POSIVA 2008-02
Microbiology of Olkiluoto Groundwater
2004 – 2006
Karsten Pedersen
February 2008
POSIVA
OY
Olkiluoto
FIN-27160
EURAJOKI,
FINLAND
Phone (02) 8372 31 (nat.), (+358-2-) 8372 31 (int.)
Fax (02) 8372 3709 (nat.), (+358-2-) 8372 3709 (int.)
POSIVA 2008-02
Microbiology of Olkiluoto Groundwater
2004 – 2006
Karsten Pedersen
Microbial Analytics Sweden AB
February 2008
Base maps: ©National Land Survey, permission 41/MYY/08
POSIVA
OY
Olkiluoto
FI-27160
EURAJOKI,
FINLAND
Phone (02) 8372 31 (nat.), (+358-2-) 8372 31 (int.)
Fax (02) 8372 3709 (nat.), (+358-2-) 8372 3709 (int.)
ISBN 978-951-652-161-2
ISSN 1239-3096
The conclusions and viewpoints presented in the report are
those of author(s) and do not necessarily coincide
with those of Posiva.
Posiva-raportti – Posiva Report
Raportin tunnus – Report code
POSIVA 2008-02
Posiva Oy
Olkiluoto
FI-27160 EURAJOKI, FINLAND
Puh. 02-8372 (31) – Int. Tel. +358 2 8372 (31)
Julkaisuaika – Date
February 2008
Tekijä(t) – Author(s)
Toimeksiantaja(t) – Commissioned by
Karsten Pedersen,
Microbial Analytics Sweden AB
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, sulphatereducing bacteria
ISBN
ISSN
ISBN 978-951-652-161-2
Sivumäärä – Number of pages
156
ISSN 1239-3096
Kieli – Language
English
Posiva-raportti – Posiva Report
Raportin tunnus – Report code
POSIVA 2008-02
Posiva Oy
Olkiluoto
FI-27160 EURAJOKI, FINLAND
Puh. 02-8372 (31) – Int. Tel. +358 2 8372 (31)
Julkaisuaika – Date
Helmikuu 2008
Tekijä(t) – Author(s)
Toimeksiantaja(t) – Commissioned by
Karsten Pedersen,
Microbial Analytics Sweden AB
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 mikrobiologista, 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
ISSN
ISBN 978-951-652-161-2
Sivumäärä – Number of pages
156
ISSN 1239-3096
Kieli – Language
Englanti
1
TABLE OF CONTENTS
ABSTRACT
TIIVISTELMÄ
PREFACE
................................................................................................................ 5
1
INTRODUCTION .................................................................................................. 7
1.1
Research, development, and technical design programme: TKS-2003.......... 7
1.1.1
TKS-2003 Geogases and microbes present at Olkiluoto .......................... 7
1.1.2
TKS-2006 Hydrogeochemistry ............................................................... 9
1.2
This work......................................................................................................... 9
1.3
Microbes – what are they?............................................................................ 10
1.3.1
Bacteria ................................................................................................... 11
1.3.2
Archaea................................................................................................... 12
1.3.3
Unicellular fungi....................................................................................... 13
1.3.4
Unicellular animals .................................................................................. 14
1.3.5
Unicellular photosynthetic organisms...................................................... 14
1.3.6
Viruses .................................................................................................... 18
1.4
Microbial processes ...................................................................................... 20
1.4.1
Closed systems....................................................................................... 21
1.4.2
Open systems ......................................................................................... 22
1.4.3
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........ 27
2.1.1
Sampling point descriptions .................................................................... 27
2.1.2
Packer control tests with nitrogen ........................................................... 27
2.1.3
Sterilization of borehole pumps............................................................... 28
2.1.4
Test for reproducibility of groundwater chemistry and microbiology over
time ......................................................................................................... 29
2.1.5
Sample collection for microbiological analyses....................................... 29
2.2
Sampling groundwater from deep boreholes ................................................ 29
2.2.1
Packer-equipped deep boreholes sampled for microbiology .................. 30
2.2.2
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 ............................ 33
2.3.4
Sampling and analysis of dissolved gas ................................................. 34
2.4
Microbiological analyses ............................................................................... 36
2.4.1
Determining total number of cells............................................................ 36
2.4.2
ATP analysis ........................................................................................... 36
2.4.3
Determining cultivable aerobic bacteria .................................................. 37
2.4.4
Preparing media for most probable numbers of cultivable anaerobic
microorganisms....................................................................................... 38
2
2.4.5
2.4.6
2.4.7
Inoculations and analysis for anaerobic microorganisms........................ 38
Inoculations and analysis for aerobic methane-oxidizing bacteria .......... 39
Quality controls for the most probable number analysis ......................... 42
3
RESULTS ........................................................................................................... 43
3.1
Analysis of physical and chemical parameters ............................................. 43
3.1.1
Field measurements of physical parameters .......................................... 43
3.1.2
Chemical analyses of groundwater ......................................................... 44
3.2
Sampling, extraction, and analysis of gas..................................................... 49
3.2.1
Dissolved gas in shallow groundwater – comments on the methods...... 49
3.2.2
Dissolved gas in deep groundwater – comments on the methods.......... 49
3.2.3
Distribution of gases in Olkiluoto groundwater........................................ 51
3.3
Analysis of biological parameters ................................................................. 60
3.3.1
Sterilization of borehole pumps............................................................... 60
3.3.2
Comparison of sampling using the SOLINST sampler and using the
borehole pump ........................................................................................ 61
3.3.3
Test for reproducibility of groundwater microbiology over time ............... 61
3.3.4
Tests for reproducibility of the pressure vessel method.......................... 61
3.3.5
Biomass determinations.......................................................................... 62
3.3.6
Cultivable heterotrophic aerobic bacteria................................................ 63
3.3.7
Most probable number of metabolic groups of bacteria .......................... 64
4
DISCUSSION...................................................................................................... 75
4.1
Sampling procedures for shallow groundwater ............................................. 75
4.1.1
Selection of sampled shallow groundwater boreholes ............................ 75
4.1.2
Sampling of shallow groundwater ........................................................... 76
4.1.3
The oxygen blockage packer test ........................................................... 77
4.1.4
Sterilization of borehole pumps............................................................... 77
4.1.5
Comparison of sampling using the SOLINST sampler and using the
borehole pump ........................................................................................ 77
4.2
Sampling procedures for deep groundwater microbiology............................ 78
4.3
Evaluating the analysis methods .................................................................. 79
4.3.1
Analysis of physical parameters.............................................................. 80
4.3.2
Chemical parameters .............................................................................. 80
4.3.3
Microbiological parameters ..................................................................... 81
4.4
Geochemical conditions of the investigated aquifers .................................... 86
4.4.1
Physical parameters................................................................................ 87
4.4.2
Chemistry dissolved solids................................................................... 88
4.4.3
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 ................................................ 96
4.6.1
Aerobic processes................................................................................... 97
4.6.2
Anaerobic processes............................................................................... 98
4.7
Microbial processes in deep groundwater .................................................... 98
4.7.1
Aerobic processes................................................................................... 98
4.7.2
Anaerobic processes............................................................................. 100
4.8
Relevance of microbiological processes to ONKALO ................................. 104
4.8.1
Oxygen reduction and maintenance of anoxic and reduced conditions 104
4.8.2
Bio-corrosion of construction materials ................................................. 105
4.8.3
Bio-mobilization and bio-immobilization of radionuclides, and the effects
of microbial metabolism on radionuclide mobility.................................. 106
3
REFERENCES ........................................................................................................... 107
A.
APPENDIX........................................................................................................ 115
4
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
6
7
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:
x Oxygen reduction and maintenance of anoxic and reduced conditions
x Bio-corrosion of construction materials
x 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
8
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.
Borehole
cells mL1
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
b
Below detection limit (0.2 cells mL1).
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 L1), 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 sulphaterich zone, as indicated by a few low 13CH4 values. Methane concentrations were several
hundreds of mL L1 in deep saline groundwater at Olkiluoto. Bacterial methane
formation was evident deep in the bedrock, but insufficient isotopic data on dissolved
9
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 L1 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
10
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 36 May 2004,
1014 October 2005, 2428 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, Brock
Biology 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 Pm 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 Archaea
are 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.
11
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 (60–113qC), 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 (0–60qC) 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
12
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 15–20qC, 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 80qC to 50qC 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 105qC and it survives in temperatures of up to 113qC. Remarkably,
this species “freezes” to death when the temperature goes below below 90qC. Many
other genera of Archaea grow best at approximately 100qC. 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.
13
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 Pm (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 Pm 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 Pm) 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
0.20
0.25
C
0.15
0.20
-1
Growth rate (h )
-1
Growth rate (h )
A
0.10
0.05
0.15
0.10
0.05
0
0
10
20
30
40
50
0
60
Incubation temperature (°C)
0
0.25
0.50
0.75
1.00
1.25
1.5
NaCl (M)
0.50
_
B
0.40
-1
Growth rate (h )
Figure
1-3.
Methanobacterium
subterraneum is a genus of Archaea
isolated 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 50qC.
0.30
0.20
0.10
0
6
6.5
7.0
7.5
8.0
8.5
9.0
9.5
pH
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.
10
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 8000u, bar = 2 Pm), b) strain J2 (9000u, bar = 2
Pm), c) J3 (enlargement 8000u, bar = 2 Pm), d) strain C (9000u, bar = 1 Pm, arrow
shows typical bud scar), and e) strain 5e (6750u, bar = 2 Pm; 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).
18
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 subgroups, in accordance with recent assessments of prokaryotic virus diversity
(Ackermann 2007). In addition, a tailed virus that infects the indigenous sulphatereducing 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 a
and b. Images c and d show viruses (indicated by arrows) at the surface of a bacterium.
Images were taken using 70,000u magnification in ac and 45,000u 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 ac 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
Hydrolysis
Organic polymers
Monomers
O2
CO2
Aerobic bacteria
Hydrolysis
NO3
N2
Denitrifying
bacteria
Oligo- and
monomers
Manganesereducing
bacteria
Fermentative
bacteria
CO2
Mn4+ Mn2+
CO2
Fe3+
Fe2+
Iron-reducing
bacteria
CO2
SO42
Acetate
Organic acids,
alcohols
H2O
H2 + CO2 2
Syntrophic bacteria
Sulphate-reducing
bacteria
S2
CO2
S0
S2
Sulphur-reducing
bacteria
CO2
Methanogens
CH4
H2 + CO2
Acetogenic bacteria
Acetate
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.
22
Living cells
per ml
10 000 000
Stationary phase
1 000 000
cli
De
Log
10 000
e
as
ph
phas
e
n
tio
na
100 000
Relative activity
per cell
1 000
1
100
10
0
1
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.
23
Living cells
per ml
Energy availability
over time decreases
10 000 000
Energy availability
over time increases
1 000 000
100 000
Relative activity
per cell
10 000
1 000
1
100
10
0
1
Time
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:
2CH3CHOHCOOí + SO42í ĺ 2CH3COOí + 2CO2 + 2H2O + S2í
(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 membranebound respiration chain. Consequently, the oxidation of the organic carbon is not
25
Sulphate-reducing
bacterium
Genetic control
DNA
Cell membrane
inside
outside
Lactate
Lactate
4H2
X
H2-ase
LDH
8H+
Acetate + Formate
Pyruvate
8e
CO2 + H2
Cyt c3
SO42
ATP
Hmc
X
e
FeS
protein
2e
APS
ATP-sulfurylase
SO32
ATP
H+
H2S
SO42
ATP-ase
6e
Sulphitereductase
H+
ADP
H2S (excreted)
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 SO32) 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.
26
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.
27
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 36 May 2004,
1014 October 2005, 2428 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 min1) out through the sampling
adapter. The adapter was removed after 2 min and the remaining 8 L of water were
pumped out (8 L min1). 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.
29
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 min1,
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 drillwater 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 1012 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.
