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Organic Sulfur-Bearing Species as Subsurface Carbon

Storage Vectors

Yim, Calista

Yim, C. (2019). Organic Sulfur-Bearing Species as Subsurface Carbon Storage Vectors

(Unpublished master's thesis). University of Calgary, Calgary, AB.

http://hdl.handle.net/1880/110919

master thesis

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UNIVERSITY OF CALGARY

Organic Sulfur-Bearing Species as Subsurface Carbon Storage Vectors

by

Calista Yim

A THESIS

SUBMITTED TO THE FACULTY OF GRADUATE STUDIES

IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE

DEGREE OF MASTER OF SCIENCE

GRADUATE PROGRAM IN GEOLOGY AND GEOPHYSICS

CALGARY, ALBERTA

SEPTEMBER, 2019

© Calista Yim 2019

ii

Abstract

To tackle climate change issues, this study investigates whether residual biomass can be

converted to a suitable form for permanent subsurface sequestration. Natural sulfurization

processes in sedimentary organic matter are investigated as mechanisms to generate biologically

refractory water-soluble organic molecules. Such molecular vectors could be sequestered in

shallow, saline, contaminated aquifers through solubility trapping. Sulfur-rich oils were analyzed

with gas chromatography mass spectrometry and Fourier transform ion cyclotron resonance mass

spectrometry to reveal molecular compositions of complex organosulfur compounds in such oils.

Sulfurized compounds including C20-28, C35 and C40 species were detected with double bond

equivalent values suggesting the occurrence of sulfurized lipids. Laboratory sulfurization

experiments on lipids yielded products with up to 7 sulfur atoms, which suggests labile

biomolecules can be altered to biologically refractory molecules. Biodegradation resistance and

water solubility estimates of various model compounds show sulfinyl functional groups

improves water solubility and biodegradation resistance of molecules.

iii

Preface

This thesis investigates an innovative potential solution to sequestering atmospheric carbon in

the geosphere to reach global targets to limit climate change. The Alternative Vectors for Carbon

Storage (AVECS) research project recreates carbon sequestration through the development of

biologically refractory and water soluble molecules using sulfurized organic compounds. This

idea was inspired by organic sulfur compounds found in sulfur-rich oils which are known to be

resistant to microbial attack. To develop and assess this approach, the geochemistry of sulfur-

rich oils and the environmental settings which form organic sulfur compounds were analyzed

(Chapter 2 and 3). The results from the molecular analysis of sulfur-rich oils assisted in the

development and understanding of sulfur incorporation reactions into organic molecules. A

method was developed to extract sulfur-rich hydrocarbon fractions from organic materials in

Chapter 4, which can be used for future oxidation experiments to increase water solubility of the

refractory molecule. In Chapter 5, chemical modelling software was used to estimate the

solubility and biodegradation resistance of various putative model compounds that might serve

as carbon storage vectors. Chapter 6 involves laboratory sulfurization experiments on lipids and

carbohydrates.

Chapter 1 reports the background to the severity of climate change and how the AVECS project

is different from current carbon sequestration methods.

Chapter 2 discusses the importance of the sulfur commodity, why it was selected for chemical

reactions in the AVECS project and the sulfur cycle.

Chapter 3 shows the results from molecular analysis of sulfur-rich oils from Peace River oil

sands (Alberta), Jianghan Basin (China) and Rozel Point (United States). The oils were analyzed

with the GC-MS and FTICR-MS to determine environmental conditions that promote sulfur

incorporation processes into organic matter.

Chapter 4 demonstrates the process of method development for the separation and isolation of

different sulfur compound classes in sulfur-rich oils. The sulfur-rich fractions are separated into

reactive and non-reactive fractions and can be directly oxidized in future oxidation experiments.

Chapter 5 utilizes ChemAxon and EPI Suite software to generate a depiction of the ideal

AVECS molecule, which is carbon-rich, water soluble and biodegradation resistant. Molecular

compounds such as lipids, carbohydrates, glycerol and long hydrocarbon chains were modified

iv

with sulfur and oxygenated functional groups to identify how sulfur incorporation and oxidation

affect the solubility and rate of biodegradation for organic molecules.

Chapter 6 shows the experimental process and results for laboratory sulfurization experiments

on lipids (cholesterol, squalene, linolenic acid and β-carotene) and carbohydrates (glucose, starch

and sucrose).

Chapter 7 provides ideas and suggestions for future work to advance project.

This thesis includes original unpublished work by Calista Yim. I was involved in most aspects of

the work presented in the thesis including oil sample processing, computer modelling, method

development for sulfur species fractionation and laboratory sulfurization experiments and

geochemical interpretations. Laboratory staff, from the Petroleum Reservoir Group (PRG) at the

University of Calgary, assisted my project in running various samples on the Fourier transform

ion cyclotron resonance mass spectrometer (FTICR-MS) and gas chromatography mass

spectrometer (GC-MS). Oil samples were collected by the PRG group (University of Calgary).

Furthermore, Renzo C. Silva provided expertise and assistance in processing FTICR-MS data

plots. The sulfur content (weight %) in oil samples were measured by the Applied Geochemistry

group – Isotope Science Lab at the University of Calgary.

v

Acknowledgements

This research was undertaken thanks in part to funding from the Canada First Research

Excellence Fund (CFREF).

I have learned so much from many individuals since the start of Master of Science degree

in 2017. I would like to first express my gratitude for my supervisors Dr. Steve Larter and Dr.

Haiping Huang for always providing me with guidance, wisdom and patience. I really enjoyed

my thesis project and I would like to thank my supervisors for inspiring my interest in

geochemistry and negative emissions technologies. Despite their busy schedules, my supervisors

have always found a way to make time to guide me through my endless questions and concerns.

I am thankful for my supervisory committee, which also included Dr. Lloyd Snowdon

and Dr. Benjamin Tutolo, for their time and insightful discussions with me. I truly appreciate my

committee’s constructive feedback which improved my research and thesis work.

I have received so much support and kindness from every member of the PRG research

Group at the University of Calgary. The expertise and wisdom from Kim Nightingale, Priyanthi

Weerawardhena, and Melisa Brown have assisted me in fine-tuning my laboratory skills, trouble

shooting problems, and their encouraging words have helped me push through problem after

problem. I am deeply grateful for Susan Dooley for supporting me through hard times and who

was my shoulder to lean on when my grandpa passed away in February 2019. I would like to

thank Dr. Thomas Oldenburg, Dr. Jagoš Radović, and Dr. Renzo Silva for generously sharing

their technical expertise and life experiences with me. I really appreciate Ryan Snowdon for his

technical assistance. I am so grateful for Dr. Aprami Jaggi, and Dr. Qianru Wang for their

continuous encouragement and for helping me navigate through my graduate studies.

I am deeply appreciative of Keith Lau for being my rock and my greatest supporter

throughout my undergraduate and graduate studies. I am also indebted to my dear parents,

Patrick and Cissy, and my loving sisters, Amanda and Brianna, for their unconditional love.

vi

Dedication

To my dear grandparents, mom and dad

vii

Table of Contents

Abstract .............................................................................................................................. ii

Preface ............................................................................................................................... iii Acknowledgements ............................................................................................................v Dedication ......................................................................................................................... vi Table of Contents ............................................................................................................ vii List of Tables .................................................................................................................... xi

List of Figures ................................................................................................................. xiv List of Abbreviations .....................................................................................................xxv

Chapter One: Introduction ..............................................................................................1

1.1 What is Global Warming? .............................................................................................1 1.2 Paris Agreement .............................................................................................................1

1.3 Complexities ..................................................................................................................3 1.4 Severity of Climate Change ...........................................................................................4

1.5 The Carbon Cycle ..........................................................................................................6 1.6 Greenhouse Gas Effect ..................................................................................................7 1.7 Carbon Capture and Storage ........................................................................................10

1.7.1 Carbon Storage in Saline Aquifers .......................................................................11 1.8 Research Objective ......................................................................................................14

1.9 Thesis Summary...........................................................................................................17 1.10 Conclusions ................................................................................................................19

Chapter Two: Sulfur Incorporation in Natural Settings .............................................20

2.1 Introduction ..................................................................................................................20 2.1.2 A Solution to Two Problems ................................................................................21 2.1.3 Why Sulfur? ..........................................................................................................23

2.1.3 Geochemical Sulfur Cycle ....................................................................................25

2.2 Sulfur Incorporation During Early Diagenesis ............................................................25 2.2.1 Assimilatory Sulfate Reduction ............................................................................26 2.2.2 Dissimilatory Sulfide Oxidization ........................................................................27 2.2.3 Dissimilatory Sulfate Reduction ...........................................................................28

2.2.4 Other Mechanisms ................................................................................................29 2.2.5 Sulfur Oxidizing and Reducing Microorganisms .................................................30

2.3 Sulfur in the Environment ............................................................................................31 2.3.1 Sulfur Sinks ...........................................................................................................32

2.3.2 Stratified Lacustrine Waters .................................................................................33 2.3.3 Marine, Lagoonal and Coastal Environments .......................................................34 2.3.4 Hydrothermal Vents ..............................................................................................35

viii

2.4 Generation of Sulfur-Rich Crude Oils .........................................................................35 2.4.1 Organic Sulfur Compounds ..................................................................................37 2.4.2 Sulfurized Lipids ...................................................................................................38 2.4.3 Sulfurized Carbohydrates .....................................................................................39

2.5 Microbial Recalcitrance of Sulfur Compounds ...........................................................40

2.5.1 AVECS Molecule .................................................................................................42

Chapter Three: Molecular Analysis of Sulfur-rich Oils and Sulfurization in Natural

Settings ..............................................................................................................................44

3.1 Introduction ..................................................................................................................44

3.2 Sulfur Incorporation Mechanisms................................................................................46

3.2.1 Steroids and Hopanoids ........................................................................................48 3.2.2 Carotenoids ...........................................................................................................48

3.3 Sample Selection and Geological Background ............................................................50

3.3.1 Peace River Oil Sands ...........................................................................................51 3.3.2 Rozel Point ............................................................................................................53

3.3.3 Jianghan Basin ......................................................................................................54 3.3.4 Bohai Bay Basin ...................................................................................................55

3.4 Methodology ................................................................................................................58

3.4.1 Elemental Sulfur Analysis ....................................................................................58

3.4.2 Florisil – Small Scale Separation (SSS) ...............................................................58 3.4.3 Solid Phase Extraction (SPE) ...............................................................................59 3.4.4 Liquid Chromatography on Silver Nitrate Impregnated Silica Gel: .....................59

3.5 Mass Spectral Data Processing and Analysis ..............................................................59 3.5.1 GC-MS ..................................................................................................................59 3.5.2 FTICR-MS ............................................................................................................60

3.6 Results and Discussion ................................................................................................60 3.6.1 GC-MS ..................................................................................................................60

3.6.1.1 Biomarkers ...................................................................................................60 3.6.1.2 Source and Depositional Environment .........................................................61

3.6.1.3 Thermal Maturity ..........................................................................................69 3.6.1.4 Biodegradation .............................................................................................71

3.6.2 FTICR-MS ............................................................................................................74 3.6.2.1 Chemical Composition of Organic Sulfur Compounds ................................74 3.6.2.2 Carbon Number Distribution ........................................................................76 3.6.2.3 Double Bond Equivalents .............................................................................78

3.7 GC-MS and FTMS Data Summary..............................................................................81

ix

3.8 Sulfur Incorporation Environmental Conditions .........................................................83

3.9 Conclusions ..................................................................................................................85

Chapter Four: Sulfur Species Fractionation .................................................................86

4.1 Introduction ..................................................................................................................86

4.2 Reactive and Non-Reactive Sulfur Compound Classes ...............................................87 4.2.1 Fractionation Method ............................................................................................88

4.3 Liquid Chromatography on Silver Nitrate Impregnated Silica Gel .............................89 4.3.1 Experiment Design by Wei et al. (2012) ..............................................................91

4.3.2 Materials ...............................................................................................................92 4.3.3 Results and Discussion .........................................................................................92

4.4 Method Development Process .....................................................................................94 4.4.1 Trial One ...............................................................................................................94 4.4.2 Trial Two ..............................................................................................................98

4.4.3 Trial Three ..........................................................................................................103 4.4.4 Trial Four ............................................................................................................107

4.4.4.1 Sulfur Compounds Standard Preparation ...................................................107 4.4.4.2 Method ........................................................................................................108

4.4.5 Trial Five .............................................................................................................110

4.4.6 Trial Six Final Procedure ....................................................................................114

4.5 Analytical Methods ....................................................................................................115 4.5.1 GC-MS ................................................................................................................115 4.5.2 FT-MS .................................................................................................................115

4.6 Results and Discussion ..............................................................................................116 4.6.1 GC-MS Analysis .................................................................................................116 4.6.2 FTICR-MS ..........................................................................................................119

4.7 Conclusions and Future Work ...................................................................................122

Chapter 5 Solubility and Biodegradation Rate Predictions for Model Organic Sulfur

Compounds Using Quantitative Structure-Activity Relationships (QSAR) ............124

5.1 Introduction ................................................................................................................124

5.2 Methods......................................................................................................................125 5.2.1 EPI Suite .............................................................................................................125 5.2.2 ChemAxon ..........................................................................................................126

x

5.3 Results and Discussion ..............................................................................................127 5.3.1 Experiment 1 – Sulfurization and Oxidation of Lipids .......................................127 5.3.2 Experiment 2 – Sulfurization and Oxidation of Sulfurized Carbohydrates ........135 5.3.3 Experiment 3 – Sulfurization and Oxidation of Isoprenoids ..............................137 5.3.4 Experiment 4 – Sulfurization and Oxidation of Glycerol ...................................141

5.3.5 Experiment 5 – Sulfurization and Oxidation of Hydrocarbons ..........................144

5.3.6 Experiment 6 – The Biodegradation Rate of Oxidized OSC ............................1448

5.4 Conclusions: ...............................................................................................................151

Chapter Six: Sulfurization of Organic Molecules .......................................................153

6.1 Introduction ................................................................................................................153

6.2 Experimental Methods ...............................................................................................153 6.2.1 Lipid Sulfurization Reactions .............................................................................153 6.2.2 Carbohydrate Sulfurization Attempts .................................................................155

6.3 Analytical Methods ....................................................................................................157 6.3.1 Freeze-Dry ..........................................................................................................157

6.3.2 FTICR-MS Analysis ...........................................................................................157 6.3.3 ChemAxon ..........................................................................................................158

6.4 Results ........................................................................................................................158

6.4.1 Experiment 1: Lipid Sulfurization for 5 days .....................................................158

6.4.2 Experiment 2: Lipid Sulfurization for 30 days ...................................................159

6.4.3 Experiment 3: Lipid Sulfurization for 30 days at 50°C .......................................160

6.4.4 Experiment 4: Carbohydrate Sulfurization for 30 days at 50°C ..........................165

6.5 Discussion ..................................................................................................................165 6.5.1 Viable products for AVECS processing .............................................................166

6.6 Conclusions ................................................................................................................167

Chapter 7 Conclusions and Future Work ...................................................................168

References ........................................................................................................................173 Appendix ..........................................................................................................................186

xi

List of Tables

Table 1.1 Summary of the consequences which occur with less than 1.5°C increase in

temperature, 1.5°C to 2°C temperature increase and warming of 3°C. (Hoegh-Guldberg

et al., 2018). ............................................................................................................................ 6

Table 1.2 Anthropogenic greenhouse gas (GHG) emissions and the corresponding average

residence time in the atmosphere. (IPCC, 2007, 2013; EPA, 2013; Crank and Jacoby,

2015). .................................................................................................................................... 10

Table 1.3 Strength and weaknesses of Carbon Capture and Storage (CCS) technology. BHT

refers to bottom-hole temperature (BHT) and EOR refers to enhanced oil-

recovery.(Gislason et al., 2014; Tawiah et al., 2018; Harrison et al., 2019). ....................... 16

Table 1.4 Strengths and weaknesses of early-stage Alternative Vectors for Carbon Storage

(AVECS) technology. In comparison to established CCS technology, AVECS

technology has potential to reduce costs through utilizing inexpensive reactants and

more globally accessible environments such as shallow saline contaminated aquifers as

carbon storage locations. ....................................................................................................... 17

Table 2.1 World production and reserves (all sulfur forms) in 2018. Units are in thousands of

metric tons. (Apodaca, 2019). ............................................................................................... 22

Table 2.2 Sulfur and sulfuric acid consumption in the United States (Apodaca, 2018). Units

are in thousands of metric tons. ........................................................................................ 23

Table 2.3 Sulfur species and corresponding oxidation states. * Thiosulfate has one sulfur

atom that is reduced and the other is oxidized. (Modified after Bertrand et al., 2015) ........ 25

Table 2.4 Four lineages of anoxic phototrophic bacteria. ............................................................. 31

Table 2.5 Examples of reactive and non-reactive sulfur compound classes in petroleum

(Lobodin et al., 2015b). ......................................................................................................... 37

Table 2.6 Sulfur-containing functional groups and corresponding carbon skeletons which

form organic sulfur compounds identified in nature (Modified from Sinninghe Damsté

and De Leeuw, (1990). .......................................................................................................... 39

Table 3.1 Sulfur-rich crude oil sample set and sulfur content (weight %) was retrieved

through elemental sulfur analysis. Bluesky, Gething Reno and West Cadotte field oils

were collected from research of Adams et al. (2013). .......................................................... 51

Table 3.2 Lithology and basin evolution of the Cangdong sag which consists of the same

formations as the Dongying depression except the Es4 member of the Shahejie

formation does not extend to the Cangdong sag. .................................................................. 56

xii

Table 3.3 Pr/Ph ratios for sulfur-rich oil sample set. All values are below 1.0, which suggests

anoxic source rock depositional settings. Bluesky (BS), Gething Reno (GR), West

Cadotte (WC), Rozel Point (RP), Shahejie formation (S) and Jianghan Basin (JH). ........... 61

Table 3.4 Summary of source, depositional environment, maturity and biodegradation on

biomarker ratios of sulfur-rich oil sample set. ...................................................................... 83

Table 4.1 Mass balance calculation for trial three elutions. Hexane was eluted first, followed

by DCM (dichloromethane) and lastly DCM and acetone. The total input mass in the

silver-ion column was 20 mg of whole oil, the total output mass (calculated from the

sum of each fraction) was 10.7 mg. This means that the accumulation of material in the

column is estimated to be 9.3 mg. ....................................................................................... 107

Table 4.2 Trial 4 elution order starts with hexane and ends with acetone/acetonitrile. The

concentration (volume/volume) for each solvent and the volume used to elute the two

different classes of sulfur compounds. ................................................................................ 108

Table 5.1 The molecular formula and weight fraction of each model compound and the

corresponding estimated water solubility, carbon solubility and biodegradation rank (0 -

5). Degradation time for biodegradation rank values: 3.25 – 5.00 = days to hours, >2.75

- 3.25 = weeks, >2.25 - 2.75 = weeks to months, >1.75 - 2.25 = months, <1.75 =

recalcitrant. The target carbon solubility for AVECS molecules is 15 kg C/ m3 and the

target biodegradation rank is <1.75. The best model compounds within each category

(lipids, carbohydrates, alkanes, water soluble compounds, and insoluble hydrocarbons)

are highlighted in yellow as they show greatest carbon solubility and most

biodegradation resistance compared to the other molecules within the same category...... 131

Table 5.2 Sulfurized and oxidized cholesterol exhibits highest carbon solubility (0.0965 kg

C/m3), followed by linolenic acid derivatives (0.0022 kg C/m

3). Squalene species show

negligible carbon solubility (2.24E-07 kg C/m3). ............................................................... 135

Table 5.3 BIOWIN 3 (ultimate biodegradation survey model) was used to determine the

biodegradation rate value for molecule (Ui) (EPA, 2011)………………………………...151

Table 6.1 Model compounds selected for lipid sulfurization experiments. ................................ 154

Table 6.2 All reactants and corresponding molar ratios and amounts used in the lipid

sulfurization experiments. Molar ratios and choice of reagents followed methods by De

Graaf et al. (1992) and Schouten et al. (1993). ................................................................... 154

Table 6.3 Reactants and sulfurized products from each experiment and the corresponding

measured mass to charge (m/z) and ion formulae as indicated in FTICR-MS plots. .......... 163

Table 6.4 Organic sulfur compound products from the reaction of squalene, linolenic acid

and β-Carotene with elemental sulfur and NaHS in DMF under different lipid

xiii

sulfurization conditions. Weight of sulfurized products were measured after liquid-

liquid and rotavapor solvent extraction. .............................................................................. 164

Table 6.5 The molecular formula, biodegradation rank and estimated water solubility of lipid

compounds (squalene, linolenic acid, B-carotene) and the sulfurized forms produced

from lipid experiment #3 (highlighted in yellow). The degradation rate for

biodegradation rank values: 3.25 – 5.00 = days to hours, >2.75 - 3.25 = weeks, >2.25 -

2.75 = weeks to months, >1.75 - 2.25 = months, <1.75 = recalcitrant. The target

solubility for AVECS molecules is 15 kg C/ m3 and the target biodegradation rank is

<1.75. .................................................................................................................................. 167

xiv

List of Figures

Figure 1.1 Temperature changes and evolution in comparison to the pre-industrial era and the

temperature projection trend for the near future. (Allen et al., 2018). .................................... 2

Figure 1.2 Average annual temperature (2006 – 2015) in comparison to preindustrial period

from 1850 – 1900. Temperatures are warming on land regions while oceans show less

temperature increase. (Allen et al., 2018). Green boxes indicate the 26 coded regions in

the report by Christensen et al. (2013). ................................................................................... 3

Figure 1.3 CO2 Concentration (ppm) measured at the Mauna Loa Conservatory by Scripps

Institution of Oceanography since 1958. CO2 concentrations have been increasing since

the industrial revolution (mid-18th century). (Keeling et al., 2001) ........................................ 5

Figure 1.4 Percentage of major GHG emissions in the U.S in 2017. Percentages do not add

up to 100% due to rounding. (U.S. Environmental Protection Agency, 2019) ...................... 9

Figure 1.5 The main sources of carbon dioxide emissions in the U.S. in 2017. (U.S.

Environmental Protection Agency, 2019) ............................................................................... 9

Figure 1.6 Stratigraphic column showing the Basal Cambrian Sand (BCS) CO2 storage

complex from the Quest CCS project operated by Shell Canada. (Tawiah et al., 2018). ..... 12

Figure 1.7 (a) Saline aquifers (blue) present in Canada and the U.S. (National Energy

Technology Laboratory, 2007). (b) Location and outline of the Western Canada

Sedimentary Basin (WCSB) which includes the Alberta Basin and Williston Basin.

(Singh et al., 2017). ............................................................................................................... 13

Figure 1.8 Salinity concentration of the hydrostratigraphic unit (HSU) of the Wapiti

formation - Belly River Group strata in the Alberta Basin (Alberta Geological Survey,

2019). .................................................................................................................................... 14

Figure 1.9 Diagram indicating thesis chapters which includes an introduction to the purpose

of this research and what the AVECS project is (Chapter 1). Sulfur incorporation

processes in natural settings are explored in Chapter 2. Molecular analysis was

conducted on sulfur-rich oils to reveal the environmental settings which contributed to

the oil generation and the structure of organic sulfur compounds found in the oils were

discussed in Chapter 3. The method development process for isolating sulfur-rich

hydrocarbon fractions is discussed in detail in Chapter 4. Then, Chapter 5 identifies how

sulfur incorporation and oxidation affects hydrocarbon solubility and biodegradation

rate using chemical modelling software. In Chapter 6, laboratory sulfurization

experiments were tested on lipids and carbohydrates (Chapter 6) and conclusions and

future work (Chapter 7). ....................................................................................................... 18

Figure 2.1 Increasing elemental sulfur stockpiles at Fort McMurray, Alberta, Canada (AER,

2017). .................................................................................................................................... 22

xv

Figure 2.2 Biogeochemical systems in marine sediment. Sulfate-reducing bacteria thrive in

the presence of organic matter and anoxic conditions (Goldhaber, 2005)............................ 27

Figure 2.3 The sulfur cycle pathways. In numerical order, pathways 1 to 4 refer to

assimilatory sulfate reduction, mineralization (sulfhydrization), dissimilatory sulfate-

reduction and dissimilatory sulfide oxidation (Bertrand et al., 2015). ................................. 29

Figure 2.4 Sulfur metabolism pathways. Assimilatory sulfate reduction (blue). Sulfur

oxidation (green). Elemental sulfur disproportionation (purple)( Fike et al., 2015). ........... 30

Figure 2.5 Sulfur cycle, sulfur reservoirs and different sulfur flux pathways. DMS refers to

dimethyl sulfide and COS refers to carbon oxysulfide (Bertrand et al., 2015)..................... 31

Figure 2.6 Organic matter sinks below the anoxic boundary and activates sulfate reduction

pathways in fresh water lakes (modified after Fenchel et al., 2012). ................................... 34

Figure 2.7 Four main sulfur compound classes found in petroleum (Modified after Han et al.,

2018) ..................................................................................................................................... 37

Figure 2.8 Examples of polycyclic aromatic sulfur heterocycles (PASH). Image from Nocun

and Andersson, (2012). ......................................................................................................... 40

Figure 2.9 (a) Second degradation pathway for dibenzothiophene (DBT), which targets

carbon-sulfur bonds and preserves carbon-carbon bonds. DszA , DszB, DszC refers to

different proteins in organism Rhodococcus erythropolis. (b) Third degradation pathway

by Brevibacterium species which completely mineralizes DBT. (Modified from Gogoi

and Bezbaruah, 2002). .......................................................................................................... 42

Figure 3.1 The transformation from phytane carbon skeleton to cyclic organic sulfur

compounds during diagenesis through two pathways: intramolecular sulfur

incorporation and intermolecular sulfur addition reactions. (Kohnen et al. 1991) ............... 47

Figure 3.2 a) Sulfur compounds form through intramolecular incorporation of polysulphides

(Kohnen et al., 1991). b) General scheme for sulfur incorporation into unsaturated lipid

precursors (Sinninghe Damsté et al., 1989). ......................................................................... 47

Figure 3.3 Intramolecular sulfur incorporation into double bonds of isoprenoids. Diagenesis

of kerogen forms saturated, aromatic and organic sulfur compound products. (Peters et

al 2005). ................................................................................................................................ 48

Figure 3.4 There are more than 600 types of natural carotenoids, however the carotenoids

shown above are the most abundant in marine environments. Isorenieratene and

Chlorobactene are common in green sulfur bacteria. (Peters et al., 2005b) ......................... 50

Figure 3.5 Geologic timescale and the Peace River area which is comprised of the Bullhead

and Fort St. John Groups. (Modified from AER, 2017 and Adams et al., 2013) ................. 52

xvi

Figure 3.6 The location of Peace River oil samples. Sulfur-rich oils were collected form

Gething Reno Field (green), West Cadotte (purple) and Bluesky formation (blue).

Modified from Jennifer Adams et al. (2012). ....................................................................... 52

Figure 3.7 Location of Rozel Point on map. (Utah Geological Survey, 2005)............................. 53

Figure. 3.8 The Jianghan basin located in Hubei province of China and the location of the

Qianjiang depression. (Modified after Brassell et al., 1988) ................................................ 54

Figure 3.9 Location of Bohai Bay basin and the Dongying depression where the Shahejie

formation lies. ....................................................................................................................... 56

Figure 3.10 Schematic map showing the Dongying depression within the Bohai Bay Basin

and the lithology facies of source rocks: a) ES4 member and b) ES3 member (Li et al.,

2003). .................................................................................................................................... 57

Figure 3.11 Formation of pristane and phytane from phytol side chain of chlorophyll is

dependent on oxic and anoxic environmental conditions. .................................................... 62

Figure 3.12 Cross plot of dibenzothiophene/phenanthrene (DBT/P) vs pristane/ phytane

(Pr/Ph) to determine source rock depositional environments (modified after Hodairi and

Philp, 2012). Sulfur-rich oil samples Rozel Point (RP), Jianghan (JH), Gething Reno

(GR) fall in the marine carbonate and lacustrine zone (purple square) and the ratios

indicate that source rocks from Bluesky (BS), West Cadotte (WC), and Shahejie (S)

were deposited in mainly lacustrine environments (blue square). ........................................ 63

Figure 3.13 Gammacerane index 10*(GAM/GAM+30H) and pristane/phytane (Pr/Ph) ratio

for sulfur-rich oil sample set. High gammacerane indices indicate increased water

salinity, water stratification or natural sulfurization processes. ............................................ 64

Figure 3.14 m/z 191 Chromatogram showing homohopanes (C31 – C35) distribution in sulfur-

rich crude oil samples from: (a) Bluesky Formation, (b) Gething-Reno Formation, (c)

West Cadotte field, (d) Rozel Point, (e) Jianghan Basin and (f) Shahejie Formation.

GAM represents gammacerane.. ........................................................................................... 67

Figure 3.15 Homohopane Index (C35/ C31-C35) and Norhopane/hopane (C29/C30) which are

source and depositional setting indicators. High homohopane indices (>0.09) suggests

high redox potential, anoxic reducing environments, marine sources, and bacterial input

from bacteriohopanetetrol (Peters et al., 2005) ..................................................................... 67

Figure 3.16 Ternary diagram with relative distribution of C27, C28 and C29 sterane

abundances. ........................................................................................................................... 68

Figure 3.17 Biomarkers which are indicative of the degree of thermal maturity:

dibenzothiophene/phenanthrene (DBT/P) is plotted against 28, 30-bisnorhopane/ 25, 28,

30-trisnorhopane (BNH/TNH). ............................................................................................. 69

xvii

Figure 3.18 Thermal maturity parameters C31 homolog (22S/22S+22R) and C29 sterane

(20S/20S+20R). .................................................................................................................... 70

Figure 3.19 Biomarker biodegradation scale which ranks biodegradation severity based on

the presence of hydrocarbon classes. L, M, H refers to lightly biodegraded, moderately

biodegraded and heavily biodegraded, respectively. (Peters and Moldowan, 1993). ........... 72

Figure 3.20 m/z 85 chromatograms which show n-alkane and isoprenoid distributions in

sulfur-rich crude oil samples from: (a) Bluesky formation, (b) Gething-Reno formation,

(c) West Cadotte field, (d) Rozel Point, (e) Jianghan Basin and (f) Shahejie formation.

IS1 represents squalane internal standard. ............................................................................ 74

Figure 3.21 Organic sulfur compound fractions obtained from liquid chromatography using

silver nitrate impregnated silica gel compared to whole oils. ●, indicates radical atoms.

RMI, relative monoisoptopic intensity (a) Liquid chromatography method removed

hydrocarbons and enhanced sulfur intensities (b) Whole oils. ............................................. 76

Figure 3.22 The relative monoisotopic intensity (RMI) and carbon number distributions for

sulfur-rich oil sample set. Rozel Point oil (red) shows high intensity peaks at C20, C29

and C40. Jianghan Basin oil (orange) shows peaks at C20, C24, C26, C28, C30, and C40.

Shahejie oil (black) also shows similar peaks at C14, C27, C29, and C40. Alberta oils (blue,

green, pink) are depleted in low carbon numbers but show increased RMI for higher

carbon number classes. ......................................................................................................... 77

Figure 3.23 Double bond equivalent distributions. (a) Radical S1 class. (b) Protonated S1

class. Black circle emphasizes DBE 1 peak which is unique only to Jianghan Basin oil..... 78

Figure 3.24 Carbon distribution for radical sulfur class S1 at a) DBE 2 b) DBE 3 c) DBE 5

and d) DBE 6. ....................................................................................................................... 79

Figure 3.25 (a) Double bond equivalent (DBE) distribution for sulfur class S3. (b) Carbon

number distribution for sulfur class S3 at DBE 7……………………………………………………………………..80

Figure 3.26 (a) DBE distribution for sulfur class S5. (b) Carbon number distribution for sulfur

class S5 at DBE 13. ............................................................................................................... 81

Figure 4.1 AVECS pathways to determine organic compounds which have potential to form

biologically refractory water soluble organic molecules. Pathway 1 refers to utilizing

sulfurization reaction on organic biomass waste and pathway 2 refers to isolating sulfur-

rich fractions from sulfur-rich oils and analyzing the S containing compounds as models

for AVECS molecules. .......................................................................................................... 86

Figure 4.2 Sulfur compound structures and reactivity classification. (Modified after Lobodin

et al., 2015) ........................................................................................................................... 88

xviii

Figure 4.3 Polycyclic aromatic sulfur heterocycles commonly found in petroleum (PASH)

(Wang and Stout, 2007) ........................................................................................................ 88

Figure 4.4 Interaction and bonding between silver ions and double bonds. The complexes

between the silver-ion and double bond are a type of charge-transfer mechanism. The

unsaturated compound donates an electron to the silver ion and results in the formation

of a sigma bond between the orbitals of the double bond and silver ion. Ag+ represents

silver-ions. (Modified after Nikolova-Damyanova, 2018). .................................................. 91

Figure 4.5 Silver nitrate impregnated silica gel column design following methods by Wei et

al. (2012). The S1 fraction (saturated hydrocarbons) was eluted with 3mL of hexane,

followed by 8mL DCM eluted the S2 fraction (non-reactive OSC), and lastly the S3

fraction (reactive sulfides) were eluted with 2 mL of acetone. ............................................. 92

Figure 4.6 Cloudy S3 fraction (eluted with acetone) which contained crystal-like precipitate.

Acetone was evaporated with nitrogen gas. The S3 fraction was soluble in toluene,

however the precipitate was only miscible with methanol. Therefore, the sample was

redissolved in toluene and passed through a glass wool column to remove any

particulates. ........................................................................................................................... 94

Figure 4.7 Acetone fraction from blank columns (no sample). (A) Silica gel-only column

shows no precipitate. (B) Silver nitrate impregnated silica gel column shows crystal-like

precipitate. ............................................................................................................................. 94

Figure 4.8 The silver-ion column was modified with reduced volume of AgNO3 impregnated

silica gel and less whole oil analyte, compared to original experiment design by Wei et

al. (2012), to improve sulfur compounds separation and prevent precipitation. The S1

fraction was eluted first with 3 mL of hexane, followed by 8 mL of DCM which eluted

the S2 fraction, and lastly the S3 fraction was eluted with 2 mL of acetone. ....................... 95

Figure 4.9 S3 fraction (acetone elution) from trial one method development (see Fig. 4.8 for

column design). A) Precipitate formed as fraction was concentrated using nitrogen gas.

B) White crystal-like precipitate is observed at the bottom acetone fraction from the

blank column. ........................................................................................................................ 96

Figure 4.10 Comparison of GC-MS chromatograms. (A) Total ion chromatogram of

Athabasca sulfur-rich whole oil from S2 fraction (eluted with DCM). (B) Extracted ion

chromatogram of Athabasca sulfur-rich whole oil from S2 fraction. (C) Total ion

chromatogram of Athabasca whole oil from S3 fraction (eluted with acetone). (D)

Extracted ion chromatogram of Athabasca whole oil from S3 fraction. Non-reactive

aromatic sulfur compounds shown in extracted ion chromatograms: dibenzothiophenes

(m/z 184) (black), methyldibenzothiophene (m/z 198)(blue), dimethyldibenzothiophenes

(m/z 212)(red), naphthobenzothiophene (m/z 234) (grey) and

methylnaphthobenzothiophene (m/z 248)(yellow). .............................................................. 97

xix

Figure 4.11 1.0 mg of DBT (dibenzothiophene) standard loaded into a silver-ion column

comprised of 0.400g of silica gel and 0.200g of silver nitrate (10 wt%) impregnated

silica gel. The column was first eluted with 8.0 mL of DCM followed by 8.0 mL of

acetone. ................................................................................................................................. 99

Figure 4.12 Total ion chromatograms. A) DCM fraction which shows (m/z 184) DBT peak

and B) acetone fraction indicate that DBT was eluted fully into DCM fraction. ................. 99

Figure 4.13 Trial two of silver nitrate impregnated silica gel column method development.

One silver-ion column (left) was loaded with 1 mg of dibenzothiophene (DBT) standard

and the other silver-ion column (right) was loaded with 20 mg of Athabasca whole oil.

Each column was eluted with four different solvents and the elutions were collected in

separate fractions. The first elution involved 8 mL of DCM, followed by 8 mL of

acetone, then toluene and lastly tetrahydrofuran (THF). .................................................... 100

Figure 4.14 Trial two sulfur fractionation elutions. Top images represent elution which came

from column on the right which contained 20mg of whole oil. Bottom images are from

left column which was loaded with 1 mg of DBT standard. Precipitate was observed in

acetone fractions from both columns. DCM = dichloromethane, ACET = acetone, TOL

= toluene, THF = tetrahydrofuran. ...................................................................................... 101

Figure 4.15 Chromatograms from the silver-ion column containing whole oil. (A) The

dichloromethane (DCM) elution shows several aromatic sulfur compounds. (B) Acetone

fraction shows some aromatic sulfur compounds, but less than the DCM fraction.

Contaminants (benzenes) and unknown compounds are observed in the toluene fraction

(C) and tetrahydrofuran fraction (D). Dibenzothiophenes (DBT),

methyldibenzothiophene (MDBT), dimethyldibenzothiophenes (DMDBT),

naphthobenzothiophene (NBT), methylnaphthobenzothiophene (MNBT). ....................... 102

Figure 4.16 Trial three column design to prevent silver-ion leakage and precipitate from

forming in acetone fraction. ................................................................................................ 104

Figure 4.17 Trial three method development. A) Column design with silver nitrate

impregnated silica gel sandwiched between two layers of plain silica gel. B) Eluates

starting from the left: Hexane, DCM, DCM to acetone following gradual polarity

increase and pure acetone fraction. ..................................................................................... 104

Figure 4.18 Extracted ion chromatograms (m/z 134, 148, 176, 212, 234, 248). (A) Whole oil.

(B) Hexane elution. (C) Dichloromethane (DCM) and acetone gradient fraction. (D)

Pure acetone fraction. Higher molecular weight sulfur compounds, such as

dibenzothiophene and methylnaphthobenzothiophene, are observed in the DCM and

acetone gradient fraction, while lower molecular weight sulfur compounds such as

sulfides are more dominant in the pure acetone fraction. ................................................... 106

xx

Figure 4.19 (A) Extracted ion chromatogram showing five pure sulfur compounds that make

up the standard: thiophene, thiolane, 1-benzothiophene, dibutyl sulfide and

dibenzothiophene. (B) The sulfur compounds were identified through mass

chromatography with target ions 84, 88, 134, 146 and 184, respectively. ......................... 110

Figure 4.20 Trial four column design. ........................................................................................ 110

Figure 4.21 Left column loaded with 10 μL of sulfur compounds standard, the center column

is loaded with 5 mg of sulfur-rich whole oil from the Athabasca oil sands, and the

column on the right is loaded with 5 mg of Athabasca whole oil as well as 10 μL of

sulfur compounds standard. ................................................................................................ 111

Figure 4.22 Fractions which eluted from the silver-ion column which was loaded with 10 μl

of sulfur standard. (A) S1 fraction (hexane elution) show no sulfur compounds. (B)

Aromatic sulfur compounds (thiophenes, 1-benzothiophene and dibenzothiophene) were

identified in the S2 fraction (DCM/acetone gradient elution) from target ions 84, 134

and 184. (C) Sulfide compounds (thiolane and dibutyl sulfide) were identified in the S3

fraction (acetone/acetonitrile elution). ................................................................................ 113

Figure 4.23 The colour of the S1 eluate was monitored to ensure that coloured aromatic

compounds do not break through in the S1 fraction (hexane eluate). This was done by

watching the movement of coloured fronts within the silver-ion column. ......................... 115

Figure 4.24 Extracted ion chromatogram of the Athabasca oil S1 fraction (hexane eluate) oil

in experiment trial 6. Saturated hydrocarbons are present and sulfur compounds were

not observed in this fraction. ............................................................................................... 117

Figure 4.25 Extracted ion chromatogram of the S2 fraction (hexane/DCM eluate) of

Athabasca oil in experiment trial 6. Aromatic sulfur compounds 1-benzothiophene

(DBT) and dibenzothiophene (DBT) are present in this fraction. .................................... 118

Figure 4.26 Extracted ion chromatogram of the S3 fraction of Athabasca oil in experiment

trial 6. Non-aromatic sulfur compounds, thiolane and dibutyl sulfide, are present in this

fraction. ............................................................................................................................... 118

Figure 4.27 FTICR-MS plot showing compound class distribution for Athabasca whole oil

(black), S2 fraction (dark grey) and S3 fraction (light grey). Relative monoisotopic

intensity (RMI) is the signal measured from a fragment ion that is made up of the most

abundant natural isotope of each atom in the molecular ion............................................... 119

Figure 4.28 FTICR-MS plot shows compound class distribution for oil fractions from Rozel

Point (red), Jianghan Basin (blue), and Athabasca oil sands (grey). (A) Fraction #2 or

the S2 fraction shows predominantly 1 to 3 sulfur atoms per molecule. (B) Fraction #3

or the S3 fraction shows 1 to 5 sulfur atoms per molecule and also mixed nitrogen-

oxygen and nitrogen-sulfur molecules. ............................................................................... 120

xxi

Figure 4.29 FTICR-MS DBE distribution for Athabasca whole oil (black), S2 fraction (dark

grey) and S3 fraction (light grey). ....................................................................................... 121

Figure 5.1 Formation of thiolane and thiophene through intramolecular incorporation of

polysulphides (after Kohnen et al., 1991). .......................................................................... 125

Figure 5.2 Sulfurization and oxidation of squalene model compounds. (A) Squalene. (B)

Sulfur incorporation into squalene results in the formation of two thiolanes. (Bi)

Subsequent oxidation forms sulfoxide groups. (Bii) The most oxidized state (two

sulfone groups) of the sulfurized squalene model compound............................................. 128

Figure 5.3 Hypothesized pathway for forming sulfurized steroids in Ace Lake Sediments.

