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A life cycle assessment of the environmental impacts of small to medium sports events Dolf, Mathew (Matt) 2017

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   A LIFE CYCLE ASSESSMENT OF THE ENVIRONMENTAL IMPACTS OF SMALL TO MEDIUM SPORTS EVENTS   by  Mathew (Matt) Dolf  B.A., The University of Victoria, 2001 M.A.S., Ecole polytechnique fédérale de Lausanne, 2006    A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  Doctor of Philosophy   in   THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES  (Kinesiology)    THE UNIVERSITY OF BRITISH COLUMBIA  (Vancouver)    December 2017  © Mathew (Matt) Dolf, 2017 ii Abstract  In the face of climate change and environmental concerns, sport event organizers have incorporated measures to improve environmental sustainability into their event planning. In 1994, the International Olympic Committee (IOC) added the environment as the third pillar of the Olympic Movement, alongside sport and culture, to signal its importance. However, event organizers don’t have a clear picture of the impacts of their events and are only beginning to use quantitative data as part of their planning process. The scientific literature and the event industry have recognized the need for theoretical and methodological work to better assess and understand the pattern of environmental impacts of events. The need is greatest for small to medium sized events.  The goal of this research was to analyze the explanatory power and use-value of Life Cycle Assessment (LCA) to examine the environmental impacts and inform planning of small to medium events. Two case studies were conducted: the UBC Athletics & Recreation varsity 2011–2012 athletic season (UBC Athletics) held at the University of British Columbia over a one-year period, and the Special Olympics Canada 2014 Summer Games (SOC 2014) held over five days in Vancouver, British Columbia. LCA methodology was used to quantify and compare the environmental impacts in key organizational areas.  The findings show that LCA has the potential to identify environmental impacts within small to medium sport events. They also show that impacts related to venues dominated across all environmental impact categories for UBC Athletics due to energy consumption and iii construction materials. Travel was the dominant contributor for SOC 2014 and was a major contributor for UBC Athletics – largely due to people travelling from out of town. The activities related to accommodation, materials, waste, communication and food were significantly smaller contributors to the overall environmental footprint. Sport organizers would benefit from applying LCA as a quantitative tool to rigorously identify areas of significant impact and target planning efforts accordingly, particularly for long distance travel and activities with significant energy use. Finally, I conclude that organizers need to be more aspirational in how they design events and leverage societal change to become environmentally sustainable. iv Lay Summary  Environmental concerns, and climate change in particular, are pressing issues for humanity. We currently have a poor understanding of the environmental impacts of sport events and how a clearer picture might catalyze change towards environmental sustainability. This dissertation measures the environmental impacts of two case studies: the UBC Athletics & Recreation varsity 2011–2012 athletic season, and the Special Olympics Canada 2014 Summer Games. I reviewed and applied Life Cycle Assessment (LCA) methodology as a novel approach to measure environmental impacts for the following organizational areas: transportation, food, accommodation, venues, office, communication, and waste. The findings show that each event exhibits a different pattern of environmental impact. Overall, energy use in venues and long-distance participant travel were the areas of greatest impact and opportunity for reduction. LCA proved a useful method for analyzing the impacts of small to medium events and planning them in a more environmentally sustainable manner.  v Preface  This dissertation is an original intellectual product of the author, Matt Dolf. I conducted all identification and design of the research, performance of the various parts of the research, and analysis of the research data.  The full text in Chapter 5: Section 5.3 has been published as Dolf, M., & Teehan, P. (2015). Reducing the carbon footprint of spectator and team travel at the University of British Columbia’s varsity sports events. Sport Management Review, 18(2), 244–255. I was the lead investigator responsible for all major areas of concept formation, data collection and analysis, as well as manuscript composition. Paul Teehan contributed to concept formation, data analysis, and manuscript edits. Portions of the text and Figure 10, Figure 11, Figure 12, Figure 13, and Figure 14 in Chapter 5: are used with permission from Dolf & Teehan and the applicable sources.  All projects and associated methods were approved by the University of British Columbia’s Research Ethics Board (BREB). BREB ID’s: #H12-02820 and #H14-00514. vi Table of Contents  Abstract .......................................................................................................................................... ii	Lay Summary ............................................................................................................................... iv	Preface .............................................................................................................................................v	Table of Contents ......................................................................................................................... vi	List of Tables ................................................................................................................................ xi	List of Figures .............................................................................................................................. xii	List of Abbreviations ................................................................................................................. xiv	Acknowledgements ......................................................................................................................xv	Dedication ................................................................................................................................... xvi	Chapter 1: Introduction and Rationale .......................................................................................1	1.1	 Climate Change and Environmental Concerns .................................................................. 1	1.2	 Sport and the Environment ................................................................................................ 3	1.3	 Environmental Impact Assessment of Sport Events .......................................................... 5	Chapter 2: Literature Review .......................................................................................................8	2.1	 Sustainability...................................................................................................................... 8	2.1.1	 The Rise of Sustainable Development and Sustainability .......................................... 8	2.1.2	 Sustainability as Attractor and Ecological Modernization Theory ........................... 12	2.1.3	 Regenerative Design Theory ..................................................................................... 15	2.2	 Life Cycle Assessment (LCA) ......................................................................................... 19	2.2.1	 History – Environmental Assessment and the Rise of LCA ..................................... 19	2.2.1.1	 Phase 1: Goal and Scope .................................................................................... 21	2.2.1.2	 Phase 2: Inventory Analysis ............................................................................... 22	2.2.1.3	 Phase 3: Impact Assessment .............................................................................. 25	2.2.1.4	 Phase 4: Interpretation ....................................................................................... 27	2.2.2	 Applicability of LCA ................................................................................................ 27	2.2.2.1	 Uncertainty ......................................................................................................... 29	2.2.2.2	 Limited Coverage of Environmental Impacts .................................................... 31	2.2.2.3	 Accuracy ............................................................................................................ 32	vii 2.2.2.4	 Resource Requirements ..................................................................................... 33	2.2.2.5	 Data Requirements ............................................................................................. 33	2.2.2.6	 Appropriate Impact Categories and LCA Methods ........................................... 34	2.2.2.7	 Complexity ......................................................................................................... 38	2.2.2.8	 Lack of Sector-specific LCA Tools ................................................................... 39	2.2.2.9	 Geographic Specificity ....................................................................................... 40	2.3	 Sport Events and the Environment .................................................................................. 41	2.3.1	 Event Impacts, Leveraging and Legacy .................................................................... 41	2.3.2	 Characteristics of Small and Medium Events ........................................................... 44	2.3.3	 Environmental Sustainability Standards for Events ................................................. 46	2.3.4	 “What Gets Measured Gets Done” ........................................................................... 50	2.3.5	 Use of LCA in Sports Events .................................................................................... 53	Chapter 3: Research Questions ..................................................................................................55	3.1	 Thesis Goal Statement ..................................................................................................... 55	3.2	 Research Questions .......................................................................................................... 55	3.3	 Research Objectives ......................................................................................................... 55	3.4	 Assumptions ..................................................................................................................... 56	Chapter 4: Methods .....................................................................................................................57	4.1	 Research Design: Case Study .......................................................................................... 57	4.2	 Overview of Case Studies ................................................................................................ 59	4.2.1	 Case 1: UBC Thunderbirds Teams, Events, and Venues .......................................... 59	4.2.2	 Case 2: Special Olympics Canada 2014 Summer Games ......................................... 60	4.3	 Geographic Context and Site of Research ....................................................................... 60	4.4	 Research Method: Life Cycle Assessment ...................................................................... 62	4.4.1	 Goals of the study ..................................................................................................... 63	4.4.2	 Functional Unit ......................................................................................................... 63	4.4.3	 Product System Boundary ......................................................................................... 64	4.4.4	 Primary Functions of the Product System ................................................................ 66	4.4.5	 LCA Assessment Methods ........................................................................................ 