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This PhD work on "Biomethanation of Non-Extractable Coal: An Engineering-Economic Model of Sustainable Energy & Environment Security" concludes that biomethane (biogenic methane) harvesting from any and all types of coal is feasible, however, capacity building research for microbial characterization of targeted coal is imperative.
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BIOMETHANATION OF NON-EXTRACTABLE
COAL: AN ENGINEERING-ECONOMIC MODEL OF
SUSTAINABLE ENERGY AND ENVIRONMENT
SECURITY
A Thesis
SUBMITTED TO
BIRLA INSTITUTE OF TECHNOLOGY
FOR THE AWARD OF THE DEGREE OF
DOCTOR OF PHILOSPHY
in
ENGINEERING
By
UMESH PRASAD SINGH
DEPARTMENT OF BIOTECHNOLOGY
BIRLA INSTITUTE OF TECHNOLOGY
MESRA: RANCHI, INDIA
2011
This thesis is dedicated to the memory of my wife
Meera Singh (7th November 1956 2nd January 2011)
i
APPROVAL OF THE GUIDE
Recommended that the thesis entitled Biomethanation of Non-Extractable
Coal: An Engineering-Economic Model of Sustainable Energy and Environment
Security prepared by Mr. U. P. Singh under my supervision and guidance be
accepted as fulfilling this part of the requirements for the degree of Doctor of
Philosophy.
To the best of my knowledge, the contents of this thesis did not form a basis
for the award of any previous degree to anybody else.
Date:
(Dr. A. S. Vidyarthi)
Guide
Professor& Head
Department of Biotechnology
BIT, Mesra, Ranchi
India
ii
ACKNOWLEDGEMENTS
I accolade my highest respect to Dr. A. S. Vidyarthi, Professor and Head,
Department of Biotechnology, BIT, Mesra and Chairperson of my doctoral
committee for his acceptance to guide an inter-disciplinary subject, immense
encouragement, necessary facilities, constant monitoring, instant availability to
support and guide during the course of my research work and preparation of this
manuscript.
I tender my sincere thanks to Dr. A Sachan, Dr. Usha Jha, and Dr. S. K. Bose
members of my doctoral committee for giving their continued invaluable suggestions
to improvise my research work, encouragement, and support to cross the inter-
disciplinary hurdles since beginning to date.
I am thankful to Dean, PG & Research, for his time to time suggestions to
make this study more focused and purposeful.
I thank Prof. Ashok Mishra for valued discussions that helped in giving an
academic shape to this inter-disciplinary industrial problem and Miss Meenakshi
Singh for her tips on conversion of concepts to graphics. My candid thanks are to
Prabhat Ji, Amit Ji, and Mr. Sankaracharya for their constant support and co-
operations.
This work is effort of many people. I thank all of them. In last 23 years of my
association with coal industry, I had gone through a number of books, research
papers, conferences/ seminars proceedings, paper clippings, web sites, etc.; and had
personal discussions with a number of people (experts in their own fields) to
conceptualize this multi-disciplinary coal biomethanation project. I acknowledge
contributions from all these corners that directly or indirectly helped me in coming to
this stage. I express my gratitude to all of them.
Last but not the least, I am thankful to BIT for giving me an opportunity to
take up this research work here.
(Umesh Prasad Singh)
iii
TABLE OF CONTENTS
Page Nos.
Approval of the Guide i
Acknowledgement ii
Table of Contents iii-x
Abstract xi-xii
Abbreviations xiii-xv
Notations Used xvi- xx
List of Figures xxi-xxiii
List of Tables xxiv
Chapter 1: Introduction 1-12
1.1 Energy Scenario of India 1-4
1.1.1 Energy Demand 1
1.1.2 Energy Supply 1-2
1.1.3 Options to Bridge the Gap 2
1.1.4 Augmentation of Resources 2-4
1.1.5 Coal Mainstay Fuel 4
1.2 Energy Security of India 5
1.1.6 Environment Security under Threat 5
1.1.7 Challenges 5
1.3 Non-Extractable Coal 6 7
1.3.1 CBM Recovery 6
1.3.2 In-situ Thermal UCG 6-7
1.3.3 Non-Extractable Coal as a CO2 Sink 7
1.4 In-situ Biomethanation of Non-Extractable Coal 7 -8
1.4.1 Hypothesis 8
1.5 Objectives of the Research work 8 -9
1.6 Scope and Organization of the Research Work 9 -12
Chapter 2: Literature Review 13-53
2.1 Biomethanation of Coal 13-19
2.1.1 Methanogenesis Pathways 15-17
2.1.1.1 Hydrogen Pathways 17
iv
Page Nos.
2.1.2 Microbial Growth and Environment 17
2.1.3 In-situ Coal Biomethanation 17-18
2.1.4 Sources of Microbial Consortia 18-19
2.2 Coal Chemistry 19-34
2.2.1 Macromolecular Geopolymers 20-21
2.2.2 Structure of Coal 21-26
2.2.2.1 Structural Changes with Rank 22-25
2.2.2.2 Lithotypes 25-26
2.2.3 Constituents of Coal 26-27
2.2.4 Oxygen in Coal 27-28
2.2.5 Water in Coal 28-29
2.2.6 Coal Porosity and Other Related Properties 29- 33
2.2.6.1 Cleat System and Natural fracturing 29-31
2.2.6.2 Microbial Accessibility of Coal 31-32
2.2.6.3 Apparent Density of Coal 33
2.2.6.4 Swelling of Matrix 33
2.2.7 Microbial Uniqueness of Coal 33-34
2.3 CO2 Sequestration 34-35
2.4 Anaerobic Hydrolysis of Complex Substrate 35-52
2.4.1 Enzymatic Hydrolysis Process 35-37
2.4.2 Factors Affecting Anaerobic Hydrolysis 37-43
2.4.2.1 Environmental Factors 37-38
2.4.2.2 Substrate Related Factors 39-40
2.4.2.3 Inhibitors 40-43
2.4.3 Hydrolysis Acceleration 43-45
2.4.3.1 Pre-Treatment 43-44
2.4.3.2 Enzyme Addition 44
2.4.3.3 Amorphogenesis 44-45
2.4.4 Hydrolysis Kinetics 45-50
2.4.5 Hydrolysis of Lignocellulosic Substrates 50-52
2.5 Conclusions 52-53
v
Page Nos.
Chapter 3: Coal Hydrolysis 54-63
3.1 Mechanism 54-56
3.1.1 Oxic and Anoxic 55
3.1.2 Attachment 55-56
3.1.2.1 Biofilm Formation 55-56
3.2 Depolymerization 56-58
3.3 Solubilization 58-60
3.3.1 Solvents and Surfactants 59-60
3.4 Products of Hydrolysis 60-62
3.5 Hydrolysis Rate Limiting Step in Coal
Biomethanation 62
3.6 Methodology for Hydrolysis Assessment: Substrate
Utilization Rate 63
3.7 Conclusions 63
Chapter 4: CoalBioreactor: An Economical and Accelerated in-situ
Coal Biomethanation Mechanism 64-90
4.1 Design 64-69
4.1.1 Fractured Coal within Impermeable Boundary 64-65
4.1.2 Purpose 65
4.1.3 Aim 65
4.1.4 Features and Components 66-67
4.1.5 Facilities 67-69
4.1.5.1 Subsurface 67-68
4.1.5.2 Surface 68-69
4.1.5.3 Subsurface and Surface Connectivity 69
4.2 Construction 69-79
4.2.1 Site Selection 70
4.2.1.1 Data Collection 70
4.2.1.2 Data Generation: Seismic Survey and
Reservoir Imaging 70-71
4.2.2 Technologies and Techniques Selection 71
4.2.3 Well Development 71-73
4.2.3.1 Diameter, Casing Size, and Material 72-73
vi
Page Nos.
4.2.4 Fracturing 73-77
4.2.4.1 Perforating 75
4.2.4.2 Jetting 76
4.2.4.3 Fracture Gradient 76
4.2.4.4 Coal Subsidence 76
4.2.4.5 Fracturing Fluids 76-77
4.2.5 Impermeable Boundary 77-79
4.2.6 Sump 79
4.3 Connectivity with Surface 79-81
4.3.1 Hydraulic Fracturing Pipe/ Production Pipe
for Recovery of Biomethane 79
4.3.2 Spray of Growth Medium, Nutrients, and
Other amendments 80
4.3.3 CO2 Injection Pipe 80
4.3.4 Recovery of Spent Medium 81
4.4 Operation 81-88
4.4.1 Biofilm Formation 81-82
4.4.1.1 Retention of Microbes 82
4.4.2 Biomethane Generation (Harvesting) 83-84
4.4.3 Measurement and Control of Parameters 84-85
4.4.4 Sequence of Injecting Fluids, Microbes, and
Nutrients 86-88
4.5 CO2 Sequestration 88-89
4.6 Advancement of Construction Sites 89
4.7 Conclusions 90
Chapter 5: CoalBioreactor Kinetics 91-118
5.1 Microbial Growth: Substrate Limited 91-93
5.1.1 Quantity of Primary Substrate (Coal) in
CoalBioreactor 91
5.1.2 Quantity of Coal Carbon Polymers 91
5.1.3 Quantity of Actual Substrate (Hydrolysable
Coal Carbon Polymers) 92-93
5.2 Hydrolysis: Rate Limiting Step 93
5.3 Acidogens in CoalBioreactor 94-101
vii
Page Nos.