Inorganic sulfur species react with both 5a-stan-3-ones and 5B-stan-3-ones to form

sulfurized steroids. Furthermore, the transformation from stanones to stanols is a

reversible process. (After Kok et al., 2000). ....................................................................... 129

Figure 5.4 Sulfurization and oxidation of steroid model compounds. (C) Cholesterol. (D)

Sulfur incorporation into hydroxyl group. (Di) Addition of a sulfonate group after

oxidation. (E) Sulfur incorporation into hydroxyl group and the formation of thiolane

through double bond reduction. (Ei) Subsequent oxidation forms sulfonate and sulfoxide

groups. (Eii) The most oxidized state of the sulfurized cholesterol model compound

includes sulfonate and sulfone groups. ............................................................................... 130

Figure 5.5 Weight fraction of oxygen and carbons and the influence on carbon solubility for

derivative lipid molecules (kg C/m3). Increasing carbon solubility is indicated by the

increased bubble size. See Table 5.1 for carbon solubility values for modified

compounds: squalene (Bi, Bii), b) cholesterol (Di – Eii), c) linolenic acid (F-Gii). .......... 133

Figure 5.6 Sulfurization and oxidation of linolenic acid model compounds. (F) Linolenic

acid. (G) Sulfur incorporation into double bonds to form thiolane. (Gi) Oxidation results

in the addition of a sulfoxide group. (Gii) Subsequent oxidation forms sulfone group,

which is the most oxidized state of the sulfurized linolenic acid model compound. .......... 134

Figure 5.7 Weight fraction of carbon and oxygen to carbon solubility for sulfurized and

oxidized squalene (Bi), cholesterol (Ei) and linolenic acid (Gi) model compound

modifications. ...................................................................................................................... 134

Figure 5.8 Monosaccharides: arabinose (H), lyxose (I), and xylose (J) and corresponding

sulfurized products (Hi, Ii, Ji) which formed in the carbohydrate sulfurization

experiments by van Dongen et al. (2003). .......................................................................... 136

Figure 5.9 Pentose monosaccharides (H, I, and J) show higher carbon solubility (399 kg/m3)

compared to sulfurized carbohydrates (Hi, Ii, and J) with carbon solubility of 1.53

kg/m3. .................................................................................................................................. 137

xxii

Figure 5.10 Inorganic sulfur species incorporate into phytol and phytadiene to form sulfur

bounded phytane derived structures (van Dongen, 2003)................................................... 138

Figure 5.11 Sulfurization and oxidation of isoprenoid model compounds. (K) Phytol. (L)

Sulfurization forms thiophene. (Li) Oxidation forms sulfone group. (M) Sulfur

incorporation into phytol forms thiolane structure. (Mi) Oxidation results in the addition

of a sulfoxide group. (Mii) Subsequent oxidation forms sulfone group. ............................ 139

Figure 5.12 The sulfurized isoprenoids with thiolane (orange) show a slightly higher carbon

solubility (2.19E-07 kg C/m3) compared to the isoprenoid which formed thiophenes

(blue) (1.34E-07 kg C/m3). ................................................................................................. 140

Figure 5.13. Oxidation of isoprenoid thiolane (M, orange) showed increased carbon solubility

through the addition of sulfoxide to model compound (Mi, blue). Model compound (Mi)

shows greater carbon solubility compared sulfurized model compound (Mii, gray) which

consists of a sulfone group. ................................................................................................. 140

Figure 5.14 Sulfurization and oxidation of glycerol model compounds. (N) Glycerol. Sulfur

incorporation occurs at hydroxyl groups in glycerol to form thiols (O, P, and Q).

Oxidation of sulfurized glycerol model compounds form sulfonate groups (Oi, Pi, and

Qi). ...................................................................................................................................... 141

Figure 5.15 Effect of thiol groups on carbon solubility of glycerol. (See Fig. 5.14 for

progression of N, O, P and Q) ............................................................................................. 142

Figure 5.16 The effect on carbon solubility due to the addition of sulfonate groups on

sulfurized glycerol (See Fig. 5.14 Q and Qi). ..................................................................... 143

Figure 5.17 A fullerene molecule (C60) that is also informally known as the carbon

buckyball. The fullerene molecule could be a potential model compound for the ideal

AVECS molecule. ............................................................................................................... 145

Figure 5.18 Sulfur incorporation into tri-unsaturated C37 hydrocarbon. After Sinninghe

Damsté et al. (1989). ........................................................................................................... 145

Figure 5.19 Sulfurization and oxidation of C30

hydrocarbon chains. (R) C30

H62

. Conceptual

sulfur incorporation form thiolanes (S, T, and U). Oxidation of sulfurized C30

hydrocarbons form sulfoxide groups (Si, Ti, and Ui). ........................................................ 146

Figure 5.20 Sulfurization and oxidation of C60 hydrocarbon chains. (V) C30H62. Conceptual

sulfur incorporation form thiolanes (W and X). Oxidation of sulfurized C30

hydrocarbons form sulfoxide groups (Wi and Xi). ............................................................. 146

xxiii

Figure 5.21 The effect of number of thiolane-1-oxide groups on the carbon solubility in water

for (a) C30 H62 and (b) C60 H122. Green horizontal line delimits AVECS target water

solubility (> 15 kg C/m3). ................................................................................................... 147

Figure 5.22 Sulfurized and oxidized model compounds (from each experiment) with the

greatest carbon solubility. Lipids (Ei), carbohydrates (Hi), isoprenoids (Mi), glycerol

(Qi), hydrocarbon chains (Ui and Xi). ................................................................................ 149

Figure 5.23 Biodegradation rate of oxidized OSC (Ei, Hi, Mi, Qi, Ui, Xi). See figure 5.22 for

structures. Red data points are recalcitrant. Yellow indicates biodegradation will take

weeks to months, and green indicates biodegradation will take weeks (EPA, 2011). ........ 150

Figure 5.24 Process for sulfolane synthesis. Sulfolane is synthesized by the reaction between

1,3-butadiene (1) with sulfur dioxide (2) to form sulfolene (3). The hydrogenation of

sulfolene forms sulfolane (4). (Tilstam, 2012; Bak et al., 2018). ....................................... 151

Figure 6.1 Analytical scheme of lipid sulfurization experiments ............................................... 155

Figure 6.2 Liquid-liquid extraction on sulfurized β-carotene reaction mixtures. ....................... 155

Figure 6.3 (a) Carbohydrate sulfurization experimental set up. (b) Addition of pure copper

flakes to remove excess elemental sulfur. Copper turns black (copper sulfide)

instantaneously. (c). After 24 hours of stirring, the entire solution appears black. ............ 156

Figure 6.4 (a) Pasteur pipette filled with pure copper granules and glass wool. (b) Copper

turns black after eluting sulfurized sample through the column. ........................................ 157

Figure 6.5.a) Sulfurized carbohydrates in freeze-dry machine after removing excess sulfur b)

Freeze dried sulfurized carbohydrates. From the left: sucrose, glucose, starch and blank. 157

Figure 6.6 FTICR-MS mass spectrum showing peak intensity, mass to charge (m/z) ion and

molecular formula. Sulfurization of squalene (C30H52S) was detected in experiment #1

(lipid sulfurization for 5 days). ........................................................................................... 159

Figure 6.7 Possible organic sulfur compound structure with molecular formula C30H52S.

Sulfurization of squalene in experiment #1 (lipid sulfurization for 5 days) may have

formed one thiolane intramolecularly. ................................................................................ 159


molecular formula. Sulfurized squalene (C30H54S2) is detected in experiment #2 (lipid

sulfurization for 30 days). ................................................................................................... 159

Figure 6.9 Possible organic sulfur compound structure with molecular formula C30H54S2.

Sulfurization of squalene (experiment #2 - lipid sulfurization for 30 days) may have

formed two thiolanes intramolecularly. .............................................................................. 160

xxiv

Figure 6.10 Possible organic sulfur compound structure with molecular formula C18H32O2S2.

Sulfurization of linolenic acid (experiment #3 - lipid sulfurization for 30 days at 50°C)

may have formed two thiolanes intramolecularly. .............................................................. 160


molecular formula. Sulfurized linolenic acid (C18H32O2S2) is detected in experiment

#3 (lipid sulfurization for 30 days at 50°C). ....................................................................... 161


Sulfurization of squalene (experiment #3 - lipid sulfurization for 30 days at 50°C) may

have formed four thiolanes intramolecularly. ..................................................................... 161



sulfurization for 30 days at 50°C). ...................................................................................... 162


computed ion formula. Sulfurized β-carotene (C40H68S7) is detected in experiment #3

(lipid sulfurization for 30 days at 50°C). ............................................................................ 163


Sulfurization of β-Carotene (experiment #3 - lipid sulfurization for 30 days at 50°C)

may have formed four thioanes and 3 thiolanes intramolecularly. ..................................... 163

Figure 6.16 (a) Chemical structure of linolenic acid (C18H30O2) compared to possible

sulfurized linolenic acid structures (b) C18H34O2S and (c) C18H32O2S2, which are

molecular formulas extrapolated from the FTICR-MS mass spectrum (Fig. 6.11). ........... 165

xxv

List of Abbreviations

Symbol Definition

APPI Atmospheric Pressure Photo Ionization

APPI-P Atmospheric Pressure Photo Ionization in Positive ion mode

AVECS

BT

Alternative Vectors for Carbon Storage

Benzothiophene

BCS Basal Cambrian Sands

CCS Carbon Capture and Storage

CH4 Methane

CO2 Carbon Dioxide

Da Dalton

DBE Double Bond Equivalent

DBT Dibenzothiophene

DCM:MeOH Dichloromethane:Methanol

FTICR-MS Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

GC-MS Gas Chromatography- Mass Spectrometry

GHG Greenhouse Gas

HC Hydrocarbon

IPCC Intergovernmental Panel on Climate Change

Kg C/m3 Kilograms of Carbon per Cubic Meter

mD millidarcy

Mg/L Milligrams per Litre

μm Micromolar

μL Microlitre

MS Mass Spectrometry

m/z Mass to Charge Ratio

MeOH Methanol

NDC Nationally Determined Contributions

xxvi

NO3 Nitrous Oxide

OSC Organic Sulfur Compounds

PASH Polycyclic Aromatic Sulfur Heterocycles

ppm Parts Per Million

RMI Relative Monoisotopic Intensity

S Sulfur

SPE Solid Phase Extraction

SSS Small-Scale Separation

THF Tetrahydrofuran

Wt Weight

1

Chapter One: Introduction

This thesis involves the discussion, analysis and development of a potential carbon sequestration

method inspired by natural sulfurization processes in sedimentary organic matter.

1.1 What is Global Warming?

Over the past 170 years, scientists observed the climate to follow an increasing warming

trend for both air and sea temperatures. This increase in surface temperatures is known as the

global warming phenomenon and temperatures are expected to continue to rise unless more

stringent policies on carbon management are enforced and development and application of

carbon negative technology is accelerated. Some argue that this trend belongs to earth’s natural

climate fluctuations while abundant empirical evidence shows recent global warming is

predominantly human-induced (Keeling et al., 2001; Wong, 2015; Hoegh-Guldberg et al., 2018).

Anthropogenic factors, such as greenhouse gas (GHG) emissions from transportation and

industrial uses, have strongly contributed to long term global changes in temperature. Some

consequences of global warming and rising atmospheric carbon dioxide levels include sea level

rise, ocean acidification, and extreme weather activity (Wong, 2015). As a result of these effects

over the past several decades, most countries are concerned and acknowledge climate change as

a high priority global threat.

1.2 Paris Agreement

In an effort to implement global initiatives of environmental remediation and desirable

pathways to delay increasingly warm climates, the Paris Agreement was established in 2016 to

unite 130 countries to prevent future temperatures from increasing no more than 2°C above

temperatures during the pre-industrial era (1850 – 1900) (Lewis, 2016). However, the ideal

global target is less than 1.5◦C increase above pre-industrial levels (Allen et al., 2018). As of

2017, the average global temperature increase, since the pre-industrial era, is estimated to be

1.04°C (Fig. 1.1) and temperatures are increasing up to 0.33°C per decade (Allen et al., 2018).

Despite these global averages, 20-40% of the world population live in areas that have already

reached 1.5°C (Fig. 1.2). Over the past few decades, more warming is observed in land regions

and, especially, in the Artic where a 1.0°C increase per decade has been recorded over the past

2

30 years (Christensen et al., 2013). Furthermore, the current nationally determined GHG

reductions for the period from 2016-2030 will not only fail to limit global warming to 1.5°C but

is, in fact, projecting towards a 3 – 4°C temperature increase by 2100 (Allen et al., 2018).

Figure 1.1 Temperature changes and evolution in comparison to the pre-industrial era and

the temperature projection trend for the near future. (Allen et al., 2018).

3

Figure 1.2 Average annual temperature (2006 – 2015) in comparison to preindustrial

period from 1850 – 1900. Temperatures are warming on land regions while oceans show

less temperature increase. (Allen et al., 2018). Green boxes indicate the 26 coded regions in

the report by Christensen et al. (2013).

1.3 Complexities

It is well established that one of the largest sources of GHG emissions come from

burning fossil fuels, which produces CO2 pollution (Moreira and Pires, 2016). However, the

transition away from fossil fuels has been slow as many rely on petroleum resources for energy

supply. Although the obvious solution would be to immediately abandon the use of fossil fuels

(natural gas, coal, oil), this strategy is complex and difficult to carry through especially when

many countries rely heavily on petroleum resources for energy supply with political and

economic considerations being a primary driver of behaviour. Fossil fuel resources are more

affordable, globally accessible and show more economic potential within current economic

models, compared to clean alternative fuels (Dobrotkova et al., 2018; National Energy Board,

2018). Canadians, for example, rely on fossil fuel products for 73.9% of energy use (Statistics

Canada, 2019), while 79.7% of the world’s energy consumption (in 2015) is from fossil fuel

products (OECD and IEA, 2015). For these reasons, the transition away from fossil fuels has

been slow. Furthermore, according to Kemper (2015), even if fossil fuel consumption is

completely phased out by 2050, there would still be a tremendous amount of excess CO2 in the

4

atmosphere that will require removal, hence carbon negative technologies are needed to reach

global environmental targets and prevent climate change from worsening.

There are other complexities besides fossil fuel consumption and economics, which slow

climate policy implementation. Extreme weather news reports have appeared more frequently in

the media spotlight especially during the last decade. However, media rarely informs the

audience the seriousness of climate change, which causes many communities to have trouble

understanding the correlation between anthropogenic activity, greenhouse gases and climate

change (Wong, 2015). In other words, if people do not understand the seriousness of global

warming, policies and implementations will not be supported and communities will not put in

effort to reach environmental targets. While many realize the importance of conserving energy

and becoming less wasteful, the public is only willing to make minimal changes to daily habits

because they do not see the scientific evidence of climate change and the human activity that is

causing it. Citizens in developed countries are often shielded from sites such as overflowing

landfills and fossil fuel combustion, therefore this often leads to the public misunderstand that

climate change is a future problem for generations to come when, in reality, it is a problem that is

affecting us now.

Scientific information and evidence on climate change is most definitely challenging to

communicate to the general public in a concise manner, especially when most audiences are

generally interested in other current events. For example, information that is difficult to convey

include different types of greenhouses gases and the fact that carbon dioxide (CO2) is one of the

most impactful gases as it not only prevents outbound infrared radiation from leaving the

atmosphere, but it also takes several centuries to vanish from the atmosphere (Wong, 2015).

1.4 Severity of Climate Change

As of 2019, the carbon dioxide concentration measured at the Mauna Loa observatory in

Hawaii is 414.30 parts per million (ppm) (Fig. 1.3). Compared to pre-industrial concentrations

before 1958 which was 280 ppm (Keeling et al., 2001), CO2 levels have increased nearly 48%

since the industrial revolution. These levels are the highest CO2 concentrations recorded in the

last 800,000 years and 68% of this increase occurred in the last 50 years (Wong, 2015).

5

Figure 1.3 CO2 Concentration (ppm) measured at the Mauna Loa Conservatory by Scripps

Institution of Oceanography since 1958. CO2 concentrations have been increasing since the

industrial revolution (mid-18th century). (Keeling et al., 2001)

The largest contributors to this exponential increase of atmospheric carbon dioxide come

from the combustion of fossil fuels for electricity, transportation and production of industrial

materials (Bui et al., 2018). Many suggest that the solution to slow climate change is to minimize

fossil fuel usage and consume less energy, however convincing the average person to drive less

or utilize more environmentally-friendly products is difficult and has shown limited success.

After all, most people refuse to make habit changes if they do not believe the problem will affect

them directly. Table 1.1 shows the many effects of climate change that are currently happening

even with a warming of less than 1.5°C. Such effects include food and crop scarcity, insufficient

water supply, and human and organism mortality (Hoegh-Guldberg et al., 2018).

6

Table 1.1 Summary of the consequences which occur with less than 1.5°C increase in

temperature, 1.5°C to 2°C temperature increase and warming of 3°C. (Hoegh-Guldberg et

al., 2018).

1.5 The Carbon Cycle

To understand why industrial emissions affect earth’s environment and how atmospheric

CO2 can be captured from a source and be safely stored away in a sink, it is essential to first

7

decipher what occurs throughout the carbon cycle. The carbon cycle involves a complex

sequence of events that allows carbon to propagate through the four spheres of earth:

atmosphere, biosphere, hydrosphere and lithosphere. In the atmosphere, carbon exists as carbon

dioxide, which is absorbed by plants for photosynthesis to generate energy. Living organisms in

the biosphere consume these plants and continue to pass carbon to other living organisms that are

higher up in the food chain. Then, the carbon is eventually released back into the atmosphere or

hydrosphere as carbon dioxide when land animals, aquatic creatures or plants respire. As animals

or plants decay, the carbon atoms that make up their organic structures enter the lithosphere.

Then with pressure, heat, and time, the carbon forms resources such as coal, oil and natural

gases. Energy suppliers and other key emitters utilize petroleum resources to generate energy and

products through combustion, which causes lithospheric carbon to enter the atmosphere at an

accelerated rate. Consequently, excessive atmospheric carbon exists due to anthropogenic

induced processes, thus creating a greenhouse effect on earth. Furthermore, natural carbon sinks

are depleting due to anthropogenic land use which has greatly reduced vegetative species that

have the ability to absorb and store carbon.

1.6 Greenhouse Gas Effect

The greenhouse effect begins when sunlight comes in contact with the earth’s surface.

Some of the inbound sunlight passes through earth’s atmosphere and becomes absorbed, while

some is re-radiated as infrared radiation from the earth’s surface. Furthermore, some of the light

is reflected from the atmosphere as outbound energy into space. The accumulation of greenhouse

gases in the atmosphere acts as an infrared radiation absorber which retains re-radiated infrared

energy in the atmosphere (Wong, 2015). The extra radiation becomes trapped in and beneath

earth’s atmosphere and the cycle repeats as the GHG layer becomes thicker and surface

temperatures increase due to incoming energy that is trapped as heat.

There are several types of GHGs including nitrous oxide (N2O), methane (CH4), water

vapor (H2O), fluorinated gases, and the most well-known carbon dioxide (CO2). The common

characteristic among these abundant GHGs is that they are all polyatomic molecules, this means

that the molecules are comprised of three or more atoms, and each atom may have a different

electronegativity. The unbalanced sharing of electrons on an atomic level is what makes GHG

molecules strong absorbers of infrared energy. Furthermore, each GHG has a different infrared

8

absorption cross-section and impact on the greenhouse gas effect. For instance, agricultural

irrigation systems are a major source of GHG emissions in form of H2O vapor since it evaporates

into the atmosphere, but H2O vapor does not typically cause long term greenhouse gas effects

because, within a span of 10 days, H2O vapor condenses and returns back to liquid water through

precipitation (IPCC, 2013). On the other hand, methane requires approximately 12 years to

become removed from the atmosphere as it is converted into H2O and CO2 vapors through

chemical reactions with hydroxyl (OH) radicals in the atmosphere (Table 1.2). Nitrous oxide

takes over 100 years to disappear (Table 1.2) while fluorinated gases and CO2 can take up to

several tens of thousands of years to become eliminated (Table 1.2). However, the global

warming contribution from fluorinated gases is relatively small compared to the other GHGs

because the atmospheric abundance of fluorinated gas emissions is approximately 3% of total

GHG emissions, whereas CO2 emissions is 82% (Fig. 1.4) (U.S. Environmental Protection

Agency, 2019). One of the reasons why fluorinated gases and CO2 last much longer in the

atmosphere is because there is no dominant process that completely removes these gases from

the atmosphere. Typically, many natural removal processes occur, but do not fully recycle the

gasses even after thousands of years (EPA, 2013).

As an illustration, CO2 from the atmosphere can dissolve into ocean waters to form carbonic acid

within a few centuries, however increased carbonic acid causes ocean acidification (Gill, 2015;

Wong, 2015). Some biomasses and soils can also absorb up to 25 – 30% of CO2 emissions

(Reichstein et al., 2013), however these natural carbon sinks are not enough to keep up within

increasing emissions. Furthermore, land development and extreme weather events caused by

climate change, induce further land alteration and destroys natural carbon sinks which ultimately

causes carbon sinks to release CO2 back into the atmosphere (Reichstein et al., 2013). As a

result, natural carbon sinks are not sufficient to make a large impact on reducing carbon

emissions on short human timescales of decades or centuries.

Since CO2 is the greatest contributor to anthropogenic GHG emissions (Fig 1.4 and Fig

1.5), this research project focuses on the removal of CO2 through the development and analysis

of a carbon capture and storage technology called Alternative Vectors for Carbon Storage

(AVECS), which can potentially remove carbon from the atmosphere and store that carbon in a

stable state in subsurface geologic formations.

9

Figure 1.4 Percentage of major GHG emissions in the U.S in 2017. Percentages do not add

up to 100% due to rounding. (U.S. Environmental Protection Agency, 2019)

Figure 1.5 The main sources of carbon dioxide emissions in the U.S. in 2017. (U.S.

Environmental Protection Agency, 2019)

10

Table 1.2 Anthropogenic greenhouse gas (GHG) emissions and the corresponding average

residence time in the atmosphere. (IPCC, 2007, 2013; EPA, 2013; Crank and Jacoby, 2015).

Greenhouse Gas (GHG) Average Residence Time in

Atmosphere

Water (H2O) Vapor 10 days

Methane (CH4) 11.2 ± 1.3 years

Nitrous Oxides (N2O) 131 ± 10 years

Fluorinated Gases 3,000 to 50,000 years Carbon Dioxide (CO

2) 200 - 100,000 years +

1.7 Carbon Capture and Storage

Carbon Capture and Storage (CCS) is also known as geologic CO2 sequestration and it is

a process that decarbonizes global emissions through net removal of CO2 from the atmosphere by

storing CO2 in deep subsurface reservoirs with impermeable seals. CCS technology, such as the

Shell Quest CCS project, works by capturing gaseous CO2 and then injecting highly compressed

CO2 (often at supercritical state or dense-phase) into deep saline aquifers or other geologic

formations. When CO2 reaches supercritical state at high pressures and temperatures, it displays

characteristics of both gas and liquid. Since supercritical CO2 is denser than CO2 gas, it occupies

less volume and enables more efficient storage into geologic storage complexes (Wong, 2015).

However, supercritical CO2 is more buoyant than brine water in saline aquifers, therefore several

existing natural impermeable seal layers within the storage complex are essential to prevent CO2

from escaping the storage site. This type of CCS mechanism is the most common type CO2

storage mechanism known as structural trapping, and it is estimated to safely store CO2 for

approximately 1000 years (Hauck et al., 2012).

There are other processes which trap CO2, however. Several authors have noted mineral

trapping as a process which may permanently sequester CO2 in the subsurface (Thomson, 2009;

Wong, 2015; Harrison et al., 2019). The mineralization process occurs when dissolved CO2

reacts with surrounding host rock, which then releases metal cations that combine with carbon

and oxygen to form carbonate minerals (Harrison et al., 2019). As a result, CO2 is converted to a

stable solid state. Therefore CO2 mobility and leakage concerns are lessened. However, mineral

precipitation often occurs gradually over long geological timescales and can take up to 10,000

11

years or more, depending on the reactivity of the rocks and the abundance of carbonate-forming

cations within the geologic storage complex, to form carbonate minerals (Harrison et al., 2019).

1.7.1 Carbon Storage in Saline Aquifers

Deep saline aquifers are geological formations comprised of permeable sedimentary rock

saturated with brine. Furthermore, saline aquifers have large storage capacities and CO2

dissolution processes occur in brine which makes saline aquifers favorable for CCS projects

(Emami-Meybodi, 2015; Tawiah et al., 2018). There are several saline aquifers in Canada,

however, not all are suitable for geologic supercritical CO2 sequestration as many geologic

parameters must be met to ensure safe storage (Table 1.3). An example of an acceptable deep

saline aquifer for CCS is the one located in the north-east of Edmonton (Alberta, Canada) known

as the Basal Cambrian Sands (BCS) of the Western Canadian Sedimentary Basin (Tawiah et al.,

2018). Since August 2015, the BCS aquifer has been used for the Quest CCS project (operated

by Shell) and over 4 million tons of CO2 has been stored within the BCS storage complex in a

period of four years (Shell Canada, 2019).

The composition of the BCS aquifer is dominantly sandstone with an average thickness

of 45 m and it is approximately 2000 m beneath the surface (Fig. 1.6). In addition, the total

dissolved solids (TDS) concentration in the BCS storage area is approximately 300,000 mg/L

(Hauck et al., 2012). Typically, aquifer waters with more than 10 000 mg/L of TDS are suitable

for CCS projects, as high TDS levels indicates that the water is unacceptable for use as water

supply and has low economic value (Bruant et al., 2002). Moreover, the BCS deep saline aquifer

is a suitable storage location for CCS is because it has a large CO2 storage area of approximately

450,000 km2, good porosity (17%) and high permeability (1000 mD) sandstones, and several

layers of thick impermeable seals which overlay the BCS injection target unit (Fig. 1.6) (Hauck

et al., 2012; Tawiah et al., 2018). It is estimated that the Quest CCS project will continue to

capture and store CO2 at a rate of 1 million tons per year for the next 25 years within the BCS

aquifer.

12

Figure 1.6 Stratigraphic column showing the Basal Cambrian Sand (BCS) CO2 storage

complex from the Quest CCS project operated by Shell Canada. (Tawiah et al., 2018).

There are many other saline aquifers located within sedimentary basins in Canada (Fig.

1.7) (Natural Resources Canada, 2016). For example, in the Alberta Basin, the salinity of saline

aquifers range from 600 mg/L to 15,000 mg/L (Fig. 1.8). While the depths of saline aquifers in

Alberta range from ≤ 500 m to 3500 m (Nakevska et al., 2017). Although there are other saline

aquifers, many may not be suitable for structural trapping of supercritical CO2 due to reasons

such as shallow storage depths and lack of impermeable seal layers. However, could such saline

aquifers be suitable for storing another form of carbon besides supercritical CO2? This thesis

researches a different route called the Alternative Vectors for Carbon Storage (AVECS) project,

which may allow shallow saline aquifers with high TDS concentrations or other contaminants to

act as possible carbon storage locations for AVECS molecules. In brief, the AVECS molecule is

designed to be water soluble, therefore carbon can be trapped through a mechanism known as

solubility trapping where carbon-rich molecules are dissolved into fluids in the aquifer and the

fluid gradually become denser as more carbon dissolves. The dissolved carbon-rich fluid

eventually sinks to the bottom of the formation. Solubility trapping occurs on a faster timescale

compared to mineral trapping (Gislason et al., 2014), but it is less stable compared to

mineralization as carbon is trapped within fluids rather than in a solid mineral. However,

13

solubility trapping is regarded as a more stable carbon storage mechanism compared to structural

trapping (Gislason et al., 2014; Harrison et al., 2019). Therefore shallow saline aquifers can be

considered for storing AVECS molecules through solubility trapping as there is less concern for

caprock or high-pressure reservoir requirements to maintain supercritical phases. One of the

reasons why the AVECS route is considered is because it may provide more opportunities to

utilize geographically abundant shallow saline aquifers which are unsuitable for supercritical

CO2 storage.

Figure 1.7 (a) Saline aquifers (blue) present in Canada and the U.S. (National Energy

Technology Laboratory, 2007). (b) Location and outline of the Western Canada

Sedimentary Basin (WCSB) which includes the Alberta Basin and Williston Basin. (Singh

et al., 2017).

14

Figure 1.8 Salinity concentration of the hydrostratigraphic unit (HSU) of the Wapiti

Formation - Belly River Group strata in the Alberta Basin. (Alberta Geological Survey,

2019).

1.8 Research Objective

Energy companies are implementing renewable energy technologies to supply the

world’s energy demand, however it will require time to gradually transition from relying heavily

on fossil fuel energy sources to utilizing primarily renewable energy. Therefore, innovative and

inexpensive technologies which can remove carbon emissions from the atmosphere are desired,

as fossil fuels will continue to remain as a main source of global energy for the next few decades.

More importantly, there is no single solution to climate change, but rather a team of solutions is

needed to tackle this massive challenge. The more negative emissions technologies that are

available, the greater the chance of reaching global targets which may prevent catastrophic

damage caused by continuous warming of the earth. Therefore, in this thesis project, a new

potential carbon negative technology (Alternative Vectors for Carbon Storage — AVECS) is

explored and developed.

The AVECS route is inspired by geologic CO2 sequestration and natural sulfurization

processes (discussed in Chapter 2). The AVECS approach (Table 1.4) differs from traditional

15

CCS (Table 1.3) because it aims to reduce carbon capture cost by utilizing inexpensive reactants

such as abundant sulfur resources and carbon-rich biomass waste to form biodegradation

resistant molecules. Furthermore, AVECS molecules will undergo oxidation reactions, in future

work, to increase water solubility to enable solubility trapping in shallow saline aquifers and

reduce concerns for potential leaks which can alter the environment or cause catastrophic

eruptions (Bruant et al., 2002).

16

Table 1.3 Strengths and weaknesses of Carbon Capture and Storage (CCS) technology.

BHT refers to bottom-hole temperature (BHT) and EOR refers to enhanced oil-recovery.

(Gislason et al., 2014; Tawiah et al., 2018; Harrison et al., 2019).

Technology Strengths WeaknessesThe Quest CCS project by Shell

captures 1 million tons of CO2 per

year

Frequent and continuous monitoring

required

Excellent rock volume and storage

capacities in deep saline aquifers

Relatively short time period of storage

(~1000 years) depending on environment

and caprock integrity

Minor pressure buildup in aquifer

system when pressure is monitored

carefully

CCS is affected by non-isothermal

conditions and water vaporization rate (ex.

Increased BHT in the summer decreases

CO2 injectivity rate by 5 - 8%)

CO2 injection rates increases in

the winter as BHT is lower

CO2 - rich fluids may dissolve rocks and

compromise caprock integrity, induce salt

dissolution and precipitation which leads to

porosity and permeability impairment

CO2 injections may also be used

for EOR applications

Carbon capture is typically five times or

more expensive compared to the carbon

storage component

Several different ways of CO2

trapping is possible such as

through solubility, structural and

mineralizaiton trapping.

Potential leakage pathways include

boreholes, fractures and compromised

caprock. Leakage of hazardous trace

minerals, different brine and pH water

compositions may enter overlying

freshwater aquifers.

Requires distinct geological parameters such

as deep saline aquifers (>2 km) with many

natural seals, minimal structural complexity,

and must be far away from wells and fresh

water resources for storage in sedimentary

rock. Difficult to locate deep saline aquifers

that meet such requirements

Capture Capture

and Storage

(CCS)

17

Table 1.4 Strengths and weaknesses of early-stage Alternative Vectors for Carbon Storage

(AVECS) technology. In comparison to established CCS technology, AVECS technology

has potential to reduce costs through utilizing inexpensive reactants and more globally

accessible environments such as shallow saline contaminated aquifers as carbon storage

locations.

1.9 Thesis Summary

With the AVECS research project, atmospheric carbon will be safely stored as

biologically refractory (the material does not biodegrade quickly back to carbon dioxide or

methane) water soluble organic molecules in geologically abundant shallow saline aquifers that

Technology Strengths Weaknesses

OSC will be oxidized to increase

water solubility so OSC would not

escape easily after injection.

Furthermore, injection into shallow

saline or contamined aquifers is

possible as OSC will remain in

solution and will not be buoyant.

More work is needed

to test the

biodegradation

resistance, water

solubility, and mobility

of organic sulfur-

bearing species in

shallow saline

contaminated aquifers

Utilizes biomass waste and sulfur,

which are low value commodities, as

important reactants. Therefore cost

of capture capture will be

decreased.

Shallow saline or contaminated

aquifers are geographically abundant

and more easily accessible

compared to deep saline aquifers

More flexibility with geological

requirements for storage (ex.

caprock may not necessary), which

makes carbon storage more globally

accessible as more aquifer selections

are suitable for storage.

Less aquifer monitoring may be

possible compared to supercritical

CO2 storage in deep saline aquifers

Alternative

Vectors for

Carbon

Storage

(AVECS)

Sulfurization and

oxidation reactions

convert carbon-rich

biomass waste to

organic sulfur

compounds prior to

injection into storage

location. This process

may require more time

compared to CCS.

18

have been contaminated naturally (by petroleum, for example), or through human activity. The

approach to develop such molecules is to convert organic waste material to organic sulfur

compounds (OSC) (by using sulfurization reactions), which are biodegradation resistant. This

thesis (Fig. 1.9) focuses on understanding sulfur incorporation reactions in natural settings

(Chapter 2), molecular analysis of sulfur-rich oils which are comprised of different OSC

(Chapter 3), development of a method for isolating sulfur-rich hydrocarbon fractions (Chapter 4),

identification on how sulfur incorporation and oxidation affects hydrocarbon solubility and

biodegradation rate using chemical modelling software (Chapter 5), laboratory sulfurization

experiments on lipids (Chapter 6) and conclusions and future work (Chapter 7).

Figure 1.9 Diagram indicating thesis chapters which includes an introduction to the

purpose of this research and what the AVECS project is (Chapter 1). Sulfur incorporation

processes in natural settings are explored in Chapter 2. Molecular analysis was conducted

on sulfur-rich oils to reveal the environmental settings which contributed to the oil

generation and the structure of organic sulfur compounds found in the oils were discussed

in Chapter 3. The method development process for isolating sulfur-rich hydrocarbon

fractions is discussed in detail in Chapter 4. Then, Chapter 5 identifies how sulfur

incorporation and oxidation affects hydrocarbon solubility and biodegradation rate using

chemical modelling software. In Chapter 6, laboratory sulfurization experiments were

tested on lipids and carbohydrates (Chapter 6) and conclusions and future work (Chapter

7).

19

1.10 Conclusions

Current carbon sequestration methods are effective, however more tools are needed to

reach global targets to prevent warming beneath 1.5°C. The AVECS project aims to develop a

sustainable and cost-effective carbon storage method which stores atmospheric carbon in the

subsurface — such as geographically abundant shallow saline aquifers. Biodegradation resistant

organic species, found in oils, provide conceptual templates of molecular structures which might

represent AVECS molecules adapted to convert carbon-rich biomass materials into molecules

which are: (1) Resistant to biodegradation and oxidation, and (2) water soluble for injection into

polluted shallow saline aquifers. The approach to chemically modify biomass to form non-

biodegradable carbon-rich molecules is to use reactions involving sulfur, which will be discussed

in following chapters. Additionally, for future work discussed in chapter 7, oxygenated

functional groups and oxidation reactions will be used to improve water solubility of the carbon

molecule. As part of government strategies to alleviate anthropogenic carbon emission effects,

cost effective and globally deployable technologies are needed to permanently remove CO2 from

the atmosphere.

20

Chapter Two: Sulfur Incorporation in Natural Settings

2.1 Introduction

Sulfur is a unique chemical element to study because it is considered both an

environmental contaminant as well as an essential commodity to sustain agriculture life and

industry. Sulfur exists in several forms including: elemental sulfur (S8), organosulfur

compounds, metal sulfides and gasses. It is estimated that the world houses 5 billion metric tons

of elemental sulfur reserves in natural gas, petroleum, oil sands, metal ores and evaporitic and

volcano deposits. As well, an estimate of 600 billion tons of elemental sulfur situates in rocks

rich in organic matter such as coal and oil shale which require extraction methods to produce

(Apodaca, 2019). The estimated worldwide total sulfur recovery (all forms) in 2018 was 80

million metric tons (Mt) (Table 2.1).

Sulfur is not only abundant but also an inexpensive natural resource due to an imbalance

in the sulfur market where sulfur production exceeds demand and consumption. In 2015,

worldwide sulfur consumption was nearly equivalent to sulfur production, however an

undoubted surplus of sulfur is predicted to emerge in the future (Apodaca, 2018). Reasons for a

predicted increase in sulfur production is because sulfur recovery is not governed by sulfur

demand, but rather, a function of demand for fossil fuels and metals (AER, 2018). When low

sulfur content fossil fuel sources become depleted in the future, more refineries will turn to

process high sulfur content crude oils for sulfur recovery to improve fossil fuel quality.

Furthermore, sulfur present in crude oil leads to corrosion on refinery equipment and catalyst

deactivation in chemical reactions needed for refining processes (Demirbas et al., 2015).

Petroleum refineries are required to reduce sulfur content in fossil fuels to meet

international environmental laws by continuously improving the efficiency of sour gas

processing and crude oil refining. Furthermore, developing countries are expected to strive

towards higher environmental standards. Typically this is accomplished through the modified

Claus process, the industry standard, for the majority of worldwide sulfur recovery (Chandra

Srivastava, 2012). In this process, H2S is converted to elemental sulfur and removed through

combustion of sulfur-rich fossil fuels. However, this process leads to sulfur dioxide (SO2)

emission, which is corrosive and hazardous especially when mixed with rain water to form acid

21

rain. Therefore, environmental protection acts are becoming more stringent over time to ensure

hazards caused by SO2 emissions and combustion of sulfur-rich fossil fuels are limited. In

Canada, the maximum amount of sulfur allowed in gasoline was 40 mg/ kg in 2016, now

petroleum refineries are required to produce fossil fuels with less than 12 mg/kg of sulfur by

January 1, 2020 (Government of Canada, 2019). In summary, sulfur production will continue to

rise as fossil fuel demand increases and because of further sulfur content reductions in fossil

fuels by international environmental protection acts to improve air quality. In 2018, over 90% of

sulfur produced was used for producing sulfuric acid, which is then used for mining metal ores

and as fertilizers (Apodaca, 2019). While elemental sulfur is mainly used in petroleum refining

processes and agriculture (Table 2.2). The gap between sulfur supply and demand will continue

widen as sulfur consumption has not been able to meet sulfur production since 2015 and other

uses for elemental sulfur have not increased for many years, hence sulfur stockpiles are

accumulating around the world, such as the ones found in Alberta, Canada (Fig. 2.1) (Apodaca,

2018).

2.1.2 A Solution to Two Problems

To limit global warming from reaching 1.5°C warmer than pre-industrial levels would

require major advancements in innovative technology and rapid shift towards sustainable

development in society. Otherwise, failure for global commitment to meet 1.5°C pathways will,

inevitably, lead to irreversible consequences which cause harm to all life forms on earth (Allen et

al., 2018). The current pathway to progress is to ensure national reductions in GHG emissions,

which will cumulatively contribute to limiting warming, however the present intended

contributions from each nation will not limit warming to 1.5°C. In fact, it is estimated that

current GHG emissions reductions are insufficient, and by 2100 will project towards a global

warming of 3–4°C compared to pre-industrial temperatures (UNFCCC, 2016). Reducing global

emissions attempts to limit or slow global warming, but to lower global surface temperatures

requires net removal of anthropogenic CO2 emissions (Allen et al., 2018).

The AVECS research project targets large scale net negative removal of CO2 and, at the

same time, utilizes elemental sulfur as a key element in sulfurization reactions which will also

alleviate the sulfur surplus problem. AVECS technology is unique in the sense that it approaches

22

CO2 removal with a natural approach by utilizing naturally-occurring and affordable reactants

such as biomass waste and sulfur which are sustainable for long term use due to the large

abundance of such resources.

Table 2.1 World S production and reserves (all sulfur forms) in 2018. Units are in

thousands of metric tons. (Apodaca, 2019).

Figure 2.1 Increasing elemental sulfur stockpiles at Fort McMurray, Alberta, Canada

(AER, 2017).