67	4.4.6	 LCA Inventory Data Sources .................................................................................... 67	4.4.7	 Data Collection and Impact Assessments by Event Organizational Area ................ 68	viii 4.4.8	 Sensitivity Analysis .................................................................................................. 68	4.5	 Limitations ....................................................................................................................... 69	4.6	 Self-reflection .................................................................................................................. 71	Chapter 5: UBC Athletics ...........................................................................................................73	5.1	 Introduction ...................................................................................................................... 73	5.2	 UBC Athletics Venues ..................................................................................................... 74	5.2.1	 Methodological Considerations for Venue Impact Assessment ............................... 80	5.3	 Reducing the Carbon Footprint of Spectator and Team Travel at the University of British Columbia’s Varsity Sports Events ................................................................................ 83	5.3.1	 Introduction ............................................................................................................... 83	5.3.2	 Carbon Footprinting and Sports Events .................................................................... 89	5.3.2.1	 Life Cycle Assessment – Measure to Manage ................................................... 92	5.3.3	 Methods..................................................................................................................... 95	5.3.3.1	 Carbon Footprint ................................................................................................ 95	5.3.3.2	 Spectator Travel Survey ..................................................................................... 97	5.3.3.3	 Occupancy Rates ................................................................................................ 98	5.3.3.4	 Team Travel ..................................................................................................... 100	5.3.4	 Results ..................................................................................................................... 100	5.3.4.1	 Spectators ......................................................................................................... 100	5.3.4.2	 Teams ............................................................................................................... 103	5.3.5	 Discussion ............................................................................................................... 104	5.3.5.1	 Methodological Implications ........................................................................... 104	5.3.5.2	 Patterns and Impacts ........................................................................................ 107	5.3.5.3	 Opportunities for Carbon Footprint Reduction ................................................ 108	5.3.5.4	 Theoretical Implications .................................................................................. 112	5.3.6	 Conclusion .............................................................................................................. 112	Chapter 6: Special Olympics Canada 2014 Summer Games .................................................115	6.1	 Introduction .................................................................................................................... 115	6.2	 About the Games ............................................................................................................ 116	6.2.1	 Event Overview ...................................................................................................... 117	6.2.2	 Games Venues ........................................................................................................ 118	ix 6.2.3	 Games Participants .................................................................................................. 118	6.3	 Methods.......................................................................................................................... 119	6.3.1	 Environmental Impact Assessment ......................................................................... 119	6.3.1.1	 The Climate Change Impacts of Travel ........................................................... 120	6.3.1.2	 Data Collection Methods for Participant Travel to the Games ........................ 121	6.3.1.3	 Travel for Participants at the Games ................................................................ 123	6.3.2	 Data Collection Methods for Other Organizational Areas of the Games ............... 124	6.4	 Results ............................................................................................................................ 125	6.4.1	 Travel Distance and Region of Origin .................................................................... 129	6.4.2	 Mode Choice and Participant Type ......................................................................... 132	6.4.3	 Occupancy Rates and Sensitivity ............................................................................ 134	6.5	 Discussion ...................................................................................................................... 136	Chapter 7: Discussion ................................................................................................................140	7.1	 Comparison of Event Characteristics ............................................................................. 140	7.2	 Comparison of Impact Patterns Across Events .............................................................. 142	7.3	 Opportunities for Events to Contribute to Environmental Sustainability ...................... 146	7.4	 Reflections on Using LCA to Measure Environmental Impacts of Events ................... 150	Chapter 8: Conclusion ...............................................................................................................155	8.1	 LCA for Events .............................................................................................................. 155	8.2	 Opportunities for Environmental Impact Reduction ...................................................... 156	8.3	 Revisiting Sustainability: The Opportunity for Small to Medium Events ..................... 160	8.4	 Contributions ................................................................................................................. 163	Bibliography ...............................................................................................................................165	Appendices ..................................................................................................................................176	Appendix A Case 1: Data Collection & Impact Assessments by Event Organizational Area for UBC Athletics & Recreation ............................................................................................. 176	A.1	 Accommodation - UBC Athletics & Recreation .................................................... 177	A.2	 Communication - UBC Athletics & Recreation ..................................................... 178	A.3	 Food - UBC Athletics & Recreation ....................................................................... 179	A.4	 Office & Management - UBC Athletics & Recreation ........................................... 180	A.5	 Waste - UBC Athletics & Recreation ..................................................................... 181	x A.6	 Travel - UBC Athletics & Recreation ..................................................................... 182	A.7	 Venues - UBC Athletics & Recreation ................................................................... 185	A.8	 Emission Factors - UBC Athletics & Recreation ................................................... 199	Appendix B Case 2: Data Collection & Impact Assessments by Event Organizational Area for SOC 2014 .......................................................................................................................... 201	B.1	 Accommodation – SOC 2014 ................................................................................. 202	B.2	 Communication – SOC 2014 .................................................................................. 203	B.3	 Food – SOC 2014 ................................................................................................... 204	B.4	 Waste – SOC 2014 .................................................................................................. 205	B.5	 Travel – SOC 2014 ................................................................................................. 206	B.6	 Venues – SOC 2014 ................................................................................................ 208	B.7	 Emission factors – SOC 2014 ................................................................................. 211	Appendix C SOC 2014 Organizing Committee Expenditures ............................................... 213	Appendix D SOC 2014 Map ................................................................................................... 214	Appendix E SOC 2014 Participant Break-down .................................................................... 215	Appendix F Event Carbon Footprint Estimator ...................................................................... 216	 xi List of Tables  Table 1: Simple economic input-output table appended with air pollution data (table simplified and adapted by author from Leontief, 1970). .........................................................23	Table 2: Pedigree matrix for inventory data ............................................................................70	Table 3: Carbon footprint emission factors (EF) and vehicle occupancy (VO) rates for North America (NA) and the UBC spectator context. .............................................................96	Table 4: Spectator behaviour change scenarios and resulting change in overall spectator carbon footprint. .....................................................................................................................109	Table 5: Team behaviour change scenarios and resulting change in overall team carbon footprint. .................................................................................................................................110	Table 6: Carbon footprint emission factors (EF) and vehicle occupancy (VO) rates for North America (NA) and SOC 2014 context. ........................................................................120	Table 7: Shuttle vehicle travel at the event. ...........................................................................123	Table 8: Vehicle fleet travel at the event. ..............................................................................124	Table 9: Percentage contribution of SOC 2014 organizational areas for each IMPACT 2002+ environmental damage category. ................................................................................127	Table 10: Participant travel distances to SOC 2014 by region of origin. ..............................130	Table 11: A comparison of UBC Athletics and SOC 2014 event characteristics. .................141	Table 12: Spectator, staff and team quotas for SOC 2014 by Province/Territory. These are unique registered participants, not total daily attendees. .................................................215	Table 13: Team quotas for the SOC 2014 by Province/Territory. .........................................215	 xii List of Figures  Figure 1: Visual representations of sustainability: a) overlapping circles; b) nested circles; c) planner’s triangle .................................................................................................................12	Figure 2: The four phases of an LCA according to ISO 14044 ...............................................21	Figure 3: Simplified unit process diagram showing examples of material, energy, and emission flows across the life