A Case Study of the Hydrogen Economy and the News

THE USE OF LANGUAGE AND ITS IMPACT ON ENERGY POLICY

DISCOURSE: A CASE STUDY OF THE HYDROGEN ECONOMY AND

THE NEWS MEDIA DURING THE G.W. BUSH ADMINISTRATION

Alexander Francis Waegel

A dissertation submitted to the Faculty of the University of Delaware in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Energy and Environmental Policy

Spring 2015

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THE USE OF LANGUAGE AND ITS IMPACT ON ENERGY POLICY

DISCOURSE: A CASE STUDY OF THE HYDROGEN ECONOMY AND

THE NEWS MEDIA DURING THE G.W. BUSH ADMINISTRATION

Alexander Francis Waegel

Approved: ______John Byrne, Ph.D. Professor in charge of the dissertation on behalf of the Committee

Approved: ______Young-Doo Wang, Ph.D. Associate Director of the Graduate Energy and Environmental Policy Program

Approved: ______George H. Watson, Ph.D. Dean of the College of Arts and Sciences

Approved: ______James Richards, Ph.D. Vice Provost for Graduate and Professional Education

I certify that I have read this dissertation and that in my opinion it meets the academic and professional standard required by the University as a dissertation for the degree of Doctor of Philosophy.

Signed: ______John Byrne, Ph.D. Professor in charge of dissertation

Signed: ______Young-Doo Wang, Ph.D. Member of dissertation committee

Signed: ______Raymond Scattone, Ph.D. Member of dissertation committee

Signed: ______Mark Alan Hughes, Ph.D. Member of dissertation committee

ACKNOWLEDGEMENTS

I would like to thank the many people who have supported me throughout the process of writing this dissertation and throughout my graduate studies. First and foremost I would like to acknowledge Dr. John Byrne who has been my advisor since I began at UDel. I would never have been able to complete this dissertation without his guidance and patience. I would also like to thank the rest of my committee, Dr. Young- Doo Wang, Dr. Ray Scattone, and Dr. Mark Alan Hughes. Each of these individuals provided crucial insights that helped me evolve my proposal into my final dissertation and they were always willing to sit down and discuss any issues that I was having.

My family and friends were also of great support to me as I worked on my dissertation. I would like to thank my parents, Drs. William and Alice Waegel, for their emotional and financial support as I went through school as well as their insider advice on how to navigate academia. My brother, Daniel, was especially helpful to me as he frequently would run papers to CEEP for me, sparing me the long drive from Philadelphia. Finally I would like to thank Elspeth Anne Misiaszek, whose love and support has made my life wonderful in what would have been an otherwise very stressful time.

TABLE OF CONTENTS

LIST OF FIGURES ...... viii ABSTRACT ...... xiii

THESIS STATEMENT ...... xvi

Chapter

1 INTRODUCTION ...... 1

1.1 Information as Constructed Narratives in Policy Discourse ...... 1 1.2 The Role of Fact in Policy Development ...... 3 1.3 The Specialization of Knowledge ...... 6 1.4 The Basics of Hydrogen Technology ...... 9 1.5 The Current Hydrogen Energy Economy ...... 14 1.6 Quantifying Speech and Text ...... 18 1.7 The Presence and Impact of Sourcing in the Discourse of H2 .... 23

2 RHETORIC, LANGUAGE, AND ENERGY POLICY ...... 27

2.1 Language, Meaning, and Information ...... 27 2.2 The Model of Propaganda ...... 31 2.3 Identifying Constructed Narratives in Language ...... 41 2.4 Identifying Targets for Constructed Narratives ...... 45 2.5 Language and Stated Goals of Hydrogen Policy ...... 47

2.5.1 Federal H2 Policy During the Bush Administration ...... 48 2.5.2 Federal Level Incentives ...... 61 2.5.3 State Level Policy ...... 63

2.6 Language and Policy Conclusions ...... 67

3 PROPERTIES OF THE HYDROGEN ECONOMY ...... 69

3.1 Definition of the Hydrogen Energy Economy ...... 69 3.2 The Hydrogen Fuel Cell ...... 71

3.3 The Generation of Hydrogen as an Energy Carrier ...... 73

3.3.1 Hydrogen from Fossil Fuel Feedstocks ...... 79 3.3.2 Hydrogen from Electrolysis of Water ...... 91

3.4 Hydrogen Distribution and Storage ...... 98

3.4.1 The Compression and Storage of Hydrogen ...... 99 3.4.2 Distributing Hydrogen ...... 105 3.4.3 Hydrogen Distribution and Storage Conclusions ...... 110

3.5 The Role of Hydrogen in a Transitioning Energy Economy ...... 111

4 METHODOLOGY ...... 117

4.1 Content Analysis ...... 118 4.2 Applying Content Analysis to the Case Study ...... 123 4.3 Methodology for Coding and Analyzing the H2 Case Study ..... 129 4.4 Analyzing the Potential Outcomes...... 142

5 RESULTS ...... 145

5.1 The Collecting and Coding the Data ...... 145 5.2 Conducting the Single and Multivariable Regression ...... 153 5.3 Results of the Methodology ...... 157 5.4 Summary of Results ...... 173

6 CONCLUSIONS ...... 180

6.1 Implications of Sourcing on Hydrogen Energy...... 184 6.2 Implication of Sourcing on Energy Policy ...... 187 6.3 Countering the Spread of Narratives through Sourcing ...... 191 6.4 Lessons from the Methodology ...... 195 6.5 Future Research ...... 196 6.6 Concluding Remarks ...... 198

REFERENCES ...... 203

Appendix

A LIST OF SOURCE DATA ANALYZED ...... 222 B REGRESSION ANALYSIS RESULTS ...... 235

B.1 Bush Only Analysis, Single Variable ...... 236

B.1.1 Bush, 2001-2008 ...... 236 B.1.2 Bush, 2001-2005 ...... 238 B.1.3 Bush, 2006 ...... 240 B.1.4 Bush, 2007-2008 ...... 242

B.2 Energy Policy Indicators Only, Single Variable Regression ...... 244

B.2.1 Energy Policy, 2001-2008 ...... 244 B.2.2 Energy Policy, 2001-2005 ...... 246 B.2.3 Energy Policy, 2006 ...... 248 B.2.4 Energy Policy, 2007-2008 ...... 250

B.3 Bush and Energy Policy Indicators, Multivariable Regression .. 252

B.3.1 Bush & Energy Policy, 2001-2008 ...... 252 B.3.2 Bush & Energy Policy, 2001-2005 ...... 254 B.3.3 Bush & Energy Policy, 2006 ...... 256 B.3.4 Bush & Energy Policy, 2007-2008 ...... 258

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LIST OF FIGURES

Figure 1- Flow of Technical Information to the Public ...... 30

Figure 2- Flow of Information Examined in Hydrogen Case Study ...... 30

Figure 3- Basic Fuel Cell Operation ...... 72

Figure 4- Flow Chart of Methodology, Example Graph...... 137

Figure 5- Example of Coding (Bush Sample)...... 147

Figure 6- Example of Coding (Energy Policy Sample) ...... 148

Figure 7- Sample of Coding Results ...... 149

Figure 8- Timeline of Incidence of All Indicators ...... 150

Figure 9- Timeline of All Indicators, Normalized by Relevant Paragraph Count ...... 151

Figure 10- Timeline of All Indicators, Norm. by Relevant Para, 3 Month Ave ...... 152

Figure 11- Preparation for Analysis: Chronological Arrangement of Article ...... 154

Figure 12- Preparation for Analysis: Aggregation of Indicators to Create Indexes ...... 154

Figure 13- Timeline of Indexes for Each Source ...... 156

Figure 14- Summary of Regression Results: 2001-2008 ...... 159

Figure 15- Standardized Coefficients ...... 160

Figure 16- Timeline of Indexes for Each Source, 2001-2005 ...... 161

Figure 17- Scatterplot of the Bush Index vs. the NYT Index, 2001-2005 ...... 162

Figure 18- Combined Multivariable Regression Statistics for Pre2006 ...... 163

Figure 19- Summarized Regression Results: 2001-2005...... 164

Figure 20- Timeline of Indexes for Each Source, 2006 ...... 165

Figure 21- Scatterplot of Bush Index vs. NYT Index, 2006 ...... 165

viii

Figure 22- Combined Multivariable Regression Statistics for 2006 ...... 166

Figure 23- Summary of Regression Statistics: 2006...... 168

Figure 24- Timeline of Indexes for Each Source, 2007-2008 ...... 170

Figure 25- Scatterplot of Bush + Energy Policy Indices vs. NYT Index, 2007-2008 ..... 170

Figure 26- Combined Multivariable Regression Stats for Post 2006 ...... 171

Figure 27- Summarized Regression Results: 2007-2008...... 172

Figure 28- Summary Table of Multivariable Regression Results for 3 Timeframes ..... 178

Figure 29- List of Source Material Collected from Bush Administration ...... 222

Figure 30- List of Source Material Collected from New York Times ...... 224

Figure 31- List of Source Material Collected from Energy Policy ...... 229

Figure 32- Regression Results: Combined Bush Indicators, 2001-2008 ...... 236

Figure 33- Regression Results: Bush GHG Indicators, 2001-2008 ...... 236

Figure 34- Regression Results: Bush Efficiency Indicators, 2001-2008 ...... 236

Figure 35- Regression Results: Bush Sustainability Indicators, 2001-2008...... 237

Figure 36- Regression Results: Bush Sequestration Indicators, 2001-2008 ...... 237

Figure 37- Regression Results: Bush Sources Indicators, 2001-2008 ...... 237

Figure 38- Regression Results: Combined Bush Indicators, 2001-2005 ...... 238

Figure 39- Regression Results: Bush GHG Indicators, 2001-2005 ...... 238

Figure 40- Regression Results: Bush Efficiency Indicators, 2001-2005 ...... 238

Figure 41- Regression Results: Bush Sustainability Indicators, 2001-2005...... 239

Figure 42- Regression Results: Bush Sequestration Indicators, 2001-2005 ...... 239

Figure 43- Regression Results: Bush Sources Indicators, 2001-2005 ...... 239

Figure 44- Regression Results: Combined Bush Indicators, 2006 ...... 240

Figure 45- Regression Results: Bush GHG Indicators, 2006 ...... 240

Figure 46- Regression Results: Bush Efficiency Indicators, 2006 ...... 240

Figure 47- Regression Results: Bush Sustainability Indicators, 2006 ...... 241

Figure 48- Regression Results: Bush Sequestration Indicators, 2006 ...... 241

Figure 49- Regression Results: Bush Sources Indicators, 2006 ...... 241

Figure 50- Regression Results: Combined Bush Indicators, 2007-2008 ...... 242

Figure 51- Regression Results: Bush GHG Indicators, 2007-2008 ...... 242

Figure 52- Regression Results: Bush Efficiency Indicators, 2007-2008 ...... 242

Figure 53- Regression Results: Bush Sustainability Indicators, 2007-2008...... 243

Figure 54- Regression Results: Bush Sequestration Indicators, 2007-2008 ...... 243

Figure 55- Regression Results: Bush Sources Indicators, 2007-2008 ...... 243

Figure 56- Regression Results: Combined Energy Policy Indicators, 2001-2008 ...... 244

Figure 57- Regression Results: Energy Policy GHG Indicators, 2001-2008 ...... 244

Figure 58- Regression Results: Energy Policy Efficiency Indicators, 2001-2008 ...... 244

Figure 59- Regression Results: Energy Policy Sustainability Indicators, 2001-2008 .... 245

Figure 60- Regression Results: Energy Policy Sequestration Indicators, 2001-2008 .... 245

Figure 61- Regression Results: Energy Policy Sources Indicators, 2001-2008 ...... 245

Figure 62- Regression Results: Combined Energy Policy Indicators, 2001-2005 ...... 246

Figure 63- Regression Results: Energy Policy GHG Indicators, 2001-2005 ...... 246

Figure 64- Regression Results: Energy Policy Efficiency Indicators, 2001-2005 ...... 246

Figure 65- Regression Results: Energy Policy Sustainability Indicators, 2001-2005 .... 247

Figure 66- Regression Results: Energy Policy Sequestration Indicators, 2001-2005 .... 247

Figure 67- Regression Results: Energy Policy Sources Indicators, 2001-2005 ...... 247

Figure 68- Regression Results: Combined Energy Policy Indicators, 2006 ...... 248

Figure 69- Regression Results: Energy Policy GHG Indicators, 2006 ...... 248

Figure 70- Regression Results: Energy Policy Efficiency Indicators, 2006 ...... 248

Figure 71- Regression Results: Energy Policy Sustainability Indicators, 2006 ...... 249

Figure 72- Regression Results: Energy Policy Sequestration Indicators, 2006...... 249

Figure 73- Regression Results: Energy Policy Sources Indicators, 2006 ...... 249

Figure 74- Regression Results: Combined Energy Policy Indicators, 2007-2008 ...... 250

Figure 75- Regression Results: Energy Policy GHG Indicators, 2007-2008 ...... 250

Figure 76- Regression Results: Energy Policy Efficiency Indicators, 2007-2008 ...... 250

Figure 77- Regression Results: Energy Policy Sustainability Indicators, 2007-2008 .... 251

Figure 78- Regression Results: Energy Policy Sequestration Indicators, 2007-2008 .... 251

Figure 79- Regression Results: Energy Policy Sources Indicators, 2007-2008 ...... 251

Figure 80- Regression Results: Combined EP & Bush Indicators, 2001-2008 ...... 252

Figure 81- Regression Results: EP & Bush GHG Indicators, 2001-2008 ...... 252

Figure 82- Regression Results: EP & Bush Efficiency Indicators, 2001-2008 ...... 252

Figure 83- Regression Results: EP & Bush Sustainability Indicators, 2001-2008 ...... 253

Figure 84- Regression Results: EP & Bush Sequestration Indicators, 2001-2008 ...... 253

Figure 85- Regression Results: EP & Bush Sources Indicators, 2001-2008 ...... 253

Figure 86- Regression Results: Combined EP & Bush Indicators, 2001-2005 ...... 254

Figure 87- Regression Results: EP & Bush GHG Indicators, 2001-2005 ...... 254

Figure 88- Regression Results: EP & Bush Efficiency Indicators, 2001-2005 ...... 254

Figure 89- Regression Results: EP & Bush Sustainability Indicators, 2001-2005 ...... 255

Figure 90- Regression Results: EP & Bush Sequestration Indicators, 2001-2005 ...... 255

Figure 91- Regression Results: EP & Bush Sources Indicators, 2001-2005 ...... 255

Figure 92- Regression Results: Combined EP & Bush Indicators, 2006 ...... 256

Figure 93- Regression Results: EP & Bush GHG Indicators, 2006 ...... 256

Figure 94- Regression Results: EP & Bush Efficiency Indicators, 2006 ...... 256

Figure 95- Regression Results: EP & Bush Sustainability Indicators, 2006 ...... 257

Figure 96- Regression Results: EP & Bush Sequestration Indicators, 2006 ...... 257

Figure 97- Regression Results: EP & Bush Sources Indicators, 2006 ...... 257

Figure 98- Regression Results: Combined EP & Bush Indicators, 2007-2008 ...... 258

Figure 99- Regression Results: EP & Bush GHG Indicators, 2007-2008 ...... 258

Figure 100- Regression Results: EP & Bush Efficiency Indicators, 2007-2008 ...... 258

Figure 101- Regression Results: EP & Bush Sustainability Indicators, 2007-2008...... 259

Figure 102- Regression Results: EP Bush Sequestration Indicators, 2007-2008 ...... 259

Figure 103- Regression Results: EP & Bush Sources Indicators, 2007-2008 ...... 259

xii

ABSTRACT

The development of policy is subject to many different influences. The subjects are often complex and citizens must rely on information provided by third parties in order to participate in the discussion. The news media has traditionally been the primary provider of such information and are counted upon to publish unbiased accounts of events. However, the news media gets information from its own sources and this offers an opportunity for powerful, well-organized groups to influence the presentation of these topics. This is done through the creation and dissemination of constructed narratives, which remove the contexts from facts to present different conclusions (Barthes, 1957).

Sourcing discusses how the news media may be influenced by powerful organizations providing free, easily published material (Herman, 1988). The 24 hour news cycle, the demand for ratings, and the impossibility of funding independent research journalism for every topic requires them to seek information from sources viewed as reliable and authoritative, such as the government or major corporations. The wealthier and more powerful organizations are better able to provide this large quantity of information in a readily publishable format and thus have the potential to influence the presentation to reflect positively on their positions. As a technologically and politically complex subject, energy policy would be particularly prone to the influence of sourcing.

Hydrogen energy was used as a case study to search for the presence of sourcing.

Hydrogen fuels cells offer potential for the reduction of greenhouse gasses and other

xiii benefits, but have significant disadvantages as well. While the academic community remained divided on the technology, the G.W. Bush administration offered it unwavering support. The Bush administration and the academic community both released a great deal of information about hydrogen but each set presented a very different outlook.

Articles, press releases, and speeches from three sources were collected: the Bush administration, The New York Times, and Energy Policy and a methodology was created to attempt to analyze this phenomena. Every paragraph was coded for indicators in five different categories regarding the merits of hydrogen: greenhouse gasses, efficiency, sources, carbon sequestration, and sustainability. Each paragraph was coded for each category as critical, neutral or optimistic and profiles were developed representing each category over time. These profiles were then statistically analyzed to show the correlation between the views in The New York Times and either the Bush administration’s views or those found in Energy Policy.

This analysis showed that the views presented by The New York Times were highly correlated to those published by the Bush administration and the magnitude of the presence of those views could be predicted by the intensity of their usage by the Bush administration. Additionally these views were highly optimistic compared to those presented in Energy Policy, but these more critical views did not significantly influence the presentation of hydrogen by the media until 2006, with the publication of a special issue devoted to hydrogen, which raised their profile and, along with the beginning of the lame duck portion of the Bush presidency, allowed for a more balanced presentation of hydrogen in The New York Times. These results show that the methodology developed

xiv was successfully able to analyze the material to identify potential sourcing, proving its usefulness as a tool in investigating this phenomena.

THESIS STATEMENT

Policy development is a complicated process that is subject to the influence of many different actors. One influence on policy is public opinion, but complex issues often cannot be digested by lay readers and interpretation by an intermediary can play an important role in the understanding of an average citizen. The news media is one of the most common intermediaries offering digested information regarding current events. In turn, the news media rely on a host of reliable sources for the information that they release. This provides the opportunity for large well-organized groups, such as government agencies or corporate interests, to introduce constructed narratives supporting their views into the public discussion by preferentially supplying information favorable to their position through an effect called ‘sourcing’ (Herman & Chomsky,

1988).

Energy topics are especially subject to this influence as they are technologically and politically complex, which increases public reliance on the news media for information on these topics (Littlefield, 2013; Shwom, 2010; Nisbet, 2009; Nissani

1999). This dissertation uses the public discussion on the development of a hydrogen energy economy under the G. W. Bush administration as a case study to test a methodology that could provide evidence suggesting that sourcing impacted the presentation of this technology. As a proponent of the hydrogen economy President Bush organized his administration to develop and distribute press releases and policy papers

xvi providing consistently optimistic views of the technology and rarely voiced criticisms of the option. This was dissimilar to the discourse presented by the academic and research communities, represented in this case study by Energy Policy, an international research journal widely read by professionals and experts in the field.

The news media requires large amounts of readily available, easily printed material from sources that appear authoritative on each subject discussed. Large, well- organized groups can readily supply this information and can use this opportunity to introduce constructed narratives into presentations to support their positions. The news media is less likely to receive this quantity and quality of information from less powerful sources, which may not have the resources to supply this level of information or may not have the intent in doing so. Without an easily accessed and digested argument from other sources, the news media are likely to rely on information provided by powerful groups

(Shwom, 2010; Nisbet 2009). This provides a direct avenue for the more powerful organizations to feed their version of information to the public.

The methodology developed for this dissertation seeks empirical support for the presence of this influence by examining an issue that was actively debated and conducting a statistical analysis of the written materials provided by political and academic sources compared to the balance of those views later found in news articles. If the effect is not present, then the views of each group will be found in the news media without a statistically identifiable skew in their distribution. The methodology analyzes if there is a correlation between the positions expressed by the more powerful, highly organized sources and the news media while a correlation with the positions of other authoritative but less powerful, less organized sources is weaker or non-existent. While

xvii news articles are derived from many different pathways, sourcing should create a detectible correlation. This dynamic does not change unless other sources increase their level of organization and effort to counter this effect. Support for the thesis will be provided if the methodology is successful in demonstrating its effectiveness in analyzing the hydrogen discussion for the presence of sourcing and if it can be used to provide useful insights into the influences affecting the hydrogen discussion in the news media during the Bush administration, 2001-2008.

xviii

Chapter 1

INTRODUCTION

1.1 Information as Constructed Narratives in Policy Discourse

The development of policy is a complicated process subject to input from many factors. One significant factor in shaping policy is public opinion, but complex issues require an intermediary to digest and repeat them at a level that may be readily absorbed by the average citizen. One of the most accessible intermediaries is the news media, which serves as the primary outlet for the public to access information on current events

(Shwom, 2010; Littlefield, 2013). This adds a layer of abstraction to the discourse and creates the opportunity for large well organized groups, such as governments, NGOs, and corporations, to introduce influence the presentation of information to support their positions through several mechanisms. This dissertation proposes a methodology which could be used to analyze and quantify this phenomena.

Energy topics are especially subject to this influence as they are technologically and politically complex which forces the average citizen to rely on summaries of events and new technologies (Littlefield, 2013; Shwom, 2010; Nisbet, 2009) This dissertation uses the public discussion on the development of a hydrogen energy economy under the

G. W. Bush administration as a case study to provide evidence suggesting that the effect of sourcing impacted the presentation of this hotly debated technology. As a proponent of

1 the hydrogen economy the Bush administration releases provided consistently optimistic views of the technology and rarely voiced criticism (Lokey, 2007) This was dissimilar to the discourse presented by the academic and research communities, represented by

Energy Policy, which provided a balance of critical and optimistic positions acknowledging the technology’s strengths and flaws (Romm, 2004; Hammerschlag,

2004; Ogden, 2003; Winters, 2009)

One mechanism for this influence, known as ‘sourcing’, occurs when the news media requires large amounts of inexpensive, easily reproduced material from sources that appear authoritative on the subject. Larger, well-organized groups, such as the Bush administration or large corporations, can readily supply this information and can use this opportunity to selectively present this information to provide support for their positions

(Herman and Chomsky, 1988) The news media is less likely to receive this quantity and quality of information from less powerful sources which might present opposing views and so is more likely to pass along the introduced constructed narratives to the public.

This provides a direct avenue for the more powerful organizations to feed a specific version of information to the public, but with the appearance of a balanced presentation through the news media (Littlefield, 2013; Nisbet, 2009)

The thesis of this dissertation proposes that empirical evidence for the presence of this influence may be found by selecting an issue that was actively debated and conducting a statistical analysis of the written materials provided by political and academic sources compared to the balance of those views later found in news media articles. If sourcing is not an influence, then the positions of each source will be equally effective in predicting the later presentation of that information by the news media and

2 there will not be an identifiable skew in the distribution of the data. If constructed narratives have been introduced by a well-organized group, then there will be a correlation between the positions expressed by this source and the news media while a correlation with the positions of other sources will be lesser or non-existent (Herman,

1988) This dynamic does not change unless another source increases its level of organization and effort to counter this effect. The developed methodology was applied to the issue of hydrogen energy during the Bush Administration, comparing their speech to that found in Energy Policy and considering the correlation between each and the resulting text found discussing hydrogen in The New York Times in the following months.

Statistical analysis showed that from 2001-2005 the views promoted by the Bush administration regarding the hydrogen economy serve as an accurate predictor of the views printed in The New York Times while the views found in Energy Policy have a minimal influence. This dynamic only changed when Energy Policy released a special issue devoted to, and highly critical of, hydrogen. Beginning in 2006, the views presented by Energy Policy began to appear more regularly in The New York Times and equal weight was given to both positions. This evidence supports the thesis that the developed methodology can determine when sourcing is influencing the presentation of complex policy issues and suggests that this effect can be countered, but only through the concerted efforts of the less powerful actors and highlights the vulnerability of energy issues to this effect.

1.2 The Role of Fact in Policy Development

At the end of the twentieth century the public, organizations, and governments began to recognize the potential impact of global warming. Lengthy discussions ensued

3 regarding the cause and scale of the problem, with some parties arguing that we couldn’t even be sure that anything unnatural was occurring (Switzer, 2004; Nissani, 2009; Nisbet,

1999; Shwom 2010; Littlefield, 2013). How much would temperatures rise? When would these changes occur? Was the problem anthropogenic or the result of a natural cycle of the Earth’s climate?

While the debate has continued into the early twenty-first century, several key points have since been agreed upon by most major stakeholders. 1) The Earth’s global, mean temperature is rising and it is due to the accumulation of greenhouse gasses in the atmosphere. 2) The accumulation of the greenhouse gasses, of which carbon dioxide is the chief contributor to warming, has been caused by the actions of humanity, not due to natural processes. 3) While exact dates are still uncertain, global level environmental catastrophes will occur within the next century if a significant change in humanity’s greenhouse gas emissions does not occur within the next twenty-five to fifty years (IPCC,

2007). Accompanying the debate, a widespread consensus has emerged that we, as a species, not only can, but should, do something to change the course that our civilization has set (Bang, 2010) But, while the worldwide consensus can be found at the general level, the methods for reaching that goal have been a subject of great debate and disagreement (Switzer, 2004; Byrne, 2007; Lokey, 2007a; Blanchette, 2008; Shwom,

2010; Bakker, 2012).

The first significant attempt at a worldwide consensus on how to deal with the threat of global warming was the Kyoto Protocol, which was developed in 1997. The goal of the Kyoto Protocol was to have the emissions of developed, or Annex 1, nations drop to an average level of 5% below the 1990 greenhouse gas emission levels by 2012, at

4 which point the treaty would expire (Byrne., 2007; Grubb, 1999). Though developed and signed in 1997, the treaty would not go into effect until 2005, when Russia ratified the treaty. This was due to a part of the Kyoto Protocol which stated that the agreement would not go into effect until 55 nations ratified the agreement. In addition, the nations ratifying the agreement had to account for at least 55% of global carbon dioxide gas emissions. The 55% accountability requirement of the treaty was originally not met due to three of the largest emitters failing to ratify the agreement: Russia, Australia, and the

United States. While Australia has since signed the agreement, the United States, now the world’s second largest emitter of carbon dioxide behind non-Annex 1 China, never ratified the Kyoto Protocol (Crowley, 2010; Guan, 2009).

Why, in the face of significant scientific support and intense international pressure, did the United States not join in the Kyoto Protocol? The political disagreement in the

U.S. is generally not whether the climate is changing or even whether the actions of mankind are responsible for that change, but what types of action will be taken to address the problem, how quickly those actions must be taken, and by whom ( (Bang, 2010) The

United States has stated two primary objections to the treaty, 1) the exclusion of non-

Annex 1 countries being bound to reduce their emissions and 2) the idea that making the reductions required by the treaty would endanger jobs and the economy within the United

States (Byrne., 2007; Crowley, 2010; Shwom, 2010).

Ultimately, the United States was able to hold back from signing the Kyoto

Protocol because, despite general acceptance by the scientific community and the global community there is continued public debate in the United States regarding the scientific facts of global warming, who should bear responsibility, and the urgency with which the

5 issue must be addressed compared to other societal issues. The lack of cohesion in the public mindset has been brought about by doubts raised repeatedly by public figures and disseminated through the media, regardless of the scientific consensus agreeing to the basic facts of climate change (Bang, 2010; Hovi, 2012; Nisbet, 2009; Shwom, 2010).

This is possible because the general public does not have the capacity to conduct an independent analysis of many technical issues (Davies, 2004; Hodson and Marvin, 2006;

Zimmer and Welke, 2012) and thus can only rely on the information that is made available through the media and direct sources of information from governmental releases or popular science publications (Hamilton, 2009).

1.3 The Specialization of Knowledge

As the body of knowledge generated by humanity grows in breadth and complexity the percentage of that knowledge that any one individual can potentially master grows smaller. Before the specialization of livelihoods, it may have been possible for early humans to absorb the majority of knowledge gathered by humanity up until that point and utilize it in their day-to-day lives ( (Boose, 1989) But with the rise of agrarian societies, which allowed some individuals to give up the pursuit of food as a profession to become specialists, it has become impossible to expect any one individual to master in- depth knowledge in all of the fields of specialization which have developed over several millennia (Davies, 2004). In the modern era, this problem has worsened as the rate of scientific discovery has rapidly increased. This has caused an acceleration of the rate at which the gap grows between what is known collectively as a species and what an individual is capable of learning. As this occurs, disciplines subdivide and specialization occurs in ever narrower areas of study (Vanderberg, 2009).

This is concerning for several reasons. Increasing specialization allows an individual to become an expert in a specific area at the cost of considering how elements within that sub-field may affect other sectors of society (Vanderberg, 2009). One concern is how this effect would impact the political sector. It is the responsibility of the government to create and enforce laws which regulate many different aspects of human life and economic activity. However, the capacity of some elected officials and the public at large to understand the relevant technical issues being discussed in the public arena has proportionally decreased. This has led to a situation whereby neither the public, nor in some cases the politicians, fully understand the technical complexities of the issues which are being legislated (Nissani, 1999; Lambright, 2008; Nisbet, 2009; Littlefield, 2013).

The lack of the knowledge necessary to create informed policy or to make informed voting choices is of particular concern when a party with a stake in the decision intervenes by supplying digested and summarized information. By selectively presenting the information in terms favorable to their position, they could exert control over the public perception of an issue and thus can heavily influence the development of policy

(Herman, 1988; Lokey, 2007; Lokey, 2007a; Littlefield, 2013). Since specialized knowledge would be required to refute or comment critically on any of the supplied information, only a small portion of the population would be able to effectively respond to this sort of manipulation.

The issue is further compounded by the current state of the news industry. With print-based news media slowly declining in terms of circulation and advertising revenues, and with the rise of ‘infotainment’ and highly editorialized opinion shows on news networks such as Fox News and MSNBC, budgets for investigative journalism and

7 journalistic research have been steadily falling across the globe (Hamilton, 2009). In an atmosphere where the gap between what individuals can know and the collective mass of information is growing larger each day, the media is able to devote fewer and fewer resources to doing their own research on important issues. Instead they are forced to rely heavily on pre-generated content which is supplied by experts, corporations, or governmental sources (Lokey, 2007a; Blanchette, 2008; Mullen, 2010). The largest suppliers of information to media outlets are a relatively small number of organizations with the budgets and expertise capable of generating vast amounts of information. While there are many different avenues by which the news media pursues and develops stories, this may lead to an increase in the presentation of information in the news media that reflects the position of the powerful information supplier (Payne, 2008).

For technological issues, since this effect cannot be detected, let alone contradicted, by the average lay-person due to their lack of specialized knowledge, it would then begin to be incorporated into the general public’s world view (Hodson and

Marvin, 2006; Lokey, 2007) Language and phrasing may be used in this way to emphasize a technology’s benefits while ignoring complicating factors that would make it seem less environmentally or economically sound. This could lead to the public acceptance of policies that perform differently than expected or desired ( (Zimmer and

Welke, 2012) Due to the urgency of the global warming issue and the high cost of pursuing any alternative energy system, making policy decisions based on incomplete data could be costly, both financially and environmentally (Hammerschlag, 2005;

Littlefield, 2013).

1.4 The Basics of Hydrogen Technology

The purpose of this dissertation is to demonstrate that the replication of constructed narratives from governmental sources does occur in the U.S. printed news media and that this has contributed to the uneven presentation of technical issues in the field of energy production and policy. This was accomplished by examining the treatment of the hydrogen economy and developing hydrogen technologies during the George W.

Bush administration. In 2003 President Bush announced a large funding initiative designed to accelerate the adoption of hydrogen gas as an energy carrier (Fuel Cells

Bulletin, 2003, 2003a, 2003b, 2005, 2008; Tidball, 2009). While the technical qualities of and potential drawbacks to using hydrogen were still being considered, the Bush administration was viewed by skeptics as presenting a largely optimistic image of the technology, even in areas that were being actively contested by the scientific experts

(Hodson and Marvin, 2006; Lokey, 2007a; Blanchette, 2008; Hultman, 2011).

The uncertainty shown by the experts can be seen in the journal literature from those years, when a lively debate took place regarding the merits of hydrogen

(Hammerschlag, 2005; Rifkin, 2002; Romm, 2004; Blanchard and Perkaus, 2004;

Hodson and Marvin, 2006; Lokey, 2007; Lokey, 2007a; Blanchette, 2008; Barbir, 2009; do Sacramento, 2013; Littlefield, 2013; Jewell. 2014). The news media also discussed the potential hydrogen economy extensively during this time. As the hydrogen economy is a technically complex issue, it is the information presented in the news media that was most likely to be adopted by society at large as this was the most comprehensible, comprehensive set of information to which the public had easy access (Hodson and

Marvin, 2006; Lokey, 2007; Mullen, 2010).

This case study examines the use of language at the federal level to promote the formation of hydrogen energy policy and the potential influence that the chosen language had on the information disseminated by the news media on hydrogen technology during the George W. Bush administration. This topic was chosen as the target for this study due to the prominence of phrases in the media and in political speech such as, “zero- emissions hydrogen cars” or “emits only water.” These phrases can be misleading concerning the ecological and societal impacts of these technologies depending on the context provided (Hodson and Marvin, 2006; Lokey, 2007; Lokey, 2007a; Littlefield,

2013)

Some of the methods for generating hydrogen have been briefly mentioned, and while they will be discussed in great detail in Chapter 3, it would be useful at this point to have a short discussion regarding the myriad of methods that exist for creating hydrogen.

There are currently three different categories of feedstock from which hydrogen is extracted: water, fossil fuels, and biomass (Ogden, 2004; NAS, 2004; Fayaz, 2012). Each of these sources for hydrogen fuel can be processed in a variety of different ways typically by breaking down the feedstock through the application of heat or electricity.

Fossil fuels have been the traditional source for hydrogen, with natural gas supplying more than 90% of the hydrogen that is generated in the United States (Ogden,

1999; Romm, 2004; Blanchette. 2008; Han, 2012; Hajjaji, 2012). The process for extracting hydrogen from different fossil fuels is essentially the same, with a few steps added or left out depending on the fuel. The first requirement is that the feedstock be gaseous, which means that solid and liquid fuels, such as coal or petroleum, must first be gasified. The gasified fossil fuel is then subjected to a process known as steam

10 reformation. In this process the fossil fuel gas is exposed to super-heated steam. In doing so the hydrogen is stripped from both the fossil fuel gas and the water (Ogden, 1999;

NAS, 2004; Rand, 2005; Hajjaji. 2012). The resultant gas streams are separated and the hydrogen is captured and stored while carbon dioxide is either released into the atmosphere or, potentially, is captured and sequestered. At this point in time, however, carbon sequestration is still a developing technology and has not been widely applied to hydrogen generation plants (Lal, 2008; Han, 2012; Yang and Ogden, 2013; Chi, 2014).

While most of the hydrogen generated in the United States currently comes from the reformation of natural gas, coal is viewed to be one of the likely primary sources for hydrogen generation in the future (NAS, 2004; Barbir, 2009; Han, 2012; Ren at al, 2013).

While there is currently a boom in the production of natural gas due to the advent of hydraulic fracking techniques, historically our demand for the fuel has outstripped the domestic capacity for production (Han, 2012). Coal, however, has been abundantly available in vast quantities. The northern Midwest and western states have often been referred to as the Saudi Arabia of coal due to their extensive coal beds (Goodell, 2006).

Coal is also projected to be one of the least expensive future sources for hydrogen production because coal itself is so inexpensive. Because of this hydrogen from coal ranks highly according to two of the criteria on which energy technology is judged, energy security and economics (NAS, 2004; Blanchette, 2008; Han, 2012; Yang and

Ogden, 2013).

On the other hand, coal sourced hydrogen ranks rather poorly when it comes to the environmental impact of the technology. Extracting hydrogen from coal first requires that the coal be mined and processed. This is extremely destructive to the environment

11 since modern mining techniques typically involve mountaintop removal or strip mining, both of which include removing massive amounts of surface soil and substrata of rock and soil in order to get to the coal (Goodell, 2006). In addition to this localized disruption of the environment, extracting the hydrogen from the coal once it has been processed releases significant amounts of carbon dioxide. So much so that, unless it is sequestered, a person driving a vehicle powered by hydrogen derived from coal will be producing carbon dioxide emissions at levels as high as if they were driving a vehicle powered by gasoline (NAS, 2004; Ogden, 1999; Reichmuth, 2013; Ren, 2013a). The emissions produced when hydrogen is reformed from natural gas include carbon dioxide as well, though at a rate substantially lower than those produced when extracting hydrogen from coal (NAS, 2004; Huss, 2013; Ren, 2013).

Hydrogen may also be extracted from water through a process known as electrolysis. Electrolysis is the electrochemical splitting of hydrogen from H2O.

Electrolysis occurs when an electrical current is passed through a body of water, producing both pure hydrogen as well as pure oxygen gasses (Ogden, 1999; Barbir, 2009;

Ren, 2013). The device that performs this action is known as an electrolyzer. Since the action of electrolysis is performed by electricity, nearly any power producing technology can be used to generate hydrogen (NAS, 2004). This is especially useful for those renewable energy technologies which are intermittent in nature as they can use excess power to generate hydrogen when they are producing more than they can use at the time and then use the hydrogen to supply power when the original power source is not available (Rand, 2005; Suppes, 2006; do Sacramento, 2013; Huss, 2013; Sanchez and

Gonzalez, 2013; Xhang and Wan, 2014). This allows for a balancing of supply and

12 demand that would normally have to take place through electrochemical batteries or some other energy storage technology.

The electrolytic generation of hydrogen may also be useful in taking advantage of energy technologies that are available on demand but which are equally available during off-peak periods as during peak periods. These technologies include nuclear and hydroelectric power. In many of these cases it is easier to keep these plants running at a capacity that would exceed demand at the time in order to produce hydrogen during the off-peak times (Ogden, 1999; NAS, 2004; Rand, 2005; Mazloomi and Gomes, 2012;

Ren, 2013). Many envision a future where much of the electrical power in the U.S. is generated from nuclear power plants and that during the off-peak hours of the day, these plants would be used to generate hydrogen for use in transportation services.

Just as in the production of hydrogen from fossil fuels, the generation of hydrogen through electrolysis must be judged based on the source of the energy used to produce it.

Hydrogen produced from solar electricity would be available domestically, equitable, and have a low impact on the environment, but would rate poorly on the economic scale unless the price of solar panels can be drastically reduced from current levels (

(Bozoglan, 2012; Caliskan, 2013; Anandaraja, 2013; Ren, 2013; Marino, 2013) If the electricity were to come from a coal-fired power plant, then similar environmental impacts would occur as when hydrogen was directly extracted from the coal (Barbir,

2009; Ren, 2013; Reichmuth et el, 2013). In fact the environmental and economic impact of hydrogen from coal powered electrolysis would be even worse than if the hydrogen were removed from the coal directly due to inefficiencies introduced into the energy chain by the electrolytic process (NAS, 2004; Hammerschlag, 2005; Marino, 2013).

The final source for hydrogen is from biomass. Since fossil fuels are simply biomass that has been under varying levels of heat and pressure for millions of years it makes sense that biomass would have significant levels of hydrogen as well. There are a number of processes that can be used to extract hydrogen from biomass. At the most basic are thermolytic processes similar to those used to extract hydrogen from fossil fuels. These involve turning the biomass into a synthetic gas that can be reformed into its component parts under high temperatures and pressures (NAS, 2004; Ren, 2013;

Trchounian, 2014). But more exciting are the biological methods for the production of hydrogen. These biological processes involve the manufacture of hydrogen from organic materials.

While biological methods for production are still in the experimental stages there has been limited success in generating hydrogen from specifically selected and engineered algae and bacteria which have been altered to generate hydrogen gas as a metabolic waste product (NAS, 2004; Trchounian, 2013). It is difficult to say where exactly these technologies will fit into the grander scheme of hydrogen generation because they are still new and experimental. It is possible that someday massive amounts of hydrogen will be generated from extensive fields of vats full of algae or bacteria colonies, but as of right now it is unknown what the costs or impacts of such a system might be.

1.5 The Current Hydrogen Energy Economy

At this point in time hydrogen has only found a few niche applications in limited commercial areas and more expansive demonstration projects ( (Park, 2013, Brown,

2012; Yang and Ogden, 2013) In the commercial sector hydrogen technologies have been

14 used in areas where backup power is needed for sensitive operations, such as hospitals, banks, and other financial institutions. This is due to the relatively quick start up time for hydrogen fuel cells, many of which can provide power in under a minute of notice (Rand,

2005). For institutions that handle many millions of dollars every hour, being without power can represent a tremendous financial loss and thus expensive hydrogen fuel cell backup power systems are considered to be a sound investment ( (Anandarjara, 2013)

Fuel cells have also seen some use in providing power to off-grid applications, although most of these systems are demonstration projects or a part of a study as they are rarely the most economical choice for off-grid energy storage (Isherwood, 2000;

Kelouwani, 2005; Santarelli; 2004; Shakya, 2005; Blanchette, 2008 Anandarjara, 2013).

Additionally, hydrogen is also being used in space as a clean and efficient method of both providing electrical power and water to astronauts who are living in a small closed system.

One of the most exciting areas in which hydrogen currently applied, however, is in the field of transportation (Fayaz, 2012). Across the nation demonstration projects, including fuel cell powered cars and hydrogen fueling stations, are being set up to show how the transportation systems of the future might operate. As of this point these programs are nearly all cooperative projects being run between the federal or state governments and corporations in a cost sharing effort (California Energy Commission,

2001; NAS, 2004; California, 2005; Byrne; 2005; Brown, 2012; Yang and Ogden, 2013).

California has long been the leader in alternative transportation, and renewable energy in general, and it is no surprise that they are the leaders in developing a hydrogen based transportation system in the United States. By being the first customer for the hydrogen

15 transportation economy governmental entities, along with their corporate partners, may be able to kick start the hydrogen economy in a way that private industry alone might not

(Hu, 2011; Brown, 2012).

The reality of hydrogen is that it is still a developing technology and the path that it will follow is unclear. The greatest question is, where will hydrogen come from and how will it be separated from its feedstock? This is significant primarily because of the economic and environmental impact differences between the different options (Barbir,

2009, Ren, 2013). The reformation of fossil fuels has historically dominated the field of hydrogen generation because the fuels are available domestically and the process is relatively inexpensive as compared to other means of hydrogen generation (Ogden, 1999;

NAS, 2004; Ren, 2013). But the emissions from the reformation of fossil fuels to produce hydrogen can be significant, possibly as high as emissions levels from conventional usages of fossil fuels (Hammerschlag, 2004).

One saving grace for hydrogen through the reformation of fossil fuels is the potential for carbon sequestration. This is because, unlike many conventional uses of fossil fuels, reformation could potentially occur in a centralized location rather than in many distributed locations, which may make it possible to capture, store, and sequester emissions. But this technology remains unproven on a large scale and could significantly increase the cost of generating hydrogen (Lal, 2008; Yang and Ogden, 2013; Chi, 2014).

Electrolysis of water and biomass sources may be able to bypass some of these environmental concerns as well, but these methods are too expensive to be commercially competitive with the reformation of fossil fuels (Barbir, 2009; Han, 2012; Anandarjara,

2013).

When discussing the potential for hydrogen, it is important to examine, not just the end point of an established hydrogen economy but to also examine the steps that would be taken to get from our current hydrogen reality to that potential state. The hydrogen potential really describes a system where a massive shift in how the United

States produces power has occurred. The transformation would not be just in the transportation sector or the electrical generation sector, but all areas where energy is used and produced. The potential of hydrogen is in the ability of hydrogen and fuel cell technology to aid in the general transition to a green energy economy (Waegel, 2006;

Blanchette, 2008; Clark, 2008; Andrews and Shabani, 2012).

When examining green energy, such as solar or wind power, one of the primary stumbling blocks to the adoption of these energy sources is the problem of intermittency, when the supply of energy cannot be controlled to meet the immediate demand

(MacKenzie, 1992; Anderson, 2009; Marino, 2013; Sanchez and Gonzalez, 2013).

Hydrogen can be used as an energy carrier as a means of overcoming the problem of intermittency so that the grid can be kept stable. In addition to this capability, the versatility gained by being able to store and transfer the energy produced from sustainable, green energy sources will allow them to be more easily utilized for transportation uses (Rand, 2004; NAS, 2004; Balta-Ozkan and Baldwin, 2013). In this fashion, the introduction of hydrogen technology can allow for traditional fossil fuels to be phased out of the energy economy and new, renewable and sustainable energy sources can be implemented in their stead.

But how can such a transition take place? There are numerous economic and technological barriers that would have to be overcome in order to implement a hydrogen-

17 based sustainable energy economy and any transition of this magnitude cannot occur overnight. Instead it must be an extended and well planned process, taking place over decades according to a well-defined set of policies (NAS, 2004; Waegel, 2006; Andrews and Shabani, 2012a, McDowall, 2012).

1.6 Quantifying Speech and Text

Given the complexity of the issue, the hydrogen economy and its various associated technologies may be described in many different ways (Hodson and Marvin,

2006; Lokey, 2007; Lokey, 2007a; Clark, 2008; Hwang, 2013). Each description may be analyzed through the identification of opposing core positions defined by the information they provide and withhold. These positions may be used to define optimistic and critical indicators, the presences of which indicate constructed narratives containing incomplete information in either direction (Barthes, 1957). This section will describe the characteristics of both optimistic and critical indicators for hydrogen. These indicators will form the basis on which the treatment of hydrogen by the press, politicians, and experts will be analyzed and compared.

Hydrogen optimistic indicators are used to identify claims regarding the hydrogen economy and hydrogen technology in which the speaker posits that hydrogen is benign or beneficial in terms of its environmental and economic impact. An optimistic indicator can take many forms but they frequently may be reduced to the idea that hydrogen produces no emissions when used to produce power or that the production of hydrogen is sustainable without consideration of the source (Hodson and Mavin, 2006; Reichmuth,

2013) These claims are not false, but rather they skirt the truth while omitting specific facts. Hydrogen does not, in fact, produce emissions other than water vapor when

18 combusted or when run through a fuel cell. But what this optimistic indicator fails to recognize is that emissions may or may not have been created when the hydrogen itself was generated (Lokey, 2007).

What the hydrogen optimistic indicators typically fail to acknowledge is that hydrogen is not an energy source but rather an energy carrier and thus will be subject to many of the same impacts as its source and will not simply negate them (Rand, 2005;

Hammerschlag, 2005; Waegel, 2006; Lokey, 2007; Ren, 2013a). Thus hydrogen may well have a variety of impacts that will go unaccounted for if the source of the hydrogen is not examined closely. In fact, since any added conversions in an energy chain will introduce additional inefficiency into a system, storing an energy source in the form of hydrogen may mean that the negative impacts of the energy source will actually be amplified this resource will be used less efficiently after all of the energy transfers, storage, transportation and finally use in a fuel cell are taken into account (Hammerschlag, 2005;

Marino, 2012).

The hydrogen optimistic indicators identify language which promotes hydrogen as a zero emissions energy source, even though the energy policy in the United States at the time was directed towards developing hydrogen productions techniques from some of the highest emissions sources for hydrogen possible: natural gas and coal (NAS, 2004;

Romm, 2004; Lokey, 2007a; Blanchette, 2008; McDowall, 2012). While carbon capture and sequestration offer potential solutions to the emissions created by the reformation of fossil fuels into hydrogen, the technology is untested and unproven on the scale that would be required in order to sequester the massive amounts of carbon dioxide that would be produced if enough hydrogen were to be generated to meet even a small portion

19 of the nation’s energy demands (Lal, 2009; Yang and Ogden, 2013). Thus the idea that hydrogen is emissions free is dubious at best and deceitful at the worst, unless significant caveats are made regarding the generation of the hydrogen.

The hydrogen critical indicators perform the opposite role as the optimistic indicators. For each optimistic indicator there is an opposing critical indicator that argues an opposing viewpoint. However, like the optimistic indicators, the critical indicators also identify language that shows unfairly critical views towards hydrogen. If an optimistic indicator would be to state that ‘hydrogen produces no emissions other than water vapor’ then the opposing critical indicator is ‘hydrogen produces more emissions than current electrical generation sources.

Just as the optimistic indicator is partially true, true under certain circumstances, the critical indicator is also only partially true, since hydrogen generated through coal gasification without sequestration does emit more CO2 than a modern, high efficiency natural gas turbine (NAS, 2004) but hydrogen from many other sources would not. Both indicators only examine one link of the hydrogen production and utilization chain or only consider a single pathway for the hydrogen economy as a viable pathway. In both cases assumptions are made which, if taken to be true, makes their arguments valid, but which ignore the great variety of developmental paths a hydrogen economy might take (Hodson and Marvin, 2006; Barbir, 2009; Hwang, 2013; Ren, 2013). Critical indicators can be as misleading as optimistic indicators in terms of presenting an energy technology to an audience of lay people and they create the potential to hinder the development of a technology which could play a useful role in a transitioning energy economy.

Since the focus of the dissertation is on the use of language at the federal executive level, this research focuses on former President G.W. Bush and the Department of Energy under the Bush administration. The press releases and transcripts of speeches were all provided to the public and to news organizations free of charge and from them a timeline can be created showing the rate of incidence of positive and critical statements on the subject of the hydrogen economy from the administration (President George W.

Bush Library, N.D.). This body of text was examined for the presence of optimistic and critical indicators which were then used to gauge the direction and degree of treatment in the former president’s public presentation of hydrogen.

