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Analysis of Motivation, Methodology, and Potential in Campus Carbon Emissions Measurement and Mitigation Planning

Permanent Link: http://ufdc.ufl.edu/UFE0044061/00001

Material Information

Title: Analysis of Motivation, Methodology, and Potential in Campus Carbon Emissions Measurement and Mitigation Planning
Physical Description: 1 online resource (162 p.)
Language: english
Creator: Goldsmith, David Scott
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2012

Subjects

Subjects / Keywords: campuses -- carbon -- construction -- mitigation -- sustainability
Design, Construction and Planning -- Dissertations, Academic -- UF
Genre: Design, Construction, and Planning Doctorate thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: This work examines the carbon mitigation planning efforts being conducted as part of the American Association of College and University Presidents' Climate Commitment program. Under the program signatories commit to eliminate carbon emissions from campus operations by a set future date. The source of data for the study are the plans created by participating institutions and include a standard set of data regarding sources of emissions, enrollment, and other structural factors. This study approaches the examination of the plans from the perspective of wanting to discern influential factors of the institutions in their resulting plans. The participating institutions are divided into four strata by factors of ownership, majority of degrees awarded, and enrollment. In examining the planned methods of mitigation the study has focused on the use of purchased carbon offset credits and how that relates to the aforementioned structural factors. In addition to the structural examination and study of the use of offset credits, this research has utilized a content analysis methodology to examine the use of certain types of language and to look for the expression of ethical or motivational language in the plans. The findings of the content analysis are then related to the structural factors of the signatory institutions in an effort to find relationships between the type of institutions and the narrative content it creates. The narrative speech of an institution reflects its understanding of its relationship with the environment and its participation in the Climate Commitment Program.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by David Scott Goldsmith.
Thesis: Thesis (Ph.D.)--University of Florida, 2012.
Local: Adviser: Ries, Robert J.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2012-11-30

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2012
System ID: UFE0044061:00001

Permanent Link: http://ufdc.ufl.edu/UFE0044061/00001

Material Information

Title: Analysis of Motivation, Methodology, and Potential in Campus Carbon Emissions Measurement and Mitigation Planning
Physical Description: 1 online resource (162 p.)
Language: english
Creator: Goldsmith, David Scott
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2012

Subjects

Subjects / Keywords: campuses -- carbon -- construction -- mitigation -- sustainability
Design, Construction and Planning -- Dissertations, Academic -- UF
Genre: Design, Construction, and Planning Doctorate thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: This work examines the carbon mitigation planning efforts being conducted as part of the American Association of College and University Presidents' Climate Commitment program. Under the program signatories commit to eliminate carbon emissions from campus operations by a set future date. The source of data for the study are the plans created by participating institutions and include a standard set of data regarding sources of emissions, enrollment, and other structural factors. This study approaches the examination of the plans from the perspective of wanting to discern influential factors of the institutions in their resulting plans. The participating institutions are divided into four strata by factors of ownership, majority of degrees awarded, and enrollment. In examining the planned methods of mitigation the study has focused on the use of purchased carbon offset credits and how that relates to the aforementioned structural factors. In addition to the structural examination and study of the use of offset credits, this research has utilized a content analysis methodology to examine the use of certain types of language and to look for the expression of ethical or motivational language in the plans. The findings of the content analysis are then related to the structural factors of the signatory institutions in an effort to find relationships between the type of institutions and the narrative content it creates. The narrative speech of an institution reflects its understanding of its relationship with the environment and its participation in the Climate Commitment Program.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by David Scott Goldsmith.
Thesis: Thesis (Ph.D.)--University of Florida, 2012.
Local: Adviser: Ries, Robert J.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2012-11-30

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2012
System ID: UFE0044061:00001


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1 ANALYSIS OF MOTIVATION, METH O DOLOGY, AND POTENTIAL IN CAMPUS CARBON EMISSIONS MEASUREMENT AND MITIGATION PLANNING By DAVID SCOTT GOLDSMITH A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PA RTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2012

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2 2012 David Scott Goldsmith

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3 To friends and family all

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4 ACKNOWLEDGMENTS I would like to thank my committee chair Dr. Robe rt Ries for his professional guidance and mentorship throughout my graduate education. I would also like to thank my committee co chair Dr. Charles Kibert, and members Dr. Ruth Steiner, and Dr. Mark Brown. The analysis methods used were developed under the advice of Dr. Mike Daniels. I am grateful for the support of my parents Ronald and Elizabeth. My wife Jessica, and sons Orville and Woodrow have been there for me every step of the way. Everyone needs confidants, colleagues, and friends; for that, thank you Bricky, Charlie, Tim, and Q uimby

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 8 LIST OF FIGURES ................................ ................................ ................................ ........ 12 LIST OF ABBREVIATIONS ................................ ................................ ........................... 13 ABSTRACT ................................ ................................ ................................ ................... 14 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 16 Background of the Study ................................ ................................ ......................... 16 Scope of the Project ................................ ................................ ................................ 20 Research Questions ................................ ................................ ............................... 21 2 LITERATURE REVIEW ................................ ................................ .......................... 24 General University Sustainability ................................ ................................ ............ 25 Growth Planning in a Sustainable Context ................................ .............................. 29 Scales of Carbon Mitigation Efforts ................................ ................................ ......... 31 Effectiveness of Ca rbon Mitigation Strategies ................................ ........................ 34 ...................... 37 Institutional Carbon Emissions Mitigation Planning in Context ............................... 40 Carbon Mitigation Planning in Institutions of Higher Education ............................... 42 Carbon Neutrality in Other Institutions ................................ ................................ .... 45 Expected Use of Purchased Carbon Offset Credits ................................ ................ 46 Content Analysis ................................ ................................ ................................ ..... 49 3 METHODOLOGY ................................ ................................ ................................ .... 50 Objectives of the Study ................................ ................................ ........................... 50 Main Objectives ................................ ................................ ................................ 50 Sub objectives ................................ ................................ ................................ .. 50 Hypotheses ................................ ................................ ................................ ...... 51 Study Design ................................ ................................ ................................ .......... 53 Problems and Limitations ................................ ................................ ........................ 55 Population ................................ ................................ ................................ ............... 56 Selection Methodology ................................ ................................ ............................ 64 Variables ................................ ................................ ................................ ................. 65 General Variables ................................ ................................ ............................. 65 Variables in the Emissions Mitigation Section ................................ .................. 65

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6 Variables in the Content Analysis Section ................................ ........................ 65 Measurement Procedures ................................ ................................ ....................... 66 Purchased Carbon Offset Credit Correlation Analysis ................................ ............ 68 Content Analysis ................................ ................................ ................................ ..... 70 Statistical Methods for Content Analysis ................................ ................................ 73 4 RESULTS ................................ ................................ ................................ ............... 77 Strata Comparison and Classification ................................ ................................ ..... 77 Expected use of Carbon Offset Credits ................................ ................................ ... 79 Content Analysis ................................ ................................ ................................ ..... 80 5 DISCUSSION AND CONCLUSION ................................ ................................ ........ 88 Discussion of The Populatio n Analysis ................................ ................................ ... 88 Discussion of Offset Purchase Analysis ................................ ................................ .. 95 Discussion of the Content Analysis ................................ ................................ ......... 97 Research Questions ................................ ................................ ............................... 99 Future Research ................................ ................................ ................................ ... 100 Conclusion ................................ ................................ ................................ ............ 104 APPENDIX A SAMPLE INSTITUTIONAL DATA SET INSTRUMENT ................................ ......... 107 B CONTENT ANALYSIS DATA INSTRUMENT ................................ ....................... 108 C 2 YEAR S TRATUM NUMERICAL DATA ................................ .............................. 109 D 4 YEAR PUBLIC SMALL STRATUM NUMERICAL DATA ................................ ... 110 E 4 YEAR PUBLIC LARGE STRATUM NUMERICAL DATA ................................ ... 111 F 4 YEAR PRIVATE STRATUM NUMERICAL DATA ................................ .............. 112 G 2 YEAR CONTENT ANALYSIS STRATUM DATA ................................ ............... 113 H 4 YEAR PUBLIC SMALL CONTENT ANALYSIS STRATUM DATA ..................... 120 I 4 YEAR PUBLIC LARGE CONTENT ANALYSIS STRATUM DATA .................... 129 J 4 YEAR PRIVATE CONTENT ANALYSIS STRATUM DATA ............................... 136 K CONTENT ANALYSIS CONSOLIDATED DATA TABLES ................................ .... 148 L ................ 152 LIST OF REFERENCES ................................ ................................ ............................. 157

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7 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 162

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8 LIST OF TABLES Table page 3 1 Breakdown of institutional strata and relevant sorting data. ............................... 75 3 2 Strata Content Analysis Data Table ................................ ................................ .... 76 4 1 Expected growth in enrollment and emissions for study population. .................. 83 4 2 Correlation analysis for 4 Year Public Small str ata. ................................ ............ 85 4 3 Correlation analysis for 4 Year Public Large strata. ................................ ........... 85 4 4 Correlation analysis for Private strata. ................................ ................................ 85 4 5 squared test results summary table. ................................ ............ 86 4 6 .... 86 B 1 Data Instrument form used to record content analysis. ................................ .... 108 C 1 2 year stratum population numerical data. ................................ ....................... 109 D 1 4 year public small stratum population numerical data. ................................ .... 110 E 1 4 year public large stratum population numerical data. ................................ .... 111 F 1 4 year private stratum population numerical data. ................................ ............ 112 G 1 Delta College content data. ................................ ................................ .............. 113 G 2 Northern Essex Community College content data. ................................ ........... 114 G 3 Chabot College content data. ................................ ................................ ........... 115 G 4 Onondaga Community College content data. ................................ ................... 116 G 5 Madison Area Technical College content data. ................................ ................ 117 G 6 Cabrillo College content data. ................................ ................................ ........... 118 G 7 University of South Carolina Sumter content data. ................................ ........... 119 H 1 University of Idaho content data. ................................ ................................ ...... 120 H 2 Eastern Washington University content data. ................................ ................... 121 H 3 niversity of Colorado at Colorado Springs content data. ................................ ... 122

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9 H 4 William Paterson University of New Jersey content data. ................................ 123 H 5 New College of Florida content data. ................................ ................................ 124 H 6 J ames Madison University content data. ................................ .......................... 125 H 7 University of Minnesota Morris content data. ................................ .................... 126 H 8 Northern Arizona University c ontent data. ................................ ........................ 127 H 9 Oregon State University content data. ................................ .............................. 128 I 1 University of Oklahoma Norman content data. ................................ ................. 1 29 I 2 University of Utah content data. ................................ ................................ ........ 130 I 3 George Mason University content data. ................................ ........................... 131 I 4 University of California, Berkeley content data. ................................ ................ 132 I 5 Grand Valley State University content data. ................................ ..................... 133 I 6 Unive ................................ ........................ 134 I 7 University of California, Santa Barbara content data. ................................ ....... 135 J 1 Union College content data. ................................ ................................ ............. 136 J 2 Kalamazoo College content data. ................................ ................................ ..... 137 J 3 Wesleyan College content data. ................................ ................................ ....... 138 J 4 Rhodes College content data. ................................ ................................ .......... 139 J 5 Gettysburg College content data. ................................ ................................ ..... 140 J 6 Franklin College of Indiana content data. ................................ ......................... 141 J 7 Keystone College content data. ................................ ................................ ........ 142 J 8 University of Miami content data. ................................ ................................ ...... 143 J 9 Dickinson College content data. ................................ ................................ ....... 144 J 10 University of Puget Sound content data. ................................ .......................... 145 J 11 LaGrange College content data. ................................ ................................ ....... 146 J 12 Lewis & Clark College content data. ................................ ................................ 147

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10 K 1 2 year public stratum content analy sis summary table. ................................ .... 148 K 2 4 year public small stratum content analysis summary table. ........................... 149 K 3 4 year public large stratum conte nt analysis summary table. ........................... 150 K 4 4 year private stratum content analysis summary table. ................................ ... 151 L 1 squared test for strata and presence of ethical language. ......... 152 L 2 squared test for strata and presence of motivational language. 152 L 3 squared test for strata and ethical language expected distribution. ................................ ................................ ................................ ....... 152 L 4 squared test for strata and motivational language expected distribution. ................................ ................................ ................................ ....... 152 L 5 squared test for strata and hedging or imperative language present. ................................ ................................ ................................ ............ 153 L 6 squared test for strata and imperative language present. .......... 153 L 7 squared test for strata and hedging language present. .............. 153 L 8 hi squared test for any language present. ................................ ...... 153 L 9 squared test for strata and histogram distribution of imperative language present. ................................ ................................ ............................. 154 L 10 squared test for strata and histogram distribution of hedging language present. ................................ ................................ ............................. 154 L 11 squared test for strata and histogram distribut ion of normative imperative language present. ................................ ................................ ........... 154 L 12 squared test for strata and histogram distribution of normative hedging language present. ................................ ................................ ............... 154 L 13 squared test for strata and presence of stated neutrality date. .. 155 L 14 squared test for strata and presence of ethical or motivational language. ................................ ................................ ................................ .......... 155 L 15 year public large and small strata, and ethical language. ................................ ................................ ................................ .......... 155 L 16 Fis year public combined and 2 year strata, and ethical language. ................................ ................................ ................................ .......... 155

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11 L 17 language. ................................ ................................ ................................ .......... 155 L 18 year public combined and private strata, and ethical language ................................ ................................ ................................ .......... 156 L 19 year pu blic large and small strata, and presence of any language. ................................ ................................ ................................ ... 156 L 20 year public combined and 2 year strata, and presence of any language. ................................ ................................ ............... 156 L 21 any language. ................................ ................................ ................................ ... 156 L 22 year public combin ed and private strata, and presence of any language. ................................ ................................ ............... 156

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12 LIST OF FIGURES Figure page 3 1 Breakdown of strata showing proportion of institutions submitting complete data needed for the purchased carbon offset analysis portion of this study. ...... 75 3 2 ................................ ................................ ...................... 75 3 3 ................................ ................................ ............................ 76 4 1 Baseline and BAU Emissions. ................................ ................................ ............ 82 4 2 Correlation of Baseline and BAU Emissions with Correla tion of Enrollment and Baseline Emissions. ................................ ................................ .................... 82 4 3 Enrollment and baseline emissions scatter plot of all four strata. ....................... 83 4 4 Ba seline Emissions Distribution for Study Population ................................ ........ 84 4 5 Emissions/Student Normal Distribution for Study Population. ............................ 84 4 6 I mperative and hedging phrases mean per page. ................................ .............. 87

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13 LIST OF ABBREVIATION S AACUP American Association of College and University Presidents CC Climate Commitment CCX Chicago Climate Exchange CSAF Campus Sust ainability Assessm ent Framework LEED Leadership in Energy Efficient Design MTCO2E Metric tones of carbon dioxide equivalent normalized unit used to quantify emissions. PCOC Purchased Carbon Offset Credit

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14 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy ANALYSIS OF MOTIVATI ON, METH O DOLOGY, AND POTENTIA L IN CAMPUS CARBON EMISSIONS MEA SUREMENT AND MITIGAT ION PLANNING By David Scott Goldsmith May 2012 Chair: Robert Ries Major: Design, Construction, and Planning This work examines the carbon mitigation planning efforts being conducted as part Commitment p rogram. Under the program signatories commit to eliminate carbon emissions from campus operations by a set future date. The source of data for the study are the plans created by participating institutions and include a standard set of data regarding sources of emissions, enrollmen t, and other structural factors. This study approaches the examination of the plans from the perspective of wanting to discern influential factors of the institutions in their resulting plans. The participating institutions are divided into four strata by factors of ownership, majority of degrees awarded, and enrollment. In examining the planned methods of mitigation the study has focused on the use of purchased carbon offset credits and how that relates to the aforementioned structural factors. In additi on to the structural examination and study of the use of offset credits, this research has utilized a content analysis methodology to examine the use of certain types of language and to look for the expression of ethical or motivational language in

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15 the pla ns. The findings of the content analysis are then related to the structural factors of the signatory institutions in an effort to find relationships between the type of institutions and the narrative content it creates. The narrative speech of an instituti on reflects its understanding of its relationship with the environment and its participation in the Climate Commitment Program.

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16 CHAPTER 1 INTRODUCTION Background of the Study College campuses have been at the forefront of sustainable development in exa mining their resource use and creating innovative strategies to limit their environmental impact. The unique situation of campuses with their constant construction, renovation, large populations, available resources, and a progressive approach to facilitie s management make them a useful study in sustainable development. The intent of this study is to examine a wide range of college carbon emissions reduction plans in an effort to learn the prime motivations and methods for these efforts. This research has u tilized the planning undertaken under the Climate Commitment program of the American Associational of College and University Presidents. The primary source of carbon emissions identified in these planning efforts is campus buildings including construction maintenance, and operation. Between the declared motivations and intents of the college and university organizations and their proposed efforts to limit or control carbon emissions is some understanding of the relationship between the buildings and their environment. This research will consider that understanding in an ethical context in an effort to better understand the planning choices made. The construction, use, and maintenance of buildings are the focus of all the pla nning efforts studied. Building are the largest proxies for the production of greenhouse gases, in order to reduce carbon emissions to the level proposed in the plans, buildings will have to be the primary area in which reduction efforts are

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17 implemented. B uildings are the physical body of the campus and their metabolizing of resources is directly under the control of the college or university itself. Lastly buildings represent much of the tradition and stature of the university whether through their history architecture, or their social significance as the places where students live, professors work, and research is conducted, they are the showcase of the university as well as the body and therefore deserve and receive a great deal of attention. Capital pro jects, such as major renovations or new building construction have been a part of the boom in university growth and a sign of prosperity and prestige for the university and the administration which succeeds in providing these big projects. The modern campu s is defined not just by its historic structures and spaces but also by the near constant construction taking place on virtually every campus. This rate of building and locus of sustainability problems in buildings has resulted in their being the primary c omponent in any kind of sustainability planning including the carbon emissions planning studied here. In addition to institutional motivations there also exist ethical imperatives that are driving the efforts to eliminate carbon emissions from campuses. U niversities have been some of the first institutions to recognize their responsibility, even outside of business case or legislative command, to reduce carbon emissions and to accomplish that by beginning to think differently about buildings. An ethical ap proach to buildings goes moral component to what is done to erect a structure for human use. This research will examine the nature of ethical motivation and expression in the plans by conducting a content analysis of the language of explanation or justification in the plans.

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18 Climate change has been recognized and is slowly being accepted as the great challenge of our time. The anthropogenic causes of warming trends has at its root the wide scale burning of fossil fuels and the associated emitted gases, which then linger in the atmosphere and prevent radiated energy from escaping back into space by acting as an insulator of sorts. The sources of these emissions are associ ated with all aspects of modernity and it could be argued that the driver of modernity has been this availability of nearly limitless, costless, high density energy. Modern society has become a sort of machine whose function is to free sequestered carbon f rom subterranean sources, stored there over epochs by the natural processes of life and geology. As those processes played out they fundamentally altered the composition of the planet's atmosphere and climate. The machine of the modern has reversed this pr ocess and proceeded to free and reintroduce that carbon back into the atmosphere and start the process of returning its composition and climate to an antediluvian state. Those uses of energy, worldwide and essentially the same in the United States, breakdo wn into thirds: transportation, industry, and buildings. Transportation receives a great deal of attention. Transportation is something everyone deals with everyday; it is in front of us, around us, it literally drives our lives. We know exactly how much i t costs us personally in purchase and fuel. Transportation is part of the cultural make up of the United States, our so called 'car culture.' The personal choices we make with our transportation whether it be a personal automobile, public transit, first cl ass or coach flying, or any number of others helps define who we are in a consumer culture. The choice to drive a large truck or a small car is almost entirely driven by personal expression rather than utility. Part of the popularity of

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19 transportation as n exus of emissions concerns is almost certainly because it is reduced to a single number, the much vaulted miles per gallon. A single number is easy, it makes direct comparison easy, and it is intuitive. Seemingly similar means of comparison such as energy used per square foot are only useful with qualifying conditions of the building such as location, use, occupancy, or other specialized factors The problem for those of us concerned with emissions reduction from the perspective of climate change is those p ersonal choices are driven not by technology or need but by fashion and personality. The efficiency of moving a particular mass a particular distance is very easy to describe mathematically and has real physical barriers to the degree to which high levels of efficiency may be achieved. In other words, the problem of transportation efficiency from a technical standpoint is easy to understand but difficult to implement. The equally large prob lem of energy use in buildings is much more difficult to quantify, c onceptualize, and manage. The scale of the built environment and its associated emissions operates from the small end, a single apartment for instance, to the global scale. Part of the question of building sustainability, particularly with regards to emis sions, is which scale is most appropriate to effect substantive reductions in emissions. The individual can turn off their lights, unplug their appliances, and shut off the HVAC system. This substantively effects the emissions associated with that personal space, but the net effect is negligible. Doing something similar on a global scale would have impact but impossible to implement. Those of us examining this problem of emissions in the built environment must try and find the scale at which we can effect m aximum mitigation but still manage and implement the changes required. Architects may address this problem on the single

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20 building scale using systems such as the Leadership in Energy Efficiency Design program (LEED), nations may address the problem from ma ndating building codes and efficiency standards, and in between those extremes communities and institutions may undergo planning and implementation of programs addressing the net emissions of operations not just from the operation of buildings but incorpor ating transportation and industrial activities. At the forefront of these community and institutional scales are colleges and universities. Playing their traditional role of providing innovation and long term thinking to solve pressing problems, colleges a nd universities have begun to address carbon emissions from their own operations, essentially using the campus as a whole as laboratory for emissions mitigation incorporating scales from individual classrooms to hundreds of acres serving tens of thousands of people. This research occurs at a time when the first steps are being taken to thoroughly measure, document, and plan for the reduction of carbon emissions at a wide scale and in a vertically integrated context. As these specific plans and as societal e fforts over the coming generation succeed and fail in their efforts to reduce emissions it will be important to have studies such as this one that exist in a historical context and that have helped to inform the process along the way. Scope of the Project The American College and University President's Climate Commitment ( http://www.presidentsclimatecommitment.org/ ) represents over 600 colleges and universities and has created a set of guidelines and formats for creating comparable carbon mitigation plans as well as a reporting system to keep track of the progress being made in implementing the plans. The data sources for the study are the plans and

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21 the reporting system implemented by the Climate Commitment program. The goal of this study is to both compare the goals and methods of the plans but also to try and understand the intent and motivation of the respective colleges and universities in creating these plans. The study looks for demonstrable relationships between the emissions of institutions, their use of particular mitigation strategies, and their narrative explanations of their participation and efforts. Research Questions Carbon emissions and mitigation plans: How do essential factors of the participating institutions effect their emissions? How do those factors affect the use of particular emissions mitigation strategies? What role do carbon offset credit purchases play in the mitigation plans of differing types of institution? Narrati ve content analysis: Is there a relationship between the institutions expressed motivations and the type of institution? How often is hedging language used? How often is imperative language used? Is there an explicit ethical view described? Is there an ex plicit source of motivation described? Do certain types of institutions create certain types of plans? What condition of the institution seems to influence the planned efforts? There is a confluence of planning for sustainability as well as carbon emissi ons reductions and resource management in much of the program material. This project will

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22 puzzle out which of these competing motivations and goals are best addressed by the plans. Sustainability thinking and institutional motivations have worked together in creating these plans but what ethical frameworks were parts of that motivation? Even ambiguous or ambivalent statements of motive or goals can give way to clear underlying attitudes and thinking about environmental issues and those attitudes and premis es. From an environmental point of view the most important factor in these plans will be carbon emissions measurement, control, and reduction. How each school handles the questions of carbon emissions will form the bulk of the research. All the participat ing plans tended to propose similar mitigation strategies: Efficiency: replacing older equipment with newer, using efficiency as a higher Behavioral changes: encouraging changing patterns o f transportation, encouraging the turning off of things, and providing incentives for reduced emissions producing behavior. Changes in infrastructure: broad changes in the source of energy used in operations, often employing alternative energy, on campus energy production, or exerting influence on energy providers to change their sources. Purchasing offsets: nearly always addressed in planning and often utilized. Purchasing offsets plays an essential role in addressing emissions that are either difficult or impossible to mitigate through institutional actions. The research and analysis consists of two distinct parts. The first is an analysis of the reported data for each participating institution. The analysis consists of certain data that is available fo r all or nearly all institutions and is meant to develop a complete picture of the program and its participants. The analysis in this section provides insights into how structural factors of the institutions (ownership, size, and types of degrees

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23 awarded) relate to their emissions, planned future emissions, and use of purchased offset credits. The second part utilizes a representative sample to conduct a content analysis of the plans to find relationships between certain types of language used and the struc tural factors as well as their emissions mitigation strategies to find relationships between the use of certain language and structural factors.

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24 CHAPTER 2 LITERATURE REVIEW The primary documents for this study consist of the campus sustainability plans the mselves and their supporting documentation. The program's guidelines require that the institutions conduct a long term planning effort and submit their completed plans to the program tracking system. Participation in the program requires regular plan updat es and reporting of emissions levels. The program requires institutions to implement two of seven emissions reducing measures described in the commitment text. The literature and available materials on sustainability topics is vast and quickly growing. Thi s project looks narrowly at the institutional data reported as part of the Climate Commitment and the motivation and ethical basis for these planning efforts. The scope of the literature review will be limited to published works specifically on campus sust ainability planning and similar community sustainability planning in contexts similar to campuses; central control, small populations, progressive action, and the financial infrastructure available to implement planned actions. A review of the literature o f content methodology in the narrow context of planning is included. There is extensive literature available on the motivations for carbon neutrality. Virtually any text on modern ethics, environmental ethics, environmental policy, or sustainability will discuss the obligation to reduce carbon emissions, an obligation taken up by individuals and organizations despite a lack of leadership at the national level. By becoming signatories to the President's Climate Commitment, the colleges and universities in t his study have demonstrated their imperative to take action on the issue of carbon emissions. Their specific arguments and motivations for this represent the content analysis part of the study and the results are discussed in that chapter.

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25 General Univers ity Sustainability Michael M'Gonigle and Justine Starke in 'Planet U' try to understand campus sustainability in a holistic manner before dividing it into particular actions. Their concept is that only a post modern constructivism will allow the university to reground itself in 'reconstruction' rather than 'deconstruction.' They argue the university as institution must find a new set of roots not in the abstract world of knowledge, driven by corporate and government money, but in the core of the university itself, in its home, the campus. (M'Gonigle & Starke, 2006) (p41) M'Gongile and Starke continue to try and put the university into a societal context in order to understand how it might approach a sustainable transition. It becomes clear with little resear ch that the university in a modern context is not so much a physical place of learning anymore than it is a cloister of transcribing monks; both archaic manifestations of the university. The university has become the corporate and government research depar tment, more focused on grants and donations than on learning, the accumulation of knowledge, and teaching. Research outside of a critical context is not worthy of the mission of the university and has lead to a situation in which the essential future of no t only the university but of society itself is being called into question. If a university cannot sustain itself then how can society as a whole be expected to? The hubris of the university is the source for the shortsightedness of our society, the univer sity needs to take up its traditional role of leader and innovator, not in commerce but in the larger realm of humanity. In discussing transportation as a source for emissions and central to the sustainability of urban and suburban universities M'Gonigle describes a dialectic

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26 between a 'territorialist' system and a centrist system of community development and hence transportation. (p83) The university is at the heart of this tension because of its reliance on transport and its position as hub of sorts in a ny particular community. The transition of transportation from individual mandate in the form of personal cars to a system of community transport, making better use of resources both material and social, and human powered bicycles, M'Gonigle and Starke arg ue, is an essential step in creating a sustainable university. The argument is for reshaping community through 'smart growth', with the implication that by 'smart growth' we really mean a filling in of blanks within the social system rather than growing it s boundaries, to provide the social and university situation in which efficient transportation can exist by creating efficient communities. This approach to understanding the problem of sustainability in the context of universities represents an understan ding of the solution not being more of the same with greater efficiencies, but of a fundamental shift in the built environment's metabolism of resources. M'Gonigle describes the essential truth that the orders of magnitude improvement in energy use (and po tentially renewable energy) is required rather than the slight of hand improvements of so called 'hybrid' cars, which are still entirely powered by fossil fuels. Any change toward sustainability that is not a fundamental and dramatic change to existing sys tems is not sufficient to achieve sustainability. While acknowledging that most universities exist outside of city centers, M'Gonigle does not adequately address the transit needs of rural and suburban universities, that is to say his arguments are all pr edicated on the existence of a dense urban center or otherwise compact development that lends itself to mass transit or human powered

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27 transit of various types. The problem of emissions and infrastructure support in smaller and less dense universities is le ft unresolved. This approach covers many of the institutions around the world but the development of the university system in the United States created a situation in which many institutions are located outside of urban centers. M'Gonigle provides an esse ntial observation that transformative policies require a transformed decision making process to create an environment in which those transformations can take place. (p103) In general M'Gonigle touts the planner new urbanism party line about dense multiuse development. The important boundary between university and town seem to be being blurred in his vision, even so far as use development with retail and other services at the street level and housing, offices a (p103) This suggestion of further integration of commercial use, even small scale, in the university strikes me as a n assault on the essential ly separate character of the university from other urban development. New urb anism's approach to development, with its emphasis on integration of housing, commerce, and other services, would only serve to homogenize the urban landscape and further blur the important social and physical boundaries between different human institution s. Should churches also have coffee shops on their first floors with loft apartments above? The vertical stratification of the urban landscape may serve certain planning purposes but it does not directly address the problem of sustainability in universitie s. M'Gonigle and Starke do not

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28 directly address how the application of urbanist principles to the setting of higher education furthers the goals of either. press release mat erial without using any critical tools to examine claims or even to contextualize percent reduction goals. Claims to plan to reduce emissions of certain percentages leave out several important facts: whether those goals are met, the total that those percen tages are reductions from, whether those reductions are meaningful in a larger growth system, and how those reductions are achieved whether by shifting the emissions to other sites or by reducing the metabolism of the site in question. M'Gonigle and Stark e come to the sustainability discussion interested in aspects of urban community, planning, and particularly social sustainability. Environmental sustainability seems to be seen as a subset of social sustainability. The emphasis is on local action and chan ging power structures as part of the hierarchical system. Sarah Hammond Creighton discusses the differences between systemic and incremental changes in emissions and focuses the text on incremental changes as being more readily achievable by most institutions. If those incremental changes aren't going to solve the problem then why attempt them? (Rappaport & Hammond, 2007) (p48) Rappaport and Creighton devote a significant portion of the book to discussing the power structures and decision making processes used at many institutions and how they will influence sustainability planning and projects on the campus.

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29 Rappaport and Creighton deliver a complete analysis of cli mate change m itigation strategy, history, players, and i mplementation in a university context. M'Gonigle is focused more on the social aspects of sustainability and the universities connection to the local community. Rappaport directly addresses the problems of this re search but the planning and social aspects discussed in M'Gonigle are also important in designing a plan that goes beyond simple commitments and idealism and toward functionality and long term viability in the social setting of the university. Growth Plan ning in a Sustainable Context In a very general sense this study examines subjects generally covered under the and economy, plan to grow larger over time. This condi tion is being challenged by a seemingly contradictory demand that institutions also reduce their negative way. This new imperative has created a broad new field of planni ng and inquiry of which this study is part. Recognizing the importance of the impact of carbon emissions on the prospect of sustainability has resulted in many planners rethinking how to contextualize their plans in a carbon limited policy environment. (Wh ite, Jonas, & Gibbs, 2010) In addition to the top down approach of centralized planning there is a simultaneous bottom up grass roots approach occurring that is emphasizing the same goals of reducing or eliminating carbon emissions but also providing for s ocial and economic sustainability. (Seyfang, 2009) As these two approaches begin to meet in the middle the conflicts that arise are often those of values, of which aspects of sustainability are most important to the grass roots individuals and their civic organizations and to the larger planning scale and their goals for sustainable communities. (Seyfang, 2006)

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30 the communities. The study's data was composed of the community planning efforts and the methodology included an evaluation protocol similar to the method proposed for this study. The literature on planning for growth and sustainability includes a number of similar studies both at the plan development stage (Berke & Conroy, 2000), and through the post planning evaluation of results stage. (Talen, 1996) Perhaps most interesting in relation to this study are developments in sustainable development in China. central and powerful power structure that can implement wide ranging and large scale changes to operations, a progressive population that is forward thinking on the topics of sustainability, a nd the resources to implement a wide range of activities to achieve their population is that is goal, in which the Chinese often lack specificity, and in scale where the Chine se are operating at a scale that is orders of magnitude larger than the Colleges and Universities studied in this research. (Lehmann, 2012) Interestingly the same grass roots activities that are driving sustainability initiatives in the west (often focused on food and housing issues) are encountering the same planning activities for sustainability in China (often focused on carbon emissions.) (Zhu & Lin, 2004) (Zhang & Ye, 2010) The findings of Zhu and Lin in China and the findings of Seyfang studying popul ations in the US paint a different picture of greater cooperation in the Chinese group and a seeming retrenchment of the two camps in the American case.

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31 Scales of Carbon Mitigation Efforts The scale of sustainability efforts varies greatly and determining the best scale of action for particular problems in sustainability is an important part of developing sustainable societies. The action we take as individuals toward sustainability have small effects but are straightforward to design and implement. Action s taken at the other extreme of the global scale would have a very high level of impact, but implementation would also present global scale challenges. At the individual and family scale there are many ways to address emissions resulting from activities. R educing domestic energy use and increasing the efficiency of transportation are straightforward and easily implemented techniques to reduce emissions. The problem in emissions mitigation planning at the individual scale is how to alter the behavior of indi viduals in order to mitigate emissions. (Heiskanen, Johnson, Robinson, Vadovics, & Saastamoinen, 2010) Heiskanen et al argue that traditional means of motivating individuals to alter behavior, such as education and financial i ncentives, are not consistently successful because of more difficult to address factors (Guy, 2006) Because of the social context of all individuals and its influence on their c arbon emitting associated behavior the individual scale is less effective than a larger scale that focuses on larger groups of people. The likelihood of individuals to make carbon mitigating changes in their own behavior is positively correlated to their e xpectation and endorsement of larger scale mitigation efforts. (Akter & Bennett, 2011) City scale carbon mitigation efforts have been a focus of research in mitigation methods and have shown efficiencies and possibilities not possible for individuals and that would not be applicable in a larger geospatial context. (Davies, Edmondson,

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32 Heinemeyer, Leake, & Gaston, 2011) Similar scaled but intra organizational communities have attempted to integrate i nstitutional and municipal efforts at carbon mitigation. This integrated approach is more complicated and still in the framework building stage mirroring the planning efforts of the Climate Commitment. (Ramaswami A. et al., 20 11) In studying mitigation planning done by the city of Denver Colorado Ramaswami et al were able to develop a framework for understanding the different actors from individuals acting for themselves, designers and managers implementing mitigation efforts and those in the policy realm. The results of that study demonstrated the low rates of emissions mitigation possible through individual behavioral change efforts and the importance of larger scale efforts. (Ramaswami, et al., 2 012) At the scale of nations, carbon mitigation takes on a much wider range of options and challenges. Political considerations are more pronounced and influential and the actors involved shift from the individuals that are the actors in mitigation strat egies in the smaller scale to nations and whole institutions that make up the functioning parts of the national scale. (Hertwich & Peters, 2009) At this time the most compelling and complete research in national scale carbon mi tigation efforts is coming from China. Similar to the institutions making up the subject of this research, China has a centralized political and economic control hierarchy that is capable of national change quickly and more radically than western democraci es. (Li & Colombierb, 2009) Chinese models of carbon mitigation have provided a sound groundwork for future evaluation of mitigation successes by examining the problem from a perspective of large point source emissions and from a n evaluation of the emissions associated with individual citizens. In the first case, Zang et al model and describe the current state of

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33 to the baseline emissions measu rement methods employed in the Carbon Commitment plans. (Zhanga, Ma, Liu, Zhangb, & Li, 2012) Modeling of this sort, in combination with institutional modeling, begins to construct a framework for a complete vertical integratio n of emission from source to use. A similar set of frameworks available in a single national context would be essential to a comprehensive carbon model at the national level. The second case of modeling being conducted in China and other nations from the individual level to trace the distribution of the results of emitting activities leads into the international scale of carbon mitigati on. Chakravarty et al have constructed a model of individual distribution of carbon emissions from the national scale to t he citizen scale and removing other scales in between, arguing that equitable distribution of resources and any sort of cap and limit efforts would be most successful when considering the unit of emissions to be the citizen described only by their national ity. Chakravarty et al have also provided in their model of national and individual emissions considerations such as business as usual emissions if no mitigation efforts are undertaken and placed a limit on the low end of emissions. This model has demonstr ated that by limiting the low end of emissions allows for equitable distribution without the need for substantial reductions in the resources used in the fight against extreme poverty. This pioneering research has provided a context for national emissions mitigation predicated on the baseline and business as usual emissions allowable under an equitable distribution system of emissions allowance. (Chakravarty, Chikkatur, de Coninck, Pacala, Socolow, & Tavoni, 2009)

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34 These modeli ng efforts have provided essential context at the international level of mitigation planning. Calvin, Fawcett, and Kejun have begun the task of taking the emissions models of Asian nations and evaluating the ability of those nations mitigation planning eff orts to achieve their stated goals. The diversity of plans and the influence upon those plans by international carbon mitigation agreements is an essential step in understanding how planning takes place. The use of regional comparative evaluations provides the beginning of a narrative of mitigation that will continue as plans are implemented. (Calvin, Fawcett, & Kejun, 2012) Because climate change is a worldwide problem involving absolute levels of atmospheric greenhouse gases t he construct of scales and the entities that comprise them is not limited by geopolitical boundaries, economic situations, or other traditional national scale of emissions assembles cohorts of nations accord ing to emissions levels and levels of economic development. (Chen & Chen, 2011) This freedom to find otherwise unassociated scales of emissions is an instructive model and mirrors the distribution of institutions into strata ba sed on structural factors that this research utilizes. Effectiveness of Carbon Mitigation Strategies Most of the plans and indeed most planning guides and guidelines pay most attention to the construction of new facilities. It should be clear that new con struction will represent more emissions than existing buildings whose initial emissions are already being amortized over the useful life of the building, a time span often measured in centuries. It should be a maxim in green building that the greenest buil ding is the one already built.

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35 A similar case to the situation of many universities trying to justify continued new perienced a great deal of resistance from the public and from attentive government representatives who have noted many problems with the proposed developments but the most essential criticism being that the new developments don't account for the carbon emi ssions from their construction or from their daily operation beyond basic services. In addition, their location in less than central localities could imply future emissions from travel. These critics contend that retrofitting existing housing would be far developments, which is virtually the opposite of any serious green thinking about buildings. (Hibbert, 2009) Carbon mitigation is a difficult problem and many nearly standard approaches have failed to deliver the straig htforward gains in energy efficiency promised. In particular, the popular LEED certification programs have failed to demonstrate actual increases in energy efficiency compared to similar buildings without LEED certification. John Scofield at Oberlin Colleg e has conducted research examining the methodology of LEED's claims to energy efficiency and found compared to EPA methods the LEED approach will distort the actual emissions occurring from the energy used by the buildings in questions. (Scofield, 2009) Th e Adam Joseph Lewis Center at Oberlin College in Oberlin, Ohio, near Cleveland is rightly hailed as a major breakthrough in the experiment of integrated and ecological design of buildings. For all its integration and technology the argument put forth by Sc ofield is that it has essentially lost sight of the point While certainly impressive and important, the integration of all these functions into

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36 a single building, rather than treating a collection of buildings as a group and serving their needs with local but central services is probably more in keeping in the appropriate scale of services from an ecological standpoint. The scale of a campus is an excellent scale from which to offer various services and operate them in an ecological manner. The living mach ine artificial wetland of the Lewis center is an amazing achievement but is each new building to support its own wetland? Wouldn't it make more ecological sense to design campuses with integrated or utilized wetlands for groups of buildings or the entire c ampus? The project has been widely written about but the problem of scale has not been directly addressed. (Orr, 2004) Scofield's analysis uses the idea of measuring emissions from the power generation source, which is the end game for efficiency after al l. Using energy efficiency of a building against a base line is only a proxy for the real goal of emissions reductions. This type of analysis could be considered as expressing the principle of Goodhart's Law, a maxim in economics that states once an indica tor is utilized a surrogate indicator for another measurement for the purpose of, in Goodhart's case, influencing economic policy, in our case, influencing building efficiency measurements in respect to greenhouse gas emissions, that surrogate factor will be gamed by the system it was meant to measure until it is effectively useless as a proxy measure for the thing meant to be tracked. (Goodhart, 1975) The implication for our purposes in criticizing LEED as a measure of greenhouse emissions is that it has b ecome adapt to optimizing its own measurement system for building efficiency without actually introducing measures and techniques to the buildings themselves that reduce greenhouse gas emissions. That is

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37 essentially Scofield's point in his analysis of Ober lin College's performance in reducing greenhouse gas emissions. LEED and similar programs have been successful in implementing a range of improvements to the built environment. In the sub set of efforts aimed at carbon emissions mitigation these efforts h ave been successful in broadening consciousness of the problem and in promoting new and innovative approaches to reducing emissions. The improvements in efficiency though have not addressed the real problem of total emissions, the only relevant measurement in regards to environmental problems. A unique property of the Climate Commitment is its goal of complete elimination of emissions rather than some arbitrary reduction in the increase in emissions as is often the effect of other programs. C ollege and Uni versity Systems to There are numerous systems developed for evaluating the green performance of colleges and universities. Some of these are prescriptive, offering more a vision and a set of evaluation and planning tools, oth er offer more in the way of evaluating actual performance of implemented measures. The following section will examine and put these programs and methodologies into the context of this research and the studied system. In addition to the more general framew ork systems, many colleges and universities choose to design and implement their own ranking system. I can suggest several reasons for this. This may be because each campus is unique, having different climates, different scales, different needs, and differ ent levels of support both politically and financially for such projects There is also a component of competition amongst institutions; none want to be beholden to another institution for their building design or

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38 rating so they develop their own, often he avily based on existing frameworks. Universities have great support for such projects and have a lot of available participation for developing their own plans. I t is far cheaper and easier to develop frameworks, suggest research projects or otherwise study the problem rather than take action to change the way the campus operates. It is not difficult to convince students or faculty that more research is required and given the opportunity to try and solve such problems completely before acting, a university p opulation is more apt to put off action and pursue planning. The situation of colleges and universities presents a dichotomy of being both institutions like many others and being fundamentally academic in nature and purpose. The confluence of the ability to study and innovate with the ability to implement and refine, ultimately contributing those experiences to society makes the study population so interesting. One of the defining characteristics of the population is who the driver of the efforts is, wheth er it is students, faculty, administration, facilities management, or higher up political figures. The experience of Audrey Chang developing sustainable construction guidelines at Stanford University seem typical of many such experiences of students tryin g to engage faculty and administration in making commitments and changes to the normal operating procedures of campus construction. In addition to the usual reticence of administration to address the problem of sustainability there were conflicts with othe r student groups and a desire for the university to develop its own green building guidelines rather than try and implement or build upon existing standards, particularly LEED. (Chang, 2004)

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39 In attempts to standardize campus carbon emissions planning and other aspects of sustainability planning several general planning frameworks have been developed The National Wildlife Federation's 'Guide to Climate Action Planning: Campus Ecology' provides a set of studies and participation exercises for evaluating ca mpus ecology but does not focus on carbon emissions specifically and the accounting needed to track their reduction. (National Wildlife Federation, 2010) The Canadian 'Campus Sustainability Assessment Framework' (CSAF) is an evaluation program similar to t he tracking system of the ACCUP's program associated with th e Climate Commitment Planning. Lindsey Cole developed the program for use in evaluating the sustainability planning of Canadian Universities. This project was aimed at improving planning feedback and plan development rather than the feasibility of the plan as is the focus of this research (Cole, 2003) Almut Beringer implemented the CSAF in his evaluation of Canadian university sustainability planning and implementation. He points out that the weak point in the CSAF is the lack of rigorous accounting of carbon emission and mitigation efforts. (Berlinger, 2006) The work of Herremans and Allwright looked at comparing institutions globally and developed a system aimed more at direct comparisons. (Herre mans & Allwright, 2000) Creating a broader set of tools or frameworks to compare institutions beyond the US and Canada becomes more difficult due to differing standards in emissions reporting, cultural ideas about sustainability, and the influence of emiss io ns reduction efforts. (Wright 2002) Studies of individual institutions abound and as each institution progresses in implementing their plans and reporting their results case studies will proliferate. (Thurston & Eckelman, 2011) Comparison studies of sus tainability

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40 measurement tools have provided substantial results such as the case with Michael sustainability tools have been more broadly focused, rather than singling out carbon mitigation planning. Many of the studies are now nearly or more than a decade old there is an opportunity to revisit these methodologies and evaluate the predictive value of that research in light of ten years worth of results. Institutional Carbon Emissions Mitigation Planning in Context The reduction of carbon emissions from human activity is central to developing sustainable ways of living. As easy as that statement is to make it has proven difficult to decide on how to make emission reductions. Even with substantial increases in affluence have combined to create a steady increase in carbon emissions. (Cranston & Hammond, 2010) Indur Goklany argues that rising l evels of affluence over history have always led to greater human wellbeing, but that same rise also contributed to a dip in environmental quality. While affluence first causes pollution and degradation, it also provides the means and desire to clean up and restore the environment. Rising levels of affluence in the West have demonstrated this but it remains to be seen if raising levels of affluence globally will affect the sort of planet wide problem like greenhouse gas emissions in the same way it mitigated pollution in specific geographic locations. (Goklany, 2009) Businesses have played a role in developing expectations of institutional responsibility beyond their traditional role of actors concerned purely with economic development. In the business world range of social and environmental topics and has become a common factor in business

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41 ty in business has consciously created situations in which profits and other traditional measures of business success have been reduced in order to implement these principles. (Reinhardt & Stavins, 2010) In other sources the opposite has been argued, that businesses pursue factors of social responsibility for underlying reasons such as reducing cost and risk; strengthening legitimacy and reputation; building competitive advantage; and creating win win situations through synergistic value creation. The ongoi ng research focusing on businesses and their relationship to social responsibility efforts represents a period of attitude formation and a self reflective effort within the business community in an attempt to understand their role in the social and environ mental consequences of their activities. (Kurucz, Colbert, & Wheeler, 2008) Carbon emissions mitigation planning in businesses has taken an ad hoc approach in the United States with institutions developing their own efforts for their own reasoning. This ma kes direct comparisons between businesses difficult. The same is true in institutions of higher education in general and specifically the participants in the Climate Commitment. Some findings have indicated similar influences in carbon mitigation planning in businesses to those used in institutions of higher education. Ownership, public or private, and institutional culture represented at levels of management and broad institutional attitudes have influence as well. (Carroll & Shabana, 2010) A further diffe rence between corporate efforts and public efforts at carbon mitigation planning is the successful use of incentives to motivate employees to make suggestions or change behaviors to reduce emissions. (Aggarwal & Dow, 2011)

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42 Municipalities are conducting mi tigation planning efforts similar to corporations and businesses. The use of case studies in examining planning at this level and in the public sphere has demonstrated a variety of approaches to carbon mitigation. (DuBose, 2000) The lack of standardized em issions accounting and an agreed upon goal has limited the ability to directly compare planning efforts and conduct the kind of analysis made possible by the consistency of planning and reporting provided by the Climate Commitment program. Increasingly re search is showing that the most active and ambitious planning is taking place at the local level rather than the national level. This research points to the issue of scale as the defining characteristic of significant planning efforts. (Ramaswami, et al., 2011) The scale of these municipal systems is similar to that of the institutions who are participating in the Climate Commitment. Carbon Mitigation Planning in Institutions of Higher Education Colleges and universities have begun to take an active role i n shaping the response to climate change by making the effort to mitigate their own emissions from operations. The traditional role of institutions of education and research has been expanded to include this meta responsibility in utilizing the campus to a ct as social and technological laboratory. (Irandoust, 2009) American colleges and universities have been at the forefront of sustainability efforts of all kinds and have developed a wide range of reporting and evaluating systems to track activities associ ated with all things developing their own systems of reporting, it has not been a straightforward task to directly compare institutions beyond limited case study comparisons. (F onseca, Macdonald, Dandy, & Valenti, 2011) These efforts by institutions to develop frameworks

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43 have been influenced by their respective institutional cultures as well as planning efforts at every scale up to the international. In particular the influence o f international declarations on sustainability topics has been noted as prevalent in the planning process. (Wright 2002) The Climate Commitment program has served to focus a portion of sustainability planning on the problem of carbon emissions and it has provided a framework for direct comparison of efforts to ward specific goals and a thorough but reasonable reporting system has contributed to a wide range of insti tutions participating. (White 2009 ) This range of participants strengthens the system and provides for a rich and diverse set of comparable efforts. The plans submitted by participating institutions, for the most part, do adhere to the goals of the planning process. Many of the plans incl ude a range of information that could be called with carbon emissions mitigation. In many cases the plan documents are not on the topic of carbon mitigation planning, misunderstand the goals of the program, and are explicit in not expecting to meet the goal, or even misunderstand the type of institution the plan represents. Those are the exceptions; in general the planning efforts conducted under the Climate Commitment program do direct ly address their stated purpose and offer a roadmap for their respective institutions to follow in order to fulfill the Climate Commitment. The plans are all available online at the Climate Commitment reporting system web site. ( http://rs.acupcc.org/ ) The choice in this study was to focus on structural features of the population (ownership, size, majority type of degrees awarded) but other studies have examined

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44 other dividing factors. Ned Fetcher has published work desc ribing the same population group in terms of their location, institutional size, and type of institution by degrees 2 year and majority 4 year as we have in our study.) emissions scaled closely with building area but less closely with enrollment. Geographic methodologies did not allow for disentangling type of energy used and climatic conditions and confounding factors such as energy used for cooling in warm climates being as significant as energy used for warming in cool ones. Those findings covered a population of 238 institutions and were a significant porti on of the total population. While his methodologies differed from the ones utilized here, his findings and those of this study are compatible. (Fetcher, 2010) Looking at the same Climate Commitment population but examining in more depth the emissions as ra te by enrollment and by type of building area, Cynthia Klein Banai and Thomas Theis found that factors such as the activities that take place in buildings and the total enrollment were significant in predicting the emissions of the study population. (Klein Banai & Theis, 2011) The examination of emissions as a rate per enrollment or building area is perhaps the most common means of describing institutional emissions. This makes sense since the rate description is representing the efficiency of the instituti program focused on efficiency but on an absolute goal of zero emissions. For that reason this study has tried to remain focused on the absolute emissions of the

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45 participating institutions rather tha n on other explanations and descriptions of emissions such as geography and enrollment. Carbon Neutrality in Other Institutions The fundamental goal of the p lans studied in this project are reducing or even eliminating carbon emissions from campuses. The college or university is certainly a unique type of institution but not unique in the problems they face in reducing carbon emissions. The same problems are faced by businesses, towns, neighborhoods, tourist destinations, and other sorts of 'places.' The similar qualities between these groups include: Defined Places: there is a geographical area with known boundaries in which the entities activities take place. Emissions are quantifiable: there exists some reasonable means by which to calculate emissions from the place. Organization: there is some sort of organization with power to make decisions on issues of services and energy within the place. In the case of colleges and universities this is the administration and its parts both up and down the chain of command, faculty, community, donors, and students. In the case of businesses or towns there is some sort of elected or owner leadership. Even in neighborhoods there are decisions made about services either by a municipality or by citizen organization and action. Motivation: for various reasons a desire and motivation exists to take on problems that are not being addressed at some other level either because they are too onerous at a smaller level such as individual homes or buildings, or because of lack of political will or consensus at a larger scale. A dedicated set of users, be they students, clients, customers, or residents seems to be a requirement for serious action. The problem of scale in emissions reductions seems to be solving itself organically. The larger international and national scales lack the political will to address the problem in a serious way. The regional scale can muster the will but lacks the control and accounting to understand and address the problem. The scale of individuals

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46 or in dividual buildings seems to make the problem too burdensome or difficult, the above example of the Lewis Building at Oberlin College not withstanding (perhaps the exception that proves the rule?) The scale of community, college, university, business, or ec o focused destination seems to be the correct one for addressing this particular problem. Expected U se of Purchased Carbon Offset Credits The market for carbon offset credits is growing rapidly; i t can be difficult to voluntary Chicago Climate Exchange (CCX), which operates more like a traditional commodities market, and various other systems associated with other markets or not as the case may be. We can say that the rate of growth in 2005 2006 was about 200% with subsequent years supporting that upward trend. (Hamilton, Sjardin, Marcello, & Xu, 2008) At this time the nascent carbon markets do not provide a level of consumer confidence in the value of their credits or the methods by which they are generated. The level of commitment to their use found in this research would seem to reinforce findings by Dhandra and Hartman that consumer literacy on the topic o f carbon offset markets is still low. (Dhanda & Hartman, 2011) As these markets expand they are beginning to define themselves in the mind of the consumer. Research published by Lovell et al in 2009 utilized a methodology of critical analysis and interview s to understand the narrative being created by these developing markets and the consumers who buy carbon offset credits. This research has similarly used critical analysis as well as other sources of data to determine the extent to which the subject instit utions are planning to rely on purchased carbon offset credits (PCOCs). Lovell et al

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47 decision to purchase carbon offsets. Because the buyer receives no goods and (regulatory or self imposed mandat e aside) has no need for the product the use of such narratives becomes pivotal in the purchasing decision. (Lovell, Bulkeley, & Liverman, 2009) In this research the motivation for purchasing credits is to fulfill the Climate Commitment, which is utilized as one among many proposed mitigation methods. The use of offsets is described in the above cited works from a market perspective and in the intended application of the purchased offsets. As part of a planning program many of the studied institutions have conducted their own analysis as part of their participation in the Climate Commitment. Duke University has published several reports generated by graduate students working in their Nicholas School of the Environment and Earth Sciences highlighting their e xpected use of offsets as well as research into Strauss, 2011) (Conrad & Hodgson, 2011) (Wangerman, Kaufmann, & Tang, 2011) The conclusion of the researchers at Duke was tha t there existed substantial potential in the Duke forest holdings for the production of carbon offsets to be used or sold but there remained a great deal of uncertainty related to the cost of development of those credits and risks associated with whatever regulatory and tax regime may ultimately regulate such markets. Many of the Climate Commitment plans expressed reluctance to utilize offset credits as part of their mitigation plan. Research conducted in support of the Climate Commitment planning effort a t George Mason University examined attitudes of the campus population and found a high degree of skepticism in the legitimacy of offsets and whether the purchase of offsets had the same effect of reducing local emissions

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48 levels at the nominal rate of the c redit purchased. (McCauley, Robertson, Krueger, & Gurkin, 2009) Similar objections were expressed in the development of guidelines for the carbon neutrality at the Victoria University School of Architecture and Design. (Ryu, 2010) In each case it was expre ssed that without some tangible locally visible effort the claimed reductions from purchased offset credits were somehow less meaningful than localized action. In environmental terms and in terms of the Climate Commitment, the source of carbon emissions mi tigation is irrelevant, the point is to reduce emissions, but in human terms as expressed above and in the narrative of many of the plans, there is a preference for more visible and local action. This distrust is warranted by the current lack of regulated and institutional carbon markets in which the integrity of the credits could be evaluated. In other cases the use of offsets was implemented without reservation such as was reported in research describing the Climate Commitment planning process at Central Connecticut State University and at Colgate University. (Button, 2009) (Greenfield, Leslie, & Stimmel, 2010) Planning at Yale University has taken a middle ground in recognizing the psychological impact of a visible and local project designed to mitigate e missions but also describing purchased offset credits as viable and useful tools in reaching mitigation goals. (Raunch & Newman, 2009) Another common description in the plans of the use of offsets is to tie their use to a particular activity, usually air t ravel. Air travel is one of the few sources of emissions related to campus operations that the institution has little opportunity to mitigate through technology, behavior, or other means. In a short article, Kathleen Smythe describes alternatives to the u se of offset credits in mitigating emissions from air travel by rethinking and rearranging the behaviors associated with air travel. She suggests

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49 reducing the range of conference attendance and reducing the size of conferences in order to limit the number of travelers. (Smythe, 2010) Content Analysis Content analysis is a method of extracting information from a narrative text that through frequency, type, emphasis, or other facts can be used to examine and compare the text with similar texts, provide inform ation on the writer, or be used to make comparisons with factors of the subject of the text. Co ntent analysis can be used in a range of ways to examine and compare documents Content analysis is used in many fields as a tool to examine planning efforts for a range of activities including carbon mitigation. (Freedman & Jaggi, 2009) (Klver, 2009) Content analysis allows for an additional means of seeing the reported data from a particular organization. The use of this method in this research has been to try to provide a description of the motivations and attitudes of the institutions producing carbon mitigation plans. Similar studies have been used as a check on the use of carbon mitigation planning in companies and provides a supporting set of research that has examined similar problems with similar tools. Particularly the work of Sue Hrasky who used content analysis to describe and assess the strength of action proposed in companies in Australia The study is very similar research objectives were different. (Hrasky, 2011) Prendeville, et al utilized content analysis in conjunction with carbon foot printing and life cycle analysis in an effort to develop a broad based tool incorporating all those techniques and use Welsh bu sinesses as a test case for the methodology. (Prendeville, O'Connor, & Palmer, 2011)

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50 CHAPTER 3 METHODOLOGY Objectives of the Study Main Objective s The main objective s of this study are t o ascertain the degree of ethical motivation in university carbon m itigation planning and to ascertain differences between the four strata populations in regards to their use of purchased carbon offset credits for reaching their goal of eliminating carbon emissions from operations. This study utilizes the carbon mitigatio n plans of the 680 or so colleges and universities participating in the American College and University President's Climate Commitment. Using a representative sample of this population we have considered the language of motivation and intent in the plans t o try and understand the relationship the institution has to its carbon mitigation efforts; the 'why' and the world view expressed in the plans. Secondly, the research will consider the carbon emissions at the baseline year, in a business as usual case of continued growth in emissions to a set end date, and the proposed quantities of carbon offset credits needed in addition to other measures to reach the goal of eliminating emissions entirely. The study examines how factors such as size of institution, regi on, ethics, and others affect the planning efforts and proposed mitigation strategies. Sub objectives 1. What methodology was followed in creating these plans? 2. What kind of institutional force has been put behind implementation and tracking of these plans? 3. W hat was the motivation for participating in the program ? W as there a particular process used in some cases or others or was an individual or group responsible for the impetus to participate?

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51 4. How does the institution view itself in this process of planning for sustainability? 5. Was there an educational motivation particular to institutions of higher learning ? Hypotheses 1. There will be a range of ethical and theoretical approaches used in addressing the problems identified in the plans. 2. There will be a relati onship between how the institution views these problems of emissions and how they are addressed, represented by the proportion of mitigation that relies upon purchased carbon offset credits rather than structural or institutional changes. 3. There will be a r elationship between expected growth of emissions in a business as usual case and the portion of mitigation coming from purchased carbon offset credits. 4. Emissions mitigation strategies will be insufficient to meet reduction goals; they will not be sufficien tly broad, will not be sufficiently funded, not be supported, or not be feasible. The hypothesis in this research project is that there will be a range of ethical and theoretical approaches used in addressing the goals of these plans In some cases the mo tivation will be sustainable by nature, it will be focused on environmental quality issues that effect the populations of campuses; in some cases the motivation will be economic, seeking to take advantage of incentives, funding, and cost savings associated with reduced resource use; in some cases ethical responsibility of the university will lead to the motivation to reduce carbon emissions; there are myriad reasons for supporting the plans with a range of sustainability, environmental, and economic goals.

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52 B uildings are the largest source of emissions from university operations and are the source most easily controlled by the institution (compare d with commuting, municipal resource use or travel.) The campus built environment is the focus of most of the st udies and recommendations. While the institutions utilize differing methods of accounting for emissions, they are roughly similar in what is included and the reported emissions are broadly consistent across similar institutions, allowing for direct compari son with little error introduced in the reporting methodology. For the purposes of this study, the reported emissions are the subject rather than a critical accounting of the carbon emissions measurement process. Through understanding the motivations, theo retical underpinnings and interpretation of sustainability, and by evaluating the emission levels and mitigation strategies this study will create its own framework for mitigation plan comparison as the implementation periods increase and the dividends fro m implementation are realized The entire population of institutions is used in the first quantitative portion of the study in which emissions, future emissions, expected m itigation, and expected purchase of carbon offset credits is considered. The content analysis portion of the study utilizes randomly sampled group s in each of the strata. The drive toward sustainabi lity is a natural and noble one. I t in all aspects of our lives, we see a recognition that we need to conduct more in depth and thoughtful pl anning of resource use and begin to take control of the energy and material flows that occur in our activities. A portion of this research is concerned with whether what is proposed actually moves the campuses in question carbon neutral operations or wheth er the end result is meaningful In the planning process it is easy to lose sight of

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53 the original goal and this research will act as a check on these plans and their outcomes. Significantly there is always a motivation and ethical framework in which susta inability thin king takes place B y reading for motivation and intent we will be able to sort the plans into different ethical frameworks and use that as criteria in evaluating effectiveness. Theoretically we can place bets on which framework will produce th e most effective plan and ultimately we can test those theories as results and tracking data become available in the future. That groundwork is best laid now at out outset of these plans and the tracking and reporting regimes that will provide future resea rch data. There is often an impetus to want to reduce measurement of complex problems, like sustainability, into single numbers or metrics to make them easily digestible and comparable such as the miles per gallon for automobile efficiency which serves to reduce the 'greenness' of a vehicle to a single number but ignores all the mitigating, and arguably far more important factors. However emissions are measured and treated in these plans might create an effective or ineffective commensurability between p lans or it might over simplify a complicated problem. In studying the carbon emissions measurement and mitigation methodologies we will improve future planning efforts. The quantitative portion of the study will put into context the scale and method propos ed to achieve zero emissions; the content analysis portion will provide the context of the planning efforts. Study Design This study is a cross sectional retrospective non experimental study employing both qualitative and content analysis methodologies.

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54 The entire population is utilized in the emissions and mitigation section of the study, the population being manageable enough to examine and use all the available data from the plans. The study will look at the plans participating in the Climate Commitmen t at the time the study is conducted, approximately Spring of 2011. There is potential to continue the methodology in future studies to examine additional schools as they participate in the program and submit their plans but this research is aimed at the e arly planning efforts being made before substantive efforts have been implemented according to the plans. Examining the effects of the duration of participation in the program as well as progress will have to be left for future studies Longitudinal studie s can be conducted to follow the participating schools as they report progress in implementation. Additionally, future work can be conducted in examining particular school plans using the developed instrument and methodologies to focus and refine understan ding of individual schools or at the behest of particular institutions. This research is a first step and will be taking a complete look at carbon emissions reported, planned growth, expected mitigation, and expected carbon offset purchases, the content an alysis portion examines a cross section of a large data group at a particular point and will provide insight into how differing types of institutions are approaching their roles in achieving their goals. This study's reference period is a retrospective on e in that it's data set is the existing plans available from the ACUPCC. Future studies could broaden the research into prospective studies of future outcomes from plan implementation but that is beyond the scope of this study. There will be some effort to evaluate the potential success of the stated goals of the plans in the data set but only in so far as accounting for their

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55 emissions estimation and mitigation strategies. The study data is retrospective in nature. Non experimental research involves retro spectively linking the effect to the cause in the experiment and does not allow for controlling the independent variable in order to test hypotheses. The goal is to examine the relationship between the ethical language and motivation of the participants an d their carbon emissions and mitigation strategies as well as compare emissions measurement methodologies employe d with their mitigation plans. T his will all take place using the existing plans without the ability to further, experimentally, test the study 's findings. Future studies could be conducted as experimental studies if there are strong results from this study and the study influences future planning efforts in a testable and comparable way. Both quantitative and content analysis methodologies will be employed in this research. The first section of the study involving c arbon emissions reporting and carbon mitigation strategies will be a quantitative analysis utilizing data from the entire population for d irect comparison between strata and providing correlation analysis of data within each stratum Problems and Limitations The data set is limited to institutions in the United States that have first chosen to be a member of the AACUP and secondly have decided to participate in the Climate Commitment program. Some participants in the program have not submitted plans or submitted plans of such a limited or incomplete nature as to render them useless for this study. Among those who have submitted the required data and substantive plans some have proposed mitigation strategies that do not utilize carbon offset credits T hose are included in the study as part of the range of approaches to emissions mitigation.

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56 A study like this one has to address the problem of self selection in the participant's data set. The United States hosts somewhere around 4800 colleges and universities. Of that group the current participation in the climate action plan initiative is about 680. An effort will be made to determine the source of this self selection, what types of instit utions are participating and what types are not in so as far to credibly address the problem of self selection in the data set. More than likely a large number of those institutions not participating are either very small or very focused on a particular ty pe of education to which the climate action plans woul d be difficult to apply such as urban institutions with discontinuous campuses online schools, religious schools, or schools that for what ever reason have chosen not to participate. There is a range o f types and sizes of institutions participating in the climate action plan program and the results of this research will apply to typical colleges and universities. Additional reasons for non participation include not seeing the program goals as imperative to the institutional mission, implementing another emissions reduction framework that does not fit the rigid goals and requirements of the Climate Commitment, or a belief that solutions will come about through extra institutional means such as geo enginee ring, carbon sequestration, or technological breakthroughs. Population The American College and University President's Climate Commitment ( http://www.presidentsclimatecommitment.org/ ) represents over 680 colleges and universities and has created a set of guidelines and formats for creating comparable plans as well as a reporting system to keep track of the progress being made in implementing the plans. These approximately 680 colleges and universi ties make up

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57 the population of this study. The population includes all types and sizes of institutions from community colleges to large and small public schools to private schools as well. The motivation for joining this project and creating these climate mitigation plans is varied and sometimes well discussed and explained and some times not addressed in the plan documents The institutional motivation for participating is of interest to this study and ascertaining the ethical relationship expressed by the institutions for the environment makes up the content analysis portion of this research. Motivation and relationship is important for a variety of reasons. The 'why' of an institution's actions can offer insights into their choice of emissions reporting a nd mitigation efforts, which are studied in the quanti tative section of this project In general we can say that motivation can be important in which efforts are implemented to reduce carbon emissions and provide for the future of the institution, particul arly since the planning period is beyond the typical length of employment of those developing them; we can also imagine these climate change and energy efficiency. The s ource of that motivation, whether it is legislative, administrative, the result of a group, or the project of an individual should have some relationship to the ultimate plans and also the actual efforts towards emissions mitigation. Even without empirical results there should be some relationship between who is motivating the planning and what action is planned and potentially the actions taken. This study cannot determine that specific relationship but can begin to examine the issue. Problem awareness is the first step in taking action to solve a problem. This population has taken that step, recognized the problem and committed resources to

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58 plan to solve it. Taking the next step of committing resources to implementation will no doubt be predicated on the ability of the planning process and its product s to convince decision makers of the desirability to implement the plan. So we have an interesting situati popul ation is no doubt keen to solve and which by and large accepts t he gravity and necessity of solving, and a planning effort that will not only find the most efficient and effective method of solving it but also be effective in convincing the rest of the community, administration and the owners, board members, and/or le gislatures of the goodness of their efforts. The choice of colleges and universities for this study was not accidental. The la rge size of the data se t, about 680 institutions participating, and the uniformity of the plans allows for direct comparison of a t least some aspects of the plans. Colleges and universities offer a set of unique circumstances that also make them an interesting case in carbon mitigation efforts. They are centrally administered; this leaves planning more in the realm of dictate than c onsensus. Many of the plans were created by large and diverse working groups, representing different factions of the university community, professional as well as public; but the ultimate support, implementation, and success of these efforts will rest on t he motivation of administration to fund and oversee their fruition. Compared to municipalities, local, state, national, or international planning efforts these are dramatically more straight forward projects and their plans much more definite and their suc cess much more discernible. The scale of organization and oversight varies with differing problems. Peace between nations cannot be organized at the local level, it requires an international effort; similarly, school boards are almost all local or state in scale rather than the larger national or smaller neighborhood scale. For

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59 whatever reason certain problems work better at different scales than others. Sustainability planning in general and carbon mitigation planning in particular may be best handled at t he community scale and that is what we're seeing in these colleges and universities. Colleges and universities offer an excellent case study in community carbon mitigation efforts. The first ste p in mitigation is measurement because we must k now what we'r e trying to reduce, establish baseline carbon production figures and ascertain their sources. Being centrally administered as well as the majority of carbon emissions resulting from expensive energy consumption we can hope for excellent tracking and record ing of energy consumption by these institutions. The source of carbon production estimates in these cases is an amalgamation of consumption figures rather than a direct measurement of carbon emissions. While this is a limitation for the planning groups it is most important to have consistency in the relationship between the baseline carbon emissions figures and their mitigation measurements over time. Even given that actual emissions may be different from the calculated emissions, as long as all sources of emissions are included and all mitigation efforts are accurately measured in a manner similar to the production method the result should be representative of the success of mitigation. The question of what to include in emissions calculations is addressed in varying ways by the plans. As long as there is a consistency within each plan of what to include and measurement and what is addressed in mitigation then there will not be a problem. Some plans include commute r emissions and fleet vehicles and some do not. T his seems to be the major factor either included or not and has a dramatic effect on the

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60 emissions measured by each institution. The comparison of any particular member of the population to any other needs to be based not on absolute reported levels of emissions or mitigation but on a ratio of the two to remove these differing strategies from bearing on the consideration. There may be a revealing bit of information in the rates of commuting amongst schools and their likelihood of including those emiss ions in consideration. It might be the case schools with high rates of commuters might not include those emissions in their calculations or it might be the case that irrespective of the source of emissions the consideration in planning is to what degree an d at what cost can emissions be reduced compared to their levels of emission. For instance, if carpooling and public transportation can be inexpensively used to reduce commuters then the cost per unit of reduction might be quite low and in that case a scho ol may well decide to include those emissions in their plan. Unlike many communities that have similar motivations, talents, and commitment; colleges and universities also have the funds or the power to raise the funds to accomplish virtually any goal ima ginable. As a source of first line science and technology as well as the repository of human knowledge and understanding colleges and universities should be taking the reigns in solving the problem of carbon emissions. Funding through grants, endowments, p ublic monies, and all level of finance mean that if the institutional mind is put toward implementation of these planning efforts the potential failure point should not be funding. The scope of the projects, fifty years, allows for all sorts of creative fu nding from long term investments to planning for future technologies to address the problem while simultaneously arranging the financing today for these future needs at a point where the funds are available and the technology can

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61 solve the problem. How man y dollars invested today would be required to solve this problem with 25 years to go 25 years from now? These are the sorts of questions only answerable by economists, scientists, and administration; most other communities lack these sorts of resources in their planning efforts. Details in emissions are important. In the most basic case a population member may simple look at their power bills to ascertain the amount of emissions they are responsible for. This is an over simplification but the effort to roo t out all the sources of emissions can become quite onerous and if consideration is given to the embodied energy or materials in use on the campus it may become too complicated to accurately track and understand. There is necessarily a divide between a suf ficient level of detail in emissions tracking and too much detail just as there is between too little. Our hope is that these plans not only take into account large and obvious emitters such as energy consumption, fuel use, materials consumption, and lands cape development and maintenance; but also that the institution thinks creatively about where they may be emitting and how they can address rather than ignore that. The method of emissions mitigation offers the most difficult aspect of these planning effo rts. How, over the next fifty years and untold technological and policy changes, will they succeed in fulfilling their planned promise of today to reduce emissions to zero? That will be the most interesting part of the study. We can only hope that this hit herto unsolved problem of completely emissions reduction can be solved by what should be the most capable parts of our society. A grasp of technology, science, policy, population, and most of all an understanding of the changing face of our world are requi rements in making these planning efforts. This population of colleges and

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62 universities, like few other communities on the planet, should be capable of unique, innovative, and lasting solutions. The excitement of discovering the solutions reached by these i nstitutions is palpable and their success or failure will be the first legacy of the 21 st century. We can absolutely see these efforts at the scale of colleges and universities as the first test case in community carbon mitigation efforts. If colleges and universities make headway in reaching their goals they can serve as test beds and models for other communities and larger and smaller scale groups to implement if not similar solutions at least similar planning efforts. This population represents the firs t of a future range of planning efforts. To that end it will be important to understand this population s set of motivations, efforts, and ultimately in a future study, their results. Societies as a whole tends to lag in implementation if not awareness of these types of large problems, allowing the idealistic and capable populations of colleges and universities solve societal, technological, scientific, and human problems first. The success of these herculean efforts will either reveal a future in which we can address carbon emissions in a successful way and retain our currently energy intensive quality of life with fewer resources or it will be a harbinger of more radical actions as energy and carbon conspire to change the way humans operate. The community of colleges and universities is made up of trustees, legislatures (in the case of public institutions), administrators, faculty, staff, employees, suppliers and utilities, local government, and of course students. Different places place different levels o f emphasis on these community members and their power and influence varied greatly but in general each has some ability to influence the process and action taken by the

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63 institution. The largest group, and potentially the most vocal, is the student populati on, followed by the faculty. Colleges and universities tend to have an active, progressive, and innovative approach to community problems such as the subject of this study. This may be a reason they have been the first to adopt a large scale, coordinated, and comparable set of plans and future efforts to address the very large problem of climate change due to carbon emissions. If we think about how larger scale efforts have so far had little consensus and success of defining planning to reduce carbon emissi ons in a dramatic way and if we consider that small scale efforts such as made by individuals to reduce carbon emissions simply are not substantial enough to make a difference we can see the community scale as being the best chance for success in reducing carbon emissions. The community scale could be l arge enough to m ake a difference and small enough to take action. The magnitude of the problem is such that even at this scale with its advantages and motivations, these planning efforts are still half centur y efforts, larger and more daring than just about any other project in the recent past. The building of the great monuments of history required this level of commitment of time and resources but not of institutional transition, the great revolutions of his tory occurred more quickly and with great drama but out of necessity rather than foresight. A half century of efforts based on a few years of planning and subsequent updates in an effort to completely change the workings of major institutions in coordinati on with the rest of society and continuing in their mission is comparable to the Manhattan Project and the Protestant Reformation occurring simultaneously. If anyone can accomplish it, it will have to be colleges and universities

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64 Selection Methodology Mo st of the plans contain the key data points of enrollment and baseline emissions. The signatories analyzed in this study were screened by those institutions that had completed plan submissions (317 of 680.) Of the 317 submitted plans only those institution s reporting enrollment, baseline emissions, and business as usual emissions were included in the study, a total of 103 institutions. Reported enrollment from the Climate Commitment system was used throughout the study, though it should be noted that enroll ments often differed from those reported by the Carnegie Foundation for the Advancement of Teaching Classification for Higher Education System. (Carnegie Foundation) Institutions analyzed in this study were divided into four strata by ownership, size, and majority of degrees awarded: 2 Year Public Institutions: 8 Institutions 4 Year Small Public Institutions, having an enrollment of fewer than 15,000 students: 35 Institutions 4 Year Large Public Institutions, having an enrollment of greater than 15,000 stud ents: 21 Institutions All Private Institutions: 39 Institutions The strata characteristics were determined based on common and easily defined distinctions in the institutions; these distinctions are hypothesiz ed to lead to a range of emissions mitigation a pproaches and efforts. There are no conclusions to draw about the many institutions of higher learning in the United States and of institutions belonging to the American Association of College and University Presidents who choose not to partic ipate All r esults, findings, and analysis only apply to the submitted plans. Sample selection from the population used the random number table method without replacement. (Kumar, 2005)

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65 Variables General V ariables Date of carbon neutrality Student population of scho ol Type of institution: public or private Type of majority of degrees awarded: bachelors or associates Length of plan, number of pages Who worked on developing the plan [categorical] Variables in the Emissions Mitigation S ection Methods of emissions reduct ions [categorical] Expectations for reduction in emissions given planned methods Plan to handle future emissions due to growth or other factors [yes/no] Position of the institution on the use of carbon off set credits in reducing net emissions [yes/no; wh y] How will progress be recorded and reported Is there a feedback process for modifying the plan over time [yes/no] Variables in the Content Analysis Section Is there a definite ethical world view discernible in the plan [yes/no] [quantity] [quantity] Source of motivation for planning efforts [yes/no]

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66 Measurement Procedures This study utilized the data provided in the Climate Commitment program plans submitted from participating institutions. Of the roughly 4300 institutions of higher learning in the US, about 660 have committed to the program. The signatories analyzed in this study were screene d by those institutions that had completed plan submissions, which was done by 317 of the 660. The list of participating institutions is available from the AACUP reporting web site, as is emissions and enrollment. The 317 plan submitting institutions were divided into four strata reflecting enrollment, ownership, and majority of degrees awarded. The strata reflected what we believe to be the defining characteristics of how institutions will address their carbon emissions mitigation efforts. The division bet ween 2 Year and 4 Year institutions reflects the majority of degrees awarded, the former being community colleges. The 4 Year Public group is divided into 'large' and 'small' based on enrollment with 15,000 students and above representing the large group a nd below that enrollment the small group. 'Private' refers to non public institutions. All institutions fell into these four specific strata with the exception of one 2 year private college, the College of Menominee Nation, a tribal college of about 600 st udents in Wisconsin. They were included in the 2 Year group. The breakdown of the strata was chosen because it was these factors that were thought to provide the clearest demarcations between differing approaches to sustainability on campuses. The emission s mitigation plans of the Climate Commitment program are publicly available at the program website. Most contain the key data points of enrollment and baseline emissions Reported enrollment of each institution differs, often substantially, from the instit utions' websites or the Carnegie Classifications of Higher Education enrollment data. For the purposes of this study, the data r eported to the AACUP was used.

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67 The essential data for this study were: enrollment, total emissions, predicted future emissions if no action is taken, and planned level of or lack thereof of purchased carbon offset credits. Institutions providing all of this data are herein referred to as having full data. While having full data for the purpose of this study reflects a complete eva luation of carbon emissions mitigation planning, the choice by some institutions to not utilize PCOCs did not exclude them. The failure to discuss or mention this common method of emissions migration in their planning efforts did exclude those institutions from the study. This research study does not imply that lack of discussion or use of purchased carbon offset creates an incomplete or unworkable plan, just that plans analyzed in this study met certain criteria. It is not the purpose of this study to advo cate for or against the use of PCOCs, but to examine how the use of credits relates to other structural factors of the institutions that have decided to utilize them or not. The strata were chosen based on an analysis of which factors showed the most dif ferentiation amongst the institutions. Enrollment and ownership was used to sort the data. Among the strata, only 2 Year institutions saw a negative correlation between enrollment and submission of full data needed for this study. The other three strata ea ch showed a stronger correlation between mean enrollment and enrollment of those providing full data. Public 4 Year institutions were the most likely to submit plans containing full data and for those higher enrollments indicated increased likelihood of su bmitting full data. A breakdown of strata along the lines of enrollment demonstrated that lower enrollments tended to have less complete data reported. The addition of the ownership criteria and the further split of the Public 4 Year groupings were introdu ced

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68 for the purpose of examining how enrollment influenced the intention to purchase carbon offset credits. (Table 3 1) The sample was further refined to include only those institutions whose plans included the data required for the study. The breakdown of the strat a is shown in Figure 3 1 Individual institutional plans were assessed through a critical analysis of plan content using a random sample of 10% of each stratum that included full data. This critical reading provides the basis for the discussion o f the plans contents below. Data on business as usual (BAU) emissions was used to show expected growth in institutional carbon emissions and the rate of implied growth of operations or enrollment that would drive an increase in emissions over time. These levels of emissions rates are generally straight line estimates based on a few past years of growth and do not reflect the capital and growth planning of the institutions. A stronger planning effort on the part of the institutions would have included the c apital, financial, and growth plans of the institutions, which often take place over similar time periods and a similar scale. The business as usual case is necessary because the end date level of emissions, defined by the program as zero, is the rate of i ncreased emissions against which mitigation efforts must work. To mitigate the start date emissions by the end date would only mitigate a fraction of the to tal emissions at that end date. Purchased Carbon Offset Credit Correlation Analysis Purchased carbon offset credits are utilized in most plans in a number of ways. They are used as a constant strategy to reduce net emissions by purchasing a set amount each year or a proportion of emissions as other strategies are introduced. They are used only at the end date to eliminate remaining emissions after all other strategies have been implemented in order to fulfill their program commitments. In a minority of

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69 plans they are used to mitigate specific emissions, most often emissions from air travel of faculty or s taff. The use of purchased carbon offset credits for this specific purpose most likely represents an institutional decision to apply this form of emissions reduction to the most intractable emissions problem rather than rely on calculating net emissions fr om all activities and allowing mitigation efforts of any kind to offset emissions of any kind. Targeting specific mitigation measures to specific emissions is one strategy employed as opposed to the 'big pot' strategy in which mitigation is not tied to spe cific emissions but works against total emissions. This distinction was never explicit or consistently described within plans and is stated here as an observation of the approach to emissions mitigation. Plans in the former group tended to enumerate specif ic buildings or emissions sources and target them for specific changes, while the latter approach led to introducing projects generally targeted toward the goal of emissions mitigation. All the plans were a mix of these two strategies. Data on purchased c arbon off set credits and BAU emissions were not reported as part of the AACUP reporting system. Those data were extracted by critical analysis of the plans themselves. The consistency of the AACUP reported data contrasted with the ad hoc reporting of the other relevant data. In some cases the data for the use of PCOCs was provided in the discussion, in others it was provided in the tables or data but not discussed. The 2 Year Public strata data set was excluded from the correlation analysis because only on e of the institutio ns indicated the use of PCOCs. Not included in this study is an analysis of expected economic issues with PCOCs. Part of the appeal and widespread adoption of this strategy is the ease with which they can be planned for and accounted fo r. PCOCs will have a specific price and effect, they

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70 will be easily knowable, accounted for, and implemented. In cases where some accounting for the expected cost was conducted the expectation of the cost of credits in a carbon market was dramatically vari able to the point of not making a meaningful estimate of market price for the carbon credits. Many plans offered logical inconsistencies in their estimation of costs compared to other capital projects to achieve the same ends. For instance, estimating the cost of a ton of carbon emissions mitigated through a particular capital project at $500 and an equivalent PCOC at $2. Those cursory estimates are not the focus of the planning or this analysis and are therefore not included in the analysis. Content Analy sis Content analysis is a quantitative methodology. By counting words or phrases we can compare individual items to others but the method is limited in that it cannot draw conclusions about things outside of the case study. The content analysis method is u seful for describing the participating strata and in comparing those strata to each other. The method is used in this study to test for the independence of the frequency and type of language used and looks for characteristics of the strata. The content ana lysis template used to record the data can be found in Appendix B. The following steps were used in developing the content analysis instrument and in implementing this portion of the study and are based on a methodology developed at the Colorado State Univ ersity by Mike Palmquist (Busch, et al., 2005): 1. Decide the level of analysis: a. Coding is for words or short phrases that include hedging or imperative language.

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71 b. Ethical and motivational coding should be explicit explanations or descriptions of the motivatio n and the source of that motivation. 2. Decide how many concepts to code for: a. Four concepts total i. Imperatives ii. Hedging iii. Ethical iv. Motivational 3. Decide whether to code for existence or frequency of a concept: a. Coding for frequency in the case of hedging or imperati ve. b. Coding for existence in the case of ethics and motivation. 4. Decide on how you will distinguish among concepts: a. The frequency coded concept will be grouped into the two concepts and a list kept of the phrases used for each type of content. i. Hedging lang ii. r essential act or commitment to an act. b. The existence concept will be recorded as a single event and in a single form.

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72 i. The presence of ethical or motivational language of any kind will be on the nature of those ethical and motivational drivers are kept for use in future research but are not utilized in this study. 5. Develop rules for coding texts: a. Words and phrases will be consistently assigned a group or validity under the existing content. b. In order to be coded in any category a phrase must: i. Be in the plan itself, captions, text, etc. ii. Appendixes are excluded from the content analysis. iii. If a phrase is repeated in any context it is recorded as many times as it occurs. iv. Phrases must be directly r 2 e mitigation. For example, phrases expressly related to recycling are not counted. v. Phrases lacking specificity as to their subject are assumed to be on the plan topic of mitigation and are included. 6. Decide what to do wit h irrelevant information. a. Irrelevant information (such as language explicitly on topics other than the subject of the plans) will be ignored. (Weber, 1990) 7. Code the texts:

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73 a. The analysis coding of the texts occurred in a consistent and continuous manner by a n individual researcher in order to maintain consistency and comparability of the data. b. Coding was conducted manually without the use of coding software with the results and other relevant details of the plans noted in a spreadsheet. 8. Analysis (methodology is further explained in this chapter with this section describing the general process): a. The content analysis is related to the emissions analysis section both within the strata and between the strata. b. The content analysis is examined using the Chi Squared Exact tests to determine the level of dependence in the strata variables and the results of the content analysis. Statistical Methods for Content Analysis The results of the content analysis were distilled from the form given in Appendix B to a data set for each of the four stratum. consultation with Dr. Michael Daniels in the Department of Statistics. (Figure 3 2, Figure 3 3 ) We considered the use of ANOVA analysis but decided on the Chi Squared and categorical data. The analysis was carried out in accordance with the methods described by Alan Agresti in An Introduction to Categor ical Data Analysis. (Agresti, 1996) The Chi Squared test was used to determine the independence of variables in the data set rather than as a test of goodness of fit. The null hypothesis for each of the Chi Squared tests was that there was an independent r elationship between the

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74 variables. When the Chi Squared test rejected the null hypothesis and confirmed the used to compare each of the strata distinguishing characteristics to further determine if any of the individual characteristics played a stronger role in determining dependence than any other. In the case of examining multinomial data the data was divided into bins describing a histogram like distribution of the data. T he results of the Chi of the relationship between the categorical data collected in the content analysis and the likelihood that relationship extends to the rest of the population. Those test resul ts provide for the data to describe the relationships that exist in the types of institutions and the ethical, motivational, imperative, and hedging content of their plans. The content analysis also included additional tests. The number of statements was normalized for the length of plans in order to see if a relationship was more evident in the relative quantity of statements rather than the absolute number of statements. The normalized mean number of statements per page was also used to create histograms describing the numbers of hedging and imperative statements present. The content analysis was used to describe a statistical norm for each of the measures of emissions pe r enrollment and per emissions/unit of building space.

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75 Table 3 1. Breakdown of institutional strata and relevant sorting data. Strata Percent and number with full data submission Mean enrollment of full strata Mean enrollment of institutions providing full data Public 2 Year 11% 8 9860 7895 Public 4 Year Small 43% 35 9077 10898 Public 4 Year Large 46% 21 27937 31143 Private 15% 39 3795 4733 Figure 3 1 Breakdown of strata showing proportion of institutions submitting complete data needed fo r the purchased carbon offset analysis portion of this study. Figure 3 2

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76 Figure 3 3 Table 3 2. Strata Content Analysis Data Table

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77 CHAPTER 4 RESULTS Strata Comparison and Classification The first an alysis used a strata comparison between enrollment current emissions, and future emissions in a BAU case. Correlation demonstrates the degree to which two factors are related, this study included two sets of correlation analysis between the four strata. Correlation analysis of factors was consistent between the four strata. Strong to very strong correlations were found between baseline emissions and BAU case. Strong correlations between this data in the four strata demonstrate that there are similar expec tations about future emissions in a BAU case based on current emissions regardless of size and type of institution. Enrollment data for 4 Year Public Large institutions reported far larger emissions per enrolled student compared to the other strata. (Figur e 4 1) The lowest correlation was between enrollment and baseline emissions in the 4 Year Public Large strata (Figure 4 2) The mean expected emissions growth rate was analyzed with outliers, those institutions reporting expected emissions growth rates abo ve 1000%, removed. The assumption is that unusually high emissions increase s were the result of typographical errors since the unusually high rates were not addressed in the plans. Expected growth in enrollment was not reported, but was extrapolated from e xpected growth in emissions assuming a linear relationship between enrollment and emissions Nearly all institutions expected their BAU emissions to grow from their baseline, with outliers reporting small percentage drops in BAU emissions compared to the b aseline. A few reported drastic reductions in BAU rates, again, most likely due to typographical errors The assumption

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78 of typographical errors producing expected growth in the range of thousands of percent could be accurately reported by the respective in stitutions, if so, this behavior would be the subject of a future study (Table 4 1 ) Th e use of emissions per student, emissions per square foot of building space, or other relative measures of efficiency in institutional emissions shows the different stra ta do significantly vary in their emissions in a relative measure that i s independent of enrollment. The smallest in stitutions, private ones, have the highest emissions per student. Because the Climate Commitment's goal is net zero of emissions, the effici ency or relative quantity of emissions would not affect whether that goal is achieved. Even a very high level of efficiency in terms of services provided per emissions would still represent a non zero set of emissions and therefore not achieve the commitme nt. Calculations that rely on relative levels of emissions can contextualize the respective planning of the institutions but are not themselves a measure of effectiveness in fulfilling the commitment. A moderately strong linear relationship was found be tween enrollment and baseline emissions in each stratum The greatest range is seen in the 4 Year Public Large strata. The relatively high amount of emissions per enrollment in the Private strata can be partially explained by a few outlying institutions wh ile most are in the same range as institutions with similar enrollments. (Figure 4 3 ) Normal distributions of the population in to tal baseline emissions (Figure 4 4 ) and in em issions per enrollment (Figure 4 5 ) are provided to demonstrate the distribution of emissions within institutions of the study. In each case the distributions skew right.

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79 Expected use of Carbon Offset Credits The analysis indicates that reliance on the use of PCOCs to reach the goal of eliminating carbon emissions from institutional op erations is not expected in the 4 Year Public Small strata. Factors affecting this could be ethical decision making of the institution representing the planners and administrators expectations of budgeting, technology, or behavioral factors. Expected grow th rate did not correlate to use of offsets. Use of PCOCs is seen as a separate part of the carbon emissions mitigation planning process rather than associated with rate of growth. The expectation of the institutions must be that as they grow, whether quic kly or slowly, they can effectively mitigate new emissions rather than rely on PCOCs to mitigate growth. The lack of correlation between growth rate and the use of PCOCs could be explained by several factors. The institutions could be expecting future grow th in the form of new construction and campus expansion will be more efficiently implemented than existing infrastructure. This is a reasonable expectation and one that is described in nearly all of the plans. A large portion of emissions comes from genera ted electricity, an emissions source dependent on local utilities and rarely directly controlled by the institutions. However, since institutions are large customers and consume a great deal of power, varying with factors of location and type of institutio n, they may exert influence over utility infrastructure alternatives in the future. Institutional expectation plays a role in reducing net emissions even as net consumption grows. The relationship between enrollment and rate of emissions offset of PCOCs in each stratum indicates the use of PCOCs is not infl uenced by size of institution. ( Tables 4 2 4 3, and 4 4 )

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80 Rate of growth and enrollment are only marginally related to expected use of PCOCs, the primary factor having a positive significant correlation o f emissions is expected BAU emission, which itself correlates to baseline emissions. These quantities of emissions represent an indicator of the expected use of PCOCs to fulfill the institutional commitment to eliminating emissions. The significance of th e correlations was tested using a two tailed t test. In each stratum there was a significant correlation between BAU emissions and baseline emissions. In the 4 Year Public Large and Private strata there was a significant correlation between BAU emissions a nd the expected use of offsets. The 4 Year Public Small strata showed no correlation between BAU emissions and expected use of offsets. There was no significance found in the other correlations. Expected rates of growth did not correlate to the expected us e of PCOCs. Content Analysis in Table 4 5 and 4 6 respectively. The analysis tables are given in Appendix L. l hypothesis and to demonstrate a dependent relationship between the variables The first of those is the test of dependence between the four strata and whether or not ethical language was present in the plan document. (Table L 1) The other forms of langua ge (hedging, imperative, and motivational) did not show any dependence individually, but the other test finding of dependence used the variable of the presence of any language and did find dependence. (Table L 8) The two dependent findings were then divide combining and comparing the strata with the same ethical language and presence of

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81 language variables to determine which factors were responsible for the finding of dependence. The findings are summarized in Table 4 6. I n the first set of findings, that of dependence in the presence of ethical language, the only factor of the strata that showed dependence in the finding was the size of the 4 year pu blic stratum. In the second set of findings, that of dependence in the pr esence of any of the tested language, none of the tested factors were found to be the source of the dependence. The null hypothesis of independence was found in all the remaining tests including when the use of language was normalized for the length of pl an (Table s L 11 and L 12), and when presence of language was distributed into categories as might be done in constructing a histogram distribution of the phrase counts (Tables L 9 and L 10 ) Total imperative and hedging phases per page are shown in Figure 4 6 and demonstrate the rate at which phrases were recorded when plan length is taken into account.

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82 Figure 4 1. Baseline and BAU Emissions. Figure 4 2. Correlation of Baseline and BAU Emissions with Correlation of Enrollment and Baseline Emissions.

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83 Table 4 1. Expected growth in enrollment and emissions for study population. Strata Mean Enrollment Emissions Per Student Expected Growth of Emissions Projected Mean Enrollment 2 Year Public 7,896 3.47 MTCO 2 e 34% 10,580 4 Year Public Small 10,898 5. 94 MTCO 2 e 77% 19,290 4 Year Public Large 31,143 8.16 MTCO 2 e 40% 43,600 All Private 4,733 8.49 MTCO 2 e 34% 6,340 Figure 4 3 Enrollment and baseline emissions scatter plot of all four strata.

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84 Figure 4 4. Baseline Emissions Distribution for Study Popu lation Figure 4 5. Emissions/Student Normal Distribution for Study Population.

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85 Table 4 2. Correlation analysis for 4 Year Public Small strata. 4 Year Public Small r df p Correlation of BAU Emissions Growth and Proportion of Offsets at End 0.03 33 0. 8642 Correlation of BAU Emissions and Quantity of Offsets at End 0.06 33 0.7321 Correlation of BAU Emissions and Baseline Emissions 0.68 33 0.001 Correlation of Enrollment and Percent of Emissions Mitigated by Offsets at End 0.09 33 0.9591 Table 4 3. Correlation analysis for 4 Year Public Large strata. 4 Year Public Large r df p Correlation of BAU Emissions Growth and Proportion of Offsets at End 0.15 19 0.5163 Correlation of BAU Emissions and Quantity of Offsets at End 0.58 19 0.0058 Correlation of BAU Emissions and Baseline Emissions 0.77 19 0.001 Correlation of Enrollment and Percent of Emissions Mitigated by Offsets at End 0.12 19 0.6044 Table 4 4. Correlation analysis for Private strata. Private r df p Correlation of BAU Emissions Growth and Proportion of Offsets at End 0.07 37 0.6720 Correlation of BAU Emissions and Quantity of Offsets at End 0.75 37 0.001 Correlation of BAU Emissions and Baseline Emissions 0.67 37 0.001 Correlation of Enrollment and Percent of Emissions Mitigated by Offsets at End 0.09 37 0.5858

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86 Table 4 squared test results summary table. Table 4 6

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87 Figure 4 6. Imperative and hedging phrases mean per page.

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88 CHAPTE R 5 DISCUSSION AND CONCL USION Discussion of The Population Analysis These plans suggest a variety of approaches toward carbon mitigation, but the most common path toward emissions elimination fall into three categories and representing the major sources of campus emissions: transportation, building operations, and growth. Carbon emissions from transportation include commuters, official travel, and intra campus travel. Campus plans suggest using traditional strategies, such as, encouraging car pooling, prov iding bicycle paths, and increasing mass transit availability. Official travel consists mostly of faculty and administration traveling for conferences, research, or business. The only suggested solution specifically aimed at mitigation of air travel was th e purchase of carbon offset credits. Increasing the availability of options for travel within campus includes alternative fuel buses, displacing commuter vehicles with bicycles, and increased efficiency of transportation. The common thread in each of these strategies to reduce emissions is that they don not eliminate emissions; they only increase the efficiencies of existing approaches Increases in efficiency alone cannot reach a point of zero emissions and physical and technical barriers exist that create diminishing returns in efficiency as technology improves. The mandate of the Climate Commitment essentially requires the elimination of or offset of the use the majority of energy derived from sources associated with carbon emissions. Emissions from tran sportation tend to account for a larger share of emissions from commuting in the 2 Year Public strata.

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89 The major source of emissions from campus operations is the built environment of the campus itself. Buildings are great metabolizers of resources, both the material resources that construct them and the energy and water that makes them environments for people and production. Services provided in buildings include heating and cooling, water supply, waste treatment, lighting, classroom technology, elevators security, communications, and maintenance all of which consume energy. Campus buildings consistently represent not only the largest portion of energy use and greenhouse gas emissions but also represent the best opportunities for reducing carbon emission s. Older buildings can be retrofitted to reduce energy use and emissions. Many of the oldest buildings, the most inefficient on campuses today, were at one time the most efficient and probably more efficient than even the newest and most advanced buildings constructed today. Buildings predating air conditioning, classroom technology and elaborate electrical systems would have utilized very little electricity in their original state while still providing the essential campus function as a place for instruct ion and many forms of research. Lighting was their main energy use and lighting is one area in which efficiency improvements have been dramatic in the transition from incandescent lighting to fluorescent and in the coming move toward potentially even more efficient LED lighting. While removing climate control systems such as mechanical cooling and heating may be a dramatic way to reach a state of zero emissions, a focus on the sources of emissions may spur the development of alternative strategies. A better question than 'how could we do as much as we do with less' would be 'how can we do as much as we need with what is available.' Its the question of efficiency versus effectiveness. Even as we manage to provide additional services with less energy, by

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90 incre asing efficiency, the quantity of services continues to increase. The Climate Commitment's goal of zero emissions cannot be achieved by increase efficiencies alone, it requires a focus on the source of emissions and their elimination, providing building an d campus services in an effective manner is a secondary concern rather than the primary focus. In other words, increasing efficiency is a proxy measurement for the actual goal of providing effective services with available resources based on the emissivity of those resources. The focus of planning efforts on increasing efficiency is not sufficient to fulfill the program commitments. The Climate Commitment provides many suggested paths and aspects of planning toward the zero emissions goal; one of these is to require all new building to meet the U.S. Green Building Council's Leadership in Energy and Environmental Design (LEED) Silver standard or equivalent. The LEED certification program can produce buildings providing the same services with lower energy use than a standard code compliant building and thus lower emissions from operations per some standard of use, generally carbon emissions per square foot of building or carbon emissions per student. The addition of newer and more efficient buildings certainly help lower normalized emissions somewhat but the end result is a building that is more efficient than buildings a few decades old but probably use s more energy per square foot. More important than the problem of efficiency is that unless some less effici ent buildings that utilized more energy per the same services provided are closed down, the net quantity of carbon emissions from building operations will increase. Increasing efficiency in this way, and measuring progress toward the net zero goal of emiss ions per area or per user, works against the emissions elimination goal of the program The dramatic rise of business as

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91 usual emissions reported in the plans demonstrates the trajectory of emissions without any intervention. Growth is a fundamental aspe ct and problem within these planning efforts. Worldwide, despite decades of increasing efficiencies and awareness of problems in energy and emissions, emissions have continued to rise (Boden & Marland, 2009.) Increasing efficiencies and efforts to reduce a nd clean up energy production and use has not reversed the trend of rising emissions per year. This problem is one of growth and expectations, while we may be getting more from less, there are also a lot more of us, and we all expect more from our building s, technologies, and lifestyles. Growing affluence and reluctance to change have exacerbated the problem. This culture of growth extends to colleges and universities. Trustees, alumni, students, prospective students, governance or ownership; all these stak e holders expect growth from their institutions. More students, bigger buildings, better technology, and more extensive operations are the norms in institutional planning (Schofer & Meyer, 2005.) How do these plans deal with growth when accounting for thei r carbon emissions over time? Those that do address growth make estimates, sometimes based on given assumptions, sometimes just extensions of current trends, and some conspicuously assume growth rates smaller than current ones (current growth occurring in a time of reduced economic activity no less) or smaller than other institutional planning documents expect. It is difficult to expect the goal of zero emissions to be achievable given current planning efforts focused on efficiency and growth. The expectati ons of nearly every participant in the program include either one or both of the following: the use of

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92 purchased carbon offset credits or a technologist assumption. Carbon offset credits are commodity priced credits expected to be available sometime in the future traded in a price adjusting market, similar to other commodities markets. There are currently carbon offset credits available from various sources, but most have weak systems of certification or verification. The current ad hoc market does not repr esent a substantial resource in the reduction of emissions (Lovell & Liverman, 2010). The use of purchased carbon offset credits is assumed in many of the plans as a way to eliminate whatever emissions are remaining at the end date in order to fulfill the promise of the Climate Commitment. Estimates of pricing and availability of those credits varies wildly. The forces of supply and demand along with regulation and the methods employed to create the credits could easily conspire to make substantial credit p urchases impractical. Nearly every plan includes a technologist view of carbon emissions reduction. That is to say, none of them describe a plan to eliminate emissions given current technology; they all assume some future undefined technology will become available to achieve the goals of the program. Taken to an extreme not reached in the plans, the technologist assumption reaches a point of infinite technology providing infinitely available services for infinitely small resource inputs. Embodied by the w ork of Ray Kurzweil on what he calls the 'technological singularity,' an event set to occur in 2045 at which point the intelligence of machines surpasses that of humanity leading to a crescendo of all consciousness becoming one with an intelligent universe (Kurzweil, 2005.) It is an intriguing coincidence the Kurzweil's prediction coincides with the Climate Commitment's promised neutrality date. While assuming some technological progress over the decades of plan implementation

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93 is appropriate, the degree to which reliance is placed on assumptions of technological adaptions and the trajectory of efficiency improvements is worrisome. Lost in much of these planning efforts was the sheer scope of the commitments the program requires. Carbon emissions and the ene rgy use they closely parallel are essential components of institutional operations at colleges and universities. Current carbon emissions control strategies focus on increased efficiency and new technologies to try and reduce emissions. Another way to thin k of the problem is to work backwards: begin with the premise that these institutions could achieve their goal by simply stopping the use of energy in any form, from purchased electricity, to campus commuting, landscaping equipment, waste treatment, fuels used for cooking, and emissions from research activities. A planning process that begins from the premise of zero energy use is a far cry from current practice in emissions mitigation From this theoretical baseline, the institution operating from zero emi ssions, planning could then work upward, determining how to run operations on the energy available from non greenhouse gas sources such as wind, solar, biomass, tidal, geothermal, or nuclear. Each institution would be plotting an individual course in exami ning available resources and what kinds of activities they could perform with those resources. Transportation of commuters to campus and faculty to conferences and field research would present a host of new challenges, again, each tailored to the instituti on. Imagining students bicycling in to campus is easy enough but professors may not be willing to sail to conferences over seas. The Climate Commitment is a terribly ambitious program. Achieving its goal implies a dramatic change in the way these intuition s organize, manage, and operate.

