m
United States
Environmental Protection
Agency
Microfracture Surface
" Characterizations: Implications
for In Situ Remedial Methods in
Fractured Rock
Bedrock Bioremediation Center
Final Report
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EPA/600/R-05/121
June 2006
Microfracture Surface Characterizations:
Implications for In Situ Remedial Methods
in Fractured Rock
Bedrock Bioremediation Center
Final Report
T.T. Eighmy
J.C.M. Spear
J. Case
H. Marbet
J. Casas
W. Bothner
J. Coulburn
LS.Tisa
M. Majko
E. Sullivan
M. Mills
K. Newman
N.E. Kinner
Cooperative Agreement No. CR-827878-01-0
Project Officer
Mary Gonsoulin
Ground Water and Ecosystems Restoration Division
National Risk Management Research Laboratory
Ada, Oklahoma 74820
National Risk Management Research Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Cincinnati, OH 45268
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Notice
The U.S. Environmental Protection Agency through its Office of
Research and Development funded, managed, and collaborated
in the research described here under Cooperative Agreement No.
CR-827878-01-0 to the USEPA. It has been subjected to the Agency's
peer and administrative review and has been approved for publication
as an EPA document. Mention of trade names or commercial
products does not constitute endorsement or recommendation for use.
All research projects making conclusions or recommendations based on
environmentally related measurements and funded by the U.S. Environmental
Protection Agency are required to participate in the Agency Quality
Assurance Program. This project did not involve environmentally related
measurements and, as such, did not require a Quality Assurance Plan.
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Foreword
The U.S. Environmental Protection Agency is charged by Congress with protecting the Nation's land, air,
and water resources. Under a mandate of national environmental laws, the Agency strives to formulate
and implement actions leading to a compatible balance between human activities and the ability of natural
systems to support and nurture life. To meet this mandate, EPA's research program is providing data
and technical support for solving environmental problems today and building a science knowledge base
necessary to manage our ecological resources wisely, understand how pollutants affect our health, and
prevent or reduce environmental risks in the future.
The National Risk Management Research Laboratory is the Agency's center for investigation of
technological and management approaches for preventing and reducing risks from pollution that threatens
human health and the environment. The focus of the Laboratory's research program is on methods and
their cost-effectiveness for prevention and control of pollution to air, land, water, and subsurface resources;
protection of water quality in public water systems; remediation of contaminated sites, sediments and ground
water; prevention and control of indoor air pollution; and restoration of ecosystems. NRMRL collaborates
with both public and private sector partners to foster technologies that reduce the cost of compliance and
to anticipate emerging problems. NRMRL's research provides solutions to environmental problems by:
developing and promoting technologies that protect and improve the environment; advancing scientific and
engineering information to support regulatory and policy decisions; and providing the technical support
and information transfer to ensure implementation of environmental regulations and strategies at the
national, state, and community levels.
This publication has been produced as part of the Laboratory's strategic long-term research plan. It is
published and made available by EPA's Office of Research and Development to assist the user community
and to link researchers with their clients.
Stephen G. Schmelling, DirecJ
Ground Water and Ecosystems; Restoration Division
National Risk Management Research Laboratory
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Table of Contents
Notice ii
Foreword iii
Executive Summary E1
List of Tables vii
List of Figures viii
Abbreviations x
Chapter 1 Introduction 1
1.1 Microfractures and Their Role in Reaction and Transport 1
1.2 Microfracture Definition 3
1.3 Microbes in Bedrock 4
1.4 Microbe-Mineral Interactions 5
1.5 Chlorinated Solvent Abiotic and Biotic Transformations 6
1.6 Determination of Likely Terminal Electron Accepting Processes 10
1.7 Related Field Work on Bedrock TCE Contaminated Sites 10
1.8 Spectroscopic Characterization of Surfaces 11
1.9 Objectives of This Study 11
Chapter 2 Materials and Methods 12
2.1 Core/Microfracture Locations 12
2.2 Core/Microfracture Sample Collection 15
2.3 Microfracture Sample Preparation 16
2.4 Overall Analytical Sequence 16
2.5 SEM-Morphology and Biopatch Distribution 17
2.6 SEM-EDAX Spatial Maps 18
2.7 Microfracture Surface Precipitate Fixation & Embedding forTEM 18
2.8 TEM-Microbial Ultrastructure 18
2.9 Petrographic Thin Sections 18
2.10 SEM-EDAX Spatial Mapping Microfracture Surface Precipitates and Host Rock 19
2.11 XRD Analysis of Microfracture Surfaces and Host Rock 19
2.12 XPS Speciation of Microfracture Surfaces 20
2.13 SIMS Fingerprints of Microfracture Surfaces 21
2.14 MlPof Host Rock 21
2.15 Packer Water Collection 22
2.16 Geochemical Modeling 22
2.17 Microbe Extraction 22
2.18 Microbial Characterization Using Molecular Biological Techniques 23
2.19 Primers and Polymerase Chain Reaction Assay 24
2.20 Denaturing Gradient Gel Electrophoresis 24
2.21 DMA Sequencing & Analysis 24
2.22 Data Quality 25
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Table of Contents, continued
Chapter 3 Results & Discussion 28
3.1 Microfracture Locations 28
3.2 Microfracture Surface Precipitate Morphology 28
3.3 Microfracture Element Spatial Maps 30
3.4 Microfracture Biopatch Distribution and Morphology 32
3.5 Microfracture Microbial Populations Situated Within Surface Precipitates 35
3.6 Petrographic Characterization of Host Rock and Microfracture Surfaces 39
3.7 Mineralogy of Microfracture Surfaces and Host Rock Based on XRD 45
3.8 Element Speciation of Microfracture Surfaces Based on XPS 49
3.9 Packer Water Characterization and Geochemical Modeling 59
3.10 Mass Fragment Fingerprints of Microfracture Surfaces 63
3.11 Porosity and Pore Size Distribution of Host Rock 65
3.12 Microbes Identified on Microfractures 65
3.13 Relationship between Packer Water Samples and Microfracture Geochemical
Environment 67
3.14 Likely Terminal Electron Accepting Processes in the Open Fracture System 68
3.15 Likely Terminal Electron Accepting Processes in the Microfracture Network 69
3.16 Microfracture Surface Speciation and Adherent Microbial Population Metabolism
and Diversity 70
3.17 Role of Microfracture Surfaces in TCE Transformation and Microbial Ecology 72
Chapter 4 Conclusions 73
Acknowledgements 76
References 77
VI
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List of Tables
Table 1.1 Microfracture Description Protocol 3
Table 1.2 Conditions for Abiotic and Biotic Transformation of Chlorinated Solvents
(adapted from McCarty, 1997b) 8
Table 1.3 Environmental Conditions for Biological Reductive Dechlorination Reactions
(adapted from McCarty, 1997b) 8
Table 1.4 Properties of Some Direct Chlorinated Solvent Dechlorinators
(adapted from Gossett and Zinder, 1997) 9
Table 2.1 Microfracture Location, Cluster Assignment, and Description 14
Table 2.2 Analytical Methods Applied to the Host Rock and Microfracture Samples 15
Table 3.1 Summary Description of Surface Precipitate Morphologies 29
Table 3.2 Summary Description of Element Association in Spatial Maps 31
Table 3.3 Mineral Phases Identified by Petrography in Host Rock 42
Table 3.4 Mineral Phases Identified by Petrography in Microfracture Surface Precipitates 44
Table 3.5 Summary of Crystalline Minerals Identified in Host Rock Samples 47
Table 3.6 Microfracture Surface Precipitate Candidate Minerals Based on XRD 48
Table 3.7 Microfracture MF02 - Candidate Minerals by XPS 50
Table 3.8 Microfracture MF03 - Candidate Minerals by XPS 51
Table 3.9 Microfracture MF04 - Candidate Minerals by XPS 52
Table 3.10 Microfracture MF05 - Candidate Minerals by XPS 53
Table 3.11 Microfracture MF06 - Candidate Minerals by XPS 54
Table 3.12 Microfracture MF07 - Candidate Minerals by XPS 55
Table 3.13 Microfracture MF08 - Candidate Minerals by XPS 56
Table 3.14 Microfracture MF09 - Candidate Minerals by XPS 57
Table 3.15 Microfracture MF10 - Candidate Minerals by XPS 58
Table 3.16 Packer Water Characterizations 60
Table 3.17 Candidate Controlling Solid Minerals in Packer Waters Identified by Geochemical
Modeling 62
Table 3.18 Presence or Absence of Prokaryotic Groups on Borehole BBC5 Microfracture
Surfaces as Determined by Amplification with Specific Primer Sets 66
Table 3.19 Prokaryotic Groups on Borehole BBC5 Microfracture Surfaces Relative to Fe, S,
andC 71
VII
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List of Figures
Figure 1.1 Conceptual model of adherent biopatch (in cross section) on a microfracture
surface 2
Figure 1.2 Suite of analytical methods for characterization of bulk and surface chemistry 11
Figure 2.1 Cross section through BBC site 12
Figure 2.2 Plan view of borehole locations at Site 32 13
Figure 2.3 Cross section through boreholes BBC5 and BBC6 showing microfracture
locations and hydrologic connections between the two boreholes 14
Figure 2.4 Schematic depiction of microfracture-type sampling 16
Figure 2.5 Analytical scheme 17
Figure 3.1 SEM micrographs of typical microfracture morphology 29
Figure 3.2 Typical EDS elemental spatial map in X-Y plane for microfracture MF03 30
Figure 3.3 Biopatch SEM micrographs 32
Figure 3.4 Biopatch SEM micrographs 33
Figure 3.5 Biopatch SEM micrographs 34
Figure 3.6 TEM micrographs of stalked morphologies present in calcite precipitates
on microfracture MF11 35
Figure 3.7 TEM micrographs of spirillum morphologies in calcite precipitates
in microfracture MF11 36
Figure 3.8 TEM micrographs of filamentous morphologies in calcite precipitates
in microfracture MF11 37
Figure 3.9 TEM micrographs of inclusion bodies within cell structures in calcite precipitates
in microfracture MF11 38
Figure 3.10 Petrographic thin section of Kittery metasandstone 39
Figure 3.11 Photomicrographs of the same region of a petrographic thin section in (a) plane,
(b) cross-polarized, and (c) reflected light 39
Figure 3.12 Diabase dike textures and microfracture fillings 40
Figure 3.13 Photomicrographs of microfracture textures and morphology 41
Figure 3.14 Petrographic micrographs of host rock and microfracture surfaces 43
Figure 3.15 Element spatial map of microfracture MF07 thin section showing host rock and
microfracture face in cross section 44
Figure 3.16 Typical raw diffractogram 45
Figure 3.17 Typical diffractogram after background removal and smoothing 45
Figure 3.18 Typical peak ID as determined by search match routine 46
Figure 3.19 Diffractogram of host rock from microfracture MF07 46
Figure 3.20 Diffractogram of microfracture surface precipitate from microfracture MF07 47
Figure 3.21 Typical XPS low resolution survey scan of microfracture MF02 49
Figure 3.22 Typical component curve fit exercise for the C1s photoelectron
from a high resolution scan for microfracture MF02 49
VIM
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List of Figures, continued
Figure 3.23 SIMS negative mass fragment (0-50 atomic mass units) fingerprint 63
Figure 3.24 SIMS positive mass fragment (0-50 atomic mass units) fingerprint 63
Figure 3.25 SIMS positive mass fragment (50-100 atomic mass units) fingerprint 64
Figure 3.26 MIP cumulative porosity and pore size distribution for borehole BBC5 host rock
specimen 65
Figure 3.27 Polymerase chain reaction-denaturing gradient gel electrophoresis bacterial
community profiles of borehole BBC5 microfractures MF01 - MF07 66
Figure 3.28 Cluster analysis of the denaturing gradient gel electrophoresis banding patterns
of borehole BBC5 microfracture surfaces based on the position of bands using
unweighted paired group method with arithmetic averages 67
IX
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Abbreviations
AFCEE Air Force Center for Environmental Excellence
BBC Bedrock Bioremediation Center
DCA dichloroethane
DCE dichloroethene
DGGE denaturing gradient gel electrophoresis
DPR drilling parameter recorder
EDAX energy dispersive analysis of x-rays
ESCA electron spectroscopy for chemical analysis
FESEM Field Emission Scanning Electron Microscopy
GC guanine-cytosine
GC/MS gas chromatography/mass spectrometry
ICDD International Center for Diffraction Data
IHSS International Humic Substances Society
MIP mercury intrusion porosimetry
NIST National Institute for Standards and Technology
NOM natural organic matter
NPDOC non-purgeable dissolved organic carbon
PCE perchloroethene
PCR polymerase chain reaction
SEM scanning electron microscopy
SIMS secondary ion mass spectrometry
TCE trichloroethene
TEM transmission electron microscopy
Tl Technical Impracticability
TOF time-of-flight
UST underground storage tank
VC vinyl chloride
XPS x-ray photoelectron spectroscopy
XRD x-ray diffraction
XRPD x-ray powder diffraction
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Executive Summary
Purpose: The Bedrock Bioremediation Center (BBC) at the University of New Hampshire is a center specializing in
multi-disciplinary research on bioremediation of organically-contaminated bedrock aquifers. The focus of its present
work is a field research-based program conducted at Site 32 at the Pease International Tradeport (formerly Pease
Air Force Base) in Portsmouth, NH. The U.S. EPA supports the overall mission of the BBC to (i) examine whether
microbial communities in organically-contaminated bedrock aquifers are capable of biodegrading the contaminants,
(ii) more efficiently and economically characterize the direction of groundwater flow and fracture patterns (size,
direction, secondary mineralization) in contaminated bedrock aquifers, (iii) improve and develop new field technologies
to control hydraulic and flow conditions in the contaminant zone, (iv) develop laboratory and field methods to estimate
and accelerate in situ rates of bioremediation of organic contaminants in bedrock aquifers, and (v) to develop and
apply innovative microbial, molecular biology and other advanced techniques to enhance in situ bioremediation and
assess the efficacy of remediation strategies. One of the major outreach efforts of the BBC is to transfer information
gained during its research to federal, state, and local regulatory agencies and environmental consultants.
Background: Site 32 contains a contaminant plume of trichloroethylene (TCE) and its transformation products
dichloroethylene (DCE) and vinyl chloride (VC). These are the principal contaminants. The site is situated on a variable
thickness upper sand layer overlying a marine clay layer overlying a variable thickness lower sand layer. These
unconsolidated layers are situated over the Kittery Formation, a tightly folded, biotite-grade partially metamorphosed
sandstone and shale crosscut by numerous porphryitic diabase dikes. The contaminant plume extends downward
and laterally northeast ~0.5 km via migration through weathered and competent bedrock. The groundwater in the
bedrock is predominately contaminated with c/s-DCE (280-440 ug/L) with some frans-DCE (26-48 ug/L), TCE (24-59
ug/L), and VC (8-22 ug/L). Since 1997 the overburden has been managed using a sheet pile containment system
coupled with pump and treat. The bedrock groundwater zone was given a technical impracticability (Tl) waiver.
Research Questions: The overarching questions addressed by this portion of the project relate to possible relations
between microfracture networks in the bedrock, the surface geochemistry of these microfractures, and the ecology
and metabolic activity of attached microbes relative to terminal electron accepting processes and TCE biodegradation.
Questions include the following: (1) How does the microfracture surface influence attachment and growth? (2) How
does the geochemistry of the microfracture surface influence population ecology and metabolism? (3) What is the
relationship between the relatively high specific surface area of the microfracture network and the adjacent relatively
open and more voluminous open fracture system? More specifically, how does the microfracture surface influence
the dominant terminal electron acceptor processes in the microfracture network? (4) Lastly, what is the precise
nature of TCE biodegradative processes within the microfracture network?
As part of the overall research plan to better understand these questions, we studied 11 microfractures extracted
from competent bedrock cores from two wells at Site 32 (BBC5 and BBC6) so as to characterize, with a variety of
surface spectroscopic and microbial techniques, the relation, if any, between microfracture surface geochemistry
and the ecology and metabolic activity of attached microbial populations relative to terminal electron accepting
processes or to chlorinated solvent biodegradation.
Results are highlighted relative to host rock and microfracture mineralogy and geochemistry, groundwater
geochemistry, microfracture microbiology, and terminal electron accepting processes.
Host Rock and Microfracture Mineralogy and Geochemistry: A variety of spectroscopic techniques are needed
to characterize the mineralogy and chemical speciation of the host rock and the minerals coating the microfracture
surfaces. Mercury intrusion porosimetry (MIP), petrography, scanning electron microscopy- energy dispersive analysis
of x-rays (SEM-EDAX), x-ray powder diffraction (XRD), x-ray photoelectron spectroscopy (XPS), and secondary
ion mass spectrometry (SIMS) were all used to characterize the host rock and microfracture surface precipitates.
Eleven microfractures (MF 01 -11) were extracted from competent rock from cores from two boreholes (BBC5 and
BBC6) located at the study site. Microfracture samples were taken at depths > 21.3 m (70 ft) below ground and
within the contaminant plume. Using MIP, the partially metamorphosed sandstones and shales were found to be
very impermeable. The host rock had three nominal pore throat sizes (131.1, 1.136, and 0.109 urn), a porosity of
0.8%, and a permeability of < 1 uDarcy. The host rock mineralogy was typical of metasandstones and metashales
(quartz, feldspar, white mica, chlorite and/or biotite). Carbonate minerals and quartz were the dominant microfracture
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surface precipitates. Likely oxidized and reduced iron species were identified on the microf racture surfaces with XPS,
including siderite (FeCO3), pyrrhotite (FeS), wustite (FeO), goethite (a-FeOOH), hematite (Fe2O3), aged hydrous ferric
oxide (Fe2O3 • 1.57 H2O), limonite (Fe2O3 • nH2O), and magnetite (Fe3O4). Carbon functional groups characteristic
of humic substances and aquatic natural organic matter (NOM) were also identified with XPS. SIMS mass fragment
fingerprints revealed chlorinated carbon fragments which suggested that TCE or perhaps its transformation products
were partitioned to the NOM on the microfracture surfaces. The level of spatial resolution of this technique was on
the order of 10s of urn. Heterogeneity in mineral abundance on the microfracture surfaces was seen at that level.
Groundwater Geochemistry: Packer sampling techniques were used to collect groundwater samples from
packer intervals associated with some of the collected microfracture samples in boreholes BBC5 and BBC6. The
water collected in the packer intervals (termed packer water) was characterized using various field and laboratory
techniques to describe pH, alkalinity, dissolved gases (H2,O2), and dissolved geochemical constituents. The
analyses were then used to model and interpret (subject to limitations) the geochemistry of the packer waters with
the thermodynamic equilibrium model Visual MINTEQ. Given the volume of the microfracture network relative to
the open fracture system, the samples were expected to reflect more from the composition of the open fractures.
Packer waters were alkaline (131-190 mg/L as CaCO3, pH 8.8 to 9.6), mildly reducing (Eh of -208 to 160 mV, DO
of 0.4 to 2.5 mg/L), with low NPDOC values (0.8 to 1.7 mg/L), and measurable Fe(ll) (0.1 mg/L) and Fe(lll) (0.02
to 0.3 mg/L). H2 was present in a number of the BBC wells at the site (2.2 - 7.3 nM). These levels are capable of
supporting reductive dechlorination and are indicative of sulfate reduction as a dominant terminal electron accepting
process; however, sulfate was the dominant anion in the packer sample water (110-120 mg/L), and no sulfide was
detected. Additionally, no fixed nitrogen was detected. The packer waters were in apparent pseudo-equilibrium with
many of the observed major mineral phases (carbonates and iron oxides) in the host rock and on the microfracture
surfaces. Estimations of Eh using the Nernst equation and activities of Fe2+ and Fe3* suggested that the dominant
redox couple was Fe(ll)/Fe(lll). Estimated values were similar to those measured with a polished platinum inert
redox probe and reference Ag/AgCI electrode.
Microfracture Microbiology: The microbiology of the microfracture surfaces was investigated using SEM, transmission
electron microscopy (TEM), and a number of molecular biology techniques. SEM of microfracture surfaces revealed
occasional biopatches of attached microbes. The biopatches were located in small depressions, cracks, or crevices on
the microfracture surfaces. The microbes were predominantly rod-shaped (1.0 urn in diameter by 2.0 urn in length). In
some instances, the bacteria had possible extracellular polymeric substances associated with them. In other cases,
the microbes appeared encased in a film of organic material or surface precipitate-like material. TEM micrographs
of soft calcite surface precipitate samples from one microfracture revealed more diverse prokaryotic morphologies
(e.g., spirilla, stalked bacteria, filaments). In some cases, flagella and possible cell division septa may have been
present. Many cells contained large, clear organelles and small dark organelles. These may have been storage
bodies. Amplification with specific primer sets of microfractures from borehole BBC5 showed the presence of both
bacteria and Archaea (which includes methanogens) in all of the borehole BBC5 microfracture samples. Positive
results were also observed for dehalorespirers (Dehalococcoides sp.), sulfate reducing bacteria, and iron reducing
bacteria (specifically the Geobacteraceae). Denaturing gradient gel electrophoresis community profiles of the
polymerase chain reaction-amplified bacterial 16S rDNA showed between 7 and 27 band; indicating significant
population diversity of the microfracture surfaces. Dendograms showed that two of seven of the microfractures tested
were similar. All other samples showed significantly different banding patterns, indicating the bacterial communities
on the fracture surfaces were, in most cases, compositionally unique. Microfracture porewater likely differed from
packer water in composition as the microfracture network may have been more reducing than the open fracture
system based on the presence of obligate anaerobes found on the microfracture surfaces.
Terminal Electron Accepting Processes: The preceding information can be used to infer about possible terminal
electron accepting processes occurring in the open fracture system and the microfracture networks. The microfracture
network, by virtue of its smaller volume, reduced communication with the open fracture system, and likely mass
transfer limitations probably did not significantly contribute to the contaminant or biogeochemical signatures seen
in the packer waters collected under fairly transmissive conditions for fractured bedrock at the site. In terms of
identification of likely terminal electron accepting processes in the open fracture system, the H2 values observed for
borehole BBC6 suggested sulfate reduction. However, high levels of sulfate and the non detection of sulfide in the
packer water samples suggested that sulfate reduction was not dominant, rather, Fe(lll) reduction might have been
the dominant terminal electron accepting process. Iron was a dominant microfracture surface element. Both Fe(ll)
and Fe(lll) candidate minerals were observed on the microfracture surfaces. The spatial prevalence of Fe as well
as its situation in the top few nm of the microfracture surface suggested that Fe(lll) was available for iron-reducing
bacteria. The spectroscopic characterization of the microfracture surfaces points to Fe(lll) reduction as perhaps a
dominant process in the microfracture network. There was generally good agreement between SEM-EDAX, XRD,
and XPS about identification of C, S, and Fe within the microfracture surface precipitates and on their surfaces.
However, the observed population diversity cannot be related to the speciation of any of the three elements on the
MF surfaces. The spatial heterogeneity of minerals was quite high on the microfracture surfaces. Mineral grain sizes
were on the order of urn. While minerals may have been common to all observed microfracture surfaces, their relative
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spacing and proximity to each other and to surface topography were quite varied. It may be that the biopatches
that were observed with SEM reflect more localized microbial population response to microfracture surface mineral
speciation.The level of resolution of SEM, SEM-EDAX, and XPS, however, was not high enough to discern such
spatial relationships though such relations are likely.
Possible TCE Biodegradative Processes: The presence of transformation products of dehalorespiration as well
as H2 concentrations supported the role of Dehalococcoides sp. in dehalorespiration in the microfracture networks
under conditions where Fe(lll) reduction was strongly correlated to the presence of oxidized iron species on the
microfracture surfaces. Other means of TCE biodegradation, including abiotic as well as aerobic and anaerobic
respiratory and cometabolic processes, cannot be excluded.
Significance: The bulk of the data suggested that the microfracture networks supported diverse microbial
communities. The communities differed spatially and were not similar to open fracture system planktonic population
compositions. The adherent populations were patchy and associated with microfracture topography. Microbes were
also found within the microfracture surface precipitates themselves, suggesting a more complex mineral-microbe
spatial relationship.The dominant mineralogy on the microfracture surfaces (Fe(ll) and Fe(lll) oxides and carbonates)
was related to the microbial metabolism of some of the identified isolates, notably iron reducers. However, other
types, including obligate anaerobes, suggested that the microfracture network was perhaps more reducing than the
open fracture system, perhaps particularly within the microfracture surface precipitate structure. Dehalococcoides sp.
was a predominant component of the microfracture microbial population and suggested that reductive dechlorination
was one principal process whereby TCE was transformed.
A number of follow on activities are suggested. Methods to collect and characterize microfracture porewaters may help
to better describe terminal electron accepting processes and may elaborate on real differences with packer sample
composition. The relative absence of NOM in the system, as well as the concentration of NOM on microfracture
surfaces deserves further examination. Understanding NOM bioavailability on microfracture surfaces may help to
explain the phylogenetic and metabolic diversity seen on the microfracture surfaces. Studies looking at partitioning
of TCE and transformation products to partitioned NOM under controlled isotherm conditions may help to better
describe partitioning with respect to microfracture surface organic carbon fractions, particularly if more sensitive
SIMS methods (such as time of flight SIMS) are used. Understanding the spatial proximity of adhering microbes of
terminal electron accepting process activity to minerals necessary to that terminal electron accepting process may
help to describe the heterogeneous nature of terminal electron accepting processes in the microfracture network and
at the microscale within the formation. Determining the extent of the microfracture specific surface area relative to
that of the open fracture network would help in determining the role of microfractures in terminal electron accepting
processes and biodegradative processes within contaminated bedrock aquifers. The role of mass transfer between
the open fracture system and the microfracture network, as well as redox zonations that might develop relative to
proximity to the open fractures might be subjected to mass transfer and reaction path modeling exercises. Additional
work defining the complex microbial communities, their metabolic interactions, and their possible syntrophy with
respect to TCE degradation may help to explain observed accumulations of transformation products. Further, the
expression of enzymatic activity relative to terminal electron accepting processes and TCE biodegradation would
help determine the metabolic activity on microfracture surfaces and why these might differ from those occurring in
the open fracture groundwaters.
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1.0 Introduction
The Bedrock Bioremediation Center (BBC) at the University of New Hampshire is a center specializing in multi-
disciplinary research on bioremediation of organically-contaminated aquifers. Field research is conducted at Site 32 at
the Pease International Tradeport (formerly Pease Air Force Base) in Portsmouth, NH. Site 32 contains a contaminant
plume dominated by trichloroethylene (TCE). The site is situated on a variable thickness upper sand layer overlying
a marine clay layer overlying a variable thickness lower sand layer. These unconsolidated layers are situated over
the Kittery Formation, a tightly folded, biotite-grade metasandstone and metashale crosscut by numerous porphryitic
diabase dikes. The contaminant plume extends downward and laterally northeast ~0.5 km via migration through
weathered and competent bedrock. The groundwater in the bedrock is predominately contaminated with c/s-DCE
(280-440 ug/L) with some frans-DCE (26-48 ug/L), TCE (24-59 ug/L), and VC (8-22 ug/L). The principal contaminant
released was TCE. Since 1997, the overburden contamination is being managed using a sheet pile containment
system coupled with pump and treat. The bedrock zone was given a technical impracticability (Tl) waiver.
Over the last few years, a number of BBC investigatory boreholes have been installed in and around the plume at Site
32. Most of these boreholes have been used for extraction of cores from the competent bedrock as a function of depth.
Our focus on microfracture characterization was limited to eleven microfractures extracted from two boreholes: BBC5
and BBC6. Eleven microfractures extracted from competent bedrock cores (comprised of Kittery Formation rock and
not diabase dike rock) from boreholes BBC5 and BBC6 were characterized with a variety of surface spectroscopic
and microbial techniques to determine if a relation, if any, exists between microfracture surface precipitates and the
ecology and metabolic activity of attached microbial populations relative to predominant terminal electron accepting
processes such as Fe(lll) reduction, or sulfate reduction, or to chlorinated solvent biodegradation.
1.1 Microfractures and Their Role in Reaction and Transport
Contaminant transport and reaction in fractured bedrock are important processes, yet poorly understood and difficult
to study and model. Large scale fractures with apertures from mm to many cm in size clearly play a dominant role
in transport. Open microfractures with apertures less than 1 mm potentially play an important role in reaction by
virtue of their extensive specific surface area.
Microfractures tend to be sub-millimeter in open width and vary in their planar or sub-planar extent (both length
and depth). They are produced by a variety of deformational processes in massive host rock. Historically, in the
literature, they have been referred to, somewhat interchangeably, as microcracks, cracks, or microfractures (Kranz,
1983). The term microfracture has been adopted for use in this report. Many microfractures constitute a network;
such networks are situated within the more open fracture system.
Microfractures are introduced when stress exceeds strain at the local level. Local stresses are induced mechanically or
thermally. Microfractures tend to locate at grain boundaries, intra-crystalline cavities, intra-crystalline cleavage planes,
and internal surfaces corroded by chemically active fluids (Kranz, 1983). Microfractures can also be trans-granular
and propagate along cleavage planes. Typically, microfractures propagate along paths of maximum stress.
Microfractures have one or two dimensions that are smaller than the third dimension. For reference purposes,
x denotes length, y denotes depth, and z denotes open width. For flat microfractures, the width to length ratio
(the microfracture aspect ratio, z/x), must be less than 10"2 and is frequently between 10~3 and 10"5 (Simmons and
Richter, 1976).
Frequently, the surface of the microfracture is coated with secondary mineral surface precipitate (also referred to
as a skin) (Kranz, 1983). This controls whether the microfracture is open relative to porewater communication with
adjacent connected microfractures (and larger transmissive fractures) in a microfracture network or fracture system.
Coating can be complete, wherein the microfracture is completely in filled (or healed or sealed), or partial, where
the microfracture is only partially filled (or sealed or healed).
-------
These secondary minerals are frequently deposited at higher temperatures during metamorphic intrusion (Kranz,
1983). However, more recent geologic processes associated with lower temperature hydrologic mineral weathering
and precipitation of dissolved ions from porewater solutions may also be important; especially at the contact interfacial
surface between porewaters and microfracture surface minerals.
The microfracture surface can also form a weathering rind: over time, elements in the host rock undergo incongruent
dissolution and diffuse, via Fickian diffusion, from within the mineral out to the mineral-porewater interface, and into
the porewater. This occurs on the scale of nanometers to microns and leaves a concentration profile in the host
rock that decreases closer to the mineral-porewater interface. Such diffusion profiles are driven by concentration
gradients between the host mineral and the porewater, the porewater behaving as an infinite sink.
A conceptual model of the mineralized microfracture interface with an open pore is provided (Figure 1.1). At the
interface of the microfracture and the open pore, there are minerals deposited on the microfracture surface, and
natural organic matter (NOM) present in the porewater is sorbed to these surfaces. Microbes will be adherent to the
mineral surface and/or the NOM located at the surface. The microfracture surface plays an important role in the fate
of contaminant solutes (both inorganic and organic) present in the groundwater moving through the microfracture
network and in the framework of more open fractures that connect the microfracture networks.
> 1 pm 1-2
Surface Precipitate
Host Rock
Zone of
Diffusional
Loss
and/or
Zone of
Diffusional
Increase
Sorbed
Interface Natural Organic Matter,
Fe Species
Biopatch
Fracture
Porewater
Depth (Z-)
Skin/Rind/
Alteration Zone
Depth (Z+)
Variable Width
Microfracture
Figure 1.1. Conceptual model of adherent biopatch (in cross section) on a microfracture surface.
The reactions at the microfracture surface include: reactions between the solute and the secondary mineral
directly (specific or non-specific adsorption) and reactions between the NOM and the mineral directly (specific or
non-specific adsorption) which in turn can react with solutes (specific and non-specific adsorption). Further, the
mineral surface can also play a role in selection or metabolism of adherent microbes in the microfracture network.
These microbes, in turn, can directly react with contaminants by (i) specific or non-specific adsorption processes,
(ii) contaminant metabolism, (iii) alteration of the mineral interface where the microbe resides, or (iv) secondary
mineral precipitation.
-------
Open microfractures are connected to the fracture system and therefore are in communication with larger fractures.
Typically, diffusive processes are involved at a variety of scales: diffusion of components out of the host rock into
microfractures (whereby solid state diffusion predominates) and diffusion within wetted microfractures where tortuous
aqueous (or matrix) diffusion predominates. In the later case (Shapiro, 2001), the diffusivity of a non-absorbing ion
(D, m2/yr) is:
= nrmaDw = nrmDrm
[Eq.1.1]
where Dw frees diffusivity in water (m2/yr), nrm is the effective porosity of the rock matrix (unitless), a is a tortuosity
factor (unitless), and Drm is the effective diffusion coefficient in the tortuous rock matrix (m2/yr). Typically, Drm is one
to three orders of magnitude lower than D. Recent work by Shapiro (Becker and Shapiro, 2000; Shapiro, 2001) has
documented the role that matrix diffusion plays in transport processes at the large scale (km).
Robinson et al. (1998) developed analytical solutions for solute transport in a dual porosity (fracture-matrix) system
with skins present along the fracture faces. Their results suggested that fracture skins may increase or decrease
transport processes depending on their porosity relative to the host rock. This has implications relative to residence
time or retardation during transport.
1.2 Microfracture Definition
A protocol (See Table 1.1.) was established to better describe the microfractures to be sampled relative to the cores
extracted from the boreholes. Microfracture types are characterized by their extent for being continuous across the
core, discontinuous across the core, or induced by drilling stresses. The attitude of the microfractures (relative to
the horizontal ground surface) is classified as horizontal (0°), vertical (90°), or somewhere in between and therefore
inclined. The aperture width or thickness of the microfracture is used to describe the opening in the microfracture.
These measurements are rough estimates based on use of scales with enlarged digital micrographs. Surface
mineralization is a general descriptor for the degree of secondary mineralization associated with the microfracture
surface.
Table 1.1. Microfracture Description Protocol
Extent & Type
- Continuous
- Bedding
- Cross bedding
- Discontinuous
- Bedding
- Cross bedding
- Induced
(mechanical break - likely
restricted to core)
- Bedding
- Cross bedding
Attitude
- Horizontal (0°)
- Vertical (90°)
- Steeply
inclined (> 60°)
- Moderately inclined
(30-60°)
- Low angle (<30°)
- Horizontal (0°)
- Vertical (90°)
- Steeply
inclined (> 60°)
- Moderately inclined
(30-60°)
- Low angle (<30°)
- Horizontal (0°)
- Vertical (90°)
- Steeply inclined (>60°)
- Moderately inclined
(30-60°)
- Low angle (<30°)
Typical aperture
width (mm)
>1.0
>0.8
>0.6
>0.4
<0.4
>1.0
>0.8
>0.6
>0.4
<0.4
>1.0
>0.8
>0.6
>0.4
<0.4
Surface area with
secondary mineralization
- Little (< 10%)
-Some (10 to 30%)
- Extensive (>30%)
- Little (< 10%)
-Some (10 to 30%)
- Extensive (>30%)
- Little (< 10%)
-Some (10 to 30%)
- Extensive (>30%)
-------
1.3 Microbes in Bedrock
Microorganisms are found in many subsurface environments. Their metabolic activity affects the chemistry and
physical properties of the surrounding environments. In recent years, there has been considerable interest in the
microbiota of the deep subsurface including continental and oceanic crust and marine sediments. While microbes
are present in the deep subsurface, they may be growing slowly and exhibit little metabolic activity. There is a dearth
of information on the microbial populations that exist in crystalline bedrock aquifers (Pederson 1997; Lovley and
Chapelle, 1995; Fredrickson and Onstott, 1996). Open microfractures in the bedrock in communication with larger
fractures constitute a surface for microbial colonization and metabolism. Surfaces may very well confer numerous
advantages to bacteria and can influence metabolic processes.
Most studies have focused on microbial communities from groundwater aquifers or sediment deposits (i.e., Ekendahl
et ai, 1994; Fredrickson & Onstott, 1996; Pedersen 1997, 2000; Fry et ai, 1997; Chandler et ai, 1998; Bekins et
ai, 1999), with only a limited number on competent bedrock, which comprises the majority of habitable subsurface
environments (i.e.; Colwell et al., 1997; Fredrickson etal., 1997; Haveman et al., 1999; Onstott et ai, 1998; Onstott
et ai, 2003). Composition of the microbial communities has been investigated by the use of enrichment cultures
(Onstott et ai, 1998; Lehman et ai, 2001 a) or molecular techniques in simulated models (Lehman et ai, 2001 b).
Microbes have been characterized in extreme systems in the deep subsurface. Onstott et ai (1998) characterized
microbes from sidewall cores of rock 2800 m below ground surface in hydrocarbon reservoirs. Bacterial phospho-
lipids biomass indicated cell concentrations up to 4 x 105 cells/g of rock, a relatively low cell density by comparison
to porous media.
Onstott et ai (2003) conducted microbial analyses on rock from a 3.2 km depth in an active gold mine in South
Africa. The host rock was comprised of a carbonaceous, quartz, sulfide, uraninite, and gold- bearing layer, referred
to as the Carbon Leader, sandwiched between quartzite and conglomerate deposits. The microorganisms in the
Carbon Leader were mostly mesophilic, aerobic heterotrophic, nitrate reducing, and methylotrophic, and p- and
J-Proteobacteria. Combined phospholipid fatty acid and terminal restriction fragment length profile analyses show
indigenous microorganisms were present at < 102 cells/g of rock. Phospholipid fatty acids, 35S autoradiography,
and enrichment cultures suggested that the adjacent quartzite contained ~103 cells/gram of rock of thermophilic
sulfate reducing bacteria, including some 8-Proteobacteria. Porewater and rock geochemical analyses indicated
that sulfate for the sulfate-reducing bacteria was made available, via diffusion, from the adjacent Carbon Leader
via radiolysis of the sulfides.
Haveman et al. (1999) characterized the free-swimming microbes and geochemistry of groundwater samples from
200- to 950-m depths in four igneous rock sites in Finland. At these sites, fractures are partially filled with precipitated
minerals such as calcite, dolomite, pyrite, epidote, or chlorite. These minerals were believed to precipitate and dissolve
as a result of changing groundwater conditions over geological time. Some of the fracture-filling minerals are cycled
by microorganisms, such as sulfide in pyrite, carbon dioxide in calcite, and ferric iron in iron oxyhydroxides. At these
four sites, free-swimming sulfate-reducing bacteria predominated in sites where iron sulfide fracture-filling minerals
were present. Free-swimming iron-reducing bacteria were dominant where iron sulfide fracture-filling minerals were
not present, but iron hydroxide fracture-filling minerals were prevalent. They observed that fracture-filling minerals
were a better indicator of planktonic microbial populations than was groundwater chemistry. Isotopic signatures
in fracture-filling minerals seem to be reliable indicators of past and present microbial activity, especially if stable
isotope ratios are analyzed.
In bench-scale fractured bedrock column studies (Lehman et al., 2001a), attached microbial communities were
compositionally different from those in the porewater flowing through the fractures. Fracture surfaces were enriched in
gram-positive bacteria and a-Proteobacteria and depleted in fi-Proteobacteria. Lehman and colleagues suggested that
microbial communities will be partially controlled by the surrounding geological media (Lehman et al., 2001 b).
The ability of microbes to colonize fracture surfaces is clearly constrained by both the aperture size or pore throat
width of the microfracture network, hydraulic connectivity, and advective or diffusive transport of groundwater,
planktonic microbes, and entrained nutrients from near surface environs. Fredrickson et al. (1997) studied microbial
activity in shale and sandstone cores from New Mexico relative to aperture pore width. They found that core samples
dominated by pore throat widths < 0.2 um generally did not support activity. This width is believed to be the lower
limit of microbe size. Core samples with predominant pore throat widths > 0.2 um did support significant activity
as measured by 14C-acetate and 14C-glucose mineralization and 35S-sulfate reduction assays. Colwell et al. (1997)
studied biomass distributions in deep subsurface Late Cretaceous and Early Tertiary rock cores in the Piceance Basin
in western Colorado. They found that distribution in the deep subsurface was controlled by hydrologic connection
-------
to the surface, formation temperature, and an interconnected fracture system. Cores with higher pore throat widths
(>1 urn), porosities (up to 12%) and permeabilities (0.1 to 1.0 mDarcy) correlated to higher levels of biomass. In
contrast, cores with lower pore throat widths (<1 um), porosities (< 5%) and permeabilities (<1 uDarcy) did not
contain significant biomass or metabolic activity.
The deep subsurface also poses additional problems relative to availability of electron donors and acceptors for
metabolism. It is important to note that carbon deposited in a geologic formation and surviving tectonic burial and
partial metamorphism may provide a source of electron-rich carbon (e.g., Krumholz et al., 1996; Colwell et al., 1997;
Hohnstock-Ashe et al., 2001) that does not require communication with the shallow subsurface.
Such studies pose intriguing questions about the role of microfracture surfaces and microfracture surface minerals: Is
there an advantage to an attached rather than planktonic existence within the porewaters of the microfracture network
or open fractures? What advantages do attachment and growth provide? Are microbial populations syntrophic at
the surface? Does the geochemistry of the surface influence population ecology and metabolism? More specifically,
how does local availability of C (organic and inorganic), Fe (and perhaps Mn), and S influence the dominant terminal
electron accepting process in the microfracture network? There is a growing body of work that has examined the
interactions between mineral surfaces and microbes. Reviewing this literature is useful to place into context the
depth and breadth of the possible interactions between microbes and the microfracture surface.
1.4 Microbe-Mineral Interactions
There is a growing body of literature on microbe-mineral interactions. Adherent or endolithic bacteria can cause
mineral weathering (Fisk et al., 1998). They are involved in the deposition of minerals in extracellular regions,
frequently within the extracellular polymeric substance region, and on cell surfaces and appendages. Some recent
examples of calcite, dolomite, and ferroan dolomite deposition have been found (Brassant et al., 2002; Horath et
al., 2002; Rogers and Bennett, 2001). In deep ocean vents, microbes can also mediate the precipitation of Fe and
Si (Kruber et al., 2002).
One question of interest is whether elements available for metabolism within crystalline or amorphous mineral
phases are transformed during metabolism. Desulfitobacterium frapp/en strain G2, is capable of using ferric and
ferrous iron containing minerals for respiration. The organism is capable of reducing poorly crystalline Fe (III) oxide
minerals during the redox reaction. It can also participate in reversible redox reactions of iron within the lattice of
phyllosilicates (Shelobolina et al., 2003).
There is also a growing body of evidence that microbes seek out surfaces to adhere to that may be of nutritional
benefit. Lower et al. (2001) report nanoscale interactions involved in "recognition" of goethite by Shewanella. In Fe-
limited growth media, Pseudomonas sp. will preferentially attach to the Fe (lll)-bearing minerals goethite (a-FeOOH)
and hematite (Fe3O4) and use the Fe nutritionally (Forsythe et al., 1998). Dissimilatory iron-reducing bacteria will
also preferentially attach to a-FeOOH (Lower et al., 2001).
Recent work by Kalinowski and colleagues has shown that an Arthrobacter species will produce a Fe-siderophore
when attached to the mineral hornblende and extract the Fe from the mineral with these chelators (Kalinowski et al.,
2000a and 2000b; Liermann et al., 2000b). Biofilms (or perhaps biopatches) can produce a measurable ApH across
the biofilm that helps to enhance mineral dissolution and may be related to growth rate, production of low molecular
weight organic acids, physical properties of the synthesized extracellular polymeric substances, or production of the
siderophore (Liermann et al., 2000a). In carbon-rich anoxic groundwaters where P is scarce, microbes will colonize
hornblende surfaces that have apatite (Ca5(PO4)3OH) inclusions and solubilize the P for nutritional use (Rogers et
al., 1998).
Dong et al. (2003) examined microbially mediated reduction of Fe(lll) in illite. Shewanella putrefaciensCN32 and native
illites from St. Peter Formation sandstone in Ogle County, IL, were used. The illite contained a minor component of
goethite (a-FeOOH) in addition to fibrous illite. Mossbauer spectroscopy of the bioreduced material indicated that both
goethite and illite were reduced, but to different degrees. Transmission electron microscopy (TEM) showed dramatic
change in illite morphology upon bioreduction; the dominant morphology went from fibrous needles to plates.
At the petroleum-contaminated aquifer site in Bemidji, MN, in situ distribution of attached bacteria is related to the
nutritional content of the host minerals (Rogers et al., 1998 and 1999; Bennett et al., 1999). Research by Bennett
and colleagues (Bennett et al., 1996; Bennett et al., 2000; Bennett et al., 2001; Hiebert and Bennett, 1992; Rogers
et al., 2001) has also shown that colonized mineral surfaces weather faster than uncolonized ones. Adherent
microorganisms can dissolve growth-limiting nutrients from a variety of silicate minerals, which, in turn, can enhance
-------
growth and biodegradation of the contaminants at the site (Rogers et al., 1999; 2001). Preference is shown for
silicates containing P and Fe, rather than for those containing Al, Pb, and Ni (Rogers et al., 1998 and 1999).
1.5 Chlorinated Solvent Abiotic and Biotic Transformations
Chlorinated solvents such as perchloroethene (PCE) and trichloroethene (TCE) have been widely used as industrial
cleaning solvents and degreasing agents and also as chemical feedstocks (ATSDR, 1999). Consequently, these
solvents are prevalent groundwater contaminants at many military, industrial, and municipal landfill sites (Vogel,
1994; ATSDR, 1999).
Chlorinated solvents can undergo abiotic transformations, though at fairly slow rates when compared to most
microbially-mediated processes. Substitution and elimination are the predominant reactions (Vogel, 1994; Vogel
et al., 1987). The former involves replacement of a halogen moiety with a hydroxyl group. The latter involves the
removal of a hydrogen halide from the compound with the resultant formation of an alkene. The reaction path is
dependent upon the degree of halogenation. There are a number of abiotic processes that lead to dechlorination.
For instance, abiotic reactions between sulfide or ferrous iron and chlorinated organics can lead to destruction of
the chlorinated organics (Amonette et al., 2000; Butler and Hayes, 2000, 2001; Devlin and Muller, 1999; Ferrey et
al., 2004; Kenneke and Weber, 2003; Lee and Batchelor, 2003).
Biodegradation of chlorinated solvents such as PCE and TCE can occur aerobically and anaerobically (McCarty,
1997a, 1997b; Chapelle et al., 2003). Under aerobic conditions, chlorinated ethenes are oxidized (Hartmans et al.,
1985; Davis and Carpenter, 1990; Phelps et al., 1991; Bradley and Chapelle et al., 1996a, 1998a, 1998b; Bradley
et al., 1998b) or fortuitously cometabolised (Wilson and Wilson, 1985; Semprini et al., 1990, 1991; McCarty and
Semprini, 1994; Semprini, 1995). Under anaerobic conditions, chlorinated ethenes are oxidized (Bradley and Chapelle,
1996, 1997, 1998b; Bradley et al., 1998b) or reductively dechlorinated (Vogel and McCarty, 1985; Barrio-Lage et
al., 1987, 1990; Bouwer, 1994; McCarty and Semprini, 1994; Vogel, 1994; Odum et al., 1995).
The propensity to aerobically oxidize chlorinated ethenes increases with decreasing chlorination (Vogel et al., 1987;
Chapelle et al., 2003). The aerobic degradation of vinyl chloride (VC) to CO2 has been seen in laboratory cultures
and in aquifer sample enrichments (Hartmans et al., 1985; Davis and Carpenter, 1990; Phelps et al., 1991; Bradley
and Chapelle 1996, 1998a, 1998b; Bradley et al., 1998b; Coleman et al., 2002). VC can be used as a sole carbon
source for growth and metabolism (Hartmans et al., 1985; Hartmans and deBont, 1992; Coleman et al., 2002). In
vitro mineralization of dichloroethene (DCE), as the sole carbon source, can also occur aerobically (Bradley and
Chapelle 1998b; Bradley et al., 1998b, 1998c). Mineralization of DCE has been observed in aquifer sediments
(Bradley and Chapelle, 1998b; Bradley et al., 1998b, 1998c) and in cultures containing DCE as the sole carbon
source and oxygen as the terminal electron acceptor (Bradley and Chapelle, 2000).
Aerobic cometabolism is another transformation process (Chapelle et al., 2003). Cometabolic oxidation of
chloroethenes does not supply energy for metabolism or cell growth, instead, microorganisms contain nonspecific
oxygenases that fortuitously oxidize chloroethenes to CO2. Identified oxygenases include methane monooxygenase,
toluene monooxygenase, and toluene dioxygenase (Fox et al., 1990; Li and Wackett, 1992; Newman and Wackett,
1997). Consequently, aerobic cometabolism of chloroethenes requires the presence of oxygen and a primary substrate
to initiate the synthesis of the oxygenase. Wilson and Wilson (1985) first showed that methanotrophic bacteria are
capable of mineralizing TCE to CO2. Aerobic propane-, ethene-, aromatic organic-, ammonium-, and isoprene-
oxidizers are able to convert TCE, DCE, and VC to CO2 (Chapelle et al., 2003; McCarty and Semprini, 1994).
Microorganisms can also oxidize VC to CO2 under anaerobic conditions (Chapelle et al., 2003). Oxidation requires
a strong oxidant to drive microbial degradation, typically Fe (III). In an experiment conducted with sediment from a
Fe(lll)-reducing aquifer, addition of Fe(lll) to anaerobic microcosms resulted in VC mineralization rates comparable
to those observed under aerobic conditions (Bradley and Chapelle 1996). Bradley et al. (1998a) have also conducted
microcosm work where [1,214-C] VC and [1,2-14C] dichloroethane (DCA) were mineralized under anaerobic conditions
to 14CO2 where humic acid was used in the terminal electron accepting process.
In the presence of a suitable electron donor and catalyst, microbes use H2 to replace a chlorine moiety on a
chlorinated ethene molecule (Chapelle et al., 2003). This process is called reductive dechlorination, chloridogenesis,
chlororespiration, or dechlororespiration (Loffler et al., 1996; Loffler et al., 2000; McCarty, 1997a; Sanford et al.,
1996; Chapelle et al., 2003). Microbial reductive dechlorination is fairly ubiquitous in anaerobic, PCE- and TCE-
contaminated aquifers. The accumulation of PCE and TCE transformation products has been observed in many
anaerobic groundwater systems (Barrio-Lage et al., 1987, 1990; Bouwer, 1994; McCarty and Semprini 1994; Vogel
1994; Odum et al., 1995; Vogel and McCarty, 1985). Generally, dechlorination of PCE and TCE occurs under
-------
mildly reducing conditions such as nitrate or Fe(lll) reduction; however, dechlorination of DCE to VC requires more
strongly reducing conditions typical of methanogenesis (Vogel etal., 1987). Field studies suggest that the extent of
dechlorination is highly variable from site to site (Bouwer, 1994; McCarty and Semprini, 1994; Vogel, 1994; Chapelle,
1997; Gossett and Zinder, 1997; McCarty, 1997b; Chapelle etal., 2003).
Generally, the propensity of individual species of microbes to reductively dechlorinate decreases with decreasing
chlorine substitution (Vogel et al., 1987; Bouwer, 1994; McCarty and Semprini, 1994; Vogel, 1994), though it is now
known that the metabolic interactions amongst consortial members in a microbial community where dechlorination
takes place can be much more complex. PCE readily undergoes anaerobic reductive dechlorination to TCE.
Reductive dechlorination of TCE to c/s-DCE occurs during Fe(lll)-reduction. Reductive dechlorination of c/s-DCE to
VC can occur under sulfate-reducing conditions (Vogel et al., 1987; Chapelle, 1997) and during methanogenesis.
Reductive dechlorination of VC to ethene occurs during methanogenesis (Vogel and McCarty, 1985; Barrio-Lage et
al., 1987, 1990; Freedman and Gossett, 1989; DiStefano etal., 1991;de Bruin etal., 1992; Bouwer, 1994; Maymo-
Gatell et al., 1997 and 1999; Odum et al., 1995; Wu et al., 1995). Reductive dechlorination of PCE and TCE can
be incomplete in the subsurface. The accumulation of c/s-DCE and VC occurs unless certain dehalorespirers are
present in significant numbers (Wiedemeier et al., 1998; Chapelle et al., 2003).
Several PCE-dechlorinating isolates of the Proteobacteria, Desulfitobacteria, and the Dehalococcoides cluster have
been identified (Chang et al., 2000; Holliger etal., 1998; Krumholz et al., 1996; Maymo-Gatell et al., 1997; Miller
et al., 1997; Scholz-Muramatsu et al., 1995, Sharma and McCarty, 1996; Suyama et al., 2002; Wild et al., 1996;
He et al., 2003). Some isolates are versatile and use H2 or organic acids as electron donors. Dehalobacter and
Dehalococcoides sp. require H2. Desulfuromonas chloroethenica, a member of the Desulfuromonas cluster in the
Geobacteraceae, uses acetate. Complete reductive dechlorination of PCE and TCE to ethene or ethane occurs in
anaerobic enrichment cultures (deBruin etal., 1992; DiStefano etal., 1991). Almost all of the dechlorinating bacteria
that have been isolated reduce PCE or TCE only to c/s-DCE (Gerritse etal., 1996; Scholz-Muramatsu etal., 1995).
The anaerobe Dehalococcoides ethenogenes, however, completely dechlorinates PCE or TCE; in fact, it can also
use c/s-DCE, 1,1-DCE, and 1,2-DCA as electron acceptors (Maymo-Gatell etal., 1997; 1999).
Many dehalorespirers are gram-positive bacteria in the Clostridium-Bacillus subphylum or thea and y branches of the
Proteobacteria (Holliger etal., 1999). D. ethenogenes is more phylogenetically dissimilar to the other dehalorespiring
bacteria and has an Archaea-\\ke cell wall structure (Maymo-Gatell et al., 1997). Phylogenetically, it may be closer
to the green non-sulfur bacteria (Hugenholtz et al., 1998).
Dehalogenation is catalyzed by reductive dehalogenases which are typically membrane-bound and use chlorinated
ethenes or chloroaromatics as substrates (Christiansen and Ahring, 1996; Cole et al., 1995; Holliger et al., 1998;
Loffler etal., 1996; Magnuson etal., 1998; Maymo-Gatell etal., 1997; Miller et al., 1998; Neumann etal., 1994 &
1998; Ni et al., 1995; Utkin et al., 1994). The reductive dehalogenase subunit molecular mass ranges from 50 to
65 kDa and contains cobalamin and iron-sulfur clusters (Holliger et al., 1999). The PCE reductive dehalogenase
from D. ethenogenes accepts only PCE as a substrate. Unlike other dehalorespirers, however, D. ethenogenes also
uses a second enzyme, TCE reductive dehalogenase that is less specific and dechlorinates TCE, DCEs, and VC
to ethene (Magnuson et al., 1998).
The U.S. EPA and the Air Force Center for Environmental Excellence (AFCEE) have developed and evaluated a
protocol and scoring system for assessing the natural attenuation potential of chlorinated aliphatics in groundwater
(U.S. EPA, 1998; Wilson, 2002; Wiedemeier et al., 1998). The system has been applied at numerous contaminated
porous media sites. Three types of chlorinated solvent natural attenuation scenarios are identified: Type 1 behavior
occurs where the primary substrate is anthropogenic carbon which drives reductive dechlorination. Type 2 behavior
occurs when high concentrations of biologically available NOM are present. Type 3 behavior dominates in areas that
are characterized by low concentrations of NOM and/or anthropogenic carbon and by DO concentrations greater
than 1.0 mg/L. Under these conditions, reductive dechlorination will not occur, but VC can be oxidized. Sites that
are mixtures of these regimes also exist.
Stiber et al. (1999) developed an expert system to evaluate naturally-occurring reductive dechlorination for TCE-
contaminated groundwater. In their study, 22 experts were queried as part of system development. Observation
of biodegradation daughter and/or end products was identified as the most valuable indication of natural
attenuation.
Flynn etal. (2000) conducted some interesting microcosm work to examine the potential role of community metabolism
during in situ TCE dechlorination. They obtained subcultures from river sediments that reductively dechlorinated
c/s-DCE or VC; the subcultures came from three independent enrichments that completely dechlorinated PCE to
-------
ethene. The three subcultures completely dechlorinated c/s-DCE and VC and could be transferred indefinitely in
basal salts minimal medium with H2as the electron donor. Dilution transfers were then used to attenuate the ability
to dechlorinate. Two of the subcultures eventually failed to dechlorinate PCE, but the third subculture maintained
its ability. Analysis of the 16S rRNA genes (rDNA) from these enrichments using terminal restriction fragment
length polymorphism and denaturing gradient gel electrophoresis showed changes in community composition in
the attenuated subcultures, but not in the subcultures that maintained the PCE-dechlorinating activity. The data
suggested that at least two populations were responsible for the sequential dechlorination of PCE to ethene in these
cultures and that consortia can cooperate in the complete dechlorination of PCE.
He et al. (2002) studied community dechlorination activity at the chloroethene-contaminated Bachman Road site
in Oscoda, Ml. Microcosms were established using aquifer samples from various locations and depths inside
the contaminant plume. A number of electron donors were evaluated along with various chlorinated ethenes as
electron acceptors. Microcosms treated with donors showed dechlorination activity. However, precise end points for
dechlorination were varied and suggested spatially heterogeneous distribution of the dechlorinating potential in the
plume. Acetate treatments showed complete dechlorination of PCE to ethane; microcosms rapidly converted PCE to
c/s-DCE. PCE dechlorination in H2- treated microcosms occurred after a lag phase and after acetate had accumulated
by H2/CO, acetogenic activity. In their view, H2 can be the sole electron donor for reductive dechlorination to ethene
provided syntrophic acetate-oxidizing population(s) and H2/CO2 acetogenic population(s) are present.
Table 1.2 summarizes the known conditions for abiotic and biotic transformations of chlorinated solvents. Table 1.3
summarizes the environmental conditions required for reductive transformations of chlorinated solvents. Table 1.4
summarizes what is known about prokaryotes that engage in reductive dechlorination.
Table 1.2. Conditions for Abiotic and Biotic Transformation of Chlorinated Solvents
(Adapted from McCarty, 1997b.)
Transformation
Biotic-Aerobic
Primary substrate
Co-metabolism
Biotic-Anaerobic
Primary substrate
Co-metabolism
Hazardous
intermediates
Abiotic hydrolysis
Abiotic reduction or
elimination
Carbon
Tetrachloride (CT)
No
No
Perhaps
Yes
Yes
Perhaps
Yes
Tetrachloroethene
(PCE)
No
No
Yes
Yes
Yes
No
Yes
Trichloroethene
(TCE)
No
Yes
Yes
Yes
Yes
No
Yes
1,1,1-Trichloroethane
(TCA)
No
Perhaps
Perhaps
Yes
Yes
Yes
Yes
Table 1.3. Environmental Conditions for Biological Reductive Dechlorination Reactions
(From McCarty 1997b.)
Chlorinated Solvent
Carbon tetrachloride
(CT)
1 ,1 ,1-Trichloroethane
(TCA)
Tetrachloroethene
(PCE)
Trichloroethene (TCE)
Redox Environment
All environments
TCA-M.1-DCE +
CH3COOH
Denitrification
CT-> Chloroform
-
-
-
Sulfate reduction
CT->C02+C|-
TCA-M.1-DCA
PCE-M.2-DCE
TCE->1,2-DCE
Methanogenesis
-
TCA->CO2 + C|-
PCE-»Ethene
TCE-»Ethene
-------
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1.6 Determination of Likely Terminal Electron Accepting Processes
Lovley, Chapelle and colleagues (Lovleyand Phillips, 1987; Lovley and Goodwin, 1988;Chapelle etal., 1995; 1996b;
2003) have developed and advanced a methodology for deducing the dominant terminal electron accepting process
within zones in contaminant plumes or aquifers. Three components are needed: (i) the consumption of electron
acceptors (e.g., O2(g), NCv, Fe(lll), SO42', CO2(g)), (ii) the production of metabolic end products (e.g., CO2(g), N2(g),
Fe(ll), S2', CH4(g)), and (iii) the measurement of concentrations of transient intermediate products, especially H2, a
characteristic intermediate product of anaerobic (largely fermentative) microbial metabolism. Different terminal electron
accepting processes generally have characteristic H2 steady state concentrations in solution that reflect dominant
metabolic redox reaction and are relatively independent of reactant consumption or final product production (Lovley
and Goodwin, 1988). Nitrate reduction maintains H2 concentrations below 0.1 nM. Iron (III) reduction maintains
H2 concentrations between 0.2 and 0.8 nM. Sulfate reduction has a characteristic range between 1 and 4 nM.
Methanogenesis typically results in H2 concentrations in the 5 to 15 nM range. This scheme has been applied in
numerous settings by Chapelle and colleagues (See Chapelle et al., 1996b, 2003; U.S. EPA, 1997.) though some
exceptions have been observed in colder groundwater settings (Jakobsen et al., 1998).
McGuire et al. (2000) used the terminal electron accepting process deduction scheme to examine a plume in a
shallow groundwater site contaminated with fuel and chlorinated solvents. Terminal electron accepting process
parameters including methane, dissolved Fe, and H2 were measured within the plume over a 3-year period. The
terminal electron accepting process parameters changed on different time scales, in part driven by recharge events.
Some terminal electron accepting process parameters changed on short time scales (months), while others had
longer time scales (years). The authors believed that when interpreting terminal electron accepting process conditions
in aquifers contaminated with a variety of organic chemicals, such as those with petroleum hydrocarbons and
chlorinated solvents, one must consider additional hydrogen-consuming reactions such as dehalogenation. They
also recommended determinations of microbial community structure and activity.
Lendvay et al. (2003) used the terminal electron accepting process deduction scheme to look at the impacts of
adjacent surface waters of Lake Michigan on a lake-side shallow TCE contaminant plume. A spatially discretized,
multilevel well array was employed for sampling in and around the plume. Samples were analyzed for TCE, DCE,
VC, ethene, O2(g), Fe(ll), SO42', S2', CH4(g), H2(g) and redox potential (Eh). Methane and chloroethene decreased as
the groundwater became more oxidized closer to the interface between the lake water and the plume. On the other
hand, c/s-1,2- DCE remained unchanged or slightly increased at the same locations. A negative correlation was
seen between the chloroethene and methane data when compared to oxygen. The authors surmise that chloro-
ethene is co-oxidized by methane-oxidizing bacteria in the shallow region of the plume. Reductive dechlorination
of the chlorinated solvents remained the predominant biotransformation process in the deeper, more anaerobic
zones of the plume.
1.7 Related Field Work on Bedrock TCE Contaminated Sites
A number of excellent field studies and case histories can be found in Chapelle et al. (2003), U.S. EPA (1997), and
U.S. EPA (2002). Some relevant studies are discussed here.
Yager et al. (1997) conducted hydrogeological, geochemical, and microcosm experiments to examine TCE
biodegradation in a fractured dolomitic aquifer in Niagara Falls, NY. Field observations suggested that TCE is
biodegraded by sequential dechlorination to ethene through reductive dechlorination under anaerobic conditions.
The groundwater samples in and around the plume showed that H2(g) was linked to Fe(lll) reduction as the terminal
electron accepting process. Bacteria from the fractured dolomite were able to sequentially dechlorinate TCE in
microcosms. Dechlorination was enhanced when crushed dolomite was added to the reactions. Naturally occurring
petroleum hydrocarbons present in low concentrations in the formation were the source of electrons for respiration.
Amplified ribosomal DNA restriction analysis of the microbial populations indicated a low diversity, sulfur-transforming
community outside the plume. Inside the plume, a highly diverse community, including D. ethenogenes-iype
microorganisms, was present (Hohnstock-Ashe et al., 2001).
Hendrickson et al. (2002) looked at the environmental distribution of Dehalococcoides group organisms and their
association with chloroethene dechlorination activity at 24 chloroethene-contaminated sites scattered throughout
North America and Europe. Soil or earth matrices were tested for the presence of Dehalococcoides species using
polymerase chain reaction assay for Dehalococcoides 16S rDNA sequences. Sequences were detected at 21 of the
24 sites. Complete dechlorination to ethene occurred at these sites. Dehalococcoides sequences were not detected
in samples from three sites where only partial dechlorination to 1,2-c/s-DCE occurred. They used phylogenetic
analysis of the 16S rDNA amplicons to show Dehalococcoides sequences formed a unique 16S rDNA group. Three
10
-------
subgroups were identified based on specific base substitution patterns. These data suggest that members of the
Dehalococcoides sp. are widely distributed geographically and geologically.
1.8 Spectroscopic Characterization of Microfracture Surfaces
The use of surface and mineralogical analyses to characterize the x-y and the y-z planes of the microfracture surface
can provide useful information about the morphology and mineral composition of secondary mineral deposits on
the outer surface, the spatial relation between microorganisms and mineral deposits, the spatial distribution of
elements in the x-y plane, the depth profiles of elements of interest with depth in the rind in the y-z plane, the types
of crystalline minerals present, and the depth profiles of mineral phases or species.
A suite of methods is frequently needed to study surface mineralogy and bulk mineralogy relative to adherent
microbes (Figure 1.2).These methods have inherent strengths and weaknesses (frequently detection limit issues), or
they rely on databases not particularly suited to the poorly crystalline secondary minerals found in the environment.
However, when used in a complementary fashion, they are powerful analytical tools. More detailed and exhaustive
reviews of this subject can be found in Geesey et al. (2002), Perry et a/.(1990), Coyne and McKeever (1990), and
Galas and Hawthorne (1988). These methods are also thoroughly described in the Materials and Methods section
of this report.
X-Ray Powder
Diffraction (XRPD)
- Bulk Method
- Mineralogy of
Crystalline Materials
• Detect as Low as
3.000 ppm
- Large Database
X-Ray Photoelectron
Spectroscopy (XPS)
- Surface Method
- Speciation of Elements
- Detect Organic, Inorganic Compounds
- Depth Profiling
- Detect as Low as
10,000 ppm
- Variable Database
Secondary Ion Mass
Spectrometry (SIMS)
- Surface Method
- Atomic Mass & Abundance
- Detect Organic, Inorganic Compounds
- Spatial Mapping
- Depth Profiling
- Detect Low ppb
- Large Database
Microfracture Surface
Characterization
Field Emission Scanning
Electron Microscopy
(FESEM)
- Surface Method
- Morphology
• Spatial Mapping
- Detect as Low as 1 %
MINTEQA2 Geochemical
Modeling of Ground Waters
In Fracture/Veins
- Model Complex, Heterogeneous
Equilibrium Reactions
(Dissolution, Precipitation, Sorplion)
- Compare Geochemistry to
Solid State
- Small Database
Mercury Intrusion Porosimetry (MIP)
- Effective Pore Sizes
- Pore Size Distributions
- Porosity
- Effective Surface Area
Figure 1.2. Suite of analytical methods for characterization of bulk and surface chemistry.
1.9 Objectives of This Study
In the context of the recent literature, important questions remain about the nature of the interaction between the
microfracture surface and the adherent microbes. How does the surface influence attachment and growth? How
does the geochemistry of the microfracture surface influence population ecology and metabolism? More specifically,
how does the microfracture surface influence the dominant terminal electron accepting process in the microfracture
network? What is the nature of TCE biodegradative processes? Is Dehalococcoides-driven dehalorespiration a
dominant transformative process?
As part of the overall research plan to better understand relevant transport, retardation, and attenuation processes
for TCE in competent bedrock, we studied 11 microfractures extracted from competent bedrock cores from boreholes
BBC5 and BBC6 so as to characterize, with a variety of surface spectroscopic and microbial techniques, the relation,
if any, between microfracture surface geochemistry and the ecology and metabolic activity of attached microbial
populations relative to terminal electron accepting processes or to chlorinated solvent biodegradation.
11
-------
2.0 Materials and Methods
2.1 Core/Microfracture Locations
As part of its research program, the University of New Hampshire's Bedrock Bioremediation Center (BBC)
[http://www.unh.edu/civil-engineering/research/erg/bbc] has conducted research on a TCE-contaminated saturated
bedrock field study site (Site 32) in southeast New Hampshire.
Site 32, which is located at the Pease International Tradeport (formally Pease Air Base) in Portsmouth, NH, is
situated on a variable thickness upper sand layer overlying a marine clay layer overlying a variable thickness lower
sand layer. These unconsolidated layers are situated over bedrock of the Kittery Formation (See Figure 2.1.). The
groundwater in the bedrock is predominately contaminated with DCE (100 to 700 ug/L) with lesser amounts of
TCE and VC. The contaminant plume extends about 0.5 km through a metasandstone (partially metamorphosed
sandstone) of the Silurian and Ordovician Kittery Formation interbedded with Jurassic diabase dikes.
West-Southwest
East-Northeast
S 574 • 20
•
-70
,
I IflodtocfclBHl
I lunreSHncMlt
\ MWBKI Ony ima &a (MCS)
I UMMT Snotf (US)
Figure 2.1. Cross section through BBC site.
Site 32,'Ja (BinkJinys 113 and 119)
Stage 3. Record at Oecteton
Peasa AW Force Base. New Hampshire
CONCEPTUAL MODEL OF DISSOLVED CONTAMINANT
MIGRATION PATHWAYS IN GROUNOWATER AT SITE 32
12
-------
The source of the TCE originated from an underground storage tank (UST) behind Building 113 where, between
1955 and 1991, aircraft munitions systems and avionics were maintained. Vapor degreasing occurred from 1956
to 1966. A 4,488 L (1,200 gal) concrete UST at the northeast corner of the building received TCE via a floor drain.
In 1977, 3,740 L (1,000 gal) of waste TCE were removed, and the tank was filled with sand. In 1988, the tank
was excavated and removed. At that time, an overflow discharge pipe was discovered. The pipe and 441 tons of
contaminated soil were removed in 1990 (footprint and depth of excavation unknown). A pilot pump and treat system
was used to treat the lower sand layer and weathered bedrock from 1991 to 1995. The site was deemed to be a Tl
zone, and sheet piles were installed down to competent bedrock in 1996. Groundwater pumping within the sheet
pile area commenced in 1997 and has been ongoing since that time.
Over the last few years, six investigatory boreholes (termed BBC1 through BBC6) have been installed in and
around the plume at Site 32 (Figure 2.2). These boreholes have served a variety of purposes. All but one of these
boreholes have been used for extraction of cores from the competent bedrock as a function of depth. Our focus on
microfracture characterization was limited to 11 microfractures extracted from boreholes BBC5 and BBC6. These
boreholes are about 7.6 m (25 ft) from each other. The bedrock portion of borehole BBC5 was drilled between
December 6, 2001, and January 9, 2002. The bedrock portion of borehole BBC6 was drilled between August 30,
2002, and October 7, 2002.
Pease International Tradeport, Site 32
Extent of VOC Contaminant Plume in 1992, 1998 and 2002
1212700 1212900 1213100 1213300 12135(1(1 I2I37M1 12139(10 1214100 1214300 1214500 12147(10
212600 -
212400 -
212200 —
212000 -
GO
5;; 211X00 —
~4_t
o
^ 211600 -'
211400 -'
211200 —
211000
• Bedrock Borehole
Approx. Location of Former
Underground Storage Tank
Extent of VOC Plume. 2002
Extent of VOC Plume. 1998
• Extent of VOC Plume, 1992
A A See plume cross-section
212600
- 21240(1
-.- 212200
2120(10
- 211X00
211600
211400
- 211201)
110(111
1212700 1212901) 1213100 1213300 1213500 1213700 1213900 I2I4IOO 1214300 1214500 I2I47(H)
Easting (feet)
Coordinate System: NH Slate Plane (NAD 83 Datum)
Figure 2.2. Plan view of borehole locations at Site 32.
13
-------
Borehole BBC!
Microfractures
sr1 ^^
;r2 MF04
MF07 ,
y 3 MFOe--^?*
Hydraulic /
Connection
5 Depth Below E
Telescoping Top
of Casing (ft)
25.0
500
75.0
100.0
s^
/ M25.0
150.0 L
i
Borehole BBC6
Microfractures
MF09
MF08
i
MF10
MF11
Cluster 4
Microfractures from borehole
BBC5 were collected
on December 20, 2001.
Microfractures from borehole
BBC6 were collected on
September 24, 2002. The
locations of these microf ractures
(designated MF01 to MF11) as
a function of depth are shown
in Figure 2.3. All microfracture
samples that were collected
from the Kittery Formation and
not from the diabase dikes are
reported relative to the top of
the telescoping casing installed
through the overburden and
weathered bedrock.
Figure 2.3. Cross section through boreholes BBC5 & BBC6 showing
microfracture locations and hydrologic connections between the two boreholes.
Table 2.1 provides a generalized description of the 11 microfractures, their assignment into four spatial clusters,
and the gross appearance of each microfracture surface as well as their gross features relative to core stratigraphy.
Descriptions are based on BBC protocols identified in Table 1.1. Table 2.2 summarizes the analyses that were
applied to each microfracture sample.
Table 2.1. Microfracture Location, Cluster Assignment, and Description
Micro-
fracture
#
MF01
MF02
MF03
MF04
MF05
MF06
MF07
MF08
MF09
MF10
MF11
Well
BBC5
BBC5
BBC5
BBC5
BBC5
BBC5
BBC5
BBC6
BBC6
BBC6
BBC6
Core interval
/fracture
depth, ft
70.5-75.5
/71.5
70.5-75.5
/73.0
70.5-75.5
/73.0
95.5-100.2
/97.0
119.9-124.7
/ 122.7
119.9-124.7
/ 122.0
119.9-124.7
/121.5
107.39-112.14
/112
107.39-112.14
/ 107.4
112.14-116.94
/ 113.31
112.14-116.94
/ 116.72
Cluster
1
1
1
2
3
3
3
4
4
4
4
Microfracture exposed
surface visual
appearance after removal
from the core
Wetted, Olive Green
Precipitate, Flakey,
Homogenous, Some Pyrite
Wetted, White Precipitate,
Molted/Patchy, Some
Flakey (Soft), No Pyrite
Wetted, Fine Grained Grey
Black Surface,
No Apparent Precipitate,
No Pyrite
Wetted, Fine Grained
Grey-Black Surface With
White Precipitate Traces,
No Pyrite
Wetted, Chalky Slate Blue
Precipitate, Some Quartz
Veins, Homogenous, No
Pyrite
Wetted, Shiny Green-
Yellow Precipitate,
Homogenous, No Pyrite
Wetted, Olive Green-Black
Precipitate, Very Fine
Grained, No Pyrite
Wetted, White Precipitate,
Homogenous, No Pyrite
Wetted, White Precipitate,
Homogenous, No Pyrite
Wetted, White Precipitate,
Homogenous, No Pyrite
Wetted, White Precipitate,
Homogenous, No Pyrite
Extent
Continuous
Continuous
Continuous
Continuous
Discontinuous
Continuous
Continuous
Continuous
Discontinuous
Continuous
Continuous
Type
Cross
Bedding
Bedding
Bedding
Bedding
Cross
Bedding
Bedding
Cross
Bedding
Bedding
?
?
?
Attitude
Low Angle
Steeply
Inclined
Steeply
Inclined
Low Angle
Steeply
Inclined
Moderately
Inclined
Low Angle
Horizontal
?
Moderately
Inclined
Steeply
Inclined
Aperture
width in mm
(aspect
ratio, z/x)
>0.4
(< 0.003)
<0.4
(< 0.001)
<0.4
(< 0.001)
>1
(< 0.006)
>0.6
(< 0.004)
>0.6
(< 0.004)
>1
(< 0.006)
>0.4
(< 0.003)
>0.8
(< 0.005)
>0.4
(< 0.003)
<0.4
(< 0.001)
Exposed
surface area
with secondary
mineralization
Extensive
(>30%)
Some
(10-30%)
Little
(<10%)
Little
(<10%)
Extensive
(>30%)
Extensive
(>30%)
Little
(<10%)
Extensive
(>30%)
Extensive
(>30%)
Extensive
(>30%)
Extensive
(>30%)
14
-------
Table 2.2. Analytical Methods Applied to the Host Rock and Microfracture Samples
Micro-
fracture
#
Well
Cluster
MIP
of
HR
SEM
of
MF
SEM-
EDAX
spatial
mapping
of
HR/MF
Petrography
of
HR/MF
XRD
of
HR/MF
TEM
of
MF
SIMS
of
MF
XPS
of
MF
Packer
sampling
inMF
regions
PCR Primers/
DGGE/
gene
sequencing
from MF
MF01
BBC5
MF02
BBC5
MF03
BBC5
MF04
BBC5
MF05
BBC5
General
host
rock
samples
from
BBC5
Yes
MF
HR
HR/MF
No
No
Yes
MF
HR/MF
HR/MF
Yes
No
Yes
MF
HR
HR
Yes
Yes
No
Yes
MF
HR
HR/MF
Yes
Yes
Yes
MF
HR
HR
Yes
Yes
MF06
BBC5
Yes
MF
HR/MF
HR/MF
Yes
Yes
MF07
BBC5
Yes
HR/MF
HR
HR/MF
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
MF08
BBC6
None
Yes
MF
HR
HR/MF
Yes
No
MF09
BBC6
Yes
HR/MF
HR
HR/MF
Yes
No
MF10
BBC6
Yes
MF
HR
HR/MF
Yes
Yes
MF11
BBC6
Yes
MF
HR/MF
HR/MF
Yes
No
Yes
Abbreviations:
DGGE - Denaturing Gradient Gel Electrophoresis
HR - Host Rock
MF- Microfracture
MIP - Mercury Intrusion Porosimetry
PCR - Polymerase Chain Reaction
SEM-EDAX - Scanning Electron Microscopy - Energy Dispersive Analysis of X-Rays
SIMS -Secondary Ion Mass Spectrometry
TEM -Transmission Electron Microscopy
XPS - X-Ray Photoelectron Spectroscopy
XRD - X-Ray Diffraction
2.2 Core/Microfracture Sample Collection
Competent bedrock cores extending into the Kittery Formation and (in some cases) sections of diabase dike, were
collected for microbial analysis using a triple barrel corer as described in Volume 1: Fractured Rock Drilling. As
noted in Volume 4: Fractured Rock Microbiology, the drilling fluid was from a non-contaminated pristine bedrock
well and was not re-circulated so as to minimize microbial cross contamination with depth. BBC researchers have
developed unique drilling procedures to obtain and process 10.16 cm (4-inch) diameter cores that contain intact,
representative, microbial populations. These procedures allow for the option of maintaining and examining cores
under anoxic conditions. Using these procedures, the BBC installed six bedrock boreholes (BBC1 to BBC6) . Each
borehole was installed with telescoping casing through the overburdened and fractured bedrock in an effort to limit
contamination by these zones.
Each completed borehole was analyzed by the following methods: videologging, omni-directional borehole radar,
acoustic and optical televiewer scanning, heat pulse flowmeter, natural gamma, caliper, single-point resistivity, and fluid
temperature/resistivity. In addition, BBC4 through BBC7 were monitored during completion with a drilling parameter
recorder (DPR). The DPR is a computerized system that automatically collects data from a series of transducers
installed on conventional drilling equipment. The data include information on the advance rate, down-thrust and
pull-up pressures, rod torque, rotation time, mud/water pressure and flow, depth, and time. All cores reamed from
the boreholes were examined for standard lithological features by a geologist. Data from the DPR, videologs, and
geophysical logs were used to select fracture zones in each borehole for further study. These fracture zones were
the focus of the groundwater sampling and hydraulic testing conducted in each borehole.
Selection of microfractures for analysis involved some initial trials. Basically, microfractures had to be exposed by
breaking apart the core so that the break occurred within the microfracture surface itself, as this was the weakest
portion of the rock sample. If struck correctly, the core would break apart and expose two surfaces of the microfracture.
In some cases, the surface precipitates adhered to only one side of the break, in others precipitates adhered to
both sides. We elected to analyze those specimens that had surface precipitates on them. Further, we had to select
microfractures with steep inclination relative to the length of the core so that thin specimens could be collected
15
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and fitted into spectroscopic instruments for analysis. Consequently, the microf ractures needed to be extensive across
the entire thickness of the core, with steep inclination, and have an apparent aperture width that was measurable
and open in appearance. Tightly sealed microf ractures frequently would not break apart after repeated hammer
blows.
Subsequently, partially mineralized, partially sealed microf ractures which were readily exposed by striking with
a surface-sterilized geology hammer were collected from each of the boreholes. A typical microfracture and the
orientation of the microfracture face relative to the core are shown in Figure 2.4. All of the microfractures were
separately processed for microbiological and geological analyses.
BEDROCK CORE
Open Fracture (mm to cm)
iDROCK COR
Microfracture Surface
Surface
Precipitate
Microfracture (urn to mm)
Figure 2.4. Schematic depiction of microfracture-type sampling.
2.3 Microfracture Sample Preparation
The recovered microfracture surfaces were further broken into pieces between one and 30 cm3 using a sterilized
chisel. Samples were marked on all sides except on the surface face of the microfracture with solvent-free water-
soluble ink. All samples were stored in sterile 100-mL plastic specimen bottles. Further preservation required for
specific analyses is described below.
2.4 Overall Analytical Sequence
The general sequence of sampling and analysis is shown in Figure 2.5. The sequence involved drilling, core
extraction, core processing, microfracture sampling, extraction of the adherent microbes, borehole characterization,
characterization of the microfracture surfaces, packer sampling over the interval in which the microfracture was
located, characterization of the porewater, and geochemical modeling of the porewater.
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Bedrock Coring
• 4" (10 cm) Hollow Stem Auger
Microfracture *>
Extraction
• Sterile Hammer & Chisel
• Microfracture Photography
Borehole
Characterization
• Flow
. • Videologging
s^' Lithologic Logging
• Geophysical Logging
Microfracture
Surface Analysis
• Petrography (bulk)
• SEM (surface) v
• SEM/EDAX (Mm)
• XRPD (bulk)
• XPS (nm)
• Static SIMS (atomic layers)
• MIP (Bulk) \
Geochemical
Modeling
of Porewaters
Microbial
Extraction
• Phosphate Buffer
Solution/Sonication
• Polymerase Chain
Reaction/ Denaturing
-^ Gradient Gel
Electrophoresis
• Sequencing
Porewater
Extraction/
Chemistry
• Packer Sampling
• 0.22 |jm Filtered
• Organ ics/
Inorganics/
Gases
Visual MINTEQ
Figure 2.5. Analytical scheme.
2.5 SEM-Morphology and Biopatch Distribution
SEM is used to examine the morphology of microfracture surfaces in the x-y plane. It also is used to determine
the presence of adherent microorganisms as well as examine morphology and extracellular features. SEM uses
secondary and backscattered electrons from the primary interaction of an electron beam with nuclei of atoms in the
near surface region of the sample. It produces a reflected energy beam picture of the sample. The sample is analyzed
in a high vacuum (unless environmental SEM is used), so samples must be dehydrated prior to analysis.
The primary electron beam penetrates the sample to a depth of 2 to 3 urn. Emitted secondary or backscattered
electrons originate from shallower depths. Frequently, specimens must be sputter-coated with Au or Pd to make
them electron dense or reflective. Carbon paint is used to provide good contact to prevent charging (localized charge
build-up). Precise detail can be observed up to magnifications of 5,000x. A review by Blake (1990) provides further
details about this method.
If SEM is used to characterize the adherent microbial population, some treatments of the sample are required to
stabilize the cell structure for analysis under vacuum with a high energy beam. This frequently involves cell fixation
with buffered glutaraldehyde solutions (at in vivo, buffered pH values, 2% glutaraldehyde), followed by graded
ethanol series dehydration, and then by critical point drying with liquid CO2 under high pressure. Such treatments
can induce dehydration artifacts and remove less firmly adhered microorganisms.
Samples for SEM examination of adherent biopatches were prepared by 2.5% glutaraldehyde fixation in 0.1 M caco-
dylate buffer (CB, pH 8.0) and then graded ethanol series dehydration. Samples were critical point dried prior to
storage and examination in an AMRAY 3300FE field emission SEM. The samples were sputter-coated with Au/Pd
prior to analysis. The same samples were used for SEM examination of the surface precipitate morphology.
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2.6 SEM- EDAX Spatial Maps
SEM's primary excitation beams cause characteristic x-rays to be emitted. As a result, SEM can be coupled with
either energy dispersive analysis of x-rays (SEM-EDAX) to quantify elements with atomic numbers greater than
8 in a sample. Detection limits are on the order of 10'15 g (0.1 to 1 wt %). Samples can be characterized visually
with spatial maps of elements in the x-y plane (or y-z plane if cross-sectional thin sections are analyzed) and then
quantified using microprobe analysis. The probe is calibrated with primary standards, and elemental quantification
of surface material can be accomplished by counting the number of x-rays in discrete channels over a continuum
of energies. Spatial maps showing the origin of emission of the characteristic x-ray can be used to spatially locate
elements at the um to sub-urn scale. There are techniques that use standardless calibrations. Bulk quantitation
must be used with caution given the depth of profiling that occurs; however, they do provide very useful analysis of
element associations, particularly if it is coupled with petrography.
SEM-EDAX was performed using an AMRAY 3300Fe SEM outfitted with a PGT Imix-PC energy dispersive x-ray
microanalysis system for quantitation and spatial mapping. Analysis was performed at multiple locations on the
sample and at various magnifications (30x - 1000x). Elemental spatial mapping was used to identify elemental
distribution in the selected view field. Elements examined included Al, Ca, Fe, K, Mg, Na, O, S, Si, and Ti. Higher
elemental concentration in a given region was indicated by a more intense color display in the spatial map. The color
display was user selected and not specific to each element. Color palette choices were not equivalent in intensity
to concentration for a given map, so intensity may only be compared within an element map, not between maps. By
comparing features on the spatial maps of each element, associations between various elements were identified.
2.7 Microfracture Surface Precipitate Fixation & Embedding forTEM
Calcite-dominated surface precipitate minerals from microfracture MF011 were readily removed from the micro-
fracture surface with a sterile stainless steel spatula by simple scraping. The mineral material was prefixed in 2.5%
glutaraldehyde in CB for 3 h (at which time the precipitate was carefully crushed into sub mm particles), rinsed with
CB three times using careful decantation, followed by fixation with 1 % osmium tetroxide in CB for 3 h. After fixation,
the samples were rinsed in CB three times, dehydrated in a graded ethanol series (5, 10, 25, 50, 75, 100, 1000,
100%), and embedded by traditional resin techniques using either Spurr's or Epofix. After curing, the samples were
thin sectioned with a diamond knife, post stained with 15 min in 0.5% uranyl acetate (in 50% methanol) and 2 min
in 0.4% lead citrate. The presence of small quartz minerals in the precipitate made sectioning difficult. Epofix was
found to be better than Spurr's resin. The quartz crystals damaged the diamond knife.
2.8 TEM-Microbial Ultrastructure
The JEOL 100S was used at accelerating voltages ranging from 40, 60, 80, and 100kV and at magnifications
ranging from 1,000x to 100,000x.
2.9 Petrographic Thin Sections
Petrography can be used to examine phase morphology of rock minerals. Samples are embedded in epoxy resins,
cut and polished to produce 30 um thin sections. This method can be coupled with modal analysis to quantify
the relative abundance of phases in a cross-section (Hutchinson, 1974). Modal analysis produces an accurate
representation of the distribution and volume percent of the mineral within a petrographic thin section. Typically, a
point count method is used where each mineral type occurrence along a series of traverse lines across a given
thin section is documented. For a statistically valid result, > 2,000 individual points must be counted. The number of
grains counted, the spacing between points, and successive traverse lines are dependant on the mean grain size
of the sample and affect the percent abundance calculations.
When light is transmitted through mineral grains or mineral petrographic thin sections, a number of characteristic
properties of the mineral can be ascertained depending on the behavior of the light. Light wavelengths can be
shortened and slowed down. Light can be reflected, refracted, dispersed, and adsorbed. For isotropic minerals where
mineral orientation is identical in all directions, polarized light will be adsorbed when the polarizing filters are cross
polar. Mineral identification of isotropic materials can be made by examining grain structure and comparing this
information to databases of isotropic minerals. Anisotropic minerals exhibit a characteristic uniaxial or biaxial nature
using interference microscopy. Birefingence, the resolution or splitting of a light wave into two waves with mutually
perpendicular vibration directions, can also be used to characterize the mineral. Such properties are characteristic
of anisotropic minerals. Coupled with refractive index measurements of mineral grains, such information can be
used to identify minerals (Nesse, 2003).
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Petrographic thin sections to characterize host rocks (metasandstone and metashale of the Silurian-Ordovician
Kittery Formation and cross-cutting Jurassic diabase dikes) were prepared by Mineral Optics Laboratory (Wilder,
VT) and in-house. Sections were cut normal to layering; some were polished for subsequent analytical work, others
were covered. Standard petrography was performed on all, using both plane and cross-polarized light and a range
of objectives (4x, 10x, 20x, and 40x).
Primary mineral phases were identified for rock classification. Because of the fine-grained nature of these rocks,
modes of primary mineral phases were determined by visual point counts along traverses across thin sections. Rock
textures, contact relationships, and microfaults were noted within and between the three major rock types to evaluate
metamorphic, deformation, and intrusive effects on these rock units. Careful examination was made of secondary
and/or alteration minerals particularly at the boundary between host and vein and microfracture fillings.
2.10 SEM-EDAX Spatial Mapping Microfracture Surface Precipitates and Host Rock
Thin sections were also examined by EDAX, and spatial mapping was employed as described in Section 2.6. The
elemental spatial mapping was focused on the intersection of the microfracture surface and the underlying host
rock in order to highlight elemental differences between these two areas.
2.11 XRD Analysis of Microfracture Surfaces and Host Rock
XRD is a very important tool for characterizing the mineralogy of crystalline phases in host rock or microfracture
surface precipitate samples. The detailed principles of this method are given in Bish and Post (1989) and Whan
(1986).
XRD of powder samples relies on Bragg's Law and uses an x-ray from a non-monochromated or monochromated
source that is rotated through a powdered sample. Diffracted x-rays, generated by crystal inter planar (d-spacing)
reflections in the crystalline structure of the mineral assemblages, are collected by an x-ray detector as a function
of the diffraction angle (theta) as the sample is rotated through the beam using a goniometer. The source can also
rotate about a stationary sample. The diffraction pattern that is generated shows diffraction peaks of varying intensity
as a function of the diffraction angle. The resulting diffractogram is compared to diffractograms of known mineral
samples that contain precise locations of peaks and relative peak intensity. The International Centre for Diffraction
Data (ICDD, See http://www.icdd.com/.) maintains databases of the many thousands of minerals and inorganic
compounds that are used for comparison with either manual (visual comparison of diffraction patterns between
candidate and experimental spectra) or computer-based search-match routines. Typically, XRD has a detection
limit of about 1 to 2 % by weight. Care must be taken in selection of the target element to generate characteristic
monochromatic x-rays (in this case, Ka x-rays) because of the potential for adsorption of x-rays of certain wavelengths.
Cu is usually used, but Co can be used when samples contain a high percentage of Fe.
Powder preparation is very important. Hutchinson (1974) and Zussman (1976) discuss preparation methods. Particle
sizes that are too large cause problems such as extinction and microabsorption. They can also interfere with the
underlying assumptions of random orientation. For very coarse-grained or coarse-phased crystals in rock, particle
size production will create a particle size equal to a phase size. For very fine-grained or fine-phased crystals in
rock, particle size may exceed phase size. It is best if powders are ground close to 10 urn in diameter or that phase
size is less than 10 urn. Larger particle sizes give qualitative information; smaller particle sizes can be used for
quantification (Snyder and Bish, 1989). Snyder and Bish (1989) also discuss methods of sample mounting (smears,
packed tubes, thin films), requisite sample thickness, characteristics needed for the sample surface, and procedures
for optimizing intensities.
Because rock specimens contain numerous major mineral constituents, as well as numerous minor ones, the
identification of mineral phases can be quite complex using typical manual search-match procedures. Computer-
aided methods are available (Smith, 1989) and can be used to identify candidate minerals with some measure of
likelihood or probability (termed figure of merit) based on peak location and peak intensity. However, verification
of information from the computer search routines should be done using standard identification methods, such as
petrography.
XRD can also be used for semi-quantitative analysis of crystalline phases in solids. This can increase sample
analytical times from one to two hours to up to fifteen hours. Additional details are provided in Whan (1986).
Host rock and/or microfracture surface precipitates were analyzed by XRD. Mineral deposits were scraped from
the host rock using a stainless steel spatula and ground by hand with mortar and pestle. Host rock samples were
also ground by hand with a mortar and pestle. All samples were ground to a fine powder (< 100 urn) and loaded
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on a glass slide. XRD was performed with a Rigaku Geigerflex rotating anode goniometer using a Cu-Kasource
(45kV, 35 mA). Data were collected from 4 to 90 degrees 2-theta, with a step size of 0.05 degrees and a rate of 0.6
degrees/min. A tungsten standard was added to the sample to serve as a 2-theta reference. Mineral identification
was performed using Jade 5.0, which utilizes the ICDD database. Element exclusion was used to limit the searchable
database. A fairly rigorous routine was employed for searching (three lines of match, 0.1 degrees 2-theta error).
During search-match, a figure of merit is assigned by Jade to each mineral identified in the sample. A smaller
figure of merit indicated a high degree of certainty in mineral identification. Mineral matches with a figure of merit
less than 20 were included in the candidate mineral list. Given the large number of minerals in the ICDD database,
many unreasonable minerals were identified and discarded. Jade designates mineral phases as major, minor, or
trace based on relative peak intensity in the sample diffractogram. This serves as an indirect measure of mineral
abundance.
2.12 XPS Speciation of Microfracture Surfaces
XPS, formerly known as electron spectroscopy for chemical analysis (ESCA), is an extremely sensitive surface
analysis technique. In XPS, high energy non-monochromated or monochromated x-rays are directed at a sample.
The x-rays induce ionization of the surface atoms in the sample. As an atom ionizes, a photoelectron is emitted
from the atom. The ejected photoelectron has an energy that is, in part, characteristic of its binding energy. Over a
range of binding energies, emitted photoelectrons can be counted in discrete channels. Usually, at least one peak or
doublet appears for each element (except hydrogen). Peak intensity is used for quantitative analysis. Peak shift, or
chemical shift, is also an extremely valuable tool for documenting valency, nearest neighbor effects and speciation.
A variety of techniques are used to quantify peak shift. Frequently, energy referencing to the adventitious carbon
(binding energy of 284.80 eV) peak is used as this contaminant (from vacuum pump oil) is present on the surface
of all samples, even under high vacuum. This peak can be discriminated from other types of carbon peaks in the
sample. Detailed reviews are given in Hochella (1988) and Perry et al. (1990).
XPS can detect most elements. It has a spatial resolution of urn. Since photoelectrons are readily absorbed, only
those emitted from the top ten of angstroms of a surface are detected. Thus the technique is considered to be a
true surface spectroscopy. The sample must be dried and degassed in a roughing vacuum before analysis under
high vacuum. Interesting applications are provided by Eggleston et al. (1996) and Eighmy et al. (1999).
XPS is usually conducted with an ion sputtering apparatus to allow for removal of adventitious carbon and oxygen.
It can also allow for removal of the top atomic layers of a sample. The method is very slow, so quantitative and
chemical shift analysis can take many hours. Charging can be a problem with insulated samples. The large beam
size means that individual particles cannot be analyzed. Some spatial mapping can be done, but with low spatial
resolution. The technique is very elegant for looking at speciation and abundance with depth if coupled with the
sputtering techniques. Whan (1986) provides more detail on the method.
For the BBC work, surface species were detected using a Kratos Axis HS spectrometer. The instrument was equipped
for surface analysis, surface chemical mapping, and depth profiling of metallic, semi-metallic, and nonmetallic samples.
The sample is typically evacuated to 10'9 Terror better, for quality measurements. The system was designed around
a 127 mm mean radius hemispherical analyzer, which was equipped with a triple channeltron detection system for
improved sensitivity. By using a magnetic immersion lens, high sensitivity was apparent on small analysis areas. The
charge neutralization system allowed high resolution spectra to be obtained from insulating materials using either
the standard Mg/AI or Al monochromatic source. The instrument was controlled by the VISION data system, on a
SUN computer workstation and a Windows environment. Methods are described elsewhere (Eighmy et al., 1999;
Meima etal., 2002).
The microfracture face of each sample was examined. A non-monochromated Mg Ka X-ray source was used.
High-resolution scans were performed with a pass energy of 40 eV, a current of 10mA, and a step size of 0.1 eV.
Duration of data collection for each element was based on the relative intensity of the peak to be characterized. The
elements and lines characterized by XPS were AI2p, C1s, Ca2p3/2, Fe2p3/2, Mg2p, O1s, and Si2p. Peak fitting was
performed using the software package CasaXPS provided by the manufacturer. For energy referencing, a binding
energy correction was applied to all data based on the C 1s line for adventitious carbon at 284.80 eV (Hochella,
1988). The National Institute for Standards and Technology (NIST) XPS database, version 3.3 (See http://srdata.
nist.gov/xps.), was used to identify likely candidate minerals based on the binding energy of the fitted peaks. For
mineral identification, each element in the mineral had to have a binding energy characteristic of that mineral for
the mineral to be a candidate. An error of ± 0.3 eV was allowed during the search routine. Given the large number
of phases in the NIST database, many unreasonable phases were identified and discarded.
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Additionally, binding energy values for Ca, Mg, O and C in calcite and dolomite were obtained from the literature
(Baer etal., 1992; Gopinath et al., 2002; Stipp and Hochella, 1991). Binding energy values for Ca, Si, Al, and O in a
synthetic zeolite similar to faujasite (CaAI2Si4O16 • 6H2O) were also obtained from the literature (Barr, 1983). Binding
energy values for Fe and O in goethite (a-FeOOH), fresh amorphous hydrous ferric oxide (nominally Fe(OH)3 but
thermogravimetrically Fe2O3 • 3.26 H2O), aged hydrous ferric oxide (Fe2O3 • 1.57 H2O, likely some crystalline goethite
present) and limonite (Fe2O3 • nH2O) were obtained from the literature (Harvey and Linton, 1981). Binding energy
values for C in various chemical states in (NOM) Leonardite humic acid and soil humic acid from the International
Humic Substances Society (IHSS), or from purified Aldrich humic acid were obtained from the literature (Boughriet
et al., 1992; Monteil-Rivera et al., 2000) and used to assign principal peaks to C functional groups. Assigned C1s
binding energy values are: aromatic C-C/C-H (284.41 to 284.66 eV), aliphatic C-C/C-H (285.00 eV), alpha C-C(O)
(285.42 to 285.63 eV), ether/alcohol C-O (286.38 to 286.58 eV), ketone C=O (287.50 to 287.68 eV), amide C(O)N
(288.43 to 288.47 eV), carboxylic C(O)O (289.02 to 289.26 eV), and n-n (290.88 to 291.35 eV).
2.13 SIMS Fingerprints of Microfracture Surfaces
SIMS is an excellent near-surface analytical technique. Molecular fragments from the surface can be quantified to
extremely low levels (< 1 ppb). High degrees of spatial resolution are obtainable (Hochella, 1988). The method works
by bombarding a specimen with an ion beam (Cs+, O2+, or O) which sputters atomic and molecular ions from the
sample into the vacuum of the instrument. The sputtered ions are then extracted into a mass spectrometer where
they are quantified with magnetic and electrostatic sector analyzers. More recently, time-of-flight (TOF) SIMS has
been employed that allows for greater detection of mass fragments (See for example, Briggs et al., 2002.). The
system operates under high vacuum, and charging can be problematic in insulated samples. Topography plays a
large role in both the mass fragment yield and sputter crater that are produced during ion bombardment, so very
flat, planar samples are preferred for analysis. Detailed methods are provided by Metson (1990). Some applications
are described by Bancroft et al. (1987)
A Varian VG quadrapole filter type static SIMS was used for mass fragment detection under high vacuum. This
instrument is located at the University of Massachusetts at Lowell. A sample from microfracture MF03 was used for
analysis. A Ga+ ion beam was used for bombardment. Rock specimens were mounted on In foil to help minimize
charging. Generally, the ion source was operated at 10keV and 10 nA. Target biases were 13V.
2.14 MIP of Host Rock
MIP is a method used to study and characterize a material's interconnected pores (pore network) particularly as they
relate to or comprise the microfracture network in the rock. The principle of MIP is that a sample of known volume
is subjected to a pressure within a mercury penetrometer. As pressure increases, larger pores and microfractures
are first filled with Hg. At higher pressures, smaller pores or microfractures are then filled. The change in Hg volume
within the penetrometer is directly related to sample porosity. The pressure at which the pores or microfractures are
filled is related to the pore diameter using the Washburn equation:
d = -4Ycos9/p [Eq.2.1]
where d is pore diameter (nm), Y is surface tension of the Hg (N/m), 9 is the contact angle between the Hg and
the rock sample (degrees), and p is the pressure applied to the penetrometer (MPa). Pore size distributions may
be obtained by differentiating the change in pressure versus pressure applied plot.
Slices (1.5-2 cm in height) of borehole BBC5 core material were precisely cut into 1.4 x 1.4 x 2.0 cm cubes using
a Buehler Isomet Precision Saw. A diamond blade was used to cut the sample. Minimal water was used for cooling
the blade. These block dimensions were the maximum possible for use in the penetrometer, but small relative to
the spatial distribution of microfractures. Attempts to cut blocks with intact microfractures almost always resulted in
the separation of the microfracture. Sample blocks were freeze-dried for 3 days to remove water from the internal
portions of the cube.
MIP was performed with a Micromeritics Autopore III. The penetrometer selected for analysis was a 15-cc bulb
with a stem volume of 0.387 cc. This allowed for maximum sample size and sensitivity of mercury intrusion into the
bedrock sample block. The instrument was calibrated and checked with both non-porous (steel cube) and porous
(aluminosilicate powders) standards of known porosity or pore size. According to Micromeritics, at least 25% of the
Hg loaded into the penetrometer stem volume must intrude to generate reliable data. Data were collected over a
pressure range of 0 psia to 30,000 psia. Corrections were made for blank pen runs, compression of Hg (modified
Tait Equation), and the sample compressibility at high pressures. Preliminary work indicated the BBC host rock to
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be monolithic with low porosities (< 1%), making MIP difficult to use. Of the 10 samples that were analyzed, only
one sample gave reasonable readings relative to the 25% intrusion requirement. Much of the host rock was found
to be very impermeable to intrusion.
The method of Swanson (1981) was used to estimate host rock permeability (in Darcys) based on mercury intrusion
capillary pressures (psia) and cumulative porosity (%). The method is based on the principles embodied in Thormeer
capillary pressure plots. A nomograph is used to estimate permeability based on correlations between permeability
and porosity for many sandstones and carbonate rocks. The method was used previously by Colwell et al. (1997),
Fredrickson et al. (1997), and Onstott et al. (2003).
2.15 Packer Water Collection and Analytical Methods
Straddle packer interval sampling techniques were used to isolate regions in the borehole for segregation, purging,
and then sampling of waters (termed packer waters). Four sampling events were conducted. Microfracture MF04
(Cluster 2) was sampled on July 20, 2002. Microfracture MF05-MF06-MF07 (Cluster 3) was sampled on April 15,
2002, and May 29, 2002, and microfractures MF10-MF11 (Cluster 4) was sampled on June 3, 2003. Cluster 1 in
borehole BBC5 (microfractures MF01-MF02-MF03) was not sampled as the location was too close to the bottom
of the telescoping casing.
In the field, temperature (calibrated probe, Standard Methods 2510.B), pH (calibrated probe), Eh (polished platinum
inert redox electrode combined with an Ag/AgCI reference electrode checked with two reference solutions made of
K4Fe(ll)(CN)6»3H2Oand K3Fe(lll)(CN)6), alkalinity (titration), soluble Fe2+(Chemetrics Field Kit), and sample filtration
(0.22 urn) were conducted (Eighmy et al., 2002a and 2002b). Samples were then preserved as needed and sent to
Resource Laboratories Inc. (Hampton, NH) for analysis of soluble ions by ion chromatography, metals by flame or
graphite furnace atomic absorption spectrometry, and organics by various gas chromatography/mass spectrometry
(GC/MS) methods. Methane, ethane, and hydrogen were also determined. Fe3+ was determined by the difference
between total dissolved Fe and soluble Fe2+.
The following analytical methods were used: temperature (Standard Methods 2510.B), dissolved oxygen (Chemetrics
Field Kit), pH (Standard Methods 4500 H+B), alkalinity (Standard Methods 2320.B), specific conductivity (Standard
Methods 2510.B), ammonium (EPA 350.1), nitrate (EPA 300.0), nitrite (EPA 300.0), bromide (EPA 300.0), chloride
(EPA 300.0), sulfate (EPA 300.0), sulfide (Standard Methods 4500 SF), ferric iron (Standard Methods 3500.b),
ferrous iron (Standard Methods 3500.b), ferrous iron (Chemetrics Field Kit), metals (e.g., K, Cu, Cd, Pb, Zn, EPA
6010), hydrogen (Chapelle et al., 1995), DOC (EPA 415.1), ethane (EPA 8015), ethene (8015), methane (EPA
8015), and volatile organics (EPA 8260 or 524). Dr. Frank Chapelle and Dr. Paul Bradley of the USGS (Columbia,
SC) conducted the H2 analyses.
2.16 Geochemical Modeling
The modeling of apparent inorganic chemical pseudo-equilibrium conditions between packer waters and the
microfracture surfaces was done by using the Windows-based version of MINTEQA2, Visual MINTEQ (Meima et
al., 2002; Apul et al., 2002). Model inputs included all aqueous components measured as described in Section 2.15,
pH, temperature, total alkalinity (mg/L as CaCO3), the redox couple Fe2+/Fe3+ and the measured concentrations of
Fe2+ and Fe3+. No solids were allowed to precipitate. Output from the model included ion balances, aqueous phase
speciation, mass distributions, log ion activity products, saturation indices for all possible controlling solids, and
Eh.
The use of thermodynamic models to interpret solid phase control of dominant dissolved constituents, buffer
systems, redox reactions, and related geochemical processes must be done with some caution. Such analyses may
indicate pseudo-equilibrium for certain reaction types (particularly acid-base reactions), but that additional inference
is complicated by the likely presence of kinetically-controlled reactions occurring simultaneously with equilibrium-
controlled reactions. Further, there is no certainty that the system being modeled, a microfracture network comprised
of more open microfractures connected by spatially and temporally at pseudo-equilibrium, particularly when microbial
processes and diffusion limitations are likely to influence the system. At best, such analyses may shed some light
on some dominant geochemical processes.
2.17 Microbe Extraction
Cores were removed from the boreholes located within the TCE contaminated plume at Site 32. Drilling protocols
were developed to obtain core samples that contained intact representative microbial populations (See Volume
1: Fractured Rock Drilling.). Microfractures were identified, depths measured, and faces exposed with a sterilized
geological hammer. Seven microfractures were identified for analysis from borehole BBC5 (Table 2.1).
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To remove the microorganisms associated with the identified microfracture surfaces, samples were exposed to 15
minutes of treatment at a medium power setting in a small sonication bath that contained sterile phosphate-buffered
saline (0.61g/L KH2PO4, 0.96g/L K2HPO4, 8.5g/L NaCI; pH 7). Before sonication treatment, the core side walls were
first wiped down with ethanol (70%v/v) to reduce potential microbial contamination, particularly induced from drilling. It
will not destroy adsorbed nucleic acid material. Microorganisms liberated from the fracture surfaces were concentrated
by filtration through a 0.22 urn pore size GV membrane filter (Durapore, Millipore Corporation, MA). The filters were
stored at -80°C until analysis. Genomic DNA was extracted from the filtered samples with UltraClean™ Water (Mo Bio
Laboratories, Inc., CA), according to the manufacturer's recommendations. The extracted genomic DNA samples were
concentrated and further purified using QIAEX II Kit (Qiagen, CA).
2.18 Microbial Characterization Using Molecular Biological Techniques
The use of molecular biology techniques allows for the detection of small quantities of microbial nucleic acid in
environmental samples that are characteristic of the microbe, or population of microbes, from that sample. Ribosomal
RNA is an informational molecule from a microbe that is frequently targeted for detection. Ribosomal RNA is single
stranded, but highly structured. It can be separated into different size groups (e.g., 16s). Analyses of many 16s ribosomal
RNA nucleotide sequences resulted in the understanding that microorganisms are highly related through depiction in
phylogenetic trees of life.
The target for specific detection in this work was the segment of microbial DNA that contains the gene that codes for
the 16s RNA segment of the bacterial ribosome. This piece of DNA, unique to each microbial genera, contains many
16srDNA genes. Small quantities of this extracted gene obtained from the sample genomic DNA extraction process
were amplified using the polymerase chain reaction assay as a means to exponentially increase the quantity of 16rDNA
genes from the extract. Sufficient quantities are needed for detection with electrophoresis separatory methods and gene
sequencing. Polymerase chain reaction amplifies a specific DNA sequence, in this case the V3 region of the 16S rRNA
gene, by the use of repeated temperature-mediated stages using specific primers targeted for the gene and a DNA
polymerase to catalyze the reaction. The V3 region of the 16S rRNA gene is commonly used for molecular identification
as it is a highly variable DNA sequence between microorganisms and thus characteristic of the microbes in the sample.
Primers are short single-stranded segments of DNA, complementary to the 5' ends of the strands of the target DNA
to be amplified. Therefore, a pair of primers are chosen to flank the target DNA to be amplified, known as forward
and reverse primers, indicating which strand of the denatured double stranded DNA to which they anneal or bind. The
three stages of a PCR cycle are DNA denaturation, primer annealing, and primer extension. During DNA denaturation,
extracted double stranded genomic DNA is separated. The primers are then able to anneal to the target DNA using
specific temperatures. The extension of the primers will then occur using the DNA polymerase enzyme, replicating
the target gene. Multiple cycles are used to exponentially amplify the target gene. The presence or absence of specific
prokaryotic groups was analyzed by polymerase chain reaction using primer sets for partial 16S rDNA sequences of
specific groups, including bacteria, Archaea (a phylogenetic domain of prokaryotes, genetically distinct from bacteria, and
consist of methanogens, and most extreme halophiles and hyper-thermophiles), Dehalococcoides sp., Desulfuromonas
sp., Geobacteraceae and sulfate-reducing bacteria.
The diversity of prokaryotic bacterial communities and their phylogenetic affiliation (a system of classification of
organisms that aims to show their evolutionary history/relatedness) was determined by the analysis of the denaturing
gradient gel electrophoresis fingerprinting profiles and the sequencing of the 16S rDNA for the bacterial population.
Denaturing gradient gel electrophoresis is an increasingly popular and powerful method of profiling complex microbial
communities and inferring the phylogenetic relationships of the community members (Muyzer et al., 1996). Nucleic
acids were purified from extracts. Polymerase chain reaction was used to amplify a region of the 16S rDNA from the
mixed microbial populations present in each extract using primers specific for that gene. One of the primers included
a guanine-cytosine (GC)-rich sequence (termed a GC clamp) that imparted melting stability to the polymerase chain
reaction products which means the amplified double stranded DNA can't completely denature (separate) and run
completely through the DGGE gel. The products were essentially all the same size and were separated into discrete
melting domains during electrophoresis through an acrylamide gel that contained an increasing linear gradient of
denaturants. Individual, double stranded DNA molecules denatured along their length adjacent to the GC-clamp according
to their melting characteristics (or sequences). This property resulted in a distinct banding pattern in the gel used for
each sample. Each band represented essentially a different rDNA sequence, and hence, a different member within the
microbial community. Each lane in the gel provides a phylogenetic profile of the microbial community in that sample. The
number of samples processed can be greatly increased because denaturing gradient gel electrophoresis is much less
labor intensive than traditional microbial community analysis. This increased experimental reproducibility and statistical
relevance to the results. Denaturing gradient gel electrophoresis has a high degree of sensitivity because it can detect
single-base pair differences between DNA molecules.
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2.19 Primers and Polymerase Chain Reaction Assay
The V3 region of the 16S rDNA of bacteria was amplified by polymerase chain reaction with primers 907R (Lane et al.,
1985) and 338F (Amann et al., 1990) using 10ng of genomic DNA template. A GC-Clamp (Muyzer and Smalla, 1998)
was attached to the 5' end of the forward primer, 338F, for denaturing gradient gel electrophoresis analysis. Nested
polymerase chain reaction was performed to amplify the V3 region of the archaeal 16S rDNA, V3 region. Nested
polymerase chain reaction means that two pairs of polymerase chain reaction primers were used for a single gene. The
first pair amplifies the gene as seen in any polymerase chain reaction experiment. The second pair of primers (nested
primers) bind within the first polymerase chain reaction product and produce a second polymerase chain reaction product
that will be shorter than the first one. The reasoning for this is to increase the amplification success of lower abundance
of microorganisms and that if the wrong locus were amplified by mistake, the probability is very low that it would also
be amplified a second time by a second pair of primers.
The primers 21F and 1492R (Giovannoni et al., 1988 and Lane, 1991) were used to amplify the entire 16S rDNA with
25ng of genomic DNA template, and the primers 340Fand 915R (0vreas et al., 1997; Amann et al., 1995) were used to
amplify the V3 region using 1 uL of purified 16S polymerase chain reaction product. The following primer sets, presumptive
for the presence of these microbial groups, were used to amplify partial sequences of the 16S rDNA for prokaryotic
groups: sulfate-reducing bacteria with the 385F and 907R primers (Lane etal., 1985; Amann et al., 1990), dehalorespirers
including D. ethenogenes and Dehalococcoidessp. (strain FL2) with 728F and 1172R primers, Desulfuromonas group,
including Desulfuromonas sp. (strain BB1) and D. chloroethenica with 205F and 1033R primers (Loffler et al., 2000),
and Fe (III) reducing Geobacteraceae with 338F and Geo825R primers (Snoeyenbos-West et al., 2000).
The polymerase chain reaction was performed using a PTC-200 Peltier Thermal Cycler (MJ Research, Cambridge,
MA) in triplicate 25 uL reaction volumes, using 0.5 uM of each primer and Qiagen HotstarTaq Master Mix (1.25 Units
HotstarTaq DNA polymerase/reaction) (Qiagen, CA).The following thermal cycling parameters were used for bacterial
16S rDNA, V3 region and archaeal 16S rDNA amplification. An initial activation step of 15 min at 95°C was performed
to activate HotstarTaq DNA Polymerase, followed by an initial DNA denaturation step at 94°C for 2.5 min. Eleven cycles
followed of denaturation at 94°C for 30 s, primer annealing at 56°C for 45 s, and primer extension at 72°C for 1 min.
This step was followed by 11 cycles of denaturation at 94°C for 30 s, primer annealing at 56°C for 1 min and primer
extension at 72°C for 1 min 30 s. This stage was followed by 14 cycles of 30 s denaturation at 94°C, primer annealing
at 56°C for 1 min 15s, primer extension at 72°C for 2 min 15s and a final extension step of 7 min 30 s. For all other
amplifications, an annealing temperature of 58°C was used. Polymerase chain reaction products were pooled and purified
using QIAquick Polymerase Chain Reaction Purification Kit (Qiagen, CA). Products were run on an agarose gel (1%),
and visualized using a GelDoc 2000 system (Bio-Rad).
2.20 Denaturing Gradient Gel Electrophoresis
Denaturing gradient gel electrophoresis was performed on the amplified bacterial 16S rDNA with a GC-clamp with
the Bio-Rad Dcode™ Universal Detection System. Samples were loaded on an 8% (w/v) polyacrylamide gel with a
denaturing gradient ranging from 40% to 60% denaturant gradient, starting at 40% and running to 60%, created with
formamide and urea within an acrylamide gel. Gels were run in Tris-acetate-EDTA buffer (20 mM Tris, 10 mM acetate,
0.5 mM EDTA, pH 7.4) for 16 h at 70 V and were stained for 20 min in Tris-acetate-EDTA buffer containing ethidium
bromide (50 ug/ml). Gel was destained for 30 min in Tris-acetate-EDTA buffer and photographed on an UV transilluminator
(FVSTI-88).The resulting banding patterns were analyzed by the use of Quantity One program (Bio-Rad Laboratories,
CA). A dendrogram spatially depicting similarities between phylogenetic trees was created from the cluster analysis
by using an unweighted paired group method with arithmetic averages. A similarity coefficient of >0.70 indicates that
the samples are similar while those values < 0.70 indicate the samples are very different (Roling et al., 2001). A lower
value indicates a greater difference between the samples.
2.21 DNA Sequencing & Analysis
DNA was eluted from excised denaturing gradient gel electrophoresis bands and re-amplified using the primers cited
in Section 2.19. Denaturing gradient gel electrophoresis was re-performed on individual bands, to check band purity.
These bands were removed and DNA eluted and re-amplified using the above primer set without a GC-Clamp. These
polymerase chain reaction products were used as a template for sequencing reactions with a DYEnamic ET Terminator
Cycle Kit (Amersham Pharmacia, NJ) and an ABI 377A automated sequencer (Applied Biosystems, CA). The 338F primer
was used for these sequencing reactions. The sequences were compared with the 16S rDNA available from GeneBank
and EMBL database by the use of the BLAST program (http://www.ncbi.nlm.nih.gov/BLAST; Altschul et al., 1997).
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2.22 Data Quality
A quality assurance project plan was prepared for the entire BBC research project (Kinner et al., 2001). The plan details
data quality assurance objectives, training, documentations and records, sampling, chain of custody, analytical methods
requirements, quality control, instrumentation, calibration and frequency, inspection, data management, assessment
and oversight, and data validation and usability.
This portion of the BBC project was considered exploratory in nature. The study of microbial populations and mineralogy
on the surface of competent bedrock microfractures is a new field with many of the methods requiring development of
protocols that could enable samples to be collected and characterized. Consequently, data quality objectives are more
qualitative in nature with a focus on the description of the nature of the microfracture surfaces.
Table 2.2 provides an overview of the methods that were applied to each of the microfracture samples (host rock or
microfracture surface precipitate). Where applicable, qualitative assessments of data quality are offered. When appropriate,
specific discussions of data quality measures such as precision, accuracy, completeness, representativeness (a measure
of the degree to which data accurately and precisely represent characteristics of the population) and comparability (the
confidence with which one data set or method can be compared to another) are offered for each method used in this
report.
Cores were obtained in 1.5 meters maximum lengths. Special handling procedures were used to retrieve the cores in
order to minimize microbial contamination and alteration. These procedures included handling the cores in a specially
constructed, on-site anaerobic glove chamber. The chamber was housed in a "laboratory" trailer, located at Site 32 for
the duration of this study.
The drill rig and all support equipment were brought on site and were decontaminated by steam cleaning within a
decontamination pad. The steam cleaning was followed by a 30 minute soak in a dilute chlorine bleach solution for drill
rod, drill bits, roller bits, wrenches, and other support equipment for drilling. The support equipment was allowed to sit
for 30 minutes to give the bleach solution adequate contact time to kill the bacteria. After 30 minutes, the equipment was
rinsed with clean water from a well in the deep bedrock formation that was confirmed uncontaminated. Decontamination
wastes were captured by a plastic liner, collected, and containerized for ultimate disposal at the Pease Site 8 groundwater
treatment facility.
All pumps and hose lines used during drilling procedures were decontaminated using a dilute chlorine bleach solution.
The pump and hose lines were either completely filled and left to soak for 30 minutes (contact time required to kill
bacteria spores), or the water was pumped through the system and continuously recirculated for at least 30 minutes.
This was followed by a flushing rinse with the clean rinse water. Decontamination wastes were containerized and stored
for ultimate disposal at the Pease Site 8 water treatment facility.
Microfracture sampling protocols were developed to collect microfractures as a function of depth with the correct altitude
so that, upon removal, aseptic samples could be produced that (i) were representative of the microfracture surface,
(ii) could be sub-sampled for all spectroscopic analyses, and then (Hi) were sufficiently thin and of correct area to allow for
insertion in various analytical instrumentation. As such, sampling was somewhat a trial and error process. Nevertheless,
11 microfractures were collected for analysis from the two boreholes.
SEM, as a descriptive tool to visually examine the microbial and mineral morphology of microfracture surfaces, was
really only dependent upon sample geometry. All 11 microfracture subsamples were examined using SEM at various
magnifications and examining hundreds of images. Magnifications were used to provide low magnification depictions
of larger areas (mm by mm) to much higher magnifications of cells. Detection limits were not applicable. No standards
were run. No replicates were run. Precision and accuracy are not applicable. The images were typical of the 11 sampled
microfractures and thus comparable amongst the collected samples. It is not known how representative they may be
of the microfracture surfaces generally at the site within the Kittery Formation, though based on well logs, the types of
microfractures and their densities were relatively uniform through the drilled regions.
SEM-EDAX can detect elements with atomic numbers greater than 8 with detection limits typically of 0.1 to 1.0 % with
spatial resolutions on the order of 10-100 nm (Geesey et al., 2002). The EDAX detector was calibrated routinely with
primary standard thin sections of known composition. The optics of the electron gun were optimized before analysis. The
EDAX detector was operated so as to provide optimum counts within energy channels. All 11 microfracture subsamples
were examined using SEM-EDAX at various magnifications and mapping hundreds of images. No replicates were run.
Precision and accuracy are not applicable. The spectra and spatial maps were typical of the 11 sampled microfractures
and thus comparable amongst the collected samples. It is not known how representative they may be of the microfracture
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surfaces generally at the site within the Kittery Formation, though based on well logs, the types of microfractures and
their densities were relatively uniform through the drilled regions. TEM, as a descriptive tool to visually examine the
microbial morphology of cells within the microfracture surface precipitates, was very exploratory and was conducted
on only one microfracture surface precipitate sample sufficiently soft, (containing low levels of quartz and high levels of
carbonates) amenable to fixation, embedding, and thin sectioning with a diamond knife. Approximately 100 thin sections
were generated from the various embedded samples. These were all carefully examined for cell structures and features.
No standards were run. No replicates were run. Precision and accuracy are not applicable. Hundreds of micrographs
were taken at various magnifications. It is difficult to ascertain how comparable and representative these data are.
Petrographic thin sections can detect minerals that are 1.0 to 2.0 mm in size within a petrographic thin section. This
represents the lower limit for optical microscopic characterization and modal analysis. All 11 host rock samples were
analyzed. However, only three of the 11 attendant adherent microfracture surface precipitates were sufficiently thick to
characterize minerals within the surface precipitates. During point counts along transects, hundreds of digital photographs
were taken under various optical systems to allow for mineral identification. No standards were run. No replicates were
run. Precision and accuracy are not applicable. It is difficult to ascertain how comparable and representative these data
are.
XRD can detect crystalline minerals when they constitute about 1 to 2% of the bulk sample. As described earlier, complex
statistics are used to match diffraction patterns to known patterns from mineral libraries. All 11 host rock specimens
were analyzed. However, only nine of the 11 samples had surface precipitates that were sufficiently thick to produce the
necessary quantities for XRD. No standards were run. No replicates were run. Precision and accuracy are not applicable.
The diffractograms and mineral identifications were typical of the 11 sampled microfractures and thus comparable
amongst the collected samples. It is not known how representative they may be of the microfracture surfaces generally
at the site within the Kittery Formation, though based on well logs, the types of microfractures and their densities were
relatively uniform through the drilled regions. Also, similar petrographic data were obtained in an earlier study.
XPS can detect elements with atomic numbers >3 with detection limits typically of 1.0% with spatial resolutions on
the order of 10s of urn (Geesey et al., 2002). The XPS is calibrated using Au and Pd standards to examine accuracy
over the linear energy scale. The detectors are controlled to obtain statistically significant counts above background.
During analysis, internal charge referencing is done with adventitious carbon at 284.80 eV. Mineral identification is done
using NIST protocols and databases. Nine of the 11 microfracture samples were examined with XPS. No replicates
were run. Precision and accuracy are not applicable. The spectra were typical of the nine analyzed microfractures and
thus comparable amongst the collected samples. It is not known how representative they may be of the microfracture
surfaces generally at the site within the Kittery Formation, though based on well logs, the types of microfractures and
their densities were relatively uniform through the drilled regions.
SIMS can detect mass fragments with atomic mass units >1 with detection limits typically of 0.001 to 1.0% (depending
on surface roughness, geometry, charging) with spatial resolutions on the order of 10s of urn (Geesey et al., 2002). Only
one sample was subjected to SIMS analysis. No standards were run. No replicates were run. Precision and accuracy
are not applicable. It is difficult to ascertain how comparable and representative these data are.
MIP can detect pore widths of 0.01 um provided that the rock sample has porosities > 1 %. Many host rock samples were
run, but had very low porosities (<1%), making MIP analyses difficult. The MIP was calibrated using standard protocols
for pen operation. Standard reference samples of known porosity were run and were always within 95% of the certified
value. Eventually, only one sample of the 40 that were attempted had proper porosity and pore size data. No replicates
were run. Precision and accuracy are not applicable. It is difficult to ascertain how comparable and representative these
data are.
Groundwater sampling/monitoring occurred at several stages throughout the BBC research. Prior to drilling activities,
initial sampling of isolated fractures using well packers in select deep bedrock wells (32-631, 32-632, 32-633, 32-6012,
32-6027, and 32-6031) was conducted. The objective of the initial sampling was to obtain more detailed information
about the contamination flowing into each well from particular fracture zones. Groundwater samples were also collected
from the discrete fractures within each of the preliminary and test boreholes once drilling was complete. Initially, the
identified fracture locations were based on the analyses of the borehole geophysical testing and video logs of existing
deep bedrock wells. This information was used to plan sampling depths and intervals for each well. Packers were used
to isolate the fractures during pre-drilling groundwater sampling. Groundwater samples from specific fracture zones in
the preliminary and test boreholes were also collected using a straddle-packer. Groundwater samples collected, as part
of this research, from preliminary and/or test boreholes were considered critical samples (required to meet the BBC
research objectives).
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The straddle-packer method consisted of a pneumatic sampling pump (does not generate hydrogen) that was set between
two inflatable packers. The straddle-packer was lowered so that the pump intake was at the elevation of the fracture to be
sampled. The packers were inflated above and below the sampling interval (using compressed N2 gas) to hydraulically
isolate the fracture from the rest of the well. A series of samples were collected during any given sampling event. When
sampling was completed, the packers were deflated and raised or lowered to the next fracture. This sampling process
continued until all the selected fractures were sampled.
The sampling of each fracture was meant to obtain representative water samples (and attendant water quality) from the
individual fracture. pH, conductivity (n), and temperature (T) were monitored and the values recorded once pumping of
a given fracture was initiated. This procedure was continued until the monitoring indicated that the real time parameters
(pH, n, and T) had stabilized. After collecting the groundwater samples in the appropriate sample containers, the sample
containers were placed on ice in a cooler and transported to the laboratory.
Purge water removed from the wells was collected, stored in carboys at the Site 32 treatment plant, and finally disposed
of at the Pease Site 8 groundwater treatment plant when a sufficient volume had been collected.
The packer and pump assembly consisted of as much Teflon and stainless steel materials, along the water sample
pathway to the surface, as practical, in order to minimize adsorption of groundwater constituents to sampling equipment
during pumping and to eliminate the need for decontaminating the packer apparatus between sampling intervals within
the same borehole. All sampling equipment was decontaminated between wells to prevent cross-contamination. This
included successive rinses with laboratory soap, and either bottled spring water or water from a nearby bedrock well
that had been confirmed clean. All decontamination fluids were containerized, stored as above, and disposed of at the
Pease Site 8 groundwater treatment plant. Each well was capped and secured following completion of the sampling.
The analyses conducted on the packer water samples included volume, collection time, temperature, pH, conductivity,
DO, Eh, TCE, trans-1,2-DCE, cis-1,2-DCE, 1,2 DCE, VC, acetone, methane, ethane, ethene, NPDOC, NH4+, alkalinity
(as CaCO3), Ch, SO42-, NO3-, S2-, Fe2+, Al, As, Ba, B, Ca, Cr, Cu, Fe, Pb, Mg, Mn, L, Si, Na, and Zn. Kinner et al. (2001)
discusses the methods. Table 3.16 (page 60) shows detection limits. The groundwater characterization program was
subject to extensive QA/QC as described by Kinner et al. (2001). The methods of collection and subsequent analyses
were typical of the entire sampling campaign associated with the project and thus comparable amongst all the collected
samples. The analyses for these samples were also typical of the entire sampling campaign and thus representative.
Hydrogen analyses were performed as a small side study. Hydrogen analyses were performed on water samples following
the methods developed by Dr. Francis H. Chapelle (USGS; Columbia, SC). Dr. Chapelle and Paul M. Bradley (USGS;
Columbia, SC) traveled to New Hampshire to sample and analyze groundwater for hydrogen, as an indicator of microbial
activity. Sampling was performed using a piston-type pump (e.g., pneumatic positive displacement pump) powered by
compressed air to avoid problems with generation of hydrogen typical of electrically driven pumps. The sampling and
analytical methods for hydrogen are outlined in Chapelle et al. (1995). It is difficult to ascertain how comparable and
representative these data are.
Polymerase chain reaction (PCR) was used to amplify a region of the 16S rRNA gene from the DMA extracted from
mixed microbial populations using primers specific for that gene. Detection limits are around 0.1 ug of DMA. This was
performed to determine the diversity of prokaryotic microbial communities found associated with the fracture surfaces of
BBC5 microfractures with various mineral deposits. Seven of the 11 microfracture samples were run (as intended). All
of the samples were from BBC5. PCR reactions were performed in triplicate with s1 ug template DNA, with a positive
DMA control (certified DNA strands from E. colior B. subtillus), to show assay specificity and a negative water control
to test for user contamination. In cases where the positive or negative controls indicated problems, samples were rerun.
The triplicates were then pooled for denaturing gradient gel electrophoresis analysis. No replicates were run. Precision
and accuracy are not applicable. It is difficult to ascertain how representative and comparable the analyses were.
Denaturing gradient gel electrophoresis (DGGE) is a molecular fingerprinting method which enables visualization of
PCR amplified genes as a distinct banding pattern. DGGE has a high degree of sensitivity because it can detect single
base pair differences in the amplified gene, creating a different band and hence a different microorganism within the
community (Muyzer & Smalla, 1998). Band definition depends on the amount of DNA in the sample. Volumes of extract
to be denatured on the gel are modified to produce clear, bright bands that are neither too dim nor too bright. The bands
are quantified by computer analysis of scanned images that uses statistical protocols for identifying band pixel brightness
and band area extent definition compared to background. During runs, controls are run in the two perimeter lanes. If
the behavior of the controls (band patterns and migration) were incorrect, gels were re-run. The large number of bands
indicates a higher level of microbial diversity both on and between the microfracture surfaces. Banding patterns for each
sample were analyzed and compared to give similarity coefficients (Roling et al., 2001). Only two fractures were shown
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to be similar, indicating bacterial communities were independent of each other. No replicates were run. Precision and
accuracy are not applicable. Given the focus on comparing patterns between microfractures, the data are considered
to be highly representative. It is difficult to ascertain how comparable the analyses were.
DMA sequencing was performed on DNA eluted from excised DGGE bands and re-amplified to identify specific bacteria.
Sequencing was done only on DGGE bands from MF4. Sequences were compared with the 16S rRNA genes available
from the GeneBank library and EMBL database by the use of the BLAST program (http://www.ncbi.nltri.nih.gov/BLAST
Altschul et al., 1997). The method requires 0.1 to 10 picomoles of DNA. Standards are run with pure phage DNA (M13)
to ensure proper protocols and sequencer performance. Chromatograms of the sequenced product were examined
for purity. In the case that the chromatograms were diffused, the original samples were re-purified and run again. No
replicates were run. Precision and accuracy are not applicable. Given the focus on matching sequences to library data,
the data are considered to be highly representative. These sequences are considered highly comparable as the microbes
in the library have been recovered from similar ecosystems.
3.0 Results & Discussion
3.1 Microfracture Locations
The microfractures collected from borehole BBC5 were distributed in three clusters (Figure 2.3): Cluster 1 [those at
around 21.79 to 22.25 m (71.5 to 73.0 ft) below top of telescoping casing (microfractures MF01, MF02, MF03)], Cluster
2 [those at 29.56 m (97 ft) below top of telescoping casing (microfracture MF04)], and Cluster 3 [those at around 37.03
to 37.39 m (121.5 to 122.7ft) below top of telescoping casing (microfractures MF05, MF06, MF07)].The microfractures
collected from borehole BBC6 were distributed in a fourth cluster [those at around 32.73 to 35.57 m (107.4 to 116.72
ft) below top of telescoping casing (microfractures MF08, MF09, MF10, and MF11)]. Further, microfractures MF02 and
MF03 in Cluster 1 from borehole BBC5 were adjacent to each other, but were not connected, at least within the volume
of the core.
Two of the four cluster regions were subjected to hydraulic testing to ascertain transmissivity. The region around Cluster
3 (borehole BBC5) had a borehole transmissivity of 0.139 m2/d (1.5 ft2/d). The region around Cluster 4 (borehole BBC6)
had a borehole transmissivity of 0.185 m2/d (2 ft2/d).
Three of the four clusters were from one well (borehole BBC5) and were separated by at most 15.24 m (50 ft) of bedrock
vertical depth. The fourth cluster (borehole BBC6) is at a similar depth, but over 7.6 m (25 ft) of lateral distance away.
The hydraulic connection between boreholes BBC5 and BBC6, based on hydraulic tests, is in a major fracture that runs
from a depth of about 33.52 to 35.35 m (110 to 116 ft) below top of telescoping casing in BB5 to a depth of about 39.62
to 40.84 m (130 to 134 ft) below top of telescoping casing in borehole BBC6. Transmissivities in these regions were
relatively high, 0.836 to 1.393 m2/d (9 to 15 ft2/d). This major fracture(s) was just 1.67 m (5.5 ft) above microfracture MF7
and 4.04 m (13.28 ft) below microfracture MF11. The exact point of planar intersection, if any, between the microfracture
and the open fracture is not known. Consequently, the exact fluid flow line (or diffusion path) distance between any of
the microfractures that were sampled and open fractures cannot be estimated. Further discussions about site hydraulics
are given in Volume 3: Fractured Rock Hydraulics.
3.2 Microfracture Surface Precipitate Morphology
The microfracture surface morphology, revealed through SEM, had four general characteristics (Figure 3.1). A smooth
surface, which seemed to be the host rock, was apparent on some samples. At higher magnifications (data not shown), the
host rock microfracture face appeared chonchoidal.The surface was etched in some regions, an indication of weathering
and incongruent dissolution of the rock. On other microfractures, the surface appeared smooth at low magnification, but
at high magnification, was clearly a distinct, flaky texture (e.g., microfracture MF06, Figure 3.1c). A third surface feature
was small diameter (< 1.0 um to 100 urn) granular precipitates (e.g., microfracture MF08, Figure 3.1d). Typically angular
in nature, these granules were found upon the smoother surface of the underlying host rock. Finally, some areas had a
fine structured web-like material (e.g., microfracture MF01, Figure 3.1 a; microfracture MF05, Figure 3.1b) .The expanse
of this morphology varied between samples. More than one morphology could be observed on a single microfracture
sample. Table 3.1 summarizes the surface precipitate morphologies observed on the microfractures.
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(a)
100|im
10 jam
1 fim
Figure 3.1. SEM micrographs of typical microfracture morphology: (a) web formation with prismatic mineral grains
on microfracture MF01 (250x), (b) web formation on microfracture MF07 (7,250x), (c) flakey appearance to surface
minerals on microfracture MF06 (1,000x), and (d) granular mineral precipitate on microfracture MF08 (6,100x).
Table 3.1. Summary Description of Surface Precipitate Morphologies
Microfracture #
MF01
MF02
MF03
MF04
MF05
MF06
MF07
MF08
MF09
MF10
MF11
Surface Description
Fine structured web-like precipitation with large quartz grains distributed throughout.
Host rock visible with angular granular materials dispersed over surface. Grains had a size
range of 100 urn to less than 1 urn.
At low magnification, the surface appeared smooth with intermittent cracks. At high
magnification, there was a consistent flakey appearance, which was visible throughout the
microfracture surface.
Significant coverage of surface with angular mineral grains similar to microfracture MF02.
Much of host rock was obscured. Some areas with flakey appearance as in microfracture
MF03.
Smooth coverage, almost blanket like. In areas where the coverage appeared worn away, a
web-like formation with high surface area and significant structure was visible.
Flakey appearance similar to precipitate on microfracture MF03.
Similar to microfracture MF05.
Similar to microfracture MF02.
Areas of flakey formations and angular granules resting on a smoother base.
Similar to microfracture MF05.
Host rock exposed with both angular granules and web-like formations visible.
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3.3 Microfracture Element Spatial Maps
Figure 3.2 shows a typical EDS element spatial map of microfracture MF03 showing spatial distribution of Al, Ca, Fe,
K, Mg, Na, O, S, Si, and Ti.The spatial heterogeneity of minerals is high; the surface is quite diverse at the ten's of urn
scale. Table 3.2 shows dominant and minor elemental phases revealed by SEM-EDAX in microfracture MF01 -MF11.
Samples were sputter coated with carbon to prevent charging; therefore, carbon occurring naturally in the sample could
not be characterized. Typical dominant elemental phases in microfracture MF01- MF11 were Si-AI-O, with K and/or Mg
enrichment, and Ca-O. Fe enrichment in either a calcium phase or an aluminosilicate phase occurred in seven of the
11 microfractures. Sulfur-bearing iron compounds (Fe-S), nominally pyrite (FeS2), occurred as minor phases in four of
the 11 samples.
X Image Display 1
Filer) Edit r) Viewr) Setupr)
Image ~| 11 8 bit 512x408 image.
Figure 3.2. Typical EDS elemental spatial map in X-Y plane for microfracture MF03. Each window is 250 by 200 urn.
(a) Si-AI-Mg-K-Fe-O, (b) Ca-O, (c) Ti, (d) Si-O.
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Table 3.2. Summary Description of Element Association in Spatial Maps
Microfracture #
MF01
MF02
MF03
MF04
MF05
MF06
Dominant Phases
Si-AI-Mg-O
Si-AI-K-O
Si-AI-K-Mg-O
Ca-O
Si-AI-K-O
Si-AI-K-Mg-O
Ca-O
Si-AI-K-O
Si-AI-K-Mg-O
AI-Mg-Fe-O
Si-AI-Fe-O
Si-Fe-O
Fe-S
Si-O
Si-AI-K-O
Si-AI-K-Na-O
Ca-Mg-Fe-O
Minor Phases
Si-O
Si-Mg-AI-K-O
Ca-O
Si-O
Fe-S
Si-AI-K-Mg-Fe-O
Ti
Si-O
Ca-O
Fe-S
Ti
Si-O
AI-K-O
AI-K-Na-O
Ca-O
Ca-Mg-O
Fe-S
Ti
Si-O
Fe-O
Ti
Microfracture #
MF07
MF08
MF09
MF10
MF11
Dominant Phases
Si-AI-Fe-O
Si-O
Si-AI-K-O
Ca-O
Si-AI-K-O
Si-K-O
Ca-Mg-Fe-O
Si-AI-K-O
Si-AI-K-Fe-O
Si-AI-K-Fe-Ca-O
Si-AI-Mg-Fe-O
Si-AI-K-Mg-Fe-O
Ca-O
Minor Phases
Si-O
Si-AI-K-O
Si-AI-Na-O
Ca-O
Si-AI-O
Fe-O
Si-AI-Na-O
Fe-S
Si-O
Ti
Si-O
Si-AI-K-O
Si-AI-Na-O
Si-AI-Fe-O
31
-------
3.4 Microfracture Biopatch Distribution and Morphology
The extent and distribution of prokaryotic populations on microfracture surfaces were characterized with SEM (Figures
3.3, 3.4, and 3.5). The ability to view microbes on the surface of the microfracture seemed to be limited by the morphology
or topography of the surface precipitates. Smooth, exposed host rock revealed greater numbers of microbes than the
fine structure web-like surfaces typical of the surface precipitates (See Figure 3.5.). The flakey surface morphology
required careful examination to discern microbial forms from the precipitates.
Figure 3.3. Biopatch SEM micrographs, (a) Biopatch on microfracture MF04. The microbes are situated in a crevice.
(b) Microbe with extensive extracellular material on microfracture MF04. (c) Microbial populations on microfracture
MF03 embedded in possible organic matrix, (d) Biopatch on microfracture MF04. The microbes are again in a crevice.
32
-------
"1 - %.•
1 jLim
•^•^-v/;
;;" . • • '-^f-
-J>!
f
1 '£ '-;ci^l?
(b)
1 jam
Figure 3.4. Biopatch SEM micrographs, (a) Biopatch on a smoother surface coated with possible organic material
on microfracture MF07. Note the dividing cells with division septa, (b) Microbes on rough surface on microfracture
MF07. Note the small grains on the surface of the microbes, (c) Coated biopatch on microfracture MF06. (d) Coated
biopatch (close-up of box in image C on microfracture MF06).
33
-------
Figure 3.5. Biopatch SEM micrographs, (a) Microbe in a crevice on microfracture MF09. (b) Microbe among angular
material on microfracture MF09. (c) Microbe on smooth surface on microfracture MF11. (d) Biopatch on flakey
material on microfracture MF11.
Microbes were often found in crevices or topographical features. Once a single microbe was sighted, a more thorough
examination of the surrounding area typically revealed other microbes in a biopatch. In some cases, evidence of cell
division was seen. The typical microbial morphology found in the SEM investigation was a rod of 1.0 - 2.0 um in length
and 0.5 -1.0 um in width. This suggests that a low diversity of morphologies may be present on the samples.
Microfracture MF04 had the largest apparent microbial population (Figure 3.3 a and b). The other microfracture
samples had sparse to moderate microbial numbers, relative to microfracture MF04. Approximate cell densities (based
on cell counts just in lower magnification micrographs) were relatively low (e.g., < 104/cm2). These cell densities are
only indirectly comparable to other measures of numbers of cells or biomass reported in the literature. For instance,
Onstott et al. (2003) used phospholipid fatty acid and terminal restriction fragment length profile analyses to show that
indigenous microorganisms were present at < 102 cells/g of rock in deep bedrock in South Africa. Microfracture MF06,
which had a flakey surface, had microbial populations that appeared to be coated by an organic surface material. The
semi-exposed cell features were often accompanied by outlines of more cell features under a blanket-like surface (See
Figure 3.4 c and d.).
It is surprising that only one morphological type (rod) was observed with SEM. Related work with epifluoresence
microscopy on porewater microbes reveals a variety of morphologies (e.g., rod, coccoid, filamentous, stalked). (See
Volume 4: Fractured Rock Microbiology.) Further, this morphology differs from some of those seen within the surface
precipitate with TEM (See Section 3.5.). It is not clear if the surface selects for one morphology, if an artifact has been
introduced by fixation and critical point drying, or if the three dimensional structure of the surface precipitates prevents
observation of other morphologies with SEM. The later hypothesis, given the observations with TEM, may be most
relevant. There is little data from the literature on microfracture adherent microbial populations with which to compare.
34
-------
3.5 Microfracture Microbial Populations Situated Within Surface Precipitates
The TEM work revealed that a diverse population was present in the calcite and quartz surface precipitates that were
prevalent on microfracture MF11 from borehole BBC6. A number of stalked morphologies were seen (Figure 3.6). The
cell sizes were large (0.7 urn in diameter, 1.5 to 2.0 urn in length). In some cases, the stalk was very apparent. Figure
3.7 shows some spirillum morphologies which were also prevalent. The cells were generally larger than the rod shaped
cells seen with SEM. Both 0.1 um diameter electron-opaque and 0.3 um diameter electron transparent inclusion bodies
were present in the cells (Figure 3.8). Most of the cells observed with these organelles appeared to be filamentous.
At this time, the elemental composition of these organelles is unknown. Additional filamentous morphologies, some
with pronounced inclusion bodies, were observed (Figure 3.9). The filaments, in some instances, were over 8 um in
length.
(a)
(b)
2.0 pm
1.0
(c)
(d)
2.0
1.0 \im
Figure 3.6. TEM micrographs of stalked morphologies present in calcite precipitates on microfracture MF11. The
cells appear to have inclusion bodies.
35
-------
2.0 urn
(b)
(c)
(d)
2.0
1.0
Figure 3.7. TEM micrographs of spirillum morphologies in calcite precipitates in microfracture MF11. The cells
appear to have inclusion bodies.
36
-------
'" - (b,
2.0 pm 2.0 |jm
(c) (d)
4^ ••*
- «
Figure 3.8. TEM micrographs of filamentous morphologies in calcite precipitates in microfracture MF1 1 . The cells
appear to have inclusion bodies.
37
-------
(a)
0.5
(b)
(c)
1.0
(d)
Figure 3.9. TEM micrographs of inclusion bodies within cell structures in calcite precipitates in microfracture MF11.
Note that some bodies are electron dense (dark) while others are electron opaque (grey).
38
-------
3.6 Petrographic Characterization of Host Rock and Microfracture Surfaces
Lithological observations involved examination of core material during well logging as well as petrographic analysis of
thin sections. From a thin section perspective, the microfracture surfaces were independent of rock type. Fracture-fill
material, dominated by carbonate mineral(s), crossed lithologic boundaries (bedding surfaces, minor faults, and fractures
of varying types). Figure 3.10 illustrates three fracture filling types. Figure 3.11 illustrates layering and textural relations
of the metasandstone and metashale in the Kittery Formation.
Calcite
\
Quartz
Folded
Quartz +
Calcite
Vein V
^—Location of
Calcite Vein
With Halo
Figure 3.10 Petrographic thin
section of Kittery metasandstone.
The imageshowsthree generations
of fracture fillings, all crosscutting
weakly foliated host rock. The
quartz plus calcite vein shows
folding. A very thin vein of calcite
traverses the thin section. There
is an alteration halo on either side
of the vein when viewed at higher
magnification.
Figure 3.11 Photomicrographs of the same region of a petrographic thin section in (a) plane, (b) cross-polarized,
and (c) reflected light. The images illustrate mineralogy, texture, "bedding parallel" fracture, discontinuous "early"
quartz lens, and the presence of sulfides within the matrix and along boundaries of the vein and host rock. The
dominant fine-grained calcareous metasandstone and biotite phyllite and a deformed quartz vein with pyrite within and
at the terminus of the quartz lens is best seen in (c). Boundaries between the metasedimentary layers and between
lens and phyllite are sharp. The bar scale is applicable for (a), (b) and (c).
39
-------
Metasandstone was the dominant lithology (80-90%) of the host assemblage. It is composed of fine grained (< 0.5 mm)
quartz, feldspar, white mica, chlorite, and/or biotite depending on its metamorphic grade. Interstitial carbonate varied
from a few percent to as much as 30% exclusive of vein or fracture fillings. Pyrite (best seen in reflected light) and
apatite occurred as accessory minerals. Iron hydroxides typical of limonite (Fe2O3 • nhkO) and probable clays dominated
as alteration minerals. Much of the quartz and feldspar (mostly albite) grains were recrystallized, but the larger sized
polycrystalline quartz grains may have reflected original sedimentary grains. Phyllosilicates showed preferred orientation
as a function of recrystallization and reorientation. For the metasandstones, the preferred orientation remained parallel
to the original layering.
Field observations revealed that the thin metashale layers (10-20%) were intercalated with dominant metasandstone.
Some layers were as thick as a few 10's cm, but many were only 2 - 10 cm thick. They contained the same mineral
assemblage, but with less quartz and feldspar and more phyllosilicate. Preferred orientation was strong throughout. The
phyllosilicates showed a second preferred orientation that cross cut an earlier "bed" parallel foliation.
Porphryitic diabase dikes were encountered in all BBC boreholes. Thin sections across contacts with the Kittery Formation
showed a typical chill margin containing microphenocrysts of plagioclase and microxenoliths from the host rock (Figure
3.12). No attempts to assess intrusive direction, based on preferred orientation of microphenocrysts, were made in this
study. After olivine, phenocrysts of zoned plagioclase, clinopyroxene, and chlorite pseudomorphous were set in fine
grained diabasic texture in the more central parts of the dikes here and throughout the Great Bay area. The dikes were
generally massive, with fewer fractures and veins than the Kittery host rock. Figure 3.12 illustrates the contact relations
between dike and Kittery host and cross-cutting mineralized vein and amygdular fillings.
Figure 3.12 Diabase dike textures and
microfracture fillings, (a) Photomicrograph of contact
between Kittery (top) and chill margin of porphryitic
diabase. Note that the microfractures are roughly
parallel to contact, rip-ups (microxenoliths), and
weakly aligned phenocrysts of plagioclase and
pyroxene. Sub-horizontal fractures are filled with
chlorite. The micrograph was produced with plane
polarized light, (b) Photomicrograph from the center
of diabase dike. The felty matrix is a coarse-grained
plagioclase and pyroxene, magnetite and sulfide, and
chlorite. Note the large (3 mm) amygdule filled with
calcite (top) and a 0.2 mm partially sealed fracture
composed of calcite, chlorite, and opaques. The
micrograph was produced with plane polarized light.
40
-------
Several generations of veins and fracture fillings were recognized in the metasandstone and metashale of the Kittery
Formation (Figure 3.10). Early carbonate and quartz veins were separated from later veins by cross-cutting relationships
and the degree of deformation (microfolding, gradational boundaries with host versus sharp discordant boundaries and
planar character, Figure 3.10). Strongly strained quartz grains (identified by undulatory extinction and strong preferred
orientation, Figures 3.11 and 3.12) and calcite (bent twins and curved cleavage traces) were common in earlier veins
and fractures. Apparently, younger veins and fracture fillings were characterized by an absence of preferred orientation,
open and/or discontinuous precipitation of calcite, quartz, and minor zeolite (Figure 3.13).
Figure 3.13 Photomicrographs of microfracture textures and morphology. The images were taken with cross
polarized light, (a) A general view of the host rock displaying a strong foliation and micro-fault with larger re-crysta-
llized grains of quartz and carbonate (right). The main foliation is parallel to the lateral edges of the photomicrograph
and defined by shape-preferred orientation of quartz. The trace of the traverse for the analysis crosscuts the struc-
tures as shown, (b) Ductile deformation of quartz vein in metashale crosscut by microfaults. Calcite often shows
the same degree of ductile deformation by bent cleavage and twins, (c) Multiple parallel fractures alternated with
filled calcite (left) and quartz (right middle) veins. The foliation in the host rock is approximately parallel to the veins.
The veins lack significant deformation, (d) Thick, un-deformed quartz plus calcite vein approximately parallel to the
foliation in metasandstone host rock. There is no apparent reaction between the host rock and vein material. The
irregular right edge is hammer induced fracturing.
41
-------
Table 3.3 reports the specific mineralogy of the host rock associated with the 11 microfractures as determined by
petrographic analysis of thin sections cross cutting the microfracture surface minerals and underlying host rock. The host
rock contained the following minerals and relative abundances (based on modal analysis) generally distributed among all
11 samples: quartz (SiO2, 10-40%); feldspar (mostly albite NaAISi3O8 with minor KAISi3O8 0-25%); carbonates (CaCO3,
CaMg(CO3)2, FeMgCO3, 0-32%); biotite (K2(Mg,Fe)6AI2Si6O2o(OH,F)4, 0-45%) and/or chlorite ((Mg,AI,Fe)3(Si,AI)4O10(OH)2
•(Mg,AI,Fe)3(OH)6), 0-30%); white mica (KAI2(AISi3O10)(OH)2), 0-15%); and accessory apatite (Ca5(PO4)3OH), zircon
(ZrSiO4), and opaques dominated by pyrite (FeS2).
Table 3.3. Mineral Phases Identified by Petrography in Host Rock
Micro-
fracture
#
Apatite
(% area)
Biotite
(% area)
Carbonate
(% area)
Chlorite
(% area)
Feldspar
(% area)
Opaques
(% area)
Quartz
(% area)
White Mica
(% area)
Zircon
(% area)
MF01
Trace
15
10
20
40
Trace
MF02
15
20
10
10
35
Trace
MF03
Trace
25
15
40
15
Trace
MF04
Trace
20
15
1-2
45
15
MF05
Trace
20
15
1-2
45
15
MF06
Trace
20
25
1-2
35
20
MF07
45
15
25
1-2
13
MF08
10
40
10
<5
15
15
Trace
MF09
25
25
<5
45
MF10
Trace
10
35
10
<5
20
15
MF11
30
15
1-2
40
10
Mineral Formulas (Nesse, 2003):
Apatite - Ca5(PO4)3(F,CI,OH)
Biotite - K2(Mg,Fe)6AI2Si6020(OH,F)4
Carbonate - primarily CaCO3, others include CaMg(CO3)2, FeMg(CO3).
Chlorite - (Mg,AI,Fe)3(Si,AI)4O10(OH)2*(Mg,AI,Fe)3(OH)6
Feldspar- (Na,Ca)(AI,Si)2Si2O8; may include minor KAISi3O8
Opaques- FeSx
Quartz - SiO2
White Mica - KAI2(AISi3O10)(OH)2
Zircon - ZrSiO4
Trace = trace amount; accessory mineral
Identification of the minerals in the microfracture surface precipitates was limited to three of the 11 samples. The
optical mineral determination used a point counting method to estimate mineral composition and for the majority of
microfracture samples, the mineral surface coating was not sufficiently abundant to make such estimates. Figure 3.14
shows photomicrographs of these three samples at the intersection of the mineral coating on the microfracture face
and the host rock. The mineral identification results of the three characterized microfracture faces are found in Table
3.4. The microfracture surface precipitates contained the following minerals and relative abundances (based on modal
analysis) generally distributed among all three microfractures: carbonates (CaCOs, CaMg(CO3)2, FeMgCO3, 5-50%),
chlorites ((Mg,AI,Fe)3(Si,AI)4Oio(OH)2» (Mg,AI,Fe)3(OH)6), 0-15%), and quartz (SiO2, 35-95%). No pyrites were found
in the surface precipitates.
42
-------
Figure 3.14 Petrographic micrographs of
host rock and microfracture surfaces. The
images were taken with cross polarized light.
(a) Microfracture MF02 - a general view of the
host rock in contact with the calcite-quartz
microfracture surface, (b) Microfracture MF06 -
a view showing the crosscutting relation between
the microfracture with crystalline carbonate and
quartz and the foliation in the host rock. The
foliation makes an angle of about 35 degrees
with the top margin of the photo.
(c) Microfracture MF11 - the emplacement of the
thick quartz-calcite microfracture is interpreted
as the latest petrogenic event as there is no sign
of deformation as it crosscuts the host rock.
0.25 mm
43
-------
Table 3.4. Mineral Phases Identified by Petrography in Microfracture Surface Precipitates
Micro-
fracture #
MF02
MF06
MF11
Carbonate
(% area)
50
35
5
Chlorite
(% area)
15
Quartz
(% area)
35
65
95
Opaque
(% area)
Trace
Mineral Formulas (Nesse, 2003):
Carbonate - primarily CaCO3, others include CaMg(CO3)2, FeMg(CO3)2
Chlorite - (Mg,AI,Fe)3(Si,AI)4O10(OH)2*(Mg,AI,Fe)3(OH)6
Quartz - SiO2
Opaque - FeSx
Trace = trace amount; accessory mineral
EDS investigation of the microfracture face and host rock in the y-z plane, as found on the thin section slides, was
conducted on two samples, microfractures MF07 and MF09. Microfracture MF07 showed a distinct elemental difference
at the microfracture surface of higher Fe content and lower Si content than in the underlying host rock. In Figure 3.15,
this is seen as the more intense red at the center-right region of the Fe map and a less intense green area in the
coordinating location on the Si map. The fracture face was composed of Al, Mg, and O accompanying the Fe and Si
concentrations. The underlying host rock was composed of Si-AI-K-Mg-Fe-O phases, as well as interspersed Ca-O
and Ti phases. The fracture surface of microfracture MF09 was composed of a Ca-Mg-Fe-O phase, distinct from the
immediate underlying Si-AI-K-O phases.
X Image Display 1 selected for processing
File rj Edit TJ View r) Setup r )
Image ~| 12 1G *"*- SI2"*08 inage.
Open
I '
Host Rock
Precipitate *
I
SEM
x1,070
Figure 3.15 Element spatial map of microfracture MF07 thin section showing host rock and microfracture face in
cross section. Each window is about 300 by 200 um.
44
-------
3.7 Mineralogy of Microfracture Surfaces and Host Rock Based on XRD
XRD was used to identify crystalline minerals in the BBC host rock and microfracture surface precipitate materials.
Mineral identification was limited to those identified from matches with the ICDD database. Due to the complex nature
of the diffractogram and the search/match process, it was not unusual to identify minerals that were not likely present
in the sample. Despite this, XRD was still a useful method of analysis, especially when used in conjunction with other
analytical methods.
Figures 3.16, 3.17, and 3.18 reflect the data processing method in several steps. Figure 3.16 is a typical raw XRD
diffractogram for a microfracture sample. Figure 3.17 is the same diffractogram after background correction and smoothing
to remove excessive noise. Figure 3.18 shows typical identification of minerals as determined by the search match program.
Figure 3.19 shows a diffractogram of host rock material from microfracture MF07. Figure 3.20 shows a diffractogram of
the microfracture surface precipitate of microfracture MF07. A high degree of crystallinity, as evidenced by the number
of peaks observed, is apparent in both samples. Some common major peaks are present, but the diffractograms show
significant differences in mineral composition.
1600
1400
1200
1000
•r soo
f
I 600
400
200
10 20
30 40 50 60
2-theta (Degrees)
70
80
90
Figure 3.16 Typical raw diffractogram.
900
800
700
600
2"
I 500
" 400
300
200
100
0
10
20
30
40 50 60
2-theta (Degrees)
Figure 3.17 Typical diffractogram after background removal and smoothing.
70
80
90
45
-------
3500-
3000-
2500-
1500-
1000
500-
[B5F9H01 .MDIl <2T(0>-0.385>
lllite-2M1 -(K.H30>ai2Si3^01D(OH)2
10
20
30
40 50
2-ThetaO
—I—\—I—I—I—I—I—I—I—I—I—
60 70 80
•100
•90
•80
•70
•60
•50
•40
•30
20
•10
0
Saturday. Dec 20. 2003 07:47a (MDI/JADE5)
Figure 3.18 Typical peak ID as determined by search match routine. The right hand Y axis is relative intensity (%
6000
5000
4000
3000
2000
1000
10 20 30 40 50 60 70 80 90
2-theta (Degrees)
Figure 3.19 Diffractogram of host rock from microfracture MF07.
46
-------
1600
1400
1200
•g 1000
~ soo
'«
c
1 600
400
200
0 10 20 30 40 50 60 70 80
2-theta (Degrees)
Figure 3.20 Diffractogram of microfracture surface precipitate from microfracture MF07.
90
Table 3.5 lists all reasonable candidate minerals identified in the host rock material. Dominant major candidate minerals
included quartz (SiO2), clinochlore (a chlorite), and albite ((Na,Ca)AI(Si,AI)3O8).
Table 3.5. Summary of Crystalline Minerals Identified in Host Rock Samples
Mineral Name (Formula)
Quartz (SiO2)
Clinochlore ((Mg,Fe2*,Fe3+,Mn,AI,)12[(Si,AI)8O20] (OH)16)
Albite ((Na,Ca)AI(Si,AI)308)
Potassium Mica (KAIjSip,,)
Illite ((K,H30)AI2Si3AI010(OH)2)
Potassium Manganese Oxide Hydrate (K05Mn2O4)
K(Mg,AI)204(Si334AI066)010(OH)2
(Mg, Fe2-, Fe3*,Mn,AI)12[(Si,AI)8O20] (OH)16
Zeolite (Na20-Si02-AI203)
Lizardite Aluminian ((Mg,Fe2i,Fe3+,Mn,AI)l2[(Si,AI)8O20](OH)16)
Chamosite ((Fe,AI,Mg)6(Si,AI)4O10(OH)8)
Anorthoclase ((Na,K)(Si3AI)O8)
Anorthite (Na[AISi3O8]-Ca[AI2Si2O8])
Sanidine(K2(Mg,Fe2+)6-4(Fe^AI,Ti)0-2[Si6-5AI2-3020](OH,F)4)
Baratovite (Li2KCaJi2Si12O3_F)
Iron Silicate Hydroxide (Fe3Si2O5(OH)4)
Muscovite ((K,Na)(AI,Mg,Fe)2(Si31AI09)010(OH)2)
Microfracture #,
Mineral Phase Relative Abundance (Search-Match FOM)
MF01
3.0
10.8
12.6
MF02
2.2
3.4
13.2
MF04
0.6
MF06
0.6
13.4
MF07
3.0
10.7
4.6
2.6
2.9
7.4
12.4
14.7
15.0
16.0
19.2
MF08
2.6
MF09
0.7
10.8
5.4
19.1
17.4
16.3
18.2
MF10
1.3
8.6
3.6
2.1
12.5
10.9
5.6
14.0
15.1
MF11
3.0
9.0
9.1
47
-------
Table 3.6 lists all reasonable minerals identified in the surface precipitates for each microfracture sample. Surface
precipitates from microfractures MF03 and MF05 were not analyzed by XRD because an insufficient amount of surface
precipitate material was recovered from the sample to allow for this analysis. The tables show that the surface precipitates
were generally different from the host rock in mineral composition, generally containing carbonates (CaCO CaMg(CCO
FeMgCO3), chlorite ((Mg,AI,Fe)3(Si,AI)4O10(OH)2 • (Mg,AI,Fe)3(OH)6), and quartz (SiO2).
Table 3.6. Microfracture Surface Precipitate Candidate Minerals Based on XRD
Mineral Name (Formula)
Calcite
CaCO3
Magnesian Calcite
(Ca,Mg)C03
Dolomite
CaMg(C03)2
Kutnohorite
Ca(Mn,Mg)(C03)2
Ankerite
Ca(Fe,Mg)(C03)2
Quartz
SiO2
Sanidine
K(AISi3)08
Clinochlore
Mg3Mn2AISi3AI010(OH)8
Microcline
KAISi3O8
Albite
NaAISi3O8
Calcian Albite
(Na,Ca)AI(Si,AI)3O8
Anorthite
(Ca,Na)(Si,AI)A,
Sodium Aluminum Silicate
NaAISiO4
Potassium Aluminum Silicate
K1+xxAl1+xSi1,04
Potassium Mica
KA^Si-A,
Illite
(K,H3O)AI2Si3AIO10(OH)2
Badeleyite
ZrO2
Aluminum Iron Zirconium
Ali.65"~e035Zr
Wustite
FeO
Microfracture Number,
Mineral Phase Relative Abundance (Search-Match FOM)
MF01
Major
(18.2)
Major
(20.4)
MF02
Major
(1.3)
Major
(14.3)
MF04
Major
(1.4)
Major
(7.2)
Minor
(14.3)
Minor
(16.4)
MF06
Major
(8.7)
Major
(8.8)
Major
(16.9)
Major
(1.0)
Major
(18.6)
MF07
Major
(3.6)
Major
(4.7)
Major
(9.1)
Major
(17.0)
Major
(17.9)
Major
(10.8)
Minor
(19.0)
MF08
Major
(6.2)
MF09
Major
(6.0)
Major
(2.8)
Major
(4.7)
Major
(6.3)
Major
(17.1)
Minor
(19.9)
MF10
Major
(3.1)
Major
(7.4)
Major
(8.8)
Major
(3.2)
Major
(1.9)
MF11
Major
(5.7)
The colors of the microfracture faces varied between samples and were noted as white, blue, green, or black. Microfractures
MF01, 02, 06, 07, 08, 09, 10, and MF11 were recorded as white, blue, or green. Microfracture MF04 was black in color.
Calcite, dolomite, and other carbonate minerals were dominant in the white surface precipitates and present in the blue
and green precipitate, but not identified in the black. The black surface precipitate may have been the host rock.
48
-------
3.8 Element Speciation of Microfracture Surfaces Based on XPS
XPS was used to identify speciation of surface-associated elements. XPS offers one principal advantage as a surface
spectroscopy— it can provide speciation information for the surface in contact with the microf racture porewater. Mineral
identification is limited by the NIST database which can result in the identification of irrelevant candidate minerals because
initial searching is based on the binding energy of the fitted peak and the element and photoelectron in question. Because
of the high surface sensitivity of the method (e.g., information from the top few nm), many of the minerals identified may
reflect recent precipitation from porewater rather than the mineral phases in the bulk of the surface precipitate.
Figure 3.21 shows a typical low resolution survey scan and indicates which elements were identified in this scan of
microf racture MF02. Figure 3.22 shows the curve fitting of the C1s photoelectron data from microf racture MF02. The
example minerals identified by the NIST database are indicated for the fitted peaks.
2500
2000
1500
01s
CO
Q.
O
C1s
Ca2p I
AI2p
:
\ O2s
1000
Ca2s
Si2p \
Si2s \
\ I
\ T \ \ \ \
^^^^^^
1200
1000
800 600 400
Binding Energy (eV)
200
Figure 3.21 Typical XPS low resolution survey scan of microfracture MF02.
40-
T3
8
0)
_
o>
Q.
1
£
o
30-
20
10-
Raw
Spectra
C1s Ether/
Alcohol
Summary
Curve
C1s
Adventitious
Carbon
C1s Amide
C1s
Carbonate
294 292 290 288 286
Binding Energy (eV)
284
282
280
Figure 3.22 Typical component curve fit exercise for the C1 s photoelectron from a high resolution scan for
microfracture MF02.
49
-------
Tables 3.7 - 3.15 show the final lists of candidate minerals for each of the microfractures as identified by XPS.
Microfractures MF01 and MF11 were not analyzed due to spatial limitations of the sample holder in the vacuum chamber.
A high degree of internal consistency was seen in the peak assignments. Most microfracture precipitate surfaces
contained simple carbonates (calcite or dolomite), oxyhydroxides of Fe and Al, and silicates.
Table 3.7. Microfracture MF02 - Candidate Minerals by XPS
Element
AI2p
C1s
Ca2p
Fe2p
Binding
Energy (eV)
74.15
284.80
286.53
287.76
289.38
346.83
347.54
348.38
708.77
709.84
71 1 .22
714.14
Peak
Area %
100.0
71.7
4.8
7.6
15.9
46.1
15.3
5.3
22.7
22.5
35.9
18.8
Candidates (Range +/- 0.3 eV)
Mol Sieve, Ca form (73.9-74.75)
AI2O3 (71 .47-77.3)
Al0,Si0,0,2(74.4)
Adventitious Carbon (284.8)
NOM Ether or Alcohol
(286.4-286.6)
NOM Ketone or Aldehyde
(287.5-287.7)
CaCO3 (288.2-290.4)
CaMg(CO3)2 (289.8)
NOM Carboxylic (289.1-289.3)
CaCO3 (346.6-347.7)
CaO (346. 1-347.3)
CaSiO3 (346.7-347.3)
CaCO3 (346.6-347.7)
CaMg(CO3)2(347.3)
CaO (346. 1-347.3)
CaSiO3 (346.7-347.3)
Mol Sieve, Ca form
(347.9-348.6)
Fe3O4 (708.1 -71 1.4)
FeS2 (706.6-708.6)
Fe3O4 (708. 1-71 1.4)
FeO (709.2-71 0.7)
Fe2O3 (709.9-71 1 .6)
Fe3O4 (708. 1-71 1.4)
Fe2O3 (709.9-71 1 .6)
FeS (71 0.3-71 3.6)
Fe(OH)O (71 0.8-71 1.8)
Fe2O3*nH2O aged HFO
(710.7-711.1)
FeO(OH)*nH2O (711. 1-711.3)
Fe2O3*nH2O fresh HFO
(711.3-711.9)
Unidentified
Element
O1 s
Si2p
Binding
Energy (eV)
530.14
530.88
531.76
532.82
102.13
102.95
Peak
Area %
13.8
52.8
28.8
4.6
59.5
40.5
Candidates (Range +/- 0.3 eV)
FeO (529.8-530.1)
Fe2O3 (529.5-530.3)
Fe3O4 (529. 1-530.1)
CaO (529.4-531 .3)
AI2O3 (530.0-532.7)
CaO (529.4-531 .3)
CaCO3 (530.5-531.5)
AI2O3 (530.0-532.7)
Mol Sieve, Ca form
(531.05-532)
CaCO3 (530.5-531.5)
CaMg(CO3)2 (531 .7)
CaSiO3(531.5-531.6)
AI2O3 (530.0-532.7)
Fe2(S04)3 (531 .6-532.2)
SiO2 (532-534.3)
AI2O3 (530.0-532.7)
SiO2 (532-534.3)
Mol Sieve, Caform (101.8-102.8)
CaSiO3(102.36)
Mol Sieve, Caform (101.8-102.8)
SiO2 (103.2-104.1)
Alo.2sio.8°2.2(103-2)
50
-------
Table 3.8. Microfracture MF03 - Candidate Minerals by XPS
Element
AI2p
C1s
Fe2p
Binding
Energy (eV)
74.54
75.20
75.92
284.80
286.39
288.06
289.82
709.32
710.93
712.22
713.93
716.25
Peak
Area %
60.6
20.3
19.1
52.6
27.7
7.5
12.2
20.3
30.1
20.3
20.1
9.1
Candidates (Range +/- 0.3 eV)
AI2O3 (71.47-77.3)
Mol Sieve, Ca form (73.9-74.75)
AI2OSiO4 (74.58-74.8)
Al0,Si0,0,2(74.4)
AI2O3 (71.47-77.3)
AI2O3 (71.47-77.3)
Adventitious Carbon (284.8)
NOM Ether or Alcohol
(286.4-286.6)
NOM Amide (288.4-288.5)
CaCO3 (288.2-290.4)
CaMg(CO3)2 (289.8)
NOM Carboxylic (289.1-289.3)
Fe3O4 (708.1 -71 1.4)
FeO (709.2-71 0.7)
Fe3O4 (708. 1-71 1.4)
FeO (709.2-71 0.7)
Fe2O3 (709.9-71 1 .6)
FeS (71 0.3-71 3.6)
Fe(OH)O (71 0.8-71 1.8)
Fe2O/nH2O aged HFO
(710.7-711.1)
FeO(OH)*nH2O (71 1.1-711 .3)
FeS (71 0.3-71 3.6)
Unidentified
Unidentified
Element
O1 s
Si2p
Binding
Energy (eV)
531.36
533.08
102.34
103.32
104.32
Peak
Area %
84.6
15.4
12.3
32.7
55.0
Candidates (Range +/- 0.3 eV)
CaCO3 (530.5-531.5)
CaO (529.4-531. 3)
CaSiO3(531.5-531.6)
AI2O3 (530.0-532.7)
AI2OSiO4 (531. 3-531 .88)
Mol Sieve, Ca form (531.05-532)
Fe(OH)O(530.1-531.8)
SiO2 (532-534.3)
CaSiO3(102.36)
Mol Sieve, Ca form
(101.8-102.8)
AI2OSiO4 (102.6-1 03)
AI2OSiO4 (102.6-1 03)
Alo.2sioA.2(103-2)
SiO2 (103.2-104.1)
SiO2 (103.2-104.1)
51
-------
Table 3.9. Microfracture MF04 - Candidate Minerals by XPS
Element
AI2p
C1s
Ca2p
Fe2p
Binding
Energy (eV)
74.82
75.69
284.80
285.46
286.26
287.78
289.49
346.62
347.56
348.64
710.50
713.26
716.42
Peak
Area %
60.9
39.1
50.3
31.1
12.7
4.3
1.6
10.3
52.4
37.4
49.0
30.1
20.9
Candidates (Range +/- 0.3 eV)
AI2O3 (71.47-77.3)
Mol Sieve, Ca form (73.9-74.75)
AI2OSiO4 (74.58-74.8)
AI2(S04)3 (74.9)
AI203 (71.47-77.3)
Adventitious Carbon (284.8)
NOM Carboxylic Neighbor
(285.4-285.6)
NOM Ether or Alcohol
(286.4-286.6)
NOM Ketone or Aldehyde
(287.5-287.7)
CaCO3 (288.2-290.4)
NOM Carboxylic (289.1-289.3)
CaCO3 (346.6-347.7)
CaO (346. 1-347.3)
CaMg(CO3)2(347.3)
CaCO3 (346.6-347.7)
CaSO4 (347.6-348.4)
Mol Sieve, Ca form
(347.9-348.6)
CaSO4 (347.6-348.4)
Fe2O3 (709.9-71 1 .6)
Fe3O4 (708.1 -71 1.4)
FeO (709.2-71 0.7)
FeS2 (706.6-708.6)
FeS (71 0.3-71 3.6)
FeS (71 0.3-71 3.6)
Unidentified
Element
O1 s
Si2p
Binding
Energy (eV)
530.43
532.49
533.49
101.98
102.84
103.70
Peak
Area %
6.2
50.8
18.1
12.4
37.4
50.2
Candidates (Range +/- 0.3 eV)
FeO (529.8-530.1)
Fe3O4 (529. 1-530.1)
Fe2O3 (529.5-530.3)
CaO (529.4-531. 3)
CaCO3 (530.5-531.5)
AI2O3 (530.0-532.7)
CaO (529.4-531. 3)
CaCO3 (530.5-531.5)
CaMg(C03)2 (531 .7)
AI2O3 (530.0-532.7)
AI2OSiO4 (531. 3-531 .88)
Mol Sieve, Ca form (531.05-532)
AI2O3 (530.0-532.7)
SiO2 (532-534.3)
SiO (532.5)
CaSO4 (532-532.9)
AI2(S04)3 (532.4)
SiO2 (532-534.3)
SiO (101.7-102.7)
Mol Sieve, Ca form
(101.8-102.8)
SiO (101.7-102.7)
Mol Sieve, Ca form
(101.8-102.8)
AI2OSiO4 (102.6-1 03)
SiO2 (103.2-104.1)
52
-------
Table 3.10. Microfracture MF05 - Candidate Minerals by XPS
Element
AI2p
C1s
Ca2p
Fe2p
Binding
Energy (eV)
74.45
284.80
286.39
289.45
347.57
348.47
709.32
710.88
712.41
Peak
Area %
100.0
82.1
12.9
5.1
69.8
30.2
7.8
87.4
4.8
Candidates (Range +/- 0.3 eV)
AI2O3 (71.47-77.3)
Mol Sieve, Ca form (73.9-74.75)
AI2OSiO4 (74.58-74.8)
AI0.2SiO.S°2.2 <74'4)
Adventitious Carbon (284.8)
NOM Ether or Alcohol
(286.4-286.6)
CaCO3 (288.2-290.4)
FeCO3 siderite (289.6)
NOM Carboxylic (289.1-289.3)
CaCO3 (346.6-347.7)
CaMg(C03)2 (347.3)
CaO (346. 1-347.3)
CaSiO3 (346.7-347.3)
Mol Sieve, Ca form
(347.9-348.6)
Fe3O4 (708. 1-71 1.4)
FeO (709.2-71 0.7)
FeCO3 siderite (710.4-710.7)
Fe2O3 (709.9-71 1 .6)
Fe3O4 (708. 1-71 1.4)
FeO (709.2-71 0.7)
Fe(OH)O (71 0.8-71 1.8)
FeSO4 (71 1.2-71 3.6)
Element
O1 s
S2p
Si2p
Binding
Energy (eV)
529.66
531.44
532.31
533.80
168.72
169.41
102.06
103.11
103.52
103.94
Peak
Area %
4.6
69.5
22.1
3.7
33.2
66.8
7.8
54.1
16.3
21.8
Candidates (Range +/- 0.3 eV)
FeO (529.8-530.1)
Fe3O4 (529. 1-530.1)
Fe2O3 (529.5-530.3)
FeOOH (529.7-531 .7)
CaO (529.4-531. 3)
FeOOH (529.7-531 .8)
CaO (529.4-531. 3)
CaCO3 (530.5-531.5)
CaMg(CO3)2 (531 .7)
CaSiO3 (531.5-531.6)
AI2O3 (530.0-532.7)
AI2OSiO4 (531. 3-531 .88)
Mol Sieve, Ca form (531.05-532)
FeCO3 siderite (532.1)
FeSO4 (532.3)
AI2O3 (530.0-532.7)
Mol Sieve, Ca form (531.05-532)
SiO2 (532-534.3)
SiO (532.5)
CaSO4 (532-532.9)
AI2(S04)3 (532.4)
SiO2 (532-534.3)
FeSO4 (168.7-1 68.8)
Fe2(S04)3 (168.6-169.1)
FeS2 (161 .7-1 62.9)
CaSO4 (169-170.1)
Fe2(S04)3 (168.6-169.1)
AI2(S04)3 (169.5)
CaSO4 (169-170.1)
SiO (101.7-102.7)
Mol Sieve, Ca form
(101.8-102.8)
CaSiO.(102.36)
AI2OSiO4 (102.6-1 03)
AI2OSiO4 (102.6-1 03)
Al0,Si0,02, (103.2)
SiO2 (103.2-104.1)
SiO2 (103.2-104.1)
SiO2 (103.2-104.1)
53
-------
Table 3.11. Microfracture MF06 - Candidate Minerals by XPS
Element
AI2p
C1s
Ca2p
Fe2p
Mg2p
Binding
Energy (eV)
74.75
75.65
284.80
285.66
286.92
288.24
289.45
347.32
348.13
349.09
710.88
714.67
50.51
Peak
Area %
64.6
35.4
57.6
22.4
10.4
4.2
5.3
26.7
52.9
20.4
69.8
30.2
100.0
Candidates (Range +/- 0.3 eV)
AI203 (71.47-77.3)
Mol Sieve, Ca form (73.9-74.75)
AI2OSiO4 (74.58-74.8)
Al0,Si0,0,2(74.4)
AI2(S04)3 (74.9)
AI2O3 (71.47-77.3)
Adventitious Carbon (284.8)
NOM Carboxylic Neighbor
(285.4-285.6)
NOM Ether or Alcohol
(286.4-286.6)
NOM Amide (288.4-288.5)
CaCO3 (288.2-290.4)
CaMg(CO3)2 (289.8)
CaCO3 (346.6-347.7)
CaMg(CO3)2(347.3)
CaO (346. 1-347.3)
CaSO4 (347.6-348.4)
Mol Sieve, Ca form
(347.9-348.6)
CaSO4 (347.6-348.4)
Unidentified
Fe(OH)O(711-711.8)
FeS (71 0.3-71 3.6)
Unidentified
CaMg(C03)2 (50.5)
Element
O1 s
Si2p
Binding
Energy (eV)
531.14
532.10
533.05
534.38
101.80
102.87
103.63
104.69
Peak
Area %
21.1
54.6
20.6
3.7
6.8
44.0
41.7
7.5
Candidates (Range +/- 0.3 eV)
Fe(OH)O(530.1-531.8)
CaCO3 (530.5-531.5)
CaO (529.4-531. 3)
Mol Sieve, Ca form (531.05-532)
AI2O3 (530.0-532.7)
AI2OSiO4 (531. 3-531 .88)
AI2(S04)3 (532.4)
AI2O3 (530.0-532.7)
AI2OSiO4 (531. 3-531 .88)
CaSO4 (532-532.9)
Fe(OH)O(530.1-531.8)
Mol Sieve, Ca form (531.05-532)
SiO2 (532-534.3)
Al0,Si0,022 (532.9)
CaSO4 (532-532.9)
SiO2 (532-534.3)
SiO2 (532-534.3)
Mol Sieve, Ca form
(101.8-102.8)
Mol Sieve, Ca form
(101.8-102.8)
AI2OSiO4 (102.6-1 03)
SiO2 (103.2-104.1)
Unidentified
54
-------
Table 3.12. Microfracture MF07 - Candidate Minerals by XPS
Element
AI2p
C1s
Ca2p
Fe2p
Mg2p
Binding
Energy (eV)
74.07
74.93
284.80
285.92
286.88
288.67
290.28
347.29
347.88
348.55
709.6
711.37
713.15
715.41
50.79
Peak
Area %
50.0
50.0
83.0
5.8
6.2
2.3
2.8
24.1
57.3
18.5
27.2
38.2
25.5
9.1
100.0
Candidates (Range +/- 0.3 eV)
Al,03 (71.47-77.3)
Mol Sieve, Ca form (73.9-74.75)
AI2O3 (71.47-77.3)
AI2(S04)3 (74.9)
Mol Sieve, Ca form (73.9-74.75)
AI2OSiO4 (74.58-74.8)
Adventitious Carbon (284.8)
NOM Carboxylic Neighbor
(285.4-285.6)
NOM Ether or Alcohol
(286.4-286.6)
CaCO3 (288.2-290.4)
NOM Amide (288.4-288.5)
CaCO3 (288.2-290.4)
CaCO3 (346.6-347.7)
CaMg(CO3)2(347.3)
CaO (346. 1-347.3)
CaCO3 (346.6-347.7)
Mol Sieve, Ca form
(347.9-348.6)
Mol Sieve, Ca form
(347.9-348.6)
Fe3O4 (708. 1-71 1.4)
FeO (709.2-71 0.7)
Fe2O3 (709.9-71 1 .6)
Fe3O4 (708.1 -71 1.4)
Fe2O3 (709.9-71 1 .6)
FeS (71 0.3-71 3.6)
FeO (709.2-71 0.7)
Fe(OH)O (71 0.8-71 1.8)
Fe2O3*nH2O aged HFO
(710.7-711.1)
FeO(OH)*nH2O (711. 1-711.3)
Fe2O3*nH2O fresh HFO
(711.3-711.9)
FeS (71 0.3-71 3.6)
Fe2(S04)3 (713.3)
Unidentified
CaMg(C03)2 (50.5)
Element
O1 s
S2p
Si2p
Binding
Energy (eV)
530.39
531.64
532.58
534.07
169.01
170.03
103.08
Peak
Area %
6.0
54.8
35.0
4.3
49.6
50.4
100.0
Candidates (Range +/- 0.3 eV)
Fe2O3 (529.5-530.3)
Fe3O4 (529. 1-530.1)
Fe(OH)O(530.1-531.8)
CaO (529.4-531. 3)
CaCO3 (530.5-531.5)
Mol Sieve, Ca form (531.05-532)
AI2O3 (530.0-532.7)
CaCO3 (530.5-531.5)
CaMg(CO,)2 (531 .7)
Fe(OH)O(530.1-531.8)
AI2O3 (530.0-532.7)
AI,OSiO4 (531. 3-531 .88)
SiO2 (532-534.3)
AI2OSiO4 (531. 3-531 .88)
SiO2 (532-534.3)
FeSO4 (168.7-168.8)
Fe2(SO4)3 (168.6-169.1)
CaSO4 (169-170.1)
CaSO4 (169-170.1)
SiO2 (103.2-104.1)
Al0,Si0,02, (103-2)
AI2OSiO4 (102.6-1 03)
Mol Sieve, Ca form
(101.8-102.8)
55
-------
Table 3.13. Microfracture MF08 - Candidate Minerals by XPS
Element
AI2p
C1s
Ca2p
Fe2p
Mg2p
Binding
Energy (eV)
74.23
74.93
75.22
284.8
285.83
287.8
288.93
290.38
347.30
347.67
348.24
710.24
712.15
713.92
715.79
50.73
Peak
Area %
9.9
25.6
64.4
62.8
27.3
2.5
2.5
4.9
16.6
25.5
57.9
25.52
36.98
24.06
13.44
100.0
Candidates (Range +/- 0.3 eV)
Al,03 (71.47-77.3)
Mol Sieve, Ca form (73.9-74.75)
Al0,Si0,0,2(74.4)
AI2O3 (71.47-77.3)
AI2(S04)3 (74.9)
AI2OSiO4 (74.58-74.8)
AI2(S04)3 (74.9)
Adventitious Carbon (284.8)
NOM Carboxylic Neighbor
(285.4-285.6)
NOM Ketone or Aldehyde
(287.5-287.7)
CaCO3 (288.2-290.4)
NOM Carboxylic (289.1-289.3)
CaCO3 (288.2-290.4)
CaMg(CO3)2(347.3)
CaCO3 (346.6-347.7)
CaO (346. 1-347.3)
Ca(OH)2 (347.7)
CaCO3 (346.6-347.7)
Mol Sieve, Ca form
(347.9-348.6)
Mol Sieve, Ca form
(347.9-348.6)
CaSO4 (348)
Fe3O4 (708. 1-71 1.4)
FeO (709.2-71 0.7)
Fe2O3 (709.9-71 1 .6)
FeS (71 0.3-71 3.6)
FeS (71 0.3-71 3.6)
Fe2O3*nH2O fresh HFO
(711.3-711.9)
Unidentified
Unidentified
CaMg(C03), (50.5)
Element
O1 s
Si2p
Binding
Energy (eV)
530.59
531.98
532.38
532.98
103.12
103.45
104.06
Peak
Area %
1.4
12.0
55.6
31.0
61.0
14.4
25.5
Candidates (Range +/- 0.3 eV)
Fe(OH)O(530.1-531.8)
CaO (529.4-531. 3)
CaCO3 (530.5-531.5)
CaMg(CO3)2 (531 .7)
AI2O3 (530.0-532.7)
Fe(OH)O(530.1-531.8)
CaMg(CO3)2 (531 .7)
AI2O3 (530.0-532.7)
AI,OSiO4 (531. 3-531 .88)
Mol Sieve, Ca form (531.05-532)
SiO2 (532-534.3)
CaSO4 (532-532.9)
SiO2 (532-534.3)
CaSO4 (532-532.9)
AI2(S04)3 (532.4)
AI02Si08022 (532.9)
AI2O3 (530.0-532.7)
Alo.2Sio.8°2.2 <532-9)
CaSO4 (532-532.9)
AI2O3 (530.0-532.7)
AI2OSiO4 (102.6-1 03)
Alo.2sio.8°2.2(103-2)
SiO2 (103.2-104.1)
Alo,2Sio.8°2.2(103-2)
SiO2 (103.2-104.1)
SiO2 (103.2-104.1)
56
-------
Table 3.14. Microfracture MF09 - Candidate Minerals by XPS
Element
AI2p
C1s
Ca2p
Fe2p
Binding
Energy (eV)
74.72
284.8
286.14
287.04
288.53
290.33
347.35
347.63
348.72
709.44
711.51
714.14
Peak
Area %
100.0
59.6
3.1
1.6
1.5
34.2
58.2
34.3
7.5
40.4
33.0
26.6
Candidates (Range +/- 0.3 eV)
AI203 (71.47-77.3)
Mol Sieve, Ca form (73.9-74.75)
AI2OSiO4 (74.58-74.8)
AI2(S04)3 (74.9)
Al0,Si,802.2(74.4)
Adventitious Carbon (284.8)
NOM Ether or Alcohol
(286.4-286.6)
Unidentified
NOM Amide (288.4-288.5)
CaCO3 (288.2-290.4)
CaMg(C03)2 (347.3)
CaCO3 (346.6-347.7)
CaO (346. 1-347.3)
CaSO4 (347.6-348.4)
CaCO3 (346.6-347.7)
Ca(OH), (347.7)
Mol Sieve, Ca form
(347.9-348.6)
CaSO4 (347.6-348.4)
Mol Sieve, Ca form
(347.9-348.6)
Fe3O4 (708. 1-71 1.4)
FeO (709.2-71 0.7)
Fe3O4 (708. 1-71 1.4)
Fe2O3 (709.9-71 1 .6)
FeS (71 0.3-71 3.6)
Fe(OH)O (71 0.8-71 1.8)
FeO(OH)*nH2O(711.1-711.3)
Fe2O3*nH2O fresh HFO
(711.3-711.9)
Unidentified
Element
O1 s
Si2p
Binding
Energy (eV)
530.97
531.80
533.36
103.22
103.81
104.12
Peak
Area %
13.4
81.2
5.4
68.8
17.0
14.2
Candidates (Range +/- 0.3 eV)
Ca(OH)2 (531.2)
CaCO3 (530.5-531.5)
Fe(OH)O(530.1-531.8)
Mol Sieve, Ca form (531.05-532)
(Mg/Fe)SiO4 (531.2)
AI2O3 (530.0-532.7)
(Mg/Fe)SiO3 (531.7)
AI2O3 (530.0-532.7)
AI2OSiO4 (531. 3-531 .88)
CaCO3 (530.5-531 .5)
CaMg(C03)2 (531 .7)
CaSO4 (532-532.9)
Fe(OH)O(530.1-531.8)
Mol Sieve, Ca form (531.05-532)
SiO2 (532-534.3)
SiO2 (532-534.3)
AI2OSiO4 (102.6-1 03)
AI,2Si0,0,2 (103.2)
SiO2 (103.2-104.1)
SiO2 (103.2-104.1)
SiO2 (103.2-104.1)
57
-------
Table 3.15. Microfracture MF10 - Candidate Minerals by XPS
Element
AI2p
C1s
Ca2p
Fe2p
Mg2p
Binding
Energy (eV)
74.18
75.12
75.63
284.8
286.73
288.62
290.21
347.31
347.69
348.23
709.97
71 1 .62
712.85
714.55
50.81
Peak
Area %
11.7
70.4
17.8
69.9
10.4
2.3
17.4
20.3
48.0
31.7
25.8
33.1
21.4
19.7
100.0
Candidates (Range +/- 0.3 eV)
AI203 (71.47-77.3)
Mol Sieve, Ca form (73.9-74.75)
AI,2Si0,02,(74.4)
AI2O3 (71.47-77.3)
AI2(S04)3 (74.9)
AI2O3 (71.47-77.3)
Adventitious Carbon (284.8)
MOM Ether or Alcohol
(286.4-286.6)
NOM Amide (288.4-288.5)
CaCO3 (288.2-290.4)
CaCO3 (346.6-347.7)
CaMg(CO3)2(347.3)
CaO (346. 1-347.3)
CaSiO3 (346.7-347.3)
CaSO4 (347.6-348.4)
Ca(OH)2 (347.7)
CaCO3 (346.6-347.7)
Mol Sieve, Ca form
(347.9-348.6)
CaSO4 (347.6-348.4)
Mol Sieve, Ca form
(347.9-348.6)
CaSO4 (347.6-348.4)
Fe3O4 (708. 1-71 1.4)
FeO (709.2-71 0.7)
Fe2O3 (709.9-71 1 .6)
FeS (71 0.3-71 3.6)
Fe3O4 (708. 1-71 1.4)
Fe2O3 (709.9-71 1 .6)
FeS (71 0.3-71 3.6)
Fe(OH)O (71 0.8-71 1.8)
Fe2O3*nH2O fresh HFO
(711.3-711.9)
FeS (71 0.3-71 3.6)
Unidentified
CaMg(CO3)2(50.5)
Element
O2p
Si2p
Binding
Energy (eV)
530.04
531.67
532.71
103.16
103.87
Peak
Area %
6.5
82.7
10.8
67.4
32.6
Candidates (Range +/- 0.3 eV)
AI2O3 (530.0-532.7)
CaO (529.4-531.3)
Fe(OH)O(530.1-531.8)
Fe2O3 (529.5-530.3)
Fe3O4 (529. 1-530.1)
FeO (529.8-530.1)
CaCO3 (530.5-531 .5)
CaMg(CO.)2 (531 .7)
CaSiO3 (531.5-531.6)
Fe(OH)O(530.1-531.8)
AI2O3 (530.0-532.7)
AI2OSiO4 (531. 3-531 .88)
Mol Sieve, Ca form (531.05-532)
SiO2 (532-534.3)
CaSO4 (532-532.9)
AI2O3 (530.0-532.7)
AI2(S04)3 (532.4)
Al0,Si0,0,2 (532.9)
AI2OSiO4 (102.6-1 03)
Alo.2sio.8°2.2(103-2)
SiO2 (103.2-104.1)
SiO2 (103.2-104.1)
58
-------
Carbonates were the dominant minerals observed on the microfracture surfaces. Candidate minerals included siderite
(FeCO3), calcite (CaCO3), and dolomite ((CaMgCO3)2). Generally, calcite was more prevalent than dolomite and in almost
all cases, was identified with the Ca2p3/2, C1s and O1s photoelectrons.
Iron was also detected in high resolution scans of all the microfracture surfaces. A number of candidate minerals were
identified, including both ferrous (e.g., siderite, pyrrhotite (FeS), wustite ((FeO)), ferric minerals (e.g., goethite (a-FeOOH)),
hematite (Fe2O3), aged hydrous ferric oxide (Fe2O3 • 1.57 H2O, limonite ((Fe2O3 • nH2O)), and mixed ferrous and ferric
minerals (e.g., magnetite ((Fe3O4)). The presence of ferric minerals such as goethite indicated that iron reduction was
possible on the microfracture surface. The presence of Fe(ll) minerals such as siderite is perhaps evidence of Fe(lll)
reduction.
Sulfur was directly detected in some of the high resolution spectra for microfractures MF05 and MF07. Species
assignments were for sulfates (Fe2(SO4)3). It was also indirectly detected in Fe spectra. The assignment of FeS or FeS2
was tentative, largely based on the fact that pyrites were seen with petrography and SEM/EDAX.
In all cases, organic carbon was also observed on the microfracture surfaces. Some of this carbon was adventitious
(e.g., at 284.80 eV) and an artifact of analysis under high vacuum. Though the presence of TCE or its daughter products
on the surface was suspected using SIMS at extremely low detection limits (see Section 3.10), the detection limit of
XPS for the C1s photoelectron for sorbed TCE was likely not sufficiently low enough to detect the TCE. The bulk of the
carbon is at much higher binding energy values typical of NOM functional groups. NOM can form conditioning films on
inorganic surfaces in aquatic settings (Leis et ai, 2000). The sorption of NOM model compounds to mineral surfaces
has also been demonstrated (Evanko and Dzombak, 1998). On the microfracture surfaces, ethers, alcohols, ketones,
aldehydes, amides, and carboxylic acids were observed that are characteristic of a variety of humic substances (Monteil-
Rivera et al., 2000) and aquatic NOM (Boughriet et al., 1992) on particulates from the Seine River.
3.9 Packer Water Characterization and Geochemical Modeling
Straddle packers were used to isolate the bore holes over 1.52 m (5.0 ft) intervals where some of the microfractures
were situated. The packer intervals (28 L) were purged for at least two interval volumes prior to sample collection. During
purging, conductivity and pH were monitored and would stabilize over the purge cycle. The packer intervals were purged
for at least two interval volumes prior to sample collection (termed packer water). In some cases (Clusters 2 and 4), this
purging required 2 or 3 days of continuous pumping. Four sampling events were conducted (Table 3.16). Microfracture
MF04 (Cluster 2) was sampled on July 20, 2002. Microfractures MF05-MF06-MF07 (Cluster 3) were sampled on April
15, 2002, and May 29, 2002, and microfractures MF10-MF11 (Cluster 4) were sampled on June 3, 2003. Cluster 1 in
borehole BBC5 (microfractures MF01-MF02-MF03) was not sampled as the location was too close to the bottom of
the telescoping casing.
The sample collection times and volumes collected after purging for the samples were 3 h and 5.4 L for microfracture
MF04 (Cluster 2) on July 20, 2002, 1.45 h and 224 L for microfractures MF05-MF06-MF07 (Cluster 3) on April 15,
2002, and 0.83 h minutes and 224 L for microfractures MF05-MF06-MF07 (Cluster 3) on May 29, 2002, and 1.167 h
and 14.35 L for microfractures MF10-MF11 (Cluster 4) on June 3, 2003. These differential volumes reflect the different
hydraulic conductivities across the intervals. The longer sample collection times for Clusters 2 and 4 suggest that these
intervals had relatively low hydraulic conductivities.
Generally, the packer waters were typical of groundwater temperatures (10°C). Observed pH values (8.79-9.56) were in
agreement with the alkaline nature of the water (131-190 mg/L alkalinity as CaCO3). Dissolved oxygen values were low
(0.4 to 2.5 mg/L), but conditions were not always anaerobic. Non-purgeable organic carbon concentrations were generally
low (0.82-1.66 mg/L). As noted previously, it is not clear what signatures were derived from the microfracture network
relative to the more open fracture system comprising the bulk of the sample collected in the straddle packers.
Eh values as determined by polished platinum electrode were mildly reducing (+160 to -208 eV). Interestingly, both Fe2+
and Fe3+ were observed, usually both at low concentrations. This suggested that the biogeochemistry of the system was
poised around the Fe2+/Fe3+ couple. Geochemical modeling with Visual MINTEQ with a Fe2+/Fe3+ couple at the observed
concentrations showed the system to have mildly reducing Eh values based on Nernst equation calculations, suggesting
that the observed Eh values in the field were reasonable estimates.
59
-------
Table 3.16. Packer Water Characterizations
Well
Interval
Cluster
Applicable Microfractures
Sampling Date
Packer Volume Collected
Collection Time
Temperature
PH
Conductivity
DO
Eh
TCE
trans-1,2-DCE
cis-1,2,DCE
1,1-DCE
VC
Acetone
Methane
Ethane
Ethene
NPDOC
NH/
Alkalinity (as CaCO3)
ci-
so42-
NCy
s2-
Fe2+
Al
As
Ba
B
Ca
Cr
Cu
Fe
Pb
Mg
Mn
K
Si
Na
Zn
Units
L
h
°C
PH
mS
mg/L
mV
Mg/L
M9/L
Mg/L
Mg/L
Mg/L
Mg/L
Mg/L
Mg/L
Mg/L
mgC/L
MgN/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
DL
-
-
-
-
-
0.1
-
2
2
2
1
2
10
4
4
1
0.10
5
1
4
10
0.1
0.004
0.10
0.1
0.04
0.002
0.3
1
0.001
0.001
0.05
0.02
1
0.05
1
0.3
10
0.1
BBC5
95.4- 100.4ft
2
MF04
7/20/02
5.4
3
10.29
9.56
0.56
2.5
-84.8
43
45
320
ND
14
120
260
ND
11
NA
ND
131
14
110
ND
ND
0.10
0.76
ND
0.007
ND
3.6
0.02
NA
0.18
ND
1.6
ND
6.8
4.4
77
0.07
BBC5
121 .4 -126.4 ft
3
MF05-MF07
4/15/02
224
1.45
ND
8.79
0.60
0.40
NA
110
76
480
2
25
ND
360
ND
15
0.80
ND
158
11
110
ND
ND
0.10
ND
ND
ND
ND
7.40
ND
ND
0.30
ND
2.90
ND
8.00
4.10
110.00
ND
BBC5
121 .4 -126.4 ft
3
MF05-MF07
5/29/02
224
0.83
10.33
9.00
0.60
0.40
160.9
NA
NA
NA
NA
NA
NA
NA
NA
NA
0.82
ND
190
12
120
ND
ND
0.10
0.09
0.01
0.02
0.03
8.60
0.002
0.002
0.11
ND
3.20
0.03
6.00
5.20
120.00
0.02
BBC6
112.0- 117.0ft
4
MF10-MF11
6/3/03
14.35
1.167
NA
8.94
0.56
0.7
-208.8
33
37
340
1
15
ND
170
ND
6
1.66
72
165
12
120
ND
ND
0.1
ND
ND
ND
ND
3.8
ND
ND
0.11
ND
1.3
ND
4.4
7
140
ND
DL = Detection Limit; ND = Not Determined; NA = Not Analyzed; - = Not relevant.
60
-------
The presence of dissolved oxygen at relatively low concentrations around 0.5 mg/L and detectable Fe(ll) concentrations
in the packer samples warrant some discussion. Similar occurrences of detectable Fe(ll) and low dissolved oxygen
concentrations have been observed at TCE-contaminated field sites before (Yager et al., 1997). The system was poised
at the redox boundary between Fe(ll) oxidation and Fe(lll) reduction. However, it is not clear if the system is at pseudo-
equilibrium. The data suggest that perhaps either Fe(ll) oxidation was kinetically constrained or that mixing of two sample
types (more oxic open fracture groundwater with small volumes of more reducing microfracture network porewater) may
have occurred. The high O2 value of the one sample (2.5 mg/L) could also reflect improper packer operation in that case.
Fe(ll) oxidation in controlled aqueous solutions (with respect to pH, CO2 partial pressures, ionic strength) is typically
first order with respect to Fe(ll) and O2 concentrations and second order with respect to OH"concentrations. Oxidation
rates are dramatically slower at lower pH values (<5). The presence of reactive surfaces, solution-phase complexants,
and microbial catalysts can also influence aqueous oxidation rates. Abiotic reductive dissolution of Fe(lll) oxides is also
kinetically constrained by slow detachment of the Fe(ll) ion.
No nitrates or sulfides were detected in the packer water samples. The dominant form of sulfur in the packer water
samples was sulfate (110 to 120 mg/L), suggesting that sulfate reduction was probably not occurring in the open fracture
system or that sulfate was not limiting in the open fracture system. Pyrite (FeS2) was found in all 11 of the host rock
samples with petrography. Pyrite was also seen in some of the microfracture samples (microfractures MF02, MF04,
MF05, and MF09) with SEM/EDAX. This method has the ability to detect mineral associations at depths of up to 1 urn.
In a few cases, pyrite was inferred with XPS based on Fe spectra in microfractures MF04, MF05, MF06, MF08, and
MF09 though S was seen on only two microfracture surfaces (microfractures MF05, MF07) and both spectra indicated
oxidized sulfur was present. This spectroscopy is a surface sensitive technique (penetration depths of ca. 10 A). No
significant levels of S were detected by SIMS, another surface spectroscopy (ejection depths of ca. 100 A). These data
collectively suggest that much of the source of sulfate in the system may have been derived from pyrite oxidation, but
less pyrite was available at the microfracture surface, either by depletion or by occlusion from calcite-dominated surface
precipitates, for oxidation.
In all cases where it was analyzed, dissolved methane was detected (170 to 360 ug/L) in the packer waters during three
sampling events. These data suggest that some level of methanogenesis is occurring in the open fracture system or in
the microfracture networks. The import of more surficial overburden waters containing methane cannot be discounted.
The surficial and groundwater hydrology is discussed in greater detail in Volume 3: Fractured Rock Hydraulics.
In terms of contaminants, c/s-1,2 DCE was by far the dominant chlorinated compound (320 to 480 ug/L). Some frans-1,2
DCE was observed as well, but at low concentrations (37-76 ug/L). Very little 1,1-DCE was observed (ND to 2 ug/L).
TCE concentrations were moderate (33 to 110 ug/L). VC concentrations were also low (14-25 ug/L). Interestingly, ethene
was detected (ND to 11 ug/L). These data suggest that some mechanism of biodegradation of TCE had occurred,
resulting in some of the TCE becoming completely dechlorinated. However, much of the contaminant had undergone
only partial dechlorination to DCE.
The packer water composition was dominated by Na, Cl, K, Ca, Mg, Si, and carbonate. Other constituents (e.g., Al,
Fe, Mn, As) were present at lower concentrations. As shown in Table 3.17, the likely controlling solids for these packer
waters were carbonates, quartz, and simple oxyhydroxides (e.g. Fe(OH)3, FeOOH, AI(OH)3, AIOOH). These phases were
all identified by XPS, XRD, and petrography. If detection limit values for S2" were introduced into the model, saturation
index values for amorphous FeS and mackinawite (FeS) were slightly under saturated (e.g., saturation indices of -0.749
to-1.399).
As noted earlier, the use of thermodynamic models to interpret solid phase control of dominant dissolved constituents,
buffer systems, redox reactions, and related geochemical processes must be done with some caution. Analyses suggest
that with respect to simple acid-base reactions (e.g., carbonate dissolution, hydrolysis reactions), the microfracture
network may be closer to pseudo-equilibrium. The principal buffer in network, dominated by carbonates from calcite
and Ca-Mg carbonates, is found as a dominant mineral in the closed microfractures, open microfractures, and on the
borehole walls of the wells.
The bulk of the data suggests that the presence of methane, Fe(ll), hydrogen, and low DO values points to some type
of reduced environments somewhere in the fracture system, likely within the microfracture networks. This is discussed
later in Section 3.13.
61
-------
Table 3.17. Candidate Controlling Solid Minerals in Packer Waters Identified by Geochemical Modeling
Mineral
AI(OH)3 (Soil)
BaHAsO4»H2O
Barite
Boehmite
CaCO3 • H2O
Calcite
Dolomite (dis.)
Dolomite (ord.)
Fe(OH)2 (am.)
Fe(OH)2 (c)
Gibbsite (c)
Goethite
Halloysite
Huntite
Hydrozincite
Imogolite
K-Jarosite
Magnesite
MnCO3 (am.)
Quartz
Rhodochrosite
Sepiolite
Sepiolite (am.)
Siderite
SiO2 (am, gel)
SiO2 (am, ppt)
Smithsonite
Zincite
Zn(OH)2
ZnCO3
ZnCO3 • H2O
Formula
AI(OH)3
BaHAsO4 • H2O
BaCO3
AIOOH
-
CaCO3
CaMg(C03)2
CaMg(C03)2
-
-
AI(OH)3
FeOOH
AI2SiO2(OH)6»H2O
CaMg3(C03)4
Zn5(C03)2(OH)6
AI2SiO4(OH)2»H2O
Fe3(S04)(OH)5.2H20
MnCO3
-
SiO2
MnCO3
Mg2Si308.2H20
Mg2Si308.2H20
FeCO3
-
-
ZnCO3
ZnO
Zn(OH)2 (beta)
-
-
MF04
(7/20/02)
Log
IAP
-
-
-
-
-
-8.10
-16.36
-16.36
11.55
11.55
-
-
-
-
-
-
-12.30
-
-
-3.84
-
15.35
-
-10.15
-3.84
-3.84
-
-
-
-
-
SI
-
-
-
-
-
0.38
0.19
0.73
-1.94
-1.34
-
-
-
-
-
-
-1.30
-
-
0.16
-
-0.41
-
0.441
-1.13
-1.10
-
-
-
-
-
MF05-MF07
(4/1 5/02)
Log
IAP
8.36
-25.39
-10.14
8.36
-7.81
-7.81
-15.76
-15.76
11.92
11.92
8.36
-
9.20
-31.75
6.79
12.96
-
-7.98
-1 1 .06
-3.76
-1 1 .06
16.47
-
-9.93
-3.76
-3.76
-11.75
10.10
10.10
-11.75
-
SI
0.07
-0.75
-0.16
-0.22
-0.67
0.68
0.76
1.31
-1.57
-0.97
0.62
-
-0.37
-1.78
-1.90
-0.04
-
-0.52
-0.56
0.24
-0.05
0.71
-
0.66
-1.05
-1.02
-0.85
-1.13
-1.65
-0.95
-
MF05-MF07
(5/29/02)
Log
IAP
8.73
-
-10.61
8.73
-7.93
-7.93
-15.93
-15.93
12.86
12.86
8.73
7.25
9.54
-31.94
8.94
13.50
-
-8.00
-
-3.97
-
17.47
17.47
-9.83
-3.97
-3.97
-11.83
10.86
10.86
-1 1 .82
-11.75
SI
0.44
-
-0.63
0.16
-0.79
0.55
0.61
1.16
-0.63
-0.03
0.99
6.76
-0.04
-1.97
0.24
0.50
-
-0.54
-
0.03
-
1.71
-1.31
0.76
-1.25
-1.23
-0.92
-0.37
-0.89
-1.02
-1.49
MF1— MF11
(6/3/03)
Log
IAP
-
-
-
-
-8.26
-8.26
-16.73
-16.73
11.82
11.82
-
-
-
-
-
-
-
-8.47
-
-3.62
-
15.87
-
-10.03
-3.62
-3.62
-
-
-
-
-
SI
-
-
-
-
-1.12
0.22
-0.19
0.36
-1.67
-1.07
-
-
-
-
-
-
-
-1.01
-
0.38
-
0.11
-
0.56
-0.91
-0.88
-
-
-
-
-
IAP = Ion Activity Product
SI = Saturation Index
62
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3.10 Mass Fragment Fingerprints of Microfracture Surfaces
The static SIMS work conducted on microfracture MF03 was preliminary, but illustrative of the organics and contaminants
present. Significant problems were experienced with sample charging.
Negative (0-50 atomic mass units) and positive mass fragments (0-50, 50-100 atomic mass units) observed with
SIMS are shown in Figures 3.23, 3.24, and 3.25, respectively. A number of mass fragments associated with dominant
isotopes of major elements were observed. These included Fe, Na, Si, Mg, K, Ca, and Ti, all of which were seen with
other spectroscopic methods. Additionally, Ga was seen as it was implanted during ion bombardment. Isotope mass
distributions observed generally reflected their natural abundances: 28SiV29Si+/30Si+ of 92/5/3 %, 39K+/41K+ of 93/7 %,
40Ca+/44Ca+ of 97/2 %, and 35CI737C|- of 76/24 %.
o
o
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1e+5
1e+4
1e+3
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I 1e+2
23 Na+ 39 K+
24 l\
III
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27A|+ I
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28 Sj+ ||
"9+ C2H5+']1K+
||
29Si+
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44Ca+
. 48 Jj +
I [^C35C\+
47 ,C37CI
III 49
Illii
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Positive Static SIMS
Ga+ Primary Beam (10KeV, 10nA)
Target Bias 13.0V
0.05 Atomic Mass Unit Step Size,
200 ms per channel, 1 scan
0 10 20 30 40 50 60
Atomic Mass Units
Figure 3.23 SIMS negative mass fragment (0-50 atomic mass units) fingerprint. The sample was microfracture MF03.
1e+5
1e+4
1e+3
T3
C
O
o
o
U)
!_
CD
0_
C
I 1e+2
O
Negative Static SIMS
Ga+ Primary Beam (10KeV, 10nA)
Target Bias 13.0V
0.05 Atomic Mass Unit Step Size,
200 ms per channel, 1 scan
-10 0 10 20 30 40 50 60
Atomic Mass Unit
Figure 3.24 SIMS positive mass fragment (0-50 atomic mass units) fingerprint. The sample was microfracture MF03.
63
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1e+5
8
-------
3.11 Porosity and Pore Size Distribution of Host Rock
The core material was generally insufficiently porous to be characterized by MIR Samples, despite apparent sealed
microfractures on the surface, did not allow the minimum mercury intrusion volumes needed to gather reliable data. Samples
with larger, less sealed fractures broke apart during the cube cutting process and so could not be characterized.
Of the 10 sample cubes from borehole BBC5 analyzed by MIP, one sample was sufficiently porous to provide reliable
mercury intrusion data. Figure 3.26 shows the cumulative porosity and the differential pore size distribution, respectively,
collected from this sample cube. Peaks on the differential pore size distribution plot corresponded to threshold pore widths
and represented pore diameters where an increased amount of Hg was intruded into the sample. This plot indicated the
relative population of pores of a given width based on the increased Hg intrusion at that pore width.
g
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0.8-
0.6-
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Porosity
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0.01
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Pore Width (microns)
Figure 3.26 MIP cumulative porosity and pore size distribution for borehole BBC5 host rock specimen.
The MIP data for this sample showed three significant pore throat sizes, reflected as peaks in the plot in Figure 3.26.
These pore throat sizes were 131.1 um, 1.136 urn, and 0.109 um. The sample was found to have a porosity of 0.8% and
density of 2.65 g/cm3. These data are typical for the type of rock that was studied (e.g., Guillot et ai, 2000; Colwell et
al., 1997; Fredrickson et ai, 1997; Onstott et ai, 2003). Estimated permeabilities for this sample, based on the method
of Swanson (1981), were < 1 uDarcy.
In the case of the rock sample from borehole BBC5, the observed pore throat sizes were more similar to those observed
by Colwell et ai (1997) than those reported by Onstott et ai (2003). The borehole BBC5 sample was found to have a
porosity of 0.8%, a value closer to those reported by Onstott et ai (2003). The borehole BBC5 host rock sample had
an estimated permeability of < 1 uDarcy, a value closer to values reported by Onstott et ai (2003) than those reported
by Colwell et ai (1997).
3.12 Microbes Identified on Microfractures
Amplification with specific primer sets (Table 3.18) showed the presence of both bacteria and Archaea in all of the borehole
BBC5 microfracture samples. Positive results were also observed for Dehalococcoides sp., except for microfracture
MF06, and sulfate-reducing bacteria, except microfractures MF05 and MF07. Geobacteraceae were observed only on
microfracture MF04. No Desulfuromonas species were detected with the primer set used. These genes, amplified by
polymerase chain reaction, are for partial 16S rDNA sequence for these prokaryotic groups and do not imply active
metabolism. In the case of the Archaea domain, the presence of 16S rDNA could indicate the presence of methanogens.
Further, in the case of iron-reducing bacteria, the Geobacteraceae 16S rDNA does not include all genera of iron-reducing
bacteria.
65
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Table 3.18. Presence or Absence of Prokaryotic Groups on Borehole BBC5 Microfracture Surfaces as Determined by
Amplification with Specific Primer Sets
Microfracture
01
02
03
04
05
06
07
Specific Primer Set
Bacteria
+
+
+
+
+
+
+
Geobacteracea
-
-
-
+
-
-
-
SRB
+
+
+
+
-
+
-
Dehalococcoides
sp.
+
+
+
+
+
-
+
Desulfuromonas
sp.
-
-
-
-
-
-
-
Archaea
+
+
+
+
+
+
+
SRB = Sulfate Reducing Bacteria
A culture-independent approach, denaturing gradient gel electrophoresis molecular fingerprinting using bacterial primers,
was used to determine the diversity of prokaryotic microbial communities found associated with the fracture surfaces
of borehole BBC5 microfractures and their mineral deposits. The community profiles of the polymerase chain reaction-
amplified 16S rDNA (Figure 3.27) showed the number of denaturing gradient gel electrophoresis bands observed varied
between microfractures. The number of discrete bands was distributed as follows for the indicated microfractures: MF01:
23, MF02: 23, MF03: 25, MF04: 27, MF05: 12, MF06: 10, and MF07: 7.
M3246175M
»f
40%
-• A
60%
Figure 3.27 Polymerase chain reaction-denaturing gradient gel electrophoresis bacterial community profiles
of borehole BBC5 microfractures MF01-MF07. Lanes labeled (M) include markers (A) Shewenalla algae BrY,
(B) Bacillus subtilus, (C) Streptomyces griseus.
66
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The moderate number of bands observed indicates a significant level of microbial diversity within and between the
microfracture surfaces. The banding patterns from each microfracture surface were analyzed by unweighted paired
group method with arithmetic averages to determine the similarity of the samples (Figure 3.28). The dendrogram shows
the similarity coefficient of the samples. Only the banding patterns of microf ractures MF01 and MF03 were shown to be
similar, with a similarity coefficient of 0.82. All other samples showed significantly different banding patterns, indicating
the bacterial communities on the fracture surfaces were, in most cases, compositionally unique. It is important to note
the lack of similarity in community composition, despite their relative spatial proximity of microfractures (even within
a cluster) and the general similarity of surface precipitates among microfractures. The degree of hydraulic connection
between microfractures MF01 and MF03 is unknown.
0.
34 0.50 0.70 0.80
1
L| 056
0.34
040
m 54.
1 In «9
1.00
MF07
Mcnc
MFflfi
MFflA
MFO?
••^/\ 0.75 are deemed similar in community
composition.
The observed banding patterns in the denaturing gradient gel electrophoresis gel differ from banding patterns from
boreholes BBC5 and BBC6 packer water samples (See Volume 4: Fractured Rock Microbiology.). The banding patterns
for unattached prokaryotes in the packer waters show remarkable consistency and little variation (See Volume 4.) and
likely represent the blending of significant volumes of open fracture water with small volumes of microfracture network
water. These data suggested that the communities on the microfracture surfaces were specialized and perhaps adapted
to a surface-associated (thigmotrophic) existence.
Bands from microfracture MF04 were excised, purified, and sequenced to identify the closest phylogenetic group. Partial
sequences of the V3 region of the 16S rDNA (~500bp) of the denaturing gradient gel electrophoresis bands showed
the closest phylogenetic affiliation with an uncultured bacterial clone P39B-52 (98% sequence identity; #AF414577), a
uranium mine sediment isolate; Ultrabacterium strain D-7, (99% sequence identity; #AB008505), a soil isolate; and an
uncultured bacterial clone RA13C10 (99% sequence identity;#AF407400), achlorobenzene-contaminated groundwater
isolate. These data suggested that the microbes associated with the microfracture surfaces were similar to those found
in other subsurface environments (Pedersen, 1997).
Given the large number of bands and the suggestion of diverse metabolic potential on the microfracture surfaces, the
identity of the remaining bands is important. It might help to elucidate syntrophic relationships, dependency upon mineral
abundance for redox reactions and mineral cycling, and the nature of the advantages offered by surface growth.
3.13 Relationship Between Packer Water Samples and Microfracture Geochemical
Environment
The packer water sampling and characterization of microfractures from boreholes BBC5 and BBC6 represent a spatially
discrete and very small sub-sample from the entire contaminated bedrock plume at Site 32. Further, the pump and
treat remediation strategy instituted in 1997 likely altered initial discrete redox zonation within the plume by changing
the hydraulic conditions (e.g., drawing groundwater back towards the sheetpile). Comparison of packer water and
microfracture snapshots may not necessarily reflect temporal and spatial trends within the plume because they were,
by necessity, collected at different times. Further, the installation of boreholes introduced hydraulic connections that
may not have existed prior to drilling and will most likely have impacted the chemical signature of the packer water
samples. Nevertheless, it is useful to compare the results from packer water samples and the likely microenvironments
that existed in the porewater and microfracture surfaces within the microfracture network.
67
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Even with the assumption of a relatively high microf racture-specific surface area, the total volume of porewater available
in the microfractures was likely many orders of magnitude less than those volumes collected during packer water
sample collection, particularly for highly transmissive intervals (e.g., Cluster 2, 3). This suggested that open fractures
likely contributed the most significant proportion (e.g., > 99%) to the packer water samples. The estimated permeability
of the microfracture network in the host rock (< 1 ud) also implied that diffusive, rather than advective, transport was
probably occurring between the microfracture network and the more open fracture system. As a result, discerning the
exact composition of the microfracture porewaters using packer sampling is difficult and subject to some uncertainty
for quantitative estimation.
Some evidence suggested that the porewaters in contact with the microfracture surfaces were somewhat similar to the
packer water and thus connected (though not necessarily similar from a geochemical perspective). For example, TCE
or its transformation products were possibly identified on the one microfracture surface that was analyzed (microfracture
MF03) using SIMS and in the packer water for that packer water interval, suggesting similar groundwater moving through
them. Additionally, Dehalococcoides sp. primers were identified on a number of microfracture surfaces. This suggested
that TCE or its transformation products had migrated from the open fracture system to the tighter microfracture network
and that Dehalococcoides sp. present there may have been able to metabolize it. Finally, the dominant minerals such
as carbonates identified on the microfracture surfaces were generally in local pseudo-equilibrium, as determined by
the geochemical model Visual MINTEQ, with aqueous constituents measured in the packer waters, suggesting either
some degree of communication between the packer water and the microfracture network or, more likely, the presence
of similar minerals in the microfracture network and open fracture system.
A stronger body of evidence suggests that the packer water was not very representative of the local biogeochemical
environment in the microfracture network. The microfracture network may have been more reducing than the open fracture
system based on the preponderance of primer data. Primers for Archaea (including anaerobic methanogens) were found
on all seven of the microfracture surfaces tested, yet the concentrations of methane in the packer samples were relatively
low (170-360 ug/L). Primers for anaerobic Dehalococcoides sp. were found on six of the seven microfractures. Primers
for anaerobic sulfate-reducing bacteria were found on five of the seven microfractures, yet no sulfide was quantified in
the packer waters, and the packer waters were dominated by very high levels of sulfate (110-120 mg/L). If the packer
waters were reflective of clearly delineated zones associated with methanogenesis or sulfate reduction, higher levels
of methane or sulfide might be expected.
One reason for the low cell densities on the microfracture surfaces and the reducing conditions in the microfractures
was the low levels of NPDOC in the groundwater at Site 32. This, in turn, limits H2 production which is required as an
electron donor for Dehalococcoides sp. In contrast, Wiedemeier et al. (1997) observed 1,420 to 1,600 ug/L of methane
in the methanogenic zone of a sandy aquifer TCE contaminant plume at Pittsburgh Air Force Base. NPDOC levels
were up to 80 mg/L. Chapelle (1997) observed up to 8,000 ug/L of methane in the methanogenic zone and up to 60
mg/L sulfide in the sulfate reducing zone of a TCE contaminant plume in a shallow, sandy aquifer at the Cecil Field
Naval Air Station in Florida. While NPDOC levels were not reported, hydrocarbon contaminants were also present in
the contaminant plume.
Perhaps the most likely scenario is that the microfracture network, by virtue of its smaller volume, reduced communication
with the open fracture system, and likely mass transfer limitations into and out of the microfractures from the open fracture
system, does not significantly contribute to the contaminant or biogeochemical signatures seen in the packer waters
collected under fairly transmissive conditions for fractured bedrock at the site. The region around Cluster 3 (borehole
BBC5) had a borehole transmissivity of 0.139 m2/d (1.5 ft2/d). The general region around Cluster 4 (borehole BBC6)
had a borehole transmissivity of 0.185 m2/d (2 ft2/d). Based on the observed permeability of the borehole BBC5 host
rock, water movement through the microfractures was unlikely to have been this high.
3.14 Likely Terminal Electron Accepting Processes in the Open Fracture System
The succession of terminal electron accepting processes in order of decreasing redox potential and free energy
yield is generally: oxygen reduction, nitrate reduction, manganese reduction, Fe(lll) reduction, sulfate reduction, and
methanogenesis (McGuire et al., 2000). Using the general guide provided by Chapelle et al. (2003), the following
observations were noted about the packer water samples.
While H2 was not measured in the packer samples, it was measured in borehole BBC6 in regions within 3 m (10 ft) to
sampled packer intervals. Sampling occurred on June 24-26, 2003. Concentrations ranged from 2.2 to 7.3 nM. H2 was
detected at 32.6 m (107ft) at concentrations of 2.7 nM (depths relative to top of telescoping casing). It was also detected
at 40.53 m (133 ft) at concentrations of 7.3 nM. It was also detected at 54.5 m (179 ft) at concentrations of 2.2 nM.
68
-------
The presence of H2 is indicative of hydrogenotrophic fermentive reactions that can result in a pool of H2 that can have
signature steady state concentrations with high turnover. The H2 values observed for borehole BBC6 suggested sulfate
reduction and possible methanogenesis (Chapelle etal., 2003) at 40.53 m (133ft). However, the high levels of sulfate (up
to 120 mg/L), the absence of sulfide (<0.04 mg/L), and the low NPDOC in the packer water samples suggested that sulfate
reduction was not the dominant terminal electron accepting process in the open fracture system. Interestingly, hydraulic
testing showed a clear connection between 32.6 m (107 ft) and 54.5 m (179 ft) where lower methane concentrations
were present and little to no connection at 40.53 m (133 ft) where methane was higher.
The dissolved oxygen concentrations in the packer samples ranged from 0.4 to 2.5 mg/L. Three of the four determinations
were low (0.4, 0.4, 0.7 mg/L). The high value may be erroneous. These data suggested that DO was depleted in the
open fracture system. The low values indicated a system dominated by nitrate, ferric iron, sulfate, or carbon dioxide
reduction (Chapelle et al., 2002). When compared and contrasted with the NPDOC data (concentrations ranging from
0.80 to 1.66 mg/L), the open fracture system seemed poised for sulfate reduction, but was likely limited by organic
carbon bioavailability. At this time, the exact nature of the NPDOC (e.g., molecular weight distribution, hydrophobicity/
hydrophilicity, aromaticity, functional group distribution, biodegradability) nor its source has been determined.
The supply of fixed nitrogen was limited in the packer samples. Both ammonium and nitrate concentrations were very
low to non-detect. These data suggest that nitrate reduction was not a dominant terminal electron accepting process in
the open fracture system. This was expected, given the low levels of N in the system.
Fe(ll) and Fe(lll) were present as dissolved constituents in the packer samples at modest concentrations. A comparison
between measured Eh values using a polished platinum inert electrode and Ag/AgCI reference electrode in the packer
water samples and predicted Eh values based on Nernst Equation calculations using the Fe(ll)/Fe(lll) couple with Visual
MINTEQ modeling, showed the following: for microfracture MF04 (Cluster 2) on July 20, 2002, -84.8 mV versus -126.5
mV; microfractures MF05-MF06-MF07 (Cluster 3) on May 29, 2002, 160.9 mV versus -61.1 mV; and microfractures
MF10-MF11 (Cluster 4) on June 3, 2003, -208.8 mV versus -48.47 mV. There are limitations to using platinum electrodes,
mostly related to reactivity on the electrode's surface. This can be minimized by polishing. The electrode is responsive
to the predominant aqueous electron-donating and electron-receiving species in solution and may not be responsive to
kinetically-restrained reactions. Given these limitations, these data suggested that the observed redox conditions and
dissolved iron species were in general agreement and that ferric iron reduction might have been the dominant terminal
electron accepting process in the open fracture system.
Yager et al. (1997) developed similar conclusions about a TCE plume in highly fractured and weathered dolomite at a
contaminated bedrock site near Niagara, NY. They observed pH values of 6.6 to 6.9, alkalinity values of 250 to 340 mg/L
as CaCO3, low DO values (<0.01 mg/L), fairly low values of NPDOC (1.4 to 3.2 mg/L), high levels of chloride (21-790
mg/L) and sulfate (500 to 1800 mg/L, largely influenced by gypsum dissolution in the formation), and detectable levels of
sulfide (0.13 to 75 mg/L), Fe(ll) (<0.2 to 1 mg/L), H2 (0.26 to 1.4 nM), methane (1.5 to 37 mg/L), as well as TCE, DCE,
VC, and ethene. The observed levels of H2 and Fe(ll) were used to determine that Fe(lll) reduction was the dominant
terminal electron accepting process at the site.
The presence of methane in the packer water samples indicated that methanogenesis was occurring somewhere in the
open fracture system, most likely in the microfracture network. However, as noted previously in Section 3.14, it was not
a likely dominant terminal electron accepting process in the open fracture system. Methane is soluble in water and can
be readily transported. Its presence in the packer samples may not be indicative of local generation.
3.15 Likely Terminal Electron Accepting Processes in the Microfracture Network
Surface spectroscopies, particularly XPS, were used to look at element speciation on microfracture surfaces where
adherent microbes were present and where porewaters were in contact with those surfaces. These spectroscopic
methods were useful in deducing which terminal electron accepting process might dominate in the microfracture network,
particularly as related to C, S, and Fe metabolism. For instance, Haveman et al. (1999) characterized the microbiology
and geochemistry of groundwater samples from deep igneous rock sites in Finland dominated by gneiss, granodiorite,
and Fe-rich granite. They found that free-swimming, sulfate-reducing bacteria in the fracture porewater predominated
where iron sulfide fracture-filling minerals were present. Further, they found that free-swimming, iron-reducing bacteria
in the fracture porewater were dominant where iron hydroxide fracture minerals were prevalent. Such relations may exist
between adherent microbes and the dominant mineral forms on the BBC microfracture surfaces.
Both organic and inorganic C were ubiquitously observed on all microfracture surfaces. The bioavailability of the sorbed
NOM is not known; however, its localized concentration on the microfracture surface was quite high relative to the
69
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concentrations found in solution in the packer water samples. Using XPS, C concentrations in the top few atomic layers
of the microfracture surfaces ranged from 18,555 to 330,000 mg/kg (data not shown). The majority (>80%) of this C was
organic. This carbon may have been available for aerobic or anaerobic respiration. The inorganic carbon, also present
at locally high concentrations on the microfracture surfaces, was a ready source of inorganic C for methanogenesis.
Sulfur was also observed on some of the microfracture surfaces (microfractures MF05, MF07). Concentrations were
much less significant than those seen for C or Fe. Using XPS, S concentrations ranged from 5,000 to 16,000 mg/kg
on two microfracture surfaces (data not shown). Most of the observed species were S (VI) and not (-II). Sulfides were
below detection limits in the packer water samples (< 0.04 mg/L). No likely candidate controlling solids were observed
for sulfate minerals with Visual MINTEQ. If detection limit values for S2' were introduced into the model, then saturation
index values for amorphous FeS and mackinawite (FeS) were slightly under saturated (-0.749 to -1.399). This indicated
that the packer waters might be close to pseudo-equilibrium for FeS as a controlling solid if actual sulfide concentrations
were just below detection limits. If sulfate reduction was occurring on the microfracture surfaces, then no spectroscopic
evidence of a solid precipitate was detected using the various spectroscopies.
Iron was a dominant microfracture surface element on all microfracture surfaces. Using XPS, Fe concentrations ranged
from 25,300 to 201,600 mg/kg (data not shown). Both Fe(ll) and Fe(lll) candidate minerals were identified on the mi-
crofracture surfaces, including pyrrhotite (FeS), wustite (FeO), goethite (ex-FeOOH), hematite (Fe2O3), aged hydrous
ferric oxide (Fe2O3 • 1.57 H2O), limonite (Fe2O3 • nH2O)), and mixed ferrous and ferric minerals (e.g., magnetite (Fe3O4)).
Some oxidized Fe species (e.g., goethite (a-FeOOH)) are known substrates for iron-reducing bacteria (Lower et al.,
2001; Dong et al., 2003). Iron-reducing bacteria are capable of reducing poorly crystalline Fe(lll) oxide minerals during
the redox reaction (Shelobolina et al., 2003). The spatial prevalence of Fe, as well as its situation in the top few nm of
the microfracture surfaces, suggested that Fe(lll) was available for iron-reducing bacteria. The occurrence of Fe(ll) on
the microfracture surface may reflect bacteria-mediated Fe(lll) reduction reactions. The spectroscopic characterization
of the microfracture surfaces points to Fe(lll) reduction as perhaps a dominant terminal electron accepting process in
the microfracture network.
Based on these spectroscopic observations, all three likely terminal electron accepting processes (ferric iron, sulfate,
or carbonate reduction) may have been occurring. Further, some degree of redox zonation may occur spatially within
the microfracture network depending on the network's proximity to the open fracture system, diffusivities, and diffusion
gradients.
3.16 Microfracture Surface Speciation and Adherent Microbial Population Metabolism and
Diversity
Table 3.19 summarizes the known speciation information for C, Fe, and S species within or on the microfracture surface
precipitates. These three elements were likely candidates for terminal electron accepting processes. The speciation
information was related to adherent microbial population community structure and to identified primers for microfractures
MF01 through MF07.
There is generally good agreement between SEM-EDAX, XRD, and XPS about identification of C, S, and Fe with
the microfracture surface precipitates on their surfaces. However, the observed population diversity as determined by
denaturing gradient gel electrophoresis community similarity indices or denaturing gradient gel electrophoresis banding
numbers cannot be precisely related to the speciation of any of the three elements on the microfracture surfaces.
The situation is analogous for the primers that were identified on the microfracture surfaces. In all cases, carbonates
were seen on microfracture surfaces where Archaea primers were seen. In two of four cases where sulfate-reducing
bacteria primers were seen, oxidized or reduced S was seen. In the one case where iron-reducing bacteria primer was
seen, oxidized and reduced Fe was detected. The problem stems from a lack of spatial resolution in identifying direct
association between adherent microbial populations and the heterogeneous distribution of minerals on the microfracture
surfaces.
The fact that the attached microbial populations differed in composition from the unattached populations (See Volume
4: Fractured Rock Microbiology.) suggested some role of the microfracture surface in influencing community diversity.
Haveman et al. (1999) found a similar relationship. For example, they observed that free-swimming, sulfate-reducing
bacteria predominated in groundwater samples from 200- to 950-m depths in four igneous rock sites in Finland where
iron sulfide fracture filling minerals are common. The iron-reducing bacteria were the main population in one site where
iron sulfide fracture minerals were not present, but iron hydroxide fracture minerals predominated. They observed that
fracture filling minerals were a better indicator of microbial populations than was groundwater chemistry.
70
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Based on the SEM-EDAX work, the spatial heterogeneity of minerals was quite high on the microf racture surface. Mineral
grain sizes were on the order of tens of urn. While minerals may be common to all observed microfracture surfaces, their
relative spacing and proximity to each other and to surface topography were quite varied. It may be that the biopatches
that were observed with SEM reflected a more localized microbial community response to microfracture surface speciation.
The proximity between microbes and mineral surfaces of metabolic value usually requires direct contact, frequently
requiring cell membrane enzyme availability at the mineral surface to facilitate electron transfer between the mineral
surface and electron transport proteins (See Rogers etal., 1999; 2001; Lower etal., 2001; Shelobolina etal., 2003.). The
level of resolution of SEM, SEM-EDAX, and XPS was not high enough to discern such spatial relationships though such
relations were likely. Hence, different areas on a microfracture surface may exhibit different terminal electron accepting
processes depending on the minerals present with differences occurring over small distances (tens of urn).
3.17 Role of Microfracture Surfaces in TCE Transformation and Microbial Ecology
Biodegradation transformation products of TCE dechlorination were found in the packer water samples, including c/s-1,2
DCE, frans-1,2 DCE, VC, and ethene. In each packer water sample, c/s-1,2 DCE was most prevalent (37-480 ug/L),
followed by frans-1,2 DCE (37-76 ug/L), VC (14 to 25 ug/L), and ethene (6-15 ug/L).
The presence of Dehalococcoides sp. was observed on five of seven microfractures from borehole BBC5 with primers
aligned for the V3 region of the 16S rDNA of Dehalococcoides ethenogenes and Dehalococcoides sp. (strain FL2).
This was indicative of the presence of a dehalorespirer that is capable of dechlorinating TCE to ethene (Loffler et al.,
2000). Dehalococcoides sp. uses H2 as an electron donor. There has been some work relating dehalorespiration and
poised H2 levels. Yang and McCarty (1998) found that a mixed culture growing at 28 °C on benzoate with c/s-DCE as
the terminal electron acceptor poised the H2 concentration at 2 nM, suggesting a minimum concentration of H2 that
would support reductive dechlorination. Fennell and Gossett (1998) reported that the lowest H2 concentration allowing
dechlorination (at 35 °C) was 1.5 nM. In the case of the BBC site, H2 was certainly present in the open fracture system
of borehole BBC6 at Site 32 at concentrations that would support dechlorination. Concentrations of H2 in the associated
microfracture networks of borehole BBC6 are not known. The endpoint for complete dechlorination is ethene, also
observed in the packer water samples.
The dominant terminal electron accepting process in the open fracture system appears to be Fe(lll) reduction. The
possible terminal electron accepting processes in the microfracture network could be methanogenesis, sulfate reduction,
and ferric iron reduction. Dechlorination reactions can occur under all of these terminal electron accepting process
conditions (Bouwer, 1994).
At this time, reductive dechlorination mediated by Dehalococcoides sp. appears to be one biodegradative pathway at the
BBC site, at least in the microfracture networks. Other biotic and abiotic processes can not be discounted. Dehalococcoides
sp. is widely distributed geospatially in soil and sediment samples at TCE contaminated sites (Hendrickson et al., 2002).
Dehalococcoides sp. has also been observed in highly fractured and weathered dolomite contaminated with TCE
(Hohnstock-Ashe etal., 2001; Hendrickson etal., 2002). The fact that c/s-1,2 DCE was the predominant daughter product
implied that Dehalococcoides sp. was perhaps rate limited in its dechlorination potential or not able to dechlorinate all of
the available DCE. It is not clear if a dechlorinating consortium was involved (Flynn et al., 2000). Other means of TCE
biodegradation, including aerobic and anaerobic respiratory and cometabolic processes, cannot be excluded.
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4.0 Conclusions
The University of New Hampshire's Bedrock Bioremediation Center (BBC) uses a TCE contamination site at the former
Pease Air Force Base in Portsmouth, NH, to study fundamental and applied geological, hydrological, microbial, and
remedial processes in competent fractured bedrock. Eleven microfractures extracted from competent bedrock cores
from boreholes BBC5 and BBC6 were characterized with a variety of surface spectroscopic and microbial techniques to
determine if a relation exists between microfracture surface precipitates and the ecology and metabolic activity of attached
microbial communities relative to terminal electron accepting processes or to chlorinated solvent biodegradation.
The microfracture surface precipitates showed various degrees of infilling, surface coverage, and precipitate thicknesses.
These microfractures were all wetted when extracted and were various colors (white, yellow/green, slate blue, or black).
Carbonate minerals (siderite, FeCO3; calcite, CaCO3; dolomite, CaMg(CO3)2) and quartz (SiO2) were the dominant
minerals in the surface precipitates. Other minerals, typical of the Kittery Formation metasandstones and metashales,
were also observed. Limonite (Fe2O3 • nH2O) and pyrite (FeS2) were present as accessory minerals.
The MIP data for this competent bedrock showed (with only one of 10 samples) three significant pore throat sizes of
131.1 um, 1.136 um, and 0.109 um. The sample was found to have a porosity of 0.8%, a density of 2.65 g/cm3, and a
permeability of < 1 uDarcy. These data are similar to other competent deep bedrock sites where microbial biomass and
metabolic activity have been observed in microfractures with similar pore throat widths.
XPS was particularly useful in identifying NOM functional groups and Fe mineral speciation on the microfracture
surfaces. Ether, alcohol, ketone, aldehyde, amide, and carboxylic acid functional groups characteristic of a variety of
humic substances and aquatic NOM were observed on the microfracture surfaces using the C1s photoelectron. NOM
can form conditioning films on mineral surfaces. A number of candidate iron species were seen, including siderite,
pyrrhotite (FeS), wustite (FeO), goethite (a-FeOOH), hematite (Fe2O3), aged hydrous ferric oxide (Fe2O3 • 1.57 H2O),
Hmonite(Fe2O3»nH2O)), and mixed ferrous and ferric minerals (e.g., magnetite (Fe3O4)).TheFe(lll) minerals are capable
of supporting microbial populations that reduce Fe(lll).
Surface mass fragment fingerprints of chlorinated carbon fragments (1 and 2 carbons) obtained suggested that TCE,
PCE, or VC was partitioned in the NOM conditioning layers on the microfracture surfaces. TCE is probably the species,
given its hydrophobicity. More work is needed with this sensitive technique to confirm this observation.
Packer waters were alkaline (total alkalinity of 131-190 mg/L as CaCO3, pH 8.8 to 9.6), dominated by the Fe3+/Fe2+
couple at mildly reducing conditions (Eh of -208 to -160 mV, DO of 0.4 to 2.5 mg/L), and contained TCE, DCE, VC, H2,
methane, and ethene. H2 was present in a number of the BBC boreholes at the site, including BBC6 (2.2 - 7.3 nM).
c/s-1,2-DCE was by far the most prevalent transformation product (up to 480 ug/L). NPDOC values were relatively
low (0.8 to 1.7 mg/L). Sulfate was the dominant anion in the packer waters (110-120 mg/L). No sulfide was detected.
The packer water chemistry was dominated by Ca, Si, Al, and Fe and was generally controlled by surface chemistry
precipitation and dissolution reactions in a system at pseudo-equilibrium with the carbonates and quartz in the surface
precipitates (e.g., CaCO3, CaMg(CO3)2, (Ca,Fe)CO3, SiO2) and with simple Fe and Al oxy-hydroxides (e.g., Fe(OH)2,
FeOOH, AI(OH)3, AIOOH).
SEM of microfracture surfaces revealed occasional biopatches of attached microbes. The biopatches were located in
small depressions, cracks, or crevices on the microfracture surfaces. The microbes were predominantly rod-shaped and
had dimensions of 1.0 um (diameter) and 2.0 um (length). In some instances, the bacteria had extracellular polymeric
substances associated with them. In other cases, the microbes appeared to be encased in a film of organic material or
surface precipitate-like material. Rod-shaped prokaryotes were the only morphology observed. TEM micrographs of calcite/
quartz surface precipitates from microfracture MF11 revealed more diverse prokaryotic morphologies (e.g., spirilla, stalked
bacteria, filaments). In some cases, flagella and possible cell division septa may have been present. There were many cells
that contained large, clear organelles and small dark organelles. These may have been possible storage bodies.
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All borehole BBC5 microfracture surfaces contained attached microbes that were extracted and characterized by
denaturing gradient gel electrophoresis. Phylogenetic relationships were examined. In one case, gene sequencing and
type identification were conducted. A large number of types (typically up to 20), as indicated by denaturing gradient gel
electrophoresis banding, were present on the microfracture surfaces. Of the seven microfracture surfaces examined, only
two had similar populations of microbes. The other five all significantly differed from each other and the two that were
similar. This diversity is remarkable given the spatial proximity of microfracture samples. The unattached microbes from
packer water samples differed from the attached populations. Three excised bands were sequenced and matched to
DNA sequences in the DMA database. The matches were for an uncultured bacterium clone P39B-52 (98% sequence
identity; #AF414577, a uranium mine sediment isolate), Ultrabacterium strain D-7, (99% sequence identity; #AB008505,
a soil isolate), and an uncultured bacterium clone RA13C10 (99% sequence identity; #AF407400, a chlorobenzene-
contaminated groundwater isolate).
Primers were used to identify the presence of bacteria, Archaea (including methanogens), sulfate-reducing bacteria,
and dehalorespirers. Bacteria and Archaea were present on all seven microfractures tested. Sulfate-reducing bacteria
were found on six of the seven microfractures tested. Dehalorespirers were found on six of the seven microfractures
tested. These data at least suggest that dehalorespirers were present on the microfracture surfaces where TCE or its
transformation product was co-located.
Although it could not be collected, microfracture porewater likely differed from packer water in chemical composition.
The microfracture network may have been more reducing than the open fracture system based on the preponderance
of primer data indicating the presence of sulfate-reducing bacteria and Archaea.The microfracture network in the Kittery
Formation, by virtue of its smaller volume, reduced communication with the open fracture system, and likely mass transfer
limitations probably did not significantly contribute to the contaminant or biogeochemical signatures seen in the packer
waters collected under fairly transmissive conditions for fractured bedrock at the site. More work is needed to be able
to better collect and analyze microfracture porewaters to see their relative pseudo-equilibria (or disequilibria) relative to
the local mineralogical environment.
In terms of identification of a likely terminal electron accepting process in the open fracture system, the H2 values
observed for borehole BBC6 suggested sulfate reduction. However, high levels of sulfate, the absence of sulfide, and
the low NPDOC values in the packer water samples suggested that sulfate reduction was not the dominant terminal
electron accepting process, rather Fe(lll) reduction might have been the dominant terminal electron accepting process.
Observed H2 levels in open samples from borehole BBC6 were also at levels supportive of reductive dechlorination.
Iron was a dominant microfracture surface element. Both Fe(ll) and Fe(lll) minerals were observed on the microfracture
surfaces. The spatial prevalence of Fe, as well as its situation in the top few nm of the microfracture surfaces, suggested
that Fe(lll) was readily available for iron-reducing bacteria.The spectroscopic characterization of the microfracture surfaces
pointed to Fe(lll) reduction as perhaps a dominant terminal electron accepting process in the microfracture network.
There was generally good agreement between SEM-EDAX, XRD, and XPS about identification of biogeochemically-
cycled C, S, and Fe within the microfracture surface precipitates and on their surfaces. However, the observed population
diversity could not be related to the speciation of any of the three elements on the microfracture surfaces. The spatial
heterogeneity of minerals was quite high on the microfracture surface. Mineral grain sizes were on the order of tens of
urn. While minerals may have been common to all observed microfracture surfaces, their relative spacing and proximity
to each other and to surface topography were quite varied. It may be that the biopatches that were observed with SEM
reflect more localized microbial population response to surface mineral speciation and therefore explain how a number
of terminal electron accepting processes could be occurring. Unfortunately, the level of spatial resolution of SEM, SEM-
EDAX, and XPS was not high enough to discern such spatial relationships though such relations are likely.
The presence of transformation products of dehalorespiration, as well as H2 concentrations, supported the role of
Dehalococcoides sp. in dehalorespiration in the microfracture network. Dehalorespiration was strongly correlated to the
presence of oxidized iron species on the microfracture. However, other means of TCE biodegradation, including aerobic
and anaerobic respiratory and cometabolic processes, as well as abiotic degradation processes cannot be excluded.
A number of follow-on activities are suggested. Methods to collect and characterize microfracture porewaters may
help to better describe terminal electron-accepting processes and may elaborate on real differences with packer water
sample composition. The relative absence of NOM in the system, as well as the concentration of NOM on microfracture
surfaces, deserve further examination. Understanding NOM bioavailability on microfracture surfaces may help to explain
the phylogenetic and metabolic diversity seen on the microfracture surfaces. Studies looking at partitioning of TCE and
transformation products to sorbed NOM under controlled isotherm conditions may help to better describe partitioning
with respect to microfracture surface organic carbon fractions, particularly if more sensitive SIMS methods (such as
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time of flight SIMS) are used. Understanding the spatial proximity of adhering microbes of terminal electron-accepting
process activity to minerals necessary to that terminal electron accepting process may help describe the heterogeneous
nature of terminal electron-accepting processes in the microfracture network and at the microscale within the formation.
Determining the extent of the microfracture specific surface area relative to that of the open fracture network would
help in determining the role of microfractures in terminal electron-accepting processes and biodegradative processes
within contaminated bedrock aquifers. The role of mass transfer between the open fracture system and the microfracture
network, as well as redox zonations that might develop relative to proximity to the open fractures, might be subjected
to mass transfer and reaction path modeling exercises. Additional work defining the complex microbial communities,
their metabolic interactions, and their possible syntrophy with respect toTCE degradation may help to explain observed
accumulations of transformation products. Further, the expression of enzymatic activity relative to terminal electron-
accepting processes and TCE biodegradation would help determine the metabolic activity on microfracture surfaces
and why these might differ from those occurring in the open fracture groundwaters.
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Acknowledgments
This work was supported by Cooperative Agreement CR 827878-01-0 from the U.S. EPA. Dr. Mary Gonsoulin
of the U.S. EPA, Robert S. Kerr Environmental Research Center in Ada, OK, was the Project Officer. Special
thanks to Dr. Frank Chapelle and Dr. Paul Bradley of the U.S. Geological Survey Stephenson Center in
Columbia, SC, for their work on H2 measurements at the BBC study site, to Mr. Dan Oblas at the University of
Massachusetts at Lowell for assistance with SIMS, to Ms. Nancy Cherim of the UNH Instrumentation Center for
assistance with SEM EDAX, and to Dr. John Wilson (U.S. EPA, Robert S. Kerr Environmental Research Center),
Mr. Richard Willey and Mr. Steve Mangion (U.S. EPA Region 1), and three anonymous reviewers for their technical reviews.
Particularthanks to Mr. Steve Vandegrift (U.S. EPA, Robert S. Kerr Environmental Research Center), Quality Assurance Officer.
We also thank the BBC Advisory Board (from the U.S. EPA: Dr. Mary Gonsoulin, Dr. John Wilson, and Mr. Richard Willey;
from the U.S. Geological Survey: Dr. Frank Chapelle, Dr. Ronald Harvey, Dr. Allen Shapiro, and Mr.Thomas Mack; from the
U.S. Air Force: Maj. Darrin Curtis and Mr. A. Ditto; and from the N.H. Department of Environmental Services:
Mr. John Regan). Also thanks to Ms. Kathy Tynsky of Computer Sciences Corporation for assisting in the preparation
of this report.
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