Political rhetoric may create a false impression of a technology through omission, such as in the common description of hydrogen as a zero emissions energy source, when emissions from hydrogen are a complex issue that can range from as much CO2 as gasoline to creating essentially no emissions at all (Ogden, 1999, NAS, 2004; Barbir,

2009; Hodson and Marvin, 2006; Lokey, 2007; Ren, 2013). The Bush administration actively developed and distributed materials promoting the benefits of the hydrogen economy and frequently repeated the positive aspects of hydrogen technologies and their potential to decrease national GHG emissions. At the same time the administration generally failed to discuss the negative aspects and criticisms of the technology leveled by some academics and environmentalists (Blanchard and Perkaus, 2004; Hodson and

Marvin, 2006; Lokey, 2007a; Blanchette, 2008.).

During Bush’s tenure in office, hundreds of millions of dollars were budgeted for research into hydrogen technologies and a long-term, multi-billion dollar investment was begun into the development of a national hydrogen infrastructure (Fuel Cells Bulletin,

2003; Fuel Cells Bulletin, 2003a; Fuel Cells Bulletin, 2003b; Fuel Cells Bulletin, 2005;

Fuel Cells Bulletin, 2008). However, in a sign of the political forces that were artificially inflating the demand for and utility of hydrogen, since President Bush left office

President Obama has drastically reduced hydrogen and fuel-cell funding at the federal level and the discussion of hydrogen as a serious contender in the energy field in the near to intermediate future has dropped precipitously (Biello, 2009). The question this dissertation asked was: could this be mathematically demonstrated and could it be shown to have an impact on how hydrogen was treated by the news media?

The effect of the language from the Bush administration was measured by examining a news journal of record during the period of time that he held office. For the purposes of this research The New York Times was selected as a representative source for the news media. This newspaper was used due to its reputation for high quality news research and its perceived slight liberal leanings. It was expected that it would be amongst the more resistant of the major newspapers to the influences of sourcing. The

New York Times articles were analyzed and coded for optimistic and critical indicators using the same criteria as the material analyzed from the Bush administration. The results of that coding were then used to determine if the positions identified in the materials promoted by the Bush administrations predicted an identifiable skew in the distribution of the positions later found in The New York Times.

To determine whether or not The New York Times was being influenced by the language used by the Bush administration as a governmental source of information, it was not only necessary to see if Bush administration positions had predictive power over the positions presented in The New York Times, but also to see if these positions ran

22 counter to those of a perceived neutral source which was also producing publicly available information. A peer-reviewed research journal should be more likely to produced balanced information due to diverse backgrounds of the journal contributors and their lack of a financial or political stake in the outcome of the policy discussion.

Articles about hydrogen from a peer reviewed scientific journal from that same time period are more likely to contain a mix of both optimistic statements about the benefits of hydrogen and also critical statements which point out its flaws and limits. To this end the journal Energy Policy, an international journal widely read by experts in the field, was used to represent the a neutral position from the scientific research community, once again using articles relating to hydrogen from a period of time that is concurrent with the

Bush administration’s terms in office.

All three sources were coded for the presence of optimistic and critical indicators for hydrogen across five categories. If sourcing was factoring into the presentation of hydrogen topics in the public forum, then the discussion in The New York Times would parallel the presentation of the topic by the Bush administration, while dissenting views as represented by Energy Policy would be less likely to be represented. This would lead to an identifiable skew in the distribution of indicators in The New York Times based on the materials from the Bush administration and no such skew when considering the positions found in Energy Policy.

1.7 The Presence and Impact of Sourcing in the Public Discourse of Hydrogen

By comparing the chronological incidence of optimistic and critical statements regarding the potential of the hydrogen economy in the Bush press releases, Energy

Policy, and The New York Times a picture is formed that suggests a flow of information

23 from the primary sources to the public, showing which information is adopted and passed on by the news media and what is not. This analysis shows that the hydrogen positions promoted by the Bush administration have a greater prevalence of optimistic indicators than Energy Policy regarding hydrogen and that a similar position was produced in The

New York Times in the months following. Concurrently it was determined that the positions presented in Energy Policy were a mix of critical and optimistic hydrogen positions, presenting a balanced view as expected, and that these positions only have predictive power for the positions in The New York Times after a significant effort was made by the community to have them recognized through the publication of an issue dedicated to the discussion of hydrogen.

A strong correlation between the expected optimistic positions presented by the

Bush administration and those found in The New York Times, along with a weaker correlation with the mix of positions found in Energy Policy, suggests that the Bush administration was able to use language to create an optimistic public presentation of information about hydrogen technology and that this influenced the presentation of the subject by the news media, despite concerns raised by the scientific community, and that any technical issue raised in a policy discussion would be similarly susceptible to this manner of influence.

However an initial examination of the data revealed two distinct behaviors between the periods of 2001-2005 and 2006-2008. The earlier period followed the pattern expected if sourcing was at work but the later period did not. The beginning of the later period coincided with the publication of an issue of Energy Policy dedicated to hydrogen which presented a strong counter argument to the optimistic position presented by the

Bush administration. This event broke the pattern seemingly established by sourcing and a new pattern dictated by shared influence from both Energy Policy and the Bush administration takes hold.

These findings support the thesis of this dissertation, which is that the developed methodology will detect the presence of sourcing and its impact on the discussion in the public sphere of energy issues. However it also highlights that this impact is not unshakable and alternative viewpoints can break through if an effort is made to promote and provide this information to the news media. In this case it took a focused effort from a group of authors from Energy Policy before their concerns were passed on by the news media. Evidence of the influence of sourcing in regards to hydrogen has broader implications for the field of energy policy in general and illuminates both how these issues may be subject to influence as well as providing a case study examining the impacts of that influence.

In this way the findings of this dissertation can help to understand the nature of the debate surrounding energy topics, which optimally would be evaluated according to economic and scientific fact, and how the news media may be used to influence public opinion to support less than optimal solutions. An examination of this influence will be vital to understanding how this mechanism can be used to influence policy to encourage technological choices based on partial information for political and financial gain at the cost of a higher economic and ecological burden placed on the public. Perhaps of greater importance will be the exceptions to this influence, when sourcing gives way to more comprehensive reporting. The identification of these circumstances could lead to approaches for limiting the influence of sourcing on the public discussion of energy

25 policy and in other policy arenas. Through the development of a methodology that is capable of providing a statistical analysis that detects and quantifies the presence of sourcing in the flow of information, a powerful tool is created for mitigating its effects.

Chapter 2

RHETORIC, LANGUAGE, AND ENERGY POLICY

2.1 Language, Meaning, and Information

The role that rhetoric and language plays in the formation of energy policy is a difficult issue to examine. There are usually positive and negative aspects to energy technologies that can be used to discuss them optimistically or critically, depending on how they are presented (Winter, 2009; Hammerschlag, 2005; Hodson and Marvin, 2006;

Lokey, 2007). Additionally, since the average person does not have the background to analyze complex energy technologies themselves, the public is almost entirely reliant on outside sources of information to provide information on a policy’s impact on the economy and on the environment (Payne, 2008; Zimmer and Welke, 2012). In the case of hydrogen there is an added complication as there are many different pathways along which the technology could develop, each of which would have dramatically different economic costs and varying levels of impact on the environment, which can serve to further confound the discussion (Ogden, 1999; NAS, 2004; Romm, 2005; Waegel, 2006;

Blanchette, 2008, Mansilla, 2012; Ren, 2013).

Roland Barthes, in Mythologies, states that myths are created when a signifier is stripped of its context, allowing its true meanings to be distorted. In the formation of hydrogen policy, the technological context that would allow for an understanding of the impacts of the technology has been removed from the discussion (Barthes, 1957).

Predicted results from the use of hydrogen as an energy carrier may be presented, but nearly all such instances presented in the public discourse abandon any thorough examination of the subject and instead pass on the end results without a deeper discussion of the assumptions that were used to build the scenario (Waegel, 2006; Hammerschlag,

2004; Lokey, 2007a; McDowall, 2012; Littlefield, 2013). In situations such as that encountered with hydrogen, where the impact of the technology is dependent on the source energy used to create the hydrogen causing it to be highly variable, removing the analytical context of the discussion allows the discourse surrounding the subject to be presented with a created context derived from partial details and omission: the hydrogen

‘myth’ (Modson and Marvin, 2006; Lokey, 2007; Lokey, 2007a; Littlefield, 2013)

The case study of hydrogen demonstrates that the creation of such managed information is possible and occurred under the Bush administration. Through the coding and statistical analysis of critical and optimistic indicators in the Bush, New York Times, and Energy Policy releases, the managed information can be identified as a skew in the distribution of the indicators found in the political and academic sources compared to those found in the news media and it can be determined which narratives and context created by the sources have predictive power over the positions later appearing in The

New York Times. This can be used to suggest a flow of optimistic hydrogen narratives created by the Bush administration as they penetrate into the public realm through their repetition in the news.

Figure 1 shows a diagram demonstrating how information might flow through various sources and news outlets to reach the public and be absorbed as knowledge. This diagram can be broadly split into three groups of actors who may either generate

28 information through research or obtain digested knowledge from another source. Each individual actor may receive or produce knowledge and many will do both. The three groups illustrated in Figure 1 are the knowledge digesters, who generate comprehensible information through basic research and previously conducted studies. This group includes any organization involved in basic research or data integration. The second group is the news distributors, whose task it is to gather digested knowledge and to present it for public consumption. Finally, the consumers of knowledge form the third group and this represents the target audience of the digested knowledge. While this diagram could be envisioned as a one way flow of information from basic research to news content to absorption by the public, in reality the flow of information is likely to be multidirectional and higher level actors may frequently be subject to feedback from the consumers of knowledge. This figure shows one possible configuration, but many different arrangements for the flow of information could be envisioned.

In Figure 2 the one sidedness of this flow of information is demonstrated by showing that the balanced mix of optimistic and critical indicators appearing in scientific journals do not similarly transition into the information distributed by the news media except when extraordinary effort is made. Establishing a clear correlation between the presentation of hydrogen by the Bush administration and the replication of that portrayal by the news media illustrates how vulnerable energy technologies are to this influence and highlights several of the negative outcomes that arise from this distortion. This chapter discusses the supporting theories that indicate the mechanism by which this influence is carried out and the means of detecting the impacts of that influence on public

29 discourse. The case study for this dissertation specifically examines the relationship between the three actors highlighted by the red box in Figure 2.

Figure 1- Flow of Technical Information to the Public

Figure 2- Flow of Information Examined in Hydrogen Case Study

2.2 The Model of Propaganda

To examine the core issues of this topic it is necessary to consider and adopt a model to understand how the rhetoric that is illustrated by the optimistic and critical indicators would be capable of influencing the media’s portrayal and the public’s perception of hydrogen technologies. One well regarded model of propaganda was proposed by Edward Herman and Noam Chomsky in their 1988 work entitled,

Manufacturing Consent: The Political Economy of the Mass Media (Herman, 1988). In this book the authors detail a “model of propaganda” which describes how the mass media is, in many ways, an extension of the rhetoric machinery of the dominant political and social powers of the western world.

The “model of propaganda” consists of five basic tenets, or filters, that describe the ways in which political and social actors are able to exert influence so that the information that is carried by various types of media, including newspapers, television, movies, magazines, and all other types of mass media, reflects the general attitudes and specific information that those actors wish to be disseminated amongst the public and excludes information and ideas that are counter to their interests (Herman, 1988). These five tenets include: 1) size, ownership, and profit orientation of the mass media; 2) the advertising license to do business; 3) sourcing mass media news; 4) flak and the enforcers; and 5) anticommunism as a control mechanism (Herman, 1988). Through these five tenets the authors describe the ways in which the media is influenced by the dominant actors in a society and in this fashion becomes a propaganda extension of those powers.

While it is the third tenet that is most important to the basic questions of this research, it is important that the entirety of the model be understood. The model provides the basic framework used in the later chapters of the dissertation to show that the message promoted by the news media was unduly influenced by the message promoted by the Bush administration and relatively unaffected by the critics of hydrogen in the academic and scientific community, except in unusual circumstances ( (Lokey, 2007;

McDowall, 2012)This provides support for the idea that the Bush administration was able to influence the public presentation of hydrogen energy (Hodson and Marvin, 2006;

Lokey, 2007) This allowed hydrogen technology to be portrayed as an environmentally friendly energy technology while ignoring the criticisms of the technology which indicated that hydrogen, especially if it is developed along the path envisioned by the

Bush administration, could have a negative net impact on the environment (Blanchette,

2008; Hodson and Marvin, 2006; Lokey, 2007a; McDowall, 2012).

The first tenet, size, ownership, and profit orientation of the mass media, describes the way in which the mass media is susceptible to influence by political and social powers due to the current nature of the basic economic institutions that control and own the media outlets. The propaganda model describes a power structure for the mass media in which the media outlets are, as time passes, being controlled by fewer and larger corporations and how, with that consolidation of corporate ownership, control over the majority of mass media now rests primarily in the hands of a few families and individuals

(Owen, 2012). This is a trend that has been underway since the mid nineteenth century and which, by the late 20th century, has completely changed the corporate landscape of the mass media. This has led to media empires that often control numerous major media

32 outlets across a variety of different forms, such as newspapers, television stations, and radio (Herman, 1988).

This concentration of ownership has been accomplished through several different means. Firstly, the industrialization of the mass media has led startup costs for even small media endeavors, such as a single metropolitan paper or magazine, to rise to hundreds of thousands if not millions of dollars. Additionally increased deregulation of the media has led to an increase in the number and scale of takeovers and mergers of media institutions

(Owen, 2012). These factors have led to the increasing focus of these institutions on profitability in order to placate the owners and decrease the attractiveness of a takeover to outside entities. This has led to the development of twenty four major media outlets that control the majority of the mass media in the western world (Herman, 1988).

Due to the concentration of control over the media in the hands of a few families, these institutions have developed extraordinary amounts of wealth and high values. This gives these organizations a vested interest in maintaining the status quo and thus an interest in supporting the social, political, and economic powers that have allowed this system to develop (Herman, 1988). A prime example of this has been uncovered in the wake of the News of the World scandal, which has exposed the close and often improper connections between Rupert Murdoch’s News Corp media empire and the United

Kingdom’s government (Keitley, 2012). The effect of this influence is further supported by a significant ownership of the media institutions by banks and other large investing interests.

The structure of the modern mass media has also led to the potential for control and influence by the government through the requirement of government licenses and

33 franchises that expose these institutions to government control or harassment. The countermeasure applied by the mass media organizations to this control has been the development of close ties with the government and its officials, high levels of lobbying, and other political expenditures. This can be seen through the fact that a significant number of the executives of mass media institutions are former government officials.

The net result of these factors is a mass media system where there are only a handful of dominant mass media institutions (Owen, 2012). These institutions are controlled by the very wealthy and are highly susceptible to market forces and profit orientation. Finally, due to their close ties with the corporate world and the government, these institutions share many of the same goals and interests as the major corporations, banks, and the government. These factors combine into the first filter that will affect the choices of mass media when it comes to the portrayal and selection of new stories

(Herman, 1988).

The second tenet of the model of propaganda is the advertising license to do business. This tenet describes the way in which media choices regarding news are significantly impacted by the rising importance and influence of advertising in the media realm. Since advertising essentially subsidizes the cost of producing and distributing media, it allows for content to be distributed to the public either at no cost or at a significantly lower cost than production costs would otherwise necessitate in order to provide a profit. This means that any media that is lacking for advertising will be at a significant disadvantage when compared to their competitors with advertising. This gives advertisers a significant level of control over the content of any given media because they

34 can withhold advertising dollars from any content of which they disapprove (Reuter,

2006; Herman, 1988).

The effects of advertising are significant on working-class oriented media sources, which are usually smaller and more prone to dissension with the political and corporate ruling elite. This is because the consumers of this media tend to be of more modest means and thus attract less advertising money, which tends to be directed towards those with a greater amount of disposable income. The fact that a reduced amount of advertising and less profitable advertising will increase the price of the media has a doubly increased impact because the consumers are of lower means. This further drives down the consumption of the media by their core base and creates a cycle that eventually drives the working class media out of business (Herman, 1988).

Because of advertising, media seeks to attract affluent consumers, and thus will be encouraged through the lure of advertising dollars to create content that will appeal more to the affluent people in a society. Even among mainstream media, small changes in the size of the consumer base can cause dramatic shifts in the level of advertising revenue that is attracted. Thus even mainstream media is held captive by the lure of advertising dollars being brought to the company (Herman, 1988). As was discussed in the first tenet, the bottom line in mass media is primarily profit driven and so advertising is capable of exerting a high level of control over the content of any mass media outlet.

This effect is well documented in real world situations, where advertisers have refused to do business with media outlets that have provided content that is politically or socially opposed to their own particular ideals and interests. These ideals and interests are almost universally politically and socially conservative. In this fashion, advertisers are

35 able to weed out undesirable content with the very real threat of withholding advertising dollars. This covers a broad range of issues ranging from criticism of corporate policies to governmental issues (Roberts, 1994). As the importance of advertising increases along with the price of advertising costs, the influence that the advertising has over content increases as well (Herman, 1988).

The overall impact of this filter is to drive media away from content that covers serious or disturbing issues and instead seeks content that will place the consumer into a purchasing mood. Such content tends to be less critical and more entertainment based.

While this is not a universal trend and some companies will sponsor more serious programming, the vast majority of advertising (and thus the content) will tend towards lighter and less substantial fare (Herman, 1988).

The third tenet of the propaganda model, and that which is of the greatest importance to the dissertation, is that of sourcing mass media news. The basis of this tenet is that the mass media relies on large sources of information in order to keep up with the demand for news in an economically viable and timely fashion. Due to the limits on the ability of any new organization to cover the events of the world, almost universally news outlets rely on outside sources for news coverage ( (Herman, 1988) This is because they are unable to pay to have reporters and cameras available at all times and locations where newsworthy events occur. So instead they concentrate their efforts in those locales where news is made available to them: press briefings, press releases, government releases of information (Grabe, 1999). Not only does this push the burden of collecting the news worthy data onto outside entities, but it also defers the cost of supporting a significantly larger news team.

The sources of data range widely from government of all levels to corporate interests and even non-profit organizations. These organizations produce large amounts of information that is dispersed freely and in a highly digestible format and thus they are attractive as sources of news content (Grabe, 1999). Government sources, especially, are viewed to be highly creditable and recognizable sources of news and thus are particularly valued as sources by the news teams. This allows the news teams to provide news that they have had to do very little in order to procure that they can still say is accurate and objective as it came from a credible source (Berkowitz, 1993).

The news producing arms of entities like the federal government and large industries are truly massive in scale and breadth of coverage. The amount of money, time, and man-hours that are expended by news producers unaffiliated with a media outlet dwarfs the amount of money, time and man hours that can be put into play by the actual news organizations (Herman, 1988). The Pentagon alone has a publishing operation that is sixteen times larger than that of the biggest publisher in the U.S.A. This includes media and news releases in a myriad of forms including: magazines, books, newspapers, press releases, interviews, TV stations, news conferences, and speeches. The corporate sector is likewise able to put forward a comparable news production effort to that of the military and the government (Gans, 2006).

These large news promoters are able to maintain their position as the primary source for news in part by making it incredibly easy for their news to be disseminated to the mass media. This is done by not only providing the information needed to fill the news coverage of any given event, but to provide this service for free. In addition they provide news organizations with places to convene, advanced copies of speeches, press

37 releases that are worded for easy use in the news, and photo opportunities. In effect they subsidize the news production process and make it extremely difficult for a news organization to compete unless they participate in this subsidy (Gans, 2006). It is interesting to note that since so much of this activity is occurring within the government, the citizens are essentially paying taxes to propagandize themselves (Herman, 1988).

Because of the new media’s dependency on these news sources, they may be influenced to circulate news that they otherwise would not, less they alienate themselves from the news provider. So not only are critical sources of news more difficult to find and obtain news from, but the use of these sources may offend the primary sources of newsworthy data, such as the government or big business. The big providers of news to the media have a long and significant history of refusing to play ball in situations where criticism might be levied at them from outside sources (Herman, 1988).

Through these means, large news producing arms of the government and big business are able to exert a tremendous influence on the news that reaches the average consumer. Not only do they control and produce the majority of the news which is filtered through the media to the consumers, but they are also able to exert their influence in order to suppress criticism and negative news (Grabe, 1999; Gans, 2006). Through the combination of these factors, the news media has very little control over the content of the news that they are distributing. Instead it mainly comes from outside corporate or partisan governmental sources that, in many cases, essentially write the news stories themselves. These sources are viewed as credible by the news media and are passed on as such to the general public (Herman, 1988; Hodson and Marvin, 2006; Lokey, 2007a;

Littlefield, 2013).

The fourth tenet of the model of propaganda is known as flak and it ties closely in with the tenet of sourcing. Flak is essentially complaints and protest, either from individuals or from an organization, directed at the media in response to the release of information that criticizes or disagrees with their point of view. It can come in many different forms including letter writing, bills passed by congress, petitions, lawsuits and many other forms of complaint as well. On a large scale, flak is capable of creating significant discomfort to the mass media, as well as proving to be extremely costly if advertising ends up being withdrawn either directly in protest or indirectly to avoid association with all of the negative attention (Herman, 1988).

While any organization, and even individuals, can produce flak, it takes flak from a powerful source to have a significant impact on the mass media. These sources of power might be corporate interests, government groups, or highly organized non-profit organizations. It can also be direct or indirect. Examples of direct flak would include things like letters or phone calls from the White house to a news anchor, interference from the FCC, or angry advertisers confronting the media regarding their programming.

Indirect flak includes appeals made, not to the media, but to the public at large in protest.

Examples would include advertising campaigns or the funding of political campaigns that have goals counter to those of the mass media (Herman, 1988).

Fear of these sorts of attacks is used to keep the media in check and toeing the desired line. Due to fear the media rarely confronts these attacks and instead seeks to mollify those whom it might offend. The government is a major source of flak, and regularly uses this technique to keep the media from straying too far from the message they desire to impart to the public. When the previous filters have failed to direct the

39 media into the proper course and the media delivers a message that defies the established order, then flak is used to beat the media back into the desired course through threats, demands, and public attacks (Herman, 1988).

The fifth and final filter is one that tends to have far less significance these days and it is anticommunism as a control mechanism. The theory of propaganda delivered by

Herman and Chomsky was created at the tail end of the cold war, prior to the fall of the

U.S.S.R. in 1988. Because of this the role of communism and the western struggle against it could not help but play a major part in any propaganda model describing government and capitalistic control over the mass media (Herman, 1988). But the question must be asked, does anticommunism still have relevance in the world today?

Classically anticommunism could be used as a tool against labor and the left, who sought greater equality and redistribution of wealth. But without the specter of communism to use as an excuse to blindly maintain the status quo this tool for enforcing a right wing agenda has lost much of its previous power. What has replaced much of the anticommunist fervor, however, is an exultation of capitalism; after all, capitalism won the cold war. This has only served to strengthen the market forces from which the other tenets draw their power (Herman, 2003). Ultimately, the strengthening of capitalism allows the filters of concentration of power, advertising, sourcing, and flak all to exert a greater influence on the mass media.

Taken together, the five tenets (filters) of the propaganda model described by

Herman and Chomsky represent the controlling forces behind the industries that deliver to us all of our media. While the dissertation primarily focuses on the tenet of sourcing as the means of introducing constructed narratives, it likely that some combination of the

40 tenets could be at work in influencing the language that is found in public discussion of hydrogen. But while the Model of Propaganda suggests that powerful organizations can promote their position by influencing the language used in the public discourse of the topic, it fails to offer a means of measuring this influence so that its presence and level of impact may be analyzed quantitatively ( (Lokey, 2007)

2.3 Identifying Constructed Narratives in Language

With a better understanding of the underlying mechanisms by which language may be used to introduce constructed narratives into the information presented in public discourse of complex issues, it is now possible to begin a consideration of how such constructed narratives can be identified and measured in the real world. Chapter 1 introduces the idea of indicators as a tool for quantitating the presence of particular views within language. While a deeper discussion of the methodology for this process can be found in Chapter 4, the remainder of this chapter delves deeper into the definition of the indicators and their roots in Barthes’ ‘myths’. One way to view the indicators would be as categories of myths, or meta-myths, representative of a group of commonly constructed narratives with specifically selected information supporting a particular position (Barthes,

1957) For every conflict, indicators may be identified that would suggest the introduction of constructed narratives from either the supporters or the opponents of the position and be grouped as optimistic or critical indicators. While the indicators may each address very different arguments, their combined count can be used to gauge overall support for or opposition against a position.

The term optimistic indicator will be defined for this study as it applies to the hydrogen energy economy and energy policy in general as follows: An optimistic

41 indicator identifies a claim or statement about the potential benefits of an energy technology that omits details which mitigate the strength of that claim. While the language identified by the optimistic indicators may be technically true, it makes claims regarding the potential of the technology that would only be achieved in specific situations (Hodson and Marvin, 2006; Lokey, 2007)

Optimistic indicators identify more than just a reduction in complexity. Rather, they highlight the omission of specific details and the emphasis of others, which leaves the consumer of this information with only a partial understanding of the impacts of the technology (Whitmarsh, 2009; Hodson and Marvin, 2006; Lokey, 2007a). Specific criteria are set describing the claims that must be made and the information that must be omitted for any language to be considered an optimistic indicator in each criteria being analyzed.

Optimistic indicators about hydrogen tend to be dominated by language regarding the future potential of hydrogen technology rather than what it is more likely to be capable of in the near future. This leaves the listener with a grossly distorted sense of the technical capabilities of the hydrogen energy economy (Lokey, 2007; Barbir, 2009).

While future hydrogen technology could be capable of fulfilling the promises made by the hydrogen optimistic indicators, those benefits would only be accrued if certain choices are made regarding which path the technology develops along into the future

(Waegel, 2006; Hodson and Marvin, 2006; Ren, 2013). What makes these ‘optimistic’ indicators is that the choices that are currently being made in terms of federal hydrogen policy and by the industry are unlikely to encourage the evolving hydrogen economy

42 towards the ending point that would provide all of the benefits described in the optimistic scenario.

At the opposite end of the spectrum from optimistic indicators are critical indicators. As the optimistic indicators identify language which highlights the positive aspects of the technology while ignoring the negative, critical indicators identify language that raises the negative aspects of an energy technology without discussing the positive aspects or other factors which could reduce the impact of some of the elements being criticized. Similarly to optimistic indicators, language may only be identified as a critical indicator by meeting specific criteria regarding the claims made and information omitted.

An example of this would be to discuss the negative environmental impacts of hydrogen since most hydrogen produced in the U.S. today comes from natural gas and that coal is a likely source for the majority of our future hydrogen demands (Ogden,

1999, NAS, 2004; Blanchette, 2008; Han, 2102). This is a valid criticism of hydrogen, as extracting hydrogen from either source will result in the emission of CO2 and the unsustainable consumption of fossil fuels. But this discussion leaves out several alternate scenarios for the development of the hydrogen economy, including a version that would be used in support of a renewable energy network using hydrogen as energy storage and producing no carbon emissions (Ogden, 1999; NAS, 2004; Clark, 2008; Ren, 2013). As with optimistic indicators, critical indicators identify language that primarily focuses on the negative aspects of hydrogen and omit details that would allay those criticisms.

The challenge of discussing the hydrogen economy and developing a realistic evaluation of the potential of hydrogen is that the public is unlikely to participate in this

43 complexity (Whitmarsh, 2009; Zimmer and Welke, 2012). Expert groups recognize this problem and seek to increase their influence over policy formation by attempting to convince the public with simplified rhetoric (Berkowitz, 2009; Lokey, 2007a; Littlefield,

2013). However, the true potential for hydrogen can only be represented by the full set of narratives, expert knowledge, and technical data that has been gathered about hydrogen technology and represents the current status of that technology in addition to the various ways it could develop (Han, 2012; Ren, 2013). It is in the comparison against the evaluation of this comprehensive potential that the criteria for the optimistic and critical indicators must be based.

To develop a comprehensive evaluation of impact of a hydrogen energy economy it is necessary to account for every step of the hydrogen production, transportation, storage, and utilization process ( (Clark, 2008; Ren, 2013; Reichmuth, 2013; Hwang,

2013) The hydrogen optimistic and critical indicators can be used to highlight language that focuses on a small section of the entire hydrogen fuel cycle, or a single scenario for the development of the hydrogen economy (Hodson and Marvin, 2006; Littlefield, 2013).

Only by completing a deeper level of analysis is it possible to develop an accurate accounting of the potential for environmental, economic, and social impact of the technology. While the details of the hydrogen economy will be explored in depth in the next chapter, it is important for this section to conduct a rudimentary discussion of the potential for hydrogen so that language containing the optimistic and critical indicators may be differentiated from statements reflecting a more balanced understanding.

2.4 Identifying Targets for the Introduction of Constructed Narratives

Each of these three concepts, hydrogen optimistic indicators, critical indicators and the potential of hydrogen, rely on an accurate evaluation of the benefits and attributes of hydrogen, hydrogen technologies, and the hydrogen economy. But what has not yet been discussed is on what basis such an evaluation should take place. There are four basic categories on which any energy system may be judged: economics, energy security, environmental impact, and equity (Ren, 2013a). As such, these are areas that are potential targets for the introduction of constructed narratives.

The economics of the hydrogen economy may seem, at first, like a simple summation of the costs associated with producing the hydrogen and the cost of the equipment to utilize the hydrogen as fuel. In reality, the issue is significantly more complicated. In addition to the costs of the hydrogen fuel and the equipment to turn that hydrogen into electricity are infrastructure costs, changing costs as the technology develops, externalities, and the costs of hydrogen as compared to other alternatives that might be adopted instead of hydrogen (Ogden, 1999; Romm, 2004; NAS, 2004, Waegel,

2006, Byrne, 2008; Lucas, 2012; Bakker, 2012; Anandarjara, 2013; Jewell, 2014). All of these issues tremendously complicate the economics of adopting hydrogen as a major carrier of energy in the world. These issues will be discussed in depth in Chapter 3.

The environmental impact of the hydrogen economy is the primary area in which the hydrogen optimistic and critical indicators diverge. Depending on the path that the hydrogen energy economy developed along the environmental impacts could be minimal or even worse than the traditional energy economy (Waegel, 2006; Clark, 2008; Ren,

2013; Reichmuth, 2013). The possible differences between the various pathways for the

45 hydrogen economy and their impact on the environment will be more fully explored later in Chapter 3, which will examine the different methods by which hydrogen might be produced, stored, distributed, and used to power the hydrogen economy.

Energy security is considered by many to be the primary motivator for the transition away from an oil based transportation system and energy economy to one that utilizes resources that are found domestically rather than imported from abroad

(Awerbuch, 2006; Andrews and Shabani, 2012). In this era of peak oil and unrest in the

Middle East concern has been raised about the steady and continuous supply of oil that is imported into the U.S. and is responsible for meeting more than 90 percent of our transportation needs, as well as supplying many important feedstocks for the creation of synthetic materials and plastics and other energy uses, such as heating oil (Hirsch, 2005).

Hydrogen, on the other hand, is a very secure energy technology as it is available domestically from a wide range of energy sources and feedstocks (Waegel, 2006, Romm,

2004; Ogden, 1999; Barbir, 2009; Andrews and Shabani, 2012; van der Zwann, 2013;

Pepitas, 2014).

Energy equity, the final category on which an energy technology might be evaluated, is a more nebulous and a difficult concept to define. Energy equity refers to the ability of all people to access an energy technology and benefit from its advantages. An energy source is equitable if it affordable and accessible for the majority of the citizens of a region (Roberts, 2008; Ren, 2013). Equity combines aspects of energy security and economics, but also represents a healthy measure of social justice as well. In an equitable energy system all citizens of an area would have equal access to the same arsenal of

46 energy technologies, both physically and economically, and could utilize the ones which best allowed them to gather local energy resources.

2.5 Language and Stated Goals of Hydrogen Policy

The governmental push to develop the hydrogen energy economy during this time period can be seen coming from two distinct levels: federal and state. While federal policy focused on developing a better understanding of the technology and did so through significant resource allocation towards research and development, the states’ policies tended to be more applied. Some states, such as California, have already begun constructing the infrastructure that will be needed to develop a hydrogen based personal transportation system with their Hydrogen Highways program ( (Ogden, 2003; Brown,

2012; Yang and Ogden, 2013) The states with hydrogen policies enacted during the Bush administration were California, Connecticut, Florida, Georgia, Hawaii, Idaho, Illinois,

Iowa, Minnesota, Missouri, Montana, New Jersey, New Mexico, New York, North

Dakota, Oregon, South Carolina, Texas, and Washington. In addition to these nineteen states, there were many states who had incentives or laws that cover hydrogen where hydrogen technology was not mentioned specifically but had been included with other alternative fuels. Since this dissertation is primarily focused on the federal level of government and its formation of hydrogen policy this chapter will focus on the federal policies enacted during the Bush administration and discuss these positions in terms of their implications for the impact of the proposed hydrogen economy and then will briefly discuss the state level policies.

2.5.1 Federal Hydrogen Policy During the Bush Administration

During the 2003 State of the Union Address, President Bush made a commitment to the development of a hydrogen energy economy, particularly for transportation purposes. During that speech, the president proposed $1.2 billion dollars in funding for research, much of which was distributed as grants to researchers through the DOE and the NSF (Fuel Cells Bulletin, 2003; Fuel Cells Bulletin, 2003a; Lokey, 2007a) This was the first major federal commitment to hydrogen technology and seemed to be an incredible opportunity to explore and develop a hydrogen energy economy. The exact wording of his commitment to hydrogen technologies is as follows:

“Tonight I'm proposing $1.2 billion in research funding so that America can lead the world in developing clean, hydrogen-powered automobiles. A simple chemical reaction between hydrogen and oxygen generates energy, which can be used to power a car, producing only water, not exhaust fumes. With a new national commitment, our scientists and engineers will overcome obstacles to taking these cars from laboratory to showroom, so that the first car driven by a child born today could be powered by hydrogen, and pollution-free. Join me in this important innovation to make our air significantly cleaner, and our country much less dependent on foreign sources of energy.”

(Bush, 2003)

During the Bush administration the federal government primarily focused on providing funding for research and development to overcome the hurdles that are preventing hydrogen and fuel cell technologies from marketplace introduction as well as cost sharing for demonstration projects ( (Blanchard and Perkaus, 2004; Lokey, 2007a;

McDowall, 2012) From 2003 to 2005, the government had distributed $640 million for

48 these projects and the remainder of this section will discuss how that money was spent and how that reflects on the goals and vision of the Bush administration for the development of a hydrogen energy economy ( (Fuel Cells Bulletin, 2003; Fuel Cells

Bulletin, 2003a, Fuel Cells Bulletin, 2003b; Fuel Cells Bulletin, 2005; Bush, 2003;

Lokey, 2007a, McDowall, 2012)

Of the $640 million, $120 million went into research on hydrogen production technologies. This money was split three ways: $43 million was used to research hydrogen from coal and carbon sequestration technologies; $75 million was split between renewable energy production methods and steam reformation of natural gas; and $2 million was used to research the nuclear thermolytic splitting of water ( (Hydrogen

Posture Plan, 2005; Fuel Cells Bulletin, 2003; Fuel Cells Bulletin, 2003a, Fuel Cells

Bulletin, 2003b; Fuel Cells Bulletin, 2005) This accurately reflects the government’s desire to achieve an overall shift away from foreign sources of energy towards domestically available energy sources, as the government seems to place a roughly equal weight on funding research into the production of hydrogen from coal, natural gas, and renewable sources.

The plan identifies natural gas as the optimal source in the beginning of this transition process citing established technology and a relatively low cost of feedstock and production. Through the research that was funded by the government, the production cost of hydrogen from natural gas fell from $5/gge in 2002 to $3/gge in 2006 ( (Hydrogen

Posture Plan, 2005) But they also identify natural gas as a poor long term source for hydrogen as the nation would be trading a dependence on foreign oil for a dependence on foreign natural gas, though the recent exploitation of the Marcellus Shale may alter that

49 prognosis (National Hydrogen Energy Roadmap, 2003; Blanchard and Perhaus, 2004;

Blanchette, 2008; Han, 2012; McDowall, 2012).

The production of hydrogen from coal gasification was a method that was identified as an important future source of the gas. Hydrogen policy during this period was often coupled with a Bush initiative called Future Gen, which researched the application of carbon sequestration technologies. It was believed that with Future Gen it would be possible to generate hydrogen from coal without the high levels of emissions that would negate the benefits of switching to hydrogen. This production technology received the largest amount of funding and the cost of hydrogen from coal gasification was brought to under $2/gge (Hydrogen Posture Plan). This begins a pattern in government policy during this time where clean coal and hydrogen are consistently linked ( (Hydrogen Posture Plan, 2005; National Hydrogen Energy Roadmap; and A

National Vision of America’s Transition to a Hydrogen Economy- To 2030 and Beyond,

2007; Lokey, 2007a; Blanchette, 2008; Han, 2012; Mansilla, 2012; Yang and Ogden,

2013)

The distribution of funds clearly shows a preference in the Bush administration for the production of hydrogen from fossil fuels rather than from renewable technologies.

This can be especially seen in the only proposal for the possible distribution of future sources for hydrogen proposed by the Bush administration which was outlined by the

National Hydrogen Energy Roadmap (2002). This report shows a possible distribution for the generation of hydrogen and only 10% of the hydrogen was to come from renewable electrolysis of water. Another 10% was to come from the nuclear thermolytic splitting of

50 water and the remaining 80% was to come from fossil fuel reformation and gasification

(National Hydrogen Energy Roadmap; Lokey, 2007a; Ren, 2013)

Another $150 million was spent on storage technologies. The federal government recognized that no existing hydrogen storage technology currently meets all of the specifications that would be required to commercialize hydrogen based technology, particularly for mobile applications. As such, the $150 million was spent on a variety of projects including advanced research on new materials, that can absorb the hydrogen rather than simply compressing or liquefying it, as well as new materials that are lighter and stronger for the storage of compressed hydrogen gas ( (Hydrogen Posture Plan, 2005;

Fuel Cell Bulletin, 2003a)

An additional $132 million has been spent researching the fuel cells themselves.

Specifically, the research and development efforts being funded with this money were designed to improve the durability of the fuel cells, lower the cost of the finished units, and to find alternative electrolytes to replace expensive and rare platinum. Each of these factors has been identified as a potential stumbling block on the way to a fully developed hydrogen energy economy and must be addressed before the economy can move forward into the future stages that are envisioned ( (Hydrogen Posture Plan, 2005; Fuel Cells

Bulletin, 2003)

$170 million dollars, out of the total $640 million, was spent on demonstration projects which were designed to test existing and new technologies to find potential faults and to determine the optimal operating conditions for these devices. For the most part, these demonstration projects were done cooperatively, on a cost share basis, with a corporation or business. In this fashion costs are reduced and both sides benefit from the

51 research. This is particularly common with fuel cell bus programs due to the centralized nature of the buses route ( (Hydrogen Posture Plan, 2005; Fuel Cells Bulletin, 2003b)

These projects also help to develop infrastructure that is either open to the public, or may one day be open to the public. This helps to overcome the chicken vs. the egg paradox that might otherwise be difficult to overcome and places the federal government in the role of both first customer and first supplier of hydrogen (National Hydrogen Energy

Roadmap, 2006; Brown, 2012; Park, 2013; Yang and Ogden, 2013)

The final $69 million dollars was spent on developing a set of codes, standards and safety procedures, $5 million, and on basic research, $64 million (Hydrogen Posture

Plan) Developing a set of unified codes and standards is of particular concern for two primary reasons. The first reason is that there is a great deal of concern at the public level regarding the safety of using hydrogen as a fuel. Many recall the Hindenburg accident and feel as though hydrogen is a dangerously explosive gas that is more dangerous than conventional fuels. While the reality is that hydrogen is generally safer than other fuels due to its low energy density and diffuse nature, it is a flammable gas and might be stored under conditions that have it highly compressed or cryogenically liquefied, either of which would make any gas potentially dangerous to handle. Even without the concern for safety, there is a need to develop a unified set of codes and standards for hydrogen equipment. Another major concern is that several regional networks of hydrogen energy economies will develop but each will be using a different set of codes and standards from each other making interconnection difficult.

The overall Bush administration vision of the development hydrogen economy can be seen as four overlapping stages of development for the hydrogen economy

(Hydrogen Posture Plan, 2005) The first of these stages has already begun and is labeled

“Technology Development”. During this phase of development the government plays a strong role in promoting research and development. During this stage, hydrogen technology has not yet been commercialized and many technological and economic barriers prevent hydrogen technology from entering the marketplace and the research and development is specifically designed to make the technologies market ready. While the plan tentatively places the end of this stage in 2015, the planners were unsure as to whether or not it may need to be extended as far as 2030, depending on how quickly breakthroughs are achieved and barriers overcome (McDowall, 2012; Yang and Ogden,

2013).

The second stage is entitled “Initial Market Penetration” and was supposed to begin in 2010. In this stage hydrogen technologies have proven to be both economical and technologically ready for applications in the real world and the government still plays a strong role. This is especially true early in this stage, when the federal and state governments may be playing the role of “first customer” in order to kick start the market for hydrogen technologies (Yang and Ogden, 2013) By the end of this stage, however, which they envision to occur around 2025, the government’s role in the hydrogen energy economy has been drastically reduced and individual and corporate entities have begun to drive the market for these technologies. At the time of this writing, 2010 is four years into the past and it is clear that the envisioned timeline did not come to pass.

This would have led directly to the third stage of the developing hydrogen energy economy entitled, “Expansion of Markets and Infrastructure”. By this point in the hydrogen energy economy, hydrogen technologies will have been fully and successfully

53 commercialized. Hydrogen technologies, by the end of this stage are now entirely economically competitive with existing technologies and have taken over many of the roles that had been commonly held by conventional energy technologies. Large regional areas will now have hydrogen transportation networks and fuel cells will be utilized in a wide variety of applications. By the final stage of the hydrogen energy economy, “Fully

Developed Markets and Infrastructure”, hydrogen energy has become ubiquitous. Not only is it economically competitive with conventional energy sources but in many ways, technologically, environmentally and economically, hydrogen has outstripped conventional energy technologies. The utilization of hydrogen is now nationwide and a cohesive set of infrastructure for fueling and hydrogen supply has been developed

(Hydrogen Posture Plan, 2005; Lokey, 2007a; Clark, 2008; Andrews and Shabani, 2012;

Han, 2012)

Many technological barriers still impede the progress of the hydrogen energy economy, such as the lack of suitable storage technologies, expensive catalysts, fuel cells that do not have the required durability, and other issues (Bakker, 2012; Pepitas, 2014)

The phase of research and development was supposed to finish in 2015, but even in the plan it was acknowledged that this stage may extend for as many as 15 years beyond that.

Additionally, the economics and environmental impact of the growing hydrogen energy economy are highly variable depending on the source of the hydrogen and whether or not clean coal technologies can be made to work, since the Hydrogen Posture Plan stated continued reliance on that particular energy source ( (Ren, 2013; Reichmuth, 2013. If clean coal technology proves to be a failure, however, then it is possible that the

54 hydrogen energy economy could develop into an extension of the current fossil fuel dominated energy economy complete with greenhouse gas emissions (Han, 2012).

In nearly every instance in which former President Bush mentioned hydrogen, it was described as a clean technology. Accompanying these statements were often phrases such as “no emissions other than water vapor” (Lokey, 2007a, Clark, 2008). As will be discussed in detail in Chapter 3, many different technologies exist for producing hydrogen from different sources (Ren, 2013), but of all the various methods for producing hydrogen, only a few of the techniques actually produce no emissions at all, such as electrolysis using renewable energy sources or using nuclear power to split water via electrolytic or thermolytic processes (Anadarjara, 2013, Bozoglan, 2012). If hydrogen is produced from coal, natural gas, petroleum, or even biomass, then the picture as to how environmentally friendly hydrogen is becomes a lot more nebulous.

So what manner of hydrogen economy was the President discussing and what implications does that have for emissions? Federal policy during this time heavily relied on the technology known as clean coal, especially the FutureGen program, which the

Bush administration claimed would be able to remove nearly all of the carbon dioxide from both burning coal for electricity or removing the hydrogen (Goodell, 2006; Hodson and Marvin, 2006; Lokey, 2007a). Without this process, extracting coal from hydrogen would release as much carbon dioxide into the atmosphere as simply continuing to burn gasoline in our vehicles (Ren, 2013). But even today uncertainties remain about the viability of this technology.

If the technologies exist to avoid using coal all together, why would anyone choose to use such a carbon intensive fuel? Why is there conflict about whether or not the

55 technology will work or not? These questions raise both doubts and hopes in anyone who is pondering the future of the hydrogen economy as the answers will shape the course of the hydrogen economy for decades and possibly into the next century. Coal is a controversial energy source because it has many benefits, but it is also one of the most polluting and damaging energy sources. Of the fossil fuels, coal has the highest carbon content and can hold many heavy metals and other pollutants that are released when burned (Goodel, 2006; Han, 2012; Ren, 2013; Dayhim, 2014)

However, unlike some fossil fuels, it is available domestically which makes it important for energy security. North America has vast, untapped coal reserves that are easily within reach and this gives coal a high degree of energy security ( (Goodel, 2006)

While the nation is currently experiencing a natural gas boom, historical fluctuations in natural gas price and availability have been volatile. Dwindling supplies or increased demand could throw the supply of natural gas into question. Finally, coal is incredibly cheap compared to other fossil fuels, and especially compared to renewable energy sources. Electricity from coal costs only a few cents per kilowatt hour to generate and hydrogen from coal costs under $2 per kilogram (Hydrogen Posture Plan, 2006; Ren,

2013; Marino, 2013; Anandarjara, 2013; Yand and Ogden, 2013). It should be no surprise then that coal is the preferred source of hydrogen in the coming decades by the federal government.

Methods for eliminating sulfur and nitrogen emissions from exhaust streams has been well developed and may be easily applied to existing technologies, but these lessons are not easily applied to the removal of carbon dioxide as it is relatively non-reactive.

While it can be done, it is difficult to retrofit existing coal fired power plants to do so.

Instead, most carbon sequestration methods rely on a process known as integrated gasification combined cycle, which uses heat and pressure to gasify the coal. These gasses are burned in a turbine similar to that of a natural gas turbine (Goodell, 2006; Han,

2012; Chi, 2014)

The advantages to such a system are many. Efficiency is improved by 10%, less water is utilized for cooling; only one half the solid waste and ash is produced, and they run nearly as cleanly as a natural gas power plant. Additionally, the resultant synthetic gas may be used to produce hydrogen. But the most important thing of all is the greater ease with which the carbon dioxide may be separated and sequestered from the waste stream of an IGCC plant than from a conventional power plant ( (Goodell, 2006; Han, 2012; Chi,

2014)

There are, however, several downsides to such technology. The first is that it relies on carbon sequestration, which has been unproven on a large scale or long term basis. Additionally, the IGCC plants cost 10-20% more than a traditional plant and, since it is financially impossible to convert older plants, it would potentially leave a great deal of stranded assets in the form of older plants that still have decades of life left before they would be decommissioned. It is estimated that the technology could cause electricity prices to rise by 20-25% (Goodell, 2006; Han, 2013; Ren, 2013)

When considering the overall state of hydrogen policy in the United States today it is easiest to consider it in terms of the transitional roadmap that was laid out by the federal Hydrogen Posture Plan. Very clearly, states must be considered individually and they are not easily grouped together with the federal government. The federal government is definitely still in the first stage, research and development, while many of the states

57 have developed no hydrogen plan at all. Some states, especially the state of California, have surpassed the federal government (albeit with federal support and funding) and moved into the beginnings of the second phase, initial market penetration (Ogden, 2003;

Brown, 2012; Yand and Ogden, 2013).

Of greatest concern in the United State federal policy is the growing dependency on coal to meet future energy needs, including that of hydrogen. While coal presents many advantages to the United States energy economy, primarily that it is inexpensive and widely abundant within U.S. borders, it also represents a great threat to the overall sustainability and desired lower greenhouse gas emissions that could be garnered from a transition to a hydrogen energy economy. The Bush administration attempted to allay those fears through the development of clean coal technologies, but this technology is unproven on a large scale (Hodson and Marvin, 2006; Lokey, 2007a; Blanchette, 2008;

Clark, 2008)

Despite the various potential pitfalls associated with pursuing a coal based hydrogen energy economy, it appear that this was the Bush administration plan for producing the majority of the hydrogen to be used to fuel the developing hydrogen economy and that coal will be the fuel of choice for some time to come ( (Blanchette,

2008; Han, 2012; McDowall, 2012; Yand and Ogden, 2013) This is evident in the allocation of funding in federal government research as well as federal government projections about the sourcing of hydrogen in the future. While the discussion around hydrogen always includes passages about how clean it will be and how there are no emissions from fuel cells other than water vapor, the federal government is actively

58 pursuing a fossil fuel based hydrogen economy for reasons of energy security and because it is less expensive.

While the federal government has been placing most of its funding into demonstration projects and basic research, some of the state level governments have leapfrogged directly into the implementation phase of the hydrogen energy economy

(Blanchette, 2008; Yang and Ogden, 2013) At the forefront of this movement is

California, which over the last several years has been slowly adding hydrogen fueling stations and hydrogen powered vehicles to its highways. This has been accomplished primarily through government-corporate cooperative efforts and cost sharing. It has allowed the state to develop a rudimentary hydrogen fueling infrastructure and at the same time is beginning to create a market for the vehicles by acting in the role of first customer.

Many other states appear to be following California’s lead by developing their own plans for the implementation of hydrogen fueling corridors, and often these efforts are cooperative between a handful of adjoining states. These plans all follow the same basic methodology. Begin with a few demonstration projects in metropolitan areas that are unlinked, each with a small number of hydrogen vehicles services by a single station

(Fayaz, 2012; Yang and Ogden, 2013; Park, 2013; Dayhim, 2014; Pepitas, 2014) As the number of these stations grows into a cluster they are slowly opened to the public so that they may take advantage of the existing fueling infrastructure. As the demand for hydrogen fuel grows, stations are constructed along transportation corridors, linking the clusters. Now that hydrogen fuel is widely available, the customer base is able to expand to include a greater and greater number of hydrogen vehicles owned and operated by the

59 public rather than by the government or corporate entities. This process of developing a hydrogen highway takes many years and can cost hundreds of millions of dollars to complete to a point where market forces can fully take over and continue to grow the hydrogen fueling infrastructure without support from the government.

One of the primary concerns about the fueling infrastructure being constructed at the state level is that the technologies, codes, and standards used will not be uniform across the country. This could lead to potential interconnection issues when the various state level hydrogen highways grow and are in a position to be interconnected, or if a traveler is able to drive from one to another. This is one reason why the federal government should be taking a more active role in coordinating the development of a nationwide hydrogen fueling infrastructure, even if it only provides basic guidelines to those states that are ready to move forward with their own fueling infrastructure right now. By developing a national set of codes and standards a great deal of aggravation and potential stranded assets could be avoided down the road (McDowall, 2012)

Overall, it seems as though the states have progressed significantly further along with the development of a hydrogen energy economy that the federal government, which has primarily focused on research and development as of this point in time. But the research and development is much needed, perhaps more so than the construction of actual infrastructure (Blanchette, 2008). But as long as the majority of the attention and money is being given towards the development of clean coal, hydrogen from coal, and carbon sequestration technologies rather than to technology designed to produce hydrogen from renewable and environmentally friendly energy sources then there is a significant chance that the hydrogen energy economy that develops will be nothing more

than an extension of our current fossil fuel based energy economy and all of the problems

that accompany it (Clarke, 2008).

2.5.2 Federal Level Incentives

This section will describe all of the laws, incentives and programs that the federal

government currently has enacted that affect the development of hydrogen economy. For

the most part these laws, incentives, and programs are relatively small compared to the

programs that many of the states have enacted. Instead of planning hydrogen fueling

infrastructure networks or the massive procurement of fuel cell vehicles, current federal

policy for hydrogen is mostly hydrogen being grouped together with other alternative

fuels or renewable energy programs. For the most part these laws and incentives involve

funding for research or the availability of a tax credit. The government’s broader view of

how the hydrogen economy should develop will be described in the following section and

will cover those areas not covered by laws that have already been enacted.

 Air pollution Control Program- This program is a federal assistance programs that helps

local and state governments develop plans to improve air quality by focusing on

alternative fuels, vehicle maintenance, and transportation choices to reduce vehicle miles

traveled. In addition to assisting in the planning of these projects, the federal government

is also able to provide as much as 60% of the costs of implementation ( (AFDC, 2014)

 Congestion Mitigation and Air Quality (CMAQ) Improvement Program- Specifically

aimed at controlling emissions and congestions in those areas of the country that are in

non-attainment of federal air quality standards. While hydrogen is not directly addressed

by the statute, hydrogen based programs can be funded as they become more cost

effective. The primary significance of the law is the level of funding, over $8 billion.

Unfortunately, only about 5% of these funds have been used for AFV projects ( (FHWA,

2014)

 Renewable Energy Systems and Energy Efficiency Improvements Grant- This program

is designed to assist rural agricultural sectors and rural businesses transition to cleaner

and greener alternative energy technologies by installing an alternative energy

technology. The applicants must pay for at least 75% of the total costs of the project, but

the remainder may be eligible for up to $750,000. Qualifying systems include: biofuels,

hydrogen, and energy efficiency, as well as solar, geothermal, and wind ( (AFDC, 2014)

 Clean Fuels Grant Program- Aimed at the introduction of low emission busses into

fleets in order to replace conventional vehicles, of particular interest to this program are

bio diesel buses and other advanced propulsion technologies such as electric and

hydrogen fueled vehicles. The program is also interested in the development of the

accompanying infrastructure, such as fueling stations. Nearly $29 million was made

available during the 2008 fiscal year under this program. This money was allocated

across ten different metropolitan transit authorities, although it is unclear as to how those

funds were utilized once distributed ( (AFDC, 2014)

 State Energy Program (SEP) Funding- Provides funding and grants to state energy

agencies to explore and implement emerging renewable energy technologies. The grants

have typically been for policy research, small demonstration projects, and outreach

programs. This program distributes $50 million dollars each year, but only a small

portion goes towards hydrogen ( (EERE SEP, 2014)

 Alternative Fuel Excise Tax Credit- This incentive provides a $0.50 per gallon tax credit

to retailers of a variety of alternative fuels, including liquefied hydrogen ( (AFDC, 2014)

 Fuel Cell Motor Vehicle Tax Credit- A tax credit for anyone who purchases a fuel cell

powered light duty vehicle. Until 2009 the tax credit was worth $8,000, after which it was

dropped to be $4,000. This is one of the few laws or incentives that directly and solely

addresses the purchase and acquisition of fuel cell vehicles ( (AFDC, 2014)

 Alternative Fuel Infrastructure Tax Credit- Encourages consumers and commercial

fueling station owners to install alternative fuel infrastructure. It was scaled so that up to

50% of the project’s cost could be recovered through a tax credit, not exceeding $50,000

for commercial owners and $2,000 for individuals. However, an exception was made for

hydrogen so that the maximum level of tax credit is capped at $200,000 (AFDC, 2014).

 National Fuel Cell Bus Technology Development Program- To introduce cost

competitive, commercial ready fuel cell buses into the market. In 2009 $13.5 million was

awarded in grants, up to 50% of project costs, to of lower costs, increase durability, and

double efficiency ( (Federal Transportation Administration, 2014)

2.5.3 State Level Policy

California was the first of the states to develop a plan for the development a

hydrogen fueled transportation network. In April of 2004, Gov. Arnold Schwarzenegger

announced that California would be developing the Hydrogen Highway. Envisioned was

a series of hydrogen fueling stations along California’s major highways so that most of

the state’s citizens would have access to hydrogen and to catalyze the development of a

hydrogen transportation system ( (CA Hydrogen Highways, 2014) California wanted “to

achieve the following by 2010: 1) Build a network of hydrogen fueling stations; 2) ensure

that hydrogen vehicles are commercially available for purchase; 3) incorporate hydrogen

63 vehicles into the state fleet; 4) develop safety standards for hydrogen fueling stations and vehicles; and 5) establish incentives to encourage the use of hydrogen vehicles and encourage the development of renewable sources of energy for hydrogen production.”

(AFCD, 2014). Reasons cited included a reduction in dependence on foreign oil, improving air quality, reducing greenhouse gas emissions, and helping to grow

California’s economy. This announcement was backed up through the allocation of funding to develop and construct hydrogen fueling stations in strategic areas and towards the procurement of fuel cell vehicles, leading to the overall construction of 21 hydrogen fueling stations located around the state with 18 more funded and designed. Currently the state devotes nearly $20 million each year to this effort.

As the second state, Hawaii, finds itself in a unique position as an island state.

This tends to make fuel, especially for transportation, high cost compared to other states.

As a result Hawaii has enacted the Hawaii Renewable Hydrogen Program, which envisions a significant transition to a hydrogen energy economy by 2020. This program indicates an emphasis on geothermally generated hydrogen (FuelCells.org, N.D.) and was to promote outreach and education, fund research and development, and provide funding for the direct purchase of fuel cell vehicles (AFCD, N.D.) In 2006, $10 million was set aside as an investment capital special fund for the aid of research and construction of hydrogen infrastructure which has led to several demonstration projects, including a fleet of buses at the Hawaii Volcanoes National Park. Finally, Hawaii is also in the planning stages to install its first hydrogen fueling station, located on the Big Island, which may well be the first in a potential Hawaii Hydrogen Highway, however these efforts have stalled in recent years and no station has been built (Hi-Hydrogen.com, N.D.)

Minnesota is a state that has taken a less direct approach with the development of a hydrogen energy economy. They are active participants in a coalition of Midwestern states that are considering the construction of a hydrogen fueling network that would link several states. In addition to this they have their “Minnesota Renewable Hydrogen

Initiative” which seeks to explore the potential for hydrogen to play a role in meeting the state’s energy demands. However, Minnesota does not yet have a concrete plan to physically develop a hydrogen infrastructure. Currently the state of Minnesota has budgeted $10 million for hydrogen related activities within the state. That money includes developing a Minnesota Hydrogen Roadmap, along with funding for hydrogen demonstration projects across the state. The roadmap, which is based primarily on research goals, should be completed by 2015.

New York can be compared to California in their approach to developing a hydrogen energy economy. The NY Hydrogen Roadmap, which was finalized in 2005, identifies a strategy similar to California’s that begins by building clusters of hydrogen fueling stations which would eventually be linked by the state’s highways. This work was to occur in three phases. During first phase, New York focused on funding research and development, providing high level demonstration projects, establishing codes and standards, and promoting public outreach programs aimed at the K-12 levels of education. Demonstration projects included several busses, dozens of taxicabs, and electrolytic and NG reforming hydrogen fueling stations (NYSERDA, N.D.)

After this period of time, the actual construction of a hydrogen fueling infrastructure was to have begun with what they term the three C’s: clusters, cities, and corridors. Specifically they wanted to expand the number of hydrogen busses and taxis

65 and to complete a fueling corridor between Buffalo and New York City. Additionally they hoped to have additional improvements to their stationary hydrogen projects including:

250MW of generation using hydrogen generated from renewable resources, a 500MW coal gasification plant that would feed a hydrogen pipeline, and a number of smaller scale hydrogen generation plants from small scale natural gas reformation (

(http://www.nyserda.org) In the third phase, it was hoped that hydrogen would have been successfully commercialized and more widely used by the public allowing commercial investment in hydrogen infrastructure and technology will be made without additional government investment or incentive. It was hoped that consumers would be able to purchase hydrogen passenger vehicles and that 2% of New York’s transportation fuel would have come from hydrogen at this time (NYSERDA, N.D.). These phases never came to be, however, as momentum was lost in 2008.

The state of Texas has developed the Texas Hydrogen Roadmap Project, which attempts to identify those areas in which the development of a hydrogen energy economy would benefit the state. This project is currently running and has not yet come up with any concrete plans for enacting a hydrogen fueling network, although they express great expectations of Texas’s potential for hydrogen, stating it is currently the biggest producer of hydrogen in the nation and that they have vast untapped renewable wind resources.

But before this project came the Texas Fuel Cell Initiative (TFCI, N.D.), which grew from the desire to enhance energy security and the economy of the agricultural western side of the state. The TFCI is attempting to cultivate a hydrogen economy by boosting nascent market forces within the state, consolidating existing programs and incentives under a single framework, and working heavily with businesses and research institutions.

A primary strategy for TFCI is bulk procurement of fuel cells and through the provision of training and demonstration projects on fuel cells as stationary power sources. TFCI is a stationary power production system rather than a distributed fueling network, and thus will require fewer infrastructure additions. Furthermore, a great deal of hydrogen infrastructure already exists along the Gulf Coast of Texas for industrial purposes and the state views natural gas as the source of hydrogen for the foreseeable future.

2.6 Language and Policy Conclusions

This chapter lays the theoretical background for this dissertation by describing the ways in which language can be used to control the imparted message through the creation of a context that provides support for a specific position. Facts and information can be presented in different ways to carry very different messages and this specifically contextualized information is passed along by the news media due to a variety of forces, but especially sourcing. By influencing the public discourse in this fashion, the powerful can gain public support for their policy positions.

In addition to identifying the theoretical framework for the influence of power over language of public policy discourse, this chapter also discusses a means for how evidence of this influence may be measured. The core issues at contention in a policy disagreement become the indicators by which the presences of constructed narratives within the article are judged. Each topic can be assigned an optimistic and critical indicator, which signifies the presence of a particular constructed narrative within that language. This allows these subjects to be quantified and compared statistically so that it can be determined if message of the political or academic sources of any policy position

67 appears to have larger influence over the public discussion of the topic by skewing the distribution of the indicators found in the news media.

A final conclusion of this chapter is that the identification of optimistic and critical indicators is impossible without a deep understanding of the complexities of the topic. An effort must be made to understand the basic science and technical detail behind a technology in order to be able to provide a baseline against which an optimistic or critical position can be identified and defined. Chapter 3 is devoted to a deeper understanding of the hydrogen energy economy. This information is necessary in Chapter

4 and Chapter 5 to define specific indicators for the hydrogen energy economy and optimistic and critical positions for each, which are then used as the unit of analysis for this case study.

Chapter 3

PROPERTIES OF THE HYDROGEN ECONOMY

3.1 Definition of the Hydrogen Energy Economy

The possibility of a hydrogen economy has been frequently passed around in political and popular media circles during the past 15 years, but rarely is the term itself examined or explained. What exactly is the hydrogen economy and why is an understanding of this term so important? “Hydrogen economy” refers to the set of technologies and policies that would be required for the broad utilization of hydrogen as an energy carrier across a variety of different possible sectors (Romm, 2004; Hodson and

Marvin, 2006; Clark, 2008; Ren,, 2013; Hwang, 2013) It includes the entire chain of supply and use of hydrogen and the acquisition of all the equipment needed to generate, move, store, and use the hydrogen.

This chapter will provide grounding in the current technologies and processes being used to generate hydrogen, transport it to its point of use, and convert it into electricity. While this chapter will focus on the technological aspects of the hydrogen energy economy, Chapter 4 will use this information to construct a methodology to approach the issue of identifying constructed narratives in speech and text. Once the baseline for the potential of hydrogen has been established it will be possible to develop criteria that define indicators for language that introduces constructed narratives into the discussion of the technology.

Hydrogen is the most common element in the universe by a significant margin. It makes up the majority of the matter that exists in the universe and is wildly abundant on

Earth (Romm, 2004, Ren, 2013). Hydrogen is also the simplest element that can exist, consisting of a proton, a neutron, and an electron, or, more commonly, just a proton and an electron. When it is in its natural and pure form and is under normal earth-like conditions hydrogen takes the form of a highly diffuse, lightweight gas consisting of two hydrogen atoms bonded together to form a single molecule of gaseous hydrogen, or H2

(Romm, 2004; Dunn, 2002; Ogden, 1999). Hydrogen gas also has the highest energy content by weight of any other fuel, but its low density gives it low energy content by volume at atmospheric pressures (California Energy Commission, 2001; Blanchette,

2008).

Using hydrogen for energy is not a novel concept. In fact, life as we know it is almost completely dependent on the utilization of hydrogen for energy. Our sun, like all stars, acts as a gigantic fusion reactor, a giant burning ball of hydrogen gas that is being subjected to tremendous heat and pressure and causing the nuclei of two hydrogen atoms to fuse together into a single helium atom, the next lightest element, and releasing large amounts of energy. This is a process known as nuclear fusion and it is what allows the sun, and all stars, to give light, warmth and energy to the orbiting planets (Romm, 2004).

Nuclear fusion can also be found in other locations, including here on the Earth. The hydrogen bomb utilizes the energy from a conventional nuclear blast to spur the fusion of a relatively small amount of hydrogen gas, which quickly releases an incredible amount of energy in an out-of-control and uncontained cascade of nuclear fusion. The ability to

70 fuse hydrogen allows hydrogen bombs to be many times more powerful than the conventional atomic weapons that were used to destroy Hiroshima and Nagasaki.

But fusion is also being pursued on Earth for more peaceful purposes. The effort to create a controlled fusion reaction to provide cheap and abundant energy to the entire world has been the lifelong quest of a whole generation of nuclear physicists and continues to be the Holy Grail in the nuclear physics world. Modern attempts to harness the power of hydrogen fusion for cheap, abundant energy draw closer to success but current technologies have not allowed for a controlled process of fusion that will release more energy than it takes to initiate. Currently nuclear fusion is, at best, a zero-sum game

(Sharp, 2007).

3.2 The Hydrogen Fuel Cell

But hydrogen fusion is not the only means of harnessing hydrogen for energy in the near future. For the most part, the technology being referred to in the discussions on the hydrogen energy economy is not nuclear fusion, but rather the utilization of a fuel cell to convert hydrogen directly into electrical power. This is also not a new technology, but has been used for decades already by NASA in order to supply electricity and clean, potable water to the astronauts in the space shuttles (Romm, 2004).

The workings of a fuel cell are fairly simple. There are no moving parts within the cell itself and only three main sections. These are an anode, a cathode, and a membrane separating the two, all suspended in an electrolyte. Molecular hydrogen enters the anode of the fuel cell and within the anode is a catalyst. The catalyst is traditionally a platinum based material (Romm, 2004; Ren, 2013; Hwang; 2013). The catalyst strips the electrons from the hydrogen molecule and reduces the gas to hydrogen ions (protons) and their

71 unattached electrons. The protons are able to pass into the cathode, but the electrons are prevented from transiting the membrane (Kotz, 1999).

An electrical potential now exists between the anode and the cathode and the only pathway for the electrons to get to the cathode is through an electrical circuit connecting the two. This electrical circuit is whatever electronic device you have connected to the fuel cell. The electrons pass through the device and enter the cathode. Electricity is just electrons passing through a medium, in the case the circuitry of the device you are powering, so there is now an electrical current. Once within the cathode, they recombine with the protons and with oxygen that is naturally present in the air to form water (Kotz,

1999).

Figure 3- Basic Fuel Cell Operation

Now the cyclic nature of the fuel cell system can be seen. It is possible to have an energy cycle that uses a fuel that is not only harmless to humans but is beneficial: water.

This is known as the solar hydrogen cycle. Energy from the sun is used to split water, separating and storing the hydrogen for the fuel cycle and allowing the oxygen to escape or be used for other purposes. That energy used in the process is stored as chemical potential energy in the separated gasses and is released when the oxygen and the hydrogen recombine to form water. The cycle’s beginning and end points are pure water and the in-between states are hydrogen, a non-toxic gas and oxygen, a gas we need to survive (Ogden, 1999; NAS, 2004; Hwang, 2013).

3.3 The Generation of Hydrogen as an Energy Carrier

It has already been stated that hydrogen is the most common element in the universe and that hydrogen is widely available domestically. But what has not yet been discussed is that hydrogen is almost never found on the Earth in its gaseous, molecular form, H2 (Ogden, 1999; Romm, 2004; NAS, 2004; Ren, 2013). Instead the hydrogen is almost always locked up as a part of other molecules, both organic and inorganic. The potential sources for hydrogen are staggering in their range and availability. All biomass, fossil fuels, and water are sources of significant amounts of hydrogen. In order to generate pure hydrogen for use in a fuel cell, the hydrogen atoms must be split away from the other elements in the molecules of the feedstock (Ogden, 1999; NAS 2004; Ren,

2013).

It is this property that causes hydrogen to act more like an energy carrier rather than an energy source. The primary distinction to be made between these two terms largely depends on whether or not it takes a significant amount of energy to extract and

73 utilize the fuel compared to the amount of energy that will be provided when the fuel is utilized ( (Balta-Ozkan and Baldwin, 2013) For hydrogen it typically takes more energy to extract the hydrogen from its feedstock than the hydrogen will produce when run through a fuel cell (Zuttel, 2008; Barbir, 2009; Marino, 2013; Ren, 2013). This makes hydrogen an energy carrier rather than an energy source because it is essentially carrying the energy that was available in some other form and allowing it to be used later in the form of hydrogen being run through a fuel cell. Other examples of energy carriers include electrochemical batteries, pumped hydro energy storage systems, and compressed air energy storage systems (Waegel, 2006; Bakker, 2012).

There are several important points to be made about the nature of energy carriers and their uses. Firstly, because it is essentially a means of transferring one form of energy into another, hydrogen adopts the characteristics of the original source (NAS, 2004;

Waegel, 2006; Clark, 2008; Barbir, 2009; Ren, 2013). Feedstocks such as coal or natural gas, which need to be extracted from the earth in order to be used traditionally, must still be extracted from the earth in order to remove the hydrogen from the other elements.

Thus all of the negative environmental aspects and economic aspects that are associated with the mining of coal or the extraction of natural gas must still be contended with, even if these feedstocks are being used to generate hydrogen (Romm, 2004; Waegel, 2006;

Byrne, 2005; Ren, 2013). Additionally, and perhaps more insidiously, the emissions that would be generated through the traditional combustion of these fuels still occurs when the hydrogen is extracted from them. On the other hand, positive attributes of energy sources used to generate hydrogen are carried through as well. When solar energy is used to generate hydrogen through the electrochemical splitting of water, the hydrogen carries

74 the attributes associated with solar, such as no emissions, equitable distribution of the resource, and domestic availability (Romm, 2004; Waegel, 2006; Barbir, 2009; Periera and Coelho, 2013; Huss, 2013; Sanchez and Gonzalez, 2013; Zhang and Wan, 2014).

As an energy carrier, hydrogen is useful for two primary reasons. The first of these reasons is that hydrogen is a very versatile fuel. This means that it can be used for a wide variety of types and scales of application, which the original energy source might not have been capable of accomplishing (Barbir, 2009; Balta-Ozkan and Baldwin, 2013).

A good example is in the realm of transportation. While coal has been utilized to provide locomotion through steam power, it has never been successfully commercialized as a fuel for personal transportation and its use in mass transit has been all but completely phased out. Hydrogen, however, is being developed as the transportation fuel of the future

(Fayaz, 2012; Yang and Ogden, 2013).

Since the technology for transforming coal into hydrogen gas is already well established it can be easily seen how coal, a relatively inflexible and un-versatile fuel could be turned into hydrogen and then utilized in the transportation sector (Ogden, 1999;

DOE, 2002; Yang and Ogden, 2013). In addition to transportation, hydrogen can be used for a wide range of applications including powering personal electronics, powering offices, and heating homes (Romm, 2004; Fayaz, 2012). Whereas a laptop could never have been powered by petroleum or a car could never be driven by coal, through the intermediary step of hydrogen, many energy sources that could only be used in limited situations can suddenly become extremely versatile.

The second reason that hydrogen is useful as an energy carrier is for the purpose of energy storage (Hammerschlag, 2005; Mazloomi and Gomes, 2012; Gao, 2014;

Rangel and Sansores, 2014; Petitpas, 2014). Hydrogen is capable of storing the energy from one energy source almost indefinitely in the form of a gas, liquid, or having been absorbed by some other material (Ogden, 1999; Gao, 2014; Rangel and Sansores, 2014;

Petitpas, 2014). The specifics will be discussed in later sections of this chapter, but hydrogen is capable of storing large quantities of energy for extended periods of time and the capacity for that storage is relatively inexpensive as compared to other storage media, such as electrochemical batteries, and is not dependent on massive infrastructure or geological formations, such as pumped hydro energy storage or compressed air energy storage (Rand, 2005; Agbossou, 2001; Bakker, 2012).

The ability of hydrogen to store energy is particularly useful in dealing with renewable energy sources such as solar, wind, and tidal power (Agbossou, 2001; Huss,

2013; Ngoh and Njomo, 2012; Sanchez and Gonzalez, 2013; Zhang and Wan, 2014). All of these energy sources are intermittent in nature. This means that they are only available during certain periods, that the availability is uncontrollable, and the unavailability may even be unpredictable. Intermittent energy sources are not always available when the demand for energy comes and this gives them a significant problem in trying to meet the energy needs of modern civilization, which has grown accustomed to having the exact amount of energy needed available whenever it is desired (Anderson, 2009; Sanchez and

Gonzalez, 2013; Zhang and Wan, 2014).

The ability to produce power when it is needed in sufficient quantities is accomplished through the development of the power grid and power plants that run on coal, hydroelectric, natural gas, or nuclear power, which can be turned on or off relatively quickly to meet the demand that is being placed on the grid. The most environmentally

76 friendly sources of energy, which also tend to be the most intermittent sources, cannot be controlled in this way (Anderson, 2004; Sanchez and Gonzalez, 2013; Zhang and Wan,

2014). The grid thus becomes unstable and likely to fail as the percentage of its power sources made up from intermittent energy sources increases, especially when intermittent sources account for more than 20% of the power provided to the grid (Anderson, 2009;

Sanchez and Gonzalez, 2013; Zhang and Wan, 2014).

In smaller off grid applications the problem of intermittency has traditionally been solved through the application of deep-cycle lead acid batteries, which can economically handle the day to day intermittency that is associated with a solar or wind powered home

(Schaber, 2004; Rand, 2005; Huss, 2013; Marino, 2013). But when the scale of the energy application reaches the size of the national energy grid, then an alternative form of energy storage is required. Through the utilization of hydrogen energy storage, diurnal and seasonal intermittency on both the large and small scales could be circumvented and a steady stream of power from these sources could be provided on demand (NAS, 2004;

Rand, 2005; Andrews and Shabani, 2012).

Thus, as an energy carrier hydrogen is capable of performing several tasks that cannot be easily accomplished with other fuels or technologies. Hydrogen proves to be an excellent storage medium for energy as it is stable, lightweight, scalable, and can be accessed quickly and easily through the use of fuel cells (Rand, 2005; Suppes, 2005;

Huss, 2013; Zhang and Wan, 2014). Hydrogen is also useful as an energy carrier due to the versatility that the technology can add to nearly any energy source (Balta-Ozkan and

Baldwin, 2013). Since hydrogen can be extracted from so many different feedstocks through nearly any type of energy input and because it can be used in so many different

77 and flexible fashions, hydrogen as an energy carrier is capable of allowing energy sources that could not normally be used for certain types of activities to be used in nearly any energy service (Barbir, 2009).

But although fuel cells emit only water, one must be careful to remember that hydrogen carries with it the attributes of its source (Waegel, 2006; Hammerschlag, 2005;

Ren, 2013). Hydrogen that is formed through the reformation of coal must still contend with the emissions from the breaking down of the coal. Hydrogen formed through the reformation of natural gas still produces impacts from the extraction of the gas (NAS,

2004; Hammerschlag, 2005; Waegel, 2006; McDowall, 2012). As an energy carrier, all of the impacts energy used to generate the hydrogen are still attached, even if they are not observed at the point of use of the hydrogen.

The hydrogen economy and its associated technologies are highly complex and technical in nature which creates an opportunity to control the public’s understanding of the issues surrounding hydrogen. This is accomplished through the use of language identifiable by optimistic or critical indicators. While these indicators do not indicate outright falsehoods, they show how language can be used to create misperceptions of the technology that encourage support or opposition while ignoring facts that would suggest opposing or mixed results from the adoption of hydrogen. This section illustrates the many paths and options that are available for the pursuit of hydrogen as an energy carrier and provides the factual basis by which both the optimistic and critical indicators of interest can be identified.

3.3.1 Hydrogen from Fossil Fuel Feedstocks

Most of the hydrogen produced today comes from fossil fuels. Fossil fuels originate from plant matter that has been underground for long periods of time under heat and pressure. Depending on the conditions, the process results in one of several different hydrocarbon molecules and a variety of impurities. These fossil fuels consist of a chain of carbon atoms linked together with two hydrogen atoms bonded to each carbon atom, except for the carbon atoms at the end of the chain which have three hydrogen atoms each bonded to them. The fossil fuels are named based on the number of carbon atoms in the chain. Methane (natural gas) has just a single carbon atom and four hydrogen atoms, while octane has eight carbon atoms and eighteen hydrogen atoms.

The basic process for extracting the hydrogen from the fossil fuel molecules involves the application of intense heat and pressure. This causes the molecules to split apart into its component elements. The hydrogen can be recaptured as molecular hydrogen gas (H2) and the carbon is bonded to atmospheric oxygen forming carbon monoxide and carbon dioxide (Ogden, 1999; NAS, 2004; Rand, 2005; Han, 2012; Ren,

2013) Because the different fossil fuels have different hydrogen to carbon ratios, each one produces a different amount of carbon dioxide when producing the same amount of hydrogen. The carbon dioxide produced in these processes is important to consider because hydrogen is promoted as a GHG emissions free energy carrier and yet there are circumstances when using hydrogen from fossil fuels can produce carbon dioxide than simply burning the fossil fuel conventionally (Ren, 2012; Lokey, 2007, Lokey, 2007a).

When talking about extracting hydrogen from fossil fuels there are two primary feedstocks to be examined: natural gas and coal. Both of these fuels offer similar benefits,

79 especially when compared to petroleum, the fuel they would be replacing. Both are available domestically in significant quantities (NAS, 2004) Coal, especially, is available in vast amounts on the North American continent (Goodell, 2006) While natural gas is less abundant, it has a higher domestic availability than petroleum, especially with the recent development of shale gas fields and the countries that we trade natural gas with are considered to be less hostile to U.S. interests than the Middle East (Petitpas, 2014)

In part because of their availability, natural gas and coal are also significantly more economical than oil. In addition to costing less than oil per unit of energy, domestic availability means that fewer dollars are being sent abroad and are instead going to support local industry ( (NAS, 2004; Park, 2013) While no fossil fuel can be used on a large scale sustainably, we are living in the era of peak oil and it is possible that we will run out of economically feasible petroleum in the next few decades ( (Rand, 2005)

Natural gas, however, is estimated to have over one hundred years of supply remaining at current rates of consumption and coal reserves are estimated to be even greater (

(Hohmeyer, 1992)

While coal and natural gas offer many benefits over the usage of petroleum, they are not without their own set of environmental, social, and economic impacts. The two primary issues to be examined for each of these are: 1) the emission of carbon dioxide; and 2) the impact on supply and demand forces that greater reliance on these fuels will create. This section will examine the process of creating hydrogen gas from both natural gas and coal. An in-depth look at their benefits, costs, and impacts will be made as well as an assessment of current and potential future problems for implementing large scale production of hydrogen from these sources.

Currently the steam reformation of natural gas is the most common production technique for creating molecular hydrogen, accounting for over 95% of the hydrogen produced in the U.S. today (Romm, 2004; Barbir, 2009; Ren, 2013) This is the method that has classically been used for the production of hydrogen in the U.S. chemical industry where it is used as a material feedstock in the creation of chemicals such as ammonia. As a result there is already a large infrastructure developed for the production and distribution of hydrogen from steam reformation plants (Ogden, 1999; NAS, 2004;

Ren, 2013). This experience makes steam reformation an established technology with low production costs, almost no technological barriers, and an economy of scale that could easily absorb the initial demands of a budding hydrogen energy economy (Ogden,

1999; Park, 2013; Yang and Ogden, 2013).

Natural gas is made up almost entirely of CH4, methane. The hydrogen is split from the carbon in several stages. In the first stage heated natural gas is introduced to hot steam, creating the following reaction:

(CH4)gas + (H20)gas  3(H2)gas + (CO)gas

The steam and the methane react to form hydrogen and carbon monoxide. The hydrogen is shunted off and the carbon monoxide is exposed to more steam with the reaction:

(CO)gas + (H20)gas  (CO2)gas + (H2)gas

In the final stage of the process all of the hydrogen gas is separated from the carbon dioxide and any remaining carbon monoxide. It is then purified, compressed and stored for eventual distribution. The waste gasses of carbon dioxide, carbon monoxide, water vapor, and some methane are then vented into the atmosphere (Ogden, 1999, Ren, 2013)

This process is already a mature technology that has gone through decades of refinement. While there is some room for improvement in terms of cost and carbon dioxide emissions from these plants, the reduction in both factors is proportionally less than might be expected in other hydrogen production technologies (NAS, 2004; Ogden,

1999; Hajjaji, 2012) Currently the steam reformation of natural gas can produce a kilogram of hydrogen for $3.51 at a natural gas price of $6.50 per million Btu. The price of the hydrogen could be expected to fluctuate by 12% should the price of natural gas rise or fall by $2.00. This price is expected to be able to drop to as little as $2.33 over time.

The process also generates 12.1kg of carbon dioxide for every kilogram of hydrogen produced and this is expected to drop to 10.3kg ( (NAS, 2004; Ren, 2013;

Hajjaji, 2012) For comparison, a gallon of gasoline, which is equivalent in energy content to a kilogram of hydrogen, releases approximately 19kg of carbon dioxide when burned.

While producing hydrogen from natural gas does release some carbon dioxide, and thus cannot be considered emission free, it does produce less than an equivalent amount of gasoline ( (NAS, 2004; Clark, 2008; Ren, 2013)

Despite its benefits, the reformation of natural gas is seen to be more of a transitional production technique for hydrogen gas, rather than a permanent method of procuring the gas. While the federal government is currently investigating large-scale, centralized steam reformers, this is not necessarily the optimal path for the development.

Instead, as a transition technology, it would be more beneficial if steam reformation was used to supply hydrogen in a distributed fashion rather than through centralized production (NAS, 2004; Ren, 2013). This is because the technology will be utilized at a time when an extensive hydrogen infrastructure is not yet in place. By distributing the

82 natural gas reformers the budding hydrogen economy can take advantage of the existing natural gas distribution infrastructure and generate the hydrogen on site. Additionally, due to the low long term viability of hydrogen generation from natural gas, having smaller distributed natural gas reforming stations will reduce the potential for stranded investments as a the transition to a longer term source for hydrogen occurs.

The downside of a distributed natural gas reformation system is that it drastically reduces the potential for carbon sequestration. In a centralized natural gas steam reformation plant, it might be possible to sequester the carbon dioxide produced and store it in subterranean geological structures, thus reducing the amount of carbon dioxide released into the atmosphere during the reformation process by as much as four fifths

(Romm, 2004 ). But in a distributed system of natural gas steam reformers, such sequestration would be economically and technologically infeasible (NAS, 2004; Ren,

2013; Yang and Ogden, 2013; Chi, 2014)

Hydrogen production from natural gas presents exciting opportunities for the development of the hydrogen economy. Because it is a mature technology there are few technological barriers to implementing the systems and the costs and energy expenditures has already been optimized to a certain degree. These factors combine to provide hydrogen inexpensively and reliably. Additionally, due to the low carbon content of natural gas, the carbon dioxide emissions associated with the production of hydrogen through stream reformation of natural gas are significantly lower than emissions for a similar amount of energy from gasoline and other fossil fuels (Han, 2012; Yang and

Ogden, 2013)

However, natural gas faces many of the same problems that currently affect the gasoline energy economy. There is an uncertain amount of natural gas left in reserves, and even conservative estimates say that there is only 150-200 years left at the current rates of consumption. By utilizing natural gas to fill energy needs beyond what it currently does, especially if it is used in an attempt to displace petroleum from the transport sector, then the reserves of natural gas would last for a far shorter time, which would raise prices and create a similar problem in securing our energy needs for the future as we are facing now (Clark, 2008; Marino, 2013)

As a result, it seems that natural gas could serve as a suitable transition source of hydrogen as the hydrogen economy develops. It will do so by taking advantage of its status as an established technology with low costs and few technological issues. By distributing, rather than centralizing, the natural gas reformers, the growing hydrogen economy can take advantage of the existing natural gas distribution infrastructure to transport the hydrogen feedstock to its distribution centers where it can then be reformed.

This drastically reduces the upfront costs of developing the early hydrogen economy and avoids many of the chicken and egg paradoxes that might otherwise slow the adoption of hydrogen fuel cell technology (NAS, 2004; Ogden, 1999; Ren, 2013; Yang and Ogden,

2014)

As mentioned in earlier chapters, the prospect of extracting hydrogen from coal has been receiving a significant amount of support and enthusiasm from the federal and many state level governments (McDowall, 2012; Lokey, 2007a). Hydrogen from coal has a number of advantages which place it in a very favorable position compared to many other generation technologies. But the very nature of coal presents many issues regarding

84 hydrogen extraction. This has become the core of a growing controversy on how exactly the future hydrogen economy should develop (Hammerschlag, 2005; Waegel, 2006;

Lokey, 2007a; Marino, 2012; Reichmuth, 2013).

The process of removing the hydrogen from coal is actually quite similar to that of removing the hydrogen from natural gas, only with an additional initial step added to the process. As coal is a solid in its natural form, before it can undergo steam reformation it must first be gasified. This is accomplished through a process of partial oxidation when the coal is heated and placed under pressure in an oxygen rich environment (Ren, 2013).

Under these conditions the coal is converted into a syngas, which as a combination of mostly hydrogen and carbon monoxide with lower levels of steam and carbon dioxide.

This syngas is then subjected to steam reformation in a process similar to that of steam reformation of natural gas (Chi, 2014). This removes much of the carbon monoxide, converting it into carbon dioxide and hydrogen. The resultant gasses are then separated into carbon dioxide and hydrogen and purified (Ogden, 1999; NAS, 2004; Han, 2012;

Ren, 2013).

There are several significant advantages that hydrogen from coal has over other hydrogen generation technologies. The U.S. has large unused reserves of coal and has often been referred to as the “Saudi Arabia of coal” (Goodell, 2006). Having such a significant domestic supply imparts two benefits. First, the U.S. will not have to rely on imports of coal in the near future, even if its use is expanded to create sufficient hydrogen to supply a developed hydrogen economy. This gives hydrogen a high level of energy security will bolster the economy by retaining dollars within the national economy and creating jobs in the U.S. marketplace (Petitpas, 2014). Secondly, since estimated coal

85 reserves are substantially higher than estimated reserves of other fossil fuels, it could conceivably supply us with a relatively stable energy source for the next several generations.

The gasification of coal is also the lowest cost method of creating hydrogen, with current productions costs estimated to be as low as $1.03/kg of hydrogen (NAS, 2004;

Ren, 2013). Coal gasification is already in use as a “clean coal” technology, with the syngas that is produced from the first process being used as a substitute for natural gas.

The cost for hydrogen from coal is estimated to be able to drop as low as $0.90/kg in the future, which would make it highly economically competitive compared to almost any other fuel source (NAS, 2004; Ren, 2013; Park, 2013).

The third and final advantage to using coal to create hydrogen is that the coal gasification process is efficient at large scales and could be combined with a coal power plant to provide electricity in order to take advantage of waste heat and existing coal supply infrastructure. This would lead to the centralization of hydrogen production, which would be ideal for the development of carbon sequestration technologies (NAS,

2004; Yang and Odgen, 2013). This could potentially eliminate nearly all carbon emissions from these combined power and hydrogen generating stations, if the carbon sequestration technology can be economically and technologically implemented successfully at these large scales.

This raises the most pressing disadvantage to utilizing coal to generate hydrogen.

Coal is the most carbon intensive of all fossil fuels and when the hydrogen is extracted from the coal it emits the same amount of carbon dioxide as it would have if it were combusted to produce electricity or heat. Despite discussions of “clean coal’ technology

86 these are concepts that have yet to be technologically proven and it remains to be seen whether or not carbon sequestration will be applicable for controlling emissions from a large number of coal plants, whether they are combusting the coal for power or breaking it down to retrieve the hydrogen. While the proponents of carbon sequestration will point out that it has been demonstrated on a small scale and that it is capable of capturing over

90% of the carbon dioxide emissions from a coal burning power plant, opponents remain skeptical and question the long-term viability of the practice (Clark, 2008; Lokey, 2007a;

Blanchette, 2008; Reichmuth, 2013.

The questions that must be answered in order to determine this are not easily answered. The first is: can the technology be scaled, economically, so that a large coal combined power plant and hydrogen generating station could sequester all of its emissions? Secondly, once sequestered, how long will the carbon remain in the geological formations used to trap it? Finally, what are the limits to how much total carbon dioxide can be stored in the available U.S. geological formations and, at the rate of production of carbon dioxide from all the coal plants in U.S., how long until they have been filled to capacity? As of this point none of these questions have been answered to the satisfaction of the majority of the scientific community and the debate continues.

With carbon sequestration as an uncertain technology, what is the impact of creating hydrogen from coal if there is no way to capture and sequester the carbon? In producing a kilogram of hydrogen from coal 19kg of carbon dioxide is created (NAS,

2004; Han, 2012; Yang and Ogden, 2013). As established earlier in this chapter, in order to get the same amount of energy from gasoline, 19kg of carbon dioxide would be produced as well. Thus, in terms of emissions, using hydrogen from coal would produce

87 just as much carbon dioxide as burning an equivalent amount of gasoline. Additionally, since the hydrogen from coal is produced centrally, there are a number of efficiency losses that are not taken into account in the above figures such as losses from compression, transportation, and distribution.

These figures have been adjusted to account for the difference in efficiency between fuel cell and a gasoline burning internal combustion engine. However, these adjustments were based on the historical efficiency of gasoline internal combustion engines, which is about 21 miles per gallon. With hybrid gasoline electric vehicle technology, however, it is shown that gasoline powered vehicles can become two to three times as efficient (Hammerschlag, 2005; Ren, 2013). When these factors are accounted for then it is possible that hydrogen from coal could actually produce far more carbon dioxide emissions than the continued use of gasoline (Waegel, 2006; Byrne, 2008; Clark,

2008; Ren, 2013).

A second disadvantage to the use of coal to as a feedstock for hydrogen generation is the local and regional environmental toll that is paid by the communities where coal mining operations occur. Older methods for mining coal involved simply digging a shaft deep into the ground and tunneling along veins of coal. Extracting coal in this fashion has a relatively low impact on the surrounding areas but has been declining, proportionally, as a means for extracting coal from the ground (Goodell, 2006). It has been increasingly replaced, especially in the western states, with strip mining. In this method of extraction the top soil from a large swath of land is removed through excavation and blasting to expose coal seams (Goodell, 2006). While regulations have substantially reduced the environmental impact of this practice, the ability of today’s

88 restoration techniques to return the environment to its previous state still falls short, often leaving behind areas that are unsuitable as habitat and limited in diversity (Goodell,

2006).

A final concern regarding coal from hydrogen is the idea that we would simply be replacing one unsustainable energy source for another. While there are substantially larger reserves of coal than either petroleum or natural gas, the amount of coal on the planet is still limited and will eventually be consumed. While this may not occur in our lifetimes, at that point a new energy infrastructure will need to be developed (Waegel,

2006; McDowall, 2012; van der Zwaan, 2013; Dayhim, 2014). The transition to any new energy economy will require billions, if not trillions, of dollars in investments, subsidies, incentives, and direct government purchases (Ogden, 1999; California Energy

Commission, 2001; van der Zwaan, 2013; Dayhim, 2014). In order to sustain a hydrogen- from-coal energy economy, not only will hundreds of hydrogen producing coal plants need to be constructed, but so will the facilities to sequester the carbon and thousands of miles of pipeline to ship the hydrogen from its generation sites to points of distribution.

Changing an energy economy is an expensive and lengthy prospect, and not one that should be undertaken lightly.

It is readily apparent that extracting hydrogen from fossil fuels provides many advantages in a budding hydrogen economy. Much of the technology that would be needed to develop a hydrogen generating infrastructure already exists and is in wide scale use today. This can be seen in the hydrogen generating steam reformation of natural gas plants that currently supply our chemical industry with hydrogen as a feedstock for industrial processes and the coal gasification programs that are developing as a part of the

“clean coal” initiative. These technologies are already well along the experience curve, present few technical barriers, and also represent the lowest cost method of currently generating hydrogen (Yang and Ogden, 2013, Ren, 2013).

But these advantages do not negate the serious disadvantages associated with the continued utilization of fossil fuels. In the process of extracting hydrogen from either natural gas or coal carbon dioxide is going to be produced. Even if the carbon dioxide can be sequestered successfully, there is still the inescapable fact that these processes of generating hydrogen are unsustainable, as would be the process of sequestering the hydrogen in geological formations. Eventually the nation will have no choice but to switch from fossil fuels for a renewable alternative and with the tremendous amount of capital that will be required in order to transition the current energy economy into a hydrogen energy economy, why expend that capital on a system that piggybacks onto the existing fossil fuel energy economy?

Fossil fuels can play a transitory role in the development of a hydrogen energy economy through dual use of existing infrastructure and by lowering the overall costs of using hydrogen as an energy carrier (Adamson, 2004; Waegel, 2006; Yang and Ogden,

2013; Park, 2013). But in the long-term, continued utilization of fossil fuels, regardless of whether they are converted into hydrogen or burned in power plants, is unsustainable.

Hydrogen and hydrogen fuel cells should be viewed as a technology that will allow fossil fuels to be abandoned, rather than a technology that will extend their use. Any other choice will simply pass our current energy issues on to a later generation.

3.3.2 Hydrogen from Electrolysis of Water

In the political discussion surrounding the hydrogen economy, one of the most common talking points is that the only waste product coming from a fuel cell running on pure hydrogen is water vapor, formed in the fuel cell when the hydrogen combines with oxygen ambient in the atmosphere. It is therefore rather fitting that one of the most promising sources of hydrogen is water. Since water molecules are formed of two atoms of hydrogen and a single atom of oxygen, water seems to be an ideal source of hydrogen gas. When split water becomes molecular H2 gas and molecular O2 gas. This forms a rather neat symmetry whereby the only byproduct of the production of hydrogen is then pulled from the atmosphere and the original feedstock is recreated.

Hydrogen is split from water in an electrochemical process known as electrolysis.

An electrical potential is placed across a body of water. The water conducts a current between the two leads by splitting into hydrogen and oxygen, each forming at a different lead. These elements collect as gas bubbles on the leads and eventually rise to the surface where they can be captured and stored for later use (Ogden, 1999; Ren, 2013).

Electrolysis is not a new technology and has gone through decades of refinement and improvement. But it is not the process of electrolysis that can introduce negative impacts it is the source of the electricity that is used.

The process of electrolysis is more expensive than the reformation of fossil fuels.

The basic cost of hydrogen from electrolysis can be estimated using the formula:

Cost in $/kg of H2 = $2.00 + $0.50*(cents/kWh)

The initial $2.00 baseline cost represents the expense of purchasing and maintaining the electrolyzer while the $0.50 for every cent per kWh shows the costs incurred for meeting

91 the electricity needs of the system. Thus the cost of hydrogen from electrolysis is highly dependent on the cost of the electricity being utilized. In order to be competitive with hydrogen from natural gas or coal, the cost of electricity would have to be extremely low.

The cost of generating hydrogen through electrolysis from grid electricity would vary from region to region along with the price of the electricity; however an estimated cost of

$7 per kilogram of hydrogen is given by the National Academy of Sciences, which would match with a cost of 10 cents per kilowatt hour (NAS, 2004; Ren, 2013; Lee, 2012;

Zhang and Wan, 2014).

But there are several reasons why electrolysis might be the preferred method of hydrogen generation in the future. The first of these reasons is that the technology is easily scalable and requires minimal additional infrastructure. This is because the only feedstocks needed are electricity and a supply of water, both of which are available at most sites. Because it is scalable, smaller installations could be set up without the need to raise large amounts of capital (NAS, 2004; Bozoglan, 2012; Ren, 2013; Huss, 2013;

Zhang and Wan, 2014). Secondly, the actual process of electrolysis does not incur any negative environmental impacts, with water going into the electrolyzer and nearly the same amount of water coming out of the fuel cell. This water can be reused, making the actual water inputs needed relatively low, assuming it is recaptured.

Finally, the process of electrolysis pairs very well with electrical generation from intermittent renewable energy sources such as solar photovoltaics and wind turbines.

Since these energy sources only produce power according to nature’s schedule, matching their supply to the demand at any given moment can be difficult, but electrolysis and hydrogen fuel cells offer an attractive method of transferring the energy from one period

92 of time to another (Schaber, 2004; Andrews and Shabani, 2012; Sanchez and Gonzalez,

2013; Marino, 2013). Additionally, the concentration and increase in versatility of these energy sources allows hydrogen generated from solar or wind power to fuel a vehicle would otherwise consume fossil fuels.

Electricity is, itself, an energy carrier, and so the environmental impact of hydrogen from electricity is in turn dependent on the source of the electricity (Waegel,

2006; Rosler, 2014). Because of this, electricity from clean, zero or low emission sources would provide hydrogen that is not accompanied by any significant greenhouse gas emissions. Electricity from fossil fuel sources, however, would produce hydrogen that carries with it the emissions produced from those sources. What compounds this issue is the fact that any negative impacts from the source of the electricity are actually going to be amplified by the process of using that power to generate hydrogen that will eventually be used produce electricity once again. This is because of the inefficiency and loss that is intrinsic to any energy conversion (Hammerschlag, 2005; Ren, 2013; Rosler, 2014).

Because the process of utilizing hydrogen from electrolysis requires several steps in order to make the transition from electrolysis to utilization in a fuel cell (electrolysis, compression, storage, transportation/distribution, hydrogen leaks, and utilization in the fuel cell), each of which has its own efficiency, the net efficiency of the whole process can be relatively low, between 25-50% (Rand, 2005; Rosler, 2014). Utilizing hydrogen as an energy carrier for electricity could double or triple the amount of electricity needed to fulfil the same task, depending on the efficiency of each step in the process of creating, storing, and using the hydrogen. Comparatively, the storage of electricity with conventional electrochemical batteries can have net efficiencies as high as 80-95%

93 depending on the battery technology and usage patterns (Rand, 2005; Rosler, 2014). This is not to say that hydrogen storage of energy does not have benefits of its own or that the efficiency of the steps involved will not improve, but this given the relative versatility of electricity and the efficiency of alternate storage options, the inefficiency of hydrogen must be considered.

In the U.S. the vast majority (~70%). of the power provided to the grid comes from fossil fuel sources, and nearly half of the power comes from coal (Goodell, 2006).

Thus, hydrogen generated through electrolysis from grid provided electricity could not be considered emissions free unless special arrangements are made to ensure that the power consumed is being specifically offset by renewable or nuclear generated power. The impact of hydrogen through grid electrolysis is not necessarily static, however. If the technologies continue to improve and reach their optimal efficiencies, then the overall efficiency of the process can be improved (Ren, 2014).