cycle stages of a widget. ..........................................................24	Figure 4: Number of International Tennis Federation events classified by the European Commission small-medium enterprise designation in 2011 and showing estimated turnover. ...................................................................................................................................46	Figure 5: Total annual environmental impacts for the UBC Thunderbirds 2011/2012 season normalized to the number of average Canadians per year contributing the same amount of environmental impact. ............................................................................................75	Figure 6: Total annual climate change impacts for all UBC Athletics venues for the UBC Thunderbirds 2011/2012 season. .............................................................................................77	Figure 7: Total environmental impacts for UBC Thunderbirds for the 2011/2012 season normalized to the average Canadian person’s impact per year for a) UBC Aquatic Centre, b) UBC Doug Mitchell Arena, c) UBC War Memorial Gym, d) UBC Baseball Diamond. ....79	Figure 8: Climate change contribution of Doug Mitchell Arena to men’s ice hockey team based on different allocation scenarios. ...................................................................................81	Figure 9: Climate change contribution of Warren Field to Women’s soccer team based on different allocation scenarios. ..................................................................................................82	Figure 10: Frequency distribution of the passenger occupancy rate for spectators traveling to UBC varsity events by car. ..................................................................................................99	Figure 11: Distance in km travelled by spectators to sampled UBC events showing all data points (upper graph) and a close-up view of box plots (lower graph). ..........................101	Figure 12: Car travel was the most frequently used mode by spectators at 66% while plane and car travel dominated the spectator carbon footprint both on an average per person basis and for the overall total. ....................................................................................102	Figure 13: Spectators largely originated from within the Vancouver Regional District but the predominant GHG emissions were due to travel coming from outside the region. .........103	Figure 14: Carbon footprint of the UBC team by event type and subdivided by mode. .......104	xiii Figure 15: Total environmental impacts for the SOC 2014 event normalized to the number of average Canadians per year contributing the same amount of environmental impact. ....................................................................................................................................126	Figure 16: a) the normalized environmental contributions for the organizational area of food and b) the percentage contribution for each food ingredient. ........................................128	Figure 17: SOC 2014 had a total carbon footprint of 2,500 tonnes of CO2e with travel to the event contributing the most among the organizational areas. ..........................................129	Figure 18: Travel distance on a log scale by event participants to the Games by mode and faceted by region of origin showing all data points (upper graph) and box plots (lower graph). ....................................................................................................................................131	Figure 19: Total (a) trip count and (b) distance in km by mode and participant type travelling  to SOC 2014. ........................................................................................................132	Figure 20: Total carbon footprint by mode and participant type travelling to SOC 2014. ....133	Figure 21: Influence of occupancy rate on in emission factors (kg CO2e per passenger km) by mode. Red markers show occupancy rate used by SOC 2014. .................................135	Figure 22: Total carbon footprint for each participant type travelling to SOC 2014 by mode for higher occupancy rate scenario, actual occupancy rates used, and lower occupancy rate scenario. ........................................................................................................136	Figure 23: Screenshot of event travel carbon footprint tool. Users can enter number of people originating from each region to estimate total travel impacts. ...................................216	Figure 24: Screenshot of assumptions table which feeds into estimator tool. The parameters can be adjusted to suit each event. ......................................................................216	xiv List of Abbreviations  EM Ecological Modernization Theory ES Environmental Sustainability FIFA Fédération Internationale de Football Association GDP Gross Domestic Product GHG Greenhouse Gas Emissions GWP Global Warming Potential IOC International Olympic Committee IPCC United Nations Intergovernmental Panel on Climate Change ISO International Standards Organization kg CO2e Kilograms of carbon dioxide equivalents t CO2e Tonnes of carbon dioxide equivalents LCA Life Cycle Assessment LCI Life Cycle Inventory RD Regenerative Design Theory SOC Special Olympics Canada UBC University of British Columbia UNEP United Nations Environmental Program  xv Acknowledgements  It is with tremendous gratitude that I thank my PhD committee members. Professor Bob Sparks, you were a deeply thoughtful and widely knowledgeable mentor to me throughout this journey, with a remarkable passion for this topic. Professor Gunilla Öberg, you helped me navigate the complexities of interdisciplinary and sustainability work through wonderful conversations and guidance. Professor Jan-Anders Månson, I wouldn’t have even started this journey without your encouragement, friendship, and vision for bridging academia and the real world. Professor Olivier Jolliet, I felt privileged to have benefitted from your expertise and your passion for doing work that makes a real difference in the world.   I would also like to thank the University of British Columbia, UBC Athletics & Recreation, Quantis International, and the Special Olympics family, who showed keen interest along the way and made it possible for me to conduct my research in the real world.   This journey in learning would not have been possible without the support of many fellow grad students in Kinesiology and the Institute for Resources, Environment, and Sustainability. Cathy, Stefan, Paul, Alex, and many more, I honestly couldn’t have done this without your encouragement, your bright minds, and our “support groups.”   And finally, thank you to my family and your love, patience, encouragement, and for instilling in me a life-long passion for learning, critical thinking, and trying to make a difference in the world. xvi Dedication  To my wife Eve and my daughter Leyla, who inspire me beyond words and make every day better than the last. Eve, you believed in me and made it all possible. To my parents Ben and Cathy, and my brother Nick, for your love and support.  1 Chapter 1: Introduction and Rationale  “Maybe the most important aspect of our joint future is linked to the environment (...) it is extremely important that athletes, as role models, and sporting federations show pro-activeness in caring about the environment” (Kofi Annan, 2010, p. 9).  There is a growing realization by the sports industry that it must reduce its environmental impacts. Some academics have suggested that sport events – mega events in particular – could effect broader change and, because of their popularity, offer an exceptional platform to help raise consciousness about important issues (Horne, 2007). A key challenge is that few events measure the environmental impacts of their activities, nor do they embed this type of information into planning decisions. Approaches such as Life Cycle Assessment (LCA) are increasingly used in other sectors to understand the environmental attributes of products and services. LCA has yet to be applied to sport events in a comprehensive way and research is needed to determine whether this method can be adapted to this role and how the results might benefit decision makers and reduce environmental impacts.  1.1 Climate Change and Environmental Concerns Climate change caused by human activities is a pressing concern that could lead to extreme levels of social, ecological and economic disruption over the next century. Gribbin (1990) has said that climate change is “the most important problem facing mankind over the next 50 years” (p. preface). The United Nations Intergovernmental Panel on Climate Change (IPCC), the most widely accepted source of climate change science, highlights the level of 2 environmental change that is occurring in its most recent Climate Change Assessment Report Summary for Policy Makers:  Warming of the climate system is unequivocal, and since the 1950s, many of the observed changes are unprecedented over decades to millennia. The atmosphere and ocean have warmed, the amounts of snow and ice have diminished, sea level has risen, and the concentrations of greenhouse gases have increased (IPCC, 2013, p. 3).  The same IPCC Report (2013) cautions that society needs to act in order to mitigate the problem: “Continued emissions of greenhouse gases will cause further warming and changes in all components of the climate system. Limiting climate change will require substantial and sustained reductions of greenhouse gas emissions” (p. 14). By extension, it is often argued that individuals and organizations share a responsibility to adapt their behaviour to mitigate the risk of contributing to harmful climate change and other environmental challenges.  Climate change is not the only important global environmental challenge society faces. For example: Bio-diversity impacts due to human intervention are significant as evidenced by the fact that over 90% of the large fish stocks have disappeared from our oceans since 1950 (Myers & Worm, 2003); 884 million people do not have access to improved – or safe – water sources (UNICEF & World Health Organization, 2008); and earth’s growing population is using up our natural resources faster than they can naturally be replaced (Wackernagel & Rees, 1996). All of these are important issues and provide a useful context for considering the broad range of potential impacts of the sports industry. 3 1.2 Sport and the Environment The activities of the sports industry are substantial and may contribute to environmental change. The Canadian sports industry contributed approximately 1.2% of national GDP and 2% of employment in 2005 (Bloom, Grant, & Watt, 2005). The industry includes sporting goods companies, sports facility owners, governing bodies of sport, sport tourism operators, sport event owners, and sport media. Areas of potential environmental concern resulting from the sports industry include: GHG emissions from event-induced travel; materials, water, and energy consumption required for the construction and operation of event venues; biodiversity alteration of alpine ecosystems due to concentrated numbers of outdoor sports enthusiasts; and air and water quality changes linked with sporting goods. Further, Thibault (2009) has linked the increasing globalization of the sports industry with exacerbation of the level of environmental change, particularly through the increase in sport event and tourism consumption and the travel this has induced. The rate of environmental change linked to this industry may therefore be increasing rather than decreasing.  Recognizing these concerns, the industry has begun to put in place mechanisms to address its environmental impacts. In 1994, the Olympic Congress – a highly influential body within the sports industry – made the environment the official third pillar of the Olympic Movement alongside sport and culture. In the same year, the United Nations Environmental Program (UNEP) created a Sports and Environment committee. In 1999, the IOC published the Olympic Movement’s Agenda 21 for Sport and the Environment. It was based on the principles set out in Agenda 21, which had been adopted by 178 governments during the Rio Earth Summit in 1992. Cantelon and Letters (2000) contrast the environmental contexts of 4 Albertville 1992 and the Lillehammer 1994 Games and argue that the experience in Albertville was a key reason for the IOC taking this step. Albertville was widely criticized as an “environmental disaster,” largely because of the damage to alpine ecosystems due to construction of venues such as the bobsleigh track, ski jump, downhill run, and Nordic skiing courses.   Albertville 1992 was the first major event to be widely discussed in the sport and environment literature. Numerous articles cited it as an impetus for the IOC and Olympic Games bid cities to improve environmental sustainability (hereafter referred to as ES) policies, kicking off a movement within the sports industry to embed ES into the planning and management of sport programs, events, sponsors, and organizing bodies (Cantelon & Letters, 2000; Cashman & Hughes, 1999; Chappelet, 2008; Lesjø, 2000; May, 1995). Flagship events such as the Olympic Games and FIFA World Cup have international exposure and provide a global stage to focus on environmental issues.  Sport events can both create and suffer the consequences of environmental damage, which may explain the increased green consciousness of the sports industry (Maguire, Jarvie, Mansfield, & Bradley, 2002). Commonly cited causes of environmental impacts are linked to the construction of venues, transportation, accommodation, materials, waste, and food consumption. For example, the United Nations Environment Program estimates that the global warming impact of the FIFA 2010 World Cup in South Africa totalled over 2 million tons of CO2 equivalent emissions (CO2e) with the largest contributors being 65% due to international travel, 17% due to national travel, and 13% from accommodation energy use 5 (“UNEP Climate Neutral Network – Greening 2010 FIFA World Cup,” n.d.). Collins et al. measured the Football Association Cup international soccer match in Wales: spectators increased their ecological footprint seven times over the daily average (Collins, Flynn, Munday, & Roberts, 2007). The daily footprint of a Welsh citizen is itself three times higher than the Earth is likely to be able to sustain (“What is footprint? – Foot Print Wales,” n.d.).  The academic literature also contains numerous examples of how sport events are directly affected by environmental change. Winter sports on snow are seeing shortened ski seasons due to global warming and rely increasingly on snow making machines (Scott, McBoyle, & Mills, 2003). Air pollution levels are another oft-cited problem as evidenced by the concerns for athlete safety surrounding the Beijing 2008 Olympic Games due to the high levels of particulate matter (Streets et al., 2007). Finally, polluted water concerns have brought together numerous partnerships between sports bodies and environmental NGOs such as the International Rowing Federations “Clean Water” partnership with the World Wildlife Federation (WWF).  1.3 Environmental Impact Assessment of Sport Events Getz (2009) argues that when it comes to sustainable events, “Standardized measures and methods will be required, but currently only the financial/economic measures are well-developed” (p. 71). At present the assessment of environmental impacts are not given the same importance (Collins, Jones, & Munday, 2009; Sherwood, Jago, & Deery, 2005). A growing literature has emphatically called for more research to address the lack of 6 appropriate quantitative environmental impacts assessment methods for the sports sector (Collins et al., 2009; Getz, 2009; Hiller, 1998; Jones, 2008).  Without empirical data, event organizers may not know which activities have the biggest environmental impacts, nor which solutions can address these impacts most effectively. To illustrate, events commonly prioritize so-called “zero waste” efforts to divert waste from landfill and incineration to composting and recycling. But is waste actually one of the major impacts of the event? The impact of waste in Canada is 3% percent of total GHG emissions compared to 81% arising from the energy sector (Environment Canada, 2012), indicating that the reduction of energy consumption should be a higher priority for event organizers than it currently is.  The past decades have seen rapid improvements in methods, tools, and databases related to environmental impact assessment. Carbon footprinting is an example of an LCA-derived method that has received widespread support from governments and business communities, perhaps in part because most countries have agreed to report their GHG emissions to the IPCC and much of the data is therefore standardized and freely available. By contrast, LCA approaches incorporating multiple impact categories are often used in industry to compare different environmental impacts – such as ecosystem damage, climate change potential, or resource use – but they are more costly and complex than single impact categories such as carbon footprinting. In order to best meet the needs of events, additional research is needed to clarify how LCA might be applied to events rigorously yet parsimoniously and cost effectively. 7 In this dissertation research, I take up some of these issues and conduct quantitative investigations in two case studies with the aim of improving our understanding of the environmental impacts of small to medium events, and how LCA can assist event managers in planning more sustainable events.  The dissertation begins with a review of the literature on sustainability, LCA and environmental impact assessment, and sport event management. The methods chapter outlines the approach and considerations for conducting an LCA of two case studies: the UBC Athletics & Recreation varsity 2011–2012 athletic season; and the Special Olympics Canada 2014 Summer Games. A chapter is then dedicated to each case study, focusing primarily on assumptions, methods, results, analysis, and implications of assessing the environmental impact of seven event organizational areas with the heaviest emphasis on participant travel. In the discussion and conclusion chapters I reflect on the research questions in light of the results from both cases and consider implications for theory and practice.  8 Chapter 2: Literature Review  While a growing body of research has investigated environmental sustainability (ES), sport event management, and environmental impact assessment, my literature review shows that researchers have only recently begun investigating the intersection of these three areas. This chapter begins by introducing the broader concepts of sustainability and ES. In the second part, it provides an overview of theoretical and methodological implications of using LCA to assess the environmental impacts of events. The chapter concludes by reviewing the existing literature related to sport events and the implications for measuring ES.  2.1 Sustainability  2.1.1 The Rise of Sustainable Development and Sustainability The concept of sustainable development has been widely adopted over the past several decades by industry, government, and academia. Although the term has been in use since at least the early 1970’s, it gained broader public awareness with the publication of Our Common Future, typically referred to as the Brundtland Report, which provided what has become the most widely cited definition of sustainable development, that is, “development that meets the needs of the present without compromising the ability of future generations to meet their own needs”(World Commission on Environment and Development, 1987). The Brundtland Report highlights the ecological pressure that industrialized nations are placing on the planet and argues that societal growth is taking place at an unsustainable rate, squandering biological capital faster than it is being replenished. The report strongly 9 contends that new technologies, consumption patterns, and international policies are needed to achieve sustainable levels of growth.  Robinson (2004) argues that while the term sustainable development is more commonly used by private sector and government organizations, sustainability is gaining widespread use among NGOs and academics. This is largely because the word “development” implies growth, a central principle of capitalism, whereas the term “sustainability” requires preservation and absolute limits. Robinson also suggests that sustainability is seen more as a value change whereas sustainable development must be seen as a technical fix. While the distinctions are important, in practice the two terms are often used interchangeably along with other concepts such as corporate social responsibility and triple bottom line. Dryzek similarly suggests that the debate is more important than a standardization of the concept (World Commission on Environment and Development, 1987). He compares this to the debate surrounding the concept of democracy, which faces the same definitional and implementation challenges – we all know generally what it is but disagree on the specifics.  Dryzek (1997) identifies two main camps in environmental discourse: survivalists and prometheans. In Dryzek’s terminology, survivalists call to limit our growth to prevent ecological collapse before our environmental degradation reaches a tipping point. A common metaphor used by survivalists is the concept of spaceship earth to represent the carrying capacity of our planet and its natural limits. They subscribe to underpinning environmental concepts laid out in Tragedy of the Commons by Garret Hardin (1968), the Club of Rome report Limits to Growth by Meadows et al. (1972), as well as the problem of exponential 10 population growth as laid out by Malthus in his influential work written in his 1798 An Essay On The Principle Of Population (2013). A similar case is made by Lester Brown in The Twenty-Ninth Day (1978), which highlights the geometric increase of population if left unchecked by natural resource limits.  Prometheans, on the other hand, believe that nature is limitlessly bountiful and that human ingenuity and technological innovation can solve all problems. The term comes from Prometheus in Greek Mythology who stole fire from Zeus and as a result provided humans with the capacity to use technology and change their world. Prometheans emerged with the industrial revolution, which led to rapid increase in the pace of technical change, access to resources, accumulation in human wealth, and improvement in the quality of life. According to Dryzek, they subscribe to Ricardian economics and Barnett and Morse’s (1963) concept of scarcity and growth and further argue that the free market and technology will effectively manage supply and demand. Prometheans do not see population as an issue, but rather as a source of increased ingenuity. They also do not see nature as an entity unto itself but rather a resource to be used for our purposes indefinitely.  This dichotomy in environmental discourse highlights two poles of a philosophical spectrum in how organizers of sports events may view or assess ES. For example, from a survivalist perspective, sports events need to alter their activities to avoid unsustainable use of natural resources. This would include, for example, curtailing airline travel to events until renewable fuels replace fossil fuels and reducing or eliminating logging and forest destruction to build downhill ski runs and sliding centres. Prometheans, on the other hand, might prioritize 11 putting in place technology to make an event more “green” than otherwise might be the case but not to the extent that growth is curtailed. As will be presented later in this chapter, current ES guidance documents do not specify which paradigm of sustainability they endorse, leaving open to interpretation what really would constitute an environmentally sustainable event.  The most widely used conceptions of sustainability distinguishes three distinct but related domains or spheres of overlapping concerns: society, economy, and environment (Connelly, 2007; Goodland & Daly, 1996; Mebratu, 1998). Three common representations of sustainability with differing interpretations of how these domains are connected are illustrated in Figure 1. The Venn diagram shows environment, social, and economic components as separate yet interconnected (Connelly, 2007). The second diagram uses the same spheres but shows them as nested, implying a hierarchy where the economy can only exist with a sustainable society which in turn can only exist within a sustainable environment (Lozano, 2008). The Planners Triangle emphasizes the conflicts that arise between these spheres and implies that sustainability can only exist when these poles are in balance (Campbell, 1996).  12    Figure 1: Visual representations of sustainability: a) overlapping circles; b) nested circles; c) planner’s triangle  In the following section I briefly outline Ecological Modernization Theory (EM) and Regenerative Design Theory (RD) as two theoretical perspectives that help to elucidate these frameworks and inform how organizers might use environmental strategies in an event context.  2.1.2 Sustainability as Attractor and Ecological Modernization Theory Mol (2010) has investigated the implications of sustainability for sport mega events such as the Beijing Olympics and argues that sustainability can act like an attractor by reshaping the structure and patterns of these events as it gains widespread adoption among large governmental and non-governmental organizations. According to Mol (2010), the concept of sustainability as attractor can be tied to ecological modernization which he describes as “the emergence of an ecological rationality in processes of production and consumption, next to and partly independent of economic, political and other rationalities” (p. 538).  Specifically with regards to Beijing, the Games were partly awarded to China by the International Olympic Committee in the hope that the global spotlight would lead to reforms 13 related to sustainability. The first Beijing bid was unsuccessful and barely mentioned environmental aspects. The second and winning Beijing bid incorporated strong commitments to environmental considerations – likely a result of Sydney’s much discussed Green Games (Cashman & Hughes, 1999). Mol further suggests that Beijing’s aggressive green promises appeared to lead to almost breathtakingly quick reforms in the lead-up to the Games in China: environmental impact assessments were extensively carried out, five new metros were installed, 14 new wastewater facilities were built, new vehicle emission standards matched Europe’s, half the vehicles were taken off the road in the lead up to the Games, factories were shut down, most buses and taxies were converted to natural gas, large reforestation and green space protection projects were put in place.  There is an ongoing debate in the literature, however, about whether this level of short term change can be sustained and concerns have been raised around these green promises amounting to little more than greenwashing if they cannot be rigorously substantiated (discussed in more depth in Section 2.3.1). There is also a growing recognition among academics and sport governing bodies that attempts to reduce environmental harm are not enough and that social and human rights issues need to be given stronger consideration. Mol notes that while the 2008 Games may have improved certain environmental areas, there is still much to critique in Beijing’s environmental practices such as ongoing air quality issues and the lack of external verifications of environmental efforts. Regardless, Mol argues that sustainability can become an attractor, or a focal point, for mega events to orient their aspirational efforts. These mega events are – according to Mol – “time-space compressions” 14 and the reorganized networks and patterns have the potential to yield longer term changes in the region/country that are difficult to measure but nonetheless significant.  Critics of Ecological Modernization Theory (EM) contend that no matter how much ecological protection is linked to capitalist modes of production and governance, the fundamental structure of capitalism may be flawed and has not yet been proven to be an effective way of dealing with our current ecological crisis (York & Rosa, 2003). Wilson and Millington (2013) have discussed EM theory in relation to sport events and suggested that ecological rationality can take both strong and weak forms. Strong refers to a belief that the industry needs to be pushed sufficiently to address environmental concerns, while a weaker version reflects a faith that market forces will inherently adapt to take care of environmental concerns on their own. Regardless of the form, Wilson and Millington point out that EM does not adequately address the fundamental power inequity between industry actors and environmental stakeholders. They also suggest that EM is being used by event organizers to frame environmental promotion in a way that avoids having to choose between economic growth and environmental progress. Events, therefore, run a risk of being used as a vehicle for “greenwashing” if environmental commitments are not held to account or deviate only slightly from standard practice as a way of deflecting criticism.  The “greening” of an event that furthers our levels of industrialization may be just a slightly more sustainable form of business as usual rather than a departure towards a more survivalist version of sustainability. A UNEP report published in 2011 highlights this challenge by showing that while we are seeing indications of GDP growth decoupling from resource use 15 (common indicators for the economy and ecological balance) globally – we have not yet been able to achieve a simultaneous increase in GDP and decrease in resource use (UNEP, 2011).  2.1.3 Regenerative Design Theory Regenerative design theory (RD) is an emerging sustainability theory arguing that sustainability concepts and implementation strategies should employ a more aspirational set of principles. According to Cole (2012), “Within the regenerative literature, ‘sustainability’ is often presented as an intermediate stage between green and regenerative – a ‘neutral’ state that, once attained, provides the necessary base condition that permits regenerative capabilities to evolve” (p. 45). RD represents a change in thinking from an anthropocentric view that humans should develop nature and society to meet its needs in a sustainable manner, to a regenerative approach which insists we look for place-based patterns in the ecosystem to bring nature and humans into harmony (Mang & Reed, 2011). This is in contrast to preservationists, who, at the other end of the spectrum, aim to protect the environment in its pristine form devoid of human interaction. Regenerationists see humans as part of the ecosystem, neither separate from it nor dominating.  The concept of RD is generally attributed to John T. Lyle and his 1996 book Regenerative Design for Sustainable Development (Mang & Reed, 2011). RD has strong roots in the Permaculture concept, which promotes a “… shift from dominance to intimacy with nature through mutually beneficial interaction with the entity of place” (Marvick and Murphy, 1998, p. 24). The word permaculture is a derivation of the terms permanent agriculture and permanent culture, thereby tying in both the environmental and social domains. Regenerative 16 design is also closely connected to the concept of “cradle to cradle” thinking (Lyle, 1996), a foundation for life cycle assessment: “Regenerative design means replacing the present linear system of throughput flows with cyclical flows at sources, consumption centers, and sinks” (McDonough & Braungart, 2002).  The notion of regeneration differs from sustainability in that it explicitly emphasizes the need to restore what may have been lost. The root of the word regenerative is “re” – again – and “generate” – to produce or create. The term regenerative itself refers to the potential for a transformed condition through rebirth or renewal (Wackernagel & Rees, 1996). Sustainability focuses on the idea of self-sustaining or maintaining, it does not account for what has been taken out of the system already. This is an important distinction if the earth is currently in a state of overshoot in terms of resource and ecosystem depletion (Lyle, 1996, p. 10). RD suggests that we cannot simply maintain the state we are in if we are to bring our ecosystems and social systems back into balance.  Certain principles of design and implementation recur regularly in the RD literature. The first is the idea that we should aim to do more good rather than less bad. According to Cole, the current arguments around the danger of doing nothing have failed to resonate with the public. A positive vision, by contrast, may be more effective in inspiring change. RD employs ecological systems theory, which suggests that we need to consider disparate things as part of a working whole rather than as individual parts. According to systems thinking, the whole is greater than just the sum of its parts; the behaviour of the system cannot be inferred from an inspection of its parts. Isolated data is not as useful as viewing patterns of information in a 17 context. Systems thinking also employs different modes of causality, such as circular flows, rather than linear causes and effects. For example, so-called waste materials and products can be fed back into the system rather than seen as end-of-life. Thirdly, Mang & Reed (2011) suggest that place is the starting point for design, connecting people to the spirit of place and motivating them to care for it. Place-based thinking considers nature as both model and context. Tied to the notion of place is the concept of thinking at different and relevant scales. The emergence of bioregionalism projects like the 100 Mile Diet is an example of the focus on integrating communities and ecosystems (Smith & MacKinnon, 2007). Stories are also rooted in the deep connection to place needed to enact enduring change: “Research shows that the human memory is story based, not data based, and that stories are fundamental to how people learn and organize what they know” (Mang & Reed, 2011). Finally, community and stakeholder engagement is another essential part of the RD process. Stakeholders become co-designers in the processes from the beginning and there is an emphasis on building human capacities and stewardship to maintain the system (Cole, Oliver, & Robinson, 2013). This supports the notion that better information and regular feedback will achieve closer alignment between system operators and function. This latter argument suggests that the use of environmental impact assessment tools like LCA may hold promise to assist event planners in achieving more environmentally sustainable events.  RD has yet to be applied by the event industry and more research is needed to ascertain its usefulness in this setting. There has, however, been some research on its application in the building sector. According to Cole (1996), building design has seen a shift over the past three decades from a focus on traditional to green to sustainable, and now to regenerative design. 18 An example is a project at UBC, where the university has applied RD principles to the aspirational goal of constructing a regenerative building. The Centre for Interactive Research in Sustainability (CIRS) was completed in 2012 and set net positive targets in areas important to the ecosystem and human health. For example, CIRS is meant to become net energy positive by using renewable energy sources, capturing waste heat from nearby buildings, and using passive shading and insulation systems. It also seeks to be water self-sufficient through green-roof filtration, water flow capture systems, and on-site wastewater treatment. On the social side, the building is designed to improve occupant health, happiness, and productivity through such measures as natural daylight for offices and democratic tools to control building operations such as heating and lighting. In practice, the building has not yet achieved these net positive targets, but it remains to be seen whether the commitments to long-term research, testing and improvement will be able to achieve this over time. In sum, there are at present clear philosophical distinctions between various conceptions of sustainability. EM and RD provide two contrasting theoretical frames. The former proposes considering ecological rationality alongside of or in addition to underlying neoliberal assumptions of economic growth emphasizing technological efficiency gains and working within the modern industrial system. RD on the other hand favours human and ecological balance, de-growth, and nature-based design. Whether event organizers use these frames to guide planning decisions – either implicitly or explicitly – may have implications for how the ES of events is evaluated and communicated.  19 2.2 Life Cycle Assessment (LCA) This section provides a brief overview of the history, context and scientific debate around the use of LCA as a method to quantify environmental impacts both in general use and in an event context.  2.2.1 History – Environmental Assessment and the Rise of LCA Environmental assessment methods have increased significantly in number and complexity, partly because of the growing awareness of the need to address environmental concerns and partly due to the proliferation of technology that enables researchers to measure and compute large amounts of data for the first time. A range of approaches are available to assist event organizers including Ecosystems Services (ES), Risk Assessment (RA), Environmental Impact Assessment (EIA), Material Intensity per Unit of Service (MIPS), Ecological Footprint (EF), Life Cycle Assessment (LCA), and Cost-Benefit Analysis (CBA), each with its own particular applications and considerations (see for e.g., Finnveden & Moberg, 2005; Ness, Urbel-Piirsalu, Anderberg, & Olsson, 2007). Among these, LCA appears to be the most promising for application to events because of its comprehensiveness and its ability to inform planning as well as post hoc assessment.  The first LCAs were carried out in 1969 on packaging options for the beverage industry with the goal of facilitating the management of environmental trade-offs between energy, materials, waste treatment, and transportation. At the time, the methods used were referred to by multiple names including Resource & Environmental Profile Analysis (REPA) and ecobalance – the French still refer to an LCA as an “ecobilan” and the Germans as an 20 “Ökobilanz.” The term Life Cycle Assessment was popularized in 1991 (Baumann & Tillman, 2004). LCA methods varied widely in the early years and debates were widespread about generating more consistent approaches for conducting studies and applying impact assessment methods among other things. Under the leadership of the Society for Environmental Toxicology and Chemistry (SETAC), a standardized protocol was set out in 1997 in an International Standards Organization (ISO) document ISO 14044. The current iteration of the standard is ISO 14044:2006 Environmental management – Life cycle assessment – requirements and guidelines (ISO, 2006b).  The idea of an LCA is to measure the environmental impacts of a product or service across the entire life cycle – cradle to grave – including the stages of resource extraction, manufacture, distribution, use, and disposal/reuse (Jolliet, Saadé, & Crettaz, 2005). Finnveden et al. (2009) have distinguished two main types of LCA: attributional and consequential. An attributional LCA examines the impacts of a good or service at a specific point in time, and typically entails a backward-looking approach. Consequential LCAs are used to inform decisions on changes to a system and are typically forward-looking. In order to carry out a peer reviewed LCA as set out by ISO 14044, four iterative phases are applied: goal and scope definition, inventory analysis, impact assessment, and interpretation as shown in Figure 2 (ISO, 2006b). Sections 2.2.1.1 to 2.2.1.4 provide a brief overview of each phase of an LCA.  21  Figure 2: The four phases of an LCA according to ISO 14044  2.2.1.1 Phase 1: Goal and Scope LCA methods require a clear definition of the primary and secondary functions of a product, service, or activity that are operationalized as a “functional unit.” This step makes it possible to compare various means to achieve the same desired outcome (Baumann & Tillman, 2004). For example, the functional unit of the environmental consequences of “one square meter of wall finishing over 5 years” would allow multiple solutions, such as paint or wallpaper, to be compared. For the purposes of comparison, it is vital that all relevant functions of a product or service are considered when determining the functional unit (e.g., aesthetics or insulation for the example above) and that clear temporal and geographic boundaries are set. In the case of an event, the functional unit might be all goods and services that go into providing an entertainment experience for one participant over the duration of the event. Secondary functions would include the provision of food, transport, a safe environment, etc. A common functional unit can allow for different products, services or activities to be compared with the same goals and scope of study.  InterpretationGoal and ScopeDefinitionInventory AnalysisImpact Assessment22 2.2.1.2 Phase 2: Inventory Analysis This phase involves data collection, data format and validation, allocation, and definition of cut-off criteria. The system boundaries must be defined such that all relevant cradle to grave impacts are identified and all substance flows are balanced. There are three main approaches to conducting inventory and impact assessment: economic input-output (EIO), unit process, and hybrid, with the latter combining EIO and unit process approaches (Suh & Huppes, 2005). The top-down input-out approach allows for hot-spot identification of major impacts in a complete system whereas the bottom-up unit process approach provides detailed and specific understanding of individual processes (Finnveden et al., 2009).  Each approach has its own strength and weaknesses that should be considered before choosing the most appropriate one. EIO LCAs take a top-down approach by using economic input-output tables and appending resource extraction and environmental discharge data to assess environmental impacts for a variety of impact categories including climate change, energy use, or toxic releases (Hendrickson, Lave, & Matthews, 2006). Input-output tables, originally developed by Leontief (1936), quantify the contributions and interdependencies between various economic sectors. Table 1 shows a simplified example of an EIO table showing economic inputs and outputs and appended with air pollution outputs.  23 Outputs Sector 1 Sector 2 Final demand  Inputs Agriculture Manufacture households Total output Sector 1 Agriculture (bushels and $) 25 $52 20 $47 55 $110 100 $209 Sector 2 Manufacture (yards of cloth and $) 14 $73 6 $35 30 $150 50 $258 Air pollution (grams of pollutant) 50  10    60  Totals ($) $125 $82 $260   Table 1: Simple economic input-output table appended with air pollution data (table simplified and adapted by author from Leontief, 1970).  EIO-based LCAs have the advantages of being relatively quick, capturing all related economic inputs and outputs for the sector under review, capturing the production and consumption patterns in the market, and avoiding many of the system boundary cut-off decisions inherent in a unit process approach. On the other hand, results are not technologically explicit in that different technologies within the sector cannot be compared. Additionally, Hendrickson et al. (2006) cite the following sources of uncertainty when estimating impacts with an EIO-LCA approach: survey errors in EIO tables due to sampling and reporting; outdated EIO tables; incomplete data since certain industrial sectors may not be included in the EIO data; missing data, as only a few environmental data indicators primarily related to air emissions are collected; sector level aggregated data (500 sectors in the case of the US EIO data); and omission of imports in national EIO tables.  A unit process LCA takes a bottom-up approach to sum up each individual material and energy flow in the system under review. Figure 3 shows a simplified example of a unit process flow diagram highlighting the material and energy inputs and emission outputs 24 related to the cradle to grave stages of resource extraction, manufacturing, distribution, use, and disposal for a widget. Depending on the goal and scope of the LCA, the diagram could also show a cradle to cradle model, with material and energy flows from disposal being fed back into the system.  Figure 3: Simplified unit process diagram showing examples of material, energy, and emission flows across the life cycle stages of a widget.  Unit Process LCA studies are usually far more time-consuming to conduct than an EIO LCA because they necessitate significantly more data collection. For an LCA on a car, for example, there are thousands of material and energy flows, to say nothing of the associated material mining/extraction machinery or production factories. Hendrickson et al. (2006) cite an automobile LCA study as having cost USD$8 million and taken two years to complete. The unit process approach is also open to interpretation errors leading to, for example, truncation error, when items may not be included in the system boundary that may contribute Wood[kg]Widget[kg]Energy[k Wh]Emissions toair / land / water[kg]Steel[kg]ManufactureExtractionDistributionUseDisposalGlass[kg]25 to the overall impact (Suh et al., 2004). On the plus side, this approach is very technologically explicit and far more adaptable in terms of desired specificity than input-output analysis. Over time, it should also become increasingly feasible to conduct unit process LCAs on a broader range of uses as studies are performed, methods developed, and databases become larger and more standardized.  Hybrid LCA approaches combine economic and physical units as well as sector and process level data (Suh et al., 2004). While Hybrid LCAs hold promise as a way of bridging the best of both input-output and unit process techniques, it remains a relatively complex method and does not appear to have reached a sufficient level of maturity for widespread use.  2.2.1.3 Phase 3: Impact Assessment Part of defining the goal and scope of an LCA is selecting the environmental impact categories to be used in the impact assessment stage. A number of multi-category methods exist including Eco-indicator 99, TRACI, EDIP, and IMPACT 2002+ (Finnveden et al., 2009). IMPACT 2002+, the method I apply in this dissertation research as discussed in Chapter 3, groups impacts from thousands of material and energy flows into 14 mid-point impact categories: Human Toxicity, Respiratory Effects, Ionizing Radiation, Ozone Layer Depletion, Photochemical Oxidization, Aquatic Ecotoxicity, Aquatic Eutrophication, Terrestrial Acidification/Nutrification, Land Occupation, Global Warming, Non-renewable Energy, and Mineral Extraction (Humbert, Margni, & Jolliet, 2011; Jolliet et al., 2003). Most LCA methods also provide guidance for decision makers to apply weighting and 26 normalization factors to consolidate these impacts into end-point, or damage, categories. In the case of IMPACT 2002+ the damage categories are: • Climate Change: Characterized by carbon dioxide equivalents emitted into the air over a 100-year time frame (kg CO2e). • Human Health: Characterized by disability adjusted life years (DALY). This category applies a mortality (years of life lost) and morbidity (quality of life lost) value to substances that have a health impact on humans through disease. One DALY represents one year of life lost over the general population. • Ecosystem Quality: Characterized by the potentially disappeared fraction of species over a certain area during a certain time per mass of an emitted substance (PDF·m2·yr). 0.1 PDF/m2·yr represents the loss of 10% of a species on one m2 of earth surface per year. • Resources: Characterized by megajoules of primary energy (MJ/unit consumed), both mineral extraction and non-renewable energy use are represented.  Midpoint categories have been defined as “a parameter in a cause-effect chain or network (environmental mechanism) for a particular impact category that is between the inventory data and the category endpoints” (Bare, Hofstetter, Pennington, & de Haes, 2000). These impacts are characterized as potential impacts, rather than actual impacts, to help us better understand how the environment may be damaged by our activities. For example, climate change impact category might use a 20, 100, or 500-year time horizon to model potential environmental impacts of GHG emissions. End-point damage categories represent stressors at the end of a cause-effect chain and reflect society’s understanding of a final effect. For 27 example, high levels of phosphate and nitrate emissions may lead to eutrophication (midpoint) on a body of water, which in turn can be represented as an overall reduction in ecosystem quality (endpoint). End-point categories have higher uncertainty than mid-point categories, however they offer simpler interpretation and decision-making (Reap, Roman, Duncan, & Bras, 2008b).  2.2.1.4 Phase 4: Interpretation The final phase of an LCA interprets the results of the inventory and environmental impact assessment relative to the goals of the study. Interpretation should be considered an iterative process which informs the other three phases throughout. According to ISO 14044 (2006b), the interpretation phase should consider the following elements: • Identify significant issues arising from the inventory analysis and impact assessment phases. • Regularly evaluate completeness, sensitivity, and consistency. • Disclose conclusions, limitations, and recommendations.  2.2.2 Applicability of LCA This section discusses considerations for the application of LCA as a method for environmental impact assessment. LCA typically addresses the environmental aspect of sustainability. There are also life cycle-based approaches that address the economic and social spheres, such as Life Cycle Management (LCM), Life Cycle Costing (LCC), Social LCA (S-LCA), and Ecological LCA (Eco-LCA) (Finnveden & Moberg, 2005). Of these, LCAs and LCCs are arguably the most developed in terms of methodology. The two 28 approaches are complementary, but cannot be used interchangeably because there are fundamental methodological differences regarding system boundaries, time perspectives, and calculation procedures (Guinée et al., 2011). S-LCA (Benoît et al., 2010) and Eco-LCA (Zhang, Singh, & Bakshi, 2010) hold promise but are still in an early stage of development.  LCA is gaining widespread acceptance as a robust method for modeling and interpreting environmental impacts of a product or service from cradle to grave (Finnveden et al., 2009). As such, it is used for a wide range of applications including evaluating business strategies, product and process design, environmental labeling, and environmental product declarations (Baumann & Tillman, 2004). According to Robert Crawford (2008), “LCA is one of the best tools for environmental assessment of a range of products and services.” However, he cautions that it might be best suited for industrial processes. This may still be largely true because of how resource intensive LCA is with respect to data collection, analysis and interpretation. However, as databases and computing tools evolve, LCA holds promise for wider applications.  A key goal of this dissertation research is to explore whether the resource intensity of LCA can be reduced to a level that is reasonable for event managers. The application of LCA comes with important considerations, particularly when used on a smaller scale for sports events. There are nine such considerations that are discussed below in sub-sections 2.2.2.1 to 2.2.2.9. While not intractable, each concern needs to be addressed through further research and development, namely: uncertainty, accuracy, resource requirements, data requirements, appropriate impact categories, complexity, lack of sector-specific tools for LCA, lack of 29 geographic specificity, and limited coverage of environmental impacts. The low adoption rate and unfamiliarity among sports events may partly be a result of these factors.  2.2.2.1 Uncertainty As the statistician George E. P. Box (1987) said: “Essentially, all models are wrong, but some are useful” (p. 424). Dealing with questions of uncertainty is one of the main challenges of conducting an LCA and we must therefore recognize them and be explicit about the assumptions we make in the model. Uncertainties exist at all stages of conducting an LCA including modeling choices, defining system boundaries, gathering inventory data, calculating impacts, and interpreting the results. Various strategies have been developed to tackle this. At the Life Cycle Inventory (LCI) stage, for example, a Pedigree Matrix is recommended by Weidema (1998) to assign uncertainty values for data reliability. The Pedigree Matrix consists of a numerical score of 1–5 applied based on expert judgment to the data characteristics of: completeness, temporal correlation, geographical correlation, technological correlation, and sample size (Frischknecht et al., 2004). These uncertainty factors can then be statistically quantified as a contribution to the square of the geometric standard deviation. Uncertainty within cumulative LCI’s can also be statistically tested with Monte Carlo simulations – a statistical method that generates a random sample of results to observe the distribution of an unknown probabilistic entity. These statistical methods are useful to numerate uncertainty for some of the stages of an LCA listed above but much work still needs to be done before we can have a high degree of confidence in the results. It is also worth noting that while uncertainties around environmental impacts will always exist, this 30 uncertainty can be reduced by comparing two or more options with similar underlying assumptions – improving our ability to select one option relative to another.  Modeling choices is another factor that can significantly affect LCA results. A celebrated example of questionable boundary setting methodology was a study that showed the Hummer H3 as having lower per km energy use than a Toyota Prius (CNW Marketing Research, Inc., 2007). This result was roundly criticized by Gleick (2007), who demonstrated that the results were significantly skewed by, for example, applying the questionable vehicle life assumptions of 35 years for the Hummer and 12 for the Prius.  Tied to the issue of modeling choices is the difficulty of allocating environmental loads that are shared between activities, a hotly debated issue in the LCA community (Reap, Roman, Duncan, & Bras, 2008a). Allocation issues arise out of three scenarios: multiple inputs, multiple outputs, recycling and reuse (Baumann & Tillman, 2004). Allocation is generally done on economic or physical grounds (mass, volume, energy content, number of units) but other options include ownership (i.e., attributable to a process or event) and time. An example of a multiple inputs scenario for event transportation would be spectators flying on commercial planes along with passengers who are not affiliated with the event. In this case an allocation must be made to determine what portion of the flight impacts get attributed to the spectators, likely on a per person occupancy rate basis. In terms of multiple outputs, various products may end up in landfill (e.g., magazines, plastic cups, etc.) and therefore allocations of these end-of-life impacts need to be done, perhaps on a per mass basis. 31 With regards to the recycling scenario, two main solutions are usually suggested: closed loop, and open loop. The key difference here is whether to allocate recycling impacts to the product (good or service) under study or to the next product that makes use of these materials. In terms of reuse, a common event-based example might be a beach volleyball event that rents sand or temporary bleachers for a short time. In this case, it would make sense to only allocate a portion of the total life cycle impacts of these materials to the event, perhaps on a time of use basis.  The question of the most appropriate allocation methods specific to event-related factors has not been explored in the literature to any great extent and more research is needed before we can standardize event-based LCA approaches.  2.2.2.2 Limited Coverage of Environmental Impacts Not all environmental impacts are covered by an LCA. Commonly cited examples of impacts left out include noise, land use, biodiversity, and non-toxic human impacts among others (Finnveden, 2000; Jolliet et al., 2004). Another critique is the fact that LCAs primarily focus on abiotic materials such as energy and metallic minerals and do not actively assess natural resources depletion (Zhang et al., 2010). The concept of Ecosystems Services (ES) has grown in recent years with the aim of examining “the conditions and processes through which natural ecosystems, and the species that make them up, sustain and fulfill human life” (Daily, 1997). Events that seek to answer the question of site-specific interaction with natural ecosystems may be better suited to apply ES-based approaches (Reap et al., 2008b). While no LCA model can include everything, event organizers should specify which factors they 32 can or cannot effectively evaluate and should identify complementary methods where necessary to ensure that their assessments address local conditions and are appropriately comprehensive and sensitive to these conditions.  2.2.2.3 Accuracy The accuracy of LCA results is often questioned since the method requires building a model of environmental impacts, and necessarily relies on assumptions, cut-offs, and allocation choices since not every possible material can be included. The uncertainty can be very high, for example, regarding toxicity impacts (Finnveden et al., 2009). In order for LCA to be used as a basis for comparative purposes, therefore, investigators must understand the limitations and ensure that the same assumptions are being used with regards to key aspects such as system boundaries, data quality, impact methods, and allocation procedures (ISO, 2006b). In recent years, industry sectors have begun to utilize Environmental Product Declarations (EPD’s) for specific product categories as a way to publicly disclose their environmental performance in a consistent manner across producers of the same product (Borghi, 2012). An EPD label on a product is analogous to a nutrition label on food. EPD’s are typically created by “program operators” – usually government agencies, environmental agencies or standards bodies – and standardized in accordance with ISO 14025:2006, Environmental labels and declarations – Type III environmental declarations – Principles and procedures (ISO, 2006a). EPD’s should lead to greater consistency of approaches and greater confidence by policy makers and consumers since the approach is validated by multiple stakeholders.  33 2.2.2.4 Resource Requirements A full peer-reviewed LCA can take many months to complete and easily run over $50,000. The tools and datasets can also have significant cost-barriers. In terms of tools, some of the more sophisticated LCA software solutions such as SimaPro cost between $8,000 – 16,000 (“www.pre-sustainability.com,” n.d.). Datasets are also required to model the background data of the product under study. The ecoinvent 3.0 database, for example, contains over 4,000 datasets, costs approximately $3,500, and requires a substantial level of prior knowledge to interpret (“ecoinvent Centre,” n.d.).  Some events make use of the increasingly available free online carbon or ecological footprint calculators, some of which have event-specific metrics such as myclimate.ch, Julies Bicycle, and Bonneville Environmental Foundation. These free carbon calculators may be cheap and easy to use but they are criticized for being over-simplified, not methodologically transparent, and leading to often inaccurate and diverging results (Kenny & Gray, 2009; Padgett, Steinemann, Clarke, & Vandenbergh, 2008). As the availability of LCA-tools and databases increases, the financial costs and time to conduct studies will likely decrease over time.  2.2.2.5 Data Requirements LCA requires extensive data collection, which is often the most time-consuming part of conducting a study (Hendrickson et al., 2006). Organizations that do not already have data collection procedures in place will find this a significant hurdle. Access to the required data can also prove difficult. To investigate impacts of food sold at events, for example, data need 34 to be gathered from suppliers. This can be particularly challenging if suppliers are neither directly under their control nor invested in the process. Some organizations may also be reluctant to supply this information if they consider it sensitive in nature. Another important issue particularly relevant for events is that a significant contribution comes in the form of value in-kind, donations, partner agreements, or volunteer time and may therefore not be captured in a formal statement. Data collection will likely prove to be one of the biggest hurdles for events wishing to conduct environmental impact assessments. This may change as new sustainability event guidelines are developed and adopted, such as the Global Reporting Initiative - Event Organizer Supplement, which encourages events to track key economic, social, and environmental metrics (GRI, 2012).  