5.3.1 Inoculation of Single Seed Concentration of
Consortium (SSCC) 94
5.3.2 Attachment of Acidogens to Coal Surfaces 94-98
5.3.2.1 Biofilm Formation on Coal Surfaces 95-97
5.3.2.2 Contact-Inhibited Growth of Acidogens 97-98
5.3.3 Hydrolysis Mechanism 98-101
5.3.3.1 Accumulation of Enzymes in
Hydrodynamic Boundary Layer 98
5.3.3.2 Diffusion of Enzymes in Coal Pores 98-99
5.3.3.3 Diffusion of Enzymes in Crystalline
Coal Macerals 99
5.3.3.4 Actual Substrate-Enzyme Surface Area
and Enzyme Penetration Rate 99-101
5.4 Kinetic Parameters: SBK Model 101-116
5.4.1 Hydrolysis Rate 112
5.4.2 Biomethanation Potential (BMP) 112-115
5.4.2.1 Enhanced BMP 114
5.4.2.1 Commercial BMP 114-115
5.4.3 CO2 Sequestration Potential (CSP) 115
5.4.4 Commercial Energy Availability 115-116
5.4.5 Project Carbon Neutrality 116
5.4.6 CoalBioreactor Starting Period 116
5.4.4.1Best Case Scenario (BCS) 116
5.4.4.2 Worst Case Scenario (WCS) 116
5.5 Conclusions 117-118
Chapter 6: Engineering-Economic Model 119-144
6.1 Challenges 119-123
6.1.1 Uncertain Parameters 119-120
6.1.1 Project full of Risk and Experimentation 120-121
6.1.2 Is Non-Extractable Coal Biomethanation
Project Worth It? 121-123
6.2 Development of an Engineering-Economic Model 123-125
6.2.1 Major Reasons 124
6.2.2 Main Objectives 124-125
viii
Page Nos.
6.3 Basic Components 125-128
6.3.1 Engineering Model 125-126
6.3.1.1 Design and Construction of an in-situ
CoalBioreactor 125
6.3.1.2 CoalBioreactor Kinetics 125
6.3.1.3 Mathematical Model 126
6.3.2 Economic Model 126-128
6.3.2.1 Net Present Value 126
6.3.2.2 Costs 127
6.3.2.3 Benefits 127
6.3.2.4 Financial Adjustments 127
6.3.2.5 Benefit-Cost Analysis 127-128
6.4 Mathematical-Economic Models 128-142
6.4.1 Inputs 128-137
6.4.1.1 Validation of Data 129
6.4.1.2 Input Assumptions 129-137
6.4.2 Simulation 137
6.4.3 Parameters Forecasted 137-138
6.4.4 Frequency Distribution Forecasted Results 138-139
6.4.5 Monte Carlo Simulation for Risk Analysis 139-140
6.4.6 Software Used: Excel Spreadsheet with
Crystal Ball 140-141
6.4.7 Model Assumptions Made 141
6.4.8 Mean Standard Error 142
6.4.9 Correlations 142
6.5 Compromise Made 142-144
6.6 Conclusions 144
Chapter 7: Results and Discussions 145-167
7.1 Deterministic Exploratory SSCC Model 145-146
7.2 Stochastic Exploratory SSCC Model 146-154
7.2.1 Project: Time Duration 149-151
7.2.1.1 Dynamic Time Duration of Project 149
ix
Page Nos.
7.2.1.2 Fixed Buildup Phase Time Duration
(FBPTD) 149-150
7.2.1.3 Sensitivity Analysis for Identification
of Inputs Values 150-151
7.2.2 Stochastic SSCC Model with FBPTD and VIV 151-154
7.3 Impact of Common Apprehensions, Inhibitions, and
Hopes 154-160
7.3.1 Apprehensions 154-155
7.3.2 Inhibitions 155
7.3.3 Hopes 155
7.3.4 Findings 155-159
7.3.4.1 20% Reduction in Bioavailability of
Actual Substrate 157
7.3.4.2 20% Reduction in Actual substrate-
Enzyme Surface Area 157-158
7.3.4.3 20% Reduction in Enzyme Penetration
Rate 158
7.3.4.4 20% Reduction in Specific Growth Rate
of Acidogens 158
7.3.4.5 20% Enhanced Coal to Biomethane
Conversion Factor due to ECHRMP 158-159
7.3.5 Wax Accumulation Problem 159-160
7.4 Gross Sensitivity Analysis and Stress Testing 160-163
7.4.1 Impact of Varying Microbial Geological
Biomethanation Conditions 161-162
7.4.2 Real Challenges: Feasibility of WMGBC
Project 162-163
7.5 End Result: Hydrolysis Rate Constant for Coal 163-164
7.6 Impact of Non-Extractable Coal Biomethanation
on Economy 164-166
7.6.1 Economics 165
7.6.2 Energy Security 165
7.6.3 Environment Security 165
7.6.4 Sustainability of Energy and Environment
Security 166
7.7 Conclusions 166-167
x
Page Nos.
Chapter 8: Verification & Validation of Models 168-176
8.1 Model Verification and Validation Process 169
8.2 Verification 169-170
8.3 Validation 171-176
8.3.1 Modified View Points on Validation 172-174
8.3.2 Model Implemented is the Model Intended 175-176
8.3.2.1 Development of Scientific
Understanding 175
8.3.2.2 Testing the Effect of Changes in the
System 175
8.3.2.3 Decision Making Aid 176
8.4 Conclusions 176
Chapter 9: Conclusions 177-179
Future Scope of Works 180
References 181-201
List of Patents & Publications 202
xi
Biomethanation of Non-Extractable Coal: An Engineering-Economic
Model of Sustainable Energy and Environment Security
Abstract
Biomethanation of coal in-situ is an innovative approach to utilize non-
extractable coal as a source of energy as well as a sink for CO2 sequestration to add in
energy and environment security of an economy. Though scientists and technologists
are aware of chemical energy potential of in-situ coal, however to date there is no
basis even to guess how far and how fast this energy would be available commercially
at surface in form of biogenic methane (biomethane). Therefore, decision makers, at
present, are apprehensive about success (techno-economic feasibility) of an in-situ
coal biomethanation project.
The natural process of biomethanation can be accelerated in such coals that
have favourable microbial geological biomethanation conditions (MGBC), and there
are some proposals and schemes for the same. However, there is no proposal and
scheme for biomethanation of coals that lack natural favourable MGBC.
This study hypothesizes that biomethanation of all types of coal in-situ is
techno-economically feasible.
To test the hypothesis, a mechanistic engineering-economic model has been
developed that assesses prospect of an envisaged in-situ biomethanation project in any
and all types of coal. Basic components of engineering model are: (a) design and in-
situ construction of a CoalBioreactor initially on a part or total of the target coal, (b)
CoalBioreactor kinetics, and (c) a mathematical model. CoalBioreactor is an envisaged
engineered, natural, at times imitated, trouble-free, cost-effective in-situ mechanism to
make biomethanation of all types of coal in-situ possible. It considers hydrolysis as the
rate limiting step in biomethanation of solid, dry, insoluble complex coal substrate in-
situ. CoalBioreactor kinetics formulates operational effectiveness of CoalBioreactor.
CoalBioreactor and its kinetics combined together provide the basic framework for
development of the mathematical model. For economic analysis of this engineering
model, an economic model has been developed that is basically a benefit-cost-analysis
(BCA) model that helps in rational decision making regarding Is an in-situ non-
extractable coal biomethanation project to date in a target coal worth it?
xii
The mathematical-economic (CoalBioreactor Biomethanation) model is a
dynamic, quantitative, lumped, stochastic, mechanistic, continuous, sub-model based,
verified, and virtually validated (V & VV) model. It has been developed in Microsoft
Excel Spreadsheet with Crystal Ball add-in that has used Monte Carlo simulation for
risk analysis. Model inputs are based on abstraction and generalization of limited
empirical hard data documented in literature. It also includes secondary data derived
from these primary hard data based on mechanistic logical conclusion, and assumption
of some missing inputs (initially). It computes forecasted parameters (outputs) on
discrete points in time. Exploratory analysis of model rudimentary estimates
(forecasts) of buildup phase time duration (i.e. the time acidogens take to fully cover
the entire coal surfaces exposed to them), and inputs values help in identifying more
rational values of inputs. Simulation run of the model with these validated inputs
values estimates the ultimate probability distribution of the forecasted parameters.
Decision makers know the certainty level attached with each forecasted result, and
therefore, the risk associated in accepting a forecast.
Model could be used as an exploratory e-laboratory to tackle the real world
challenges of in-situ coal biomethanation. Based on substrate depletion rate, the
surface based hydrolysis rate constant, in an envisaged CoalBioreactor, is in the range
of 2.06 to 2.67 gm m-2
d-1
with 2.506 gm m-2
d-1
as the most likely value. This estimates
commercial energy availability (CEA) in the range of 56.83 to 75.35% with a mean
value of 66%, project carbon neutrality (PCN) of 72.54%, and 100% certainty of
commercial viability of a project in a most probable MGBC coal. By identifying and
suggesting most appropriate technology mix, model demonstrates techno-economic
feasibility of a biomethanation project even in a worst MGBC coal. This verifies the
hypothesis that biomethanation of all types of coal is possible by designing and
constructing a CoalBioreactor in the target coal.
Impact analysis of in-situ non-extractable coal biomethanation on economy
(Indian) suggests average net present earning of more than 340 INR (in the range of 70
to 810 INR) per tonne of in-situ coal. It alone has potential of meeting primary energy
requirement of the country for more than 37 years and mitigating total emission for
more than 40 to about 60 years, considering 2031-32 as the base year.
xiii
Abbreviations
ABCDE : Alkaline substances Biocatalysts Chelators Detergents Esterases
AD : Anaerobic Digestion
ASTM : American Society for Testing and Materials
BAU : Business as Usual
BCA : Benefit Cost Analysis
BCM : Billion Cubic Meters
BCS : Best Case Scenario
BMGBC : Best Microbial Geological Biomethanation Conditions
BMP : Biomethanation Potential
BT : Billion Tonne
BTU : British Thermal Unit
CBCF : Coal to Biomethane Conversion Factor
CBM : Coalbed Methane
CDM : Clean Development Mechanism
CEA : Commercial Energy Availability
CER : Certified Emission Reduction
CHRMP : CO2-H2 Reduction Methanogenesis Pathways
CIL : Coal India Limited
CMPDIL : Coal Mine Planning & Design Institute Limited
CSP : CO2 Sequestration Potential
CT : Coiled Tubing
DNA : Deoxyribonucleic Acid
DSM : Demand Side Management
ECBCF : Enhanced Coal to Biomethane Conversion Factor
ECBM : Enhanced Coalbed Methane
ECHRMP : Enhanced CO2-H2 Reduction Methanogenesis Pathways
EMPCF : Enhancement in Microbial Porosity of Coal through Fracturing
ENPV : Expected Net Present Value
EPR : Enzyme Penetration Rate
EPS : Extracellular Polymeric Substances
FAL : Fulvic Acid Like
FBPTD : Fixed Buildup Phase Time Duration
xiv
FTIR : Fourier Transform Infrared Spectroscopy
GCV : Gross Calorific Value
GDP : Gross Domestic Product
GHG : Green House Gas
GOI : Government of India
GSI : Geological Survey of India
HAL : Humic Acid Like
HEC : Hydroxethyl Cellulose
HMMW : Horizontal Multi-lateral Multi-seam Well
INR : Indian Rupee
IPCC : Intergovernmental Panel on Climate Change
LHW : Liquid Hot Water
LNG : Liquefied Natural Gas
LWD : Logging While Drilling
MCM : Million Cubic Meters
MECoM : Microbially Enhanced Coalbed Methane
MF : Methano Furan
MGBC : Microbial Geological Biomethanation Condition
MPa : Mega Pascal
MPMGBC : Most Probable Microbial Geological Biomethanation Condition
MPS : Most Probable Scenario
MPT : Methano Pterin
MSE : Mean Standard Error
MT : Million Tonne
Mtoe : Million Tonne Oil Equivalent
MW : Mega Watt
NIR-X ray : Near Infra Red X-ray
NMR : Nuclear Magnetic Resonance
NPV : Net Present Value
PAC : Poly Anionic Cellulose
PAH : Polycyclic Aromatic Hydrocarbons
PCN : Project Carbon Neutrality
PD : Probability Distribution
xv
PDF : Probability Distribution Function
PERT : Program Evaluation and Review Technique
py-FIMS : Pyrolysis-Field Ionization Mass Spectrometry
py-GC : Pyrolysis Gas Chromatography
RASESA : Reduction in Actual Substrate Enzyme Surface Area
RBAS : Reduction in Bioavailability of Actual Substrate
RE : Renewable Energy
REPR : Reduction in Enzyme Penetration Rate
RSGRA : Reduction in Specific Growth Rate of Acidogens
SBK : Surface Based Kinetics
SEM : Scanning Electron Microscope
SME : Subject Matter Expert
SP : Submergible Pump
SSCC : Single Seed Concentration of Consortium
TERI : The Energy Resources Institute
THF : Tetra Hydro Furan
TPCES : Total Primary Commercial Energy Supply
TPES : Total Primary Energy Supply
TPNCES : Total Primary Non Commercial Energy Supply
UCG : Underground Coal Gasification
UNFCCC : United Nation Framework Convention on Climate Change
VFA : Volatile Fatty Acid
VIV : Validated Input Value
V&V : Verified and Validated
V&V V : Verified and Virtually Validated
WCS : Worst Case Scenario
WMGBC : Worst Microbial Geological Biomethanation Condition
xvi
Notations Used
a [L] : Radius of acidogens fractional/partial patch on spherical coal
particles
A : Pre-exponential factor
A [L2] : Area of the surface available for hydrolysis
A0
[L] : Angstrom
A0 [L] : Acidogens population per patch at t = 0
Aas-e [L2] : Actual substrate-enzyme surface area
Ah [L2] : Area of hydrodynamic boundary layer
Amax-cp : Maximum number of acidogens required to cover surface area
of a coal particle
Amax-cs : Maximum number of acidogens required to cover all exposed
surfaces available in one cubic meter of coal
App-cs : Acidogens population per patch on flat surface
App-cs-l : Number of acidogens required to cover the side surface of coal
matrix block
App-cs-s : Number of acidogens required to cover the front or back surface
of coal matrix block (patch area)
avcrc [L3] : Total volume of CO2 adsorbed in residual coal
: A constant
B : Cos-1
(1-20) (An assumption)
bbtu : Fraction of biomethane recovered getting discounted for BTU
adjustment
bcs : Fraction of biomethane recovered getting used for operation of
machineries at site
BMPumc [L3M
-1] : Biomethane (volume) recovered per unit mass of coal
: Ratio of patch area to total area of sphere
0 : Ratio of patch area to total area of sphere at time t0
C1 : Swelling Factor
Ca [L2] : Surface area of coal per unit mass
ca [L] : Cleat aperture size
cbio [M] : Bioavailable coal carbon
cbecf : Coal to biomethane energy conversion factor
CBl [L] : CoalBioreactor length
CBw [L] : CoalBioreactor width
xvii
CBh [L] : CoalBioreactor height/ thickness
CBv [L3] : CoalBioreactor volume
cc [%] : Carbon content in coal
cch [%] : Hydrolysable coal carbon
cfb : Commercial biomethane factor
cfcb : Conversion factor for coal to biomethane
cfcco2 : Conversion factor for coal to CO2
cfco2b : Conversion factor for CO2 to biomethane due to enhanced CO2-
H2 reduction methanogenesis pathways (ECHRMP)
ci-mpi-f [L3/L
3] : Increase in original porosity of coal due to fracturing
cmpi [L3/L
3] : Effective porosity (microbial) of coal (void/per cubic meter
volume of coal) initial
cps [L] : Coal pore size
CSPc [M] : CO2 sequestration potential (mass) per unit mass of coal
CSPm [M] : CO2 sequestration potential (mass)
CSPrc [L3] : CO2 sequestration potential (volume) per unit mass of residual
coal
CSPv [M] : CO2 sequestration potential (volume)
cs [L] : Cleat spacing
csa [L] : Coal surface area
csai [L2] : Initial exposed coal surface area for microbes/cubic meter of
coal
Cx : Hydrolytic enzymes
d [L] : Depth of coal
da [L] : Diameter of acidogen
Dc [ML-3
] : Coal density
Dca [ML-3
]
: Density of actual substrate
DCH4 [ML-3
] : Density of biomethane
DCO2 [ML-3
] : Density of CO2
Dcp [ML-3
] : Density of primary substrate
dcp [L] : Coal particles diameter
Dh [L2T
-1] : Diffusion constant of hydrolases
Dpores [L2T
-1] : Diffusion constant of actual substrate
dpp-cp [L] : Diameter of acidogens patch on spherical coal particle
Ea [JMol-1
] : Activation Energy
xviii
ecb : CoalBioreactor efficiency
ep [LT-1
] : Enzyme penetration rate in actual substrate-enzyme surface area
F [ML-3
] : Fracture gradient
fhole : Fraction of maximum density of possible acidogens in a biofilm
hole opening
fholeeq : Fraction of cell missing in the confluent areas in the centre of
the patches
GCVbm [JL-3
] : Gross calorific value of unit volume of biomethane
GCVc [JM-1
] : Gross calorific value of unit mass of coal
h [L2] : Patch area on coal particles covered by acidogens
H4MPT : Tetra hydro methanopterin
Has-bio [ML-3
] : Concentration of hydrolyzed actual substrate in biofilm
bioavailable to acidogens
Has-pores [ML-3
] : Concentration of hydrolyzed actual substrate in pores
Hc-hbl [ML-3
] : Concentration of hydrolases in hydrodynamic boundary layer
Hc-pores [ML-3
] : Concentration of hydrolases in pores
hems [L] : Hydrolyzing enzyme molecule size
iam [M] : Inoculated acidogens mass
J [Joule] : Joule
k [MolL-3T-1] : Reaction rate constant that depends on temperature
k [T-1
] : Acidogens 1st order death rate constant
K [T-1
] : Hydrolyzed substrate transport first order rate coefficient
Kh [ML-2
T-1
] : Hydrolysis rate constant
kh [T-1
] : 1st order hydrolysis rate constant
Ksbk [ML-2
T-1
] : Surface based hydrolysis constant
Ksi [ML-1
] : Half saturation constant of limiting substrate
Kx1 : Contois constant
m [M] : Mass of substrate
ma [M] : Acidogens Mass per cell
Mhbp [M] : Mass of actual substrate hydrolyzed during buildup phase
Nc : Number of face and butt cleats (average)/per sq. meter of coal
ncp : Number of coal particles (average 8 m size) in CoalBioreactor
Nm : Number of coal matrix block per cubic meter of coal
np : Number of patches on exposed coal surface
xix
m [L] : Nano meter
P [ML-3
] : Concentration of microbes in bulk liquid
p [psi] : Wellbore pressure
pa [L2] : Area of a fully grown patch
pabp [L2] : Fractional patch area (size) covered with acidogens at any point
of time
pas-e [L2] : Actual substrate-enzyme surface area per unit area of coal
exposed to acidogens
Pav-pd [L] : Average enzyme penetration rate in coal surface
PD1 : Probability distribution representing quantity of coal in
CoalBioreactor
PD2 : Probability distribution representing % of coal carbon polymers
in coal in CoalBioreactor
PD3 : Probability distribution representing % of hydrolysable coal
carbon polymers
pesa [L2] : Actual substrate-enzyme surface area per gm of coal
pwsa [L2] : Pore water surface area
[ML-3] : Apparent density of particle substrate
Qas-pores [M] : Mass of hydrolyzed actual substrate in pores
Qh [M] : Mass of hydrolases secreted by acidogens and accumulated in
hydrodynamic boundary layer
r [L] : Radius of acidogen patch on a coal particle i.e. dpp-cp/2
R [JK-1Mol-1] : Gas Constant
rfb : Biomethane recovery factor
Rg : Biomethane to CO2 ratio in a biogas
ri [MT-1
] : Rate of hydrolysis of primary substrate
R0 [L] : Particle mean radium, initial
Rt [L] : Particle mean radium at time t
s [ML-2
] : Overburden stress
S [ML-3
] : Substrate concentration
S0 [ML-3
] : Substrate concentration in bulk liquid
Shcr [MT-1
] : Rate of hydrolysis during plateau phase or rate of hydrolysis per
patch area
Shvr [MT-1
] : Rate of hydrolysis during buildup phase
Ssurf [L2] : Surface area of organic solid
xx
Sucr [MT-1
] : Substrate utilization at constant rate during plateau phase
Suvr [MT-1
] : Substrate utilization at varying rate during buildup phase
t [T] : Time
T [K] : Temperature
Tsucr [T] : Time taken by acidogens beyond Tsuvr to fully hydrolyze the
remaining (left out) actual substrate at constant rate i.e. plateau
phase duration of actual substrate hydrolysis at constant rate
Tsuvr [T] : Time taken by acidogens to fully cover the exposed coal
surface area under a patch i.e. buildup phase duration of actual
substrate hydrolysis at varying rate
Ttsu [T] : Total time of substrate utilization
: Fraction coverage of surface
[T-1
] : Specific growth rate of acidogens
i [T-1
] : Specific growth rate of respective species
mi [T-1
] : Maximum growth rate of respective species
net [T-1
] : 1st order net growth rate constant of acidogens
m [L] : Micro meter
v : Poissons ratio
vco2(volume) [L3] : Volume of CO2 produced
vco2(mass) [M] : Mass of CO2 produced
Vi [L3L
-3] : Natural porosity of coal
vvhc [L3] : Void created due to hydrolysis of coal
wms [L] : Water molecule size
wmc/mhc [M] : Water mass consumption per unit mass of hydrolyzed coal
x(1,2,..) [L] : Diffusion path length
Yi [MM-1
] : Microbial yield coefficient
xxi
List of Figures
Sl. Nos. Title Page Nos.
