked MPN values between overburden (PVP) and shallow rock (PR, PP) boreholes.
Table 3-4. The most probable numbers of various physiological groups of microorganisms in two different boreholes sampled on 14 October 2004 and 9 February 2005.
Physiological groupa KJ0052F01:1 KJ0052F01:2 KJ0052F01:1
/
KJ0052F01:2
IRB (cells mL 1) <0.2 <0.2 1
MRB (cells mL 1) <0.2 <0.2 1
SRB (cells mL 1) 300 (100–1300)b 1600 (600–5300) 0.19
AA (cells mL 1) 1600 (600–5300) 1600 (600–5300) 1
HA (cells mL 1) 1600 (600–5300) 1600 (600–5300) 1
AM (cells mL 1) 17 (7–48) 5 (2–17) 3.4
HM (cells mL 1) 2.3 (0.9–8.6) 2.3 (0.9–8.6) 1
KJ0052F03:1 KJ0052F03:2 KJ0052F03:1
/
KJ0052F03:2
IRB (cells mL 1) <0.2 0.8 (0.3–2.4) <1
MRB (cells mL 1) 5.0 (2–17) 1.1 (0.4–2.9) 4.6
SRB (cells mL 1) 2.3 (0.9–8.6) 5 (2–17) 0.46
AA (cells mL 1) 5 (2–17) 17 (7–48) 0.30
HA (cells mL 1) 8 (3–25) 11 (4–30) 0.73
AM (cells mL 1) 2.3 (0.9–8.6) 0.4 (0.1–1.5) 8.0
HM (cells mL 1) 1.3 (0.5–3.8) <0.2 >1
a TNC = total number of cells, ATP = adenosine-tri-phosphate, CHAB = cultivable heterotrophic aerobic bacteria, IRB = iron-reducing bacteria, MRB = manganese-reducing bacteria, SRB = sulphate-reducing bacteria, AA = autotrophic acetogens, HA = heterotrophic acetogens, AM = autotrophic methanogens, HM = heterotrophic methanogens, and MOB = methane-oxidizing bacteria. b Lower and upper 95% confidence limits.
The stacked number profile of MPN values (Table A-11) in deep groundwater remained homogenous over depth for the first 120 m. Thereafter, the MPNs decreased until a depth of 294 m, where the values increased and some of the highest values were found
65
at a depth of approximately 328 m (Figure 3-26). The NRB analysis was introduced into the sampling programme in 2005, so values are missing from some of the stacked MPN bars for deep groundwater. This may partly explain why the stacked bars for boreholes KR2, KR7, KR10, KR19, and KR27 are shorter than the remaining bars, which incorporate NRB data.
The MPN of NRB over depth displayed a range over four orders of magnitude in the shallow groundwater samples. The highest NRB value was found at a depth of 328 m in borehole OL-KR6 (Table A-11). The MPN of IRB was low in most samples with a few values above 10 cells mL 1 in the shallow groundwater. The deep groundwater samples displayed a peak relative to the other MPN values of IRB, with four IRB values significantly above the detection limit at a depth of approximately 300 m. In the case of MRB, the situation was similar to that of IRB, but with several more values above 10 and 100 cells mL 1 in shallow and intermediate–depth groundwater, respectively. As for IRB, four of the MRB values peaked at a depth of approximately 300 m. The MPN of SRB followed the trends of IRB and MRB with scattered values in shallow groundwater up to approximately 1000 cells mL 1 and four values above the detection limit at a depth of approximately 300 m.
The MPN results for AA and HA displayed similar patterns. The data were scattered over a range of four orders of magnitude in the shallow groundwater. At a depth of approximately 300 m, there was a peak in the MPN values as was also observed for NRB, IRB, MRB, and SRB. There were some detectable AM and HM in shallow groundwater and there were very few detectable methanogens at depth. As in all other MPN analyses, peak values were observed at a depth of approximately 300 m.
The MPN analysis of MOB was only performed on shallow groundwater. This metabolic group of microorganisms was present in most samples analysed, with a peak observed in borehole PVB3B water in spring 2004. This borehole was turbid as a result of dispersed bentonite from the packer of the casing, which may have influenced the results.
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3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0
10Log(TNC) (cells mL 1)
0
100
200
300
400
500
De
pth
(m
)
Figure 3-21. The distribution of total number of cells (TNC) versus depth in Olkiluoto groundwater.
3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0
10Log(ATP) (amol mL 1)
0
100
200
300
400
500
Depth
(m
)
Figure 3-22. The concentrations of ATP distributed over depth in Olkiluoto groundwater.
67
0.0 1.0 2.0 3.0 4.0 5.0
10Log(CHAB) (cells mL 1)
0
2
4
6
8
10
12
14
16
Depth
(m
)
Figure 3-23. The distribution of cultivable heterotrophic aerobic cells (CHAB) versus depth in shallow Olkiluoto groundwater.
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0
10Log(CHAB) (cells mL 1)
0
100
200
300
400
500
De
pth
(m
)
Figure 3-24. The distribution of cultivable heterotrophic aerobic cells (CHAB) versus depth in Olkiluoto groundwater.
68
MOB HM AM HA AA SRB MRB IRB NRB
0 2 4 6 8 10 12 14 16 18 20
Stacked 10log(MPN) (cells mL 1)
PVP1, 3.9 m
2005-10-11
2006-04-27
2006-10-12
PVP13, 5.6 m
2005-10-12
2006-04-26
2006-10-12
PVP14, 9.0 m
2005-10-13
2006-04-26
2006-10-10
PVP4A, 10.2 m
2005-10-12
2006-04-27
2006-04-27
2006-10-10
PVP20, 12.8 m
2005-10-13
2005-10-13
2006-10-10
PR1, 6.0 m
2005-10-10
2006-04-25
2006-10-11
PP36, 12.1 m
2005-10-10
2006-04-25
2006-10-09
PP39, 14.1 m
2005-10-11
2006-04-24
2006-10-11
PP2, 14.7 m
2005-10-12
2006-04-24
2006-10-11
PP9, 14.7 m
2005-10-13
2006-04-27
2006-10-09
Figure 3-25. Stacked values of most probable numbers of various physiological groups of microorganisms in shallow Olkiluoto groundwater. NRB = nitrate-reducing bacteria, IRB = iron-reducing bacteria, MRB = manganese-reducing bacteria, SRB = sulphate-reducing bacteria, AA = autotrophic acetogens, HA = heterotrophic acetogens, AM = autotrophic methanogens, HM = heterotrophic methanogens, and MOB = methane-oxidizing bacteria.
69
HM AM HA AA SRB MRB IRB NRB
0 2 4 6 8 10 12 14 16 18 20
Stacked 10log(MPN) (cells mL 1)
KR32, 34.6
KR8, 57.3
KR33, 70.6
KR6, 73.7
KR39, 88.2
KR6, 94.1
KR6, 101.8
KR10, 106.0
KR37, 111.6
KR31, 122.4
KR27, 193.5
KR7, 249.4
KR8, 260.7
KR13, 294.0
KR13, 294.0
KR2, 306.2
KR10, 316.0
KR6, 328.4
KR39, 344.8
KR27, 391.7
KR19, 449.6
Bo
reh
ole
, d
ep
th (
m)
Figure 3-26. Stacked values of most probable numbers of various physiological groups of microorganisms in deep Olkiluoto groundwater. NRB = nitrate-reducing bacteria, IRB = iron-reducing bacteria, MRB = manganese-reducing bacteria, SRB = sulphate-reducing bacteria, AA = autotrophic acetogens, HA = heterotrophic acetogens, AM = autotrophic methanogens, and HM = heterotrophic methanogens.
0 1 2 3 4 5
10Log(NRB) (cells mL 1)
0
100
200
300
400
500
Depth
(m
)
Figure 3-27. The distribution of nitrate-reducing bacteria (NRB) versus depth in Olkiluoto groundwater.
70
0 1 2 3 4 5
10Log(IRB) (cells mL 1)
0
100
200
300
400
500
Depth
(m
)
Figure 3-28. The distribution of iron-reducing bacteria (IRB) versus depth in Olkiluoto groundwater.
0 1 2 3 4 5
10Log(MRB) (cells mL 1)
0
100
200
300
400
500
De
pth
(m
)
Figure 3-29. The distribution of manganese-reducing bacteria (MRB) versus depth in Olkiluoto groundwater.
71
0 1 2 3 4 5
10Log(SRB) (cells mL 1)
0
100
200
300
400
500
Depth
(m
)
Figure 3-30. The distribution of sulphate-reducing bacteria (SRB) versus depth in Olkiluoto groundwater.
0 1 2 3 4 5
10Log(AA) (cells mL 1)
0
100
200
300
400
500
Depth
(m
)
Figure 3-31. The distribution of autotrophic acetogens (AA) versus depth in Olkiluoto groundwater.
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0 1 2 3 4 5
10Log(HA) (cells mL 1)
0
100
200
300
400
500
Depth
(m
)
Figure 3-32. The distribution of heterotrophic acetogens (HA) versus depth in Olkiluoto groundwater.
0 1 2 3 4 5
10Log(AM) (cells mL 1)
0
100
200
300
400
500
De
pth
(m
)
Figure 3-33. The distribution of autotrophic methanogens (AM) versus depth in Olkiluoto groundwater.
73
0 1 2 3 4 5
10Log(HM) (cells mL 1)
0
100
200
300
400
500
Depth
(m
)
Figure 3-34. The distribution of heterotrophic methanogens (HM) versus depth in Olkiluoto groundwater.
0 1 2 3 4 5
10Log(MOB) (cells mL 1)
0
2
4
6
8
10
12
14
16
Depth
(m
)
Figure 3-35. The distribution of methane-oxidizing bacteria (MOB) versus depth in shallow Olkiluoto groundwater.
74
75
4 DISCUSSION
The microbiology of shallow and deep groundwater in Olkiluoto was analysed by Microbial Analytics Sweden AB and Göteborg University for almost three years from 2004 to 2006, and previously by Göteborg University between 1996 and 2000 (Table 1-1). The extensive sampling and analysis programme from 2004 to 2006 has produced a very substantial database, including 60 analytical datasets on the microbiology of Olkiluoto groundwater. This database comprises 39 complete analytical datasets assembled on four sampling campaigns from measurements from 16 shallow observation tubes and boreholes ranging in depth from 4 to 24.5 m. The database also contains 21 analytical datasets covering 13 deep boreholes ranging in depth from 35 to 450 m. In addition, the database contains 33 completed analyses of gas covering 14 deep boreholes ranging in depth from 40 to 742 m. Most of these analyses were completed before the onset of ONKALO construction, and the remaining samples were collected before ONKALO construction had extended below a depth of 100 m; therefore, this dataset captures the undisturbed conditions before the building of ONKALO. Future sampling and analysis will reveal whether ONKALO construction has influenced biogeochemical conditions in the surrounding groundwater. If such an influence is found, it will, hopefully, be possible to model the underlying reasons for this influence and to predict its continuation.
The following discussion first deals with the selection of sampling points, procedures, and methods and the quality-control tests done. Then the research results will be evaluated and interpreted, after which a descriptive model of the microbiological processes deemed most important will be presented. Finally, the outcome of the reported research will be discussed with reference to ONKALO.
4.1 Sampling procedures for shallow groundwater
Four microbiology and gas sampling campaigns have been performed in the shallow groundwater of Olkiluoto: the first was in May 2004, the second was completed in October 2005, and the last two were completed in April and October 2006, respectively. The methods and techniques used generally worked well. Several activities were conducted specifically to test and possibly improve the methods. The sampling and analysis procedures were adjusted as deemed necessary to improve the quality and reproducibility of results. The strategies underlying the selection of boreholes and methods and the outcome of the method tests are discussed next.
4.1.1 Selection of sampled shallow groundwater boreholes
The boreholes selected for the 2004 and the 2005–2006 sampling campaigns differ. Four boreholes were used in both the 2004 and 2005–2006 sampling campaigns (PVP1A, PVP4A, PR1, and PP2, but six boreholes were abandoned after 2004 and replaced with new ones in fall 2005. The selection of boreholes was changed for several reasons. First, one borehole sampled in 2004 collapsed (PP8) and two became contaminated with dispersed bentonite from the packer of the casing (PVP3A and PVP3B). Two were found to have closely related chemistry and microbiology profiles
76
(PVP4A and PVP4B), so one of them was abandoned (PVP4B). Finally, two of the 2004 boreholes became inaccessible after 2004 (PP3 and PP7), due to the ongoing construction of ONKALO and new buildings. The new selection of boreholes made for the 2005 field campaign was retained for the remaining three sampling campaigns. Five overburden and five shallow rock boreholes were selected, to capture the largest possible distribution of the content of dissolved solids. These particular boreholes were also selected to ensure that the ONKALO construction would not interfere with repeated sampling activities in the future (Figure 2-1). Such repeated field activities should be able to return datasets that represent a wide selection of Olkiluoto shallow groundwater environments over time. It will be possible to continue monitoring these boreholes in the future and evaluate whether the construction of ONKALO has influenced the shallow groundwater microbiology and gas content.
4.1.2 Sampling of shallow groundwater
Sampling of shallow boreholes for microbiology differed in many respects from the sampling of deep boreholes. The most obvious difference is that specific fractures in the deep boreholes were isolated with packers and pumped out for several weeks before sampling. The shallow boreholes were not supplied with packers and could only be pumped out for a few hours; instead, they were open and in contact with the air. It is a general practice to pump out a borehole before sampling. This ensures that standing groundwater containing dissolved air, precipitation, and dust from the ground surface is removed before a sample is taken. Therefore, groundwater was sampled after 1.5 h or more of pumping. The boreholes extended to various depths, usually several metres, beneath the surface of the groundwater table. The groundwater flowing into a specific borehole during pumping may therefore be of several different origins. For example, one component may originate from very shallow groundwater layers, while a second one may originate from a deeper inflow location. All this is related to the preferential flow paths of the aquifers in the sampled ground. For consistency, the total depth of a shallow borehole is used here when discussing relationships between measured parameters and depth.
The stability of the chemical conditions during prolonged pumping was tested in borehole PVP4A in spring 2006. Samples were collected for physical, chemical, and microbiological analyses at times separated by 6 h of pumping. The volume of the groundwater pumped out of the borehole between the sampling occasions was approximately 1440 L. When compared as ratios between the first and second sampling occasions, the results indicated very small differences in most of the analysed parameters (indicated in blue in Table A-4). The only parameter that changed significantly was the ferrous iron content, which decreased from 3.05 mg L 1 to 1.64 mg L 1. The groundwater chemistry conditions appeared to be very stable in this borehole. Although this test was only done once for one borehole, it can yet be concluded that the chemical conditions in the shallow boreholes were borehole specific and reproducible over the seasons. A comparison of data from each borehole over the whole sampling period supports this conclusion. For example, comparing the amounts of total dissolved solids (TDS), which represents the sum of all dissolved species analysed for separately as well, indicates good reproducibility per borehole over time. It can be concluded that
77
the applied pumping methodology rendered reproducible results with respect to most physical and chemical parameters.
The deep boreholes were sampled using the PAVE system, which has up to three closed containers that collect pressurized samples. This procedure was initially used for the shallow boreholes, using the SOLINST borehole sampler (using a borehole sampler is optional, as one can collect samples directly from the pump tubing). However, it had to be demonstrated that the pumps could indeed be sterilized between pumping out the different boreholes. It was also deemed important to test the difference between pumped samples and samples collected using the SOLINST sampler, as discussed below.
4.1.3 The oxygen blockage packer test
The shallow boreholes were open and in contact with air. It was therefore deemed possible that air might have mixed with the sampled water during pumping, as oxygen was found in most samples in the May 2004 investigation. A packer system was tested in the October 2005 investigation to determine whether the pumping was enough to keep air from contaminating the samples. The results indicated that oxygen did not mix with the water, irrespective of whether or not the packer was used (Pedersen 2007). It was concluded that a packer is not needed to hinder oxygen in air from mixing with the sampled groundwater.
4.1.4 Sterilization of borehole pumps
The use of chlorine dioxide (FreeBact 20; XINIX) for pump sterilization worked very well (Table 3-1). The MPN of microorganisms obtained after sterilization was below the detection limit of 0.2 cells mL 1 for all analyses except NRB, which produced a number just above the detection limit. It can thus be concluded that the sampling pump systems did not cross-contaminate the sampled boreholes.
4.1.5 Comparison of sampling using the SOLINST sampler and using the borehole pump
In the case of borehole PVP20, the microbiology results obtained from samples made with the borehole pump were generally equal to or lower than those obtained from samples made with the SOLINST sampler, except in the case of MOB (Table 3-2). The largest difference was found in the case of NRB and AA. When sampling with the SOLINST sampler, it was observed that the groundwater became slightly more turbid after retrieving the borehole pump and lowering the SOLINST sampler. The increase in turbidity was only observed in overburden boreholes. This difference most likely resulted from hydrodynamic disturbance caused by raising and lowering the pump and sampler in the boreholes. Sediment and colloids that became suspended in groundwater due to disturbance during sampling would certainly harbour attached microorganisms, which would subsequently increase the biomass estimates in turbid as compared with non-turbid groundwater. The greater ATP biomass value in borehole PVP20S than in borehole PVP20P may be attributed to the fact that the ATP analysis method extracted ATP from both planktonic and biofilm microorganisms on particles in the turbid water. In the case of total counts, the situation was similar, with higher numbers evident in the
78
SOLINST sample than in the pump sample. Groundwater from borehole PVP20S was also associated with the detection of the greatest number of metabolic groups. This would again be due to higher numbers of microorganisms in the SOLINST samples caused by the presence of more sediment particles with attached microorganisms.
In choosing whether to use the SOLINST or pump method for sampling, it can be argued that the SOLINST method gives higher microorganism numbers related to particles in the groundwater. These are of course true results, in that these organisms were indeed present and possibly active in the sampled borehole. At the same time, the SOLINST method introduced uncertainty into the results, as it is impossible to reproducibly cause turbidity in the boreholes. For comparative purposes, it was deemed better to sample from the borehole pump in the field activities in 2006 and in the future. Otherwise, results from overburden borehole samples may overestimate the planktonic cell numbers compared with results from bedrock borehole samples that were free of turbidity caused by sampling activities in the borehole.
It has been demonstrated that attached microorganisms in deep groundwater environments significantly outnumber planktonic microorganisms (Pedersen and Ekendahl 1992a, b; Pedersen 2001). However, it can be assumed that the planktonic numbers and diversity reflect the numbers and diversity of attached microorganisms. High activity and growth of attached microorganisms will result in an increased number of microorganisms that slough off due to hydrodynamic forces or that migrate from growing colonies. The investigations of shallow groundwater were intended to build our understanding of seasonal variation and of the future impact of ONKALO on groundwater biogeochemistry. It was thus deemed more important to use reproducible methods than methods that may yield the highest possible numbers as a result of manipulating the particle content of the analysed groundwater. The two first field activities reported here, those of May 2004 and October 2005, formed a solid method and technology basis for the design of future field activities. The only major change made in the 2006 investigations was that samples were taken directly from the pumps for microbiology analysis. The SOLINST sampler was used one more time, to obtain samples for the analysis of groundwater gas content and composition, but only to compare the results obtained using SOLINST with those using a glass bottle sampling method, as discussed below (4.4.3).
4.2 Sampling procedures for deep groundwater microbiology
The reproducibility test for groundwater samples taken simultaneously in borehole KFM06A from the 353.5 360.0-m depth section in Forsmark using the PVB sampling system indicated very good reproducibility (Table 3-3). The difference between the two samples was generally represented by a difference of only a single tube in the MPN analyses. The 95% confidence interval for MPN analyses using five parallel tubes equalled approximately 1/3 and 3 times the obtained value (Greenberg et al. 1992). The maximum difference between the two samples was 1.6, so the two samples were not significantly different. In comparison, there were significant differences between the groundwater samples analysed in the different Äspö HRL boreholes (Table 3-4). Groundwater from borehole KJ0052F01 yielded significantly higher values in all analyses than did groundwater from borehole KJ0052F03. The results from the Äspö
79
HRL had previously indicated the heterogeneity of microbial populations in fractured rock. Boreholes KJ0052F01 and KJ0052F03 are only separated by a maximum of 50 m of rock (Pedersen 2000b); however, they intersect fractures with different hydrogeochemistry characteristics, resulting in groundwaters with very different microbiological profiles. In conclusion, the reproducibility test demonstrated the analytical protocols for microbiological analyses to be reproducible between samples.
The reproducibility of the sampling and analysis methods used for groundwater from borehole sections over a 3.5-month interval was also tested. This test required groundwater samples from borehole sections that did not change their microbiology profiles over time. The Äspö HRL MICROBE site was suitable for such a test, because there is a record of groundwater analysis results extending back to the May 1999 drilling (Pedersen 2000b). For the reproducibility testing, six consecutive samplings for microbiological analysis were performed over 20 months (Pedersen 2005b), including the two results presented here. It was found that the results per borehole section were reproducible over time, as shown in Table 3-4. With a few exceptions, the results did not differ significantly between the sampling times. The two different groundwater samples tested were, however, significantly different. Taking all these results into consideration, it must be concluded that testing over time indicated extremely good reproducibility. The MPN procedures and the analyses appeared to be very robust and reproducible both between samples (as shown in Table 3-3) and over sampling times and between boreholes as shown in Table 3-4.
The stability of the microbiological analyses over prolonged pumping was tested in borehole PVP4A in spring 2006, as was done for physical and chemical parameters as described above (section 4.1.2). Samples were collected for microbiology analysis at times separated by 6 h of pumping. The volume of the groundwater pumped out of the borehole between the sampling occasions was approximately 1440 L. When compared as ratios between the first and the second sampling occasions, the results indicated varying differences in the analysed parameters (indicated in blue in Table A-7). The CHAB results displayed the largest difference, decreasing 13.5-fold between the first and second sampling occasion. The MPN of HA also decreased significantly, by a factor of ten. These differences may, however, be due to a change in the microbiological composition of the groundwater, rather than to any variability in the methods used. The pumping may have had a filtering effect on the unattached cells, which would result in decreasing values, as was the case for all analysed parameters except AA. The ATP value also decreased, which suggests that the volume of active biomass actually was reduced somewhat. Still, the variability of the PVP4A data appeared reasonably coherent compared with the variability between boreholes (Figure 3-25).
4.3 Evaluating the analysis methods
An array of analytical methods was used in this research to explore the microbiology of the Olkiluoto site groundwater. Correctly interpreting the results of the performed analyses depends on a basic understanding of the possible limitations of the methods and of the overlaps and gaps in the dataset. Some methods, like those used to measure temperature, produce reliable data with clear meaning in most situations, while
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interpreting and understanding the results of other methods, such as MPN analysis, require a thorough knowledge of the underlying rationale of the procedures and of their limitations, sensitivity, and precision. In the following sections, the methods used will be evaluated in the context of the results obtained.
4.3.1 Analysis of physical parameters
The temperature (Table A-1), pH (Figure 3-1), and conductivity (Figure 3-2) of Olkiluoto groundwater have long been analysed, and there should be few problems with the results of these analyses. In contrast, dissolved oxygen in shallow groundwater has not been analysed on an ongoing basis, and the dataset presented here for oxygen is thus important for the Olkiluoto site. Three methods were used to measure dissolved oxygen: electrochemical analysis in the field with electrodes (Figure 3-3), chemical analysis in the laboratory with titration (Figure 3-3), and gas chromatography in the laboratory (Figure 3-10). The results of the electrochemical analysis agreed well with those of titration (Figure 3-4). The titration method was more reliable at low oxygen concentrations below approximately 0.5 mg O2 mL 1, because electrodes are difficult to calibrate for concentrations close to zero. The gas chromatography method did not work well, due to problems with air intrusion in the glass sample vessels during extraction. The electrochemical method has the advantage of being easy to perform by personnel in the field, while Winkler titration requires a chemist in the laboratory to titrate the samples. When large datasets are required for routine data collection, as is the case with seasonal variation in many boreholes (Figure 3-6), the electrochemical method is the most cost effective.
4.3.2 Chemical parameters
Chemical analysis is routine work in Olkiluoto and has recently been reviewed (Pitkänen et al. 2007), and so will not be evaluated again here. In general, Pitkänen et al. (2007) concludes that much work and experience have been gained over time regarding how to obtain high-quality data. This experience was available and used when the hydrochemical data used in the present report were collected. The concentrations of DOC, ferrous iron, sulphide, and sulphate in groundwater are of special interest for microbiological investigations, because these chemical species play significant roles in microbial processes (Figure 1-8).
Several groundwater gases can be produced and consumed by microorganisms. Methanogens produce methane from hydrogen and carbon dioxide and acetogens can produce acetate from hydrogen and carbon dioxide. Microbial metabolism of organic carbon generates carbon dioxide and some microorganisms metabolize methane to carbon dioxide. Consequently, research into microbial processes in groundwater necessitates the development of analytical methods for detecting gases in environmental and laboratory samples. Dissolved groundwater gases in deep Olkiluoto groundwater have been sampled using the PAVE system and analysed since 1997. Previously, gas had been sampled using glass and aluminium vessels (Gascoyne 2005). Seventy-one deep groundwater samples taken using PAVE between 1997 to 2005, together with associated analyses, have been evaluated in detail elsewhere (Pitkänen and Partamies
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2007), so that evaluation is not repeated here. Briefly stated, the authors report that the amount of gas is notable at depth and that the major gases are nitrogen and methane. The gas composition closely follows the stratification of redox conditions, a significant shift observable at a depth of approximately 300 m. Furthermore, they conclude that gas formation is of substantial importance for repository safety and that is essential to obtain more data regarding hydrogen, methane, hydrocarbons, dissolved inorganic carbon, fracture calcites, and microorganisms. Further studies should examine the interface between the methanic and sulphidic systems below and above a depth of 300 m, respectively. The work presented in the present report is a first step in the direction identified by Pitkänen and Partamies (2007).
In the present research, two methods have been used to collect gas in shallow and deep groundwater for subsequent extraction and analysis, as described in the Appendix (see page 149). Evacuated glass bottles were used for shallow groundwater analysis and the PAVE system was used for deep groundwater sampling and analysis. As a rule of thumb, the larger the water sample and the more the gas, the better the precision and detection obtained. Samples of deep groundwater from Olkiluoto have usually contained large volumes of gas, while shallow groundwater has contained less dissolved gas (Figure 3-9). The glass bottle sampling method still worked well because the uncertainty of using single samples and extractions was compensated for by using triplicates of independent samples, extractions, and analyses. In future research, the glass bottle methods used for shallow groundwater can be improved by using larger bottles. An attempt to use the SOLINST sampler for gas did not turn out well, due to contamination of the sample with the nitrogen used to open and close the sampler (2.1.5). A similar problem was occasionally encountered with the PAVE sampling equipment, where the gas in the pressure compartment, i.e., nitrogen or argon, contaminated the samples (3.2.2). Finally, there was a problem with the air contamination of samples due to poor (i.e., not vacuum-tight) seals on the original device used to connect the PAVE pressure vessel and the extraction equipment. This problem was later solved by constructing a new device with vacuum-tight seals.
4.3.3 Microbiological parameters
The microbial biomass in granitic rock aquifers of the Fennoscandian Shield has been analysed in terms of total and viable numbers for almost two decades (Pedersen 2001); total number estimates have ranged from 103 to 106 cells mL 1, while viable number estimates have ranged from 100 to 105 cells mL 1. Between 0.00084 and 14.8% of the total numbers have been cultivated and detected using most probable number (MPN) methods (Haveman and Pedersen 2002a). Although low viable numbers have been detected relative to the total numbers observed, in vitro radiographic and radiotracer estimates have suggested that the absolute majority of the total cells observed using microscopy was viable (Pedersen and Ekendahl 1990, 1992a, b). Consequently, there was a significant gap between estimates of potentially viable total numbers and evidently viable cultivable numbers. Hence, a method for estimating the total amount of viable biomass in groundwater was sought. A recent investigation found that analysing the ATP concentration in shallow and deep Fennoscandian groundwater (including Olkiluoto groundwater) using a commercial assay supplied needed information about
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the metabolic state and biovolume of the bacteria present (Eydal and Pedersen 2007). The assay appeared robust and reliable and had a detection range that took in all samples analysed. The analysed ATP concentrations were found to correlate both with the microscopic counts and with the volume and metabolic status of the investigated pure culture and groundwater cells. The results suggested that bacterial populations in deep groundwater vary significantly in size, and that metabolic activity is a function of prevailing environmental conditions.
ATP was first analysed in Olkiluoto groundwater in fall 2004. When ATP was analysed concomitantly with TNC, a good correlation was obtained (Figure 4-1). As ATP is an energy transport compound present in all living cells (confer Figure 1-11), measuring its concentration indicates the biovolume and metabolic state of the biomass in any system. A groundwater containing many active cells should thus have a higher ATP concentration than one containing few such cells. If the cells are large, this will increase the content of ATP per cell. It has been demonstrated that the ATP/TNC ratio is a good indicator of the metabolic activity of cells in groundwater (Eydal and Pedersen 2007). The average ATP/TNC ratio for 109 shallow Olkiluoto groundwater determinations was 1.02, and for 166 deep Fennoscandian shield groundwater determinations was 0.43. Any ratio higher than these two in shallow or deep groundwater, respectively, thus suggests that the microbial population analysed is more active than average, while a lower-than-average ratio suggests that the population analysed is less active than average.
The MPN methods for enumerating microorganisms in deep groundwater was first used for analysing methanogens and acetogens in Äspö HRL groundwater (Kotelnikova and Pedersen 1998). Later, the methods was further developed, and it has been used to analyse more types of microorganisms in deep groundwater from Finland (Haveman et al. 1999; Haveman and Pedersen 2002a), including from Olkiluoto (Table 1-1), and from the natural nuclear reactors in Bangombé, Gabon, Africa (Haveman and Pedersen 2002b). The methods have been modified and changed over time. As the numbers of samples and types of organisms analysed have increased, the manual preparation of single tubes, as used for analysing methanogens and acetogens in Äspö HRL groundwater (Kotelnikova and Pedersen 1998), has had to give way to methods that could handle the approximately three thousand MPN tubes (2.4.4) needed during each of the Olkiluote field investigations of shallow groundwater.
The expression “the great plate count anomaly” was coined by Staley and Konopka (1985) to describe the difference in orders of magnitude between the numbers of cells from natural environments that form colonies on agar media (CHAB) and the numbers countable by means of microscopic examination (TNC). In general, only 0.01–0.1% of bacterial cells sampled from various environmental aquatic systems produce colonies when using standard plating techniques so, as expected from the relevant literature results, there were no correlations between TNC and CHAB data for Olkiluoto groundwater (Figure 4-2). The anaerobic cultivation methods presented here represent the culmination of almost 10 years of development, testing, and adaptation for deep groundwater. The success and usefulness of these methods are reflected in the maximum MPN cultivability of 30% of the TNC in the sample from the borehole OL-KR6 422–425 m section and the 0.01–30.25% MPN cultivability range in all groundwater samples (Table A-10). The use of multiple, liquid anaerobic media (Table 2-3) has obviously overcome much of the discrepancy found between TNC and
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cultivations that use agar media only. However, it should be understood that there may still be microorganisms in the groundwater not cultivable using the applied methods. One example is that of anaerobic methane-oxidizing bacteria (ANME), which as of the time of writing have escaped successful cultivation by the world microbiology community. ANME have been observed in environmental samples but their successful cultivation in the laboratory has yet not been described in the literature.
The CHAB and MOB were analysed under aerobic conditions, unlike all other cultivation methods, which were performed under anaerobic conditions. Many bacteria are known to be facultative anaerobes, i.e., they can switch from aerobic respiration using oxygen to anaerobic respiration using nitrate and often also ferric iron and manganese(IV) as alternative electron acceptors (Madigan and Martinko 2006). Microorganisms in groundwater must be adapted to anoxic conditions but, if oxygen should appear, it is advantageous for the microbe to be able to switch to oxygen respiration. Indigenous groundwater microorganisms should consequently be detectable as both CHAB and NRB, while contaminants from the surface should have a smaller tendency to do so. Comparing the CHAB data to the NRB data indicates a reasonably good correlation (Figure 4-3), suggesting that the microorganisms analysed as CHAB were generally indigenous.
Some of the metabolic groups analysed using MPN may overlap in numbers. At the onset of this investigation it was unclear whether AA and HA would differ in numbers. The acetogens are known to be a diverse group of organisms that may switch between different metabolic states (Drake et al. 2002). Comparing the MPN numbers of AA and HA indicates that they correlated well, although there was a clear tendency for AA to outnumber HA in several samples (Figure 4-4). Similarly, it is known that one organism can have the abilities to reduce both iron and manganese (DiChristina and DeLong 1993). Comparing the IRB with the MRB numbers indicates that MRB tended to outnumber IRB in several samples (Figure 4-5). More research will be needed before we have a full understanding of the potential differences between AA and HA, and between IRB and MRB numbers.
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3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0
10Log(TNC) (cells mL-1)
3.0
3.5
4.0
4.5
5.0
5.5
6.0
6.5
7.0
10Lo
g(A
TP
) (
am
ol m
L-1
)
ATP = 0.6309+0.7795*x; 0.95 Conf.Int.
Figure 4-1. The relationship between the total number of cells (TNC) and the concentration of ATP in Olkiluoto groundwater. Dashed lines denote the 95% confidence interval.
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0
10Log(CHAB) (cells mL 1)
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1
2
3
4
5
6
7
10Log(T
NC
) (c
ells
mL
1)
Figure 4-2. The relationship between the total number of cells (TNC) and the numbers of cultivable aerobic heterotrophic bacteria (CHAB) in Olkiluoto groundwater.
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0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0
10Log(CHAB) (cells mL 1)
0
1
2
3
4
5
10L
og
(NR
B)
(ce
lls m
L1)
NRB = 0.8179*CHAB 0.1803
Figure 4-3. The relationship between the numbers of cultivable aerobic heterotrophic bacteria (CHAB) and the most probable numbers of nitrate-reducing bacteria (NRB) in Olkiluoto groundwater. Dashed lines denote the 95% confidence interval.
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0
10Log(AA) (cells mL 1)
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0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
10Log(H
A)
(cells
mL
1)
Figure 4-4. The relationship between AA and HA in Olkiluoto groundwater samples. The line denotes a one-to-one relationship.
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0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0
10Log(MRB) (cells mL 1)
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1.0
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2.0
2.5
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3.5
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10Log(I
RB
) (c
ells
mL
1)
Figure 4-5. The relationship between IRB and MRB in Olkiluoto groundwater samples. The line denotes a one-to-one relationship.
4.4 Geochemical conditions of the investigated aquifers
Establishing baseline conditions in Olkiluoto before the start of excavations for ONKALO was deemed very important (Andersson et al. 2007b; Pitkänen et al. 2007). These baseline conditions now include the microbiological data from 2004 to 2006 cited in the present report as well as microbiological data from the earlier site investigations (Table 1-1). Seasonal variations may have an effect on microbial processes that will be significant in shallow groundwater, but will rapidly diminish with increasing depth. The possible anomalous mixing of groundwater at a depth of approximately 300 m due to the long-term pumping of open boreholes has been established (Pitkänen et al. 2007). It was speculated that shallow groundwater may flow through open boreholes to the subhorizontal hydrogeological zone HZ20, which would act as an outflow route for groundwater in Olkiluoto (Figure 7-7, Andersson et al. 2007b). This type of mixing may expose microorganisms to anomalous conditions at a depth of approximately 300 m.
What geochemical parameters are then important for microbiology? Temperature influences the reaction rates of most chemical processes. The rate of microbial processes thus increases with increasing temperature. The pH is less important for microorganisms, as they generally have large ranges of several pH units within which they can be active. Conductivity reflects the amount of dissolved solids and, as with pH, microorganisms generally have a relatively large range of dissolved solids concentrations within which they can be active (see Figure 1-3 for an example of the temperature, pH, and NaCl ranges for a deep groundwater microorganism). The presence and concentration of oxygen has a profound influence on microbial diversity
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and activity. Many deep groundwater microorganisms are killed by oxygen, but those that can use oxygen as an electron acceptor in their metabolisms use it more efficiently than the electron acceptors they utilize under anaerobic conditions (Figure 1-8). The presence and concentrations of oxidized and reduced electron acceptors and donors, presented in Figure 1-8, are important to understand. For example, DOC can be used as a source of energy and carbon by heterotrophic microorganisms, while autotrophic microorganisms produce DOC, for example, acetate production by AA. Finally, Eh is an important parameter. Microbial processes tend to lower the Eh of any system in which they are active by consuming oxygen and producing reduced electron acceptors such as ferrous iron and sulphide. Next, the conditions in the investigated groundwater, with respect to the above parameters, are discussed.
4.4.1 Physical parameters
The average shallow groundwater temperature was 7.1 C in spring and 9.1 C in fall (Figure 4-6). The difference in temperature between seasons was most pronounced at depths of less than 10 m, where the water temperatures in shallow boreholes such as PVP1 and PR1 differed by up to 6 C. The pH range was almost three units, 4.7–7.7, in the shallow groundwater, and stabilized above 7 at depth (Figure 3-1). The effect of the different pH values on microbial processes will be indirect, as pH influences many geochemical parameters such as mineral dissolution and precipitation, carbon dioxide solubility, and various solid–aqueous phase equilibria. Microbial processes produce carbon dioxide from the respiration of DOC. Less carbon dioxide will precipitate as calcite at low pH in dilute shallow groundwater than in deep groundwater where the pH and dissolved solids concentration are higher. This is reflected in the carbon dioxide concentrations, which were much higher in shallow than in deep groundwater. The input of biodegradable organic carbon from surface plant and animal ecosystems can be assumed to be higher in shallow than in deep groundwater; thus, the production rate of carbon dioxide by microorganisms will be higher in shallow than in deep groundwater.
The concentration of oxygen decreased rapidly with depth in the shallow groundwater (Figure 3-3). Many microorganisms prefer oxygen for their metabolisms, so oxygen is the first electron acceptor to disappear in groundwater. Thereafter, the microorganisms use other electron acceptors that, when reduced, will force the Eh towards more negative values. In shallow groundwater, the measured Eh was lower at low oxygen concentrations (Figure 4-7). This correlation supports the general model of microorganisms as important moderators of Eh in groundwater, just as they are in many other systems, for example, in aquatic sediments (Madigan and Martinko 2006).
The variation in temperature over the seasons should correlate with the input of organic material to shallow groundwater. In winter and fall, the input will be low as will be the temperature. This will decrease the rate of microbial processes with a concomitant reduction in the consumption of oxygen. In summer and early fall, the input of organic material will increase as will the temperature. Microbial processes will speed up and the consumption of oxygen should increase. Such seasonal variation in oxygen was also noted over a one-year cycle (Figure 3-6). In summer 2006, only two of a total of 10 boreholes had significant concentrations of oxygen. One of these was the shallow borehole PVP1, where the groundwater surface almost coincides with the sampling
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depth in summer, and oxygen easily dissolves. Oxygen has not been routinely measured in the shallow Olkiluoto groundwater programme lately, so the reproducibility over the years is impossible to test. It is thus strongly recommended that oxygen be added to the shallow groundwater analysis protocols. The intrusion of oxygen into the ONKALO site is undesired. If any such intrusion should occur, its extent would probably be season related. However, microbial processes will continue to reduce oxygen in the groundwater and form a biological Eh front that will possibly fluctuate up and down with the season. The fluctuation range will probably be relatively narrow, as judged from the results of previous experiments. Research conducted during the construction of the Äspö HRL tunnel could not confirm the intrusion of oxygen via a 70-m-long fault that was intersected by the tunnel (Banwart et al. 1994, 1996). More than 15 years have passed since that large-scale experiment was finished, and oxygen has still not reached the tunnel. The current explanation of this is that continuous microbial processes have reduced oxygen in the intruding groundwater, as explained above.
4.4.2 Chemistry dissolved solids
The concentrations and distribution of the electron acceptors oxygen, nitrate, manganese(IV), ferric iron, and sulphate are important to analyse, as these species determine what microbial processes are or are not possible with respect to available electron acceptors. Oxygen was discussed above, and ferric iron and manganese(IV) are solids that cannot be analysed in groundwater. When reduced, water, carbon dioxide, nitrogen, ferrous iron, manganese(II), sulphide, methane, and acetate are formed according to the reactions in Figure 1-8. The chemical analyses can detect the presence of DOC, the oxidized electron acceptors nitrate and sulphate, and the reduced electron acceptors sulphide, ferrous iron and manganese(II).
The distribution of DOC was scattered over the analysed depth (Figure 3-7), with no clear trends over depth. However, when compared with the concentration of ATP (Figure 4-8) a weak trend was evident, high concentrations of ATP being correlated with high concentrations of DOC (r = 0.98, p < 0.05, n = 24). This strongly suggests a relationship between microbial activity and DOC concentration in Olkiluoto groundwater, which is perfectly in line with our understanding of microbial processes. Heterotrophic microorganisms consume DOC and autotrophic ones produce DOC and they all contain ATP. It is, however, impossible to conclude from concentrations only which of these two processes dominates.
The concentration of nitrate was below the detection limit in most samples (Table A-4). This implies either that nitrate was not present in the analysed deep groundwater at all, or that it is consumed as soon as it appears from unknown sources. The general presence of high numbers of NRB (Figure 3-27) suggests that nitrate is turned over immediately if it appears. It is important to realize that knowing the concentrations of the constituents of a microbial process is not in itself enough to predict the relevance of the process. Turnover rates are needed, as exemplified here by nitrate. Sulphate was scattered over a large concentration range at depths down to 400 m, after which the sulphate concentration approached zero (Figure 4-9). Some of the shallowest groundwater samples were very dilute and had low sulphate concentrations as well. This profile implies that microbial sulphate reduction is currently possible to a maximum depth of 400 m at Olkiluoto.
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Spring Fall2 4 6 8 10 12 14
Temperature ( C)
0
2
4
6
8
10
12
14
16
18
De
pth
(m
)
Figure 4-6. Temperature distribution over fall and spring in shallow Olkiluoto groundwater. The dashed lines indicate the average spring (blue) and fall (red) temperatures.
0 1 2 3 4 5 6 7
O2 (mg L 1)
-200
-100
0
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Eh (m
V)
Figure 4-7. The relationship between Eh and dissolved oxygen in shallow groundwater analysed using the pIONeer 10 portable pH meter and the HQ10 HACH Portable LDO™ dissolved oxygen meter, respectively.
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The concentration of manganese(II) was scattered over depth, displaying somewhat higher values in shallow than in deep groundwater (Table A-4). Ferrous iron and sulphide displayed different profiles with depth (Figure 3-8). Ferrous iron displayed a tendency to decrease exponentially with depth, while sulphide was low in all samples analysed in this work, except those from a depth of approximately 300 m. If all available ferrous iron data are plotted, it becomes clear that the concentration range in shallow groundwater is ten times the range in deep groundwater (Figure 4-10). There is no clear trend in ferrous iron concentration in the deep groundwater. The peak in sulphide concentration at approximately 300 m is very obvious in the scatter plot of all Olkiluoto data (Figure 4-11). This peak is almost 100 times the background sulphide concentrations at all other analysed depths. This profile is indicative of intensive sulphate reduction at a depth of 300 m but, before discussing this indication, data on gases are needed.
1 10 100
DOC (mg C L 1)
1000
10000
100000
1000000
AT
P (
am
ol m
L1)
Figure 4-8. The relationship between dissolved organic carbon (DOC) and ATP in Olkiluoto groundwater.
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0 100 200 300 400 500 600
Sulphate (mg L 1)
0
100
200
300
400
500
600
700
800
900
Depth
(m
)
Figure 4-9. The distribution of sulphate in Olkiluoto groundwater. All available Olkiluoto data between 1992 and 2006 have been included in the scatter plot.
0.00 0.01 0.10 1.00 10.00 100.00
Fe2+ (mg L 1)
0
100
200
300
400
500
600
700
800
900
De
pth
(m
)
Figure 4-10. The distribution of ferrous iron in Olkiluoto groundwater. All available Olkiluoto data between 1992 and 2006 have been included in the scatter plot. The value of observations of ferrous iron below the detection limit was set to 0.005 in the scatter plot.
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0.00 0.01 0.10 1.00 10.00
Sulphide (mg L 1)
0
100
200
300
400
500
600
700
800
900
De
pth
(m
)
Figure 4-11. The distribution of sulphide in Olkiluoto groundwater. All available Olkiluoto data between 1992 and 2006 have been included in the scatter plot. The value of observations of sulphide below the detection limit was set to 0.005 in the scatter plot.
4.4.3 Origins and amounts of dissolved gases in Olkiluoto groundwater
The origins of the gases observed in Olkiluoto groundwater depend on various mechanisms, as discussed elsewhere (Gascoyne 2005; Pitkänen and Partamies 2007). These reports suggest that nitrogen mainly originates from the entrapment of atmospheric nitrogen during groundwater recharge. However, this process would not explain the excess of nitrogen at depth. It is much more likely that the nitrogen in groundwater originates from crustal degassing of the bedrock, as outlined below. The highest amount of nitrogen gas found in the present investigation was 247 mL nitrogen L 1 groundwater 1 in borehole OL-KR29 at a depth of 742 m (Figure 3-14), with a total gas volume of 1380 mL L–1 groundwater 1 (Figure 3-9) at atmospheric pressure. This corresponds to 10.6 mmol L–1 or 0.31 g nitrogen per L of groundwater. The solubility of nitrogen gas in water at atmospheric pressure at 10 C is 0.024 g kg-1 (Aylward and Findley 2002), which corresponds to 0.9 mmol L–1 or 21 mL L–1. The amount of nitrogen dissolved in the OL-KR29 groundwater sample was almost 12 times higher than its solubility would permit at atmospheric pressure. In reality the amount of nitrogen is even higher, because other shallow groundwater gases, in particular carbon dioxide and oxygen, will reduce the solubility of nitrogen during the entrapment of atmospheric nitrogen. The numbers used here are thus conservative. It is deemed very unlikely that the observed excess of dissolved nitrogen in the deep Olkiluoto groundwater originates from atmospheric entrapment during groundwater recharge. Most dissolved nitrogen must instead originate from deep crustal sources. The increase
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in nitrogen concentration is exponential over depth (Figure 3-14), which suggests that diffusion is the major process transporting nitrogen from deep crustal sources. Actually, only a few of the shallowest groundwater samples have nitrogen concentrations at or below the solubility limit (21 mL L 1) at atmospheric pressure (Figure 3-14); the absolute majority of the gas samples had nitrogen concentrations above this limit, supporting the suggested deep crustal origin.
There are four helium reservoirs on Earth, namely, the air, crust, and upper and lower mantle (Apps and van de Kamp 1993). Since helium cannot be retained in the atmosphere by gravity, its concentration in air is very low (5.24 ppm by volume). The helium in air comes mainly from out-gassing of the continental crust and degassing of the mantle. Helium is present as a mixture of two stable isotopes, 3He and 4He, in abundances of 1.38 10–4% and 99.999862%, respectively. 3He is mainly of primordial origin but is also produced by beta decay of 3H to 3He, though this reaction is rare. 4Heis produced by radioactive decay of the uranium- and thorium-series radionuclides. Helium is constantly produced in the crust and mantle by means of these reactions (Marshall and Fairbridge 1999). Consequently, the rate of diffusion of helium to the atmosphere is controlled by its production rate at depth, as inferred by the exponential increase with depth of helium in the analysed groundwater (Figure 3-15).
The total amount of dissolved gas in Olkiluoto groundwater increased exponentially with depth down to the deepest level examined in this work, which was 742 m (Figure 3-9). This profile suggests that most of the analysed gases, except carbon dioxide, are migrating from deep underground towards the surface, as discussed above in the case of helium. The three major gases present were carbon dioxide, nitrogen, and methane (Figure 3-11). Carbon dioxide comprised 20–50% of the extracted gas in samples from shallow groundwater. Thereafter, nitrogen dominated down to a depth of approximately 300 m, at which point methane started to account for a significant part of the dissolved gas, becoming the dominant gas in samples from 320 m and deeper. The concentrations of dissolved methane and ethane increased markedly by approximately 100 times in analysed groundwater from depths below 300 m (Figure 3-16, Figure 3-20). These observations are in line with previous results (Pitkänen and Partamies 2007).
There are two possible hypotheses explaining of the sharp shift in methane concentration at a depth of approximately 300 m. Hypothesis 1 (H1): If there is a flow of groundwater containing low concentrations of methane and ethane in hydrogeological zone HZ20 (Andersson et al. 2007b), it would replace high-methane-concentration groundwater and a rapid drop in the concentrations would result, just as is observed. Hypothesis 2 (H2): There is a process at a depth of approximately 300 m that consumes methane and possibly also ethane. Methane and ethane are accompanied by other gases on its diffusion towards the surface from their respective origins. Helium is an inert gas and thus cannot be consumed or precipitated in any way. A dilution effect of flowing groundwater according to H1 should result in the equal dilution of both helium and methane, the ratio of which should not change. If H1 is valid, then the methane/helium ratio should be approximately the same over most of the analysed depth range. Helium diffuses somewhat faster than methane does, so a slight increase in the ratio can be assumed under H1. Inspecting this ratio over depth reveals that the ratio decreases distinctly by approximately 1000-fold from 300 m up to 200 m (Figure 4-12).
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This effect is less pronounced for ethane/helium ratio. It seems clear that H2 is valid, at least for methane. However, the methane/helium ratio can also drop if the concentration of helium should increase for some unexpected reason. Plotting nitrogen, which like helium is also an inert gas, against helium results in a ratio that increases significantly at depths of less than 300 m (Figure 4-13). This indicates that helium is decreasing in concentration relative to nitrogen; it could also indicate that the nitrogen concentration is increasing, except that such an increase was not observed at depths of less than 300 m. If helium actually is decreasing in concentration due to its more rapid diffusion, then the methane/helium ratio in Figure 4-12 actually underestimates the methane consumption.
CH4 / He
C2H6 / He0.001 0.010 0.100 1.000 10.000 100.000
Gas ratio
0
100
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300
400
500
600
700
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De
pth
(m
)
Figure 4-12. The methane/helium and ethane/helium ratios for Olkiluoto groundwater gas samples.
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N2 / He
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(m
)
Figure 4-13. The nitrogen/helium ratios for Olkiluoto groundwater gas samples.
Some methane/helium ratios from a depth of approximately 100 m are larger than some from depths of 200–300 m. This could be due to anaerobic methane production by microorganisms or may simply reflect the very heterogeneous character of the fractured rock mass sampled, in which several different types of groundwater mix at the same depth.
4.5 Specialists, generalists, opportunists, and antagonists in the world of microbes
The evolution of the microbial world has been continuous for almost four billion years. Over this time, microbes have evolved and adapted to all the environments on our planet where life is possible. To exist, life needs energy, water, and a temperature range between 20 C and +113 C. The phylogenetic tree depicted in Figure 1-1 reflects the enormous diversity of microbes. Over this evolutionary process, several important strategies have been developed. Some microorganisms have become specialized for life in a very narrow range of conditions. One extreme example is the heat-loving microbes that live in hot springs at temperatures close to 100 C. Many actually “freeze” to death when the temperature drops towards room temperature. Other microorganisms have evolved to be very general in their required environmental conditions. They survive in soil and water and can tolerate relatively large ranges of pH, salinity, and temperature. The drawback of specialization is that specialists are restricted to a very narrow niche, but the advantage is little competition, as most other microorganisms will die if they enter the specialist niche. The generalist, on the other hand, will encounter hard competition with many other microorganisms, which may require fine tuning of their
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characteristics, such as the ability to grow rapidly when conditions become favourable. If you can grow faster than other microbes, you have an advantage, of course. Many microorganisms are thus opportunistic: they wait for favourable conditions when they can prosper and multiply. While waiting, they may enter various dormancy states, such as spore formation or starvation, in which they can remain for many years. Finally, some microorganisms have developed ways to compete with other organisms by producing substances that kill their antagonists. Some bacteria can initiate chemical warfare; the actinomycetes are specialists in this, as they produce many different antibiotics, including streptomycin. Then we have the viruses, which do not strictly speaking constitute life, but can be very powerful microbe-killing agents. Taken together, these different strategies create ecosystems of microbes that are in ecological balance over the long term, although some species may occasionally take over and dominate when given a chance.
The implications of the above microbial strategies for Olkiluoto and any other underground environment should be obvious. In a completely stagnant groundwater system, transport rates are limited to diffusion, which is a very slow process over long distances (i.e., in the meter range or more) but very quick in the micrometer range. Microbial processes in such systems will be very slow. Opportunistic microbes in stagnant systems can wait for many years for conditions to change. If hydrodynamic conditions change to a flow situation in which different groundwaters mix, it is very likely that opportunists will respond with rapid growth and microbial processes will speed up significantly for as long as the new flow conditions last. The same thing will happen during the construction of a deep underground tunnel such as ONKALO, or when boreholes are drilled and pumped. Boreholes left without packers, and water conducting fractures intersected by the tunnel, will “short circuit” various fractures and mobilize substances that microbes need.
When opportunists are given good growth conditions, the ATP concentration will increase together with the TNC and numbers of cultivable microbes. High concentrations of organic material should trigger growth of opportunists, as discussed above. The relationship between ATP and DOC (Figure 4-8) suggests that this is occurring in Olkiluoto groundwater. By comparing the biomass and DOC data from different boreholes and depths in Olkiluoto, it is possible to identify “hot spots” where microbial processes are occurring at a rate exceeding the average rates in Olkiluoto.
4.6 Microbial processes in shallow groundwater
The shallow groundwater of Olkiluoto is obviously in close contact with plant and animal life on the surface. There is an input of rainwater to the ground that will transport dissolved organic material from degradation processes in the surface soils into shallow groundwater. Oxygen from the air will dissolve in the recharging rainwater and follow it into the ground. Life processes in the topsoil and deeper in the overburden will actively degrade particulate and dissolved organic material, which will reduce the oxygen. This is a continuous biological process with a clear seasonal variation: freezing conditions in winter will slow down the processes significantly, though the recharge will also stop when the ground freezes. In spring, meltwater will intrude and oxygen
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transport into the ground will peak, as was observed in 2006 (Figure 3-6). The shallow groundwater environment can consequently alternate between aerobic and anaerobic conditions, which most microorganisms are able to handle. Generalist microbes such as NRB and many IRB and MRB can switch from using oxygen as an electron acceptor when available, to using nitrate, ferrous iron, or manganese(IV) when needed. Such organisms are denoted facultative anaerobes. Other microbes can initiate fermentative processes when oxygen disappears.
4.6.1 Aerobic processes
The degradation of organic material with oxygen is a rapid process that is more energetically favourable than is degradation with other electron acceptors (cf. Figure 1-8). Therefore, oxygen-reducing aerobic processes will dominate as long as oxygen is available. This is reflected by the oxygen profiles in shallow Olkiluoto groundwater. Except for a few boreholes, the oxygen concentration was 10% or less of saturation (Figure 3-3), which suggests that aerobic biological processes are consuming oxygen in shallow Olkiluoto groundwater.
In addition to the organic material from the surface, methane migrating from biogenic and thermogenic methanogenesis in deeper layers plus methane produced in overburden layers such as wetlands can contribute to oxygen reduction by microorganisms. The shallow groundwater investigations have documented the presence of MOB that oxidize methane with oxygen (Figure 3-35). Active MOB populations are expected to reduce the oxygen concentration. Inspecting the relationship between the MPN of MOB and the concentrations of dissolved oxygen in shallow groundwater revealed a clear relationship (Figure 4-14). There was more MOB in groundwater with low concentrations of oxygen than in groundwater with high oxygen concentrations. Six samples contained no detectable oxygen and had a range of different MOB numbers. Comparing MOB with the amount of dissolved methane also revealed a relationship in the case of most samples (Figure 4-15). If the three outliers in parentheses in the figure are excluded, the numbers of MOB would appear to be higher in samples low in methane and vice versa. The interpretation of these observations is complex, because they represent snapshots of ongoing processes. It is clear, however, that low methane and oxygen concentrations coincided with high numbers of MOB in several samples. This suggests that aerobic methane oxidation is an important process in removing oxygen from intruding oxygenated recharge water. Some water samples were anaerobic, containing various numbers of MOB. It must be noted that MOB are obligate aerobes, unlike ANME consortia, which are strictly anaerobic in their nature (Boetius et al. 2000). It can be hypothesized that these groundwaters may have contained oxygen before the sampling occasion, and that the oxygen was reduced before sampling. What was observed were remaining MOB populations in various stages of adjustment to oxygen-free conditions. These opportunistic MOB were possibly in various states of reducing their populations into dormancy until the next time oxygen appeared. This hypothesis can be tested if time series are performed over seasons, as was done with oxygen in 2006 (Figure 3-6).
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4.6.2 Anaerobic processes
The MPN analyses demonstrated the presence of most of the anaerobic microorganisms tested for, but the variability in numbers and diversity was large. Samples from boreholes PP2 and PP9 and two samples from PVP14 contained very low numbers, as depicted in Figure 3-25. In contrast, samples from borehole PP39 and two samples from PR1 had among the highest stacked MPN values observed. The reasons for these differences are difficult to define in detail. It is obvious, however, that the environmental conditions in different boreholes were reflected by the presence and probably also the activity of various microorganisms. Borehole PVP1 had a very high stacked value in spring 2006, the reason being a flooding event that lifted the DOC value ten times or more (196 mg L 1) above the values in most other boreholes analysed (Table A-4). Consequently, an extreme event preceding sampling of this borehole in spring 2006 was clearly reflected in the microbiological analyses. This is good example of an opportunistic outburst of microbial activity and multiplication. Borehole PP39 groundwater had the second highest concentration of DOC found in the shallow groundwater, which may explain why it also had among the highest stacked MPN values. As discussed before in relation to Figure 4-8, a clear positive correlation existed between ATP and DOC concentrations. High concentrations of ATP reflect many and active microorganisms (Eydal and Pedersen 2007). A high DOC input to shallow groundwater will rapidly increase the reduction rate of oxygen, and the microbial ecosystem will switch to anaerobic processes as soon as oxygen has disappeared.
4.7 Microbial processes in deep groundwater
4.7.1 Aerobic processes
Oxygen will not reach very deep in groundwater due to the reducing activity of shallow groundwater microorganisms discussed above. However, if oxygen should penetrate due to some extreme event, the processes described for shallow groundwater will operate in deeper groundwater, and the intruding oxygen will soon be reduced to water by groundwater organisms.
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0 1 10 100 1000 10000
MOB (cells mL 1)
0,00
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10,00
O2 (
mg L
1)
Figure 4-14. The relationship between the numbers of methane-oxidizing bacteria (MOB) and the concentration of dissolved oxygen analysed with the Winkler titration method.
0.1 1.0 10.0 100.0 1000.0
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4 (
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L1 g
rou
nd
wa
ter
1)
( )
( )
( )
Figure 4-15. The relationship between the numbers of methane-oxidizing bacteria (MOB) and the concentration of dissolved methane.
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4.7.2 Anaerobic processes
The MPN analysis results indicated the presence of NRB, AA, and HA in all samples analysed for these metabolic groups (Table A-11). IRB, MRB, and SRB were found predominately in samples from the first 100 m and at the 300-m level (Figure 3-28, Figure 3-29, Figure 3-30). Methanogens were found sparsely distributed throughout the depth range (Figure 3-33, Figure 3-34). The production of sulphide by SRB in Olkiluoto groundwater is important, because sulphide would have the potential to corrode the copper canisters used to store spent nuclear fuel. The production of acetate by AA is also important, because acetate can be utilized by SRB, thereby contributing to the amount of produced sulphide. The safety analysis of any future repository requires detailed information regarding how much sulphide can be formed under various circumstances in the deep aquifers surrounding a repository and in the near field of such a repository. The microbial and inorganic processes involved in sulphur transformations can be summarized in the following conceptual model of the coupled reactions that lead to sulphide production.
Microbial processes
AA: H2 + CO2 acetate (Eq. 4-1)
IRB: acetate + Fe3+ Fe2+ + CO2 (Eq. 4-2)
SRB: acetate + SO42– (+ H2) H2S + CO2 (Eq. 4-3)
SRB: DOC + SO42– H2S + CO2 (Eq. 4-4)
AM + SRB: CH4 + SO42– H2 + CO2 + SO4
2– H2S + CH2O (Eq. 4-5)
Inorganic processes (pH > 6.5)
H2S + 2FeOOH S0 + 2Fe2+ + 4OH (Eq. 4-6)
H2S + Fe2+ FeS + 2H+ (Eq. 4-7)
3FeS + 3S0 Fe3S4 + 2S0 3FeS2 (Eq. 4-8)
In a hypothetical aquifer in Olkiluoto rock, the model suggests that AA can produce acetate from hydrogen and carbon dioxide at a rate determined by the inflow of hydrogen (Eq. 4-1). The acetate produced can be utilized by IRB as a source of carbon and energy; as a result, ferrous iron and carbon dioxide are formed from ferric iron minerals and acetate, respectively (Eq. 4-2). Sulphate-reducing bacteria oxidize the acetate produced by AA to carbon dioxide, while sulphate is reduced to sulphide (Eq. 4-3). Several genera of SRB can oxidize acetate, but Desulfovibrio species need hydrogen to be able to utilize acetate. If degradable organic carbon (i.e., DOC and TOC) is available, SRB will produce sulphide and carbon dioxide from this energy and carbon source (Eq. 4-4). A special type of sulphate reduction is coupled to anaerobic methane oxidation (Eq. 4-5). This reaction is common in many marine sedimentary environments (Boetius et al. 2000), but has not yet been demonstrated in deep groundwater. If present, it would have a significant impact on any sulphide production model, because the
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analysed concentration of methane in deep Olkiluoto groundwater is generally much higher than the analysed hydrogen concentration. This possibility has been discussed by Pitkänen and Partamies (2007). The above microbial reactions result in the production of sulphide, ferrous iron, acetate, and carbon dioxide. Hydrogen sulphide produced via equations 4-3 to 4-5 may reduce iron in minerals such as goethite, resulting in the formation of elemental sulphur and ferrous iron (Eq. 4-6). Together with hydrogen sulphide, the ferrous iron produced via equations 4-2 and 4-6 can form iron sulphide (Eq. 4-7). This is a solid compound, and the dissolved sulphide that reacts with ferrous iron in equation 4-7 will precipitate from the groundwater. Finally, pyrite may form (Eq. 4-8) when oversaturation occurs. Pyrite formation has been found to occur rapidly in surface sediments following seasonal variations in sulphide concentrations (Howarth 1979). It was concluded that the rate of sulphate reduction may be grossly underestimated if pyrite formation is ignored. Equations 4-1 to 4-8 may explain the observations reported here. However, the bedrock at Olkiluoto provides a very reducing environment, and iron oxyhydroxides have only been observed at very shallow depths, despite the scattered observations of dissolved ferrous iron at depth (Figure 4-10) which suggest the ongoing reduction of iron oxyhydroxides. The assumed limited availability of iron oxyhydroxides at depth may explain why very high sulphide concentrations are observed at a depth of 300 m (Andersson et al. 2007b). The rate of sulphate reduction will then significantly over-ride the rate of ferric iron reduction.
It was previously concluded in this report that merely knowing the concentrations of chemical markers provides insufficient information with which to judge whether or not a microbial process is taking place. As exemplified by Figure 1-11, the rationale behind and regulation of rates of microbial processes are complicated. Above all, if the reactions are occurring at similar rates, the result will be steady-state concentrations of dissolved ferrous iron and sulphide within a fairly narrow range of values. Inspecting the concentration profiles of ferrous iron (Figure 4-10) and sulphide (Figure 4-11) reveals a clear peak in the sulphide concentration at approximately 300 m, but it is impossible to resolve any peak of iron. If the model above is correct, ferrous iron concentrations should approach zero, according to Eq. 4-7, when sulphide concentrations increase. If the ferrous iron/sulphide ratio is plotted against sulphide, a clear relationship is evident (Figure 4-16). The figure indicates that the ferrous iron concentration decreases relative to the increase in sulphide concentration. The iron concentration decreases almost ten times faster than the sulphide concentration increases. This must be due to the effect of equation 4-7 and because the rate of sulphide production (Eq. 4-3 to 4-5) is faster than that of ferrous iron (Eq. 4-2 and 4-6). Small ferrous iron/sulphide ratios thus indicate samples and sites in Olkiluoto where the microbial production rate of sulphide is much faster than that of ferrous iron. Ferrous iron can be produced both by microbial processes and via equation 4-6. Plotting the ferrous iron/sulphide ratio versus depth enables the identification of sampling points with a high sulphide concentration relative to iron. These points are all located at the 300-m level and have 100 times or more dissolved sulphide than ferrous iron. These points in Olkiluoto can be concluded to harbour very active microbial populations. The next question then concerns the microbial processes going on at these points.
Before answering this question, we must first consider anaerobic methane-oxidizing microorganisms (ANME). For a long time, scientists have observed profiles of methane,
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sulphate, sulphide, and carbon dioxide in anaerobic aquatic sediments that strongly suggested the presence of active ANME (Zehnder and Brock 1980; Thomsen et al. 2001). It was not until very recently, however, that the microorganisms behind this process were identified (Boetius et al. 2000). It was demonstrated that two organisms co-operate in oxidizing methane: methanogens first oxidize methane to hydrogen and carbon dioxide (Eq. 4-9), after which sulphate reducers sweep up the hydrogen and carbon dioxide and produce hydrogen sulphide (Eq. 4-10). Both types of organisms gain reducing power from the reactions used to synthesize organic molecules, with carbon dioxide as the carbon source. To do this, the two organisms must be in very close proximity; typically, the methane oxidizers are surrounded by sulphate reducers in small aggregates.
Methane oxidizer: CH4 + 3H2O 4H2 + HCO3– + H+ (Eq. 4-9)
Sulphate reducer: 4H2 + SO42– +H+ HS + 4 H2O (Eq. 4-10)
Sum reaction: CH4 + SO42– HS– + HCO3
– + H2O (Eq. 4-11)
From Figure 3-16 and Figure 4-9 it is obvious that strong methane and sulphate gradients meet in several locations at a depth of 300 m in Olkiluoto. Furthermore, it is obvious from determinations of ATP levels and of the MPNs of various physiological groups of bacteria, that microbial abundance and activity both peak at these sample locations. Finally, sulphide concentrations are also very high at the same locations. Of the sites evaluated and discussed here, KR6-328 m, KR10-316 m, and KR13-294 m have the greatest potential for pronounced anaerobic methane oxidation; these three locations have ferrous iron/sulphide ratios of 0.1, 0.01, and 0.05, respectively (Table A-4). They also have high concentrations of ATP and DOC and high MPNs of NRB, SRB, AA, and HA, relative to those of other deep groundwater samples. The last piece of evidence needed is proof of the presence of ANME in groundwater at these locations. Ongoing investigations are focusing on this task using DNA technology and available genetic information (Thomsen et al. 2001).
That acetogens may be active is suggested by the presence of hydrogen in groundwater samples from Olkiuoto (Figure 3-12). Samples from deep layers have high concentrations of this gas (Andersson et al. 2007b), but most of the samples reported on here were from depths that were too shallow to harbour these high hydrogen concentrations (Figure 3-18). In addition to a deep source of hydrogen, it is possible that the ANME process may leak hydrogen to acetogenesis, if AA are located close enough to the ANME aggregates. This possibility is still speculative, and successful isolation of ANME in pure laboratory cultures will be needed in order to conduct detailed studies.
The MPNs of sulphate reducers and methanogens in Olkiluoto groundwater were generally at or below the detection limits for each type of microorganism, unlike what was observed previously (Table 1-1). The protocols used to cultivate these organisms (Table 2-3) have worked very well at other Fennoscandian sites, such as the Swedish Forsmark and Laxemar investigation sites and the Äspö HRL (the MPN of SRB has reached 10,000 cells mL 1 in some groundwater samples from these sites). The same protocols should work well for samples from Olkiluoto as well. However, it could be that Olkiluoto groundwater is dominated by ANME, and that our cultivation protocols
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did not detect them. So far, pure cultures of ANME have not been described in the literature. ANME may be so strongly linked and interdependent that they cannot be cultivated separately in the SRB and AM media used. Alternately, the drilling and pumping out of many new boreholes in Olkiluoto may have disturbed the microbial populations and reduced their numbers. Such an effect was observed at the Äspö HRL, in the case of SRB in particular (Pedersen 2005b). That would explain why the numbers of SRB were significantly lower in the 2004–2006 samples than in the 1996–2000 samples (Table 1-1). Finally, changes in the PAVE system sampling methodology may have introduced this difference. Previously, the pressure vessels were not pumped out after being opened. Later, in 2004–2006, the microbiological sampling vessels began to be pumped out for some hours after being opened. However, it is not obvious how this difference in sampling methodology could have influenced microbial numbers; tests will be required to explore this point.
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Figure 4-16. The relationship between the ferrous iron/sulphide ratio and sulphide.
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pth
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Figure 4-17. The relationship between the ferrous iron/sulphide ratio and depth.
4.8 Relevance of microbiological processes to ONKALO
The introduction to this report identified three main effects of microorganisms in the context of a KBS-3 type repository for radioactive waste in Olkiluoto bedrock. The research, results, and conclusions presented here constitute an important baseline for understanding how microbiological processes may interact with ONKALO and a future HLW repository. The evaluated dataset from 2004 to 2006 comprised 60 sets of microbiological analyses coupled to analyses of physical and chemical parameters and the amounts of dissolved gases over the 4–450 m depth range. Continuous microbiological research can now focus on processes deemed significant on the basis of this report, as outlined next. The relevance of microbiological processes to ONKALO can be evaluated as follows.
4.8.1 Oxygen reduction and maintenance of anoxic and reduced conditions
Shallow groundwater in Olkiluoto contained dissolved oxygen at approximately 10% or less of saturation. The presence of aerobic and anaerobic microorganisms, including methane-oxidizing bacteria, has been documented. The data suggest that microbial processes reduce intruding oxygen in the shallow groundwater, DOC and methane being the main electron donors. Biological processes are temperature dependent and seasonal variation was expected and could be documented. Construction of ONKALO may cause the opening of discrete fractures leading towards the tunnel wall, resulting in increased
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inflow to the tunnel [It is possible that oxygen could reach deeper groundwater, carried along by intrusive shallow groundwater that penetrates to greater depths via such disturbed fractures.] However, it can be hypothesized that opportunistic microbial processes could mitigate this oxygen effect if proper electron donors are available. The continuation of the shallow groundwater research programme is recommended. New data can be compared with the data presented here and with data produced by the hydrogeochemical monitoring programme in Olkiluoto. Significant drawdown effects, if any, caused by ONKALO construction should be detectable with this programme. In addition, sampling ONKALO boreholes in the upper part of the tunnel in time series will increase our understanding of how microbial processes in shallow fractures react to tunnel construction.
Fractures opened by the construction of ONKALO will allow for increased water flow. This will allow opportunistic microbes to become activated, resulting in different microbial processes that will influence the geochemistry. After repository closure, when the groundwater table has been restored and stabilized, the rates of microbial processes will again be reduced. The prediction of long-term evolution of hydrogeochemical conditions in the vicinity of ONKALO and the repository requires data pertaining to the surrounding groundwater. It is important to understand how these conditions have been influenced by the construction of ONKALO. What new conditions will persist for a long time and what conditions will return to their original pre-construction states? Detailed knowledge of microbial processes is needed for such modelling work, because these processes influence several important geochemical conditions. A very important geochemical parameter strongly influenced by microbial processes is the Eh.
4.8.2 Bio-corrosion of construction materials
Microbiological and geochemical data strongly suggest that the anaerobic microbial oxidation of methane (ANME) is active at a depth of approximately 300 m in Olkiluoto. It appears as though ANME is limited to the 0–300 m depth interval due to a lack of sulphate at depths below 300 m. This implies that the rate of sulphide production in the ANME process at a depth of 300 m is limited by the transport rate of methane from deeper layers. The construction of ONKALO will probably influence the ANME processes. If groundwater that contains sulphate is drawn down to the bottom of the completed ONKALO tunnel, the ANME processes at that level could speed up, in line with what was discussed for opportunists (4.5). Sulphate seems to be the only component needed by ANME that is missing at depth. As groundwater drawdown currently seems to be boosting the sulphide concentration more than 100-fold at a depth down to 300 m, it is very important to monitor this process because sulphide can corrode copper. The fact that the conditions necessary for ANME growth will again become limited, extending no deeper than 300 m after tunnel closure and backfilling, will be beneficial for the long-term safety of the repository. This matter may call for detailed modelling when data are available regarding how the ANME processes react to the construction of ONKALO.
A programme of research into ANME should be initiated. The study of these still poorly understood microorganisms is in the forefront of microbiological research. New tools in
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molecular biology, such as DNA technology, are needed for such research. ANME samples can be collected on site in ONKALO, using the PAVE system and monitoring boreholes. The polymerase chain reaction (PCR) method of DNA analysis can be used to detect DNA sequences specific to ANME microbes, and thus map the distribution and diversity of ANME in Olkiluoto groundwater over the construction period. Any ANME microbes present can be quantified using the real-time polymerase chain reaction (RT-PCR) method. Analysing m-RNA, by applying RT-PCR to copy DNA, can be used to detect possible ongoing ANME activity. In addition, cultivation methods will be developed and improved. If ANME can be brought into the laboratory, much new knowledge of ANME processes can be gained and applied to the evolution of ONKALO groundwater.
Marked sulphide production appears to be ongoing at the 300-m level in Olkiluoto. When sulphide comes in contact with air, sulphuric acid may form, which is corrosive for metals and concrete. The extent and limiting factors of this process in ONKALO are currently unknown but, as the consequences include the deterioration of “shotcrete” and the concrete sealing of fractures, they should be explored.
As a safety measure for employees and construction workers, extra caution should be taken if the ONKALO tunnel should pass through sulphide-producing rock environments that may have high sulphide concentrations, since hydrogen sulphide gas is very toxic and lethal to humans.
4.8.3 Bio-mobilization and bio-immobilization of radionuclides, and the effects of microbial metabolism on radionuclide mobility.
It is well known that microbes can mobilize trace elements (Pedersen 2002). First, unattached microbes, including viruses, may act as large colloids, transporting radionuclides on their surfaces with the groundwater flow (Moll et al. 2004). Second, microbes are known to produce ligands that can mobilize trace elements and that can inhibit trace element sorption to solid phases (Kalinowski et al. 2004, 2006). One group of microorganisms produces very powerful bioligands, usually denoted pyoverdins, which have a very strong binding affinity for many radionuclides (Johnsson et al. 2006; Essén et al. 2007; Moll et al. 2007). Pyoverdin-producing microbes have been found in shallow Olkiluoto groundwater and in the slime that grows on the tunnel walls of ONKALO. It is important to investigate whether the microbial production of bioligands in deep groundwater may exceed the safety limit for a repository. Groundwater samples from ONKALO can be analysed for DNA signatures typical of pyoverdin producers such as Pseudomonadaceae and Shewanella. The direct interaction between radionuclides and any pyoverdins that may be present in deep groundwater should also be investigated. Biofilms in aquifers may also influence the retention processes of radionuclides in groundwater (Anderson et al. 2006).
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115
A. APPENDIX
Table A-1. Sampling data for four consecutive sampling campaigns in the shallow boreholes in 2004–2006.
Borehole Measured
borehole
depth
(m)
Pump and
sampling
level
(m)
Date and time
(y-m-d/time)
Ground-
water
level
(m)
Yield
(L/min)
Notes
PR1 6 5 2004-05-03/14:30 3.50 12.0 start
2004-05-03/16:20 4.85 12.0
2004-05-03/19:00 4.98 12.0 stop
2004-05-03/07:50 3.60 12.0 start
2004-05-04/08:40 5.07 12.0 stop
PR1 6.0 4.0 2005-10-10/10.35 3.47 4.8
2005-10-10/10.35 3.84 4.5
2005-10-10/10.35 3.85 4.5 clear water
2005-10-10/10.35 3.78 4.5 sampling
PR1 14.72 4.0 2006-04-25/06.30 2.84 5.5 pump start
2006-04-25/06.35 3.10 5.5
2006-04-25/08.05 3.26 5.6
2006-04-25/09.25 3.32 - sampling
PR1 14.72 4.0 2006-10-11/06.20 3.08 - pump start
2006-10-11/06.35 3.29 3.8
2006-10-11/08.00 3.40 3.8
2006-10-11/09.25 3.45 3.8 sampling
PP2 24.5 10 2004-05-04/16:00 2.10 6.0 start
2004-05-04/17:00 5.67 5.0 stop
2004-05-05/07:50 2.09 5.5 start
2004-05-05/08:30 5.65 5.5 stop
PP2 14.90 5.0 2005-10-12/08.00 2.05 4.8 pump start
2005-10-12/08.40 3.93 4.8
2005-10-12/09.30 - - sampling
2006-10-09/12.40 - - sampling
PP2 14.80 6.0 2006-04-24/07.50 1.95 - pump start
2006-04-24/08.00 3.20 3.6
2006-04-24/09.40 3.37 3.6
2006-04-24/10.45 3.40 3.6 sampling
PP2 14.72 4.0 2006-10-11/10.15 2.42 - pump start
2006-10-11/10.30 3.07 2.1
2006-10-11/12.00 3.19 2.2
2006-10-11/13.45 - 2.1
2006-10-11/14.50 - - sampling
116
PP3 14.5 10 2004-05-05/09:50 0.55 7.2 start
2004-05-05/11:00 7.0 stop
PP7 16.5 10 2004-05-05/12:20 1.14 0.85 start
2004-05-05/13:35 7.65 0.80
2004-05-05/15:35 stop
PP8 7.0 6.0 2004-05-05/16:40 3.95 start
2004-05-05/17:00 4.10 5.40
2004-05-05/17:40 4.12 stop
2004-05-06/08:05 3.93 5.50 start
2004-05-06/08:45 4.13 5.5 stop
PP9 14.70 6.0 2005-10-13/12.25 1.31 0.43
2005-10-13/08.35 3.95 0.44 roily water
2005-10-13/12.55 4.15 0.40 sampling
PP9 14.70 6.0 2006-04-26/10.15 0.80 - pump start
2006-04-26/10.25 1.39 0.61
2006-04-26/11.50 3.46 0.58 roily water
2006-04-26/14.05 3.53 0.57 sampling
PP9 14.70 6.0 2006-10-11/07.10 0.78 0.255 pump start
2006-10-11/07.20 1.21 0.255
2006-10-11/08.05 1.26 0.180
2006-10-11/10.30 - 0.185
2006-10-11/12.00 - 0.190 roily water
2006-10-11/15.15 - - sampling
PP36 12.05 6.0 2005-10-10/09.30 4.31 7.2 pump start
2005-10-10/12.05 - -
2005-10-10/13.05 - - clear water
2005-10-10/13.40 - - sampling
PP36 - 4.0 2006-04-25/06.45 3.47 5.04 pump start
2006-04-25/06.50 3.64 5.04
2006-04-25/07.55 3.68 5.04
2006-04-25/12.35 3.70 4.70 sampling
PP36 11.00 5.0 2006-10-09/08.40 3.27 - pump start
2006-10-09/10.50 2.43 6.2
2006-10-09/11.55 - 6.0
2006-10-09/12.05 - 6.2 sampling
PP39 14.10 6.0 2005-10-11/08.30 1.32 0.4 pump start
2005-10-11/10.00 - - roily water
2005-10-11/12.50 - - sampling
PP39 14.04 5.0 2006-04-24/08.10 1.08 - pump start
2006-04-24/08.20 2.01 0.67
2006-04-24/09.55 2.08 0.65
117
2006-04-24/11.05 2.10 0.64
2006-04-24/14.10 2.14 - sampling
PP39 14.10 6.0 2006-10-11/07.30 1.57 - pump start
2006-10-11/07.45 3.20 0.9
2006-10-11/09.00 3.40 0.9
2006-10-11/11.45 - 0.9
2006-10-11/12.45 - - sampling
PVP1 4.0 3.0 2004-05-03/16.35 1.05 start
2004-05-03/15.45 1.05 2.0
2004-05-03/17.30 3.05 1.8
2004-05-03/18.45 2.85 0.25 stop
2004-05-04/08.00 1.06 0.25 start
2004-05-04/10.00 2.90 0.25 Stop
PVP1 3.90 2.50 2005-10-11/07.40 0.69 2.8
2005-10-11/09.50 1.19 2.4 brownwater
2005-10-11/12.10 1.01 2.0 sampling
PVP1 3.92 2.50 2006-04-27/06.35 0.43 - pump start
2006-04-27/06.55 1.25 2.6
2006-04-27/07.45 1.19 2.6 brownwater
2006-04-27/10.20 1.19 2.4 sampling
PVP1 3.93 2.50 2006-10-12/06.20 0.70 -
2006-10-12/06.50 1.32 3.4 pump start
2006-10-12/08.00 1.80 3.0
2006-10-12/09.00 1.90 3.0
2006-10-12/09.25 - - sampling
PVP3B 4.5 3 2004-05-03/12:20 0.60 4.0 start
2004-05-03/13:55 2.60 3.0 run
2004-05-03/15.30 2.65 2.5 stop
PVP3A 8.5 7.5 2004-05-03/09:50 0.70 start
2004-05-03/10:00 2.96
2004-05-03/10:35 6.90 2.7
2004-05-03/12:15 7.08 2.5
2004-05-03/13:30 7.00 Stop
PVP4A 10 9 2004-05-04/13:15 1.25 start
2004-05-04/13:20 6.0
2004-05-04/14:45 7.30 6.0 stop
PVP4A 10.20 5.0 2005-10-12/07.40 1.14 4.8 pump start
2005-10-12/09.55 - 4.5
2005-10-12/12.10 - - sampling
118
PVP4A 10.36 6.0 2006-04-27/06.20 0.85 - pump start
2006-04-27/06.35 2.85 4.5
2006-04-27/08.00 3.27 4.4
2006-04-27/08.35 3.36 3.9 sampling 1
2006-04-27/14.45 3.16 - sampling 2
PVP4A 10.20 5.0 2006-10-10/11.10 1.17 6.0 pump start
2006-10-10/11.20 3.04 5.5
2006-10-10/12.50 - -
2006-10-10/13.20 - - sampling
PVP4B 9.5 8 2004-05-04/13.45 1.80 start
2004-05-04/14:55 6.70 0.70
2004-05-04/17:10 0.70 stop
PVP13 5.60 4.0 2005-10-12/10.40 1.51 1.06 roily water
2005-10-12/10.40 1.87 0.80 clear water
2005-10-12/10.40 1.99 0.85 sampling
PVP13 5.64 3.0 2006-04-26/06.35 0.89
2006-04-26/06.45 1.95 1.10 pump start
2006-04-26/08.00 1.91 1.10
2006-04-26/09.05 1.93 1.10
2006-04-26/11.00 1.64 0.76 sampling
PVP13 5.60 4.0 2006-10-12/10.40 2.49 0.75 pump start
2006-10-12/10.40 - 0.70
2006-10-12/10.40 2.98 0.70
2006-10-12/10.40 - - sampling
PVP14 9.0 5.0 2005-10-14/07.45 2.29 5.2
2005-10-14/08.50 - 5.2
2005-10-14/09.35 - 5.2 sampling
PVP14 9.08 6.0 2006-04-26/06.20 1.34 - pump start
2006-04-26/06.30 3.18 5.1
2006-04-26/08.10 3.39 4.9
2006-04-26/08.45 - - sampling
PVP14 9.08 5.5 2006-10-10/06.25 4.6 4.2 pump start
2006-10-10/07.30 - 1.8
2006-10-10/08.30 - 1.8
2006-10-10/09.30 - 1.8
2006-10-10/10.15 - - sampling
PVP20 12.80 5.0 2005-10-13/07.53 0.71 0.4 pump start
2005-10-13/09.20 0.4
2005-10-13/09.30 sampling
PVP20 - - 2006-04-26/00.00 - - frozen
PVP20 12.80 5.0 2006-10-10/07.45 1.14 1.05 pump start
119
2006-10-10/09.45 - 1.06
2006-10-10/12.30 - -
2006-10-10/14.35 - -
2006-10-10/15.20 - - sampling
120
Table A-2. Pre-treatment of the groundwater samples.
Parameter Container (L) N2- shielding
/ Filtering Preserving chemicals and details Laboratory
Conductivity, density, pH, NH4
1 0.5 HDPE -/- - TVO
Alkalinity, acidity
1 0.5 Duran bottle
x/x Sampling with titration sampler. TVO
S2– 3 0.1 measuring bottle
x/x 0.5 mL Zn(Ac)2 and 0.5 mL
0.1 M NaOH. Sampling with sampler. TVO
Cl, Br, SO4, Stot 1 0.25 HDPE -/x TVO F 1 0.25 HDPE -/x TVO
Fe2+, Fetot6 0.05
measuring bottle x/x
Adding a ferrozine reagent to Fe2+
samples in nitrogen atmosphere. Sampling with sampler.
TVO
Sodium fluorescein
1 0.05 measuring bottle
-/x TVO
DIC/DOC1 0.05 brown
glass bottle -/x Sampling with sampler. TVO
Na, Ca, K, Mg, Fe, Mn, SiO2
1 0.25 PE, acid washed
-/x 2.5 mL conc. HNO3 / 250 mL TVO
PO4 1 0.25 HDPE -/x 2.5 mL 4 M H2SO4/ 250 mL TVO
Sr, Btot1 0.1 HDPE, acid washed
-/x 1 mL suprapur HNO3 / 100 mL VTT
Ntot, NO2, NO3 1 0.25 HDPE -/xRauman ymp. lab.
H-2, O-18 1 0.125
Nalgene bottle -/- Bottle is filled to the brim. GTK
H-3 1 0.25 glass
bottle -/-
TheNetherlands
C-13 / C-14 1 0.2 brown
class bottle -/x Uppsala
Sr-87 / Sr-86 1 0.125
Nalgene, acid washed
-/- GTK
Rn-222 1 0.01
Ultimagold solution bottle
-/- Sampling time is written down. STUK
S-34 (SO4), O-18 (SO4)
1 Nalgene -/-
Sample volume depends on SO4-concentration. Zn(Ac)2 is added to sample according to Posiva water
sampling quide.
Waterloo
Uranium, U-238 1 1 PE,
HCl-washed -/x
50 mL conc. HCl / 1 L. Filters are sent to HYRL for analyses.
HYRL
Uranium, U-234/U-238
1 1 PE, HCl-washed
-/x50 mL conc. HCl / 1 L.
Filters are sent to HYRL for analyses. HYRL
PE = polyethylene, HDPE = high-density polyethylene Laboratories: TVO Teollisuuden Voima Oy VTT VTT Technical Research Centre of Finland Rauman ymp. lab. Rauman ympäristölaboratorio Uppsala Ångström-laboratory, University of Uppsala, Sweden GTK Geological Survey of Finland Waterloo Environmental Isotope Lab, University of Waterloo, Canada The Netherlands Centre for isotope research, Groningen, The Netherlands STUK Radiation and Nuclear Safety Authority, Helsinki, Finland HYRL Department of Radiochemistry, University of Helsinki, Finland
121
Table A-3. Methods and detection limits for groundwater chemistry.
Parameter Apparatus and method Detection limit Uncertainty of the
measurement
pH pH meter ISO-10532
0.05
Conductivity Conductivity analyser SFS-EN-27888
5 µS/cm 5%
Density Posiva water sampling guide /1 0.001 g/cm3
Sodium fluorescein Fluorometry 1 µg/l 15 µg/l: 0.8% 200 µg/l: 1.2% 275 µg/l: 0.4%
Alkalinity Titration/Posiva water sampling guide /1
0.05 mmol/L 5%
Acidity Titration/Posiva water sampling guide /1
0.05 mmol/L 10%
DOC/DIC SFS-EN 1484 0.1 mg/L Fetot Spectrophotometry/ Posiva
water sampling guide /1 0.01 mg/L 5%
Fe2+ Spectrophotometry/ Posiva water sampling guide/1
0.01 mg/L 5%
Fetot,, Mn K, Na SiO2
CaMg
ICP/OES 0.002 mg/L 0.5 mg/L 0.01 mg/L 0.1 mg/L 0.02 mg/L
SrBtot
ICP-MS 0.5 µg/L 2 µg/L
Cl Titration/Posiva water sampling guide/1
5 mg/L 2.5%
Br IC, conductivity detector. SFS-EN ISO 10304-1
0.5 mg/L 4.2%
F ISE/ Posiva water sampling guide/1
0.1 mg/L 5%
PO4 Spectrophotometer SFS-EN 1189
0.012 mg/L ± 24%
S2– Spectrophotometer SFS 3038
0.01 mg/L 0.07 mg/L: 36% 0.17 mg/L: 17% 0.53 mg/L: 10%
SO4 IC, conductivity detector. SFS-EN ISO 10304-1
1.25 mg/L ± 3.2%
Stot H2O2 oxidation +IC 0.2 mg/L NH4 Spectrophotometer
SFS 3032 0.002 mg/L 4%
Total nitrogen, Ntot HPLCSFS3031
0.20 mg/L
Nitrate, NO3 HPLCInternal method n:o 10
3.0 mg/L 3.0–5.0 mg/L: 12% >5.0 mg/L: 7%
Nitrite, NO2 Spectrophotometer SFS3029:1976
0.010 mg/L 0.010–0.10 mg/L: 10%
>0.10 mg/L: 8% 18O MS < 0.1‰ 18O (SO4) MS 0.5‰
122
Table A-3 (continued). Methods and detection limits for groundwater chemistry.
3H Electrical enrichment + home
made Proportional Gas counter (PGC) detection method
0.2 TU 100 ± 2, 20 ± 0.5 and 1.00 ± 0.10 TU
2H MS 1‰ 13C (DIC) MS 0.3 pM 0.05‰ 14C (DIC) AMS 0.1 pM 86Sr/87Sr MS 0.003‰ 34S (SO4) MS 0.1 mBq/L 0.2‰
Rn-222 Liquid scintillation counting / 2 5–10%
U(tot) ja U-234/U-238
Alfaspectrometer ASTM D3648-95, 1995
0.2 mBq/L
References 1 Paaso, N. (toim.), Mäntynen, M., Vepsäläinen, A. ja Laakso, T. 2003. Posivan vesinäytteenoton
kenttätyöohje, rev.3, Posiva Työraportti 2003-02. 2 Salonen L. and Hukkanen H., Advantages of low-background liquid scintillation alpha-
spectrometry and pulse shape analysis in measuring 222Rn, uranium and 226Ra in groundwater samples, Journal of Radioanalytical and Nuclear Chemistry, Vol. 226, Nos. 1–2, 1997.
Table A-4. Physical and chemical data for the sampled groundwater.
Bore-hole Sampling date
(Y-M-D)
Depth
(m)
T
(oC)
pH Conduct-
ivity (mS
m–1
)
TDS (mg
L–1
)
Alkalinity
HCO3
(mg L–1
)
Acidity
(Meq L–1
)
DOC
(mg C
L–1
)
DIC
(mg C
L–1
)
O2
HACH
electrode
(mg L–1
)
O2
Winkler
(mg L–1
)
Eh
HACH-
electrode
(mV)
PR1 2004-05-04 6 4.6 5.0 12 78 23.7 2.80 469
PR1 2005-10-10 6 11.2 5.2 12 110 30.5 0.94 21.5 0.08 402
PR1 2006-04-25 6 3.9 5.3 15 120 33.6 1.12 6.50 16.4 0.42 0.44 134
PR1 2006-10-11 6 10.2 5.5 0 98 27.5 0.88 6.10 13.3 0.21 0.23 224
PP2 2004-05-05 14.7 6.2 7.2 80 575 271.0 0.45 81.5
PP2 2005-10-12 14.7 7.3 7.4 81 650 282.0 0.24 59.9 <0.05 <0.05 121
PP2 2006-04-24 14.7 7.6 7.4 83 620 290.0 0.39 <1.8 58.6 0.26 <0.05 –36
PP2 2006-10-11 14.7 7.1 7.3 78 620 289.0 0.37 3.70 56.2 0.23 <0.05 –100
PP3 2004-05-05 14.3 4.6 6.7 41 350 241.0 0.52 117
PP7 2004-05-05 16.2 7.8 7.7 222 1400 365 0.73 58.3
PP8 2004-05-06 15.2 6.6 33 269 159.0
PP9 2005-10-13 14.7 9.9 6.8 27 270 149.0 0.37 32.6 0.61 0.40 280
PP9 2006-04-27 14.7 6.7 7.3 22 200 119.0 0.19 7.40 21.2 2.35 4.24 240
PP9 2006-10-09 14.7 11.9 6.8 7 140 79.9 0.24 15.60 14.4 1.85 1.07 83
PP36 2005-10-10 12.1 9.9 5.8 23 190 65.3 0.92 23.7 <0.05 <0.05 360
PP36 2006-04-25 12.1 7.0 5.8 11 93 35.4 0.66 15.80 10.3 1.24 1.25 167
PP36 2006-10-09 12.1 10.5 5.8 9 84 30.5 0.53 20.70 10.9 1.35 1.36 234
PP39 2005-10-11 14.1 12.6 7.0 152 1150 355.0 0.43 81.6 <0.05 <0.05 131
PP39 2006-04-24 14.1 10.6 6.9 1 740 329.0 0.94 28.50 68.5 <0.05 <0.05 –64
PP39 2006-10-11 14.1 7.9 6.8 111 990 401.0 1.32 38.80 89.3 0.10 0.03 –116
PVP1 2004-05-04 3.9 12.7 6.0 17 121 46.5 5.17 429
PVP1 2005-10-11 3.9 11.9 4.9 10 120 48.2 2.69 19.7 0.56 0.08 357
123
PVP1 2006-04-27 3.9 3.6 4.8 16 160 76.9 2.24 196.00 3.4 2.11 0.44 126
PVP1 2006-10-12 3.9 10.4 5.3 11 93 20.1 0.57 19.20 5.5 5.95 4.31 208
PVP3A 2004-05-03 7.8 5.6 6.8 59 413 179.0 1.73 247
PVP3B 2004-05-03 3.8 6.6 6.5 59 382 123.0 0.25 315
PVP4A 2004-05-04 9.6 6.4 7.0 73 553 286.0 1.04 216
PVP4A 2005-10-12 10.2 9.3 7.2 80 750 336.0 0.44 64.4 <0.05 <0.05 150
PVP4A:1 2006-04-27–0 h 10.2 5.8 7.3 81 610 294.0 0.45 <1.8 57.6 0.05 <0.05 97
PVP4A:2 2006-04-27–6 h 10.2 8.6 7.1 82 620 301.0 0.43 <1.8 57.6 <0.05 <0.05 86
PVP4A:1/2 2006-04-27 1.00 0.67 1.03 0.99 0.98 0.98 1.05 - 1.00 - - 1.13
PVP4A 2006-10-10 10.2 7.5 7.2 83 630 289.0 0.38 3.10 59.8 0.15 <0.05 –19
PVP4B 2004-05-04 8 11.2 7.0 71 548 285.0 4.85 242
PVP13 2005-10-12 5.6 9.8 7.2 55 540 349.0 0.34 69.9 <0.05 <0.05 153
PVP13 2006-04-26 5.6 8.2 7.3 55 520 338.0 0.41 4.10 65.3 0.12 <0.05 14
PVP13 2006-10-12 5.6 8.3 7.2 53 530 339.0 0.43 7.50 65.8 <0.05 <0.05 –14
PVP14 2005-10-13 9 9.4 7.0 64 610 356.0 0.32 73.8 <0.05 <0.05 150
PVP14 2006-04-26 9 5.3 7.3 61 560 355.0 0.25 <1.8 67.9 0.06 <0.05 –64
PVP14 2006-10-10 9 5.9 7.4 62 580 347.0 0.43 3.40 70.6 0.06 <0.05 –14
PVP20S 2005-10-13 12.8 7.6 7.1 60 510 265.0 0.40 56.0 <0.05 137
PVP20P 2005-10-13 12.8 7.6 7.1 60 510 265.0 0.40 56.0 <0.05 137
PVP20 2006-04-26 12.8 9.4 7.4 56 470 255.0 0.30 10.40 50.9
PVP20 2006-10-10 12.8 6.8 7.3 63 520 275.0 0.37 17.50 54.9 0.20 <0.05 –30
OL-KR2 2004-12-20 306.2 7.4 1009 5480 58.9 0.10 30.50 12.9
OL-KR6 2006-05-11 328.4 7.0 1789 10350 20.1 <0.05 3.80 2.8
OL-KR6 2006-06-26 94.1 7.5 1265 7540 107.0 0.14 2.70 21.1
OL-KR6 2006-08-22 101.8 7.6 1221 7230 111.0 0.17 2.70 22.3
OL-KR6 2006-10-16 73.7 7.40 815 4670 195 0.28 5.90 36.0
OL-KR7 2005-03-01 249.4 7.7 547 3110 187.0 0.09 <1.8 39.6
124
OL-KR8 2005-10-25 57.3 7.3 65 490 221.0 <0.05 <1.8 48.0
OL-KR8 2006-06-06 260.7 7.4 1329 7760 67.7 0.12 <1.8 13.8
OL-KR10 2005-02-21 106 10.3 8.2 301 1810 272.0 <0.05 5.00 57.1
OL-KR10 2006-06-19 316 7.6 1370 7700 30.5 0.06 7.00 6.0
OL-KR13 2004-10-12 294 7.1 964 5340 136.0 0.23 2.50 27.2
OL-KR13 2006-03-14 294 7.6 857 4730 171.0 <0.05 10.60 34.6
OL-KR19 2004-11-08 449.6 11.9 7.1 5510 35160 7.6 <0.05 35.60 <1.5
OL-KR27 2004-11-09 193.5 7.5 1066 6110 140.0 0.18 <1.8 27.3
OL-KR27 2005-01-17 391.7 8.6 7.9 2182 12670 8.2 <0.05 19.20 <1.5
OL-KR31 2006-10-24 122.4 7.8 338 1980 264.0 <0.05 5.00 52.5
OL-KR32 2006-01-10 34.6 7.5 69 580 324.0 0.10 23.70 62.6
OL-KR33 2006-01-24 70.6 7.8 449 2680 306.0 0.15 3.80 59.0
OL-KR37 2006-11-28 111.6 7.6 612 3410 215.0 0.15 5.50 40.7
OL-KR39 2006-04-03 344.8 7.7 1131 6180 25.6 0.42 13.60 4.5
OL-KR39 2006-05-30 88.2 7.9 173 1180 379.0 <0.05 11.40 69.5
125
Table A-4. Continued.
Borehole Sampling date Depth
(m)
Eh Pt-probe
(mV)
SO42–
(mg L–1
)
S2–
(mg L–1
)
Fe2+
(mg L–1
)
Ntot
(mg L–1
)
NO2–
(mg L–1
)
NO3–
(mg L–1
)
NH4
(mg L–1
)
Cl-
(mg L–1
)
F-
(mg L–1
)
Br-
(mg L–1
)
PR1 2004-05-04 6 33.00 0.54 4 0.10 <0.5
PR1 2005-10-10 6 38.00 <0.01 1.23 <3.0 3 0.10 <0.5
PR1 2006-04-25 6 43.00 <0.01 1.60 0.68 0.01 <3.0 3 0.10 <0.5
PR1 2006-10-11 6 35.00 <0.01 0.68 1.00 <0.01 3.28 <2.5 0.10 <0.5
PP2 2004-05-05 14.7 49.00 <0.02 98 0.60 0.60
PP2 2005-10-12 14.7 24.00 <0.01 1.54 <3.0 103 0.60 <0.5
PP2 2006-04-24 14.7 44.00 <0.01 3.46 0.26 0.02 <3.0 101 0.50 <0.5
PP2 2006-10-11 14.7 43.00 <0.01 4.36 0.28 <0.01 <0.02 103 0.60 <0.5
PP3 2004-05-05 14.3 5.40 <0.02 16 0.50 <0.5
PP7 2004-05-05 16.2 120.00 <0.02 483 0.4 1.7
PP8 2004-05-06 15.2 35.00 <0.02 9 0.30 <0.5
PP9 2005-10-13 14.7 27.00 <0.01 0.32 <3.0 6 0.30 <0.5
PP9 2006-04-27 14.7 21.00 <0.01 0.07 <0.2 <0.010 <3.0 4 0.30 <0.5
PP9 2006-10-09 14.7 9.10 <0.01 3.67 0.45 <0.01 <0.02 5 0.30 <0.5
PP36 2005-10-10 12.1 32.00 <0.01 0.34 <3.0 31 0.20 <0.5
PP36 2006-04-25 12.1 18.00 <0.01 0.15 1.20 <0.010 4.40 7 0.10 <0.5
PP36 2006-10-09 12.1 15.00 <0.01 0.24 2.00 <0.01 6.64 4 0.10 <0.5
PP39 2005-10-11 14.1 230.00 <0.01 2.83 <3.0 191 0.40 1.00
PP39 2006-04-24 14.1 110.00 <0.01 7.75 1.50 0.06 <3.0 74 0.40 <0.5
PP39 2006-10-11 14.1 150.00 <0.01 15.30 2.20 <0.01 <0.02 119 0.40 <0.5
PVP1 2004-05-04 3.9 37.00 <0.02 6 0.20 <0.5
PVP1 2005-10-11 3.9 1.40 0.02 14.40 <3.0 7 0.20 <0.5
PVP1 2006-04-27 3.9 9.40 0.02 22.60 4.90 <0.010 <3.0 8 0.20 <0.5
126
PVP1 2006-10-12 3.9 23.00 <0.01 1.67 1.00 <0.01 1.11 9 0.20 <0.5
PVP3A 2004-05-03 7.8 55.00 <0.02 64 0.20 <0.5
PVP3B 2004-05-03 3.8 63.0 <0.02 84 0.20 0.60
PVP4A 2004-05-04 9.6 49.00 <0.02 73 0.40 <0.5
PVP4A 2005-10-12 10.2 47.00 <0.01 4.89 <3.0 89 0.50 <0.5
PVP4A:1 2006-04-27 10.2 47.00 <0.01 3.05 0.27 0.02 <3.0 93 0.50 <0.5
PVP4A:2 2006-04-27–0 h 10.2 47.00 <0.01 1.64 0.38 <0.010 <3.0 93 0.50 <0.5
PVP4A:1/2 2006-04-27–6 h 1.00 1.00 - 1.86 0.71 - - 1.00 1.00 -
PVP4A 2006-10-10 10.2 47.00 <0.01 5.04 0.23 <0.01 <0.02 96 0.50 <0.5
PVP4B 2004-05-04 8 50.00 <0.02 69 0.40 <0.5
PVP13 2005-10-12 5.6 32.00 <0.01 0.26 <3.0 8.9 0.90 <0.5
PVP13 2006-04-26 5.6 34.00 <0.01 2.88 0.28 0.02 <3.0 6.7 0.80 <0.5
PVP13 2006-10-12 5.6 40.00 <0.01 3.10 0.26 <0.01 <0.02 7.9 0.90 <0.5
PVP14 2005-10-13 9 60.00 <0.01 1.72 <3.0 13.6 1.10 <0.5
PVP14 2006-04-26 9 53.00 <0.01 1.26 <0.2 0.01 <3.0 8.9 1.00 <0.5
PVP14 2006-10-10 9 50.00 <0.01 2.34 0.15 <0.01 <0.02 9.9 1.10 <0.5
PVP20S 2005-10-13 12.8 31.00 <0.01 5.70 <3.0 49.9 0.50 <0.5
PVP20P 2005-10-13 12.8 31.00 <0.01 5.70 <3.0 49.9 0.50 <0.5
PVP20 2006-04-26 12.8 31.00 <0.01 0.88 0.45 <0.01 <0.02 40.3 0.50 <0.5
PVP20 2006-10-10 12.8 32.00 <0.01 2.40 0.64 <0.01 <0.02 51.1 0.50 <0.5
OL-KR2 2004-12-20 306.2 150.00 <0.01 0.19 3.10 <0.02 0.03 0.04 3134 0.90 19.00
OL-KR6 2006-05-11 328.4 420.00 3.10 <0.01 0.61 <0.010 NR 0.04 6080 1.40 25.00
OL-KR6 2006-06-26 94.1 490.00 0.03 0.34 0.35 <0.01 <0.02 0.41 4260 0.40 13.80
OL-KR6 2006-08-22 101.8 460.00 0.02 0.32 0.32 <0.01 <0.02 0.33 4010 0.30 13.20
OL-KR6 2006-10-16 73.7 320.00 <0.01 1.200 0.69 <0.01 <0.02 0.610 2510 0.4 8.6
OL-KR7 2005-03-01 249.4 200.00 0.05 0.22 0.18 <0.02 <0.02 0.08 1590 0.50 6.30
OL-KR8 2005-10-25 57.3 –220 28.00 0.03 0.42 0.27 <0.010 <3.0 0.24 88 0.50 0.60
127
OL-KR8 2006-06-06 260.7 470.00 0.08 0.10 0.21 <0.01 <0.02 0.10 4410 0.60 15.80
OL-KR10 2005-02-21 106 –200.0 110.00 <0.01 0.39 0.23 <0.02 <0.02 <0.02 786 1.70 2.90
OL-KR10 2006-06-19 316 <1.25 1.15 0.12 0.08 <0.01 0.030 0.02 4770 1.10 28.90
OL-KR13 2004-10-12 294 98.00 7.15 0.04 0.19 <0.02 <0.02 0.10 3140 0.90 16.00
OL-KR13 2006-03-14 294 86.00 6.73 0.05 0.64 0.01 NR 0.08 2720 1.00 14.40
OL-KR19 2004-11-08 449.6 –70 <1.25 0.02 0.020 2.70 <0.02 0.03 <0.02 22200 1.5 170
OL-KR27 2004-11-09 193.5 –280 400.00 <0.01 0.56 0.60 <0.02 <0.02 0.75 3400 0.60 15.00
OL-KR27 2005-01-17 391.7 –260 <1.25 0.04 0.02 0.35 <0.02 <0.02 0.20 7900 0.90 57.00
OL-KR31 2006-10-24 122.4 160.00 <0.01 0.17 0.52 <0.01 0.02 0.58 869 0.70 2.60
OL-KR32 2006-01-10 34.6 28.00 <0.01 1.12 0.44 0.01 <3.0 0.18 52 0.60 <0.5
OL-KR33 2006-01-24 70.6 280.00 <0.01 0.20 0.40 <0.01 <3.0 0.15 1130 0.30 3.80
OL-KR37 2006-11-28 111.6 250.00 <0.01 1.01 0.88 <0.010 <0.02 1.18 1760 0.50 5.70
OL-KR39 2006-04-03 344.8 13.00 <0.01 0.06 1.50 <0.010 NR 0.02 3780 1.50 28.10
OL-KR39 2006-05-30 88.2 100.00 <0.01 0.49 0.41 <0.01 0.14 0.16 331 0.30 0.80
128
Table A-4. Continued.
Borehole Sampling date Depth (m) SiO2
(mg L–1
)
Na
(mg L–1
)
K
(mg L–1
)
Ca
(mg L–1
)
Mg
(mg L–1
)
Mn
(mg L–1
)
Sr
(mg L–1
)
B
(mg L–1
)
U
(µg L–1
)
PR1 2004-05-04 6 4 1.1 7 3.7
PR1 2005-10-10 6 13.4 6 1.7 8 4.0 0.32 0.025
PR1 2006-04-25 6 11.3 7 1.6 10 4.8 0.38 0.032 0.02 0.6
PR1 2006-10-11 6 12.3 5 1.7 8 3.8 0.27 0.023 0.03 0.7
PP2 2004-05-05 14.7 51 7.5 79 18.3
PP2 2005-10-12 14.7 22.4 46 7.8 134 23.2 1.12 0.3
PP2 2006-04-24 14.7 21.6 40 7.2 94 19.1 1.13 0.4 0.05 <0.1
PP2 2006-10-11 14.7 21.1 40 7.7 94 18.8 1.20 0.3 0.04 <0.2
PP3 2004-05-05 14.3 27 7.8 36 15.9
PP7 2004-05-05 16.2 288 15.50 98.0 27.27
PP8 2004-05-06 15.2 11 4.3 41 8.3
PP9 2005-10-13 14.7 17.2 17 5.4 34 10.6 0.09 0.0
PP9 2006-04-27 14.7 10.0 12 3.6 21 7.8 0.05 0.1 0.03 11.7
PP9 2006-10-09 14.7 12.8 6 2.7 13 4.3 0.04 0.039 0.02 6.4
PP36 2005-10-10 12.1 16.3 28 3.1 11 4.5 0.09 0.06
PP36 2006-04-25 12.1 8.6 8 1.6 7 2.9 0.04 0.03 0.01 1.4
PP36 2006-10-09 12.1 11.0 5 1.7 7 2.5 0.05 0.03 0.02 1.5
PP39 2005-10-11 14.1 22.7 240 18.7 56 26.5 0.66 0.2
PP39 2006-04-24 14.1 27.2 107 10.2 48 20.7 0.76 0.2 0.13 1.3
PP39 2006-10-11 14.1 29.8 145 17.7 71 32.0 1.23 0.3 0.16 2.4
PVP1 2004-05-04 3.9 8 2.2 16 5.6
PVP1 2005-10-11 3.9 26.3 6 1.6 8 3.7 0.08 0.03
PVP1 2006-04-27 3.9 13.0 7 5.1 7 4.5 0.10 0.03 0.03 6.3
129
PVP1 2006-10-12 3.9 19.6 7 2.0 5 3.1 0.07 0.02 0.03 2.1
PVP3A 2004-05-03 7.8 54 7.3 41 12.0
PVP3B 2004-05-03 3.8 61 6.8 32 11.0
PVP4A 2004-05-04 9.6 29 5.9 94 15.1
PVP4A 2005-10-12 10.2 24.6 57 10.6 160 19.3 1.77 0.2
PVP4A:1 2006-04-27–0 h 10.2 21.2 31 6.4 97 15.7 1.36 0.3 0.04 0.1
PVP4A:2 2006-04-27–6 h 10.2 20.9 32 6.9 99 16.5 1.39 0.3 0.04 <0.1
PVP4A:1/2 2006-04-27 1.00 1.01 0.97 0.93 0.98 0.95 0.98 1.04 0.98 -
PVP4A 2006-10-10 10.2 22.7 33 6.4 108 16.8 1.42 0.2 0.04 <0.1
PVP4B 2004-05-04 8 28 6.1 94 15.3
PVP13 2005-10-12 5.6 22.4 16 8.8 80.8 19.3 0.94 0.05
PVP13 2006-04-26 5.6 18.6 14 7.8 73.8 18.3 0.86 0.23 0.04 0.7
PVP13 2006-10-12 5.6 21.1 18 6.0 78.6 17.3 0.88 0.18 0.05 1.3
PVP14 2005-10-13 9 22.3 35 7.6 103 11.1 0.82 0.04
PVP14 2006-04-26 9 17.6 16 4.9 97.1 8.8 0.70 0.13 0.03 3.4
PVP14 2006-10-10 9 21.2 18 5.7 110 9.8 0.82 0.10 0.03 3
PVP20S 2005-10-13 12.8 22.2 61 8.3 50.7 12.4 0.86 0.09
PVP20P 2005-10-13 12.8 22.2 61 8.3 50.7 12.4 0.86 0.09
PVP20 2006-04-26 12.8 18.0 53 6.5 47.6 11.4 0.77 0.22 0.07 0.4
PVP20 2006-10-10 12.8 20.4 64 6.9 52.8 12.4 0.73 0.24 0.09 0.7
OL-KR2 2004-12-20 306.2 8.9 1500 6.3 540 43.0 0.15 5.7 1.00
OL-KR6 2006-05-11 328.4 8.9 2680 9.5 1000 85.0 0.28 11.5 1.63 <0.1
OL-KR6 2006-06-26 94.1 11.0 1710 19.0 710 210.0 1.20 8.2 0.67 1.1
OL-KR6 2006-08-22 101.8 11.0 1760 19.0 650 180.0 1.20 8.1 0.62 1.1
OL-KR6 2006-10-16 73.7 12 1050 18 420 130 1.30 4.6 0.44 2.8
OL-KR7 2005-03-01 249.4 12.0 830 6.7 220 52.0 0.24 2.3 0.62
OL-KR8 2005-10-25 57.3 13.0 90 6.7 32 10.8 0.22 0.2 0.13
130
OL-KR8 2006-06-06 260.7 11.0 1800 7.9 810 160.0 0.62 8.4 0.63 0.6
OL-KR10 2005-02-21 106 11.0 543 2.5 62 11.0 0.05 0.6 0.64
OL-KR10 2006-06-19 316 10.0 1790 7.8 990 58.0 0.55 9.9 1.30 <0.2
OL-KR13 2004-10-12 294 12.0 1430 7.2 500 39.0 0.19 5.7 1.20
OL-KR13 2006-03-14 294 13 1260 6.5 420 28.0 0.20 4.6 1.10 0.1
OL-KR19 2004-11-08 449.6 6.4 6060 14.0 6800 17.0 0.16 73 1.00
OL-KR27 2004-11-09 193.5 12.0 1410 20.0 510 190.0 1.00 5.7 0.39
OL-KR27 2005-01-17 391.7 11.0 2540 6.8 2100 39.0 0.27 22.0 1.00
OL-KR31 2006-10-24 122.4 13.0 519 11.0 100 36.0 0.28 1.0 0.33 3.1
OL-KR32 2006-01-10 34.6 15.0 118 7.0 23 8.7 0.31 0.1 0.17
OL-KR33 2006-01-24 70.6 11.0 760 9.0 130 42.0 0.30 1.5 0.49
OL-KR37 2006-11-28 111.6 12.0 823 18.0 230 88.0 0.74 2.3 0.34 2.3
OL-KR39 2006-04-03 344.8 7.4 1880 7.2 410 18.0 0.24 3.5 1.57 <0.2
OL-KR39 2006-05-30 88.2 13.4 267 7.7 54 19.0 0.14 0.5 0.33 3.8
131
Table A-5. Gas data for the sampled shallow groundwater. Rows in italics with “-SD%” after the borehole code show the standard deviations in percent of the average. The number of samples (n) was 2 for the April 2006 analyses and 3 for the October 2006 analyses.
Borehole Pump
level
(m)
Depth
Z-up
(m)
Sample and
extraction
date
Volume
water
(mL)
Extracted
gas
(mL)
Extracted
gas
(mL L–1
)
Oxygen
(ppm)
Hydrogen
(ppm)
Helium
(ppm)
Argon
(ppm)
PR1 4 6 2006-04-25 91.5 6.2 66.5 35450 24.4 0 n.a.
PR1-SD% 4 6 2006-04-25 7.0 37.9 31.4 61.6 41.5
PR1 4 6 2006-10-11 104.7 6.4 61.0 10650 52.5 0 n.a.
PR1-SD% 4 6 2006-10-11 2.8 36.5 37.8 61.0 43.8
PP2 6 14.7 2006-04-24 97.5 2.9 28.5 82400 31.7 0 n.a.
PP2-SD% 6 14.7 2006-04-24 6.5 86.8 82.6 45.7 82.9
PP2 4 14.7 2006-10-11 104.0 3.1 29.4 55695 37.3 0 n.a.
PP2-SD% 4 14.7 2006-10-11 3.5 24.5 22.6 31.5 12.6
PP9 6 14.7 2006-04-26 93.5 4.0 42.8 259500 13.2 0 n.a.
PP9-SD% 6 14.7 2006-04-26 0.8 0.0 0.8 80.4 8.1
PP9 6 14.7 2006-10-09 97.3 2.4 24.6 43600 42.7 0 n.a.
PP9-SD% 6 14.7 2006-10-09 4.6 22.0 18.2 28.0 29.2
PP36 4 11 2006-04-25 102.5 5.4 53.2 30350 10.8 0 n.a.
PP36-SD% 4 11 2006-04-25 9.0 35.7 43.9 34.2 19.1
PP36 5 11 2006-10-11 95.0 3.9 41.8 69000 40.8 0 n.a.
PP36-SD% 5 11 2006-10-11 6.9 53.4 57.0 62.5 73.1
PP39 5 14 2006-04-24 82.0 4.0 48.3 22950 15.1 0 n.a.
PP39-SD% 5 14 2006-04-24 5.2 9.0 14.1 44.1 22.1
PP39 6 14 2006-10-11 97.7 7.2 73.6 10650 13.6 0 n.a.
PP39-SD% 6 14 2006-10-11 5.8 28.0 24.8 61.0 22.1
PVP1 2.5 3.9 2006-04-27 101.5 5.0 49.3 49600 11.6 0 n.a.
132
PVP1-SD% 2.5 3.9 2006-04-27 2.1 0.0 2.1 1.1 6.7
PVP1 2.5 3.9 2006-10-12 99.3 5.3 53.8 29333 21.4 793 n.a.
PVP1-SD% 2.5 3.9 2006-10-12 1.2 28.6 29.8 14.3 22.7 156
PVP4A-1 6 10.2 2006-04-27–0 h 96.0 2.3 23.4 40250 20.1 0 n.a.
PVP4A-1-SD% 6 10.2 2006-04-27–0 h 5.9 15.7 9.9 59.6 1.4
PVP4A-2 6 10.2 2006-04-27–6 h 95.5 4.1 43.0 17600 20.2 0 n.a.
PVP4A-2-SD% 6 10.2 2006-04-27–6 h 0.7 65.5 66.1 53.0 47.4
PVP4A 5 10.2 2006-10-11 101.3 3.6 36.0 31900 24.8 0 n.a.
PVP4A-SD% 5 10.2 2006-10-11 2.3 17.9 19.7 32.3 12.9
PVP13 3 5.6 2006-04-26 101.0 3.6 35.7 37000 17.9 0 n.a.
PVP13-SD% 3 5.6 2006-04-26 1.4 15.7 17.1 81.4 11.1
PVP13 4 5.6 2006-10-12 99.0 4.5 45.5 8120 20.0 0 n.a.
PVP13-SD% 4 5.6 2006-10-12 5.3 29.6 32.4 105.7 49.2
PVP14 6 9.1 2006-04-26 83.5 3.2 37.7 30000 18.3 0 n.a.
PVP14-SD% 6 9.1 2006-04-26 2.5 11.2 8.7 0.9 4.6
PVP14 5.5 9.1 2006-10-10 95.0 4.7 49.7 23400 26.7 0 n.a.
PVP14-SD% 5.5 9.1 2006-10-10 1.1 31.8 32.3 21.1 18.7
PVP20 12.8 12.8 2006-10-10 100.3 3.8 38.5 27340 30.8 0 n.a.
PVP20-SD% 12.8 12.8 2006-10-10 6.8 28.5 33.9 124.5 25.2
PVA1 ONKALO 20 2006-04-28 98.0 4.0 40.8 55150 24.8 0 n.a.
PVA1-SD% ONKALO 20 2006-04-28 2.9 0.0 2.9 3.2 0.0
PVA1 ONKALO 20 2006-10-11 99.3 4.0 39.9 8873 69.3 0 n.a.
PVA1-SD% ONKALO 20 2006-10-11 1.5 31.9 31.1 48.9 51.6
133
Table A-5. Continued
Borehole Sample and
extraction
date
Nitrogen
(ppm)
CO
(ppm)
CO2
(ppm)
CH4
(ppm)
C2H6
(ppm)
C2H2–4
(ppm)
total gas
(%)
PR1 2006-04-25 431500 44.1 529500 2905 0 0 99.9
PR1-SD% 2006-04-25 39 14.6 27 35 0.1
PR1 2006-10-11 461667 29.0 472000 258 0 0 94.5
PR1-SD% 2006-10-11 23 22.0 19 17 3.4
PP2 2006-04-24 706500 96.2 239000 4650 0 0 103.3
PP2-SD% 2006-04-24 36 68.8 86 82 0.6
PP2 2006-10-11 706334 41.4 202218 2044 0 0 96.6
PP2-SD% 2006-10-11 3 28.6 10 16 1.8
PP9 2006-04-26 523500 54.8 249000 327 0 0 103.2
PP9-SD% 2006-04-26 32 11.5 4 5 3.1
PP9 2006-10-09 501000 125.0 454333 295 0 0 99.9
PP9-SD% 2006-10-09 28 16.5 32 18 1.7
PP36 2006-04-25 566000 91.5 433000 230 0 0 103.0
PP36-SD% 2006-04-25 24 27.0 24 55 2.3
PP36 2006-10-11 449667 112.1 453667 262 0 0 97.3
PP36-SD% 2006-10-11 65 83.3 57 105 2.1
PP39 2006-04-24 542000 35.8 451000 22500 0 0 103.9
PP39-SD% 2006-04-24 19 22.1 19 18 0.1
PP39 2006-10-11 461667 29.0 472000 258 0 0 94.5
PP39-SD% 2006-10-11 23 22.0 19 17 3.4
PVP1 2006-04-27 439000 78.6 528500 432 0 0 101.8
PVP1-SD% 2006-04-27 0 26.6 2 72 0.9
PVP1 2006-10-12 591667 60.6 293333 674 0.1 0 91.6
134
PVP1-SD% 2006-10-12 8 69.3 18 37 100 3.2
PVP4A-1 2006-04-27–0 h 700000 37.2 306000 4140 0 0 105.0
PVP4A-1-SD% 2006-04-27–0 h 10 16.7 13 15 0.8
PVP4A-2 2006-04-27–6 h 786000 44.5 246500 2820 0 0 105.3
PVP4A-2-SD% 2006-04-27–6 h 23 45.8 66 46 0.5
PVP4A 2006-10-11 697667 31.4 265000 2730 0 0 99.7
PVP4A-SD% 2006-10-11 6 22.1 12 14 0.2
PVP13 2006-04-26 785500 46.5 207500 2370 0 0 103.2
PVP13-SD% 2006-04-26 1 40.4 24 17 1.5
PVP13 2006-10-12 715667 28.2 228000 1082 0 0 95.3
PVP13-SD% 2006-10-12 4 13.8 33 30 10.4
PVP14 2006-04-26 795000 41.4 220500 289 0 0 104.6
PVP14-SD% 2006-04-26 6 45.0 21 1 0.4
PVP14 2006-10-10 800333 12.6 157000 38 0 0 98.1
PVP14-SD% 2006-10-10 6 135.4 23 138 0.8
PVP20 2006-10-10 769333 28.6 193333 827 0 0 99.1
PVP20-SD% 2006-10-10 11 50.0 22 31 0.9
PVA1 2006-04-28 716000 32.5 40350 3415 8 0 81.5
PVA1-SD% 2006-04-28 0 74.0 13 20 8 0.7
PVA1 2006-10-11 926000 43.5 70400 6817 0 0 101.2
PVA1-SD% 2006-10-11 4 34.5 16 29 1.7
135
Table A-6. Gas data for the sampled deep groundwater.
Borhole Upper
level
(m)
Lower
level
(m)
Depth
Z-up
(m)
Sample
date
Extraction
date
Time from
sampling to
analysis (d)
Volume
water
(mL)
Extracted
gas
(mL)
Extracted
gas
(mL L–1
)
Analysed
air
(%)
OL-KR2 596.5 609.5 560 2006-02-28 2006-03-07 7 90 47.0 522.2 0.76
OL-KR6 422 425 328 2005-08-02 2005-08-24 22 254 15.5 61.0 11.40
OL-KR6 135 137 102 2005-09-27 2005-10-17 20 82 9.5 115.9 2.20
OL-KR6 120 125 90 2005-11-02 2005-12-12 40 77 7.5 97.4 4.80
OL-KR6 98.5 100.5 73 2005-12-27 2006-01-13 17 201 9.5 47.3 1.10
OL-KR6 125 130 94 2006-06-26 2006-07-02 6 76 10.0 131.6 1.89
OL-KR6 135 137 116 2006-08-22 2006-08-28 6 65 5.0 76.9 1.13
OL-KR6 98.5 100 74 2006-10-16 2006-10-24 8 70 6.2 88.6 1.22
OL-KR7 284 288 257 2006-04-25 2006-05-11 16 220 8.6 39.1 5.20
OL-KR7-Ar 220 230 197 2005-04-25 2005-08-22 119 30 5.6 186.7 12.10
OL-KR7-N2 220 230 197 2005-04-25 2005-08-23 120 74 7.2 97.3 14.40
OL-KR8 77 84 57 2005-10-25 2005-12-12 48 183 5.9 32.2 1.85
OL-KR8 556.5 561 490 2006-04-27 2006-05-11 14 95 41.1 432.6 0.86
OL-KR8 302 310 261 2006-06-06 2006-06-09 3 101 9.2 91.1 0.64
OL-KR8 77 84 57 2006-08-15 2006-08-28 13 195 6.8 34.9 1.59
OL-KR10 259 262 249 2005-04-04 2005-06-26 83 178 14.0 78.7 12.40
OL-KR10 326 328 316 2006-06-19 2006-06-21 2 236 29.5 125.0 2.60
OL-KR10-Ar 326.5 328.5 316 2005-04-04 2005-08-23 141 100 9.4 94.0 8.70
OL-KR10-N2 326.5 328.5 316 2005-04-04 2005-08-23 141 127 23.6 185.8 0.90
OL-KR13 362 365 294 2006-03-14 2006-03-27 13 100 11.4 114.0 0.31
OL-KR19 110 131 101 2005-09-05 2005-10-05 30 88.4 7.2 81.4 2.60
OL-KR19 455 468 433 2005-10-31 2005-12-12 42 107 25.4 237.4 1.12
136
OL-KR22 147 152 116 2005-12-13 2006-01-13 31 231 15.8 68.4 2.94
OL-KR22 390 394 320 2006-03-01 2006-03-07 6 244 83.0 340.2 0.00
OL-KR22 147 152 102 2006-08-17 2006-08-28 11 95 5.2 54.7 3.38
OL-KR29 320 340 293 2005-06-06 2005-08-23 78 65 7.0 107.7 13.30
OL-KR29 800 800 742 2005-04-16 2005-08-23 129 163 225.0 1380.4 1.70
OL-KR30 50 54 40 2005-08-04 2005-08-24 20 111 4.6 41.4 17.40
OL-KR31 143 146 122 2006-10-24 2006-10-26 2 250 8.2 32.8 3.72
OL-KR33 95 107 71 2006-01-24 2006-01-26 2 73 8.0 109.6 9.75
OL-KR37 166 176 112 2006-11-28 2006-11-30 2 92 4.8 52.2 4.34
OL-KR39 403 406 345 2006-04-03 2006-04-06 3 107 15.5 144.9 1.39
OL-KR39 108 110 88 2006-05-30 2006-06-09 10 79 4.2 53.2 1.96
137
Table A-6. Continued
Borehole Hydrogen
(ppm)
Helium
(ppm)
Argon
(ppm)
Nitrogen
(ppm)
CO
(ppm)
CO2
(ppm)
CH4
(ppm)
C2H6
(ppm)
C2H2–4
(ppm)
total gas
(%)
OL-KR2 68.6 24400 241 290000 6.30 140 699000 6250.00 0.00 102.0
OL-KR6 8.4 54800 3000 671000 8.80 2980 267000 1330.00 0.00 100.0
OL-KR6 40.9 1490 35700 954000 26.80 6980 2100 23.80 0.00 100.0
OL-KR6 2710.0 1730 4590 905000 72.00 15400 13400 60.10 1.09 94.3
OL-KR6 11.6 1130 2440 1010000 16.40 25400 1580 3.97 0.00 104.1
OL-KR6 16.0 1030 398 973000 25.80 10900 3090 30.20 0.00 98.8
OL-KR6 6.5 1130 4090 973000 9.30 26400 1020 3.90 0.00 100.6
OL-KR6 11.2 715 0 981000 15.40 32900 761 4.51 0.00 101.5
OL-KR7 5.2 11900 695 953000 6.00 16800 13900 21.20 0.00 99.6
OL-KR7-Ar 20.5 30200 51800 904000 20.40 10100 3820 23.80 0.00 100.0
OL-KR7-N2 24.7 0 15900 949000 28.40 23500 11000 119.00 0.00 100.0
OL-KR8 7540.0 0 1330 936000 27.70 14500 6150 65.90 0.00 96.6
OL-KR8 6.5 22500 166 237000 2.30 152 744000 4170.00 0.00 100.8
OL-KR8 18.7 8670 893 981000 41.00 8140 2000 24.40 0.00 100.1
OL-KR8 27.7 0 4970 953000 15.60 56300 2600 9.08 0.00 101.7
OL-KR10 51.9 8030 2500 972000 33.40 5310 12400 30.40 7.31 100.0
OL-KR10 21.4 35200 312 440000 14.40 1830 547000 2120.00 0.00 102.6
OL-KR10-Ar 5.8 19100 4790 751000 4.30 2040 222000 627.00 0.00 100.0
OL-KR10-N2 28.6 18600 10200 654000 4.70 1470 315000 1300.00 0.00 100.1
OL-KR13 651.0 30900 1740 769000 5.80 16100 175000 773.00 0.00 99.4
OL-KR19 54.0 1630 17100 959000 7.40 21400 841 4.50 0.00 100.0
OL-KR19 1320.0 18000 1570 481000 17.40 366 493000 2780.00 0.00 99.8
OL-KR22 31.9 898 1810 975000 30.80 33100 14100 57.90 0.00 102.5
OL-KR22 33.8 2460 529 986000 6.10 4130 28500 79.80 0.00 102.2
138
OL-KR22 10.0 978 3667 942000 8.80 59400 17200 41.80 0.00 102.3
OL-KR29 15.6 5330 6430 968000 9.90 2190 16800 1090.00 0.58 100.0
OL-KR29 51.8 14900 2660 186000 3.00 1460 779000 15400.00 0.00 100.0
OL-KR30 107.0 0 0 976000 32.60 14000 10800 220.00 0.00 100.1
OL-KR31 9.7 920 30000 916000 44.30 34200 5320 2.27 1.62 98.6
OL-KR33 94.0 0 0 922000 74.80 9940 582 5.68 0.00 93.3
OL-KR37 22.3 1400 17100 933000 22.00 55000 2860 5.86 0.00 100.9
OL-KR39 18.3 19600 743 408000 12.40 7170 582000 1470.00 0.00 101.9
OL-KR39 7.6 0 377 960000 15.10 22600 1080 7.12 0.00 98.4
139
Table A-7. Biomass determinations for shallow groundwater in Olkiluoto, sampled over spring and fall seasons. TNC = total number of cells,SD = standard deviation, n = number of observations, CHAB = cultivable heterotrophic aerobic bacteria, MPN = sum of all most probable number of cells values (see Table A-8), and n.a. = not analysed for various reasons, for example, inapplicable because the analysis had not yet been introduced, sample turbidity, or analytical error.
Borehole sampled
(Y-M-D)
Depth
(m)
TNC
(cells mL1)
SD n ATP
(amol mL1)
SD n CHAB
(cells mL1)
SD n CHAB/
TNC
(%)
ATP/
TNC
MPN/
TNC
(%)
PR1 2004-05-04 6.0 57000 57000 6 n.a. 5150 1450 3 9.04 0.29
PR1 2005-10-10 6.0 2000000 450000 6 266000 7270 3 11700 117 3 0.59 0.133 1.46
PR1 2006-04-25 6.0 820000 84000 3 626000 34700 3 1600 2040 3 0.20 0.763 0.30
PR1 2006-10-11 6.0 390000 21000 3 128000 8590 3 827 107 3 0.21 0.328 0.64
PP2 2004-05-05 14.7 32000 16000 6 n.a. n.a. - - 0.01
PP2 2005-10-12 14.7 110000 53000 6 25100 2440 3 310 399 3 0.28 0.228 0.12
PP2 2006-04-24 14.7 55000 1400 3 13300 680 3 553 98 3 1.01 0.242 0.04
PP2 2006-10-11 14.7 10000 1100 3 1900 50 3 27 46 3 0.27 0.190 0.10
PP3 2004-05-05 14.3 190000 84000 6 n.a. 93 65 3 0.05 0.00
PP7 2004-05-05 16.2 31000 23000 6 n.a. 240 150 3 0.77 0.06
PP8 2004-05-06 15.2 1500000 160000 5 n.a. 1900 707 2 0.13 0.02
PP9 2005-10-13 14.7 200000 46000 6 24500 1770 3 13 6 3 0.01 0.123 0.01
PP9 2006-04-27 14.7 n.a. 109000 1400 3 70 46 3
PP9 2006-10-09 14.7 220000 5400 3 104000 4610 3 677 508 3 0.31 0.473 0.10
PP36 2005-10-10 12.1 110000 45000 6 26900 1080 3 37 6 3 0.03 0.245 0.08
PP36 2006-04-25 12.1 370000 29000 3 220600 10600 3 427 60 3 0.12 0.596 0.09
PP36 2006-10-09 12.1 400000 15000 3 146000 13600 3 740 42 2 0.19 0.365 0.05
PP39 2005-10-11 14.1 580000 560000 6 198000 10800 3 913 93 3 0.16 0.341 0.14
PP39 2006-04-24 14.1 540000 140000 3 90400 3110 3 553 64 3 0.10 0.167 0.21
PP39 2006-10-11 14.1 410000 42000 3 170000 5220 3 983 145 3 0.24 0.415 1.09
140
Table A-7. continued.
Borehole sampled
(Y-M-D)
Depth
(m)
TNC
(cells mL1)
SD n ATP
(amol mL1)
SD n CHAB
(cells mL1)
SD n CHAB/
TNC
(%)
ATP/
TNC
MPN/
TNC
(%)
PVP1 2004-05-04 3.9 1500000 400000 6 n.a. 15100 5130 3 1.01 0.00
PVP1 2005-10-11 3.9 2500000 670000 6 685000 59900 3 917 218 3 0.04 0.274 0.01
PVP1 2006-04-27 3.9 1100000 18000 3 7920000 307000 3 4400 3200 3 0.40 7.200 2.67
PVP1 2006-10-12 3.9 200000 16000 3 624000 61800 3 530 125 3 0.27 3.120 0.10
PVP3A 2004-05-03 7.8 150000 66000 6 n.a. 1060 482 3 0.71 - 0.00
PVP3B 2004-05-03 3.8 41000 53000 6 n.a. 6690 3610 3 16.32 0.17
PVP4A 2004-05-04 9.6 96000 55000 6 13200 3 690 539 3 0.72 0.01
PVP4A 2005-10-12 10.2 660000 14000 6 30200 4160 3 1240 59 3 0.19 0.046 0.20
PVP4A 2006-10-10 10.2 9500 1400 3 1860 170 3 0 0 3 0.00 0.196 0.14
PVP4A:1 2006-04-27 10.2 7600 1300 3 11400 2800 3 2330 115 3 30.66 1.500 3.05
PVP4A:2 2006-04-27 10.2 7800 1100 3 6320 630 3 173 60 3 2.22 0.810 2.02
PVP4A:1/2 2006-04-27 10.2 0.97 1.80 13.5
PVP4B 2004-05-04 8.0 51000 19000 6 n.a. 79200 17300 3 155.29 0.01
PVP13 2005-10-12 5.6 120000 17000 6 79400 10300 3 1400 106 3 1.17 0.662 0.73
PVP13 2006-04-26 5.6 17000 1400 3 12800 560 3 83 40 3 0.49 0.753 2.28
PVP13 2006-10-12 5.6 17000 1400 3 12300 790 3 23 12 3 0.14 0.724 0.62
PVP14 2005-10-13 9.0 90000 80000 6 3570 480 3 57 30 3 0.06 0.040 0.02
PVP14 2006-04-26 9.0 20000 2600 3 3620 670 3 10 7 3 0.05 0.181 0.05
PVP14 2006-10-10 9.0 9300 1900 3 4520 280 3 30 26 3 0.32 0.486 3.85
PVP20S 2005-10-13 12.8 320000 43000 6 106000 7740 3 2220 415 3 0.69 0.331 0.56
PVP20P 2005-10-13 12.8 150000 76000 6 76100 3890 3 1970 225 3 1.31 0.507 0.14
PVP20 2006-04-26 12.8 ICE- COVERED
PVP20 2006-10-10 12.8 n.a. - 3 367000 51500 3 783 196 3 - - -
141
Table A-8. The most probable numbers of nitrate-, iron-, manganese-, and sulphate-reducing bacteria (NRB, IRB, MRB, and SRB, respectively)in shallow groundwater of Olkiluoto. L and U limits are the 95% confidence values. n.a. = not analysed for various reasons, for example, inapplicable because the analysis had not yet been introduced, sample turbidity, or analytical error.
Bore-
hole
sampled
(Y-M-D)
Depth
(m)
NRB
(cells
mL1)
L
limit
U
limit
IRB
(cells
mL1)
L
limit
U
limit
MRB
(cells
mL1)
L
limit
U
limit
SRB
(cells
mL1)
L
limit
U
limit
PR1 2004-05-04 6.0 n.a. 0.4 0.1 1.7 0.0 3.0 1.0 12.0
PR1 2005-10-10 6.0 24000.0 10000.0 94000.0 1.3 0.5 3.8 0.8 0.3 2.4 23.0 9.0 86.0
PR1 2006-04-25 6.0 1700.0 700.0 4800.0 2.3 0.9 8.6 70.0 30.0 210.0 24.0 10.0 94.0
PR1 2006-10-11 6.0 2400.0 1000.0 9400.0 0.2 0.1 1.1 1.3 0.5 3.8 3.0 1.0 12.0
PP2 2004-05-05 14.7 n.a. <0.2 <0.2 <0.2PP2 2005-10-12 14.7 <0.2 <0.2 <0.2 2.3 0.9 8.6
PP2 2006-04-24 14.7 2.3 0.9 8.6 <0.2 0.4 0.1 1.7 <0.2PP2 2006-10-11 14.7 0.2 0.1 1.1 <0.2 <0.2 <0.2PP3 2004-05-05 14.3 n.a. <0.2 <0.2 0.4 0.1 1.7
PP7 2004-05-05 16.2 n.a. <0.2 <0.2 <0.2PP8 2004-05-06 15.2 n.a. <0.2 <0.2 <0.2PP9 2005-10-13 14.7 8.0 3.0 25.0 <0.2 0.4 0.1 1.5 <0.2PP9 2006-04-27 14.7 13.0 5.0 39.0 <0.2 0.8 0.3 2.4 0.4 0.1 1.7
PP9 2006-10-09 14.7 30.0 10.0 120.0 <0.2 <0.2 5.0 2.0 17.0
PP36 2005-10-10 12.1 1.7 0.7 4.6 <0.2 0.8 0.3 2.4 2.3 0.9 8.6
PP36 2006-04-25 12.1 70.0 30.0 210.0 <0.2 17.0 7.0 48.0 1.3 0.5 3.8
PP36 2006-10-09 12.1 80.0 30.0 250.0 <0.2 0.4 0.1 1.7 1.3 0.5 3.8
PP39 2005-10-11 14.1 300.0 100.0 1200.0 1.7 0.7 4.6 17.0 8.0 41.0 26.0 12.0 65.0
PP39 2006-04-24 14.1 23.0 9.0 86.0 17.0 7.0 46.0 170.0 70.0 480.0 500.0 200.0 2000.0
PP39 2006-10-11 14.1 1300.0 500.0 3900.0 14.0 6.0 36.0 28.0 12.0 69.0 50.0 20.0 170.0
142
Table A-8. Continued.
Bore-
Hole
sampled
(Y-M-D)
Depth
(m)
NRB
(cells
mL1)
L
limit
U
limit
IRB
(cells
mL1)
L
limit
U
limit
MRB
(cells
mL1)
L
limit
U
limit
SRB
(cells
mL1)
L
limit
U
limit
PVP1 2004-05-04 3.9 n.a. 0.4 0.1 1.7 9.0 4.0 25.0 0.8 0.3 2.4
PVP1 2005-10-11 3.9 160.0 <0.2 1.3 0.5 3.8 1.3 0.5 3.8
PVP1 2006-04-27 3.9 24000.0 10000.0 94000.0 1.3 0.5 3.8 500.0 200.0 2000.0 1600.0 600.0 5300.0
PVP1 2006-10-12 3.9 140.0 60.0 360.0 0.4 0.1 1.7 2.3 0.9 8.6 5.0 2.0 17.0
PVP3A 2004-05-03 7.8 n.a. n.a. n.a. n.a.PVP3B 2004-05-03 3.8 n.a. 0.4 0.1 1.7 0.0 2.3 0.9 8.6
PVP4A 2004-05-04 9.6 n.a. 1.3 0.5 3.8 0.0 0.2 0.1 1.1
PVP4A 2005-10-12 10.2 800.0 300.0 2500.0 0.2 0.1 1.1 1.4 0.6 3.5 <0.2PVP4A 2006-10-10 10.2 2.7 1.2 6.7 <0.2 0.8 0.3 2.4 <0.2PVP4A:1 2006-04-27 10.2 110.0 40.0 300.0 <0.2 <0.2 0.8 0.3 2.4
PVP4A:2 2006-04-27 10.2 50.0 20.0 150.0 <0.2 <0.2 0.2 0.1 1.1
PVP4A:1/2 2006-04-27 10.2 2.2 - - 4PVP4B 2004-05-04 8.0 n.a. 1.3 0.5 3.8 2.3 0.9 8.6 1.3 0.5 3.8
PVP13 2005-10-12 5.6 500.0 200.0 1700.0 1.3 0.5 3.8 33.0 15.0 77.0 5.0 2.0 17.0
PVP13 2006-04-26 5.6 50.0 20.0 170.0 2.3 0.9 8.6 24.0 10.0 94.0 8.0 3.0 25.0
PVP13 2006-10-12 5.6 50.0 20.0 170.0 0.8 0.3 2.4 2.3 0.9 8.6 0.0PVP14 2005-10-13 9.0 0.4 0.1 1.7 <0.2 5.0 2.0 17.0 0.4 0.1 1.5
PVP14 2006-04-26 9.0 0.8 0.3 2.4 1.3 0.5 3.8 0.4 0.1 1.7 0.4 0.1 1.7
PVP14 2006-10-10 9.0 50.0 20.0 170.0 <0.2 24.0 10.0 94.0 <0.2PVP20S 2005-10-13 12.8 130.0 50.0 390.0 2.2 0.9 5.6 8.0 3.0 25.0 5.0 2.0 15.0
PVP20P 2005-10-13 12.8 2.3 0.9 8.6 0.4 0.1 1.7 2.3 0.9 8.6 3.0 1.0 12.0
PVP20 2006-04-26 12.8 ICE- COVER
PVP20 2006-10-10 12.8 300 100 1200 1.3 0.5 3.8 1600 3.0 1.0 12.0
143
Table A-9. The most probable numbers of autotrophic acetogens (AA) and methanogens (AM), heterotrophic acetogens (HA) and methanogens (HM), and methane-oxidizing bacteria (MOB) in shallow groundwater from Olkiluoto. L and U limits are the 95% confidence values. n.a. = not analysed for various reasons, for example, inapplicable because the analysis had not yet been introduced, sample turbidity, or analytical error.
Bore-
hole
sampled
(Y-M-D)
Depth
(m)AAcells
mL1
L
limit
U
limitHAcells
mL1
L
limit
U
limitAMcells
mL1
L
limit
U
limitHMcells
mL1
L
limit
U
limitMOB
cells
mL1
L
limit
U
limit
PR1 2004-05-04 6.0 160.0 <0.2 0.2 0.1 1.1 0.2 0.1 1.1 n.a.PR1 2005-10-10 6.0 50.0 20.0 170.0 50.0 20.0 170.0 <0.2 <0.2 5000 2000.0 20000
PR1 2006-04-25 6.0 500.0 200.0 2000.0 80.0 30.0 250.0 14.0 6.0 36.0 17.0 8.0 41.0 24.0 10.0 94.0
PR1 2006-10-11 6.0 50.0 20.0 170.0 8.0 3.0 25.0 0.0 0.7 0.2 2.1 17.0 7.0 48.0
PP2 2004-05-05 14.7 <0.2 <0.2 1.1 0.4 2.9 0.7 0.2 2.1 n.a.PP2 2005-10-12 14.7 110.0 40.0 300.0 2.3 0.9 8.6 <0.2 <0.2 13.0 5.0 39.0
PP2 2006-04-24 14.7 11.0 4.0 30.0 3.0 1.0 12.0 0.2 0.1 1.0 0.0 5.0 2.0 17.0
PP2 2006-10-11 14.7 2.2 0.9 5.6 8.0 3.0 25.0 <0.2 <0.2 4.3 0.9 18
PP3 2004-05-05 14.3 0.4 0.1 1.5 1.4 0.6 3.5 1.1 0.4 2.9 1.1 0.4 2.9 150 40 430
PP7 2004-05-05 16.2 5.0 2.0 17.0 5.0 2.0 17.0 6.0 3.0 18.0 3.0 1.0 12.0 4.3 0.9 18
PP8 2004-05-06 15.2 220.0 100.0 580.0 5.0 2.0 15.0 1.7 0.7 4.0 0.9 0.3 2.5
PP9 2005-10-13 14.7 1.1 0.4 2.9 0.8 0.3 2.4 <0.2 <0.2 3.0 1.0 12.0
PP9 2006-04-27 14.7 1.7 0.7 4.6 2.3 0.9 8.6 0.4 0.1 1.7 <0.2 0.9 0.3 2.4
PP9 2006-10-09 14.7 50.0 20.0 170.0 140.0 60.0 360.0 <0.2 <0.2 3.0 1.0 12.0
PP36 2005-10-10 12.1 50.0 20.0 150.0 30.0 10.0 130.0 <0.2 <0.2 2.3 0.9 8.6
PP36 2006-04-25 12.1 110.0 40.0 300.0 130.0 50.0 390.0 0.3 0.1 1.2 0.4 0.1 1.7 14.0 6.0 36.0
PP36 2006-10-09 12.1 80.0 30.0 2500.0 30.0 10.0 120.0 <0.2 <0.2 8.0 3.0 25.0
PP39 2005-10-11 14.1 130.0 50.0 390.0 50.0 20.0 170.0 3.0 1.0 12.0 <0.2 300.0 100.0 1200.0
PP39 2006-04-24 14.1 220.0 100.0 580.0 170.0 70.0 480.0 2.3 0.9 8.6 0.4 0.1 1.7 13.0 5.0 39.0
PP39 2006-10-11 14.1 1100 400.0 3000.0 1700 700 4800 2.7 1.2 6.7 2.7 1.2 6.7 280.0 120.0 690.0
144
Table A-9. Continued
Borehole sampled
(Y-M-D)
Depth
(m)AAcells
mL1
L
limit
U
limitHAcells
mL1
L
limit
U
limitAMcells
mL1
L
limit
U
limitHMcells
mL1
L
limit
U
limitMOB
cells
mL1
L
limit
U
limit
PVP1 2004-05-04 3.9 <0.2 11.0 4.0 30.0 1.3 0.5 3.8 <0.2 <0.2PVP1 2005-10-11 3.9 30.0 10.0 120.0 30.0 10.0 130.0 <0.2 <0.2 5.0 2.0 17.0
PVP1 2006-04-27 3.9 1600.0 1600.0 <0.2 <0.2 14.0 6.0 36.0
PVP1 2006-10-12 3.9 30.0 10.0 120.0 23.0 9.0 86.0 <0.2 <0.2 1.7 0.7 4.6
PVP3A 2004-05-03 7.8 n.a. n.a. n.a. n.a. n.a.PVP3B 2004-05-03 3.8 30.0 10.0 130.0 30.0 10.0 130.0 3.4 1.6 8.0 3.3 1.5 7.7 11000 18000 41000
PVP4A 2004-05-04 9.6 n.a. n.a. 3.4 1.6 8.0 0.4 0.1 1.7 460 90 2000
PVP4A 2005-10-12 10.2 110.0 40.0 300.0 130.0 50.0 390.0 <0.2 <0.2 300.0 100.0 1200.0
PVP4A 2006-10-10 10.2 2.2 0.9 5.6 7.0 3.0 21.0 <0.2 <0.2 0.2 0.1 1.1
PVP4A:1 2006-04-27 10.2 30.0 10.0 120.0 30.0 10.0 120.0 11.0 4.0 30.0 <0.2 50.0 20.0 170.0
PVP4A:2 2006-04-27 10.2 80.0 30.0 250.0 3.0 1.0 12.0 <0.2 <0.2 24.0 10.0 94.0
PVP4A:1/2 2006-04-27 10.2 0.38 10 - - 2.1PVP4B 2004-05-04 8.0 n.a. n.a. 0.8 0.3 2.4 0.8 0.3 2.4 n.a.PVP13 2005-10-12 5.6 240.0 100.0 940.0 90.0 40.0 250.0 0.8 0.3 2.4 <0.2 2.3 0.9 8.6
PVP13 2006-04-26 5.6 220.0 100.0 580.0 80.0 30.0 250.0 2.2 0.9 5.6 <0.2 1.3 0.5 3.8
PVP13 2006-10-12 5.6 30.0 10.0 120.0 22.0 10.0 58.0 <0.2 <0.2 0.2 0.1 1.1
PVP14 2005-10-13 9.0 5.0 2.0 17.0 3.0 1.0 12.0 <0.2 <0.2 n.a.PVP14 2006-04-26 9.0 2.7 1.2 6.7 2.3 0.9 8.6 <0.2 <0.2 1.3 0.5 3.8
PVP14 2006-10-10 9.0 30.0 10.0 120.0 24.0 10.0 94.0 <0.2 <0.2 230.0 90.0 860.0
PVP20S 2005-10-13 12.8 1600.0 600.0 5300.0 30.0 10.0 130.0 <0.2 <0.2 2.3 0.9 8.6
PVP20P 2005-10-13 12.8 170.0 70.0 480.0 30.0 10.0 120.0 <0.2 <0.2 1.2 0.5 2.9
PVP20 2006-04-26 12.8 ICE COVER
PVP20 2006-10-10 12.8 2800 1200 6900 2200 1000 5800 0.2 0.1 1.1 <0.2 5.0 2.0 17.0
145
Table A-10. Biomass determinations for deep groundwater in Olkiluoto. TNC = total number of cells, SD = standard deviation, n = number ofobservations, CHAB = cultivable heterotrophic aerobic bacteria, MPN = sum of all most probable number of cells values (see Table A-11), and n.a. = not analysed for various reasons, for example, inapplicable because the analysis had not yet been introduced, sample turbidity, or analytical error.
Borehole sampled
(Y-M-D)
Section
upper–lower
(m)
Mid
elevation,
z
(m)
TNC
(cells
mL1)
SD n ATP
(amol
mL1)
SD n CHAB
(cells
mL1)
SD n CHAB/
TNC
(%)
ATP/
TNC
MPN/
TNC
(%)
OL-KR2 2004-12-20 328.5–330.5 306.2 120000 24000 6 206000 40500 3 n.a. 1.717 0.70
OL-KR6 2006-05-11 422–425 328.4 100000 7800 2 66800 1520 3 120000 5600 3 120.00 0.668 30.25
OL-KR6 2006-06-26 125–130 94.1 2700 1400 3 5720 1390 3 503 187 3 18.63 2.119 20.00
OL-KR6 2006-08-22 135–137 101.8 23000 3900 3 15300 410 3 16300 4730 3 70.87 0.665 22.55
OL-KR6 2006-10-16 98.5–100.5 73.7 4500 1300 3 3090 170 3 1090 21 3 24.22 0.687 1.08
OL-KR7 2005-03-01 275.5–289.5 249.4 74000 15000 6 15800 210 3 n.a. 0.214 0.02
OL-KR8 2005-10-25 77.0–84.0 57.3 130000 27000 6 6960 440 3 497 21 3 0.38 0.054 0.16
OL-KR8 2006-06-06 302.0–310.0 260.7 11000 2800 3 5730 320 3 820 123 3 7.45 0.521 1.89
OL-KR10 2005-02-21 115.5–118.5 106.0 140000 21000 6 20800 10900 3 n.a. 0.149 0.22
OL-KR10 2006-06-19 326.0–328.0 316.0 110000 15000 3 25000 1800 3 1390 21 3 1.26 0.227 0.32
OL-KR13 2004-10-12 362.0–365.0 294.0 110000 27000 6 82200 9580 3 n.a. 0.00 0.747 0.07
OL-KR13 2006-03-14 362.0–365.0 294.0 27000 14000 6 15580 200 3 16300 3400 3 60.37 0.577 3.56
OL-KR19 2004-11-08 525.5–539.5 449.6 150000 25000 6 n.a. n.a. 0.17
OL-KR27 2004-11-09 247.0–264.0 193.5 29000 14000 6 36400 4590 3 n.a. 1.255 0.05
OL-KR27 2005-01-17 503.0–506.0 391.7 21000 4000 6 n.a. n.a. - 0.12
OL-KR31 2006-10-24 143.0–146.0 122.4 19000 2600 3 10929 940 3 4230 351 3 22.26 0.575 6.20
OL-KR32 2006-01-10 50.0–52.0 34.6 26000 7600 6 23400 1890 3 2430 379 3 9.35 0.900 5.30
OL-KR33 2006-01-24 95.0–107.0 70.6 40000 15000 5 6970 490 3 10 10 3 0.03 0.174 0.37
OL-KR37 2006-11-28 166–176 111.6 14000 730 3 8020 200 3 3070 473 3 21.93 0.573 21.66
OL-KR39 2006-04-03 403.0–406.0 344.8 22000 7600 3 7440 260 3 180 25 3 0.82 0.338 1.60
OL-KR39 2006-05-30 108.0–110.0 88.2 21000 960 3 13080 750 3 3150 778 2 15.00 0.623 1.83
146
Table A-11. The most probable numbers of nitrate-, iron-, manganese-, and sulphate-reducing bacteria (NRB, IRB, MRB, and SRB, respectively), autotrophic acetogens (AA) and methanogens (AM), heterotrophic acetogens (HA) and methanogens (HM), and methane-oxidizing bacteria (MOB) in deep groundwater from Olkiluoto. L and U limits are the 95% confidence values. n.a. = not analysed for various reasons, for example, inapplicable because the analysis had not yet been introduced, sample turbidity, or analytical error.
Borehole sampled
(Y-M-D)
Section
upper–lower
(m)
Mid
elevation,
z
(m)
NRB
(cells
mL1)
L
limit
U
limit
IRB
(cells
mL1)
L
limit
U
limit
MRB
(cells
mL1)
L
limit
U
limit
SRB
(cells
mL1)
L
limit
U
limit
OL-KR2 2004-12-20 328.5–330.5 306.2 n.a. 300 100.0 1300.0 300.0 100.0 1300 <0.2
OL-KR6 2006-05-11 422–425 328.4 30000 10000.0 130000 28.0 12.0 69.0 30.0 10.0 120.0 90.0 30.0 290.0
OL-KR6 2006-06-26 125–130 94.1 500.0 200.0 1500.0 2.3 0.9 8.6 2.3 0.9 8.6 1.3 0.5 3.8
OL-KR6 2006-08-22 135–137 101.8 5000.0 2000.0 20000.0 <0.2 170.0 80.0 410.0 1.3 0.5 3.8
OL-KR6 2006-10-16 98.5–100.5 73.7 28.0 12.0 69.0 2.3 0.9 8.6 0.2 0.1 1.1 3.0 1.0 12.0
OL-KR7 2005-03-01 275.5–289.5 249.4 n.a. <0.2 <0.2 <0.2OL-KR8 2005-10-25 77.0–84.0 57.3 110.0 40.0 300.0 0.2 0.1 1.1 0.4 0.1 1.7 3.0 1.0 12.0
OL-KR8 2006-06-06 302.0–310.0 260.7 80.0 30.0 250.0 0.4 0.1 1.7 <0.2 7.0 3.0 21.0
OL-KR10 2005-02-21 115.5–118.5 106.0 n.a. <0.2 <0.2 0.2 0.1 1.1
OL-KR10 2006-06-19 326.0–328.0 316.0 240.0 100.0 940.0 <0.2 <0.2 24.0 10.0 94.0
OL-KR13 2004-10-12 362.0–365.0 294.0 n.a. 0.8 0.3 2.8 <0.2 <0.2OL-KR13 2006-03-14 362.0–365.0 294.0 800.0 300.0 2500.0 5.0 2.0 17.0 70.0 30.0 210.0 13.0 5.0 39.0
OL-KR19 2004-11-08 525.5–539.5 449.6 n.a. <0.2 <0.2 <0.2OL-KR27 2004-11-09 247.0–264.0 193.5 n.a. 1.7 0.7 4.6 1.1 0.4 2.9 <0.2OL-KR27 2005-01-17 503.0–506.0 391.7 n.a. <0.2 <0.2 <0.2OL-KR31 2006-10-24 143.0–146.0 122.4 1100.0 400.0 3000.0 0.8 0.3 2.4 22.0 10.0 58.0 1.3 0.5 3.8
OL-KR32 2006-01-10 50.0–52.0 34.6 1300.0 500.0 3900.0 24.0 10.0 94.0 24.0 10.0 94.0 0.4 0.1 1.7
OL-KR33 2006-01-24 95.0–107.0 70.6 8.0 3.0 25.0 80.0 30.0 250.0 22.0 9.0 56.0 7.0 2.0 21.0
OL-KR37 2006-11-28 166–176 111.6 3000.0 1000.0 12000.0 0.4 0.1 1.7 2.3 0.9 8.6 3.0 1.0 12.0
OL-KR39 2006-04-03 403.0–406.0 344.8 300.0 100.0 1200.0 11.0 4.0 30.0 2.2 0.9 5.6 1.3 0.5 3.8
OL-KR39 2006-05-30 108.0–110.0 88.2 240.0 100.0 940.0 0.7 0.2 2.1 0.4 0.1 1.7 11.0 4.0 30.0
147
Table A-11. Continued.
Borehole sampled
(Y-M-D)
Section
upper–lower
(m)
Mid elevation,
z
(m)
AA(cells
mL1)
L
limit
U
limitHA(cells
mL1)
L
limit
U
limitAM(cells
mL1)
L
limit
U
limitHM(cells
mL1)
L
limit
U
limit
OL-KR2 2004-12-20 328.5–330.5 306.2 110.0 40.0 300.0 130.0 50.0 390.0 0.4 0.1 1.7 2.3 0.9 8.6
OL-KR6 2006-05-11 422–425 328.4 24.0 10.0 94.0 80.0 30.0 250.0 <0.2 0.2 0.1 1.1
OL-KR6 2006-06-26 125–130 94.1 17.0 7.0 48.0 17.0 7.0 48.0 <0.2 <0.2OL-KR6 2006-08-22 135–137 101.8 2.3 0.9 8.6 13.0 5.0 39.0 <0.2 <0.2OL-KR6 2006-10-16 98.5–100.5 73.7 7.0 3.0 21.0 8.0 3.0 25.0 <0.2 <0.2OL-KR7 2005-03-01 275.5–289.5 249.4 3.0 1.0 12.0 8.0 3.0 25.0 5.0 2.0 17.0 2.3 0.9 8.6
OL-KR8 2005-10-25 77.0–84.0 57.3 70.0 30.0 210.0 30.0 10.0 120.0 <0.2 <0.2OL-KR8 2006-06-06 302.0–310.0 260.7 50.0 20.0 170.0 70.0 30.0 210.0 0.2 0.1 1.1 0.2 0.1 1.1
OL-KR10 2005-02-21 115.5–118.5 106.0 130.0 50.0 390.0 170.0 70.0 480.0 <0.2 2.3 0.9 8.6
OL-KR10 2006-06-19 326.0–328.0 316.0 30.0 10.0 120.0 50.0 20.0 170.0 0.2 0.1 1.1 2.3 0.9 8.6
OL-KR13 2004-10-12 362.0–365.0 294.0 24.0 10.0 94.0 13.0 5.0 38.0 13.0 5.0 39.0 24.0 10.0 94.0
OL-KR13 2006-03-14 362.0–365.0 294.0 50.0 20.0 200.0 24.0 10.0 94.0 <0.2 <0.2OL-KR19 2004-11-08 525.5–539.5 449.6 170.0 80.0 410.0 80.0 30.0 250.0 2.3 0.9 8.6 2.3 0.9 8.6
OL-KR27 2004-11-09 247.0–264.0 193.5 0.4 0.1 1.7 7.0 2.0 21.0 1.3 0.5 3.8 2.3 0.9 8.6
OL-KR27 2005-01-17 503.0–506.0 391.7 0.4 0.1 1.7 1.3 0.5 3.8 0.2 0.1 1.1 24.0 10.0 94.0
OL-KR31 2006-10-24 143.0–146.0 122.4 30.0 10.0 120.0 23.0 9.0 56.0 0.2 0.1 1.1 <0.2OL-KR32 2006-01-10 50.0–52.0 34.6 17.0 7.0 48.0 13.0 5.0 39.0 <0.2 <0.2OL-KR33 2006-01-24 95.0–107.0 70.6 24.0 10.0 94.0 8.0 3.0 25.0 <0.2 <0.2OL-KR37 2006-11-28 166–176 111.6 24.0 10.0 94.0 3.0 10.0 12.0 <0.2 <0.2OL-KR39 2006-04-03 403.0–406.0 344.8 30.0 10.0 130.0 8.0 3.0 25.0 <0.2 <0.2OL-KR39 2006-05-30 108.0–110.0 88.2 50.0 20.0 170.0 80.0 30.0 250.0 0.2 0.1 1.1 2.3 0.9 8.6
148
149
ANALYSIS OF DISSOLVED GASES IN GROUNDWATER
Samples can consist of any combination of gas only, gas and groundwater in separate phases, or groundwater containing dissolved gas, all in closed pressure-safe containers. The sample is transferred to a vacuum container and any gas in the water is boiled off under vacuum (i.e., water vapour pressure) at room temperature (Figure A-1). After this extraction, the gas is compressed and transferred to a 10 mL syringe (SGE Analytical Science, Victoria, Australia) and the volumes of extracted gas and water are measured. The captured gas is subsequently transferred to a 6.6-mL glass vial stoppered with a butyl rubber stopper sealed with an aluminium crimp seal (Figure A-1). Large gas samples can be transferred to a 27-mL vial instead. The vial is evacuated and flushed twice with nitrogen, in two cycles, and is left at high vacuum (10 4 Bar). Copper sulphate (dehydrant) is added to adsorb any traces of water remaining in the gas (water causes troublesome baseline drifts in the gas chromatographs). The vials are stored under water. Any leakage will result in the blue, dry copper sulphate turning pink.
Figure A-1. The 500-mL cylindrical gas extractor with a 6.6-mL sample vial attached, lower right. Gas collection syringes are visible below the metallic SGE 6-port valves. The blue box is the manometer used to measure pressure in the samples. The gray cylinder is the cryo-trap for removing moisture from samples.
Air contamination during extraction is difficult to avoid. New adaptor equipment has been developed and found to be very efficient. Apparently, any remaining
150
contamination can be explained by problems with the PAVE samplers. Currently,a few a 100 uL air is intruding the extraction procedure, which does not occur when dummies of pure nitrogen are extracted. There is no oxygen in the analysed deep groundwater samples obtained using PAVE, so air contamination was subtracted from the results before recording the data.
Figure A-2. The Varian Star 3400CX gas chromatograph is standing closest to the manometers, in the centre of the image. The blue KAPPA V gas chromatograph is visible behind the Varian.
Uncertainties of the used methods
Volumes of 1–1000 µL are injected into the gas chromatograph. The volume used is adjusted according to the sensitivity range of the particular instrument and detector. Several injections are usually needed to determine the proper amount of each gas to inject.
The precision of the methods used is the subject of ongoing testing at our laboratory. Recently, we attached three samplers to one groundwater circulation at borehole KJ0052F01 at the MICROBE laboratory at Äspö (see the SKB International Progress Report IPR-05-05 for a detailed description of this laboratory; Pedersen 2005a). The pressure vessel used, the PVB sampler, represents the Swedish analogue of the Finnish PAVE sampler. The results are given in the last section of this method description. The main conclusions were:
151
The precision of the extractions is currently approximately ± 6% (Table A-12).
The uncertainty of the instruments and repeated injections is low, typically 0–4% (Table A-13).
The calibration gases used have a maximum accepted mixing uncertainty of ± 2%.
In total, the analytical uncertainty is currently a maximum of ± 12%.
Set-up and calibrations
Two gas chromatographs are currently in use, as shown in Figure A-2.
The chromatographs are calibrated and tested using the four “gas mixtures described below. Multiple points are used for the Varian Star 3400CX gas chromatograph (Varian, Palo Alto, CA, USA), while the KAPPA V gas chromatograph uses single-point calibrations. Calibration gases are analysed immediately before analysis of samples, and the calibration results are used in calculating the concentrations of the gases in the samples.
Special gas 1 (Linde Gas, Pullach, Germany), AGA, certificate no: 28810-3:
He 25,700 ppm H2 964 ppm O2 10,900 ppm Nitrogen 962,436 ppm
Special gas 2 (Linde Gas), AGA, certificate no: 28757-1:
Ar 1000 ppm CH4 2740 ppm CO2 1040 ppm CO 9.75 ppm Nitrogen 995,210 ppm
Special gas 3 (Linde Gas), AGA, certificate no: 28749-1:
C2H6 253 ppm C2H4 257 ppm C2H2 248 ppm C3H8 252 ppm C3H6 238 ppm Nitrogen 998,752 ppm
Special gas 4 (Linde Gas), AGA, certificate no: 30008-1:
H2 24.6 ppm CO 24.9 ppm Nitrogen 999,950 ppm
152
Analysis of gas
Low concentrations of hydrogen (<20 ppm) were analysed on a KAPPA-5/E-002 analyser (Trace Analytical, Menlo Park, CA, USA) gas chromatograph equipped with a 156 1/16-inch stainless steel HayeSep column in line with a 31 1/8-inch stainless steel molecular sieve 5A column, which was subsequently attached to a reductive gas detector (RGD). Nitrogen was used as the carrier gas. The sample was injected into a 1000-µL injection loop. The sample usually had to be diluted to reach the detection range of the instrument. This instrument has the most sensitive hydrogen detector on the market. Calibration gas 4 was used.
The detection limit of the instrument with a 0.1-mL injection loop is 10–12 L (1 ppb).
High concentrations of hydrogen (>20 ppm) were analysed on a Varian Star 3400CX gas chromatograph using a thermal conductivity detector (TCD) with an oven temperature of 65°C, a detector temperature of 120°C, and a filament temperature of 250°C. The hydrogen gas was separated using a Porapak-Q column (2 m 1/8 inch diameter; Agilent Technologies) followed by a molecular sieve 5A column (6 m 1/8 inch) with argon as the carrier gas. Calibration gases 1 and 2 are used.
The detection limit of the instrument with a 250-µL injection loop is 5 10–9 L (20 ppm).
Carbon monoxide was analysed on a KAPPA-5/E-002 analyser gas chromatograph equipped with a 156 1/16-inch stainless steel HayeSep column in line with a 31 1/8-inch stainless steel molecular sieve 5A column, which was subsequently attached to a reductive gas detector (RGD). Nitrogen was used as the carrier gas. The sample was injected into a 1000-µL injection loop. The sample usually had to be diluted to reach the detection range of the instrument. This instrument has the most sensitive carbon monoxide detector on the market. These results were compared with those obtained using the Varian Star 3800CX analyser and reported when they agreed.
The detection limit of the instrument with a 0.1-mL injection loop is 10–12 L (1 ppb).
Helium was analysed on a Varian Star 3400CX gas chromatograph using a thermal conductivity detector (TCD) with an oven temperature of 65°C, a detector temperature of 120°C, and a filament temperature of 250°C. The helium gas was separated using a Porapak-Q column (2 m 1/8 inch diameter) followed by a molecular sieve 5A column (6 m 1/8 inch) with argon as the carrier gas.
The detection limit of the instrument with a 250-µL injection loop is 5 10–9 L (20 ppm).
Nitrogen was analysed on a Varian Star 3400CX gas chromatograph using a thermal conductivity detector (TCD) with an oven temperature of 65°C, a detector temperature of 120°C, and a filament temperature of 250°C. The nitrogen gas was separated using a Porapak-Q column (2 m 1/8 inch diameter) followed by a molecular Sieve 5A column (6 m 1/8 inch). Argon or helium can be used as the carrier gas. The results obtained
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using argon were compared with those obtained using helium and reported when they agreed.
The detection limit of the instrument with a 250-µL injection loop is 25 10–9 L (100 ppm).
Oxygen was analysed on a Varian Star 3400CX gas chromatograph using a thermal conductivity detector (TCD) with an oven temperature of 65°C, a detector temperature of 120°C, and a filament temperature of 250°C. The oxygen gas was separated using a Porapak-Q column (2 m 1/8 inch diameter) followed by a molecular sieve 5A column (6 m 1/8 inch) with argon as the carrier gas.
The detection limit of the instrument with a 250-µL injection loop is 25 10–9 L (100 ppm).
Argon was analysed on a Varian Star 3400CX gas chromatograph using a thermal conductivity detector (TCD) with an oven temperature of 65°C, a detector temperature of 120°C, and a filament temperature of 250°C. The argon gas was separated using a Porapak-Q column (2 m 1/8 inch diameter) followed by a molecular sieve 5A column (6 m 1/8 inch) with helium as the carrier gas. Argon was very difficult to separate from oxygen. The strategy used was to analyse the total amount of oxygen and argon with this configuration; then the result was reduced by the amount of oxygen analysed, using argon as the carrier gas.
The detection limit of the instrument with a 250-µL injection loop is 25 10–9 L (100 ppm).
Carbon dioxide was analysed on a Varian Star 3400CX gas chromatograph using a flame ionization detector (FID) with an oven temperature of 65°C and a detector temperature of 200°C. The carbon dioxide gas was separated using a Porapak-Q column (2 m 1/8 inch diameter) and transformed to methane using a 10% Ni2NO3
“methanizer” fed with hydrogen gas (9.375 1/8 inch diameter, temperature 370°C). Carbon dioxide was finally analysed as methane on the FID with nitrogen as the carrier gas. This configuration used a 156 1/16-inch stainless steel HayeSep and an FID detector.
The detection limit of the instrument with a 250-µL injection loop is 0.1 10–9 L (0.4 ppm).
Methane was analysed on a Varian Star 3400CX gas chromatograph using a flame ionization detector (FID) with an oven temperature of 65°C and a detector temperature of 200°C. The methane gas was separated using a Porapak-Q column (2 m 1/8 inch diameter) and analysed on the FID with nitrogen as the carrier gas. This configuration used a 156 1/16-inch stainless steel HayeSep and a FID detector.
High concentrations of methane, above 1%, require very small injection volumes, with nitrogen as the carrier gas, on the FID. The use of a small injection volume
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increases the uncertainty of the results. Therefore, the sensitivity of the analysis was reduced as required by analysing methane with helium as the carrier gas and using the TCD. The results obtained using an FID were compared with those obtained using a TCD and reported when they agreed.
The detection limit of the instrument with a 250-µL injection loop is 0.1 10–9 L (0.4 ppm).
Ethane, ethane + ethylene were analysed on a Varian Star 3400CX gas chromatograph using a flame ionization detector (FID) with an oven temperature of 65°C and a detector temperature of 200°C. The ethane, ethaneand ethylene, gases were separated using a Porapak-Q column (2 m 1/8 inch diameter) and analysed on the FID with nitrogen as the carrier gas. This configuration used a 156 1/16-inch stainless steel HayeSep and a FID detector.
Ethene and ethylene cannot be separated using the present configuration (i.e., a Porapack-Q column).
The detection limit of the instrument with a 250-µL injection loop is 0.1 10–9 L (0.4 ppm).
Reproducibility tests
Three pressure samplers were attached on 2005-11-24 to one groundwater circulation at borehole KJ0052F01 at the MICROBE laboratory, at a depth of 450 m at the Äspö HRL. They were left overnight at a flow rate of 30 mL/min and detached in the morning of 2005-11-25. The samplers were transported to the laboratory in Göteborg and extracted on 2005-12-13. The extraction data are shown in Table A-12.
The volume of water obtained was a function of the pressure in the gas compartment of the pressure vessel. The variability was 2%. The variability of the volume of gas extracted, reduced by the water volume variability, was 6%. This should be the variability of the extraction, but as the variability of the pressure vessel was unknown, this number simply represents a maximum value. The volumes extracted and analysed varied by approximately 6% as well. The air contamination was small, less than 0.2 mL per extraction, the lowest amount of contamination being 0.053 mL.
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Table A-12. Measured and calculated variables for three pressure sampler replicates attached to a groundwater circulation at the MICROBE laboratory.
Measured/calculated variable KJ52F01-1 KJ52F01-2 KJ52F01-3 Average (±
SD%)
Volume of water 176 168 170 171 (± 2%)
Volume of extracted gas 10.4 9.0 10.8 10.1 (± 8%)
1. Volume of extracted gas /L 61.2 53.6 61.4 58.7 (± 6.2%)
2. Volume of analysed gas with air /L
60.1 52.4 60.8 57.8 (± 6.6%)
3. Volume of analysed gas without air /L
59.4 52.1 59.7 57.1 (± 6.2%)
4. Air contamination, % 1.13 0.59 1.74 1.15 (± 41%)
Volume of air in the extracted gas, L
118 53 188 120 (± 46%)
The reproducibility of repeated injections from the sample vials is shown in Table A-13. This variability ranges from 0 to 3.8%. If the extraction uncertainty is 6% and the injection precision is a maximum of 4%, then we have 10% uncertainty in the analysis procedure.
Table A-13. Repeated injections into the gas chromatograph, a and b, for analysis of carbon gases.
Gas KJ52F01-1 a KJ52F01-1 b Average (± SD%)
Carbon dioxide 63.1 64.1 63.6 (± 0.8%)
Methane 333 317 325 (± 2.5%)
Ethane 0.35 0.37 0.36 (± 1.4%)
KJ52F01-2 a KJ52F01-2 b Average (± SD%)
Carbon dioxide 31.5 33 32.3 (± 2.3%)
Methane 263 284 274 (± 3.8%)
Ethane 0.12 0.120 0.12 (± 0%)
KJ52F01-3 a KJ52F01-3 b Average (± SD%)
Carbon dioxide 57.5 59.3 58.4 (± 1.5%)
Methane 379 407 393 (± 3.5%)
Ethane 0.18 0.19 0.19 (± 2.6%)
The analysis results are shown in Table A-14. In general, the table shows decreasing variability with increasing amounts of gas analysed. The obtained variability can have several explanations. First, the variability may of course be a result of analytical errors.
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Second, variability in the status of the pressure containers may influence the variability of the gas data. Third, it was assumed that three pressure samplers in series would collect identical gas concentrations if those concentrations remained stable over time in the flowing groundwater. This assumption has not yet been demonstrated. On the contrary, multiple analyses from the MICROBE site suggest an inherent variability in dissolved gas concentrations in the MICROBE groundwater (Pedersen 2005a). It may actually be that gas concentrations vary from volume to volume of groundwater in an aquifer.
Table A-14. Measured gas components for three pressure samplers attached to a groundwater circulation at the MICROBE laboratory. The data refer to the ppm of each gas in the extracted gas (not in the groundwater).
Gas KJ52F01-1
(ppm)
KJ52F01-2
(ppm)
KJ52F01-3
(ppm)
Average (±
SD%)
Hydrogen 87.2 18.2 24.3 43.2 (± 72%)
Helium 69,000 79,100 95,000
81030 (± 13.2%)
Argon 2170 2150 5190 3170 (± 45%)
Nitrogen894,000 885,000 865,000
881300 (± 1.4%)
Carbon monoxide 21.5 15.9 35.3 24.2 (± 33.7%)
Carbon dioxide 1030 587 937 851 (± 22.4%)
Methane 5450 4910 6170 5510 (± 9.4%)
Ethane 5.680 2.260 2.970 3.637 (± 35%)
Ethene + Ethylene <0.4 <0.4 <0.4 -
Propane <0.4 <0.4 <0.4 -
Propene <0.4 <0.4 <0.4 -
1 (1)
LIST OF REPORTS
POSIVA-REPORTS 2008
POSIVA 2008-01 KBS-3H design Description 2007 Jorma Autio, Pekka Anttila, Lennart Börgesson, Torbjörn Sandén,
Paul-Erik Rönnqvist, Erik Johansson, Annika Hagros, Magnus Eriksson, Bo Halvarsson, Jarno Berghäll, Raimo Kotola, Ilpo Parkkinen
ISBN 978-951-652-160-5
POSIVA 2008-02 Microbiology of Olkiluoto Groundwater, 2004–2006 Karsten Pedersen, Microbial Analytics Sweden AB
ISBN 978-951-652-161-2
: