Microbial Aspects of Shale Flowback Fluids and Response to Hydraulic Fracturing Fluids THESIS Presented in Partial Fulfillment

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Microbial Aspects of Shale Flowback Fluids and Response to Hydraulic Fracturing Fluids

THESIS

Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University

Maryam Ansari Cluff

Graduate Program in Environmental Science

The Ohio State University

2013

Master's Examination Committee:

Paula J. Mouser, Advisor, Assistant Professor of Civil, Environmental and Geodetic

Engineering, The Ohio State University

John J. Lenhart, Associate Professor of Civil, Environmental and Geodetic Engineering,

The Ohio State University

Charles J. Daniels, Professor of Microbiology, The Ohio State University

Copyrighted by

Maryam Ansari Cluff

2013

Abstract

Recent technological advancements in hydraulic fracturing and horizontal drilling as applied to shale formations have revived interest in Ohio’s oil and natural gas reserves.

In many cases, short and long-term impacts to the environment from this exploration are not well understood as production in the field outstrips conducted research. The following two studies explore microbial community dynamics in shale well flowback fluids and their response to synthetic fracturing fluid exposure, respectively, and may yield insight into ecological impacts to the surface and subsurface as a result of shale gas development. Microbial diversity in the shale well fluids studied decreased significantly.

The microbial ecology of these fluids shifted from one dominated by microbes present in source waters to one consistent with a brine system. In addition, significant enrichment of various hydrocarbon-degrading biomarkers was observed in an aquifer response to frack fluid exposure. Overall, significant dissolved organic carbon attenuation, largely attributed to biodegradation, was observed in both studies. Characterizing microbial community content and dynamics of fluids through hydraulic fracturing, flowback and production periods of shale gas stimulation may aid well operators in maximizing natural gas recovery and practitioners in making informed decisions on wastewater management strategies. In addition, examining how the biogeochemistry of a typical aquifer system responds to fracking fluid exposure can be used as a timely indicator of surface and groundwater pollution by these shale gas-associated fluids. ii

Dedication

I lovingly dedicate this thesis to my best friend and husband Taylor, whose limitless support never fails to build me up and confirm in me my ability to accomplish so much

more than I ever thought possible.

iii

Acknowledgments

I would like to express my greatest gratitude to Dr. Paula J. Mouser, my thesis advisor, for countless moments of help and support throughout my graduate education at

The Ohio State University. Her scientific knowledge and aptitude in this field are praiseworthy and have played an invaluable part of my academic and professional success here at OSU.

Thank you to Dr. John J. Lenhart and Dr. Charles J. Daniels for agreeing to serve on my committee and offering knowledge and advice along the way. Special thanks to

Dr. Angela Hartsock, post-doctoral research associate at the Department of Energy’s

National Energy Technology Laboratory, for facilitating access to samples and information crucial to shale well flowback fluid study. An enormous thank you to Dr.

Jean D. MacRae, Associate Professor of Civil and Environmental Engineering at the

University of Maine, for her invaluable contribution of raw data reduction for the majority of the data presented herein.

I wish to thank my graduate colleague Shuai Liu (MS in Civil, Environmental and

Geodetic Engineering) for his help in coordinating and carrying out the microcosm portion of this research and his subsequent contribution of geochemical data. A sincere thanks to Mike Brooker (MS in Environmental Science) for offering up his wealth of research knowledge and advice whenever I was in need of help. He is always willing to help out his labmates even in inconvenient times and for that I am very grateful.

Thanks to Mike Zianni and Anthony McCoy, Senior Research Associate and

Research Associate Laboratory Technician, respectively, at the Plant-Microbe Genomics iv

Facility at The Ohio State University for their technical expertise in sequencing technologies.

Lastly, I wish to thank the entities which are responsible for the funding of this research, namely the Ohio Water Development Authority, Environmental Science

Graduate Program at The Ohio State University through a GAA appointment, and an

Ohio State University Fellowship.

Vita

2011 ...... B.S. Biology, The University of Maine

2013 ...... M.S. Environmental Science, The Ohio

State University

Fields of Study

Major Field: Environmental Science

Table of Contents

Abstract ...... ii

Acknowledgments ...... iv

Vita ...... vi

Fields of Study ...... vi

Table of Contents ...... vii

List of Tables ...... x

List of Figures ...... xi

Chapter 1: Introduction ...... 1

Brief History of Oil and Natural Gas Development in Ohio ...... 1

Early Exploration Techniques ...... 2

Recent Development in Ohio’s Marcellus and Utica Shale ...... 3

The Formation of Hydrocarbons in the Marcellus and Utica Shale ...... 8

Physical Characteristics of Shale ...... 11

Origin of Methane in Marcellus and Utica Shale ...... 12

Horizontal Hydraulic Fracturing Technique ...... 13

Hydraulic Fracturing Fluids ...... 16

Flowback and Produced Water ...... 20

vii

Management of Flowback Fluids ...... 22

Microbial Sources ...... 24

Microorganisms Associated with Shale ...... 25

Microorganisms Associated with Oil and Gas Operations ...... 26

Conclusion ...... 28

Chapter 2: Microbial Community Shifts in Shale Well Flowback Fluids ...... 30

Introduction ...... 30

Methods ...... 31

Results ...... 32

Discussion ...... 43

Conclusions ...... 51

Introduction ...... 52

Methods ...... 53

Results ...... 54

Discussion ...... 75

Conclusions ...... 80

Chapter 4: Research Implications ...... 82

Bibliography ...... 84

Appendix A: Microbial Community Shifts in Shale Well Flowback Fluids Methods ... 102 viii

Sample Collection and Preparation ...... 102

DNA Extractions, PCR Amplification, Cloning and Sequencing ...... 104

16s rRNA Gene Sequence Analysis ...... 107

Appendix B: Microbial Response to the Introduction of Fracturing Fluid Methods ...... 108

Sample Collection ...... 108

Microcosm Setup ...... 108

Sampling Procedure ...... 111

DNA Extraction, PCR Amplification and Pyrosequencing ...... 112

16s rRNA Gene Sequence Analysis ...... 115

List of Tables

Table 1.1. Ingredients, relative percent composition and purpose of every component within a representative fracking fluid of all horizontal hydraulically fractured wells in

Ohio.……………………………………….……………………………………………..17

Table 1.2. Early and late flowback constituent concentrations from several shale gas productions sites in western Pennsylvania…………………………..…………….……..22

Table 2.1. Summary of dominant genera and their key traits for frack, flowback and produced water samples………………………………………………………………….47

Table 3.1. Key genera with high similarity to biomarkers detected in microcosm experiments, and summary of their significant physiological and metabolic traits……...78

Table A1. Indication of sample type and physical description of fluids sample upon receipt for the three wells…………………………………………………………….....103

Table B1. The content of the synthetic frack fluid by component and their respective disclosed ingredients……………………………………………………………………110

List of Figures

Figure 1.1. Ohio geologic profile cross-section showing formation name, bedrock, source, and approximate depth………………...…...………...……………………...……2

Figure 1.2a. Extent and depth to Marcellus shale base…...…………...……...... ………...5 Figure 1.2b. Extent and depth to Utica shale base…………………..……………………6 Figure 1.3. The numbers of drilling permits issued by month from April 2006 through

March 23, 2013 by the Ohio Department of Natural Resources for the Marcellus and

Utica shale formations………………….…………………….…………………………...8

Figure 1.4. Marcellus shale image showing nanoscale pores visible in the kerogen (light deposits) within inorganic matter (dark deposits)………………………………………..11

Figure 1.5. Depiction of vertical and horizontal wellbores with corresponding steel and cement casing layers in a horizontally-fractured well…………………………………...14

Figure 1.6. Mapped fracture treatments in Marcellus shale indicating the true vertical depth of horizontal well perforations and height of propagated fractures in relation to known aquifer depths………………………………………………………………...…..15

Figure 1.7. 20/40 SLC resin-coated sand and CARBOEconoprop 20/40, a lightweight ceramic proppant……………………………………………………………………...….19

Figure 1.8. Class II brine injection well locations in Ohio…………………...……...….24

Figure 1.9. Geomicrobial processes and environment at a shale-sandstone interface…..26

Figure 2.1a. Total dissolved solids (TDS) concentration versus days post fracturing for frack and flowback samples obtained from three hydraulically fractured wells in the

Marcellus shale…………………………………………………………………………..33

Figure 2.1b. Dissolved organic carbon (DOC) concentration versus days post fracturing for flowback samples obtained from three hydraulically fractured wells in the Marcellus shale. ………..…………………………………………………………………………...34

Figure 2.2. The number of observed biomarker operational taxonomic units (OTUs) at the genus level through time for Wells 1-3………..……………………………………..35

Figure 2.3a. Microbial community compositions at the genus level in terms of percent

16s rRNA for a subset of fluid samples from Well 1 in the Marcellus shale, June-August

2012……………………………………………………………………………………....36

Figure 2.3b. Microbial community compositions at the genus level in terms of percent

16s rRNA for a subset of fluid samples from Well 2 in the Marcellus shale, June-August

2012………………………………………………………………………………….…..37

Figure 2.3c. Microbial community compositions at the genus level in terms of percent

16s rRNA for a subset of fluid samples from Well 3 in the Marcellus shale, June

2012…………...……………………………………………………………………….…37

Figure 2.4a. Percent of 16s rRNA community through time for key genera in Well

1…………………………………………………………………………………………..39

Figure 2.4b. Percent of 16s rRNA community through time for key genera in Well

2…………………………………………………………………………………………..39

Figure 2.4c. Percent of 16s rRNA community through time for key genera in Well

3…………………………………………………………………………………………..40

Figure 2.5a. Temporal diversity indices for Well 1 which include the number of OTUs,

Shannon-Weiner Index (H’), and Jaccard Index (J)……………………………….…….41

xii

Figure 2.5b. Temporal diversity indices for Well 2 which include the number of OTUs,

Shannon-Weiner Index (H’), and Jaccard Index (J)………………………… ……….....41

Figure 2.5c. Temporal diversity indices for Well 3 which include the number of OTUs,

Shannon-Weiner Index (H’), and Jaccard Index (J) …………………….…………...….42

Figure 2.6. Comparison at the genus level between the frack fluids of all wells at a distance of 0.03, and indication of Jaccard Index value (J)…………..………………….43

Figure 3.1. Dissolved organic carbon (DOC) concentration through time across several microcosm treatments. Ambient denotes biotic aerobic 0%; BA denotes biotic aerobic;

BAn denotes biotic anaerobic…………………………….……………………………...55

Figure 3.2a. Dissolved oxygen concentrations through time across several microcosm treatments. Ambient denotes biotic aerobic 0%; BA denotes biotic aerobic; BAn denotes biotic anaerobic………….……………………………………………………………….56

Figure 3.2b. Iron concentrations through time across several microcosm treatments.

Ambient denotes biotic aerobic 0%; BA denotes biotic aerobic; BAn denotes biotic anaerobic…………………………………………………………………………………57

Figure 3.2c. Sulfate concentrations through time across several microcosm treatments.

Ambient denotes biotic aerobic 0%; BA denotes biotic aerobic; BAn denotes biotic anaerobic……………………………...……………………………………………...…..58

Figure 3.3a. Temporal diversity indices for the ambient biotic aerobic treatment (no or

0% added synthetic frack fluid), which include the number of OTUs, Shannon-Wiener

Index (H’), and Jaccard Index (J) at the genus level……………………………………..59

xiii

Figure 3.3b. Temporal diversity indices for the biotic aerobic treatment containing 25% synthetic frack fluid concentrations, which include the number of OTUs, Shannon-

Wiener Index (H’), and Jaccard Index (J) at the genus level…………………………….60

Figure 3.3c. Temporal diversity indices for the biotic aerobic treatment containing 100% synthetic frack fluid concentrations, which include the number of OTUs, Shannon-

Wiener Index (H’), and Jaccard Index (J) at the genus level……………..….…..………61

Figure 3.3d. Temporal diversity indices for the ambient biotic anaerobic treatment (no or

0% added synthetic frack fluid), which include the number of OTUs, Shannon-Wiener

Index (H’), and Jaccard Index (J) at the genus level……………………………………..62

Figure 3.3e. Temporal diversity indices for the biotic anaerobic treatment at 25% synthetic frack fluid concentration, which include the number of OTUs, Shannon-Wiener

Index (H’), and Jaccard Index (J) at the genus level……………………………..……....63

Figure 3.3f. Temporal diversity indices for the biotic anaerobic treatment at 100% synthetic frack fluid concentration, which include the number of OTUs, Shannon-Wiener

Index (H’), and Jaccard Index (J) at the genus level…………………....…………..…....64

Figure 3.4a. Microbial community compositions at the class and genus level in terms of percent 16s rRNA for a subset of microcosm samples from the biotic aerobic and biotic anaerobic treatments at 0% synthetic frack fluid concentration. ………………………..67

Figure 3.4b. Microbial community compositions at the class and genus level in terms of percent 16s rRNA for a subset of microcosm samples from the biotic aerobic treatment at

25% synthetic frack fluid concentrations………………………………..……………….68

xiv

Figure 3.4c. Microbial community compositions at the class and genus level in terms of percent 16s rRNA for a subset of microcosm samples from the biotic aerobic treatment at

100% synthetic frack fluid concentrations….……………………….………..………….69

Figure 3.4d. Microbial community compositions at the class level in terms of percent 16s rRNA for a subset of microcosm samples from the biotic anaerobic treatment at 25% synthetic frack fluid concentrations………………………………….……………….….70

Figure 3.4e. Microbial community compositions at the class level in terms of percent 16s rRNA for a subset of microcosm samples from the biotic anaerobic 100% synthetic frack fluid concentrations……….………………………..….…………………………..……..71

Figure 3.5. Microbial community composition comparison in terms of percent 16s rRNA between the duplicate controls: the biotic aerobic treatment at 25% synthetic frack fluid concentrations on day 4………………………..…………………….....…………….….72

Figure B1. Treatment summary for microcosms outlining aerobic biotic, aerobic abiotic, anaerobic biotic and anaerobic abiotic treatments at a concentration of 0, 25, 50 or 100% synthetic frack fluid, run in duplicate…………………………………………………..111

Chapter 1: Introduction

Brief History of Oil and Natural Gas Development in Ohio

The state of Ohio has a long and successful history of oil and gas development starting in 1814 with the discovery of oil in Noble County (Ohio Oil 2011). Oil production began in earnest in 1860, followed by commercial natural gas production two decades later in 1884. Often considered to be the state’s peak year, 24 million barrels of oil were produced in Ohio in 1896 (Alkire 1951). A noteworthy 6,399 oil wells were drilled in a single year, 1899, to further exploit the discovery of substantial reserves within the state (Alkire 1951). Oil and gas production, which occurs in 76 of Ohio’s 88 counties, occurs predominantly within the eastern portion of the state (Ohio Oil 2011).

With just over 264,000 drilled wells, the state is considered to be highly active in regards to its oil and gas industry compared to others in the nation’s ranks.

Ohio oil and gas exploration history is best characterized by several boom stages, the first of which began in 1884. This stage, termed the Lima-Findlay Trenton Oil Boom, was a result of the discovery of the Trenton limestone field and placed Ohio as the nation’s leading oil producer at the time (Ohio Oil 2011). Concomitantly to the Lima-

Findlay were the Berea and Shallow Sands Boom. Eastern plays, known as the Berea,

Germantown, Macksburg, Big Injun, Cow Run and Weir, were discovered and exploited at this time (Figure 1.1).

Figure 2.1 Ohio geologic profile cross-section showing formation name, bedrock, source, and approximate depth (taken from Ohio Department of Natural Resources 2012).

Early Exploration Techniques

Limestone plays, such as the Trenton, are highly permeable and therefore result in high-volume oil production. The previously enumerated eastern plays of the Berea and

Shallow Sands Boom are sandstone and naturally possess an adequate degree of porosity 2 and permeability. Economic exploitation of these formations depended upon the application of an early technique of oil and gas well development, known as nitro-shot stimulation (Ohio Oil 2011). First successfully used in 1867, nitro-shot stimulation is a form of high energy fracturing which utilizes the explosive power of nitroglycerin to fracture a formation (Analog 2010).

The first successful commercial hydraulic fracture job was completed in 1949 in the Texas Barnett shale by Halliburton (Montgomery 2010). The introduction of vertical hydraulic fracturing technology in the early 1950’s dramatically increased well completions and yields, renewing interest in previously condemned “dry” wells. The

Clinton sandstone play in Fairfield County particularly benefited from this new stimulation technology (Ohio Oil 2011). Ultimately, both the Clinton and Berea plays were heavily developed from 1970-1981 due to rising oil and gas prices and demand for local natural gas supplies. As of 2010, 64,378 wells were operating in Ohio (McCormac

2010). Ultimately, the first successful application of the modern technique of horizontal slickwater hydraulic fracturing occurred in 1998 (Trembath 2012).

Recent Development in Ohio’s Marcellus and Utica Shale

Energy from natural gas and natural gas plant liquids constituted approximately

34% of American energy production in 2011 with shale gas as the largest source to the

US natural gas supply (US, EIA 2011). Providing for the projected US natural gas consumption of around 25 trillion ft3/year by 2035 necessitates the rapid stimulation of proven shale gas reserves (US, EIA 2013).

The exploration of the Marcellus and Utica shale resources in the northeast region has revived interest in Ohio’s oil and natural gas supply. This new development phase has been brought about by recent advancements in horizontal hydraulic fracturing

(hydrofracking) technologies. Highly politicized due to its extensive application on shale plays in various states such as Pennsylvania, North Dakota and Oklahoma, the technique of hydrofracking is exceedingly controversial (Nolon 2012). Perceived public fear, whether valid or untenable, is that the hydrofracking technique causes water contamination, depletion of potable surface water resources, and detrimental health affects from chemicals found in fracturing fluids and reduced air quality (NY State 2011).

Particular controversy surrounds the practice of nondisclosure due to proprietary rights of industry leaders in regards to fracturing fluid chemical content (Patrick 2011).

Regardless of the tenability of these factors, the hydrofracking industry, as applied to Ohio’s Marcellus and Utica shale resources, will continue to burgeon as the newest stage of natural gas development in the state. Located in the eastern portion of

Ohio, the Marcellus shale formation is found between 2,000 to 9,000 ft below the surface and can be anywhere from less than 50 ft to more than 350 ft thick, thinning toward southwest (Figure 1.2a) (Penn State MCOR 2013a). Current estimates indicate that the

Marcellus formation may yield up to 13.8 trillion m3 of natural gas (Engelder 2009).

Western-lying Utica shale is found at depths less than 2,000 ft to greater than 14,000 ft below ground surface with thicknesses ranging between 100 and 500 ft (Figure 1.2b)

(Penn State MCOR 2013b).

Figure 1.2a Extent and depth to Marcellus shale base (taken from the Penn State Marcellus Center for Outreach and Research, 2013).

Figure 1.2b Extent and depth to Utica shale base (taken from the Penn State Marcellus Center for Outreach and Research, 2013).

Ordovician-aged Utica shale is of particular interest to industry as it has yielded valuable natural gas liquids (i.e. ethane, butane and propane) in addition to large quantities of natural gas (Junkins 2012). Initial estimates from the Ohio Geological

Survey indicate that the Utica shale could yield between 1.3 and 5.5 billion barrels of oil and between 3.8 and 15.7 trillion cubic feet of natural gas (OGS 2010).

Due to its economic value, exploration and development of Utica shale has significantly outpaced that of the Marcellus in Ohio (Figure 1.3). As of February 2013,

236 wells have been drilled out of 518 wells permitted in the Utica, in comparison to 20 wells permitted and only 7 drilled in the Marcellus (ODNR 2013). The Ohio Oil and Gas

Energy Education Program estimates that more than 3,400 wells will be completed by

2016, primarily in the Utica shale (OOGEEP 2011). It is expected that many of these wells will involve horizontal drilling and hydraulic fracturing techniques.

45 Marcellus 40 Utica

15 PermitsIssued

0 Jul-11 Jul-11 Jul-09 Jul-12 Oct-11 Oct-11 Jan-11 Jan-11 Jun-11 Oct-10 Oct-12 Apr-06 Apr-12 Jan-12 Jun-12 Jan-13 Mar-11 Mar-11 Feb-11 Feb-11 Nov-11 Nov-11 Dec-11 Aug-11 Aug-11 Sep-11 Mar-12 Mar-13 Feb-10 Feb-12 Feb-13 Nov-10 Dec-10 Nov-12 Dec-12 Aug-09 Aug-12 Sep-12 May-11 May-11 May-12 Date Issued Figure 1.3 The numbers of drilling permits issued by month from April 2006 through March 23, 2013 by the Ohio Department of Natural Resources for the Marcellus and Utica shale formations (data compiled from the Ohio Department of Natural Resources 2013).

The Formation of Hydrocarbons in the Marcellus and Utica Shale

The black shales of the Marcellus and Utica formations were deposited 390 and

450 million years ago, respectively, in the Appalachian basin of Northeastern United

States (Lee 2011). Deposition began when organic rich terrestrial sediments collected in a depressed anoxic marine basin (Barrett 2008). Highly reducing conditions prevented the organic matter in the sediment from oxidizing. The shale’s black coloring is attributed to the subsequent mineral reactions and minimal aerobic decay rates which led to significant organic carbon accumulation. 8

The Marcellus and Utica shale contain upwards of 2-10% organic matter content and up to 16 wt% total organic carbon (Blatt 1996; Petsch 2005; Tourtelot 1979; Schlegel

2010, Nyahay 2007). In context with other soil types, desert topsoils can contain less than

1% organic matter while upland soil contains 1-6% and wetlands contain up to 90%

(Troeh 2005).

Shale is a carbonaceous, fine-grained sedimentary rock comprised of silt and clay- sized mineral particles (Sedimentary Rock 2011). The mineral composition of these clay particles usually consists of quartz, illite, calcite, kaolinite, smectite, feldspar and chert

(Laughley 2011). Dependent upon the depositional conditions (sedimentation rates, organic activity and oxygen availability), shale may also include various compositions of carbonate, iron oxide and sulfide minerals (Tourtelot 1979). Trace metals such as Co,

Mo, Ni, V and Zn are also regularly present in shale deposits (Liermann 2011).

After deposition, the sediment then goes through diagenesis wherein the organics and inorganics lithify and undergo biogeochemical changes to kerogen (Figure 1.4)

(Bloch 1992). Kerogen is a waxy mixture of metamorphosed organic chemical compounds (Bloch 1992). During diagenesis, organic carbon transforms into hydrocarbon-associated products when it reaches temperatures greater than 100˚C and is buried at a depth of 2-4 km (Marshal 2004). At this depth temperatures progressively convert organic carbon to kerogen then to oil, tar and natural gas. At temperatures exceeding 160°C any residual tar and oil forms into natural gas (Marshal 2004). Early petroleum generation during Marcellus diagenesis began 240 million years ago at a depth of 2.7 km and a temperature of 100˚C (Ryder 1998). The main petroleum generation

9 phase occurred 230 million years ago at a maximum burial depth of 3.1 km where temperatures exceed 120˚C (Ryder 1998).

At 280 million years ago, the Utica was buried at a depth of approximately 3.1 km and began generating about 10-25% of its eventual petroleum content (Ryder 1998). 260 million years ago at 3.5 km the Utica generated the majority of its petroleum at temperatures exceeding 130˚C (an additional 25-65%) (Ryder 1998). Late generation of petroleum in the Utica began at maximum burial at 4.4 km 230 million years ago where temperatures exceeded 150˚C (Ryder 1998). Temperatures and pressures during maximum diagenesis burial effectively sterilized both the Marcellus and Utica formations

(Schlegel 2010). Current formation pressures and temperatures of the Marcellus and

Utica vary regionally but fall within the range of 12-55 mPa and 15-69˚C, and 12-85 mPa and 15-107˚C. These ranges are based off a 25˚C/km and 20 mPa/km earth temperature and pressure gradient, respectively (Fridleifsson 2008, Jones 2010, Driscoll 1986).

Figure 1.4. Marcellus shale image showing nanoscale pores visible in the kerogen (light deposits) within inorganic matter (dark deposits), taken using a Helios NanoLab Dual Beam system from FEI (courtesy of imaging-git.com).

Physical Characteristics of Shale

Shale formations have low natural porosity and permeability unlike traditional limestone and sandstone targets. Sandstone porosity (5-30%) and limestone porosity (5-

50%) significantly exceed shale porosity at 1-10% (Myers 2008, Kovacik 2006). Throat diameter (the diameter of pores) is <0.03-0.2 µm in shale and 0.06-13 µm in sandstone

(Frederickson et al. 1997). In addition, low shale pore connectivity inhibits economical natural gas extraction (Lee 2011). 11

Prior to fracturing, natural shale permeability (10-21 – 10-17 m2) is 11 to 7 orders of magnitude lower than sandstone (10-10 m2) and 9 orders of magnitude lower than limestone (10-12 m2) (Lee 2011, Myers 2008). Due to low natural permeability shale strata act as hydrocarbon seals (Milici et al. 2006). Natural gas is found in pores, fractures and adsorbed onto organics and minerals (Agbaji et al. 2009). Marcellus shale gas water

3 content is around 1.1 g H2O/m gas (Lee 2011).

These physical characteristics are why the Marcellus and Utica deposits are classified as unconventional natural gas reservoirs, in that these reservoirs were historically uneconomical to develop. However, current technological advances in horizontal drilling and hydraulic fracturing technology have the potential to increase shale permeability up to 7 orders of magnitude, thereby allowing for more economical natural gas extraction (Lee 2011).

Origin of Methane in Marcellus and Utica Shale

Methane can be formed from biogenic activity, such as methanogenesis, or thermogenic origin, via intense heat and pressure (Naturalgas.org). Natural gas derived from the Marcellus and Utica formations appear to originate from thermogenic as opposed to biogenic methanogenesis (Osborn 2010). Natural gas consists of 70-90% methane, 0-20% ethane, propane and butane, 0-8% carbon dioxide, as well as small amounts of oxygen, nitrogen, and hydrogen sulphide (Naturalgas.org). When consisting predominantly of methane, natural gas is considered dry, which differs from wet gas containing heavier natural gas liquids such as ethane (Naturalgas.org).

Horizontal Hydraulic Fracturing Technique

Drilling for a hydrofracking operation involves vertical drilling to the desired depth, then directional or horizontal drilling into the targeted shale deposit. Horizontal drilling lines can extend 2,000-5,000 feet out from the vertical drill shaft portion of the well (Figure 1.5) (Beauduy 2009). Horizontal drilling maximizes the fractured surface area and intersects natural vertical fracture networks (Chesapeake 2011, Engelder et al.

2008). As both the vertical and horizontal wellbores are drilled, five to seven layers of casing and corresponding cement are sequentially installed to maximize wellbore stability and integrity, particularly within the aquifer regions used for water resources (Figure 1.5)

(Ottaviani 2009). A perforating gun with directional explosive charges successively perforates sections of the horizontal line’s casing and cement to target specific fracture zones. Maintaining adequate downhole pressure to stimulate the entire lateral length at one time is unlikely (Overbey 1988). Consequently, the formation is fractured in multiple stages, usually around 500 ft per stage, with the application of large quantities of frack fluid at high pressures (48-68 mPa) into the borehole (Chesapeake 2011, Barbot 2013).

Figure 1.5. Depiction of vertical and horizontal wellbores with corresponding steel and cement casing layers in a horizontally-fractured well (courtesy of energyfromshale.org).

Slickwater fracturing, as opposed to oil, alcohol or gel-based fracturing, tends to produce long slender fractures (Kundert and Mullen 2009). These tensile fractures tend to grow vertically, perpendicular to the minimal fracture force, which is horizontal

(Maxwell 2011). Consequently, these hydraulic fractures will connect with any natural 14 formation fractures, creating a large stimulation network (Gaurav 2012). Geomechanical conditions which tend to restrict hydraulically-generated fracture growth include formation compressibility and stress load (Maxwell 2011). Composite layering in shale also limits fracture height as the fracture terminates at the interface between two layers

(Maxwell 2011). On average, fractures tend to reach an upward height of 80 m and a downward depth of 73 m, often with higher lateral than height length (Maxwell 2011,

Fisher 2011). However, hydraulically-induced fractures in the Marcellus have extended over 600 m vertically above the targeted formation (Figure 1.6) (Fisher 2010). The discrepancy between upward and downward fracture length is due to decreased stress at shallower depths and frack fluid buoyancy effects (Maxwell 2011).

Consequently, the depth differential between the average fracture heights and groundwater aquifers is frequently more than 1 km, discounting theories of frack fluid migration from fractures to groundwater aquifers (Maxwell 2011, Fisher 2010). Once fracturing is complete, a period of flowback begins as a mixture of fracking and formation fluids return to the surface.

Hydraulic Fracturing Fluids

Frack fluids are comprised of 98-99.5% water and proppant with the remainder comprised of chemical additives (FracFocus 2013a; Chesapeake 2012, GWPC & ALL

Consulting 2009, Lee et al. 2011). Average frack fluid content in Ohio effectively aligns with national figures, comprising of 99.27% water and proppant and 0.73% chemicals

(Table 1.1). Over 375 chemical compounds are reported to be in use in hydraulic fracturing operations (US EPA 2012). These compounds were reported by FracFocus and nine service operators, estimated to have conducted around 95% of fracturing services in the United States in 2003, and consequently offer a comprehensive picture of chemical additives in use today (US EPA 2004).

Additive use is dependent upon geological formation characteristics, fracturing stage and chemical characteristics of the water supply (Arthur 2008, Barbot 2013). The purpose behind each of these components is outlined in Table 1.1. Some chemicals are encountered in common household and food products such as the surfactant isopropanol, which is used as a component in multi-surface cleaners and hair color products

(Hydraulic 2011). In particular, biocides target sulfur-reducing and acid producing

16 bacteria which contribute to the biofouling of the wellbore. These bacteria proliferate in the microenvironments created by biofilms (Cripps 2010).

Table 1.1. Ingredients, relative percent composition and purpose of every component within a representative fracking fluid of all horizontal hydraulically fractured wells in Ohio. (Raw data obtained from FracFocus.org, 2012)

Proppant, as its name implies, props the fractures open across the height and length of the fracture while simultaneously maintaining a permeable pathway for gas extraction (LaFollette 2010). Proppants derive from various sources and include natural and resined sands, sintered bauxite, ceramics, glass and synthetic composites (Figure 1.7)

(Economides 1989). Improper design or pre-processing of proppant can obstruct the nanodarcy-scale permeability of the fracture network (LaFollette 2010, Kaufman and

Penny 2008). Additional fracturing stages from increased length of horizontal wells requires ten times more proppant than is traditionally used, which can amount to 3-5 million lbs of proppant (Beckwith 2011). Consequently, demand for raw proppant materials has risen sharply within the past five years, such as in the demand for sandstone in Texas, Oklahoma and the upper Midwest to yield sand proppant (Masterson 2011;

Jones 2006).

Figure 1.7. 20/40 SLC resin-coated sand (left) and CARBOEconoprop 20/40, a lightweight ceramic proppant (right). (Taken from Santrol Proppants (Beckwith 2011)).

An average well in Ohio requires approximately 5.8 million gallons of water to be fractured, based off of raw data from FracFocus 2012. This water is often drawn from shallow surface or subsurface aquifers, municipal supplies or recycled from a previous frack operation (Chesapeake 2011). States with longer histories of shale gas development have established commissions to regulate water withdrawals on the scale needed for hydraulic fracturing. Pennsylvania, for instance, instituted the Susquehanna River Basin

Commission to document water withdrawals and applied use regarding regional

Marcellus gas shale development (Veil 2010). Within Ohio, the Department of Natural

Resources, the Division of Soil and Water Resources, regulates water usage for commercial purposes (ODNR Water Withdrawal 2012).

Section 1521.16 of the Ohio Revised Code requires any facility with the capacity to withdraw greater than 100,000 gallons of water per day to register with the Ohio

Department of Natural Resources Division of Soil and Water Resources (ODNR Water

Withdrawal 2012). In addition, section 1501.32 of the Ohio Revised Code requires a permit to divert more than 100,000 (capped at 2 million) gallons per day over a 30-day period out of the Ohio River basin into the Lake Erie basin (ODNR Water Withdrawal

2012). These regulations are in place to prevent the egregious misuse or overuse of water resources by the shale oil and gas industry.

Flowback and Produced Water

As much as 10-70% of frack fluid ultimately resurfaces alongside formation brines, constituting “flowback” prior to well production (GWPC and ALL Consulting,

2009; US EPA, 2011f). Total flowback percentage varies by region and is ultimately determined by formation characteristics and the operating parameters of the well

(Gregory 2011). As flowback volume diminishes the well is placed into production.

Fluids recovered concomitantly with gas during well production constitute “produced water” (King 2010, Barbot 2013). Produced water, in addition to natural gas, is coproduced with natural gas liquids, such as ethane, propane and butane.

Both fluids contain fractions of brine and organics and minerals dissolved off the producing formation. High levels of total dissolved solids (TDS), total suspended solids, strontium, barium, bromide, chloride, sodium, magnesium, calcium and organic carbon characterize flowback fluids and produced water (Chapman 2012, Blauch 2009). The high concentrations result from interactions between the frack fluid, brines at depth, and 20 the producing formation, which in itself may be a source of salinity (Blauch 2009, Barbot

2013). TDS, in particular, often exceeds 200,000 mg/l (Chapman 2012). In context, seawaters and salt lakes are defined as having an upper limit of 50,000 mg/l (Al-Malahy

2003). Organic carbon derives from the source rock and chemical additives in the form of alkanes, and aliphatic and aromatic hydrocarbons (King 2010). Low sulfate and carbonate concentrations also characterize flowback fluids (Barbot 2013). Reduction in sulfate concentrations may be due to barium sulfate precipitation and low natural sulfate levels in the formation (Barbot 2013).

In addition, these fluids contain elevated levels of naturally occurring radioactive material (NORM) that originate from the shale’s minerals (Alley 2010). In part, fluid content is dependent upon its interaction time with the shale play. Consequently, TDS levels in produced water and late flowback can increase four-fold over that of early flowback (Table 1.2). Similarly, total suspended solids increase over 100-fold between early and late flowback (Table 1.2).

Table 1.2. Early and late flowback constituent concentrations from several shale gas productions sites in western Pennsylvania. “Total” denotes the sum of dissolved and suspended solid phase concentrations. Data adapted from Gregory 2011. Constituent Early Flowback Late Flowback

(mg/l) (mg/l)

TDS 66000 261000

TSS 27 3200

Strontium 1400 6900

Total barium 2300 4700

Bromide 720 1600

Chloride 32000 148000

Sodium 18000 44000

Total calcium 3000 31000

Sulfate ND 500

Management of Flowback Fluids

As the hydrofracking process requires vast amounts of water, concern over the depletion of public drinking water and agricultural supplies and in some cases the exacerbation of local drought conditions has led industry professionals to adopt improved water management strategies. The practice of on site recycling of wastewater increases as disposal costs and water usage concerns grow. Ohio requires operators to either recycle or inject their flowback into Class II brine deep injection wells (ODNR Wastewater

2012). 22

Physical and chemical characterization of water is an initial step in determining treatment and management strategies. These aforementioned constituents regularly exceed maximum contaminant levels (MCLs) established by the US EPA. For example, the US EPA MCLs for TDS, barium, and chloride are 500, 2, and 250 mg/l, respectively

(US EPA 2009). Consequently, these fluids will either be treated for reuse, discharged into surface waters post-treatment or disposed of through underground injection wells

(Figure 1.8) (Kharaka et al. 2008). Recycling techniques include filtration, metal precipitation for removal, ion exchange, and reverse osmosis (Fracturing 2011, Barbot

2013). Dissolved solids, organic compounds and trace metals must be removed to a sufficient degree for successful reuse (Sirivedhin 2004). For example, reuse is limited by high calcium, barium and strontium concentrations which pose scaling issues if present in recycled water (Gregory 2011, Barbot 2013). Apart from chemical parameters, wastewater managers should also consider microbial parameters when evaluating management options.

Figure 1.8. Class II brine injection well locations in Ohio (taken from the Ohio Department of Natural Resources 2012).

Microbial Sources

Microorganisms associated with fluids that return from wells may derive from varying sources. It is unlikely indigenous subsurface microorganisms co-deposited with the shale remain in the formation due to effective formation sterilization during Marcellus

24 and Utica diagenesis. However, microorganisms could have been introduced into the formation through interconnected fractures during geological-time scale fluid intrusion processes. At present, microorganisms are introduced via drilling and fracturing operations and perhaps via advective groundwater transport into the formation from other recent exploration activities (Li 2007, Chapelle and Lovley 1990, Schlegel 2010).

Nonsterile drilling and fracturing equipment, drilling fluids and water sources all contribute to microbial sources within the subsurface system (Li 2007, Fitcher 2008).

Microorganisms Associated with Shale

Fermentative and syntrophic microorganisms are associated with shale formations

(Figure 1.9) (Fredrickson and Balkwill 2006). Typically, there is low microbial activity in shale because the formation is limited in electron acceptors such as sulfate, Fe(III) and

CO2 (Fredrickson and Balkwill 2006). In addition, these shale-associated subsurface bacteria require interconnected pore throat diameters >0.2 µm for colonization to occur

(Fredrickson et al. 1997). Since shale pore throat diameters range from 0.03-0.2 µm and most known microorganisms range from 0.1-10 µm in diameter, shale-associated microorganisms likely inhabit natural fractures (Fredrickson et al. 1997, Fredrickson and

Balkwill 2006).

Areas of high microbial activity occur in subsurface interfaces between shale and adjacent electron donor limited formations of higher permeability, such as sandstone

(Fredrickson and Balkwill 2006, Krumholz et al. 1999). Carbon and electron donor sources diffuse across the interface stimulating acetogenic and sulfate-reducing bacteria

(Fredrickson and Balkwill 2006). Understandably, we also see these higher areas of 25 microbial activity in natural fracture networks in shales where colonization occurs.

Consequently, creating artificial fracture networks through hydraulic fracturing is likely to alter the subsurface biogeochemistry in significant ways by stimulating microbial activity.

Figure 1.9. Geomicrobial processes and environment at a shale-sandstone interface (Taken from Fredrickson and Balkwill 2006).

Microorganisms Associated with Oil and Gas Operations

The microbial ecology of deep subsurface systems encountered in oil and natural gas production have been studied, in part, due to their role in energy production and industrial technology development. These microbial applications to industrial technology include oil spill remediation, microbially enhanced oil recovery, and biofiltration of volatile hydrocarbons (Prince et al. 1999, Banat et al. 2000, Ergas et al. 1999). 26

Known organisms associated with oil and gas operations are, in general, physiologically characterized as thermophiles, fermenters, acetogens, methanogens, sulfidogens, sulfate reducers, and manganese and iron reducers (Li 2007, Grassia et al.

2007, Davydova-Charakhch’yan et al. 1993, Nilsen & Torsvik 1996, L’Haridon et al.

2005, Rueter et al. 1994, Greene et al. 1997; Slobodkin et al. 1999). Explicitly, bacteria associated with oil and gas operations often belong to the phyla Firmicutes,

Proteobacteria, Thermotogae, and Nitrospirae (Li 2007). Within Proteobacteria, species capable of denitrification and alkane and aromatic hydrocarbon degradation have been reported in these environments (Heylen et al. 2006, Palleroni et al. 2004). Additionally, species within Firmicutes shown in these environments include thermophilic hydrocarbon oxidizers (Riessen and Antranikian 2001, Nazina et al. 2001). Thermotogae include hyperthermophiles tolerant of high sulfide levels (Takahata et al. 2001, Skirnisdottir et al.

2000).

Archaea associated with these operations belong to the genera Methanobacter,

Methanobrevibacter, Methanococcus and Methanothermobacter and class Thermoprotei

(Li 2007). As their names suggest, these organisms are involved in methanogenic and fermentative metabolic processes. Detection of mesophilic organisms, such as

Pseudomonas and Acinetobacter, in production water from these systems can be attributed firstly, to exogenous microbial introduction and secondly, to mesophile survival in production well equipment (Li 2007, Orphan et al. 2000).

Additionally, numerous studies concerning the Deepwater Horizon oil spill in

April 2010 characterize key microorganisms associated with oil operations and, in

27 particular, their capacity as hydrocarbon degraders under high pressures and salinity

(Hazen et al. 2012). A variety of phylotypes are known or suspected participants in microbial mitigation of hydrocarbons during oil spills. The following genera, to name a few, have been reported as capable hydrocarbon degraders: Acinetobacter, Arthrobacter,

Colwellia, Corynebacterium, Cycloclasticus, Flavobacterium, Marinobacter,

Oceanospirillales, Pseudomonas, Pseudoalteromonas and Sphingomonas (Mason 2012,

Redmond and Valentine 2011, Das 2011, Jones et al. 1983, Adebusoye et al. 2007,

Yakimov et al. 2007). At the phyla level, microbial enrichment of Proteobacteria (α, β, γ, and δ-proteobacteria) and Alteromonadales occurs. These organisms are involved in in situ ethane, propane, and simple and polycyclic aromatic hydrocarbon degradation

(Mason 2012, Redmond and Valentine 2011).

The order of microbial hydrocarbon degradation from labile to recalcitrant is as follows: first linear alkanes, then branched alkanes, simple aromatics, cyclic alkanes, and lastly polycyclic aromatics (Perry 1984, Bragg 2009). In general, phylotype richness is low in these high temperature, high salinity, anoxic systems which indicate that extant phylotypes are equipped with ecologically beneficial traits (Li et al. 2006, Li 2007,

Reysenbach et al. 2007).

Conclusion

The oil and gas industry has evolved throughout its almost 200 year history in

Ohio in terms of exploration and production technologies, scale, targeted formations and public interest. The newest era in this history is marked by the recent exploration of

Ohio’s Marcellus and Utica shale resources. In many cases, short and long-term impacts 28 to the environment from this exploration are not well understood as production in the field outstrips conducted research. Consequently, research into microbial community dynamics may yield insight into ecological impacts to the surface and subsurface as a result of shale gas development. In addition, the effects of accidental releases of shale gas-associated fluids on surface and groundwater biogeochemistry are not well understood. Understanding these changes and shifts is key to using microbial community response as a result of shale gas-associated fluid exposure as a timely indicator of surface and groundwater pollution.

The following chapters explore microbial community aspects in shale well flowback fluids and microbial response to synthetic fracturing fluid exposure. Chapter 2 describes microbial community content and dynamics of fluids shift through hydraulic fracturing, flowback and production periods of shale gas stimulation. Chapter 3 investigates how indigenous soil and groundwater communities respond and mineralize a synthetic fracture fluid across a range of redox conditions. Chapter 4 summarizes implications for these observations for industry and practitioners.

Chapter 2: Microbial Community Shifts in Shale Well Flowback Fluids

Introduction

The ecological impacts to microbial communities during shale gas development are largely unknown owing, in part, to the lack of benchmark data which characterize ambient microbial or geochemical conditions. The introduction of novel organisms to the subsurface via drilling operations and injection of frack fluid alters the subsurface in undetermined ways. We are currently aware of two studies that have investigated microbial aspects of flowback fluids from shale. These studies have come from various flowback and produced fluids from Texas Barnett shale wells. Data suggest that various

Proteobacteria and Actinobacteria are present in initial frack fluids, and that Firmicutes dominate flowback fluids (Structhemeyer and Elshahed 2011). These organisms were characterized as halotolerant, non-spore-forming thermophiles (Structhemeyer and

Elshahed 2011).

Microbial community response during oil development and large-scale oil spills are characterized by enrichment in known petroleum degraders, low diversity, high hydrocarbon degradation rates, and preferential attenuation of simple over complex hydrocarbon compounds (Hazen et al. 2010, Mason et al. 2012, Valentine et al. 2010,

Valentine et al. 2011). This study focuses on investigating how microbial communities initially present in hydraulic fracturing fluids responded to the addition of chemicals, 30 fluid injection to the subsurface, hydraulic fracturing, and ultimately fluid flowback to the surface. The study builds on existing work by observing community dynamics through a coarse temporal series in multiple boreholes that were hydraulically fractured on one wellpad.

We hypothesized that 1) the microbial ecology of these fluids would shift from one dominated by microbes present in source waters to one consistent with a brine system, and that 2) the microbial diversity in these fluids would decrease through time.

This study, which also seeks to provide insight into microbial community dynamics observed in shale gas-associated fluids, reports similar findings to those previously mentioned during oil development, which may imply that a level of hydrocarbon biodegradation capacity is intrinsic to microbial communities associated with shale gas fluids. Characterizing these fluids may aid well operators in maximizing natural gas recovery and practitioners in making informed decisions on wastewater management strategies.

Methods

To determine these microbial community dynamics a series of fracking and flowback fluids and produced waters were sampled between 8 June 2012 and 29 August

2012 by personnel from the Department of Energy’s National Energy Technology

Laboratory (Pittsburgh, PA) from a hydraulically fractured site located in Carmichaels,

Pennsylvania within the Marcellus shale (see Appendix A for a further description of samples and methods). Frack and flowback fluid samples from the three boreholes cover a period of approximately 2 weeks. After a break in sampling, produced water samples 31 are available for 49 and 82 days. The privately operated site is comprised of one wellpad with three communicating 8,000-ft deep, 7,000 ft long, horizontally fractured boreholes.

All three boreholes were fractured with a mixture of recycled and freshwater-derived fracking fluid.

In total, the microbial and select geochemical properties of 32 fluid samples from three different wellbores were analyzed (Appendix A). Note that no fluid samples were available beyond one week for Well 3, as flowback volume waned for this well.

Consequently, geochemical and microbial data after this time cannot be determined. For tracking of microbial community dynamics, cells were separated from fluid samples by filtration (0.22 µm) and/or centrifugation. Total nucleic acids were extracted from biomass using the Powersoil DNA Isolation kit (MoBio, Carlsbad, CA). Biomarkers from the 16S rRNA gene were amplified using Polymerase Chain Reaction (PCR) and primers targeting the V4 region. Sequencing was conducted using Sanger sequencing and multiplex 454-pyrosequencing approaches. NCBI Blast and Mothur programs were used in data reduction to generate clone libraries and construct community profiles. Specific details on laboratory and computational methods can be found in Appendix A.

Results

The general trend in flowback fluid geochemical evolution is evident in total dissolved solid (TDS) concentrations, which represent the general level of salts within a system. TDS concentrations increased through time for all wells, transitioning from levels initially consistent with brackish water to those consistent with brine systems within about 5 days (Figure 2.1a). The TDS concentrations of produced fluids ended at 32 concentrations greater than 60 g/l after more than two months (data not included in

Figure 2.1a). The final concentrations represent a TDS concentration increase of 70-84%.

Dissolved organic carbon (DOC) concentrations exhibited an inverse trend to TDS, with levels decreasing throughout the flowback period for all wells (Figure 2.1b).

Concentrations decreased by 36-59% between the injected fracturing fluid concentrations and the first flowback samples. Overall concentrations (from the initial injected fluid to the end of the produced fluids) decreased between 53-78% across all three wells.

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Significant reductions in microbial biodiversity were evident in 16S rRNA biomarkers in injected and flowback fluids for all three wellbores. Within the first week, we observed a 75-85% decrease in the number of operational taxonomic units (OTUs), or genus in this case (Figure 2.2). Microbial biomarkers detected after 2.5 months represented an overall 57-65% reduction in OTUs from the initial fracturing fluid concentration. Interestingly, Well 1 began and ended with approximately 2 times the genus abundance present in the other wellbores (Figure 2.2).

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Sequence analysis of temporal samples indicated a rapid and dramatic shift in the relative abundance of OTUs across this time period (Figures 2.3a-c). Biomarkers observed in the fracturing fluid samples were closely related to typical mesophile communities found in surface waters and groundwater environments, with slight intrusions by marine biomarkers that likely represent recycled fluids. Biomarkers observed in flowback and produced fluid samples had high similarity (89 to 100%) to those found in ocean or other saline environments. Noted metabolisms of closely related species included anaerobic, halotolerant and thermophilic bacteria capable of oxidizing alkanes and aliphatic and aromatic hydrocarbons.

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Figure 2.3b. Microbial community compositions at the genus level in terms of percent 16s rRNA for a subset of fluid samples from Well 2 in the Marcellus shale, June-August 2012.

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Figure 2.3c. Microbial community compositions at the genus level in terms of percent 16s rRNA for a subset of fluid samples from Well 3 in the Marcellus shale, June 2012.

Fracturing fluid microbial profiles (day 0 in Figures 2.3a-c) were dominated by

16S rRNA biomarkers with high similarity (cutoff threshold 97%) to Pseudomonas (6-

34%), Cobetia (5-68%), Leuconostoc (0-5%), Pseudoalteromonas (0-14%), Arcobacter

(4-6%), and Marinobacterium (2-9%) species. Early flowback fluid samples (4-9 days in

Figures 2.3a-c) were dominated by biomarkers with high similarity to Arcobacter (0-

50%), Halolactibacillus (0-99%), Marinobacterium (0-32%) and Vibrio (0-26%) species.

Late flowback fluid samples (10-13 days in Figures 2.3a-c) were dominated by biomarkers with high similarity to Halolactibacillus (17%), Idiomarina (31%), and

Marinobacter (51%). Produced fluids (49 and 82 days in Figures 2.3a-b) are characterized by the dominance of Halanerobium (67-91%), Clostridium (3-6%),

Anaerobaculum (8-15%), Selenihalanaerobacter (0-4%), and Idiomarina (0-5%).

The enrichment or reduction of seven key genera and other unclassified sequences was plotted through time for all wellbores (Figures 2.4a-c). In all three wells, initial dominant biomarkers (Pseudomonas in Well 1 and 3, and Cobetia in Well 2) are replaced by enrichment in Arcobacter and Halolactibacillus species during initial flowback, with a combination of Marinobacter and Halolactibacillus species in later flowback samples

(Figure 2.4a-c). As the well advances into production, Halolactibacillus is outcompeted by Halanaerobium which ultimately also comprises more than 67% of detected biomarkers in Wells 1 and 2 (Figure 2.4a-b).

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Figure 2.4c. Percent of 16s rRNA community through time for key genera in Well 3.

Two common ecological indices were used to characterize microbial biodiversity in this study, including the Shannon-Wiener Index and the Jaccard Index. The Shannon-

Wiener Index describes both the abundance and evenness of the OTUs while the Jaccard

Index quantifies the similarity of detected OTUs between any two samples. In this case,

Jaccard comparisons were made between background or initial fracturing fluid samples and respective temporal samples to assess overall diversion within a wellbore from injected fluids. The Jaccard Index ranges from 0-1, with 1 indicating identical OTU makeup and 0 representing no shared OTUs. The Shannon-Wiener Index showed a decreasing trend for all three wellbores (Figures 2.5a-c), suggestive of a reduction in both biodiversity and evenness of the microbial communities. Interestingly, the lowest

Shannon-Wiener values were observed after one week, suggesting an initial die-off from injected fluids to a bloom in native or persistent species after a lag or adaptation period. 40

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Figure 2.5b. Temporal diversity indices for Well 2 which include the number of OTUs, Shannon-Weiner Index (H’), and Jaccard Index (J).

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As expected, Jaccard Indices generally decrease with time for fluids in all three wellbores, with final communities having only approximately 20% of initial members

(Jaccard Index of 0.17-0.19 in Figures 2.5a and 2.5b). Given that approximately one million gallons of flowback are typically mixed with four million gallons of freshwater prior to injection of fracturing fluids (1:5 dilution ratio), this percentage of similarity is consistent with the estimated rate of dilution in recycled fluids. A Jaccard Index analysis was performed between the microbial community profiles of hydraulic fracturing fluids to characterize the degree of similarity for injected fluids between all wellbores. Jaccard

Index values indicate that the biomarkers of injected fluids are not notably similar, ranging from 12-32% (J of 0.12-0.32 in Figure 2.6). Given the dramatic shifts and similarities in dominant members observed in flowback fluid communities, this suggests a persistent and possibly indigenous group of organisms exists with these shales. 42

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Figure 2.6. Comparison at the genus level between the frack fluids of all wells at a distance of 0.03, and indication of Jaccard Index value (J).

Discussion

An inverse relationship was observed between TDS and DOC concentrations for all wells. TDS in early flowback was less concentrated in comparison to late flowback due to dilution from significant amounts of water injected during the hydraulic fracturing process. However, in later flowback, as the volume of recovered fluids decreased, TDS increased due to fluid interactions with the producing formation’s waters and salts

(Chapman 2012, Barbot 2013, Blauch 2009). In addition, mineral dissolution via salts and inorganics from the shale formation increased TDS concentrations.

The attenuation of DOC can be attributed to both biotic and abiotic processes, namely sorption, biochemical reactions and microbial degradation. Chemical additives within frack fluid serve as a significant source of organic carbon for microorganisms. Of the fraction of biologically-mediated DOC attenuation, a large portion of this carbon was likely labile and bioavailable. A smaller portion was likely comprised of complex carbon compounds, such as aliphatic and aromatic hydrocarbons. In part, the residual, unattenuated carbon can be attributed to the shale’s natural organic carbon content found in the form of hydrocarbons such as methane. During flowback and production, it is likely abiotic dissolution of organic carbon from the source rock occurred, the magnitude of which is unknown. Consequently, the degree of microbially-mediated DOC attenuation is likely underrepresented due to the influx of organic carbon from the shale into solution.

The number of genera observed through time in all wells followed a similar trend.

The significant drop in genera abundance, ranging from 75-81%, and in diversity within the first week can be attributed to the drastic difference in environments experienced at the surface and within the subsurface. Apart from biological stressors from added biocides, chemical toxicity from hydraulic fracturing constituents, shear stresses from pipes and proppants, and other mechanical stresses from the hydraulic fracturing process, the relative abundance of mesophile genera acquainted with surface temperatures and pressures diminish quickly as they are likely physiologically unequipped to survive fluid

44 changes and deep subsurface conditions. This decline in relative abundance continues, but at a significantly lower rate, until after 1.5 months.

The microbial communities in all samples have low phylotype similarity to their respective frack fluid, indicating that microbial communities in all wells consistently become dissimilar phylotypically through time. The variation in diversity between the three frack fluids can be attributed to variation in composition as the three wells were fracked successively with different water sources. Jaccard Index values indicate the greatest degree of similarity between Wells 1 and 2 correspond to the fact that Well 3 was first hydraulically fractured with freshwater. Well 2 and then Well 1 were sequentially fractured using recycled water from the previous frack job. The increase in number of genera between 1.5 and 2.75 is likely due the survival of certain persistent genera which began to thrive under new production well conditions.

Biomarkers observed in the fracturing fluid samples were closely related to typical mesophile communities found in surface waters and groundwater environments, with slight intrusions by marine biomarkers that likely represent recycled fluids.

Dominant biomarkers detected in later flowback and produced fluids are characterized by their ability to oxidize alkanes and aromatic and aliphatic hydrocarbons.

Fracturing fluid communities were dominated by a variety of genera ubiquitous to fresh and groundwater environments (Table 2.1). For example, Pseudomonas is a widely distributed and metabolically versatile mesophilic genus. The representative species, P. stutzeri, is a denitrifying, facultative anaerobe that is capable of degrading alkanes and aromatic hydrocarbons and utilizing ethylene glycol as a sole carbon source (Cladera

2006; Lalucat 2006). The early presence of P. stutzeri can be attributed to the heavy use of aromatic hydrocarbons and ethylene glycol in various fracturing fluid constituents, including scale inhibitors, iron control agents, breakers and biocides (Lalucat 2006). P. stutzeri is also capable of metabolizing benzoate, fluoranthene, fluorene, naphthalene, phenanthrene, phenol, dimethylphenol, pyrene, salicylate, quinolone and xylene which are all chemicals that have been recently identified in frack, flowback and produced fluids (Lalucat 2006; US, EIA 2011). Cobetia is another environmentally diverse microorganism, being present in brackish to saline waters. Aerobic, slightly halotolerant and alkaliphilic, the representative species C. marina is an efficient nitrate-reducer

(Arahal 2002). The Leuconostoc genus contains acid producing bacteria (Schillinger

1989). The presence of Pseudoalteromonas, Arcobacter, Halanaerobium,

Marinobacterium, Myroides and Roseovarius, all hypersaline or marine-associated genera, in the fracturing fluid may be attributed to the mixing of recycled waters with freshwater sources for fracturing fluid makeup at this site (Romanenko 2003, Ivanova

2011, Chang 2007, Zhang 2008, Labrenz 1999).

Table 2.1. Summary of dominant genera and their key traits for frack, flowback and produced water samples. Frack Fluid Early Flowback Late Flowback Produced Water

Pseudomonas Halolactibacillus Marinobacter Halanaerobium Facultative anaerobe Anaerobic Aerobic Anaerobic Mesophile Hypersaline environments Hypersaline/oil fields Hypersaline/oil fields Denitrifier Halophilic Halophile Degrades aromatic compounds Degrades aliphatic and Alkaliphilic lactic acid bacteria Degrades hydrocarbons Produces methylmercaptan aromatic hydrocarbons Bacteriocin production H2S producer 60 ˚C 40 ˚C Up to 47 ˚C

Cobetia Arcobacter Idiomarina Selenihalanaerobacter Aerobic Obligate microaerophile Aerobe Obligate anaerobe Water/soil bacterium Saline environments Halotolerant Halophile – wastewater/brines Slightly halophilic Non-sporulating Marine-associated Respires selenate Slightly alkaliphilic Sulfide-oxidizer 37 °C 42 ˚C

Marinobacterium Vibrio Halolactibacillus Anaerobaculum Degrades hydrocarbons Facultative anaerobe Previously noted Thermophilic Vestige from recycled fluids Marine-associated Sulfur-reducing anaerobe 6% NaCl (halotolerant) Pseudoalteromonas Nitrate reducer Acinetobacter Non-sporulating Aerobic Marine-associated 37 °C Vestige from recycled fluids Degrade aromatic compounds Marinobacterium Previously noted

Flowback fluids were dominated by marine or hypersaline environment- associated genera (Table 2.1). The representative Halolactibacillus species, H. miurensis, is an anaerobic, highly halotolerant, fermentative lactic acid bacteria capable of growing in up to 25% w/v NaCl and at 45˚C (Ishikawa 2005). The dominance of Halolactibacillus during flowback correlates with the presence of fermentative bacteria in shale formations as observed by Fredrickson and Balkwill 2006. M. halophilum, the representative

Marinobacterium species, is an aerobic, moderately halotolerant isolate from a tidal flat, capable of growing in up to 45˚C and 12% w/v NaCl (Chang 2007). Vibrio is a nitrate- reducing, facultative anaerobe (Yoshizawa 2009). Previous food industry reports have documented that various Vibrio species have inherent thermal resistance at temperatures 47 as high as 50˚C (V. vulnificus), 55˚C (V. parahaemolyticus) and 82˚C (V. cholerae), well beyond the 35-51˚C formation depth temperatures reached within the Marcellus (Cook and Ruple 1992, Delmore and Chrisley 1979, Hinton and Grodner 1985, Driscoll 1986).

Arcobacter is an obligate microaerophilic sulfide-oxidizer that has expressed growth at

42˚C (Collado 2009, Lehner 2004). Idiomarina is a halotolerant marine aerobe (Brettar

2003).

Produced fluids were overwhelmingly dominated by biomarkers with close similarity to Halanaerobium (Table 2.1). Extremely halotolerant anaerobes,

Halanaerobium isolates are associated with hypersaline oil fields and gas wellheads and can consequently survive in salt concentrations and temperatures as high at 30% w/v

NaCl and 60˚C, respectively (Ravot 1996, Ivanova 2011). Biomarkers with high similarity to H. praevalans degrade nitro-substituted aromatic hydrocarbons producing intermediate metabolites for sulfate-reducers and methanogens, which correlates with the presence of syntrophic bacteria in shale formations as observed by Fredrickson and

Balkwill 2006 (Zeikus 1983). H. praevalens also produces methylmercaptan, a natural constituent in oil and crude gas in some regions, from complex organic matter, which can be used as a methanogenesis substrate by some anaerobic soil bacteria (Zeikus 1983).

Another dominant species detected, H. congolense, is a sulfur and thiosulfate-reducer that produces hydrogen sulfide gas, a major cause of well fouling (Ravot 1996).

Aerobic, moderately halotolerant Marinobacter is also a hydrocarbon degrading sulfur-cycler which can live in up to 47˚C (Xu 2008). It is capable of degrading aromatic and aliphatic hydrocarbons such as naphthalene, phenol, hexane, decane and hexadecane

(McGowan 2004, Moxley 2012, Hedlund et al. 2001). Acinetobacter is another aerobic aromatic hydrocarbon degrader with inherent biocide resistance and biofilm formation capacities (Nishimura 1988). Clostridium is an endospore-forming obligate anaerobe

(Inglett 2010). Anaerobaculum is a thermophilic, sulfur-reducing anaerobe which respires crotonate (Menes 2002). Lastly, Selenihalanaerobacter is an obligately anaerobic halophile which respires selenate and has been used previously in briny wastewater systems for bioremediation purposes (Blum 2001).

Methanogenic Archaeal species were only detected in one late produced fluid sample at a relative abundance of 1%, which supports the thermogenic origins of methane in the Marcellus (Osborn 2010). The lack of detected Archaea was unexpected, as these organisms are typically of an extremophile nature and better equipped to handle deep subsurface environments. There was also a pointed lack of thermophilic methanogens in this study as would seem appropriate to this particular environment (Li 2007).

Additionally, several genera detected in the sample fluids include species which are or are closely related to known or suspected pathogens. Acinetobacter baumannii is linked to nosocomial infections such as meningitis, pneumonia and bacteremia as well as necrotizing fasciitis (Charnot-Katsikas 2009). Arcobacter butzleri, A. cryaerophilus, and

A. skirrowii have been linked to human extraintenstinal diseases, acute diarrhea and chronic diarrhea, respectively (Lehner 2004, Bücker 2009, Ho et al. 2006). Halomonas stevensii, H. hamiltonii and H. johnsoniae are linked to human bacteremia cases

(Hamilton 2009). Leuconostoc lactis has been linked to liver abscesses associated with bacteremia (Mylona-Petropoulou 2002). Pseudomonas aeruginosa and P. stutzeri are a

49 well-known human opportunistic pathogen and a suspected human pathogen in clinical settings, respectively (Van Eldere 2003 and Lalucat 2006). P. stutzeri, in particular, has been associated with cases of osteomyelitis, endocarditis and pneumonia (Lalucat 2006).

Vibrio spp. includes notorious human pathogens causing cholera, septicemia and gastroenteritis (Faruque 2008). While there would be no physiological advantage for pathogenic traits in the deep subsurface, it does suggest enrichment of organisms closely related to those with antimicrobial resistance or persistence from selection pressures, such as rapid environmental changes.

The dramatic community shifts observed in this study are consistent with those observed in the deep ocean in response to the introduction to the Deepwater Horizon oil release (Redmond 2012, Mason 2012). The hydraulic fracturing fluid and released oil both contain a large portion of labile carbon that is readily degraded by halotolerant bacteria (Natter 2012), with the residual likely being comprised of complex carbon compounds (Natter 2012, Mason 2012, Lu et al. 2012, Das and Chandran 2011) that are slowly mineralized by aliphatic hydrocarbon degraders (Mason 2012, Lu et al. 2012, Das and Chandran 2011). Furthermore, enrichment of thermophilic, anaerobic, hydrocarbon- degrading microorganisms was likewise observed in response to oil release in Deepwater

Horizon (Mason 2012, Horel 2012, Hamdan 2011, Kostka 2011). Significant enrichment of Firmicutes, Alphaproteobacteria, and Gammaproteobacteria, was evident in both these and oil spill microbial findings (Kostka 2011, Hamdan 2011). Though not a hydrocarbon degrader, enrichment of various Vibrio species (V. natriegens, V. alginolyticus, and V. fluvialis) was likewise detected in the microbial community response (Hamdan 2011, Tao

2011, Gauglitz 2012). In addition, substantial oil influx into the microbial community significantly impacted and decreased microbial abundance as is similarly evident in this study (Kostka 2011).

Conclusions

This study’s findings improve our understanding of the types of organisms capable of living at depth and of temporal microbial selectivity or enrichment of robust microorganisms equipped with various beneficial physiological traits during fracturing and production processes. Additionally, this study provides insights into largely unknown subsurface ecological impacts from shale exploration in terms of microbial biodiversity and degree of dissolved organic carbon attenuation. Lastly, this study provides select reference data for microbial communities and geochemical conditions one might encounter in their study of the Marcellus shale.

Microbial community shifts in flowback fluids have implications for wastewater management, particularly as applied to treatment or recycling fluids for reuse. Since various biogeochemical and physical pressures drive microbial selection within these fluid communities, the growing industry trend of recycling produced fluids for future hydraulic fracturing operations could lead to the inadvertent selection of persistent extremophiles. Understanding how selecting for and reintroducing these recalcitrant microorganisms into the subsurface via injected fluids affects surface and subsurface microbial communities necessitates further research and could lead to improved water management strategies in the future.

Chapter 3: Microbial Response to the Introduction of Fracturing Fluid

Introduction

Several potential risks are posed to surface and groundwater resources during hydraulic fracturing operations via accidental fluid spills or equipment failure. These include the fate of unrecovered fracturing fluids which remain in deep subsurface formations, and the mishandling of various production fluids prior to their injection, reuse, treatment, or disposal (Rush 2010). In the Marcellus shale, fracturing occurs deep enough that contamination of potable aquifers is unlikely. The greatest risk from fracturing itself appears to be poorly cased wells, natural faults, or improperly abandoned boreholes that facilitate fluid migration toward the surface (Osborn 2010, Myers 2008).

Given the likelihood of these incidents and the proximity to surface and shallow groundwater aquifers, release of frack chemicals may degrade water supplies as they contain organic compounds, biocides, strong acids, and salts that present human and environmental toxicity hazards (Kargbo 2010, Rush 2010). Consequently, it is necessary to understand the fate of these fluids under natural conditions to avoid such hazards.

Landfill leachate, like hydraulic fracking fluids, is a significant source of nutrients that alter surface and groundwater biogeochemistry in the event of landfill leaks (Mouser et al. 2010). Landfill leachate contaminates these waters with heavy loading of dissolved organic matter, xenobiotic organic compounds, inorganics and metals (Kjeldsen et al. 52

2002, Christensen et al. 1994, Kylefors et al. 1999). Major fracking fluid chemical components derive from aromatic hydrocarbons, halogenated and chlorinated compounds, and phenols and are similar to components encountered in landfill leachates

(Kjeldsen et al. 2002). In landfill leachate systems aquifer response is characterized by enrichment in phylotypes capable of degrading complex organics, attenuation of organic compounds and oxygen depletion in the case of leaching into surface waters (Mouser et al. 2010, Kjeldsen et al. 2002). Likewise, microcosm system response to incremental increases in fracking fluid concentrations will likely parallel these typical aquifer responses to landfill leachate. This response, in terms of statistical changes or shifts in key microbial communities, can be used to detect or discriminate between samples with fracking fluids versus those with background conditions.

Methods

To determine these microbial community dynamics, untreated groundwater was collected on 22 October 2012 at the Parsons Avenue Water Treatment Facility

(Columbus, OH). Soil was collected on 23 October 2012 in an agricultural field adjacent to the Waterman Dairy Center at The Ohio State University (Columbus, OH).

Microcosms consisted of a soil-groundwater mixture, with certain treatments exposed to a synthetic frack fluid developed in-lab (see Appendix B for a further description of samples and methods). In total, the microbial and geochemical properties of 24 fluid samples were analyzed. For tracking of microbial community dynamics, total nucleic acids were extracted from biomass using the Powersoil DNA Isolation kit (MoBio,

Carlsbad, CA). Biomarkers from the 16S rRNA gene were amplified using Polymerase 53

Chain Reaction (PCR) and primers targeting the V4 region. Sequencing was conducted using multiplex a 454-pyrosequencing approach. NCBI Blast and Mothur programs were used in data reduction to generate clone libraries and construct community profiles.

Specific details on laboratory and computational methods can be found in Appendix B.

Results

Dissolved organic carbon (DOC) concentrations, representative of the sum of organic constituents added in the synthetic hydraulic fracturing fluid, decreased through time for all biotic treatments (Figure 3.1). Ambient DOC remained well below 5 mg/l, indicative of typical freshwater DOC levels (Muylaert 2005). The DOC in biotic aerobic treatments (25% and 100%) decreased by 65-76% within the first four days whereas a similar level of DOC mineralization under anaerobic conditions took approximately two weeks (Figure 3.1). Over a 39 day period, 80-92% and 76-82% of DOC was mineralized in the aerobic and anaerobic treatments, respectively. Final DOC concentrations were about 2-11 times the average ambient DOC levels. In contrast, DOC attenuation from abiotic processes ranged from less than 1% to 17% for all treatments (data not shown in

Figure 3.1).

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Dissolved oxygen (DO) concentrations indicate aerobic treatments held oxygen concentrations between 2-5 mg/l while the DO of anaerobic treatments was below 1.5 mg/l throughout the 39-day experiment (Figure 3.2a). Iron concentrations remained below 0.3 mg/l (Figure 3.2b) while sulfate concentrations remained fairly constant for the ambient and aerobic treatments (Figure 3.2c). Conversely, a rapid increase of dissolved iron (Figure 3.2c) occurred concurrent with a loss in sulfate between 4-15 days for the anaerobic treatments, suggesting the onset of microbially-mediated Fe(III)- and sulfate- reduction.

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The number of operational taxonomic units (OTUs) at the genus level decreased for the ambient and aerobic treatments as microorganisms adapted to the introduction of groundwater and/or fracturing fluids (Figure 3.3a-c). Genus abundance for the aerobic

0% and 25% treatments similarly decreased by about 15% overall (Figures 3.3a and

3.3b). In addition, the loss in genus abundance in the aerobic 100% treatment was two times more than the loss experienced in the previous two treatments (Figure 3.3c). Over the first four days, genus abundance under aerobic conditions increased by 27% when stimulated by low levels (25%) of fracture fluids, but decreased by 37% at high levels

(100%) of fracturing fluids. After this initial stimulation, low level treatments (25%)

58 experienced a 38% reduction in genus abundance whereas high level (100%) treatments had a slight resurgence in abundance during the remainder of the experiment. No genera were detected in the abiotic aerobic 0% treatment, as expected (data not shown in figures). The number of operational taxonomic units (OTUs) at the genus level decreased overall for the anaerobic 0% treatment by 53%, remained approximately the same for the anaerobic 25% treatment, and increased overall by 54% in the anaerobic 100% treatment

(Figure 3.3d-f).

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Two ecological indices were again used to characterize microbial biodiversity in this study: the Shannon-Wiener Index and the Jaccard Index. The Shannon-Wiener Index describes both the abundance and evenness of the OTUs while the Jaccard Index quantifies the similarity of detected OTUs between any two samples. In this case, Jaccard comparisons were made between initial day 0 samples and respective temporal samples to assess overall diversion within a treatment. The Jaccard Index ranges from 0-1, with 1 indicating identical OTU makeup and 0 representing no shared OTUs.

In general, the Shannon-Wiener diversity index decreased 19% for the aerobic ambient treatment while increasing slightly when low or high percentages of fracturing fluids were added (Figures 3.3a-c). Shannon values indicate ambient treatments were 64 most biodiverse while low concentration fracture fluid treatments ended with the most biodiversity. Under anaerobic conditions, biodiversity indices decreased 10-17% under no or low levels of fracture fluids while increasing 11% under high concentrations of fracture fluids (Figures 3.3d-f). Shannon values indicate ambient treatments were initially most diverse while low level fracture fluid treatments were the least diverse. Diversity values of the anaerobic treatments were approximately double the diversity values calculated in aerobic treatments.

Jaccard Indices denote that the microbial communities in all aerobic treatments became dissimilar from its original microbial community (Figures 3.3a-c). Microbial communities in the aerobic 0% treatment remain slightly the most similar to that in its original community as compared to 25% and 100% treatments with J=0.41. This indicates that 41% of community members present in the initial fluids still remain by day

39. In comparison, 35-39% of original community members remain in the 25% and 100% treatments by day 39. However, it should be noted that the microbial communities in the

25% and 100% treatments declined to their lowest point of phylotype similarity after just

4 days (J=0.25-0.29) then gradually increased to become more similar by the end of the experiment as noted.

Jaccard Indices in all anaerobic treatments became dissimilar from their original microbial community as time progresses (Figures 3.3d-f). Microbial communities in the anaerobic 0% treatment became the least similar to that in its original community as compared to 25% and 100% treatments with J=0.4. In comparison, 60-63% of original community members remain in the 25% and 100% treatments by day 39. However, it

65 should be noted that the microbial communities in the 25% and 100% treatments declined to their lowest point of phylotype similarity after 12 days (J=0.2-0.5) then gradually increased to become more similar by the end of the experiment, as noted.

Classification of microbial community shifts was conducted at the class and genus level in order to minimize the relative abundance of unclassified organisms within a given community and detect larger percentage shifts in populations. Figures 3.4a-c denote temporal microbial community composition shifts at the class and genus level for various aerobic treatments while Figures 3.4d-e represent changes under anaerobic conditions. Similarity of microbial populations for the duplicate experimental control are shown in Figure 3.5 (J=0.76 and 0.67 at the class and genus level, respectively).

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igure 3.4b. Microbial community compositions at the class and genus level in terms of percent 16s rRNA for a subset of microcosm samples from the biotic aerobic treatment at 25% synthetic frack fluid concentrations.

.BB-+ !"#$%&'()"&%*+ JK9&7'3'$$CG+;-+ !,'-.#*#//01+ >%C$9:%#1)3++ 2)0/'()"&%*+ IB-+ E-+ 23*4-%'()"&%*#01+ >$9&13'*'CG++ 2/'-&*#5#01+ EB-+ F&)C*9G9"%&++ HB-+ 6%"3/'*'1'$)-+ H;-+ 607)$%//)+ 64)5'()"&%*+ ?B-+ F&)C*9G9"%&++ 8%'()"&%*+ F&)C*9G9"%&++ I-+ 8*)"#/#()"&%*+ ,B-+ .D-+ 012)3++ 9)7$%&'-.#*#//01+ .D-+ :.#&0&0-+ ;B-+ 012)3+48)"C&5++ ;)%$#()"#//0-+ /D-+ 012)3+48)"C&5++ A=7391)9:%#1)3'%++ ;3%$4/'()"&%*#01+ F&)C*9G9"%&++ .,-+ DB-+ /D-+ .B-+ ;-%05'1'$)-+ <.'*'10-)+ @=7391)9:%#1)3'%+,-+

F)3#)"1+.,&+3LMJ+>9GGC"'1N+ :&3%*+=7%$0->+ HB-+ @=7391)9:%#1)3'%+;-+ !"?$'()"&%*#)+ 012)3+48)"C&5++ >$9&13'*'%+;-+ <=7391)9:%#1)3'%+;-+ @A.*'&%'()"&%*#)+ <=7391)9:%#1)3'%++ E-+ /B-+ .,-+ 672'"89:%#1)3'%+;-+ BA.*'&%'()"&%*#)+ <=7391)9:%#1)3'%+,-+ 2/'-&*#5#)+ .B-+ >$9&13'*'%+?-+ CA.*'&%'()"&%*#)+ 012)3+4#$%&&5+,-+ !"#%$&&'()*+ DA.*'&%'()"&%*#)+ <=7391)9:%#1)3'%+;-+ ./-+ !"#$%&&'()*+,-+ <.3#$7'()"&%*#)+ B-+ :&3%*+=2/)-->+ B+ D+ ./+ HI+ O%N&+ E$"/)--#F%5+ Figure 3.4c. Microbial community compositions at the class and genus level in terms of percent 16s rRNA for a subset of microcosm samples from the biotic aerobic treatment at 100% synthetic frack fluid concentrations.

*55)& !"#$%&'"()*#'+ G2HA/012"$%31&& G2HA/012"$%31&8)& G2HA/012"$%31&<)& *5)& !",-%&'"()*#'+ 45)& D?/E"%3F31&& .'"#//#+ D?/E"%3F31&& **)& 01/%*'"#$%&'"()*#'+ +5)& '*)& 0/%2(*#$#'+ @.1%"/012"$%31&& @.#3AB/012"$%31&& 85)& *5)& @.1%"/012"$%31&& !.3"C"1$&9)& 3#(*%24#*'+ 4)& *()& 54#(6(')+ <5)& =#$%>/?$/.#3?31&<)& ;-.%/"$/012"$%31& @.1%"/012"$%31&& 7)$%241')*')+ 4)& ;-.%/"$/012"$%31&<)& ;-.%/"$/012"$%31&& **)& 7/'-"(%89")'+ 95)& **)& :-.%/"$/012"$%31&8)& :-.%/"$/012"$%31&9)& :%/#&'"()*)2+ 7-.%/"$/012"$%31& 7-.%/"$/012"$%31& :-.%/"$/012"$%31&+)& :4'*(%&'"()*#'+ (5)& *5)& +)& 7-.%/"$/012"$%31&8)& 7-.%/"$/012"$%31&9)& :41#-;%&'"()*#'+ ,-.%/"$/012"$%31&& 65)& ,-.%/"$/012"$%31& ,-.%/"$/012"$%31&& <1'68'*"1')%('+

I$%2$A"&*>CA3"L& *')& *4)& *5)& ,-.%/"$/012"$%31& <1)*8%/)%41#/#'++ '6)& '5)& =>4*%()%&'"()*#'+ !"#$%&& !"#$%&& ?>4*%()%&'"()*#'+ *5)& '()& !"#$%& *+)& '*)& !"#$%&& @>4*%()%&'"()*#'+ *')& 5)& A>4*%()%&'"()*#'+ 5& (& *'& 64& 5(1)*+ M1LE& Figure 3.4d. Microbial community compositions at the class level in terms of percent 16s rRNA for a subset of microcosm samples from the biotic anaerobic treatment at 25% synthetic frack fluid concentrations.

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

G$%2$>"&';B&%HIE&@/JJK>3"L& '8)& ,-.%/"$/012"$%31& @A8*%()%&'"()*+', *4)& ,-.%/"$/012"$%31& '4)& !"#$%&& BA8*%()%&'"()*+', '4)& !"#$%& (+)& *+)& !"#$%&& CA8*%()%&'"()*+', '4)& !"#$%&& '+)& DA8*%()%&'"()*+', '()& 4)& E(0)*,F".'33G, 4& 8& '*& (6& M1LB& Figure 3.4e. Microbial community compositions at the class level in terms of percent 16s rRNA for a subset of microcosm samples from the biotic anaerobic 100% synthetic frack fluid concentrations.

1AA)& 7,/"$%-08$"$9& 5A)& 7,/"$%-08$"$9& :;<=<-><&/?,99@&12)& :;<=<-><&/?,99@&1')& H/08-.,/"$%0,& DA)& 7,/"$%-08$"$9& 34+%-"$-.,/"$%0,&& :;<=<-><&/?,99@& 6A)& 34+%-"$-.,/"$%0,&& 25)& 26)& 34+%-"$-.,/"$%0,& CA)& L$JJ,MJ-<,8$"$9&

BA)& N"$8-<-.,/"$%0,&

(A)& *+,%"-.,/"$%0,&12)& *+,%"-.,/"$%0,&12)& O$"#,<-J0/%-.0,&

'A)& *+,%"-.,/"$%0,& E$%/$<"&1C9&%FGH&I-JJ;<0"K& 2A)& !"#$%&& !"#$%& !"#$%& '()& '()& 1A)&

A)& 1& 2& *,J+?$&&

Figure 3.5. Microbial community composition comparison in terms of percent 16s rRNA between the duplicate controls: the biotic aerobic treatment at 25% synthetic frack fluid concentrations on day 4.

In general, the aerobic communities were dominated at the class level by

Proteobacteria (α, β, γ, and δ-proteobacteria), including Acidobacteria, Actinobacteria,

Clostridia, Spartobacteria, and Sphingobacteria (Figures 3.4a and 3.4b). This primarily included Acinetobacter, Azospirillum, Caulobacter, Cellvibrio, Chryseobacterium,

Clostridium, Dechloromonas, Dyadobacter, Flavobacterium, Geobacter,

Phenylobacterium, Pseudomonas, Magnetospirillum, and Sphingomonas genera.

Apart from a slight enrichment in β− and δ-proteobacteria, the ambient aerobic treatments had similar microbial communities at 0 and 39 days. (Figure 3.4a). γ- proteobacteria decreased for aerobic treatments stimulated by fracturing fluids while β- proteobacteria abundance increased across this same period. The aerobic treatment with a 72 high concentration of fracture fluid was further enriched by Clostridia (28-fold increase at

4 days) and α-proteobacteria (5-fold increase at 39 days).

At the genus level, Pseudomonas decreased 4 and 2-fold overall in the 100% and

25% treatments, having comprised 35 and 29% of the initial microbial community contents, respectively. Acinetobacter abundance decreased by 100% overall in the aerobic 25% treatment. This same treatment was enriched in Cellvibrio,

Sphingobacterium, Dyadobacter and Phenylobacterium by 100, 100, 100 and 95%, respectively, on day 4. In addition, the same treatment was enriched in Flavobacterium and Ohtaekwangia by 98 and 95% on days 12 and 39, respectively. The aerobic 100% treatment at the genus level was enriched overall by Phenylobacterium, Azospirillum and Caulobacter which increased to 4, 5 and 8% from 0%, respectively. Both

Magnetospirillum and Dechloromonas enriched the aerobic 100% treatment by 4% within 4 and 12 days, respectively. Lastly, Clostridium increased 106-fold in 4 days.

Similarly to aerobic conditions anaerobic communities were dominated at the class level by a variety of Proteobacteria (α, β , γ, and δ-proteobacteria), including

Actinobacteria, Clostridia, Planctomycea, Spartobacteria, Sphingobacteria and

Thermoleophilia (Figures 3.4a, 3.4d and 3.4e). This included dominance of Azoarcus,

Chthoniobacter, Clostridium, Geobacter, Opitutus, Paenibacillus. Pseudomonas and

Thermomonas at the genus level.

Actinobacteria, Planctomycea and Clostridia were slightly enriched in anaerobic ambient treatment after 39 days while a slight reduction in Sphingobacteria,

Alphaproteobacteria and Thermoleophilia was observed across this same period (Figure

3.4a). Relative abundance for various Proteobacteria remained similar during the incubation (Figure 3.4a).

At the class level for the anaerobic 25% treatment, there was an overall reduction in abundance for Actinobacteria, Alphaproteobacteria, Betaproteobacteria,

Gammaproteobacteria and Clostridia by 39-85%, respectively (Figure 3.4d). The overall abundance of Deltaproteobacteria, Opitutae and Planctomycea was enriched by 47-79%.

At the genus level, Geobacter, Clostridium and Opitutus abundance were enriched by 78-

99%.

At the class level for the anaerobic 100% treatment, abundance for

Actinobacteria, Spartobacteria and Gammaproteobacteria decreased by 52-79% overall

(Figure 3.4e). This treatment was enriched by Clostridia and Bacilli by 32-70% by day

12, and overall in Sphingobacteria by 79%. Chthoniobacter, Thermomonas,

Pseudomonas and Flavobacterium comprised 3-8% of the relative community composition on day 0. Clostridium, Geobacter, Azoarcus and Paenibacillus comprised 5-

21% of the relative community composition at 12 days.

For quality control purposes a sequence control was implemented. The aerobic

25% treatment at day 4 was sequenced twice to indicate a level of confidence in the data presented herein (Figure 3.5). The Jaccard Index value indicates that 76% and 67% of the community members present in the original sample at the class and genus level, respectively, were detected in the duplicate.

Discussion

Approximately 76-92% of added DOC compounds were readily mineralized after

39 days under both aerobic and anaerobic conditions, suggesting chemical additives within the synthetic fracturing fluids appear to serve as a nutrient source for stimulating microbial growth and/or population shifts. A large portion of this carbon appears to be labile and bioavailable, while a small portion (8-25%) may be comprised of complex or recalcitrant compounds. Aerobic treatments biodegraded an additional 10% added DOC over their anaerobic counterparts, suggesting that certain compounds are more easily mineralized in the presence of oxygen, or occur at faster rates under aerobic conditions.

Iron and sulfate concentrations in anaerobic treatments exhibited an inverse trend indicative of concomitant reduction phases within the first 2 weeks. While iron and sulfate levels remained relatively constant for the aerobic treatments, a rapid increase in iron and a simultaneous decline in sulfate occurred between days 4-15 which corresponds to low levels of DO in the anaerobic treatments that are favorable for microbial iron and sulfate reduction processes (Chapelle et al. 2009).

The decline in genus abundance, particularly in background (0%) and the aerobic

25% and 100% treatments, through time corresponds to trends in diversity indices observed in other aquifer systems (Mouser et al. 2010, Griebler and Lueders 2009). The decline in genus abundance was particularly expected in treatments with 25% and 100% synthetic frack fluid, however, the genera abundance in the anaerobic 100% treatment more than doubled. This may be attributed to the delay with some genera in establishing the particular carbon compounds in the frack fluid as their carbon source. Peaks in

75 diversity and/or genus abundance in aerobic 25% and 100% treatments may be due to a bloom in native species after an adaptation period to this nutrient-rich environment.

Diversity-wise, initial microbial communities in the 0% and anaerobic 25% treatments were more diverse than their final microbial communities. The Jaccard indices denote that there is the lowest phylotype similarity in the aerobic and anaerobic treatments around day 4 and day 12, respectively. Both 0% treatments retained about

40% of its original community members. After these points of low phylotype similarity, the microbial communities then become similar phylotypically through time.

Several dominant biomarkers were detected at the class level for the aerobic treatments. There was significantly more relative abundance of various Proteobacteria in the treatments stimulated by frack fluid in comparison to the ambient treatment. In particular, Alphaproteobacteria fill diverse biological roles, usually intracellularly, as animal pathogens or plant mutualists and include many marine cellular organisms

(Williams et al. 2007, Batut et al. 2004, Giovannoni et al. 2005). Various

Alphaproteobacteria are also associated with hydrocarbon degradation (Kostka 2011).

There was 2 x’s more relative abundance of Alphaproteobacteria in the 100% treatment than in the ambient treatment. Betaproteobacteria include a variety of aerobic nitrogen fixers, ammonium oxidizers and sulfur oxidizers found in freshwater, wastewater and soil environments (Laanbroek 2012, Kowalchuck and Stephen 2001). Highly capable of a variety of degradation pathways, Betaproteobacteria also include plant, animal and human pathogens (Garrity et al. 2005). There was more than two times the relative abundance of Betaproteobacteria in the frack fluid treatments than in the ambient.

Gammaproteobacteria include photoautotrophs (i.e. obligate anaerobes known as purple sulfur bacteria) and heterotrophs (Stackebrandt et al. 1988). These heterotrophs are aerobic and facultatively anaerobic methane oxidizers in highly reducing environments

(Stackebrandt et al. 1988). Gammaproteobacteria contains several genera which can degrade hydrocarbons and are obligate hydrocarbonoclastic bacteria (OHCB’s) (Yakimov

2007, Kostka 2011). There was more than three times the relative abundance of

Gammaproteobacteria in the frack fluid treatments than in the ambient treatment.

Deltaproteobacteria include many aerobic sulfur and sulfate reducing bacteria which are capable of forming spores and are capable of the uptake and removal of complex metals in the environment (Karlin et al. 2006).

Acidobacteria include soil bacteria found in boreal and arctic environments that are capable of biodegrading complex lignocellulosic plant biomass (Eichorst et al. 2011,

Rawat et al. 2012). They are resilient to nutrient-deficiency and large temperature fluctuations (Dedysh et al. 2006). Actinobacteria include a variety of aerobic soil, marine and freshwater organisms key to organic matter decomposition and humus formation

(Ventura et al. 2007). Some members are nitrogen fixers and pathogens and produce abundant secondary metabolites (Ventura et al. 2007, Schrempf 2001). Clostridia include obligate anaerobes to aerotolerant microorganism found in soil and intestinal flora (Wells

1996). In addition, this class includes a number of spore formers and opportunistic human pathogens (Wells 1996). Spartobacteria include mesophilic, facultative or obligate anaerobes found in the soil (Bergmann et al. 2011).

Cellvibrio and Ohtaekwangia in particular were unique to the aerobic 25% treatment. Cellvibrio are aerobic, cellulolytic nitrate-reducers found in soil (Table 3.1)

(Blackall et al. 1985, Mergaert et al. 2003). Ohtaekwangia are aerobic, non-sporeforming marine bacteria that can survive in low nutrient environments (Yoon et al. 2011).

Clostridium, Caulobacter and Azospirillum were unique to the aerobic 100% treatment.

Clostridium are obligate anaerobes which form spores and produce organic solvents via fermentation (Wilde et al. 1989, Nolling et al. 2001). They are found in soil, marine and wastewater environments (Wilde et al. 1989). Caulobacter are aerobic aquatic organisms effective at degrading heavy oil components (Nierman et al. 2001). Azospirillum are nitrogen-fixers which exhibit chemotaxis towards aromatic hydrocarbons and specifically utilize benzoate, naphthalene, toluene and catechol as sole carbon and energy source

(Steenhoudt 2000, Lopez-de-Victoria 1993, Chen et al. 1992).

Table 3.1. Key genera with high similarity to biomarkers detected in microcosm experiments, and summary of their significant physiological and metabolic traits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

The following biomarkers were present in the aerobic 25% and 100% treatments and are capable of hydrocarbon degradation: Acinetobacter, Dyadobacter,

Flavobacterium, Pseudomonas, Sphingomonas, Dechloromonas and Geobacter (Table

3.1) (Mazzoli et al. 2007, Willumsen et al. 2005, Hemalatha 2011, Adebusoye et al.

2007, Yakimov et al. 2007, Chakraborty 2005, Lovley 1993). Though present at a relatively small abundance within these communities, the presence of these genera indicate the capacity of microorganisms present in these systems to biodegrade organic carbon components of the synthetic frack fluid under aerobic conditions.

In addition to the Proteobacteria (α, β, γ, and δ -proteobacteria), Actinobacteria,

Clostridia, Spartobacteria and Sphingobacteria were detected in the aerobic treatments.

Planctomycea and Thermoleophilia were detected at the class level for the anaerobic treatments though no literature expounding the characteristics of these two classes could be found at this time. Again, there was significantly more relative abundance of various

Proteobacteria in the treatments stimulated by frack fluid in comparison to the ambient treatment. There was up to 2.5 times more relative abundance of δ-proteobacteria in the frack fluid treatments than in the ambient treatment. There was up to three times more relative abundance of γ-proteobacteria and more than two times more relative abundance of β-proteobacteria in the 100% treatment than in the ambient treatment. At the genus level, Opitutus was unique to the anaerobic 25% treatment and Thermomonas, Azoarcus and Paenibacillus were unique to the anaerobic 100% treatment. Opitutus is an obligately anaerobic fermenter and nitrate-reducer found in rice paddy soils (Chin et al. 2001).

Thermomonas are aerobic thermophiles isolated from paper production processes (Busse

79 et al. 2002). Azoarcus are halotolerant, nitrogen-fixing aerobes (Reinhold-Hurek 1993).

Lastly, Paenibacillus are spore-forming facultative anaerobes found in soil and aquatic environments (Ash 1993). In addition to genera detected in the aerobic treatments

(Pseudomonas, Geobacter, and Clostridium), Chthoniobacter was also detected in the anaerobic 100% treatment. Chthoniobacter are aerobic mesophiles found in the soil

(Sangwan et al. 2004).

The following genera were present in the anaerobic 25% and 100% treatments at very low abundance and are capable of hydrocarbon degradation: Acinetobacter,

Flavobacterium, Pseudomonas, Sphingomonas, Dechloromonas and Geobacter (Table

3.1) (Mazzoli et al. 2007, Hemalatha 2011, Adebusoye et al. 2007, Yakimov et al. 2007,

Chakraborty 2005, Lovley 1993). The presence of these biomarkers indicates the capacity of some microorganisms to directly biodegrade organic carbon components of the synthetic frack fluid under aerobic conditions.

Conclusions

Consequently, significant enrichment in classes and genera associated with hydrocarbon degradation was detected under aerobic and anaerobic treatments when stimulated by frack fluid. In addition, the significant degree of DOC mineralization in frack fluid exposed treatments can be attributed, in large part, to microbial biodegradation. This indicates that frack fluid serves as a nutrient source for stimulating microbial growth. It also, appears that frack fluid, particularly at low concentrations, is not toxic to microorganisms under aerobic or anaerobic conditions.

This study’s findings advance our understanding of microbial community response to fracking fluid exposure and in particular, the types of organisms that may be temporally enriched for in the event of a fracking fluid release to surface or groundwater.

Enrichment in hydrocarbon-degrading microorganisms observed at the class and genus level in the study’s treatments exposed to varying levels of synthetic fracking fluid denote that this response could be used as an indicator of frack fluid releases in surface and groundwater. These microbial community data will aid in interpretations for a larger study looking at the combined geochemical-microbial changes in environments with fracking fluid exposure and may ultimately aid in developing parameters for a fracking fluid release detection model.

Chapter 4: Research Implications

The findings from this research confirm that organisms indeed survive and thrive in subsurface conditions encountered in the Marcellus shale and may play an important role in hydraulic fracturing fluid attenuation under shallow and deep subsurface environments. The studies provide insight into the types of organisms being enriched for both temporally during fracturing and production processes and as a response to frack fluid exposure. In addition, it improves our understanding of the temporal microbial selectivity of robust microorganisms equipped with various beneficial physiological traits during fracturing and production processes. Lastly, key changes and shifts in the microbial community as a result of shale gas-associated fluid exposure can be further studied to be used as a timely indicator of surface and groundwater pollution.

Unfortunately, we still lack insight into where the microorganisms associated with production fluids originate from.

These studies also indicate that the majority of frack fluid components are readily mineralized under shallow subsurface conditions which can be attributed, in large part, to microbial biodegradation. The identities of these recalcitrant chemical compounds remain unknown. The large degree of DOC attenuation indicates that frack fluid serves as a nutrient source for microbial stimulation and is not toxic to these microorganisms at low concentrations. 82

In addition, this study provides select reference data for microbial communities and geochemical conditions one might encounter in their study of the Marcellus shale.

The characterization of frack, flowback and produced fluids from fracturing and production processes can aid well operators in maximizing natural gas recovery and practitioners in making informed decisions on wastewater management strategies. Lastly, characterizing these fluids may aid policymakers make informed decisions regarding improved wastewater management policies.

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Appendix A: Microbial Community Shifts in Shale Well Flowback Fluids Methods

Sample Collection and Preparation

Samples were shipped overnight and arrived in sterile 500 ml or 1 L Nalgene bottles filled to capacity on ice. Samples were stored at 4˚C and processed within 24 hours. Frack fluid samples were viscous and urine yellow with no solids (Table A1).

Flowback fluids ranged from clear to opaque, pale to dark yellow, and contained small fractions of green, brown or black sand. Produced waters were opaque pale yellow with no fine sediments.

102

Table A1. Indication of sample type and physical description of fluids sample upon receipt for the three wells. !"##$%&'$($)*+,#"$-.,"$ )*+,#"$/"0123,43&5 !"##$6 !"#$%& '"()*&+*,,-. !,-./#$%&0 1*"+&,(234&+*,,-.&.(43&5*"+&67#,,&8"#$4(-)&-8&8()*&2"**)&6#)9 !,-./#$%&: 1*"+&,(234&+*,,-.;&,*66&5(6$-<6&43#)&43*&8"#$%&8,<(9 !,-./#$%&= 1*"+&>#,*?&#,7-64&$,*#"&+*,,-.@&1*"+&67#,,&8"#$4(-)&-8&8()*&/"-.)&6#)9@& !,-./#$%&A 1*"+&,(234&+*,,-.&.(43&5*"+&67#,,&8"#$4(-)&-8&8()*&/"-.)&6#)9 !,-./#$%&B C(234&+*,,-.&D2"**)&4()2*E;&67#,,&8"#$4(-)&-8&/,#$%&6#)9 !,-./#$%&F G#,*&+*,,-.;&)-&6#)9&8"#$4(-) !,-./#$%&H I#"%&+*,,-.;&5*"+&67#,,&8"#$4(-)&-8&8()*&/"-.)&6#)9 !,-./#$%&J I#"%&+*,,-.&D/"-.)K2"**)&4()2*E;&67#,,&/,#$%&6#)9&8"#$4(-) !,-./#$%&L I**>&+*,,-.&D2"**)K/,#$%&4()2*E;&)-&6#)9&8"#$4(-) G"-9<$*9&.#4*"&0 M>#N<*&>#,*&+*,,-.;&)-&6#)9&8()*6 G"-9<$*9&.#4*"&: M>#N<*&>#,*&+*,,-.;&)-&6#)9&8()*6

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

!"##$8$$ !"#$% '"()*&+*,,-. !,-./#$% I#"%&+*,,-.&D"*9&4()2*E;&)-&6#)9;&>"*$(>(4#4*&-/6*"5*9 !,-./#$% I#"%&+*,,-.&D"*9&4()2*E;&67#,,&9#"%&8"#$4(-)&-8&/,#$%K"*9&6#)9 !,-./#$% 1*"+&>#,*&+*,,-.K$-,-",*66;&)-&6#)9&8"#$4(-) !,-./#$% 1*"+&>#,*&+*,,-.K$-,-",*66;&)-&6#)9&8"#$4(-) !,-./#$% I**>&+*,,-.;&)-&6#)9&8"#$4(-) !,-./#$% I#"%&+*,,-.&D"*9&4()2*E;&)-&6#)9 !,-./#$% C(234&+*,,-.;&9**>&/"-.)K"*9&2"-.43&,#+*"&()&,(N<(9& !,-./#$% C(234&+*,,-.;&5*"+&67#,,&/"-.)&6#)9&8"#$4(-)

103

Sample preparation for microbial analysis included running 300 ml of each sample through a 1.2-µm glass fiber filter using a sterile vacuum apparatus. Flow-through was transferred to multiple conical tubes and spun down at 5,000 rpm for 30 minutes at

4˚C. Pellets were resuspended in 1 ml of supernatant solution. If pellets did not form during the pelleting process, a second centrifugation step was performed at 5,500 rpm for

30 minutes at 4˚C. Flow-through fluid was hand-filtered through a 0.22 µm Sterivex filter if no pellets formed during this secondary spin. Pellets, glass fiber filters and Sterivex filters were flash frozen at -80˚C for future use.