32
Table 2-1. Identification information for the deep boreholes sampled for microbiological 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
2.3.1
Physical parameters, chemistry, and gas content of the sampled
groundwater
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 Ÿ 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 Ÿ 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 Ÿ S4O62 + 3I
2.3.3
(Eq. 2-3)
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,
SO42, 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
102 mBar 2–4 h before sampling. Water from the pump was led via poly-ether-etherketon (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
OL-KR-2-N2
OL-KR-6-N2
OL-KR-6-N2
OL-KR-6-N2
OL-KR-6-N2
OL-KR-6-N2
OL-KR-6-N2
OL-KR-6-N2
OL-KR-7-N2
OL-KR-7-Ar
OL-KR-7-N2
OL-KR-8-N2
OL-KR-8-N2
OL-KR-8-N2
OL-KR-8-N2
OL-KR-10-N2
OL-KR-10-N2
OL-KR-10-Ar
OL-KR-10-N2
OL-KR-13-N2
OL-KR-19-N2
OL-KR-19-N2
OL-KR-22-N2
OL-KR-22-N2
OL-KR-22-N2
OL-KR-29-N2
OL-KR-29-N2
OL-KR-30-N2
OL-KR-31-N2
OL-KR-33-N2
OL-KR-37-N2
OL-KR-39-N2
OL-KR-39-N2
Sampled
section
(m)
596.5–609.5
422–425
135–137
135–137
125–130
120–125
98.5–100.5
98.5–100.5
284–288
220–230
220–230
302–310
77–84
77–84
556.5–561
326–328
259–262
326.5–328.5
326.5–328.5
362–365
110–131
455–468
390–394
147–152
147–152
320–340
800–800
50–54
143–146
95–107
166–176
403–406
108–110
Mid elevation,
z
(m)
560
328
116
102
94
90
74
73
257
197
197
261
57
57
490
316
249
316
316
294
101
433
320
116
102
293
742
40
122
71
112
345
88
Sampling
date
Analysis
date
2006-02-28
2005-08-02
2006-08-22
2005-09-27
2006-06-26
2005-11-02
2006-10-16
2005-12-27
2006-04-25
2005-04-25
2005-04-25
2006-06-06
2005-10-25
2006-08-15
2006-04-27
2006-06-19
2005-04-04
2005-04-04
2005-04-04
2006-03-14
2005-09-05
2005-10-31
2006-03-01
2005-12-13
2006-08-17
2005-06-06
2005-04-16
2005-08-04
2006-10-24
2006-01-24
2006-11-28
2006-04-03
2006-05-30
2006-03-07
2005-08-24
2006-08-28
2005-09-27
2006-07-02
2005-12-12
2006-10-24
2006-01-13
2006-05-11
2005-08-22
2005-08-23
2006-06-09
2005-12-12
2006-08-28
2006-05-11
2006-06-21
2005-06-26
2005-08-23
2005-08-23
2006-03-27
2005-10-05
2005-12-12
2006-03-07
2006-01-13
2006-08-28
2005-08-23
2005-08-23
2005-08-24
2006-10-26
2006-01-26
2006-11-30
2006-04-06
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
2.4.1
Microbiological analyses
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 0.22µm-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. 266311; 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 4.0mL, 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 s1). 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 s1 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 107 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 mL1 (n = 10) were
obtained with clean solutions, while solutions displaying values above 1600 amol ATP
mL1 were disposed of.
The ATP concentration of the analysed samples was calculated as follows:
amol ATP mL1 = (Ismp Ibkg) / ((I smp + std I bkg ) – (I smp – I bkg)) u 109 / sample volume
where I represents the light intensity measured as RLU s1, smp represents sample, bkg
represents the background value of the reagent HS, and std represents the standard
(referring to a 107 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 L1 of peptone (Merck), 0.5 g L1 of yeast extract (Merck), 0.25 g L1 of
sodium acetate (Merck), 0.25 g L1 of soluble starch (Merck), 0.1 g L1 of K2HPO4, 0.2
g L1 of CaCl2 (Merck), 10 g L1 of NaCl (Merck), 1 mL L–1 of trace element solution
(see Table 2-3 D), and 15 g L1 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 50qC in a water bath, and finally distributed in 15-mL portions in 9-cmdiameter 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 L1 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 L1 of 100 g L1 NaCOO, 3 mL L1 of 6470 mM
trimethylamine, 4 mL L1 of methanol, and 20 mL L1 of a 20 g L1 solution of
NaCH3COO. The HA medium also contained 20 mL L1 of 100 g/L NaCOO, 3 mL L1
of 6470 mM trimethylamine, and 4 mL L1 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 813 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 u 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/RBiopharm, 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 L1 of KNO3, 1 g L1 of
MgSO4 u 7 H2O, 0.2 g L1 of CaCl2 u 2 H2O, 1 mg L1 of CuCl2 u 2H2O, 7 g L1 of
NaCl, 1 mL L1 of an iron solution made of 0.5 g of ferric (III) chloride in 1000 mL of
AGW, 1 mL L1 of a trace element solution according to Table 2-3D and 2 mL L1 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 L1
of copper chloride dihydrate. This is because the soluble and particulate methane
monooxygenase (s/pMMO) common to all known MOB is controlled by a copperinducible 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 20qC. 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
mL1.
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
Component (mL/L)
Basal medium (Table B)
Trace elements (Table C)
Trace elements (Table D)
Vitamins (Table E)
Vitamins (Table F)
Thiamine stock (Table G)
Vitamin B12 stock (Table G)
Fe stock (Table G)
Resazurin (Table G)
Cysteine hydrochloride (Table G)
NaHCO3 (Table G)
Yeast extract (Table G)
NaCH3COO (Table G)
Lactate (Table G)
KNO3 (G)
Sodium sulphide (0.2 M)
NRB
925
1.0
1.0
1.0
1.0
30
1.0
25
5.0
10
-
Metabolic groupa
IRB & MRB
SRB
AA & HA
940
860
860
10
10
1.0
1.0
10
10
1.0
1.0
1.0
1.0
1.0
1.0
5.0
5.0
2.0
2.0
10
10
30
60
60
1.0
10
10
25
5.0
7.5
10
AM & HM
890
10
10
1.0
1.0
5.0
2.0
10
60
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
Component (g)
AGW
NaCl
CaCl2*2H2O
KCl
NH4Cl
KH2PO4
MgCl2*6H2O
MgSO4*7H2O
MnCl2*4H2O
Na2MoO4*2H2O
a
NRB, IRB, & MRB
1000
7
1.0
0.1
1.5
0.2
0.1
0.1
0.005
0.001
Metabolic groupa
SRB
AA & HA
1000
1000
7
7
1.0
1.0
0.67
0.67
1.0
1.0
0.15
0.15
0.5
0.5
3.0
-
AM & HM
1000
7
0.28
0.67
1.0
0.15
0.5
-
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
AGW
Nitrilotriacetic acid
Fe(NH4)2(SO4)2*6H2O
Amount
1000 mL
1500 mg
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
F) Vitamin mixture for SRB, AA, HA, AM, and
HM
Component
Amount
1000 mL
Sodium phosphate buffer 10
mM
pH 7.1
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
D) Non-chelated trace elements
Component
AGW
HCl (25% = 7.7 M)
FeSO4*7H2O
H3BO3
Amount
987 mL
12.5 mL
2.1 g
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
Sodium phosphate buffer 10 mM
pH 7.1
4-Aminobenzoic acid
D(+)-biotin
Amount
100 mL
4 mg
1 mg
Nicotinic acid
10 mg
Pyridoxine dihydrochloride
15 mg
Calcium D(+) pantothenate
5 mg
G) Stock solutions
Component
NaHCO3
Thiamine chloride
dihydrochloride in a 25 mM
sodium phosphate buffer, pH
3.4
Cyanocobalamin (B12)
KNO3
NaCH3COO
Yeast extract
Fe(NH4)2(SO4)2*6H2O,
initially dissolved in 0.1 mL
of concentrated HCl
Resazurin
Cysteine-HCl
Sodium lactate solution
Amount
84 g L1
100 mg L1
50 mg L1
100 g L1
100g L1
50 g L1
2 g L1
500 mg L1
50 g L1
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 m1 (Figure 3-2), with the exception of
groundwater from boreholes PR1 (sampled 2006-10-11) and PP39 (sampled 2006-0424), 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 L1) were much
higher than the LDO data (2.35 mg O2 L1) 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 mL1, 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 mL1 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 mL1 up to 39 mg DOC mL1. One sample
displayed an exceptionally high DOC value of 196 mg DOC mL1. 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
1
Depth (m)
10
100
1000
4.5
5.0
5.5
6.0
6.5
7.0
7.5
8.0
8.5
pH
Figure 3-1. The pH in groundwater samples from Olkiluoto against depth.
1
Depth (m)
10
100
1000
0.1
1.0
10.0
100.0
1000.0
10000.0
Conductivity (mS m-1)
Figure 3-2. The electrical conductivity in groundwater samples from Olkiluoto over
depth.
46
0
Depth (m)
5
10
15
20
0
1
2
3
4
5
6
7
O2 (mg L1)
O2 HACH
O2 Winkler
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).
1
O2 Winkler (mg L )
10.0
1.0
0.1
0.0
0.0
0.1
1.0
10.0
O2 LDO electrode (mg L1)
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
0
2
4
Depth (m)
6
8
10
12
14
16
18
-200
-100
0
100
200
300
400
500
Eh HACH-electrode (mV)
Figure 3-5. The relationship between Eh , as analysed using the pIONeer 10 portable
pH-Eh , meter and depth.
6
5
18 - 23rd
May 2006
O2 (mg L1)
4
3
24 - 28th
April 2006
th
10 - 14
October 2005
9 - 13th
October 2006
7 - 12th
July 2006
2
1
0
1
2
3
4
5
6
7
8
9
10
11
12
PR1
PP2
PP9
PP36
PP39
PVP1
PVP4A
PVP13
PVP14
PVP20
Time (months)
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
Depth (m)
10
100
1000
1
10
100
1
DOC (mg L )
Figure 3-7. The concentrations of dissolved organic carbon (DOC) in groundwater
samples from Olkiluoto over depth.
1
Depth (m)
10
100
1000
0.01
0.10
1.00
10.00
S2
Fe2
1
(mg L )
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 L1 in borehole PVP4A-1 (2006-04-27)
to 7.2 mL L1 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 r 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 L1 groundwater1 were
found. The amounts then increased up to a maximum of 1380 mL of gas L1
groundwater1 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 L1 groundwater1 (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 L1 groundwater1. 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 L1 groundwater1 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 L1 groundwater1; 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
0
100
Depth (m)
200
300
400
500
600
700
800
10
100
1000
10000
Gas (mL L1 groundwater1 )
Figure 3-9. The total amount of extractable dissolved gas in Olkiluoto groundwater.
12
1
GC O2 (mL L )
10
8
6
4
2
0
0
1
2
3
4
5
Winkler O2 (mg L1
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.
Depth (m)
54
PVP1 - 4
PVP1 - 4
PVP13 - 6
PVP13 - 6
PR1 - 6
PR 1 - 6
PVP14 - 9
PVP14 - 9
PVP4A - 10
PVP4A - 10
PVP4A - 10
PP36 - 11
PP36 - 11
PVP20 - 13
PP39 - 14
PP39 - 14
PP9 - 15
PP9 - 15
PP2 - 14
PP2 - 14
PVA1 - 20
PVA1 - 20
KR30 - 40
KR8 - 57
KR8 - 57
KR33 - 71
KR6 - 73
KR6 - 74
KR39 - 88
KR6 - 90
KR6 - 94
KR19 - 101
KR6 - 102
KR22 - 102
KR37 - 112
KR22 - 116
KR6 - 116
KR31 - 122
KR7 - 197
KR7 - 197
KR10 - 249
KR7 - 257
KR8 - 261
KR29 - 293
KR13 - 294
KR10 - 316
KR10 - 316
KR10 - 316
KR22 - 320
KR6 - 328
KR39 - 345
KR19 - 433
KR8 - 490
KR2 - 560
KR29 - 742
0
200
400
600
800
1000
Major gas components (mL L1 gas1 )
Methane
Carbon dioxide
Helium
Nitrogen
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.
Depth (m)
55
PVP1 - 4
PVP1 - 4
PVP13 - 6
PVP13 - 6
PR1 - 6
PR 1 - 6
PVP14 - 9
PVP14 - 9
PVP4A - 10
PVP4A - 10
PVP4A - 10
PP36 - 11
PP36 - 11
PVP20 - 13
PP39 - 14
PP39 - 14
PP9 - 15
PP9 - 15
PP2 - 14
PP2 - 14
PVA1 - 20
PVA1 - 20
KR30 - 40
KR8 - 57
KR8 - 57
KR33 - 71
KR6 - 73
KR6 - 74
KR39 - 88
KR6 - 90
KR6 - 94
KR19 - 101
KR6 - 102
KR22 - 102
KR37 - 112
KR22 - 116
KR6 - 116
KR31 - 122
KR7 - 197
KR7 - 197
KR10 - 249
KR7 - 257
KR8 - 261
KR29 - 293
KR13 - 294
KR10 - 316
KR10 - 316
KR10 - 316
KR22 - 320
KR6 - 328
KR39 - 345
KR19 - 433
KR8 - 490
KR2 - 560
KR29 - 742
Carbon monoxide
0
50
100
150
650
700
Minor gas components (µL L1 gas1 )
Hydrogen
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.
Depth (m)
56
PVP1 - 4
PVP1 - 4
PVP13 - 6
PVP13 - 6
PR1 - 6
PR 1 - 6
PVP14 - 9
PVP14 - 9
PVP4A - 10
PVP4A - 10
PVP4A - 10
PP36 - 11
PP36 - 11
PVP20 - 13
PP39 - 14
PP39 - 14
PP9 - 15
PP9 - 15
PP2 - 14
PP2 - 14
PVA1 - 20
PVA1 - 20
KR30 - 40
KR8 - 57
KR8 - 57
KR33 - 71
KR6 - 73
KR6 - 74
KR39 - 88
KR6 - 90
KR6 - 94
KR19 - 101
KR6 - 102
KR22 - 102
KR37 - 112
KR22 - 116
KR6 - 116
KR31 - 122
KR7 - 197
KR7 - 197
KR10 - 249
KR7 - 257
KR8 - 261
KR29 - 293
KR13 - 294
KR10 - 316
KR10 - 316
KR10 - 316
KR22 - 320
KR6 - 328
KR39 - 345
KR19 - 433
KR8 - 490
KR2 - 560
KR29 - 742
Ethane
Ethene + Ethylene
1
10
100
1000
10000
Minor gas components (µl L1 gas1)
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
0
100
Depth (m)
200
300
400
500
600
700
800
10
100
1000
10000
Nitrogen (mL L groundwater)
Figure 3-14. The amount of extractable dissolved nitrogen gas in Olkiluoto
groundwater.
0
100
Depth (m)
200
300
400
500
600
700
800
10
100
1000
10000
100000
Helium (µL L1 groundwater1)
Figure 3-15. The amount of extractable dissolved helium gas in Olkiluoto groundwater.
58
0
100
Depth (m)
200
300
400
500
600
700
800
1
10
100
1000
CH4 (µL L
1
10000
100000
1000000
1
groundwater )
Figure 3-16. The amount of extractable dissolved methane gas in Olkiluoto
groundwater.
0
100
Depth (m)
200
300
400
500
600
700
800
1
10
100
CO2 (µL L
1000
1
10000
100000
1000000
1
groundwater )
Figure 3-17. The amount of extractable dissolved carbon dioxide gas in Olkiluoto
groundwater.
59
0
100
Depth (m)
200
300
400
500
600
700
800
0.1
1.0
10.0
1
100.0
1
Hydrogen (µL L groundwater )
Figure 3-18. The amount of extractable dissolved hydrogen gas in Olkiluoto
groundwater.
0
100
Depth (m)
200
300
400
500
600
700
800
0.1
1.0
CO (µL L
10.0
1
100.0
1
groundwater )
Figure 3-19. The amount of extractable dissolved carbon monoxide gas in Olkiluoto
groundwater.
60
0
100
Depth (m)
200
300
400
500
600
700
800
0.01
0.10
1.00
10.00
100.00
1000.00
10000.00
C2H6 (µL L1 groundwater1)
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
TNC (cells mL1)
ATP (amol mL1)
CHAB (cells mL1)
NRB (cells mL1)
IRB (cells mL1)
MRB (cells mL1)
SRB (cells mL1)
AA (cells mL1)
HA (cells mL1)
AM (cells mL1)
HM (cells mL1)
MOB (cells mL1)
AGW water
produced in the
Onkalo laboratory
12000 (2200)b
9725 (3209)
-d
-
Sterile AGW water
for washing pumps
and samplers
110 (120)
472 (214)
3 (6)
-
Sterile AGW water
after pumping and
sampling
7000 (3700)
3351 (86)
43 (15)
0.4 (0.1–1.7)c
<0.2
<0.2
<0.2
<0.2
<0.2
<0.2
<0.2
-
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
12.80
12.80
-
15 (7.6)
2.1
10.6 (0.77)
7.61 (0.39)
1.4
0.22 (0.042)
0.20 (0.023)
1.1
1.33
0.5
2 (0.9–8.6)
65.0
2.2 (0.9–5.6)
0.4 (0.1–1.7)
5.5
8.0 (3–25)
2.3 (0.9–8.6)
3.5
5 (2–15)
3 (1–12)
1.7
1
1600 (600–5300)
170 (70–480)
9.4
1
30 (10–130)
30 (10–120)
1.0
1
<0.2
<0.2
-
1
<0.2
<0.2
-
MOB (cells mL )
2.3 (0.9–8.6)
24 (10–94)
0.1
6MPN of TNC (%)
0.56
0.15
3.7
Depth (m)
TNC u 104 (cells L1)
1
ATP u 10 (amol L )
4
1
CHAB u 10 (cells L )
4
32 (4.3)
CHAB of TNC (%)
1
NRB (cells mL )
1
IRB (cells mL )
1
MRB (cells mL )
1
SRB (cells mL )
AA (cells mL )
HA (cells mL )
AM (cells mL )
HM (cells mL )
1
b
0.68
130 (50–390)
c
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 u 103 to 2.5 u 106 cells mL1 in the shallow groundwater
(Figure 3-21) and the overall average was 3.9 u 105 cells mL1. There were fewer cells
in the deep groundwater, which had a maximum of 1.5 u 105 cells mL1 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 u 104 cells mL1, 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 353.5360.0 m.
Analysisa and
physiological group
Sample
KFM06A:1
b
KFM06A:2
KFM06A:1/KFM06A:2
TNC u 104 (cells mL1)
7.2 (1.7)
5.2 (1.7)
1.4
ATP u 104 (amol mL1)
1.51 (0.07)
0,95 (0.05)
1.6
IRB (cells mL1)
30 (10–120)c
23 (9–86)
1.3
MRB (cells mL1)
13 (5–39)
30 (10–130)
0.44
1
0.8 (0.3–2.4)
0.4 (0.1–1.7)
2.0
1
30 (10–130)
24 (10–94)
1.3
1
HA (cells mL )
24 (10–94)
24 (10–94)
1.0
AM (cells mL1)
<0.2
0.2 (0.1–1.1)
<1.0
0.2 (0.1–1.1)
0.4 (0.1–1.7)
0.5
SRB (cells mL )
AA (cells mL )
1
HM (cells mL )
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 mL1, 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 u 103 cells mL1. 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 u 103 cells mL1, 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.
64
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
IRB (cells mL1)
1
KJ0052F01:1
KJ0052F01:2
KJ0052F01:1
/
KJ0052F01:2
<0.2
<0.2
1
<0.2
1
b
1600 (600–5300)
0.19
1
1600 (600–5300)
1600 (600–5300)
1
1
1600 (600–5300)
1600 (600–5300)
1
1
AM (cells mL )
17 (7–48)
5 (2–17)
3.4
HM (cells mL1)
2.3 (0.9–8.6)
2.3 (0.9–8.6)
1
KJ0052F03:1
KJ0052F03:2
KJ0052F03:1
/
KJ0052F03:2
<0.2
0.8 (0.3–2.4)
<1
MRB (cells mL )
5.0 (2–17)
1.1 (0.4–2.9)
4.6
SRB (cells mL1)
2.3 (0.9–8.6)
5 (2–17)
0.46
AA (cells mL1)
MRB (cells mL )
SRB (cells mL1)
AA (cells mL )
HA (cells mL )
IRB (cells mL1)
1
<0.2
300 (100–1300)
5 (2–17)
17 (7–48)
0.30
1
8 (3–25)
11 (4–30)
0.73
1
AM (cells mL )
2.3 (0.9–8.6)
0.4 (0.1–1.5)
8.0
HM (cells mL1)
1.3 (0.5–3.8)
<0.2
>1
HA (cells mL )
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 mL1 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 mL1 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 mL1 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.
66
0
Depth (m)
100
200
300
400
500
3.0
3.5
4.0
4.5
10
5.0
5.5
6.0
6.5
7.0
Log(TNC) (cells mL1 )
Figure 3-21. The distribution of total number of cells (TNC) versus depth in Olkiluoto
groundwater.
0
Depth (m)
100
200
300
400
500
3.0
3.5
4.0
4.5
10
5.0
5.5
6.0
6.5
7.0
Log(ATP) (amol mL1)
Figure 3-22. The concentrations of ATP distributed over depth in Olkiluoto
groundwater.
67
0
2
Depth (m)
4
6
8
10
12
14
16
0.0
1.0
2.0
10
3.0
4.0
5.0
1
Log(CHAB) (cells mL )
Figure 3-23. The distribution of cultivable heterotrophic aerobic cells (CHAB) versus
depth in shallow Olkiluoto groundwater.
0
Depth (m)
100
200
300
400
500
0.0
0.5
1.0
1.5
10
2.0
2.5
3.0
3.5
4.0
4.5
5.0
Log(CHAB) (cells mL1 )
Figure 3-24. The distribution of cultivable heterotrophic aerobic cells (CHAB) versus
depth in Olkiluoto groundwater.
68
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
0
2
4
6
Stacked
8
10
10
12
14
16
1
18
20
MOB
HM
AM
HA
AA
SRB
MRB
IRB
NRB
log(MPN) (cells mL )
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 = sulphatereducing bacteria, AA = autotrophic acetogens, HA = heterotrophic acetogens, AM =
autotrophic methanogens, HM = heterotrophic methanogens, and MOB = methaneoxidizing bacteria.
Borehole, depth (m)
69
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
0
2
4
6
8
10
12
14
16
18
Stacked 10log(MPN) (cells mL1)
20
HM
AM
HA
AA
SRB
MRB
IRB
NRB
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 = sulphatereducing bacteria, AA = autotrophic acetogens, HA = heterotrophic acetogens, AM =
autotrophic methanogens, and HM = heterotrophic methanogens.
0
Depth (m)
100
200
300
400
500
0
1
2
3
4
5
10
Log(NRB) (cells mL1)
Figure 3-27. The distribution of nitrate-reducing bacteria (NRB) versus depth in
Olkiluoto groundwater.
70
0
Depth (m)
100
200
300
400
500
0
1
2
10
3
4
5
1
Log(IRB) (cells mL )
Figure 3-28. The distribution of iron-reducing bacteria (IRB) versus depth in Olkiluoto
groundwater.
0
Depth (m)
100
200
300
400
500
0
1
2
10
3
4
5
Log(MRB) (cells mL1 )
Figure 3-29. The distribution of manganese-reducing bacteria (MRB) versus depth in
Olkiluoto groundwater.
71
0
Depth (m)
100
200
300
400
500
0
1
2
10
3
4
5
1
Log(SRB) (cells mL )
Figure 3-30. The distribution of sulphate-reducing bacteria (SRB) versus depth in
Olkiluoto groundwater.
0
Depth (m)
100
200
300
400
500
0
1
2
10
3
4
5
1
Log(AA) (cells mL )
Figure 3-31. The distribution of autotrophic acetogens (AA) versus depth in Olkiluoto
groundwater.
72
0
Depth (m)
100
200
300
400
500
0
1
2
10
3
4
5
1
Log(HA) (cells mL )
Figure 3-32. The distribution of heterotrophic acetogens (HA) versus depth in Olkiluoto
groundwater.
0
Depth (m)
100
200
300
400
500
0
1
2
10
3
4
5
Log(AM) (cells mL1 )
Figure 3-33. The distribution of autotrophic methanogens (AM) versus depth in
Olkiluoto groundwater.
73
0
Depth (m)
100
200
300
400
500
0
1
2
10
3
4
5
1
Log(HM) (cells mL )
Figure 3-34. The distribution of heterotrophic methanogens (HM) versus depth in
Olkiluoto groundwater.
0
2
Depth (m)
4
6
8
10
12
14
16
0
1
2
10
3
4
5
1
Log(MOB) (cells mL )
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 L1 to 1.64 mg
L1. 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 mL1 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 353.5360.0-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
80
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 mL1, 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
81
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 mL1, while viable number
estimates have ranged from 100 to 105 cells mL1. 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
82
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-thanaverage 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 OLKR6 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
83
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.
84
7.0
6.5
10
Log(ATP) (amol mL-1)
ATP = 0.6309+0.7795*x; 0.95 Conf.Int.
6.0
5.5
5.0
4.5
4.0
3.5
3.0
3.0
3.5
4.0
4.5
5.0
5.5
10
6.0
6.5
7.0
-1
Log(TNC) (cells mL )
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.
7
10
Log(TNC) (cells mL1)
6
5
4
3
2
1
0
0.0
0.5
1.0
1.5
10
2.0
2.5
3.0
3.5
4.0
4.5
5.0
1
Log(CHAB) (cells mL )
Figure 4-2. The relationship between the total number of cells (TNC) and the numbers
of cultivable aerobic heterotrophic bacteria (CHAB) in Olkiluoto groundwater.
85
5
NRB = 0.8179*CHAB 0.1803
3
2
10
Log(NRB) (cells mL1 )
4
1
0
0.0
0.5
1.0
1.5
10
2.0
2.5
3.0
3.5
4.0
4.5
5.0
Log(CHAB) (cells mL1)
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.
4.0
3.0
2.5
2.0
1.5
10
Log(HA) (cells mL1)
3.5
1.0
0.5
0.0
0.0
0.5
1.0
1.5
10
2.0
2.5
3.0
3.5
4.0
Log(AA) (cells mL1)
Figure 4-4. The relationship between AA and HA in Olkiluoto groundwater samples.
The line denotes a one-to-one relationship.
86
4.0
10
Log(IRB) (cells mL1)
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
0.0
0.5
1.0
1.5
10
2.0
2.5
3.0
3.5
4.0
1
Log(MRB) (cells mL )
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
87
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 7.1qC in spring and 9.1qC 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 6qC. 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
88
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.
89
0
2
4
Depth (m)
6
8
10
12
14
16
18
2
4
6
8
10
12
Spring
Fall
14
Temperature (qC)
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.
500
400
Eh (mV)
300
200
100
0
-100
-200
0
1
2
3
4
5
6
7
O2 (mg L1)
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.
90
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.
ATP (amol mL1)
1000000
100000
10000
1000
1
10
100
DOC (mg C L1)
Figure 4-8. The relationship between dissolved organic carbon (DOC) and ATP in
Olkiluoto groundwater.
91
0
100
200
Depth (m)
300
400
500
600
700
800
900
0
100
200
300
400
500
600
1
Sulphate (mg L )
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
100
200
Depth (m)
300
400
500
600
700
800
900
0.00
0.01
0.10
1.00
10.00
100.00
1
Fe2+ (mg L )
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.
92
0
100
200
Depth (m)
300
400
500
600
700
800
900
0.00
0.01
0.10
1.00
10.00
Sulphide (mg L1)
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
L1 groundwater1 in borehole OL-KR29 at a depth of 742 m (Figure 3-14), with a total
gas volume of 1380 mL L–1 groundwater1 (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 10qC 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
93
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 L1) 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 u 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. 4He
is 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-methaneconcentration 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).
94
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.
0
100
Depth (m)
200
300
400
500
600
700
800
0.001
0.010
0.100
1.000
Gas ratio
10.000
100.000
CH4 / He
C2H6 / He
Figure 4-12. The methane/helium and ethane/helium ratios for Olkiluoto groundwater
gas samples.
95
0
100
200
Depth (m)
300
400
500
600
700
800
1
10
100
1000
10000
N2 / He
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 20qC and +113qC. 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 100qC. 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
96
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
97
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).
98
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 L1) 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
4.7.1
Microbial processes in deep groundwater
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.
99
10,00
O2 (mg L1)
1,00
0,10
0,01
0,00
0
1
10
100
1000
10000
1
MOB (cells mL )
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.
1
groundwater )
1000
100
CH4 (µL L
1
( )
10
( )
1
0.1
( )
1.0
10.0
100.0
1000.0
MOB (cells mL1 )
Figure 4-15. The relationship between the numbers of methane-oxidizing bacteria
(MOB) and the concentration of dissolved methane.
100
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 Ÿ acetate
(Eq. 4-1)
IRB:
acetate + Fe3+ Ÿ Fe2+ + CO2
(Eq. 4-2)
SRB:
acetate + SO42– (+ H2) Ÿ H2S + CO2
(Eq. 4-3)
SRB:
DOC + SO42– Ÿ H2S + CO2
(Eq. 4-4)
AM + SRB: CH4 + SO42– Ÿ H2 + CO2 + SO42– Ÿ H2S + CH2O
(Eq. 4-5)
Inorganic processes (pH > 6.5)
H2S + 2FeOOH Ÿ S0 + 2Fe2+ + 4OH
(Eq. 4-6)
H2S + Fe2+ Ÿ FeS + 2H+
(Eq. 4-7)
3FeS + 3S0 Ÿ Fe3S4 + 2S0 Ÿ 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. 43). 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
101
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,
102
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 Ÿ 4H2 + HCO3– + H+
(Eq. 4-9)
Sulphate reducer:
4H2 + SO42– +H+ Ÿ HS + 4 H2O
(Eq. 4-10)
Sum reaction:
CH4 + SO42–Ÿ 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 mL1 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
103
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.
10000.00
1000.00
Fe2+/S2
100.00
10.00
1.00
0.10
0.01
0.00
0.00
0.01
0.10
1.00
10.00
Sulphide (mg L1 )
Figure 4-16. The relationship between the ferrous iron/sulphide ratio and sulphide.
104
0
100
200
Depth (m)
300
400
500
600
700
800
900
0.00
0.01
0.10
1.00
10.00
2+
100.00
1000.00 10000.00
2
Fe /S
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
105
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
106
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).
107
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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 Pump and
Date and time Ground- Yield
Notes
borehole sampling
water
depth
level
level
(m)
(m)
(y-m-d/time)
(m)
(L/min)
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
PP7
16.5
PP8
PP9
PP9
PP9
PP36
PP36
PP36
7.0
14.70
14.70
14.70
12.05
-
11.00
PP39
14.10
PP39
14.04
10 2004-05-05/09:50
2004-05-05/11:00
10 2004-05-05/12:20
2004-05-05/13:35
2004-05-05/15:35
6.0 2004-05-05/16:40
2004-05-05/17:00
2004-05-05/17:40
2004-05-06/08:05
2004-05-06/08:45
6.0 2005-10-13/12.25
2005-10-13/08.35
2005-10-13/12.55
6.0 2006-04-26/10.15
2006-04-26/10.25
2006-04-26/11.50
2006-04-26/14.05
6.0 2006-10-11/07.10
2006-10-11/07.20
2006-10-11/08.05
2006-10-11/10.30
2006-10-11/12.00
2006-10-11/15.15
6.0 2005-10-10/09.30
2005-10-10/12.05
2005-10-10/13.05
2005-10-10/13.40
4.0 2006-04-25/06.45
2006-04-25/06.50
2006-04-25/07.55
2006-04-25/12.35
5.0 2006-10-09/08.40
2006-10-09/10.50
2006-10-09/11.55
2006-10-09/12.05
6.0 2005-10-11/08.30
2005-10-11/10.00
2005-10-11/12.50
5.0 2006-04-24/08.10
2006-04-24/08.20
2006-04-24/09.55
0.55
1.14
7.65
3.95
4.10
4.12
3.93
4.13
1.31
3.95
4.15
0.80
1.39
3.46
3.53
0.78
1.21
1.26
4.31
3.47
3.64
3.68
3.70
3.27
2.43
1.32
1.08
2.01
2.08
7.2
7.0
0.85
0.80
start
stop
start
stop
start
5.40
5.50
5.5
0.43
0.44
0.40
0.61
0.58
0.57
0.255
0.255
0.180
0.185
0.190
7.2
5.04
5.04
5.04
4.70
6.2
6.0
6.2
0.4
0.67
0.65
stop
start
stop
roily water
sampling
pump start
roily water
sampling
pump start
roily water
sampling
pump start
clear water
sampling
pump start
sampling
pump start
sampling
pump start
roily water
sampling
pump start
117
PP39
14.10
PVP1
4.0
PVP1
3.90
PVP1
PVP1
3.92
2006-04-24/11.05
2006-04-24/14.10
6.0 2006-10-11/07.30
2006-10-11/07.45
2006-10-11/09.00
2006-10-11/11.45
2006-10-11/12.45
3.0 2004-05-03/16.35
2004-05-03/15.45
2004-05-03/17.30
2004-05-03/18.45
2004-05-04/08.00
2004-05-04/10.00
2.50 2005-10-11/07.40
2005-10-11/09.50
2.10
2.14
1.57
3.20
3.40
1.05
1.05
3.05
2.85
1.06
2.90
0.69
1.19
2005-10-11/12.10
2.50 2006-04-27/06.35
2006-04-27/06.55
2006-04-27/07.45
1.01
0.43
1.25
1.19
2006-04-27/10.20
2006-10-12/06.20
2006-10-12/06.50
2006-10-12/08.00
2006-10-12/09.00
2006-10-12/09.25
2004-05-03/12:20
2004-05-03/13:55
2004-05-03/15.30
2004-05-03/09:50
2004-05-03/10:00
2004-05-03/10:35
2004-05-03/12:15
2004-05-03/13:30
2004-05-04/13:15
2004-05-04/13:20
2004-05-04/14:45
2005-10-12/07.40
2005-10-12/09.55
2005-10-12/12.10
1.19
0.70
1.32
1.80
1.90
0.60
2.60
2.65
0.70
3.93
2.50
PVP3B
4.5
3
PVP3A
8.5
7.5
PVP4A
PVP4A
10
10.20
9
5.0
6.90
7.08
7.00
1.25
7.30
1.14
-
0.64
- sampling
- pump start
0.9
0.9
0.9
- sampling
start
2.0
1.8
0.25
stop
0.25
start
0.25
Stop
2.8
2.4
brown
water
2.0 sampling
- pump start
2.6
2.6
brown
water
2.4 sampling
3.4 pump start
3.0
3.0
- sampling
4.0
start
3.0
run
2.5
stop
start
2.96
2.7
2.5
Stop
start
6.0
6.0
stop
4.8 pump start
4.5
- sampling
118
PVP4A
PVP4A
PVP4B
10.36
10.20
9.5
PVP13
5.60
PVP13
5.64
PVP13
PVP14
PVP14
PVP14
PVP20
PVP20
PVP20
5.60
9.0
9.08
9.08
12.80
12.80
6.0 2006-04-27/06.20
2006-04-27/06.35
2006-04-27/08.00
2006-04-27/08.35
2006-04-27/14.45
5.0 2006-10-10/11.10
2006-10-10/11.20
2006-10-10/12.50
2006-10-10/13.20
8 2004-05-04/13.45
2004-05-04/14:55
2004-05-04/17:10
4.0 2005-10-12/10.40
2005-10-12/10.40
2005-10-12/10.40
3.0 2006-04-26/06.35
2006-04-26/06.45
2006-04-26/08.00
2006-04-26/09.05
2006-04-26/11.00
4.0 2006-10-12/10.40
2006-10-12/10.40
2006-10-12/10.40
2006-10-12/10.40
5.0 2005-10-14/07.45
2005-10-14/08.50
2005-10-14/09.35
6.0 2006-04-26/06.20
2006-04-26/06.30
2006-04-26/08.10
2006-04-26/08.45
5.5 2006-10-10/06.25
2006-10-10/07.30
2006-10-10/08.30
2006-10-10/09.30
2006-10-10/10.15
5.0 2005-10-13/07.53
2005-10-13/09.20
2005-10-13/09.30
- 2006-04-26/00.00
5.0 2006-10-10/07.45
0.85
2.85
3.27
3.36
3.16
1.17
3.04
1.80
6.70
1.51
1.87
1.99
0.89
1.95
1.91
1.93
1.64
2.49
2.98
2.29
1.34
3.18
3.39
4.6
0.71
1.14
4.5
4.4
3.9
6.0
5.5
-
pump start
sampling 1
sampling 2
pump start
sampling
start
0.70
0.70
stop
1.06 roily water
0.80 clear water
0.85 sampling
1.10
1.10
1.10
0.76
0.75
0.70
0.70
5.2
5.2
5.2
5.1
4.9
4.2
1.8
1.8
1.8
0.4
0.4
pump start
sampling
pump start
sampling
sampling
pump start
sampling
pump start
sampling
pump start
sampling
frozen
1.05 pump start
119
2006-10-10/09.45
2006-10-10/12.30
2006-10-10/14.35
2006-10-10/15.20
-
1.06
-
sampling
120
Table A-2. Pre-treatment of the groundwater samples.
Parameter
Conductivity,
density, pH, NH4
Alkalinity,
acidity
S2–
Cl, Br, SO4, Stot
F
2+
Fe , Fetot
Sodium
fluorescein
DIC/DOC
Na, Ca, K, Mg,
Fe, Mn, SiO2
PO4
Sr, Btot
Ntot, NO2, NO3
H-2, O-18
H-3
C-13 / C-14
Sr-87 / Sr-86
Rn-222
S-34 (SO4),
O-18 (SO4)
Uranium, U-238
Uranium,
U-234/U-238
Container (L)
N2- shielding
/ Filtering
Preserving chemicals and details
Laboratory
1 u 0.5 HDPE
-/-
-
TVO
1 u 0.5 Duran
bottle
3 u 0.1 measuring
bottle
1 u 0.25 HDPE
1 u 0.25 HDPE
x/x
Sampling with titration sampler.
TVO
x/x
0.5 mL Zn(Ac)2 and 0.5 mL
0.1 M NaOH. Sampling with sampler.
TVO
6 u 0.05
measuring bottle
x/x
1 u 0.05
measuring bottle
1 u 0.05 brown
glass bottle
1 u 0.25 PE,
acid washed
1 u 0.25 HDPE
1 u 0.1 HDPE,
acid washed
1 u 0.25 HDPE
1 u 0.125
Nalgene bottle
1 u 0.25 glass
bottle
1 u 0.2 brown
class bottle
1 u 0.125
Nalgene, acid
washed
1 u 0.01
Ultimagold
solution bottle
1 u Nalgene
1 u 1 PE,
HCl-washed
1 u 1 PE,
HCl-washed
-/x
-/x
TVO
TVO
Adding a ferrozine reagent to Fe2+
samples in nitrogen atmosphere.
Sampling with sampler.
-/x
TVO
TVO
-/x
Sampling with sampler.
TVO
-/x
2.5 mL conc. HNO3 / 250 mL
TVO
-/x
2.5 mL 4 M H2SO4/ 250 mL
TVO
-/x
1 mL suprapur HNO3 / 100 mL
VTT
Rauman
ymp. lab.
-/x
-/-
Bottle is filled to the brim.
GTK
-/-
The
Netherlands
-/x
Uppsala
-/-
GTK
-/-
-/-
-/x
-/x
Sampling time is written down.
Sample volume depends on SO4concentration. Zn(Ac)2 is added to
sample according to Posiva water
sampling quide.
50 mL conc. HCl / 1 L.
Filters are sent to HYRL for analyses.
50 mL conc. HCl / 1 L.
Filters are sent to HYRL for analyses.
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
STUK
Waterloo
HYRL
HYRL
121
Table A-3. Methods and detection limits for groundwater chemistry.
Parameter
pH
Conductivity
Density
Sodium fluorescein
Alkalinity
Acidity
DOC/DIC
Fetot
Fe2+
Fetot,, Mn
K, Na
SiO2
Ca
Mg
Sr
Btot
Cl
Br
F
PO4
S2–
SO4
Stot
NH4
Total nitrogen, Ntot
Nitrate, NO3
Nitrite, NO2
18
18
O
O (SO4)
Apparatus and method
pH meter
ISO-10532
Conductivity analyser
SFS-EN-27888
Posiva water sampling guide /1
Fluorometry
Titration/Posiva water
sampling guide /1
Titration/Posiva water
sampling guide /1
SFS-EN 1484
Spectrophotometry/ Posiva
water sampling guide /1
Spectrophotometry/ Posiva
water sampling guide/1
ICP/OES
ICP-MS
Titration/Posiva water
sampling guide/1
IC, conductivity detector. SFSEN ISO 10304-1
ISE/ Posiva water sampling
guide/1
Spectrophotometer
SFS-EN 1189
Spectrophotometer
SFS 3038
IC, conductivity detector. SFSEN ISO 10304-1
H2O2 oxidation +IC
Spectrophotometer
SFS 3032
HPLC
SFS3031
HPLC
Internal method n:o 10
Spectrophotometer
SFS3029:1976
MS
MS
Detection limit
Uncertainty of the
measurement
r 0.05
5 µS/cm
5%
0.05 mmol/L
r 0.001 g/cm3
15 µg/l: 0.8%
200 µg/l: 1.2%
275 µg/l: 0.4%
r 5%
0.05 mmol/L
r 10%
0.1 mg/L
0.01 mg/L
r 5%
0.01 mg/L
r 5%
0.002 mg/L
0.5 mg/L
0.01 mg/L
0.1 mg/L
0.02 mg/L
0.5 µg/L
2 µg/L
5 mg/L
r 2.5%
0.5 mg/L
r 4.2%
0.1 mg/L
r 5%
0.012 mg/L
± 24%
0.01 mg/L
1.25 mg/L
0.07 mg/L: 36%
0.17 mg/L: 17%
0.53 mg/L: 10%
± 3.2%
0.2 mg/L
0.002 mg/L
r 4%
1 µg/l
0.20 mg/L
3.0 mg/L
0.010 mg/L
3.0–5.0 mg/L: 12%
>5.0 mg/L: 7%
0.010–0.10 mg/L:
10%
>0.10 mg/L: 8%
< 0.1‰
0.5‰
122
Table A-3 (continued). Methods and detection limits for groundwater chemistry.
3
H
H
C (DIC)
14
C (DIC)
86
Sr/87Sr
34
S (SO4)
Electrical enrichment + home
made Proportional Gas counter
(PGC) detection method
MS
MS
AMS
MS
MS
Rn-222
Liquid scintillation counting / 2
2
13
0.2 TU
0.3 pM
0.1 mBq/L
100 ± 2,
20 ± 0.5 and
1.00 ± 0.10 TU
1‰
0.05‰
0.1 pM
0.003‰
0.2‰
5–10%
U(tot) ja
Alfaspectrometer
0.2 mBq/L
U-234/U-238
ASTM D3648-95, 1995
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 alphaspectrometry 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- TDS (mg
ivity (mS
L–1)
–1
m )
PR1
2004-05-04
6
4.6
5.0
12
78
23.7
PR1
2005-10-10
6
11.2
5.2
12
110
30.5
0.94
PR1
2006-04-25
6
3.9
5.3
15
120
33.6
1.12
6.50
16.4
PR1
2006-10-11
6
10.2
5.5
0
98
27.5
0.88
6.10
13.3
PP2
2004-05-05
14.7
6.2
7.2
80
575
271.0
PP2
2005-10-12
14.7
7.3
7.4
81
650
282.0
0.24
PP2
2006-04-24
14.7
7.6
7.4
83
620
290.0
0.39
PP2
2006-10-11
14.7
7.1
7.3
78
620
289.0
0.37
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
PP9
2006-04-27
14.7
6.7
7.3
22
200
119.0
0.19
PP9
2006-10-09
14.7
11.9
6.8
7
140
79.9
0.24
PP36
2005-10-10
12.1
9.9
5.8
23
190
65.3
0.92
PP36
2006-04-25
12.1
7.0
5.8
11
93
35.4
0.66
PP36
2006-10-09
12.1
10.5
5.8
9
84
30.5
0.53
PP39
2005-10-11
14.1
12.6
7.0
152
1150
355.0
0.43
PP39
2006-04-24
14.1
10.6
6.9
1
740
329.0
0.94
PP39
2006-10-11
14.1
7.9
6.8
111
990
401.0
1.32
PVP1
2004-05-04
3.9
12.7
6.0
17
121
46.5
PVP1
2005-10-11
3.9
11.9
4.9
10
120
48.2
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)
2.80
21.5
469
0.08
402
0.42
0.44
134
0.21
0.23
224
0.45
81.5
59.9
<0.05
<0.05
121
<1.8
58.6
0.26
<0.05
–36
3.70
56.2
0.23
<0.05
–100
0.61
0.40
280
7.40
21.2
2.35
4.24
240
15.60
14.4
1.85
1.07
83
23.7
<0.05
<0.05
360
15.80
10.3
1.24
1.25
167
20.70
10.9
1.35
1.36
234
81.6
<0.05
<0.05
131
28.50
68.5
<0.05
<0.05
–64
38.80
89.3
0.10
0.03
–116
19.7
0.56
429
0.08
357
123
32.6
5.17
2.69
Eh
HACHelectrode
(mV)
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
PVP4A:1
2006-04-27–0 h
10.2
5.8
7.3
81
610
294.0
0.45
PVP4A:2
2006-04-27–6 h
8.6
0.67
7.1
1.03
82
0.99
620
0.98
301.0
0.98
64.4
<0.05
<0.05
150
<1.8
57.6
0.05
<0.05
97
0.43
1.05
<1.8
-
57.6
1.00
<0.05
-
<0.05
-
86
1.13
0.38
3.10
59.8
0.15
<0.05
–19
2006-04-27
PVP4A
2006-10-10
10.2
7.5
7.2
83
630
289.0
PVP4B
2004-05-04
8
11.2
7.0
71
548
285.0
PVP13
2005-10-12
5.6
9.8
7.2
55
540
349.0
0.34
PVP13
2006-04-26
5.6
8.2
7.3
55
520
338.0
0.41
PVP13
2006-10-12
5.6
8.3
7.2
53
530
339.0
0.43
PVP14
2005-10-13
9
9.4
7.0
64
610
356.0
0.32
PVP14
2006-04-26
9
5.3
7.3
61
560
355.0
0.25
PVP14
2006-10-10
9
5.9
7.4
62
580
347.0
0.43
PVP20S
2005-10-13
12.8
7.6
7.1
60
510
265.0
0.40
PVP20P
2005-10-13
12.8
7.6
7.1
60
510
265.0
0.40
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
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
4.85
242
69.9
<0.05
<0.05
153
4.10
65.3
0.12
<0.05
14
7.50
65.8
<0.05
<0.05
–14
73.8
<0.05
<0.05
150
<1.8
67.9
0.06
<0.05
–64
3.40
70.6
0.06
<0.05
–14
56.0
<0.05
137
56.0
<0.05
137
<0.05
–30
0.20
124
PVP4A:1/2
10.2
1.00
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
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
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
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
10.3
11.9
8.6
125
OL-KR8
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)
Cl(mg L–1)
F(mg L–1)
Br(mg L–1)
0.54
4
0.10
<0.5
<3.0
3
0.10
<0.5
NO3–
(mg L–1)
NH4
(mg L–1)
2004-05-04
6
33.00
PR1
2005-10-10
6
38.00
<0.01
1.23
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
<3.0
8
0.20
<0.5
4.90
<0.010
126
PR1
PVP1
2006-10-12
3.9
23.00
PVP3A
2004-05-03
7.8
PVP3B
2004-05-03
PVP4A
1.67
1.00
<0.01
9
0.20
<0.5
55.00
<0.02
64
0.20
<0.5
3.8
63.0
<0.02
84
0.20
0.60
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
PVP4A:1/2 2006-04-27–6 h
10.2
1.00
47.00
1.00
<0.01
-
1.64
1.86
0.38
0.71
<0.010
-
<3.0
-
93
1.00
0.50
1.00
<0.5
-
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
28.00
0.03
0.42
0.27
<0.010
<3.0
0.24
88
0.50
0.60
127
1.11
–220
<0.01
OL-KR8
2006-06-06
260.7
0.08
0.10
0.21
<0.01
<0.02
0.10
4410
0.60
15.80
OL-KR10
2005-02-21
106
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
–200.0
128
470.00
Table A-4. Continued.
Borehole
Sampling date Depth (m)
PR1
2004-05-04
6
PR1
2005-10-10
6
PR1
2006-04-25
PR1
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)
1.1
7
3.7
13.4
6
1.7
8
4.0
0.32
0.025
6
11.3
7
1.6
10
4.8
0.38
0.032
0.02
0.6
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
4
PVP1
2006-10-12
3.9
PVP3A
2004-05-03
PVP3B
19.6
7
2.0
5
3.1
0.07
0.02
7.8
54
7.3
41
12.0
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
PVP4A:1
2006-04-27–0 h
10.2
21.2
31
6.4
PVP4A:2
2006-04-27–6 h
20.9
1.01
32
0.97
22.7
0.03
2.1
19.3
1.77
0.2
97
15.7
1.36
0.3
0.04
0.1
6.9
0.93
99
0.98
16.5
0.95
1.39
0.98
0.3
1.04
0.04
0.98
<0.1
-
33
6.4
108
16.8
1.42
0.2
0.04
<0.1
28
6.1
94
15.3
2006-04-27
PVP4A
2006-10-10
10.2
PVP4B
2004-05-04
8
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
PVP4A:1/2
10.2
1.00
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
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
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
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
<0.2
0.1
3.1
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)
PR1
PR1-SD%
Depth
Sample and
Volume
Extracted
Extracted
Z-up
extraction
water
gas
gas
date
(m)
4
4
Hydrogen
Helium
Argon
(ppm)
(ppm)
(ppm)
–1
(mL L )
(mL)
(mL)
Oxygen
(ppm)
6
2006-04-25
91.5
6.2
66.5
35450
24.4
6
2006-04-25
7.0
37.9
31.4
61.6
41.5
104.7
6.4
61.0
10650
52.5
4
6
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
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
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
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
PP9-SD%
6
14.7
2006-10-09
4.6
22.0
18.2
28.0
29.2
11
2006-04-25
102.5
5.4
53.2
30350
10.8
11
2006-04-25
9.0
35.7
43.9
34.2
19.1
11
2006-10-11
95.0
3.9
41.8
69000
40.8
6.9
53.4
57.0
62.5
73.1
PP36
PP36-SD%
PP36
4
4
5
PP36-SD%
5
11
2006-10-11
PP39
5
14
2006-04-24
82.0
4.0
48.3
22950
15.1
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
PP39-SD%
6
14
2006-10-11
5.8
28.0
24.8
61.0
22.1
2.5
3.9
2006-04-27
101.5
5.0
49.3
49600
11.6
PVP1
n.a.
0
n.a.
0
n.a.
0
n.a.
0
n.a.
0
n.a.
0
n.a.
0
n.a.
0
n.a.
0
n.a.
0
n.a.
132
PR1
2006-10-11
0
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
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.
10.2
2006-04-27–6 h
0.7
65.5
66.1
53.0
47.4
10.2
2006-10-11
101.3
3.6
36.0
31900
24.8
0
n.a.
2.3
17.9
19.7
32.3
12.9
0
n.a.
0
n.a.
0
n.a.
0
n.a.
0
n.a.
0
n.a.
0
n.a.
PVP4A-2-SD%
PVP4A
6
5
5
10.2
PVP13
3
5.6
2006-04-26
101.0
3.6
35.7
37000
17.9
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
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
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
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
PVP20-SD%
12.8
12.8
2006-10-10
6.8
28.5
33.9
124.5
25.2
20
2006-04-28
98.0
4.0
40.8
55150
24.8
20
2006-04-28
2.9
0.0
2.9
3.2
0.0
20
2006-10-11
99.3
4.0
39.9
8873
69.3
20
2006-10-11
1.5
31.9
31.1
48.9
51.6
PVA1
PVA1-SD%
PVA1
PVA1-SD%
ONKALO
ONKALO
ONKALO
ONKALO
133
PVP4A-SD%
2006-10-11
n.a.
Table A-5. Continued
Borehole
Sample and
extraction
date
Nitrogen
CO
CO2
CH4
C2H6
C2H2–4
total gas
(ppm)
(ppm)
(ppm)
(ppm)
(ppm)
(ppm)
(%)
PR1
2006-04-25
431500
44.1
529500
2905
PR1-SD%
2006-04-25
39
14.6
27
35
PR1
2006-10-11
461667
29.0
472000
258
2006-10-11
23
22.0
19
17
2006-04-24
706500
96.2
239000
4650
68.8
86
82
PR1-SD%
PP2
PP2-SD%
PP2
2006-10-11
706334
41.4
202218
2044
PP2-SD%
2006-10-11
3
28.6
10
16
PP9
2006-04-26
523500
54.8
249000
327
PP9-SD%
2006-04-26
32
11.5
4
5
PP9
2006-10-09
501000
125.0
454333
295
PP9-SD%
2006-10-09
28
16.5
32
18
PP36
2006-04-25
566000
91.5
433000
230
PP36-SD%
2006-04-25
24
27.0
24
55
PP36
2006-10-11
449667
112.1
453667
262
PP36-SD%
2006-10-11
65
83.3
57
105
2006-04-24
542000
35.8
451000
22500
2006-04-24
19
22.1
19
18
29.0
472000
258
PP39
PP39-SD%
PP39
2006-10-11
461667
PP39-SD%
2006-10-11
23
22.0
19
17
PVP1
2006-04-27
439000
78.6
528500
432
PVP1-SD%
2006-04-27
0
26.6
2
72
PVP1
2006-10-12
591667
60.6
293333
674
0
99.9
0.1
0
0
0
0
0
0
94.5
3.4
103.3
0.6
96.6
1.8
0
0
103.2
3.1
0
0
99.9
1.7
0
0
103.0
2.3
0
0
0
0
0
0
97.3
2.1
103.9
0.1
94.5
3.4
0
0
101.8
0.9
0.1
0
91.6
134
2006-04-24
36
0
PVP1-SD%
8
69.3
18
37
100
PVP4A-1
2006-10-12
2006-04-27–0 h
700000
37.2
306000
4140
0
0
PVP4A-1-SD%
2006-04-27–0 h
10
16.7
13
15
PVP4A-2
2006-04-27–6 h
786000
44.5
246500
2820
0
0
PVP4A-2-SD%
2006-04-27–6 h
23
45.8
66
46
PVP4A
2006-10-11
697667
31.4
265000
2730
PVP4A-SD%
2006-10-11
6
22.1
12
14
PVP13
2006-04-26
785500
46.5
207500
2370
PVP13-SD%
2006-04-26
1
40.4
24
17
PVP13
2006-10-12
715667
28.2
228000
1082
PVP13-SD%
2006-10-12
4
13.8
33
30
PVP14
2006-04-26
795000
41.4
220500
289
PVP14-SD%
2006-04-26
6
45.0
21
1
PVP14
2006-10-10
800333
12.6
157000
38
2006-10-10
6
135.4
23
138
2006-10-10
769333
28.6
193333
827
50.0
22
31
PVP20
PVP20-SD%
105.0
0.8
105.3
0.5
0
0
99.7
0.2
0
0
103.2
1.5
0
0
95.3
10.4
0
0
104.6
0.4
0
0
0
0
0
98.1
0.8
2006-10-10
11
PVA1
2006-04-28
716000
32.5
40350
3415
8
PVA1-SD%
2006-04-28
0
74.0
13
20
8
PVA1
2006-10-11
926000
43.5
70400
6817
0
PVA1-SD%
2006-10-11
4
34.5
16
29
99.1
0.9
81.5
0.7
0
101.2
1.7
135
PVP14-SD%
3.2
Table A-6. Gas data for the sampled deep groundwater.
Borhole
Upper
level
Lower
level
Depth
Z-up
(m)
(m)
(m)
Sample
Extraction
date
date
Time from
sampling to
analysis (d)
Volume
Extracted
Extracted
Analysed
water
gas
gas
air
–1
(mL L )
(mL)
(mL)
(%)
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-KR2
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
Helium
Argon
Nitrogen
CO
CO2
CH4
C2H6
C2H2–4
total gas
(ppm)
(ppm)
(ppm)
(ppm)
(ppm)
(ppm)
(ppm)
(ppm)
(ppm)
(%)
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-KR2
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, 6MPN = 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
Depth
(Y-M-D)
(m)
SD
TNC
n
1
ATP
SD
n
1
(cells mL )
CHAB
SD
n
1
(amol mL )
(cells mL )
CHAB/
ATP/
6MPN/
TNC
TNC
TNC
(%)
2004-05-04
6.0
57000
57000
6
n.a.
PR1
2005-10-10
6.0
2000000
450000
6
266000
7270
PR1
2006-04-25
6.0
820000
84000
3
626000
PR1
2006-10-11
6.0
390000
21000
3
128000
PP2
2004-05-05
14.7
32000
16000
6
n.a.
PP2
2005-10-12
14.7
110000
53000
6
25100
2440
PP2
2006-04-24
14.7
55000
1400
3
13300
PP2
2006-10-11
14.7
10000
1100
3
1900
PP3
2004-05-05
14.3
190000
84000
6
PP7
2004-05-05
16.2
31000
23000
PP8
2004-05-06
15.2
1500000
PP9
2005-10-13
14.7
200000
PP9
2006-04-27
14.7
n.a.
PP9
2006-10-09
14.7
220000
5400
3
PP36
2005-10-10
12.1
110000
45000
6
PP36
2006-04-25
12.1
370000
29000
3
PP36
2006-10-09
12.1
400000
15000
3
PP39
2005-10-11
14.1
580000
560000
PP39
2006-04-24
14.1
540000
PP39
2006-10-11
14.1
410000
(%)
5150
1450
3
9.04
0.29
3
11700
117
3
0.59
0.133
1.46
34700
3
1600
2040
3
0.20
0.763
0.30
8590
3
827
107
3
0.21
0.328
0.64
n.a.
-
-
3
310
399
3
0.28
0.228
0.12
680
3
553
98
3
1.01
0.242
0.04
50
3
27
46
3
0.27
0.190
0.10
n.a.
93
65
3
0.05
0.00
6
n.a.
240
150
3
0.77
0.06
160000
5
n.a.
1900
707
2
0.13
0.02
46000
6
24500
1770
3
13
6
3
0.01
0.123
0.01
109000
1400
3
70
46
3
104000
4610
3
677
508
3
0.31
0.473
0.10
26900
1080
3
37
6
3
0.03
0.245
0.08
220600
10600
3
427
60
3
0.12
0.596
0.09
146000
13600
3
740
42
2
0.19
0.365
0.05
6
198000
10800
3
913
93
3
0.16
0.341
0.14
140000
3
90400
3110
3
553
64
3
0.10
0.167
0.21
42000
3
170000
5220
3
983
145
3
0.24
0.415
1.09
0.01
140
PR1
Table A-7. continued.
Borehole
sampled
(Y-M-D)
Depth
(m)
SD
TNC
n
1
ATP
SD
n
1
(cells mL )
CHAB
SD
n
1
(amol mL )
(cells mL )
CHAB/
ATP/
6MPN/
TNC
TNC
TNC
(%)
2004-05-04
3.9
1500000
400000
6
n.a.
15100
5130
3
1.01
PVP1
2005-10-11
3.9
2500000
670000
6
685000
59900
PVP1
2006-04-27
3.9
1100000
18000
3
7920000
PVP1
2006-10-12
3.9
200000
16000
3
624000
PVP3A
2004-05-03
7.8
150000
66000
6
PVP3B
2004-05-03
3.8
41000
53000
6
PVP4A
2004-05-04
9.6
96000
55000
6
PVP4A
2005-10-12
10.2
660000
14000
6
PVP4A
2006-10-10
10.2
9500
1400
PVP4A:1
2006-04-27
10.2
7600
PVP4A:2
2006-04-27
10.2
7800
PVP4A:1/2
2006-04-27
10.2
0.97
PVP4B
2004-05-04
8.0
51000
19000
PVP13
2005-10-12
5.6
120000
PVP13
2006-04-26
5.6
PVP13
2006-10-12
5.6
PVP14
2005-10-13
PVP14
0.00
3
917
218
3
0.04
0.274
0.01
307000
3
4400
3200
3
0.40
7.200
2.67
61800
3
530
125
3
0.27
3.120
0.10
n.a.
1060
482
3
0.71
-
0.00
n.a.
6690
3610
3
16.32
0.17
0.01
13200
3
690
539
3
0.72
30200
4160
3
1240
59
3
0.19
0.046
0.20
3
1860
170
3
0
0
3
0.00
0.196
0.14
1300
3
11400
2800
3
2330
115
3
30.66
1.500
3.05
1100
3
6320
630
3
173
60
3
2.22
0.810
2.02
1.80
13.5
6
n.a.
79200
17300
3
155.29
17000
6
79400
10300
3
1400
106
3
1.17
0.662
0.73
17000
1400
3
12800
560
3
83
40
3
0.49
0.753
2.28
17000
1400
3
12300
790
3
23
12
3
0.14
0.724
0.62
9.0
90000
80000
6
3570
480
3
57
30
3
0.06
0.040
0.02
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
-
-
-
0.01
141
PVP1
(%)
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.
Borehole
sampled
(Y-M-D)
NRB
(cells
mL1)
n.a.
24000.0
1700.0
2400.0
n.a.
<0.2
2.3
0.2
n.a.
n.a.
n.a.
8.0
13.0
30.0
1.7
70.0
80.0
300.0
23.0
1300.0
PR1
2004-05-04
6.0
PR1
2005-10-10
6.0
PR1
2006-04-25
6.0
PR1
2006-10-11
6.0
PP2
2004-05-05
14.7
PP2
2005-10-12
14.7
PP2
2006-04-24
14.7
PP2
2006-10-11
14.7
PP3
2004-05-05
14.3
PP7
2004-05-05
16.2
PP8
2004-05-06
15.2
PP9
2005-10-13
14.7
PP9
2006-04-27
14.7
PP9
2006-10-09
14.7
PP36
2005-10-10
12.1
PP36
2006-04-25
12.1
PP36
2006-10-09
12.1
PP39
2005-10-11
14.1
PP39
2006-04-24
14.1
PP39
2006-10-11
14.1
L
limit
U
limit
10000.0
94000.0
700.0
4800.0
1000.0
9400.0
0.9
8.6
0.1
1.1
3.0
25.0
5.0
39.0
10.0
120.0
0.7
4.6
30.0
210.0
30.0
250.0
100.0
1200.0
9.0
86.0
500.0
3900.0
IRB
(cells
mL1)
0.4
1.3
2.3
0.2
<0.2
<0.2
<0.2
<0.2
<0.2
<0.2
<0.2
<0.2
<0.2
<0.2
<0.2
<0.2
<0.2
1.7
17.0
14.0
L
limit
U
limit
0.1
1.7
0.5
3.8
0.9
8.6
0.1
1.1
0.7
4.6
7.0
46.0
6.0
36.0
MRB
(cells
mL1)
0.0
0.8
70.0
1.3
<0.2
<0.2
0.4
<0.2
<0.2
<0.2
<0.2
0.4
0.8
<0.2
0.8
17.0
0.4
17.0
170.0
28.0
L
limit
U
limit
0.3
2.4
30.0
210.0
0.5
3.8
0.1
1.7
0.1
1.5
0.3
2.4
0.3
2.4
7.0
48.0
0.1
1.7
8.0
41.0
70.0
480.0
12.0
69.0
SRB
(cells
mL1)
3.0
23.0
24.0
3.0
<0.2
2.3
<0.2
<0.2
0.4
<0.2
<0.2
<0.2
0.4
5.0
2.3
1.3
1.3
26.0
500.0
50.0
L
limit
U
limit
1.0
12.0
9.0
86.0
10.0
94.0
1.0
12.0
0.9
8.6
0.1
1.7
0.1
1.7
2.0
17.0
0.9
8.6
0.5
3.8
0.5
3.8
12.0
65.0
200.0
2000.0
20.0
170.0
142
Depth
(m)
Table A-8. Continued.
BoreHole
sampled
(Y-M-D)
Depth
(m)
NRB
(cells
mL1)
PVP1
2004-05-04
3.9
PVP1
2005-10-11
3.9
PVP1
2006-04-27
3.9
L
limit
2006-10-12
3.9
PVP3A
2004-05-03
7.8
PVP3B
2004-05-03
3.8
PVP4A
2004-05-04
9.6
PVP4A
2005-10-12
10.2
PVP4A
2006-10-10
10.2
PVP4A:1
2006-04-27
10.2
PVP4A:2
2006-04-27
10.2
PVP4A:1/2
PVP4B
2006-04-27
2004-05-04
10.2
8.0
PVP13
2005-10-12
5.6
PVP13
2006-04-26
5.6
PVP13
2006-10-12
5.6
PVP14
2005-10-13
9.0
PVP14
2006-04-26
9.0
PVP14
2006-10-10
9.0
PVP20S
2005-10-13
12.8
PVP20P
2005-10-13
12.8
PVP20
2006-04-26
12.8
ICE-
COVER
PVP20
2006-10-10
12.8
300
100
IRB
(cells
mL1)
200.0
1700.0
20.0
170.0
20.0
170.0
0.1
1.7
0.3
2.4
20.0
170.0
50.0
390.0
0.9
8.6
0.4
<0.2
1.3
0.4
n.a.
0.4
1.3
0.2
<0.2
<0.2
<0.2
1.3
1.3
2.3
0.8
<0.2
1.3
<0.2
2.2
0.4
1200
1.3
10000.0
94000.0
60.0
360.0
300.0
2500.0
1.2
6.7
40.0
300.0
20.0
150.0
L
limit
0.1
U
limit
1.7
MRB
(cells
mL1)
0.9
5.6
0.1
1.7
9.0
1.3
500.0
2.3
n.a.
0.0
0.0
1.4
0.8
<0.2
<0.2
2.3
33.0
24.0
2.3
5.0
0.4
24.0
8.0
2.3
0.5
3.8
1600
0.5
3.8
0.1
1.7
0.1
1.7
0.5
3.8
0.1
1.1
0.5
3.8
0.5
3.8
0.9
8.6
0.3
2.4
0.5
3.8
L
limit
U
limit
4.0
25.0
0.5
3.8
200.0
2000.0
0.9
8.6
0.6
3.5
0.3
2.4
0.9
8.6
15.0
77.0
10.0
94.0
0.9
8.6
2.0
17.0
0.1
1.7
10.0
94.0
3.0
25.0
0.9
8.6
SRB
(cells
mL1)
0.8
1.3
1600.0
5.0
n.a.
2.3
0.2
<0.2
<0.2
0.8
0.2
4
1.3
5.0
8.0
0.0
0.4
0.4
<0.2
5.0
3.0
3.0
L
limit
U
limit
0.3
2.4
0.5
3.8
600.0
5300.0
2.0
17.0
0.9
8.6
0.1
1.1
0.3
2.4
0.1
1.1
0.5
3.8
2.0
17.0
3.0
25.0
0.1
1.5
0.1
1.7
2.0
15.0
1.0
12.0
1.0
12.0
143
PVP1
n.a.
160.0
24000.0
140.0
n.a.
n.a.
n.a.
800.0
2.7
110.0
50.0
2.2
n.a.
500.0
50.0
50.0
0.4
0.8
50.0
130.0
2.3
U
limit
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.
Borehole
sampled
(Y-M-D)
Depth
(m)
PR1
2004-05-04
6.0
PR1
2005-10-10
6.0
PR1
2006-04-25
6.0
2006-10-11
6.0
PP2
2004-05-05
14.7
PP2
2005-10-12
14.7
PP2
2006-04-24
14.7
PP2
2006-10-11
14.7
PP3
2004-05-05
14.3
PP7
2004-05-05
16.2
PP8
2004-05-06
15.2
PP9
2005-10-13
14.7
PP9
2006-04-27
14.7
PP9
2006-10-09
14.7
PP36
2005-10-10
12.1
PP36
2006-04-25
12.1
PP36
2006-10-09
12.1
PP39
2005-10-11
14.1
PP39
2006-04-24
14.1
PP39
2006-10-11
14.1
160.0
50.0
500.0
50.0
<0.2
110.0
11.0
2.2
0.4
5.0
220.0
1.1
1.7
50.0
50.0
110.0
80.0
130.0
220.0
1100
L
limit
U
limit
20.0
170.0
200.0
2000.0
20.0
170.0
40.0
300.0
4.0
30.0
0.9
5.6
0.1
1.5
2.0
17.0
100.0
580.0
0.4
2.9
0.7
4.6
20.0
170.0
20.0
150.0
40.0
300.0
30.0
2500.0
50.0
390.0
100.0
580.0
400.0
3000.0
HA
cells
mL1
<0.2
50.0
80.0
8.0
<0.2
2.3
3.0
8.0
1.4
5.0
5.0
0.8
2.3
140.0
30.0
130.0
30.0
50.0
170.0
1700
L
limit
U
limit
20.0
170.0
30.0
250.0
3.0
25.0
0.9
8.6
1.0
12.0
3.0
25.0
0.6
3.5
2.0
17.0
2.0
15.0
0.3
2.4
0.9
8.6
60.0
360.0
10.0
130.0
50.0
390.0
10.0
120.0
20.0
170.0
70.0
480.0
700
4800
AM
cells
mL1
0.2
<0.2
14.0
0.0
1.1
<0.2
0.2
<0.2
1.1
6.0
1.7
<0.2
0.4
<0.2
<0.2
0.3
<0.2
3.0
2.3
2.7
L
limit
0.1
U
limit
1.1
6.0
36.0
0.4
2.9
0.1
1.0
0.4
2.9
3.0
18.0
0.7
4.0
0.1
0.1
1.7
1.2
1.0
12.0
0.9
8.6
1.2
6.7
HM
cells
mL1
0.2
<0.2
17.0
0.7
0.7
<0.2
0.0
<0.2
1.1
3.0
0.9
<0.2
<0.2
<0.2
<0.2
0.4
<0.2
<0.2
0.4
2.7
L
limit
0.1
U
limit
1.1
8.0
41.0
0.2
2.1
0.2
2.1
0.4
2.9
1.0
12.0
0.3
2.5
0.1
1.7
0.1
1.7
1.2
6.7
MOB
cells
mL1
n.a.
5000
24.0
17.0
n.a.
13.0
5.0
4.3
150
4.3
3.0
0.9
3.0
2.3
14.0
8.0
300.0
13.0
280.0
L
limit
U
limit
2000.0
20000
10.0
94.0
7.0
48.0
5.0
39.0
2.0
17.0
0.9
18
40
430
0.9
18
1.0
12.0
0.3
2.4
1.0
12.0
0.9
8.6
6.0
36.0
3.0
25.0
100.0
1200.0
5.0
39.0
120.0
690.0
144
PR1
AA
cells
mL1
Table A-9. Continued
Borehole
sampled
(Y-M-D)
Depth
(m)
PVP1
2004-05-04
3.9
PVP1
2005-10-11
3.9
PVP1
2006-04-27
3.9
PVP1
2006-10-12
3.9
PVP3A
2004-05-03
7.8
AA
cells
mL1
L
limit
2004-05-03
3.8
PVP4A
2004-05-04
9.6
PVP4A
2005-10-12
10.2
PVP4A
2006-10-10
10.2
PVP4A:1
2006-04-27
10.2
PVP4A:2
2006-04-27
10.2
PVP4A:1/2
PVP4B
2006-04-27
2004-05-04
10.2
8.0
PVP13
2005-10-12
5.6
PVP13
2006-04-26
5.6
PVP13
2006-10-12
5.6
PVP14
2005-10-13
9.0
PVP14
2006-04-26
9.0
PVP14
2006-10-10
9.0
PVP20S
2005-10-13
12.8
PVP20P
2005-10-13
12.8
PVP20
2006-04-26
12.8
ICE
COVER
PVP20
2006-10-10
12.8
2800
1200
10.0
120.0
10.0
120.0
10.0
130.0
40.0
300.0
0.9
5.6
10.0
120.0
30.0
250.0
100.0
940.0
100.0
580.0
10.0
120.0
2.0
17.0
1.2
6.7
10.0
120.0
600.0
5300.0
70.0
480.0
6900
HA
cells
mL1
11.0
30.0
1600.0
23.0
n.a.
30.0
n.a.
130.0
7.0
30.0
3.0
10
n.a.
90.0
80.0
22.0
3.0
2.3
24.0
30.0
30.0
L
limit
U
limit
4.0
30.0
10.0
130.0
AM
cells
mL1
40.0
250.0
30.0
250.0
10.0
58.0
1.0
12.0
0.9
8.6
10.0
94.0
10.0
130.0
10.0
120.0
1.3
<0.2
<0.2
<0.2
n.a.
3.4
3.4
<0.2
<0.2
11.0
<0.2
0.8
0.8
2.2
<0.2
<0.2
<0.2
<0.2
<0.2
<0.2
2200 1000
5800
0.2
9.0
86.0
10.0
130.0
50.0
390.0
3.0
21.0
10.0
120.0
1.0
12.0
L
limit
U
limit
0.5
3.8
0.1
1.6
8.0
1.6
8.0
4.0
30.0
0.3
2.4
0.3
2.4
0.9
5.6
1.1
HM
cells
mL1
<0.2
<0.2
<0.2
<0.2
n.a.
3.3
0.4
<0.2
<0.2
<0.2
<0.2
0.8
<0.2
<0.2
<0.2
<0.2
<0.2
<0.2
<0.2
<0.2
<0.2
L
limit
U
limit
1.5
7.7
0.1
1.7
0.3
2.4
MOB
cells
mL1
<0.2
5.0
14.0
1.7
n.a.
11000
460
300.0
0.2
50.0
24.0
2.1
n.a.
2.3
1.3
0.2
n.a.
1.3
230.0
2.3
1.2
5.0
L
limit
U
limit
2.0
17.0
6.0
36.0
0.7
4.6
18000
41000
90
2000
100.0
1200.0
0.1
1.1
20.0
170.0
10.0
94.0
0.9
8.6
0.5
3.8
0.1
1.1
0.5
3.8
90.0
860.0
0.9
8.6
0.5
2.9
2.0
17.0
145
PVP3B
<0.2
30.0
1600.0
30.0
n.a.
30.0
n.a.
110.0
2.2
30.0
80.0
0.38
n.a.
240.0
220.0
30.0
5.0
2.7
30.0
1600.0
170.0
U
limit
Table A-10. Biomass determinations for deep groundwater in Olkiluoto. TNC = total number of cells, SD = standard deviation, n = number of
observations, CHAB = cultivable heterotrophic aerobic bacteria, 6MPN = 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)
2004-12-20
2006-05-11
2006-06-26
2006-08-22
2006-10-16
2005-03-01
2005-10-25
2006-06-06
2005-02-21
2006-06-19
2004-10-12
2006-03-14
2004-11-08
2004-11-09
2005-01-17
2006-10-24
2006-01-10
2006-01-24
2006-11-28
2006-04-03
2006-05-30
328.5–330.5
422–425
125–130
135–137
98.5–100.5
275.5–289.5
77.0–84.0
302.0–310.0
115.5–118.5
326.0–328.0
362.0–365.0
362.0–365.0
525.5–539.5
247.0–264.0
503.0–506.0
143.0–146.0
50.0–52.0
95.0–107.0
166–176
403.0–406.0
108.0–110.0
Mid
elevation,
z
(m)
306.2
328.4
94.1
101.8
73.7
249.4
57.3
260.7
106.0
316.0
294.0
294.0
449.6
193.5
391.7
122.4
34.6
70.6
111.6
344.8
88.2
TNC
SD
n
(cells
mL1)
120000
100000
2700
23000
4500
74000
130000
11000
140000
110000
110000
27000
150000
29000
21000
19000
26000
40000
14000
22000
21000
ATP
SD
n
(amol
mL1)
24000
7800
1400
3900
1300
15000
27000
2800
21000
15000
27000
14000
25000
14000
4000
2600
7600
15000
730
7600
960
6
2
3
3
3
6
6
3
6
3
6
6
6
6
6
3
6
5
3
3
3
206000
66800
5720
15300
3090
15800
6960
5730
20800
25000
82200
15580
n.a.
36400
n.a.
10929
23400
6970
8020
7440
13080
CHAB
SD
n
(cells
mL1)
40500
1520
1390
410
170
210
440
320
10900
1800
9580
200
3
3
3
3
3
3
3
3
3
3
3
3
4590
3
940
1890
490
200
260
750
3
3
3
3
3
3
n.a.
120000
503
16300
1090
n.a.
497
820
n.a.
1390
n.a.
16300
n.a.
n.a.
n.a.
4230
2430
10
3070
180
3150
CHAB/
ATP/
6MPN/
TNC
TNC
TNC
(%)
(%)
5600
187
4730
21
3
3
3
3
120.00
18.63
70.87
24.22
21
123
3
3
0.38
7.45
21
3
3400
3
1.26
0.00
60.37
1.717
0.668
2.119
0.665
0.687
0.214
0.054
0.521
0.149
0.227
0.747
0.577
22.26
9.35
0.03
21.93
0.82
15.00
1.255
0.575
0.900
0.174
0.573
0.338
0.623
351
379
10
473
25
778
3
3
3
3
3
2
0.70
30.25
20.00
22.55
1.08
0.02
0.16
1.89
0.22
0.32
0.07
3.56
0.17
0.05
0.12
6.20
5.30
0.37
21.66
1.60
1.83
146
OL-KR2
OL-KR6
OL-KR6
OL-KR6
OL-KR6
OL-KR7
OL-KR8
OL-KR8
OL-KR10
OL-KR10
OL-KR13
OL-KR13
OL-KR19
OL-KR27
OL-KR27
OL-KR31
OL-KR32
OL-KR33
OL-KR37
OL-KR39
OL-KR39
Section
upper–lower
(m)
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 methaneoxidizing 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)
2004-12-20
2006-05-11
2006-06-26
2006-08-22
2006-10-16
2005-03-01
2005-10-25
2006-06-06
2005-02-21
2006-06-19
2004-10-12
2006-03-14
2004-11-08
2004-11-09
2005-01-17
2006-10-24
2006-01-10
2006-01-24
2006-11-28
2006-04-03
2006-05-30
328.5–330.5
422–425
125–130
135–137
98.5–100.5
275.5–289.5
77.0–84.0
302.0–310.0
115.5–118.5
326.0–328.0
362.0–365.0
362.0–365.0
525.5–539.5
247.0–264.0
503.0–506.0
143.0–146.0
50.0–52.0
95.0–107.0
166–176
403.0–406.0
108.0–110.0
Mid
elevation,
z
(m)
306.2
328.4
94.1
101.8
73.7
249.4
57.3
260.7
106.0
316.0
294.0
294.0
449.6
193.5
391.7
122.4
34.6
70.6
111.6
344.8
88.2
NRB
(cells
mL1)
n.a.
30000
500.0
5000.0
28.0
n.a.
110.0
80.0
n.a.
240.0
n.a.
800.0
n.a.
n.a.
n.a.
1100.0
1300.0
8.0
3000.0
300.0
240.0
L
limit
U
limit
10000.0
200.0
2000.0
12.0
130000
1500.0
20000.0
69.0
40.0
30.0
300.0
250.0
100.0
940.0
300.0
2500.0
400.0
500.0
3.0
1000.0
100.0
100.0
3000.0
3900.0
25.0
12000.0
1200.0
940.0
IRB
(cells
mL1)
300
28.0
2.3
<0.2
2.3
<0.2
0.2
0.4
<0.2
<0.2
0.8
5.0
<0.2
1.7
<0.2
0.8
24.0
80.0
0.4
11.0
0.7
L
limit
U
limit
MRB
(cells
mL1)
L
limit
U
limit
100.0
12.0
0.9
1300.0
69.0
8.6
0.9
8.6
100.0
10.0
0.9
80.0
0.1
1300
120.0
8.6
410.0
1.1
0.1
0.1
1.1
1.7
0.1
1.7
0.3
2.0
2.8
17.0
30.0
210.0
0.7
4.6
0.4
2.9
0.3
10.0
30.0
0.1
4.0
0.2
2.4
94.0
250.0
1.7
30.0
2.1
300.0
30.0
2.3
170.0
0.2
<0.2
0.4
<0.2
<0.2
<0.2
<0.2
70.0
<0.2
1.1
<0.2
22.0
24.0
22.0
2.3
2.2
0.4
10.0
10.0
9.0
0.9
0.9
0.1
58.0
94.0
56.0
8.6
5.6
1.7
SRB
(cells
mL1)
<0.2
90.0
1.3
1.3
3.0
<0.2
3.0
7.0
0.2
24.0
<0.2
13.0
<0.2
<0.2
<0.2
1.3
0.4
7.0
3.0
1.3
11.0
L
limit
U
limit
30.0
0.5
0.5
1.0
290.0
3.8
3.8
12.0
1.0
3.0
0.1
10.0
12.0
21.0
1.1
94.0
5.0
39.0
0.5
0.1
2.0
1.0
0.5
4.0
3.8
1.7
21.0
12.0
3.8
30.0
147
OL-KR2
OL-KR6
OL-KR6
OL-KR6
OL-KR6
OL-KR7
OL-KR8
OL-KR8
OL-KR10
OL-KR10
OL-KR13
OL-KR13
OL-KR19
OL-KR27
OL-KR27
OL-KR31
OL-KR32
OL-KR33
OL-KR37
OL-KR39
OL-KR39
Section
upper–lower
(m)
Table A-11. Continued.
Borehole
sampled
(Y-M-D)
Section
Mid elevation,
upper–lower
z
(m)
(m)
2004-12-20
328.5–330.5
306.2
OL-KR6
2006-05-11
422–425
328.4
OL-KR6
2006-06-26
125–130
94.1
OL-KR6
2006-08-22
135–137
101.8
OL-KR6
2006-10-16
98.5–100.5
73.7
OL-KR7
2005-03-01
275.5–289.5
249.4
OL-KR8
2005-10-25
77.0–84.0
OL-KR8
2006-06-06
302.0–310.0
260.7
OL-KR10
2005-02-21
115.5–118.5
106.0
OL-KR10
2006-06-19
326.0–328.0
316.0
OL-KR13
2004-10-12
362.0–365.0
294.0
OL-KR13
2006-03-14
362.0–365.0
294.0
OL-KR19
2004-11-08
525.5–539.5
449.6
OL-KR27
2004-11-09
247.0–264.0
193.5
OL-KR27
2005-01-17
503.0–506.0
391.7
OL-KR31
2006-10-24
143.0–146.0
122.4
OL-KR32
2006-01-10
50.0–52.0
34.6
OL-KR33
2006-01-24
95.0–107.0
70.6
OL-KR37
2006-11-28
166–176
111.6
OL-KR39
2006-04-03
403.0–406.0
344.8
OL-KR39
2006-05-30
108.0–110.0
88.2
57.3
(cells
mL1)
110.0
24.0
17.0
2.3
7.0
3.0
70.0
50.0
130.0
30.0
24.0
50.0
170.0
0.4
0.4
30.0
17.0
24.0
24.0
30.0
50.0
L
limit
U
limit
40.0
300.0
10.0
94.0
7.0
48.0
0.9
8.6
3.0
21.0
1.0
12.0
30.0
210.0
20.0
170.0
50.0
390.0
10.0
120.0
10.0
94.0
20.0
200.0
80.0
410.0
0.1
1.7
0.1
1.7
10.0
120.0
7.0
48.0
10.0
94.0
10.0
94.0
10.0
130.0
20.0
170.0
HA
(cells
mL1)
130.0
80.0
17.0
13.0
8.0
8.0
30.0
70.0
170.0
50.0
13.0
24.0
80.0
7.0
1.3
23.0
13.0
8.0
3.0
8.0
80.0
L
limit
U
limit
50.0
390.0
30.0
250.0
7.0
48.0
5.0
39.0
3.0
25.0
3.0
25.0
10.0
120.0
30.0
210.0
70.0
480.0
20.0
170.0
5.0
38.0
10.0
94.0
30.0
250.0
2.0
21.0
0.5
3.8
9.0
56.0
5.0
39.0
3.0
25.0
10.0
12.0
3.0
25.0
30.0
250.0
AM
(cells
mL1)
0.4
<0.2
<0.2
<0.2
<0.2
5.0
<0.2
0.2
<0.2
0.2
13.0
<0.2
2.3
1.3
0.2
0.2
<0.2
<0.2
<0.2
<0.2
0.2
L
limit
0.1
U
limit
1.7
2.0
17.0
0.1
1.1
0.1
1.1
5.0
39.0
0.9
8.6
0.5
3.8
0.1
1.1
0.1
1.1
0.1
1.1
HM
(cells
mL1)
2.3
0.2
<0.2
<0.2
<0.2
2.3
<0.2
0.2
2.3
2.3
24.0
<0.2
2.3
2.3
24.0
<0.2
<0.2
<0.2
<0.2
<0.2
2.3
L
limit
U
limit
0.9
8.6
0.1
1.1
0.9
8.6
0.1
1.1
0.9
8.6
0.9
8.6
10.0
94.0
0.9
8.6
0.9
8.6
10.0
94.0
0.9
8.6
148
OL-KR2
AA
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 (104 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
x The precision of the extractions is currently approximately ± 6% (Table A-12).
x The uncertainty of the instruments and repeated injections is low, typically 0–
4% (Table A-13).
x The calibration gases used have a maximum accepted mixing uncertainty of ±
2%.
x 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
H2
O2
Nitrogen
25,700
964
10,900
962,436 ppm
ppm
ppm
ppm
Special gas 2 (Linde Gas), AGA, certificate no: 28757-1:
Ar
CH4
CO2
CO
Nitrogen
1000
2740
1040
9.75
995,210 ppm
ppm
ppm
ppm
ppm
Special gas 3 (Linde Gas), AGA, certificate no: 28749-1:
C2H6
C2H4
C2H2
C3H8
C3H6
Nitrogen
253
257
248
252
238
998,752 ppm
ppm
ppm
ppm
ppm
ppm
Special gas 4 (Linde Gas), AGA, certificate no: 30008-1:
H2
CO
Nitrogen
24.6
24.9
999,950 ppm
ppm
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 u 1/16-inch stainless steel HayeSep column in line with a 31 u 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 u 1/8 inch
diameter; Agilent Technologies) followed by a molecular sieve 5A column (6 m u 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 u 10–9 L (20
ppm).
Carbon monoxide was analysed on a KAPPA-5/E-002 analyser gas chromatograph
equipped with a 156 u 1/16-inch stainless steel HayeSep column in line with a 31 u 1/8inch 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 u 1/8 inch diameter) followed by a molecular sieve 5A column
(6 m u 1/8 inch) with argon as the carrier gas.
The detection limit of the instrument with a 250-µL injection loop is 5 u 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 u 1/8 inch diameter) followed by a molecular Sieve 5A column
(6 m u 1/8 inch). Argon or helium can be used as the carrier gas. The results obtained
153
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 u 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 u 1/8 inch diameter) followed by a molecular sieve 5A column
(6 m u 1/8 inch) with argon as the carrier gas.
The detection limit of the instrument with a 250-µL injection loop is 25 u 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 u 1/8 inch diameter) followed by a molecular sieve 5A column
(6 m u 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 u 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 u 1/8 inch diameter) and transformed to methane using a 10% Ni2NO3
“methanizer” fed with hydrogen gas (9.375 u 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 u 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 u 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 u 1/8 inch
diameter) and analysed on the FID with nitrogen as the carrier gas. This configuration
used a 156 u 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
154
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 u 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 u 1/8 inch diameter) and analysed on the FID with nitrogen as
the carrier gas. This configuration used a 156 u 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 u 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.
155
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, PL
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%)
0.35
KJ52F01-2 a
0.37
KJ52F01-2 b
0.36 (± 1.4%)
Average (± SD%)
Carbon dioxide
31.5
33
32.3 (± 2.3%)
Methane
263
284
274 (± 3.8%)
0.12
KJ52F01-3 a
0.120
KJ52F01-3 b
0.12 (± 0%)
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%)
Ethane
Ethane
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.
156
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
Hydrogen
KJ52F01-1
(ppm)
KJ52F01-2
(ppm)
KJ52F01-3
(ppm)
Average (±
SD%)
87.2
18.2
24.3
43.2 (± 72%)
Helium
Argon
69,000
79,100
95,000
81030 (±
13.2%)
2170
2150
5190
3170 (± 45%)
Nitrogen
894,000
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
: