Microfracture Surface 

Characterizations: Implications 

for In Situ Remedial Methods in 

Fractured Rock

Bedrock Bioremediation Center 

Final Report
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

L.S. 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
ii

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.
iii

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, Director

Ground Water and Ecosystems Restoration Division

National Risk Management Research Laboratory
v

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 for TEM ..................................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 MIP of 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 DNA Sequencing & Analysis ...........................................................................................24

2.22 Data Quality .....................................................................................................................25
vi

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

Table of Contents, continued
vii

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,

and C .........................................................................................................................71
viii

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
ix

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

List of Figures, continued
x

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

TI 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

Abbreviations
E1

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 cis-DCE (280-440 μg/L) with some trans-DCE (26-48 μg/L), TCE (24-59 

μg/L), and VC (8-22 μg/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 (TI) 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 μm), a porosity of 

0.8%, and a permeability of < 1 μDarcy. 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 
E2

surface precipitates. Likely oxidized and reduced iron species were identified on the microfracture surfaces with XPS, 

including siderite (FeCO3), pyrrhotite (FeS), wüstite (FeO), goethite ( -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 μm. 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(II) (0.1 mg/L) and Fe(III) (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(II)/Fe(III). Estimated values were similar to those measured with a polished platinum inert 

redox probe and reference Ag/AgCl 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 μm in diameter by 2.0 μm 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(III) reduction might have been 

the dominant terminal electron accepting process. Iron was a dominant microfracture surface element. Both Fe(II) 

and Fe(III) 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(III) was available for iron-reducing 

bacteria. The spectroscopic characterization of the microfracture surfaces points to Fe(III) 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 μm. While minerals may have been common to all observed microfracture surfaces, their relative 
E3

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(III) 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(II) and Fe(III) 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. 
1

1.0 Introduction

The Bedrock Bioremediation Center (BBC) at the University of New Hampshire is a center specializing in multidisciplinary 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 cis-DCE 

(280-440 μg/L) with some trans-DCE (26-48 μg/L), TCE (24-59 μg/L), and VC (8-22 μg/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 (TI) 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(III) 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). 
2

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.

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.
3

Extent & Type Attitude Typical aperture 

width (mm)

Surface area with 

secondary mineralization

- Continuous 

 - Bedding

 - Cross bedding 

- Horizontal (0°)

- Vertical (90°)

- Steeply 

 inclined (> 60°)

- Moderately inclined 

 (30-60°)

- Low angle (< 30°)

> 1.0

> 0.8

> 0.6

> 0.4

< 0.4

- Little (< 10%)

- Some (10 to 30%)

- Extensive (> 30%)

- Discontinuous 

 - Bedding

 - Cross bedding 

 

- Horizontal (0°)

- Vertical (90°)

- Steeply 

 inclined (> 60°)

- Moderately inclined 

 (30-60°)

- Low angle (< 30°)

> 1.0

> 0.8

> 0.6

> 0.4

< 0.4

- Little (< 10%)

- Some (10 to 30%)

- Extensive (> 30%)

- Induced 

(mechanical break – likely 

restricted to core)

 - Bedding

 - Cross bedding 

- Horizontal (0°)

- Vertical (90°)

- Steeply inclined (> 60°)

- Moderately inclined

 (30-60°)

- Low angle (< 30°)

> 1.0

> 0.8

> 0.6

> 0.4

< 0.4

- Little (< 10%)

- Some (10 to 30%)

- Extensive (> 30%)

 

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:

 D = nrm Dw = nrmDrm [Eq. 1.1]

where Dw frees diffusivity in water (m2/yr), nrm is the effective porosity of the rock matrix (unitless), 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
4

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 al., 1994; Fredrickson & Onstott, 1996; Pedersen 1997, 2000; Fry et al., 1997; Chandler et al., 1998; Bekins et 

al., 1999), with only a limited number on competent bedrock, which comprises the majority of habitable subsurface 

environments (i.e.; Colwell et al., 1997; Fredrickson et al., 1997; Haveman et al., 1999; Onstott et al., 1998; Onstott 

et al., 2003). Composition of the microbial communities has been investigated by the use of enrichment cultures 

(Onstott et al., 1998; Lehman et al., 2001a) or molecular techniques in simulated models (Lehman et al., 2001b).

Microbes have been characterized in extreme systems in the deep subsurface. Onstott et al. (1998) characterized 

microbes from sidewall cores of rock 2800 m below ground surface in hydrocarbon reservoirs. Bacterial phospholipids 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 al. (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 - and 

 -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 -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 -Proteobacteria and depleted in -Proteobacteria. Lehman and colleagues suggested that 

microbial communities will be partially controlled by the surrounding geological media (Lehman et al., 2001b). 

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 μm 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 μm 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 
5

to the surface, formation temperature, and an interconnected fracture system. Cores with higher pore throat widths 

(> 1 μm), 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 μm), porosities (< 5%) and permeabilities (< 1 μDarcy) 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 frappieri 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 Felimited growth media, Pseudomonas sp. will preferentially attach to the Fe (III)-bearing minerals goethite ( -FeOOH) 

and hematite (Fe3O4) and use the Fe nutritionally (Forsythe et al., 1998). Dissimilatory iron-reducing bacteria will 

also preferentially attach to -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 pH 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)

3

OH) inclusions and solubilize the P for nutritional use (Rogers et 

al., 1998).

Dong et al. (2003) examined microbially mediated reduction of Fe(III) in illite. Shewanella putrefaciens CN32 and native 

illites from St. Peter Formation sandstone in Ogle County, IL, were used. The illite contained a minor component of 

goethite ( -FeOOH) in addition to fibrous illite. Mössbauer 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 
6

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 isopreneoxidizers 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(III)-reducing aquifer, addition of Fe(III) 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 (Löffler et al., 1996; Löffler et al., 2000; McCarty, 1997a; Sanford et al., 

1996; Chapelle et al., 2003). Microbial reductive dechlorination is fairly ubiquitous in anaerobic, PCE- and TCEcontaminated 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 
7

mildly reducing conditions such as nitrate or Fe(III) reduction; however, dechlorination of DCE to VC requires more 

strongly reducing conditions typical of methanogenesis (Vogel et al., 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 et al., 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 cis-DCE occurs during Fe(III)-reduction. Reductive dechlorination of cis-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 et al., 1991; de Bruin et al., 1992; Bouwer, 1994; MaymóGatell 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 cis-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 et al., 1998; Krumholz et al., 1996; Maymó-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 et al., 1992; DiStefano et al., 1991). Almost all of the dechlorinating bacteria 

that have been isolated reduce PCE or TCE only to cis-DCE (Gerritse et al., 1996; Scholz-Muramatsu et al., 1995). 

The anaerobe Dehalococcoides ethenogenes, however, completely dechlorinates PCE or TCE; in fact, it can also 

use cis-DCE, 1,1-DCE, and 1,2-DCA as electron acceptors (Maymó-Gatell et al., 1997; 1999).

Many dehalorespirers are gram-positive bacteria in the Clostridium-Bacillus subphylum or the and branches of the 

Proteobacteria (Holliger et al., 1999). D. ethenogenes is more phylogenetically dissimilar to the other dehalorespiring 

bacteria and has an Archaea-like cell wall structure (Maymó-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; 

Löffler et al., 1996; Magnuson et al., 1998; Maymó-Gatell et al., 1997; Miller et al., 1998; Neumann et al., 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 TCEcontaminated 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 et al. (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 

cis-DCE or VC; the subcultures came from three independent enrichments that completely dechlorinated PCE to 
8

Transformation Carbon 

Tetrachloride (CT)

Tetrachloroethene 

(PCE)

Trichloroethene 

(TCE)

1,1,1-Trichloroethane

(TCA)

Biotic-Aerobic

Primary substrate No No No No

Co-metabolism No No Yes Perhaps

Biotic-Anaerobic

Primary substrate Perhaps Yes Yes Perhaps

 Co-metabolism Yes Yes Yes Yes

 Hazardous 

 intermediates Yes Yes Yes Yes

Abiotic hydrolysis Perhaps No No Yes

Abiotic reduction or 

elimination Yes Yes Yes Yes

Chlorinated Solvent

Redox Environment

All environments Denitrification Sulfate reduction Methanogenesis

Carbon tetrachloride 

(CT)

TCA 1,1-DCE + 

CH3

COOH

CT Chloroform CT CO2

 + Cl- - 

1,1,1-Trichloroethane 

(TCA) - TCA 1,1-DCA TCA CO2

 + ClTetrachloroethene 

(PCE) - PCE 1,2-DCE PCE Ethene

Trichloroethene (TCE) - TCE 1,2-DCE TCE Ethene

ethene. The three subcultures completely dechlorinated cis-DCE and VC and could be transferred indefinitely in 

basal salts minimal medium with H2 as 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, MI. 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 

cis-DCE. PCE dechlorination in H2- treated microcosms occurred after a lag phase and after acetate had accumulated 

by H2 /CO2 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.)

Table 1.3. Environmental Conditions for Biological Reductive Dechlorination Reactions

(From McCarty, 1997b.)
9

Table 1.4. Properties of Some Direct Chlorinated Solvent Dechlorinators(Adapted in part from Gossett and Zinder, 1997.)

Organism Dechlorination reactions Electron donors Other electron acceptors Morphology Phylogenetic position References

Dehalobacterrestrictus

PCE, TCE cis-DCE H2 None Rod Gram +

Desulfotomaculumgroup

Holliger et al., 1998; 1999

Dehalospirillummultivorans

PCE, TCE cis-DCE H2, 

formate,pyruvate, etc.

Thiosulfate, nitrate,fumarate, etc.

Spirillum Proteobacteria Neumann et al., 

1994, 1998

Strain TT4B PCE, TCE cis-DCE Acetate None Rod ? Krumholz et al., 

1996

Enterobacteragglomerans

PCE, TCE cis-DCE Nonfermentable

substrates

O2, nitrate, etc. Rod Proteobacteria Sharma and

McCarty, 1996

Desulfitobacteriumsp. strain PCE1

PCE, TCE (cis-DCE)

o -chlorophenols

Lactate,

pyruvate,butyrate,ethanol, etc.

Sulfite, 

thiosulfate,fumarate

Curved rod Gram +

Desulfotomaculumgroup

Gerritse et al., 1996

Desulfitobacteriumfrappieri strain TCE1

PCE, TCE (cis-DCE) H2

formate,lactate,butyrate,crotonateethanol, etc.

Sulfite, thiosulfate,nitritefumarate

Curved rod Gram +

motile

Gerritse et al., 1999

Dehalococcoidesethenogenesstrain 195

PCE, others ethane H2 None Irregular coccus Novel eubacterium Maymó-Gatell et al., 

1997

Dehalococcoidessp. strain BAV1

VC, cis-DCE, trans-DCE, 

1,1-DCE, others ethene

H2 None Non-motile disc ? He et al., 2003

Desulfuromonas michiganensis sp. nov. (Strain BB1, 

BRS1)

PCE cis-DCE Acetate, lactate, 

pyruvate, succinate, malate,fumarate

None Short, ovoid 

rods (some clubshaped rods seen in early stationary phase when grown on fumarate)

Desulfuromonascluster of Proteobacteria

Sung et al., 2003
10

1.6 Determination of Likely Terminal Electron Accepting Processes

Lovley, Chapelle and colleagues (Lovley and Phillips, 1987; Lovley and Goodwin, 1988; Chapelle et al., 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), NO3

-

, Fe(III), SO4

2-, CO2(g)), (ii) the production of metabolic end products (e.g., CO2(g), N2(g), 

Fe(II), 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(II), SO4

2-, 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, cis-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 chloroethene 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(III) 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-type 

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-cis-DCE occurred. They used phylogenetic 

analysis of the 16S rDNA amplicons to show Dehalococcoides sequences formed a unique 16S rDNA group. Three 
11

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 al.(1990), Coyne and McKeever (1990), and 

Calas and Hawthorne (1988). These methods are also thoroughly described in the Materials and Methods section 

of this report.

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.
12

Figure 2.1. Cross section through BBC site.

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 μg/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.
13

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 TI 

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.

Figure 2.2. Plan view of borehole locations at Site 32.
14

Microfracture 

#

Well

Core interval

/ fracture 

depth, ft 

Cluster

Microfracture exposed 

surface visual 

appearance after removal 

from the core

Extent Type Attitude

Aperture 

width in mm

(aspect 

ratio, z/x)

Exposed 

surface area 

with secondary

mineralization

MF01 BBC5 70.5-75.5 

/ 71.5 1

Wetted, Olive Green 

Precipitate, Flakey, 

Homogenous, Some Pyrite

Continuous Cross 

Bedding Low Angle > 0.4

(< 0.003)

Extensive

 (> 30%)

MF02 BBC5 70.5-75.5 

/ 73.0 1

Wetted, White Precipitate, 

Molted/Patchy, Some 

Flakey (Soft), No Pyrite

Continuous Bedding Steeply 

Inclined

< 0.4 

(< 0.001)

Some

(10-30%)

MF03 BBC5 70.5-75.5 

/ 73.0 1

Wetted, Fine Grained Grey 

Black Surface, 

No Apparent Precipitate, 

No Pyrite

Continuous Bedding Steeply 

Inclined

< 0.4

(< 0.001)

Little

(< 10%)

MF04 BBC5 95.5-100.2

 / 97.0 2

Wetted, Fine Grained 

Grey-Black Surface With 

White Precipitate Traces, 

No Pyrite

Continuous Bedding Low Angle > 1 

(< 0.006)

Little

(< 10%)

MF05 BBC5 119.9-124.7

 / 122.7 3

Wetted, Chalky Slate Blue 

Precipitate, Some Quartz 

Veins, Homogenous, No 

Pyrite

Discontinuous Cross

Bedding 

Steeply 

Inclined

> 0.6

(< 0.004)

Extensive

(> 30%)

MF06 BBC5 119.9-124.7 

/ 122.0 3

Wetted, Shiny GreenYellow Precipitate, 

Homogenous, No Pyrite

Continuous Bedding Moderately 

Inclined

> 0.6

(< 0.004)

Extensive

(> 30%)

MF07 BBC5 119.9-124.7

 / 121.5 3

Wetted, Olive Green-Black 

Precipitate, Very Fine 

Grained, No Pyrite

Continuous Cross

Bedding Low Angle > 1 

(< 0.006)

Little

(< 10%)

MF08 BBC6 107.39-112.14 

/ 112 4 Wetted, White Precipitate, 

Homogenous, No Pyrite Continuous Bedding Horizontal > 0.4 

(< 0.003)

Extensive

(> 30%)

MF09 BBC6 107.39-112.14 

/ 107.4 4 Wetted, White Precipitate, 

Homogenous, No Pyrite Discontinuous ? ? > 0.8 

(< 0.005)

Extensive

 (> 30%)

MF10 BBC6 112.14-116.94 

/ 113.31 4 Wetted, White Precipitate, 

Homogenous, No Pyrite Continuous ? Moderately 

Inclined

> 0.4

(< 0.003)

Extensive

(> 30%)

MF11 BBC6 112.14-116.94 

/ 116.72 4 Wetted, White Precipitate, 

Homogenous, No Pyrite Continuous ? Steeply Inclined

< 0.4

(< 0.001)

Extensive

(> 30%)

Microfractures from borehole 

B B C 5 we r e c o l l e c t e d 

on December 20, 2001. 

Microfractures from borehole 

BBC6 were collected on 

September 24, 2002. The 

locations of these microfractures 

(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
15

Microfracture 

#

Well Cluster 

MIP

of 

HR

SEM

of 

MF

SEMEDAX

spatial 

mapping

of 

HR/MF

Petrography 

of

HR/MF

XRD

of

HR/MF

TEM

of 

MF

SIMS

of

MF

XPS

of

MF

Packer 

sampling

in MF

regions

PCR Primers/

DGGE/

gene 

sequencing

from MF

MF01 BBC5 1 General 

host 

rock 

samples 

from 

BBC5

Yes MF HR HR/MF - - No No Yes

MF02 BBC5 1 Yes MF HR/MF HR/MF - - Yes No Yes

MF03 BBC5 1 Yes MF HR HR - Yes Yes No Yes

MF04 BBC5 2 Yes MF HR HR/MF - - Yes Yes Yes

MF05 BBC5 3 Yes MF HR HR - - Yes Yes Yes

MF06 BBC5 3 Yes MF HR/MF HR/MF - - Yes Yes Yes

MF07 BBC5 3 Yes HR/MF HR HR/MF - - Yes Yes Yes

MF08 BBC6 4 None Yes MF HR HR/MF - - Yes No -

MF09 BBC6 4 Yes HR/MF HR HR/MF - - Yes No -

MF10 BBC6 4 Yes MF HR HR/MF - - Yes Yes -

MF11 BBC6 4 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

Table 2.2. Analytical Methods Applied to the Host Rock and Microfracture Samples

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
16

and fitted into spectroscopic instruments for analysis. Consequently, the microfractures 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 microfractures frequently would not break apart after repeated hammer 

blows. 

Subsequently, partially mineralized, partially sealed microfractures 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. 

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 watersoluble 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.

Figure 2.4. Schematic depiction of microfracture-type sampling.
17

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 μm. 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 0.1M cacodylate 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.

Figure 2.5. Analytical scheme.
18

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 μm to sub-μm 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 for TEM

Calcite-dominated surface precipitate minerals from microfracture MF011 were readily removed from the microfracture 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 μm 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).
19

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, K 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 μm in diameter or that phase 

size is less than 10 μm. 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. Computeraided 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 μm) and loaded 
20

on a glass slide. XRD was performed with a Rigaku Geigerflex rotating anode goniometer using a Cu-K source 

(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 μm. 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 Torr or 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/Al 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 et al., 2002).

The microfracture face of each sample was examined. A non-monochromated Mg K 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 Al2p, 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.
21

Additionally, binding energy values for Ca, Mg, O and C in calcite and dolomite were obtained from the literature 

(Baer et al., 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 (CaAl2Si4O16 • 6H2O) were also obtained from the literature (Barr, 1983). Binding 

energy values for Fe and O in goethite ( -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 - (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 13 V. 

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 = -4 cos /p [Eq. 2.1]

where d is pore diameter (nm), is surface tension of the Hg (N/m), 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 
22

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/AgCl reference electrode checked with two reference solutions made of 

K4Fe(II)(CN)6 • 3H2O and K3Fe(III)(CN)6), alkalinity (titration), soluble Fe2+ (Chemetrics Field Kit), and sample filtration 

(0.22 μm) 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 equilibriumcontrolled 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).
23

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 NaCl; 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 μm 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 UltraCleanTM 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. 
24

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 340F and 915R (Øvreas et al., 1997; Amann et al., 1995) were used to 

amplify the V3 region using 1 μL 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 et al., 1985; Amann et al., 1990), dehalorespirers 

including D. ethenogenes and Dehalococcoides sp. (strain FL2) with 728F and 1172R primers, Desulfuromonas group, 

including Desulfuromonas sp. (strain BB1) and D. chloroethenica with 205F and 1033R primers (Löffler 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 μL reaction volumes, using 0.5 μM 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 15 s, primer extension at 72°C for 2 min 15 s 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 DcodeTM 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 μg/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 (Röling 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). 
25

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 (iii) 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 
26

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 μm (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 μm (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 μm 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).
27

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 ( ), 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, , 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), Cl-, SO4

2-, 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 DNA extracted from 

mixed microbial populations using primers specific for that gene. Detection limits are around 0.1 μg of DNA. 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 1 μg template DNA, with a positive 

DNA control (certified DNA strands from E. coli or 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 (Röling et al., 2001). Only two fractures were shown 
28

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.

DNA 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.nlm.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 122.7 ft) 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 μm to 100 μm) 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 3.1a; 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.
29

Table 3.1. Summary Description of Surface Precipitate Morphologies

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).

Microfracture # Surface Description

MF01 Fine structured web-like precipitation with large quartz grains distributed throughout.

MF02 Host rock visible with angular granular materials dispersed over surface. Grains had a size 

range of 100 μm to less than 1 μm.

MF03 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.

MF04 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.

MF05 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. 

MF06 Flakey appearance similar to precipitate on microfracture MF03. 

MF07 Similar to microfracture MF05.

MF08 Similar to microfracture MF02. 

MF09 Areas of flakey formations and angular granules resting on a smoother base. 

MF10 Similar to microfracture MF05.

MF11 Host rock exposed with both angular granules and web-like formations visible.
30

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 μm 

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-Al-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. 

Figure 3.2. Typical EDS elemental spatial map in X-Y plane for microfracture MF03. Each window is 250 by 200 μm.

(a) Si-Al-Mg-K-Fe-O, (b) Ca-O, (c) Ti, (d) Si-O.
31

Table 3.2. Summary Description of Element Association in Spatial Maps

Microfracture # Dominant Phases Minor Phases Microfracture # Dominant Phases Minor Phases

MF01 Si-Al-Mg-O Si-O

Si-Mg-Al-K-O

Ca-O

MF07 Si-Al-Fe-O Si-O

Si-Al-K-O

Si-Al-Na-O

Ca-O

MF02 Si-Al-K-O

Si-Al-K-Mg-O

Ca-O

Si-O

Fe-S

MF08 Si-O

Si-Al-K-O

Ca-O

Si-Al-O

Fe-O

MF03 Si-Al-K-O

Si-Al-K-Mg-O

Ca-O

Si-Al-K-Mg-Fe-O

Ti

MF09 Si-Al-K-O

Si-K-O

Ca-Mg-Fe-O

Si-Al-Na-O

Fe-S

MF04 Si-Al-K-O

Si-Al-K-Mg-O

Al-Mg-Fe-O

Si-O

Ca-O

Fe-S

Ti

MF10 Si-Al-K-O

Si-Al-K-Fe-O

Si-Al-K-Fe-Ca-O

Si-O

Ti

MF05 Si-Al-Fe-O

Si-Fe-O

Fe-S

Si-O

Al-K-O

Al-K-Na-O

Ca-O

Ca-Mg-O

Fe-S

Ti

MF11 Si-Al-Mg-Fe-O

Si-Al-K-Mg-Fe-O

Ca-O

Si-O

Si-Al-K-O

Si-Al-Na-O

Si-Al-Fe-O

MF06 Si-O

Si-Al-K-O

Si-Al-K-Na-O

Ca-Mg-Fe-O

Si-O

Fe-O

Ti
32

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. 
33

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). 
34

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 μm in length 

and 0.5 –1.0 μm 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 < 10 2 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.

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.
35

Figure 3.6. TEM micrographs of stalked morphologies present in calcite precipitates on microfracture MF11. The

cells appear to have inclusion bodies.

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 μm in diameter, 1.5 to 2.0 μm 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 μm diameter electron-opaque and 0.3 μm 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 μm in 

length. 

(a) (b)

(c) (d)

2.0 μm

2.0 μm

1.0 μm

1.0 μm
36

Figure 3.7. TEM micrographs of spirillum morphologies in calcite precipitates in microfracture MF11. The cells

appear to have inclusion bodies.

(a) (b)

(c) (d)

2.0 μm

2.0 μm 1.0 μm

0.5 μm
37

Figure 3.8. TEM micrographs of filamentous morphologies in calcite precipitates in microfracture MF11. The cells

appear to have inclusion bodies.

(a) (b)

(c) (d)

2.0 μm 2.0 μm

2.0 μm

2.0 μm
38

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).

(a) (b)

(c) (d)

0.5 μm

1.0 μm

1.0 μm

1.0 μm
39

Figure 3.10 Petrographic thin 

section of Kittery metasandstone. 

The image shows three 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.

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.

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).
40

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 • nH2O) 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.
41

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-crystallized 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 structures 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.
42

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 NaAlSi3O8 with minor KAlSi3O8, 0-25%); carbonates (CaCO3, 

CaMg(CO3)2, FeMgCO3, 0-32%); biotite (K2(Mg,Fe)6Al2Si6O20(OH,F)4, 0-45%) and/or chlorite ((Mg,Al,Fe)3(Si,Al)4O10(OH)2

•(Mg,Al,Fe)3(OH)6), 0-30%); white mica (KAl2(AlSi3O10)(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

Microfracture 

#

Apatite

(% area)

Biotite

(% area)

Carbonate

(% area)

Chlorite

(% area)

Feldspar

(% area)

Opaques

(% area)

Quartz

(% area)

White Mica

(% area)

Zircon

(% area)

MF01 Trace 15 10 5 20 5 40 5 Trace

MF02 15 20 10 10 5 35 Trace

MF03 Trace 25 15 5 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 5 30 15 1-2 40 10

Mineral Formulas (Nesse, 2003):

Apatite – Ca5

(PO4)

3

(F,Cl,OH)

Biotite – K2

(Mg,Fe)6Al2Si6O20(OH,F)4

Carbonate – primarily CaCO3, others include CaMg(CO3)

2

, FeMg(CO3)

2

Chlorite – (Mg,Al,Fe)3(Si,Al)4O10(OH)2*(Mg,Al,Fe)3(OH)6

Feldspar – (Na,Ca)(Al,Si)2Si2O8 ; may include minor KAlSi3O8

Opaques – FeSx

Quartz – SiO2

White Mica – KAl2(AlSi3O10)(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 (CaCO3, CaMg(CO3)2, FeMgCO3, 5-50%), 

chlorites ((Mg,Al,Fe)3(Si,Al)4O10(OH)2 • (Mg,Al,Fe)3(OH)6), 0-15%), and quartz (SiO2, 35-95%). No pyrites were found 

in the surface precipitates.
43

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.
44

Table 3.4. Mineral Phases Identified by Petrography in Microfracture Surface Precipitates

Microfracture #Carbonate 

(% area)

Chlorite

(% area)

Quartz

(% area)

Opaque

(% area)

MF02 50 15 35 Trace

MF06 35 65

MF11 5 95

Mineral Formulas (Nesse, 2003):

Carbonate – primarily CaCO3, others include CaMg(CO3)

2

, FeMg(CO3)

2

Chlorite – (Mg,Al,Fe)3(Si,Al)4O10(OH)2*(Mg,Al,Fe)3(OH)6

Quartz – SiO2

Opaque – FeSx

Trace = trace amount; accessory mineral

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 μm.

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-Al-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-Al-K-O phases.
45

Figure 3.16 Typical raw diffractogram.

Figure 3.17 Typical diffractogram after background removal and smoothing.

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. 
46

Figure 3.18 Typical peak ID as determined by search match routine. The right hand Y axis is relative intensity (%).

Figure 3.19 Diffractogram of host rock from microfracture MF07.
47

Table 3.5. Summary of Crystalline Minerals Identified in Host Rock Samples

Mineral Name (Formula)

Microfracture #, 

Mineral Phase Relative Abundance (Search-Match FOM)

MF01 MF02 MF04 MF06 MF07 MF08 MF09 MF10 MF11

Quartz (SiO2 ) 3.0 2.2 0.6 0.6 3.0 2.6 0.7 1.3 3.0

Clinochlore ((Mg,Fe2+,Fe3+,Mn,Al,)12 [(Si,Al)8

O20 ] (OH)16 ) 10.8 3.4 10.7 10.8 8.6 9.0

Albite ((Na,Ca)Al(Si,Al)3

O8 ) 12.6 13.2 13.4 4.6 5.4 9.1

Potassium Mica (KAl3

Si3O11) 2.6 3.6 

Illite ((K,H3

O)Al2Si3 AlO10(OH)2 ) 2.9 2.1 

Potassium Manganese Oxide Hydrate (K0.5Mn2

O4 ) 7.4 

K(Mg,Al)2.04(Si3.34 Al0.66 )O10(OH)2 12.4 12.5 

(Mg, Fe2+, Fe3+,Mn,Al)12 [(Si,Al)8

O20 ] (OH)16 14.7 10.9 

Zeolite (Na2

O-SiO2- Al2O3 ) 15.0 

Lizardite Aluminian ((Mg,Fe2+,Fe3+,Mn,Al)12 [(Si,Al)8

O20 ](OH)16 ) 16.0 

Chamosite ((Fe,Al,Mg)6

(Si,Al)4O10(OH)8 ) 19.2 

Anorthoclase ((Na,K)(Si3

Al)O8 ) 19.1 

Anorthite (Na[AlSi3

O8 ]-Ca[Al2Si2O8 ]) 17.4 

Sanidine (K2

(Mg,Fe2+)

6

-4(Fe3+,Al,Ti)0-2[Si6-5Al2-3O20 ](OH,F)4 ) 16.3 5.6 

Baratovite (Li2

KCa8Ti2Si12O37F) 18.2 

Iron Silicate Hydroxide (Fe3

Si2O5(OH)4 ) 14.0 

Muscovite ((K,Na)(Al,Mg,Fe)2

(Si3.1Al0.9 )O10(OH)2) 15.1 

Figure 3.20 Diffractogram of microfracture surface precipitate from microfracture MF07.

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)Al(Si,Al)3O8).
48

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. 

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 (CaCO3

, CaMg(CO3)

2

, 

FeMgCO3), chlorite ((Mg,Al,Fe)3(Si,Al)4O10(OH)2 • (Mg,Al,Fe)3(OH)6), and quartz (SiO2).

Table 3.6. Microfracture Surface Precipitate Candidate Minerals Based on XRD

Mineral Name (Formula)

Microfracture Number,

Mineral Phase Relative Abundance (Search-Match FOM)

MF01 MF02 MF04 MF06 MF07 MF08 MF09 MF10 MF11

Calcite

CaCO3

Major

(18.2)

Major

(1.3)

Major

(6.2)

Major

(6.0)

Major

(5.7)

Magnesian Calcite

(Ca,Mg)CO3

Major

(14.3)

Dolomite

CaMg(CO3)2

Major

(8.7)

Major

(2.8)

Kutnohorite

Ca(Mn,Mg)(CO3)2

Major

(8.8)

Ankerite

Ca(Fe,Mg)(CO3)2

Major

(16.9)

Major

(4.7)

Quartz

SiO2

Major

(1.4)

Major

(1.0)

Major

(3.6)

Major

(6.3)

Major

(3.1)

Sanidine

K(AlSi3)O8

Major

(7.2)

Major

(4.7)

Major

(7.4)

Clinochlore

Mg3Mn2AlSi3AlO10(OH)8

Minor

(14.3)

Major

(8.8)

Microcline

KAlSi3O8

Minor

(16.4)

Albite

NaAlSi3O8

Major

(9.1)

Calcian Albite

(Na,Ca)Al(Si,Al)3O8

Major

(18.6)

Anorthite

(Ca,Na)(Si,Al)4O8

Major

(17.0)

Sodium Aluminum Silicate

NaAlSiO4

Major

(20.4)

Potassium Aluminum Silicate

K1+xxAl1+xSi1-xO4

Major

(17.9)

Potassium Mica

KAl3Si3O11

Major

(17.1)

Major

(3.2)

Illite

(K,H3O)Al2Si3AlO10(OH)2

Major

(1.9)

Badeleyite

ZrO2

Major

(10.8)

Aluminum Iron Zirconium

Al1.65Fe0.35Zr

Minor

(19.0)

Wustite

FeO

Minor

(19.9)
49

Figure 3.21 Typical XPS low resolution survey scan of microfracture MF02.

Figure 3.22 Typical component curve fit exercise for the C1s photoelectron from a high resolution scan for 

microfracture MF02.

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 microfracture 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 

microfracture MF02. Figure 3.22 shows the curve fitting of the C1s photoelectron data from microfracture MF02. The 

example minerals identified by the NIST database are indicated for the fitted peaks. 
50

Table 3.7. Microfracture MF02 - Candidate Minerals by XPS

Element Binding 

Energy (eV)

Peak

Area % Candidates (Range +/- 0.3 eV)

Mol Sieve, Ca form (73.9-74.75)

Al2

O3 (71.47-77.3)

Al2p 74.15 100.0 Al0.2Si0.8O2.2 (74.4)

284.80 71.7 Adventitious Carbon (284.8)

286.53 4.8 NOM Ether or Alcohol 

(286.4-286.6)

287.76 7.6 NOM Ketone or Aldehyde 

(287.5-287.7)

CaCO3

 (288.2-290.4)

CaMg(CO3

)

2

 (289.8)

C1s 289.38 15.9 NOM Carboxylic (289.1-289.3)

CaCO3 (346.6-347.7)

CaO (346.1-347.3)

346.83 46.1 CaSiO3

 (346.7-347.3)

CaCO3 (346.6-347.7)

CaMg(CO3

)2 (347.3)

CaO (346.1-347.3)

347.54 15.3 CaSiO3

 (346.7-347.3)

Ca2p 348.38 5.3 Mol Sieve, Ca form 

(347.9-348.6)

Fe3

O4 (708.1-711.4)

708.77 22.7 FeS2

 (706.6-708.6)

Fe3O4 (708.1-711.4)

FeO (709.2-710.7)

709.84 22.5 Fe2

O3 (709.9-711.6)

Fe3O4 (708.1-711.4)

Fe2O3 (709.9-711.6)

FeS (710.3-713.6)

Fe(OH)O (710.8-711.8)

Fe2

O3*nH2O aged HFO 

(710.7-711.1)

FeO(OH)*nH2

O (711.1-711.3)

711.22 35.9 Fe2

O3*nH2O fresh HFO 

(711.3-711.9)

Fe2p 714.14 18.8 Unidentified

Element Binding 

Energy (eV)

Peak

 Area % Candidates (Range +/- 0.3 eV)

FeO (529.8-530.1)

Fe2

O3 (529.5-530.3)

Fe3O4 (529.1-530.1)

CaO (529.4-531.3)

530.14 13.8 Al2

O3 (530.0-532.7)

CaO (529.4-531.3)

CaCO3 (530.5-531.5)

Al2

O3 (530.0-532.7)

530.88 52.8 Mol Sieve, Ca form 

(531.05-532)

CaCO3 (530.5-531.5)

CaMg(CO3

)

2

 (531.7)

CaSiO3 (531.5-531.6)

Al2O3 (530.0-532.7)

Fe2

(SO4)3 (531.6-532.2)

531.76 28.8 SiO2

 (532-534.3)

Al2O3 (530.0-532.7)

O1s 532.82 4.6 SiO2

 (532-534.3)

Mol Sieve, Ca form (101.8-102.8)

102.13 59.5 CaSiO3

 (102.36)

Mol Sieve, Ca form (101.8-102.8)

SiO2 (103.2-104.1)

Si2p 102.95 40.5 Al0.2Si0.8O2.2 (103.2)

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.
51

Table 3.8. Microfracture MF03 - Candidate Minerals by XPS

Element Binding 

Energy (eV)

Peak 

Area % Candidates (Range +/- 0.3 eV)

Al2

O3 (71.47-77.3)

Mol Sieve, Ca form (73.9-74.75)

Al2

OSiO4 (74.58-74.8)

74.54 60.6 Al0.2Si0.8O2.2 (74.4)

75.20 20.3 Al2O3 (71.47-77.3)

Al2p 75.92 19.1 Al2

O3 (71.47-77.3)

284.80 52.6 Adventitious Carbon (284.8)

286.39 27.7 NOM Ether or Alcohol

 (286.4-286.6)

288.06 7.5 NOM Amide (288.4-288.5)

CaCO3

 (288.2-290.4)

CaMg(CO3

)

2

 (289.8)

C1s 289.82 12.2 NOM Carboxylic (289.1-289.3)

Fe3

O4 (708.1-711.4)

709.32 20.3 FeO (709.2-710.7)

Fe3

O4 (708.1-711.4)

FeO (709.2-710.7)

Fe2

O3 (709.9-711.6)

FeS (710.3-713.6)

Fe(OH)O (710.8-711.8)

Fe2

O3*nH2O aged HFO 

(710.7-711.1)

710.93 30.1 FeO(OH)*nH2

O (711.1-711.3)

712.22 20.3 FeS (710.3-713.6)

713.93 20.1 Unidentified

Fe2p 716.25 9.1 Unidentified

Element Binding 

Energy (eV)

Peak 

Area % Candidates (Range +/- 0.3 eV)

CaCO3 (530.5-531.5)

CaO (529.4-531.3)

CaSiO3

 (531.5-531.6)

Al2O3 (530.0-532.7)

Al2OSiO4 (531.3-531.88)

Mol Sieve, Ca form (531.05-532)

531.36 84.6 Fe(OH)O (530.1-531.8)

O1s 533.08 15.4 SiO2

 (532-534.3)

CaSiO3

 (102.36)

Mol Sieve, Ca form 

(101.8-102.8)

102.34 12.3 Al2

OSiO4 (102.6-103)

Al2OSiO4 (102.6-103)

Al0.2Si0.8O2.2 (103.2)

103.32 32.7 SiO2

 (103.2-104.1)

Si2p 104.32 55.0 SiO2

 (103.2-104.1)
52

Table 3.9. Microfracture MF04 - Candidate Minerals by XPS

Element Binding 

Energy (eV)

Peak 

Area % Candidates (Range +/- 0.3 eV)

Al2

O3 (71.47-77.3)

Mol Sieve, Ca form (73.9-74.75)

Al2

OSiO4 (74.58-74.8)

74.82 60.9 Al2

(SO4)3 (74.9)

Al2p 75.69 39.1 Al2

O3 (71.47-77.3)

284.80 50.3 Adventitious Carbon (284.8)

285.46 31.1 NOM Carboxylic Neighbor 

(285.4-285.6)

286.26 12.7 NOM Ether or Alcohol 

(286.4-286.6)

287.78 4.3 NOM Ketone or Aldehyde 

(287.5-287.7)

CaCO3

 (288.2-290.4)

C1s 289.49 1.6 NOM Carboxylic (289.1-289.3)

CaCO3 (346.6-347.7)

346.62 10.3 CaO (346.1-347.3)

CaMg(CO3

)

2 (347.3)

CaCO3 (346.6-347.7)

347.56 52.4 CaSO4

 (347.6-348.4)

Mol Sieve, Ca form 

(347.9-348.6)

Ca2p 348.64 37.4 CaSO4

 (347.6-348.4)

Fe2

O3 (709.9-711.6)

Fe3

O4 (708.1-711.4)

FeO (709.2-710.7)

FeS2 (706.6-708.6)

710.50 49.0 FeS (710.3-713.6)

713.26 30.1 FeS (710.3-713.6)

Fe2p 716.42 20.9 Unidentified

Element Binding 

Energy (eV)

Peak 

Area % Candidates (Range +/- 0.3 eV)

FeO (529.8-530.1)

Fe3

O4 (529.1-530.1)

Fe2O3 (529.5-530.3)

CaO (529.4-531.3)

CaCO3 (530.5-531.5)

530.43 6.2 Al2

O3 (530.0-532.7)

CaO (529.4-531.3)

CaCO3 (530.5-531.5)

CaMg(CO3

)2 (531.7)

Al2O3 (530.0-532.7)

Al2OSiO4 (531.3-531.88)

Mol Sieve, Ca form (531.05-532)

Al2O3 (530.0-532.7)

SiO2 (532-534.3)

SiO (532.5)

CaSO4 (532-532.9)

532.49 50.8 Al2

(SO4)

3

 (532.4)

O1s 533.49 18.1 SiO2

 (532-534.3)

SiO (101.7-102.7)

101.98 12.4 Mol Sieve, Ca form

 (101.8-102.8)

SiO (101.7-102.7)

Mol Sieve, Ca form 

(101.8-102.8)

102.84 37.4 Al2

OSiO4 (102.6-103)

Si2p 103.70 50.2 SiO2

 (103.2-104.1)
53

Table 3.10. Microfracture MF05 - Candidate Minerals by XPS

Element Binding 

Energy (eV)

Peak 

Area % Candidates (Range +/- 0.3 eV)

Al2

O3 (71.47-77.3)

Mol Sieve, Ca form (73.9-74.75)

Al2

OSiO4 (74.58-74.8)

Al2p 74.45 100.0 Al0.2Si0.8O2.2 (74.4)

284.80 82.1 Adventitious Carbon (284.8)

286.39 12.9 NOM Ether or Alcohol

(286.4-286.6)

CaCO3

 (288.2-290.4)

FeCO3 siderite (289.6)

C1s 289.45 5.1 NOM Carboxylic (289.1-289.3)

CaCO3 (346.6-347.7)

CaMg(CO3

)

2 (347.3)

CaO (346.1-347.3)

347.57 69.8 CaSiO3

 (346.7-347.3)

Ca2p 348.47 30.2 Mol Sieve, Ca form

(347.9-348.6)

Fe3

O4 (708.1-711.4)

709.32 7.8 FeO (709.2-710.7)

FeCO3

 siderite (710.4-710.7)

Fe2O3 (709.9-711.6)

Fe3O4 (708.1-711.4)

FeO (709.2-710.7)

710.88 87.4 Fe(OH)O (710.8-711.8)

Fe2p 712.41 4.8 FeSO4

 (711.2-713.6)

Element Binding 

Energy (eV)

Peak 

Area % Candidates (Range +/- 0.3 eV)

FeO (529.8-530.1)

Fe3

O4 (529.1-530.1)

Fe2O3 (529.5-530.3)

FeOOH (529.7-531.7)

529.66 4.6 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)

Al2O3 (530.0-532.7)

Al2

OSiO4 (531.3-531.88)

531.44 69.5 Mol Sieve, Ca form (531.05-532)

FeCO3

 siderite (532.1)

FeSO4

 (532.3)

Al2O3 (530.0-532.7)

Mol Sieve, Ca form (531.05-532)

SiO2 (532-534.3)

SiO (532.5)

CaSO4 (532-532.9)

532.31 22.1 Al2

(SO4)

3

 (532.4)

O1s 533.80 3.7 SiO2

 (532-534.3)

FeSO4

 (168.7-168.8)

Fe2

(SO4)

3

 (168.6-169.1)

FeS2 (161.7-162.9)

168.72 33.2 CaSO4

 (169-170.1)

Fe2(SO4)

3

 (168.6-169.1)

Al2

(SO4)

3

 (169.5)

S2p 169.41 66.8 CaSO4

 (169-170.1)

SiO (101.7-102.7)

Mol Sieve, Ca form

(101.8-102.8)

CaSiO3

 (102.36)

102.06 7.8 Al2

OSiO4 (102.6-103)

Al2OSiO4 (102.6-103)

Al0.2Si0.8O2.2 (103.2)

103.11 54.1 SiO2

 (103.2-104.1)

103.52 16.3 SiO2 (103.2-104.1)

Si2p 103.94 21.8 SiO2

 (103.2-104.1)
54

Table 3.11. Microfracture MF06 - Candidate Minerals by XPS

Element Binding 

Energy (eV)

Peak 

Area % Candidates (Range +/- 0.3 eV)

Al2

O3 (71.47-77.3)

Mol Sieve, Ca form (73.9-74.75)

Al2

OSiO4 (74.58-74.8)

Al0.2Si0.8O2.2 (74.4)

74.75 64.6 Al2

(SO4)3 (74.9)

Al2p 75.65 35.4 Al2

O3 (71.47-77.3)

284.80 57.6 Adventitious Carbon (284.8)

285.66 22.4 NOM Carboxylic Neighbor 

(285.4-285.6)

286.92 10.4 NOM Ether or Alcohol

(286.4-286.6)

288.24 4.2 NOM Amide (288.4-288.5)

CaCO3

 (288.2-290.4)

C1s 289.45 5.3 CaMg(CO3

)

2 (289.8)

CaCO3 (346.6-347.7)

CaMg(CO3

)

2 (347.3)

CaO (346.1-347.3)

347.32 26.7 CaSO4

 (347.6-348.4)

Mol Sieve, Ca form

(347.9-348.6)

348.13 52.9 CaSO4

 (347.6-348.4)

Ca2p 349.09 20.4 Unidentified

Fe(OH)O (711-711.8)

710.88 69.8 FeS (710.3-713.6)

Fe2p 714.67 30.2 Unidentified

Mg2p 50.51 100.0 CaMg(CO3

)

2

 (50.5)

Element Binding 

Energy (eV)

Peak 

Area % 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)

Al2

O3 (530.0-532.7)

531.14 21.1 Al2

OSiO4 (531.3-531.88)

Al2(SO4)

3

 (532.4)

Al2

O3 (530.0-532.7)

Al2

OSiO4 (531.3-531.88)

CaSO4 (532-532.9)

Fe(OH)O (530.1-531.8)

Mol Sieve, Ca form (531.05-532)

532.10 54.6 SiO2

 (532-534.3)

Al0.2Si0.8O2.2 (532.9)

CaSO4 (532-532.9)

533.05 20.6 SiO2

 (532-534.3)

O1s 534.38 3.7 SiO2

 (532-534.3)

101.80 6.8 Mol Sieve, Ca form

(101.8-102.8)

Mol Sieve, Ca form

(101.8-102.8)

102.87 44.0 Al2

OSiO4 (102.6-103)

103.63 41.7 SiO2 (103.2-104.1)

Si2p 104.69 7.5 Unidentified
55

Table 3.12. Microfracture MF07 - Candidate Minerals by XPS

Element Binding 

Energy (eV)

Peak 

Area % Candidates (Range +/- 0.3 eV)

Fe2

O3 (529.5-530.3)

Fe3

O4 (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)

530.39 6.0 Al2

O3 (530.0-532.7)

CaCO3 (530.5-531.5)

CaMg(CO3

)2 (531.7)

Fe(OH)O (530.1-531.8)

Al2O3 (530.0-532.7)

531.64 54.8 Al2

OSiO4 (531.3-531.88)

SiO2 (532-534.3)

532.58 35.0 Al2

OSiO4 (531.3-531.88)

O1s 534.07 4.3 SiO2

 (532-534.3)

FeSO4

 (168.7-168.8)

Fe2

(SO4)

3

 (168.6-169.1)

169.01 49.6 CaSO4

 (169-170.1)

S2p 170.03 50.4 CaSO4

 (169-170.1)

SiO2

 (103.2-104.1)

Al0.2Si0.8O2.2 (103.2)

Al2OSiO4 (102.6-103)

Si2p 103.08 100.0 Mol Sieve, Ca form

(101.8-102.8)

Element Binding 

Energy (eV)

Peak 

Area % Candidates (Range +/- 0.3 eV)

Al2

O3 (71.47-77.3)

Mol Sieve, Ca form (73.9-74.75)

Al2

O3 (71.47-77.3)

Al2(SO4)3 (74.9)

74.07 50.0 Mol Sieve, Ca form (73.9-74.75)

Al2p 74.93 50.0 Al2

OSiO4 (74.58-74.8)

284.80 83.0 Adventitious Carbon (284.8)

285.92 5.8 NOM Carboxylic Neighbor 

(285.4-285.6)

286.88 6.2 NOM Ether or Alcohol

(286.4-286.6)

CaCO3

 (288.2-290.4)

288.67 2.3 NOM Amide (288.4-288.5)

C1s 290.28 2.8 CaCO3

 (288.2-290.4)

CaCO3 (346.6-347.7)

CaMg(CO3

)

2 (347.3)

347.29 24.1 CaO (346.1-347.3)

CaCO3 (346.6-347.7)

347.88 57.3 Mol Sieve, Ca form

(347.9-348.6)

Ca2p 348.55 18.5 Mol Sieve, Ca form

(347.9-348.6)

Fe3

O4 (708.1-711.4)

FeO (709.2-710.7)

709.6 27.2 Fe2

O3 (709.9-711.6)

Fe3O4 (708.1-711.4)

Fe2O3 (709.9-711.6)

FeS (710.3-713.6)

FeO (709.2-710.7)

Fe(OH)O (710.8-711.8)

Fe2

O3*nH2O aged HFO

(710.7-711.1)

FeO(OH)*nH2

O (711.1-711.3)

711.37 38.2 Fe2

O3*nH2O fresh HFO

(711.3-711.9)

FeS (710.3-713.6)

713.15 25.5 Fe2

(SO4)

3

 (713.3)

Fe2p 715.41 9.1 Unidentified

Mg2p 50.79 100.0 CaMg(CO3

)

2

 (50.5)
56

Table 3.13. Microfracture MF08 - Candidate Minerals by XPS

Element Binding 

Energy (eV)

Peak 

Area % Candidates (Range +/- 0.3 eV)

Al2

O3 (71.47-77.3)

Mol Sieve, Ca form (73.9-74.75)

74.23 9.9 Al0.2Si0.8O2.2 (74.4)

Al2O3 (71.47-77.3)

Al2

(SO4)3 (74.9)

74.93 25.6 Al2

OSiO4 (74.58-74.8)

Al2p 75.22 64.4 Al2

(SO4)3 (74.9)

284.8 62.8 Adventitious Carbon (284.8)

285.83 27.3 NOM Carboxylic Neighbor 

(285.4-285.6)

287.8 2.5 NOM Ketone or Aldehyde 

(287.5-287.7)

CaCO3

 (288.2-290.4)

288.93 2.5 NOM Carboxylic (289.1-289.3)

C1s 290.38 4.9 CaCO3

 (288.2-290.4)

CaMg(CO3

)

2 (347.3)

CaCO3 (346.6-347.7)

347.30 16.6 CaO (346.1-347.3)

Ca(OH)2 (347.7)

CaCO3 (346.6-347.7)

347.67 25.5 Mol Sieve, Ca form

(347.9-348.6)

Mol Sieve, Ca form

(347.9-348.6)

Ca2p 348.24 57.9 CaSO4

 (348)

Fe3

O4 (708.1-711.4)

FeO (709.2-710.7)

Fe2

O3 (709.9-711.6)

710.24 25.52 FeS (710.3-713.6)

FeS (710.3-713.6)

712.15 36.98 Fe2

O3*nH2O fresh HFO

(711.3-711.9)

713.92 24.06 Unidentified

Fe2p 715.79 13.44 Unidentified

Mg2p 50.73 100.0 CaMg(CO3

)

2

 (50.5)

Element Binding 

Energy (eV)

Peak 

Area % 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)

530.59 1.4 Al2

O3 (530.0-532.7)

Fe(OH)O (530.1-531.8)

CaMg(CO3

)

2

 (531.7)

Al2O3 (530.0-532.7)

Al2OSiO4 (531.3-531.88)

Mol Sieve, Ca form (531.05-532)

SiO2

 (532-534.3)

531.98 12.0 CaSO4 (532-532.9)

SiO2 (532-534.3)

CaSO4 (532-532.9)

Al2(SO4)

3

 (532.4)

Al0.2Si0.8O2.2 (532.9)

532.38 55.6 Al2

O3 (530.0-532.7)

Al0.2Si0.8O2.2 (532.9)

CaSO4 (532-532.9)

O1s 532.98 31.0 Al2

O3 (530.0-532.7)

Al2

OSiO4 (102.6-103)

Al0.2Si0.8O2.2 (103.2)

103.12 61.0 SiO2

 (103.2-104.1)

Al0.2Si0.8O2.2 (103.2)

103.45 14.4 SiO2

 (103.2-104.1)

Si2p 104.06 25.5 SiO2

 (103.2-104.1)
57

Table 3.14. Microfracture MF09 - Candidate Minerals by XPS

Element Binding 

Energy (eV)

Peak 

Area % Candidates (Range +/- 0.3 eV)

Al2

O3 (71.47-77.3)

Mol Sieve, Ca form (73.9-74.75)

Al2

OSiO4 (74.58-74.8)

Al2(SO4)3 (74.9)

Al2p 74.72 100.0 Al0.2Si0.8O2.2 (74.4)

284.8 59.6 Adventitious Carbon (284.8)

286.14 3.1 NOM Ether or Alcohol

(286.4-286.6)

287.04 1.6 Unidentified

288.53 1.5 NOM Amide (288.4-288.5)

C1s 290.33 34.2 CaCO3

 (288.2-290.4)

CaMg(CO3

)

2 (347.3)

CaCO3 (346.6-347.7)

CaO (346.1-347.3)

347.35 58.2 CaSO4

 (347.6-348.4)

CaCO3 (346.6-347.7)

Ca(OH)2 (347.7)

Mol Sieve, Ca form

(347.9-348.6)

347.63 34.3 CaSO4

 (347.6-348.4)

Ca2p 348.72 7.5 Mol Sieve, Ca form

(347.9-348.6)

Fe3

O4 (708.1-711.4)

709.44 40.4 FeO (709.2-710.7)

Fe3

O4 (708.1-711.4)

Fe2O3 (709.9-711.6)

FeS (710.3-713.6)

Fe(OH)O (710.8-711.8)

FeO(OH)*nH2

O (711.1-711.3)

711.51 33.0 Fe2

O3*nH2O fresh HFO

(711.3-711.9)

Fe2p 714.14 26.6 Unidentified

Element Binding 

Energy (eV)

Peak 

Area % 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)

530.97 13.4 Al2

O3 (530.0-532.7)

(Mg/Fe)SiO3 (531.7)

Al2

O3 (530.0-532.7)

Al2

OSiO4 (531.3-531.88)

CaCO3 (530.5-531.5)

CaMg(CO3

)

2

 (531.7)

CaSO4 (532-532.9)

Fe(OH)O (530.1-531.8)

Mol Sieve, Ca form (531.05-532)

531.80 81.2 SiO2

 (532-534.3)

O1s 533.36 5.4 SiO2

 (532-534.3)

Al2

OSiO4 (102.6-103)

Al0.2Si0.8O2.2 (103.2)

103.22 68.8 SiO2

 (103.2-104.1)

103.81 17.0 SiO2

 (103.2-104.1)

Si2p 104.12 14.2 SiO2

 (103.2-104.1)
58

Table 3.15. Microfracture MF10 - Candidate Minerals by XPS

Element Binding 

Energy (eV)

Peak 

Area % Candidates (Range +/- 0.3 eV)

Al2

O3 (71.47-77.3)

Mol Sieve, Ca form (73.9-74.75)

74.18 11.7 Al0.2Si0.8O2.2 (74.4)

Al2O3 (71.47-77.3)

75.12 70.4 Al2

(SO4)3 (74.9)

Al2p 75.63 17.8 Al2

O3 (71.47-77.3)

284.8 69.9 Adventitious Carbon (284.8)

286.73 10.4 NOM Ether or Alcohol

(286.4-286.6)

288.62 2.3 NOM Amide (288.4-288.5)

C1s 290.21 17.4 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)

347.31 20.3 CaSO4

 (347.6-348.4)

Ca(OH)2 (347.7)

CaCO3 (346.6-347.7)

Mol Sieve, Ca form

(347.9-348.6)

347.69 48.0 CaSO4

 (347.6-348.4)

Mol Sieve, Ca form

(347.9-348.6)

Ca2p 348.23 31.7 CaSO4

 (347.6-348.4)

Fe3

O4 (708.1-711.4)

FeO (709.2-710.7)

Fe2

O3 (709.9-711.6)

709.97 25.8 FeS (710.3-713.6)

Fe3

O4 (708.1-711.4)

Fe2O3 (709.9-711.6)

FeS (710.3-713.6)

Fe(OH)O (710.8-711.8)

711.62 33.1 Fe2

O3*nH2O fresh HFO

(711.3-711.9)

712.85 21.4 FeS (710.3-713.6)

Fe2p 714.55 19.7 Unidentified

Mg2p 50.81 100.0 CaMg(CO3

)

2 (50.5)

Element Binding 

Energy (eV)

Peak 

Area % Candidates (Range +/- 0.3 eV)

Al2

O3 (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)

530.04 6.5 FeO (529.8-530.1)

CaCO3

 (530.5-531.5)

CaMg(CO3

)2 (531.7)

CaSiO3

 (531.5-531.6)

Fe(OH)O (530.1-531.8)

Al2

O3 (530.0-532.7)

Al2OSiO4 (531.3-531.88)

531.67 82.7 Mol Sieve, Ca form (531.05-532)

SiO2

 (532-534.3)

CaSO4 (532-532.9)

Al2O3 (530.0-532.7)

Al2(SO4)

3

 (532.4)

O2p 532.71 10.8 Al0.2Si0.8O2.2 (532.9)

Al2

OSiO4 (102.6-103)

Al0.2Si0.8O2.2 (103.2)

103.16 67.4 SiO2

 (103.2-104.1)

Si2p 103.87 32.6 SiO2

 (103.2-104.1)
59

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), wüstite ((FeO)), ferric minerals (e.g., goethite ( -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(II) minerals such as siderite is perhaps evidence of Fe(III) 

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 al., 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 (MonteilRivera 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. 
60

Table 3.16. Packer Water Characterizations

Well BBC5 BBC5 BBC5 BBC6

Interval 95.4 - 100.4 ft 121.4 - 126.4 ft 121.4 - 126.4 ft 112.0 - 117.0 ft

Cluster 2 3 3 4

Applicable Microfractures MF04 MF05-MF07 MF05-MF07 MF10-MF11

Sampling Date Units DL 7/20/02 4/15/02 5/29/02 6/3/03

Packer Volume Collected L - 5.4 224 224 14.35

Collection Time h - 3 1.45 0.83 1.167

Temperature °C - 10.29 ND 10.33 NA

pH pH - 9.56 8.79 9.00 8.94

Conductivity mS - 0.56 0.60 0.60 0.56

DO mg/L 0.1 2.5 0.40 0.40 0.7

Eh mV - -84.8 NA 160.9 -208.8

TCE μg/L 2 43 110 NA 33

trans-1,2-DCE μg/L 2 45 76 NA 37

cis-1,2,DCE μg/L 2 320 480 NA 340

1,1-DCE μg/L 1 ND 2 NA 1

VC μg/L 2 14 25 NA 15

Acetone μg/L 10 120 ND NA ND

Methane μg/L 4 260 360 NA 170

Ethane μg/L 4 ND ND NA ND

Ethene μg/L 1 11 15 NA 6

NPDOC mg C/L 0.10 NA 0.80 0.82 1.66

NH4

+ μg N/L 5 ND ND ND 72

Alkalinity (as CaCO3) mg/L 1 131 158 190 165

Cl- mg/L 4 14 11 12 12

SO4

2- mg/L 10 110 110 120 120

NO3

- mg/L 0.1 ND ND ND ND

S2- mg/L 0.004 ND ND ND ND

Fe2+ mg/L 0.10 0.10 0.10 0.10 0.1

Al mg/L 0.1 0.76 ND 0.09 ND

As mg/L 0.04 ND ND 0.01 ND

Ba mg/L 0.002 0.007 ND 0.02 ND

B mg/L 0.3 ND ND 0.03 ND

Ca mg/L 1 3.6 7.40 8.60 3.8

Cr mg/L 0.001 0.02 ND 0.002 ND

Cu mg/L 0.001 NA ND 0.002 ND

Fe mg/L 0.05 0.18 0.30 0.11 0.11

Pb mg/L 0.02 ND ND ND ND

Mg mg/L 1 1.6 2.90 3.20 1.3

Mn mg/L 0.05 ND ND 0.03 ND

K mg/L 1 6.8 8.00 6.00 4.4

Si mg/L 0.3 4.4 4.10 5.20 7

Na mg/L 10 77 110.00 120.00 140

Zn mg/L 0.1 0.07 ND 0.02 ND

DL = Detection Limit; ND = Not Determined; NA = Not Analyzed; - = Not relevant.
61

The presence of dissolved oxygen at relatively low concentrations around 0.5 mg/L and detectable Fe(II) concentrations 

in the packer samples warrant some discussion. Similar occurrences of detectable Fe(II) 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(II) oxidation and Fe(III) reduction. However, it is not clear if the system is at pseudoequilibrium. The data suggest that perhaps either Fe(II) 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(II) oxidation in controlled aqueous solutions (with respect to pH, CO2 partial pressures, ionic strength) is typically 

first order with respect to Fe(II) 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(III) oxides is also 

kinetically constrained by slow detachment of the Fe(II) 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 μm. 

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 Å). No 

significant levels of S were detected by SIMS, another surface spectroscopy (ejection depths of ca. 100 Å). 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 μg/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, cis -1,2 DCE was by far the dominant chlorinated compound (320 to 480 μg/L). Some trans -1,2 

DCE was observed as well, but at low concentrations (37-76 μg/L). Very little 1,1-DCE was observed (ND to 2 μg/L). 

TCE concentrations were moderate (33 to 110 μg/L). VC concentrations were also low (14-25 μg/L). Interestingly, ethene 

was detected (ND to 11 μg/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, Al(OH)3, AlOOH). 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(II), 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.
62

Table 3.17. Candidate Controlling Solid Minerals in Packer Waters Identified by Geochemical Modeling

Mineral Formula

MF04

(7/20/02)

MF05-MF07

(4/15/02)

MF05-MF07

(5/29/02)

MF1—MF11

(6/3/03)

Log 

IAP SI Log IAP SI Log IAP SI Log IAP SI

Al(OH)3 (Soil) Al(OH)3 - - 8.36 0.07 8.73 0.44 - -

BaHAsO4 • H2O BaHAsO4 • H2O - - -25.39 - 0.75 - - - -

Barite BaCO3 - - -10.14 - 0.16 -10.61 - 0.63 - -

Boehmite AlOOH - - 8.36 - 0.22 8.73 0.16 - -

CaCO3 • H2O - - - -7.81 - 0.67 -7.93 - 0.79 - 8.26 -1.12

Calcite CaCO3 - 8.10 0.38 -7.81 0.68 -7.93 0.55 - 8.26 0.22

Dolomite (dis.) CaMg(CO3)2 -16.36 0.19 -15.76 0.76 -15.93 0.61 -16.73 - 0.19

Dolomite (ord.) CaMg(CO3)2 -16.36 0.73 -15.76 1.31 -15.93 1.16 -16.73 0.36

Fe(OH)2 (am.) - 11.55 -1.94 11.92 -1.57 12.86 - 0.63 11.82 -1.67

Fe(OH)2 (c) - 11.55 -1.34 11.92 - 0.97 12.86 - 0.03 11.82 -1.07

Gibbsite (c) Al(OH)3 - - 8.36 0.62 8.73 0.99 - -

Goethite FeOOH - - - - 7.25 6.76 - -

Halloysite Al2SiO2(OH)6 • H2O - - 9.20 - 0.37 9.54 - 0.04 - -

Huntite CaMg3(CO3)4 - - - 31.75 -1.78 - 31.94 -1.97 - -

Hydrozincite Zn5(CO3)2(OH)6 - - 6.79 -1.90 8.94 0.24 - -

Imogolite Al2SiO4(OH)2 • H2O - - 12.96 - 0.04 13.50 0.50 - -

K-Jarosite Fe3(SO4)(OH)5 • 2H2O -12.30 -1.30 - - - - - -

Magnesite MnCO3 - - -7.98 - 0.52 - 8.00 - 0.54 - 8.47 -1.01

MnCO3 (am.) - - - -11.06 - 0.56 - - - -

Quartz SiO2 - 3.84 0.16 - 3.76 0.24 - 3.97 0.03 - 3.62 0.38

Rhodochrosite MnCO3 - - -11.06 - 0.05 - - - -

Sepiolite Mg2Si3O8 • 2H2O 15.35 - 0.41 16.47 0.71 17.47 1.71 15.87 0.11

Sepiolite (am.) Mg2Si3O8 • 2H2O - - - - 17.47 -1.31 - -

Siderite FeCO3 -10.15 0.441 - 9.93 0.66 - 9.83 0.76 -10.03 0.56

SiO2 (am, gel) - - 3.84 -1.13 - 3.76 -1.05 - 3.97 -1.25 - 3.62 - 0.91

SiO2 (am, ppt) - - 3.84 -1.10 - 3.76 -1.02 - 3.97 -1.23 - 3.62 - 0.88

Smithsonite ZnCO3 - - -11.75 - 0.85 -11.83 - 0.92 - -

Zincite ZnO - - 10.10 -1.13 10.86 - 0.37 - -

Zn(OH)2 Zn(OH)2 (beta) - - 10.10 -1.65 10.86 - 0.89 - -

ZnCO3 - - - -11.75 - 0.95 -11.82 -1.02 - -

ZnCO3 • H2O - - - - - -11.75 -1.49 - -

IAP = Ion Activity Product

SI = Saturation Index
63

Figure 3.23 SIMS negative mass fragment (0-50 atomic mass units) fingerprint. The sample was microfracture MF03.

Figure 3.24 SIMS positive mass fragment (0-50 atomic mass units) fingerprint. The sample was microfracture MF03.

Negative Static SIMS

Ga+ Primary Beam (10KeV, 10nA)

Target Bias 13.0 V

0.05 Atomic Mass Unit Step Size,

200 ms per channel, 1 scan

Positive Static SIMS

Ga+ Primary Beam (10KeV, 10nA)

Target Bias 13.0 V

0.05 Atomic Mass Unit Step Size,

200 ms per channel, 1 scan

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: 28Si+/

29Si+/30Si+ of 92/5/3 %, 39K+/41K+ of 93/7 %, 40Ca+/

44Ca+ of 97/2 %, and 35Cl-

/

37Cl-

 of 76/24 %.
64

Organic carbon was also observed in the spectra. This was not surprising given the propensity of NOM to form conditioning 

films on wetted mineral surfaces (Leis et al., 2000; Evanko and Dzombak, 1998). NOM is comprised of humic substances; 

typically, humic acids, fulvic acids, and humin (Hayes, 1997). Fulvic acids have lower molecular weights, higher oxygen 

to carbon ratios, and higher ratios of acidic functional groups than humic acids. Humin is more strongly mineral bound 

than either humic or fulvic acids. All three components represent a continuum of molecular weights and functional 

group distributions. Typically, humic substances originate from proteins, carbohydrates, lipids, waxes, aliphatics, and 

aromatics. These compounds have defined functional groups or moieties: carboxylic acids, phenols, alcohols, amines, 

imides, Schiff bases, esters, ethers, and S- and P-moieties (Stevenson, 1994). A number of mass fragments typical of 

NOM were seen on the microfracture sample (Leis et al., 2000). These included CH-, CH2

-

, C2H-, C2H2

-

, C2H3

-

, COOH-, 

C4H9

+, C3H5O+, and C6H9+. 

If either TCE, DCE, or VC were present on the surface, then a number of mass fragments would be evicted under ion 

bombardment with SIMS. C-Cl fragments observed from microfracture MF03 included H35Cl-, H37Cl-, C35Cl+, C37Cl+, 

C2H2

35Cl+, C2H237Cl+, C2H335Cl+, C2H337Cl+, C2H235Cl2+, C2H235Cl37Cl+, and C2H237Cl2+. All of these fragments were observed 

by Briggs et al. (2002) using TOF SIMS on poly (vinyl chloride) polymers. Only one expected fragment was not observed: 

CH35Cl+/CH37Cl+. This is reasonably strong evidence that TCE, DCE, or VC was present on the microfracture surface. 

The mechanism of partitioning of TCE, DCE, or VC to the microfracture surface is not known. However, nonionic organic 

contaminants such as TCE, DCE, and VC are non-polar and hydrophobic and can sorb to hydrophobic NOM. NOM was 

present on the surface, but the mass of sorbed NOM as well as its degree of surface coverage is not clearly known 

(e.g., some of the SEM work suggests that sorbed NOM is patchy and visible as blankets). Partitioning could have 

occurred if the non-polar TCE will dissolve into the non-polar fraction of the NOM. TCE has an aqueous solubility of 

10-2.04 mol/L and a Kow of 102.42. VC has an aqueous solubility of 10-1.35 mol/L and a Kow of 100.60. Organic matter-water 

partition coefficients (Kom) or organic carbon-water partition coefficients (Koc) can be used to describe the partitioning 

of halogenated organics to NOM. Generally, a strong, positive linear-free energy relationship exists between Kom or Koc

and Kow (Schwarzenbach et al., 1993). The more hydrophobic TCE would expect to partition more to NOM than VC. Kom

values for TCE are theoretically expected to be 101.5 to 102.5 based on the inverse linear relationship between aqueous 

solubility and Kom. Therefore, the C-Cl fragments observed are more likely to have come from hydrophobically-partitioned 

TCE.

Garbarini and Lion (1986) studied the partitioning of TCE to many types of NOM and found a strong positive relationship 

between the NOM oxygen content and carbon content to TCE partitioning. They found Koc values ranging from 2.0 

(cellulose) to 120 (lignin), depending on the NOM. Koc values for TCE partitioning to humic acids were around 57-65. 

Xing et al. (1996) also have documented TCE sorption to soil, peat, humic acid, and silica. More recently, Chiou and 

Kile (1998) found non-linear adsorption of TCE to peat-based soils at very low TCE aqueous concentrations (< 15% of 

saturation). They reported a TCE Kom of 49.

In related work, Zhu et al. (2003) studied the partitioning of halogenated organics to soils and clays precoated with a 

cationic surfactant. The degree of partitioning to the solid phase depended on the degree of coverage of the surfactant. 

Partitioning to the sorbed surfactant was stronger than the partitioning into the organic matter in the soil particles.

Figure 3.25 SIMS positive mass fragment (50-100 atomic mass units) fingerprint. The sample was microfracture MF03.

Positive Static SIMS

Ga+ Primary Beam (10KeV, 10nA)

Target Bias 13.0 V

0.05 Atomic Mass Unit Step Size,

200 ms per channel, 1 scan
65

3.11 Porosity and Pore Size Distribution of Host Rock 

The core material was generally insufficiently porous to be characterized by MIP. 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.

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 μm, 1.136 μm, and 0.109 μm. 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 al., 2000; Colwell et 

al., 1997; Fredrickson et al., 1997; Onstott et al., 2003). Estimated permeabilities for this sample, based on the method 

of Swanson (1981), were < 1 μDarcy.

In the case of the rock sample from borehole BBC5, the observed pore throat sizes were more similar to those observed 

by Colwell et al. (1997) than those reported by Onstott et al. (2003). The borehole BBC5 sample was found to have a 

porosity of 0.8%, a value closer to those reported by Onstott et al. (2003). The borehole BBC5 host rock sample had 

an estimated permeability of < 1 μDarcy, a value closer to values reported by Onstott et al. (2003) than those reported 

by Colwell et al. (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.
66

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 reactionamplified 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.

Table 3.18. Presence or Absence of Prokaryotic Groups on Borehole BBC5 Microfracture Surfaces as Determined by

Amplification with Specific Primer Sets

Microfracture

Specific Primer Set

Bacteria Geobacteracea SRB Dehalococcoides

sp.

Desulfuromonas 

sp. Archaea

01 + - + + - +

02 + - + + - +

03 + - + + - +

04 + + + + - +

05 + - - + - +

06 + - + - - +

07 + - - + - +

SRB = Sulfate Reducing Bacteria

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.
67

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 microfractures 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.

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. The numbers denote the similarity coefficients. Values > 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), a chlorobenzene-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.
68

Even with the assumption of a relatively high microfracture-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 μd) 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 μg/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 μg/L of methane 

in the methanogenic zone of a sandy aquifer TCE contaminant plume at Plattsburgh Air Force Base. NPDOC levels 

were up to 80 mg/L. Chapelle (1997) observed up to 8,000 μg/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(III) 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 (107 ft) 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. 
69

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 et al., 2003) at 40.53 m (133 ft). 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(II) and Fe(III) 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/AgCl reference electrode in the packer 

water samples and predicted Eh values based on Nernst Equation calculations using the Fe(II)/Fe(III) 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(II) (< 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(II) were used to determine that Fe(III) 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 
70

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(II) and Fe(III) candidate minerals were identified on the microfracture surfaces, including pyrrhotite (FeS), wüstite (FeO), goethite ( -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 ( -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(III) 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(III) was available for iron-reducing bacteria. The occurrence of Fe(II) on 

the microfracture surface may reflect bacteria-mediated Fe(III) reduction reactions. The spectroscopic characterization 

of the microfracture surfaces points to Fe(III) 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.
71

Table 3.19. Prokaryotic Groups on Borehole BBC5 Microfracture Surfaces Relative to Fe, S and C

Microfracture # Petrography SEM/EDAX XRD XPS [C]s (mg/kg) [Fe]s (mg/kg) [S]s (mg/kg) Primers

01020304050607

Insufficient Thickness for 

Modal AnalysisCaCO3CaMg(CO3)2(Fe,Mg)CO3FeS2InsufficientThickness forModal AnalysisInsufficientThickness forModal AnalysisInsufficientThickness forModal AnalysisCaCO3CaMg(CO3)2(Fe,Mg)CO3InsufficientThickness forModal Analysis

NoneFe-SSi-Al-K-Mg-Fe-OAl-Mg-Fe-OFe-SAl-Mg-Fe-OFe-SSi-Al-Fe-OSi-Fe-OFe-SCa-Mg-Fe-OFe-OSi-Al-Fe-O

CaCO3CaCO3(Ca, Mg)CO3InsufficientSurfacePrecipitateNone observedInsufficientSurfacePrecipitateCaMg(CO3)2Ca(Mn,Mg)(CO3)2Ca(Fe,Mg)(CO3)2None

Sample SizeConstraintsCaCO3CaMg(CO3)2 -Fe O2 3 -FeOOHFe O3 4CaCO3CaMg(CO3)2 -Fe O2 3 -FeOOHFeOOH • nH O2

Fe HO 5 8 • 4H O2

Fe O3 4

CaCO3Fe HO 5 8 • 4H O2

FeOOH • nH O2

FeCO3

CaCO3 -Fe O2 3 -FeOOHFeCO3FeSO4KFe3(OH)6(SO4)2CaCO3CaMg(CO3)2 -Fe O2 3 -FeOOHFe HO 5 8 • 4H O2

FeCO3

CaCO3CaMg(CO3)2 -Fe O2 3 -FeOOHFeOOH • nH O2

Fe HO 5 8 • 4H O2

Fe O3 4

FeSO4

−

185,000

99,000

330,000203,900199,000136,000

−

97,000

103,000

25,000

201,600122,600164,900

−

None ObservedNone Observed

None Observed

5,000

None Observed

16,000

Bacteria

ArchaeaDehalococcoidesSRBBacteria

ArchaeaDehalococcoidesSRBBacteriaArchaeaDehalococcoidesSRBBacteriaArchaeaDehalococcoidesGeobacteraceaBacteriaArchaeaDehalococcoidesBacteriaArchaeaSRBBacteriaArchaeaDehalococcoides
72

Based on the SEM-EDAX work, the spatial heterogeneity of minerals was quite high on the microfracture surface. Mineral 

grain sizes were on the order of tens of μm. 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 et al., 1999; 2001; Lower et al., 2001; Shelobolina et al., 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 μm).

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 cis-1,2 

DCE, trans-1,2 DCE, VC, and ethene. In each packer water sample, cis-1,2 DCE was most prevalent (37-480 μg/L), 

followed by trans-1,2 DCE (37-76 μg/L), VC (14 to 25 μg/L), and ethene (6-15 μg/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 (Löffler 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 oC on benzoate with cis-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 oC) 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(III) 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 et al., 2001; Hendrickson et al., 2002). The fact that cis-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. 
73

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 μm, 1.136 μm, and 0.109 μm. The sample was found to have a porosity of 0.8%, a density of 2.65 g/cm3, and a 

permeability of < 1 μDarcy. 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), wüstite (FeO), goethite ( -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 Fe(III) minerals are capable 

of supporting microbial populations that reduce Fe(III). 

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). 

cis-1,2-DCE was by far the most prevalent transformation product (up to 480 μg/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, Al(OH)3, AlOOH). 

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 μm (diameter) and 2.0 μm (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. 
74

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 DNA 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 chlorobenzenecontaminated 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(III) 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(II) and Fe(III) 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(III) was readily available for iron-reducing bacteria. The spectroscopic characterization of the microfracture surfaces 

pointed to Fe(III) 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 biogeochemicallycycled 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 

μm. 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, SEMEDAX, 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 
75

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 to TCE degradation may help to explain observed 

accumulations of transformation products. Further, the expression of enzymatic activity relative to terminal electronaccepting 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.
76

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. 

Particular thanks 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.
77

References

Altschul, S.F., T.L. Madden, A.A. Schäffer, J. Zhang, Z. Zhang, W. Miller, and D.J. Lipman. 1997. Gapped BLAST and 

PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Research 25: 3389-3402.

Amann R.I., B.J. Binder, R.J. Olson, S.W. Chisholm, R. Devereux, D.A. Stahl. 1990. Combination of 16S rRNA-targeted 

oligonucleotide probes with flow cytometry for analyzing mixed microbial populations. Applied Environmental 

Microbiology 56: 1919-1925.

Amann, R.I., W. Ludwig, and K.-H. Schleifer. 1995. Phylogenetic identification and in situ detection of individual microbial 

cells without cultivation. Microbiological Reviews 59: 143-169.

Amonette, J.E., D.J. Workman, D.W. Kennedy, J.S. Fruchter, and Y.A. Gorber. 2000. Dechlorination of carbon tetrachloride 

by Fe(II) associated with goethite. Environmental Science & Technology 34: 4606-4613.

Apul, D.S., M. Weimer, K.H. Gardner, T.T. Eighmy, A.-M. Fällman, and R. Comans. 2002. Application of surface 

complexation/precipitation modeling to contaminant leaching from weathered steel slag. Abstracts of Papers, 224th 

ACS National Meeting, Boston, MA, United States, August 18-22, 2002. 

ATSDR. 1999. Agency for Toxic Substances and Disease Registry HazDat Database, vol. 2000. U.S. Department of 

Health and Human Services, Atlanta, GA.

Baer, D.R., A.M. Marmorstein, R.E. Williford, and D.L. Blanchard. 1992. Comparison spectra for calcite by XPS. Surface 

Science Spectra 1: 80-86.

Bancroft, G.M., J.B. Metson, and R.A. Kresovic. 1987. Leaching studies of natural and synthetic titanites using secondary 

ion mass spectrometry. Geochimica Cosmochimica Acta 51: 911-918.

Barr, T.L. 1983. An XPS study of Si as it occurs in adsorbents, catalysts, and thin films. Applications of Surface Science

15: 1-35.

Barrio-Lage, G.A., F.Z. Parsons, R.S. Nassar, and P.A. Lorenzo, P.A. 1987. Biotransformation of trichloroethene in a 

variety of subsurface materials. Environmental Toxicology and Chemistry 6: 571 – 578.

Barrio-Lage, G.A., F.Z. Parsons, R.M. Barbitz, P.L. Lorenzo, and H.E. Archer. 1990. Enhanced anaerobic biodegradation 

of vinyl chloride in ground water. Environmental Toxicology and Chemistry 9: 403 – 415.

Becker, M.W. and A.M. Shapiro. 2000. Tracer transport in crystalline fractured rock: evidence of non-diffusive breakthrough 

tailing. Water Resources Research 22, (9): 120S-134S.

Bekins, B. A., E.M. Godsy, and E. Warren. 1999. Distribution of microbial physiologic types in an aquifer contaminated 

by crude oil. Microbial Ecology 37: 263-275. 

Bennett, P.C., F.K. Hiebert, and W.J. Choi. 1996. Microbial colonization and weathering of silicates in petroleumcontaminated groundwater. Chemical Geology 132: 45-53. 

Bennett, P.C., J.R. Rogers, F.K. Hiebert, and W.J. Choi. 1999. Mineralogy and mineral weathering: fundamental components 

of subsurface microbial ecology. U.S. Geological Survey Toxic Substances Hydrology Program- Proceedings of the 

Technical Meeting, Charleston, S.C., March 8-12, 1999, Water-Resources Investigations Report 99-4018c, 169-

176. 

Bennett, P.C., F.K. Hiebert, and J.R. Rogers. 2000. Microbial control of mineral-groundwater equilibria: macroscale to 

microscale. Hydrogeology Journal 8: 47-62. 

Bennett, P. C., J.R. Rogers, and W.J. Choi. 2001. Silicates, silicate weathering, and microbial ecology. Geomicrobiology 

Journal 18:3-19.

Bish, D.L., and J.E. Post. 1989. Modern Powder Diffraction, Mineralogical Society of America, Washington, DC.

Blake, D. 1990. Scanning electron microscopy. In Instrumental Surface Analysis of Geologic Materials, ed. D.L. Perry, 

11-44. New York: VCH.

Boughriet, A., M. Wartel, and L. Gengembre. 1992. Solid-state 13C NMR, X-ray photoelectron and electron spin resonance 

spectroscopies: a suggested approach to carbon analysis in aquatic solid phases. Organic Geochemistry 18: 

457-467.
78

Bouwer, E.J. 1994. Bioremediation of chlorinated solvents using alternate electron acceptors. In Handbook of 

Bioremediation, eds. R.D. Norris, R.F. Hinchee, R. Brown, P.L. McCarty, L. Semprini, T.T. Wilson, D.H. Kampbell, 

M. Reinhard, E.J. Bouwer, R.C. Borden, T.M. Vogel, J.M. Thomas, C.H. Ward, 149-175. Boca Raton, Florida: Lewis 

Publishers.

Bradley, P.M., and F.H. Chapelle. 1996. Anaerobic mineralization of vinyl chloride in Fe(III)-reducing aquifer sediments. 

Environmental Science & Technology 30: 2084-2086.

Bradley, P.M., and F.H. Chapelle. 1997. Kinetics of DCE and VC mineralization under methanogenic and Fe(III)-reducing 

conditions. Environmental Science & Technology 31: 2692-2696.

Bradley, P.M., and F.H. Chapelle. 1998a. Effect of contaminant concentration on aerobic microbial mineralization of DCE 

and VC in stream-bed sediments. Environmental Science & Technology 32: 553-557.

Bradley, P.M., and F.H. Chapelle. 1998b. Microbial mineralization of VC and DCE under different terminal electron 

accepting conditions. Anaerobe 4: 81-87.

Bradley, P.M., and F.H. Chapelle. 2000. Aerobic microbial mineralization of dichloroethene as sole carbon substrate. 

Environmental Science & Technology 34: 221-223.

Bradley, P.M., F.H. Chapelle, and D.R. Lovley. 1998a. Humic acids as electron acceptors for anerobic microbial oxidation 

of vinyl chloride and dichloroethene. Applied and Environmental Microbiology 64: 3102-3105.

Bradley, P.M., F.H. Chapelle, and J.T. Wilson. 1998b. Field and laboratory evidence for intrinsic biodegradation of vinyl 

chloride contamination in a Fe(III)-reducing aquifer. Journal of Contaminant Hydrology 31: 111-127.

Bradley, P.M., J.E. Landmeyer, and R.S. Dinicola. 1998c. Anaerobic oxidation of [1,2-14C] dichloroethene under Mn(IV)-

reducing conditions. Applied and Environmental Microbiology 64: 1560-1562.

Brassant, O., M. Aragno, and E.P. Verrecchia. 2002. Calcium carbonate crystal morphology and mineralogy, why are 

bacteria in control? Abstract 225, p.61, Book of Abstracts, 2002 International Subsurface Microbiology Conference, 

Copenhagen, Denmark, September 9-15, 2002. 

Briggs, D., I.W. Fletcher, and N.M. Goncalves. 2002. High mass-resolution ToF-SIMS study of chlorine-containing 

polymers. Surface and Interface Analysis 33: 178-184.

Butler, E.C., and K.F. Hayes. 2000. Kinetics of the transformation of halogenated aliphatic compounds by iron sulfide. 

Environmental Science & Technology 33: 422-425.

Butler, E.C., and K.F. Hayes. 2001. Factors influencing rates and products in the transformation of trichloroethylene by 

iron sulfide and iron metal. Environmental Science & Technology 35: 3884-3891. 

Calas, G., and F.C. Hawthorne. 1988. Introduction to spectroscopic methods, p. 1-10. In (F.C. Hawthorne, ed.) Spectroscopic 

Methods in Mineralogy and Geology, Mineralogical Society of America, Washington, DC.

Chandler, D. P., F. J Brockman, T. J. Bailey, and J.K. Fredrickson. 1998. Phylogenetic diversity of Archaea and bacteria 

in a deep subsurface. Paleosols and Microbial Ecology 36: 37-50.

Chang, Y. C., M. Hatsu, K. Jung, Y. S. Yoo, and K. Takamizawa. 2000. Isolation and characterization of a tetrachloroethylene 

dechlorinating bacterium, Clostridium bifermentans DPH-1. Journal of Bioscience and Bioengineering 89 

489-491.

Chapelle, F.H. 1997. Identifying redox conditions that favor the natural attenuation of chlorinated ethenes in contaminated 

ground-water systems, p. 17-20. In Symposium on Natural Attenuation of Chlorinated Organics in Ground Water. 

U.S. Environmental Protection Agency, EPA/540/R-96/509.

Chapelle, F.H., J. E. Landmeyer, and P.M. Bradley. 2002. Identifying the Distribution of Terminal Electron-accepting 

Processes (TEAPS) in Ground- water Systems. In Workshop on Monitoring Oxidation-Reduction Processes for 

Ground-water Restoration, eds. R.T. Wilkin, R.D. Ludwig, and R.G. Ford, 3-17. Washington, DC.: U.S. EPA, EPA/600/

R-02/002. 

Chapelle, F.H., P.B. McMahon, N.M. Dubrovsky, R.F. Fujii, E.T. Oaksford, and D.A.Vroblesky. 1995. Deducing the distribution 

of terminal electron-accepting processes in hydrologically diverse groundwater systems. Water Resources Research

31: 359-371.

Chapelle, F.H., P.M. Bradley, D.R. Lovley, and D.A. Vroblesky. 1996a. Measuring rates of biodegradation in a contaminated 

aquifer using field and laboratory methods. Ground Water 34: 691-698.

Chapelle, F.H., S.K. Haack, P. Adriaens, M.A. Henry, and P.M. Bradley. 1996b. Comparison of Eh and H2 measurements 

for delineating redox processes in a contaminated aquifer. Environmental Science & Technology 30: 3565-3569.

Chapelle, F.H., M.A. Widdowson , J. S. Brauner , E. Mendez III, and C.C. Casey. 2003. Methodology for Estimating Times 

of Remediation Associated with Monitored Natural Attenuation. Water-Resources Investigations Report 03-4057, 

Denver, Colorado: U.S. Geological Survey.
79

Chiou, C.T., and D.E. Kile. 1998. Deviations from sorption linearity on soils of polar and nonpolar organic compounds 

at low relative concentrations. Environmental Science & Technology 32: 338-343.

Christiansen, N., and B. K. Ahring. 1996. Desulfitobacterium hafniense sp. nov., an anaerobic reductively dechlorinating 

bacterium. International Journal of Systematic Bacteriology 46: 442-448.

Cole, J. R., B. Z. Fathepure, and J. M. Tiedje. 1995. Tetrachloroethene and 3-chlorobenzoate dechlorination activities 

are co-induced in Desulfomonile tiedjei DCB-1. Biodegradation 6: 167-172.

Coleman, N.V., T.E. Mattes, J.M. Gossett, and J.C. Spain. 2002. Phylogenetic and kinetic diversity of aerobic vinyl 

chloride-assimilating bacteria from contaminated sites. Applied and Environmental Microbiology 68: 6162-6171.

Colwell, F.S., T.C. Onstott, M.E. Delwiche, D. Chandler, J.K. Fredrickson, Q.J. Yao, J.P. McKinley, D.R. Boone, R. Griffiths, 

T.J. Phelps, D. Ringelberg, D.C. White, L. LaFreniere, D. Balkwill, R.M. Lehman, J. Konisky, and P.E. Long. 1997. 

Microorganisms from deep, high temperature sandstones: constraints on microbial colonization. FEMS Microbiology 

Reviews 20: 425-435.

Coyne, L.M., and S.W.S. McKeever. 1990. Spectroscopic characterization of minerals and their surfaces. In Spectroscopic 

Characterization of Minerals and Their Surfaces, eds. L.M. Coyne, S.W.S. McKeever, and D.F. Blake, 1-29. Washington, 

DC: American Chemical Society.

Davis, J.W., and C.L. Carpenter. 1990. Aerobic biodegradation of vinyl chloride in groundwater samples. Applied and 

Environmental Microbiology 56: 3870-3880.

deBruin, W.P., M. J. J. Kotterman, M. A. Posthumus, Gosse Schraa, and A. J. B. Zehnder. 1992. Complete biological 

reductive transformation of tetrachloroethene to ethane. Applied Environmental Microbiology 58: 1996-2000.

Devlin, J. F., and D. Muller. 1999. Field and laboratory studies of carbon tetrachloride transformation in a sandy aquifer 

under sulfate reducing conditions. Environmental Science & Technology 33: 1021-1027.

DiStefano, T. D., J. M. Gossett, and S. H. Zinder. 1991. Reductive dechlorination of high concentrations of tetrachloroethene to ethene by an anaerobic enrichment culture in the absence of methanogenesis. Applied Environmental 

Microbiology 57: 2287–2292.

Dong, H., R. Kukkadapu, J. K. Fredrickson, J.M. Zachara, D.W. Kennedy, and H.M. Kostandarithes. 2003. Microbial 

reduction of structural Fe(III) in illite and goethite. Environmental Science & Technology 37: 1268-1276.

Eggleston, C.M., J.-J. Ehrhardt, and W. Stumm. 1996. Surface structural controls on pyrite oxidation kinetics: an XPSUPS, STM, and modeling study. American Mineralogist 81: 1036-1056. 

Eighmy, T.T., A.E. Kinner, E.L. Shaw, J.D. Eusden Jr., and C.A. Francis. 1999. Hydroxylapatite (Ca5(PO4)3OH) 

characterization by XPS: an environmentally important secondary mineral. Surface Science Spectra 6: 193-201. 

Eighmy, T.T., J.C.M. Spear, W. Naser, J. Coulburn, L.S. Tisa, E. Sullivan, A. Mumford, W. Bothner, M. Mills, K. Newman, 

and N.E. Kinner. 2002a. Preliminary spectroscopic and microbial investigations on microfracture surfaces from TCEcontaminated Kittery formation bedrock from the Bedrock Bioremediation Center study site. Abstract 134, p.26, 

Book of Abstracts, 2002 International Subsurface Microbiology Conference, Copenhagen, Denmark, September 

9-15, 2002. 

Eighmy, T.T., J.C.M. Spear, W. Naser, J. Coulburn, L.S. Tisa, E. Sullivan, A. Mumford, W. Bothner, M. Mills, K. Newman, 

and N.E. Kinner. 2002b. Mineral-microbial interactions on microfracture surfaces, Northeast FOCUS Ground Water 

Conference, National Groundwater Association, Burlington, Vermont, October 3-4, 2002. 

Ekendahl, S., J. Arlinger, F. Stahl, and K. Pedersen. 1994. Characterization of attached bacterial populations in deep 

granitic groundwater from the Stripa research mine by 16S rRNA gene sequencing and scanning electron microscopy. 

Microbiology 140: 1575-1583.

Evanko, C., and D.A. Dzombak. 1998. Influence of structural features on sorption of NOM-analogue organic acids to 

goethite. Environmental Science & Technology 32: 2846-2855.

Fennell, D.E., and J.M.Gossett. 1998. Modeling the production of and competition for hydrogen in a dechlorinating 

culture. Environmental Science & Technology 32: 2450-2460.

Ferrey, M.L., R.T. Wilkin, R.G. Ford, and J.T. Wilson. 2004. Nonbiological removal of cis -Dichloroethylene and 1,1-

Dichloroethylene in aquifer sediment containing magnetite. Environmental Science & Technology 38: 1746-1752.

Fisk, M.R., S.J. Giovanoni, and I.H. Thorseth. 1998. Alteration of oceanic volcanic glass: textural evidence of microbial 

activity. Science 281: 978-980.

Flynn, S. J., F. E. Loëffler, and J. M. Tiedje. 2000. Microbial community changes associated with a shift from reductive 

dechlorination of PCE to reductive dechlorination of cis -DCE and VC. Environmental Science & Technology 34: 

1056–1061.
80

Forsythe, J.H., P.A. Maurice, and L.E. Hersman. 1998. Attachment of a Pseudomonas sp. to Fe(III)-(hydr)oxide surfaces. 

Geomicrobiology Journal 15:293-308. 

Fox, B. G., J. G. Borneman, L. P. Wackett, and J. D. Lipscomb. 1990. Haloalkene oxidation by the soluble methane 

monooxygenase from Methylosinus trichosporium OB3b: mechanistic and environmental implications. Biochemistry 

29: 6419-6427.

Fredrickson, J. K., and T.C. Onstott. 1996. Microbes deep inside the earth. Scientific American 275: 68-73. 

Fredrickson, J.K., J.P. McKinley, B.N. Bjornstad, P.E. Long, D.B. Ringelberg, D.C. White, L.K. Krumholz, J.M. Sulflita, 

F.S. Colwell, R.M. Lehman, and T.J. Phelps. 1997. Pore-size constraints on the activity and survival of subsurface 

bacteria in a late cretaceous shale-sandstone sequence, northwestern New Mexico. Geomicrobiology Journal 14: 

183-202.

Freedman, D.L., and J.M. Gossett. 1989. Biological reductive dechlorination of tetrachloroethylene and trichloroethylene 

to ethylene under methanogenic conditions. Applied Environmental Microbiology 55: 2144-2151.

Fry, N. K., J. K. Fredrickson, S. Fishbain, M. Wagner, and D. A. Stahl. 1997. Population structure of microbial communities 

associated with two deep, anaerobic, alkaline aquifers. Applied Environmental Microbiology 63:1498-504.

Garbarini, D.R., and L.W. Lion. 1986. Influence of the nature of soil organics on the sorption of toluene and trichloroethylene. 

Environmental Science & Technology 20: 1263-1269.

Geesey, G.G., A.L. Neal, P.A. Suci, and B.M. Peyton. 2002. A review of spectroscopic methods for characterizing microbial 

transformations of minerals. Journal of Microbiological Methods 51:125-139.

Gerritse, J., V. Renard, T. M. P. Gomes, P. A. Lawson, M. D. Collins, and J. C. Gottschal. 1996. Desulfitobacterium sp. strain 

PCE1, an anaerobic bacterium that can grow by reductive dechlorination of tetrachloroethene or ortho-chlorinated 

phenols. Archives of Microbiology 165: 132-140. 

Giovannoni, S. J., E. F. DeLong, G. J. Oslen, and N. R. Pace. 1988. Phylogenetic group-specific oligonucleotide probes 

for identification of single microbial cells. Journal of Bacteriology 170: 720-726.

Gopinath, C.S., S.G. Hegde, A.V. Ramaswamy, and A. Mahapatra. 2002. Photoemission studies of polymorphic CaCO3

minerals. Material Research Bulletin 37:1323-1332. 

Gossett, J.M., and S.H. Zinder. 1997. Microbiological aspects relevant to natural attenuation of chlorinated ethenes, 

p. 1-13. In: Symposium on Natural Attenuation of Chlorinated Organics in Ground Water. U.S. Environmental 

Protection Agency, EPA/540/R-96/509.

Guillot, L., M. Siitari-Kauppi, K.-H. Hellmuth, C. Dubois, M. Rossy, and P. Gaviglio. 2000. Porosity changes in a granite 

close to quarry faces: quantification and distribution by 14C-MMA and Hg porosimetries. European Physics JournalApplied Physics 9: 137-146.

Hartmans, S., and J.A.M. deBont. 1992, Aerobic vinyl chloride metabolism in Mycobacterium aurum L1. Applied and 

Environmental Microbiology 58: 1220-1226.

Hartmans, S., J.A.M. deBont, J. Tramper, and K.C. Luyben. 1985. Bacterial degradation of vinyl chloride. Biotechnology 

Letter 7: 383-388.

Harvey, D.T., and R.W. Linton. 1981. Chemical characterization of hydrous ferric oxides by x-ray photoelectron spectroscopy. 

Analytical Chemistry 53: 1684-1688.

Haveman, S.A., K. Pedersen, and P. Ruotsalainen. 1999. Distribution and metabolic diversity of microorganisms in deep 

igneous rock aquifers of Finland. Geomicrobiology Journal 16:277-294.

Hayes, M.H.B. 1997. Emerging concepts of the compositions and structures of humic substances, pp: 3-30. In: (M.H.B 

Hayes & W.S. Wilson, eds.) Humic Substances in Soils, Peats and Waters: Health and Environmental Aspects, The 

Royal Society of Chemistry, Cambridge, England. 

He, J., K.M. Ritalahti, M.R. Aiello, and F.E. Loëffler. 2003. Complete detoxification of vinyl chloride by an anaerobic 

enrichment culture and identification of the reductively dechlorinating population as a Dehalococcoides species. 

Applied and Environmental Microbiology 69: 996-1003.

He, J., Y. Sung, M. E. Dollhopf, B. Z. Fathepure, J. M. Tiedje, and F. E. Loëffler. 2002. Acetate versus hydrogen as direct 

electron donors to stimulate the microbial reductive dechlorination process at chloroethene-contaminated sites. 

Environmental Science & Technology 36: 3945-3952.

Hendrickson, E. R., J. A. Payne, R. M. Young, M. G. Starr, M. P. Perry, S. Fahnestock, D. E. Ellis, and R. C. Ebersole. 

2002. Molecular analysis of Dehalococcoides 16S ribosomal DNA from chloroethene-contaminated sites throughout 

North America and Europe. Applied Environmental Microbiology 68: 485-495.

Hiebert, F.K., and P.C. Bennett. 1992. Microbial control of silicate weathering in organic-rich ground water. Science

258:278-281.
81

Hochella, M. 1988. Auger and photoelectron spectroscopies. In Spectroscopic Methods in Mineralogy and Geology, ed. 

F.C. Hawthorne, 573-638. Washington, DC: Mineralogical Society of America.

Hohnstock-Ashe, A.M., S.M. Plummer, R.M. Yager, P. Baveye, and E.L. Madsen. 2001. Further biogeochemical 

characterization of a trichloroethene-contaminated fractured dolomite aquifer: electron source and microbial 

communities involved in reductive dechlorination. Environmental Science & Technology 35: 4449-4456. 

Holliger, C., D. Hahn, H. Harmsen, W. Ludwig, W. Schumacher, B. Tindall, F. Vazquez, N. Weiss, and A. J. B. Zehnder. 

1998. Dehalobacter restrictus gen. nov. and sp. nov., a strictly anaerobic bacterium that reductively dechlorinates 

tetra- and trichloroethene in an anaerobic respiration. Archives of Microbiology 169: 313-321.

Holliger, C., G. Wohlfarth, and G. Diekert. 1999. Reductive dechlorination in the energy metabolism of anaerobic bacteria. 

FEMS Microbiological Reviews 22: 383-398.

Horath, T., W. Von Sigler, T. Neu, and R. Bachofen. 2002. Endolithic microbial populations in dolomite rock. Abstract 

207, p.53, Book of Abstracts, 2002 International Subsurface Microbiology Conference, Copenhagen, Denmark, 

September 9-15, 2002.

Hugenholtz, P., B. M. Goebel, and N. R. Pace. 1998. Impact of culture independent studies on the emerging phylogenetic 

view of bacterial diversity. Journal of Bacteriology 180: 4765–4774.

Hutchinson, C.S. 1974. Laboratory Handbook of Petrographic Techniques, New York: John Wiley & Sons. 

Jakobsen, R., H-J. Albrechtsen, M. Rasmussen, H. Bay, P.L. Berg, and T.H. Christensen. 1998. H2 concentrations in a 

landfill leachate plume (Grindsted, Denmark): In situ energetics of terminal electron acceptor processes. Environmental 

Science & Technology 32: 2142-2148.

Kalinowski, B. E., L.J. Liermann, S.L. Brantley, A. Barnes, and C.G. Pantano. 2000a. X-ray photoelectron evidence for 

bacteria-enhanced dissolution of hornblende. Geochimica et Cosmochimica Acta 64:1331-1343. 

Kalinowski, B. E., L.J. Liermann, S. Givens, and S.L. Brantley. 2000b. Rates of bacteria-promoted solubilization of Fe 

from minerals: a review of problems and approaches. Chemical Geology 169: 357-370.

Kenneke, J.F. and E.J. Weber. 2003. Reductive Dehalogenation of halomethanes in iron- and sulfate reducing sediments. 

1. Reactivity pattern analysis. Environmental Science & Technology 37: 713-720. 

Kinner, N.E., C.L.M. Grout, M. Gonsoulin, and S.A. Vandegrift. 2001. Pease International Tradeport Site 32 Bedrock 

Bioremediation Research Quality Assurance Project Plan, December 21, 2001.

Kranz, R.L. 1983. Microcracks in rocks: a review. Techtonophysics 100: 449-480 

Kruber, C., I.H. Thorseth, K. Lysnes, T. Torsvik, and R.B. Pedersen. 2002. Low-temperature hydrothermal mounds and 

chimneys formed by microbial mediated precipitation of Fe and Si. Abstract 320, Book of Abstracts Supplement, 

2002 International Subsurface Microbiology Conference, Copenhagen, Denmark, September 9-15, 2002.

Krumholz, L. R., R. Sharp, and S. Fishbain. 1996. A freshwater anaerobe coupling acetate oxidation to tetrachloroethene 

dehalogenation. Applied Environmental Microbioliology 62: 4108-4113.

Lane, D. J. 1991. 16S/23S r RNA sequencing. In Nucleic Acid Techniques in Bacterial Sytematics, ed. E. Stackebrandt 

and M. Goodfellow, 115-175. Chichester, UK: John Wiley & Sons Ltd.

Lane, D.J., B. Pace, G.J. Olson, D.A. Stahl, M.L. Sogin, and N.R. Pace. 1985. Rapid determination of 16S ribosomal RNA 

sequences for phylogenetic analyses. Proceedings of the National Academy for Science USA 82: 6955-6959.

Lee, W., and B. Batchelor. 2003. Reductive capacity of natural reductants. Environmental Science & Technology 37: 

536-541.

Lehman, R. M., F.S. Colwell, and G. A. Bala. 2001a. Attached and unattached microbial communities in a simulated 

basalt aquifer under fracture- and porous-flow conditions. Applied Environmental Microbiology 67: 2799-2809. 

Lehman, R. M., F.F. Roberto, D. Earley, D.F. Bruhun, S.E. Brink, S.P. O’Connell, M.E. Delwiche, and F.S. Colwell. 2001b. 

Attached and unattached bacterial communities in a 120-meter corehole in an acidic, crystalline rock aquifer. 

Applied Environmental Microbiology 67: 2095-2106. 

Leis, A., R.N. Lamb, B. Gong, and R.P. Schneider. 2000. Evidence for the contribution of humic substances to conditioning 

films from natural waters. Biofouling 15: 207-220.

Lendvay, J.M., F.E. Loffler, M. Dollhope, M.R. Aiello, G. Daniels, B.Z. Fathepure, M.G. Ebhard, R. Heine, R. Helton, 

J. Shi, R. Krajmalnik-Brown, C.L. Major, Jr., M.J. Barcelona, E. Petrovskis, R. Hickey, J.M. Tiedje, and P. Adriaens. 

2003. Bioreactive barriers: A comparison of bioaugmentation and biostimulation for chlorinated solvent remediation. 

Environmental Science & Technology 37, 1422-1431.

Li, S., and L. P. Wackett. 1992. Trichloroethylene oxidation by toluene dioxygenase. Biochemical & Biophysical Research 

Communications 185: 443-451.
82

Liermann, L. J., A.S. Barnes, B.E. Kalinowski, X. Zhou, and S.L. Brantley. 2000a. Microenvironments of pH in biofilms 

grown on dissolving silicate surfaces. Chemical Geology 171: 1-16. 

Liermann, L. J., B. E. Kalinowski, S.L. Brantley, and J. G. Ferry. 2000b. Role of bacterial siderophores in dissolution of 

hornblende. Geochimica et Cosmochimica Acta 64: 587-602. 

Löffler, F.E., R.A. Sanford, and J. M. Tiedje. 1996. Initial characterization of a reductive dehalogenase from Desulfitobacterium 

chlororespirans Co23. Applied Environmental Microbiology 62: 3809-3813.

Löffler, F.E., Q. Sun, J. Li, and J.M. Tiedje. 2000. 16S rRNA Gene- base detection of tetrachloroethene-dechlorinating 

Desulfuromonas and Dehalococcoides species. Applied Environmental Microbiology 66: 1369-1374.

Lovley, D.R., and F.H. Chapelle. 1995. Deep subsurface microbial processes. Reviews in Geophysics 33: 365-381.

Lovley, D.R., and S. Goodwin. 1988. Hydrogen concentrations as an indicator of the predominant terminal electronaccepting reactions in aquatic sediments. Geochimica et Cosmochimica Acta 52: 2993-3003.

Lovley, D.R., and E.J.P. Phillips. 1987. Competitive mechanisms for the inhibition of sulfate reduction and methane 

production in the zone of ferric iron reduction in sediments. Applied and Environmental Microbiology 53: 2636-

2641. 

Lower, S.K., M.F. Hochella, and T.J. Beveridge. 2001. Bacterial recognition of mineral surfaces: nanoscale interactions 

between Shewanella and -FeOOH. Science 292: 1360-1363. 

Magnuson, J. K., R. V. Stern, J. M. Gossett, S. H. Zinder, and D. R. Burris. 1998. Reductive dechlorination of tetrachloroethene 

to ethene by a two component enzyme pathway. Applied Environmental Microbiology 64: 1270-1275.

Maymó-Gatell, X., Y.-T. Chien, J. M. Gossett, and S. H. Zinder. 1997. Isolation of a bacterium that reductively dechlorinates 

tetrachloroethene to ethene. Science 276: 1568-1571.

Maymó-Gatell, X., T. Anguish, and S. H. Zinder. 1999. Reductive dechlorination of chlorinated ethenes and 1,2-

dichloroethane by “Dehalococcoides ethenogenes” 195. Applied Environmental Microbiology 65: 3108-3113.

McCarty, P.L. 1997a. Breathing with chlorinated solvents. Science 276: 1521-1522. 

McCarty, P.L. 1997b. Biotic and abiotic transformations of chlorinated solvents in ground water. In Proceedings of the 

Symposium on Natural Attenuation of Chlorinated Organics in Ground Water, 7-11. Washington, DC: U.S. EPA Office 

of Research and Development Report EPA/540/R-97/504.

McCarty, P.L., and L. Semprini. 1994. Ground-water treatment for chlorinated solvents. In Handbook of Bioremediation, 

eds. R.D. Norris, R.F. Hinchee, R. Brown, P.L. McCarty, L. Semprini, T.T. Wilson, D.H. Kampbell, M. Reinhard, 

E.J. Bouwer, R.C. Borden, T.M. Vogel, J.M. Thomas, C.H. Ward, 87-116. Boca Raton, Florida: Lewis Publishers.

McGuire, J.T., E.W. Smith , D.T. Long, D.W. Hyndman, S.K. Haack, M.J. Klug, and M.A. Velbel. 2000. Temporal variations 

in parameters reflecting terminal-electron-accepting processes in an aquifer contaminated with waste fuel and 

chlorinated solvents. Chemical Geology 169: 471-485.

Meima, J.A., R.D. van der Weijden, T.T. Eighmy, and R.N.J. Comans. 2002. Carbonation processes in municipal solid 

waste incinerator bottom ash and their effect on the leaching of copper and molybdenum. Applied Geochemistry

17: 1503-1513. 

Metson, J.B. 1990. Secondary ion mass spectrometry. In Instrumental Surface Analysis of Geologic Materials, 

ed. D.L. Perry, 311-354. New York: VCH. 

Miller, E., G. Wohlfarth, and G. Diekert. 1998. Purification and characterization of the tetrachloroethene reductive 

dehalogenase of strain PCE-S. Archives of Microbiology 169: 497-502.

Miller, E., G. Wohlfahrt, and G. Diekert. 1997. Comparative studies on tetrachloroethene reductive dechlorination by 

Desulfitobacterium sp. Strain PCE-S. Archives of Microbiology 168: 513-519.

Monteil-Rivera, F., E.B. Brouwer, S. Masset, Y. Deslandes, and J. Dumonceau. 2000. Combination of x-ray photoelectron 

spectroscopy and solid state 13C nuclear magnetic resonance spectroscopy in the structural characterization of 

humic acids. Analytica Chimica Acta 424: 243-255.

Muyzer, G., S. Hottentrager, A. Teske, and C. Wawer. 1996. Denaturing gradient gel electrophoresis of PCR-amplified 

16S rDNA-A new molecular approach to analyze the genetic diversity of mixed microbial communities. Molecular 

and Microbial Ecology Manuscripts 3.4.4:1-23.

Muyzer, G., and K. Smalla. 1998. Application of denaturing gradient gel electrophoresis (DGGE) and temperature gradient 

gel electrophoresis (TGGE) in microbial ecology. Antonie Van Leeuwenhoek 73, (1): 127-41. 

Nesse, W.D. 2003. Introduction to Optical Mineralogy, Oxford University Press, New York.

Neumann, A., H. Scholz-Muramatsu, and G. Diekert. 1994. Tetrachloroethene metabolism of Dehalospirillum multivorans. 

Archives of Microbiology 162: 295-301.
83

Neumann, A., G. Wohlfarth, and G. Diekert. 1998. Tetrachloroethene dehalogenase from Dehalospirillum multivorans: 

cloning, sequencing of the encoding genes, and expression of the pceA gene in Escherichia coli. Journal of 

Bacteriology 180: 4140-4145.

Newman, L. M., and L. P. Wackett. 1997. Trichloroethylene oxidation by purified toluene 2-monooxygenase: products, 

kinetics, and turnover-dependent inactivation. Journal of Bacteriology 179: 90-96.

Ni, S., J.K. Fredrickson, and L. Xun. 1995. Purification and characterization of a novel 3-chlorobenzoate-reductive 

dehalogenase from the cytoplasmic membrane of Desulfomonile tiedjei DCB-1. Journal of Bacteriology 177: 5135-

5139.

Odum, J.M., J. Tabinowski, M.D. Lee, and B.Z. Fathepure. 1995. Anaerobic biodegradation of chlorinated solvents 

— Comparative laboratory study of aquifer microcosms. In Handbook of Bioremediation, eds. R.D. Norris, 

R.F. Hinchee, R. Brown, P.L. McCarty, L. Semprini, T.T. Wilson, D.H. Kampbell, M. Reinhard, E.J. Bouwer, 

R.C. Borden, T.M. Vogel, J.M. Thomas, C.H. Ward, 17-24: Boca Raton, Florida: Lewis Publishers.

Onstott, T.C., T.J. Phelps, F.S. Colwell, D. Ringelberg, D.C. White, D.R. Boone, J.P. McKinley, T.O. Stevens, P.E. Long, 

D.L. Balkwill, W.T. Griffin, and T. Kieft. 1998. Observations pertaining to the origin and ecology of microorganisms 

recovered from the deep subsurface of Taylorsville Basin, Virginia. Geomicrobiology Journal 15: 353-385. 

Onstott, T.C., D.P. Moser, S.M. Pfiffner, J.K. Fredrickson, F.J. Brockman, T.J. Phelps, D.C. White, A. Peacock, D. Balkwill, 

R. Hoover, L.R. Krumholz, M. Borscik, T.L. Kieft, and R. Wilson. 2003. Indigenous and contaminant microbes in 

ultradeep mines. Environmental Microbiology 5: 1168-1191.

Øvreas, L., L. Forney, F.L. Daae, and V. Torsvik. 1997. Distribution of bacterioplankton in Meromictic Lake Sælenvannet, 

as determined by denaturing gradient gel electrophoresis of PCR-amplified gene fragments coding for 16S rRNA. 

Applied Environmental Microbiology 33: 3367-3373.

Pedersen, K. 1997. Microbial life in granitic rock. FEMS Microbiology Reviews 20: 399-414. 

Pedersen, K. 2000. Exploration of deep intraterrestrial microbial life: current perspectives. FEMS Microbiology Letters 

185: 9-16. 

Perry, D.L., J.H. Taylor, and C.D. Wagner. 1990. X-ray induced photoelectron and Auger Spectroscopy. In Instrumental 

Surface Analysis of Geologic Materials, ed. D.L. Perry, 45-86. New York: VCH.

Phelps, T.J., K. Malachowsky, R.M. Schram, and D.C. White. 1991. Aerobic mineralization of vinyl chloride by a bacterium 

of the order Actinomycetales. Applied and Environmental Microbiology 57: 1252-1254.

Robinson, N.I., J.M. Sharp, Jr., and I. Kreisel. 1998. Contaminant transport in sets of parallel finite fractures with fracture 

skins. Journal of Contaminant Hydrology 31: 83-109. 

Rogers, J.R., and P.C. Bennett. 2001. Ferroan dolomite mineralization by iron-reducing bacteria. EOS Transaction AGU 

82(47), Fall Meeting Supplement, Abstract B12C-0141. 

Rogers, J.R., P.C. Bennett, and W.J. Choi. 1998. Feldspars as a source of nutrients for microorganisms. American 

Mineralogist 83: 1532-1540. 

Rogers, J.R., P.C. Bennett, and W.J. Choi. 2001. Enhanced weathering of silicates by subsurface microorganisms: a 

strategy to release limiting inorganic nutrients? Water-Rock Interaction: Proceedings of the Tenth International 

Symposium on Water-Rock Interaction, Villasimus, Italy, July 10-15, 2001, A.A. Balkema, the Netherlands. 

Rogers, J.R., P.C. Bennett, and F.K. Heibert. 1999. Patterns of microbial colonization on silicates. U.S. Geological Survey 

Toxic Substances Hydrology Program--- Proceedings of the Technical Meeting, Charleston, SC, March 8-12, 1999, 

Water-Resources Investigations Report 99-4018c, 237-242. 

Röling, W.F.M., B.M. van Breukelen, M. Braster, B. Lin, and van H.W. Verseveld. 2001. Relationships between microbial 

community structure and hydrochemistry in a landfield leachate-polluted aquifer. Applied Environmental Microbiology

67: 4619-4629.

Sanford, R.A., J.R. Cole, F.E. Loëffler, and J.M. Tiedje. 1996. Characterization of Desulfitobacterium chlororespirans sp. 

nov., which grows by coupling the oxidation of lactate to the reductive dechlorination of 3-chloro-4-hydroxybenzoate. 

Applied Environmental Microbiology 62: 3800-3808.

Scholz-Muramatsu, H., A. Neumann, M. Meßmer, E. Moore, and G. Diekert. 1995. Isolation and characterization of 

Dehalospirillum multivorans gen. nov., sp. nov., a tetrachloroethene-utilizing, strictly anaerobic bacterium. Archives 

of Microbiology 163: 48-56.

Schwarzenbach, R.P., P.M. Gschwend, and D.M. Imboden. 1993. Environmental Organic Chemistry, Wiley-Interscience, 

N.Y.

Semprini, L. 1995. In situ bioremediation of chlorinated solvents. Environmental Health Perspective 103: 101-105.
84

Semprini, L., P.V. Roberts, G.D. Hopkins, and P.L. McCarty. 1990. A field evaluation of in situ biodegradation of chlorinated 

ethenes, Part 2 — Results of biostimulation and biotransformation experiments. Ground Water 28: 715-727.

Semprini, L., G.D. Hopkins, P.V. Roberts, D. Grbic-Galic, and P.L. McCarty. 1991. A field evaluation of in situ biodegradation 

of chlorinated ethenes, Part 3 — Studies of competitive inhibition. Ground Water 29: 239-250.

Shapiro, A.M. 2001. Effective matrix diffusion in kilometer-scale transport in fractured crystalline rock. Water Resources 

Research. 37: 507-522.

Sharma, P.K., and P.L. McCarty. 1996. Isolation and characterization of a facultatively aerobic bacterium that reductively 

dehalogenates tetrachloroethene to cis-1,2-dichloroethene. Applied Environmental Microbiology 62: 761-765.

Shelobolina, E.S., C.G. Vanpraagh, and D.R. Lovley. 2003. Use of ferric and ferrous iron containing minerals for respiration 

by Desulfitobacterium frappieri. Geomicrobiology Journal 20: 143-156.

Simmons, G., and D. Richter. 1976. Microcracks in rocks. In The Physics and Chemistry of Minerals and Rocks, 

ed. R.G. J. Strens, 105-137. New York: Wiley.

Smith, D.K. 1989. Computer analysis of diffraction data. In Modern Powder Diffraction, ed. D.L. Bish and J.E. Post, 

83-100. Washington, DC: Mineralogical Society of America.

Snoeyenbos-West, O.L., K.P. Nevin, R.T. Anderson, and D.R. Lovley. 2000. Enrichment of Geobacter species in response 

to stimulation of Fe(III) reduction in sandy aquifer sediments Microbial Ecology 39: 153-167.

Snyder, R.L., and Bish, D.L. 1989. Quantitative analysis. In Modern Powder Diffraction, ed. D.L. Bish and J.E. Post, 

101-136. Washington, DC: Mineralogical Society of America. 

Stevenson, F.J. 1994. Humus chemistry: Genesis, Composition, Reactions. John Wiley & Sons, N.Y.

Stiber , N.A., M. Pantazidou, and M.J. Small. 1999. Expert system methodology for evaluating reductive dechlorination 

at TCE Sites. Environmental Science & Technology 33: 3012-3020

Stipp, S.L., and M.F. Hochella, Jr. 1991. Structure and bonding environments at the calcite surface as observed with 

X-ray photoelectron spectroscopy (XPS) and low energy electron diffraction (LEED). Geochimica Cosmochimica 

Acta 55: 1723-1736.

Suyama, A., M. Yamashita, S. Yoshino, and K. Furukawa. 2002. Molecular characterization of the PceA reductive 

dehalogenase of Desulfitobacterium sp. strain Y51. Journal of Bacteriology 184: 3419-3425.

Swanson, B.F. 1981. A simple correlation between permeabilities and mercury capillary pressures. Journal of Petroleum 

Technology, December, 2488-2504.

U.S. EPA. 1997. Proceedings of the Symposium on Natural Attenuation of Chlorinated Organics in Ground Water.

U.S. EPA Office of Research and Development Report EPA/540/R-97/504, Washington, DC.

U.S. EPA. 1998. The Technical Protocol for Evaluating Natural Attenuation of Chlorinated Solvents in Ground Water. 

EPA/600/R-98/128, Washington, DC.

U.S. EPA. 2002. Workshop on Monitoring Oxidation-Reduction Processes for Ground-water Restoration. U.S. EPA Report 

EPA/600/R-02/002, Washington, DC.

Utkin, I., C. Woese, and J. Wiegel. 1994. Isolation and characterization of Desulfitobacterium dehalogenans gen. nov., 

sp. nov., an anaerobic bacterium which reductively dechlorinates chlorophenolic compounds. International Journal 

of Systematic Bacteriology 44: 612-619.

Vogel, T.M. 1994. Natural bioremediation of chlorinated solvents. In Handbook of Bioremediation, eds. R.D. Norris, 

R.F. Hinchee, R. Brown, P.L. McCarty, L. Semprini, J.T. Wilson, D.H. Kampbell, M. Reinhard, E.J. Bouwer, 

R.C. Borden, T.M. Vogel, J.M. Thomas, C.H. Ward, 201-225. Boca Raton, Florida: Lewis Publishers. 

Vogel, T.M., and P.L. McCarty. 1985. Biotransformation of tetrachloroethylene to trichloroethylene, dichloroethylene, vinyl 

chloride and carbon dioxide under methanogenic conditions. Applied Environmental Microbiology 49: 1080-1083. 

Vogel, T.M., C.S. Criddle, and P.L. McCarty. 1987. Transformation of halogenated aliphatic compounds. Environmental 

Science & Technology 21: 722-736.

Whan, R.E. 1986. Metals Handbook, v. 10 - Materials Characterization. American Society for Metals, Metals Park, 

Ohio.

Wiedemeier, T.H., M.A. Swanson, D.E. Moutoux, E.K. Gordon, J.T. Wilson, B.H. Wilson, D.H. Kampbell, P.E. Haas, 

R.N. Miller, J.E. Hansen, and F.H. Chapelle. 1998. Technical protocol for evaluating natural attenuation of chlorinated 

solvents in ground water. EPA/600/R-98/128. U.S. Environmental Protection Agency, Washington, DC.

Wiedemeier, T.H., J.T. Wilson, B.H. Wilson, and D.H. Kampbell. 1997. Natural attenuation of chlorinated aliphatic hydrocarbons at Plattsburgh Air Force Base, New York. In: Symposium on Natural Attenuation of Chlorinated Organics 

in Ground Water. U.S. Environmental Protection Agency, EPA/504/R-96/509; 1996, pp. 76-84.
85

Wild, A., R. Hermann, and T. Leisinger. 1996. Isolation of an anaerobic bacterium which reductively dechlorinates tetrachloroethene and trichloroethene. Biodegradation 7: 507-511.

Wilson, J.T. 2002. Current state of practice of oxidation reduction processes important to the biological and chemical 

destruction of chlorinated organic compounds in ground water. In Workshop on Monitoring Oxidation-Reduction 

Processes for Ground-water Restoration, eds. R.T. Wilkin, R.D. Ludwig, and R.G. Ford. 29-33 EPA/600/R-02/002. 

U.S. EPA Washington, D.C.

Wilson, J.T., and B.H. Wilson. 1985. Biotransformation of trichloroethylene in soil. Applied and Environmental Microbiology

49: 242-243.

Wu, W.-M., J. Nye, R.F. Hickey, M.K. Jain, and J.G. Zeikus. 1995. Dechlorination of PCE and TCE to ethene using 

an anaerobic microbial consortium, p.45-52. In (R.D. Norris, R.F. Hinchee, R. Brown, P.L. McCarty, L. Semprini, 

J.T. Wilson, D.H. Kampbell, M. Reinhard, E.J. Bouwer, R.C. Borden, T.M. Vogel, J.M. Thomas, C.H. Ward et al., eds), 

Handbook of Bioremediation, Lewis Publishers, Boca Raton, Florida.

Xing, B., J.J. Pignatello, and B. Gigliotti. 1996. Competitive sorption between atrazine and other organic compounds in 

soils and model sorbents. Environmental Science & Technology 30: 2432-2440.

Yager, R.M., S.E. Bilotta, C.L. Mann, and E.L. Madsen. 1997. Metabolic adaption and in situ attenuation of chlorinated 

ethenes by naturally occurring microorganisms in a fractured dolomite aquifer near Niagara Falls, New York. 

Environmental Science & Technology 31: 3138-3147.

Yang, Y., and P.L. McCarty. 1998. Competition for hydrogen within a chlorinated solvent dehalogenating anaerobic mixed 

culture. Environmental Science & Technology 32: 3591-3597.

Zhu, L., B. Chen, S. Tao, and C.T. Chiou. 2003. Interactions of organic contaminants with mineral-adsorbed surfactants. 

Environmental Science & Technology 37: 4001-4006.

Zussman, J. 1976. Physical Methods in Determinative Mineralogy, Academic Press, London.
EPA/600/R-05/121

June 2006

National Risk Management

 Research Laboratory

Cincinnati, OH 45268

Official Business

Penalty for Private Use

$300

Please make all necessary changes on the below label, 

detach or copy, and return to the address in the upper 

left-hand corner.

If you do not wish to receive these reports CHECK HERE ; 

detach, or copy this cover, and return to the address in the 

upper left-hand corner.

PRESORTED STANDARD

POSTAGE & FEES PAID

EPA

PERMIT No. G-35