DNA Extractions, PCR Amplification, Cloning and Sequencing

Nucleic acids were extracted from pellets and filters using the PowerSoil DNA

Isolation kit according to the manufacturer’s instructions with the following method alterations (MoBio, Carlsbad, CA). One sample was aliquoted into four power bead tubes. Solution C6 was incubated at 50˚C prior to addition to spin filter. The four power bead tubes were successively eluted by adding solution C6 to the first power bead tube, incubating for 2 minutes, eluting, then transferring eluted DNA to the next tube and so on until the fourth tube. The extracted DNA was quantified on a Nanodrop 2000

Spectrophotometer (Thermo Fisher Scientific, Wilmington, DE).

The 16S rRNA gene of 7 of 9 samples of extracted DNA was amplified using a two-step PCR method. The template was first amplified using the universal primer set that targets the V4 region 515F (5’-GTG CCA GCM GCC GCG GTA A-3’) and 806R

(5’-GGA CTA CVS GGG TAT CTA AT-3’) (Turner et al. 1999 & Bergmann et al.

2011). Each of the 50 µl PCR mixtures contained 1 µl DNA template, 5 µl of 10x 104 polymerase buffer, 4.5 mM MgCl2, 1 µl of bovine serum albumin (0.5 mg/ml), 200 µM deoxyribonucleoside triphosphates, 25 pmol of forward and reverse primers, and 1.25 U of Taq polymerase. Reactions were carried out in a S1000 Thermal Cycler (Bio-Rad

Laboratories, Foster City, CA) beginning with a 3-min denaturation at 95ºC followed by

20 cycles of 95ºC (30 sec), 55ºC (1 min), 72ºC (1 min) and a final 10-min elongation at

72ºC.

The secondary PCR involved a 1:50 dilution of the initial PCR product (1 µl PCR product in 49 µl of secondary PCR cocktail). All samples were PCR amplified in duplicate then pooled prior to sequencing. The template was amplified using universal barcoded primers. The 515F primer included the Lib-L Roche 454-A pyrosequencing adapter, a 10 base pair barcode (unique to each sample), and a GT linker, while 806R included the Roche 454-B sequencing adapter and a GG linker. Due to an expected larger diversity in results, the amplicons were unidirectionally sequenced resulting in greater depth of reads. Each of the 50 µl PCR mixtures were made up to the same specifications as previously related and run for ten more cycles under the aforementioned thermocycler conditions.

The PCR product was visualized using gel electrophoresis on a 1.5% agarose gel.

The amplicons were purified using AMPure paramagnetic beads (Agencourt Bioscience

Corporation Beverly, MA, USA) according to the manufacturer’s protocol. The amplicons were prepared for sequencing by the Plant-Microbe Genomics Facility at The

Ohio State University (Columbus, Ohio) using the emPCR Kit II unidirectional library sequencing protocol. The amplicons were then analyzed via pyrosequencing at the Plant-

105

Microbe Genomics. Sequencing was conducted on a 454 Life Sciences Genome

Sequencer FLX (Roche Diagnostics, Indianapolis, IN, USA).

In order to compare 454 techniques to traditional sequencing results, the 16S rRNA gene of 2 samples was amplified using the aforementioned universal primer set

515F/806R. Each of the 50 µl PCR mixtures contained a range of template DNA, 5 µl of

10x polymerase buffer, 4.5 mM MgCl2, 1 µl of bovine serum albumin (0.5 mg/ml), 200

µM deoxyribonucleoside triphosphates, 25 pmol of forward and reverse primers, and

1.25 U of Taq polymerase. Reactions were carried out in a S1000 Thermal Cycler (Bio-

Rad Laboratories, Foster City, CA) beginning with a 3-min denaturation at 95ºC followed by 20 cycles of 95ºC (30 sec), 55ºC (1 min), 72ºC (1 min) and a final 10-min elongation at 72ºC. The PCR products were visualized using gel electrophoresis to isolate PCR products of the desired length by gel extraction (Qiagen). Clone libraries were constructed by insertion of the amplified 16s DNA into the TOPO TA vector pCR 2.1 and cloning into chemically competent Escherichia coli TOP10 cells according to the manufacturer’s instruction (Invitrogen, Carlsbad, CA). Clones were selected from each clone library and amplified with M13 forward and reverse primers (Anderson et al.

2003). Reactions were purified at the Plant-Microbe Genomics Facility using AMPure beads (Agencourt Biosciences Corporation, Beverly, MA) and sequenced with an ABI

Prism cycle sequencing kit (BigDye terminator cycle sequencing kit) using an ABI 3700 instrument (Applied Biosystems, Grand Island, NY).

106

16s rRNA Gene Sequence Analysis

Pyrosequencing reads were subject to numerous quality-filtering steps. Post filtering, the sequences were sorted based on their individual barcode sequence.

Sequences with ≥97% similarity were grouped into operational taxonomic units (OTUs) and classified. Basic diversity estimates (Shannon diversity estimates, and Ace and Chao richness estimates) were calculated for each fluid sample using Mothur (Schloss et al.

2009). Abundance-based Jaccard indices and the number of shared OTUs were also calculated for each sample using Mothur (Schloss et al. 2009).

Raw Sanger sequencing data were blasted on the National Center for

Biotechnology Information’s BLAST (Basic Local Alignment Search Tool) using the 16s ribosomal RNA sequences (Bacteria and Archaea) database (Altschul et al. 1997). The sequence was classified as the organism with the highest percent similarity using a 97% cutoff.

107

Appendix B: Microbial Response to the Introduction of Fracturing Fluid Methods

Sample Collection

Water samples were collected in sterile plastic bladders and filled to capacity then stored at 4˚C for immediate processing. Soil samples were taken from the top 2 feet of soil using a handheld soil corer. Samples were transferred to sterile mason jars, which were then sealed and stored at 4˚C for immediate processing. All soil cores were homogenized for use in microcosms.

Microcosm Setup

All treatments were as outlined in Figure B1. Serum bottles were autoclave sterilized. Serum bottles (125 ml or 60 ml) were filled with soil and groundwater (20g soil:10 ml water in 125 ml bottles; 8g soil:5 ml water in 60 ml bottles), covered with sterile foil, and equilibrated for 3 days at room temperature. After equilibration, an additional 100 ml or 40 ml of a groundwater-synthetic fracturing fluid mixture was added to the 125 and 60 ml bottles, respectively. The synthetic frack fluid, whose constituents are outlined in Table B1, was added at 0, 25, 50 or 100% fracture fluid:groundwater

(vol/vol) concentration. Anaerobic treatments were gassed using 80:20 mixture of

N2:CO2 for a total of 25 minutes (15 minutes in the solution and 10 minutes in the headspace) then crimped closed with rubber septa Aerobic microcosms were covered

108 with a double layer of sterile foil. Abiotic treatments (aerobic and anaerobic) containing soil, groundwater, and fracturing fluids were twice autoclaved to heat sterilize microbial cells and cysts. Microcosms were shaken (150 rpm) at a constant temperature (25ºC) for up to six weeks in the dark. Geochemical sampling occurred in duplicate at seven time points (0, 4, 7, 12, 15, 25 and 39 days). Microbial sampling occurred at 5 time points (0,

4, 12, 25 and 39 days).

109

Table B1. The content of the synthetic frack fluid by component and their respective disclosed ingredients.

110

Sampling Procedure

Approximately 15 ml of soil from each sample were transferred to a sterile conical tube then flash frozen at -80˚C. DO and pH were measured with Thermo

Scientific Orion Star and Star Plus Meter immediately after soil transfer. The fluid from each microcosm was filtered with a 0.22µm filter. The treated fluid was used to conduct all other chemical tests.

Geochemical Testing

In addition, geochemical changes were tracked by measuring total dissolved solid

(TDS), conductivity, total carbon (TC), total organic carbon (TOC), total nitrogen (TN), anions, and cations. The solution chemistry was tested in the Environmental

Biotechnology Laboratory of the Ohio State University. A Thermo Scientific Orion Star and Star Plus Meter were used to test TDS and conductivity, respectively. TC, TOC and 111

TN were measured with a SHIMADZU TOC-V series Total Organic Carbon analyzer, while the anions were measured on a Dionex Ion Chromatography System ICS-2100.

Fluid samples were diluted to conduct these tests due to high levels of organics present within the samples which are detrimental to these pieces of equipment.

For the TC, TOC and TN samples, 1:5 dilutions for the 25% treatments, 1:10 dilutions for 50% treatments, and 1:20 dilutions for 100% treatments were made. For the

IC samples, 1:20 dilutions for the 25% treatments, and 1:50 dilutions for the 50% and

100% treatments were made. No dilutions were made for the 0% treatments. The cations were analyzed on a Varian Vista AX CCD Simultaneous ICP-AES. ICP samples were acidified with ultrapure concentrated nitric acid (HNO3). The TC, TOC, TN, IC and ICP samples were stored at 4°C for timely processing if testing was not finished on the sampling day.

DNA Extraction, PCR Amplification and Pyrosequencing

Nucleic acids were extracted from soil samples using the PowerSoil DNA

Isolation kit according to the manufacturer’s instructions with the following method alterations (MoBio, Carlsbad, CA). Solution C6 was incubated at 50˚C prior to addition to spin filter. The C6 solution was allowed to incubate for 2 minutes on the power bead tube prior to eluting. The extracted DNA was quantified on a Nanodrop 2000

Spectrophotometer (Thermo Fisher Scientific, Wilmington, DE).

The 16S rRNA gene within the extracted DNA was amplified using a two-step

PCR method. The template was first amplified using the universal primer set that targets the V4 region 515F (5’-GTG CCA GCM GCC GCG GTA A-3’) and 806R (5’-GGA 112

CTA CVS GGG TAT CTA AT-3’) (Turner et al. 1999 & Bergmann et al. 2011). Each of the 50 µl PCR mixtures contained 1 µl DNA template, 5 µl of 10x polymerase buffer, 4.5 mM MgCl2, 1 µl of bovine serum albumin (0.5 mg/ml), 200 µM deoxyribonucleoside triphosphates, 25 pmol of forward and reverse primers, and 1.25 U of Taq polymerase. Reactions were carried out in a S1000 Thermal Cycler (Bio-Rad

Laboratories, Foster City, CA) beginning with a 3-min denaturation at 95ºC followed by

20 cycles of 95ºC (30 sec), 55ºC (1 min), 72ºC (1 min) and a final 10-min elongation at

72ºC.

The secondary PCR involved a 1:50 dilution of the initial PCR product (1 µl PCR product in 49 µl of PCR cocktail). All samples were PCR amplified in duplicate then pooled prior to sequencing. The template was amplified using universal barcoded primers. The 515F primer included the Lib-L Roche 454-A pyrosequencing adapter, a 10 base pair barcode (unique to each sample), and a GT linker, while 806R included the

Roche 454-B sequencing adapter and a GG linker. Due to an expected larger diversity in results, the amplicons were unidirectionally sequenced resulting in greater depth of reads.

Each of the 50 µl PCR mixtures were made up to the same specifications as previously related and run for ten more cycles under the aforementioned thermocycler conditions.

The PCR product was visualized using gel electrophoresis on a 1.5% agarose gel.

The amplicons were purified using AMPure paramagnetic beads (Agencourt Bioscience

Corporation Beverly, MA, USA) according to the manufacturer’s protocol. The amplicons were prepared for sequencing by the Plant-Microbe Genomics Facility at The

Ohio State University (Columbus, Ohio) using the emPCR Kit II unidirectional library

113 sequencing protocol. The amplicons were then analyzed via pyrosequencing at the Plant-

Microbe Genomics. Sequencing was conducted on a 454 Life Sciences Genome

Sequencer FLX (Roche Diagnostics, Indianapolis, IN, USA).

The 16S rRNA gene of 7 of the samples of extracted DNA was amplified using the aforementioned universal primer set 515F/806R. Each of the 50 µl PCR mixtures contained 1 µl of DNA template, 5 µl of 10x polymerase buffer, 4.5 mM MgCl2, 1 µl of bovine serum albumin (0.5 mg/ml), 200 µM deoxyribonucleoside triphosphates, 25 pmol of forward and reverse primers, and 1.25 U of Taq polymerase. Reactions were carried out in a S1000 Thermal Cycler (Bio-Rad Laboratories, Foster City, CA) beginning with a

3-min denaturation at 95ºC followed by 20 cycles of 95ºC (30 sec), 55ºC (1 min), 72ºC (1 min) and a final 10-min elongation at 72ºC.

The PCR products were visualized using gel electrophoresis to confirm PCR product amplification (Qiagen). The PCR product of these 7 samples was sent to the

MrDNA Molecular Research Facility for pyrosequencing (Shallowater, TX). The amplicons were purified using AMPure paramagnetic beads (Agencourt Bioscience

Corporation Beverly, MA, USA) according to the manufacturer’s protocol. The amplicons were prepared for sequencing by the Molecular Research Facility using the emPCR Kit II unidirectional library sequencing protocol. Sequencing was conducted on a

454 Life Sciences Genome Sequencer FLX (Roche Diagnostics, Indianapolis, IN,

USA).

114

16s rRNA Gene Sequence Analysis

Pyrosequencing reads were subject to numerous quality-filtering steps. Post filtering, the sequences were sorted based on their individual barcode sequence.

Abundance-based Jaccard indices and the number of shared OTUs were also calculated for each sample using Mothur (Schloss et al. 2009).

115