Fig. 1: Overview of the Thesis 12
Fig. 2: Schematic Representation of Various Trophic Groups of
Microorganisms Involved in Anaerobic Digestion of Organic
Matters of Coal to CH4 Production 13
Fig. 3: Proposed Mechanism of Stepwise Biodegradation of Original
Material in Coal. 14
Fig. 4: Methanogenesis Pathways: Hydrogentrophic, Acetoclastic
and, Methyltrophic 16
Fig. 5: A Representative Structure of the Chemical Groups in a
Bituminous Coal 23
Fig. 6: Coal Compounds Models based on FTIR, NIR-X ray
Diffraction, NMR, py-FIMS Spectroscopy, and py-GC,
Solvent Swelling and Extraction 24
Fig. 7: Schematic of Major Constituents of Coal: Organic Material,
Inorganic Inclusions, and an Extensive Pore Network 26
Fig. 8: Oxygen in Functional Groups 27
Fig. 9: Influence of Rank on Capacity Moisture 28
Fig. 10: Brittleness of Coal 30
Fig. 11: Coal Ranks Determine Porosity 30
Fig. 12: Cleat Aperture in Coal 31
Fig. 13: Different Types of Pore in Coal 31
Fig. 14: Apparent Density of Coal 33
Fig. 15: Illustration of Hydrolysis Inhibition (A) No Inhibition, (B)
Competitive Inhibition, and (C) Non-Competitive Inhibition 41
Fig. 16: Schematic of Architectural Arrangements of Lignocellulose 51
Fig. 17: Craters on Substrate Surface due to Assimilation of
Hydrolyzed Substrate by Acidogens 54
Fig. 18: A Hypothetical Coal Structure indicating all Possible Bonds in
Coal 57
Fig. 19: The So-Called ABCDE-Mechanism of Biological Conversion
of Brown Coal 58
Fig. 20: Products of Coal Hydrolysis Shown as Intermediary Products 61
Fig. 21: Schematic of CoalBioreactor Vertical Well indicating Injection
& Collection Pipes with Representative Dimensions 73
xxii
Sl. Nos. Title Page Nos.
Fig. 22: Schematic of Fractures and Porosity in (a) Natural Coal, and
(b) After Fracturing indicating that natural porosity of coal can
be Enhanced by Inducing Fractures in coal 74
Fig. 23: Schematic of Injection of Growth Medium and Microbes in
CoalBioreactor, indicating Induced Fractures in Coal, Their
Propagation in Fractures, and Their Placement even at the
Farthest End of the CoalBioreactor 74
Fig. 24: Schematic of Coal Fractures in CoalBioreactor indicating
Pushing of Growth Medium, Microbes, & Nutrients to the
Farthest Fractured End wherein Growth Medium itself is
Acting as a Fracturing Fluid 75
Fig. 25: Schematic of Fracturing of Coal in CoalBioreactor with
Traditional Hydraulic Fracturing Fluids First and Pushing of
Growth Medium, Microbes, & Nutrients Later on 75
Fig. 26: Schematic of a CoalBioreactor indicating Impermeable
Boundaries Surrounding All Sides of the CoalBioreactor, and
a Sump with Representative Dimesnsions 78
Fig. 27: Schematic of Injection Pipes and Spent Growth Medium
Collection Pipe in the CoalBioreactor 80
Fig. 28: Schematic of Different Stages of Biofilm Formation in the
CoalBioreactor 81
Fig. 29: Schematic of Flow of Spent Growth Medium and Gases in
CoalBioreactor 83
Fig. 30: Schematic of Measurement and Control in the CoalBioreactor 85
Fig. 31: CO2 Biomethanation Pathways 89
Fig. 32: Schematic of Attached Acidogens in Coal Fractures in the
CoalBioreactor 94
Fig. 33: Schematic of Growing Monolayer Patches of Hydrolyzing
Acidogens, Acetogens Patch, and Methanogens Patch 96
Fig. 34: Schematic of Coal Matrix Blocks and Pores 99
Fig. 35: (A) Schematic of Secretion of Hydrolases by Acidogens on
Biofilm; (B) Diffusion of Hydrolases Molecules into Macro
and Some of the Mesopores of Coal Matrix Blocks; (C)
Hydrolysis of Actual Substrate in Coal Matrix Block Pores
and Diffusion of Hydrolyzed Actual Substrate; and (D)
Subsequent Acidogenesis, Acetogenesis, and Methanogenesis 100
Fig. 36: Schematic of Coal Matrix Blocks indicating Pores of Some
Selected Blocks 104
Fig. 37: Plan View of an Acidogen Patch on a Flat Coal Surface 105
xxiii
Sl. Nos. Title Page Nos.
Fig. 38: Side View of Acidogens Patch on a Coal Particle 107
Fig. 39: Growth of a Patch with Acidogen/ Coal Particle Diameter 108
Fig. 40: (a) Schematic of Enzymes in Actual Substrate-Enzyme
Surface Area, Aas-e, and (b) Schematic of Average Rate of
Enzymes Penetration (pav-pd) (Rate) in Coal Primary Substrate
Area, Ah 110
Fig. 41: Spectrum of Non-Extractable Coal Biomethanation Study 121
Fig. 42: Line Diagram of in-situ Biomethanation of Non-Extractable
Coal Study Undertaken 122
Fig. 43: Schematic of Concept of a Model 123
Fig. 44: Schematic of Engineering-Economic Model indicating
Components of Engineering Model and Mathematical
Economic Model 125
Fig. 45: Schematic of Mathematical Model of Biomethanation of Coal
in CoalBioreactor 126
Fig. 46: Forecasted Range and Statistics of Ttsu of Stochastic
Exploratory SSCC Model for Complete Hydrolysis of Actual
Substrate 147
Fig. 47: Forecasted Range and Statistics of NPVs of Stochastic
Exploratory SSCC Model 147
Fig. 48: Certainty Percentage of Mean NPV of Stochastic-SSCC
version of Model 148
Fig. 49: Certainty Percentage of Mean BMP of Stochastic-SSCC
Version of Model 148
Fig. 50: Probability Distribution of Tsuvr of Stochastic Exploratory
SSCC Model indicating (a= 10.01, b= 25.19, and m= 15.3
years) 149
Fig. 51: Sensitivity Charts of Stochastic-SSCC Version of Model for
Tsuvr and Tsucr 150
Fig. 52: BMP of VIV-FBPTD-S-SSCC Model 152
Fig. 53: NPV of VIV-FBPTD-S-SSCC Model 152
Fig. 54: (a) Sensitivity Chart of BMP of VIV-FBPTD-S-SSCC Model 152
(b) Sensitivity Chart of NPV of VIV-FBPTD-S-SSCC Model 153
Fig. 55: Estimates of Rate of Anaerobic Hydrolysis of Coal in-situ
during Buildup and Plateau Phase or Estimates of Proportional
Quantity of Substrate Depleted during Buildup and Plateau
Phase Duration 164
Fig. 56: Model Verification and Validation Process in a Simpler Form 168
xxiv
List of Tables
Sl. Nos. Title Page Nos.
Table 1: Total Primary Energy Requirement 2
Table 2: Indias Hydrocarbon Reserves 2
Table 3: Scenario Summaries for 8% Growth Fuel Mix in year 2031-32 3
Table 4: Ranges of Commercial Energy Requirement, Domestic
Production, and Imports for 8% Growth for year 2031-32 4
Table 5: Chemical Structural Comparison of Coals of Various Ranks 22
Table 6: Chemical Composition of a Typical (C100H85O21N1S0.3) Low
Rank Sub-bituminous Coal 26
Table 7: Functional Groups of Oxygen in Coal 27
Table 8: Oxygen Functional Group Distribution Reflects Coal Rank 28
Table 9: Water Surface Area in Different Raw Coals of Various Rank 29
Table 10: Kinetic Models in the Literature for Describing Hydrolysis 46
Table 11: First Order Hydrolysis Rate Constant 47-48
Table 12: Process Based Cellulose Degradation Models 49
Table 13: Chemical Composition (%) of Different Lignocellulosic
Biomass 92
Table 14: Composition of Various Potential Lignocellulosic Biomass 92
Table 15: Fact-Sheet of the CoalBioreactor Biomethanation Project 129
Table 16: Data-Sheet of the CoalBioreactor Biomethanation Model 130-134
Table 17: Cost-Sheet of the CoalBioreactor Biomethanation Model 135-136
Table 18: Estimated Parameters Values by Different VIV-FBPTD-S-
SSCC Model Prototypes 156
Table 19: Forecasted Parameters Values of Coal Biomethanation Project
under Varying Percentage Reduction in ASESA and EPR 159
Table 20: Impact of Varying Microbial Geological Biomethanation
Conditions (MGBC) of Coal 161
Table 21: Forecasted Parameters of 3 Prototypes of WMGBC Model:
General, 20% ECBCF-ECHRMP, and 20% ECBCF-ECHRMP
and EMPCF 162
1
CHAPTER 1: INTRODUCTION
Energy powers the nations industries, vehicles, homes, and offices.
Therefore, energy, especially in the form of electricity, is the lifeline of modern
civilization, and a country cannot be economically and militarily powerful unless it
has ensured not only uninterrupted supply of its energy requirement but full energy
security i.e. supply of safe, convenient, and environment benign energy to all its
citizens to satisfy their various needs at affordable costs, at all times, with prescribed
confidence level, considering shocks & disruptions that can be reasonably expected.
1.1 Energy Scenario of India
India has been endowed with both fossil and non-fossil energy resources
including renewable, exhaustible, and nuclear energy. Though country has large
reserve of thorium, reserves of oil & gas, and uranium are meager. Coal is abundant
but of poor grade. Hydro potential is significant (1, 50,000 MW) but small compared
to countrys needs. Renewable energy (RE) and non-conventional energy sources are
having great potential, if getting exploited on commercial basis, but most of them are
still at laboratory stage only.
1.1.1 Energy Demand
To deliver a sustained growth rate of 8 % through 2031-32 and to meet the
lifeline energy needs of all citizens, India needs, at the very least, 1836 to 2043
Million Tonne of Oil Equivalent (Mtoe) total primary energy (Table 1) and 8,00,000
mega watt (MW) of electricity generation capacity (Parikh, 2006).
1.1.2 Energy Supply
Energy supply is constrained by countrys energy resources. Hydro-Carbon
Energy Reserves indicated in Table 2 reveals that India is not well endowed with
natural energy resources. Though coal is abundant (276.810 Billion Tonne - BT, as
on 1.4.2010) and has low sulfur, but it has high toxic elements (Masto et al., 2007).
Moreover, it is regionally concentrated and is of low calorie and high ash content.
2
Table 1: Total Primary Energy Requirement (Mtoe) (adopted from Parikh, 2006)
Year TPCES TPNCES TPES
8% 9% 8% 9% 8% 9%
2006-07 389 397 153 153 542 550
2011-12 496 546 169 169 665 715
2016-17 665 739 177 177 842 916
2021-22 907 1011 182 181 1089 1192
2026-27 1222 1378 184 183 1406 1561
2031-32 1651 1858 185 185 1836 2043
Table 2: Indias Hydrocarbon Reserves (Mtoe) (adopted from Parikh, 2006)
Resources Unit Proved Inferred Indicated Production
in 2004-05
Net Import
in 2004-05
Reserve/
Production Ratio
(P) (I) (Q) (M) P/Q (P+I)/Q
Coal (As on
1.1.2005
Mtoe 38114 48007 15497 - - - -
Extractable
Coal
Mtoe 13489 9600-15650 157 16 86 147.18
6
Lignite (As
on 1.1.2005)
Mtoe 1220 3652 5772 - - - -
Extractable
Lignite
Mtoe 1220 - - 9 - 136 136
Oil (2005) Mt 786 - - 34 87 23 23
Gas (2005) Mtoe 1101 - - 29 3 (LNG) 38 38
Coalbed
Methane
Mtoe 765 - 1260-2340 - - - -
In-situ Coal
Gasification
? ?
1.1.3 Options to Bridge the Gap
India must expand its energy resource base, seek new and emerging energy
sources, and pursue technologies that maximize energy efficiency, demand side
management, and conservation.
In Integrated Energy Policy of Planning Commission, Govt. of India (GOI),
11 numbers of energy mix (scenarios) (Table 3) has been envisaged to meet the
above energy demand. These scenarios indicate 29 to 59% energy import
dependence (Table 4).
1.1.4 Augmentation of Resources
Energy resources can be augmented by exploration to find more coal, oil, and
gas, or by recovering a higher percentage of the in-place reserves.
3
Table 3: Scenario Summaries for 8% Growth Fuel Mix in year 2031-32 (adopted from Parikh, 2006)
Scenario No. 1 2 3 4 5 6 7 8 9 10 11
Scenario
Description
Coal
Dominant
Case
Forced
Hydro
Forced
Nuclear
Forced
Nuclear
+
Hydro
Forced
Nuclear
+
Hydro
+
Gas
Forced
Nuclear
+
Hydro
+
Gas
+
DSM
Forced
Nuclear
+
Hydro
+
Gas
+
Coal eff.
Forced
Nuclear +
Hydro +
Gas +
DSM +
Coal eff.
Forced
Nuclear +
Hydro +
Gas +
DSM +
Coal eff. +
Rail share
up
Forced
Nuclear +
Hydro +
Gas +
DSM +
Coal eff. +
Rail share up +
Transport eff.
Scenario 10
+
Forced
Renewable
A. Mtoe
Crude Oil 486 485 486 485 486 486 485 485 447 361 350
Natural Gas 104 105 104 105 197 174 191 171 171 171 150
Coal 1022 953 998 929 835 715 818 698 701 707 632
Hydro 13 35 13 35 35 35 35 35 35 35 35
Nuclear 76 76 98 98 98 98 98 98 98 98 98
Renewable 2 2 2 2 2 2 2 2 2 2 87
Non-
commercial
185 185 185 185 185 185 185 185 185 185 185
Total 1887 1842 1885 1839 1837 1695 1813 1673 1639 1558 1536
Total without
Non-
Commercial
1702 1655 1700 1554 1652 1510 1628 1488 1454 1373 1351
B. Percentage
Crude Oil 25.7% 26.4% 25.8% 26.4% 26.4% 28.7% 26.8% 29.0% 27.3% 23.2% 22.8%
Natural Gas 5.5% 5.7% 5.5% 5.7% 10.7% 10.3% 10.5% 10.2% 10.5% 11.0% 9.8%
Coal 54.1% 51.8% 52.9% 50.5% 45.5% 42.2% 45.1% 41.7% 42.8% 45.4% 41.1%
Hydro 0.7% 1.9% 0.7% 1.9% 1.9% 2.0% 1.9% 2.1% 2.1% 2.2% 2.2%
Nuclear 4.0% 4.1% 5.2% 5.3% 5.3% 5.8% 5.4% 5.9% 6.0% 6.3% 6.4%
Renewable 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 0.1% 5.6%
Non-
Commercial
9.8% 10.1% 9.8% 10.1% 10.1% 10.9% 10.2% 11.4% 11.3% 11.9% 12.0%
Total 100 100 100 100 100 100 100 100 100 100 100
4
Developing the thorium cycle for nuclear power and exploiting non-
conventional energy, especially solar power, offer possibilities for energy
independence beyond 2050.
Table 4: Ranges of Commercial Energy Requirement, Domestic Production, and Imports for
8% Growth for year 2031-32 (adopted from Parikh, 2006)
Fuel Range of
Requirement
in Scenario
(R)
Assumed
Domestic
Production
(P)
Range of
Imports*
(I)
Import
(Percent)
(I/R)
Oil (Mt) 350-486 35 315-451 90-93
Natural Gas (Mtoe)
including CBM
100-197 100 0-97 0-49
Coal (Mtoe) 632-1022 560 72-462 11-45
TPCES 1351-1702 - 387-1010 29-59
*Range of Imports is calculated across all scenario as follows:
Lower bound = Minimum requirement Maximum domestic production
Upper Bound = Maximum requirement Minimum domestic production
Domestic production of oil & gas will depend critically on new findings.
With a concerted push and 40-fold increase in contribution to primary energy,
renewable may account for only 5 to 6% of their contribution in Indias energy mix
by 2031-32.
Therefore, under the emerging energy mix, coal would remain the main stay
fuel for the country till 2031-32 and possibly beyond, despite rising environmental
concerns and contribution of almost 40% of the green house gases (GHGs) (Parikh,
2006).
1.1.5 Coal Mainstay Fuel
At present, coal accounts for over 50% of Indias commercial energy
consumption and 78% of domestic coal production are dedicated to power
generation, which is likely to increase in future. In this coal based development the
total demand for coal will increase to 2700 MT (Million Tonne) (i.e. equal to 1080
Mtoe) by 2031-32, which might be as high as 2842 MT, if 5% quality deterioration
over next 25 years is being considered, whereas the projected coal production is only
about 1400 Mt by 2031-32 for coal & lignite combined together.
5
1.2 Energy Security of India
Above discussion reveals that countrys energy is under supply, market, and
technical threats/risks.
1.2.1 Environment Security under Threat
Continuance with fossil fuels, especially with coal causes serious threats to
the environment. Combustion of coal contributes adverse environmental impacts of
local concern such as deforestation, land degradation, water & air pollution, and of
global concern such as GHGs. Though India is not required to curtail its green house
gas (GHG) emissions, as a signatory to the UNFCCC (Framework Convention on
Climate Change) and a country that has acceded to the Kyoto protocol, and emerges
as a relatively low carbon economy by global comparison, offsetting emissions in
line with the performance of the global economy (Anonymous, 2007), however,
India is very active in proposing Clean Development Mechanism (CDM) projects.
Moreover, the impact on the countrys poor, due to climate change, could be
serious. In a study conducted by The Energy Resources Institute (TERI) in 1997, the
costs of environmental damage in India, measured in terms of loss in potential gross
domestic product (GDP), have been estimated to be in excess of 10% (Anonymous,
2002a). Obviously coal is the main contributor to this damage, combustion of which
is expected to emit about 1 BT at present, to 5.5 BT per year by 2031-32 (Parikh,
2006).
Thus, under envisaged coal based energy development model, both energy
and environment securities of India are under threats (Parikh, 2006; and Anonymous,
2002a).
1.2.2 Challenges
To overcome these threats, challenges with country are to grow cleaner
energy supply from coal or/and other alternative sources.
6
1.3 Non-Extractable Coal
Out of total Indian coal geological resources, the coal reserve to extractable
coal reserves ratio is 4.7:1 (Anonymous, 2001a), thus, only 21.27 % of the
geological reserves are extractable under business as usual (BAU) scenario.