2018

9,700

900

530

5,500

1,800

17,000

940

890

3,400

2,200

510

3,500

3,500

3,100

850

550

520

1,200

2,100

7,100

6,000

610

3,300

700

3,500

80, 000

Venezuela

Other countries

World Total (Rounded)

Poland

Qatar

Russia

Saudi Arabia

Turkmenistan

United Arab Emirates

Japan

Kazakhstan

Republic of Korea

Kuwait

Mexico

Netherlands

China

Finland

Germany

India

Iran

Italy

Countries

United States

Australia

Brazil

Canada

Chile

23

Table 2.2 Sulfur and sulfuric acid consumption in the United States (Apodaca, 2018). Units

are in thousands of metric tons.

2.1.3 Why Sulfur?

Sulfur exists in a variety of states and species, including minerals in rocks, soluble sulfate

in oceans, gases and in organic matter (Kellogg et al., 1972). Sulfur has an atomic number of 16,

is multivalent and classified under the non-metallic group. Furthermore, sulfur exists as four

stable isotopes 32S (92%), 33S, 34S (4.2%) and 36S. Besides the different isotopes, sulfur also

exists in several oxidation states from –2 (sulfide) to +6 (sulfate) (Table 2.3). These sulfur forms

are known as inorganic sulfur species and the most abundant forms include sulfides (S2-), sulfate

(SO42-), and elemental sulfur (S0) (Bertrand et al., 2015). Elemental sulfur is a unique form of

sulfur as it is inert and water insoluble. Furthermore, it is typically unaffected by moisture,

24

ambient temperatures and microbes. Due to these properties, elemental sulfur is commonly used

as a fungicide and antibacterial agent in agriculture and pharmaceutical practices (Araujo et al.,

2017). Less stable forms of inorganic sulfur include the sulfide ion (S2-), sulfhydryl ion (HS-) and

hydrogen sulfide (H2S) (Bertrand et al., 2015), which are all present in earth’s spheres. In the

atmosphere, H2S transforms into sulfur dioxide (SO2) in the presence of oxygen. H2S is

considered a contaminant in the oil and gas industry, while SO2 is an air pollutant (Kellogg et al.,

1972). About 108 tonnes of gaseous SO2 and sulfur trioxide (SO3) emissions are released into the

atmosphere each year and emanate from burning fossil fuels, emissions from coal-fired plants

and other industrial processes (Gill, 2015). However, government regulations have managed to

reduce sulfur oxide emissions by 64% from 2010 to 2016 (Mos et al., 2019). Oceans house large

amounts of dissolved SO42-

which can escape into the atmosphere as sulfate aerosol particles,

also known as sea spray, when ocean bubbles burst at the water-air interface. (Edwards, 1998;

Jacobson et al., 2000). The lithosphere holds natural reservoirs of sulfur in rocks and sediments

specifically in sulfate minerals such as gypsum (CaSO4·2H2O) and anhydrite (CaSO4). Other

natural abundant sulfur minerals include pyrite (FeS2), cinnabar (HgS) and galena (PbS). In the

biosphere, sulfur species are present in organic matter as sulfur compounds, which form

important building blocks in the structure of protein and amino acids (Bertrand et al., 2015).

Particularly interesting to the AVECS project are organic sulfur compounds (OSC),

which received great focus in the past several decades, particularly in the petroleum industry, as

sulfur compounds are undesirable due to the fact that it causes environmental damage, equipment

corrosion and low quality fuel (Wardencki, 2000). Many research studies are directed at

developing techniques to purify crude oil, natural gas and coal by removing sulfur impurities.

But the benefits of OSC are not overlooked; in crude oils, OSC are known to display resistance

to microbial degradation. As a result, the difference with AVECS technology is sulfurized

organic compounds are formed rather than eliminated and the processes behind OSC formation

underpin this project. AVECS goals are to design and test reactions which simulate natural

sulfurization processes to form biologically refractory, water-soluble organic molecules for

storage in shallow, saline, contaminated aquifers as a potential carbon sequestration method. In

order for AVECS to be feasible and globally accessible, the technology must be reproducible and

25

economically sustainable by using low cost resources. Therefore sulfur is a suitable reactant for

potentially generating AVECS products.

Table 2.3 Sulfur species and corresponding oxidation states. * Thiosulfate has one sulfur

atom that is reduced and the other is oxidized. (Modified after Bertrand et al., 2015)

2.1.3 Geochemical Sulfur Cycle

Sulfur flows from different reservoirs driven by sulfur metabolism and redox reactions

(Bertrand et al., 2015). Whether a mineral or organic sulfur compound is formed is strongly

dependent on the redox state of the environmental conditions, microbial activity, availability of

inorganic sulfur species and organic matter. These factors must harmonize together to form

organic sulfur compounds (Adam et al., 1993). It is hypothesized that organic sulfur compounds

in sediments are formed when sulfides or polysulfides (Sx-2) react with functionalities in aliphatic

and aromatic lipid compounds and become incorporated into the chemical structure (Bertrand et

al., 2015). The sulfur cycle resets when organic sulfur compounds become degraded and release

simpler sulfur compounds and inorganic sulfur forms (Fig. 2.3). There are several other

pathways, discussed in the next section, which naturally produce inorganic sulfur and organic

sulfur compounds.

2.2 Sulfur Incorporation During Early Diagenesis

Wherever there is readily available inorganic sulfur, organic molecules and an active

microbial community, organic sulfur compounds are usually created. In general, when organic

matter decomposes and undergoes diagenesis at shallow depths, aerobic microorganisms

consume available oxygen to catabolize organic matter. When oxygen becomes depleted,

Sulfur Species Chemical Formula Oxidation State

Sulfate SO₄²¯ +VI

Sulfite SO₃²¯ +V

Sulfur Dioxide SO₂ +IV

Thiosulfate * S₂O₃²¯ +II

Elemental Sulfur S° 0

Sulfide S²¯ -II

26

microorganisms seek other compounds to use as an electron acceptor, such as sulfate, for

anaerobic respiration (White, 2013). At the same time, organic sulfur in dead organisms is

mineralized and released into the environment as inorganic sulfur with the aid of aerobic and

anaerobic microorganisms. Released sulfides and other inorganic sulfur forms may experience

assimilatory reduction by organisms or from direct assimilation of sulfide which allows for

reintroduction of sulfur into cellular structures (Bertrand et al., 2015). For instance, sulfur

containing amino acids degrade to form sulfides and polysulfides (Sx2-), which react with

functional groups in aliphatic and aromatic compounds present in organic matter to form more

complex and higher molecular weight organic sulfur compounds (Bertrand et al., 2015).

2.2.1 Assimilatory Sulfate Reduction

Sulfate reduction is a process that most often occurs in anoxic zones in sediments (Fig.

2.2), at depths where molecular oxygen is depleted and where sediment surfaces are occupied

with organic matter supply (Sass and Cypionka, 2007). Anaerobic microorganisms, such as

bacterium Desulfovibrio, thrive under anoxic conditions by using sulfate in place of oxygen for

respiration (Schiff, 2008). Sulfate becomes reduced during anaerobic respiration and is utilized

to oxidize other substrates; this process releases H2S and provides energy for sulfate reducers.

Whereas, assimilatory sulfate reduction is a process used by plants and prokaryotes to

form organic compounds such as proteins, carbohydrates, steroids and phenols by assimilating

inorganic sulfur compounds to use as building blocks for cell components (Bertrand et al., 2015).

Some organisms reduce sulfate with oxidation state (+6) to sulfide (-2) (Fig. 2.3), while other

organisms reduce sulfate to thiols to generate enzymes and sulfur-containing amino acids.

Assimilatory sulfate reduction is one of the main pathways for sulfur incorporation into organic

matter. Furthermore, when organic matter decomposes, sulfurized organic compounds mineralize

and release inorganic sulfur (sulfides). This process is also known as mineralization. Afterwards,

the sulfur cycle continues with dissimilatory sulfide oxidation (Fike et al., 2015).

27

Figure 2.2 Biogeochemical systems in marine sediment. Sulfate-reducing bacteria thrive in

the presence of organic matter and anoxic conditions (Goldhaber, 2005).

2.2.2 Dissimilatory Sulfide Oxidization

In sulfide oxidation, a variety of sulfur oxidizing bacteria (SOB) are involved in the

transformation of reduced sulfur compounds to sulfate as inorganic compounds are used by SOB

to obtain carbon and hydrogen sources (Kleinjan et al., 2003). Certain species of SOB, such as

purple and green phototrophic bacteria, are only capable of executing one intermediate step in

the oxidation sequence: sulfide, elemental sulfur, thiosulfate, tetrathionate, sulfite and lastly

sulfate (Fig. 2.3) (Bertrand et al., 2015). Phototrophic sulfur bacteria use solar energy during

photosynthesis and reduced sulfur compounds as electron donors as a form of carbon fixation

which, in turn, oxidizes sulfide to sulfur. Interestingly, elemental sulfur produced by certain SOB

species is stored as sulfur globules in the interior and exterior of the bacteria cell membrane

(Kleinjan et al., 2003).

28

2.2.3 Dissimilatory Sulfate Reduction

This type of energy, growth and respiratory mechanism occurs most often in reduced and

anoxic marine sediment environments and used mostly by archaea and prokaryotic sulfate-

reducers (Fig. 2.3). During this process, elemental sulfur and oxidized sulfur forms such as

sulfate (SO42-), sulfite (SO3

2-) and thiosulfate (S2O32-) are reduced to sulfides (S2-) through

oxidation of an electron donor by microorganisms (Canfield et al., 2005). Simply, this energy

generating mechanism respires sulfate, the electron acceptor, and emits H2S, similar to how

aerobes respire oxygen and release carbon dioxide to generate energy. This mechanism is

utilized when aerobic respiration is not possible, but anaerobic microorganisms in marine

sediment typically favor the following electron acceptors in the order: nitrate, manganese oxides,

iron oxides and lastly sulfates (Fig 2.2). Although sulfate is the least favorable terminal electron

acceptor, it is 50 times higher in concentration compared to the other electron acceptors.

Therefore, making dissimilatory sulfate reduction a dominant anaerobic respiration process

(Goldhaber, 2005). Another factor that influences sulfate reducing activity is the amount and

quality of food available. For example, certain species of sulfate reducers can only metabolize

low molecular weight organic compounds, such as alcohols, dicarboxylic acids, amino acids,

fatty acids (up to C20) and sugars which have undergone precursor fermentation metabolic

processes by other organisms (Bertrand et al., 2015). Some sulfate-reducing strains are able to

metabolize aliphatic and aromatic hydrocarbons in subsurface reservoirs, which cause H2S

accumulation or souring in oil reservoirs thus corrosion and reservoir plugging (Gieg et al.,

2011). To summarize, sulfate reducers have generated many different metabolic pathways to

metabolize inorganic and organic compounds to ensure survival in diverse environments

(Bertrand et al., 2015).

29

Figure 2.3 The sulfur cycle pathways. In numerical order, pathways 1 to 4 refer to

assimilatory sulfate reduction, mineralization (sulfhydrization), dissimilatory sulfate-

reduction and dissimilatory sulfide oxidation (Bertrand et al., 2015).

2.2.4 Other Mechanisms

In some environments, inorganic sulfur species are used as both an electron donor and

acceptor (Fig. 2.4) where sulfides form from reduction of the electron acceptor and sulfates form

from the oxidation of the electron donor (Bertrand et al., 2015). This mechanism, where a

compound with an intermediate oxidation state like elemental sulfur, allows conversion to other

compounds with higher and lower oxidation states (Bertrand et al., 2015). As a result,

microorganisms which cannot use sulfate as an electron acceptor may use elemental sulfur

instead to produce reduced sulfur compounds (Bertrand et al., 2015). There are a variety of sulfur

reducing species which exist in many settings, many of which are abundant in geothermal

environments, areas rich in elemental sulfur, marine or brackish waters and areas where

phototrophic green bacteria thrive. Sulfur is often used as the final electron acceptor during

oxidation of cellular materials in the dark. However, there are also thiosulfate reducers which

specialize in utilizing thiosulfate as an electron acceptor. Sulfides trapped in sediment can react

30

with ferrous iron to form iron sulfide (FeS), pyrite (FeS2) and elemental sulfur in anoxic

environments (Bertrand et al., 2015).

Figure 2.4 Sulfur metabolism pathways. Assimilatory sulfate reduction (blue). Sulfur

oxidation (green). Elemental sulfur disproportionation (purple) (Fike et al., 2015).

2.2.5 Sulfur Oxidizing and Reducing Microorganisms

Anoxic phototrophic bacteria (Table 2.4) use reduced compounds to obtain electrons in

the presence of light during photosynthesis. Electron donors for this type of bacteria are

hydrogen sulfide, reduced sulfur compounds, and other organic compounds of low molecular

weight or degraded organic material from anaerobic respiration (Bertrand et al., 2015). There are

two groups of anoxic phototrophic bacteria: sulfur and non-sulfur bacteria. Sulfur bacteria use

reduced sulfur compounds as electron donors which, after oxidation and photosynthesis, form

elemental sulfur and sulfate. On the other hand, non-sulfur bacteria utilize photo-oxidized

organic compounds. In particular, anoxic bacteria can be distinguished by 2 colors, purple and

green, as the colors indicate the intracellular pigments within the organisms

(bacteriochlorophylls and carotenoids). Purple sulfur bacteria typically form above green sulfur

bacteria as they require more light and have lower sulfide tolerance (Casamayor et al., 2001).

31

Table 2.4 Four lineages of anoxic phototrophic bacteria.

2.3 Sulfur in the Environment

The sulfur cycle closely resembles the carbon cycle as carbon storage compartments are

often also sulfur reservoirs. Other than a smaller reservoir size, sulfur moves between different

reservoirs on earth similarly to carbon (Fig. 2.5). Furthermore, sulfur fluxes occur in the form of

reduced sulfur compounds and oxidized sulfur compounds where concentrations are dependent

on the environment and ecosystem (Bertrand et al., 2015). The sulfur cycle is maintained by a

balance, known as sulfuretum, which means the amount of sulfide oxidized is relatively equal to

the amount of sulfate reduced (Kleinjan et al., 2003). For example, sulfate reducers degrade

organic matter and produce reduced compounds. The concentration of reduced sulfur compounds

vary in different environments, which, in turn, affect oxidation pathways and dominance of

certain microorganisms which oxidize reduced sulfur compounds.

Figure 2.5 Sulfur cycle, sulfur reservoirs and different sulfur flux pathways. DMS refers to

dimethyl sulfide and COS refers to carbon oxysulfide (Bertrand et al., 2015).

32

2.3.1 Sulfur Sinks

Environments and ecosystems which contribute to the functioning of the sulfur cycle are

explored in this section (Bertrand et al., 2015). In the biogeochemical sulfur cycle, there are

three main sinks where sulfur accumulates. First is sulfate minerals such as gypsum (CaSO4 ●

2H2O), which form in evaporitic environments that have increased metal, oxygen and sulfate

concentration (Fenchel et al., 2012). Weathering of sulfur-rich calcareous rocks releases sulfides

and sulfates into the surrounding environment (Edwards, 1998). Second is in ferrous sulfide

minerals which occur when H2S reacts with iron to form pyrite (FeS2), other iron sulfide

minerals or metal sulfide ores. On the other hand, the generation of organic sulfur compounds is

strongly dependent on the presence or absence of reactive iron or other metal minerals. For

example, the process of converting iron oxides to iron sulfides occurs more quickly than the

reaction between organic matter and reduced sulfur species. Which means that organic sulfur

compounds are unlikely to form in an environment with reactive metals because sulfur species

tend to be consumed quickly (Fenchel et al., 2012).

Lastly, sulfur compounds are found in biomass, sediments and oils (Kohnen, 1991).

Atmospheric sulfur dioxide and inorganic sulfur in soils are often absorbed by plants and

organisms for growth. Particularly in freshwater and wetland areas, there is lack of dissimilatory

sulfate reduction activity. Therefore sulfides formed from sulfur mineralization can be

incorporated into plant biomass to form organic sulfur compounds that make up structural

elements (Fenchel et al., 2012). When organic matter becomes metabolized and decomposed by

microorganisms, some organic and inorganic sulfur forms are released back into the environment

while others undergo diagenesis and catagenesis to form sulfur-rich oils. Sulfur regains access to

the atmosphere when fossil fuels are combusted (Edwards, 1998). In summary, organic sulfur

compounds mostly form in environments where there is low metal concentration, high microbial

activity and accumulation of reduced and oxidized sulfur forms (Kohnen, 1991). Examples of

environments which require sulfur cycling processes to sustain life are discussed below.

33

2.3.2 Stratified Lacustrine Waters

Lakes can be separated into layers or stratified through density, temperature, salinity and

water chemistry (Bertrand et al., 2015). During the summer, solar radiation warms the lake

surface and creates a temperature gradient from the warm lake surface to the cold lake floor. This

type of stratification is known as a thermocline and it separates the upper warm commonly, oxic

layer (epilimnion) from the colder, dense and anoxic water layer below (hypolimnion) (Fig. 2.6).

Due to the density of the hypolimnion, it rarely mixes with the epilimnion, however this layer

still receives organic matter from microorganisms living in the epilimnion above. Anoxic

phototrophic bacteria (red, green, and brown), typically develop in the upper part of the

hypolimnion where there is sufficient light energy and sulfides (Casamayor et al., 2001).

However, for deep lakes, green sulfur phototrophic bacteria thrive in the hypolimnion because

this type of bacteria contain abundant carotenoids and bacteriochlorophyll pigments, which are

effective at capturing long wavelengths of light beyond the usual visible spectrum. Furthermore,

green sulfur bacteria have higher pigment content as an adaptation in response to light limitation

(Casamayor et al., 2001).

The stratification intensity within a lake impacts the sulfur reduction-oxidation rate.

Lakes with increased sulfur cycling have features such as a permanent chemocline or temporary

oxic-anoxic interface, sulfate availability and organic matter supply. Sulfate enters the water

system through weathering of rock minerals, organic sulfur compounds, and leakage of

wastewater and acid mine drainage. Typically, sulfate concentration in fresh water lakes range

from 10 - 500 μM, however mesotrophic and eutrophic lakes have higher sulfate concentrations

ranging from 700 -800 μM. High sulfate concentrations in water promote optimal conditions for

sulfur reducing bacteria which further induces the productivity of sulfur oxidizing prokaryotes

that live in the warm oxygenated waters above, and are responsible for reoxidizing sulfides that

escape from the anoxic community below thus producing sulfate for sulfate-reducers. On the

contrary, acidic lakes often lack sulfur reduction processes as sulfate concentration is low and

microbial activity is diminished. As a result of stratification in lakes, active gradients of sulfides

and sulfates are created by sulfur reducing and oxidizing communities which flourish in non-

acidic waters with high sulfate and organic matter availability (Bertrand et al., 2015).

34

Figure 2.6 Organic matter sinks below the anoxic boundary and activates sulfate reduction

pathways in fresh water lakes (modified after Fenchel et al., 2012).

2.3.3 Marine, Lagoonal and Coastal Environments

Most organic matter in fresh and marine waters become consumed and remineralized by

microorganisms. However under certain environmental conditions, a small percentage escapes

mineralization and becomes buried and preserved in sediment (Raven et al., 2016). One

favorable setting which generates biodegradation resistant sulfur-rich organic matter is at coastal

environments. Fresh water from run off, precipitation and rivers intermix with marine water at

coastal environments such as lagoons and estuaries. Run off water is typically rich in organic

matter due to nutrients and effluent coming from agriculture, industries and municipalities.

Organic matter in these waters becomes remineralized by aerobic microorganisms, which also

encourages anoxic conditions in deeper waters. Similarly, when marine and freshwater mix in

coastal environments, sulfate from marine waters supports sulfate reducing activity and sulfide

production in sediments and surface waters. The most productive area for sulfate reducing

activity is in shallow sediments and the interface between water and sediment because abundant

organic compound input and sulfate is available for sulfur oxidizing microorganisms to develop.

In summary, the activity of sulfur oxidizing and sulfate reducing communities depend on

gradients of sulfide in stratified water columns, light intensity and dioxygen concentrations.

Occasionally in warm weather, the anoxic zone dominates the majority of the water column and

can even move the anoxic and oxic interface up to where air meets water. In this scenario, sulfide

35

accumulates due to increased sulfate reduction activity. Certain species of purple sulfur bacteria

thrive in environments with high sulfide concentration and can also store elemental sulfur within

their cellular composition. In situations where there is limited light or oxygen, these bacteria

utilize stored sulfur forms as an electron acceptor during organic matter degradation (Bertrand et

al., 2015).

2.3.4 Hydrothermal Vents

Oceanic hydrothermal vents are often located in the same areas as mid ocean ridges

where there is a divergent boundary between two tectonic plates on the deep sea floor. In this

setting, cold seawater entering earth’s crust becomes exposed to high temperatures and becomes

enriched in metal ions. Then heated fluids resurface from hydrothermal vents, which are rich in

reduced sulfur and ionic compounds, and mixes with cold oxygenated ocean waters. Many

microorganisms that grow in these environments use the fluids as energy resources. Moreover,

symbiotic relationships occur between marine animals that live around hydrothermal vents and

sulfur-oxidizing bacteria. The symbiotic activity involves animals providing substrates for sulfur

bacteria and these bacteria, in return, supply metabolized organic matter for dietary needs of

marine animals (Bertrand et al., 2015).

2.4 Generation of Sulfur-Rich Crude Oils

Crude oils are complex and contain thousands of compounds which change depending on

the source rock, thermal maturity, and degree of biodegradation of the oil. However, all

petroleum forms are mainly comprised of carbon, hydrogen and heteroatoms (Han et al., 2018).

Within the heteroatom class, sulfur is the most abundant element in petroleum because it

accounts for 0.03 to 14.0 wt% of the entire petroleum content (Sinninghe Damsté et al., 1987;

Han et al., 2018). The average sulfur content for most crude oils is 0.65% (Sinninghe Damsté

and Orr, 1990). Typically, the lower the sulfur content, the sweeter the crude oil is described as,

which is defined as a higher quality oil that requires less processing to remove unwanted sulfur

compounds (Han et al., 2018a). According to Han et al. (2018), crude oil is considered sweet if it

has less than 0.42 wt% of sulfur. Crude oils with high sulfur content are generally derived from

carbonate or evaporitic rock formations while low sulfur content oils originate from clastic

36

sedimentary environments (Orr and Sinninghe Damsté, 1990). Sulfur exists in oils as four main

compound classes: thiols, sulfides, disulfides, and thiophenes (Lobodin et al., 2015). These sulfur

compound classes comprise mixtures of organically bound S compounds that vary from low to

high molecular weight. There is a range of possibilities for what sulfur compound structures

form in oils and that is dependent on the source of the oil as well as environmental settings

(temperature, maturity and degree of biodegradation). In this section, the variables which affect

sulfur content and molecular type in oils and formation of organic sulfur compounds in

petroleum from sulfur incorporation processes with organic matter are explored.

The first factor is the sulfur content of the kerogen source. Kerogen is the precursor of oil

and it is derived from primary production organic matter which has been exposed to diagenesis

in aquatic depositional environments, where biochemicals are converted to complex polymeric

species in the kerogen which is then altered through catagenesis during deep burial, to produce

oil (Orr and Sinninghe Damsté, 1990). Inorganic sulfur species such as H2S and polysulfides

have a tendency to react with certain functional groups and precursor organic molecules to form

sulfur-rich kerogen during early diagenesis (Aizenshtat et al., 1995). In particular, biomolecules

with double bond functionalities, such as lipids and carbohydrates are favored. A secondary

influence on sulfur compound composition in petroleum is thermal maturity. As thermal maturity

increases, more non-sulfur compounds form which dilute the concentration of sulfur compounds

(Adam et al., 1993). Therefore, sulfur content is typically highest in early mature oils when

source rock generation temperatures are low and have yet to degrade weak carbon-sulfur and

sulfur-sulfur bonds within sulfur-rich kerogen and high molecular weight components in crude

oils such as resins and asphaltenes (Orr and Sinninghe Damsté, 1990). It is important to identify

the processes and chemical groups which trigger sulfurization reactions in organic matter to

further understand how to utilize sulfurization reactions and organic compounds as a mechanism

for carbon storage. By understanding how sulfur is incorporated into biodegradation resistant

crude oil molecules, this may provide routes to facilitate the production of sulfur-containing

biologically refractory molecules suitable as AVECS species.

37

Table 2.5 Examples of reactive and non-reactive sulfur compound classes in petroleum

(Lobodin et al., 2015b).

Reactive Non- reactive

Thiols Sulfides Polysulfides Aromatics

1-dodecanethiol thiolane dihexyl disulfide 1-benzothiophene

1-hexadecanethiol dibutyl sulfide dibenzyl disulfide dibenzothiophene

1-octadecanethiol ethyl phenyl sulfide 1,2-benzodiphenylene

dibenzyl sulfide diphenyl sulfide

benzyl phenyl sulfide

Figure 2.7 Four main sulfur compound classes found in petroleum (modified after Han et

al., 2018)

Out of the main sulfur compounds present in crude oil (Table 2.5; Fig. 2.7), mercaptans or thiols

make a small fraction of total sulfur content in oils. Mercaptans often form volatile sulfur

compounds which are converted to toxic H2S upon burial and heating. Processing oil converts

mercaptans to disulfides to meet crude oil specifications. Besides these sulfur compounds, H2S,

elemental sulfur, sulfones, sulfoxides can be found in bitumen and heavy oil fractions. In

particular, sulfones and sulfoxides form through oxidation processes in shallow reservoirs (Han

et al., 2018a).

2.4.1 Organic Sulfur Compounds

It is hypothesized that organic sulfur compounds form from the interaction between

organic matter and reactive sulfur compounds (Aizenshtat et al., 1995). However, organic matter

with varieties of double bond functionalities has increased chances of sulfur incorporation into

its molecular structure (Adam et al., 1993). From analyzing biomarkers and characterizing sulfur

species in petroleum on a molecular level, it is fascinating to observe that a small volume of

crude oil can reveal geological history as to how the oil formed and the organic matter it was

38

formed from. It is believed that double bond functionalities play an important role in forming

organic sulfur compounds because many sulfur-rich oils are comprised of biomarkers which

indicate precursors were comprised of organic molecules such as isoprenoids, carotenoids,

steranes and hopanes which all contain double bond functionalities (Adam et al., 1993). These

molecules are commonly found in carbohydrates and lipids of living organisms. In Chapter 3,

sulfur incorporation mechanisms into organic matter are discussed in further detail based on

double bond equivalents, carbon and heteroatom class distributions of compounds found in the

oils and biomarker data obtained from molecular analysis of sulfur-rich oils.

2.4.2 Sulfurized Lipids

H2S and polysulfides are common in the biosphere because they form structural elements

in protein and provide unique functions in amino acids. For instance, disulfide linkages form

readily and are commonly seen in amino acids such as cysteine and homocysteine. Besides

amino acids, several studies have identified organic sulfur compounds in crude oil and sediment

which formed from carbon skeletons such as isoprenoids and hopanoids, which are components

found in lipids (Table 2.6). The origin of these sulfur structures are believed to result from H2S

and polysulfide incorporation into functionalized lipids which then undergo cyclisation to form

organic sulfur compounds (Kohnen, 1991). Furthermore, sulfur as dioctadecyl disulfide was

discovered in sediment which consisted of remains of a species of marine coral after anaerobic

degradation (Ciereszko and Youngblood, 1971). Research studies have attempted to understand

the earth’s paleoenvironment by analyzing sediments and oils which contain microfossils and

chemical fossils, known as biomarkers, which are organic compounds with structural

information that can indicate the depositional environment, source rock, thermal maturity and

degree of oil biodegradation. In the research by Sinninghe Damsté et al. (1989), sulfurized lipids

were discovered to be useful biomarkers for indicating organic matter source, microbial activity

and overall biogeochemical sulfur cycle (Kohnen, 1991). In Chapter 3, FTICR-MS analysis on

sulfur-rich oils was used to indicate that lipid structures such as carotenoids, squalene and

steroids are susceptible to sulfur incorporation.

39

Table 2.6 Sulfur-containing functional groups and corresponding carbon skeletons which

form organic sulfur compounds identified in nature (modified from Sinninghe Damsté and

De Leeuw, (1990).

2.4.3 Sulfurized Carbohydrates

Carbohydrates also provide living organisms with carbon and energy as it is an essential

building block for plant tissues, biomass and ocean dissolved organic matter (Van Dongen,

2003). Since carbohydrates are used by many living organisms in different ways, it is thought to

undergo remineralization or breakdown quickly during early diagenesis and is rarely preserved in

the sedimentary record. However, a small percentage of organic matter (0.1 – 1.0%) escapes the

remineralization process and forms organic carbon found in sedimentary organic matter, fossil

fuels and other petroleum products, after diagenetic and catagenesis processes (Van Dongen,

2003). Research studies suggest carbohydrates may be preserved through sulfurization processes

that are driven by environmental conditions that are anoxic, sulfate reducing, and have low iron

concentrations (Van Dongen, 2003). To verify these conditions, laboratory sulfurization

experiments by Sinninghe Damsté et al. (1998) showed sulfurized carbohydrate-rich algal cell

material formed alkylthiophenes after pyrolysis which closely resembled alkylthiophene

distributions found in kerogen. This indicates that sulfurized carbohydrates are mostly likely the

precursor of the dominant alkylthiophenes with C5-7 carbon skeletons identified in the pyrolysate

kerogen because the sulfurized carbohydrates were also composed of C5-7 linear alkanes. The

40

sulfurized carbohydrate compounds likely formed from monosaccharides, the simplest form of

carbohydrate, when reduced sulfur species preferentially incorporated into functional groups

such as aldehydes, ketones and double bonds (Schouten et al., 1993b).

Figure 2.8 Examples of polycyclic aromatic sulfur heterocycles (PASH). Image from Nocun

and Andersson (2012).

2.5 Microbial Recalcitrance of Sulfur Compounds

As organic matter decomposes to smaller particles, it sinks down the water column where

less oxygen is available for microbial degradation (Raven et al., 2016). Then organic molecules

undergo polymerization reactions to form complex and stable kerogen material. Furthermore,

functional groups within organic molecules interact with polysulfides and undergo condensation

reactions to form sulfur-rich organic matter that is refractory to biodegradation (Raven, 2016).

Sulfurized organic matter is commonly discovered at shallow depths, indicating that the

sulfurization process occurs during early diagenesis. This rapid process of sulfur incorporation

into organic matter protects labile organic material from microbial degradation, enhances overall

stability and recalcitrance of organic matter during burial (Raven, 2016; Pohlabeln et al., 2017).

Organic sulfur compounds in sediment are differentiated into two broad groups: ester

sulfate (C-O-S) and carbon-sulfur (C-S) bonds (Tabatabai, 2005). Ester sulfates mostly originate

from microbial biomass and are typically mineralized faster compared to carbon-sulfur bonds as

plants and microbes can hydrolyze ester sulfates easily for absorption. Some examples of ester

sulfates include sulfated polysaccharides and sulfated lipids. Sulfur-containing amino acids are

41

examples of C-S bonded compounds, which are derived from dead plant roots, and are more

recalcitrant and difficult to break down for plants and microorganisms (Edwards, 1998).

However, a particular group of organic sulfur compounds found in crude oil, called polycyclic

aromatic sulfur heterocycles (PASH) (Fig. 2.8), are known to be the more recalcitrant compared

to the organic sulfur compounds mentioned above. PASH are rarely affected by high levels of

biodegradation as most microorganisms are unable to metabolize and break down such complex

and high molecular weight compounds in aerobic environments (Gogoi and Bezbaruah, 2002).

Previous studies have discovered various aerobic soil bacteria which are capable of

degrading smaller PASH, such as benzothiophenes and dibenzothiophenes, in a yeast or glucose

medium (Sinninghe Damsté and Orr, 1990; Gogoi and Bezbaruah, 2002). There are three

mechanisms summarized by Gogoi and Bezbaruah (2002) for degrading PASH with aerobic

microorganisms. The first microbial degradation method occurs when sulfur compound rings are

partially oxidized and altered by soil bacteria to form water soluble segments. However, the

sulfur heteroatom remains unaffected within the structure. The second degradation pathway

utilizes Gram-positive bacteria, such as Rhodococcus strains, which specifically target the

cleavage of carbon-sulfur bonds and utilizes sulfur for growth. Eventually, the sulfur is

incorporated into biomass or is released into the environment as sulfate. This pathway allows

sulfur atoms to be removed from a molecule without removing carbon at the same time (Fig.

2.9a). Therefore, a greater caloric value is retained during fuel combustion which is crucial to

maintain in the oil and gas industry (Gogoi and Bezbaruah, 2002). The third pathway occurs

when Brevibacterium species completely remineralizes an organic sulfur compound into smaller

constituents such as sulfite ions, CO2 and water (Fig. 2.9b). There are limited reports on

anaerobic degradation of sulfur compounds because only a few species of sulfate reducing

bacteria are able to degrade smaller sulfur compounds such as benzothiophenes by utilizing

sulfur as a primary source and electron acceptor at warm temperatures (30–60 °C), however the

conversion rate is low (Gogoi and Bezbaruah, 2002).

42

Figure 2.9 (a) Second degradation pathway for dibenzothiophene (DBT), which targets

carbon-sulfur bonds and preserves carbon-carbon bonds. DszA , DszB, DszC refers to

different proteins in organism Rhodococcus erythropolis. (b) Third degradation pathway by

Brevibacterium species which completely mineralizes DBT. (Modified from Gogoi and

Bezbaruah, 2002).

2.5.1 AVECS Molecule

Processes incorporating sulfur into organic matter occur rapidly under favorable

environmental conditions and can enhance chemical stability and biodegradation recalcitrance of

organic compounds during burial. The potential for utilizing sulfurization processes as a carbon

sequestration mechanism for storing carbon-rich organic compounds from biomass waste into

shallow depths such as contaminated saline aquifers will be evaluated in this thesis. In order to

identify suitable AVECS molecules or refractory sulfur compounds, it is essential to further

investigate how organic sulfur compounds are generated naturally in the environment. The next

chapter explores sulfur compounds found in sulfur-rich oils and the conditions which encourage

43

sulfurization of organic matter. The conditions and reactants required to initiate sulfurization

processes will be simulated in laboratory sulfurization experiments in Chapter 6.

44

Chapter Three: Molecular Analysis of Sulfur-rich Oils and Sulfurization in Natural

Settings

3.1 Introduction

The AVECS approach to limit increasing atmospheric CO2 concentrations, as introduced

in Chapter 1, is to modify carbon-rich biomass through sulfurization reactions to form a soluble

and inert molecule which will be stored within the pores of shallow and contaminated saline

aquifers. Sulfur is regarded as a natural preservative as it makes organic matter less susceptible

to biodegradation (Raven, 2016), therefore making the sulfurization process an important factor

influencing the diagenetic pathways of organic matter (Lu et al., 2013b). Organic sulfur

compounds form through natural sulfurization processes such as assimilatory sulfate reduction

and dissimilatory sulfate reduction, which occur in organic-rich environments that are depleted

in oxygen (Amrani, 2014; Bertrand et al., 2015). The goal of this chapter is to determine the lab

conditions that facilitate sulfurization and investigate the chemical and structural composition of

sulfurized organic compounds from sulfur-rich oils collected from Alberta, China and United

States using two analytical methods: gas chromatography-mass spectrometry (GC-MS) and

Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS).

In the past, many studies were carried out to understand when and how sulfurized organic

matter forms (Sinninghe Damsté et al., 1987; Sinninghe Damsté and Orr, 1990; Sinninghe

Damsté and De Leeuw, 1990; Richnow et al., 1993). However, most studies were conducted

over two decades ago and, since then, GC-MS and FTICR-MS technology has improved to

enhance accuracy and resolution for molecular analysis of oil. Mass spectrometers are a power

analytical tool that is used for analysis and identification of chemical compounds. Many

technological advancements have been made to mass spectrometers since the 1990s (Rabanaque

Berdié et al., 2012) including improved separation to reduce peak overlap and co-elution of

compounds with similar boiling points (Han et al., 2018b). The impactful research studies

conducted on the geochemistry of sulfur compounds in fossil fuels from the 1980s to early 2000s

utilized the GC-MS to attempt to elucidate the structure of organic sulfur compounds (Orr and

White, 1990). It was a difficult task to identify the structure of sulfur compounds solely based on

the mass spectra. Typically, a pure standard or access to reference sulfur compounds stored in

the National Institute of Standards and Technology (NIST) is required to assist in compound and

45

structural identification in spectra. However, both support tools were not as widely established

as present day. Even in modern day, if one does not know what to expect in the spectra, it can

still be challenging to identify what standards are needed to assist in compound identification.

Therefore, the GC-MS may not be the best analytical tool to use for determining the structure of

novel sulfur compounds without reference spectra. The full scan mode, in which qualitative

identification of the sample is detected as a wider mass range is selected (m/z = 50 – 400) to

identify unknown or novel compounds. However, this mode often decreases the detection

sensitivity because the detector spends less time monitoring specific ions of interest. Therefore,

novel compounds with low abundance may become overshadowed as the entire spectra is often

normalized to the peak with highest intensity (Rabanaque Berdié et al., 2012).

Furthermore, complex macromolecules like PASH are often not be detected by the GC-

MS because GC-MS analyses are most suitable for analyzing low molecular weight hydrocarbon

compounds (Lu et al., 2013a). Therefore, in this chapter, the GC-MS is used to identify and

quantify prominent biomarkers to delineate environmental deposition and source rock properties

of sulfur-rich oils. The FTICR-MS is used alongside to identify the carbon number distribution,

double bond equivalents (DBE) and number of sulfur heteroatoms in organic sulfur compounds

present in sulfur-rich oils. Recent studies (Lu et al., 2013a, 2014; Liu and Kujawinski, 2015)

utilize the FTICR-MS as a tool to distinguish the elemental composition of sulfur oils. This

chapter focuses on combining FTICR-MS data with GC-MS data to further understand the

relationship between OSC abundance, formation and depositional environments and organic

matter source.

In this chapter, sulfur-rich oils from Peace River oil sands (Alberta), Jianghan Basin

(China) and Rozel Point (United States) were analyzed with the GC-MS and FTICR-MS to

determine depositional environmental conditions that provoke sulfur incorporation processes into

organic matter, the organic structures that are prone to sulfurization, and the types of OSC

structures discovered in sulfur-rich oils. Although the oils were collected from different

countries, the results show commonality in terms of chemical properties and environmental

influences. Biomarkers indicate that the oils underwent similar environmental conditions and

these settings were the main contributions to forming high sulfur content oils.

46

3.2 Sulfur Incorporation Mechanisms

During early diagenesis, H2S and polysulfides enter a carbon framework through

intramolecular incorporation and form thiolanes, 1,2-dithianes and thiophenes (Kohnen et al.,

1991; Schaeffer et al., 2006). Sinninghe Damsté et al.(1989) hypothesized that thiophenes are

diagenetic products of thiolanes because thiophenes have higher stability compared to the other

sulfur compounds. Likewise, thiane compounds are less stable in nature and are possibly

intermediates in thiolane formation.

Thiolanes form when H2S (HS-) incorporates directly into functional groups or between

two double bond followed by cyclization and carbon skeletal rearrangement (Fig. 3.1) (Kohnen

et al., 1991). Lipid molecules such as squalene, steroids and hopanoids are chemical structures

with several functional groups and are often discovered as sulfurized compounds in oils. Under

diagenetic conditions, thiolanes transform into thiophenes (Fig. 3.2). The formation of thiolanes

and thiophenes, as discussed above, are a form of intramolecular sulfur incorporation. However

Adam et al. (1993) proposed that intermolecular sulfur addition and linkages are the most

favorable process to form sulfur compounds (Fig. 3.1). In contrast, the data and results from this

chapter suggest OSC formation is predominantly through intramolecular sulfur incorporation.

Several studies (Kohnen et al., 1991; Hofmann et al., 1992; Pohlabeln et al., 2017) propose OSC

formation through intermolecular sulfur incorporation into low molecular weight functionalized

molecules to form sulfur-rich macromolecules. The reason for this proposal is because sulfur

fractions were analyzed with the GC-MS by utilizing Raney Ni and MeLi/MeI treatment which

cleaves sulfide linkages and degrades sulfur compounds to meet molecular weight detection

limits (50 – 500 Da) of the GC-MS. Therefore, it was believed that biomarker hydrocarbon

classes such as isoprenoids, hopanoids and steroids are connected by sulfur linkages to form a

sulfur-rich geomacromolecule (Kohnen et al.,1991). The development of the FTICR-MS enabled

this study to analyze whole sulfur-rich fractions without additional derivatization or

desulfurization techniques as the FTICR-MS has high molecular weight detection limits (150 –

60 000 Da) and can detect heteroatoms like sulfur and double bond equivalents (Han et al.,

2018b). For these reasons, a more accurate representation of OSC structure is presented with the

use of the FTICR-MS as the structural pattern of sulfur compounds is not altered. The main

disadvantage with using FTICR-MS, in this study, is it does not show sulfur compound isomers

47

nor the position of sulfur atoms within the chemical structure.

Figure 3.1 The transformation from phytane carbon skeleton to cyclic organic sulfur

compounds during diagenesis through two pathways: intramolecular sulfur incorporation

and intermolecular sulfur addition reactions. (Kohnen et al. 1991)

Figure 3.2 a) Sulfur compounds form through intramolecular incorporation of polysulfides

(Kohnen et al., 1991). b) General scheme for sulfur incorporation into unsaturated lipid

precursors (Sinninghe Damsté et al., 1989).

48

3.2.1 Steroids and Hopanoids

Squalene is an unsaturated hydrocarbon, isoprenoid and lipid that is a precursor to

steroids and hopanoids. The enzyme known as squalene-hopene cyclase enables squalene to

cyclize and form pentacyclic triterpenes (Peters et al., 2005a). One of the major products of this

reaction is production of tetrahymanol, which is the precursor of gammacerane before diagenesis

processes. Tetrahymanol is mainly sourced from green sulfur bacteria and also halophilic

bacteria. Therefore the chemical structure of squalene, steroids and hopanoids may be important

structural elements for sulfur incorporation processes to occur. Additionally, sulfur incorporation

can occur before the cyclization reaction of squalene to triterpenoids as inorganic sulfides are

prone to incorporate into the squalene matrix at double bond function groups (Fig. 3.3).

Furthermore, Lu et al. (2014) postulates sulfur incorporation mechanisms target certain

functional groups in organic compounds such as hydroxyl groups, double bonds and carbonyl

groups. Such functional groups are present in sterols, which are often preserved in sediment. The

preservation and stability of sterols is enhanced further when sulfur is incorporated into steroids.

Figure 3.3 Intramolecular sulfur incorporation into double bonds of isoprenoids.

Diagenesis of kerogen forms saturated, aromatic and organic sulfur compound products.

(Peters et al., 2005).

3.2.2 Carotenoids

Carotenoids are a type of unsaturated molecule composed of series of isoprene units (Fig.

3.4). They are naturally occurring pigments found in a variety of marine organisms such as

plankton, algae, and photosynthetic organisms such as purple and green sulfur bacteria (Liaaen-

Jensen and Andrewes, 1985). These organisms and bacteria typically utilize carotenoids to

49

strengthen lipid membranes (Repeta and Gagosian, 1987; Peters et al., 2005a). There are two

main groups of carotenoids: carotenes and xanthophylls. The difference between the two is

bacteria typically use carotenes, which consists of mostly hydrocarbons, while plants more

commonly synthesize xanthophylls which are oxygen-containing terpenoids (Cai et al., 2005).

Carotenoids are normally destroyed during diagenesis because it is a water-soluble type pigment

and is easily oxidized. Also, the cleavage of polyene units within the carotenoid structure occurs

during diagenesis and increased thermal stress. However, when carotenoids are present in

sediment, it is often a strong indicator of reducing conditions in marine or lacustrine depositional

settings since carotenoid carbon skeletons were observed to become preserved only in highly

reducing conditions (Peters et al., 2005a).

Moreover, Peters et al. (2005a) propose the double bonds in the polyene units of

carotenoids, especially β-carotene, react more easily with inorganic sulfides in hypersaline

anoxic marine environments to form organic sulfur compounds. Frank et al. (2000) also

discusses how the conjugated double bonds in carotenoids are highly reactive and can change

orientations or form epoxides depending on environmental conditions such as in the presence of

limited or excess light energy. For instance, under anoxic, lacustrine and low sulfur conditions,

β-carotene is commonly reduced to β-carotane. It was believed that the presence of β-carotane

became detached from intermolecular sulfur linkages that formed sulfur-rich geomacromolecules

(Peters et al., 2005a). For example, Chen et al. (1996) observed abundant β-carotane in the first

member (ES1) of the Shahejie Formation. This formation, as mentioned above, was deposited

under hypersaline and highly restrictive lacustrine waters, however the sulfur content of each oil

was low (>0.5 wt%). Low sulfur concentrations may be the reason why β-carotene transformed

to β-carotane without undergoing sulfur incorporation reactions. Additionally, Chen et al. (1996)

notes the ES3 member of the Shahejie Formation is comprised of clastic shales and mudstones.

The clay and metallic minerals in this source rock may out compete organic matter for sulfidic

species which restricts sulfur incorporation into organic compounds.

50

Figure 3.4 There are more than 600 types of natural carotenoids, however the carotenoids

shown above are the most abundant in marine environments. Isorenieratene and

Chlorobactene are common in green sulfur bacteria. (Peters et al., 2005b)

3.3 Sample Selection and Geological Background

Six sulfur-rich crude oil samples were collected from various locations around the world

(Table 3.1). Three samples are from Peace River region in Alberta, Canada: (1) Bluesky

Formation, (2) Gething Formation and (3) West Cadotte Member. One sample is from Rozel

Point from Box Elder County, Utah (U.S.A). One oil is from the Jianghan Basin, China. The last

oil is derived from the 4th member of the Shahejie Formation (Es4) and it was collected from

offshore of Bohai Bay Basin, China.

51

Table 3.1 Sulfur-rich crude oil sample set and sulfur content (weight %) was determined

using elemental sulfur analysis. Bluesky, Gething Reno and West Cadotte field oils were

collected from research of Adams et al. (2013).

Sample Location Sulfur (wt%)

Bluesky Formation

Peace River oil sands, Alberta,

Canada

4.1 Gordondale Formation

(Gething Reno Field) 5.5

Western Cadotte Field

4.2

Rozel Point Utah, USA 9.4

Jianghan Basin Eastern China 5.6

Shahejie Formation

Bohai Bay Basin, China 1.1

3.3.1 Peace River Oil Sands

The Peace River oil sands, located in northwest - central Alberta, is one of three major

bitumen deposits in Alberta. The Peace River area is comprised two main groups, the Bullhead

Group formed by the Cadomin and Gething formations and the overlying Fort St. John Group

which, in succession, comprises the Bluesky, Spirit River, Peace River and Shaftesbury

formations (Fig. 3.5). Peace River oil reservoirs (Bluesky, Gething, McMurray) are Mesozoic in

age and are charged by several potential source rocks (Adams et al., 2012). The reservoirs are

supplied with a mixture of hydrocarbons expelled from multiple source rocks including the

Nordegg Member of Fernie Formation, Gordondale Formation, Permian Doig Formation and the

Devonian to Carboniferous Exshaw Formation (Riediger, 1994; Adams et al., 2013).

Manville Group reservoirs, Bluesky and Gething, may also be vertically charged by the

Mississippian Exshaw-Banff formations where hydrocarbons migrated upwards to permeable

Cretaceous sand units when erosion deteriorated the Poker Chip shale seal (Allan and Creaney,

1991). Peace River bitumen which exhibits higher levels of biodegradation, such as those from

the Bluesky Formation, is sourced by Exshaw - Banff source rock as these oils had longer

residence time in the reservoir. Exshaw-sourced oils with low API oil gravity may be attributed

52

to higher levels of biodegradation and low thermal history of the reservoir. Typically, heavy

crude oils require additional heat production technology for bitumen extraction. On the other

hand, deposits which are producible through cold production are generally located in the western

part of Peace River received more significant contributions from Gordondale source rock as

these oils are higher in sulfur content, less mature and have greater API gravity (Fig. 3.6)

(Adams et al., 2013).

Figure 3.5 Geologic timescale and the Peace River area which is comprised of the Bullhead

and Fort St. John Groups. (Modified from AER, 2017 and Adams et al., 2013)

Figure 3.6 The location of Peace River oil samples. Sulfur-rich oils were collected from

Gething Reno Field (green), West Cadotte (purple) and Bluesky formation (blue). Modified

from Adams et al. (2012).

53

3.3.2 Rozel Point

Rozel Point is a small peninsula located in the northern area of Great Salt Lake (Utah,

USA). The Great Salt Lake is separated into two parts, the north arm and south arm, due to

railway construction during the 1960s. The north arm, in particular, is high in salinity because it

is isolated from fresh water sources which come from snow melt by the Wasatch Mountain

Range (Fig. 3.7). Oil seep occurrences at Rozel Point are common and many oil seeps come

from shallow reservoirs, bedrock fractures at the lake bottom and from faults (Sei and Fathepure,

2009). Rozel Point oil is Miocene to Pliocene in age with high sulfur content (up to 14 wt%) and

has high viscosity. Furthermore, the source rock originated from an organic-rich playa lake

sediment deposit (Sinninghe Damsté et al., 1989; Richnow et al., 1993). The reservoir is

comprised of a porous basaltic rock layer interbedded with limestone and is approximately 1 m

thick and located 24 m below the subsurface (Eardley, 1963; Milligan, 2005). Rozel Point oil

migrated from source beds to the reservoir layer through faults and fractures, which also extend

to the surface lake bottom generating oil seeps that are visible when lake levels are low

(Milligan, 2005).

Figure 3.7 Location of Rozel Point. (Utah Geological Survey, 2005)

54

3.3.3 Jianghan Basin

The Jianghan basin, located in Eastern China, is comprised of five major tectonic units

with the Qianjiang depression being the most significant structure since most oil production

takes place in this region from the Eocene Qianjiang Formation (Fig. 3.8) (Philp and Fan, 1987).

Oils from the Qianjiang depression are sourced from the Qianjiang Formation and Xingouzui

Formation, which were deposited in anoxic, sulfate-reducing and saline lacustrine environments

during the late Cretaceous to Paleogene (Carroll and Bohacs, 2001; Hou et al., 2017). Due to

cycles of marine transgression and progradation activity, hot paleoclimate, and clastic sediment

deposition from lacustrine systems, over 220 evaporitic layers interlaced with shales and

sandstones formed the Jianghan Basin source rocks (Philp and Fan, 1987; Wang et al., 2008;

Hou et al., 2017). In addition, the Wangchang anticline, which overlies the alternating halite

layered source rocks, act as a seal to prevent hydrocarbons from migrating vertically. Lateral

accumulation is the main pathway for hydrocarbons coming from the Qianjiang Formation.

However, overlying fractured rock caused by tectonic compression and extension allows

minimal vertical migration. Therefore the Qianjiang Formation is suspected to act as both the

source rock and reservoir (Philp and Fan, 1987; Huang and Hinnov, 2014; Hou et al., 2017).

Upper Qianjiang sections act as the oil reservoir while the deeper sections and Xingouzui

formation embody the source rock.

Figure 3.8 The Jianghan basin located in Hubei province of China and the location of the

Qianjiang depression. (Modified after Brassell et al., 1988)

55

3.3.4 Bohai Bay Basin

The Bohai Bay Basin is a rift basin that is situated near the coast of eastern China (Fig.

3.9) (Wu et al., 2007). It is approximately 200,000 km2 in area and shaped by eight depressions,

five uplifts and many faults that formed during the Paleogene (Li et al., 2003; Luo et al., 2017).

The defining feature of Bohai Bay Basin is the Dongying depression, which formed when the

subsidence rate exceed the rate of deposition during the Neogene. Several formations constitute

the Dongying depression area such as the Kongdian, Shahejie, Dongying, Guanao, Minhuazhen

and Pingyuan formations (Table 3.2). Of these formations, the Shahejie formation is known as

the formation with greatest oil-producing potential (Li et al., 2003). The Shahejie Formation is

comprised of four sub members, Es4 (bottom) to Es1 (top) which was deposited during the

Eocene –Oligocene (Table 3.2). Es3 and Es4 members are important as they are potential source

rocks (Fig. 3.10). The deposition of Es4 was dominantly in a saline lacustrine setting.

Furthermore, the Es4 member is divided into two layers: (1) 40 m of organic-rich shale and (2)

300 m of mudstones and fine sandstones interbedded with gypsum and halite. Well-preserved

reef carbonates and algal fossils in basaltic dust rock were discovered in the upper part Es4,

which suggests a brackish or saline depositional settings (Li et al., 2003). Li et al. (2003)

hypothesized that during the deposition of Es4 member, intense faulting activity caused the

Dongying depression to separate into blocks. Afterwards, lake water evaporated which lead to

hypersaline lacustrine conditions. Over time, water level fluctuations brought clastic rocks along

the edges of lake forming alluvial fan shaped deposits. The lateral stratigraphy for Es4 sediments

changes clastics rocks then micritic limestone and lastly gypsum-halite from the edge of the

basin towards the depocenter (Li et al., 2003). Above lies the Es3 member, another source rock of

Bohai Bay Basin that is rich in organic matter and is approximately an 800 m layer of mudstone.

Oils in the Bohai Bay Basin vary greatly in sulfur content (ranging from 0.03% to 14.7%). High

S oils (>5.0%) have been recovered from Es2, Es3 and Es4 members of Jinxian sag of the Bohai

Bay Basin in the study by Cai et al. (2005).

56

Figure 3.9 Location of Bohai Bay Basin and the Dongying depression where the Shahejie

Formation lies (Wu et al., 2007).

Table 3.2 Lithology and basin evolution of the Cangdong sag which consists of the same

formations as the Dongying depression except the Es4 member of the Shahejie formation

does not extend to the Cangdong sag (Luo et al., 2017).

57

Figure 3.10 Schematic map showing the Dongying depression within the Bohai Bay Basin

and the lithology facies of source rocks: a) ES4 member and b) ES3 member (Li et al.,

2003).

58

3.4 Methodology

3.4.1 Elemental Sulfur Analysis

The sulfur-rich oils were was analyzed with the Costech 4010 elemental analyzer using the EAS

Clarity software. Sulfur content (wt%) data (Table 3.1) was obtained by the Applied

Geochemistry group – Isotope Science Lab (AGg – ISL) at the University of Calgary. The

Isotope Science Lab used the following Costech EA parameters: (1) helium carrier flow = 90

ml/min, 5ml of O2(gas) was delivered by the umicro loop for flash combustion, (2) the single tube

quartz reactor was at 1000 ºC, (3) the stainless steel ultratorr union at bottom of the reactor was

held at approximately 120 ºC, (4) combustion of water was removed by a Mg(ClO4)2 chemical

water trap immediately post reaction. GC separation of N2/CO2 from SO2 was achieved using a

custom built Porapak QS 50/80 x 0.8m pyrex glass column maintained at 110 ºC. Approximately

2 to 4mg of sample oil was weighed into smooth walled tin cups (Elemental Microanalysis p/n:

D4059) and cold welded shut using an in-house crimping tool. Sulfanilamide (Elementar

p/n:15.00-0062) was weighed at a range of weights and included in each day's sequence for

calibration and interspersed between each unknown (oil) sample. Flash-combustion was

achieved by careful timing of the umicro pulse of O2(gas) exactly at the time of sample drop.

Signal responses were measured by the on-board TCD. Baseline separation of N2/CO2 - SO2

peaks was approximately 30 seconds. Calibration curves were created for each day's sequence

and corrections were calculated through the Clarity software.

3.4.2 Florisil – Small Scale Separation (SSS)

The sulfur-rich oils were fractionated using liquid chromatography. Oil samples were de-

asphalted with a modified procedure of Bastow et al. (2007). About 50 mg of each sample was

accurately weighed in vials and 10 µL of standard containing naphthalene-d8, phenanthrene-d10,

1,1-binaphthyl, squalane, cholestane-d4, and adamantane-d16 was added to each vial with a

syringe to quantify the individual compounds in each sample. A small amount of

dichloromethane (DCM) was added to mobilize the heavy hydrocarbons. Samples were

transferred into Florisil® (magnesium silicate) columns which were pre-washed with pentane.

Then 5 mL of hexane was gradually added into each column followed by 3 mL of DCM. The

eluates, known as the SSS fraction, were collected in the same vial and placed under nitrogen gas

to concentrate to 0.5 mL.

59

3.4.3 Solid Phase Extraction (SPE)

To prepare saturate fractions for GC-MS, short column pipettes were plugged with cotton

wool and 0.6 g of silica gel (particle size 0.063-0.200 mm; 70-230 mesh) were prepared for each

sample. Pentane was used to flush and pack pipettes. Approximately 20 mg of the SSS fraction

was loaded on to the silica gel. GC-MS auto sampler vials were placed underneath the pipette

and 2.0 mL of pentane was added slowly into each pipette using a syringe in 50 µl increments.

The eluted saturated hydrocarbon fraction was concentrated using nitrogen to 200 µL then 1.0

mL of hexane was added on top prior to GC-MS injection. For the aromatic hydrocarbon

fractions, 8.0 mL vials were placed under the pipettes and 2.0 mL of DCM was added into each

pipette and collected. The fraction was then concentrated with nitrogen to 0.5 mL. The same vial

was placed under the pipettes where 2.0 mL of isopropyl alcohol (IPA) was added for further

elution. The fractions were evaporated to 0.5 mL and transferred into auto sampler vials for GC-

MS analysis.

3.4.4 Liquid Chromatography on Silver Nitrate Impregnated Silica Gel

Liquid chromatography was used to obtain organic sulfur compound (OSC) fractions for

FTICR-MS. Methods were modified from (Wei et al., 2012). For each sample, 300 mg of silica

gel impregnated with silver nitrate (10 wt% of silica gel) was activated at 105 °C for 3 h and

loaded on to a 146 mm Pasteur pipette column plugged with small amounts of cotton wool. The

rest of the column was filled with silica gel (70-230 mesh) activated at 225 °C for 16 h. About 50

mg of oil sample was weighed, mixed with several drops of hexane to mobilize it and loaded on

top of the silica gel. To obtain saturated HC, aromatic HC and OSC fractions, samples were

eluted with 3 mL of hexane, 8 mL of DCM and 2 mL of acetone, respectively. Our interest was

the OSC fraction as saturated and aromatic HC fractions have been obtained through GC-MS

preparation. This technique allowed cyclic sulfides to complex with Ag+ that were retained in

the silica gel column. Elution with acetone then displaced OSC compounds and allowed polar

OSC to elute which were collected as the OSC fraction.

3.5 Mass Spectral Data Processing and Analysis

3.5.1 GC-MS

Saturated and aromatic HC fractions were analyzed in full scan mode using a GC-MS

instrument (7890B GC and 5977 MS). The GC capillary columns are HP-5MS (30 m × 0.25 mm

60

× 0.25 µm). The temperature program initially operated at 40 °C for 5 minutes, followed by a

4 °C/min increase to 325 °C where it was held at this temperature for 15 minutes. Helium was

used as carrier gas at a flow rate of 1.0 mL/min (Huang et al., 2015). Data were processed with

GC/MSD ChemStation software.

3.5.2 FTICR-MS

OSC fractions and whole oil samples were analyzed with a 12 T Bruker SolariX mass

spectrometer in atmospheric pressure photoionization positive ion (APPI-P) mode. APPI-P mode

was selected to analyze OSC fractions as it has enhanced ability to recognize sulfur compounds

in complex organic mixtures without additional structural alteration or preparation methods

(Purcell et al., 2007; Radović et al., 2016). Fractions and samples were diluted with toluene to

0.25 mg/mL and infused into the krypton lamp ionization source (10.6 eV) using a syringe pump

that delivered 200 µL/h. The transfer temperature was set to 400 °C while nebulizer pressure was

at 1.0 bar. To tune the instrument and assess calibration efficiency, reference sample from

Athabasca bitumen was used and reserpine (C33H40N2O9) was added. Ions ranging from m/z 150

to 1500 were isolated by a linear quadrupole and accumulated over 110 ms in the collision cell,

before being transferred to the ICR cell. Spectra were collected in absorption mode using an

algorithm from (Kilgour et al., 2013; Qi et al., 2013). FTICR–MS raw data were processed using

CaPA v.1 (Aphorist Inc.) software.

3.6 Results and Discussion

3.6.1 GC-MS

3.6.1.1 Biomarkers

Biomarkers are often referred to as geochemical fossils because these are molecules which

have lost most functional groups but have still retained and preserved the original carbon

skeleton of a precursor molecule which originated from a particular organism or only available in

certain environments. Biomarkers give rise to information such as a particular class of organism,

age of the organic matter source, depositional setting, oxic or anoxic conditions in which the

petroleum source rock formed (White, 2013).

61

3.6.1.2 Source and Depositional Environment

Isoprenoids such as C19 pristane (Pr) and C20 phytane (Ph) are useful indicators for

organic matter source input as well as source rock depositional setting. Pristane and phytane are

two types of acyclic isoprenoids which originated from the phytyl side chain of chlorophyll. A

combination of diagenesis and anoxic or oxic environmental conditions triggered the cleavage

and transformation of phytyl to phytol (White, 2013). In oxic conditions, phytol converts to

pristane through oxidation and decarboxylation processes while phytol is converted to phytane in

anoxic conditions through reduction (Fig. 3.11). According to Peters et al. (2005b), a Pr/Ph ratio

of less than 1 indicates anoxic source rock depositional conditions and values < 0.8 indicates

hypersaline or carbonate environments.

The Pr/Ph ratios of the oil samples are low and range between 0 to 0.77 (Table. 3.3),

which suggests the source rock for sulfur-rich oils were deposited in anoxic hypersaline or

carbonate settings (Peters et al., 2005b). However, the Pr/Ph ratio was not available for Bluesky

as nearly all n-alkanes and isoprenoids were absent likely due to biodegradation.

Table 3.3 Pr/Ph ratios for sulfur-rich oil sample set. All values are below 1.0, which

suggests anoxic source rock depositional settings. Bluesky (BS), Gething Reno (GR), West

Cadotte (WC), Rozel Point (RP), Shahejie Formation (S) and Jianghan Basin (JH).

62

Figure 3.11 Formation of pristane and phytane from phytol side chain of chlorophyll is

dependent on oxic and anoxic environmental conditions.

The sulfur content of the samples has a direct proportional relationship with the

concentration of dibenzothiophene (DBT) (Fig. 3.12). The oils with higher sulfur content display

greater value of dibenzothiophene to phenanthrene (DBT/P) ratio. In studies by Hodairi and

Philp (2012) and Li et al.(2003), a DBT/P vs. Pr/Ph cross plot was used to determine source rock

and depositional settings. In Fig. 3.12, the ratios infer source rocks of sulfur-rich sample set were

deposited in lacustrine, brackish or marine water environments. All samples fall in one of two

groups: marine or lacustrine. It appears the oils which are less enriched in sulfur (< 5.0 wt%)

(WC, SH and BS) fall in the lacustrine sulfate-poor zone (blue square). Lacustrine waters

generally do not have sufficient sulfate , compared to marine waters, to enrich organic matter and

kerogen with sulfur unless there is presence of water stratification or chemocline which promotes

sulfate cycling activity by sulfate-reducing bacteria (Peters et al., 2005). On the other hand, oils

which are more enriched in sulfur (> 5.0 wt %) (RP, JH and GR) fall within the sulfur-rich

63

marine and lacustrine zone (Fig. 3.12).

Figure 3.12 Cross plot of dibenzothiophene/phenanthrene (DBT/P) vs pristane/ phytane

(Pr/Ph) to determine source rock depositional environments (modified after Hodairi and

Philp, 2012). Sulfur-rich oil samples Rozel Point (RP), Jianghan (JH), Gething Reno (GR)

fall in the marine carbonate and lacustrine zone (purple square) and the ratios indicate

that source rocks from Bluesky (BS), West Cadotte (WC), and Shahejie (S) were deposited

in mainly lacustrine environments (blue square).

Another biomarker ratio which infers depositional environment and source rock inputs is

the gammacerane index (10* gammacerane/ (gammacerane + C30 hopane) paired with Pr/Ph

(Fig. 3.13). It is hypothesized that gammacerane (GAM), a saturated triterpenoid, formed from

the reduction and dehydration of tetrahymanol, a lipid found in primitive protozoa of genus

Tetrahymena which thrive below the chemocline and use green and purple sulfur bacteria as food

sources (Sinninghe Damsté et al., 1995). Tetrahymanol is the second alternative for anaerobic

ciliates when preferred steroids are limited. However, other biohopanoids and organisms may

produce tetrahymanol as it is commonly distributed in marine sediment (Ten Haven et al., 1989).

Therefore, gammacerane presence is often linked to paleo-saline to hypersaline lake

environments, stratified water columns due to difference in water density caused by salinity or

oxygen availability, or marine crude oils sourced from carbonitic rock (Peters et al. 2005a).

Furthermore, Sinninghe Damsté et al. (1995) showed evidence that gammacerane formation is

also correlated to natural sulfurization processes as sulfur-rich macromolecules from sulfurized

64

lipids released gammacerane upon artificial diagenesis and catagenesis which cleaved weak C-

S bonds in sulfur-rich macromolecules.

Peters et al. (2005a) summarizes the trend that suggests hypersaline lacustrine deposits

and highly reducing conditions are high gammacerane indices and low Pr/Ph ratios as these

conditions favor production of tetrahymanol which is the precursor of gammacerane.

Figure 3.13 Gammacerane index 10*(GAM/GAM+30H) and pristane/phytane (Pr/Ph) ratio

for sulfur-rich oil sample set. High gammacerane indices indicate increased water salinity,

water stratification or natural sulfurization processes.

All sulfur-rich oils show a gammacerane and Pr/Ph ratio that is less than 1.0, except for

Jianghan (JH) oil, which exhibits the a gammacerane index of 7.1 which shows it formed in a

different environment compared to the rest of the sample set. JH oil shows greater gammacerane

concentration possibly because organic matter may have been exposed to highly reducing and

hypersaline conditions. Although Rozel Point oil contains high wt% S like Jianghan oil, it has a

low gammacerane index that is comparable to the other oils in the sample set. This plot suggests

RP source rock was not deposited in a hypersaline environment with water stratification or low

thermal maturity which prevented cleavage of C-S bonds in sulfur-rich kerogen thus preventing

the release of gammacerane. Since all the sulfur-rich oils display low Pr/Ph ratios (< 1), reducing

environments appear to be a common environmental factor for generating sulfur-rich oils.

According to Peters et al. (2005a), gammacerane is abundant in marine crude oils from carbonate

source rocks. Presence of this biomarker also suggests increased salinity or presence of a

stratified water column during sediment deposition.

65

The homohopane index is defined as C35/(C31 to 35) homohopanes and this index is

commonly used as an indicator for environment redox potential, bacterial source input as well as

thermal maturity (Peters and Moldowan, 1993). Typically, abundant homohopane distribution

suggests marine, carbonate or evaporitic, or highly reducing environments because homohopanes

(C31-35) originate from the precursor bacteriohopanetetrol, which is a biochemical structure found

in prokaryotes that thrive in the above environmental settings (Peters et al., 2005a). The

homohopane indices for the sulfur-rich oil sample set ranges from 0.03 to 0.13 (Fig. 3.15).

According to Mohialdeen et al.(2015), homohopane indices above 0.09 is considered high.

Therefore, the oils from Jianghan basin and Alberta show a relatively high homohopane, which

suggests these oils originated source rocks deposited in reducing marine or evaporitic

environments. Furthermore, C35 homolog predominance is often observed in immature sulfur-

rich oils, however in Fig. 3.14, the sulfur-rich oils show low homohopane indices and, rather, C31

is more favored and peak height decreases sequentially from C31 to C35. Homohopanes are often

affected by thermal maturity and will decrease in abundance with increasing maturity. According

to Peters and Moldowan (1993), during the catagenesis of source rock containing sulfur-rich

bitumen, kerogen-bound homohopanes may also crack as conditions reach the oil window, thus

increasing the concentration of C31 homologs. Low homohopane indices may also indicate

suboxic depositional conditions (Peters and Moldowan, 1993).

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Figure 3.14 m/z 191 Chromatogram showing homohopanes (C31 – C35) distribution in

sulfur-rich crude oil samples from: (a) Bluesky Formation, (b) Gething-Reno Formation,

(c) West Cadotte field, (d) Rozel Point, (e) Jianghan Basin and (f) Shahejie Formation.

GAM represents gammacerane (non-regular hopane).

The norhopane/hopane (C29/C30) is a biomarker ratio which is useful for indicating source

and maturity information. Norhopane abundance typically increases with thermal maturity as

norhopane is more stable than hopane. From this information, it appears Alberta sulfur-rich oils

(Fig. 3.15) are more thermally mature compared to the other oils as the Bluesky, Gething-Reno

and West Cadotte oils show slightly higher C29/C30H values (0.78 – 0.83) whereas oils from

Rozel Point, Jianghan Basin and Shahejie show lower C29/C30H values (0.13 – 0.30) which

suggests lower thermal maturity.

Fig. 3.15 Homohopane Index (C35/ C31-C35) and norhopane/hopane (C29/C30) which are

source and depositional setting indicators. High homohopane indices (>0.09) suggests high

redox potential, anoxic reducing environments, marine sources, and bacterial input from

bacteriohopanetetrol (Peters et al., 2005)

Steranes (C27-C28-C29) are biomarkers which are commonly used in conjunction in a

ternary diagram (Fig. 3.16) to distinguish organic matter source input, different source rocks or

facies within the same source (Peters et al., 2005a). Most steranes are derived from sterols which

originate from terrigenous organic matter, algae and eukaryotic organisms, while sterols are less

commonly produced by prokaryotes (Mohialdeen et al., 2015). For instance, C27 sterol precursors

are most abundant in phytoplankton and marine organisms. High concentrations of C28 may

relate to lacustrine algae or limnic environments and C29 steranes indicate contributions from

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terrigenous higher plants, cyanobacteria and primitive algae (Mohialdeen et al., 2015).

Furthermore, high levels of steranes may also be indicative of a clay-poor source rock (Peters et

al., 2005a). Many sulfur-rich oils originate from sulfur-rich kerogen, which means the kerogen is

likely clay-poor and contains low metal concentrations which would not compete with organic

matter for sulfur incorporation. Whereas, clay-rich marine clastic rocks contain metal oxides

which out compete organic matter for H2S utilization thus generate low-sulfur kerogen. In Fig.

3.16, all oils, except for the oil from Gething-Reno, are located in the lower center of the ternary

plot which shows C27, C28 and C29 sterol abundance are relatively equal except C27 and C28 show

a slightly higher abundance. Therefore, the data suggests source rocks of the Alberta oils,

Jianghan Basin, Rozel Point and Shahejie Formation inherited contributions from mixtures of

terrigenous non-marine and marine inputs. On the other hand, Gething-Reno oil shows a clear

C29 predominance which implies Gething-Reno source rock received more non-marine higher

plants or cyanobacteria contributions and hence the abundance of C29 steranes.

Figure 3.16 Ternary diagram with relative distribution of C27, C28 and C29 sterane

abundances.

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3.6.1.3 Thermal Maturity

Thermal maturity is referred to as the temperature conditions at which kerogen reacts to

generate petroleum. Kerogen begins to break down to hydrocarbons during catagenesis and when

it reaches the oil window which are temperatures of 100–150°C and at depths of approximately

2–3 km (Peters and Moldowan, 1993; White, 2013). The level of thermal maturation of kerogen

can be indicated through pentacyclic triterpanes such as 28,30-bisnorhopane (BNH) and

25,28,30-trisnorhopane (TNH), which are derived from chemotrophic bacteria which thrive in

anoxic-oxic interfaces and bacterial reworking in sediments (Peters et al., 2005b). As well, BNH

and TNH degrade and crack at the same time therefore the ratio BNH/TNH is relatively constant.

However high abundance of BNH/TNH may also indicate source rock deposition in clay poor

and anoxic conditions (Peters et al., 2005b). While BNH/TNH ratios decrease as source rocks

reach thermal maturity and generate oil (Peters et al., 2005a).

Figure 3.17 Biomarkers which are indicative of the degree of thermal maturity:

dibenzothiophene/phenanthrene (DBT/P) is plotted against 28,30-bisnorhopane/ 25,28,30-

trisnorhopane (BNH/TNH).

In Fig. 3.17, the cross plot shows that the higher the sulfur content in oil, the greater the

DBT/P ratio. DBT/P ratios are highest for Rozel Point and lowest for Shahejie Formation, which

correlate closely to measured sulfur content values in Table 3.1. DBT/P and BNH/TNH show an

inverse relationship where the higher the sulfur content, the lower the BNH/TNH ratio. If high

BNH/TNH and sulfur content were observed, then this proportional relationship would infer that

the oils have high thermal maturity (Adams et al., 2013). As well, the BNH/TNH ratio typically

decreases as source rocks mature and reach the oil generation window. This theory is applicable

to oil from the Shahejie Formation which has the lowest DBT/P ratio and also low BNH/TNH.

Since Shahejie oil is less enriched in sulfur (1.1%), Peters et al. (2005a) suggest low BNH/TNH

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ratio, especially for low sulfur oils, indicate that source rock has reached oil generation

maturation as BNH and TNH become depleted with increasing maturity.

Figure 3.18 Thermal maturity parameters C31 homolog (22S/22S+22R) and C29 sterane

(20S/20S+20R).

A thermal maturity parameter which is particularly useful for showing immature to early

generation oils is the 22S/(22S+ 22R) homohopane isomerization ratio (Peters et al., 2005a).

Terpanes (C31 or C32 homohopanes) are measured using m/z 191 chromatogram and the

isomerization that occurs at C-22 typically occurs early in thermal processes of oil where C-22R

configuration is biologically produced but is converted to C-22S as thermal maturity increases,

therefore high ratio between 22R and 22S is indicative of immature oils (Peters et al., 2005a).

Peters et al. (2005) states that 22S/(22S+22R) ratios below 0.54 suggest oils are early mature

while ratios between 0.57-0.62 suggest mature oils which have reached the oil-generative

window.

Sterane 20S/(20S+20R) isomerization is also a thermal maturity parameter which is

indicative of immature to mature oils. It is measured with m/z 217 chromatogram of C29 sterane.

Similarly, the C-20R configuration occurs naturally in organisms containing steroids and with

increasing maturity, C-20R gradually converts to C-20S configuration. C29 is most commonly

used because C27 and C28 steranes often show co-eluting peaks hence C29 provides more

accuracy. Low maturity oils often show a 20S/(20S+20R) ratio for C29 sterane between 0.23–

0.36 (Li et al., 2003) and the higher the ratio, the more mature the oil. However both thermal

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maturity parameters can be influenced by biodegradation and selective removal of steranes.

Meanwhile, Ten Haven et al. (1985) suggested that immature oils which originate from

hypersaline source rocks can appear mature with the sterane 20S/(20S+20R) ratio. Fig. 3.18

shows a cross plot between C31 homolog [22S/(22S+22R)] and C29 sterane [20S/(20S+20R)].

Early mature oils and bitumen show isomerization at C-22 for homohopanes and C-20

isomerization in regular steranes (Peters et al., 2005a). The sulfur-rich oil samples show C31

22S/(22S + 22R) ratios between 0.44 -0.62 and C29 20/(20S+20R) ratio is between 0.29 and 0.41.

Both thermal maturity parameters infer that Rozel Point oil is immature, whereas the rest of the

oils are mature and fall in the oil generative window. Furthermore, Peters et al. (2005) suggests

that the accuracy for these two thermal maturity ratios may be influenced by organic facies and

biodegradation. For instance, immature extracts may show greater maturity than reality

especially for oils from hypersaline rocks because unusual sterane diagenetic pathways can

occur. Ten Haven et al. (1985) also noted source rocks deposited in hypersaline conditions can

exhibit mature hopane patterns even when source rocks barely reach the oil window. Therefore,

even though thermal maturity parameters infer sulfur-rich oils from Alberta, Jianghan and

Shahejie are mature, the ratios may exhibit higher maturity than actuality as source rocks were

deposited in hypersaline environments (Sinninghe Damsté et al., 1987).

3.6.1.4 Biodegradation

The Peters and Moldowan (PM) biomarker biodegradation scale (Fig. 3.19) is a ranking

system used to determine the level and extent of biodegradation of oil (Peters and Moldowan,

1993). This system assesses the extent of biodegradation based on the abundance and enrichment

of different hydrocarbon classes in oil. Typically, resins, polar molecules, asphaltenes and

hydrocarbon classes such as naphthalenes and phenanthrenes are chemically more resistant to

microbial degradation compared to n-alkanes and isoprenoids (Peters et al., 2005a). Oftentimes,

it is difficult to determine a clear division between the levels of biodegradation because more

resistant compounds may start to biodegrade before less resistant compounds are fully removed.

Also, complex petroleum systems may contain paleobiodegraded oils mixed with fresh oil

charges (Bennett et al., 2006) and show deviation away from the common order of selective

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biodegradation observed in the biodegradation scale. Therefore, the biodegradation scale is

most accurate when used as a range rather than a specific number.

Figure 3.19 Biomarker biodegradation scale which ranks biodegradation severity based on

the presence of hydrocarbon classes. L, M, H refers to lightly biodegraded, moderately

biodegraded and heavily biodegraded, respectively. (Peters and Moldowan, 1993).

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Figure 3.20 m/z 85 chromatograms which show n-alkane and isoprenoid distributions in

sulfur-rich crude oil samples from: (a) Bluesky Formation, (b) Gething-Reno Formation,

(c) West Cadotte field, (d) Rozel Point, (e) Jianghan Basin and (f) Shahejie Formation.

Figure magnification for West Cadotte oil (c) shows dominance of C17 and phytane in m/z

85 and m/z 183 chromatograms. IS1 represents squalane internal standard.

Chromatograms (m/z 85) of the saturated HC fraction (Fig. 3.20) show most of the n-

alkanes series are absent in all sulfur-rich oil samples except for the Shahejie Formation (Fig

3.20f) while long chain n-alkanes C20 to C30 are preserved in oils from the Gething-Reno field

and Jianghan Basin (Fig. 3.20b and e). According to the Peters and Moldowan (PM)

biodegradation scale (Fig. 3.19), the sulfur-rich oils from China are lightly to moderately

biodegraded as some n-alkanes and acyclic isoprenoids are depleted. Jianghan oil (Fig. 3.20e) is

depleted in short chain n-alkanes, but isoprenoids (Pr and Ph) and medium (C12 to C30) to long (>

C30) n-alkane chains are abundant, which means Jianghan oil has a PM level between 2 and 3. As

for the Shahejie Formation (Fig. 3.20f), isoprenoids, a distribution of n-alkanes including short

chain n-alkanes (< C12) remain, which indicates biodegradation extent has reached approximately

PM level 2. In comparison, Alberta (Fig.3.20 a, b, c) and Rozel Point (Fig. 3.20 d) oils are

moderately to severely biodegraded. Out of the all sulfur-rich oils, Bluesky oil appears most

biodegraded because all n-alkanes and isoprenoids are absent, but tricyclic terpanes and hopanes

remain, therefore the oil from the Bluesky formation is most likely PM level 4, which is heavily

biodegraded. Rozel Point and West Cadotte oil both share similarities in the m/z 85

chromatogram (Fig. 3.20c and d) because both oils show depletion in n-alkanes and isoprenoids

except C17, selectively preserved pristane, and phytane. Overall, the oil samples have a PM

biodegradation level between 2 and 4 (Peters et al., 2005b).

3.6.2 FTICR-MS

3.6.2.1 Chemical Composition of Organic Sulfur Compounds

Whole oils (Fig. 3.21a) and their OSC counterpart fractions (Fig. 3.21b) were analyzed

with the FTICR-MS and showed the relative monoisotopic intensity for hydrocarbon and

heteroatom compound (N, O, S) classes. Relative monoisotopic intensity (RMI, % of sample) is

defined as the intensity signal measured from a fraction of the most abundant natural element of

each atom rather than average intensity between all isotopes of each atom, and the fraction is

normalized against the sum of all monoisotopic intensities (Carr et al., 2000).

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The graphs in Fig 3.21 show a bimodal distribution where there are two noticeable

groups with higher intensities. The whole oils show high RMI for the hydrocarbon compound

classes, on the left of the graph, and lower RMI for the sulfur heteroatom class on the right of the

graph (Fig 3.21b). On the other hand, the OSC fraction, which was obtained from liquid

chromatography using silver nitrate in silica gel, shows the opposite where the sulfur classes

show greater RMI compared than the hydrocarbon compound classes. The main difference

observed between the OSC fraction and whole oils is higher intensity of sulfur classes are

observed in the OSC fraction which indicates liquid chromatography technique using silver

nitrate successfully concentrated sulfur compounds into the OSC fraction and removed most HC

classes. However, the whole oil fraction shows up to S6 in sulfur class. This means the silver

nitrate silica gel may have trapped larger PASH which consisted of more sulfur atoms within its

structure. Additional method development is needed to optimize OSC fractionation technique

and the method development process will be discussed in Chapter 4. Since the whole oil fraction

displayed greater sulfur class distribution, the whole oil fraction was selected for further analysis

in carbon number distribution and double bond equivalents (DBE).

In the whole oil fraction (Fig 3.21b), the sulfur class distribution shows S1 radical sulfur

atoms with highest RMI followed by decreasing intensity with increasing sulfur atom class. For

Bluesky, West Cadotte and Gething Reno oils, RMI becomes negligible after S3. However, for

Rozel Point and Jianghan Basin, RMI is observed at class S5, which indicates these two oils are

more enriched in sulfur compared to the rest of the sulfur-rich oil sample set. Furthermore,

Shahejie crude oil shows very low RMI at sulfur class S2 which is not unexpected because it has

the least sulfur (1.1 wt%). As for the HC class distribution, Shahejie oil, on the other hand, has

the greatest RMI. It appears there is an inverse relationship between RMI for the sulfur class and

hydrocarbon class distributions where the greater the hydrocarbon intensities, the lower the RMI

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for sulfur classes.

Figure 3.21 Organic sulfur compound fractions obtained from liquid chromatography

using silver nitrate impregnated silica gel compared to whole oils. ●, indicates radical

atoms. RMI, relative monoisotopic intensity (a) Liquid chromatography method removed

hydrocarbons and enhanced sulfur intensities (b) Whole oils.

3.6.2.2 Carbon Number Distribution

The oils from Bluesky, Gething Reno and West Cadotte show close relationships because

the carbon distribution shows the oils overlap to form a smooth bell curve with greatest RMI

from C28 to C36 (Fig. 3.22). The overlap is likely due to the genetic similarity between the

Alberta oils as these oils were exposed to similar depositional conditions, thermal processes and

biodegradation as the Alberta oils formed within close proximity (Fig. 3.6). The GC-MS results

show Alberta oils experienced greater levels of biodegradation and increased thermal maturity

compared to the oils from Rozel Point and Jianghan Basin. These conditions removed short and

medium chain n-alkanes during biodegradation which may explain why the carbon number

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distribution for the Alberta oils is depleted in low carbon numbers but shows increased RMI is

observed for higher carbon number classes.

Other oils which show close resemblance are the oils from Rozel Point and Jianghan

Basin. Several overlapping peaks are prominent from C20 to C40 and the presence of these peaks

may be influenced by low thermal maturity and light biodegradation which allowed precursor

compounds to survive microbial attacks or degradation due to thermal processes. Rozel Point oil

shows high intensity peaks at C20, C29 and C40 while Jianghan Basin oil peaks from C20, C24, C26,

C28, C30, and C40. Shahejie oil also shows similar peaks at C14, C27, C29, and C40. The carbon

number distribution provides information about the molecular structure of precursor compounds

thus gives rise to the organic matter source and depositional environment which form sulfur-rich

oils. For instance, the intensity peak at C20 could be abundance of phytane or a C20 isoprenoid

thiolane which commonly forms in anoxic conditions. Furthermore, the C29 peak could be

enrichment of C29 steranes which come from algae contributions (steroids). Lastly, the intense

peak at C40 could be carotenoids which are also abundant in plants, algae and anoxic bacteria

which utilize carotenoids for capturing long wavelengths of light in deep lakes (Casamayor et al.,

2001; French et al., 2015). Similarly the same results are seen with Jianghan oil but with a

distinct even/odd carbon number preference from C20 to C40 which may be associated with

isoprenoid thiophenes and thiolanes. Shahejie has a slight odd/even predominance from C25 to

C29 and C29 abundance is recognized as indicating terrigenous input to the source (Peters et al.,

2005b).

Figure 3.22 The relative monoisotopic intensity (RMI) and carbon number distributions for

sulfur-rich oil sample set. Rozel Point oil (red) shows high intensity peaks at C20, C29 and

C40. Jianghan Basin oil (orange) shows peaks at C20, C24, C26, C28, C30, and C40. Shahejie oil

(black) also shows similar peaks at C14, C27, C29, and C40. Alberta oils (blue, green, pink) are

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depleted in low carbon numbers but show increased RMI for higher carbon number

classes.

Figure 3.23 Double bond equivalent distributions. (a) Radical S1 class. (b) Protonated S1

class. Black circle emphasizes DBE 1 peak which is unique only to Jianghan Basin oil.

3.6.2.3 Double Bond Equivalents

Double bond equivalents (DBE) is measure of unsaturation in a molecule and

unsaturation is defined as the number of ring systems, double bonds or both. The radical and

protonated sulfur class S1 and the DBE distribution for the whole oil fraction is presented in Fig.

3.23. Protonated refers to even numbered protonated molecular ions and radical refers to odd

numbered electron ion species (Raffaelli and Saba, 2003). Since RMI is greater with radical

ionization (Fig. 3.20a), in this study onwards, interpretation and discussions will be based on

radical sulfur classes.

From the order of lowest to highest DBE, Jianghan Basin oil shows intense peaks at DBE

1 and 3, then Rozel Point oil at DBE 5 and 6, Shahejie Formation oil and the Alberta oils show

overlapping peaks at DBE 6 with Gething Reno showing a slightly more intense signal.

Furthermore, an interesting note is the Alberta oils appear to have a slight preference towards

odd numbered DBEs at DBE 5, 7 and 9. Overall, the sulfur rich oil sample set shows a non-

symmetric bimodal DBE distribution where high intensities are observed in low DBE numbers

for Jianghan Basin oil and all sulfur-rich oils show peak overlap at DBE 6. DBE analysis shows

OSC with DBE 1(Fig. 3.23a), this observation is unique only to Jianghan Basin oil.

The carbon number distribution for DBE 1 (Fig. 3.24a) mainly shows the Jianghan Basin

with strong even/odd n-alkane predominance from C20 to C30, which may be related to precursors

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containing C28 and C30 tetracyclic steranes that come from squalene biochemical precursors

(C30H50) and marine organic matter source contributions (Peters et al., 2005b). Lu et al. (2004)

also studied Jianghan Basin oils using the FTICR-MS and hypothesized that enrichment of C20

sulfur compounds come from the sulfurization of phytanic acid and phytol. Intense peaks

observed at C22–C30 represent sulfurized short-chain steranes such as thiolane steranes or cyclic

thioethers as these structures have one sulfur atom and DBE 1 (Lu et al., 2014).

Figure 3.24 Carbon distribution for radical sulfur class S1 at (a) DBE 2 (b) DBE 3 (c) DBE

5 and (d) DBE 6.

Fig. 3.24b shows DBE 3 is a major structural component in oils from Jianghan Basin and

Rozel. The RMI for the other oils are insignificant. When compared to the carbon number

distribution, both Jianghan and Rozel Point have peaks distributed from C20 to C40, however

Jianghan is more enriched in C20 which could be a series of thiophenes or cyclic thioethers with

three rings such as isoprenoid thiophenes (Lu et al., 2014) or the origins of Jianghan may be

from the incorporation of sulfur into phytol (Brassell et al., 1988) as GC-MS results showed high

phytane abundance in Jianghan and Rozel Point. In Fig. 3.24c, Rozel Point shows an intense

peak at DBE 5 that is enriched with C26 to C30, this combination suggests presence of sulfurized

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steranes with 4 rings cyclized with thioethers to form thiolane steranes (Kok et al., 2000a;

Yang et al., 2013). At DBE 6 in Fig. 3.24d, Alberta oils display a slight right-skewed bell curve

distribution and the carbon number range between C20 to C30 show a higher intensity. This

distribution for Alberta oils could be explained by the presence of benzothiophenes series

attached to medium-chain carbons, such as isoprenoid benzothiophenes because benzothiophenes

have a DBE of 6. In contrast, Rozel Point, Jianghan and Shahejie show high intensity peaks

coinciding at C28-29, C35 and C40. Possible structures which satisfy these characteristics are

sulfurized homohopanes such as C35 pentakishomohopane which has 5 rings and originates from

bacteriohopanoid precursors which incorporated sulfur to form cyclic thioethers and increased

DBE to 6 (Schaeffer et al., 2006). This possibility is likely as GC-MS data also showed high

abundance of C35 homohopane especially for Jianghan Basin oil.

Figure 3.25 (a) Double bond equivalent (DBE) distribution for sulfur class S3. (b) Carbon

number distribution for sulfur class S3 at DBE 7.

The next most abundant sulfur class is S3 (Fig. 3.23a) and further analysis in DBE

distribution in class S3 is shown in Fig. 3.25a. In this figure, oil from Shahejie Formation did not

contain sulfur class S3, but the other oils do and two distinct groups are recognized. Rozel Point

and Jianghan Basin oil differ from Alberta oils because they show lower DBE distributions

which range from 2-10 and intensity peaks are observed at odd DBE numbers such as DBE 3, 5,

6, and 9 with the greatest intensity peak at DBE 7 for Jianghan Basin. Compared to the Alberta

oils which have higher DBE distributions that range from DBE = 3 to 25. High DBE numbers

implies many possibilities for OSC chemical structures (Lu et al., 2014), therefore OSC in

Alberta oils may comprise of more aromatic rings and double bonds within S3 containing

chemical structures compared to Rozel Point and Jianghan Basin OSC structures. Furthermore,

Alberta oils exhibit a bell curve DBE distribution where RMI gradually increases to DBE 14 and

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descends to zero by DBE 25. This trend could indicate S3-containing OSC structures in

Alberta oils preferentially form structures between DBE 10-14. In Fig. 3.25b, Rozel Point and

Jianghan Basin oil show an intense peak at C40 with DBE 7. This carbon number distribution

pattern is recognized again in sulfur class S5 in Fig. 3.26a where Rozel Point and Jianghan Basin

oils are the only ones which encompass sulfur class S5-containing OSC and a strong intensity

peak is observed at DBE 13. When the carbon number distribution for this peak (S5 class and

DBE 13) was analyzed in Fig. 3.26b, a dominant peak at C40 is observed for both Rozel Point

and Jianghan Basin samples. The chemical OSC structure complies with these characteristics

(C40, DBE 13 and class S5) could possibly be sulfurized carotenoids such as carotenes

(hydrocarbons only) and xanthophylls (oxygen-containing).

Figure 3.26 (a) DBE distribution for sulfur class S5. (b) Carbon number distribution for

sulfur class S5 at DBE 13.

3.7 GC-MS and FTMS Data Summary

GC-MS biomarker analysis indicates sulfur-rich oils in this sample set originate from

reducing and anoxic source rock depositional environments. The Pr/Ph ratios (< 0.8) and low

DBT/P ratio suggest marine or lacustrine depositional settings. Furthermore, the presence of

gammacerane infers hypersaline or stratified water columns as the precursor of gammacerane,

tetrahymena protozoa, thrive in these conditions. The abundance of steranes suggests clay-poor

source rock and organic matter contribution from cyanobacteria, marine and non-marine

organisms. The source rocks for all sulfur-rich oils show similarities. For instance, the

Gordondale member is an important source rock to Peace River oils and it is comprised of

laminated calcitic mudstones (Asgar-Deen et al., 2004). Rozel Point source rock is comprised of

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anhydrites and calcareous dark shales and siltstones (Bortz, 1984) and the Qianjiang and

Xingouzui formations are main source rocks in the Jianghan Basin and it is comprised of

evaporitic halite layers interbedded with shale and sandstone (Wang et al., 2008). Cai et al.

(2005) also recognized the Shahejie Formation was deposited in anoxic waters because the

presence of mudstones is indicative of poor water circulation and the interbedded carbonates

infers hypersaline and arid environments which form evaporites in shallow marine or lacustrine

settings.

The thermal maturity indicators show oils range from immature to mature indicated by

the terpane R and S isomers where the naturally occurring R isomer is converted to S isomer

with increasing thermal maturity. In addition, the BNH/TNH ratio decreases as oils reach

thermal maturity however low BNH and TNH is observed when exposed to sulfate reducing

conditions. Overall, the oils fall within the immature to early mature zone where Rozel Point oil

is the least mature followed by Jianghan Basin, the Alberta oil and lastly the Shahejie Formation.

Moderate to heavy biodegradation is observed in the sulfur-rich oils from the absence of

short chain n-alkanes and isoprenoids. This study on the sulfur-rich oils from Peace River oil

sands agrees with the maturity and biodegradation levels previously studied by (Adams et al.,

2013). In their study, oil from the Gething Reno field, sourced from sulfur-rich Gordondale

Member (Anderson et al., 2015), exhibited lower thermal maturity, higher sulfur content and

biodegradation compared to Bluesky and West Cadotte oil despite the close proximity in

distance between the Peace River oils.

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Table 3.4 Summary of source, depositional environment, maturity and biodegradation

on biomarker ratios of sulfur-rich oil sample set.

3.8 Sulfur Incorporation Environmental Conditions

Certain environmental conditions increase the chances of producing sulfur-rich kerogen

and bitumen. The Alberta oils were sourced from both non-marine and marine contributions and

were more thermally mature and biodegraded compared to the others. Although highly sulfur-

rich oils from Rozel Point and Jianghan formed in places on opposite sides of the world,

biomarkers suggests they were both sourced from marine or lacustrine organic matter and were

deposited in anoxic hypersaline environments. Besides these similarities, both oils showed

similar chemical compositions in carbon number distributions, sulfur class distribution and DBE

values when analyzed by FTICR-MS.

Shahejie Formation oil was different because it showed lowest sulfur class distribution

and least structural complexity compared to other sulfur-rich oils. The Alberta oils were enriched

with up to three sulfur atoms (sulfur class S3), but the most sulfur enriched oils, Rozel Point and

Jianghan, were interesting as they both included up to sulfur class S5 and showed carbon number

peaks at C20, C30 and C40 as well as high intensity beaks at DBE 5, 7 , 9 and 13. Possible OSC

structures which satisfy these characteristics are sulfurized steranes, hopanes (C26–C34) and

carotenoids (C40).

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From the molecular analysis of sulfur-rich oils, source input biomarkers indicate

organic matter input include bacteria, terrigenous plants and marine organisms which are

comprised of steroids, hopanoids and carotenoids in its cellular structure. Furthermore, in the

GC-MS and FTICR-MS results section, carotenoids appear to have incorporated sulfur

intramolecularly indicated by high DBE by FTICR-MS data analysis. It is possible that high

abundance of inorganic sulfur species is required to initiate sulfur incorporation into carotenoids.

If sulfur concentration is low, carotenoids may convert to saturated hydrocarbons instead due to

degradation.

As for the environmental conditions, sulfur-rich kerogens were produced under anoxic,

hypersaline, marine or lacustrine with stratified water conditions. These environments are also

typically where sulfate reducing bacteria thrive and produce H2S. Moreover, poor circulation in

anoxic waters enhances H2S concentrations. Since H2S is toxic to most aerobic organisms,

increased H2S can cause organic matter decomposition and deposition. However, H2S can also

convert to polysulfides and elemental sulfur, which becomes incorporated into organic matter or

combines with metals to form rocks (Peters et al., 2005). Cai et al. (2005) also agrees that sulfur

incorporation into functionalized labile hydrocarbons is mainly facilitated by bacterial sulfate

reducing communities. As inorganic sulfur species become incorporated into functional groups

of labile hydrocarbon skeletons, saturated hydrocarbons become depleted, in comparison to the

aromatics, as more thiophenic sulfur compounds form. Also, biodegradation typically attacks

saturated hydrocarbons first which then further increases the sulfur content in residual petroleum.

Cai et al. (2005) also noted that sulfur content in petroleum tends to decrease with

increasing burial depth as source rocks typically produce sulfur-rich oils at low maturity where

burial depth is less than 2400 m. Furthermore, Cai et al. (2005) suggests petroleum with high

sulfur enrichment (>5%) typically forms at paleotemperatures of less than 80 °C. However, the

temperatures which promote bacterial sulfate reduction rates vary from 27 °C–90 °C depending

the type of sulfate reducing bacteria and environmental setting (Kallmeyer and Boetius, 2004;

Sawicka et al., 2012).

In summary, based on the literature and from experimental findings, it is hypothesized

that six conditions that occur concurrently to form sulfur-rich oils and OSC: (1) anoxic, reducing,

hypersaline marine or lacustrine depositional settings, (2) active anaerobic bacterial sulfate

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reduction activity, (3) organic matter input from bacteria, marine and terrigenous organisms

which are rich in reactive functional groups such as those found in steroids, hopanoids or

carotenoids, (4) formation of type I or II kerogen that is enriched in sulfur, (5) shallow source

rock burial depth and low thermal maturity (<80 °C), (6) moderate biodegradation which

selectively removes n-alkanes and increases sulfur content in residual oil.

3.9 Conclusions

Sulfur-rich oils were analyzed with the GC-MS and FTICR-MS after isolating sulfur-rich

fractions from each oil by utilizing liquid chromatography with silver nitrate impregnated silica

gel. Sulfur enriched fractions were collected from the utilization of silver nitrate. However, high

molecular weight OSC that had several sulfur atoms (> S4) were likely retained in the silver

nitrate column and were not eluted with organic solvents. Method development on this technique

is discussed and further optimized in Chapter 4.

The whole oils which were most enriched in sulfur were oils from Rozel Point and

Jianghan Basin. Both oils showed molecules which were composed of up to S5 in sulfur class

and carbon number peaks at C20, C30 and C40 as well as high intensity peaks at double bond

equivalent (DBE) 5, 7, 9 and 13. These results indicate that organic matter sulfurization occurred

intramolecularly as up to five sulfur atoms were incorporated within a molecule. Possible

organosulfur compound structures that match results from FTICR-MS analysis include sulfurized

steranes, hopanes (C26–C34) and carotenoids (C40) (French et al., 2015).

Many factors facilitate sulfur incorporation reactions into organic matter. From the GC-

MS and FTICR-MS findings, it is hypothesized that factors which encourage sulfurization

processes include anoxic hypersaline environments, low thermal maturity, organic matter input

from organisms which are structurally comprised of steroids, hopanoids and carotenoids, and low

to moderate biodegradation exposure. These conditions provide guidance towards the variables

needed to sulfurize carbon-rich biomass and form water soluble organic molecules for storage

into shallow saline aquifers. Lab sulfurization experiments on lipids such as squalene and β-

carotene are discussed in Chapter 6.

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Chapter Four: Sulfur Species Fractionation

4.1 Introduction

Apart from utilizing sulfurization reactions on biomass waste material to form organic

sulfur compounds, another method to identify the putative chemical species that meet the goals

of the project is to isolate sulfur compounds that are already present in sulfur-rich oils (Fig. 4.1).

Sulfur-rich fractions can be extracted from crude oil, then oxidation reactions can react with

sulfur compounds to form biologically refractory water soluble organic molecules. The various

sulfur compounds in oils present models for organic compounds that could be used as AVECS

targets for synthesis. There are several varieties of sulfur compounds in oil–some are classified

as reactive sulfides as these types of sulfur compounds are corrosive and damage metallic

refinery equipment at elevated temperatures (240–380 °C). While non-reactive sulfur compounds

are considered noncorrosive and commonly make up to 2/3 of the total sulfur content in sulfur-

rich oils (Fig 4.2) (Lobodin et al., 2015).

Liquid chromatography methods in the literature (Wei et al., 2012) utilize activated silver

nitrate impregnated silica gel, however, this method did not work in a dry climate (Calgary,

Canada) as the silica gel became very reactive and held onto most components including the

desired sulfur-rich fraction. Therefore, this chapter discusses the method development process

for optimizing the use of silver nitrate impregnated silica gel, to extract and isolate reactive and

non-reactive classes of sulfur compounds, under low humidity conditions.

Figure 4.1 AVECS pathways to determine organic compounds which have potential to

form biologically refractory water soluble organic molecules. Pathway 1 refers to utilizing

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sulfurization reaction on organic biomass waste and pathway 2 refers to isolating sulfur-

rich fractions from sulfur-rich oils and analyzing the S containing compounds as models

for AVECS molecules.

4.2 Reactive and Non-Reactive Sulfur Compound Classes

There are various sulfur compound structures in crude oil and the molecular weight of

these complex OSC range from 600 to 4000 Daltons (Adam et al., 1993). Some examples of

reactive organic sulfur compounds include thiolanes, disulfides (RSSR) and thiols (RSH) (Fig.

4.2). Furthermore, Giles et al. (2017) describes reactive OSC as molecules comprised of at least

one redox active sulfur atom, or sulfur-containing functional group, and has the potential to

oxidize or reduce other biomolecules. Thiols, also known as mercaptans, constitute a small

fraction of total S in crude oils and have a low molecular weight and low boiling point (<200

°C), as thiols are typically smaller sulfur compounds comprised of less than 8 carbon atoms

(Lobodin et al., 2015). Reactive OSC also include acyclic and cyclic sulfides. Acyclic sulfides

are open chain compounds such as dibutyl sulfide, while cyclic sulfides connect to form a ring

and form OSC such as thiolane and thiane. Acyclic and cyclic sulfides are also low in molecular

weight, but sulfides and disulfides with alkyl groups have higher molecular weight and boiling

point. Aliphatic sulfides constitute a greater fraction in sulfur-rich oils compared to mercaptans

(Gogoi and Bezbaruah, 2002).

Non-reactive sulfur compounds are aromatic compounds with more structural

complexity, higher molecular weight and boiling point. Due to these characteristics, non-reactive

sulfur compounds are the most recalcitrant types of OSC (Gogoi and Bezbaruah, 2002).

Generally, it is observed that the greater the molecular weight and complexity of an aromatic

OSC or PASH, the more biodegradation resistant the compound is. Examples of non-reactive

sulfur compounds include benzothiophene, dibenzothiophene and other PASH (Fig. 4.2 and Fig.

4.3).

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Figure 4.2 Sulfur compound structures and reactivity classification. (Modified after

Lobodin et al., 2015)

Figure 4.3 Polycyclic aromatic sulfur heterocycles commonly found in petroleum (PASH)

(Wang and Stout, 2007)

4.2.1 Fractionation Method

One method for separating sulfur compounds from crude oil is known as ligand exchange

chromatography (LEC). This method uses metals that have affinity for sulfur such as silver

(Ag+), Palladium (Pd2+) and Zinc (Zn2+) (de Menezes et al., 2016). The metal is adsorbed onto a

stationary silica gel phase where sulfur-rich fractions are eluted with solvents with increasing

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eluent strength (Lobodin et al., 2015a). Wei et al.(2012) utilized liquid chromatography on

silver nitrate impregnated silica gel and showed successful separation of sulfur compounds into

mercaptans, sulfides and aromatic sulfur compounds. Silver nitrate impregnated silica gel is

commonly used to separate olefins compounds, but it has also been used to separate classes of

polycyclic aromatic sulfur heterocycles (PASH) (Wei et al., 2012; de Menezes et al., 2016).

Therefore, this method was adapted in this chapter to separate and identify sulfur compounds in

sulfur-rich oils. However, several issues arose with this method as the silver nitrate impregnated

silica gel was overactive and retained both sulfur and non-sulfur containing compounds. It is

hypothesized that the amount of silver nitrate used and heat activated silica gel technique by Wei

et al. (2012) did not accommodate low humidity conditions in Calgary, Canada. This chapter

discusses the method development processes, including adjustments made to the column design,

sample input and solvents, which were implemented to optimize liquid chromatography on silver

nitrate impregnated silica gel for use in low humidity environments to fractionate reactive and

non-reactive sulfur classes from sulfur-rich oils.

4.3 Liquid Chromatography on Silver Nitrate Impregnated Silica Gel

Silver-ion liquid chromatography is a relatively inexpensive and simple technique that

was originally used for separating different classes of lipid compounds. However, this technique

has been adapted to separate various classes of sulfur compounds in crude oil such as aromatic

sulfur compounds, sulfides, disulfides and mercaptans (Poole, 2003). Lobodin et al.(2015)

demonstrated formation of stable charged complexes between organic sulfur compounds with

silver cations. Moreover, cyclic sulfides, disulfides and mercaptans form even stronger

complexes with silver cations compared to aromatic sulfur compounds (Wei et al., 2012;

Lobodin et al., 2015b). The silver ions interact with unsaturated organic compounds through

forming reversible charge-transfer complexes between silver ions (electron acceptor) and double

bonds in unsaturated compounds (electron donor). Silver-ion chromatography techniques are

well established in planar arrangement or in silver-ion thin layer chromatography (TLC),

however the use of conventional liquid chromatography using silver-ions in a silica gel column

requires more experimentation (Holčapek, 2017). There are several factors that influence the

retention of double bond rich organic compounds, such as the overall molecular structure of the

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organic compound, number of double bonds, distance between double bonds, amount of silver

ions present in stationary phase and the choice of mobile phase (Holčapek, 2017). Furthermore,

the stability of the complexes increase as more double bonds interact with silver ions (Poole,

2003). However there are other complexities that influence the stability of complex bonding

between silver ions and double bonds in the complexed organic molecule. For example,

increasing chain length of a compound decreases complex stability, while cis isomers form

stronger complexes compared to trans isomers.

Sulfur content typically increases in the order of the following crude oil fractions:

saturated hydrocarbons < aromatic hydrocarbons < resins < asphaltenes (Gogoi and Bezbaruah,

2002). To extract sulfur-rich fractions from crude oil, saturated hydrocarbons are first removed,

through liquid chromatography using silver nitrate impregnated silica gel. Most non-sulfur

containing saturated hydrocarbons pass through the silver-ion column unimpeded, while sulfur

compounds are adsorbed onto the silver nitrate impregnated silica gel due to the strong affinity

between silver ions and double bonds in sulfur compounds. Once non-sulfur containing

hydrocarbons are removed, high eluent strength solvents are used to separate different sulfur

compound class fractions. The silver ions embedded in the silica gel, the stationary phase, form

strong bonds with reactive sulfidic compounds, followed by non-reactive (aromatic) sulfur

compounds and strongest bonds with mercaptans (Holčapek, 2017). Therefore, solvents with

increasing polarity and eluent strength were required to elute the strongly retained sulfur

compounds. Although silver-ion liquid chromatography is relatively simple to set up and can

present good separation (Wei et al., 2012), this technique, however, is seldom used due to

drawbacks such as poor reproducibility and leakage of silver ions into mobile phase (Holčapek,

2017). Many variables from the sulfur fractionation method by Wei et al.(2012) were adjusted

and the method development process is discussed below.

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Figure 4.4 Interaction and bonding between silver ions and double bonds. The complexes

between the silver-ion and double bond are a type of charge-transfer mechanism. The

unsaturated compound donates an electron to the silver ion and results in the formation of

a sigma bond between the orbitals of the double bond and silver ion. Ag+ represents silver-

ions. (Modified after Nikolova-Damyanova, 2018).

4.3.1 Experiment Design by Wei et al. (2012)

The liquid chromatography procedure using silver nitrate impregnated silica gel by Wei

et al. (2012), to generate a sulfur-rich fraction was followed closely with two exceptions. (1)

Sulfur-rich oils were not spiked with deuterated diamondoids and thiaadamantane internal

standards , as the purpose of the study by Wei et al. (2012) was to determine presence of

thiadiamondoids (indicative of thermochemical sulfate reduction) in oils, which is not a focus in

this research of separating different classes of sulfur compounds. (2) Silica gel was not activated

at 225 °C for 16 hours and silver nitrate impregnated silica gel was not activated at 105 °C for 3

hours. Due to low humidity weather conditions in Calgary, Canada, non-activated silica gel was

already dehydrated and ready for use. Heating silica gel in past experiments caused over

activation and retention of important compounds in the column despite continuous elution. In

liquid chromatography on silver nitrate impregnated silica gel experiments conducted by Wei et

al. (2012), silica gel was activated following the above conditions as humidity levels Texas, USA

are greater than Calgary and may require silica gel activation for optimal function.

For each column, 300 mg of silver nitrate impregnated silica gel (10 wt% AgNO3) was

loaded into a 146 mm Pasteur pipette column that was plugged with small amounts of cotton

wool. The rest of the column was filled with 400 mg of silica gel (Aldrich, pore size 60A, 220-

440 mesh, particle size, 35-75um). About 50 mg of whole oil from the Athabasca oil sands (4.0

wt% S) was weighed and loaded on top of the silica (Fig. 4.5). Due to the polarity of silica gel,

non-polar components tend to elute first during chromatography. To obtain the sulfur-rich

fractions, samples were eluted with hexane (3 mL), dichloromethane (DCM) (8 mL) and acetone

(2 mL) which eluted fractions S1, S2 and S3 respectively. The S1 fraction should contain non-

sulfur containing saturated hydrocarbons, S2 are non-reactive aromatic sulfur compounds and S3

are the reactive sulfidic compound class. The reactive sulfur compounds are eluted last because

Ag+ ions form strongest complexes with sulfides. Cyclic and acyclic sulfides are eluted with

acetone, as acetone forms an even stronger complex with Ag+.

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Figure 4.5 Silver nitrate impregnated silica gel column design following methods by Wei et

al. (2012). The S1 fraction (saturated hydrocarbons) was eluted with 3mL of hexane,

followed by 8 mL DCM eluted the S2 fraction (non-reactive OSC), and lastly the S3

fraction (reactive sulfides) were eluted with 2 mL of acetone.

4.3.2 Materials

Analytical grade solvents used in this experiment include n-hexane (C6H14),

dichloromethane (CH2Cl2) and acetone (C3H6O) and were purchased from VWR and Fisher

Scientific. Silica gel (60 Å, 220-440 mesh, 35-75 μm), silver nitrate (ACS reagent, >99.0%) were

purchased from Sigma-Aldrich. Sulfur-rich crude oil sample is from Athabasca oil sands (4.0

wt% S) (Alberta, Canada).

4.3.3 Results and Discussion

The silver ion column experiment following the design and procedures by Wei et al.

(2012) appeared fairly dark even after elutions with hexane, DCM and acetone (Fig. 4.5). The

dark column suggests the presence of strongly retained compounds, or the amount of Athabasca

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whole oil (50 mg) loaded into the column was excessive and did not result in proper

compound class separations. Furthermore, the reactive sulfidic fraction (S3), which was

obtained from 2 mL of acetone eluent, appeared cloudy and white crystal-like precipitate formed

when the fraction (S3) was concentrated to 500 μl (Fig. 4.6). The precipitate which formed could

not be redissolved in acetone nor DCM. To remove the precipitate, prior to FTICR-MS and GC-

MS analysis, most of the S3 fraction could be dissolved with toluene except for the precipitate.

Therefore, the dissolved portion (in toluene) was filtered with a glass wool column (Fig. 4.6), the

precipitate was successfully filtered out in the glass wool and was only soluble in methanol. It

was hypothesized that the precipitate is possibly silver chloride and formed due to leakage of

silver ions.

To confirm whether the white precipitate was associated with the silver impregnated

silica gel, two blank columns were prepared. One was filled only with silica gel, while the other

column followed the same silver-ion column design by Wei et al (2012) except whole oil sample

was not loaded at the top. The same solvent elution order was used: 3 mL hexane, 8 mL DCM,

and 2 mL acetone for both columns. White precipitate formed in the S3 fraction which was

eluted with acetone from the silver nitrate impregnated silica gel column (Fig. 4.7). Precipitate

was not observed in any of the other fractions including those from the silica gel-only column.

According to Lobodin et al. (2015), sulfur compounds, such as mercaptans, can react with silver

ions to form insoluble salts. From the experiment results, insoluble particulates may have leaked

out of the column during elution with acetone, as silver compounds are slightly soluble in

acetone. Due to strong retention of compounds remaining in the column and the additional

measures taken to remove the precipitate, material loss and contaminants were introduced into

the samples. In summary, further method development is needed to optimize sulfur species

fractionation, remove the precipitate, and decrease the retention strength in column.

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Figure 4.6 Cloudy S3 fraction (eluted with acetone) which contained crystal-like

precipitate. Acetone was evaporated with nitrogen gas. The S3 fraction was soluble in

toluene, however the precipitate was only miscible with methanol. Therefore, the sample

was redissolved in toluene and passed through a glass wool column to remove any

particulates.

Figure 4.7 Acetone fraction from blank columns (no sample). (A) Silica gel-only column

shows no precipitate. (B) Silver nitrate impregnated silica gel column shows crystal-like

precipitate.

4.4 Method Development Process

4.4.1 Trial One

The silver nitrate column design by Wei et al. (2012) (see Fig. 4.5) was altered by

reducing the total volume of silver nitrate (10 wt%) impregnated silica gel from 300 mg to 200

mg. Furthermore, the amount of Athabasca whole oil loaded into the column was reduced from

50 mg to 20 mg to improve compound separation resolution and prevent column overload (Fig.

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4.8). In this trial, two columns were made following the design in Fig. 4.8. One column was

loaded with 20 mg of Athabasca whole oil analyte, and the other was a blank column with no oil

sample. Then, the amounts and order of solvent elutions were kept the same to retrieve fractions:

S1, S2, and S3 from hexane, DCM, and acetone, respectively.

Figure 4.8 The silver-ion column was modified with reduced volume of AgNO3

impregnated silica gel and less whole oil analyte, compared to original experiment design

by Wei et al. (2012), to improve sulfur compounds separation and prevent precipitation.

The S1 fraction was eluted first with 3 mL of hexane, followed by 8 mL of DCM which

eluted the S2 fraction, and lastly the S3 fraction was eluted with 2 mL of acetone.

Despite the changes in reducing the volume of silver nitrate impregnated silica gel and

amount of crude oil analyte in the column, insoluble precipitate formed in the S3 fraction

(acetone elution) when the fraction was concentrated with nitrogen gas. Precipitate was also

present in the acetone elution from the blank column (Fig. 4.9). The precipitate was removed

from both S3 fractions to prepare for FTICR-MS analysis, and the results showed unknowns and

contaminants in the acetone fractions. It is hypothesized that the unknowns and contaminants

were introduced into the fraction during the extra processing measures required to remove the

precipitates. Furthermore, GC-MS results of the S2 fraction (eluted with DCM) show non-

reactive aromatic sulfur compounds such as dibenzothiophenes and naphthobenzothiophenes

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(Fig. 4.10 A & B). There are also some aromatic sulfur compounds in the S3 fraction

(acetone) (Fig. 4.10 C & D), which suggests the sulfur compound separation could be improved,

as aromatic sulfur compounds are not expected to be in the S3 fraction.

A hypothesis for why aromatic sulfur compounds are present in the S3 acetone fraction

may be because there is oversaturation of silver ions in the column which has caused silver ion

leakage and precipitate occurrence (Fig. 4.9), and the silver ion impregnated silica gel may have

strongly retained other hydrocarbon compounds in addition to sulfur compounds (hence the

darkness in the column in Fig. 4.8) which resulted in mediocre separation of sulfur species

classes. Organic solvents with greater elution strength or affinity to silver ions may elute retained

compounds trapped within silver nitrate silica gel.

Figure 4.9 S3 fraction (acetone elution) from trial one method development (see Fig. 4.8 for

column design). A) Precipitate formed as fraction was concentrated using nitrogen gas. B)

White crystal-like precipitate is observed at the bottom acetone fraction from the blank

column.

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Figure 4.10 Comparison of GC-MS chromatograms. (A) Total ion chromatogram of

Athabasca sulfur-rich whole oil from S2 fraction (eluted with DCM). (B) Extracted ion

chromatogram of Athabasca sulfur-rich whole oil from S2 fraction. (C) Total ion

chromatogram of Athabasca whole oil from S3 fraction (eluted with acetone). (D)

Extracted ion chromatogram of Athabasca whole oil from S3 fraction. Non-reactive

aromatic sulfur compounds shown in extracted ion chromatograms: dibenzothiophenes

(m/z 184) (black), methyldibenzothiophene (m/z 198) (blue), dimethyldibenzothiophenes

(m/z 212)(red), naphthobenzothiophene (m/z 234) (green) and

methylnaphthobenzothiophene (m/z 248)(ye).

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4.4.2 Trial Two

In attempts to release sulfur compounds from strong complexes with silver nitrate

impregnated silica gel, additional solvents, toluene and tetrahydrofuran, were used to experiment

if retention was affected by different solvents which varied in polarity and functionalities. In

addition, the darkness observed in the silver nitrate impregnated silica gel may be due to

oxidation, as the silver nitrate silica gel section of the column typically begins to darken when

solvent is introduced into the column such as when hexane was used to pack the column and

remove air bubbles. When oxidized species are introduced into the silver nitrate column, it could

lead to strong retention that is irreversible (Holčapek, 2017). Therefore, all mobile phase eluents

(hexane, DCM, acetone, toluene and tetrahydrofuran) were prepared fresh at the beginning of the

experiment and nitrogen gas was pumped into the solvents to remove oxygen and prevent

oxidation of silver nitrate impregnated silica gel, which could reduce the effectiveness for sulfur

compound class separations. As well, aluminum foil was used to cover the exterior of the column

to minimize photo-oxidation.

According to Gvirtzman et al. (2015) and Lobodin et al. (2015), Ag+ ions form stronger

complexes with sulfidic compounds compared to aromatic sulfur compounds. Therefore,

theoretically, aromatic sulfur compounds should elute before reactive sulfidic compounds

(sulfides and disulfides). To test this theory, a silver-ion column following the same design as in

the trial one experiment (Fig. 4.8) was loaded with 1.0 mg of dibenzothiophene -2,8-

dicarbaldehyde (DBT) standard (Sigma-Aldrich) instead of whole oil sample (Fig. 4.11). The

purpose for using DBT standard in the silver-ion column was to determine if 10 wt% silver

nitrate impregnated silica gel successfully retained dibenzothiophene (an aromatic sulfur

compound) until elution with DCM, and whether the acetone fraction was free from DBT, since

sulfur compound fractionation experiments by Wei et al. (2012) and Lobodin et al. (2015)

showed aromatic sulfur compounds were eluted with DCM and sulfidic compounds were eluted

with acetone.

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Figure 4.11 1.0 mg of DBT (dibenzothiophene) standard loaded into a silver-ion column

comprised of 0.400g of silica gel and 0.200g of silver nitrate (10 wt%) impregnated silica

gel. The column was first eluted with 8.0 mL of DCM followed by 8.0 mL of acetone.

Figure 4.12 Total ion chromatograms. A) DCM fraction which shows (m/z 184) DBT peak

and B) acetone fraction indicates that DBT was eluted fully into DCM fraction.

The results from the silver-ion column loaded with DBT standard showed the DBT eluted with

DCM (Fig. 4.12A), and the acetone fraction was free of DBT standard (Fig. 4.12B).

Next, the same column design was used except with an additional column which was

loaded with 20 mg of whole oil sample (Fig. 4.13). The same amounts and types of solvents

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(DCM and acetone) were used for elution. In addition to these solvents, toluene and

tetrahydrofuran was used to experiment if these solvents had a complexing effect on Ag+ to

release sulfidic compounds and other material that is retained in the column (Fig. 4.13). Toluene

was selected as it is a good solvent for dissolving non-polar compounds and hydrocarbons.

Tetrahydrofuran is a versatile solvent that can be used to dissolve polar and non-polar

compounds and it is known to form strong complexes with certain metal ions. Also, Holčapek

(2017) indicated that a combination of chlorinated solvents such as DCM along with a small

addition of higher polarity solvents may assist in eluting compounds that are strongly retained in

the column. Use of aqueous solvents are discouraged as anions could cause silver ions to

precipitate out of the column and crude oil is also not soluble in aqueous solvents (Holčapek,

2017).

Figure 4.13 Trial two of silver nitrate impregnated silica gel column method development.

One silver-ion column (left) was loaded with 1 mg of dibenzothiophene (DBT) standard and

the other silver-ion column (right) was loaded with 20 mg of Athabasca whole oil. Each

column was eluted with four different solvents and the elutions were collected in separate

fractions. The first elution involved 8 mL of DCM, followed by 8 mL of acetone, then

toluene and lastly tetrahydrofuran (THF).

Each solvent was prepared fresh at the beginning of the experiment and the solvents were

bubbled with nitrogen to minimize oxygen concentrations which may react with silver nitrate in

the column and cause oxidation. The solvent elution order was completed as follows: DCM,

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acetone, toluene and lastly THF. 8 mL of each solvent was used as this amount eluted a

fraction or band of the analyte. Furthermore, by the eighth milliliter of added solvent, colorless

eluate fluid was observed and it indicated that a stronger affinity solvent could be used to elute

other analyte components which are more strongly adhered to the silica gel. Four separate

fractions were collected from each column (Fig. 4.13). Several minutes after the final elution

with tetrahydrofuran, the acetone fraction settled and some precipitate formed at the bottom of

the vial (Fig. 4.14). The acetone fraction, from the Athabasca whole oil column, formed a dark

brown-black precipitate which would not redissolve in acetone nor DCM. This precipitate

observation also occurred in the acetone fraction from the original experiment (Fig. 4.6) and

method development trial one (Fig. 4.9). In addition, a clear to white crystal-like precipitate

formed in the acetone fraction from the DBT loaded column. The crystal-like precipitate

appeared similar to the precipitate occurrences which were observed in the original and trial one

experiments (Fig. 4.7B and Fig. 4.9B).

Figure 4.14 Trial two sulfur fractionation elutions. Top images represent elution which

came from column on the right which contained 20 mg of whole oil. Bottom images are

from left column which was loaded with 1 mg of DBT standard. Precipitate was observed

in acetone fractions from both columns. DCM = dichloromethane, ACET = acetone, TOL =

toluene, THF = tetrahydrofuran.

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Figure 4.15 Chromatograms from the silver-ion column containing whole oil. (A) The

dichloromethane (DCM) elution shows several aromatic sulfur compounds. (B) Acetone

fraction shows some aromatic sulfur compounds, but less than the DCM fraction.

Contaminants (benzenes) and unknown compounds are observed in the toluene fraction

(C) and tetrahydrofuran fraction (D). Dibenzothiophenes (DBT), methyldibenzothiophene

(MDBT), dimethyldibenzothiophenes (DMDBT), naphthobenzothiophene (NBT),

methylnaphthobenzothiophene (MNBT).

The column loaded with Athabasca whole oil appeared dark especially in the section

where silver nitrate impregnated silica gel was located. The dark colored silica gel could be an

103

indication that a lot of material is still retained within the column, since photo-oxidation risk

was minimized with aluminum foil and oxygen was removed from the solvents with nitrogen

gas. From the chromatograms in Fig. 4.15, thiophenic sulfur compounds were most abundant in

the DCM fraction (Fig. 4.15A), but these compounds were also present in small amounts in the

acetone fraction (Fig. 4.15B). As for toluene and THF fractions, there were no detectable sulfur

compounds and only contaminants, such as alkylated benzenes, and unknowns were observed.

Therefore, it was concluded that toluene and THF were not favorable solvents to use in this

experiment.

4.4.3 Trial Three

One of the most challenging aspects of these experiments was determining the reason for

precipitate formation and how the column design could be altered to prevent silver-ion related

precipitates from leaking out of the column. There are three hypotheses as to why precipitate

forms: 1) silica gel is oversaturated with silver nitrate, 2) silver compounds are slightly soluble in

acetone and precipitates over time, or 3) chlorine ions (Cl-) from dichloromethane combine with

silver ions from the silver nitrate to form silver chloride precipitate. Since silver nitrate is slightly

soluble in acetone, silver ions could be released when acetone is introduced into the silver nitrate

impregnated silica gel, then the silver ions may combine with dichloromethane or other

haloalkane remnants in the column to form silver chloride.