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94 The scope of the plans' implementation increases over the course of nearly half a century. It i s not uncommon for institutions to prepare growth and capital p lans that span similar periods. W hile many of these plans are sim ilar to previous planning this planning effort is fundamentally different. This planning extends to all areas of institution operations and culture. It will require a through rethinking of operations and possibly rebuilding in order to achieve the goal of the zero emissions state described earlier, but doing so in a way that continues to provide the level of services expected of a modern institution of higher learning. The data presented describe the current and expected future state of enrollment, emissio ns, and emissions growth if current practices continue. The methodology of the plans is to work backwards from that future scenario to eliminate emissions by increasing efficiencies, implementing expected technological changes, and other measures including purchasing carbon offset credits. As these plans are implemented and updated as living documents, generations of students will pass through the institution's gates, faculty will turn over, administrators will come and go, and cultural, environmental, and technological changes will dramatically reshape the world in which these institutions operate. Colleges and universities occupy a unique place in society and are well suited to be the first institutions to undertake of carbon neutrality. They have large pr ogressive populations, extensive human resources, and the control over infrastructure required to implement this type of planning. Being on the forefront of massive public and private efforts to mitigate emissions is a natural fit and will serve to provide the vocabulary and methodologies used in similar efforts elsewhere. The scale of institutions participating in this program range from a n enrollment of few hundred to about 65,000 students This

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95 range mimics other human institutions such as businesses, co mmunities, municipalities, governments, civic associations, and religious groups. By conducting carbon emissions mitigation planning, initiating the carbon emissions reduction process, and making regular reports on progress, this program is providing a roa d map for others to follow in developing and implementing their own plans for mitigation. A combination of a variety of approaches, understandings, and methodologies sure to be implemented; with a consistent reporting system and clear and stringent program goals make the Climate Commitment a preeminent emissions reduction program and assuredly a baseline program to compare future coordinated emissions reduction efforts. Discussion of Offset Purchase Analysis This research is important because it demonstrat es the relationship between type of institution, their emissions, and their rates of growth and use of carbon offset credits in the process of a multi generational program of institutional change. These relationships will, examined at the beginning of the implementation of the Climate Commitment program planning, become important factors in the ultimate success or failure of participating institutions ability to meet their commitments. This emissions mitigation effort is the most dramatic and well documente d effort to date. Its results will create models for the type of institutions participating in this and similar programs. It is also hoped that critical analysis and comparisons of these strata both here and in other research will create needed feedback fo r ongoing institutional carbon mitigation planning efforts. Ultimately, this study will combine with longitudinal efforts to evaluate and compare results of efforts; will result in a road map to successful carbon mitigation planning.

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96 An analysis of econom ic expectations in PCOCs will help reveal whether budgeting plays a role in the use of credits. The use of close reading and critical analysis has revealed a wide range of expectations of the cost of PCOCs. A future study will examine how the cost of credi ts and cost of other mitigation efforts affects the implementation of those strategies. Initial analysis indicates a wide range of expectations and expected roles for carbon offset credits, purchased and generated by campus programs either for institution use in offsetting other sources of emissions or to be sold. An analysis of the expected cost of PCOCs versus of the sale of PCOCs to fund other mitigation strategies represents a central question of the use of these offsets, whether colleges and universiti es will be net consumers of such credits or net producers. It is possible that a divide exists between institutions with large land holdings and rural locations, and urban and commuter campuses. Campus setting will be an important factor in future studies. The use of PCOCs is expected to play a role in reaching the goal of elimination of carbon emissions from operations at American colleges and universities participating in the Climate Commitment. The degree of those expectations varies between factors of ownership and enrollment levels with private ownership and large enrollments in public institutions being i ndicative of the use of PCOCs. The ultimate effectiveness of the use of PCOCs from mitigation and cost effectiveness perspectives will depend on a n umber of factors that will develop in the coming decades. The expectations examined in this research will play a role in how those markets develop and are utilized by these and other institutions.

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97 A market trading in carbon emissions will almost certainl y play a key factor in the process of controlling carbon emissions. Colleges and universities, being at the fore of carbon emissions mitigation efforts, will be central to the development and legitimization of these markets by their planned use and ultimat e participation as the markets develop. Leading the way forward for other groups such as businesses or municipalities confers a responsibility upon these institutions of higher education to make informed and consistent choices in their use of carbon credit s. Discussion of the Content Analysis The content analysis section of the research utilize d the rich data source of the Climate Commitment plans in ways that went beyond the standard reported data. The plans were required to provide not just data but also the description and narrative of the institution setting out on a half cent ury duration project. The hypothesis of this research that over the course of that long period as technologies and individuals change the narrative of the institution will take on a greater importance. The main findings of the content analysis is that while some type of descriptive or evocative narrative is almost used, the only type of language that is dependent on the divisions between the strata (ownership, majority of degrees a warded, and enrollment) is the presence of ethical language. More generally, the presence of any language is dependent on the type of institution but not on a single descriptive factor. The content analysis method was limited in the categories and quantit y of phraseology that could be examined. With greater resources a more robust and repeatable methodology for examining the plans could be developed. A limitation of the close reading methodology utilized in the content analysis is that it depended upon a s ingle reader and evaluator using individual judgment to identify types of phrases. This

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98 severely limits the scope of this type of study to the quantity of material a single individual can review since adding additional reviewers would introduce inconsisten cies in judgment. A sufficiently large sample size was possible in this study so that specific limitation was not a factor but would be for larger projects. Repeatability can be difficult as well when individual judgment is a major factor. The review sheet for each plan included detailed quotes and locations for each of the identified phrases and could be used in any attempt to replicate the research. (Appendices G, H, I, and J) Examination of larger scale data could be accomplished with a group of evaluato rs trained in producing consistent results, by using statistical methods to cross check different examiners by using samples reviewed by each, or by utilizing data mining techniques to allow for computer analysis of narrative content. Developing an explici t ethical position for an institution and expressing that in the process of explaining sustainability initiatives can have an impact on how planning takes place. The presence of language of any kind as dependent factor is reflected in the normative number of recorded phrases per page recorded for each stratum. (Figure 4 6) The 2 year public strata having the least amount, followed by the 4 year public small, and 4 year public large all demonstrate that as size and type of degree awarded increases the instit utions tended to use more descriptive language in their planning. This finding is reflective of the general quality of the plans and the sophistication of the planning employed in each of the stratum. The private strata continued the tr end of more hedging language tha n the 4 year public large strata but saw a decrease in the amount of imperative language. This cautionary approach may be the result of a private institutions both having less intrinsic motivation in sustainability matters owning to not

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99 being p ublic entities and in having a reticence to make speculative planning commitments. The results of the content analysis confirm the hypothesis that the presence of certain types of language has a demonstrable relationship to the type of institution doing th e planning and that the factors dividing the strata were meaningful distinctions between institutions. Research Questions The impact of structural factors is demonstrated in the results of the numerical and content analysis sections. Private institutions tend to hedge their planning to a greater degree than others. Offsets are relied upon at a greater rate as enrollment increases. 2 year institutions tended to have the least amount of narrative detail in their plans and the larger enrollment in 4 year pub lic institutions tended to correlate with increased details and fuller data provided in the plans. The use of carbon offsets represented several different strategies in the plans. In some cases they were used to offset only specific types of emissions sou rces, conclusion of the program duration to mitigate any remaining emissions after all other efforts were implemented. Some cases utilized them as part of a mix of mitig ation programs throughout the Climate Commitment duration implementing as soon as immediately. In a few cases the institutions planed to go beyond carbon neutrality and implement institutional resources in the generation, either for sale or for offset of o ther sources, their own carbon credits. There were no clear trends in the use of specific types of motivational or ethical language, just that its presence was dependent on the structural factors of the strata.

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100 Both hedging and imperative language occurre d at varying rates that showed no dependence on structural factors, but when all the recorded types of language were included there was a strong dependence in the presence of it and the structural factors that characterized the strata. While there was expl icit motivational and ethical language used at a low rate amongst the plans, there was no consistent or particularly strong approach to the types of understanding expressed by the language. Some institutions were motivated by some things, others by others ranging from legislative initiative, grass roots efforts of students, a research initiative by faculty, or institutional leadership wishing to participate in the program. Intrinsic motivation or a geocentric worldview were not noted, the ethical motivation was nearly always an anthropocentric one based on the intergenerational justice mantra of sustainability. Future Research The content analysis findings may prove to be the most interesting of the findings as the longitudinal research covering the implem entation of the plans occurs. The current findings, relating the types of language used to the type of institution, will be relatable to the success or failure of the implementation of the plans over time. Future research will be able to determine factors of institutions that were positively associated with successful results and then see how the use of narrative language relates to those factors. There may be a dependent relationship between those institutions that express ethical and motivational language now and their success in their mitigation efforts over the duration of the program. The content analysis and narrative examination performed in this research will lay the groundwork for these future studies and perhaps broader research into the institutio nal narrative of sustainability and climate change. In the same way individuals see themselves as playing a role and having an impact on a host of

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101 sustainability issues, institutions do as well. It is beyond the scope of this research to speculate on the o rigin of that motivation and the nature of the relationship between institution, expressed in plans, documents, and other expressions of the institution do exp ress a particular viewpoint, even when authorship is either unknown, diverse, or is attributed to a range of individuals. An institutional culture, defined by examination of narrative documents, and expressed in the success or failure of institutional plan ning efforts will be a pivotal factor in whether these dramatic and difficult commitments are kept. Future studies could adopt similar methodologies but examine different strata divisions, such as enrollment, geographic location, endowment, political iden tification, majority of majors, or other factors. The findings that the chosen factors (ownership, enrollment, majority types of degrees awarded) were meaningful could be combined with a more extensive study including many more factors and develop a model of institutional identification that could express the ethical or other motivational factors expressed by differing types of institutions. The major source of emissions was consistently purchased electricity, thus the local generation sources were the larg est determinate in intensity of emissions per unit of energy used. In some cases a college or university represents a large enough customer or is politically influential enough to alter the source of municipal power generation. Exerting pressure in that wa y would be an effective way to mitigate emissions and is a strategy employed by several of the participants. Transitioning to on site generation in the form of renewable energy sources is a consistent and effective strategy employed by many of the mid size d institutions but

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102 is sometimes described by the largest as impractical at their scale of operation. A focused study of the power generation sources utilized by colleges and universities would provide a greater insight into this central source of emissions a nd would provide strong framework for examining power generation sources as large parts of the emissions from operations model in studying other institutions. A study of that sort would require new methods but would be straight forward in its execution a nd r equire a great deal of original data collection and management. An immediate problem with that study and all studies looking at carbon emissions is the reliability of the methodology of determining those emissions. This study concedes that while some i naccuracy probably exists in the reported emissions, the emissions reported are likely precise providing a strong basis of direct comparison. Examining emissions measurement and reporting accuracy and reliability is itself a rich field of research and is n ot the focus of this project or other future research programs that are more interested in what is done in comparative analysis with that admittedly often unreliable data. The combination of numerical and categorical data and the use of content analysis i n this study has been a new approach that can now be utilized in examining other institutions. A project to examine and compare carbon mitigation planning at the Russell Group u niversities (top 20 research institutions of the United Kingdom) and comparable US institutions is being planned and the potential to include Canadian and Australian institutions as well as they are all embarking on similar carbon mitigation programs with different goals and baselines. Normalizing those baseline emissions, the measur ement methodologies used, and the goals of their programs is the challenge but the basic methodological framework used in this study is adaptable to all those factors.

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103 The ultimate goal is a longitudinal program of study of the implementation of the Clim ate Commitment program over its duration with a final product including a narrative of the process of planning and implementing this dramatic and transformative program, and a complete view of the planning process as it applied to sustainability, carbon em issions, and colleges and universities. Studies will be required to track emissions reporting and integrate the analysis of that data into this study. Each cycle of reporting and analysis will result in model institutions featuring factors of ownership, e nrollment, efforts undertaken, and use of PCOCs. This study will be capable of informing planning efforts as well as providing the basis to examine why certain factors lead to success and others have lesser effects. Factors to be included range from ethica l and social factors of the planners or institutions, to budgeting and utilized mitigation efforts such as increased use of building technology or differe nt types of carbon credit use. This research has helped lay the ground work for additional studies ex amining these factors from economic, social, and other perspectives as part of these planning efforts. In addition, this research is essential and provides a basis for longitudinal studies as the described planning efforts are impleme nted and the results r eported. The most significant limitation of the content analysis portion of the study was the small amount of available data. The labor intensive process of reviewing the plans in the depth required finding the individual phrases and the sparseness of the language squared method was successful in identifying ethical language and all language as the two dependent relationships in the tests. This indicates future research should focus on the

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104 presence of ethical language as a variable when evaluating carbon emissions mitigation results and could be put further as a recommendation to those working on sustainability planning. Conclusion This research has examined the planning efforts made as part of the American Commitment program has initiated efforts at signatory institutions to eliminate carbon emissions from operations by a set future date. The data for th is research has consisted of the numerical reported emissions, mitigation methods, and structural data of each institution; and a sample of plans examined for certain narrative content. The methods employed sought to define and differentiate the participat ing institutions based on certain structural factors, to examine closely a particular mitigation method employed, and to create means to compare the strata using their narrative content. The numerical examination of the data was aided by the manageable pop ulation size of just a few hundred participating institutions with even fewer providing the minimum data required by this study. Having the entire population to examine and describe helps to mitigate the fog of statistics that can cloud or complicate analy sis. The findings that the use of PCOCs is expected in such a range of institutions and is relied upon to such a varying degree demonstrate the importance carbon markets will play in any sort of carbon emissions mitigation program. How those markets develo p, the pricing of credits, and the ability of institutions to generate their own credits, discounting a major disruptive technology, are the least known factor in the planning taking place. Part of what made this research possible, and will be a major fact or in comparative studies of other institutions, was the consistency of the available data both in its

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105 formatting, use of units, and its collection methodology There is every reason to believe there is a high level of precision and comparability in the re ported emissions data, if not in the estimates for mitigation provided. Content analysis as method of planning evaluation has demonstrated itself to be useful in producing categorical data but the problems of analysis of categorical and numerical data hav e limited the applicability of the statistical sample of the strata available for content analysis versus the entire population for which accurate information is available for numerical analysis. A more robust content analysis research program could addres s the problems associated with the methods described above and produce a broadly applicable and scalable research methodology that could provide substantial insights into sustainability planning and the thinking of institutions. There remains a great deal of work to be done in integrating content analysis and other categorical methods with the numerical and structural aspects of institutions (both the ones utilized in this research and the other possibilities listed above) with the end goal of developing a complete and function model of the participating institutions, with reporting data on the success or failure of different implemented mitigation efforts, the model could be used to predict the long term success or failure of institutions based on their st ructural factors and their planned efforts. Those projections could help steer the efforts of institutions seeking to mitigate their emissions and ultimately increase the likelihood of success in the important endeavor of emissions mitigation. Sustainabil ity is still a new thing and coalescing field of study and a burgeoning professional practice. The ambitious planning that is taking place in the Climate Commitment and programs like it is essential to nothing less than the long term

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106 continuance of life an d human society on Earth. For these and other reasons the plans that make up this study and the thinking of the participating institutions is still broad, wide, and deep in its considerations and products. Some of the plans are credible, focused, and reaso nable documents providing guidance, evaluation, and process for achieving difficult ends; others less so. The bes t that can be said about the planning taking place is that with few exceptions it has clearly been done with a good intention and an intrinsic motive. The implications and impacts of the implementation of the plans over the next half century will provide a ripe region of study for those looking at measurement, planning, implementation, motivations, success, and failures, and ultimately as verdant ground for the futur e historians of sustainability.

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107 APPENDIX A SAMPLE INSTITUTIONAL DATA S ET INSTRUMENT

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108 APPENDIX B CONTENT ANALYSIS DAT A INSTRUMENT Table B 1. Data Instrument form used to record content analysis.

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109 APPENDIX C 2 YEAR STRATUM NUMERI CAL DATA Table C 1. 2 year stratum population numerical data.

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110 APPENDIX D 4 YEAR PUBLIC SMALL ST RATUM NUMERICAL DATA T able D 1. 4 year public small stratum population numerical data.

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111 APPENDIX E 4 YEAR PUBLIC LARGE ST RATUM NUMERICAL DATA T able E 1. 4 year public large stratum population numerical data.

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112 APPENDIX F 4 YEAR PRIVATE STRATUM NUMERICAL DATA T able F 1. 4 year private stratum population numerical data.

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113 APPENDIX G 2 YEAR CONTENT ANALYSI S STRATUM DATA Table G 1 Delta College content data.

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114 Table G 2 Northern Essex Community College content data.

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1 15 Table G 3. Chabot College content data.

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116 Table G 4. Onondaga Community College content data.

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117 Table G 5. Madison Area Technical College content data.

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118 Table G 6. Cabrillo Coll ege content data.

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119 Table G 7. University of South Carolina Sumter content data.

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120 APPENDIX H 4 YEAR PUBLIC SMALL CO NTENT ANALYSIS STRAT UM DATA Table H 1. University of Idaho content data.

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121 Table H 2. Eastern Washington University content data.