Even under envisaged best-case scenario (BCS) the percentage of extractable
reserves are likely to enhance say by another 50%. Though it is an optimistic
estimate but even then also extraction of only about 30% of the total coal geological
resources would be possible. 70% of the coal would be non-extractable, thus the
energy contained therein would either remain untapped and unrecovered forever or at
the most would be underutilized.
The scenario is likely to be the same worldwide, may be with a bit varying
environmental damage cost, and changed geological resources to extractable reserves
ratio.
The very high reserves of non-extractable coal contain a huge quantity of
energy in solid form (coal), gaseous form (methane i.e. coalbed methane, CBM), and
geo-thermal form. At the same time these are a good CO2 sink as well. Therefore,
these coals are an obvious and natural target for extraction of cleaner energy to
improve energy and environment security.
Adoption of coalbed methane (CBM) and thermal underground coal
gasification (UCG) technologies are efforts in this direction.
1.3.1 CBM Recovery
CBM recovery technology extracts energy available only in gaseous methane
form.
1.3.2 In-situ Thermal UCG
Extraction of energy available in solid coal form is possible through thermal
UCG. UCG is a method to utilise non-extractable coal resources between 30 to 800
meters depth for extracting energy available in solid coal form. It involves controlled
combustion of in-situ underground coal by injecting air, or oxygen, and steam down
a borehole from the land surface, and collecting the resultant combustion product i.e.
7
synthetic or syn gas consisting of CO, H2, CH4, CO2, H2O & N2 from a nearby
borehole. The method is ecologically very favourable because residual of coal after
combustion are being left in the deposit itself. Capture of higher concentrated CO2
not to be emitted in atmosphere, would be much more cost effective that could be
sequestered in the coal mines itself or elsewhere. Moreover, thermal UCG with or
without sequestration would be eligible for carbon credit.
This deceptive simplicity of thermal UCG has attracted many countries, and
off and on, for more than 100 years, it has been practiced by almost all-major coal
producing countries. However, its application, as a large-scale coal to syn gas
conversion technology for energy extraction, proves more difficult
(Anonymous,
2001b). UCG is only suitable for those non-extractable coal deposits that have low
water content. It is not suitable for aquatic coal deposits. Its suitability and
applicability is narrow and limited. While extracting effectively only a low
percentage of the energy available in coal; an UCG operation spoils the target coal
completely (Gayko, 2004), and the residual coal loses its further utility fully. Though
efforts are going on to commercialize this technology, however, its application, as a
large-scale coal to synthetic gas conversion technology
for energy extraction at
commercial scale, has not yet been deployed anywhere in the world (Parikh, 2006).
Therefore, it is imperative to identify, examine, and develop more efficient,
natural, and nature friendly innovative energy extraction technologies to extract
energy available in solid coal form in non-extractable coal deposits.
1.3.3 Non-Extractable Coal as a CO2 Sink
Carbon dioxide (CO2) has greater affinity to the solid surface than methane.
CO2 gets preferentially adsorbed over methane by coal, and therefore, non-
extractable coal is likely to be a good CO2 sink with subsequent conversion of a
fraction of CO2 to CH4 (biomethane) using designer microbes or bio-mimetic
systems (Beecy et al., 2007w).
8
1.4 In-situ Biomethanation of Non-Extractable Coal
Biomethanation or methanogenesis is a natural, ongoing, and complex
phenomenon of conversion of coal to biogenic methane (termed as biomethane now
onwards) by indigenous microbes. The conversion process occurs at a slow pace but
it would likely be accelerated to its optimum level by biostimulation and/or
bioaugmentation of non-extractable coal that have favourable environment for
sustainable microbial growth. It is expected that this optimum conversion
(biomethane harvesting) rate would be adequate to support commercial production of
harvested biomethane. Several agencies worldwide are currently exploring this
innovative possibility in search of a viable technical and economical solution. Luca
Technologies, Microbially Enhanced Coalbed Methane (MECoM) programme,
Alberta Research Council, and other agencies, based on lab experimentations, have
indicated harvesting of 0.03 to 30 m3 methane/ day/ tonne of coal (Anonymous,
2007wc; and Budwill, 2007). This indicates that technical feasibility of coal
biomethanation has been established in lab.
There are some documented proposals and schemes for acceleration of
existing natural biomethanation process in-situ. However, at present, there is no
documented proposal and scheme for in-situ biomethanation of coal that lacks
favourable environment for microbial growth.
To improve energy and environment security of an economy further,
application of innovative approach of in-situ coal biomethanation needs to be made
possible in all types of coal including non-extractable coal. This is proposed under
this study.
1.4.1 Hypothesis
Biomethanation of all types of coal in-situ is techno-economically feasible.
1.5 Objectives of the Research Work
To prove this hypothesis, it is imperative to increase knowledge and
understanding about in-situ coal biomethanation process, its imitation in coal that
lacks favourable natural environment, and mechanism of biomethanation
acceleration. It is likely that all combined and applied together would make
9
biomethanation of all types of coal feasible. Study of this inter-disciplinary research
work, a system or project for which is yet not existing, is proposed through following
objectives:
(i) Development of a mechanism for economical and accelerated methane
harvesting in non-extractable coal in-situ, and
(ii) Development of an engineering-economic model of envisaged
biomethanation project to carry out benefit-cost-analysis and risk analysis
using Monte Carlo simulation for identification of best technology mix to
optimize sustainable methane energy recovery and CO2 reduction potential.
1.6 Scope and Organization of the Research work
The thesis starts with discussing energy & environment security scenario of
the country under non-utilization or wasteful utilization of non-extractable coal. It
suggests application of innovative approach of biomethanation of non-extractable
coal in-situ for improving the energy and environment security. It hypothesizes that
biomethanation of all types of coal in-situ is techno-economically feasible. The
study is proposed through development of an in-situ mechanism for biomethane
harvesting and a mechanistic engineering-economic model of an envisaged in-situ
non-extractable coal biomethanation project, which would use this mechanism. All
these have been discussed in chapter 1. Coal as a substrate for biomethanation is
very complex and poorly understood. Literature review in chapter 2 suggests that in
anaerobic digestion of a solid, dry, and insoluble complex substrate like coal
(primary substrate), hydrolysis is likely the rate limiting step. Therefore, coal
hydrolysis has been discussed separately in detail in chapter 3 that indicates that
though depolymerization and solubilization are the two most important steps in coal
hydrolysis, however, release of enzymes by acidogens (microbes that make
anaerobic hydrolysis of coal possible) and mechanisms involved in the enzymatic
catalysis of coal under anaerobic condition are yet to be fully understood. However,
an important factor for improving hydrolysis is to bring the hydrolytic enzymes in
close contact with the minutest hydrolysable coal carbon polymers (actual substrate).
This is possible through development of a mechanism, which leads to design, in-situ
10
construction, and operation of a CoalBioreactor (unregistered trade mark of the
mechanism) in a target coal. This has been discussed in chapter 4. The design and
construction of the CoalBioreactor is such that it makes in situ biomethanation
possible in all types of coal including extractable, non-extractable, aquatic, coal with
a low water content, and coal in which natural microbial geological biomethanation
conditions (MGBC) are whether favourable or completely absent.
CoalBioreactor is an engineered-natural, at times imitated, accelerated,
trouble-free, and cost-effective in-situ biomethanation mechanism that consider
hydrolysis as the rate limiting step. It can be applied gainfully in any and all types of
coal for commercial recovery of harvested biomethane in a reasonably carbon-
neutral way. It is a low operational cost, single stage, mesophilic, slow rate,
heterogeneous, over-pressured, batch bioreactor that is surrounded by an
impermeable boundary. The purpose of the CoalBioreactor design with impermeable
boundary is to ensure (i) free flow and spread of growth medium, microbes,
nutrients inside the CoalBioreactor, so that (ii) microbial population grow and cover
maximum surfaces of coal exposed to them for its effective biomethanation, and (iii)
biomethane generated (harvested) flow freely and accumulates in CoalBioreactor
production well, for its (iv) maximum recovery (v) by sequestering produced CO2,
harvested during coal biomethanation, back in the CoalBioreactor itself; but at the
same time, not to allow (vi) flow and spread of growth medium, microbes, nutrients,
and biomethane to outside (surroundings) from the CoalBioreactor, and (vii) flow of
other things (materials) inside the CoalBioreactor from the surroundings.
CoalBioreactor kinetics (operational effectiveness of CoalBioreactor) has been
discussed in chapter 5. It formulates buildup phase time duration (i.e. the time
acidogens take to fully cover the entire coal surfaces exposed to them) of substrate
depletion/ utilization at varying rate (Tsuvr) on basis of which other parameters like
plateau phase time duration of substrate depletion/ utilization at constant rate (Tsucr),
total time of substrate utilization (Ttsu), biomethanation potential (BMP), CO2
sequestration potential (CSP), commercial energy availability (CEA), CO2 produced,
project carbon-neutrality (PCN), net present value (NPV), etc. have been
formulated. The multi-disciplinary in-situ non-extractable coal biomethanation
project to date is an early stage, high risk, uncertain, technology based project in
11
which the core of the project i.e. in-situ coal biomethanation is a less defined,
complex, and uncertain process. Obviously people at present are apprehensive about
success of an in-situ coal biomethanation project. This apprehension has been
attempted to be cleared through development of a mathematical-economic simulation
model. Model inputs are based on abstraction and generalization of limited empirical
hard data documented in literature. It also includes secondary data derived from these
primary hard data based on mechanistic logical conclusion, and initial assumption of
some of the missing inputs. Mathematical model computes forecasted parameters
(outputs) on discrete points in time. All these have been discussed under engineering-
economic model in chapter 6. CoalBioreactor discussed in chapter 4, its kinetics
discussed in chapter 5, and mathematical model discussed in chapter 6 are the
integral part of the engineering model. CoalBioreactor and its kinetics together
provide the basic framework for development of the mathematical model. Economic
model estimates economics (NPV) of the envisaged coal biomethanation project by
carrying out benefit cost analysis (BCA) of the project. The CoalBioreactor
Biomethanation model (name used for mathematical-economic model) is a dynamic,
quantitative, lumped, stochastic, mechanistic, continuous, sub-model based,
simulation model developed in Microsoft Excel Spreadsheet with Crystal Ball add-in
that use Monte Carlo simulation for risk analysis. Chapter 7 is results and
discussions of this thesis. Exploratory analysis of model rudimentary estimates
(forecasts) of buildup phase time duration, and inputs values help in identifying more
rational values of inputs. Simulation run of the model with these validated inputs
values estimates the ultimate probability distribution of the forecasted parameters.