One conventional energy technology that should be viewed separately from the others in terms of its capabilities for generating hydrogen via electrolysis is that of nuclear power. Nuclear power has several aspects which can make it particularly well suited to the generation of hydrogen. These aspects include: 1) no carbon dioxide emissions; 2) the high temperatures involved in nuclear fission can greatly increase the efficiency of splitting water through electrolysis or through thermochemical reactions; and 3) because nuclear power can run steadily throughout the day, it can use excess generation during times when demand is low (such as at night) in order to produce hydrogen and then reduce hydrogen production when electrical demand increases again

(Ogden, 1999; NAS, 2004; Mazloomi and Gomes, 2012). Most of the technologies that

94 would be needed for large scale hydrogen generation at greater efficiency than conventional electrolysis are still in developmental phases. Research and development of these technologies is ongoing, however an estimate of eventual cost and efficiency is not yet available.

In terms of benefits to the environment, electrolysis using intermittent renewable electric sources offers the greatest potential reduction in environmental impact, particularly in dealing with climate change. The benefits of these energy sources are many. They do not produce any greenhouse gasses, they do not require extensive mining or other ecological disruption, they are (in one form or another) relatively equally available around the world, and they are renewable (Ren, 2013; do Sacramento, 2013;

Caliskan, 2013).

But currently, these energy sources represent only a fraction of the overall energy supply for the U.S. There are two primary reasons for this and they are cost and intermittency. While research and development are currently underway to increase efficiency and lower the costs of the components needed in order to make the energy from these sources more affordable (and currently some of them, such as wind, are already cost competitive) the more difficult problem to handle is the issue of intermittency, which can vary a system’s ability to produce power over the course of a day or the course of a season (Andrews and Shabani, 2012; Jewell, 2014).

This intermittency makes it difficult to incorporate a significant amount of these renewable energy sources into the electrical grid because the independent system operators need to be able to bring power online when the demand increases and these intermittent sources will not always be available. Because of this, the total amount of

95 intermittent renewable energy sources that can be fed into the grid is capped at about 10-

20%, which is the limit for what the ISOs can compensate for while managing the grid.

These energy sources have been utilized, however, in off grid electrical supply for several decades and this problem of intermittency has been solved through the storage of energy

(Zhang and Wan, 2014).

Traditionally, this energy storage has come in the form of electrochemical deep cycle lead-acid batteries (Rand, 2005). These batteries have always had their limits, however. They can only go through so many cycles of charging and discharging before they begin to lose their capacity for energy storage (Stevens, 1998). Additionally, they are heavy, bulky, and contain acidic chemicals that make them inconvenient for mobile applications where large amounts of energy need to be stored, as in an electric vehicle

(Rand, 2005; Bakker, 2012). Instead, another form of energy storage must be found and hydrogen fuel cells are a promising option.

Using hydrogen to store energy could assist intermittent renewable energy sources integrate into the grid. Hydrogen generated from these intermittent energy sources would be produced through electrolysis; would be no emissions or other significant environmental damage. Additionally, since the storage tanks for hydrogen are one of the least expensive parts of a hydrogen energy storage system it would be relatively inexpensive to increase the storage capacity of these systems in order to store large amounts of energy to account for either diurnal or seasonal intermittency. Batteries, by comparison, have costs that increase nearly proportionally with their storage capacity

(Rand, 2005). A final advantage that hydrogen could provide over traditional electrochemical batteries is the ability to refuel quickly (Ogden, 1999; NAS, 2004;

Waegel, 2006; Periera and Coelho, 2013; Petitpas, 2014; Galassi, 2014). This is particularly important in mobile applications such as electronics or vehicles. Whereas it might take several hours to recharge a lead acid battery, a hydrogen system could be refueled in a matter of minutes or seconds depending on the scale of the storage capacity.

There are, however, several distinct disadvantages to utilizing hydrogen for the storage of energy from intermittent renewable sources. The single greatest of these is the inefficiency of the hydrogen generation to utilization chain. As discussed earlier in this section, the overall efficiency of the hydrogen energy storage chain is can be anywhere from 28% - 65%, with average efficiency at slightly under 50%. Electrochemical batteries, however, have efficiencies ranging between 75% and 95%, with efficiencies of around 90% being the most common (Stevens, 1998; Lucas, 2012).

This is of particular importance when discussing the storage of intermittent renewable energy sources because many of them, solar in particular, are considerably more expensive than conventional energy options. If these energy sources are to be stored as hydrogen, then their costs would be effectively doubled. Since cost is currently one of the major factors holding back the wider implementation of these energy sources, the cost increase from utilizing hydrogen to store them would present a tremendous barrier to their introduction. Because of this, hydrogen faces significant competition from other energy storage technologies that are capable of offering many of the same benefits but at a higher efficiency. Examples include pumped hydro storage and advanced battery technologies (Rand, 2005; Lucas, 2012; Bakker, 2012).

So while technologically hydrogen energy storage offers many benefits when paired with intermittent renewable energy options such as the ability to store large

97 amounts of energy over long periods of time, mobility, quick refueling, and versatility, the economic disadvantages of utilizing hydrogen may mean that competing technologies will be more likely to encourage the wide scale adoption of intermittent energy sources in the near future. In all other ways, utilizing intermittent energy sources to produce hydrogen via electrolysis is exactly the same as producing hydrogen through electrolysis using conventional grid-based electricity.

3.4 Hydrogen Distribution and Storage

In addition to the hydrogen generation section of the hydrogen economy, there are many additional technologies and infrastructure that must be in place for a hydrogen based energy economy to be sustained. These include the equipment used to transport, store, and convert the hydrogen into electricity. In this section, each of these technologies will be discussed and explored, particularly in terms of their effect on the efficiency and cost of the hydrogen energy chain as well as any technological or policy roadblocks that they may present to the wide scale adoption of hydrogen energy technology. Of greater concern is the cost of these components, which will often represent the highest cost of a hydrogen energy economy, especially the distribution network for the hydrogen and the fuel cells, which turn the hydrogen into electricity.

One of the primary technological barriers impeding the development of a hydrogen energy economy has been finding an effective low cost means of transporting the hydrogen from the site of production to the site of its end use (Petitpas, 2012; Rangel and Sansores, 2014; Andre, 2013; Dutta, 2013; Gao, 2014). The difficulty in transporting hydrogen as compared to other fuels is that, when produced, it is gaseous and highly diffuse. This causes several problems for transportation and distribution. As a diffuse gas,

98 its energy density is extremely low at standard atmospheric pressure, requiring large volumes to store and transport sufficient amounts of energy. Additionally, most of the existing technology for transporting and distributing other fuels cannot be converted to carry hydrogen because they are designed to handle liquid fuels. Even the existing natural gas infrastructure cannot be easily converted to transport hydrogen as it is more diffuse and thus leaks from natural gas pipelines and containers. Also, hydrogen can make many metals brittle as it is absorbed into their crystalline structure and so existing gas transportation technology must be heavily modified prior to use with hydrogen (Ren,

2013).

A number of means either exist, or are being developed, to overcome these barriers and a large range of technologies are used or may be used in the future for the transport of hydrogen gas. These technologies can be broadly grouped into three categories: storing the hydrogen, transporting the hydrogen, and distributing the hydrogen from a central or semi-central distribution point. But many problems exist in each of these categories and it is possible to introduce significant inefficiencies into the hydrogen energy chain at this point, which can drastically increase the cost and carbon emissions of hydrogen energy. It is for this reason that much of the current research into hydrogen technology is focusing on this aspect of the developing hydrogen energy economy.

3.4.1 The Compression and Storage of Hydrogen

As mentioned previously, in the vast majority of hydrogen generation techniques the hydrogen is produced in its gaseous state either at standard atmospheric pressure or slightly higher. This makes the gas extremely low in its volumetric energy density and means that some method of concentrating the gas must be used in order to raise that

99 energy density so that the hydrogen can be stored in a reasonable volume for both stationary and mobile purposes. While most of these methods have just the primary purpose of increasing this energy density, some have the additional benefit of making the hydrogen easier to handle by having it absorbed into other materials.

Compression of the gas and storage in a high pressure tank is most common currently used technique for storing and transporting hydrogen in a higher energy density form. This method is commonly used because it is the simplest and least expensive means of storing large amounts of hydrogen energy in a relatively small space.

Additionally, many of the processes for generating hydrogen release the gas already partially pressurized, making the task of compressing it to its final pressure less expensive and less energy intensive. In some electrolyzer systems, the hydrogen pressure at generation can be sufficiently high that no further compression is required (Ren, 2013;

Petitpas, 2014; Rangel and Sansores, 2014).

The level of pressure needed for hydrogen storage to achieve reasonable energy density varies depending on the method of transportation of the gas; in a pipeline the pressure could be as low as 250psi, while for tanker truck shipping or mobile applications that pressure could be increased to as much as 5000psi. Even with these very high pressure systems, the energy density of hydrogen is still lower than that of conventional fuels. As an example, gasoline has an energy density of 32 MJ/l while hydrogen gas at

5000psi has an energy density of 3 MJ/l. Thus, even though hydrogen may be used at twice the efficiency of gasoline, a vehicle would still need a hydrogen storage tank several times larger than the size of a gasoline tank in order to travel the same distance

(NAS, 2004; Petitpas, 2014). In order to compress the hydrogen to 5000psi 4% to 8% of

100 the energy content of the hydrogen must be spent, depending on the starting pressure of the hydrogen (NAS, 2004; Yang and Ogden, 2013; Ren, 2013).

Additionally, since hydrogen gas must be pressurized to the extremely high level of 5000psi, this pressure could be very dangerous if a tank ruptured and significant care would need to be taken in making sure that proper safety precautions were taken. In addition to the potential danger of storing the hydrogen at high pressures, the energy density of compressed hydrogen is still significantly lower than that of gasoline. While this may not be a significant disadvantage for stationary applications, mobile applications such as vehicles or electronics may encounter difficulty in fitting a storage tank of suitable capacity in the available space. This would lead to a reduced range for hydrogen vehicles and shorter running times for electronics, factors that would dramatically impact consumer acceptance of hydrogen powered products (Galassi, 2014).

Another method for increasing the energy density of hydrogen is to cryogenically liquefy hydrogen and to transport it as a liquid at extremely low temperatures. This method of hydrogen storage is more likely to be used in the earlier stages of the hydrogen energy economy for the transportation of hydrogen from the production site to a distribution point where it will likely be converted back into a gaseous form. The reason for this is that it is extremely expensive and potentially dangerous to liquefy hydrogen and thus will likely only be used when large amounts of hydrogen need to be transported where hydrogen pipelines do not yet exist. Cryogenically liquefied hydrogen would be transported in a large tank either via truck or train (Ren, 2014; Petitpas, 2014).

In order to liquefy hydrogen its temperature must be brought down to 20K, or -

253C, as well as pressurized. The energy cost of accomplishing this is approximately

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40% of the energy content of the hydrogen and the process could add as much as

$2.42/kg to the delivered cost of hydrogen (NAS, 2004; Petitpas, 2014; Ren, 2013). This would give the liquefied hydrogen an energy density of 8 MJ/l, compared to 3 MJ/l for compressed hydrogen and 32 MJ/l for gasoline (NAS, 2004; Ren, 2013; Petipas, 2014).

Once, again, even though the energy density is raised and hydrogen can be used more efficiently than gasoline, a hydrogen vehicle running on cryogenically liquefied hydrogen would still require a storage tank at least twice as large as would be required for a gasoline tank for the same vehicle range.

Liquefaction yields several benefits over compressed hydrogen gas. It has an energy density that is nearly three times as high and is a liquid, which provides some advantages when it comes to transferring the hydrogen. These advantages, however, seem small when compared to the significant obstacles and dangers that arise from using liquid hydrogen as an energy storage medium. Liquefaction introduces a tremendous level of inefficiency into the hydrogen energy chain and would significantly increase the potential negative environmental aspects of generating that hydrogen and nearly double the cost

(Ren, 2013; Petitpas, 2014). These factors greatly reduce the potential for liquefied hydrogen to play a significant role in the long term hydrogen economy, and instead push it into the role of a transition technology to be used until more economical and efficient pipelines are installed.

Liquefied hydrogen presents several other technical barriers to its adoption as an energy carrier, mostly due to the extremely low temperature needed to maintain hydrogen in a liquid form. At only 20 degrees above absolute zero, liquid hydrogen is an extremely dangerous substance, capable of maiming or killing a person nearly instantly if they come

102 into contact with even small amounts (Petitpas, 2014). This makes the handling and transporting of liquid hydrogen both difficult and dangerous compared to nearly any other energy carrier. Obviously it is not something that could be safely handled by the general public and would require specially trained handlers to transport and transfer the liquid hydrogen from one place to another.

A final method of increasing the energy density of hydrogen and increasing the ease of handling hydrogen as an energy carrier is to absorb the hydrogen gas into either a liquid or solid material. There are a wide variety of materials and substances that may be used to absorb hydrogen in this fashion, most of which are experimental and have not yet been developed for commercial application. Some examples of these include carbon nanotubes, metal hydrides, and ammonia. Each of these materials absorbs and releases the hydrogen in a different manner. Some are simply able to absorb the hydrogen under heat, pressure or a combination of the two, while others, such as ammonia, use chemical bonds to trap the hydrogen in molecules that are then easily broken down (Rangel and

Sansores, 2014; Ren, 2013).

The advantage of these types of systems is that they require neither the extremely low temperatures required for liquefaction nor the high pressures needed to compress hydrogen gas to a suitable energy density. The materials that the hydrogen is absorbed by or made a part of are relatively benign and are capable of storing large amounts of hydrogen in a relatively small volume at room temperature and standard atmospheric pressure (Rangel and Sansores, 2014). This makes them both safer and simpler to distribute to the end users. The hydrogen is released through a chemical or thermal process onboard the vehicle or within the device.

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The primary issue with most of these systems is that the materials are either high in cost, very heavy, or not yet able to absorb sufficient amounts of the hydrogen. The weight issue, in particular, has presented a significant barrier in adopting these technologies in vehicular applications as the weight is high enough to substantially reduce the fuel economy of the vehicle. Additional issues arise due to the high temperatures required to release the hydrogen from the absorbing material, which would in turn require the fuel cells to operate at a higher temperature (Rangel and Sansores,

2014; Ren, 2013; NAS, 2004).

The storage of hydrogen is one of the primary technological obstacles to the development of a hydrogen energy economy. Current technologies present several issues such as: safety concerns; high energy costs leading to greater inefficiency; high capital costs added to the final cost of the supplied hydrogen; and technical limitations that prevent the energy density from reaching levels comparable to conventional fuels

(Rangel and Sansores, 2014; Ren, 2013).

These issues have little impact on the use of hydrogen in stationary applications where energy density and weight are of less concern, but they are limiting the acceptance and development of hydrogen vehicles for the major consumer markets, which are predicted to be one of the primary entryways for hydrogen into the general energy economy as a replacement for foreign oil. This makes overcoming the issue of storage for hydrogen extremely important for the eventual development of a significant hydrogen energy economy. While a variety of materials and substances are being examined for their ability to absorb and release hydrogen gas, weight, cost, and energy density still present significant barriers to the adoption of these technologies and none of them are

104 capable of performing as well as the current hydrogen storage technologies, let alone matching the performance of conventional fuels.

3.4.2 Distributing Hydrogen

Hydrogen supply is of tremendous concern to those who are envisioning a greater hydrogen economy. Currently, only a limited network of pipelines exist to transport most hydrogen from where it is generated, in large centralized steam reformation plants, to where it will be used or distributed and the rest must be moved via tanker trucks. This makes hydrogen availability in most areas extremely low (Ren, 2013). One of the primary core issues surrounding the developing hydrogen economy is the paradox of the chicken versus the egg (Brown, 2012). The concern is that consumers will not purchase hydrogen fueled devices unless there is an easily accessible and affordable supply of hydrogen fuel. But at the same time, there is little incentive for an energy company to develop the costly hydrogen transmission and distribution network unless there is a market for the fuel, meaning consumers who own hydrogen fueled devices.

The first hydrogen distribution technology to discuss is shipping hydrogen via tanker truck or train. These tankers ship the hydrogen either as a compressed gas or as a cryogenic liquid, usually as a liquid. The primary advantage of shipping hydrogen in this fashion is that it does not require as significant an initial investment into infrastructure as pipelines. Instead the delivery capacity of the vehicles can be easily scaled up or down as needed by adding or removing individual vehicles from the delivery fleet. Shipping hydrogen in this fashion is relatively expensive per unit of energy, however, especially if the hydrogen is liquefied, due to the low temperatures that the shipping unit would need to be able to handle. Transporting hydrogen as a liquid via tanker truck or train could add

105 between $1.40 and $2.42 to each kilogram of hydrogen shipped (NAS, 2004; Ren, 2013;

Petitpas,, 2014).

The actual tanker trucks would have an effective delivery range of 300-400 miles and could deliver up to 5,000kg of liquefied hydrogen in each load. While the delivery method itself may be the most economical option in the near future, many doubt the ability of tanker trucks to supply hydrogen in this fashion without tremendous energy inefficiency. These energy costs could be mostly avoided if the hydrogen being shipped in the trucks was merely compressed rather than being liquefied, but the average tube canister on a truck would only hold about 400kg of compressed hydrogen. This amount is hardly enough to justify the large scale distribution of hydrogen at any significant distance due to the cost of purchasing the trucks and the fuel (Romm, 2004; Ren, 2013).

As for the initial cost of these tanker trucks, or compressed hydrogen gas, a tube trailer that could carry 300-400kg would cost $250,000 and a liquid tank trailer that could carry 4,000kg would cost $600,000 (Simbeck, 2002). In light of the expense of each truck this technology would be extremely expensive if it were to be applied on a large scale.

Instead, this option may be useful at the beginning of the transition to a hydrogen economy as a means of meeting lower demand.

A second hydrogen delivery technology to be explored is shipping compressed hydrogen gas via pipeline to decentralized distribution points. This method of hydrogen delivery is the lowest cost option for delivering hydrogen to an end use site or local distribution point. However, while the operation and energy costs of a hydrogen pipeline delivery system are low, the capital costs of installing such a system may be prohibitively high, especially during the initial phases of the developing hydrogen economy when the

106 amounts that are needed would be relatively low compared to the capacity of a pipeline system. But the technology has already been utilized in several different areas in order to transport hydrogen used in chemical manufacturing and industrial processes and has been proven to be a secure, stable, and cost effective means of delivering large amounts of hydrogen over a significant distance (Andre, 2013; Ren, 2013).

The added cost for shipping hydrogen via pipeline is a modest $0.42/kg of hydrogen compared to the $1.80/kg cost incurred by shipping hydrogen as a liquid via truck, and it is expected that this cost may fall even lower to $0.31/kg in the future.

Distributing the hydrogen from the pipeline is expected to add an additional cost of

$0.54/kg (expected to drop to $0.39/kg in the future) giving hydrogen shipped via pipeline an overall current added cost of $0.96/kg, which could be expected to drop to

$0.70/kg in the future. This compares very favorably to shipment as a liquid via truck, which has current added costs for delivery of $2.42/kg and future costs of $1.40/kg

(NAS, 2004; Andre, 2013). Additionally, since the hydrogen would be shipped as a compressed gas rather than as a liquid, the transport would be both safer and less energy intensive than shipment by truck.

The pipelines that would be used to transport the hydrogen are not the same that are used to transport other gasses, such as natural gas. Due to its diffuse nature and its tendency to make many metals brittle, hydrogen gas requires a special set of equipment to ship it via pipeline. This is particularly true around the seals, which would require special gaskets that would prevent leaks and fractures. As a result, hydrogen pipelines have an extremely high capitol cost on the order of $600,000/km. This figure is dependent on a number of different factors including diameter of the pipe and overall

107 length of the project, but even the lower end estimates of cost are on the order of several hundred thousand dollars per mile (Parker, 2004; Andre, 2013). Because of this, constructing a pipeline for even a modest 100 miles in order to create a metropolitan hydrogen fueling infrastructure would cost tens of millions of dollars.

Due to the high cost of hydrogen pipeline systems, it is unlikely that they will be widely employed in the near future, as the demand for hydrogen fuel is simply too low to justify the capital expenditure (Dayhim, 2014). Instead, transportation by tanker truck will likely continue to dominate the delivery of hydrogen to the point of use. The first introduction of hydrogen pipelines (other than those already being utilized for industrial purposes) will likely be in metropolitan areas where a concerted effort is made by local policy makers to develop a hydrogen fueling network.

On the other hand, it is possible that by the time that the demand for hydrogen has reached a point where a hydrogen pipeline system would be justified, a transition away from centrally produced hydrogen will have already taken place and local production of hydrogen, either by electrolysis or the reformation of natural gas (which can be delivered by conventional, already existing pipelines) will eliminate the need for the long distance transport of hydrogen in the first place (Park, 2013). There are numerous proponents of just such a system, where hydrogen would be produced on site rather than in a central location and the benefits of such a system are numerous and while there are some significant downsides to this mode of hydrogen distribution, it is uncertain whether or not they will outweigh the benefits in the long term (Ogden, 2003; Park, 2013; Yang and

Ogden, 2013).

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Earlier in the chapter, numerous technologies for the production of hydrogen were discussed. While several of these technologies can only be utilized on a large scale, many of them may be scaled down to levels that would be appropriate for either a local hydrogen distribution point or even for the use of a single individual or family. The most likely of these technologies to be used on a small scale to eliminate the need for hydrogen transportation over long distance are electrolysis and natural gas reformation. One potential downside of a distributed hydrogen infrastructure is that efficiencies obtainable via large-scale generation may not be possible when the scale is reduced to accommodate the needs of an individual or small group. This is particularly true in the case of natural gas reformation, where the energy and operating costs of a small scale reformer are significantly higher than for large centralized reformers on a per unit basis (Ren, 2013).

For the near term, transportation of hydrogen by truck and train in liquid form will be the dominant method of getting hydrogen to its point of use or local distribution.

While pipeline technology has the means to transport hydrogen more efficiently, at a lower cost, and in a safer and more convenient gaseous form, there is simply not enough demand, nor is there likely to be enough demand in the near future, to justify the tremendous initial capitol expense that would be require to create regional or national distribution networks for hydrogen gas as currently exist for natural gas. This would only change if a significant portion of the population were to utilize hydrogen as an energy carrier, most likely for transportation, only then would the costs of a hydrogen pipeline distribution system be justifiable.

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3.4.3 Hydrogen Distribution and Storage Conclusions

Just as in hydrogen production, the impacts from different types of hydrogen infrastructure can vary greatly depending on the technologies used. The first question to ask is how the hydrogen should be stored. There are currently three methods of hydrogen storage that are currently being seriously considered: 1) compression; 2) liquefaction; and

3) absorption. Compression is the simplest and currently the cheapest method of storing hydrogen (Ren, 2013). By simply storing hydrogen as a highly compressed gas there is relatively little efficiency lost and the economic costs are low as well. Unfortunately, due to hydrogen’s low energy density, compressed hydrogen gas carries only a small amount of energy for the amount of space that it takes up making this a poor option for mobile applications, such as vehicular transport and personal electronics. Liquefaction, on the other hand, can increase the energy density of hydrogen significantly but, because hydrogen must be brought to extremely low temperatures in order to become a liquid, it is both energy intensive, costly, and potentially dangerous. The final option is to absorb the hydrogen into another material. The first downside to this technique is that while there are many different materials that have been considered and are currently being developed to absorb hydrogen, all of them are still highly experimental. As of yet, of these three options can solve all three issues of efficiency, energy density, and a reasonable cost.

The next major choice in hydrogen technology is how the hydrogen is to be delivered to its final destination. There are once again three options for the delivery of hydrogen to its point of use and they are pipeline, by canister on trucks or trains, and production on site. The method of hydrogen delivery is highly dependent on the production and storage method for the hydrogen. For example, pipelines may only be

110 used while the hydrogen is in its gaseous state, although the hydrogen may be liquefied once it has reached its destination. Similarly, the low energy density of gaseous hydrogen makes it a poor candidate for transportation by canister on either a truck or a train.

Producing the hydrogen on site eliminates the need for transportation altogether, but it can usually only be accomplished through small scale natural gas reformation or electrolysis.

At the low level of hydrogen utilization in society today, the cost of building a pipeline would be prohibitive. But at higher levels of consumption, that high level of capital investment in a pipeline begins to look more and more attractive because at high volumes transport by pipeline is less expensive, especially as it would allow the hydrogen to be transported as a gas rather than as a liquid. Onsite production has the lowest costs and highest efficiency in terms of getting the hydrogen to where it needs to be. However, the scale of production, if it is at the point of use, is almost always going to be lower therefore, one must consider the loss in efficiency from producing hydrogen onsite with small scale reformation of natural gas or electrolysis and compare that to the costs of transporting it from a centralized location.

3.5 The Role of Hydrogen in a Transitioning Energy Economy

An accurate analysis of the production stage for the hydrogen economy is one of the most vital aspects of any analysis of the future potential for the hydrogen economy. It is in this stage that the majority of the environmental impacts occur and these are commonly overlooked when discussing hydrogen energy. Because utilizing hydrogen in a fuel cell produces only water vapor and no other emissions, it is easy to ignore the emissions that occur during production, and these emissions can be as high, or even

111 higher, than would be produced if fossil fuel were utilized instead. This can produce a dangerous situation, whereby proponents of a particular method of hydrogen production can claim no emissions and mask the true impact that hydrogen generation can have in terms of climate change (Clark, 2008; Lokey, 2007; Hodson and Marvin, 2006).

The greatest danger in this stage of the hydrogen energy economy is that hydrogen will be used as an extension of the current fossil fuel dominated energy economy (Lokey, 2007a; Hodson and Marvin, 2006; Blanchette, 2008; McDowall, 2012).

While certain shifts will occur, such as moving away from imported petroleum and using domestically available natural gas and coal, in the end the energy economy will still be based on fossil fuels and will have many of the same problems as the current energy economy. Emissions from the fossil fuels used to make hydrogen will still need to be accounted for, and a fossil fuel based hydrogen economy will have to rely heavily on carbon sequestration in order to avoid continued carbon emissions and this technology has not yet been proven on a scale that would be required in order to sequester the level of emissions that would be produced and many serious questions remain about the long term viability of sequestration technology. Additionally, since the coal and natural gas will still need to be extracted from the earth, a number of other environmental concerns associated with this process will not be alleviated.

A second concern with utilizing hydrogen to extend the life of the fossil fuel energy economy is the issue of sustainability. While most of the major media attention has gone to the issue of peak oil and diminishing petroleum reserves, neither coal nor natural gas can be extracted at the levels required renewably (Clark, 2008). Thus, if the utilization of these fuels is not just continued but actually expanded in order to replace

112 petroleum, sustainability is a significant concern for the extraction of hydrogen from fossil fuels. At best, utilizing hydrogen generated from natural gas and coal in order to meet our energy needs could delay a transition to a renewable energy system by perhaps a century.

While there are many down sides to using fossil fuels to generate hydrogen, there are a number of benefits that should be accounted for. The most obvious benefit would be the reduction in dependence on foreign sources of oil. If hydrogen can be used as a replacement for gasoline as the power source for vehicles then the U.S. energy security could be greatly increased as sources of hydrogen are widely domestically available.

(Andrews and Shabani, 2012; Petitpas, 2014). Additionally, since the emissions from hydrogen generation from fossil fuels would be produced at a central location, rather than issuing from the tail pipes of millions of cars, if carbon sequestration technology can be developed and is proven to be reasonable then capturing the emissions generated for transportation energy would be possible, whereas today it is not.

A less obvious but greatly important reason to utilize fossil fuels to generate hydrogen is that it would be far easier economically to begin a hydrogen economy in this fashion. The technology for generating hydrogen from coal and natural gas is already decades old and well developed. This leads not just to lower generation costs and efficient processes, but also means that there is already an established infrastructure for the generation and transportation of hydrogen from these existing plants. Since the cost of developing the infrastructure needed to support a hydrogen economy is estimated to be quite high (and will be discussed in detail in the next section) and because consumers will be reticent to purchase hydrogen fueled devices and vehicles unless there is already a

113 ready supply of hydrogen fuel, having an existing infrastructure could kick start the hydrogen economy and avoid potential “chicken vs. egg” paradoxes (Yang and Ogden,

2013).

Generating hydrogen from fossil fuels therefore presents an excellent opportunity to begin the development of the hydrogen economy and could be extremely useful in developing an economy of scale for hydrogen based technologies so that rapid growth and acceptance of hydrogen and hydrogen fuel cells could occur. But it seems important that a fossil fuel based hydrogen economy be developed only as a transition phase in the overall adoption of hydrogen as an energy carrier (McDowall, 2012; Lokey, 2007a;

Clark, 2008). If it is not planned to for fossil fuel generated hydrogen to be phased out relatively rapidly, within a decade or two of the beginning of the hydrogen economy, then there is the serious risk of hydrogen being used to extend the utilization of fossil fuels into the 22nd century. Associated with this would be rising carbon dioxide emission levels, significant climate change, environmental damage from fossil fuel extraction and a future energy supply crisis as these sources eventually are exhausted.

Other methods of generating hydrogen generation show a great deal of future potential but currently cannot economically compete with traditional energy sources or with hydrogen generated from fossil fuels (Bakker, 2012). Of particular importance amongst the other methods of generating hydrogen is electrolysis performed with electricity from intermittent renewable energy sources such as solar photovoltaic modules, wind turbines, and tidal power generators. These energy sources have very few negative environmental effects and essentially no carbon dioxide emissions but they are

114 currently being held back by comparatively higher costs, intermittency, and a lack of versatility.

Using these energy sources to create hydrogen helps to solve both the issues of intermittency and versatility by storing the energy produced in the form of hydrogen that has been separated out from water. By storing the energy as hydrogen it can be produced when there is an excess of power coming from an intermittent energy system and then used to provide power when the intermittent system is incapable of supplying the energy demand. With the proper amount of generation capability and storage capacity, hydrogen could be generated to guarantee energy supply to match demand for either diurnal or seasonal intermittency (Kouskou, 2014; Zhang and Wan, 2012; Marino, 2013).

Additionally, by storing these energy sources in the form of hydrogen, the energy becomes more versatile. Hydrogen can be used in many applications where electrochemical batteries are currently utilized, such as in powering mobile electronics or for fueling vehicles.

Hydrogen has several advantages over electrochemical batteries such as quick refueling time and a lower cost as the amount of energy needed to be stored increases.

But hydrogen also has several disadvantages compared to electrochemical batteries; primarily that it has a lower efficiency. This lower efficiency amplifies any negative environmental effects by requiring a greater level of electricity to be produced to create the hydrogen than would be needed if it were stored in a battery (Bakker, 2012; Rand,

2004; Hammerschlag, 2006). This is particularly important if grid electricity or any electricity from fossil fuels is being used to perform the electrolysis. Additionally, just as the negative environmental effects are amplified, the cost of energy stored in the form of

115 hydrogen is significantly more expensive than if the energy used to create the hydrogen were used directly. For both the negative environmental effect and cost amplification storing energy in the form of hydrogen is less efficient than storing it in electrochemical batteries and thus the amplification of negative effects is worse.

With the information from this chapter, it is possible to form a better understanding of the technical aspects of the hydrogen energy economy, creating the building blocks that allow for critical commentary of the language used by others to describe that economy. These are used in later chapters of this dissertation as the basis for comparison against which constructed narratives can be identified and definitions for critical and optimistic indicators formed.

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Chapter 4

METHODOLOGY

The thesis of this dissertation is that many issues of policy involve complex subject matter that requires specialized knowledge which forces most individuals to rely on summarized and digested information on the topic so that they can participate in the public discourse. This digested information has historically been made available through the news media, but they in turn frequently rely on sources to provide them with the large quantity of ready to publish material they need to fill the 24 hour news cycle. Large, highly organized political and corporate groups are best positioned to provide this information as they appear authoritative to the public and have the resources available to devote to the production of information that is comprehendible to the general public on matters that are important to their interest. However, this creates the opportunity to introduce constructed narratives as these organizations can then influence the presentation of information in a way that will sway public opinion to their position on contentious political issues. This effect was described in Herman and Chomsky’s Model of Propaganda as ‘sourcing’ (Herman and Chomsky, 1988; Lokey, 2007, Lokey, 2007a;

Hodson and Marvin, 2006) and represents one path by which news stories are developed.

As energy issues often involve facts and figures derived through technical analysis, the public discourse of these topics is particularly susceptible to the introduction of constructed narratives via the news media sources. This dissertation uses the

117 discussion of the hydrogen economy during the Bush administration as a case study to quantitatively demonstrate evidence suggesting the presence of sourcing and to identify if a statistically identifiable skew exists in the distribution comparing the indicators found in the political or academic sources compared to those found in the news media.

Demonstrating this process will not only draw attention to this issue, but also was able to suggest means by which this effect can be successfully countered.

In order to study language quantitatively, it was necessary to create a coding structure that could be applied to sets of text to produce statistics from the language that could then be analyzed. These statistics were developed from three sets of text representing the Bush administration, the news media, and the academic sector, which was used to represent a balanced view of hydrogen technology. The coding structure was used to quantize the level of optimistic or critical indicators in any given speech, article, or other release that was released by the three sources on the subject of hydrogen. This chapter describes how these figures were calculated and demonstrate how they can then be used to demonstrate the influence that the Bush administration’s presentation of hydrogen had on its public presentation by the news media in spite of a more critical discussion in the academic community.

4.1 Content Analysis

In order to demonstrate statistically identifiable correlation between the presentation of hydrogen technology by the Bush administration and the discussion of the subject by the news media it was necessary to utilize a methodology that was able to convert qualitative data into quantitative data that could be easily and objectively analyzed. Content analysis has been used for decades to determine trends and effects

118 stemming from the use of the written and spoken word and is the methodology used for this case study (Weber, 1990). Any research which attempts to study the political impacts of speech and rhetoric will be tasked with the arduous process of converting hundreds of pages of text into carefully coded data that will allow comparisons to be drawn between different sources and which can be used to conduct mathematically rigorous statistical analyses to show correlation or causation between the data sets. There are many different methods of approaching such a task, primarily differentiated by the source material to which they will be applied but all falling under the general heading of content analysis

(Neuendorf, 2002).

In this section the process of content analysis will be discussed, along with its strengths, weaknesses, and why it is appropriate to use this technique to analyze the data set that was examined in this case study. In the second part of this chapter, focus will be given to the development of a procedure for content analysis that will be applied to the sets of data that were gathered from each of the sources: administration, mass media, and academic experts. The application of this technique and its results will then be discussed in greater depth in order to provide detailed results regarding the connection between hydrogen indicators appearing in administration and expert sources versus their appearance in the mass media source.

Content analysis is a research method that is used to make valid inferences from a text or set of texts using a defined set of procedures (Weber, 1990). It is the “… systematic, objective, quantitative analysis of message characteristics” (Neuendorf,

2002). These inferences can be about the sender of the message or they can be about the intended audience of the message. In this case the inferences would be regarding the

119 energy policy intent of the Bush administration. There are a number of ways in which this methodology may be employed to gain information. Some examples include: comparing media or modes of communication; coding open ended questions in surveys; determining differences in language usage in different cultures or countries; and revealing the focus of an individual or group, to name just a few (Weber, 1990). Most importantly for this research, content analysis can be used to objectively identify specific trends in language and reveal the existence of propaganda in government releases and other media. It may be applied to a wide range of subject material including but not limited to: commercials, newspaper articles, speeches, press releases, television programs, and movies.

Content analysis in not a new science, but rather has its roots deep in history and has been used for hundreds, if not thousands, of years. The earliest uses of content analysis can be found in early biblical studies where the holy texts were subjected to analysis by Talmudic scholars attempting to gain a deeper insight into their meanings.

Modern content analysis, however, began in the early 1930s with the Payne Fund studies which attempted to discern the effect of movies on movie watchers, in particular in regard to the effects of violence, crime, and comedy (Neuendorf, 2002).

The utilization of content review has continued to grow in both utilization and in importance in the field of social research since this time. A particular contributor to the early development of content analysis as a scientific method for the exploration of message content was Harold Laswell who researched a wide range of social topics in the

1940s and 1950s. Laswell was known as the Da Vinci of the behavioral sciences for his wide ranging breadth of topics he investigated and his proficiency in many areas of study

(Neuendorf, 2002). His dissertation in 1927 was a study of World War I propaganda (he

120 studied dropped leaflets and military recruitment posters) and he described it as a content analysis, though it was actually a fairly qualitative study (Neuendorf, 2002). But he continued to refine his technique through World War II when he was chief of the

Experimental Division for the Study of War-Time Communications in the U.S. Library of

Congress and this experience in analyzing Nazi communications eventually lead him to a career in analyzing texts for potential communist leaning during the early Cold War. It is from this background that modern content analysis arose; particularly coder training and reliability assessment techniques that are still in use to this day (Neuendorf, 2002).

During the 1960s, the first use of computers in content analysis began. The initial efforts at using computers for content analysis began at Harvard under the direction of

Philip Stone. Stone put together a group that constructed the first computer program that would be able to analyze text. This group put together many different dictionaries that could be used in their program to analyze texts for a variety of different messages and subjects. Much of the work they did in putting together dictionaries of phrases and words to be searched for are still being actively used today (Neuendorf, 2002).

Personal computers have, of course, revolutionized the methods by which content analysis can be conducted. Researchers now have access to hundreds of dictionaries and countless textual references to analyze, and all of the coding can be done with a few simple key strokes and mouse clicks. But the core of content analysis still rests with the researcher themselves (Neuendorf, 2002). While a computer can reduce much of the manual labor that was required for the analysis of text using content analysis, the human researcher is still responsible for most of the key factors in conducting research. The selection of the proper texts to be analyzed, the selection of a dictionary containing the

121 proper words and phrases to be searched for, and the actual interpretation of results is still the responsibility of the human researcher.

Part of what sets content analysis apart from other methods of analyzing qualitative data is its adherence to the principles associated with quantitative analysis and by meeting the following characteristics of the scientific method. The first is objectivity inter-subjectivity. That is, content analysis attempts to avoid the biases of the investigator by applying a set standard, without variation, across the entire body of the subject matter being examined. Additionally, the standards to be applied to the subject matter are determined a priori. Thus the definitions and choices made in designing the content analysis are determined before, rather than after, the subject matter has been examined by the experimenter (Neuendorf, 2002).

Content analysis also seeks to meet the basic standards of both reliability and validity. Reliability refers to the ability of a testing procedure to produce the same or very close results on multiple applications of the same test to the same set of data. In the field of content analysis this generally refers to multiple coders looking at the same piece of text to be analyzed and for all of the coders to come up with the same results. This is known as reproducibility (Weber, 1990). But reliability can also refer to invariance over a period of time, in which a coder would be looking at the same piece of text and analyzing it again. This is called stability (Weber, 1990).

While reliability is a measure of the accuracy of the process of coding the text, validity refers to the accuracy of the coding to represent the values being examined in the text. Essentially, validity asks if the coding of the text is measuring those variables that the coder wishes to examine and if the variables being measured correspond to the

122 variables that they are intended to measure (Weber, 1990). Additionally, validity can refer to the ability for the results of the test to be generalized to situations outside of that which was being directly measured. This is known as generalizability and along with correspondence they make up the majority of the validity of any given test. But validity may be broken down even further into a wide range of different types of validity such as construct, hypothesis, and predictive validity (Weber, 1990). Each of these types of validity corresponds to generalizability or correspondence validity to varying degrees.

4.2 Applying Content Analysis to the Case Study

The propaganda model was developed by Herman and Chomsky in order to explain the influence over the media by those that hold power within a society, and how that power is used to influence the content of newspapers and other media outlets. This influence is broadly broken down into five categories: media ownership; advertising; sourcing; flak; and anti-communism. While anti-communism, these days, can be largely viewed as more of a pro-capitalistic viewpoint, the categories largely remain valid in describing the ways in which media content is influenced by people of power within a given social system (Herman, 1988). Combining this theory with content analysis provides a rich opportunity to study the effects of rhetoric and language on public perception.

Of particular interest in the case of this research, which examines the utilization of optimistic and critical indicators in the support of the formation of energy policy, is the third tenet of the propaganda model: sourcing (Herman, 1988). The thesis of this dissertation states that powerful organizations can form constructed narratives regarding energy technologies, which are simplified but often based on studies too complicated for

123 lay persons to analyze. These narratives are then spread to the public through the mechanism of sourcing. A one-sided view of the energy technology is formed when the newspapers fail to include the more comprehensive and even handed treatment of the subject presented by the relevant technical and peer reviewed journals (Hodson and

Marvin, 2006, Lokey, 2007). With the majority of the public lacking the necessary knowledge to adequately gauge the impact of technical issues, they are unable to question the issues using the higher level information found in the journals and so the only source available to them, the news media, can be a powerful influence on the public perception of energy technologies. In turn, the news media are bound by availability of information leaving them prone to the influence of corporate or governmental sources (Littlefield,

2013).

In order to study this hypothesis through content analysis it was necessary to compare three sets of information: 1) viewpoints being presented by the authoritative organization; 2) the viewpoints being presented by the media; and 3) the viewpoints the presented in peer reviewed journals by experts and academics. The supposition is that the positions found within the newspaper articles should be predictable given the positions put forward by the powerful, organized source and that this position will differ from that of the academic community, which will only influence the public presentation of the topic in some circumstances. This will lead to a statistically identifiable skew in the distribution of the indicators found in The New York Times.

To narrow the breadth of the study and to make it more manageable for a dissertation, the case study of hydrogen fuel cell technology during the Bush administration was examined and conclusions were generalized from those results.

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Specifically, coding shows that the Bush administration favored the introduction of hydrogen and developed and distributed speeches and written materials that were optimistic of the technology’s potential. Further it was shown that the newspapers would produce an optimistic view of hydrogen technology that closely followed the level of optimism expressed by the Bush administration in the prior months (Lokey, 2007).

Meanwhile the peer reviewed journals included a balanced mix of optimism and criticism, but neither view was found to be a significant predictor of the news media until

2006 (Clark, 2008, Reichmuth, 2013).

In order to gather this data it was necessary to utilize a quantitative methodology.

A number of case studies have been conducted in the past utilizing Herman and

Chomsky's Propaganda Model, emphasizing the third tenet. Several have been conducted in South Africa in recent years looking at a variety of topics. In 2008 Lovaas wrote

“Manufacturing Consent in Democratic South Africa: Application of the Propaganda

Model”. In it he describes three case studies that were conducted using the same methodology. In these three case studies articles were searched for in an electronic database based on a set of predefined keywords covering more than 10 years of articles.

Every relevant article that was returned was a part of the sample. There was a list of possible types of sources and for each article the types of sources used were noted. Also noted was the general category of the article; did it primarily concern finance, litigation, environmental impacts, etc. The purpose of these studies were to determine what sources the papers were using most and what sort of pieces they were writing about a variety of environmental and social issues (Lovaas, 2008).

Another case study was conducted by Ryan Malan, and examined the treatment of

125 a pollution issue from a particular corporation by two national papers. They utilized a similar methodology as Lovaas. An electronic database was used to gather articles based on searches performed looking for a set of predetermined keywords with all returned results being included in the sample. These articles were then grouped into categories for further analysis based on the type of article: “human interest”; “technology”; “finance”;

“politics”. Two years of articles were examined. These articles were then coded both qualitatively and quantitatively based on the usage of keywords (quantitative) but also on demeanor and attitude (qualitative). The results were compared against interviews with experts to gauge what should have been covered in the media from a public interest perspective (Malan, 2009).

These studies suggest an approach for the methodology that is used in the examination of the hydrogen economy during the Bush administration. For my research I considered how optimistic government hydrogen energy viewpoints entered into the media mainstream and how those viewpoints differed from the more balanced mix of optimistic and critical views being discussed by the academic journals. The selected methodology examines each of these three data sources, applying the same set of analyses to a sample from each and then compared the results. According to Chomsky and Herman, there should be a clear correlation between the results for the media and the government sources and these should diverge from what is found in the academic papers

(Herman, 1988).

Representing the corporate or governmental sources of information was the complete set of speeches, interviews, and press releases in which President Bush or his senior administration officials discuss hydrogen energy. This data was collected from the

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President Bush archive and sorted into a pool of relevant sources by searching for and including any paper, speech, or press release that contained either of the terms:

“hydrogen” or “fuel cells” (The George W. Bush Presidential Library, N.D.). The Bush administration was chosen for a number of reasons including: their tremendous level of support for a particular energy technology, hydrogen; the length of his presidency; and the temporal proximity of his terms (Lokey, 2007). Few alternatives existed and this was clearly the best choice.

The news media sample consisted of every article in The New York Times that discussed hydrogen energy from 2001-2008, inclusive. The pool of articles relevant to the hydrogen economy was sorted from the total using the exact same search terms as applied to the Bush administration’s set: “hydrogen” and “fuel cells.” The New York Times was chosen for its reputation as a fair and well researched publication. It is widely believed that, if anything, The New York Times has a liberal leaning, which would be generally more critical of hydrogen energy than conservative leaning newspapers due to Bush administration support for the technology. The appearance in this newspaper of the optimistic indicators for hydrogen energy created by the Bush administration, coupled with a lack of critical indicators that appear in academic and technical journals would be a strong indicator that the tenet of sourcing was being employed.

A large number of papers, articles, and journals exist that could be used as the basis for the academic position. A single representative journal, Energy Policy, was selected, covering the same time span as the other two sources. Energy Policy was chosen due to the large number of papers devoted to hydrogen during the 2001-2008 timespan as well as the tone of the journal, which tended to use the language of policy and politics

127 rather than dense, math heavy technical language. This was done so that the coding terms and conditions created for analysis of Bush administration releases and New York Times articles could be applied equally to the journal articles. Additionally, these articles were more likely to discuss the hydrogen economy in general, rather than focusing on a singular aspect of hydrogen technology and its technological specifications.

The following information was collected for each article being analyzed:

1. The author.

2. The date of publication / release.

3. The venue the speech was given in or the paper section the article appeared in. This does not apply to the academic journal.

4. Normalization information: The number of paragraphs, the number of paragraphs that mention hydrogen or fuel cells, the number of paragraphs relevant to one or more of the five categories of indicators being examined.

5. What indicators are present? Optimistic and critical indicators are defined for five categories, which allow any unit of text to be coded as optimistic, critical, or as having no indicator in each category. Each category is fully represented by the three options, and each paragraph of the texts was coded for all five. The five categories are:

1. Greenhouse Gas Emissions 2. Efficiency of Hydrogen Systems 3. Sustainability of Hydrogen Production and Use 4. Viability of Sequestration with Hydrogen Production 5. Sources of Hydrogen Production

Once the data was collected, then the results showing the presence of optimistic and critical indicators in the newspaper articles could be compared to the results from the government releases and the academic journals. The hypothesis suggested there would be a statistically identifiable correlation in the breakdown of the use of optimistic indicators and critical indicators between the Bush administration and The New York Times, which

128 would lean towards optimistic statements regarding hydrogen, and little to no correlation the indicators found in Energy Policy, which should express a more balanced position with significant criticism. These findings would indicate that optimistic hydrogen statements were heavily used by the government and suggest that the Bush administration positions did transfer into the media discussion of the topic during the hydrogen boom years of the previous decade.

4.3 Methodology for Coding and Analyzing the Hydrogen Case Study

The process of content analysis begins by identifying the unit of observation, the single unit of communication that was to be coded and analyzed. An example of a unit of observation would be if interviews were being conducted to determine public opinion on the efficacy of a new law. In that case, each individual interview would be the unit of observation and each would be coded separately (Neuendorf, 2002). For this case study the units of analysis came from three sources: the G.W. Bush administration, The New

York Times, and Energy Policy. To represent the Bush administration every speech, letter or interview in which former President Bush discusses hydrogen or fuel cell policy was collected. The same criteria were used to identify those articles from The New York Times and Energy Policy that discussed hydrogen and these were collected for analysis.

Many of the speeches, press releases, and articles that were collected for analysis were pages long and the references to hydrogen limited to a paragraph or two; the only sections of text that were coded are those paragraphs in which hydrogen or fuel cells were mentioned. In order to identify the individual units of analysis within each article, speech, or press release the same search terms used to identify the appropriate articles from each of the three sources were used to determine which paragraphs specifically

129 mention hydrogen or fuel cells. Each paragraph containing at least one of the terms

“hydrogen” or “fuel cells” was labeled as a “hydrogen paragraph” and marked for further analysis. All other paragraphs were counted for normalization purposes but not coded in any fashion. Each hydrogen paragraph was further analyzed and sorted to see if it contained references to any of the five categories of interest previously identified (GHGs, efficiency, sustainability, sequestration, and sources of hydrogen). If the paragraph contained references to one or more of these subjects then it was labeled as a “relevant hydrogen paragraph”. The hydrogen paragraphs which are not also relevant hydrogen paragraphs were not coded, but a separate count of these was made for normalization purposes.

In order to quantize these sets of qualitative text, each relevant hydrogen paragraph was coded by identifying the presence or absence of optimistic or critical indicators from each of the five categories. The relevant hydrogen paragraphs were the only units which were coded according to the five categories. They were coded as having an optimistic indicator, a critical indicator, or no indicator for each of the five categories.

Since the paragraphs were being studied as the individual units of observation, no paragraph could be labeled with more than one indicator in any single category, even if it contained multiple sentences, each of which could qualify as a separate instance of the same type of indicator. Therefore each relevant hydrogen paragraph received a score of 1,

0, or -1 for each category corresponding to optimistic indicator, no indicator, or critical indicator respectively.