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122 T able H 3. University of Colorado at Colorado Springs content data.

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123 Table H 4. William Paterson University of New Jersey content data.

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124 Table H 5. New College of Florida content data.

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125 Table H 6. James Madison University content data.

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126 Table H 7. University of Minnesota Morris content data.

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127 Table H 8. Northern Arizona University content data.

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128 Table H 9. Oregon State University content data.

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129 APPENDIX I 4 YEAR PUBLIC LARGE CO NTENT ANALYSIS STRAT UM DATA Table I 1. University of Oklahoma Norman content data.

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130 Table I 2. University of Utah content data.

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131 Table I 3. George Mason University content data.

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132 Table I 4. University of California, Berkeley content data.

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133 Table I 5. Grand Valley State University content data.

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134 Table I

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135 Table I 7. University of California, Santa Barbara content data.

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136 APPENDIX J 4 YEAR PRIVATE CONTENT ANALYSIS STRATUM DAT A Table J 1. Union College content data.

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137 Table J 2. Kalamazoo College content da ta.

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138 Table J 3. Wesleyan College content data.

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139 Table J 4. Rhodes College content data.

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140 Table J 5. Gettysburg College content data.

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141 Table J 6. Franklin College of Indiana content data.

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142 Table J 7. Keystone College content data.

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143 Table J 8. University of Miami content data.

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144 Table J 9. Dickinson College content data.

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145 Table J 10. University of Puget Sound content data.

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146 Table J 11. LaGrange College content data.

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147 Table J 12. Lewis & Clark College content data.

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148 APPENDIX K CONTENT ANALYSIS CONSOLIDATED DATA TABLES Table K 1. 2 year public stratum content analysis summary table.

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149 Table K 2. 4 year public small stratum content analysis summary table.

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150 Table K 3. 4 year public large stratum content analysis summary table.

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151 Table K 4. 4 year private stratum content analysis summary table.

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152 APPENDIX L TEST TABLES Table L sq uared test for strata and presence of ethical language. Strata Yes No Total 2 Ye ar Public 1 6 7 4 Year Public Small 7 2 9 4 Year Public Large 2 5 7 Private 7 5 12 Total 17 18 35 DF=3 P Value=0.047 Table L squared test for strata and presence of motivational language. Strata Yes No Total 2 Year Public 1 6 7 4 Year Public Small 3 6 9 4 Year Public Large 0 7 7 Private 0 12 12 Total 4 31 35 DF=3 P Value=0.079 Table L squared test for strata and ethical language expected distribution Strata Yes No Total 2 Year Public 3.4 3.6 7 4 Year Publ ic Small 4.37 4.63 9 4 Year Public Large 3.4 3.6 7 Private 5.83 6.17 12 Total 17 18 35 DF=3 P Value=1 Table L squared test for strata and motivational language expected distribution. Strata Yes No Total 2 Year Public 3.4 3.6 7 4 Ye ar Public Small 4.37 4.63 9 4 Year Public Large 3.4 3.6 7 Private 5.83 6.17 12 Total 17 18 35 DF=3 P Value=0.8

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153 Table L squared test for strata and hedging or imperative language present. Strata Yes No Total 2 Year Public 2 5 7 4 Y ear Public Small 7 2 9 4 Year Public Large 5 2 7 Private 9 3 12 Total 23 12 35 DF=3 P Value=0.143 Table L squared test for strata and imperative language present. Strata Yes No Total 2 Year Public 2 5 7 4 Year Public Small 5 4 9 4 Year Public Large 5 2 7 Private 5 7 12 Total 17 18 35 DF=3 P Value=0.393 Table L squared test for strata and hedging language present. Strata Yes No Total 2 Year Public 2 5 7 4 Year Public Small 7 2 9 4 Year Public Large 4 3 7 Pri vate 9 3 12 Total 22 13 35 DF=3 P Value=0.155 Table L squared test for any language present. Strata Yes No Total 2 Year Public 3 4 7 4 Year Public Small 8 1 9 4 Year Public Large 5 2 7 Private 12 0 12 Total 28 7 35 DF=3 P Value=0. 02

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154 Table L squared test for strata and histogram distribution of imperative language present. Strata None 1 or 2 3 or 4 5 or more Total 2 Year Public 5 2 0 0 7 4 Year Public Small 4 3 1 1 9 4 Year Public Large 2 2 1 2 7 Private 7 2 3 0 12 Total 18 9 27 3 35 DF=3 P Value=0.02 Table L 10 squared test for strata and histogram distribution of hedging language present. Strata None 1 or 2 3 or 4 5 or more Total 2 Year Public 5 2 0 0 7 4 Year Public Small 2 3 2 2 9 4 Yea r Public Large 3 2 1 1 7 Private 3 3 4 2 12 Total 13 10 7 5 35 DF=3 P Value=0.02 Table L 11 squared test for strata and histogram distribution of normative imperative language present. Strata None 0.01 to 0.20 0.21 to 0.40 0.41 to up Tot al 2 Year Public 5 2 0 0 7 4 Year Public Small 2 3 2 2 9 4 Year Public Large 3 2 1 1 7 Private 3 3 4 2 12 Total 13 10 7 5 35 DF=3 P Value=0.02 Note: Normalized data is for phrases per page of plan. Table L 12 squared test for strata a nd histogram distribution of normative hedging language present. Strata None 0.01 to 0.20 0.21 to 0.40 0.41 to up Total 2 Year Public 5 2 0 0 7 4 Year Public Small 2 7 0 0 9 4 Year Public Large 3 3 1 0 7 Private 3 6 1 2 12 Total 13 18 31 2 35 DF=3 P Value=0.02 Note: Normalized data is for phrases per page of plan.

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155 Table L 13 squared test for strata and presence of stated neutrality date. Strata Yes No Total 2 Year Public 2 5 7 4 Year Public Small 4 5 9 4 Year Public Large 3 4 7 P rivate 7 5 12 Total 4 31 35 DF=3 P Value=0.635 Table L 14 squared test for strata and presence of ethical or motivational language. Strata Yes No Total 2 Year Public 2 5 7 4 Year Public Small 7 2 9 4 Year Public Large 2 5 7 Private 7 5 12 Total 18 17 35 DF=3 P Value=0.129 Table L 15 year public large and small strata, and ethical language. Strata Yes No Total 4 Year Public Small 7 2 9 4 Year Public Large 2 5 7 Total 9 7 16 DF=1 P Value=0.049 Table L 1 6 year public combined and 2 year strata, and ethical language. Strata Yes No Total 4 Year Public combined 9 7 16 2 Year Public 1 6 7 Total 10 13 23 DF=1 P Value=0.089 Table L 17 and private strata, and ethical language. Strata Yes No Total Public combined 10 13 23 Private 7 5 12 Total 17 18 35 DF=1 P Value=1

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156 Table L 4 year public combined and private strata, and ethical language Strata Yes No Tota l 4 Year Public combined 10 13 23 Private 7 5 12 Total 17 18 35 DF=1 P Value=1 Table L 19 year public large and small strata, and presence of any language. Strata Yes No Total 4 Year Public Small 8 1 9 4 Year Public Large 5 2 7 Total 13 3 16 DF=1 P Value=0.55 Table L 20 year public combined and 2 year strata, and presence of any language. Strata Yes No Total 4 Year Public combined 13 3 16 2 Year Public 8 1 9 Total 21 4 25 DF=1 P Value=0.106 Table L 21 of any language. Strata Yes No Total Public combined 21 4 25 Private 12 0 12 Total 33 4 37 DF=1 P Value=0.368 Table L 22 4 year public com bined and private strata, and presence of any language. Strata Yes No Total 4 Year Public combined 1 3 3 16 Private 12 0 12 Total 25 3 28 DF=1 P Value=1

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157 LIST OF REFERENCES Aggarwal, R., & Dow, S. (2011). Corporate governance and business strategies for climate change and environmental mitigation. The European Journal of Finance, forthcoming Agresti, A. (1996). An Introduction to Categorical Data Analysis. New York: Wiley Interscience Publications. Berke, P. R., & Conroy, M. M. (2000). Are we planning f or sustainable development? An evaluation of thirty comprehensive plans. Journal of the American Planning Association, 66 (1), 21 33. Berlinger, A. (2006). Campus sustainability audit research in Atlantic Canada: pioneering the campus sustainability framew ork. International Journal of Sustainability in Higher Education, 7 (4), 437 455. Busch, C., De Maret, P., Flynn, T., Kellum, R., Le, S., Meyers, B., et al. (2005). Content Analysis Retrieved from Writing@CSU: http://writing.colostate.edu/guides/research/content/index.cfm Button, C. (2009). Towards carbon neutrality and environmental sustainability at CCSU. International Journal of Sustainability in Higher Education, 10 (3), 279 286. Carnegie Foundation. (n.d.). Carnegie Foundation for the Advancement of Teaching Retrieved from http://www.carnegiefoundation.org/ Carroll, A., & Shabana, K. (2010). The business case for corporate social responsibility: a review of concepts, research, and practice. International Journal of Management Reviews, 12 (1), 85 105. Chang, A. B. (2004). The Development of Stanford University's Guidelines for Sustainable Buildings: A student's perspective. I n P. F. Bartlett, & C. W. Geoffrey, Sustainability on Campus: Stories and Strategies for Change (pp. 177 193). Cambridge, MA: MIT Press. Cole, L. (2003). Assessing sustainability on Canadian university campuses: development of a campus sustainability asses sment framework. Environment and Management Victoria: Royal Roads University. Conrad, R., & Hodgson, W. (2011). Duke Carbon Offsets Initiative: Forestry Carbon Financial Risk Analysis. Duke University Nicholas School of the Environment and Earth Science s, Durham. Cranston, G., & Hammond, G. (2010). Egalite, fraternite, sustainabilite; evaluating the significance of regional affluence and population growth on carbon emissions. International Journal of Global Warming, 2 (3), 189 210.

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158 Dhanda, K., & Hartman, L. (2011). The Ethics of Carbon Neutrality: A Critical Examination of Voluntary Carbon Offset Providers. Journal of Business Ethics, 100 (1), 119 149. Downing, E., Fulton, E., & Strauss, J. (2011). Duke Forest Carbon. Duke University, Nicholas School of t he Environment and Earth Sciences, Durham. DuBose, J. (2000). Sustainability and Performance at Interface, Inc. Interfaces, 30 (3), 190 201. Fetcher, N. (2010). Research and Solutions: Effects of Climate and Institution Size on Greenhouse Gas Emissions fro m Colleges and Universities in the United States. Sustainability: The Journal of Record, 2 (6), 362 367. Fonseca, A., Macdonald, A., Dandy, E., & Valenti, P. (2011). The state of sustainability reporting at Canadian universities. International Journal of S ustainability in Higher Education, 12 (1), 22 40. Freedman, M., & Jaggi, B. (2009). Global warming and corporate disclosures: A comparative analysis of companies from the European Union, Japan and Canada. Advances in Environmental Accounting & Management, 4 129 160. Goklany, I. (2009). Have increases in population, affluence, and technology worsened human and environmental well being? The Electronic Journal of Sustainable Development, 1 (3), 15 40. Goodhart, C. (1975). Monetary Relationships: A view from T hreadneedle Street. Papers in Monetary Economics Greenfield, J., Leslie, N., & Stimmel, J. (2010). Carbon Offsets: An Important Component of the Effort to Become Carbon Neutral. Colgate University Hamilton, K., Sjardin, M., Marcello, T., & Xu, G. (2008 ). Forging a frontier: state of the voluntary carbon markets 2008. New York and Washington D.C.: New Carbon Finance and The Ecosystem Marketplace. Hendry, J., & Vesilind, P. (2010). Ethical motivations for green business and engineering. Clean Technologies and Environmental Policy, 7 (4), 252 258. Herremans, I., & Allwright, D. (2000). Environmental management systems at North American Universities: what drives good performance? International Journal of Sustainability in Higher Education, 1 (2), 168 181. Hibbert, L. (2009). Eco vision or greenwash? Professional Engineering, 22 (8), 18 19. Hrasky, S. (2011). Carbon footprints and legitimation strategies: symbolism or action? Accounting, Auditing & Accountability Journal, 25 (1), 174 198.

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159 Irandoust, S. (2009 ). Sustainable Development in the context of climate change: a new approach for institutions of higher learning. Sustainability Science, 4 (2), 135 137. Klver, H. (2009). Measuring Interest Group Influence Using Quantitative Text Analysis. European Union Poltics, 10 (4), 535 549. Klein Banai, C., & Theis, T. (2011). Quantitative analysis of factors affecting greenhouse gas emissions at institutions of higher education. Journal of Cleaner Production, In Press Kumar, R. (2005). Research Methodology. London: SAGE Publications Ltd. Kurucz, E., Colbert, B., & Wheeler, D. (2008). The business case for corporate social responsibility. In A. Crane, A. McWilliams, D. Matten, J. Moon, & D. Siegel, The Oxford Handbook of Corporate Social Responsibility (pp. 88 112). Oxford: Oxford University Press. Lehmann, S. (2012). Low to no carbon city: Lessons from western urban projects for the rapid transformation of Shanghai. Habitat International, In Press Lovell, H., Bulkeley, H., & Liverman, D. (2009). Carbon offsetting: s ustaining consumption? Environment and Planning A, 41 2357 2379. McCauley, A., Robertson, J., Krueger, R., & Gurkin, C. (2009). Knowing where they sit: a survey to guide the development of a climate change community engagement campaign on a university cam pus International Journal of Sustainability Communication, 4 125 141. M'Gonigle, M., & Starke, J. (2006). Planet U. Gabriola Island, BC, Canada: New Soceity Publishers. National Wildlife Federation. (2010, 10 26). Campus Solutions Retrieved 10 26, 2010 from National Wildlife Federation: http://www.nwf.org/Global Warming/Campus Solutions.aspx Orr, D. (2004). Can Educational Insitutions Learn: The creation of the Adam Joseph Lewis Ce nter at Oberlin College. In P. F. Bartlett, & G. W. Chase, Sustainability on Campus: Stories and Strategies for Change (pp. 159 175). Cambridge, MA: MIT Press. Prendeville, S., O'Connor, F., & Palmer, L. (2011). Barriers and benefits to ecodesign: A case s tudy of tool use in an SME. 2011 IEEE International Symposium on Sustainable Systems and Technology (pp. 1 6). Cardiff: Ecodesign Center. Ramaswami, A., Main, D., Bernard, M., Chavezl, A., Davis, A., Thomas, G., et al. (2011). Planning for low carbon commu nities in US cities: a particpatory process model between academic institutions, local government, and communities in Colorado. Carbon Management, 2 (4), 397 411.

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160 Rappaport, A., & Hammond, S. (2007). Degrees That Matter. Cambridge, MA: MIT Press. Raunch, J ., & Newman, J. (2009). Institutionalizing a greenhouse gas emission reduction target at Yale. International Journal of Sustainability in Higher Education, 10 (4), 390 400. Reinhardt, F., & Stavins, R. (2010). Corporate social responsibility, business stra tegy, and the environment. The Oxford Review of Economic Policy, 26 (2), 164 181. Ryu, S. (2010). Guidelines to Make Victoria University School of Architecture and Design Carbon Neutral Through Minimising its Reliance on Carbon Offsets. Victoria University School of Architecture and Design. Victoria: Victoria University School of Architecture and Design. Scofield, J. (2009). Do LEED certified buildings save energy? Not really.... Energy and Buildings, 41 (12), 1386 1390. Seyfang, G. (2009). Community action for sustainable housing: Building a low carbon future. Energy Policy, 38 (12), 7624 7633. Seyfang, G. (2006). Ecological citizenship and sustainable consumption: Examing local organic food networks. Journal of Rural Studies, 22 (4), 383 395. Shriberg, M. (2002). Institutional assessment tools for sustainability in higher education: strengths, weaknesses, and implications for practice and theory. International Journal of Sustainability in Higher Education, 3 (3), 254 270. Smythe, K. (2010). Air Travel and C limate Change: Should Faculty and Students Be Grounded? Sustainability: The Journal of Record, 3 (5), 257 258. Talen, E. (1996). Do plans get implemented? A review of evaluation in planning. Journal of Planning Literature, 10 (3), 248 59. Thurston, M., & Eckelman, M. (2011). Assessing greenhouse gas emissions from university purchases. International Journal of Sustainability in Higher Education, 12 (3), 225 235. Wangerman, E., Kaufmann, M., & Tang, C. W. (2011). Duke Carbon Offsets Initiative: Organic Was te Diversion Options & Waste to Energy Opportunities. Duke University, Nicholas School of the Environment and Earth Sciences, Durham. Weber, R. P. (1990). Basic Content Analysis. Newbury Park, Ca: SAGE Publications. White, A., Jonas, A., & Gibbs, D. (2010) From sustainable development to carbon control: eco state restructuring and the politics of urban and regional development. Transactions of the Institue of British Geographers, 35 (1), 76 93.

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162 BIOGRAPHICAL SKETCH David Goldsmith is a Ph.D. candidate in the Colleg e of Design, Construction, and Planning. His graduate research has focused on the theoretical aspects of sustainability in the built environment. This focus has developed into a research program interested in carbon mitigation planning at the institutional level. His research seeks to develop a model of institutional decision making that can be applied widely and refined through longitudinal studies into a robust and adaptable method for description and the tools of policy makers and academics working on the problems of sustainability.