Decision makers know the certainty level attached with each forecasted result, and
therefore the risk associated in accepting a decision. Model has been used as an
exploratory e-laboratory to get answers of all queries that relate to in-situ
biomethanation of non-extractable coal including apprehensions, inhibitions, and
expected hopes for further improvement in CoalBioreactor operational performance.
By identifying appropriate operational technology mix, model demonstrates techno-
economic feasibility of biomethanation project even in a worst MGBC coal. This
verifies the hypothesis. Analysis of impact of non-extractable coal on economy
suggests average net earnings of more than 340 INR per tonne of coal in-situ.
12
Considering 2031-32 as the base year, CEA of 66% of energy contained in coal alone
would meet primary energy requirement of country for more than 37 years and PCN
of 72.54% would mitigate total emission of country for more than 40 to about 60
years. Breakthrough of designer microbial consortium formulation is likely to pave
way for sustainable energy and environment security. Chapter 8 examines the model
and finds that it is a verified and virtually validated (V & VV) model. Chapter 9
concludes the thesis indicating that with design and construction of an in-situ
CoalBioreactor, it is possible to imitate and harvest biomethane in any and all types
of coal, and recover it commercially in a reasonably carbon-neutral way to add to
energy and environment security of an economy. A complete overview of thesis is
given in Fig. 1.
Test the Effects of Changes in the Coal Biomethanation Project
(Perform Experiments)
Ad
just
Da
ta C
olle
ctio
n
CoalBioreactor Kinetics
Coal Biomethanation in
CoalBioreactor Math
em
ati
cal-
Eco
no
mic
Mo
del
Co
alB
iore
acto
r-
Bio
meth
an
ati
on
Mo
del
Economic Model
Inputs from Literature and
Industry (CBM &
Biotechnology)
Co
al B
iom
eth
an
ati
on
Pro
ject
Data Collection
Mathematical Model Scientific Understanding
(Present Knowledge - What we know,
and what we do not know)
Decision Making
Strategic Decision by Planners
Tactical Decision by Decision Makers
Non-Extractable CoalWasteful and under Utilized
- Energy and Environment
Security - Problem
Chapter -1
Biomethanation of Non-Extractable CoalAn Innovative Technology and Proven Process
under Favourable Environment
Biomethantion of All Types of Coal in-situ
Feasible - Hypothesis
Literature Review for Enhanced Understanding
Chapter - 2Biomethanation of Coal
CoalCO
2 Sequestration
Anaerobic Hydrolysis of Complex Substrate
Chapter - 3Coal (Solid, Dry, Insoluble Complex
Substrate) Hydrolysis
Chapter - 4
Chapter - 5
Engineering- Economic ModelChapter - 6:
Chapter - 7: Results and Dicussions
Chapter - 8: Verification and Validation of Models
Chapter - 9: Conclusions
En
gin
eeri
ng
Mo
del
Future Scope of Works
References: Separately indicating Websites (sffixed w after the year of publication/ access)
List of Patents and Publications
Fig. 1: Overview of the Thesis
Future scope of work, references separately indicating websites (suffixed w
after the year of publication for convenience), and list of patents and publications
related to this research are given at the end.
13
CHAPTER 2: LITERATURE REVIEW
The bio-availability of coal carbon polymers, the presence of a microbial
community to convert coal carbon to biomethane, and an environment supporting
microbial growth and methanogenesis; all combined control coal deposits
biomethanation (Elizabeth et al., 2008). Therefore, to understand coal
biomethanation, it is prudent to discuss related topics like coal chemistry, anaerobic
hydrolysis of complex substrate that would likely help in understanding
bioavailability of coal carbon polymers, and CO2 sequestration to improve recovery
of biomethane.
2.1 Biomethanation of Coal
Biomethanation of coal is an anaerobic digestion (AD) process by microbes.
The microbiology of anaerobic digestion of coal is complicated (Gavala et al., 2003).
Microbes that are involved in biomethane production have synergistic and syntrophic
relationships among them (Anonymous, 2008wa). Several microbial groups are
involved in AD. Each group performs a specific role in the overall degradation
process. Figure 2 and 3 illustrate the usual four steps of hydrolysis, acidogenesis,
acetogenesis, and methanogenesis involved in AD of coal.
Fig. 2: Schematic Representation of Various Trophic Groups of Microorganisms Involved in
Anaerobic Digestion of Organic Matters of Coal to CH4 Production
Methanogenic Microbes
H2 Consuming and Acetotrophic Methanogens
Coal Complex Polymers (Polycyclic Aromatics, Phenols,
Long Chain Aliphatic)
Colloidal Polymeric
Substances
Monomers (Fatty Acids, Sugars, Amino Acids,
NH3, HS-, CO2, Acetate, H2)
Acetate, H2, CO2
CH4 + CO2
Carbonate Reduction CO2+4H2 = CH4 +2H2O
Acetoclastic
CH3COO- + H2O = CH4 + HCO3
-
or CH3COO
- + H
+ = CH4 + CO2
Hydrolytic Fermentative Microbes
Hyd
roly
tic F
erm
en
tativ
e M
icro
be
s
Syntrophic Acetogenic
Microbes
14
Though coal is extremely rich in complex organic matter, however, coal is a
solid rock, often dominated by recalcitrant, partially aromatic, and largely lignin
derived macromolecules that are relatively resistant to biodegradation. The organic
materials of coal (plant constituents or macerals) exhibit varying degree of resistance
to microbial degradation. Carbohydrates, proteins, and certain lipids get degraded
readily, whereas resins, lignins, and terpens are perhaps more stable to microbial
attack (Crawford, 1992).
Fig. 3: Proposed Mechanism of Stepwise Biodegradation of Original Material in Coal
(Macromolecular Coal and Coal Derived Oil), Annotated with Microbes Related to
Those Found in the Clone Library and Potentially Capable of Performing the Indicated
Process: (i) Defragmentation of Coal Geomolecular Structure Predominated by Fermentation Targeted at Oxygen-Linked Moieties and Oxygen Containing Functional Groups (This
Process Detaches Some of the Oxygen-Linked Aromatic Rings and Generates some Short
Organic Acids); (ii) Anaerobic Oxidation of Available Aromatic and Aliphatic Moieties,
Derived from Coal Defragmentation or From Dispersed Oil; (iii) Fermentation of Products
Available From Step (i) Described Above to H2, CO2, and Acetate; and (iv) Methanogenesis
Utilizing H2 and CO2 likely Predominating Over Homoacetogenesis and Acetoclastic
Methanogenesis. The Dark Area Represents a Droplet of Oil. (Adopted from Strapoc et al.,
2008)
Figure 2 and 3 suggest that hydrolyzing and fermenting microorganisms
(anaerobic acidogens carry out anaerobic hydrolysis) are responsible for initial attack
on macromolecular polymers found in coal and produce colloidal polymeric
substances that reduce into monomers subsequently. Under methanogenic conditions,
the paradigm for microbial conversion of complex organic matter to methane
involves the primary fermentation of polymers and monomers to fatty acids, organic
1Spirochaeta, 2Sporomusa, 3Cytophaga, 4Acidominococcus, 5Flavobacterium, 6Methanocopusculum, 7Rhodobacter
15
acids (e.g., lactate, succinate, acetate), alcohols (e.g., methanol), and hydrogen and
carbon dioxide. Degradation subsequently follows via secondary fermenting
microbes (syntrophs); homoacetogenic microbes; and acetoclastic, methyltrophic,
and hydrogentrophic methanogens (Schink, 2006). The same investigators have
hypothesized that this metabolic model is applicable to the bioconversion of coal to
biomethane as well.
In addition to the above fermentation products, coal matrices are also a source
of other substrates such as methylamines, methylsulfides, ethanol, and carbon
monoxide. The requisite methanogenic pathways can differ among basins, fields, and
wells and can depend on the physicochemical properties of the microenvironment
(Strapoc et al., 2010).
Biomethane generation from coal by microbial consortia has been
documented previously. Microflora, present in water, leached from coal mines were
shown to generate biomethane (Thielemann et al., 2004). A biomethane generating
consortium, extracted from coal was observed to grow on low volatile bituminous
coal as a sole carbon source (Shumkov et al., 1999).
2.1.1 Methanogenesis Pathways
Although there is one known methanogenic species, Methanosacineae,
metabolically and physiologically the most versatile methanogens, that can utilize up
to nine substrates (Anonymous 2011wa) like formate, CO, CO2, methanol, acetate,
methylated amines, short-chained alcohols, methyl mercaptan, etc. through three
methanogenic pathways; however, most other methanogens are highly specialized
and are capable of metabolizing only one or two substrates. However, extensive
biochemical studies have led to four pathways of methanogenesis (Paul and Metcalf,
2005), hydrogentrophic, acetoclastic, methyltrophic, and methyl reduction (Welander
and Metacalf, 2005), which can be represented by equations as given below (Zamri,
2010):
Hydrogentrophic 42 + 2 = 4 + 22 0 = 1311 (1)
Acetoclastic 31 + + = 4 + 2 0 = 36 1 (2)
16
Methyltrophic 43 + 22 = 34 + 2 + 42 0 = 36 1 (3)
Methyl Reduction 3 + 2 = 4 + 2 0 = 36 1 (4)
Out of these methanogenesis pathway most common are CO2-H2 reduction
(hydrogentrophic) and acetoclastic. Hydrogentrophic pathway using CO2 and H2 as
substrate is the widest spread, being found in all methanogenic orders.