These counts were then used to conduct statistical analyses regarding the content of the subject being analyzed, which would then be generalized to support broader

130 conclusions. The definition of the categories and the identification of specific optimistic and critical indicators for each was the next step in determining the content analysis procedure used to analyze the three sources. The categories may be broad or narrow but they were designed to be mutually exclusive of one another so that the same set of text cannot be used as an indicator in two different categories. An initial examination of the speeches and press releases made available by the Bush administration identified the five categories based on the repetition of statements regarding the hydrogen economy that were frequently contested in the academic journals. The categories identified are: 1) the emission of greenhouse gasses; 2) the efficiency of hydrogen systems; 3) the sustainability of hydrogen production; 4) the viability of sequestration paired with hydrogen production from fossil fuel sources; and 5) the sources used as feedstock or as a primary energy source for hydrogen production. These five categories for hydrogen analysis represent a broad array of contested issues regarding the net environmental benefit of utilizing hydrogen as an energy carrier.

For the purposes of this dissertation the focus of these categories was intentionally on the environmental impact of hydrogen technology rather than the economic or societal effects, though similar lists of indicators could be developed to examine the issue from economic, security, or equity positions as well. This was purposefully done because the environmental impacts from the adoption of hydrogen technology, as it performs currently as well as how it may perform in the future, are far less subject to assumptions and projections and instead can be weighed on well-known values (Barbir, 2009). The following paragraphs describe each category in greater detail and define the requirements for statements to be qualified as optimistic or critical indicators in each.

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The first category, the emission of greenhouse gasses, was the first to be identified. The Bush administration frequently touted hydrogen as being “emission free” or as “emitting only water,” a quality which is only true if the hydrogen was produced through electrolysis using carbon free electricity (Hammerschlag, 2005; Hodson and

Marvin, 2006; Lokey, 2007, Lokey, 2007a; Barbir, 2009). This is a claim that was repeated many times in all three sources. Alternatively, a number of claims were made, particularly in Energy Policy, that hydrogen would produce greater levels of greenhouse gasses than conventional energy sources (gasoline for transportation or grid-delivered electricity for stationary), but once again this is only true in certain circumstances, such as when the hydrogen is produced from coal or electrolysis from grid-based electricity.

 The optimistic indicators are defined as a statement that claims the use of hydrogen produces no carbon dioxide, or no emissions of any kind, without a qualifier indicating the reliance of zero-carbon hydrogen on the primary energy source and feedstock.

 The critical indicators are defined as any statement that claims the use of hydrogen produces carbon dioxide, or emissions of any kind, at levels higher than that of conventional sources of energy without indicating the dependence of carbon dioxide and other emissions on the primary energy source and feedstock used to generate the hydrogen.

 If a relevant hydrogen paragraph does not meet the criteria for either the optimistic indicator or the critical indicator then it is labeled ‘no indicator’.

The second category, the efficiency of fuel cell systems, was selected due to the wide range of opinions expressed regarding the efficiency of hydrogen as an energy carrier. Much of this confusion has arisen due to the high efficiency of the fuel cell compared to many conventional engines and generators. The fuel cell is an electrochemical device and hence is not subject to the same limits on efficiency as those based

132 on thermal expansion from combusting fossil fuels (Agbossou, 2003; Ren, 2013).

However, those who make an efficient hydrogen claim typically ignore the fact that hydrogen is an energy carrier and that multiple steps are required for the production, distribution, and storage of the hydrogen before it is used in the fuel cell, each of which costs energy and lowers the efficiency of the whole process. Claims of inefficient hydrogen are inaccurate for the opposite reason, with the authors focusing on a single production method for hydrogen, or only considering a single conventional energy use to compare the hydrogen efficiency to which may not be representative of the entire field of energy services to which hydrogen might be applied.

 Optimistic indicators for this category are defined as statements that claim hydrogen will be more efficient than conventional energy sources, but which makes no mention of the process by which the hydrogen is produced, distributed, and stored and the energy costs associated with these steps.

 Critical indicators for this category are defined as statements that claim hydrogen will be less efficient than conventional technologies but which do not consider the efficiency all of the different supply chains by which hydrogen might be produced and how the well-to-end use efficiencies of different conventional energy services might compare.

The third category, the sustainability of hydrogen production and use, refers specifically to the ability of society to use hydrogen on an on-going basis without the accumulation of negative effects that would eventually force the end of hydrogen use.

Hydrogen is an element and is neither created during the production of hydrogen gas nor destroyed during its use in a fuel cell. Instead it undergoes a chemical transformation and is either liberated from a hydrogen-bearing molecule during production or combined with oxygen to form water during use. Since the production of water during the use of hydrogen is sustainable, the production phase is where sustainability issues may arise,

133 particularly when concerning the source molecule that the hydrogen is to be liberated from (Ren, 2013; Han, 2013).

Most hydrogen today is produced from natural gas, and many have proposed using coal as the primary source of hydrogen in the future (Barbir, 2009; NAS, 2004). As fossil fuels, neither of these sources could be considered sustainable. Alternately, hydrogen derived from biomass or electrolysis using renewable electricity is sustainable

(Barbir, 2009; Ren, 2013). Typically positive or negative indicators for this category will only mention a single source of hydrogen or will not mention a source at all.

 Optimistic indicators for this category are defined as statements that claim hydrogen will be sustainable, but which does not differentiate between the various primary feedstocks from which the hydrogen can be split.

 Critical indicators for this category are defined as statements that claim hydrogen will be unsustainable, but which do not differentiate between the various primary feedstocks from which the hydrogen can be split.

The sequestration of carbon during the production of hydrogen is the fourth category. The viability of sequestration is a question which impacts on many areas of energy policy, not just the development of the hydrogen economy. Sequestration is especially important for the potential future of coal based power generation as the only viable means of reducing the high carbon content of the fuel and removing it from the waste streams. Sequestration is frequently paired with descriptions and evaluations of hydrogen energy because the Bush administration funded many programs designed to develop and demonstrate methods for producing hydrogen through coal gasification coupled with sequestration (DOE, 2003, Lokey, 2007; McDowall, 2012). Currently carbon capture and storage is an unproven technology, which could potentially be

134 coupled with hydrogen production to drastically reduce emissions. Thus far, however, the technology has not been demonstrated on a sufficiently large scale or been applied to other than a few demonstration projects to definitively say whether or not carbon sequestration is an effective and sustainable means of reducing greenhouse gas emissions

(Lal, 2009; Yang and Ogden, 2013).

 Optimistic indicators for this category are defined as statements which claim that emissions of greenhouse gasses for the production of hydrogen will be negligible due to the utilization of carbon capture and sequestration but which does not mention the uncertainty regarding the long term viability of the unproven technology.

 Critical indicators for this category are defined as statements which consider carbon sequestration but which claim that the technology will not lead to long term reductions in greenhouse gas emissions due to the impermanence of storage, the energy costs of sequestration, or the high economic costs.

The source of the hydrogen is the final category to be considered. Many press releases, speeches, and article only refer to a single method of producing hydrogen when discussing the positive or negative aspects of the energy carrier. Currently hydrogen is primarily produced from the steam reformation of natural gas, but in the future there are a broad array of options for the primary feedstocks and energy sources used to create hydrogen (NAS, 2004; Ren, 2013; Hwang, 2013). By only referencing a single source for hydrogen, the speaker or author can effectively paint hydrogen critically or negatively on a large number of different aspects depending on their goals (Hodson and Marvin, 2006;

Lokey, 2007).

Since the actual future source of hydrogen is unclear, any assessment of the future impact of hydrogen based on an evaluation of a single source is likely to be misleading unless it clearly states that there are many options which could be chosen and the various

135 strengths and weaknesses of each. The Bush administration policies envisioned a future where hydrogen from natural gas slowly gave way to a mixture of sources, including some renewables, but which was largely reliant on production of hydrogen via coal gasification (DOE, 2003; Yang and Ogden, 2013).

 Optimistic indicators for hydrogen source are statements which only refer to the use of renewable energy sources and feedstocks to produce hydrogen in the future. These statements will not consider the possibility that hydrogen could continue to be produced from fossil fuels for the foreseeable future.

 Critical indicators for hydrogen sources are statements which refer only to the continued production of hydrogen from fossil sources and which do not consider the possibility of creating hydrogen through biomass or electrolysis using renewably generated electricity.

With the definitions for the indicators set, the text for all three sources was coded and each unit of observation (each paragraph) was given a positive or negative score in each category indicating optimistic or critical constructed narratives. The thesis of the dissertation suggests that The New York Times would be responding to the information provided by the Bush administration message by replicating his message in their articles in the months that followed, making the values generated for The New York Times the dependent variables and the values found in the Bush material the independent variable.

The values that were generated for Energy Policy were also considered as an independent variable but the thesis suggests that they will only act to influence The New York Times values when they increase their organization in response to the message put forth by the more powerful Bush administration.

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Independent

Figure 4- Flow Chart of Methodology, Example Graph

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Once each of the three data sets had been coded for the presence of optimistic and critical indicators it was necessary to aggregate this information into indices that would produce a data point for every day of the Bush administration’s term in office. A separate index was created for each category of indicator within each of the three sources, which would allow them to be analyzed independently of each other or combined to evaluate a broader consideration of the topic. These indices were created by summing the indicators that occur within 6 months of any given date within each category for each source. Thus, for each source, five indices representing each of the indicator categories were created with a data point for each day between 2001 and 2008.

The six month time frame for summing the indicators was developed by performing regressions analyzing each individual month up to 12 months earlier for predictive value within the independent variables. While the predictive value of a single month never approached that of the combined 6 month period, moderate correlation (R2 >

0.1) was typically seen for months 1-6 which then severely dropped in the following months (R2 < 0.05). Similarly, different time frames were considered for the dependent variable aggregation, ranging from1 month to a full year after each date examined and the strongest correlations arose when considering the 6 month time frame matching the period considered for the independent variables.

Since the independent variables, Bush and Energy Policy, are the causative factors according to the hypothesis, the indices for each date for these two sources summed the values of each indicator produced in the prior six months. This value represents the tenor of the information provided to that date by each source representing their overall optimistic or critical viewpoint of hydrogen in the recent past in regards to that particular

138 indicator category. In order to determine the predictive value this information then has for

The New York Times, the aggregated indices for each date for this source was drawn from the next six months into the future from that date for each category of indicator. This allowed each category of indicator to be analyzed independently along with an analysis that combined the indices from all the categories, representing the overall tone of the hydrogen discourse within each source.

It was necessary to examine a range of dates to form an aggregated score to examine this issue because it is impossible to determine a causative effect or correlation between individual data points. In some cases it may be possible to identify an article which references a specific Bush speech, but in many cases they will be formed from the sum of what had been said to date rather than a specific instance. These date ranges were not chosen randomly, but were selected because each individual month into the future or past was analyzed for correlation and including values beyond these ranges introduced excessive noise which hid any actual effect.

In order to determine the predictive values that each of the independent variables,

Bush and Energy Policy, may have on the dependent variable, The New York Times, it was necessary to perform two types of related analyses: single variable and multivariable regression. Single variable regression only considers the effects of a single independent variable on the dependent variable while multivariable regression considers the competing or cooperating effects from two or more independent variables on the dependent variable. For each of the six indices (five categories of indicators and their combination), a single variable regression was performed for each Bush and Energy

Policy to determine their individual predictive value for the corresponding index from

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The New York Times. Additionally, for each of the six indices a multivariable regression was conducted that included both Bush and Energy Policy in the regression to determine their combined predictive value for the corresponding New York Times index.

One final division of the data sets is necessary, based on the periods of time before, during, and after the release of the special issue on hydrogen by Energy Policy.

The hypothesis stated that a strong effort by the less powerful party may disrupt the dominance of the message promoted by the more powerful party and the special issue on hydrogen appears to have had this effect from the initial observations of the data, with the tenor of The New York Times towards hydrogen noticeably changing during that time frame. Thus all of single and multivariable regressions described above were repeated for each time frame with one set of regressions for the period between 2001 and 2005, one for 2006, one for the period between 2007 and 2008, and one for the entire time span between 2001 and 2008. With three sets of regressions (two single variable and one multivariable) being performed on six indices (the five categories of indicators and their combined index) across four different time frames (2001-2005, 2006, 2007-2008, and

2001-2008) this leads to seventy-two (3*6*4=72) regression analyses from this data set, each of which was examined for relevance. This allows for the identification of important variables as well as those that had little predictive value within each time frame and for each independent variable. This information will be valuable in the analysis of the results in Chapter 5. A full listing of the results of each regression analysis is available in

Appendix B.

A strong correlation, indicated by strong coefficients and a high R2-value, between either Bush or Energy Policy on their own or when considered together would

140 indicate that the articles printed in The New York Times over any 6 month span from 2001 to 2008 are likely to reflect the same opinions towards hydrogen as the source(s) with which they are correlated expressed in the six months prior to that span. While this correlation does not prove causation, it would clearly suggest a strong relationship between the independent dependent variables.

The selected analytical technique, regression, considers a dependent variable and one or more independent variables and calculates an equation that creates a best fit linear equation using the independent variables to match the results seen in the actual data. In a perfect regression analysis all of the variables impacting the dependent variable would be included and with sufficient data points it would be possible to craft an equation that perfectly matched the resulting dependent variable for any combination of the independent variables. Since this is rarely the case, the R-value indicates how closely the generated equation matches the results seen in the data, ranging from 1.00 for a perfect match to 0, indicating no match at all. This value is often presented as R2 and is used to gauge the ability of the generated equation to predict the dependent variable, but does not necessarily indicate the relative impact that each variable will have compared to the others. This can be determined by the coefficients that are assigned to each of the variables.

If the scale of magnitude seen in each of the variables is comparable then the relative size of the coefficients determines their impact, though regardless of the scale these coefficients still represent the weight given to these factors. In addition to the coefficients, the standard error and the P-value also help indicate the statistical validity of including the variable in the equation. If the standard error is less than the coefficient for

141 that variable then the variable should be removed. Additionally, an alpha-value should be set prior to the test to decide the degree of confidence desired that the results did not arise by chance. Typically this alpha level is set at 0.05 and this is what will be used for this analysis, indicating a 5% chance that the results could arise by chance rather than by true correlation. The P-value generated during the multivariable regression should be less than the alpha-value for each variable or it should be removed from the analysis.

4.4 Analyzing the Potential Outcomes

This analysis had the potential to yield several possible outcomes, depending on what correlations were discovered, if any. Support for the thesis would be found if the past information provided by the Bush administration consistently reflected the future response from The New York Times producing a statistically identifiable skew in the distribution of indicators and a strong R2 and for the regression analyses and high coefficients for the Bush variables, as determined through the single variable and multivariable regression showing the strong correlation between the two indices, while a lower coefficient is generated for the Energy Policy variable, indicating a weak or no correlation. Additionally, a clear discrepancy between the information produced by the

Bush administration and that produced by Energy Policy should be shown. The thesis would suggest that the Bush administration would express a consistently optimistic position while that seen in Energy Policy would be more balanced with both optimistic and critical indicators present to a certain degree. The thesis also suggests that the less powerful source may be able to temporarily have their position reflected by The New

York Times if an extraordinary effort were made and their level of organization increased.

If such a scenario were to occur then the position found in The New York Times would be

142 temporarily influenced by the past positions of both the Bush administration and Energy

Policy, although the weight given to each would be uncertain. Each of the 72 regression analyses were examined to determine if a stronger correlation was found with Bush than with Energy Policy for each indicator in each time frame.

Several outcomes could arise that would not support the thesis. One possible result would be that no statistically identifiable skew in the distribution of the indicators were found at all. In this circumstance it would be possible that sourcing were occurring, but that the span of time between when the source information was provided and when the resulting news story was published is so varied that a correlation cannot be shown.

Alternately, it could mean that sourcing was not occurring at all and that other variables dictated the tone of The New York Times’ articles. It would be difficult to distinguish between these two scenarios, however, unless the other variables could be identified and a correlation shown statistically. One outcome that would clearly refute the thesis would be if The New York Times was found to have a strong statistically identifiable correlation with Energy Policy and not with the Bush administration and that the Bush administration message differed from that promoted in the other two sources. This would suggest that

Energy Policy had greater influence over the future content of The New York Times than the more powerful Bush administration, or at the very least that The New York Times content was dictated by scientific analysis rather than political sourcing.

This methodology attempts to show a statistically identifiable correlation between the optimistic indicators that can be found in the Bush administration and the indicators that later were published in The New York Times, which would serve as a counterpoint with the more critical message found in Energy Policy. This analysis would be impossible

143 without some level of aggregation, as direct correlation between any individual press release or speech and later New York Times articles would be very difficult to prove in most situations. By relying on the past information produced by the two independent variables and looking for correlation to the future response of the dependent variable, the thesis can be tested using statistical analyses, providing mathematical support for the argument that sourcing is occurring and that the Bush administration was able to use sourcing to promote an optimistic view of hydrogen despite criticism present in the academic community, represented by Energy Policy.

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Chapter 5

RESULTS

This chapter will serve to describe the results of applying the methodology from the previous chapter to the three sources. The overall results confirmed the thesis and showed that a strong, statistically identifiable correlation existed between the past hydrogen message promoted by the Bush administration and the message in the stories that then appeared in The New York Times for most of the period of time between 2001 and 2008 and a much weaker correlation to Energy Policy. While there is an exception to this relationship beginning in 2006, this corresponds to the publication of a special issue of Energy Policy that was largely critical of the technology and represented the greatest level of attention devoted to the subject by the journal during the timespan examined.

This result fits with the thesis that suggests a less powerful organization may be able to temporarily influence the presentation of the message by the news media by increasing their efforts and organization. The following sections will describe the data that was collected and illustrate the steps by which it was processed to achieve this result.

5.1 The Collecting and Coding of the Data

The raw data for each source was gathered from online resources, which greatly aided the ability to sort and search for the relevant terms. The Bush press releases, transcripts of speeches, policy papers, and interviews are available through the George W.

Bush Presidential Library. The New York Times archive was accessed via a web-based

145 subscription. The Energy Policy articles were accessed via University of Delaware’s electronic library resources. Each of these online databases had integrated search engines which allowed the relevant material to be sorted out with ease. A copy of each article containing either of the search terms “hydrogen” or “fuel cell” was saved locally.

In terms of enumerable units of analysis the press releases and other materials from the Bush administration produced 97 articles that mention hydrogen or fuel cells.

These articles contained 4,196 total paragraphs of which 237 paragraphs mention hydrogen or fuel cells and 97 paragraphs where the mention of hydrogen is relevant to one of the five categories. The search of The New York Times material produced 275 articles that mention hydrogen. These articles contain 6,758 total paragraphs of which

1,168 paragraphs mention hydrogen and 221 paragraphs where the mention of hydrogen is relevant to one of the five categories. The search of Energy Policy produced 266 articles which mention hydrogen. These articles contain 14,748 total paragraphs of which

2,440 paragraphs mention hydrogen and 503 paragraphs where the mention of hydrogen is relevant to one of the five categories. Each of the paragraphs that included a reference to hydrogen or fuel cells as well as mentioning one or more of the five categories was coded for the presence of optimistic or critical indicators for each of the five categories.

To code the relevant hydrogen paragraphs, each one was read by the researcher. If the paragraph did not pertain to any of the categories then they were automatically given a score of 0, for No Indicators found in that category. Each category that is mentioned was then considered against the criteria for the optimistic and critical indicators that were defined in Chapter 4 for each relevant category. If the statements in that paragraph met the criteria qualifying it as an optimistic or critical indicator, then it was given a score of

146 positive or negative 1, respectively, in that category. Any given paragraph could only be scored a single time for each indicator and was considered as a whole, therefore if a sentence at the beginning of the paragraph would qualify as a critical indicator but a later sentence in that paragraph mitigated that statement with qualifying facts or explanation, then the paragraph as a whole would be coded as No Indicator.

Figure 5 illustrates an example of how a paragraph of text would be coded. This selection is from the 2003 State of the Union Address in which President Bush announced a broad array of support for hydrogen energy. The first and last paragraphs were marked as irrelevant to hydrogen, but the second and third were flagged by the computer for containing the key word “hydrogen”. Both paragraphs contain indicators, and the third contains two. The second paragraph is given a score of +1GHG and the third a score of

+1 GHG and +1 Sources for a score of +2. Even though the third paragraph contains multiple optimistic GHG indicators, the paragraph still receives a +1 for that category.

Figure 5- Example of Coding (Bush Sample)

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The next example, Figure 6, is from “A green hydrogen economy” (Clarke and

Rifkin, 2006) which was published in Energy Policy 34 (17). In this section of text all four paragraphs were marked for containing references to hydrogen and fuel cells. Each was read and it was determined that paragraphs three and four relate to technical details not pertaining to any of the five categories and so they were marked as No Indicator. The first two paragraphs both contained indicators, but while the first paragraph was critical the second paragraph was optimistic. The combined score for this text would be +1, as would the GHG score, but the Sources score would be a 0.

Figure 6- Example of Coding (Energy Policy Sample)

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As each text was coded it was entered into an Excel database for that source, illustrated below in Figure 7 along with identifying and normalization information. This allowed for a separate analysis of the individual categories as well as the total number of indicators. While the author and section information was not used in the analysis, future studies could use this information to look for trends within The New York Times, such as a particular reporter who frequently uses critical indicators while others use a balance of optimistic and critical, or if the Business section is largely optimistic while the Science section is more balanced. This could grant significant insight into the mechanism by which sourcing introduced the information into the news media.

Article Information Total GHG Eff Sust Seq Source Date Title Author Section Opt Pes Opt Pes Opt Pes Opt Pes Opt Pes Opt Pes 1/6/2007 The Land of Rising Conservation; Japan Offers a Lesson in UsingMartin Technology Fackler to ReduceBusiness Energy Consumption0 0 1/25/2007 Energy Research on a Shoestring Clifford Krauss Science 4 0 1 3 2/18/2007 From 0 to 60 to World Domination Jon Gertner Magazine 0 0 2/23/2007 Bush Makes a Pitch for Amber Waves of Homegrown Fuel Edmund L. Andrews Washington 0 0 2/25/2007 Racing to Make the Pit Stops a Little Bit Greener Dave Caldwell Automotive 0 0 3/4/2007 Is the State Selling Its Fuel Cell Business Short? Jan Ellen Spiegel NY/Region 1 0 1 3/6/2007 Venture Capitalists Move From Web to Algae Clifford Krauss Business 1 0 1 3/7/2007 Green Gold, or Just Slime? Clifford Krauss Business 1 0 1 3/7/2007 What's So Bad About Big? Matthew L. Wald Business 0 0 3/14/2007 Start-Up Fervor Shifts to Energy in Silicon Valley Matt Richtel Technology 0 0 3/18/2007 Abu Dhabi Explores Energy Alternatives Hassan M. Fattah World 0 0 3/21/2007 Bush Tours 2 Auto Plants and Talks Energy Policy Matthew L. Wald National 0 0 3/28/2007 The Future of Hydrogen Cars David Pogue Technology 2 -2 1 -1 -1 1 4/1/2007 Latest Alternative Fuel: Gas from Chicken Manure Jan Ellen Spiegel NY/Region 1 0 1 4/4/2007 Solving the Car-Propulsion Problem David Pogue Technology 0 -3 -2 -1 4/15/2007 Airstream: The Concept Travels Well Phil Patton Automotive 0 0 4/15/2007 For Hartford, a Fuel-Cell Bus Milestone Jan Ellen Spiegel NY/Region 1 0 1 4/21/2007 China's Automakers, With Beijing's Prodding, Show Alternative-FuelKeith Bradsher Cars Automotive 0 0 4/29/2007 On the Road, Hope for a Zero-Pollution Car Don Sherman Automotive 3 0 2 1 5/1/2007 Coal's Energy Potential Is An Engineering Challenge Now Matthew L. Wald Science 1 0 1 5/19/2007 A Return to the Land, for Fuel Matt Villano Business 1 0 1 5/20/2007 Home Eco-nomics; The Zero-Energy Solution Mark Svenvold Magazine 0 -1 -1 6/17/2007 The Green Home of Their Dreams Valerie Cotsalas Real Estate 1 -1 1 -1 7/8/2007 The Kremlin Flexes, and a Tycoon Reels Andrew E. Kramer Business 0 0 7/15/2007 Electric Cars Nearly Ready, but Batteries Are Less So Kevin Cameron Automotive 0 0 9/23/2007 GreenTech; They're Electric, but Can They Be Fantastic? Lawrence Ulrich Automotive 0 0 10/24/2007 Getting to Green Micheline Maynard Automotive 0 0 10/24/2007 Challenging Gasoline: Diesel, Ethanol, Hydrogen Matthew L. Wald Automotive 1 0 1 10/28/2007 Go Green, Someday, For Now Go Fast Jerry Garrett Automotive 0 0 11/7/2007 The Carbon Calculus Matthew L. Wald Business 0 0

Figure 7- Sample of Coding Results Figures 8 to 10 represent the total number of optimistic and critical indicators that were counted from each source in each month. Figure 8 presents this data in its raw form, without any normalization at all. At this level there is not much that can be able to be

149 determined due to the large differences in the amount of enumerable material in each source, which may lead to little visible correlation between the three sets other than to note how each of the three balances their presentation of hydrogen information. While this level of information will provide a great deal of insight into the individual sources, variability in the volume of each source material will render the indicator counts by themselves relatively useless for the purposes of determining any correlation between the three.

20 10 0 -10

-20 2001Jan

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2002January 2003January 2004January 2005January 2006January 2007January 2008January -40 -50 -60 -70

Bush Optimistic Indicators NYT Optimisitc Indicators NYT Critical Indicators EP Optimistic EP Critical

Figure 8- Timeline of Incidence of All Indicators The clearest trend that can be seen is that the Bush administration is nearly universally optimistic in regards to the hydrogen economy. Coding of the Bush administration material yields a total of 149 instances when optimistic indicators were used and only a single instance of a critical indicator. By comparison, a similar analysis of Energy Policy showed the use of 256 optimistic indicators and 298 critical indicators, a far more balanced position. The New York Times is not as universal in their praise of hydrogen as the Bush administration, however with 216 optimistic indicators used and

150 only 47 critical indicators used this surface analysis suggests that The New York Times overall tone more closely reflected the message of the Bush administration.

Figure 9 takes the data from Figure 8, the absolute count of the combined optimistic and critical indicators, and normalized by dividing the combined number of optimistic and critical indicators in any month by the number of paragraphs mentioning hydrogen in that month. This level of normalization weeds out the paragraphs in an article which may have nothing to do with hydrogen or hydrogen technology by determining the rate of incidence of optimistic and critical indicators in paragraphs where hydrogen is actually being discussed. This shows what the correlations predicted by the thesis would appear like: peaks indicating a spike in the incidence of optimistic indicators from the Bush administration appearing in close proximity to peaks showing optimistic indicators in The New York Times. Accordingly the optimistic or the critical indicators from Energy Policy would not cause correlating peaks in The New York Times data.

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Figure 9- Timeline of All Indicators, Normalized by Relevant Paragraph Count

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Figure 10 shows the same data as in Figure 9, except it is the three month average of the rate of incidence of indicators that is being tracked rather than the rate of incidence for each specific month. This format allows for an easier visual inspection of the data and also helps to account for any delays between the appearance of indicators in either the articles from Energy Policy or the Bush administration and their induced appearance in

The New York Times. Examining this figure reveals a large number of incidences where peaks in optimistic indicators by Bush are replicated by peaks in optimistic indicators in

The New York Times. This data seems to show that a correlation is occurring between the

Bush optimistic indicators and The New York Times optimistic indicators. This would be highly indicative of Chomsky’s tenet of sourcing at play, with The New York Times essentially repeating the views of the administration while ignoring the information being presented by the scientists, policy makers, and other energy experts.

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Figure 10- Timeline of All Indicators, Norm. by Relevant Para, 3 Month Ave

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Similar figures displaying the indicators for each of the five individual categories are not included due to the relative lack of utility in the information to be gathered from them.

While these graphs are effective at demonstrating the effects that were predicted by this research, they do not provide an adequate foundation for a quantitative analysis that would determine the exact levels of correlation between the sets and the statistical significance of any coefficients. Specifically, this analysis does nothing to imply causation as it examines monthly aggregations and does not consider the effects from material before that month nor does it consider how impact from the source information might be felt in the months following. Further, this aggregation in many instances compares data points from the independent variables that occur in the end of a month to data points in the dependent variable which happened at the beginning of the month, which would make causation impossible. In order to further analyze this data a more rigorous quantitative statistical method of analysis must be applied to the data in order to calculate the correlation between Energy Policy or the Bush press releases and The New

York Times’ reporting of optimistic or negative hydrogen indicators.

5.2 Conducting the Single and Multivariable Regression Analyses

The first step in conducting the statistical analysis was to combine the databases of indicators for each source into a single spreadsheet. This spreadsheet was arranged so that a row was labeled for each day of the year for each year from 2001 to 2008. The articles and texts from each source were assigned a group of columns and the articles from that source were spread vertically throughout those columns so that they aligned with the row associated with their date of release. This is illustrated in Figure 11.

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New York Times Bush Administration Energy Policy Title Author Title Title Author 5/21/2005 Dirty Secret: Coal Plants Could Be Much Kenneth 5/22/2005 Cleaner Stier 5/23/2005 5/24/2005 Fact Sheet: Developing Clean and Secure Energy 5/25/2005 Through Hydrogen Fuel President Tours Hydrogen Fueling Station, 5/26/2005 Discuss Research 5/27/2005 5/28/2005 5/29/2005 5/30/2005 Modelling long-term oil price and extraction with 5/31/2005 a Hubbert approach: The LOPEX model Rehrl Energy for sustainable development in Malaysia: 6/1/2005 Energy policy and alternative energy Rahman Emissions from distributed vs. centralized generation: The importance of system 6/2/2005 performance Strachan Japan Squeezes to Get the Most of Costly James 6/3/2005 Fuel Brooke Honda FCX: What a Gas! A Week in Suburbia Jim 6/4/2005 With a Hydrogen Honda Motavalli Jim 6/5/2005 Putting the Hindenburg to Rest Motavalli 6/6/2005 6/7/2005 President Discusses Strengthening Social 6/8/2005 Security in Washington, DC 6/9/2005 6/10/2005 6/11/2005 President's Radio Address Figure 11- Preparation for Analysis: Chronological Arrangement of Article and Other Texts

Figure 12- Preparation for Analysis: Aggregation of Indicators to Create Indexes

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Hidden from view in this figure are the columns of information showing the optimistic and critical indicators for each source (shown in Figure 12, above), however this information is still linked to each entry. The methodology calls for an aggregated index for each source for each of the five categories as well as an index combining them wherein a data point is generated for each day of the Bush presidency. The data point for each day in the index for the source is equal to the sum of the critical and optimistic indicators within each category appearing in that source in the past or future six months and this format allows these figures to be quickly generated.

Figure 13 shows the indices representing the combination of indicators from all five categories for all three sources across the entire span of the Bush presidency. This visualization is useful since it is possible to see that for much of the time span analyzed the Bush index does appear to closely match the index generated for The New York

Times. This indicates that there should be a strong statistical correlation between these two indexes. However, this figure also shows why an initial analysis showed a low correlation between the Bush sources and The New York Times when examined over the full 8 year span. In 2006 the Bush administration index reaches its highest levels of optimistic indicators, but during this time The New York Times response index remains remarkably balanced and seems relatively unaffected by the increase in optimistic indicators. This can be seen to correlate with the most significant level of criticism seen from the Energy Policy index, which reached these extreme levels due to the publication of the special issue on hydrogen at this time, which was highly critical of the technology.

While the effect of the critical special issue of Energy Policy focused on hydrogen may damage the statistical correlation between the Bush index and The New York Times

155 index, these finding are within the possibilities suggested by the thesis. A less powerful actor may interrupt the influence of sourcing temporarily if additional efforts of organization and outreach are made. Through the publication of this special issue devoted to a critical analysis of hydrogen, the academic community may have been able to temporarily negate the sourcing effects from the Bush administration, leading to a balanced treatment of the hydrogen economy in The New York Times.

Figure 13- Timeline of Indexes for Each Source

To confirm these findings the data was split into three sections consisting of the period of time prior to the publication of the Energy Policy special issue on hydrogen

(2001-2005), the year in which the special issue was published (2006), and the two years that followed (2007-2008). According to the thesis a strong correlation between Bush and

The New York Times would exist during the first period and a low level of correlation would exist between Energy Policy and The New York Times. During the middle period both independent variables would influence the results seen in The New York Times and

156 so the correlation between each and The New York Times should be similar in strength. In the final period of time it was expected that The New York Times would return to a discussion of hydrogen that was correlated to the information released by the Bush administration while the influence of Energy Policy would correspondingly decrease. A full list of the data used may be found in Appendix A.

5.3 Results of the Methodology

The first statistical analyses that were performed were single variable regressions to determine if either the Bush indicators or the Energy Policy indicators would serve as useful predictors for the indicators that would later appear in The New York Times when considering the entire length of the Bush presidency. The results of these twelve regressions can be found summarized in Figure 14 under Bush and EP (Energy Policy), with the highlighted figures showing no statistical value. The primary statistic to examine is the R2 value for each of the indices, which serves as a measure of the value of that category of indicators as a predictor for the indicators that would then be found in The

New York Times. In order to gauge the relative weight and significance of each of these sources a technique known as linear regression was used which generates a best fit equation for the data based on independent variables [f(x,y) = a*x + b*y + c, where a, b, and c are all constant coefficients generated by the regression. Each variable also generates probability statistics indicating the importance and significance of the resultant equation and the individual coefficients.

Since an R2 value of 1 indicates a perfect correlation and a score of 0 indicates no correlation, it becomes readily apparent that neither the Bush administration’s nor Energy

Policy’s indicators are very useful on their own when predicting the response from The

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New York Times when considering the entire span of time, with the highest R2 value coming is at 0.200 when considering the combination of the Bush indicator categories, which indicates that there is a correlation, just a very weak one, and with the R2 value for the combination of the Energy Policy indicator categories nearly equaling that for the

Bush administration combination of categories with a value of 0.172. This result is not surprising as the thesis posited that a shift which of these sources would drive the appearance of indicators in The New York Times after the publication of that special issue. This would cause neither of the two sources to be effective predictors on their own when spanning the period of time before and after the publication of that special issue on hydrogen as one would be an effective predictor in the period before and the other in the period after.

However, a multivariable regression would consider the effects of both of the variables across this span of time and the results of this analysis, also seen in Figure 14, show that the combination of the two independent variables leads to an equation that serves as a much better predictor of the indicators found later in The New York Times, with an R2 value of 0.540, which is markedly higher than the R2 value for either Bush or

Energy Policy taken individually as the independent variable. While this does not show a perfect correlation, it does suggest that both independent variables are important at different point within the time span considered, findings that are consistent with the thesis of this research.

Additionally, it is possible to begin considering the impacts of the individual categories of indicators as well. For example it can be seen that the Bush indicators for

Sustainability and Sources were more likely to predict the response in The New York

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Times than the corresponding indicators in Energy Policy, but for the indicators of

Greenhouse Gasses and Efficiency the opposite was found to be the case. Also, the indicators for Sequestration proved to be the weakest predictor for both independent variables, indicating that this particular topic was less of a consideration in terms of sourcing by the news media.

All Multi Bush EP R2 Intercept BushCoef EPCoef R2 Intercept BushCoef R2 Intercept EPCoef Total 0.540 5.924 0.420 0.368 0.200 6.247 0.294 0.172 9.666 0.249 GHG 0.178 4.344 0.148 0.249 0.078 4.520 0.184 0.129 5.056 0.278 Eff 0.193 0.030 0.330 0.134 0.002 -0.246 0.065 0.153 0.093 0.111 Sust 0.182 2.413 0.413 0.476 0.131 2.246 0.454 0.075 3.070 0.574 Seq 0.075 0.624 0.080 -0.059 0.004 0.513 0.041 0.059 0.690 -0.053 Sources 0.194 0.309 0.308 0.135 0.112 -0.009 0.223 0.017 0.523 0.055 Figure 14- Summary of Regression Results: 2001-2008, highlighted values statistically insignificant To compare the relative importance of each independent variable in a multivariable linear regression is necessary to standardize the variables prior to performing the regression. This is necessary as the impact of each variable as dictated by the equation generated by the regression is dependent on both the magnitude of the variable in question as well as the size of the coefficient. An independent variable with large magnitude and a low coefficient may be just as impactful as an independent variable with a low magnitude but a high coefficient.

Standardized coefficients result from performing a regression on standardized values for each variable, which consider the mean and the standard deviation of each to convert them into measures of the number of standardized deviations each data point is from the mean. While this regression yields little other useful information, it is the only means of directly comparing the impact of multiple independent variables in a linear regression. Figure 15 shows the standardized coefficients for the multivariable

159 regressions performed on each time period and will be referenced in the following sections describing the results. When considering the entire 8 year period, the standardized coefficients for Bush and Energy Policy were 0.638 and 0.613 respectively, showing that these independent variables were comparable in terms of apparent impact on The New York Times over the entire timeframe examined.

Standardized Coefficients 2001-2008 2001-2005 2006 2007-2008 Bush 0.638 0.772 0.774 0.216 Energy Policy 0.613 0.107 1.223 0.785 Figure 15- Standardized Coefficients When a separate statistical analysis was performed for each of the three periods of time (pre-, post-, and during the year of publication of the special issue on Hydrogen by

Energy Policy) the results agreed with what was expected given the thesis. Until Energy

Policy released their special issue on hydrogen the policy the discussion on hydrogen in

The New York Times has a high correlation to the message promoted by Bush in the months prior. As the Bush administration adopted a highly optimistic view of the technology, this translated into an overly optimistic evaluation of the technology in The

New York Times, which frequently seemed to be a direct response to the Bush message.

This effect was only interrupted due to the extraordinary effort of Energy Policy, whose critical statements of hydrogen seemed to have no influence until the special issue on hydrogen, which raised the profile of their message and resulted in a more balanced presentation of the technology for a short period of time. However when this effort was not continued, the effects began to fade and the message promoted by The New York

Times began to revert to one predicted by the Bush administration’s talking points.

Figure 16 shows the index for each of the three sources for the period of time before the publication of the special issue on hydrogen. As the Bush and Energy Policy

160 indexes rely on the prior six months of data, this data begins in July of 2001. Visual examination shows that the Bush and New York Times index follow each other closely and a statistical analysis using linear regression shows a high level of correlation with an

R-value equal to 0.82 when considered on its own. A similar exercise using the Energy

Policy index rather than the Bush index shows a much lower level of correlation (R-value equal to 0.43), which supports the thesis of this dissertation. Figure 17 illustrates the linear relationship between the Bush and New York Times indexes with a scatter plot.

Figure 16- Timeline of Indexes for Each Source, 2001-2005 For the period of time between July 2001 and December 2005 the multivariable regression analysis returned results that were highly supportive of the hypothesis, that during this time there would be a high degree of correlation between the Bush index and the NYT index while a much lower correlation would be seen between Energy Policy and

The New York Times. The results of this analysis can be seen in Figure 18. The regression

161 analysis generated the equation: NYT Index = [0.61 * Bush Index] + [0.10 * Energy

Policy Index] + 5.16.

Figure 17- Scatterplot of the Bush Index vs. the NYT Index, 2001-2005 This equation had an R-value of 0.82 and an R2-value of 0.68, indicating that there is a high degree of correlation between the actual data points and the line that is described by this equation, indicating that this is an accurate representation of a true correlation between these variables. It can be seen by the standardized coefficients for this time period in Figure 15 (0.772 for Bush and 0.107 for Energy Policy) that any information provided by the Bush administration is a better predictor of The New York

Times. Since both coefficients significantly exceed the standard error and since the P- value for each coefficient and the intercepts are below the alpha level of 0.05, this indicates that all of these factors are significant and that it is highly unlikely that this relationship arose by random chance rather than as evidence of a true correlation between the indexes.

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Figure 18- Combined Multivariable Regression Statistics for Pre2006 The full set of the results of the regression analyses preformed for the period of time between 2001 and 2005 can be seen in Figure 19. It is important to note that the higher R2 value for the multivariable regression of the combined indicators for this time period is largely driven by a substantial increase in the predictive power of the Bush indicators, while the predictive power of the Energy Policy indicators remains low. This can be seen in the relatively high standardized coefficient given to the Bush variable in the multivariable regression as well as in the high R2 value seen in the combined Bush indicator single variable regression and the comparably lower R2 value seen for Energy

Policy in the corresponding single variable regression.

These results show that, in the period prior to the publication of the special issue on hydrogen by Energy Policy, the Bush indicators served as good predictors of the tone that would be published in The New York Times, while Energy Policy has substantially less predictive capabilities during this time period. This is exactly the result predicted by the thesis for the period of time prior to the publication of the special issue. Additionally, it can be seen during this time that three of the variables in particular, Greenhouse

Gasses, Sustainability, and Sources, are the primary indicators that serve as drivers for sourcing for The New York Times from the Bush administration, while the Energy Policy

163 indicators show weaker predictive value across the board. Once again, the Sequestration indicator did not serve as a predictor for either source.

Pre-2006 Multi Bush EP R2 Intercept BushCoef EPCoef R2 Intercept BushCoef R2 Intercept EPCoef Total 0.676 5.160 0.608 0.097 0.666 4.810 0.643 0.183 10.362 0.389 GHG 0.246 5.127 0.254 0.144 0.233 4.943 0.334 0.180 6.020 0.381 Eff 0.298 0.467 0.372 0.158 0.037 0.207 0.223 0.202 0.543 0.135 Sust 0.551 1.405 1.710 -0.017 0.551 1.412 1.703 0.151 3.071 1.069 Seq 0.031 0.446 0.070 -0.048 0.004 0.377 0.038 0.018 0.491 -0.037 Sources 0.295 -0.380 0.406 0.139 0.259 -0.710 0.436 0.078 0.248 0.202 Figure 19- Summarized Regression Results: 2001-2005, highlighted values statistically insignificant Figures 20 and 21 show the same information as Figures 16 and 17, except they only examine 2006, the year in which the Energy Policy special issue on hydrogen was published. The initial visual analysis of this section indicated that The New York Times index was no longer closely following the Bush index, but instead seemed to represent a balance between the Bush index and the Energy Policy index. A crude means of visually examining this and to visually display this information was to add the Bush index and the

Energy Policy index together, which is seen in Figures 20 and 21. While this method cannot show statistical support for the thesis, it does indicate that the pattern of behavior dictating the presentation of hydrogen topic in The New York Times substantially changed in 2006. Individually, neither the Bush index nor the Energy Policy index showed a high degree of correlation with The New York Times index during this period, which was reflected by very low R-values.

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Figure 20- Timeline of Indexes for Each Source, 2006

Figure 21- Scatterplot of Bush Index vs. NYT Index, 2006

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In order to determine the nature of the new relationship and to determine if a correlation could still be determined between the independent variables and the dependent variable, multivariable linear regression was once again conducted on the three data sets, the results of which may be seen in Figure 22. For this dataset the best fit equation between The New York Times and the other sources was: NYT Index = [0.18 *

Bush Index] + [0.26 * Energy Policy Index] + 7.94. The equation had an R-value of 0.77 and an R2-value of 0.60, which indicates a decreased correlation compared to the equation that was calculated during the regression for the 2001 – 2005 period, but which is still statistically significant and an indicator of a positive correlation between the dependent and independent variables.

Regression Statistics Multiple R 0.773783088 R Square 0.598740267 Adjusted R Square 0.596523363 Standard Error 2.070146709 Observations 365

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 7.935107724 0.215400584 36.83884028 1.622E-124 7.511514115 8.358701334 Bush 0.180185179 0.012648683 14.24537108 7.20519E-37 0.155311054 0.205059305 EP (Balance) 0.256582104 0.011398663 22.50984208 8.51032E-71 0.234166191 0.278998018 Figure 22- Combined Multivariable Regression Statistics for 2006

What is particularly of note in this set of statistics is to note how the standardized coefficients, as seen in Figure 15, have changed in this period as compared to what was seen previously. While in the pre2006 data set the standardized coefficient for the Bush index was significantly larger than that for Energy Policy, in this time period the standardized coefficient for Energy Policy is nearly double the coefficient for Bush

(0.774 Bush vs 1.223 Energy Policy), giving the Energy Policy index significantly more weight than the Bush index. While the coefficients for both of these indexes is lower than

166 that seen for the Bush index in the pre2006 period, the standardized coefficients indicate that they are statistically significant and that Energy Policy influences The New York

Times index slightly more than Bush.

The full set of statistics for the regression analyses performed on this time span may be seen in Figure 23. It is easy to see in this set of regressions how dramatically the situation has changed regarding the source with the best predictive power. When looking at the combined categories of indicators for the Bush administration, is can be seen that the R2 value for this time period has dropped to almost 0, indicating that on its own it has nearly no predictive power for the indicators appearing in The New York Times.

Additionally, the R2 value for the Energy Policy single variable regression of the combined indicators has more than doubled compared to the 2001-2005 timespan and is by far the better predictor of the two.

An examination of the individual categories of indicators shows that for the Bush independent variable, the issue of Sustainability seemed to be the best driver for responses in The New York Times, while for Energy Policy Greenhouse Gasses and

Sources were the primary issues that were passed along to the media. This indicates that some separation occurred between the topics focused on by each source that was later picked up by The New York Times. This also indicates why the multivariable regression returned a substantially higher R2 value than either of the independent variables did on their own. While Energy Policy begins to dominate the overall conversation, particularly in regards to the sources used to generate hydrogen, the Bush administration continued to push the concepts of low or no greenhouse gasses and overall sustainability.

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This makes sense as the arguments made in Energy Policy against hydrogen typically sought to counter the claims of sustainability and low emissions by raising the issue of the source of the hydrogen. So while they did not disagree that hydrogen could be low emissions or sustainable, they focused on a detail that was frequently left out in the creation of the Bush constructed narrative on hydrogen, which is that those qualities are entirely dependent on the source of the hydrogen and that current U.S. policy and practice will not lead to the use of the more benign sources in the near future, instead basing production efforts on the existing fossil fuel industry and infrastructure in an effort to keep initial costs at a minimum.

2006 Multi Bush EP R2 Intercept BushCoef EPCoef R2 Intercept BushCoef R2 Intercept EPCoef Total 0.599 7.935 0.180 0.257 0.037 8.122 -0.045 0.374 9.652 0.128 GHG 0.165 3.620 0.014 0.146 0.101 4.152 -0.069 0.164 3.728 0.129 Eff 0.102 -1.506 0.169 0.035 0.017 -1.714 0.099 0.058 -1.402 0.027 Sust 0.296 1.591 0.173 -0.021 0.295 1.619 0.170 0.030 2.639 0.159 Seq 0.186 1.126 0.109 -0.146 0.003 1.180 -0.039 0.169 1.219 -0.128 Sources 0.394 3.044 0.029 0.167 0.103 2.526 -0.157 0.392 3.137 0.158 Figure 23- Summary of Regression Statistics: 2006, highlighted values statistically insignificant

These results are strongly supportive of the argument in the thesis regarding the ability of a less powerful organization to interject their message through the sourcing effect so that it is considered by the news media. By issuing their special issue on hydrogen they were able to create a sufficiently loud and organized critical response to the Bush administration message to that point that it markedly impacted the presentation of the topic by The New York Times. This effect can be statistically seen in the standardized coefficients generated by the multivariable regression for the two time periods, with the Bush index coefficient dominating the earlier time period but losing

168 ground to Energy Policy dramatically after the Energy Policy special issue on hydrogen and the Energy Policy coefficient rising to account for a larger portion of the results seen in The New York Times index.

This was accomplished even though it occurred simultaneously with the period of maximum optimistic indicators from the Bush administration. As a point of comparison, the correlation between the NYT index and the Bush alone index during this period of time had an R-value of 0.19, indicating almost no relationship at all. The correlation between the Energy Policy index on its own and The New York Times index had an R- value of 0.61, which is indicative that this independent variable had a strong influence on

The New York Times index, but that this relationship is better explained when the impact from both the Bush administration and Energy Policy are considered together.

The final period of time examined consisted of the two years after 2006, when the special issue on hydrogen was published. This consists of the entirety of 2007 but only includes January through June of 2008. Just as the indexes for the Bush administration and Energy Policy are formed from data stretching six months into the past, The New

York Times index is formed from data points up to six months into the future. No data was collected beyond President Bush’s term in office to avoid confounding influences from a new president. As a result, the index stops on the last day for which there was a full 6 months of future data points to sum. Figure 24 shows these indexes plotted against each other over time and Figure 25 shows the linear relationship between The New York

Times index and a combination of the Bush and Energy Policy indexes. Once again, this crude method of adding the indices can visually confirm the suspicions regarding the correlation between them, the exact nature of this relationship and how it differed from

169 the other two time periods was through a multivariable regression analysis, the results of which may be seen in Figure 26.

-5

1/1/2007 5/1/2007 9/1/2007 1/1/2008 5/1/2008 -10

Bush NYT EP Bush + EP

Figure 24- Timeline of Indexes for Each Source, 2007-2008

Figure 25- Scatterplot of Bush Index + Energy Policy Index vs. NYT Index, 2007-2008

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Regression Statistics Multiple R 0.757581055 R Square 0.573929054 Adjusted R Square 0.572362617 Standard Error 3.883164859 Observations 547

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 2.928478384 0.500350683 5.85285178 8.35707E-09 1.945622361 3.911334407 Bush 0.869309211 0.081233234 10.70139848 2.19907E-24 0.70973998 1.028878442 EP (Balance) 0.562287132 0.020773575 27.06742294 7.6864E-103 0.521480886 0.603093378 Figure 26- Combined Multivariable Regression Stats for Post 2006

For this time period, the multivariable regression analysis generated the following formula as the best fit for The New York Times index: NYT Index = [0.87 * Bush Index] +

[0.56 * Energy Policy Index] + 2.93. The R2-value of 0.57 indicates a strong correlation between the data and the best fit line described by the equation, but shows that these variables alone do not explain all of the variability seen in The New York Times index.

The standardized coefficients have dramatically changed, with Bush and Energy Policy indices reversing roles so that Energy Policy is showing a stronger influence on The New

York Times index (0.216 Bush and 0.785 Energy Policy, see Figure 15). Energy Policy coefficient has once again become the dominant factor in the equation, while Bush still plays a significant role, but is reduced in comparison to its strength compared to the Bush index in 2006. Once again, the standard error values and the P-values indicate that the intercept and the coefficients for both variables are statistically significant and should be considered.

The summary of the regression results for the time period from 2007 to 2008 may be seen below in Figure 27. These results show that the Bush indicators on their own serve as a poor predictor of the tone set by The New York Times regarding the five

171 indicators, with only Greenhouse Gasses showing any substantial predictive value.

However, this is countered by a high predictive value for the combined indicators from

Energy Policy in addition to relatively strong R2 values for the individual categories of indicators within Energy Policy. This is likely due to President Bush entering his lame duck period, during which he spoke considerably less on the topic of hydrogen and allowed the conversation to be dominated by others. Once again, Energy Policy seems to have focused on the issues of Greenhouse Gasses and the Sources of the hydrogen, but this also marks the first instance where a discussion of Sequestration seems to have predictive value for The New York Times.

Post-2006 Multi Bush EP R2 Intercept BushCoef EPCoef R2 Intercept BushCoef R2 Intercept EPCoef Total 0.551 2.503 0.683 0.602 0.002 8.454 -0.138 0.510 6.321 0.548 GHG 0.231 1.861 0.485 0.198 0.131 2.062 0.644 0.162 3.183 0.243 Eff 0.077 -0.702 1.180 0.095 0.040 -0.795 0.650 0.000 -0.630 0.008 Sust 0.050 2.214 0.904 0.286 0.020 2.448 0.476 0.003 2.907 0.076 Seq 0.187 0.773 0.069 -0.060 0.012 0.501 0.066 0.174 0.857 -0.060 Sources 0.227 1.300 3.167 0.156 0.037 0.872 3.128 0.190 1.316 0.155 Figure 27- Summarized Regression Results: 2007-2008, highlighted values statistically insignificant

This period is marked by some interesting differences. The previous period was one of extremes, with the Bush index registering its highest level of optimistic indicators and this being opposed by the number of critical indicators presented by Energy Policy.

At the tail end of his term, as he becomes a lame duck, however, President Bush speaks less and less about hydrogen. As a result, the impact of the Energy Policy index is felt to a greater degree and while the Bush index seems to begin to return to dominance early on, as his message fades so does the influence of that index and the push from Energy

Policy becomes increasingly important. However the hypothesis is supported in that the

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Bush index retains a high coefficient in the multivariable analysis, indicating that though

Bush may not have discussed hydrogen as much during this period of time, the indicators he did use regained their potency as predictors for The New York Times and must be considered along with the discussion found in Energy Policy.

5.4- Summary of Results

While the broader implications of these results will be discussed in Chapter 6, this section will briefly summarize the results of the statistical analysis and how those results support the thesis of this dissertation. The thesis posited that energy policy was prone to the phenomena of sourcing described by Herman and Chomsky, which would allow more powerful organizations to influence the messages relayed by the news media about complex subjects, and that the developed methodology would be able to detect and quantify this phenomena. Evidence of this was sought by examining using the treatment of hydrogen during the Bush administration as a case study.

In order for the thesis to be supported by the findings, the methodology needed to be able to show that the language used by the Bush administration to describe hydrogen was optimistic when compared against academics journals’ treatment of the subject.

Additionally, it had to be shown that the optimistic message delivered by the Bush administration was correlated to the tone of the message that was later relayed to the public by the news media. By doing this it can be shown that the Bush administration delivered information with a statistically identifiable skew regarding the potential for the hydrogen economy, especially considering his vision of a coal-fueled hydrogen economy, creating a hydrogen ‘myth’. This message appears to have had a statistically identifiable influence on the articles published by The New York Times, which regularly used the

173 same language and came to similar conclusions in articles that were published shortly after the Bush administration would make their releases available.

While individual examples of direct correlation can be found, where text is replicated directly from the Bush administration to The New York Times articles, it is more useful to consider the combined influence that the multitude of Bush administration releases had on The New York Times over the span of his administration. To this end all three sources were coded for the presence of optimistic and critical indicators to gauge the level of constructed narratives that could be found in any individual article or press release. These indicators were aggregated to create an index with a data point for every day from 2001 to 2008 that is equal to the sum of the indicators from the past 6 months from that date for the Bush administration material or articles from Energy Policy and from 6 months into the future for The New York Times. Thus for each day the index indicates the number of indicators, optimistic or critical, the two dependent variables have created for their message in recent months and comparing that to the message then spread to the public by the news media in the months that follow and looking for a statically identifiable skew to their distribution.

To show that the methodology was working and to support the thesis it had to be shown that the Bush administration promoted an overly optimistic depiction of the potential for hydrogen and that this depiction statistically predicted the depiction by the news media after being released. The data leaves little question that the Bush administration materials showed significant optimistic constructed narratives in their treatment of the potential for hydrogen to reduce environmental impact. The Bush administration materials contained over 150 indicators, but only one of them was critical

174 of hydrogen, and on average 1.2 optimistic indicators was found for every paragraph pertaining to the five categories. By comparison, Energy Policy used 554 indicators and only 46% of them were optimistic. While Energy Policy used indicators overall at a rate of 1.1 per relevant paragraph, similar to the rate used by Bush, they were far more balanced in their treatment of hydrogen technology indicating the advantages of hydrogen but also the flaws that reduce its potential.

To provide evidence suggesting that this optimistic message was a driver for a similar message in The New York Times, it had to be shown both that The New York

Times maintained an optimistic position similar to that seen in the Bush administration, but also that their rate of use of the optimistic indicators was correlated to the rate at which they could be found in the Bush material over the course of his presidency. To show that the overall tone of The New York Times tended towards an optimistic position it can be seen that they used a total of 263 indicators and that 82% of them were optimistic. Like the other two, their rate of use of indicators was 1.1 per relevant hydrogen paragraph, but they clearly were closer in tone to the Bush administration.

To provide evidence that the Bush administration incidence of optimistic indicators was correlated to the optimistic trends seen in The New York Times it was necessary to show that when the Bush administration used a higher amount of indicators over a period of several months that there was a corresponding rise in the optimistic indicators seen in The New York Times in the following months. Using the index created for each source, which gauges the amount of optimistic or critical constructed narratives found in the six months before or after any given date, a multivariable linear regression correlation was conducted which discovered the degree of correlation between the

175 optimistic or critical indexes from the Bush indicators as well as the Energy Policy indicators and those later found in The New York Times. This analysis generated a best fit line with an R2-value of 0.68 and which showed that both the Bush index and the Energy

Policy index had a statistically significant correlation to The New York Times index.

However, the coefficient for Bush index was a factor of 6 greater than that for Energy

Policy, indicating that it was the dominant influence on The New York Times portrayal of hydrogen during this time frame.

One exception to this relationship that was predicted by the thesis was that the dominating influence of a powerful source, such as the Bush administration, could be temporarily disrupted with a high level of organization and concerted effort on the part of the less powerful actors. This can be seen in 2006 when Energy Policy released a special issue devoted to the hydrogen economy that was overall highly critical of the technology and for the span of a year had equal influence with the Bush administration in terms of its index acting as a predictor of The New York Times response index. During this period of time the correlation between the Bush index and The New York Times index decreases dramatically and the correlation with the Energy Policy index increases, becoming the larger influence. The same multivariable regression as used on the data set from 2001-

2005 was used to generate a similar best fit line, though the R2-value of this equations dropped to 0.60, indicating a slightly poorer match between this best fit line and The New

York Times index. This does not negate the relationship but shows that these two variables have less influence than they had before and that other unaccounted for variables are influencing The New York Times index as well. The coefficients show that the influence of Energy Policy more than doubled from the previous period while the

176 influence of the Bush administration decreased to a third its prior level. This is especially notable as this period also marks the highest rate of incidence of optimistic indicators from the Bush administration and critical indicators from Energy Policy and it shows that even though the Bush administration similarly increased their efforts, Energy Policy appears to have been able to shift the balance.

In 2007 and the first half of 2008, much of the attention that hydrogen had been receiving begins to fade. Its largest proponent, President Bush, had entered the lame duck portion of his final term and was no longer promoting hydrogen as vigorously as he had earlier in his presidency. For much of this period neither of the independent variables expressed significant criticism or optimism and this is reflected in a relatively neutral tone within The New York Times. In the final six months the Bush administration says nearly nothing about hydrogen and a moderate level of optimism from Energy Policy is reflected in The New York Times index. According to the thesis, this period should have seen a return to the dominance of the more powerful actor’s message, and this can be seen in the results of the multivariable regression analysis, however the influence of

Energy Policy does not return to pre-2006 levels, but rather remains a significant force in influencing The New York Times index. The R2-value for the best fit line for this time span drops slightly again to 0.57 but is essentially unchanged from 2006. Once again the

Bush coefficient is higher, indicating a greater degree of influence, but the overall low volume of indicators from Bush during this time period allow The New York Times index to be dominated by its correlation to the Energy Policy index, particularly in the last six months.

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The results of the statistical analysis show support for the thesis by confirming the optimism in the material released by the Bush administration and by showing a statistically valid correlation between the incidence of optimism and the incidence of optimistic indicators in The New York Times, a stronger correlation than that seen with the Energy Policy articles. Further, it is shown that these optimistic positions are not replicated in the material generated by Energy Policy during this time span and that only by exerting significant additional effort was the more balanced message promoted by

Energy Policy able to influence the message appearing in The New York Times and even then only as an equal partner with the influence from the Bush administration’s materials.

This shows that the methodology was able to identify distinct patterns of behavior in three different time periods that were capable to identifying different sourcing patterns between the two independent variables and the dependent variable.

Summary of Pre-2006 2006 Post-2006 Regression Results

R2-Value 0.68 0.60 0.76

Intercept 5.15 7.94 2.93

Bush Coefficient 0.61 0.18 0.87

Energy Policy 0.10 0.25 0.56 Coefficient Figure 28- Summary Table of Multivariable Regression Results for 3 Timeframes These findings are consistent with those predicted by the thesis and provide support for the concept that sourcing can have the ability to introduce constructed narratives via the news media in complex issues and that this did occur during the Bush

178 administration regarding the treatment of the developing hydrogen economy. Less powerful actors, such as Energy Policy, can influence this discussion as well, but it requires effort above and beyond the ordinary to temporarily achieve parity with the more powerful source, and the results of these efforts may be short lived unless they are sustained as well. The implications of this research and areas where additional investigations could be useful are explored in Chapter 6.

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Chapter 6

CONCLUSIONS

The thesis of this dissertation was that the public perception of complex policy issues is likely to be the target of sourcing and other attempts to influence the message about the topic that is relayed by the mass media and that a methodology could be developed that would allow for the statistical investigation of the presence of sourcing.

To influence the mass media into relaying a specific message, powerful organizations may construct narratives that favor a particular position using specific language. Stripped of any context that would run counter to the proposed narrative, these facts instead become constructed narratives, or myths, as described by Barthes in Mythologies (1957).

For complex policy issues the facts as reported by the mass media may be the only source of information on that topic that is available to and digestible by the average citizen.

Furthermore, the media is seen as both neutral and trustworthy and so the positions presented within are often accepted undisputed by the average citizen, especially if they are technical in nature requiring specialized knowledge to analyze independently along with detailed data that is not typically provided in a news article. This would allow a powerful and motivated group, such as a government or industry, significant influence over public opinion on that subject matter.

While a number of techniques were discussed by which powerful organizations could propagate these myths through the mass media, the tenet of sourcing from Herman

180 and Chomsky’s model of propaganda (1988) was selected as the subject of analysis.

Sourcing occurs when the pressures of the 24 hour news cycle and shrinking newsroom budgets encourage journalists to seek out large amounts of free, readily publishable material that they can use for their stories. Large, well organized groups, such as the government or corporations, can take advantage of this need by supplying a large amount of free material in the form of press releases, speeches, and other published materials and introducing optimistic or critical constructed narratives through this material.

This dissertation explored the development of a methodology for the analysis of sourcing through the use of a case study examining the treatment of hydrogen by the media during the Bush administration. Hydrogen is a complex technology for a variety of reasons and there was a substantial debate in the research literature during these years regarding the net benefit or cost of a conversion to a hydrogen energy economy. To test the hypothesis, a methodology was developed to examine the presence of optimistic or critical narratives within three sets of text: Bush policy papers, speeches, and press releases; articles from The New York Times 2001-2008; and articles from Energy Policy

2001-2008. If sourcing were present then it would be expected that there would be a correlation between the positions promoted by the Bush administration followed by a similar position being held by The New York Times represented by a statistically identifiable skew in the distribution of indicators. Less of a correlation would be expected with Energy Policy as this information is not tailored for release to the news media and the delays in the timeframe from research to publication create additional uncertainties in the utility of the data in a fast moving news cycle. This relationship would only change if a concerted effort were made by Energy Policy to address this specific issue in a political

181 context and would likely be unsustainable due to the resources required and the actual purpose of the journal.

The results of the analysis clearly show support for the hypothesis. The methodology shows a high degree of correlation between the optimistic indicators used by the Bush administration to promote hydrogen and a replication of those optimistic view points in The New York Times which is statistically shown. At the same time a more balanced view is presented in Energy Policy, but the indicators used by the journal does not have a significant correlation to the positions found in The New York Times until after their special issue addressing hydrogen topics in the context of the contemporary political debate.

While the Bush administration was nearly universally optimistic regarding the environmental benefits of hydrogen, the journal Energy Policy presented both optimistic and critical views and as such was used as the neutral scientific position, which did not follow the same correlation as seen with the Bush materials and the articles in The New

York Times. The only exception to this predicted by the hypothesis was in the presence of an extraordinary, concerted effort made by less powerful actors to draw attention to the misinformation, as was seen in 2006 with the publication of the special issue of Energy

Policy on the hydrogen energy economy. Only after this effort did The New York Times temporarily present information beyond that which was fed to them by the Bush administration.

As this dissertation could only show correlation regarding a limited section of the entire process through which constructed narratives are created and seemingly absorbed by the public, this study shows that the methodology is capable of providing evidence

182 that sourcing is occurring and that overly optimistic information was being distributed by the Bush administration regarding hydrogen and that these positions had predictive value for the positions that later appeared in The New York Times. The assumption beyond that is that the public is absorbing this misinformation and using it to make decisions in terms of their political support and it can also be assumed that similar processes are taking place in the media treatment of other technologically complex policy matters. But what are the implications of this manipulation and what can be done to limit its effects so that it cannot be used for private gain against the common good.

The remainder of this chapter will discuss the implications of constructed narratives and sourcing, which have seemingly allowed a technology that could not be evaluated independently by the public to be described by a powerful organization in order to encourage public support for government hydrogen policies. Further, it suggests that if this can be done with hydrogen policy that other technical subjects in any policy arena would be similarly vulnerable. This highlights an ingrained danger for manipulation of information and ideas through rhetoric by powerful actors that is active in our political discourse. Additionally, this chapter will discuss some of the means of countering the effects of sourcing that were suggested by this research. Despite the influence of the Bush administration’s message in early years on the presentation of hydrogen by The New York

Times, these effects were negated by significant effort by the less powerful organization,

Energy Policy, though the effect may have been temporary. As a final note, several areas where this research could be expanded were suggested which would logically follow from the findings of this study

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6.1 Implications of Sourcing on Hydrogen Energy

As suggested by this case study, the practice of sourcing allowed the Bush administration to introduce constructed narratives regarding the environmental benefits of hydrogen into the public discourse via the news media. The optimism and criticism of these narratives was measured through the use of optimistic and critical indicators that gauged an author’s optimistic or critical presentation of hydrogen. The combination of the measured indicators, along with other language that was not coded for optimistic or critical indicators, form a hydrogen “myth” which has been stripped of its technological context, which prevents independent analysis by the reader, and replaces it with selected information that creates an manufactured context for the technology casting it in the light desired by the speaker.

The Bush administration introduced a large number of optimistic indicators into their evaluation of hydrogen technologies, in particular regarding the environmental benefits to be gained by utilizing hydrogen as an energy carrier. However this narrative consistently presented the most optimistic low level of impact for the hydrogen economy rather than the level of impact that could be anticipated if the Bush administration plan for development were to have been followed. Since the news media depiction of hydrogen was highly correlated to and predictable based on the Bush administration presentation of the topic, this indicates that the Bush administration was able to exert significant control over the public opinion on the environmental impact of hydrogen. In doing so, they likely eased the passage of legislation and incentives favoring the development of hydrogen utilizing the existing fossil fuel infrastructure, a move which had both immediate payouts and potential long term influence over the energy economy

184 for the existing fossil fuel industry and other interests who would benefit from maintaining the status quo.

The promotion of hydrogen with constructed narratives, hydrogen myths, undoubtedly had significant benefits for the fossil fuel industry. Reformation of hydrogen from natural gas and coal inevitably produces carbon dioxide but the language used by the administration invariably refers to the technology as emissions free, escaping on the technicality that at its point of use hydrogen emits only water vapor. This perception serves to increase public acceptance of the technology which will serve to increase its adoption and market penetration, but it could have the further effect of increasing energy consumption, as conservation for emissions reasons seems less meaningful. By not disclosing the emissions in this way the Bush administration not only assisted the fossil fuel industry retain their hold on future markets, but allowed the public to harm themselves and society by unwittingly producing emissions. While many hydrogen pathways do have reduced carbon emissions compared to the conventional energy economy, it must be acknowledged that the emissions are not necessarily zero and that the early years of the hydrogen economy will likely be powered by some of the same fossil fuels that we are using today.

The danger of sourcing in the development of hydrogen policy is that it would allow the fossil fuel industry to continue to do business as usual, simply utilizing hydrogen as a versatile energy carrier that offers emissions reductions over the current method of burning the fossil fuels directly. While many have theorized that we have entered the era of peak oil, vast deposits of natural gas and coal remain untapped. By utilizing hydrogen as the energy carrier, these fuels can be used efficiently and in ways

185 that they never could in their original forms. Undoubtedly, there are many ways in which this hydrogen - fossil fuel energy economy represent a significant improvement over the status quo. But while fossil fuels remain the source of the hydrogen, many of the critiques of the current system remain as well.

The potential long term impact of sourcing in terms of hydrogen would be its continued use to obfuscate the environmental impacts of hydrogen when derived from fossil fuel sources thus delaying indefinitely the cost and turmoil within the industry that will result from the inevitable shift away from fossil fuels as our primary energy sources.

This would allow the negative effects of fossil fuel extraction and the emissions resulting from their consumption to continue to accumulate, but now less visible to the general public, which reduces the pressure to enact a costly change even further. But these energy sources are not renewable and will eventually run out.

Even if the emissions are captured and sequestered, simply extracting the fossil fuels causes dramatic harm to the environment in a wide variety of ways. While it could be argued that there is a legitimate benefit to utilizing fossil fuels to generate hydrogen in the short term due to the existing infrastructure and industry that could easily be adapted to hydrogen production and distribution, this should only serve as a stepping stone to allow the rapid initial development of the hydrogen economy. The only long term benefits of this system are accrued by the entrenched interests who currently control the fossil fuel energy industry.

Additionally, if this technology is accepted on the premise that hydrogen from fossil fuels is emissions free then other alternative energy technologies will be passed over for funding and public support as these resources are instead given to the developing

186 hydrogen economy. If cars are to run on hydrogen, what will happen to the electric car? If fuel cells provide electricity, what happens to photovoltaic development? Any technology which is promoted on a misleading premise will leach funds from other promising technologies. Instead, as we evaluate the best path forward to transition away from fossil fuel, high emissions, and an unsustainable energy economy every effort must be made to objectively weigh each option and consider not just the next step but the chain of steps that will be taken that leads to the most cost effective, secure, and equitable zero emissions energy economy. It is in this playing field that hydrogen must compete; otherwise it creates the potential for hidden emissions and a long term reliance on unsustainable fossil fuels.

6.2 Implication of Sourcing on Energy Policy

While the case study clearly shows the effect and impact of sourcing on the treatment of hydrogen in the public discourse and from this several conclusions could be reached about the impacts of constructed narratives delivered through sourcing, but what does this then indicate about the impact of sourcing in other areas of policy development?

The ability of the Bush administration to influence the news media’s depiction of hydrogen and thus the public perception of the technology shows that it is possible to use sourcing effectively. To determine the potential for this technique to be used in other areas of policy development it is necessary to consider why sourcing was able to be utilized with hydrogen.

Two factors in particular make hydrogen vulnerable to the effects of sources. The first is its technical nature. Fuel cells are advanced devices that are dissimilar to the

187 energy technologies being widely used today; people are not familiar with them and lacking the basic knowledge of their operation presents a roadblock to their objectively analyzing statements made by others about the benefits or impacts of the technology.

Unable to evaluate the technology, the presentation found in the mass media serves as the primary version relied on by the public when considering the policy proposals made that affect that technology. Controlling that narrative is possible because the public cannot refute it.

Secondly, the hydrogen economy is not represented by a single piece of technology or supply chain. Since it can manifest in so many different forms it is possible to evaluate two different hydrogen scenarios and find completely different impacts and costs. By being vague or by leaving out particular details it is possible to describe the hydrogen economy very optimistically or very critically. Even if this position is questioned, sufficient support remains that the attempt does not seem overtly disingenuous. While the first factor allows the message to be controlled through omission, this factor allows the message to be controlled through the selective cherry picking of the facts.

Both of these factors relate to the overall complexity of the hydrogen technology, both in the equipment, the multitude of sources, and other factors. This allows a constructed narrative, as described in Barthes’ Mythologies, to be created for the topic which has had its context selectively curated to carry a specific message that will promote the positions held by those providing the information. This complexity can be found in many other policy discussions, raising the fear that sourcing could be at play in other policy arenas as well. Any technologically complex topic will be potentially subject to

188 these forces because the public generally relies on the information provided to them on the complex subjects rather than being able to come to their own conclusions. Any such complex subject could easily have myths created that selectively present the information to carry wildly different stories. The factors that allowed for the creation of constructed hydrogen narratives are not isolated to that area of policy and the danger certainly remains for sourcing to influence other technological policy topics. This indicates that sourcing likely plays a role in many technical policy debates where the creation of narratives allows the organized and powerful to control the information available to the public

The ability to create the narrative is only one part of the equation. Additionally, the constructed narrative requires an outlet so that the general public may be exposed.

This case study provides evidence suggesting that the hydrogen myth was spread through the effect of sourcing. The Bush administration was able to effectively influence the message the public received through the mass media simply by providing the information and feeding it to the news media. Despite a conflicting message being promoted by the research community, the Bush message is the one that was replicated for many years. It was only when the research community increased their level of organization through the publication of a special volume devoted to the issue that the mass media began to consider their more balanced position in addition to the more optimistic Bush administration position.

However, from 2003 to 2006 the administration was able to largely dictate their position, and this seemed to predict the media presentation of these same constructed hydrogen narratives as the hydrogen facts. As the administration was viewed as

189 authoritative, reliable, and provide a large amount of information the narrative it seems as though the narratives were passed on largely unchallenged by the news media at which point it is likely they were accepted by an unknowing public. This is an affirmation of the suspicions raised in Herman and Chomsky’s model of propaganda, which suggests that this type of influence is rampant in the news media along with a number of other factors which allow powerful entrenched interests to control the presentation of information so that their positions are accepted by the public. This represents a gross failure of journalism, whose role is that of a gatekeeper of knowledge for the general public.

Economic pressures and competition create a scenario which essentially forces these institutions to rely on cheap and plentiful publishable material that is provided to them by outside actors who have interests in controlling the public perception of certain issues.

The combination of sourcing and narrative creation generates a lot of potential for the manipulation of public opinion. Technical subjects are particularly prone to these effects due to the complex nature of the subject matter. This is dangerous because negative impacts may be ignored and competing technologies passed over in pursuit of a false narrative. Without accurate information being provided to the public, support will be given to policies that favor corporate interests rather than the public good. While the perception remains that independent decision making based on a thorough evaluation leads to an individual’s support for a particular policy, in reality choices are taken from the individual through the selective presentation of information that invariably leads to support for a particular position. This is a dangerous scenario that could have serious repercussions for the creation of policy in general and undermines the basic premise of democracy, that the individual may participate in the political discussion and throw their

190 support behind a position based on a reasoned argument rather than partial or misleading information.

6.3 Countering the Spread of Narratives through Sourcing

This case study provided evidence that the Bush administration released specific optimistic narratives regarding the hydrogen economy and that these hydrogen narratives were then spread to the public through the mass media via the effect of sourcing. As the primary source of information for important policy topics for most individual citizens, this infiltration of narratives into the mass media represents a dangerous vulnerability for democratic discourse. Because of this it is important, not just to identify this problem, but to use this case study to suggest means of limiting its negative impacts on the policy creation process, by countering the narratives and by limiting the spread of the myths via the sourcing effect.

The problems that allow for sourcing are deeply ingrained in the modern news media and any attempt to change the forces that encourage sourcing and the other influences over the media would be a protracted and uncertain effort. In the short term, this case study suggests that the primary means of countering this effect is to interrupt the sourcing with a concerted effort at providing a large amount of information usable by the media. Energy Policy was able to interrupt the correlation between the message about hydrogen promoted by Bush and the message appearing in The New York Times by combining the efforts of a number of researchers to develop an issue of the journal devoted exclusively to the examination of hydrogen, firmly calling into question the narrative constructed by the Bush administration.

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While the critiques they raised had all been used before by individual authors in

Energy Policy and elsewhere, they had not been replicated substantially in The New York

Times until they unified their efforts in a highly publicized special issue. This clearly interrupted the sourcing effect and the resulting treatment of hydrogen by The New York

Times was far more balanced. It is unclear how long the sourcing effect would have been interrupted. Political cycles being what they are, within two years of the special issue

President Bush had left office and a democrat sat in the Oval Office. During these two years President Bush dramatically scaled back his support for hydrogen, speaking of it less and less in his speeches and papers as he entered his lame duck phase.

Because of his declining support for the technology, it is difficult to say whether the relatively neutral treatment of hydrogen by the media was due to a lingering effect from the Energy Policy special issue, or if the machines that drove the sourcing to begin with were simply grinding to a halt. However 2006, when the special issue was released, was also the year in which the President released speeches and papers containing the highest levels of optimistic indicators as measured at any other time in his presidency.

When facing a disorganized opponent sourcing was able to effectively control the media depiction of the subject, but when organized even a much weaker organization was able to disrupt the hydrogen myth narrative. In the short term it seems as though simply calling enough attention to a more truthful narrative and massing enough support and attention around that will disrupt the misinformation being promoted by the optimistic or critical sources. This approach is limited essentially to putting out fires rather than preventing them, but is the most effective means of reducing the impact of sourcing in the short term.

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The long term solutions are more varied but are much more complex and difficult to enact. Sourcing occurs when private interests pursue favorable treatment in public policy and so a narrative is created that will get the public to support an issue they normally would not, had they been given the full unabridged information. As to how to limit the influence that private interests have over politicians, that is a question well beyond the bounds of this dissertation. Ultimately it would entail limiting campaign contributions and political oversight, but more importantly it would require a massive social shift in which the public no longer accepted that sort of behavior. Failing that sort of social revolution, it is unlikely that corporate interests will stop seeking and finding means of eliciting cooperation from politicians to serve as their mouthpieces.

A different approach would not be to try and limit the presence of disinformation through sourcing, but rather to try to increase the ability of the public to respond to and counter constructed narratives when they are encountered. By acting as a source of quality, comprehensive information about a contested topic, the effectiveness of sourcing can be greatly limited as suddenly the public now has the necessary context that was missing from the narrative provided in the myth. As a sufficient number of citizens question the facts being fed to them the media will no longer be able to simply relay the story that is being fed to them and instead must try to balance the positions in their reporting. This long term approach differs from the short term approach though it uses the same basic mechanism of raising enough attention to the counter argument that the media is forced to account for it. However instead of creating the information and publicizing it yourself you are creating an informed public who will be able to act as their own interpreters.

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In addition to the public being able to act as their own interpreters for scientifically debated issues, the case study of hydrogen highlights the deeper issues regarding the manner in which western society approaches complex societal issues in general. While scientific knowledge is held in high regard and is almost exclusively used to frame the debate surrounding complex issues, this method is inherently non- democratic and automatically discounts the knowledge and perspective that could be garnered through an examination of the problem through different world views, such as one focused on societal and environmental justice. (Byrne, 2005) Increasing the democratization of these debates, increasing the diversity of the individuals tackling the problems and suggesting solutions, will by default generate alternate solutions and alternate means of considering these problems and these solutions are more likely to consider the societal, ecological, and future impacts of the issue in addition to the technological. (Visvanathan, 2009)

The described methods above may be effective in countering the effects of sourcing but a deeper question is which parties should be responsible for mitigating the effects of these narratives? Arguments could be made that all of the involved parties should take specific actions in order to curtail the negative effects of sourcing. The news media should devote more resources to investigation and research of issues rather than relying on narratives provided by third parties. The government could play a greater role in providing non-partisan data and research to the news media and the public in easy to consume formats.

Ultimately, however, the responsibility for reducing the impact of sourcing falls on the shoulders of the public who should improve their capacity for critical thinking and

194 their engagement with current developments through via variety of information outlets available through the internet. Enhanced critical thinking and evaluation skills will allow the public to treat scientific data as additional information to the debate rather than a privileged knowledge accessible only to a few and trumping other viewpoints. Sourcing is effective when the narrative provided exists without additional context, by seeking out information from multiple sources rather than accepting a single source digested content the ability of sourcing to influence public opinion rapidly diminishes.

6.4 Lessons from the Methodology

It took several attempts to find a methodology that could handle the qualitative information and effectively analyze it qualitatively. Initial attempts involved aggregation of the indicators into monthly segments of time, however it was quickly determined that in order to show a potential cause and effect it was necessary to look at how past language from the Bush administration or Energy Policy affected the future portrayal of hydrogen technologies in The New York Times. In this fashion an index was created that had a data point for each day of the 8 years of the Bush presidency, measuring the aggregated optimistic or critical indicators in the six months prior to or after that date.

This level of aggregation was necessary due to the indirect nature of the sourcing relationship and the demands of the news cycle for information. In some instances a response to a Bush speech might be the next day and in others a Bush policy paper might be reference months after it was released. It was also found that the individual categories of indicators needed to be aggregated as well. This is of special concern for the comparison of the influence of Energy Policy on The New York Times compared to that

195 of the Bush administration. While the Bush administration is providing information for the purpose of distribution to the news media, the purpose of Energy Policy is quite different and so follows a very different cycle for the production and dissemination of their materials. The differences in the time scale over which this information is published creates additional difficulties in relating this information to specific trends observed in

The New York Times data as well as create uncertainty regarding the current validity of the information being presented in the journal as it relates to the news story.

It was also impressed on the author of this research the benefits of a methodology for content analysis that is more readily computerized. While some elements of the coding of the texts were accomplished using computerized searches this was only able to identify the articles and then the block of text within the articles that mentioned hydrogen or fuel cells. However once the individual paragraphs relating to hydrogen were identified each had to be read and coded manual to determine the exact subject matter discussed and if the text matched the criteria to be considered as an optimistic or critical indicator. This was a very time consuming process that would have been greatly aided with the ability to simply search for and count key words or other specific phrases.

However the range of ways in which these concepts could be expressed was simply too varied to account for.

6.5 Future Research

The results of this study leave several areas where further investigations would be warranted. As with any dissertation, the subject matter must be focused enough to fit within a single paper and so only one small part of the overarching concept could be

196 tested, that sourcing was being used by the Bush administration to promote a selective set of information through the media. However, even showing that this is occurring leaves several questions remaining.

The first area that should be considered would be to see if this study could be expanded upon by including additional news journals. The New York Times is an effective representative for the printed news media but different papers may have substantially different inherent biases of their own and may attract different readership. In addition to adding the coded results of these other papers to the larger analysis it would be interesting to see how sourcing influenced different papers and magazines based on their existing political leanings. Replicating this study but with slight variations would both help to confirm the findings of this study as well as probe some of the lingering questions regarding the mechanisms of sourcing and if the media has any inherent resilience to its effects.

A second area to consider would be to repeat this study but using a different issue for the case study. While this study showed that the effect was occurring with hydrogen, it can only be inferred that other technical policy issues are being subjected to the same treatment. Using this methodology to examine other energy issues and even expanding beyond into other complex policy areas would test the limits of what the public must accept on faith from their information sources versus those that sufficient information exists in the public sphere to counter. Anecdotal evidence in the form of the climate change debate suggests that even high degrees of public knowledge of the basic scientific facts may not be enough to stop sourcing from influencing wide segments of the population.

197

A third area to consider is a closer examination of the mechanisms of sourcing.

While this study shows the correlation between the message promoted by Bush and the timing of a similar message being promoted by The New York Times, but the correlation does not necessarily mean causation. It would be interesting to follow up with individual authors from The New York Times to interview them on how they originated the information used in their articles. These interviews could reveal anything from direct intervention via press releases provided to them or they could be more indirect such as the administration making the information available and the reporter finding it in the course of their research. Knowing how this occurred would be a strong indicator of the

Bush administration’s intent.

A final topic to consider is not how the misinformation is introduced to the public but what the public does with the misinformation once it has it. While this case study showed that the hydrogen myths were being replicated in The New York Times it does not examine whether or not the public absorbs this information or not. A study could be fashioned that surveyed the general public’s knowledge and exposure to information about a technological subject and then expose groups to article that have been coded and found to contain optimistic or critical leanings to ascertain how this causes a deviation within these experimental groups’ opinions towards the technology compared to the general public.

6.6 Concluding Remarks

The issues of sourcing and the promotion of constructed narratives to promote optimistic or critical positions present a significant danger for the development of an

198 alternative energy economy. The methodology used in this dissertation shows that hydrogen narratives promoted by the administration were a strong predictor of the tone of the narrative printed by The New York Times, while the more critical views found in

Energy Policy were not unless extraordinary efforts were made to call attention to the issue. This was powerful support for the core idea that technologically complex subjects are particularly prone to this type of manipulation.

Support for these findings rests in the high degree of correlation between the past optimistic indicators provided by the Bush administration and the matching optimistic response this elicited from The New York Times. Using regression analysis the coded results of the texts were used to qualitatively analyze the results using statistical techniques. As suggested by the hypothesis a strong correlation was found between the

Bush materials and The New York Times from 2001-2006. In 2006 a special issue of

Energy Policy was released devoted to a balanced examination of the current and potential future hydrogen energy economy. This special issue was a sufficient effort to counteract the sourcing efforts by the administration and lead to a more balanced treatment of hydrogen energy by The New York Times.

While this supports the broader hypothesis that energy policy and other complex subjects would be equally subject to this type of influence, further studies would need to be conducted before the concept could be broadly generalized to other fields. Further studies should be conducted to probe the mechanisms by which the sourcing occurs and to ensure that the same pattern is seen for other subjects.

The findings of this dissertation are important for several reasons. Firstly, it identifies an issue that is definitely happening currently, which is the debate over the role

199 of hydrogen in our future energy economy. While the political support under the Bush administration has largely evaporated under Obama, many of the states and even the federal government continue to fund research and the development of hydrogen technologies. Ensuring that any future public debate relies on unabridged, comprehensive information that is widely accessible to the general public is necessary to guarantee that the most optimal pathway for hydrogen development is chosen.

Secondly, while it does not prove that this issue extends beyond hydrogen and the

Bush administration it is highly suggestive of the idea that any technologically complex subject matter has the potential to be manipulated in this fashion. In the same way that hydrogen must be considered on the pure facts without spin, so must any technologically complex issue where the public relies on an informed news media to provide all of the arguments for and against the technology and its applications in an easily digestible fashion. If the problems found with hydrogen are found in other subjects as well then this issue must be monitored and countered.

Finally, this dissertation suggests that the manipulation and effects of sourcing can be mitigated through the promulgation of balanced information rather than constructed narratives and through an extraordinary effort at calling attention to the debate and the facts surrounding it. While specific issues can be countered in this fashion a broader education campaign aimed at ensuring citizens are already capable of analyzing the basics of technologically complex subject through enhanced critical thinking capabilities would greatly reduce the potential for misinformation to be spread in through the effect of sourcing. Ultimately a deeper societal issue must be addressed, however, and that is the narrow range of knowledge and world views which are empowered to

200 participate in public policy debates. (Byrne, 2005) While scientific knowledge is held in high regard, other viewpoints and the players behind them are disempowered and pushed to the sideline. These players must not only be able to understand and engage in the scientific debate surrounding complex policy issues, but their worldviews and values must be incorporated into the discussion as well, making them active participants in the search for a policy solution that serves a broader segment of society, the ecosystem, and future generations instead of merely maximizing technological and economic efficiency.

(Visvanathan, 2009)

The effects of sourcing present a troubling question regarding the way our society currently conducts public discourse of public policy issues, but one final thought is whether or not this effect and the rest of Herman and Chomsky’s model of propaganda will remain as forces influencing how the public receives these issues. As the information age has unfurled and the internet has become a ubiquitous presence in the western world, the average citizen has been presented with a plethora of information and alternative news sources available on the World Wide Web. While in previous eras an individual’s primary outlet to the world was their local newspaper, one of three evening news programs, or a handful of national publications, the diversity of news sources large and small that have been made available to anyone with an internet connection has the potential to upend the manner in which we are able to access data on any topic we wish to learn about.

Not only does this disrupt the potential for sourcing through the provision of narratives to a few dominant news outlets, it also presents dramatic implications for how the public interacts with their news sources. While previously consumers were limited in

201 choice regarding the news sources they had available, it is relatively easy now to select news sources that conform to already held beliefs. Rather than helping to form opinions, self-selected groups of information consumers may form around outlets supporting their world view. While major news outlets and the effects of sourcing will not disappear overnight, the way in which the public consumes information is changing and it remains unclear whether the effects of sourcing will be amplified within these self-selected groups or if it will cease to have the influence it does today. In this way, the choice of news sources provided by internet technology presents a double edged sword, one that allows us access too many different points of view but which simultaneously allows us to narrow our field of view even further.

202

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Appendix A

LIST OF SOURCE DATA ANALYZED

BUSH ADMINISTRATION Date Title of Speech / Press Release 05/17/01 Remarks by the President to Capital City Partnership 02/23/02 President Focuses on Energy Security in Radio Address 02/25/02 President Promotes Energy Efficiency Through Technology 01/30/03 Hydrogen Fuel: A Clean and Secure Energy Future 02/01/03 Radio Address of the President to the Nation 02/06/03 Fact Sheet: Hydrogen Fuel: a Clean and Secure Energy Future 02/06/03 Hydrogen Fuel Initiative Can Make “Fundamental Difference” 02/06/03 Press Briefing by Ari Fleischer 02/27/03 Statement by the President 05/09/03 National Defense Transportation Day and National Transportation Week, 2003 06/02/03 U.S. Actions at the G-8 Summit 06/25/03 Hydrogen Economy Fact Sheet 06/25/03 Joint Statement on Hydrogen Cooperation 06/25/03 President Bush, European Leaders Act to Fight Global Terror 10/21/03 Fact Sheet- Energy Security Initiavtive 04/26/04 President Unveils Tech Initiatives for Energy Health Care, Internet 05/03/04 Remarks by the President and Mrs. Bush at “ask President Bush” Event 06/24/04 President Bush: High Tech Improving Economy, Health Care, Education 06/26/04 Fact Sheet: US-EU Summit: Cooperation on the Development of the Hydrogen Economy 07/06/04 Secretary Ridge Announces Homeland Security National Center for Food Protection and Defense 07/09/04 Q&A w/ Jim Connaughton, Chairman, Council of Environmental Quality 07/14/04 President's Remarks at Ask President Bush Event 09/04/04 President's Remarks at Ask President Bush Event in Ohio 10/09/04 Remarks by the President and Senator Kerry in Second 2004 Presidential Debate 03/09/05 President Discusses Energy Policy 03/30/05 President Discusses Strengthening Social Security in Iowa 04/16/05 President's Radio Address 04/20/05 President Speaks to US Hispanic Chamber of Commerce Conference 04/27/05 Fact Sheet: Promoting Energy Independence and Security 04/27/05 President Discusses Energy at National Small Business Conference 05/14/05 President's Radio Address 05/16/05 President Discusses Biodiesel and Alternative Fuel Sources 05/25/05 Fact Sheet: Developing Clean and Secure Energy Through Hydrogen Fuel 05/25/05 President Tours Hydrogen Fueling Station, Discuss Research 06/08/05 President Discusses Strengthening Social Security in Washington, DC 06/11/05 President's Radio Address 06/15/05 Fact Sheet: President Calls on Congress to Pass a National Energy Policy 06/15/05 President Discusses Energy Policy 06/22/05 President Discusses energy Policy, Economic Security 08/03/05 President Discusses Second Term Accomplishments and Priorities 09/08/05 President Signs Energy Policy Act 10/26/05 President Outlines Economic Growth Agenda 01/31/06 State of the Union: The Advanced Energy Initiative 02/02/06 President Discusses American Competitiveness Agenda in Minnesota 02/02/06 President's Letter 02/03/06 President Participates in American Competitiveness Panel in NM 02/17/06 President Discusses Global War on Terror Following Briefing at CENTCOM 02/20/06 President Discusses Advanced Energy Initiative in Milwaukee 02/20/06 President's Letter 02/21/06 President Participates in Energy Conservation & Efficiency Panel 02/22/06 President Addresses Asia Society, Discusses India and Pakistan 02/25/06 President's Radio Address 03/06/06 President Participates in Swearing-in of CEA Chairman Edward Lazear 03/15/06 President Discusses Medicare Prescription Drug Benefits in Maryland 03/21/06 Press Conference of the President Figure 29- List of Source Material Collected from Bush Administration

222

BUSH ADMINISTRATION (cont) Date Title of Speech / Press Release 04/20/06 President Bush Welcomes Recipients of the Presidents Environmental Youth Awards 04/21/06 President Participates in Panel on the American Competitiveness Initiative 04/22/06 President Bush Discusses Advanced Transportation Technology in California 04/22/06 President's Radio Address 04/24/06 President Attends Jon Porter for Congress Lunch 04/24/06 President Discusses Comprehensive Immigration Reform 04/25/06 President Discusses Energy Policy 05/06/06 President Bush Delivers Commencement Address at Oklahoma State University 05/07/06 Interview of the President by Sabine Christiansen of ARD German Television 05/24/06 President Discusses Energy During Visit to Nuclear Generating Station in PA 05/24/06 President Attends Pennsylvania Congressional Victory Committee Dinner 05/25/06 President Bush and Prime Minister Tony Blair of the United Kingdom Participate in Joint Press Availability 06/26/06 President Bush Meets With Supporters of U.S. Military in Iraq and Afghanistan 07/11/06 Roundtable Interview of the President by Foreign Print Media 07/27/06 President Addresses National Association of Manufacturers 10/03/06 Remarks by the President at John Doolittle for Congress Reception 10/03/06 Remarks by the President at Richard Pombo for Congress Breakfast 10/04/06 Remarks by the President at Rick Renzi for Congress Breakfast 10/12/06 National Energy Awareness Month, 2006 10/12/06 President Bush Discusses Energy at Renewable Energy Conference 11/16/06 President Bush Visits National University of Singapore 12/20/06 Press Conference by the President 01/24/07 President Bush Discusses Energy Initiative 02/10/07 President's Radio Address 03/20/07 President Bush Discusses Energy Initiatives in Missouri 03/26/07 FALSE POSITIVE, WRONG SPEAKER 03/27/07 Fact Sheet: Twenty in Ten: Powering Large Vehicle Fleets with Alternative Fuels 04/30/07 2007 US-EU Summit Statement: Energy Security, Efficiency, and Climate Change 05/31/07 President Bush Discusses United States International Development Agenda 06/01/07 Roundtable Interview of the President by Foreign Print Media 07/10/07 President Bush Visits Cleveland, Ohio 09/05/07 Press Briefing by Deputy Press Secretary Dana Perino and Senior Administration Officials 09/28/07 President Bush Participates in Major Economies Meeting on Energy Security and Climate Change 03/05/08 Fact Sheet: Increasing Our Energy Security and Confronting Climate Change Through Investment in Renewable Technologies 03/05/08 President Bush Attends Washington International Renewable Energy Conference 2008 04/16/08 President Bush Discusses Climate Change 04/29/08 Press Conference by the President 05/02/08 President Bush Discusses Economy, Trade 07/19/08 President's Radio Address 07/30/08 President Bush Meets With Cabinet Members 07/31/08 President Bush Attends 2008 Annual Meeting of the West Virginia Coal Association 08/23/08 President's Radio Address Figure 29 (continued)- List of Source Material Collected from Bush Administration

223

The New York Times Date Title Author Section 1/21/2001 Ford Puts All Its Green Eggs Into a Single Basket Jim Motavalli Automotive 3/6/2001 Pataki Names an Environmental Conservation Commisioner James C. McKinley, Jr. NY/Region 3/27/2001 Of Nanotubes and Buckyballs: Atomic-Scale Building Blocks Kenneth Chang Science 4/29/2001 The Next Generation: Energy's Future on L.I. Stewart Ain NY/Region 5/10/2001 HOW IT WORKS; Fuel Cells: Clean, Reliable (and Pricey) Electricity Catherine Greenman Science 5/18/2001 Hybrid Cars Should Merit A Tax Credit, Report Says Matthew L. Wald National 5/29/2001 G.M. Displays More Efficient Large Engine Matthew L. Wald Automotive 6/12/2001 Diesel Engines Get Spotlight in Fuel-Efficiency Contest Keith Bradsher Automotive 6/14/2001 Another G.M. Investment in Fuel Cell Development Matthew L. Wald Technology 7/22/2001 Blast From The Past Jeff Goodell Magazine 7/25/2001 New York Turns Into a Lab On the Future of Electricity Kirk Johnson NY/Region 8/8/2001 G.M. Announces Plans for Fuel Cells Danny Hakim Technology 8/23/2001 Toyota Developing a Fuel Cell Vehicle None Listed Technology 9/16/2001 Behind the Wheel/Volkswagon Lupo; A Thrifty Spin in a 99 M.P.G. Car None Listed Automotive 10/26/2001 Tokyo Show Is Smaller and Subdued, but Still Outlandish William Diem Automotive 10/27/2001 New Regulations in California Will Reduce Diesel Emissions James Stergold National 12/5/2001 Honda Opens a U.S. Factory and a Front Against the Big 3 Danny Hakim Business 12/7/2001 Recent Events Recast Debate on Fuel Economy Danny Hakim National 12/21/2001 Cadillac Too, Shifting Focus To Trucks Danny Hakim Automotive 12/23/2001 Investing; Fuel Cell Companies Offer Choice and Risk David Ludlum Business Neela Banerjee & 1/9/2002 U.S. Ends Car Plan On Gas Efficiency; Looks to Fuel Cells National Danny Hakim 1/10/2002 Bush White House Starts Own High-Milage Car Program Danny Hakim Washington 1/10/2002 Dream Car: A Dressed-Up Skateboard Danny Hakim Automotive 1/15/2002 A Fuel-Cell Initiative Too Costly for Use in Cars Matthew L. Wald Washington 1/22/2002 Differences In Congress On Fuel Use Danny Hakim Washington 2/6/2002 Politics Keep Shifting in the Gas-Mileage Debate Danny Hakim Washington 2/26/2002 Bush May Scale Back Alaska Drilling Plan Katherine Q. Seelye Washington 3/14/2002 Big Hopes for Gas From Gasoline Matthew L. Wald Technology 4/18/2002 Michigan Governor to Offer Energy Research Plan Danny Hakim National 7/15/2002 New Economy; Fuel-cell Work is Helping Build Research Prowess for Detroit Steve Lohr Automotive 7/22/2002 Auto Emission Rules in California are Forcing Changes Danny Hakim National 7/28/2002 Detroit and California Rev Their Engines Over Emissions Danny Hakim Automotive 8/8/2002 Ford Heir Says Nation's Affair With the Car Has Lost Its Zip Danny Hakim Automotive 8/14/2002 G.M. Version of Fuel-Cell Car Danny Hakim Automotive 8/20/2002 Economic Interests Keep Drive for Renewable Energy Stuck in Neutral Neela Banerjee Science 8/31/2002 Ford Abandons Venture in Making Electric Cars Micheline Maynard Automotive 9/22/2002 Automakers Look Beyond Electric Danny Hakim Automotive 9/22/2002 Ford Think City; Illuminating High-Voltage Commute Leonard M. Apcar Automotive 9/29/2002 CARS; Smokestack Visionary Danny Hakim Automotive 10/16/2002 Europe Pushes for Renewable Energy Paul Meller World 10/23/2002 New Looks; Niche Mania! James G. Cobb Magazine 11/17/2002 Private Sector; An Electrovan, Not an Edsel Danny Hakim Business 11/21/2002 Exxon-Led Group Is Giving A Climate Grant to Stanford Andrew C. Revkin Business 12/8/2002 How Green is BP? Darcy Frey Magazine 12/11/2002 Hybrid Cars Are Attracting A Broad Range of Americans Danny Hakim Automotive 12/15/2002 A First Step To Cutting Reliance On Oil Tom Redburn Business 12/24/2002 G.M. to Offer Hybrid Power In 5 Models By 2007 Danny Hakim Automotive G.E. Research Returns to Roots; Management Again Gambles on Costly Long- 12/26/2002 Claudiah H. Deutsch Business Term Ideas 1/5/2003 Auto Shows' Inspiration? The Past Michelle Krebs Automotive 1/26/2003 A Ca Man Who's Stuck in Drive Michelline Maynard Business 1/28/2003 Hybrid Autos Quick to Pass Curiousity Stage Danny Hakim Business 1/29/2003 Cheering Tax Cuts, Fearing Deficits David M. Halbfinger National Calling Iraq a Serious Threat, Bush Vows That He'll Disarm It, and Also Rebuild Richard W. Stevenson 1/29/2003 National U.S. Economy & David E. Sanger 1/30/2003 Deficits Will Rise, All Agree, But Concensus Then Fades Edmund L. Andrews National 1/30/2003 Carmakers and Environmentalists Differ Over Fuel Cell Proposal Danny Hakim National Figure 30- List of Source Material Collected from New York Times

224

The New York Times (cont) Date Title Author Section 2/2/2003 The Hydrogen Economy; A Green Car That the Industry Loves Ryan Lizza National 2/4/2003 January Auto Sales Fall 2% As Analysts See Tough Year Danny Hakim Automotive 2/4/2003 From Fuel Cell Cars to Slaughterhouse Inspection: Where the Money Goes Katherine Q. Seelye Washington 2/5/2003 Hydrogen Cars Remain Decades in the Future Under New Budget Danny Hakim Washington 2/9/2003 Balancing Act; How Would You Cut the Federal Budget David E. Rosenbaum National 2/9/2003 Can Energy Ventures Pick Up Where Tech Left Off? Amy Cortese Business 2/23/2003 On Environmental Rules, Bush Sees a Balance, Critics a Threat Douglas Jehl National 2/24/2003 A Parallel Inventor of the Transistor Has His Moment John Markoff Science 2/28/2003 U.S. Seeking Cleaner Model of Coal Plant Andrew C. Revkin National 3/2/2003 A Call for Softer, Greener Language Jennifer S. Lee Washington 3/5/2003 Hydrogen Vans and Pumps Head For Washington John Tierney Business 3/6/2003 California Offers Change in Car Rules None Listed Business 3/7/2003 White House and Europe to Concentrate on Hydrogen Neela Banerjee Business 3/8/2003 Europe's Carmakers Sticking With Diesel Mark Landler Business 3/16/2003 For Far Smaller Fuel Cells, a Far Shorter Wait Barnaby J. Feder Technology 3/25/2003 Government May Alter Line Between a Car and a Truck Danny Hakim Business 4/9/2003 G.M. and BMW to Announce Joint Venture on Fuel Cells Danny Hakim Business 4/12/2003 Advocates of Acrtic Drilling Buoyed as House Passes Bill Carl Hulse National 4/13/2003 Oil's Pressure Points Neela Banerjee Business 4/20/2003 The Id of a Hot Rod In a Minivan Land Jeff MacGregor National 4/25/2003 California Regulators Modify Auto Emissions Mandate Danny Hakim National 5/3/2003 Fuel Economy Hit 22-Year Low in 2002 Danny Hakim Business 5/21/2003 FedEx to Switch 30,000 Trucks to Hybrids Jennifer S. Lee Business 6/6/2003 Unions Back Research Plan for Energy Steven Greenhouse National 6/17/2003 Observatory Henry Fountain Science 6/17/2003 Europe and U.S. Will Share Research on Hydrogen Fuel Paul Meller World 7/19/2003 House Trims Bush Plan For Research On Weapons Carl Hulse National 7/27/2003 Europe and America, Partners (Sort of) Mark Landler World 8/8/2003 Where Every Student's Goal Is to Design a Legendary Car Janelle Brown Automotive 8/12/2003 Automakers Drop Suit on Air Rules Danny Hakim Business 8/24/2003 Arnold the Hummer Lover Revs Up a Green State Danny Hakim National 8/25/2003 Technology and Brain Power Used to Tame an Aging Grid Kenneth Chang Science 8/31/2003 Steward of a Department He Once Sought to Scrap Katharine Q. Seelye National 9/2/2003 Small Thoughts for a Global Grid Barnaby J. Feder Science 9/11/2003 Election Race? First, Check Out This Bike Noah Shachtman Technology 9/22/2003 Republicans Set to Spell Out Plan for Oil Drilling in Refuge Carl Hulse Washington 9/24/2003 Schwarzenegger Learning His Lines, and Others', for Debate Tonight Charlie LeDuff National 9/28/2003 The Alternative Alternative Fuel Pagan Kennedy Magazine 9/29/2003 In Handling Innovation, Patience Is a Virtue Julie Flaherty Technology 9/30/2003 Tough Going As Negotiators Hammer Out Energy Bill Carl Hulse Washington 10/5/2003 Special Order: A Green Hummer Jim Motavalli Automotive 10/15/2003 Pet Projects Flood Energy Bill Before Crucial Session Today Carl Hulse Washington 10/19/2003 Oct 12-18; Inside the Energy Bill Carl Hulse Washington 10/22/2003 Leased and Abandoned: Revolt of the EV-1 Lovers Chris Dixon Automotive 10/22/2003 Some Green Machines Swim in the Mainstream Braden Phillips Automotive 11/2/2003 Energy to Burn Roberta A. Hamilton Automotive 11/4/2003 As Earth Warms, The Hottest Issue Is Energy Kenneth Chang Science 11/4/2003 One Recipe for a (Mostly) Emissions-Free Economy Bill Marsh Science 11/6/2003 With Silicon's Help, A Change in Status for the Lowly Battery Peter Wayner Science 11/6/2003 G.M. Puts Off Its Hybrids, Letting Ford Go First Danny Hakim Business 11/12/2003 Will Hydrogen Clear the Air? Maybe Not, Say Some Matthew L. Wald Business 11/16/2003 Ford Focus PZEV; A Stealthy Operative In the War on Pollution Jim Motavalli Automotive 11/22/2003 Pushing Energy Conversion Into the Back Seat of the S.U.V. Neela Banerjee Business 11/22/2003 Energy Bill Would Welcome Back Diesels Danny Hakim Business 11/25/2003 Plan Gives Farmers a Role in Fighting Global Warming David Barboza National Figure 30 (continued)- List of Source Material Collected from New York Times

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The New York Times (cont) Date Title Author Section 11/30/2003 The Greening of Suburbia James G. Cobb Automotive 1/6/2004 Observatory Henry Fountain Science 2/3/2004 Energy; Offering Less For Tax Breaks Carl Hulse Washington 2/6/2004 Report Questions Bush Plan For Hydrogen Fueled Cars Matthew L. Wald Washington 2/16/2004 A Shade of Green: S.U.V.'s Try to Soften Image Danny Hakim Automotive 2/17/2004 Crystals Could End Up as the Fuel Tank of the Future Kenneth Chang Science 2/24/2004 Forecast of Rising Oil Deman Chanllenges Tired Saudi Fields Jeff Gerth Business 2/28/2004 Iconoclast Gets Consultant Fees To Tell Big Oil It's Fading Fast Barnaby J. Feder Business 2/29/2004 G Is for Guzzler, T Is for Tax, O Is for Oops Norman Mayersohn Business 3/26/2004 Kerry Is Sticking With Plan to Raise Auto Fuel Efficiency Danny Hakim Washington 3/28/2004 Carmakers Pull Plug On Electric Vehicles Chris Dixon Automotive 4/10/2004 Gas Prices Soar, Angelenos Shrug John M. Broder National 4/11/2004 Having Their S.U.V.'s and Converting Them, Too Fara Warner Business 4/26/2004 Bush Talk to Cover Economic Initiatives None Listed Washington 4/28/2004 Second Time Around, Bush Is Forgoing a Visionary Agenda Richard W. Stevenson Washington 6/10/2004 As Oil Prices Rise, a Sense of Alarm in Asia Wayne Arnold Business 6/20/2004 Suddenly, It's Hip To Conserve Energy Timothy Egan Science For a group of researchers at Sandia National Labs, sugar in the gas tank isn't 6/21/2004 Teresa Riordan Science such a bad idea. 6/22/2004 Kery Vows to Lift Bush Limits of Stem-Cell Research Jodi Wilgoren Washington 8/5/2004 Auto Industry Debates Virtues of Diesels vs. Hybrids Danny Hakim Business David M. Halbfinger & 8/6/2004 Kerry Pitches Energy Plan in Missouri Washington Neela Banerjee 8/22/2004 Ready to Bet on Alternative Energy? Well, Think Again Conrad De Aenlle Business 8/26/2004 Giving the Batter, That Stalwart, A Fuel-Cell Challenge Ian Austen Science 8/29/2004 How to reinvent the G.O.P. David Brooks Washington 9/26/2004 Ford Parks It's Natural Gas Bandwagon Chris Dixon Automotive 10/2/2004 Ford Lays Out a Move to Cut Auto Emissions Danny Hakim Business 10/5/2004 Membrane Breakthrough for Fuel Cells Matthew L. Wald Technology 10/6/2004 A Clash of Goals in Bush's Efforts on the Income Tax Edmund L. Andrews Washington 10/27/2004 New Hummer Is Slimmer and Cheaper Danny Hakim Business 11/11/2004 Washington Station Offers Gas, Snacks and Hydrogen Matthew L. Wald Business 11/22/2004 The Engine Looks Familiar, but It Runs on Hydrogen Don Sherman Automotive 11/28/2004 Hydrogen Production Method Could Bolster Fuel Supplies Matthew L. Wald Business 12/8/2004 Report on Energy Impasse, With Some Improbable Views Matthew L. Wald Business 12/9/2004 Steering California's Fight on Emissions Danny Hakim National 12/12/2004 Fuel Cells in the Deep Freeze Jim Motavalli Automotive 12/14/2004 G.M. and Daimler to Work Jointly on Hybrid Engine Danny Hakim Business 1/9/2005 George Jetson, Meet the Sequel Danny Hakim Business 2/13/2005 Trying Out a Power Source of the Future Valerie Cotsalas Real Estate 3/1/2005 Company News; Dow Chemical in Fuel Cell Deal with Millenium Cell None Listed Business 3/3/2005 Taking Down the 'No Foreign Cars' Signs in Michigan Danny Hakim Business 3/13/2005 Running on Empty Natalie Canavor NY/Region 3/14/2005 Metro Briefing: New York: Albany: Havesi Sees Green in Green Energy None Listed NY/Region 3/15/2005 Power Producers Seek Latest Models of Nuclear Reactors Matthew L. Wald Science 3/15/2005 U.S. Power Producers Window-Shop for Latest Models of Nuclear Reactors Matthew L. Wald Science 4/2/2005 Hybrid-Car Tnkerers Scoff at No-Plug-In Rule Danny Hakim Business 5/22/2005 Dirty Secret: Coal Plants Could Be Much Cleaner Kenneth J. Stier Business 6/4/2005 Japan Squeezes to Get the Most of Costly Fuel James Brooke Business 6/5/2005 Honda FCX: What a Gas! A Week in Suburbia With a Hydrogen Honda Jim Motavalli Automotive 6/5/2005 Putting the Hindenburg to Rest Jim Motavalli Automotive 7/12/2005 Great Promise in Molecular Tinkering, but Better Bathroom Will Have to Wait Barnaby J. Feder Science

8/21/2005 The Breaking Point Peter Maas Magazine 8/28/2005 Honda Civic GX; Clean, Green and Seen in Coveted Car-Pool Lanes Chris Dixon Automotive 9/7/2005 Toyota Hopes to Push Its Hybrids Beyond the Niche James Brooke Business 9/10/2005 The New Prize: Alternative Fuels Danny Hakim Business 9/11/2005 Long Island Journal; 800 Square Feet and Zero Energy Bills Marcelle S Fischler NY/Region Figure 30 (continued)- List of Source Material Collected from New York Times

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The New York Times (cont) Date Title Author Section 9/25/2005 Cars That Guzzle Grass Ted C. Fishman Magazine 11/2/2005 Taking the Future for a Drive Danny Hakim Business 11/22/2005 Saving the Environment, One Quarterly Earnings Report at a Time Claudia H. Deutsch Business 11/24/2005 Live Frome the Lab, a Culture Worth a Thousand Words Andrew Pollack National 11/29/2005 Europe: Britain: BP to Double Green Investment None Listed Business 12/4/2005 Architecture, Posed and Pondered Benjamin Gonocchio NY/Region 12/30/2005 His Car Smelling Like French Fries, Willie Nelson Sells Biodiesel Danny Hakim Business 1/7/2006 Pataki Wants Drivers to Fill Up With Ethanol or Biodiesel Danny Hakim NY/Region 1/17/2006 Custom-Made Microbes, at Your Service Andrew Pollack Science 2/1/2006 Call to Cut Foreign Oil is a Refrain 35 Years Old Matthew L. Wald Washington 2/2/2006 Pixel Counting Joins Film in Obsolete Bin David Pogue Technology 2/3/2006 In Energy Work, One Hand Giveth and the Other Taketh Matthew L. Wald National 2/7/2006 Corn Power Put to the Test Matthew L. Wald Science 2/8/2006 Buy a Hybrid, and Save a Guzzler David Leonahardt Business 2/11/2006 Power Plant Would Reuse Carbon Dioxide Matthew L. Wald Business 4/18/2006 Chemical Companies Look to Coal as an Oil Substitute Claudia H. Deutsch Business 4/23/2006 Energy Politics on Earth Day as Bush Tours California Elisabeth Bumiller Washington 5/5/2006 Conflicting Loyalties as Republicans Confront High Gas Prices Edmund L. Andrews Business 5/11/2006 Washington: An 'H-Prize' for Hydrogen Ideas None Listed National 5/27/2006 How Many Miles to the Bushel Paul B. Brown Business Addicted to Oil: Thomas L. Friedman Reporting,' a Look at an American 6/24/2006 Eric Mink Arts Addiction 6/30/2006 A Refinery Clears the Air to Grow Roses Jad Mouawad Business 7/5/2006 Search for New Oil Sources Leads to Processed Coal Matthew L. Wald Business 7/15/2006 Study Cites Plan to End U.S. Oil Imports Matthew L. Wald Business 7/16/2006 Atomic Balm? Jon Gertner Magazine 7/16/2006 Novelties; A Portable (and Squeezable) Way to Recharge Anne Eisenberg Business 7/23/2006 Collecting; Batteries Still Included: Those Eclectic Electrics Dave Kinney Automotive 7/27/2006 BP Says It Will Address Safety and Legal Problems Matthew L. Wald Business 8/16/2006 Need for Battery Power Runs Into Basic Hurdles of Science Barnaby J. Feder Technology 9/21/2006 Branson Pledges Billions to Fight Global Warming Andrew C. Revkin Science 9/21/2006 California Sues 6 Automakers Over Global Warming Nick Bunkley Business 9/24/2006 Prequel to a Hydrogen Future: Driving G.M.'s Fuel Cell Prototype Lindsay Brooke Automotive 10/8/2006 The Big-Sky Dem Mark Sundeen Magazine 10/25/2006 A Field Trip Guzzling Gas, Among the Environmentalists John M. Broder Automotive 10/30/2006 Budgets Falling in Race to Fight Global Warming Andrew C. Revkin Business 12/12/2006 The Cost of an Overheated Planet Steve Lohr Business 12/28/2006 It's Free, Plentiful and Fickle Matthew L. Wald Business The Land of Rising Conservation; Japan Offers a Lesson in Using Technology to 1/6/2007 Martin Fackler Business Reduce Energy Consumption 1/25/2007 Energy Research on a Shoestring Clifford Krauss Science 2/18/2007 From 0 to 60 to World Domination Jon Gertner Magazine 2/23/2007 Bush Makes a Pitch for Amber Waves of Homegrown Fuel Edmund L. Andrews Washington 2/25/2007 Racing to Make the Pit Stops a Little Bit Greener Dave Caldwell Automotive 3/4/2007 Is the State Selling Its Fuel Cell Business Short? Jan Ellen Spiegel NY/Region 3/6/2007 Venture Capitalists Move From Web to Algae Clifford Krauss Business 3/7/2007 Green Gold, or Just Slime? Clifford Krauss Business 3/7/2007 What's So Bad About Big? Matthew L. Wald Business 3/14/2007 Start-Up Fervor Shifts to Energy in Silicon Valley Matt Richtel Technology 3/18/2007 Abu Dhabi Explores Energy Alternatives Hassan M. Fattah World 3/21/2007 Bush Tours 2 Auto Plants and Talks Energy Policy Matthew L. Wald National 3/28/2007 The Future of Hydrogen Cars David Pogue Technology 4/1/2007 Latest Alternative Fuel: Gas from Chicken Manure Jan Ellen Spiegel NY/Region 4/4/2007 Solving the Car-Propulsion Problem David Pogue Technology 4/15/2007 Airstream: The Concept Travels Well Phil Patton Automotive 4/15/2007 For Hartford, a Fuel-Cell Bus Milestone Jan Ellen Spiegel NY/Region 4/21/2007 China's Automakers, With Beijing's Prodding, Show Alternative-Fuel Cars Keith Bradsher Automotive Figure 30 (continued)- List of Source Material Collected from New York Times

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The New York Times (cont) Date Title Author Section 4/29/2007 On the Road, Hope for a Zero-Pollution Car Don Sherman Automotive 5/1/2007 Coal's Energy Potential Is An Engineering Challenge Now Matthew L. Wald Science 5/19/2007 A Return to the Land, for Fuel Matt Villano Business 5/20/2007 Home Eco-nomics; The Zero-Energy Solution Mark Svenvold Magazine 6/17/2007 The Green Home of Their Dreams Valerie Cotsalas Real Estate 7/8/2007 The Kremlin Flexes, and a Tycoon Reels Andrew E. Kramer Business 7/15/2007 Electric Cars Nearly Ready, but Batteries Are Less So Kevin Cameron Automotive 9/23/2007 GreenTech; They're Electric, but Can They Be Fantastic? Lawrence Ulrich Automotive 10/24/2007 Getting to Green Micheline Maynard Automotive 10/24/2007 Challenging Gasoline: Diesel, Ethanol, Hydrogen Matthew L. Wald Automotive 10/28/2007 Go Green, Someday, For Now Go Fast Jerry Garrett Automotive 11/7/2007 The Carbon Calculus Matthew L. Wald Business 11/9/2007 Fuel Without the Fossil Matthew L. Wald Business 11/11/2007 Far Out: Studios Imagine Smart Cars for a World Transformed by Robots Phil Patton Automotive 11/18/2007 L.A. Auto Show; California Dreaming With a Tint of Green, at a Car Show Jerry Garrett Automotive 12/9/2007 GreenTech; Hydrogen Car Is Here, a Bit Ahead of Its Time Norman Mayersohn Automotive 12/9/2007 G.M.'s Fuel-Cell Test: 100 Cars, No Charge Lawrence Ulrich Automotive 12/9/2007 Living the Hydrogen Life Tori Tellem Automotive 12/16/2007 Getting an Early Start on Drawing the Future Tanya Mohn Automotive 12/18/2007 New Type of Coal Plant Moves Ahead, Haltingly Matthew L. Wald Business 12/20/2007 Nanotechnology Companies Planning to Sell Shares James Flanigan Business 1/14/2008 A Fuel-Cell Cadillac Jim McCraw Automotive 1/20/2008 Dr. Jekyll Meets Mr. Hybrid Lawrence Ulrich Automotive 1/27/2008 Bush's 2002 State of the Union Volunteerism Initiative Is Seen as Sputtering Sheryl Gay Stolberg Washington 1/31/2008 Higher Costs Cited as U.S. Shuts Down Coal Project Matthew L. Wald Business 2/10/2008 From Bush, Foe of Earmarks, Similar Items Robert Pear Washington 2/19/2008 Scientists Would Turn Greenhouse Gas Into Gasoline Kenneth Chang Science 3/16/2008 Hydrogen Fuel Station Opens in White Plains Diana Marszalek NY/Region 3/26/2008 For Carbon Emissions, a Goal of Less Than Zero Matthew L. Wald Business 3/28/2008 California Trims Goal for Number of Emission-Free Vehicles Felicity Barringer National 4/20/2008 Invent None Listed Magazine 4/20/2008 Click and Clack Take Manhattan Richard S. Chang Automotive 5/27/2008 Rockefellers Seek Change at Exxon Clifford Krauss Business 6/17/2008 Latest Honda Runs on Hydrogen, Not Petroleum Martin Fackler Business 6/29/2008 Eureka! Where Do I Cash the Check? George Johnson National 7/3/2008 A Land Rush Is Likely, So a Lawyer Gets Ready Peter Applebome NY/Region 7/8/2008 Europeans Reconsider Biofuel Goal James Kanter Business 7/20/2008 A Sedan Fueled By the Future Lawrence Ulrich Automotive 7/20/2008 What Is One Volt Worth Jerry Garrett Automotive 7/24/2008 Gassing Up With Garbage Matthew L. Wald Business 8/3/2008 The Courtesy Is Doing No Favors Robin Finn NY/Region 8/7/2008 And Now, to Try and Catch the Wind Alice Rawsthorn Home and Garden Geoffrey Ballard, 75, Fuel-Cell Pioneer Who Created Bus Powered by 8/12/2008 Jeremy Pearce Business Hydrogen, Dies 8/26/2008 Honda Stays True to Efficient Driving Bill Vlasic Business 9/12/2008 Europe Lowers Goals for Biofuel Use James Kanter Business 9/24/2008 Pumping Hydrogen Jad Mouawad Business 9/30/2008 Buffett Buys Stake in Chinese Battery Manufacturer Keith Bradsher Business 10/3/2008 Capitalism to the Rescue Jon Gertner Magazine 10/30/2008 Long May You Run: Neil Young's Eco-Lincoln Dan Frost Automotive 11/16/2008 At Exxon, Making the Case for Oil Jad Mouawad Business 11/16/2008 Cranking the Volt to 100 M.P.G. Don Sherman Automotive 11/22/2008 Hoping Not to Repeat the Mistakes of the Past Matthew L. Wald Business 11/22/2008 G.M.'s Latest Great Green Hope Is a Tall Order Micheline Maynard Business 11/23/2008 Future Visions of Far-Out Races Phil Patton Automotive 12/22/2008 Reeling South Carolina City Is a Snapshot og Economic Woes Peter S. Goodman Business Figure 30 (continued)- List of Source Material Collected from New York Times

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Energy Policy Issue Title Author Jan-01 United States Experiences with Gasoline Additives Nadim Jan-01 Modernise it, sustainabilise it! Swiss energy policy on the eve of electricity market liberalisation Jegen Jan-01 Power sector reform and distributed generation in sub-Saharan Africa Turkson

Jan-01 Technological progress and long-term energy demand * a survey of recent approaches and a Danish case Jan-01 Analysis of the impacts of carbon taxes on energy systems in Japan Nakata Mar-01 The renewable portfolio standard: design considerations and an implementation survey Berry Apr-01 Distortion, illusion and confusion: how to improve global oil market data Tempest Future electric power technology choices of Brazil: a possible confict between local pollution and global Apr-01 climate change Schaeffer Apr-01 The future of gas infrastructures in Eurasia Klaassen May-01 Strategic considerations for clean coal R&D McMullan

Sep-01 Who's afraid of atmospheric stabilisation? Making the link between energy resources and climate change Grubb Oct-01 Climate change levy*hot air or cold comfort? Church Oct-01 Uncertainty in estimating and mitigating industrial related GHG emissions El-fadel Nov-01 Scenarios for a clean energy future Brown Nov-01 Energy futures for the US transport sector Greene Nov-01 Electricity sector analysis in the clean energy futures study Hadley Feb-02 Conference report n/a Mar-02 Escaping carbon lock-in Unruh May-02 Green electricity in the market place: the policy challenge Fuchs Jun-02 Commercializing an alternate vehicle fuel: lessons learnedfrom natural gas for vehicles Flynn Benchmarking the energy efficiency of Dutch industry: an assessment of the expected effect on energy Jun-02 consumption and CO2 emissions Phylipsen Jun-02 Distributed generation and distribution utilities Strachan Jul-02 The Mexican energy sector: integrated dynamic analysis of the natural gas/refining system Leach Encouraging distributed generation of power that improves air quality: can we have our cake and eat it Jul-02 too? Allison Jul-02 A Shapley decomposition of carbon emissions without residuals Albrect Aug-02 CO2 in the iron and steel industry: an analysis of Japanese emission reduction potentials Gielen Sep-02 Renewables in Africa—meeting the energy needs of the poor Karekezi

Nov-02 Comparing recommendations from the World Commission on Dams and the IEA initiative on hydropower Gagnon Nov-02 Life-cycle assessment of electricity generation options: The status of research in year 2001 Gagnon Nov-02 The evolving context for hydropower development Oud Jan-03 Energy policy and climate change Jean-Baptiste Mar-03 A critical assessment of renewable energy usage in the USA Klass Globalization of the automobile industry in China: dynamics and barriers in greening of the road May-03 transportation Gan Jun-03 Role of nuclear fusion in future energy systems and the environment under future uncertainties Tokimatsu Jun-03 Green paper with green electricity? Greening strategies of Nordic pulp andpaper industry Luukkanen Jul-03 Long-term outlook of energy use and CO2 emissions from transport in Central and Eastern Europe Zachariadis Competition in the market for space heating. District heating as the infrastructure for competition among Jul-03 fuels and technologies Grohnheit Global energy scenarios meeting stringent CO2 constraints— cost-effective fuel choices in the Aug-03 transportation sector Azar The insurance and risk management industries:'newplayers in the delivery of energy-efficient and Sep-03 renewable energy products and services Mills Sep-03 A lifestyle-based scenario for US buildings: implications for energy use Diamond Sep-03 Future implications of China’s energy-technology choices Larson Oct-03 A strategy for introducing hydrogen into transportation Farrell Carbon emission and mitigation cost comparisons between fossil fuel, nuclear and renewable energy Nov-03 resources for electricity generation Sims Nov-03 Stalemate in energy markets: supply extension versus demand reduction Verbruggen Dec-03 LPG: a secure, cleaner transport fuel? A policy recommendation for Europe Johnson The potential of solar electric power for meeting future US energy needs: a comparison of projections of Jan-04 solar electric energy generation and Arctic National Wildlife Refuge oil production Byrne Figure 31- List of Source Material Collected from Energy Policy

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Energy Policy (Cont) Issue Title Author Fuel cell system economics: comparing the costs of generating power with stationary andmotor vehicle Jan-04 PEM fuel cell systems Lipmann Jan-04 OPEC’s optimal crude oil price Horn Jan-04 Societal lifecycle costs of cars with alternative fuels/engines Ogden Feb-04 Carbon exergy tax: a thermo-economic method to increase the efficient use of exergy resources Santarelli Mar-04 Baseline recommendations for greenhouse gas mitigation projects in the electric power sector Kartha Mar-04 Greening London’s black cabs: a study of driver’s preferences for fuel cell taxis Mourato May-04 Efficiency versus cost of alternative fuels from renewable resources: outlining decision parameter Kaul Jul-04 Hydrogen from renewable resources—the hundred year commitment Adamson Jul-04 Energy for sustainable development in China Weidou Jul-04 Action plan for wind energy development in the Canary Islands Calero Jul-04 The Kyoto protocol—a victimof supply security? or: if Maslow were in energy politics Frei Harvesting and redistributing renewable energy: on the role of gas and electricity grids to overcome Sep-04 intermittency through the generation and storage ofhydrogen Anderson Sep-04 Distributed generation: remote power systems with advanced storage technologies Clark Oct-04 Bioenergy policy and market development in Finland and Sweden Ericsson Scenarios for a robust policy mix: the final report of the German study commission on sustainable energy Oct-04 supply Heinneke Nov-04 Oil supply insecurity: control versus damage costs Owen Nov-04 Co-provision in sustainable energy systems: the case of micro-generation Watson Step changes for decarbonising the energy system:research needs for renewables, energy efficiency and Nov-04 nuclear power Ekins Dec-04 Will OPEC lose from the Kyoto Protocol? Barnett Dec-04 Does the Bush Administration’s climate policy mean climate protection? Blanchard The early adoption of green power by Dutch households . An empirical exploration of factors influencing Jan-05 the early adoption of green electricity for domestic purposes Arkesteijn Jan-05 Global experience curves for wind farms Junginger Mar-05 UK biomass energy since 1990: the mismatch between project types and policy objectives van der Horst Natural gas as an alternative to crude oil in automotive fuel chains well-to-wheel analysis and transition Mar-05 strategy development Hekkert Apr-05 Distributed generation: definition, benefits and issues Pepermans Jun-05 Using energy scenarios to explore alternative energy pathways in California Ghanadan Jul-05 Multi-criteria analysis of alternative-fuel buses for public transportation Tzeng Near-term technology policies for long-term climate targets— economy wide versus technology specific Aug-05 approaches Sanden Aug-05 Assessing policies towards sustainable transport in Europe: an integrated model Zachariadis Exploring the possibilities for setting up sustainable energy systems for the long term:two visions for the Sep-05 Dutch energy system in 2050 Treffers Oct-05 Accelerating residential PV expansion: demand analysis for competitive electricity markets Duke

Nov-05 UK innovation systems for new and renewable energy technologies: drivers, barriers and systems failures Foxon Nov-05 Diversification and localization of energy systems for sustainable development and energy security Li Nov-05 Questioning hydrogen Hammerschlaag Dec-05 The potential contribution of renewable energy to electricity supply in Saudi Arabia Alnatheer Jan-06 Comparison of options for distributed generation in India Banerjee Feb-06 Bio-energy in Europe: changing technology choices Faaij Mar-06 Renewable energy: Externality costs as market barriers Owen Mar-06 Polices for increasing energy efficiency: Thirty years of experience in OECD countries Geller Mar-06 Government policy and the development of electric vehicles in Japan Ahman Mar-06 Have we run out of oil yet? Oil peaking analysis from an optimist’s perspective Greene Mar-06 The economics of large-scale wind power in a carbon constrained world DeCarolis Mar-06 Limits to leapfrogging in energy technologies? Evidence from the Chinese automobile industry Gallagher Climate change dilemma: technology, social change or both? An examination of long-term transport policy Apr-06 choices in the United States Rajan Small distributed generation versus centralised supply: a social cost–benefit analysis in the residential and May-06 service sectors Gulli Market perspectives of stationary fuel cells in a sustainable energy supply system—long-term scenarios for May-06 Germany Krewitt May-06 A global survey of hydrogen energy research, development and policy Solomon Figure 31 (continued)- List of Source Material Collected from Energy Policy

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Energy Policy (Cont) Issue Title Author Jun-06 Vehicle technology under CO2 constraint: a general equilibrium analysis Schafer Jul-06 Globalizing carbon lock-in Unruh Jul-06 Electricity intensity backstop level to meet sustainable backstop supply technologies Verbruggen Transition to hydrogen-based transportation in China: Lessons learned from alternative fuel vehicle Jul-06 programs in the United States and China Zhao Development of European hydrogen infrastructure scenarios—CO2 reduction potential and infrastructure Jul-06 investment Weitschel Jul-06 Prospects for hydrogen in the German energy system Hake Jul-06 Towards sustainable energy systems: The related role of hydrogen Hennicke Jul-06 Energy system aspects of hydrogen as an alternative fuel in transport Ramesohl Forecasts, scenarios, visions, backcasts and roadmaps to the hydrogen economy: A review of the hydrogen Jul-06 futures literature McDowall What governs the transition to a sustainable hydrogen economy? Articulating the relationship between Jul-06 technologies and political institutions Hisshemoller Jul-06 Introduction to the special issue on ‘hydrogen’ in ‘Energy Policy n/a Modeling technical change in energy system analysis: analyzing the introduction of learning-by-doing in Aug-06 bottom-up energy models Berglund Aug-06 Public understanding of environmental impacts of electricity deregulation Johnson System failure, innovation policy and patents: Fuel cells and related hydrogen technology in Norway Sep-06 1990–2002 Godoe Sep-06 How much transport can the climate stand?—Sweden on a sustainable path in 2050 Akerman Sep-06 Analysis of long-range clean energy investment scenarios for Eritrea, East Africa Buskirk Sep-06 On the baseline evolution of automobile fuel economy in Europe Zachariadis Oct-06 Modelling long-term oil price and extraction with a Hubbert approach: The LOPEX model Rehrl Oct-06 Energy for sustainable development in Malaysia: Energy policy and alternative energy Rahman Oct-06 Long-term security of energy supply and climate change Turton Oct-06 Useful models for simulating policies to induce technological change Rivers Oct-06 Global challenges in energy Dorian Nov-06 Outlook for advanced biofuels Hamelink Nov-06 Beyond the learning curve: factors influencing cost reductions in photovoltaics Nemet Nov-06 Stimulating the use of biofuels in the European Union: Implications for climate change policy Ryan Nov-06 The role of hydropower in meeting Turkey’s electric energy demand Yuksek Nov-06 Energy forecasting: Predictions, reality and analysis of causes of error Utgikar Nov-06 Reconnecting the technology characterisation of the hydrogen economy to contexts of consumption Hodson Nov-06 An options approach to investment in a hydrogen infrastructure Benthem Nov-06 Emissions from distributed vs. centralized generation: The importance of system performance Strachan Nov-06 A green hydrogen economy Rifkin Nov-06 The car and fuel of the future Rohm Dec-06 Diversity and security in UK electricity generation: The influence of low-carbon objectives Grubb Dec-06 Feebates: An effective regulatory instrument for cost-constrained environmental policy Johnson Dec-06 Enhancing renewable energy in the Arab States of the Gulf: Constraints & efforts Patlitzianas Dec-06 The role of energy efficiency in reducing Scottish and UK CO2 emissions Kelly Dec-06 Public perceptions of underground coal gasification in the United Kingdom Shackley Dec-06 Perspectives of Stirling engines use for distributed generation in Brazil Corria The impact of large-scale energy storage requirements on the choice between electricity and hydrogen as Dec-06 the major energy carrier in a non-fossil renewables-only scenario Converse U.S. energy research and development: Declining investment, increasing need, and the feasibility of Jan-07 expansion Nemet Jan-07 Multi-criteria evaluation of natural gas resources Afgan Development of the auto gas and LPG-powered vehicle sector in Turkey: A statistical case study of the Jan-07 sector for Bursa Karamangil Jan-07 Challenges to a climate stabilizing energy future Green Using solar energy to arrest the increasing rate of fossil-fuel consumption: The southwestern states of the Jan-07 USA as case studies Faiman Jan-07 Structuring objectives to facilitate convergence of divergent opinion in hydrogen production decisions Yu¨ zu¨ gu¨ llu Jan-07 California’s greenhouse gas law, Assembly Bill 1493: Deficiencies, alternatives, and implications for Johnson Figure 31 (continued)- List of Source Material Collected from Energy Policy

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Energy Policy (Cont) Issue Title Author Jan-07 Incorporating stress in electric power systems reliability models Zerriffi Jan-07 Life cycle cost analysis of a car, a city bus and an intercity bus powertrain for year 2005 and 2020 Hellgren Feb-07 World energy analysis: H2 now or later? Mason Feb-07 The United States and international climate cooperation: International ‘‘pull’’ versus domestic ‘‘push’’ Bang Feb-07 Clean energy scenarios for Australia Saddler Feb-07 How would the gas exporting countries forum influence gas trade? Wagbara Feb-07 Prospects of the European gas market Kjarstad Internalisation of external cost in the power generation sector: Analysis with Global Multi-regional Feb-07 MARKAL model Rafaj Feb-07 Internalizing externalities of electricity generation: An analysis with MESSAGE-MACRO Klaassen Feb-07 Evaluation of green-certificates policies using the MARKAL-MACRO-Italy model Contaldi ACROPOLIS: An example of international collaboration in the field of energy modelling to support Feb-07 greenhouse gases mitigation policies Das Feb-07 Introduction: Technology modelling of climate policies (the ACROPOLIS project) n/a Mar-07 A crash programme scenario for the Canadian oil sands industry Soderbergh H2POWER: Development of a methodology to calculate life cycle cost Mar-07 of small and medium-scale hydrogen systems Verduzco Mar-07 Artificial neural network analysis of world green energy use Ermis Mar-07 A post-Kyoto analysis of the Greek electric sector Dagoumas Towards improved policy processes for promoting innovation in Mar-07 renewable electricity technologies in the UK Foxon Mar-07 Meso-level analysis, the missing link in energy strategies Schenk Baseload wind energy: modeling the competition between gas turbines Mar-07 and compressed air energy storage for supplemental generation Greenblatt Apr-07 Identification of key oil refining technologies for China National Petroleum Co. (CNPC) Liu Apr-07 Economic analysis of the renovation of small-scale district heating systems—4 Lithuanian case studies Dzenajavicˇiene’ Apr-07 Greenhouse-gas emissions from solar electric- and nuclear power: A life-cycle study Fthenakis Niche accumulation and hybridisation strategies in transition processes towards a sustainable energy Apr-07 system: An assessment of differences and pitfalls Raven Apr-07 Opportunities for low-cost CO2 storage demonstration projects in China Meng Apr-07 Transition strategy of the transportation energy and powertrain in China Wang Public perception related to a hydrogen hybrid internal combustion engine transit bus demonstration and Apr-07 hydrogen fuel Hickson Apr-07 An emerging market in fuel cells? Residential combined heat and power in four countries Brown Apr-07 Assessing reliability in energy supply systems McCarthy May-07 Grid-connected vehicles as the core of future land-based transport systems Gilbert A study on making a long-term improvement in the national energy efficiency and GHG control plans by the May-07 AHP approach Lee May-07 Strategies for the deployment of micro-generation: Implications for social acceptance Sauter Jun-07 Conference Report- Thermec 2006 n/a Jun-07 Life cycle cost analysis of alternative vehicles and fuels in Thailand Goedecke

Jun-07 Strategic niche management for biofuels: Analysing past experiments for developing new biofuel policies van der Laak Jun-07 Scenario-based analyses of energy system development and its environmental implications in Thailand Shrestha Jul-07 Understanding energy and exergy efficiencies for improved energy management in power plants Kanoglu The European power plant infrastructure—Presentation of the Chalmers energy infrastructure database Jul-07 with applications Kjarstad Jul-07 Is the public willing to pay for hydrogen buses? A comparative study of preferences in four cities O'Garra Jul-07 Biofuels: What a Biopact between North and South could achieve Matthews Aug-07 Societal acceptance of carbon capture and storage technologies van Alphen Aug-07 Prospects of sugarcane milling waste utilization for hydrogen production in India Singh Aug-07 What to expect from a greater geographic dispersion of wind farms?—A risk portfolio approach Drake Trade-off in emissions of acid gas pollutants and of carbon dioxide in fossil fuel power plants with carbon Aug-07 capture Tzimas Aug-07 A Northern California–British Columbia partnership for renewable energy Orans Sep-07 Should we drill in the Arctic National Wildlife Refuge? An economic perspective Kotchen Figure 31 (continued)- List of Source Material Collected from Energy Policy

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Energy Policy (Cont) Issue Title Author Developing a long-term local society design methodology towards a low-carbon economy: An application Sep-07 to Shiga Prefecture in Japan Shimada American policy conflict in the greenhouse: Divergent trends in federal, regional, state, and local green Sep-07 energy and climate change policy Byrne Sep-07 Distributed energy resources market diffusion model Maribu Oct-07 As if Kyoto mattered: The clean development mechanism and transportation Zegras Oct-07 Stakeholder perceptions of CO2 capture and storage in Europe: Results from a survey Shackley Oct-07 The 2 1C scenario—A sustainable world energy perspective Krewitt Turn of the century refueling: A review of innovations in early gasoline refueling methods and analogies Oct-07 for hydrogen Melaina Oct-07 Carbon-neutral economy with fossil fuel-based hydrogen energy and carbon materials Halloran Nov-07 Public policy and biofuels: The way forward? Charles Nov-07 Domestic futures—Which way to a low-carbon housing stock? Natarajan Nov-07 Potential of hydrogen from oil palm biomass as a source of renewable energy worldwide Kelly-Yong Nov-07 Differing perspectives of major oil firms on future energy developments: An illustrative framework Chang Nov-07 How the next US president should slow global warming Lokey Nov-07 A MERGE model with endogenous technological change and the cost of carbon stabilization Kypreos Research, development, demonstration, and early deployment policies for advanced-coal technology in Dec-07 China Zhao Dec-07 Major oil exporters may profit rather than lose, in a carbon-constrained world Persson Dec-07 Trigeneration primary energy saving evaluation for energy planning and policy development Chicco Dec-07 Surface technologies 2006—Alternative energies and policy options Rose Bioenergy expansion in the EU: Cost-effective climate change mitigation, employment creation and Dec-07 reduced dependency on imported fuels Berndes Jan-08 International technology-oriented agreements to address climate change Coninck Jan-08 Technological learning in energy–environment–economy modelling: A survey Kahouli-Brahmi Jan-08 Strategic thinking on IGCC development in China Liu Feb-08 External determinants for the adoption of stationary fuel cells—Infrastructure and policy issues Karger Feb-08 A hydrogen economy and its impact on the world as we know it Blanchette Preparing for global rollout: A ‘developed country first’ demonstration programme for rapid CCS Feb-08 deployment Gibbins Mar-08 Economics of producing hydrogen as transportation fuel using offshore wind energy systems Mathur Mar-08 Oil vulnerability index of oil-importing countries Gupta Mar-08 The Triptych approach revisited: A staged sectoral approach for climate mitigation den Elzen

Mar-08 The dimensions of the policy debate over transportation energy: The case of hydrogen in the United States Collantes Functionality of the approach of hierarchical analysis in the full cost accounting in the IRP of a metropolitan Mar-08 airport Cicone Apr-08 The capacity credit of micro-combined heat and power Hawkes

Apr-08 Is cluster policy useful for the energy sector? Assessing self-declared hydrogen clusters in the Netherlands Mans Apr-08 Intermediate steps towards the 2000W society in Switzerland: An energy–economic scenario analysis Schulz Apr-08 The competitiveness of Korea as a developer of hydrogen energy technology: The AHP approach Lee May-08 The potential role of hydrogen energy in India and Western Europe van Ruijven May-08 The possible role of nuclear energy in Italy Esposto An indicator framework for assessing US state carbon emissions reduction efforts (with baseline trends Jun-08 from 1990 to 2001) Jiusto Cost development of future technologies for power generation—A study based on experience curves and Jun-08 complementary bottom-up assessments Neij Learning for supplying as a motive to be the early adopter of a new energy technology: A study on the Jun-08 adoption of stationary fuel cells Huang Jun-08 Investigating attitudes to hydrogen refuelling facilities and the social cost to local residents O'Garra Driving forces and barriers in the development and implementation of coal-to-liquids (CtL) technologies in Jun-08 Germany Vallentin Figure 31 (continued)- List of Source Material Collected from Energy Policy

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Energy Policy (Cont) Issue Title Author Jul-08 Planning an energy-conserving policy for Taiwan based on international Lu Jul-08 Impact of tightening the sulfur specifications on the automotive fuels’ Moghaddam Jul-08 The role of nuclear energy in long-term climate scenarios: Vaillancourt Aug-08 Refueling availability for alternative fuel vehicle markets: Sufficient urban Melaina Aug-08 Policy drivers and barriers for coal-to-liquids (CtL) technologies Vallentin Aug-08 Building and interconnecting hydrogen networks: Insights from the Bento Aug-08 Sustainability assessment of a hybrid energy system Afgan Aug-08 Important roles of Fischer– Tropsch synfuels in the global energy future Takeshita Sep-08 Pollution tax heuristics: An empirical study of willingness to pay higher Hsu Sep-08 Cost of energy and environmental policy in Portuguese CO2 Simoes Sep-08 Developing pathways to low carbon land-based passenger transport in Great Bristow Sep-08 Reevaluation of Turkey’s hydropower potential and electric energy demand Yuksek Sep-08 Civilisation and energy payback Gagnon Oct-08 Nuclear hydrogen: An assessment of product flexibility and market viability Botterud Oct-08 The role of biomass in California’s hydrogen economy Parker Oct-08 A fuzzy multi-criteria decision-making model for trigeneration system Wang Oct-08 The Tyndall decarbonisation scenarios—Part II: Scenarios for a 60% CO2 Anderson Oct-08 The Tyndall decarbonisation scenarios—Part I: Development of a backcasting Mander Oct-08 What ify? Utility vision 2020 Frei Nov-08 Accelerating the transition to sustainable energy systems Jefferson Nov-08 Key policy considerations for facilitating low carbon technology transfer to Ockwell Nov-08 Externalities of the transport sector and the role of hydrogen in a sustainable Doll Nov-08 Renewable and nuclear power: A common future? Verbruggen Dec-08 Science review of internal combustion engines Taylor Dec-08 The energy and monetary implications of the ‘24/7’ ‘always on’ society Loveday Dec-08 How to support growth with less energy Barrett Dec-08 Infrastructure challenges for the built environment Roberts Dec-08 Effects of climate change on the built environment Roberts Dec-08 Futureproofconstruction—Futurebuildingandsystemsdesignforenergy and fuelflexibility Pitts Dec-08 Centralised and distributed electricity systems Bouffard Dec-08 Enabling technologies for demand management: Transport Smith Dec-08 Biofuels and the biorefinery concept Taylor Dec-08 Bioenergy for heat and electricity in the UK: A research atlas and roadmap Taylor Dec-08 New technology and possible advances in energy storage Baker Dec-08 Energy storage: The route to liberation from the fossil fuel economy? Hall Dec-08 Hydrogen and fuel cells: Towards a sustainable energy future Edwards Dec-08 Energy-storage technologies and electricity generation Hall Dec-08 Efficiency trends in electric machines and drives Mecrow Dec-08 Carbon capture and storage Gibbins Dec-08 Clean fossil-fuelled power generation Oliver Dec-08 Making a material difference in energy Driver Figure 31 (continued)- List of Source Material Collected from Energy Policy

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Appendix B

REGRESSION ANALYSIS RESULTS

This appendix contains the statistical results of the regression analyses that were performed during this case study. These results were used to help identify trends in the importance of different indicators and to establish the relative capabilities the Bush and Energy Policy indicators to serve as predictors of future indicators in The New York Times. Section B.1 contains the results of the regressions which only considered the Bush indicators as a predictor, Section B.2 contains the results of the regressions based only on the Energy Policy indicators, and Section B.3 displays the results of the multivariable regression which considered the indicators from each.

All three sections contain many regressions, categorized by the time span considered and the specific indicators that were analyzed. Four time periods were considered: 1) the entire span of the Bush presidency (2001-2008); 2) the period of time prior to the publication of the Energy Policy special issue on hydrogen (2001-2005); 3) the year of the special issue (2006); and 4) the two years following the special issue, which were also the lame duck years of the Bush presidency (2007-2008). In each time span six individual regressions were run, one for each of the individual categories of indicators (GHGs, Efficiency, Sustainability, Sequestration, and Sources) and another which looked at the sum of the indicators across all five categories.

With each source analyzed independently in a single variable regression as well as the two analyzed together in a multiple variable regression, each considering four time spans, each of which contains six independent regression analyses, this leads to a total of 72 different regressions. While the most relevant results of these analyses are presented in Chapter 5- Results, this appendix contains the full set of results.

235

B.1 Bush Only Analysis, Single Variable

B.1.1 Bush, 2001-2008 Regression Statistics Multiple R 0.447231731 R Square 0.200016221 Adjusted R Square 0.19972415 Standard Error 6.575859442 Observations 2741

ANOVA df SS MS F Significance F Regression 1 29612.91175 29612.91175 684.8194224 6.3331E-135 Residual 2739 118439.6391 43.2419274 Total 2740 148052.5509

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 6.247214705 0.165564831 37.7327399 2.8531E-251 5.92257014 6.571859271 5.92257014 6.571859271 Bush 0.294421023 0.011250732 26.16905467 6.3331E-135 0.272360245 0.316481802 0.272360245 0.316481802 Figure 32- Regression Results: Combined Bush Indicators, 2001-2008 Regression Statistics Multiple R 0.279280107 R Square 0.077997378 Adjusted R Square 0.077660758 Standard Error 3.433111024 Observations 2741

ANOVA df SS MS F Significance F Regression 1 2730.961505 2730.961505 231.707388 2.72834E-50 Residual 2739 32282.54233 11.78625131 Total 2740 35013.50383

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 4.519926591 0.089817602 50.32339413 0 4.3438095 4.696043682 4.3438095 4.696043682 Bush 0.183746948 0.012071193 15.22193772 2.72834E-50 0.160077385 0.207416511 0.160077385 0.207416511 Figure 33- Regression Results: Bush GHG Indicators, 2001-2008

Regression Statistics Multiple R 0.042557398 R Square 0.001811132 Adjusted R Square 0.001446697 Standard Error 1.307847308 Observations 2741

ANOVA df SS MS F Significance F Regression 1 8.500481616 8.500481616 4.96969169 0.02587605 Residual 2739 4684.962488 1.710464581 Total 2740 4693.46297

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -0.245680732 0.027374682 -8.974742858 5.15033E-19 -0.299357843 -0.192003621 -0.299357843 -0.192003621 Bush 0.065339911 0.029309865 2.229280532 0.02587605 0.007868235 0.122811586 0.007868235 0.122811586 Figure 34- Regression Results: Bush Efficiency Indicators, 2001-2008

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Regression Statistics Multiple R 0.361624803 R Square 0.130772498 Adjusted R Square 0.130455146 Standard Error 2.926286256 Observations 2741

ANOVA df SS MS F Significance F Regression 1 3528.650202 3528.650202 412.0737911 1.84957E-85 Residual 2739 23454.47129 8.563151255 Total 2740 26983.12149

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 2.245709103 0.065607251 34.22958717 4.361E-214 2.117064407 2.374353799 2.117064407 2.374353799 Bush 0.4535021 0.022340444 20.29960076 1.84957E-85 0.409696276 0.497307923 0.409696276 0.497307923 Figure 35- Regression Results: Bush Sustainability Indicators, 2001-2008

Regression Statistics Multiple R 0.064848692 R Square 0.004205353 Adjusted R Square 0.003841791 Standard Error 0.736223518 Observations 2741

ANOVA df SS MS F Significance F Regression 1 6.269661001 6.269661001 11.56710523 0.000680911 Residual 2739 1484.606662 0.542025068 Total 2740 1490.876323

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.51344965 0.018680466 27.48591257 4.3229E-147 0.476820423 0.550078876 0.476820423 0.550078876 Bush 0.040795199 0.011994902 3.401044726 0.000680911 0.017275229 0.064315169 0.017275229 0.064315169 Figure 36- Regression Results: Bush Sequestration Indicators, 2001-2008

Regression Statistics Multiple R 0.333931569 R Square 0.111510293 Adjusted R Square 0.111185908 Standard Error 1.899720774 Observations 2741

ANOVA df SS MS F Significance F Regression 1 1240.606728 1240.606728 343.7594045 2.17599E-72 Residual 2739 9884.883969 3.608939018 Total 2740 11125.4907

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -0.009135222 0.040836187 -0.223704077 0.823004256 -0.089208061 0.070937618 -0.089208061 0.070937618 Bush 0.2229079 0.012022594 18.54074984 2.17599E-72 0.199333632 0.246482168 0.199333632 0.246482168 Figure 37- Regression Results: Bush Sources Indicators, 2001-2008

237

B.1.2 Bush, 2001-2005 Regression Statistics Multiple R 0.816306499 R Square 0.6663563 Adjusted R Square 0.66615323 Standard Error 4.705918036 Observations 1645

ANOVA df SS MS F Significance F Regression 1 72669.11325 72669.11325 3281.414882 0 Residual 1643 36385.32687 22.14566456 Total 1644 109054.4401

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 4.809917674 0.148534259 32.3825473 2.4382E-178 4.518581257 5.101254092 4.518581257 5.101254092 Bush 0.643259877 0.011229383 57.28363537 0 0.621234465 0.665285288 0.621234465 0.665285288 Figure 38- Regression Results: Combined Bush Indicators, 2001-2005

Regression Statistics Multiple R 0.48302698 R Square 0.233315064 Adjusted R Square 0.232848426 Standard Error 3.390079758 Observations 1645

ANOVA df SS MS F Significance F Regression 1 5746.233163 5746.233163 499.9924107 6.63787E-97 Residual 1643 18882.40878 11.49264077 Total 1644 24628.64195

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 4.943261336 0.109929382 44.96760761 1.4932E-288 4.727644868 5.158877805 4.727644868 5.158877805 Bush 0.33350287 0.014914815 22.36051007 6.63787E-97 0.304248819 0.362756921 0.304248819 0.362756921 Figure 39- Regression Results: Bush GHG Indicators, 2001-2005

Regression Statistics Multiple R 0.19108137 R Square 0.03651209 Adjusted R Square 0.03592567 Standard Error 1.04252183 Observations 1645

ANOVA df SS MS F Significance F Regression 1 67.67033109 67.67033109 62.26270524 5.44302E-15 Residual 1643 1785.69745 1.086851765 Total 1644 1853.367781

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.207261299 0.027291526 7.594346187 5.16039E-14 0.153731456 0.260791141 0.153731456 0.260791141 Bush 0.223368036 0.02830786 7.89067204 5.44302E-15 0.167844749 0.278891324 0.167844749 0.278891324 Figure 40- Regression Results: Bush Efficiency Indicators, 2001-2005

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Regression Statistics Multiple R 0.742044902 R Square 0.550630636 Adjusted R Square 0.550357131 Standard Error 2.465599245 Observations 1645

ANOVA df SS MS F Significance F Regression 1 12238.81728 12238.81728 2013.235012 1.0893E-287 Residual 1643 9988.09214 6.079179635 Total 1644 22226.90942

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 1.412467668 0.071085007 19.87012079 6.54011E-79 1.273040904 1.551894433 1.273040904 1.551894433 Bush 1.702874568 0.037952066 44.86908748 1.0893E-287 1.628435048 1.777314088 1.628435048 1.777314088 Figure 41- Regression Results: Bush Sustainability Indicators, 2001-2005

Regression Statistics Multiple R 0.064773253 R Square 0.004195574 Adjusted R Square 0.003589485 Standard Error 0.759964357 Observations 1645

ANOVA df SS MS F Significance F Regression 1 3.997987035 3.997987035 6.922371995 0.008591999 Residual 1643 948.907788 0.577545824 Total 1644 952.9057751

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.377364648 0.02320359 16.26320125 2.93521E-55 0.331852921 0.422876376 0.331852921 0.422876376 Bush 0.037777521 0.014358398 2.631040098 0.008591999 0.009614831 0.065940211 0.009614831 0.065940211 Figure 42- Regression Results: Bush Sequestration Indicators, 2001-2005

Regression Statistics Multiple R 0.508765035 R Square 0.258841861 Adjusted R Square 0.258390761 Standard Error 1.867700199 Observations 1645

ANOVA df SS MS F Significance F Regression 1 2001.591855 2001.591855 573.8008603 5.2309E-109 Residual 1643 5731.283525 3.488304032 Total 1644 7732.87538

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -0.709924789 0.051154927 -13.87793568 1.71613E-41 -0.810260518 -0.609589059 -0.810260518 -0.609589059 Bush 0.436295366 0.018213777 23.95414078 5.2309E-109 0.400570703 0.47202003 0.400570703 0.47202003 Figure 43- Regression Results: Bush Sources Indicators, 2001-2005

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B.1.3 Bush, 2006 Regression Statistics Multiple R 0.192601288 R Square 0.037095256 Adjusted R Square 0.034442626 Standard Error 3.20243977 Observations 365

ANOVA df SS MS F Significance F Regression 1 143.4179839 143.4179839 13.98433027 0.000214128 Residual 363 3722.790235 10.25562048 Total 364 3866.208219

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 8.122439299 0.332967877 24.39406277 1.6742E-78 7.467651096 8.777227502 7.467651096 8.777227502 Bush -0.044832783 0.011988776 -3.739562844 0.000214128 -0.068408959 -0.021256607 -0.068408959 -0.021256607 Figure 44- Regression Results: Combined Bush Indicators, 2006

Regression Statistics Multiple R 0.318051078 R Square 0.101156488 Adjusted R Square 0.098680335 Standard Error 1.258340884 Observations 365

ANOVA df SS MS F Significance F Regression 1 64.68638713 64.68638713 40.85227825 5.04492E-10 Residual 363 574.782106 1.58342178 Total 364 639.4684932

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 4.151535328 0.130679389 31.768861 7.3501E-107 3.894551614 4.408519043 3.894551614 4.408519043 Bush -0.068606148 0.010733834 -6.391578698 5.04492E-10 -0.089714455 -0.047497841 -0.089714455 -0.047497841 Figure 45- Regression Results: Bush GHG Indicators, 2006

Regression Statistics Multiple R 0.128824939 R Square 0.016595865 Adjusted R Square 0.013886763 Standard Error 0.765077924 Observations 365

ANOVA df SS MS F Significance F Regression 1 3.585798069 3.585798069 6.125964667 0.013776984 Residual 363 212.4799554 0.58534423 Total 364 216.0657534

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -1.714171518 0.055468158 -30.90370343 1.115E-103 -1.823250797 -1.60509224 -1.823250797 -1.60509224 Bush 0.099348436 0.040139669 2.475068619 0.013776984 0.020412948 0.178283924 0.020412948 0.178283924 Figure 46- Regression Results: Bush Efficiency Indicators, 2006

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Regression Statistics Multiple R 0.543433021 R Square 0.295319448 Adjusted R Square 0.29337818 Standard Error 1.095907132 Observations 365

ANOVA df SS MS F Significance F Regression 1 182.7064564 182.7064564 152.1270305 1.96946E-29 Residual 363 435.9675162 1.201012441 Total 364 618.6739726

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 1.618617488 0.094168107 17.1885954 7.17272E-49 1.433433962 1.803801013 1.433433962 1.803801013 Bush 0.170489157 0.013822722 12.3339787 1.96946E-29 0.143306489 0.197671824 0.143306489 0.197671824 Figure 47- Regression Results: Bush Sustainability Indicators, 2006

Regression Statistics Multiple R 0.050487006 R Square 0.002548938 Adjusted R Square -0.000198861 Standard Error 0.509822721 Observations 365

ANOVA df SS MS F Significance F Regression 1 0.241108568 0.241108568 0.927628897 0.336120964 Residual 363 94.35067225 0.259919207 Total 364 94.59178082

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 1.179518072 0.046819758 25.19274198 1.06126E-81 1.087446053 1.271590092 1.087446053 1.271590092 Bush -0.039200279 0.040700714 -0.963134932 0.336120964 -0.119239073 0.040838515 -0.119239073 0.040838515 Figure 48- Regression Results: Bush Sequestration Indicators, 2006

Regression Statistics Multiple R 0.320406181 R Square 0.102660121 Adjusted R Square 0.10018811 Standard Error 1.677397652 Observations 365

ANOVA df SS MS F Significance F Regression 1 116.8485932 116.8485932 41.52899552 3.69686E-10 Residual 363 1021.359626 2.813662881 Total 364 1138.208219

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 2.52637192 0.174651119 14.46524896 9.12529E-38 2.182916889 2.869826951 2.182916889 2.869826951 Bush -0.157483703 0.024437676 -6.444299459 3.69686E-10 -0.205540898 -0.109426509 -0.205540898 -0.109426509 Figure 49- Regression Results: Bush Sources Indicators, 2006

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B.1.4 Bush, 2007-2008 Regression Statistics Multiple R 0.043481735 R Square 0.001890661 Adjusted R Square 0.000521513 Standard Error 6.458909251 Observations 731

ANOVA df SS MS F Significance F Regression 1 57.6078273 57.6078273 1.380902865 0.240331085 Residual 729 30412.06386 41.71750872 Total 730 30469.67168

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 8.45430115 0.674770483 12.52915081 9.36989E-33 7.129575916 9.779026384 7.129575916 9.779026384 Bush -0.13772717 0.117202819 -1.175118234 0.240331085 -0.367822493 0.092368153 -0.367822493 0.092368153 Figure 50- Regression Results: Combined Bush Indicators, 2007-2008

Regression Statistics Multiple R 0.362292281 R Square 0.131255697 Adjusted R Square 0.130064003 Standard Error 2.394579312 Observations 731

ANOVA df SS MS F Significance F Regression 1 631.5564458 631.5564458 110.1421931 4.30174E-24 Residual 729 4180.093349 5.734010081 Total 730 4811.649795

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 2.061865309 0.206696431 9.975330978 4.69442E-22 1.65607403 2.467656588 1.65607403 2.467656588 Bush 0.644234019 0.061385641 10.49486508 4.30174E-24 0.52372029 0.764747749 0.52372029 0.764747749 Figure 51- Regression Results: Bush GHG Indicators, 2007-2008

Regression Statistics Multiple R 0.198758875 R Square 0.03950509 Adjusted R Square 0.038187539 Standard Error 1.340891765 Observations 731

ANOVA df SS MS F Significance F Regression 1 53.91045152 53.91045152 29.98372057 5.99993E-08 Residual 729 1310.735239 1.797990726 Total 730 1364.645691

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -0.795053004 0.056361885 -14.10621746 3.96351E-40 -0.905703977 -0.68440203 -0.905703977 -0.68440203 Bush 0.649598458 0.118632102 5.475739271 5.99993E-08 0.416697135 0.882499782 0.416697135 0.882499782 Figure 52- Regression Results: Bush Efficiency Indicators, 2007-2008

242

Regression Statistics Multiple R 0.14123199 R Square 0.019946475 Adjusted R Square 0.018602094 Standard Error 2.333222074 Observations 731

ANOVA df SS MS F Significance F Regression 1 80.77110833 80.77110833 14.83692459 0.000127533 Residual 729 3968.621505 5.443925246 Total 730 4049.392613

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 2.448393424 0.139112627 17.60008041 4.73958E-58 2.175284252 2.721502595 2.175284252 2.721502595 Bush 0.475579578 0.123467101 3.851872867 0.000127533 0.23318607 0.717973086 0.23318607 0.717973086 Figure 53- Regression Results: Bush Sustainability Indicators, 2007-2008

Regression Statistics Multiple R 0.108102783 R Square 0.011686212 Adjusted R Square 0.0103305 Standard Error 0.620399866 Observations 731

ANOVA df SS MS F Significance F Regression 1 3.317797035 3.317797035 8.619983283 0.003429603 Residual 729 280.5891797 0.384895994 Total 730 283.9069767

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.500758506 0.035789135 13.99191436 1.41138E-39 0.430496438 0.571020575 0.430496438 0.571020575 Bush 0.065714082 0.022382327 2.935980804 0.003429603 0.021772573 0.109655591 0.021772573 0.109655591 Figure 54- Regression Results: Bush Sequestration Indicators, 2007-2008

Regression Statistics Multiple R 0.191799148 R Square 0.036786913 Adjusted R Square 0.035465633 Standard Error 1.182347972 Observations 731

ANOVA df SS MS F Significance F Regression 1 38.92146012 38.92146012 27.8418765 1.73789E-07 Residual 729 1019.103164 1.397946727 Total 730 1058.024624

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.872077029 0.043850859 19.88734197 1.21565E-70 0.785987994 0.958166063 0.785987994 0.958166063 Bush 3.127922971 0.592798093 5.276540202 1.73789E-07 1.964127855 4.291718087 1.964127855 4.291718087 Figure 55- Regression Results: Bush Sources Indicators, 2007-2008

243

B.2 Energy Policy Indicators Only, Single Variable Regression B.2.1 Energy Policy, 2001-2008 Regression Statistics Multiple R 0.414716121 R Square 0.171989461 Adjusted R Square 0.171687157 Standard Error 6.690057701 Observations 2741

ANOVA df SS MS F Significance F Regression 1 25463.47838 25463.47838 568.928909 2.064E-114 Residual 2739 122589.0725 44.75687204 Total 2740 148052.5509

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 9.666311622 0.130205907 74.23865641 0 9.410999912 9.921623333 9.410999912 9.921623333 EP 0.248685355 0.010426084 23.85223069 2.064E-114 0.228241573 0.269129138 0.228241573 0.269129138 Figure 56- Regression Results: Combined Energy Policy Indicators, 2001-2008

Regression Statistics Multiple R 0.358754021 R Square 0.128704447 Adjusted R Square 0.12838634 Standard Error 3.33737124 Observations 2741

ANOVA df SS MS F Significance F Regression 1 4506.393658 4506.393658 404.5946063 4.82937E-84 Residual 2739 30507.11017 11.1380468 Total 2740 35013.50383

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 5.055799335 0.066751976 75.74007032 0 4.924910027 5.186688642 4.924910027 5.186688642 EP 0.278159456 0.013828777 20.11453719 4.82937E-84 0.251043568 0.305275344 0.251043568 0.305275344 Figure 57- Regression Results: Energy Policy GHG Indicators, 2001-2008

Regression Statistics Multiple R 0.391628216 R Square 0.15337266 Adjusted R Square 0.153063559 Standard Error 1.204472327 Observations 2741

ANOVA df SS MS F Significance F Regression 1 719.8488984 719.8488984 496.1896393 3.664E-101 Residual 2739 3973.614071 1.450753586 Total 2740 4693.46297

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.093229863 0.026980081 3.455507157 0.000557614 0.040326498 0.146133228 0.040326498 0.146133228 EP 0.111166911 0.004990588 22.27531457 3.664E-101 0.101381214 0.120952607 0.101381214 0.120952607 Figure 58- Regression Results: Energy Policy Efficiency Indicators, 2001-2008

244

Regression Statistics Multiple R 0.274748792 R Square 0.075486899 Adjusted R Square 0.075149362 Standard Error 3.017912287 Observations 2741

ANOVA df SS MS F Significance F Regression 1 2036.87216 2036.87216 223.6405471 1.14868E-48 Residual 2739 24946.24933 9.10779457 Total 2740 26983.12149

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 3.069604973 0.058261259 52.68689741 0 2.955364522 3.183845425 2.955364522 3.183845425 EP 0.574151046 0.038392897 14.95461625 1.14868E-48 0.498869083 0.649433009 0.498869083 0.649433009 Figure 59- Regression Results: Energy Policy Sustainability Indicators, 2001-2008

Regression Statistics Multiple R 0.243370564 R Square 0.059229231 Adjusted R Square 0.058885759 Standard Error 0.715594016 Observations 2741

ANOVA df SS MS F Significance F Regression 1 88.30345881 88.30345881 172.4425019 3.02301E-38 Residual 2739 1402.572864 0.512074795 Total 2740 1490.876323

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.689760452 0.017079482 40.38532578 3.4937E-280 0.656270483 0.723250421 0.656270483 0.723250421 EP -0.05290376 0.004028695 -13.13173644 3.02301E-38 -0.060803348 -0.045004172 -0.060803348 -0.045004172 Figure 60- Regression Results: Energy Policy Sequestration Indicators, 2001-2008

Regression Statistics Multiple R 0.12867139 R Square 0.016556327 Adjusted R Square 0.016197275 Standard Error 1.99865722 Observations 2741

ANOVA df SS MS F Significance F Regression 1 184.1972585 184.1972585 46.11121106 1.3649E-11 Residual 2739 10941.29344 3.994630682 Total 2740 11125.4907

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.522556556 0.046844998 11.15501284 2.7283E-28 0.430701456 0.614411655 0.430701456 0.614411655 EP 0.055402644 0.008158818 6.790523622 1.3649E-11 0.039404586 0.071400703 0.039404586 0.071400703 Figure 61- Regression Results: Energy Policy Sources Indicators, 2001-2008

245

B.2.2 Energy Policy, 2001-2005

Regression Statistics Multiple R 0.428195321 R Square 0.183351233 Adjusted R Square 0.182854186 Standard Error 7.362419341 Observations 1645

ANOVA df SS MS F Significance F Regression 1 19995.26604 19995.26604 368.8808307 2.5018E-74 Residual 1643 89059.17408 54.20521855 Total 1644 109054.4401

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 10.36221053 0.181955152 56.94925595 0 10.00532207 10.71909898 10.00532207 10.71909898 EP 0.389384926 0.020273844 19.20627061 2.5018E-74 0.349619629 0.429150223 0.349619629 0.429150223 Figure 62- Regression Results: Combined Energy Policy Indicators, 2001-2005

Regression Statistics Multiple R 0.424210005 R Square 0.179954128 Adjusted R Square 0.179455013 Standard Error 3.506069527 Observations 1645

ANOVA df SS MS F Significance F Regression 1 4432.025787 4432.025787 360.5464555 7.64393E-73 Residual 1643 20196.61616 12.29252353 Total 1644 24628.64195

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 6.020185903 0.090672871 66.39456611 0 5.842339328 6.198032479 5.842339328 6.198032479 EP 0.38075465 0.020052319 18.98806087 7.64393E-73 0.341423853 0.420085446 0.341423853 0.420085446 Figure 63- Regression Results: Energy Policy GHG Indicators, 2001-2005

Regression Statistics Multiple R 0.449952661 R Square 0.202457398 Adjusted R Square 0.201971979 Standard Error 0.948503567 Observations 1645

ANOVA df SS MS F Significance F Regression 1 375.2280176 375.2280176 417.0780383 8.52464E-83 Residual 1643 1478.139764 0.899659016 Total 1644 1853.367781

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.542743494 0.02669988 20.32756333 4.00704E-82 0.490374113 0.595112876 0.490374113 0.595112876 EP 0.135211824 0.006620732 20.42248854 8.52464E-83 0.122225861 0.148197787 0.122225861 0.148197787 Figure 64- Regression Results: Energy Policy Efficiency Indicators, 2001-2005

246

Regression Statistics Multiple R 0.388402548 R Square 0.150856539 Adjusted R Square 0.150339714 Standard Error 3.38931 Observations 1645

ANOVA df SS MS F Significance F Regression 1 3353.074628 3353.074628 291.8909524 2.29746E-60 Residual 1643 18873.83479 11.48742227 Total 1644 22226.90942

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 3.07085248 0.083566309 36.74749443 2.7931E-216 2.906944778 3.234760182 2.906944778 3.234760182 EP 1.069041179 0.062572588 17.08481643 2.29746E-60 0.946310748 1.19177161 0.946310748 1.19177161 Figure 65- Regression Results: Energy Policy Sustainability Indicators, 2001-2005

Regression Statistics Multiple R 0.133627847 R Square 0.017856402 Adjusted R Square 0.017258627 Standard Error 0.754733614 Observations 1645

ANOVA df SS MS F Significance F Regression 1 17.01546817 17.01546817 29.87146463 5.32649E-08 Residual 1643 935.8903069 0.569622828 Total 1644 952.9057751

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.490907916 0.023399185 20.9797017 8.87832E-87 0.445012547 0.536803286 0.445012547 0.536803286 EP -0.03746872 0.006855523 -5.465479359 5.32649E-08 -0.050915204 -0.024022236 -0.050915204 -0.024022236 Figure 66- Regression Results: Energy Policy Sequestration Indicators, 2001-2005

Regression Statistics Multiple R 0.279356527 R Square 0.078040069 Adjusted R Square 0.077478925 Standard Error 2.083088625 Observations 1645

ANOVA df SS MS F Significance F Regression 1 603.4741285 603.4741285 139.0731084 7.17427E-31 Residual 1643 7129.401251 4.339258218 Total 1644 7732.87538

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.248046733 0.062710323 3.955437044 7.96439E-05 0.125046148 0.371047318 0.125046148 0.371047318 EP 0.202095216 0.017136986 11.7929262 7.17427E-31 0.168482578 0.235707853 0.168482578 0.235707853 Figure 67- Regression Results: Energy Policy Sources Indicators, 2001-2005

247

B.2.3 Energy Policy, 2006

Regression Statistics Multiple R 0.611392983 R Square 0.37380138 Adjusted R Square 0.372076315 Standard Error 2.582529912 Observations 365

ANOVA df SS MS F Significance F Regression 1 1445.193968 1445.193968 216.6882785 8.64258E-39 Residual 363 2421.014251 6.669460748 Total 364 3866.208219

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 9.652032076 0.222711628 43.33869835 1.4762E-145 9.214065062 10.08999909 9.214065062 10.08999909 EP 0.128252422 0.008712602 14.72033554 8.64258E-39 0.111118911 0.145385933 0.111118911 0.145385933 Figure 68- Regression Results: Combined Energy Policy Indicators, 2006

Regression Statistics Multiple R 0.404533904 R Square 0.163647679 Adjusted R Square 0.161343678 Standard Error 1.213810518 Observations 365

ANOVA df SS MS F Significance F Regression 1 104.6475349 104.6475349 71.02761133 8.36569E-16 Residual 363 534.8209583 1.473335973 Total 364 639.4684932

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 3.727566435 0.072677564 51.28909445 2.2092E-168 3.584644506 3.870488364 3.584644506 3.870488364 EP 0.128780248 0.015280433 8.427788045 8.36569E-16 0.098730961 0.158829534 0.098730961 0.158829534 Figure 69- Regression Results: Energy Policy GHG Indicators, 2006

Regression Statistics Multiple R 0.240697986 R Square 0.05793552 Adjusted R Square 0.055340301 Standard Error 0.748824371 Observations 365

ANOVA df SS MS F Significance F Regression 1 12.51788184 12.51788184 22.32394313 3.29825E-06 Residual 363 203.5478716 0.560737938 Total 364 216.0657534

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -1.402363316 0.060349137 -23.23750417 7.94097E-74 -1.521041139 -1.283685493 -1.521041139 -1.283685493 EP 0.027232412 0.005763691 4.724822021 3.29825E-06 0.015897996 0.038566829 0.015897996 0.038566829 Figure 70- Regression Results: Energy Policy Efficiency Indicators, 2006

248

Regression Statistics Multiple R 0.173703416 R Square 0.030172877 Adjusted R Square 0.027501177 Standard Error 1.285655977 Observations 365

ANOVA df SS MS F Significance F Regression 1 18.66717351 18.66717351 11.293512 0.000860431 Residual 363 600.0067991 1.652911292 Total 364 618.6739726

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 2.638514865 0.073434796 35.93003587 1.3664E-121 2.494103822 2.782925907 2.494103822 2.782925907 EP 0.158845487 0.047267254 3.360582092 0.000860431 0.065893457 0.251797518 0.065893457 0.251797518 Figure 71- Regression Results: Energy Policy Sustainability Indicators, 2006

Regression Statistics Multiple R 0.411205346 R Square 0.169089837 Adjusted R Square 0.166800828 Standard Error 0.465318612 Observations 365

ANOVA df SS MS F Significance F Regression 1 15.99450879 15.99450879 73.8703334 2.51785E-16 Residual 363 78.59727203 0.216521411 Total 364 94.59178082

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 1.218853672 0.025926833 47.01128325 1.9093E-156 1.16786802 1.269839323 1.16786802 1.269839323 EP -0.127897203 0.014880791 -8.594785245 2.51785E-16 -0.157160585 -0.09863382 -0.157160585 -0.09863382 Figure 72- Regression Results: Energy Policy Sequestration Indicators, 2006

Regression Statistics Multiple R 0.625997769 R Square 0.391873207 Adjusted R Square 0.390197927 Standard Error 1.380875789 Observations 365

ANOVA df SS MS F Significance F Regression 1 446.0333051 446.0333051 233.9149924 4.15168E-41 Residual 363 692.1749141 1.906817945 Total 364 1138.208219

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 3.137084012 0.126277092 24.84285916 2.6514E-80 2.888757504 3.38541052 2.888757504 3.38541052 EP 0.158062801 0.010334766 15.29427973 4.15168E-41 0.137739271 0.178386332 0.137739271 0.178386332 Figure 73- Regression Results: Energy Policy Sources Indicators, 2006

249

B.2.4 Energy Policy, 2007-2008

Regression Statistics Multiple R 0.713930523 R Square 0.509696792 Adjusted R Square 0.509024223 Standard Error 4.526916568 Observations 731

ANOVA df SS MS F Significance F Regression 1 15530.29392 15530.29392 757.8350615 6.1744E-115 Residual 729 14939.37776 20.49297361 Total 730 30469.67168

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 6.321418522 0.174895534 36.14396758 1.0685E-164 5.978059508 6.664777535 5.978059508 6.664777535 EP 0.5476807 0.019894823 27.52880422 6.1744E-115 0.508622716 0.586738684 0.508622716 0.586738684 Figure 74- Regression Results: Combined Energy Policy Indicators, 2007-2008

Regression Statistics Multiple R 0.403105254 R Square 0.162493846 Adjusted R Square 0.161345004 Standard Error 2.351133257 Observations 731

ANOVA df SS MS F Significance F Regression 1 781.8634817 781.8634817 141.4413653 6.18198E-30 Residual 729 4029.786313 5.52782759 Total 730 4811.649795

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 3.183432246 0.111947845 28.43674438 2.9123E-120 2.963653612 3.403210879 2.963653612 3.403210879 EP 0.242833213 0.020418313 11.8929124 6.18198E-30 0.202747501 0.282918924 0.202747501 0.282918924 Figure 75- Regression Results: Energy Policy GHG Indicators, 2007-2008

Regression Statistics Multiple R 0.021854714 R Square 0.000477629 Adjusted R Square -0.000893458 Standard Error 1.367862519 Observations 731

ANOVA df SS MS F Significance F Regression 1 0.651793717 0.651793717 0.348357585 0.555227242 Residual 729 1363.993897 1.87104787 Total 730 1364.645691

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -0.630093607 0.059366697 -10.61358706 1.43695E-24 -0.746643698 -0.513543515 -0.746643698 -0.513543515 EP 0.008201697 0.013896042 0.590218252 0.555227242 -0.019079337 0.035482732 -0.019079337 0.035482732 Figure 76- Regression Results: Energy Policy Efficiency Indicators, 2007-2008

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Regression Statistics Multiple R 0.057386155 R Square 0.003293171 Adjusted R Square 0.001925946 Standard Error 2.352961905 Observations 731

ANOVA df SS MS F Significance F Regression 1 13.33534131 13.33534131 2.408653586 0.12110011 Residual 729 4036.057272 5.536429728 Total 730 4049.392613

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 2.907020471 0.09046708 32.13346194 8.3296E-142 2.729413378 3.084627563 2.729413378 3.084627563 EP 0.075967382 0.048948568 1.551983758 0.12110011 -0.020129594 0.172064358 -0.020129594 0.172064358 Figure 77- Regression Results: Energy Policy Sustainability Indicators, 2007-2008

Regression Statistics Multiple R 0.417332707 R Square 0.174166588 Adjusted R Square 0.173033758 Standard Error 0.567114163 Observations 731

ANOVA df SS MS F Significance F Regression 1 49.44710953 49.44710953 153.7446186 3.58484E-32 Residual 729 234.4598672 0.321618474 Total 730 283.9069767

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.856623838 0.030539735 28.04948495 5.4355E-118 0.796667514 0.916580162 0.796667514 0.916580162 EP -0.060129117 0.004849365 -12.39937976 3.58484E-32 -0.069649504 -0.05060873 -0.069649504 -0.05060873 Figure 78- Regression Results: Energy Policy Sequestration Indicators, 2007-2008

Regression Statistics Multiple R 0.435399552 R Square 0.18957277 Adjusted R Square 0.188461073 Standard Error 1.084528916 Observations 731

ANOVA df SS MS F Significance F Regression 1 200.5726588 200.5726588 170.5255504 3.59168E-35 Residual 729 857.451965 1.17620297 Total 730 1058.024624

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 1.316294056 0.051756715 25.43233371 1.2417E-102 1.214684059 1.417904053 1.214684059 1.417904053 EP 0.155328833 0.011894806 13.0585432 3.59168E-35 0.131976672 0.178680995 0.131976672 0.178680995 Figure 79- Regression Results: Energy Policy Sources Indicators, 2007-2008

251

B.3 Bush Indicators and Energy Policy Indicators, Multivariable Regression B.3.1 Bush & Energy Policy, 2001-2008 Regression Statistics Multiple R 0.734645176 R Square 0.539703534 Adjusted R Square 0.539367306 Standard Error 4.98896027 Observations 2741

ANOVA df SS MS F Significance F Regression 2 79904.485 39952.2425 1605.170133 0 Residual 2738 68148.06589 24.88972458 Total 2740 148052.5509

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 5.924396177 0.125815536 47.08795418 0 5.677693202 6.171099153 5.677693202 6.171099153 Bush 0.420057134 0.008981634 46.76845551 0 0.40244567 0.437668598 0.40244567 0.437668598 EP 0.367752799 0.008181227 44.9508145 0 0.351710798 0.3837948 0.351710798 0.3837948 Figure 80- Regression Results: Combined EP Indicators & Combined Bush Indicators, 2001-2008 Regression Statistics Multiple R 0.421995491 R Square 0.178080195 Adjusted R Square 0.177479815 Standard Error 3.24202073 Observations 2741

ANOVA df SS MS F Significance F Regression 2 6235.211583 3117.605791 296.6126198 2.5206E-117 Residual 2738 28778.29225 10.51069841 Total 2740 35013.50383

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 4.343764946 0.08536521 50.88448744 0 4.176378215 4.511151677 4.176378215 4.511151677 Bush 0.148301244 0.011563411 12.82504333 1.31479E-36 0.125627352 0.170975136 0.125627352 0.170975136 EP 0.248819625 0.013627082 18.25920054 2.22468E-70 0.222099223 0.275540027 0.222099223 0.275540027 Figure 81- Regression Results: EP GHG Indicators & Bush GHG Indicators, 2001-2008 Regression Statistics Multiple R 0.439768986 R Square 0.193396761 Adjusted R Square 0.192807569 Standard Error 1.17587175 Observations 2741

ANOVA df SS MS F Significance F Regression 2 907.7005352 453.8502676 328.2408905 1.65E-128 Residual 2738 3785.762435 1.382674373 Total 2740 4693.46297

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.030318133 0.026886752 1.127623483 0.25957777 -0.022402238 0.083038505 -0.022402238 0.083038505 Bush 0.330145882 0.028324245 11.65594622 1.12066E-30 0.274606829 0.385684934 0.274606829 0.385684934 EP 0.133544082 0.005236685 25.50164555 6.8583E-129 0.123275829 0.143812335 0.123275829 0.143812335 Figure 82- Regression Results: EP Efficiency Indicators & Bush Efficiency Indicators, 2001-2008

252

Regression Statistics Multiple R 0.426223379 R Square 0.181666368 Adjusted R Square 0.181068608 Standard Error 2.83984458 Observations 2741

ANOVA df SS MS F Significance F Regression 2 4901.925689 2450.962845 303.9118139 6.3346E-120 Residual 2738 22081.1958 8.064717239 Total 2740 26983.12149

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 2.413190268 0.064949961 37.15460691 4.942E-245 2.285834385 2.540546151 2.285834385 2.540546151 Bush 0.412839649 0.021903303 18.84828317 1.31411E-74 0.369890979 0.455788319 0.369890979 0.455788319 EP 0.476280873 0.036498825 13.04921124 8.41236E-38 0.404712854 0.547848892 0.404712854 0.547848892 Figure 83- Regression Results: EP Sustainability Indicators & Bush Sustainability Indicators, 2001- 2008 Regression Statistics Multiple R 0.273104717 R Square 0.074586187 Adjusted R Square 0.073910209 Standard Error 0.709858972 Observations 2741

ANOVA df SS MS F Significance F Regression 2 111.1987796 55.59938978 110.3381946 0 Residual 2738 1379.677543 0.50389976 Total 2740 1490.876323

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.623778447 0.019567064 31.87899991 6.129E-190 0.585410745 0.66214615 0.585410745 0.66214615 Bush 0.080089642 0.011881604 6.740642439 1.91562E-11 0.056791828 0.103387457 0.056791828 0.103387457 EP -0.059246357 0.004105686 -14.43031916 1.49967E-45 -0.067296913 -0.051195802 -0.067296913 -0.051195802 Figure 84- Regression Results: EP Sequestration Indicators & Bush Sequestration Indicators, 2001- 2008 Regression Statistics Multiple R 0.440786937 R Square 0.194293124 Adjusted R Square 0.193704587 Standard Error 1.809386728 Observations 2741

ANOVA df SS MS F Significance F Regression 2 2161.606344 1080.803172 330.1291013 3.6009E-129 Residual 2738 8963.884352 3.273880333 Total 2740 11125.4907

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.309495909 0.043285871 7.150044691 1.1082E-12 0.224619641 0.394372177 0.224619641 0.394372177 Bush 0.307521121 0.012512903 24.57632051 1.0872E-120 0.282985435 0.332056806 0.282985435 0.332056806 EP 0.13537452 0.008071209 16.77252023 3.53413E-60 0.119548244 0.151200795 0.119548244 0.151200795 Figure 85- Regression Results: EP Sources Indicators & Bush Sources Indicators, 2001-2008

253

B.3.2 Bush & Energy Policy, 2001-2005 Regression Statistics Multiple R 0.822100692 R Square 0.675849548 Adjusted R Square 0.675454724 Standard Error 4.639897812 Observations 1645

ANOVA df SS MS F Significance F Regression 2 73704.39401 36852.19701 1711.7745 0 Residual 1642 35350.04611 21.52865171 Total 1644 109054.4401

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 5.160048604 0.154909731 33.31003524 2.6195E-186 4.856207143 5.463890065 4.856207143 5.463890065 Bush 0.608135284 0.012175437 49.94771611 0 0.584254262 0.632016305 0.584254262 0.632016305 EP 0.097433708 0.014050396 6.934587882 5.83751E-12 0.069875124 0.124992293 0.069875124 0.124992293 Figure 86- Regression Results: Combined EP Indicators & Combined Bush Indicators, 2001-2005 Regression Statistics Multiple R 0.495831107 R Square 0.245848486 Adjusted R Square 0.244929909 Standard Error 3.363279496 Observations 1645

ANOVA df SS MS F Significance F Regression 2 6054.91434 3027.45717 267.6406578 2.4747E-101 Residual 1642 18573.72761 11.31164897 Total 1644 24628.64195

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 5.126800622 0.114580137 44.74423523 1.531E-286 4.90206202 5.351539223 4.90206202 5.351539223 Bush 0.254095053 0.021213622 11.97791947 9.35638E-32 0.212486448 0.295703658 0.212486448 0.295703658 EP 0.144059883 0.027577249 5.223867032 1.97617E-07 0.089969597 0.198150169 0.089969597 0.198150169 Figure 87- Regression Results: EP GHG Indicators & Bush GHG Indicators, 2001-2005 Regression Statistics Multiple R 0.545696061 R Square 0.297784191 Adjusted R Square 0.296928874 Standard Error 0.89028597 Observations 1645

ANOVA df SS MS F Significance F Regression 2 551.9036261 275.951813 348.1562479 8.9612E-127 Residual 1642 1301.464155 0.792609108 Total 1644 1853.367781

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.467122561 0.025567805 18.26995176 4.97738E-68 0.416973618 0.517271503 0.416973618 0.517271503 Bush 0.371903997 0.024909905 14.92996428 2.32248E-47 0.323045465 0.420762529 0.323045465 0.420762529 EP 0.15827599 0.006403497 24.71711592 6.1863E-115 0.145716107 0.170835872 0.145716107 0.170835872 Figure 88- Regression Results: EP Efficiency Indicators & Bush Efficiency Indicators, 2001-2005

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Regression Statistics Multiple R 0.742063026 R Square 0.550657534 Adjusted R Square 0.550110223 Standard Error 2.466276107 Observations 1645

ANOVA df SS MS F Significance F Regression 2 12239.41514 6119.707568 1006.1142 5.8358E-286 Residual 1642 9987.494286 6.082517835 Total 1644 22226.90942

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 1.405176564 0.074811098 18.78299616 1.87485E-71 1.258441345 1.551911783 1.258441345 1.551911783 Bush 1.710300531 0.044745839 38.22256077 3.3892E-229 1.622535606 1.798065456 1.622535606 1.798065456 EP -0.016825519 0.053667645 -0.31351327 0.75393056 -0.122089763 0.088438725 -0.122089763 0.088438725 Figure 89- Regression Results: EP Sustainability Indicators & Bush Sustainability Indicators, 2001- 2005 Regression Statistics Multiple R 0.1757252 R Square 0.030879346 Adjusted R Square 0.029698931 Standard Error 0.749941398 Observations 1645

ANOVA df SS MS F Significance F Regression 2 29.42510698 14.71255349 26.15973854 6.54965E-12 Residual 1642 923.4806681 0.5624121 Total 1644 952.9057751

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.446492566 0.025099718 17.78874798 7.10795E-65 0.397261733 0.495723399 0.397261733 0.495723399 Bush 0.070336088 0.014973591 4.697342668 2.85529E-06 0.04096674 0.099705436 0.04096674 0.099705436 EP -0.048404012 0.0071988 -6.723900188 2.43418E-11 -0.062523809 -0.034284216 -0.062523809 -0.034284216 Figure 90- Regression Results: EP Sequestration Indicators & Bush Sequestration Indicators, 2001- 2005 Regression Statistics Multiple R 0.542859508 R Square 0.294696446 Adjusted R Square 0.293837367 Standard Error 1.822518584 Observations 1645

ANOVA df SS MS F Significance F Regression 2 2278.850888 1139.425444 343.037803 3.2867E-125 Residual 1642 5454.024492 3.32157399 Total 1644 7732.87538

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -0.380335761 0.061588385 -6.175446222 8.299E-10 -0.501135822 -0.2595357 -0.501135822 -0.2595357 Bush 0.406034139 0.018079161 22.45868262 1.24729E-97 0.370573496 0.441494782 0.370573496 0.441494782 EP 0.139342316 0.015251485 9.136311263 1.84817E-19 0.109427904 0.169256729 0.109427904 0.169256729 Figure 91- Regression Results: EP Sources Indicators & Bush Sources Indicators, 2001-2005

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B.3.3 Bush & Energy Policy, 2006 Regression Statistics Multiple R 0.773783088 R Square 0.598740267 Adjusted R Square 0.596523363 Standard Error 2.070146709 Observations 365

ANOVA df SS MS F Significance F Regression 2 2314.854542 1157.427271 270.0794012 1.6597E-72 Residual 362 1551.353677 4.285507395 Total 364 3866.208219

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 7.935107724 0.215400584 36.83884028 1.622E-124 7.511514115 8.358701334 7.511514115 8.358701334 Bush 0.180185179 0.012648683 14.24537108 7.20519E-37 0.155311054 0.205059305 0.155311054 0.205059305 EP 0.256582104 0.011398663 22.50984208 8.51032E-71 0.234166191 0.278998018 0.234166191 0.278998018 Figure 92- Regression Results: Combined EP Indicators & Combined Bush Indicators, 2006 Regression Statistics Multiple R 0.40611272 R Square 0.164927541 Adjusted R Square 0.160313881 Standard Error 1.214555516 Observations 365

ANOVA df SS MS F Significance F Regression 2 105.4659664 52.7329832 35.74765842 6.79318E-15 Residual 362 534.0025267 1.475145102 Total 364 639.4684932

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 3.620039623 0.161641419 22.39549518 2.49392E-70 3.302165498 3.937913747 3.302165498 3.937913747 Bush 0.014020345 0.018822829 0.744858552 0.456840525 -0.022995479 0.05103617 -0.022995479 0.05103617 EP 0.146055217 0.027778774 5.257799245 2.4983E-07 0.09142718 0.200683255 0.09142718 0.200683255 Figure 93- Regression Results: EP GHG Indicators & Bush GHG Indicators, 2006 Regression Statistics Multiple R 0.319191593 R Square 0.101883273 Adjusted R Square 0.096921302 Standard Error 0.732158444 Observations 365

ANOVA df SS MS F Significance F Regression 2 22.01348615 11.00674308 20.5328237 3.57465E-09 Residual 362 194.0522673 0.536055987 Total 364 216.0657534

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -1.505588803 0.063900263 -23.56154307 4.52259E-75 -1.631251151 -1.379926455 -1.631251151 -1.379926455 Bush 0.169285462 0.040221979 4.208780038 3.24216E-05 0.090187379 0.248383544 0.090187379 0.248383544 EP 0.03459763 0.005900869 5.863141167 1.02371E-08 0.022993341 0.046201919 0.022993341 0.046201919 Figure 94- Regression Results: EP Efficiency Indicators & Bush Efficiency Indicators, 2006

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Regression Statistics Multiple R 0.543862674 R Square 0.295786608 Adjusted R Square 0.291895927 Standard Error 1.09705595 Observations 365

ANOVA df SS MS F Significance F Regression 2 182.9954761 91.49773804 76.02436529 2.71941E-28 Residual 362 435.6784965 1.203531758 Total 364 618.6739726

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 1.591466963 0.109342888 14.55482833 4.18175E-38 1.37643993 1.806493996 1.37643993 1.806493996 Bush 0.17307899 0.014812111 11.68496477 5.53607E-27 0.1439504 0.202207581 0.1439504 0.202207581 EP -0.021157663 0.043175038 -0.490043865 0.624399716 -0.106063051 0.063747726 -0.106063051 0.063747726 Figure 95- Regression Results: EP Sustainability Indicators & Bush Sustainability Indicators, 2006

Regression Statistics Multiple R 0.430857894 R Square 0.185638524 Adjusted R Square 0.18113929 Standard Error 0.46129742 Observations 365

ANOVA df SS MS F Significance F Regression 2 17.55987862 8.779939308 41.26002265 7.2097E-17 Residual 362 77.03190221 0.21279531 Total 364 94.59178082

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 1.126118068 0.042774949 26.32657862 4.2059E-86 1.04199947 1.210236666 1.04199947 1.210236666 Bush 0.109421586 0.040343684 2.712235858 0.007002051 0.030084166 0.188759006 0.030084166 0.188759006 EP -0.145796064 0.016161003 -9.0214739 1.10607E-17 -0.177577304 -0.114014825 -0.177577304 -0.114014825 Figure 96- Regression Results: EP Sequestration Indicators & Bush Sequestration Indicators, 2006

Regression Statistics Multiple R 0.62784904 R Square 0.394194417 Adjusted R Square 0.390847424 Standard Error 1.380140211 Observations 365

ANOVA df SS MS F Significance F Regression 2 448.6753249 224.3376624 117.775721 4.00242E-40 Residual 362 689.5328943 1.904787001 Total 364 1138.208219

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 3.043913366 0.148954341 20.43521086 2.84761E-62 2.750988873 3.336837859 2.750988873 3.336837859 Bush 0.028939208 0.024572074 1.17772752 0.239678932 -0.01938273 0.077261145 -0.01938273 0.077261145 EP 0.166608229 0.01262304 13.19874005 9.57382E-33 0.14178453 0.191431928 0.14178453 0.191431928 Figure 97- Regression Results: EP Sources Indicators & Bush Sources Indicators, 2006

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B.3.4 Bush & Energy Policy, 2007-2008 Regression Statistics Multiple R 0.742403864 R Square 0.551163497 Adjusted R Square 0.54993043 Standard Error 4.334233282 Observations 731

ANOVA df SS MS F Significance F Regression 2 16793.7708 8396.885399 446.9857322 2.2914E-127 Residual 728 13675.90088 18.78557814 Total 730 30469.67168

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 2.50336906 0.494753054 5.059835489 5.31825E-07 1.532056046 3.474682074 1.532056046 3.474682074 Bush 0.683316732 0.083320274 8.201086012 1.07602E-15 0.519740044 0.846893421 0.519740044 0.846893421 EP 0.602316941 0.020179454 29.84802951 1.8163E-128 0.562700073 0.641933808 0.562700073 0.641933808 Figure 98- Regression Results: Combined EP Indicators & Combined Bush Indicators, 2007-2008 Regression Statistics Multiple R 0.481140913 R Square 0.231496578 Adjusted R Square 0.229385305 Standard Error 2.253742106 Observations 731

ANOVA df SS MS F Significance F Regression 2 1113.880462 556.9402312 109.6478584 2.37177E-42 Residual 728 3697.769332 5.079353479 Total 730 4811.649795

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 1.860983883 0.195628752 9.512834216 2.64508E-20 1.476920053 2.245047712 1.476920053 2.245047712 Bush 0.485352485 0.060031795 8.08492377 2.59319E-15 0.367496389 0.603208582 0.367496389 0.603208582 EP 0.19817625 0.020336976 9.744627118 3.57765E-21 0.15825013 0.23810237 0.15825013 0.23810237 Figure 99- Regression Results: EP GHG Indicators & Bush GHG Indicators, 2007-2008 Regression Statistics Multiple R 0.278065345 R Square 0.077320336 Adjusted R Square 0.074785502 Standard Error 1.315133192 Observations 731

ANOVA df SS MS F Significance F Regression 2 105.5148637 52.75743187 30.5031134 1.89959E-13 Residual 728 1259.130827 1.729575312 Total 730 1364.645691

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -0.702325085 0.057827098 -12.14525899 4.87329E-31 -0.815852859 -0.588797311 -0.815852859 -0.588797311 Bush 1.180362964 0.151591213 7.786486686 2.37146E-14 0.88275486 1.477971068 0.88275486 1.477971068 EP 0.095079714 0.017406609 5.462276485 6.45671E-08 0.060906572 0.129252855 0.060906572 0.129252855 Figure 100- Regression Results: EP Efficiency Indicators & Bush Efficiency Indicators, 2007-2008

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Regression Statistics Multiple R 0.22430516 R Square 0.050312805 Adjusted R Square 0.047703774 Standard Error 2.298367885 Observations 731

ANOVA df SS MS F Significance F Regression 2 203.7363006 101.8681503 19.28409805 6.90768E-09 Residual 728 3845.656312 5.282494934 Total 730 4049.392613

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 2.213732181 0.145409951 15.22407628 1.21336E-45 1.928259304 2.499205057 1.928259304 2.499205057 Bush 0.90430858 0.150626585 6.003645238 3.0435E-09 0.608594261 1.200022899 0.608594261 1.200022899 EP 0.285695303 0.059214975 4.824713752 1.7085E-06 0.16944281 0.401947795 0.16944281 0.401947795 Figure 101- Regression Results: EP Sustainability Indicators & Bush Sustainability Indicators, 2007- 2008 Regression Statistics Multiple R 0.432468428 R Square 0.187028941 Adjusted R Square 0.184795504 Standard Error 0.563066754 Observations 731

ANOVA df SS MS F Significance F Regression 2 53.09882129 26.54941064 83.74041597 1.85068E-33 Residual 728 230.8081555 0.31704417 Total 730 283.9069767

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 0.772969663 0.039076633 19.78086637 5.00716E-70 0.696253325 0.849686001 0.696253325 0.849686001 Bush 0.068947229 0.020315544 3.393816518 0.000726581 0.029063185 0.108831272 0.029063185 0.108831272 EP -0.060336667 0.004815144 -12.53060467 9.31358E-33 -0.069789892 -0.050883442 -0.069789892 -0.050883442 Figure 102- Regression Results: EP Sequestration Indicators & Bush Sequestration Indicators, 2007- 2008 Regression Statistics Multiple R 0.476745481 R Square 0.227286254 Adjusted R Square 0.225163414 Standard Error 1.059720943 Observations 731

ANOVA df SS MS F Significance F Regression 2 240.4744529 120.2372265 107.0670694 1.73294E-41 Residual 728 817.5501709 1.123008477 Total 730 1058.024624

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 1.300012708 0.050646517 25.66835352 5.5865E-104 1.200582051 1.399443365 1.200582051 1.399443365 Bush 3.167118281 0.53132419 5.960801976 3.91091E-09 2.124007791 4.210228771 2.124007791 4.210228771 EP 0.15571033 0.011622895 13.39686276 9.64049E-37 0.132891937 0.178528722 0.132891937 0.178528722 Figure 103- Regression Results: EP Sources Indicators & Bush Sources Indicators, 2007-2008

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