To resolve these speculations, a new column design was developed to trap potential

silver-ion leakages. A thin layer of silica gel (50 mg) was arranged at the bottom of the column,

followed by a layer of silver nitrate impregnated silica gel (150 mg) over top. Silver nitrate

impregnation was decreased to 5 wt% on the silica gel to reduce the possibility oversaturation of

silver nitrate on silica gel. Lastly, 400 mg of silica gel was layered on top of the silver nitrate

impregnated silica gel (Fig. 5.5).

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Figure 4.16 Trial three column design to prevent silver-ion leakage and precipitate from

forming in acetone fraction.

Furthermore, in addition to the changes made to the column design, other changes include using

a gradual gradient of increasing solvent polarity. 20 mg of Athabasca whole oil was first eluted

with hexane to remove saturates then by DCM which eluted aromatic sulfur compounds. After

DCM elution, the solvent polarity was gradually increased until from DCM (100), DCM/Acetone

(80:20), (50:50), (70:30) and then acetone (100). Solvent was passed through the column until

the eluate was colorless. Furthermore, the column was covered with aluminum foil to minimize

photo-oxidation.

Figure 4.17 Trial three method development. A) Column design with silver nitrate

impregnated silica gel sandwiched between two layers of plain silica gel. B) Eluates starting

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from the left: Hexane, DCM, DCM to acetone following gradual polarity increase and

pure acetone fraction.

The changes in the column design and the gradual increase in solvent polarity assisted in

preventing precipitate from forming in the fractions (Fig. 4.17B). However, the column (Fig.

4.17A) still appeared dark as compounds may still be strongly retained. GC-MS analysis was

performed and key sulfur compounds, including sulfides and aromatic sulfur compounds, were

monitored using mass chromatography with target ions of m/z 134, 148, 176, 212, 234, and 248

(Fig. 4.18) to determine which eluate contained the most sulfur compounds and whether the

chromatography experiment separated compounds effectively.

The chromatograms showed the hexane fraction (Fig. 4.18B) closely resembled the

whole oil (Fig. 4.18A). The eluted fraction using DCM/acetone consists of higher molecular

weight compounds such as dibenzothiophene and methylnaphthobenzothiophene; which were

identified on the GC-MS using mass chromatography at m/z 212 and m/z 248, respectively (Fig.

4.18C). On the other hand, the pure acetone fraction eluted lower molecular weight sulfur

species, such as dibutyl sulfide and benzothiophenes identified on GC-MS using mass

chromatography at m/z 134 and m/z 146 (Fig. 4.18D). However, both the DCM/acetone fraction

and pure acetone fraction exhibited relatively low abundance of sulfur compounds. Due to the

low abundance of sulfur compounds identified in the DCM/acetone and pure acetone fractions

(Fig. 4.18C and D), it is speculated that an ample amount of material is still confined within the

column. Furthermore, the total weight of each fraction was measured to estimate how much

material is still retained in the column after elutions (Table 4.1).

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Figure 4.18 Extracted ion chromatograms (m/z 134, 148, 176, 212, 234, 248). (A) Whole oil.

(B) Hexane elution. (C) Dichloromethane (DCM) and acetone gradient fraction. (D) Pure

acetone fraction. Higher molecular weight sulfur compounds, such as dibenzothiophene

and methylnaphthobenzothiophene, are observed in the DCM and acetone gradient

fraction, while lower molecular weight sulfur compounds such as sulfides are more

dominant in the pure acetone fraction.

107

Table 4.1 Sample weights for trial three elutions. Hexane was eluted first, followed by

DCM (dichloromethane) and lastly DCM and acetone. The total input mass in the silver-

ion column was 20 mg of whole oil, the total output mass (calculated from the sum of each

fraction) was 10.7 mg. This means that the accumulation of material in the column is

estimated to be 9.3 mg.

Fraction

Output

Sample

Weight

(mg)

Input Mass

(mg)

Total

Output

Mass (mg)

Accumulation

(Input - Output)

(mg)

Hexane 4.8 20.0 10.7 9.3 DCM/Acetone 2.4

Pure Acetone 3.5

According to the accumulation calculation in Table 4.1, the total output mass was

measured to be 10.7 mg and since 20 mg of whole oil was loaded into the column, it is estimated

that 9.3 mg of sample material remains accumulated in the column. The amount of accumulation

in the column is nearly half of the loaded input mass and this amount suggests that the column is

still strongly retaining oil components within the silver nitrate impregnated silica gel, and the

weight % of silver nitrate should be further reduced from 5% to 1% to lower retention strength.

In addition, the amount of input mass (20 mg of whole oil) should also be further reduced to

prevent column overload and poor chromatographic separation of oil components.

4.4.4 Trial Four

4.4.4.1 Sulfur Compounds Standard Preparation

10 mg of each pure sulfur compound (purchased from Sigma Aldrich): thiophene (99+%),

thiolane (99+%), 1-benzothiophene (>99.0%), dibutyl sulfide (>99.0%) and dibenzothiophene

(>99.0%) were dissolved with small amounts of DCM and transferred to a 25.0 mL volumetric

flask to make a sulfur compounds standard. For the best liquid chromatography results, 10 μL of

sulfur standard was loaded into the column (Fig. 4.20), which is approximately 0.001 to 0.01ug

of each sulfur compound. It is important to store the sulfur compounds standard in the

refrigerator and to minimize the amount of light exposure on the standard. The lower molecular

weight compounds, such as thiolane and thiophenes, are highly volatile and the concentrations

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can decrease quickly with improper storage.

4.4.4.2 Method

To better understand when sulfur compounds are released with various elution solvents,

10 μL of sulfur compound standards were loaded into a slightly different column design where

25 mg of silver nitrate (1 wt%) impregnated silica gel was used in the column (Fig. 4.20). Mobile

phases started with hexane, DCM, acetone and acetonitrile with gradual increase in polarity and

eluent strength (Table 4.2). To determine the type and volume of solvent needed to elute

aromatic sulfur compounds and sulfidic compounds, every 0.5 mL eluted constituted a fraction

and was collected in GC-MS vials. In total, 60 fractions were collected, but every third fraction

was analyzed by the GC-MS. After repeating the experiment several times, it was discovered that

the bottom silica gel layer of 50 mg was unnecessary when solvent polarity was gradually

increased from hexane to acetonitrile (Table 4.2).

Table 4.2 Trial 4 elution order starts with hexane and ends with acetone/acetonitrile. The

concentration (volume/volume) for each solvent and the volume used to elute the two

different classes of sulfur compounds.

Based on the detection of the sulfur compounds standard in the GC-MS chromatograms

(Fig. 4.19), it was possible to delineate the exact amount of solvent needed to elute aromatic

sulfur compounds, cyclic and acyclic sulfur compounds. Following the solvent elution order in

Mobile Phases

(in order) Concentration

(v:v)

Volume used (mL)

Identified Compounds

Hexane 100 3 Saturated Hydrocarbons

Hexane/DCM 50:50 2

Thiophene, 1-Benzothiophene,

Dibenzothiophene

Aromatic Sulfur

Compounds

20:80 3

DCM 100 3

DCM/Acetone

70:30 1

Thiolane, Dibutyl sulfide

Sulfides (acyclic and

cyclic)

50:50 1

30:70 1

Acetone 100 3

Acetone/Acetonitrile 50:50 2

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Table 4.2, 3 mL of hexane eluted the saturated hydrocarbons, 5 mL of Hex/DCM combined

with 3 mL of DCM eluted aromatic sulfur compounds (thiophene, 1-benzothiophene (BT) and

dibenzothiophene (DBT)). The sulfides, thiolane and dibutyl sulfide, were eluted with 3 mL of

DCM/Acetone (1 mL of each concentration), 3 mL of acetone and 2 mL of acetone/acetonitrile

(50:50). Lobodin et al. (2015) discussed how sulfidic species could be eluted with acetonitrile as

this solvent also forms stronger complexes with Ag+ ions than sulfidic compounds.

(A)

110

(B)

Figure 4.19 (A) Extracted ion chromatograms showing five pure sulfur compounds that

make up the standard: thiophene, thiolane, 1-benzothiophene, dibutyl sulfide and

dibenzothiophene. (B) The sulfur compounds were identified through mass

chromatography with target ions 84, 88, 134, 146 and 184, respectively.

Figure 4.20 Trial four column design.

4.4.5 Trial Five

Following the findings from trial four, the same column design (Fig. 4.20) was used and

three columns were prepared: (1) one column was loaded with 10 μL of sulfur compounds

111

standard only, (2) one column with 5 mg of whole oil only, and (3) one column with 5 mg of

whole oil and 10 μL of sulfur compounds standard. Trial four provided clarity in the amount of

each solvent needed to elute the two different sulfur classes. The first fraction, labelled as S1,

was eluted with hexane (3 mL) should have no sulfidic nor aromatic sulfur compounds, however

this step provides a preliminary cleansing step to remove non-sulfur containing saturated

hydrocarbons. The second fraction (S2) was eluted with 5 mL of Hex/DCM combined with 4 mL

of DCM and it should contain all aromatic sulfur compounds (Table 5.2). The third fraction (S3)

was eluted with 3 mL of DCM/Acetone, 3 mL of acetone and 2 mL of acetone/acetonitrile and

should contain the cyclic sulfides (thiolane) and acyclic sulfides (dibutyl sulfide).

Figure 4.21 Left column loaded with 10 μl of sulfur compounds standard, the center

column is loaded with 5 mg of sulfur-rich whole oil from the Athabasca oil sands, and the

column on the right is loaded with 5 mg of Athabasca whole oil as well as 10 μl of sulfur

compounds standard.

GC-MS analysis of all fractions showed anticipated sulfur compound class separation

results in the column which was loaded with sulfur compounds standard only. The fractions from

this particular column, such as the S1 fraction (3 mL of hexane) showed no sulfur compounds as

expected (Fig. 4.22A). Then, the aromatic sulfur compounds (thiophene, 1-BT and DBT) were

identified in the S2 fraction (eluted with DCM/acetone gradient) (Fig. 4.22B), then thiolane and

dibutyl sulfide was identified in fraction S3 (eluted with acetone/acetonitrile gradient) (Fig.

4.22C).

112

However, in the two columns which contained whole oil, the sulfur compound

separations were not as clearly outlined. There were sulfur compounds observed in the S1

fractions, which should actually only consist of saturated non-sulfur hydrocarbons. Furthermore,

the separation between aromatic and saturated sulfur compounds were not as clear-cut as the

column loaded with sulfur compounds standard only. The current column design and solvent

ratio performs well with sulfur standards, however, when oil is involved the chromatographic

response is not as effective. This is likely due to the many highly polar compounds in crude oil

sorbing to the chromatographic substrate and affecting the retention behaviour of the column.

There were sulfur compounds observed in the S1 fraction, sulfidic compounds were found in S2

fraction, and thiolane was not observed in any of the fractions. Although the sulfur compound

class separation was not as sharp as the standard loaded column, the procedures completed in this

trial were still effective at separating aromatic from saturated sulfur compounds. The amount of

solvent used for each fraction could be adjusted to improve sulfur compound separations

involving crude oil.

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Figure 4.22 Fractions which eluted from the silver-ion column which was loaded with 10

μL of sulfur standard. (A) S1 fraction (hexane elution) show no sulfur compounds. (B)

Aromatic sulfur compounds (thiophenes, 1-benzothiophene and dibenzothiophene) were

identified in the S2 fraction (DCM/acetone gradient elution) from target ions 84, 134 and

184. (C) Sulfide compounds (thiolane and dibutyl sulfide) were identified in the S3 fraction

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(acetone/acetonitrile elution).

4.4.6 Trial Six Final Procedure

The experiment was repeated again with the same column design as seen in Fig. 4.21,

except, in this trial, the volume of each solvent was adjusted to improve sulfur compound class

separations in silver-ion columns loaded with whole oils. To prevent aromatic sulfur compounds

from eluting into the S1 fraction (should have saturated hydrocarbons only), the amount of

hexane used was reduced to 1 mL. The S1 fraction was carefully monitored as it was eluted with

1 mL to ensure that the fraction was colorless because saturated hydrocarbons are typically

colorless, while aromatic compounds have a faint yellow to brown color. Before the yellow-

brown aromatic compounds reached the cotton plug, collection of the S2 fraction immediately

began (Fig. 4.23). Then, 5 mL of hexane/DCM eluent followed by 2 mL of DCM was used to

elute fraction S2. Compared to trial 5, 1 mL less of DCM was used to prevent sulfides (the S3

fraction) from entering the S2 fraction (aromatic compounds). In summary, 1 mL of hexane was

used to elute S1 fraction, followed by 5 mL of Hexane/DCM and 3 mL of DCM was to elute the

S2 fraction. Lastly, the S3 fraction solvent volumes were kept the same as trial five (see Table

4.2 for solvent volumes and concentrations).

115

Figure 4.23 The colour of the S1 eluate was monitored to ensure that coloured aromatic

compounds do not break through in the S1 fraction (hexane eluate). This was done by

watching the movement of coloured fronts within the silver-ion column.

4.5 Analytical Methods

4.5.1 GC-MS

GC-MS settings were adjusted, from Chapter 3 Methodology, to follow GC-MS analysis

settings from Lobodin et al. (2015). The temperature program was shortened to 3 minutes at 50

°C, then temperatures increased at 10 °C/min to a final temperature of 325 °C where it was held

at this temperature for 15 minutes. These adjustments improved detection of low molecular

weight compounds with low boiling points such as thiophene and thiolane.

4.5.2 FT-MS

See Chapter 3 Methodology. APPI positive ion mode was selected to analyze OSC

fractions and generate all plots below as it has enhanced ability to recognize aromatic species

and sulfur compounds in complex organic mixtures.

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4.6.1 GC-MS Analysis

The GC-MS results from analysis of the eluates from experiment trial six showed

effective separation of sulfur compound classes in Athabasca whole oil. The S1 fraction (hexane

eluate) contained no sulfur compounds as the purpose of this step was to remove the saturated

hydrocarbons and other low boiling fractions, which were not of interest (Fig. 4.24). The S2

fraction (hexane/DCM eluate), contained the aromatic sulfur compound class which includes

DBT and 1-BT (Fig. 4.25). Lastly, the S3 fraction (acetone eluate) contained dibutyl sulfide and

thiolane (Fig. 4.26). The solvent volumes and column design effectively separated the different

sulfur compounds into non-reactive (thiophenic) fraction and more reactive (thiolane, dibutyl

sulfide) fractions when Athabasca oil was chromatographed together with calibrating sulfur

standards. The Athabasca oil used is moderately sulfur-rich (4.0 wt% sulfur). Since the silver-ion

chromatography technique was successful with the Athabasca oil, the Rozel Point oil (9.4 wt%

sulfur) and Jianghan basin oil (5.6 wt% S) was tested using the same column design and solvent

volumes in trial six, to observe if this method worked for high sulfur content oils. The GC-MS

analysis showed the separation was not as effective because small amounts of thiolane and

dibutyl sulfide, which should be in the S3 fraction, broke through into the S2 fraction. However,

the S1 fraction remains clear of sulfur compounds (see appendix A1). The sulfides may have

been introduced into the S2 fraction likely due to the high sulfur content in Rozel Point and

Jianghan oil and the presence of numerous other more polar species which sought to the column

and deactivated it allowing premature breakthrough of the desired components. Additionally, the

silver nitrate impregnated silica gel may have been oversaturated and could not complex with

sulfur. Therefore, this sulfur fractionation technique may only be suitable for oils which are

moderately rich (< 4.0 wt%) in sulfur. In future work, it would be possible to further modify the

technique to deal with more polar oils.

117

Figure 4.24 Extracted ion chromatogram of the Athabasca oil S1 fraction (hexane eluate)

oil in experiment trial 6. Saturated hydrocarbons are present and sulfur compounds were

not observed in this fraction.

118

Figure 4.25 Extracted ion chromatogram of the S2 fraction (hexane/DCM eluate) of

Athabasca oil in experiment trial 6. Aromatic sulfur compounds 1-benzothiophene (DBT)

and dibenzothiophene (DBT) are present in this fraction.

Figure 4.26 Extracted ion chromatogram of the S3 fraction of Athabasca oil in experiment

trial 6. Non-aromatic sulfur compounds, thiolane and dibutyl sulfide, are present in this

fraction.

119

4.6.2 FTICR-MS

In addition to the separation of aromatic and non-aromatic sulfur compound fractions, it

is important to determine which sulfur fraction (S2 or S3) was more enriched in sulfur species

and how the fractions compare with the whole oil. In Fig. 4.27, the compound class distribution

for Athabasca whole oil obtained by FTMS analysis show the S2 fraction and S3 fraction in

APPI positive ion mode. When comparing the fractions to the whole oil, the S2 fraction shows

the highest total ion intensity for radical S class. This indicates that this fraction is comprised of

mostly sulfides or sulfur compounds with one sulfur atom within the molecular structure. The S3

fraction shows a wider range of sulfur compound classes and less hydrocarbons. This

observation shows that the sulfur fractionation method was effective at removing saturated

hydrocarbons and eluting compounds which are enriched with up to three sulfur atoms.

Furthermore, the S2 fraction (sulfides and low molecular weight sulfur compounds) make up a

greater portion of OSC in crude whole oil compared to the S3 fraction (aromatic OSC with

multiple sulfur atoms within molecule).

Figure 4.27 FTICR-MS plot showing compound class distribution for Athabasca whole oil

(black), S2 fraction (dark grey) and S3 fraction (light grey). Relative monoisotopic intensity

(RMI) is the signal measured from a fragment ion that is made up of the most abundant

natural isotope of each atom in the molecular ion.

120

Although the extracted GC-MS chromatograms showed ineffective sulfur species

fractionation for Rozel Point and Jianghan oils (See appendix A2 to A5), the FTICR-MS plots in

Fig. 4.28 show the trial six fractionation method was effective at eluting sulfur compounds with

fewer sulfur atoms (1-3) per molecule in the S2 fraction (Fig. 4.28A), and up to five sulfur atoms

per molecule as well as mixed nitrogen-oxygen and sulfur molecules in the S3 fraction (Fig

4.28B).

Figure 4.28 FTICR-MS plot shows compound class distribution for oil fractions from Rozel

Point (red), Jianghan Basin (blue), and Athabasca oil sands (grey). (A) Fraction #2 or the

S2 fraction shows predominantly 1 to 3 sulfur atoms per molecule. (B) Fraction #3 or the

S3 fraction shows 1 to 5 sulfur atoms per molecule and also mixed nitrogen-oxygen and

nitrogen-sulfur molecules.

121

Furthermore, the FTICR-MS DBE distribution for Athabasca oil (Fig. 4.29) shows the

similarity between the whole oil and S2 fraction where component abundance peaks are

observed at DBE 6 and 9. This infers that the whole oil and the aromatic sulfur compound (S2)

fraction are enriched in benzothiophenes (DBE 6) and dibenzothiophenes (DBE 9). The S3

fraction, on the other hand, shows a right skewed distribution towards lower DBE values, which

may suggest that the S3 fraction is enriched in OSC with multiple thiolane or thiane structures.

While the carbon number species distribution for Athabasca oil (Fig. 4.30) shows a bell curve

with a small peak at C14. This peak may indicate presence of dimethyldibenzothiophenes

(C14H12S).

Figure 4.29 FTICR-MS DBE distribution for Athabasca whole oil (black), S2 fraction

(dark grey) and S3 fraction (light grey).

122

Figure 4.30 FTICR-MS carbon number distribution for Athabasca whole oil (black), S2

fraction (dark grey) and S3 fraction (light grey).

4.7 Conclusions and Future Work

I developed a revised method for separating organic sulfur compound rich oils into

various fractions using silver-ion chromatography. Liquid chromatography using silver nitrate

impregnated silica gel on sulfur-rich oils was effective at separating aromatic and non-aromatic

sulfur compounds into two different fractions (S2 and S3). This method worked particularly well

for the Athabasca sulfur-rich oil which contained less sulfur content compared to the Rozel Point

and Jianghan Basin oils. This method, however, was not as effective for oils with high sulfur

content (>5.0 wt%) as the GC-MS extracted chromatograms show presence of sulfides in the

aromatic sulfur compound fraction indicating that with more polar oils early breakthrough of

species is common in the chromatographic columns. Nonetheless, this method is still useful for

separating OSC with low sulfur atom numbers from compounds in later fractions with higher

sulfur atom numbers. Thus, though not perfect the method had some utility in comparing the

different sulfur species in oils.

Throughout the method development process, there were several drawbacks to this

separation technique which required several trials and modifications to the column design,

solvent polarity and eluate volume. One of the drawbacks included silver-ion leakage in the

123

mobile phase which occurred when solvent polarity increased abruptly. Therefore, gradual

increase in solvent the polarity following the order from hexane, dichloromethane, acetone to

acetonitrile are recommended eluents to prevent silver-ion leakage into mobile phase.

Mercaptans (R-SH) form the strongest bonds with silver-ions and future work should

include investigation of eluting an S4 fraction where mercaptans (thiols) are eluted. In the

method described by Lobodin et al. (2015), mercaptans are eluted with 6 mL of hydrochloric

acid (HCl): methanol (MeOH), then 12 mL of toluene:MeOH, followed by another 6 mL of

HCl:MeOH then lastly elution with another 12 mL of toluene. Afterwards, the top organic

toluene phase is isolated and passed through a sodium sulfite column to remove any water which

may have formed from the reaction between HCl and MeOH. The isolated mercaptans fraction

can be directly analyzed, however, mercaptan or thiol standards are needed for more accurate

detection of mercaptans using GC-MS analysis. Other future work includes expanding the scale

of the fractionations to enable large scale fractionation using larger columns and volume of oil

samples to produce sulfur-enriched fractions for oxidation reactions.

By analyzing various heavily to severely biodegraded oils from natural petroleum

reservoirs, the biodegradation resistant compounds found included: (1) aromatic sulfidic

compounds with 1 to 3 sulfur atoms, (2) non-aromatic sulfur containing compounds with one to

five sulfur atoms and (3) mixed nitrogen oxygen and sulfur compounds with up to three sulfur

atoms. If suitably functionalized with oxidation, these sulfur compounds could have enhanced

water solubility and be suitable AVECS targets for manufacture through the reaction of abundant

elemental sulfur (from the petroleum industry), with various biomass precursors such as

agricultural waste materials. Moreover, in Chapter 5, aromatic thiophenic compounds, sulfidic

compounds, and mercaptans are tested in molecular modelling modification experiments, using

computer modelling software, to test potential subsequent oxidation on sulfur compounds to

assess the types of structures which are most likely to have desirable AVECS properties of high

water solubility and low biodegradation reactivity.

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Chapter 5 Solubility and Biodegradation Rate Predictions for Model Organic Sulfur

Compounds Using Quantitative Structure-Activity Relationships (QSAR)

5.1 Introduction

During early diagenesis, H2S and polysulfides react with sedimentary organic matter

through intramolecular incorporation and commonly form thiolanes, 1,2-dithianes and

thiophenes (Kohnen et al., 1991; Schaeffer et al., 2006). It was suggested by Sinninghe Damsté

et al. (1989) that thiophenes are diagenetic products of thiolanes, as thiophenes have higher

stability compared to the other sulfur compounds (Fig. 5.1). Thiane compounds, formed from

tetra- and penta-sulfides are less stable in nature and are possibly intermediates in thiolane

formation. With lipid molecules, thiolanes form when H2S (HS-), incorporates directly into

functional groups or adjacent to multiple double bond sites, followed by cyclization and carbon

skeletal rearrangement (Fig. 5.1) (after Kohnen et al., 1991), shows thiophene compounds can be

diagenetic products of thiolanes, however thiolanes were used as the dominant model sulfur

functional group setting for the following molecular modelling modification experiments due to

its higher water solubility compared to thiophenes and thianes.

This chapter focuses on how different putative sedimentary molecular groups, lipids and

carbohydrates, respond to sulfur incorporation and potential subsequent oxidation to assess the

types of structures most likely to have desirable AVECS properties of high water solubility and

low biodegradation reactivity. Certain functional groups and double bond positions affect where

sulfur gets incorporated in an organic structure (Sinninghe Damsté et al., 1989). For instance,

model sulfurized lipids and carbohydrates were analyzed using ChemAxon and EPI suite

software to discover the interactions between functionalized organic molecules with sulfur and

how water solubility and biodegradation rates vary when oxygenated groups or sulfur are

incorporated into organic molecules. Moreover, this chapter discusses and predicts chemical

modification patterns which can be adapted to creating an ideal AVECS molecule.

The selected carbon sequestration target for AVECS molecules is 15 kg C/m3 and was

determined based on a comparison between the carbon sequestration density (160 kg C/m3) of

supercritical CO2 CCS technology (Aydin et al., 2010), and the amount of total organic carbon

(TOC) present in boiler blowdown oil sands produced water (2.4 kg/m3) (Maiti et al., 2012). If

125

AVECS molecules have a carbon sequestration potential of 15 kg C/m3, it is estimated that 6 Gt

of carbon could be sequestered into 1% of shallow saline aquifer reserves in Alberta

(approximately 400 km3) (Alberta Energy Regulator, 2019).

Figure 5.1 Formation of thiolane and thiophene through intramolecular incorporation of

polysulfides (after Kohnen et al., 1991).

5.2 Methods

A set of model organic compounds (see Table 5.1) which includes lipids, carbohydrates,

alkanes, glycerol, and long-chain hydrocarbons were selected because they act as models of

potential extracts from biomass waste material that may react with sulfur and subsequent

oxidation to create AVECS molecules. The model organic compounds were used to test and

predict the relationship between a chemical’s molecular structure and its solubility and

biodegradation resistance. The Estimation Programs Interface (EPI) Suite TM and ChemAxon

software were used to establish chemical models which allow a water solubility estimate and the

likeliness for a molecule to be biodegraded to be determined. This relationship between a

chemical’s molecular structure and its activity is known as a quantitative structure-activity

relationship (QSAR) (Tropsha, 2010).

5.2.1 EPI Suite

The EPI SuiteTM software was developed by the U.S. Environmental Protection Agency

(EPA) and it is a tool that estimates the chemical properties and environmental fate of organic

126

and inorganic chemicals which lack experimental data. The properties of interest for this training

set include water solubility and biodegradation susceptibility. These characteristics are divided

into individual modules where predicting water solubility can be run by the modules

(WATERNT) and biodegradation resistance with BIOWIN. BIOWIN estimates the probability

for an organic compound to undergo both aerobic and anaerobic biodegradation in the presence

of mixed populations of microbes. There are several different BIOWIN models but BIOWIN 3

was used in this study as it estimates the time required for complete ultimate biodegradation to

occur in a typical aquatic environment through a fragment-based method. Ultimate

biodegradation means parent compounds are broken down to carbon dioxide, water, elements or

new resistant materials. BIOWIN retrieves structure fragment constants (see Appendix A6) that

are derived from the EPA database (consisting of 200 compounds) in which biodegradation

experts measured the time required to for each compound to reach complete biodegradation. The

measured biodegradation time for each compound was used to compute a biodegradation scale

for fragments within the compounds. The fragments were rated on a scale from 1 (recalcitrant) to

5 (takes hours to biodegrade) (Fig. 5.12). If the studied molecule does not consist of any of the

36 fragments stored in the BIOWIN model library, then the only factor that is used to estimate

the biodegradation rate of the molecule is its molecular weight (EPA, 2011). The biodegradation

rank for AVECS targets is below 1 as this indicates that the molecule is recalcitrant.

The WATERNT module estimates water solubility at 25 °C through the fragment-based

method as well except WATERNT retrieves fragment constants (see Appendix A7) from the

EPA database which consists of the measured water solubility of over 6000 measured organic

compounds.

5.2.2 ChemAxon

ChemAxon was used to draw the model organic compounds to generate a simplified

molecular input line entry syntax (SMILES). SMILES or the International Union of Pure and

Applied Chemistry (IUPAC) name are two options that can be entered into the WATERNT

program. Then WATERNT program then identifies the water solubility of each atom to atom

connection based on the SMILES input. The more fragments the database recognizes, the more

accurate the estimations (EPA, 2011). After water solubility is determined, additional

127

calculations were made to convert water solubility (mg/L) to carbon solubility (kg/m3) in water.

In this research, carbon solubility is defined as the estimated amount of carbon (in kilograms)

which dissolves into a cubic meter of water at 25 °C and at atmospheric pressure (1 atm). The

carbon solubility (equation 5.2) is calculated by multiplying the weight fraction of carbon

(equation 5.1) by water solubility, then applying the mg/L to kg/m3 conversion factor of 0.001.

Carbon Weight Fraction = 12.01 (g

mol) ∗ Number of carbon atoms in molecule

Total Molecular Weight of Molecule (g

mol)

(Equation 5.1)

Carbon Solubility = (carbon weight fraction) * (water solubility 𝑚𝑔

𝐿) * (0.001)

(Equation 5.2)


5.3.1 Experiment 1 – Sulfurization and Oxidation of Lipids

From an organic geochemistry perspective, lipid structures are most likely to be

preserved in kerogens for petroleum formation, compared to carbohydrates and proteins (White,

2013). Furthermore, an abundance of sulfurized lipid compounds were discovered as molecular

markers and biomarkers in crude oils and sediments by Sinninghe Damsté et al. (1989). As well,

lipids were easily accessible in past studies for sulfurization experiments and sulfurized products

were GC amendable due to their relatively low molecular weight (<800 Da) and non-polar nature

(Kohnen, 1991). Kohnen et al. (1993) and Sinninghe Damsté et al. (1989) both agree the

locations of C-S bonds in sulfurized lipid compounds are related to specific positions of double

bonds and functional groups in precursor molecules. Typically lipid precursors which possess

double bonds allow accessibility for sulfur incorporation especially when two double bonds are

separated by (CH2)n where n= 0–3 (Fig. 5.1). See appendix A1 for discussion.

Using the process described above as a guideline for lipid sulfurization, two thiolanes

were added to the double bonds within squalene (Fig 5.2 A) to simulate the general process of

sulfurization into unsaturated lipid precursors as suggested by Sinninghe Damsté al. (1989).

128

There were two suitable locations for the thiolane sulfur placement in squalene as shown by

Schouten et al. (1994). Afterwards all remaining double bonds were removed to simulate natural

processes which includes double bond reductions to accommodate sulfur and hydrogen atoms

(Libes, 2009). Sulfurized squalene (Fig 5.2 B) was oxidized to form sulfoxides (Fig 5.2 Bi) and

sulfones (Fig 5.2 Bii). The weight fraction of oxygen and carbon of each modified molecule was

plotted against carbon solubility to understand how increasing the carbon number or oxygens in a

molecule would affect solubility of carbon (Fig. 5.2a). Since adding oxygen atoms typically

increases molecular polarity and water solubility, it was anticipated that molecule Bii would

exhibit the highest water solubility. Surprisingly, molecule Bi, with two thiolan-1-one groups

incorporated into squalene, responded with highest estimated water solubility. The optimum

atomic ratio for increased carbon solubility for squalene is AO:C = 2:30 (see Table 5.1, Bi).

Figure 5.2 Sulfurization and oxidation of squalene model compounds. (A) Squalene. (B)

Sulfur incorporation into squalene results in the formation of two thiolanes. (Bi)

Subsequent oxidation forms sulfoxide groups. (Bii) The most oxidized state (two sulfone

groups) of the sulfurized squalene model compound.

Kohnen et al. (1993) and Kok et al. (1993) discovered strong preference for sulfur

incorporation into steroidal compounds. In the study by Kohnen et al. (1993), various

methylthio-cholestane isomers were discovered in organic sulfur-rich sediment and in crude oils

from the Rozel Point and Jianghan Basin. Furthermore, Kok et al. (1993) identified sulfurized

sterols in sediments from Ace Lake, Antarctica which may have formed from the replacement of

a steroidal ketone or hydroxyl group, at the C-3 position of stanones or stanols, by a thiol group

(Fig. 5.3). In addition, Lu et al. (2013) suggested the double bonds located on the cyclohexane or

cyclopentane rings of certain steroid compounds react with inorganic sulfur species to form

thiolanes, thiophenes or thianes.

129

Figure 5.3 Hypothesized pathway for forming sulfurized steroids in Ace Lake Sediments.

Inorganic sulfur species react with both 5a-stan-3-ones and 5B-stan-3-ones to form

sulfurized steroids. Furthermore, the transformation from stanones to stanols is a

reversible process. (After Kok et al., 2000).

Based on above interpretations for steroid sulfurization, cholesterol (Fig. 5.4 C), a type

of steroid compound, was modified to form two sulfurized steroid molecules (Fig. 5.4 D) and

(Fig. 5.4 E). The thiol group on molecule D (Fig. 5.4) was oxidized to sulfonate (Fig. 5.4 Di).

However, highest carbon solubility (Fig. 5.5b) was achieved with molecule Ei (Fig. 5.4) where it

is composed of one sulfonate and one sulfone group. The oxygen to carbon atomic ratio for

molecule Ei is Ao:c = 4:27 and the carbon solubility is 0.0956 kg C/m3 (see Table 5.1).

Although the carbon solubility increased by a factor of over 2 000 000 from molecule E

to molecule Ei due to the oxidation additions, the carbon solubility is much below AVECS target

solubility of 15 kg C/m3. Furthermore, the aerobic biodegradation rank of sulfurized lipids is

1.87, which means that it will take several months for such compounds to biodegrade. The sulfur

to carbon atomic ratio (AS:C) = 27:2 (Table 5.1) improved the biodegradation rank of cholesterol

(2.08) to model compound Ei (1.87). The ideal AVECS biodegradation rank is less than 1, as this

indicates that the molecule is recalcitrant. In summary, sulfurized and oxidized steroid

compounds may not be a feasible pathway to produce water-soluble and biodegradation resistant

AVECS molecules. Other model compounds with a greater water solubility as a starting base

may be a better suited for sulfurization and oxidation modifications.

130

Figure 5.4 Sulfurization and oxidation of steroid model compounds. (C) Cholesterol. (D)

Sulfur incorporation into hydroxyl group. (Di) Addition of a sulfonate group after

oxidation. (E) Sulfur incorporation into hydroxyl group and the formation of thiolane

through double bond reduction. (Ei) Subsequent oxidation forms sulfonate and sulfoxide

groups. (Eii) The most oxidized state of the sulfurized cholesterol model compound

includes sulfonate and sulfone groups.

131

Table 5.1 The molecular formula and weight fraction of each model compound and the

corresponding estimated water solubility, carbon solubility and biodegradation rank (0 -5).

Degradation time for biodegradation rank values: 3.25 – 5.00 = days to hours, >2.75 - 3.25

= weeks, >2.25 - 2.75 = weeks to months, >1.75 - 2.25 = months, <1.75 = recalcitrant. The

target carbon solubility for AVECS molecules is 15 kg C/ m3 and the target biodegradation

rank is <1.75. The best model compounds within each category (lipids, carbohydrates,

alkanes, water soluble compounds, and insoluble hydrocarbons) are highlighted in yellow

as they show greatest carbon solubility and most biodegradation resistance compared to

the other molecules within the same category.

132

Model Compounds Number of atoms / molecule

Molecular Weight

Weight Fraction Water

Solubility

Carbon Solubility

Biodegradation

Rank

C H O S Total g/mol C H O S Total (mg/L) (kg C/m3) (0 - 5)

Lip

ids

A 30 50 0 0 30 410.71 0.88 0.12 0.00 0.00 1.00 6.64E-10 5.82E-13 B 30 58 0 2 90 482.91 0.75 0.12 0.00 0.13 1.00 4.83E-07 3.60E-10 Bi 30 58 2 2 92 514.90 0.70 0.11 0.06 0.12 1.00 0.00032 2.24E-07

Bii 30 58 4 2 94 546.90 0.66 0.11 0.12 0.12 1.00 0.00002087 1.37E-08 C 27 46 1 0 74 386.65 0.84 0.12 0.04 0.00 1.00 0.00361 3.03E-06 2.08

D 27 46 0 1 74 402.71 0.81 0.12 0.00 0.08 1.00 2.87E-05 2.31E-08 Di 27 46 3 1 77 450.71 0.72 0.10 0.11 0.07 1.00 0.554 0.00040 E 27 46 0 2 75 434.78 0.75 0.11 0.00 0.15 1.00 5.07E-05 3.78E-08 Ei 27 46 4 2 79 498.78 0.65 0.09 0.13 0.13 1.00 147.08 0.0956 1.86

Eii 27 46 5 2 80 514.77 0.63 0.09 0.16 0.12 1.00 37.64 0.0237 F 18 39 2 0 59 287.50 0.75 0.14 0.11 0.00 1.00 0.099 0.000074 3.25

G 18 34 2 1 55 314.52 0.69 0.11 0.10 0.10 1.00 0.022 0.000015 Gi 18 34 3 1 56 330.52 0.65 0.10 0.15 0.10 1.00 3.4 0.0022 Gii 18 34 4 1 57 346.52 0.62 0.10 0.18 0.09 1.00 0.884 0.00055

Car

bo

hyd

rate

s

H 5 10 5 0 20 150.13 0.40 0.07 0.53 0.00 1.00 1.00E+06 399.93 3.50

Hi 15 22 9 1 47 378.39 0.48 0.06 0.38 0.08 1.00 3223 1.53 2.92

I 5 10 5 0 20 150.13 0.40 0.07 0.53 0.00 1.00 1.00E+06 399.93 Ii 15 22 9 1 47 378.39 0.48 0.06 0.38 0.08 1.00 3223 1.53 J 5 10 5 0 20 150.13 0.40 0.07 0.53 0.00 1.00 1.00E+06 399.93 Ji 15 22 9 1 47 378.39 0.48 0.06 0.38 0.08 1.00 3223 1.53

Alk

anes

K 20 40 1 0 61 296.53 0.81 0.14 0.05 0.00 1.00 0.01075 8.71E-06 2.70

L 20 36 0 1 57 308.56 0.78 0.12 0.00 0.10 1.00 0.000172 1.34E-07 Li 20 36 2 1 59 340.56 0.71 0.11 0.09 0.09 1.00 0.0325 2.29E-05 M 20 40 0 1 61 312.59 0.77 0.13 0.00 0.10 1.00 0.000285 2.19E-07 Mi 20 40 1 1 62 328.59 0.73 0.12 0.05 0.10 1.00 0.04403 3.22E-05 2.47

Mii 20 40 2 1 63 344.59 0.70 0.12 0.09 0.09 1.00 0.01145 7.98E-06

Wat

er

Solu

ble

s (G

lyci

ne)

N 3 8 3 0 14 92.09 0.39 0.09 0.52 0.00 1.00 1.00E+06 391.16 O 3 8 2 1 14 108.16 0.33 0.07 0.30 0.30 1.00 1.00E+06 333.07 Oi 3 8 5 1 17 156.15 0.23 0.05 0.51 0.21 1.00 1.00E+06 230.70 P 3 8 1 2 14 124.22 0.29 0.07 0.13 0.52 1.00 36957 10.72 Pi 3 8 7 2 20 220.22 0.16 0.04 0.51 0.29 1.00 1.00E+06 163.59 Q 3 8 0 3 14 140.29 0.26 0.06 0.00 0.69 1.00 428.62 0.11 Qi 3 8 9 3 23 284.28 0.13 0.03 0.51 0.34 1.00 1.00E+06 126.73 3.14

Insoluble

HC

R 30 62 0 0 92 422.81 0.85 0.15 0.00 0.00 1.00 4.23E-07 3.60E-10 S 30 60 0 1 91 452.86 0.80 0.13 0.00 0.07 1.00 4.53E-07 3.60E-10 Si 30 60 1 1 92 468.86 0.77 0.13 0.03 0.07 1.00 4.69E-07 3.60E-10

133

Figure 5.5 Weight fraction of oxygen and carbon and the influence on carbon solubility for

derivative lipid molecules (kg C/m3). Increasing carbon solubility is indicated by the

increased bubble size. See Table 5.1 for carbon solubility values for modified compounds:

squalene (Bi, Bii), b) cholesterol (Di – Eii), c) linolenic acid (F-Gii).

With linolenic acid (Fig. 5.6 F), Sinninghe-Damsté et al. (1988) showed sulfur

incorporation occurred between the double bonds of a di-unsaturated fatty acids to form a

thiolane or thiophene. Although linolenic acid is a tri-unsaturated fatty acid, only one thiolane

ring can form. Currently, there are no studies that show the formation of an OSC through H2S or

polysulfide incorporation with saturated chain carboxylic acids, which is why the extent of

sulfurizing linolenic acid is the formation of one thiolane related to the mid-chain double bonds

(Fig. 5.6 G). Similarly to squalene, improvement in water solubility (Table 5.1) was observed

with the addition of a sulfoxide group (Fig 5.6 Gi) compared to the addition of a sulfone group

Bii

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

0.20

0.00 0.20 0.40 0.60 0.80 1.00

Wei

ght

Fra

ctio

n o

f O

xyge

n

Weight Fraction of Carbon

Squalene

Cholesterol

Linolenic Acid

Gii

Eii

Ei

Gi

F

GDi

Bi

E

C

(hypothetical)

T 30 56 0 3 89 512.96 0.70 0.11 0.00 0.19 1.00 5.13E-07 3.60E-10 Ti 30 56 3 3 92 560.95 0.64 0.10 0.09 0.17 1.00 0.00641 4.12E-06 U 30 50 0 6 86 603.10 0.60 0.08 0.00 0.32 1.00 6.03E-07 3.60E-10

Ui 30 50 6 6 92 699.10 0.52 0.07 0.14 0.28 1.00 2.35E+05 121.10 1.65

V 60 122 0 0 182 843.60 0.85 0.15 0.00 0.00 1.00 8.44E-07 7.20E-10

W 60 110 0 6 176 1023.89 0.70 0.11 0.00 0.19 1.00 1.02E-06 7.20E-10

WI 60 110 6 6 182 1119.89 0.64 0.10 0.09 0.17 1.00 1.19E-06 7.66E-10

X 60 100 0 11 171 1174.14 0.61 0.09 0.00 0.30 1.00 1.17E-06 7.18E-10

Xi 60 98 12 12 182 1396.18 0.52 0.07 0.14 0.28 1.00 3.45E+04 17.8 0.11

134

(Fig. 5.6 Gii). Out of the three lipid model compounds (squalene, cholesterol and linolenic acid),

sulfurized and oxidized cholesterol (Fig 5.4 Ei) exhibited highest carbon solubility followed by

linolenic acid (Fig 5.5 Gi), and squalene (Fig 5.2 Bi) which showed negligible carbon solubility

(Table 5.1). The lipid model compound modifications with greatest carbon solubility are plotted

in Fig. 5.3.

Figure 5.6 Sulfurization and oxidation of linolenic acid model compounds. (F) Linolenic

acid. (G) Sulfur incorporation into double bonds to form thiolane. (Gi) Oxidation results in

the addition of a sulfoxide group. (Gii) Subsequent oxidation forms sulfone group, which is

the most oxidized state of the sulfurized linolenic acid model compound.

Figure 5.7 Weight fraction of carbon and oxygen to carbon solubility for sulfurized and

oxidized squalene (Bi), cholesterol (Ei) and linolenic acid (Gi) model compound

modifications.

135

Table 5.2 Sulfurized and oxidized cholesterol exhibits highest carbon solubility (0.0965 kg

C/m3), followed by linolenic acid derivatives (0.0022 kg C/m

3). Squalene species show

negligible carbon solubility (2.24E-07 kg C/m3).

Molecule Description Carbon solubility

(kg C/m3) Bi sulfurized and oxidized squalene 2.24E-07 Ei sulfurized and oxidized cholesterol 0.096 Gi sulfurized and oxidized linolenic acid 0.0022

5.3.2 Experiment 2 – Sulfurization and Oxidation of Sulfurized Carbohydrates

Carbohydrates are the most abundant group of bio-organic compounds in living

organisms and commonly make up to 50% of the dry weight in organic matter in the biosphere

(van Dongen, 2003). All living organisms utilize carbohydrates for metabolic needs, which is

why carbohydrates were not believed to be well preserved in substantial amounts in sediments.

However, van Dongen et al. (2003) showed carbohydrates have the potential to be preserved

through sulfurization and this reaction may be an important pathway for preserving organic

matter in sediments. Usually, a small fraction of organic matter (0.1–1%) escapes

remineralization by microorganisms and enters the geosphere (van Dongen et al., 2003). Over

geological time, this small fraction results in the accumulation of carbon material in the

subsurface which makes up the largest pool of organic carbon on earth (van Dongen et al., 2003).

In the carbohydrate sulfurization study by van Dongen et al. (2003a), the researchers

attempted to sulfurize arabinose, lyxose, and xylose (See Fig. 5.8 H, I, J, respectively), which

are monosaccharides, the simplest form of carbohydrates, commonly found in aquatic and

terrigenous organisms. Their reaction mixtures did not reveal any GC amenable products after

sulfurization so they thought sulfurization produced high molecular weight OSC. In an attempt to

identify the OSC structures, van Dongen et al. (2003a) were able to identify thioacetates and

acetylated hydroxyl groups which formed after methyllithium/methyl iodide and alditol acetate

treatments. Their results showed the three most abundant OSC that formed (Fig 5.8 Hi, Li and

Ji), which were acetylated monosaccharides with one sulfur atom that replaced the oxygen

originally at position one. van Dongen et al. (2003a) concluded that monosaccharides can be

136

sulfurized with reduced inorganic species reacting preferentially with carbonyl functional

groups, however hydroxyl groups were relatively inert. Schouten et al. (1993) also investigated

the reactivity of hydroxyl groups with sulfur and determined that hydroxyl groups are inert and

do not incorporate sulfur unless the hydroxyl groups dehydrate (prior to sulfurization) and form

double bonds, which do react with inorganic sulfur species (Schouten et al., 1993b).

Figure 5.8 Monosaccharides: arabinose (H), lyxose (I), and xylose (J) and corresponding

sulfurized products (Hi, Ii, Ji) which formed in the carbohydrate sulfurization experiments

by van Dongen et al. (2003).

Additional molecular modifications were not applied on carbohydrate OSC (Figure 5.8

Hi, Li and Ji) as these molecules were observed as sulfurized products from carbohydrate

sulfurization experiments by van Dongen et al. (2003a). However, EPI suite was used to estimate

and compare the carbon solubility of monosaccharides with the sulfurized products which

underwent sulfurization and alditol acetate treatment. Since the monosaccharides are isomers,

EPI suite was not able to detect any differences in solubility based on the stereochemistry of

molecules. Therefore the monosaccharides (H, I, and J) showed the same solubility (399 kg

C/m3 and the sulfurized carbohydrates (Hi, Ii, and Ji) also showed the same carbon solubility

(1.53 kg C/m3) (see Fig. 5.9).

137

Figure 5.9 Pentose monosaccharides (H, I, and J) show higher carbon solubility (399 kg/m3)

compared to sulfurized carbohydrates (Hi, Ii, and J) with carbon solubility of 1.53 kg/m3.

In Figure 5.9, it is observed that monosaccharides have much higher carbon solubility

and the oxygen to carbon atomic ratio for pentose monosaccharides is AO:C = 5:5. As for

sulfurized carbohydrates the atomic ratio is AO:C = 9:15. It appears that when the atomic ratios

(AO:C) are near 1:1, where the number of carbon atoms and oxygen atoms are near equivalent in a

molecule, increased carbon solubility is observed. Furthermore, the carbon solubility for

sulfurized carbohydrates is 1.53 kg C/m3 and that is closer to AVECS targets of 15 kg C/m3

compared to utilizing sulfurized lipids as model compounds, which had an estimated carbon

solubility of 0.095 kg C/m3. However, the estimated biodegradation rank for sulfurized

carbohydrates is 2.92 (see Table 5.1), which means that these compounds would likely degrade

in a matter of weeks. The sulfur to carbon atomic ratio for sulfurized carbohydrates is AS/C: 1:15

and the addition of sulfur improved the biodegradation rank from 3.50 (monosaccharides) to 2.92

(sulfurized carbohydrates). The lower the biodegradation rank, the more biodegradation resistant

the compound is.

5.3.3 Experiment 3 – Sulfurization and Oxidation of Isoprenoids

C20 isoprenoid thiophene structures are abundant and widespread in recent and ancient

marine sediments (Sinninghe Damsté et al., 1988). The occurrence of this compound was

explained by Brassell et al. (1986) who hypothesized sulfur was incorporated into phytol or

138

phytadiene through intramolecular processes to form alkyl thiophene structures (Fig. 5.10).

Sinninghe Damsté et al. (1987) also explained that sulfurization typically occurred at specific

positions with double bonds or functional groups within the precursor molecule and form OSC

structures in isoprenoids.

Figure 5.10 Inorganic sulfur species incorporate into phytol and phytadiene to form sulfur

bounded phytane derived structures (van Dongen, 2003).

The intramolecular sulfurization approach for isoprenoids (Fig. 5.10) identified by

Sinninghe Damsté et al. (1988) and Brassell et al. (1996) was used as a guide for molecular

modifications to phytol (Fig. 5.11 K) to create thiophene (Fig. 5.11 L) and thiolane (Fig. 5.11 M)

OSC structures. Since sulfurized isoprenoids with thiolanes are slighlty more soluble than

thiophenes (Fig. 5.12), the focus was placed on improving the solubility of the isoprenoid

thiolane (Fig. 5.11 M) through oxidation to create sulfoxide (Fig. 5.11 Mi) and sulfone groups

(Fig. 5.11 Mii) (Fig. 5.13). The modification results show the best combination to improve

carbon solubility of isoprenoid model compounds (by 150 times compared to phytol) is atomic

ratio (AO:C) = 1:20 where the weight fraction of carbon is 0.73 and weight fraction of oxygen is

0.05 (Table 5.1 Mi). The biodegradation rank of model compound Mi is 2.47, which suggests

this compound takes weeks to months to biodegrade (Table 5.1). Furthermore, the sulfur to

carbon atomic ratio for model compound Mi (AS:C= 1:20) showed increased biodegradation

resistance compared to phytol (biodegradation rank = 2.70). Therefore, the addition of a sulfur

atom to alkanes and isoprenoids improves biodegradation resistance, however, the carbon

solubility and biodegradation rank of sulfurized and oxidized isoprenoid compounds are far

below AVECS targets. There are limited functional groups in isoprenoid compounds which are

reactive to inorganic sulfur species for sulfur incorporation and this makes it difficult to improve

139

biodegradation resistance. In addition, alkanes are insoluble in water, but there are also limited

sites to increase the AO:C ratio. A different model compound with greater water solubility and

more reactive functional groups may be a better candidate for reaching AVECS goals.

Figure 5.11 Sulfurization and oxidation of isoprenoid model compounds. (K) Phytol. (L)

Sulfurization forms thiophene. (Li) Oxidation forms sulfone group. (M) Sulfur

incorporation into phytol forms thiolane structure. (Mi) Oxidation results in the addition of

a sulfoxide group. (Mii) Subsequent oxidation forms sulfone group.

140

Figure 5.12 The sulfurized isoprenoids with thiolane (orange) show a slightly higher carbon

solubility (2.19E-07 kg C/m3) compared to the isoprenoid which formed thiophenes (blue)

(1.34E-07 kg C/m3).

Figure 5.13 Oxidation of isoprenoid thiolane (M, orange) showed increased carbon

solubility through the addition of sulfoxide to model compound (Mi, blue). Model

141

compound (Mi) shows greater carbon solubility compared sulfurized model compound

(Mii, gray) which consists of a sulfone group.

5.3.4 Experiment 4 – Sulfurization and Oxidation of Glycerol

The next compound of interest for modifications is glycerol (Fig. 5.14 N), as it is a highly

water-soluble compound and is major byproduct from biodiesel production (Yang et al., 2012).

Glycerol is already water-soluble but the question is — does the sulfurization of glycerol affect

its high solubility and degradation resistance? Following the sulfur incorporation process for

cholesterol, sulfur reacts with the hydroxyl groups in glycerol to form thiols (Fig. 5.14 O, P, and

Q).

Figure 5.14 Sulfurization and oxidation of glycerol model compounds. (N) Glycerol. Sulfur

incorporation occurs at hydroxyl groups in glycerol to form thiols (O, P, and Q). Oxidation

of sulfurized glycerol model compounds form sulfonate groups (Oi, Pi, and Qi).

142

Figure 5.15 Effect of thiol groups on carbon solubility of glycerol. (See Fig. 5.14 for

progression of N, O, P and Q)

The results in Fig. 5.15 show that as thiol groups are incorporated into glycerol, the solubility

decreases by approximately 14% for the first thiol (N), then 96% for the second thiol (P) and by

the third thiol group, model compound (Q) becomes insoluble as 99% of glycerol’s original

solubility is removed. Next to consider is whether oxidation of thiol groups to sulfonates will

improve water solubility.

143

Figure 5.16 The effect on carbon solubility due to the addition of sulfonate groups on

sulfurized glycerol (See Fig. 5.14 Q and Qi).

When the first sulfonate groups were added to molecule (Q), solubility immediately

improved by nearly 2000% (Fig. 5.16). However, each additional sulfonate group added after the

first decreased carbon solubility by approximately 20%. It is important to note that the addition

of sulfonate groups did not affect water solubility of the overall molecule as the maximum water

solubility estimate was reached (1.00E+06 kg/m3), however carbon solubility did decrease with

increasing sulfonate groups (Table 5.1). This decrease is attributed to multiplying water

solubility by weight fraction of carbon to retrieve carbon solubility. Since the molecular weight

of model compound (Qi) increased due to the addition of three sulfonate groups and the atomic

O/C ratio for model compound Qi is 9:3, this means that atoms like oxygen contribute to most of

the molecular weight while the number of carbon atoms in the molecular formula remain the

same (Table 5.1). Therefore, the weight fraction of carbon is reduced, which also explains the

decreased in carbon solubility. In spite of the decreased carbon solubility, model compound Qi

has a carbon solubility of 126 kg C/m3, which is beyond AVECS targets of 15 kg C/m3. Even

though the atomic S/C ratio is highest for sulfurized glycerol compounds at 3:3, the

144

biodegradation rank is 3.14, which indicates that such compounds will degrade in weeks to

months.

In summary, sulfurization and oxidation of glycerol compounds meets carbon solubility

targets for AVECS, but not biodegradation resistance. Furthermore, the reactivity of hydroxyl

groups with sulfur is uncertain as discussed in Experiment 2 (Schouten et al., 1993b) .

Furthermore, the addition of sulfonate groups may increase water solubility, but not carbon

solubility, for model compounds like sulfurized glycerol. This means that the optimum carbon

solubility is reached when there is only one sulfonate group in sulfurized glycerol (Q).

Increasing oxidation any further results in less efficient carbon storage.

5.3.5 Experiment 5 – Sulfurization and Oxidation of Hydrocarbons

The ideal AVECS molecule should not only have a carbon solubility of at least 15 kg

C/m3, but also possess as many carbon atoms as possible, such as a fullerene molecule (Fig.

5.17) that is also known as carbon buckyball (C60), as it would improve the effectiveness of

carbon subsurface storage. To construct the ideal AVECS molecule with optimal balance of

carbon solubility and rich carbon content, long C30H62 (Fig. 5.19 R) and C60H122 hydrocarbon

chains (Fig. 5.20 V) were conceptually modified to further achieve other desired characteristics

of an AVECS molecule. However, it was difficult to apply modifications on the fullerene

molecule (using ChemAxon software) due to constrained 2D view of the molecule. Hence,

hydrocarbon chains were selected instead for modification experiments.

Similar to the sulfur incorporation study into long hydrocarbon chains (Fig. 5.18) by

Sinninghe Damsté et al. (1989), thiolanes were incorporated for molecule modification

experiments along the C30 hydrocarbon chain to increase biodegradation resistance (Fig. 5.19 U

and Fig. 5.20 X).

145

Figure 5.17 A fullerene molecule (C60) that is also informally known as the carbon

buckyball. The fullerene molecule could be a potential model compound for the ideal

AVECS molecule.

Figure 5.18 Sulfur incorporation into tri-unsaturated C37 hydrocarbon. After Sinninghe

Damsté et al. (1989).

146

Figure 5.19 Sulfurization and oxidation of C30 hydrocarbon chains. (R) C30H62. Conceptual

sulfur incorporation form thiolanes (S, T, and U). Oxidation of sulfurized C30

hydrocarbons form sulfoxide groups (Si, Ti, and Ui).

Figure 5.20 Sulfurization and oxidation of C60 hydrocarbon chains. (V) C30H62. Conceptual

sulfur incorporation form thiolanes (W and X). Oxidation of sulfurized C30 hydrocarbons

form sulfoxide groups (Wi and Xi).

Since hydrocarbons chains (Table 5.1 R and V) are very insoluble to begin with, adding

thiolanes across the chains did not affect the structures’ carbon solubility in water. Despite the

differences in thiolane additions, molecules (R and U) and (V and X) all have similar carbon

solubility values (Table 5.1).

From experiments 1 and 3, it was observed that the addition of sulfoxide to thiolane

contributed to the most improvement in carbon solubility, therefore thiolane-1-oxides were

added to the hydrocarbon chains to examine how it affected solubility.

147

Figure 5.21 The effect of number of thiolane-1-oxide groups on the carbon solubility in

water for (a) C30H62 and (b) C60H122. Green horizontal line delimits AVECS target water

solubility (> 15 kg C/m3).

In Fig. 5.21a, each additional thiolane-1-oxide added to the C30H62 hydrocarbon chain gradually

increased carbon solubility from 3.60*10-10 kg C/m3 up to a maximum of 121 kg C/m3 with six

thiolane-1-oxides (Fig. 5.19 Ui). On the other hand in Fig. 5.21b, the addition of thiolane-1-oxide

gradually increases solubility until the eighth group is added after which a sharper increase in

solubility is observed. Furthermore, molecule Xi, the C60 hydrocarbon chain with 12 thio-1-

oxides (Fig. 5.20), had an estimated carbon solubility of 17.81 kg C/m3, which meets AVECS

148

targets. In addition, the estimated biodegradation rank of molecule Xi is 0.11 (Table 5.1), which

also meets AVECS targets, as values under one indicate that the molecule has high recalcitrance.

5.3.6 Experiment 6 – The Biodegradation Rate of Oxidized OSC

Several factors affect the biodegradation rate of compounds including aromaticity, high

molecular weight, alkylation and functional groups. Essentially, any chemical characteristic that

makes the molecule more structurally complex will increase the time it takes for the compound

to biodegrade because microorganisms will take longer to transform parent compounds to

metabolites. In the experiments above, EPI suite showed high solubility for oxidized sulfurized

compounds. For this experiment, the biodegradation rate for oxidized sulfur compounds (with

highest carbon solubility) from each experiment was estimated using BIOWIN software (Fig.

5.22). This experiment narrows down the model compounds which have potential to form the

ideal AVECS molecule which is both water soluble and resistant to biodegradation.

149

Figure 5.22 Sulfurized and oxidized model compounds (from each experiment) with the

greatest carbon solubility. Lipids (Ei), carbohydrates (Hi), isoprenoids (Mi), glycerol (Qi),

hydrocarbon derived chains (Ui and Xi).

150

Figure 5.23 Biodegradation rate of oxidized OSC (Ei, Hi, Mi, Qi, Ui, Xi). See figure 5.22 for

structures. Red data points are recalcitrant. Yellow indicates biodegradation will take

weeks to months, and green indicates biodegradation will take weeks (EPA, 2011).

Usually, organic molecules which are water-soluble are typically easily biodegradable.

In Fig. 5.23, the glycerol model compound Qi (Fig. 5.22) follows this assumption as it has high

carbon solubility and high biodegradation rank (>3.25). On the other hand, the carbohydrate

model compound Hi (Fig. 5.22) shows a different pattern where it has low carbon solubility, but

relatively high biodegradation rank. In contrast, the data point that stands out is the hydrocarbon

derived model compound Ui (Fig. 5.22), which exhibits high carbon solubility (121 kg C/m3)

and is recalcitrant (biodegradation rate = 1.65). The characteristics of model compound Ui meets

AVECS targets.

In Fig. 5.23, the biodegradation rate of each model compound was calculated based on

the sum of the molecule weight parameter and an equation constant. However, the BIOWIN

software does not account for significant fragments, such as the thiolane-1-oxides, that are within

the molecule (Table 5.3). Because these structural features are not considered in this software,

the estimated biodegradation rate may not be reliable as the biodegradation rate of a molecule

may be over- or under-estimated.

151

Table 5.3 BIOWIN 3 (ultimate biodegradation survey model) was used to determine the

biodegradation rate value for molecule (Ui) (EPA, 2011).

BIOWIN3 FRAGMENT DESCRIPTION Value

Molecular Weight Parameter -1.5449

Equation constant 3.1992

Survey Model - Ultimate Biodegradation RESULT

1.6543

In terms of model compounds which represent the ideal AVECS molecule, a synthetic

chemical present in reality that is also highly soluble and recalcitrant is sulfolane. Sulfolane

(C4H8O2S), also known as tetrahydrothiophene 1,1-dioxide, is a colorless and odorless inert

organosulfur solvent with high water solubility (1,266 kg/m3 at 20 °C) and high thermal stability

(Canadian Council of Ministers of the Environment, 2006; Janda, 2016). Sulfolane is synthesized

through a cheletropic reaction where σ bonds are created between sulfur dioxide and butadiene to

create a molecule with cyclic geometry (Fig. 5.24)(Tilstam, 2012).

Biomass components with conjugated or non-conjugated diene systems, such as squalene

and β-carotene, may be reactive with sulfur and oxidants, such as oxone (KHSO5), to form OSC

structures with similar characteristics as sulfolane. In Chapter 6, laboratory sulfurization

experiments are tested on lipids including squalene and β-carotene to create OSC.

Figure 5.24 Process for sulfolane synthesis. Sulfolane is synthesized by the reaction between

1,3-butadiene (1) with sulfur dioxide (2) to form sulfolene (3) the hydrogenation of sulfolene

forms sulfolane (4). (Tilstam, 2012; Bak et al., 2018)

5.4 Conclusions

Intramolecular sulfur incorporation into lipids, carbohydrates, and hydrocarbons is an

important pathway for carbon preservation in the subsurface (Kok et al., 2000a). From the

molecular modification experiments, it is seen and expected that low molecular weight

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compounds have high water solubility while high molecular weight compounds exhibit low

solubility. What was unexpected was increased oxidation, oftentimes, reduced carbon solubility.

For example, derivatives of lipids with sulfone functionalities (Bii, Fig. 5.2) showed less

improvement in carbon solubility compared to lipid derivatives with sulfoxide functionalities

molecules (Bi, Fig. 5.2). The solubility-improving sulfoxide group was further modified to

thiolane-1-oxides and incorporated into long hydrocarbon chains (in Experiment 5), which

increased water solubility by several orders of magnitude. Although the modification

experiments showed sulfurized and oxidized model compounds with improved water solubility

and biodegradation resistance, the estimated values and results may not be accurate. As a result

of the lack of fragments and functional groups in the BIOWIN and WATERNT training set

coefficient database, water solubility and biodegradation rate predictions may be under or over-

estimated (U.S. Environmental Protection Agency, 2000) (See appendix A1 and A2 for chemical

fragments database).

The recommendations for types of compounds which are more likely to possess AVECS

molecule qualities (carbon solubility of 15 kg C/m3 and biodegradation rank below 1) are model

compounds which consist of many hydrocarbon atoms and double bond functionalities, as

double bonds are observed to be reactive sites for sulfur incorporation to form thiolane or

thiophene structures, which increases the overall biodegradation resistance of the molecule.

Organic compounds which are rich in carbon and is comprised of diene systems are terpenoids,

such as carotenoids (C40), which are commonly sourced from plants. Furthermore, sulfoxide and

sulfone functional groups are effective at improving water solubility of model compounds.

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Chapter Six: Sulfurization of Organic Molecules

6.1 Introduction

Several research studies have attempted to simulate natural sulfurization reactions on

sedimentary organic species such as phytol, monosaccharides and octanal in laboratory

conditions (De Graaf et al., 1992; Schouten et al., 1993a; Van Dongen et al., 2003b).

In this chapter, lipids (β-carotene, cholestane, linolenic acid, and squalene) undergo three

separate laboratory sulfurization experiments with elemental sulfur (S8), sodium sulfite

(Na2SO3), sodium hydrosulfide (NaHS), and dimethylformamide (DMF) as reagents. In addition,

carbohydrate sulfurization (using glucose, starch and sucrose) was attempted for a duration of 30

days at 50 °C, but sulfurized material was not observed. Sulfurized lipids yielded products with

up to 7 sulfur atoms within their structure. FTICR-MS was mainly used to analyze the sulfurized

products as the sulfurized lipids were not GC amenable and formed unresolved complex

mixtures (UCM). Laboratory sulfurization experiments on organic molecules advances towards

AVECS goals of altering residual carbon-rich biomass for permanent sequestration in the

subsurface by sulfur incorporation into lipids to produce biologically refractory species from

biomass.

6.2 Experimental Methods

6.2.1 Lipid Sulfurization Reactions

Lipids (Table 6.1) underwent three separate laboratory sulfurization experiments: (1) 5

days at ambient temperatures, (2) 30 days at ambient temperatures and (3) 30 days at 50 °C (Fig.

6.1) using elemental sulfur (S8), sodium sulfite (Na2SO3), sodium hydrosulfide (NaHS), and

N,N-dimethylformamide (DMF) to sulfurize the reactants. Reactants (Table 6.2) were purchased

from Prochem, Sigma Aldrich and TCI Chemicals. Lipid sulfurization reactions followed

methods by De Graaf et al. (1992) and Schouten et al. (1994). The model lipid compound,

elemental sulfur and anhydrous sodium hydrosulfide were transferred into a round bottom flask

following a molar ratio of 1:10:25 respectively. Reactants were dissolved in 25 mL of N,N-

dimethylformamide. For the heated sulfurization experiment, which lasted for 30 days, the

mixture was heated to 50 °C and stirred at 1000 rpm for 30 consecutive days. Aluminum foil was

wrapped around each flask to ensure minimal light exposure. After 30 days, a solution of water

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and sodium sulfite was added to quench the reaction. The sulfurized lipid compounds were

separated from the aqueous phase using hexane and liquid-liquid extraction (Fig. 6.2). The

extraction was repeated three times before hexane was evaporated with a rotavapor to

concentrate the products.

Table 6.1 Model compounds selected for lipid sulfurization experiments.

Model

Compound Purity Molecular

Formula β-Carotene ≥97.0% C

40H

56

5α –

Cholestane

– 2,2,4,4-d4

≥99% C27

H48

Linolenic

acid >70.0% C

18H

30O

2

Squalene >98.0% C30

H50

Table 6.2 All reactants and corresponding molar ratios and amounts used in the lipid

sulfurization experiments. Molar ratios and choice of reagents followed methods by De

Graaf et al. (1992) and Schouten et al. (1993).

Reactants Molar Ratio

(mmol) Amount

Model Compounds

β-Carotene

1

0.537 g

Cholestane 0.387 g

Linolenic acid 0.278 g

Squalene 0.411 g

Reagents

Elemental sulfur 25 0.80 g

Na2SO3 19.8 2.5 g

NaHS 10 0.56 g

N,N-Dimethylformamide 323 25 mL

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Figure 6.1 Analytical scheme of lipid sulfurization experiments

Figure 6.2 Liquid-liquid extraction on sulfurized β-carotene reaction mixtures.

6.2.2 Carbohydrate Sulfurization Attempts

Carbohydrate sulfurization experiments followed closely to the experimental methods

described by Kok et al. (2000). In this study, 0.0011 mol of each carbohydrate compound (200

mg glucose, 376.5 mg sucrose, 376.5 mg starch) was dissolved in 6 ml of deionized water, then

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combined with 560 mg of NaHS and 16 mg of elemental sulfur. The mixture was heated to 50 °C

and stirred at 800 rpm for 30 days. After the reaction, elemental sulfur was removed from the

extracts by adding small amounts of cleaned activated copper flakes (Sigma-Aldrich) into the

mixture (Fig. 6.3). The mixture was magnetically stirred for 24 hours. All added copper

converted to copper sulfide, which formed due to presence of sulfides. A 50:50 mixture of

MeOH and DCM was used to dissolve the sulfurized starch mixture, then copper flakes were

filtered from sample mixture using 20-25 μm pore size Whatman filter paper and deionized

water. Afterwards, 146 mm Pasteur pipettes were plugged with glass wool and filled two-thirds

full with granular copper (20-30 mesh) from J.T. Baker. The sulfurized mixtures were pipetted

into the copper columns until the mixture showed no reaction with copper (Fig. 6.4). Two

copper-filled columns were needed to extract excess elemental sulfur from each sample.

Following filtration steps, the samples were freeze dried 3 days and formed solid powder

material (Fig. 6.5).

Figure 6.3 (a) Carbohydrate sulfurization experimental set up. (b) Addition of pure copper

flakes to remove excess elemental sulfur. Copper turns black (copper sulfide)

instantaneously. (c). After 24 hours of stirring, the entire solution appears black.

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Figure 6.4 (a) Pasteur pipette filled with pure copper granules and glass wool. (b) Copper

turns black after eluting sulfurized sample through the column.

Figure 6.5 (a) Sulfurized carbohydrates in freeze-dryer after removing excess sulfur (b)

Freeze dried sulfurized carbohydrates. From the left: sucrose, glucose, starch and blank.

6.3 Analytical Methods

6.3.1 Freeze-Dry

Sulfurized carbohydrates were freeze dried using the Freezone Freeze Dryer- Labconco machine

provided by the Energy Bioengineering and Geomicrobiology group at the University of

Calgary, Calgary Canada.

6.3.2 FTICR-MS Analysis

The sulfurized lipid and carbohydrate samples were analyzed with a 12 T Bruker SolariX

mass spectrometer in atmospheric pressure photoionization positive ion (APPI-P) mode. The

APPI-P ionization technique efficiently ionizes polar and non-polar species, structurally diverse

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compounds and sulfur compounds in complex organic mixtures without the use of chemical

derivatization nor special sample preparation strategies (Purcell et al., 2007; Oldenburg et al.,

2014). See FTICR-MS methods in Chapter 3 for more instrument details. Furthermore,

monoisotopic peak intensities, displayed in the figures below, do not reflect the actual abundance

of compounds present in the sample. As well, the chemical structures and molecular formulas

assigned to sulfur-containing lipid peaks are speculative, as FTICR-MS software utilizes

absolute mass accuracy and isotopic patterns to compute a molecular formula to each

investigated peak. In addition, peaks which are left unassigned with a molecular formula do not

contain sulfur and are not discussed further.

6.3.3 ChemAxon

ChemAxon was used to draw possible chemical structures of sulfurized lipids based on the

computed molecular formula assigned to the peak of interest.

6.4 Results

6.4.1 Experiment 1: Lipid Sulfurization for 5 days

Minimal sulfurization occurred with squalene (C30H50) and formed sulfurized squalene (C30H52S)

(Fig. 6.6 and Fig. 6.7) (Table 6.3). Sulfurization was not observed in other lipids.

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molecular formula. Sulfurization of squalene (C30H52S) was detected in experiment #1

(lipid sulfurization for 5 days).

Figure 6.7 Possible organic sulfur compound structure with molecular formula C30H52S.

Sulfurization of squalene in experiment #1 (lipid sulfurization for 5 days) may have formed

one thiolane intramolecularly.

6.4.2 Experiment 2: Lipid Sulfurization for 30 days

Increased sulfurization occurred in squalene (see Fig. 6.9 for potential OSC structure of

C30H54S2), but other lipids do not exhibit sulfurization (Fig. 6.8) (Table 6.3).


160


sulfurization for 30 days).


Sulfurization of squalene (experiment #2 - lipid sulfurization for 30 days) may have formed

two thiolanes intramolecularly.

6.4.3 Experiment 3: Lipid Sulfurization for 30 days at 50 °C

Sulfurization was observed in all lipids except cholestane. Linolenic acid incorporated up

to 2 sulfur atoms (C18H32O2S2) (Fig. 6.10 and Fig. 6.11). Squalene up to 4 sulfur atoms

(C30H54S4) (Fig. 6.12 and 6.13) and β-carotene incorporated up to 7 sulfur atoms (C40H68S7) (Fig.

6.14 and Fig. 6.15). See Table 6.3 and Table 6.4 for the weight and molecular formula for

sulfurized products.

Figure 6.10 Possible organic sulfur compound structure with molecular formula

C18H32O2S2. Sulfurization of linolenic acid (experiment #3 - lipid sulfurization for 30 days

at 50 °C) may have formed two thiolanes intramolecularly.

161

Figure 6.11 FTICR-MS mass spectrum showing peak intensity, mass to charge (m/z) ion

and molecular formula. Sulfurized linolenic acid (C18H32O2S2) is detected in experiment #3

(lipid sulfurization for 30 days at 50 °C).


Sulfurization of squalene (experiment #3 - lipid sulfurization for 30 days at 50 °C) may

have formed four thiolanes intramolecularly.

162


and molecular formula. Sulfurized squalene (C30H54S4) is detected in experiment #3 (lipid

sulfurization for 30 days at 50 °C).

163


and computed ion formula. Sulfurized β-carotene (C40H68S7) is detected in experiment #3

(lipid sulfurization for 30 days at 50 °C).


Sulfurization of β-carotene (experiment #3 - lipid sulfurization for 30 days at 50 °C) may

have formed four thianes and 3 thiolanes intramolecularly.

Table 6.3 Reactants and sulfurized products from each experiment and the corresponding

measured mass to charge (m/z) and ion formulae as indicated in FTICR-MS plots.

Reactant/ Products Measured m/z Ion Formula

Experiment 1 Squalene 410.3904 C30H50

Sulfurized Squalene 444.3781 C30H52S

Experiment 2 Squalene 410.3903 C30H50

Sulfurized Squalene 444.3779 C30H52S 478.3656 C30H54S2

Experiment 3

Linolenic Acid 278.224 C18H30O2

Sulfurized Linolenic

Acid

312.2117 C18H32O2S 314.2273 C18H34O2S 344.1837 C18H32O2S2

Squalene 410.3903 C30H50

Sulfurized Squalene

444.3779 C30H52S 478.3656 C30H54S2 510.3375 C30H54S3 544.3257 C30H54S4

β-Carotene 536.4373 C40H56 570.425 C40H58S

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Sulfurized β-

Carotene

604.4127 C40H60S2 638.4004 C40H62S3 672.388 C40H64S4

706.3757 C40H66S5 740.3633 C40H68S6 772.3353 C40H68S7

Table 6.4 Organic sulfur compound products from the reaction of squalene, linolenic acid

and β-Carotene with elemental sulfur and NaHS in DMF under different lipid sulfurization

conditions. Weights of sulfurized products were measured after liquid-liquid and

rotavapor solvent extraction.

Conditions Reaction Products

Total Weight of Products (mg)

Experiment 1 Ambient

temperatures/ 5 days

Sulfurized Squalene 79.2

Experiment 2 Ambient

temperatures/ 30 days

Sulfurized Squalene 72.8

Experiment 3 50 °C / 30 days

Sulfurized Linolenic Acid 40.2

Sulfurized Squalene 233

Sulfurized β-Carotene 74.9

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6.4.4 Experiment 4: Carbohydrate Sulfurization for 30 days at 50 °C

Sulfurized carbohydrate products were not detected through FTICR-MS analysis.

6.5 Discussion

The experiment series which exhibited most sulfurization of the model compounds was

the third lipid sulfurization experiment, which ran for 30 days at 50 °C. In this experiment, three

of the four lipids were sulfurized and incorporated 2 to 7 sulfur atoms within the chemical

structure. In addition, the total weight of products was greatest in experiment 3 (Table 6.4),

which may be indicative that increased temperatures and time duration of experiment allowed for

more product formation due to increased polysulfide interactions with lipids. Based on the

product weights, squalene may be most reactive to sulfurization reactions followed by β-

carotene, linolenic acid, and then cholestane. In Chapter 3, it was hypothesized that squalene, β-

carotene and steroid skeletons such as those related to such as cholestane, formed major amounts

of OSC in sulfur-rich oils. From the results of this experiment, it appears that the double bond

functional groups in squalene (DBE= 6) and β-carotene (DBE = 13), are more prone to

sulfurization with the reagents used, compared to linolenic acid and cholestane. Linolenic acid

also displayed minor levels of sulfurization with the addition of heat. However, it is also likely

due to preferential sulfur incorporation at double bond functionalities since the calculated

molecular formulas in Fig. 6.11, show C18H34O2S and C18H32O2S2, which suggests the carboxyl

functional group was likely not the preferential location for sulfur incorporation as the oxygen

atoms are not replaced with sulfur (Fig. 6.16).

Figure 6.16 (a) Chemical structure of linolenic acid (C18H30O2) compared to possible

sulfurized linolenic acid structures (b) C18H34O2S and (c) C18H32O2S2, which are molecular

formulas extrapolated from the FTICR-MS mass spectrum (Fig. 6.11).

Van Dongen et al.(2003) showed sulfurization of monosaccharides and the importance of

carbonyl functional groups in monosaccharides as reactive sites with carbonyl functionalities

becoming replaced with sulfur. Although, in experiment 4, similar sulfurization procedures such

166

as time duration, temperature and carbohydrate materials followed Van Dongen et al.(2003),

sulfurized products were not observed. Some possibilities which may have contributed to such

results are (1) the process of removing excess sulfur using filter paper and granular copper may

have removed important sulfur compounds, (2) The extraction process may have been inefficient

at recovering highly oxygenated species or (3) structural loss of carbohydrates due to freeze

drying process. Levi and Karel (1995) reported collapsed carbohydrate systems often show poor

rehydration capabilities when time and temperature during the freeze dry process are under sub-

optimal conditions. Poor rehydration was observed in experiment four as freeze dried

carbohydrate samples formed large amounts of precipitate upon rehydration for FTICR-MS

analysis.

6.5.1 Viable products for AVECS processing

Of the lipid sulfurization experiments, the compound which would be most suitable for

AVECS processing is sulfurized β-carotene (C40H68S7) as it has a biodegradation rank of 0.85

estimated by BIOWIN software (See Chapter 5 for more details on BIOWIN), which meets

AVECS goals as a biodegradation rank <1.75 that suggests the compound is recalcitrant (Table

6.5). Furthermore, β-carotene is comprised of many carbon atoms (C40), double bond

functionalities, which are reactive sites for sulfur incorporation hence the incorporation of seven

sulfur atoms within the structure (C40H68S7), and carotenoids are abundant in nature and are

commonly found in bacteria, molds and algae (Bogacz-Radomska and Harasym, 2018). In

addition, industrial bioresidues and waste agricultural products are rich in carotenoids as many

animals (waste water, crustacean shells and fish scales) and vegetables (peels and seeds) are

sources of carotenes and xanthophylls (Martins and Ferreira, 2017). Inexpensive and abundant

sources of carbon-rich biomass waste material with double bond functionalities like carotenoids

are feasible sources for future AVECS processing. However, the estimated solubility of

sulfurized β-carotene (C40H68S7) is low (Table 6.5), but future oxidation experiments may

increase solubility of sulfurized compounds to meet AVECS targets of 15 kg C/m3.

167

Table 6.5 The molecular formula, biodegradation rank and estimated water solubility of

lipid compounds (squalene, linolenic acid, B-carotene) and the sulfurized forms produced

from lipid experiment #3 (highlighted in yellow). The degradation rate for biodegradation

rank values: 3.25 – 5.00 = days to hours, >2.75 - 3.25 = weeks, >2.25 - 2.75 = weeks to

months, >1.75 - 2.25 = months, <1.75 = recalcitrant. The target solubility for AVECS

molecules is 15 kg C/ m3 and the target biodegradation rank is <1.75.

6.6 Conclusions

Increasing temperatures from ambient temperatures to 50 °C and increasing the time

duration of experiments improved sulfurization of lipids. Squalene was most reactive to

sulfurization experiments as squalene was sulfurized in each attempted experiment, but

sulfurized squalene (C30H54S4) does not meet biodegradation rank targets for future AVECS

processing. However, organic species with similar characteristics as carotenoids may be viable

model compounds for future AVECS processing to create organic sulfur bearing species for

carbon storage, as sulfurized β-Carotene (C40H68S7) is estimated to be recalcitrant to

biodegradation. Furthermore, a desirable structural characteristic in AVECS molecules are

conjugated double bond systems, as such sites are most reactive to sulfur incorporation compared

to carboxyl, carbonyls and hydroxide functional groups. Following similar sulfurization

conditions as lipid sulfurization experiments did not result in FTICR-MS detection of sulfurized

carbohydrate products.

Model Compounds Molecular Formula

Biodegradation Rank

Water Solubility

(mg/L)

Squalene C30H50 2.29 4.10E-07

Sulfurized Squalene C30H54S4 1.99 5.43E-07

Linolenic Acid C18H30O2 3.24 0.099

Sulfurized Linolenic Acid C18H32O2S2 2.8 0.05175

B-Carotene C40H56 1.58 5.37E-07

Sulfurized β-Carotene C40H68S7 0.85 7.73E-07

168

Chapter 7 Conclusions and Future Work

Net zero CO2 emissions must be achieved in less than 15 years to remain 1.5 °C of

warming below pre-industrial levels (Rogelj et al., 2018). This means globally deployable

technologies which have potential to permanently remove CO2 from the atmosphere or achieve

negative emissions are needed urgently to limit catastrophic environmental and societal

consequences caused by climate change. This thesis addressed the research question of whether

it is possible to utilize sulfurized residual biomass waste material as a form of carbon

sequestration. To answer this question, initial stages of AVECS technology was designed and

developed to understand the future prospective of using such route as an alternative carbon

sequestration method. AVECS technology uses molecules derived from biomass and

sulfurization reactions involving elemental sulfur and polysulfides to create biologically

refractory and water-soluble organic sulfur species for subsurface carbon storage.

The approach to developing AVECS technology was to first explore the geochemical

sulfur cycle and recognize how natural sulfurization processes occur in sedimentary organic

matter. Then, sulfur-rich oils were analyzed with the GC-MS and FTICR-MS to determine the

structural composition of sulfurized organic compounds in crude oils and the lab conditions that

facilitate sulfurization of organic matter. The results from the analysis of Rozel Point and

Jianghan Basin oils showed extensive intramolecular sulfur incorporation, as up to five sulfur

atoms were discovered within molecules. These sulfurized molecules were also dominated by

species comprised of carbon numbers C20, C30 and C40 with double bond equivalent values of 5,

7, 9 and 13. Possible organic sulfur compound structures that match these results include

sulfurized steranes, hopanes and carotenoids. As for the conditions which facilitate sulfur

incorporation and preservation reactions and processes in organic matter, include anoxic

hypersaline environments, low thermal maturity, organic matter input from organisms which are

rich in steroids, hopanoids and carotenoids, and low to moderate biodegradation exposure.

The method development process for separating sulfur compound-rich oils into various

fractions using liquid chromatography on silver nitrate impregnated silica gel was revised, and

the method was effective at separating aromatic and non-aromatic sulfur compounds in crude oil

with less than 4 wt% S. The different biodegradation resistant sulfur compounds which were

169

found in heavily to severely biodegraded oil included (1) non-aromatic sulfidic compounds with

one to three sulfur atoms such as thiolanes and sulfides, and (2) aromatic sulfur compounds with

one to five sulfur atoms such as thiophenes and dibenzothiophenes. These biodegradation

resistant sulfur compounds can be used as model systems, to test future studies on oxidation

reactions and serve as AVECS targets for compounds that could form biologically refractory

sulfur-containing species through reaction of elemental sulfur sources with various biomass

precursors (agricultural waste). In future work, it would be possible to further modify the

technique to deal with more polar and sulfur enriched oils. In addition to S1 (saturated

hydrocarbons), S2 (aromatic sulfur compounds), and S3 (non-aromatic sulfur compounds)

fractions, future work should include investigation of eluting a S4 (mercaptans) fraction.

Modelled solubility and biodegradation resistance estimations were evaluated for various

model compounds including aromatic thiophenic compounds, sulfidic compounds, and

mercaptan compounds which were derived from biodegraded sulfur-rich oils. Using computer

modelling software, the results showed low molecular weight compounds have high water

solubility, while high molecular weight compounds exhibited low solubility. Moreover,

incorporating sulfinyl or sulfonyl functionality into organic structures showed increased

biodegradation recalcitrance as well as improvement in water solubility. The recommendations

for types of compounds which are more likely to possess AVECS molecule qualities (carbon

solubility of 15 kg C/m3 and biodegradation rank below 1) are model compounds which are

enriched in carbon atoms and consist of many double bond functionalities. Double bonds are

observed to be the most reactive sites for sulfur incorporation to form thiolane or thiophene

structures. These structures increase the overall biodegradation resistance of the molecule.

Organic compounds which are enriched in carbon and have diene double bond systems include

terpenoids, such as carotenoids (C40), which are commonly sourced from plants.

Laboratory sulfurization experiments were conducted on lipid molecules at 50 °C for a

time duration of 30 days. The sulfurized products included sulfur incorporation of up to two

sulfur atoms in linolenic acid, five sulfur atoms in squalene and seven atoms in β-carotene. The

outcomes from the lipid sulfurization experiments are: (1) organic species with similar

characteristics as carotenoids may be the most viable for future AVECS processing, as sulfurized

170

β-Carotene (C40H68S7) is estimated to be recalcitrant to biodegradation through computer

modelling software. Furthermore, a desirable structural characteristic in compounds for AVECS

processing are conjugated double bond systems, as such sites are most reactive to sulfur

incorporation compared to carboxyl, carbonyls and hydroxide functional groups.

In summary, the work in this thesis has contributed new insights in the prospects of

utilizing organic sulfur bearing species as a carbon sequestration method. Key findings which are

important for further advancements in AVECS technology include:

(1) Organic sulfur compounds extracted from biodegraded sulfur-rich oils appear to have

precursor characteristics which resemble sulfurized steroids, hopanoids and carotenoids. It is

hypothesized that such precursor chemicals are receptive to natural sulfurization due to

abundance of reactive chemical sites, such as double bond functionalities. For future AVECS

processing, model compounds with characteristics that resemble OSC found in biodegraded

oils may be more reactive to sulfurization reactions and serve as possible carbon storage

vectors. Intramolecular sulfur incorporation at double bonds typically form thiolane or

thiophene structures.

(2) The revised liquid chromatography on silver nitrate impregnated silica gel method is

effective at separating sulfur rich oils (< 4wt%) into non-aromatic and aromatic sulfur

compound fractions. These fractions could be used to test effectiveness of future oxidation

reactions.

(3) Computer modelling estimations on various model compounds showed sulfinyl and sulfonyl

functionalities were most effective at increasing both aerobic biodegradation recalcitrance

and water solubility of organic compounds.

(4) Lipid sulfurization experiments at increased temperatures and time durations showed that

squalene and β-carotene incorporated most sulfur atoms compared to the other lipids in the

sample set. The diene double bond systems within the terpenoids likely contributed a strong

role in successful intramolecular sulfur incorporation.

(5) From the results of the lipid sulfurization experiments, terpenoids with double bond systems

may be viable for future AVECS processing. Terpenoids, such as β-carotene, are commonly

171

sourced from plants and are abundant in biomass waste materials such as fruit peels and

seeds.

AVECS has potential to flourish as a carbon sequestration technology as it utilizes

biomass waste material as a carbon source and sulfurization reactions which helps the global

sulfur surplus dilemma. In addition, AVECS molecules will be stored in shallow, saline and

contaminated aquifers which are geographically abundant and have no economic value. The

results from this research study illustrates that organic compounds with double bond systems,

such as terpenoids, can be sulfurized to increase the overall biodegradation resistance of the

organic compound, however this raises a question—what will occur if AVECS molecules

biodegraded? If sulfurized organic compounds are biodegraded, it would release CO2 in the

storage site or shallow saline aquifer. It would be worthwhile to investigate rates of release to see

if AVECS species can be safely stored in shallow aquifer settings on say a 1000 year timescale.

Future work for further advancements in the AVECS project includes:

(1) Explore other approaches to reduce energy input and time duration for conducting

sulfurization experiments as these reductions will positively impact the overall cost.

(2) Test oxidation reactions to convert S into SOx functional groups to increase water-solubility

of organic sulfur compounds. Possible oxidations reactions could include potassium

peroxymonosulfate (oxone) as it is an oxidizing agent that converts sulfides to sulfoxides or

sulfones (Trost and Curran, 1981).

(3) Biodegradation tests (See Appendix A8), established by AVECS summer students through

dissolved organic carbon (DOC) measurements, can be applied to potential sulfurized and

oxidized organic compounds.

(4) Sulfolane degradation tests using biotic and abiotic strategies (see Appendix A9) can be used

to test the recalcitrance of AVECS molecules in natural settings, as sulfolane is a synthetic

chemical that represents the ideal AVECS molecule (highly soluble and recalcitrant).

Therefore, AVECS molecules should have a similar response to sulfolane degradation tests

in nature.

172

(5) Lastly, life cycle assessment on the feasibility of AVECS routes for negative emission

technologies and potential carbon storage in shallow, saline, contaminated aquifers are also

important future steps in this research study.

173

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187

Appendix A

Appendix A1. Extracted ion chromatogram results Rozel Point oil (a) S1 fraction, (b) S2

fraction, (c) S3 fraction, and Jianghan Basin oil (d) S1 fraction, (e) S2 fraction and (f) S3

fraction. The fractionation technique was not as effective compared to Athabasca oil. Reactive

sulfides (thiolane and dibutyl sulfide) which were supposed to elute in S3 fraction were

observed in the S2 fraction. See Figure 5.8 for sulfur compound standards.

190

Appendix A2. FTICR-MS compound class distribution for (a) Rozel Point and (b)

Jianghan Basin oil.

191

Appendix A3. FTICR-MS DBE distribution for (a) Rozel Point and (b) Jianghan Basin oil.

192

Appendix A4. FTICR-MS carbon number distribution for (a) Rozel Point and (b) Jianghan

Basin oil.

193

Appendix A5. FTICR-MS compound class distribution for Rozel Point (red), Jianghan

Basin oil (blue) and Athabasca oil (black).

194

Appendix A6. BIOWINTM (v4.10) Ultimate Biodegradation Model Fragments and

Coefficient database.

There are 36 main fragments and molecular weight parameters which were obtained and

averaged from the analysis of 200 compounds by experts. (U.S. Environmental Protection

Agency, 2000). Training Set

FRAGMENT DESCRIPTION COEFFICIENT Fragment Count**

========================================== ===================== --------------

ULTIMATE PRIMARY MIN MAX Num

***

========= ========= ===== ===== ===

=

Nitroso [-N-N=O] -0.38513 0.01848 - 1 1

Linear C4 terminal chain [CCC-CH3] 0.29834 0.26907 - 3 26

Aliphatic alcohol [-OH] 0.15997 0.12945 - 4 18

Aromatic alcohol [-OH] 0.05638 0.03969 - 3 21

Aliphatic acid [-C(=O)-OH] 0.364605 0.38557 - 1 10

Aromatic acid [-C(=O)-OH] 0.08787 0.00775 - 1 6

Aldehyde [-CHO] 0.02232 0.19664 - 1 5

Ester [-C(=O)-O-C] 0.14021 0.22896 - 4 25

Amide [-C(=O)-N or -C(=S)-N] -0.05421 0.20543 - 1 13

Triazine ring (symmetric) -0.24586 -0.05752 - 1 4

Aliphatic chloride [-CL] -0.17318 -0.10061 - 3 14

Aromatic chloride [-CL] -0.20660 -0.16534 - 6 27

Aliphatic bromide [-Br] 0.02895 0.03538 - 6 2

Aromatic bromide [-Br] -0.13600 -0.15351 - 5 4

Aromatic iodide [-I] -0.04494 -0.12707 - 2 2

Aromatic fluoride [-F] -0.40694 0.01346 - 1 1

195

Carbon with 4 single bonds & no hydrogens -0.21212 -0.15344 - 3 32

Aromatic nitro [-NO2] -0.16959 -0.10838 - 2 13

Aliphatic amine [-NH2 or -NH-] 0.02444 0.04328 - 1 7

Aromatic amine [-NH2 or -NH-] -0.13495 -0.10838 - 2 23

Cyanide / Nitriles [-C#N] -0.08238 -0.06520 - 2 11

Sulfonic acid / salt -> aromatic attach 0.14221 0.02162 - 2 8

Sulfonic acid / salt -> aliphatic attach 0.19259 0.17714 - 2 4

Polyaromatic hydrocarbon (4 or more rings) -0.79934 -0.70224 - 1 2

Pyridine ring -0.21417 -0.01874 - 1 8

Aromatic ether [-O-aromatic carbon] -0.05812 0.07712 - 1 11

Aliphatic ether [C-O-C] -0.00867 -0.00974 - 5 16

Ketone [-C-C(=O)-C-] -0.02248 -0.02222 - 4 10

Tertiary amine -0.25480 -0.28800 - 2 10

Phosphate ester 0.15373 0.46535 - 1 7

Alkyl substituent on aromatic ring -0.07485 -0.06853 - 2 36

Azo group [-N=N-] -0.30036 -0.05279 - 1 3

Carbamate or Thiocarbamate -0.04671 0.19363 - 1 6

Trifluoromethyl group [-CF3] -0.51296 -0.27440 - 1 2

Unsubstituted aromatic (3 or less rings) -0.58591 -0.34280 - 1 1

Unsubstituted phenyl group (C6H5-) 0.02201 0.00489 - 3 22

Molecular Weight Parameter -0.00220987 -0.001442756 - - -

Molecular Weight ----- ----- 53.06 697.65 -

Equation Constant 3.19917051 3.847737 - - -

** - Minimum and Maximum number of instances of the fragment in any training set

compound. Minimum is always zero.

*** - Number of compounds in the 200 compound training set containing the fragment.

196

Appendix A7. WATERNT Fragment & Correction Factor Descriptions & Coefficients

The current version of WATERNT used a total training set of 1128 compounds. The derived

fragments and correction factors are as follows:

Number

compounds

Max

occurrences

Fragment Description Coefficient containing

fragment

in any one

compound

-CH3 [aliphatic carbon] -0.32127 612 6

-CH2- [aliphatic carbon] -0.53702 416 14

-CH [aliphatic carbon] -0.52852 188 6

C [aliphatic carbon - No H, not tert] -1.05164 34 2

=CH2 [olefinic carbon] -0.47888 44 2

=CH- or =C< [olefinic carbon] -0.36460 117 6

#C [acetylenic carbon] -0.28293 7 2

-OH [hydroxy, aliphatic attach] 1.60124 78 4

-O- [oxygen, aliphatic attach] 1.27460 46 3

-NH2 [aliphatic attach] 1.96561 58 2

-NH- [aliphatic attach] 2.13570 71 2

-N< [aliphatic attach] 1.96432 64 2

-CL [chlorine, aliphatic attach] -0.28720 65 6

-CL [chlorine, olefinic attach] -0.58670 16 6

-F [fluorine, aliphatic attach] -0.15800 26 5

-F [fluorine, olefinic attach] -0.05591 2 2

-Br [bromine, aliphatic attach] -0.56883 24 2

-Br [bromine, olefinic attach] -0.41966 1 2

-I [iodine, aliphatic attach] -1.07733 5 2

Aromatic Carbon (C-H type) -0.33586 700 15

Aromatic Nitrogen [max count of 1 allowed] 1.92553 62 1

-CL [chlorine, aromatic attach] -0.48781 202 10

-Br [bromine, aromatic attach] -0.56614 27 6

-OH [hydroxy, aromatic attach] 1.65780 81 1

-N [aliphatic N, one aromatic attach] 1.27489 104 1

-O- [oxygen, one aromatic attach] 0.19797 52 3

-O- [aliphatic O, two aromatic attach] 0.31806 4 1

-CHO [aldehyde, aliphatic attach] 1.10629 8 1

-CHO [aldehyde, aromatic attach] 0.65423 10 1

-C(=O)- [carbonyl, aliphatic attach] 1.05667 37 2

-C(=O)- [carbonyl, one aromatic attach] 1.00038 7 1

-C#N [cyano, aliphatic attach] 0.80635 10 2

197

-CÃ°N [cyano, aromatic attach] -0.32546 5 2

-NO2 [nitro, aliphatic attach] 0.34153 6 1

-NO2 [nitro, aromatic attach] -0.19151 65 3

-COOH [acid, aliphatic attach] 1.18078 60 1

-COOH [acid, aromatic attach] 0.05680 55 2

-N=O [nitroso] -0.45992 12 1

-S- [aliphatic sulfur,one aromatic attach] -0.42393 12 1

Aromatic Sulfur -0.27429 15 1

-C(=O)O [ester, aliphatic attach] 0.57575 51 5

-C(=O)O [ester, aromatic attach] 0.70058 32 2

-F [fluorine, aromatic attach] 0.14286 11 2

-C(=O)N [aliphatic attach] -0.24262 68 2

-C(=O)N [aromatic attach] -0.79463 16 2

-NC(=S)N- [thiourea] -4.23842 5 1

-SH [aliphatic attach] -0.38719 3 1

Aromatic Carbon (C-substituent type) -0.53995 718 12

-S- [aliphatic attach] -0.09926 11 3

S=P [thio=phosphorus] 0.87740 39 2

-O-P [aliphatic attach] -0.38266 56 4

-O-P [aromatic attach] -0.57006 29 3

-S-P [sulfur, phosphorus attach] -0.97614 19 3

O=P 3.27482 23 1

-N-P [nitrogen, phosphorus attach] -0.04017 6 2

-I [aromatic attach] -1.40688 5 1

-SO2-N [aromatic attach] -1.20034 29 2

-SO2- [aromatic attach] 1.43056 2 1

-NC(=O)N- [urea] -2.60207 44 1

-O-N [oxygen, nitrogen attach] -0.12332 4 1

Aromatic Oxygen 0.36677 12 1

-OC(=O)N [carbamate] -1.08088 23 2

-C(=O)- [carbonyl, olefinic attach] 0.11034 24 2

-ONO2 [aliphatic attach] -0.28464 4 3

-N- [aliphatic N, two aromatic attach] 0.69882 12 1

Aromatic n=O [nitrogen oxide] 2.45192 1 1

-SS- [disulfide] -1.12316 2 1

Aromatic Nitrogen [5-member ring] 0.52650 30 3

-S- [aliphatic S, two aromatic attach] -0.28517 8 1

-C(=O)- [two aromatic attach, in ring] -0.29534 1 2

-OH [combined multiple aromatic attach] 2.62371 12 1

-S-C(=O)-N- [Thiocarbamate] -1.31223 3 1

Olefinic Carbon [two aromatic attach] 0.21070 1 1

-S(=O)- [sulfoxide, aromatic attach] 2.48195 1 1

198

-N=C=S [isothiocyanate, aliphatic attach] -0.62933 1 1

-N=C=S [isothiocyanate, aromatic attach] -1.04381 2 1

-tert Carbon [3 or more carbon attach] -0.57735 81 4

-SH [thiol, aromatic attach] -0.72008 1 1

Ketone in a ring [olefin, aromatic attach] 0.09637 1 2

-N=N- [Azo] -0.26511 2 1

-CH2- [aliphatic carbon, cyclic] -0.33084 99 8

-SO2-N [aliphatic attach] 0.03908 3 2

-OH [hydroxy, nitrogen attach] 0.34519 2 1

-N [multi aliphatic N, 1 aromatic attach] 1.75391 37 1

-O- [aliphatic, 2 aromatic attach, cyclic] -0.28163 12 2

-COOH [combined multi-aliphatic attach] 1.36027 5 1

-COOH [acid, olefinic attach] 0.46464 7 2

Carbonyl, non-cyclic, two aromatic attach 1.06545 3 1

Aldehyde, [-N-CHO; aromatic attach] 0.01671 1 1

Aldehyde, [-N-CHO; aliphatic attach] 0.00691 3 1

-S(=O)- [sulfoxide, aliphatic attach] 2.06660 5 1

-SO2- [sulfone, aliphatic attach] 1.46100 4 1

-SO2-O [sulfonate, aromatic attach] -0.71767 3 1

SO2 [two aromatic attach] -0.17566 5 1

-N-SO2-N- [sulfamide] -2.05175 4 1

-CO-CO [aromatic attach] 0.07721 4 2

-C(=S)N- [aliphatic attach] -1.56100 2 1

-S-C= [S to aliphatic, double bonded C] 0.02050 2 1

-Si- [silicon, aliphatic attach (not oxy)] -2.38500 4 1

-OH [phosphorus attach] -0.63350 4 2

Aromatic nitrogen [+5 valence type; no H] 4.53400 2 1

-S- [aliphatic sulfur, 2 nitrogen attach] -0.67133 3 1

-Hg- [mercury] -0.74550 5 1

Formaldehyde experimental value - constant 0.87200 1 1

Ã°C [acetylenic carbon-acetylenic attach] -0.35375 2 2

S=C=S [carbon disulfide, experimental] -2.05900 1 1

-C(=O)-S [thioester, aliphatic attach] 0.58900 1 1

-O-SO2-O- [sulfate, linear] -2.61750 2 1

-CO-CO [aliphatic attach] 0.21953 3 2

-C(=O)-SH [aliphatic attach] 0.31367 3 2

-OC(=O)O- [carbonate,aliphatic attach] 0.36800 2 1

CÃ°N-C=N [cyano, -C=N attach] 0.27800 2 1

-C(=S)N- [aromatic attach] -0.94800 1 1

CÃ°N-S [cyano, sulfur attach] -0.08551 3 3

-SO2-OH [sulfonic], [coef*(1+0.3*(NUM-

1))]

3.84950 4 1

199

O=C=O [carbon dioxide, experimental] -1.72400 1 1

-O- [oxygen, two silicon attach, linear] -3.40000 0 0

-O- [oxygen, two silicon attach, cyclic] -2.70000 0 0

Number compds Max

occurrences

Correction Factor Description Coefficient containing

fragment

in any one

compound

Hydrocarbon [unsubst. alkane] correction -1.50129 15 1

Hydrocarbon [unsub mono-olefin] correction -0.85243 9 1

Ring reaction -> ortho to aromatic acid 0.65626 19 2

Aliphatic alcohol(mono) on aromatic struct 0.38134 20 1

Ring ortho reaction -> -OH / -COOH -1.77658 4 1

Ring reaction -> -OH / -COOH (non-ortho) -0.99298 5 1

Ring ortho reaction -> -OH / -NO2 -1.20202 11 2

Ring reaction -> -OH / -CHO -0.95018 3 1

Ring reaction -> -OH / -ester -1.41678 6 1

Ring reaction -> -Amino / -OH -1.17596 6 1

Ring reaction -> -Amino / -NO2 -0.77862 4 1

Ring reaction -> -Amino/ -COOH (non-

ortho)

-0.55123 5 1

Ring reaction -> -Amino/ -COOH (ortho) -1.51383 2 1

Ring reaction -> -Amino / -ester -0.90295 9 1

Reaction -> -OH / nitrogen (arom 6-ring) -2.52977 5 1

Di-COOH (non-ortho) aromatic ring -1.15945 2 1

C-O-C-O-C structure correction -0.74557 7 3

Fused aliphatic ring corrections (>5) 0.26117 22 6

HO-C-C(=O)-C-OH structure correction -2.74903 7 1

HO-C-C(=O)-C-O- structure correction -2.58251 6 1

-C-C(=O)-C-OH structure correction -1.29494 4 1

-CO-N-CO-N-CO- structure correction -0.27800 15 1

-N-CO-N-CO- structure correction -1.72804 6 1

Amino triazine/pyrazine/pyrimidine correc. -1.46411 16 3

Ring rx -> Halogen ortho to arom nitrogen -0.54407 10 2

Amino acid (alpha-position) correction -1.84779 13 1

Alcohol - amino acid correction -1.31839 2 1

Ring rx -> di-,poly-COOH N-aromatic ring -2.42816 6 1

Ring rx -> N-aromatic/non-ortho

COOH(mono)

-1.45266 2 1

-S(=O)-N-S(=O)- structure correction 1.56916 2 1

200

Mono-halo acetamide [-NH-CO-C-halo] -0.49490 6 1

Di-N urea/acetamide aromatic correction 0.68745 13 2

Sulfur (+4) charged-halide type 3.80000 0 0

Number compds Max

occurrences

Estimated Fragment Description Coefficient containing

fragment

in any one

compd

-OC(=O)O- [carbonate,cyclic] 1.16500 1 1

-O-C(=S)-N- [thiocarbamate] -2.88833 3 1

-O-SO2-O- [sulfate, cyclic] -1.76700 1 1

-O-SO-O- [sulfite, linear] -1.39500 1 1

-O-SO-O- [sulfite, cyclic] -1.85333 3 1

P-O-P [oxygen, two phosphorus attach] -1.07100 1 1

-C(=O)-SH [aromatic attach] -1.67100 1 1

-C(=S)-O [aliphatic attach] -0.85675 4 1

U.S. Environmental Protection Agency, 2000. On-Line WATERNT User’s Guide Water

Solubility Estimation -Fragment Methodology.

201

Appendix A8. OECD DOC Die-Away Biodegradation Test Procedures

1) MINERAL MEDIUM

a. Stock Solutions

i. A – KH2PO4 (6.8 g), K2HPO4 (17.2 g) NaHPO4 · 2H2O (26.4 g), NH4Cl

(0.4g) dissolved in 800 mL DI water

ii. B – MgSO4 · 6H2O (18.0 g) into 800 mL

iii. C – CaCl2 · 2H2O (29.0 g) into 800 mL

iv. D – FeCl3 (0.2g) into 800 mL

b. Mineral Medium; 10 mL A, into 800 mL, add 1 mL B, 1 mL C, 1 mL D, top off

to 1 L

Check with pH paper that the pH is around 7

*add a drop of diluted HCl into stock solution before preparation of mineral medium, if

precipitate forms make new stock solution

* use new mineral medium for each BDT run, dispose of extra M.M. in inorganic waste

2) INOCULUM

a. 1 part soil (stored in fridge three), 4 parts mineral medium e.g. ~25 mL soil in 100

mL M.M., into a container, with a stir bar, stir at 350 rpm, physically agitate to

get a homogeneous mixture

b. may stir overnight if necessary

c. Save ~5 mL in a 8 mL vial (label “inoculum – date”) for future analysis

3) SAMPLE COMPOUND

a. Calculate DOC (if possible) to make a test solution with ~20 ppm of Carbon in DI

water in 100 mL volumetric flask

b. Check if soluble in Mineral Medium, if not dissolve an appropriate amount of

sample into 1 L DI water for addition to Test Flasks

4) TEST FLASKS

Replicates are important as there can be large variation because of the inconsistency in

the soil concentration, and bacterial activity

a. Sample Flask (x3)

i. 100mL of M.M.

ii. sufficient amount of compound to have a DOC of 10 ppm-40 ppm

(aim for 20 ppm)

iii. 15 mL of inoculum

iv. top off solution to 125 mL with mineral medium

v. add stir bar – stir @ 350 rpm

vi. wrap flasks in tin foil (completely dark) and loosely cover top with tin foil

(aerobic)

202

vii. label as compound i, ii, and iii

b. Control Flask (x2)

i. 100 mL of M.M.

ii. 15 mL of inoculum

iii. top of solution to 125 mL with mineral medium

iv. add stir bar – stir @350 rpm

v. wrap flasks in tin foil (completely dark) and loosely cover top with tin foil

(aerobic)

vi. label flasks control i, ii

5) TESTING

a. Shake flasks before sampling. Take between 0.1 mL – 0.25 mL of solution from

flask with a pipet, dilute in 10 mL volumetric flask with DI water (note: do not

want to take >1 mL to keep the volume as consistent as possible)

b. Mix thoroughly

c. Follow DOC procedure to test on TIC/TOC

d. Test Regularly; at least twice within 24 h, if stable test every couple days (i.e.

once a day if declining >5% rate, and every 2-3 days if slower)

6) CALCULATING %BIODEGRADATION

𝐷(𝑡) = (1 − [𝐶(𝑡) − 𝐶𝑏(𝑡)

𝐶(𝑜) − 𝐶𝑏(𝑜)]) ∗ 100

D(t) = %degradation at time t

C(t) = mean concentration of sample flasks at time t

Cb(t) = mean concentration of control flasks at time t

C(o) = initial mean concentration of sample flasks

Cb(o) = initial mean concentration of control flasks

*graphical representation has been %biodeg (percent) over time (hours)

203

Appendix A9. Literature Review on Remediation Strategies to Treat Sulfolane

Contaminated Sites by Calista Yim.

ABSTRACT

Sulfolane is a water miscible contaminant that is used in petroleum refining operations to

extract aromatic and sulfur compounds. Sulfolane typically leaks or spills from these facilities

and if it enters the soil and groundwater, it will travel as a function of groundwater velocity,

hydraulic gradient and hydraulic conductivity. The toxicity of sulfolane in humans is not well

understood but sulfolane has been observed to cause neurological damage and death in lab

animals and aquatic organisms (CCME, 2006). Several sulfolane remediation studies are

discussed in this paper including natural attenuation, biotic and abiotic remediation strategies.

Each method was evaluated to determine the efficiency and effectiveness in degrading sulfolane

and minimizing other impacts of sulfolane on the environment such as formation of intermediate

products.

INTRODUCTION

Sulfolane (C4H8O2S), also known as tetrahydrothiophene 1,1 – dioxide, is a colorless and

odorless inert organosulfur solvent with high hydrophilicity and high thermal stability (Fig. 1)

(Janda, 2016). It was invented over half a century ago as part of the Shell Sulfinol gas

sweetening process and since then it has been used extensively in Canada where sulfur-rich

petroleum is abundant (Saint-Fort, 2006). This chemical is used extensively at many sour-gas

processing plants because it is efficient at removing toxic levels of polar compounds such as

H2S, CO2, COS, CS2 and mercaptans from natural gas (Mehrabani-Zeinabad, 2016). As well, due

to its high thermal stability, natural gas plant operators find sulfolane cost-effective to use as it

can be easily regenerated and reused. However, accidental spills and leakages often occur at

landfills and surface storage ponds, with insufficient lining and monitoring systems, and allow

sulfolane to escape into the environment (CCME, 2006). When sulfolane reaches the

environment, it immediately penetrates through soils, wetlands near the plant site, vadose zone

and infiltrate groundwater (Izadifard et al., 2018).

It is important to understand that sulfolane has unique chemical properties unlike any

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other contaminant. Sulfolane has low vapor pressure which means that it is non-volatile and

cannot be easily detected through the olfactory system (CCME, 2006). Also, it has low octanol-

water partition coefficient (Kow = 0.1 to 0.01) which means sulfolane is highly miscible in the

aqueous phase but does not interact with organic particles (Stewart, 2010). Besides these water-

like characteristics, it is moderately basic and has high thermal stability with a boiling point of

285 oC (Headley et al., 2002). Once sulfolane contamination sites are identified, groundwater

and sediment samples are collected and prepared for analysis with the gas chromatography mass

spectrometry, liquid chromatography (positive ion) and electrospray negative ionization to

analyze vegetation extracts in aqueous solutions (Headley et al., 2002).

Since sulfolane behaves similarly to water, it has great potential to migrate far from

contaminated sites, travel at a velocity of groundwater flow and pose a high risk for animals and

humans (Izadifard et al., 2018). In one of many cases, a sulfolane spill incident that occurred in

2004 at the North Pole refinery in Alaska has affected over 1500 households and is still

spreading to this day (Saint-Fort, 2006). Which is why understanding the chemical

characteristics of sulfolane is essential in determining the mobility of sulfolane in the subsurface

and its potential to reach areas that pose as a risk for humans and animals (Saint-Fort, 2006).

Currently, the effect of sulfolane in humans is poorly understood however sulfolane has

been administered in high doses to lab rats and guinea pigs and its toxicological properties are

well documented with animals (Anderson et al., 1977). Sulfolane was observed to be toxic for

lab animals when doses exceeded 200 mg/kg. Some of symptoms which indicated sulfolane

toxicity are convulsions, seizures, depression and other neurological damage. Surprisingly,

sulfolane exhibits low toxicity to aquatic plants and organisms unless administered in high

concentrations (>1000 mg/L) (CCME, 2006; Headley et al., 2002; Doucette et al., 2005). The

Canadian Council of Ministers for the Environment (CCME) established the tolerable daily

intake of sulfolane for humans to be 0.0097 mg/kg*day while the limit in soil is 0.8 mg/kg for

land use based on the toxicological information on sulfolane collected from several studies on

animals and aquatic organisms (CCME, 2006).

Despite these health risks, sulfolane is an emerging contaminant that has been in use for

over five decades and is still widely used today. The persistent effect of sulfolane in the

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environment and its impact on human health are not well understood, therefore more research is

needed to understand the behaviour and fate of sulfolane in the environment (Janda, 2016). In

addition, appropriate remediation strategies, discussed in this paper, can be implemented to

minimize impact of sulfolane on the environment.

NATURAL ATTENTUATION AND BIOLOGICAL REMEDIATION STRATEGIES

If nature can stop the rapid spread of sulfolane in the environment and degrade the

contaminant over time, it would be the most cost-effective remediation method. Unfortunately,

Izadifard et al. (2018) stated that natural processes are not effective in sulfolane removal. Since

sulfolane has high water solubility, the main transport mechanism in contaminated environments

is ground water flow or advection. Saint Fort (2006) studied the natural attenuation of sulfolane

through sorption onto soil and subsurface materials collected near a sour gas plant facility north

of Calgary. This study also explored sulfolane biodegradation under aerobic and anaerobic

conditions in the presence of nitrogen. The sample materials collected included sand, silt and

clay, but Saint Fort (2006) suggests the subsurface materials were ineffective against slowing the

rate of sulfolane. Despite manipulating the different sorbent materials in which sulfolane was

passed through, the ionic strength of the contaminant solution and environment temperature,

Saint Fort (2006) could not detect significant amounts sulfolane biodegradation under anaerobic

conditions. In the study by Luther et al. (1998), the researchers also concluded that classic

aquifer material had negligible impact on sulfolane sorption except their laboratory results

showed sulfolane had better adsorption response with clay minerals compared to soil organic

matter. In both anaerobic experiments by Saint Fort (2006) and Luther et al. (1998), microcosms

continued to produce CO2, which indicated that the sulfolane concentrations used was not toxic

to the microorganisms, however the microbial community did not identify sulfolane as a food

source.

Fedorak and Coy (1996) demonstrated that aerobic conditions improved sulfolane

biodegradation in both soil and groundwater samples but minimal degradation was observed

under anoxic conditions. Saint Fort (2006) observed most sulfolane loss at sample depths of 0 -

0.20 m where aerobic microbial biodegradation was most active. Furthermore, Saint Fort (2006)

recognized that biodegradation rates decreased with increasing depth, but improvement was seen

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in biodegradation rates when additional nitrogen was supplied to microcosms at a 25 oC

environment. On the other hand, Greene and Fedorak (2001) reported an increase in the rate of

sulfolane biodegradation when phosphate supplementation was administered to aerobic

microcosms. For natural sulfolane biodegradation to occur, Saint Fort (2006) concluded that

microorganisms showed increased sulfolane biodegradation rate when supplied with oxygen,

nitrogen and warm environments (25 oC). Whereas the results from the study by Greene &

Fedorak (1998), showed most optimal microbial biodegradation of contaminated sediments when

temperatures were between 8 – 28 oC, when sufficient oxygen, nitrogen and phosphorus was

supplied and coupled with Mn (IV) and nitrate-reducing conditions. Janda (2016) also noted that

the addition of nitrogen and phosphorus stimulated biodegradation at a Canadian natural gas

plant, but it was not clear whether the soils were nutrient-deficient to begin with or if the nutrient

addition was applicable to all sulfolane contamination sites. However, Saint Fort (2006) and

Greene and Fedorak (2001) both agree that oxygen and warm environmental temperatures are

essential elements for successful sulfolane biodegradation. Adjusting the environment

temperatures for in situ aerobic biodegradation may be an issue especially for sulfolane

contamination in colder regions such as Canada.

The study by Kasanke and Leigh (2017) examined the sulfolane degradation rate in

presence of other hydrocarbon contaminants and with limited nutrients supply. Similar to the

results from Saint Fort (2006) and Greene and Fedorak (2001), Kansanke and Leigh (2017)

observed aerobic sulfolane biodegradation as well except only under nitrate, sulfate and iron

reducing conditions and nutrients amendments was not seen to accelerate biodegradation rates in

sediment unlike the studies by Saint Fort (2006) and Greene and Fedorak (2001). However

nutrient supplementation was more successful in stimulating aerobic degradation in groundwater.

Another perspective regarding aerobic biodegradation addressed by (ARCADIS, 2013) relates to

the intermediate products that are produced during the sulfolane degradation reactions. Some

intermediates produced may be easily biodegraded or are identified as food sources for microbial

communities, however other intermediates may be more toxic to human health than sulfolane

(ARCADIS, 2013).

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Chou and Swatloski (1983) studied sulfolane biodegradation in refinery wastewater using

mixed microbe cultures but biodegradation ceased when sulfuric acid formed as a product and

decreased pH which could not be tolerated by the microbe cultures. Then Greene and Fedorak

(1998) attempted to isolate pure cultures of sulfolane-degrading bacteria but showed difficulty in

obtaining aerobic bacteria. The researchers then used pH sensitive agar as a medium to develop

the sulfolane degrading colony and showed success in identifying and isolating the bacteria.

Despite successfully isolating the sulfolane-degrading bacteria under laboratory conditions, these

bacteria may not survive and thrive in natural environments.

Another natural sulfolane attenuation method is to utilize wetland plants and vegetation to

absorb sulfolane contaminated waters. Doucette et al. (2005) discovered wetland plants, around a

sour gas facility, had greater concentrations of contaminants in their structural composition.

Inspired by this discovery, they conducted sulfolane uptake experiments using cattails (Typha

Latifolia), which are common in wetlands. Despite sulfolane being one of the largest

contaminants in groundwater, it was not toxic to the cattails because sulfolane is a neutral

compound which gets readily passed through the cattails' root membrane. Therefore, wetland

plants may play a significant role in sulfolane removal in aqueous settings, that is, if the plants

do not release sulfolane during decomposition or winter dormancy (Doucette et al., 2005).

ABIOTIC REMEDIATION STRATEGIES

In situ biological remediation strategies using microcosms are often more cost effective

than abiotic remediation strategies but biotic strategies may not always be successful for

degrading sulfolane at every contamination site as it is difficult to test what stimulates

microorganisms to quickly biodegrade sulfolane when each environment varies in temperature,

sulfolane-degrading bacteria and nutrient supplies (Saint Fort, 2006; Greene et al., 2001 and

Kasanke and Leigh (2017). However consistent results are often seen with active oxidation

processes used to treat and degrade sulfolane (ARCADIS et al., 2013). In the study by Yu et al.

(2016), they discovered that sulfolane would degrade fastest under UVC irradiation in

combination with oxidants such as H2O2 or O3. Both Yu et al. (2016) and Izadifard et al. (2017)

agree that neither H2O2 nor O3 alone could degrade sulfolane efficiently, but the combination of

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using both oxidants (Fig. 2) could degrade more than 90% of sulfolane in 1 hour (Yu et al.,

2016). Furthermore, UVA radiation only worked well with oxidant TiO2 (Fig. 3) and showed

90% of sulfolane degraded in 1.5 hours (Yu et al., 2016). Izadifard et al. (2017) also tested

oxidation methods using UV radiation with O3 and found the rate of sulfolane degradation to be

even greater when calcium peroxide and lime (CaO) was used with ozone (Fig. 4) to degrade

sulfolane in water. Izadifard et al. (2017) hypothesized that CaO had a significant impact on the

reaction efficiency by raising the pH of the overall reaction and the calcium ions can bind with

intermediate products during sulfolane degradation to form insoluble precipitates. Yu et al.

(2016) concluded in their study that utilizing two oxidants (O3 and H2O2) was most effective at

achieving higher degradation rates with sulfolane. But in the study by Izadifard et al. (2017),

they showed that their CaO2/UV system worked 40% faster than systems using UV and O3. Both

Mehrabani-Zeinabad et al. (2016) and Izadifard et al. (2017) investigated the mineralization of

sulfolane using UV/O3/ H2O2 in a tubular reactor except Mehrabani-Zeinabad et al. (2016)

investigated the mineralization of sulfolane through measuring the amount of CO2, H2O and

sulfate produced while Izadifard et al. (2017) mineralized sulfolane by forming CaCO3.

Interestingly, Mehrabani-Zeinabad et al. (2016) claims that high alkalinity (CO3 2-

concentrations) conditions can quench hydroxyl radicals and inhibit degradation, but Izadifard et

al. (2017) showed results with improvement in sulfolane biodegradation occurring at high

alkaline pH conditions when CaO was used with O3/ UV system. In summary, using CaO along

with O3/ UV may be more efficient than using O3/ UV alone as this method suggested by

Izadifard et al. (2017) can be used as in situ treatment for sulfolane contaminated groundwater

and this method required less treatment time, 30% less ozone and CaO is readily available.

However, Mehrabani-Zeinabad et al. (2016) explains that laboratory sulfolane biodegradation

results are not representative of what occurs in natural environments as their sulfolane

degradation rates were lower in contaminated groundwater compared to experimental lab results.

Izadifard et al. (2017) does also discuss the disadvantages of using oxidants because oxidants

have low solubility and stability in water and high production cost. In addition, reactions

between ozone and organic matter forms aldehydes and carboxylic acids, both of which do not

react with ozone which may result in a low kinetic reaction.

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CONCLUSION

The effect of sulfolane in humans has not been documented, but the toxic effects of

sulfolane has been observed in lab animals. The chemical properties and characteristics of

sulfolane is well established such as its ability to percolate effortlessly into soils and sediments

therefore making natural attenuation through subsurface aquifer materials ineffective. However,

potential natural attenuation is observed with using wetland cattail plants to absorb sulfolane

contaminated waters. Anaerobic biodegradation is also ineffective at removing sulfolane but

aerobic conditions show more promising results depending on the oxygen supply, nutrient

amendments and reducing conditions of the contaminated site. Advanced oxidation processes

(AOP) uses a combination of ultraviolet radiation, oxidants and calcium peroxide or lime to

break down or mineral sulfolane. AOP are efficient and show much faster degradation results

compared to aerobic biodegradation which can take several days whereas AOP may take several

hours. Each remediation method has its own benefits and disadvantages but it is important to

consider all possibilities for remediation, natural, abiotic or biotic degradation methods,

depending on the budget and time allowed for each contaminated site. Sulfolane is a persistent

contaminant with high infiltration ability. Sulfolane has affected many areas and residents for the

past several decades (CCME, 2006), to prevent the risk of sulfolane exposure to humans and

animals, continued research in this area is needed to determine in situ degradation methods

which are also stable and cost effective.

Figures in Appendix A9

Figure 1. Chemical structure of sulfolane (Saint-Fort, 2006)

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Figure 2. Degradation of sulfolane using oxidants and UV radiation. (a) UVA, (b) UVC, (c)

H2O2, (d) O3, (e) H2O2 + O3 (Yu et al., 2016).

Figure 3. Degradation of sulfolane using UVA radiation and oxidants (Yu et al., 2016)

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Figure 4. Degradation of sulfolane using CaO2/O3 compared to UV/O3 (Izadifard et al. 2017)

Figure 5. Degradation of sulfolane using UV radiation combined with O3 and H2O2 (Izadifard et

al. 2017).

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