Hydrogentrophic, acetoclastic, and methyltrophic methanogenesis pathways are
shown in Fig. 4 (Bapteste et al., 2005).
formate CO2
W-containing formyl-MF dehydronase (fwdHFGDACB)MF + XH2
Methanofuran
H2O + X Mo-containing formyl-MF dehydronase (fmdECB)
formyl - MF
formyl-MF: H4MPT formyltransferase (ftr)
H4MPT
MF
Methanopterin (mpt)
formyl - H4MPT
H2O
methenyl-H4MPT cyclohydrolase
(mch)
methenyl-H4MPT
F420
- H2 or H2
F420
Coenzyme F420
(cof) F420 - reducing methylene - H4MPT dehydrogenase (mtd)
H2-forming methylene-H
4MPT dehydrogenase (hmd)
methylene -H4MPT
F420 - H2
F420 methylene -H
4MPT reductase (mer)
methyl -H4MPT acetate
methylene -H4MPT methyl transferase (mtrEDCBAFGH)
CoM-SH
H4MPT
Coenzyme M (com)
methyl -CoM methyl-amines
methanol
methyl-sulfidesCoB-SH
CoM-S-S-CoB
CH4
methyl coenzyme M reductaseI (mcrBDCGA)
methyl coenzyme M reductase II (mrtBDGA)
Fig. 4: Methanogenesis Pathways: Hydrogentrophic (solid black arrows), Acetoclastic (double-
black arrows), and Methyltrophic (broken black arrows) (adopted from Bapteste et al., 2005)
17
2.1.1.1 Hydrogen Pathways
In the absence of methanogens and other microorganisms that consume
hydrogen, the bioconversion of coal into hydrogen is possible. Fermentative
hydrogen producers, that may be facultative or obligate anaerobes, are reported in
many natural environments including the nutrient-poor Sargasso Sea (Steven et al.,
1987), from flowers, and organic waste using anaerobic bacteria (Dreszer, 2004).
There are reports of hydrogen gases being produced from coalbeds suggesting that
undiscovered fermentative hydrogen producers are present in some coal beds and
possibly in other organic-rich substrates. Fermentative hydrogen producers such as
these can be collected and added to the microbial consortia injected into the
subsurface to increase hydrogen production, which in the presence of methanogens,
will result in increased methane generation.
2.1.2 Microbial Growth and Environment
The survival and growth of microbes depend on different activities such as
nutrient assimilation, catabolism, and the synthesis of living cytoplasm and all
cellular structures. Tested nutrient additions include ammonia, phosphate, yeast
extract, tryptone, milk, agar, trace metals, and vitamins (Jin et al., 2007; Pfeiffer et
al., 2010). In-situ microbially enhanced CBM stimulation performed in the Powder
River Basin showed an increase in methane production after nutrient treatment (e.g.,
phosphate) compared with the expected production decline curve. Microbes produce
different kind of enzymes. A specific enzyme performs a specific activity. Each of
these enzymes functions best in the presence of the optimal environmental conditions
of temperature, pH, osmotic pressure, and redox potential. The optimum conditions
vary for each enzyme (Anonymous, 2007wa). Therefore, every microbe has a
preferred unique environment that suits it best and provides maximum survival
potential. Conditions of preferred environment are the optimal growth conditions for
that microbe.
2.1.3 In-situ Coal Biomethanation
Coalification process (conversion of plant material to coal) involves the
burial of plant material to produce an anaerobic organic rich environment in some of
18
the regional aquifers. These aquifers may act like geobioreactor under favourable
environment for microbial activity for biomethane generation (Anonymous,
2007wc). Moreover, uplifting of higher rank coals and their exposure to meteoric
recharge can also transport microbes into permeable coalbeds to form geobioreactor
(Scott, 2001). Abandoned mines and other underground cavities frequently contain
water and in many cases are completely flooded with water to behave like a
geobioreactor. Collapse of roof and pillars expects to expose fresh coal surfaces for
microbial attack.
Several researchers have proposed subsurface enhancement of microbial
biomethane. For example, a patent by Menger et al. (2000) suggested digestion of
lignite in an underground chamber using termite micro flora composed of acid
formers and methanogens. Jin et al. (2007) suggested fracturing the reservoir for
better simultaneous nutrient delivery and enhanced surface area of coal. The only
description of a multi-well field trial has been presented in a patent application by
Pfeiffer et al. (2010).
Apart from these, biomethanation of non-extractable coal is likely to be much
more cost-effective, if being applied in CBM wells and practiced together with CBM
production to reduce drilling and other expenses, and enhancing permeability as well.
Chances of viability of in-situ coal biomethanation project are more in these
geobioreactor and CBM blocks. Therefore, these coals need to be considered as an
initial target for carrying out various R&D activities to establish in-situ coal
biomethanation feasibility. Once the technology matures there, this could be applied
cost effectively in rest of the non-extractable coals.
2.1.4 Sources of Microbial Consortia
Jin et al. (2007) have suggested and experimented with the addition of
selected microbial consortia. Coal biomethanation consortia comprises of many
types of microbial species from a dynamic microbial community. Although dominant
microbial species within the major groups of microbes may change over time, the
relative proportions of the major groups will remain relatively constant, indicating
that even dynamic communities may maintain a stable ecosystem function.
19
These consortia can be derived from: (1) commercial entities, which supply
known species of microbes, (2) undiscovered microbial species, which may be
obtained from underground coalbeds, and which have probably adapted genetically
to efficiently metabolize coal organic matter, and (3) genetically engineered bacterial
species or consortia highly adapted to convert organic compounds into methane. The
genetic material for these species may be obtained from known microbial species and
those discovered in subsurface environments. Examples of consortia used for
methanogenic inoculation with coal in laboratory settings include a cultivated
consortium indigenous to studied coal (Pfeiffer et al., 2010), a consortium obtained
from termite guts (Srivastava and Walia 1998; Menger et al., 2000), and a
consortium obtained from an abandoned coal mine used as sewage disposal in
Appalachian Basin (Volkwein, 1995).
In-situ biodegradation studies frequently show that contaminated sites will
select for organisms that can degrade the contaminant, and these indigenous
population will perform as well as or better than any foreign microbes that are
introduced to the site (Baker, 1994; and Cookson, 1995).
2.2 Coal Chemistry
Coal is a readily combustible rock containing of, more than 50% by weight
and more than 70% by volume, carbonaceous material (ASTM-American Society for
Testing and Materials). Coal is an organic rock derived from chemical and physical
transformations of plant biopolymer (cellulose, cutin, suberin, lignin, algaenon) due
to (i) micobially mediated enzymatic process (biodegradation) occurring during early
diagenis and peat formation that is peatification, and (ii) the effects of pressure and
temperature acting over long period of time following burial of the peat
(coalification) (Stach et al., 1982).
When plants, bacteria, and algae die and fall to the ground, a biochemical
transformation, mediated primarily by microbes, proceeds rapidly to utilize the
organic components as an energy source. In the presence of adequate oxygen, the
destruction is almost complete, giving rise to CO2, H2O, NO3, and SO4. However,
when the sediment is deposited in a sub-aquatic environment, the system quickly
20
goes anaerobic, and certain organic structures tend to survive the bacterial alteration
and are preserved in the sediment with minimal alteration (Stach et al., 1982).
Coal diagenesis differs i.e. different varieties of coal arise because of
differences in the kinds of plant material (coal type), degree of coalification (coal
rank), and range of impurities (coal grade). Structurally, coal is a complex system
consisting of organic material, fragment of plant debris (macerals), inorganic
inclusions, and an extensive pore network.
2.2.1 Macromolecular Geopolymers
Biopolymers in vascular plants are the most important starting materials in
the formation of coal. Especially important is the lignocellulose biopolymer, a
structural component of which is thought to provide the basic aromatic framework
for coal (Hatcher, 1990). Most of the cellulose and protein is converted to simple
organics and utilized as a food source by microbes. Lipids are the most resistant to
degradation. Trace secondary plant metabolites such as terpenes, steroids, and
alkaloids also tend to survive and become concentrated in the sediments. Complex
polymers produced by bacteria also become encapsulated in the sediment. Thus,
basically, the initial organic deposit is microbe excreta with occasional mummified
woody plant structures which by some event were pushed deep into the sediment and
escaped oxidation (Anonymous, 1993a).
In general coal geopolymers result from a random polymerization of a variety
of starting material. Although not necessarily derived from lignin, they tend to
resemble lignin in their chemical characteristics. Lignin is a structural plant polymer
that is abundant in plants and has an aromatic structure that consists of phenyl
propane subunits that are linked by C-C or C-O-C bonds (Atlas and Bartha, 1998;
Fakoussa and Hofrichter, 1999). Formation of coal starts with the decay of plant
material, which is then transformed into low rank coals (lignite and sub-bituminous).
Therefore, most low rank coal resembles lignin in structure and composition, and
have chemical structure very much like lignin, with a large number of C=O-OH and
C-OH bonds. Cations (K, Na, - - ) can substitute for H on the coal macromolecule.
21
The moisture within the coal structure is introduced from biological material
during coalification or as a result of water intrusion from the environment. Low rank
coals are relatively rich in moisture and oxygen content. With the time and right
conditions, lignite looses OH bonds and turn into higher rank coal i. e. bituminous
and ultimately forms condensed aromatic rings (free of oxygen) i.e. anthracite,
graphite. Different wet gases like ethane, propane, and other wet gases are also
sorbed in coal due to increased reservoir pressure created by artesian (well)
overpressure. The nitrogen and sulfur heterocyclic are the ones that make the coal
most environmentally unfriendly as these compounds are oxidized to SOX and NOX.
Thus, coal has heterogeneous nature and complex mixture of carbon, metal
compounds, and several other compounds such as hydrocarbons, hydrogen sulfur
compounds, hydrogen sulfide, ammonia water, and complex molecules such as tars.
Its composition varies widely according to location. Even within a coal resource, the
composition of coal may vary significantly along the x-y and z coordinates (Hatcher,
1990).
2.2.2 Structure of Coal
From a microbial CBM perspective, increasing coal maturity increases the
level of recalcitrance to biomethanation. Strapoc et al. (2011) observed a direct
negative correlation between coal m