2.2.2.6 Appropriate Impact Categories and LCA Methods Another issue facing event organizers is the selection of appropriate impact categories. According to the international standard on LCA “ISO 14044 does not specify any specific methodology or support the underlying value choices used to group the impact categories” (ISO, 2006b, p. 31). In practice, a few multiple and single-impact category methods are available that might be appropriate for events, each with its own benefits and drawbacks. This section discusses two commonly used single impact category LCA methods, carbon footprinting and ecological footprinting, and contrasts them with some commonly used multiple impact category LCA methods.  A carbon footprint is an LCA-derived method that refers to the single environmental impact category of climate change (also referred to as Global Warming Potential [GWP]) of a 35 defined activity resulting from associated greenhouse gas (GHG) emissions over a given time horizon – usually 100 years (Wright, Kemp, & Williams, 2011). The potential impacts for major GHGs – in particular carbon dioxide, methane, and nitrous oxide – have been characterized by the United Nations Intergovernmental Panel on Climate Change (IPCC) into carbon equivalents providing a category indicator unit of measure in the mass of CO2 equivalents: kg CO2e (IPCC, 2007). The carbon footprint is arguably the most widely used single environmental impact category in the sports industry, with a host of mega events such as Vancouver 2010 and London 2012 Olympic Games and the FIFA World Cup 2010 integrating it in their environmental management strategies. The FIFA 2010 World Cup in South Africa, for example, estimated that the event contributed a total of 2 million tons additional carbon dioxide equivalent emissions (CO2e) with 65% due to international travel, 17% due to national travel, and 13% from accommodation energy use (Econ Pöyry, 2009). For events, the benefits of applying a carbon footprint approach are that it is: • a widely used benchmark for environmental impacts and therefore expertise, datasets, and resources are more easily available;  • fairly well known and can therefore easily be communicated to the public;  • applicable globally since global warming is not regionalized;  • supported by a strong consensus in the scientific community on the existence of the problem and on the characterization of impacts (IPCC, 2007).  There are some limitations to carbon footprinting. First, it does not compare potential trade-offs between different types of impacts such as climate change, human health, or water use, and may therefore lead to what Weidema et al. (2008) term “problem-shifting” – “solving 36 one environmental problem but creating a new one in the process” (p. 4). There is also currently no consistent method for how to conduct a carbon footprint assessment in terms of methods, scopes, and standards (Pandey, Agrawal, & Pandey, 2011; Wiedmann & Minx, 2008), although this concern is increasingly being addressed through efforts to harmonize the various protocols developed by the World Business Council on Sustainable Development (GHG Protocol), the British Standards Institute and the Carbon Trust (PAS 2050), and the International Standards Organization (e.g., ISO 14044 & 14064). Finally, although the characterization factors for carbon footprinting are relatively well accepted internationally compared to other impact categories, this should not serve as a rationale to ignore categories with higher levels of uncertainty. Indeed, if we choose not to use other categories based on the rationale that they are highly uncertain, this actually serves to increase the overall uncertainty of environmental impact estimates. Decision-makers should consider all environmental impacts of major concern, not just climate change because it might be more easily measured or assumed to be more reliable.  Another single indicator approach used by sports events is the Ecological Footprint. This method, originally developed at the University of British Columbia by Wackernagel and Rees (1996), measures the carrying capacity of the earth. It takes a similar approach to an EIO LCA in that it applies input-output measures to estimate the total human consumption of resources compared to the rate at which the planet can replace them. In this way it can calculate whether our activities are meeting or exceeding its regenerative capacity. The unit of measure is the bioproductive area in hectares required to maintain human consumption. A strength of this method is its ease in communicating overshoot in terms of the number of 37 planet earths required to support our activities, a unit that many people understand. According to the WWF Living Planet report, the human population currently exceeds our regenerative capacity by using the equivalent of 1.5 earths (WWF, 2010). London 2012 used the ecological footprint as a measure for achieving their sustainability platform of a “One Planet Olympics” (BioRegional & WWF, 2005). Collins et al. (2007) applied this assessment framework to measure the impact of the FA Cup international soccer match in Wales. They showed that spectators at the event increased their ecological footprint seven times over the daily average of a Welsh citizen. However, a number of researchers have discussed specific drawbacks of this method, including that i) it fails to capture the specificity of ecosystem factors such as land degradation and reduced biodiversity, ii) appropriate data are rarely at hand, and iii) scope and boundary issues are common as seen in the tendency to translate greenhouse gas (GHG) according to a per hectare of land unit which is less informative than mass-based CO2e units (Fiala, 2008; Mcmanus & Haughton, 2006).  To characterize and compare multiple environmental impacts of life cycle inventory processes, a number of LCA methods have been developed including CML, TRACI, ReCiPe, Eco-indicator 99, and IMPACT 2002+. The chief advantage of multiple impact category approaches is that they capture a range of impacts and allow us to compare trade-offs. For example, one product may have a higher impact in terms of climate change but a lower one in terms of human health. Although promising, evaluating trade-offs has challenges. There is still much debate about the best way to weight and normalize various impacts into equivalent units, and indeed each LCA method cited above takes its own approach to this (Finnveden et al., 2009). Finally, a significant consideration of this approach in the context of events is the 38 added complexity and difficulty of interpreting and communicating multiple results. Mettier et al. (2004) have suggested a communications strategy that differentiates “anchoring-and-adjustment” issues (the process of engaging complexity from the standpoint of an anchor point that is understood) from “scaling” issues (the challenge of relating quantitative information to personal experience without a normalized reference scale) when presenting stakeholders with complex information.  2.2.2.7 Complexity One of the primary difficulties of an LCA is its complexity. An LCA takes on the ambitious task of consolidating large systems of material and energy flows into a finite set of impacts useful for decision-makers. A small- to medium-sized event is unlikely to have either the financial resources or the requisite level of chemistry, engineering, and statistical expertise on-hand for a full-blown LCA. Besides the ongoing methodological and implementation challenges, communicating the results of an LCA is also complex for non-specialists as noted above. The public may be familiar with impact categories such as climate change or acid rain, but others such as eutrophication, acidification, photochemical smog, ecosystem quality, etc. are less well understood and difficult to explain in a few words. This complexity is perhaps one of the reasons why events tend to use methods that are simpler to calculate and communicate such as the single impact category carbon or ecological footprinting methods. However, as Finkbeiner (2009) has argued, the strict use of simplified approaches such as carbon footprinting may be useful and widely used, but there is a danger of oversimplification.  39 2.2.2.8 Lack of Sector-specific LCA Tools There currently exist no robust environmental impact methods or tools tailored to the sporting event sector. Software tools such as SimaPro and GaBi have become available over the past decade to help LCA practitioners carry out full LCAs by integrating massive datasets, offering multiple impact assessment methods, and performing statistical analyses. While these tools have significantly reduced the amount of time needed to perform an LCA, they still require expert users and familiarity with the data and processes. A few sector-specific LCA tools have been developed that include a pre-defined method and LCI so that practitioners can apply it to a specific project. For example, the building sector has developed a tool called Athena that can be applied to 95% of the building stock in North America.  While tools and databases have been developed and/or adapted for some government and business sectors, they do not readily lend themselves to use in the sport events sector because events exhibit different attributes. For example, most LCA methods focus on the manufacturing and construction sectors and the overarching impacts of the goods and facilities that are produced, consumed and eventually destroyed or recycled by these sectors. Sport events align more closely with the service sector although they make use of goods and facilities which relate to manufacturing and construction sectors. The main activity of events relates to public occasions that attract participants and offer a range of services including food, drink, transportation, housing and entertainment. It is not always clear who owns or controls event related services and activities. Moreover, LCA databases are not well developed for many service sectors such as food provision or hospitality. The lack of guidelines, tools, and LCA databases applicable to events and the related services sectors 40 makes it more difficult and resource intensive for event organizers to carry out rigorous and consistent impact assessments.  2.2.2.9 Geographic Specificity Tied to the issue of uncertainty is the lack of geographic specificity of both life cycle inventory data and impact assessment characterizations. LCA has not been taken up to the same degree in all countries. Expertise and inventory databases are available in a few countries notably including Switzerland, USA, the UK, the Netherlands, Denmark, Sweden, Japan, and Canada. In the absence of data specific to the region under study, LCA practitioners must make do with data from other regions. For example, the Swiss EcoInvent LCA database, one of the largest centralized LCA databases in the world, is widely used by practitioners in other countries. The problem here is that the data from one region may not be appropriate for another because the underlying processes or technologies may be different. How energy is produced makes a significant difference in the production of GHGs. For example, Switzerland and Canada have highly developed hydroelectric industries and capacity, but many other countries do not.  In addition, regional databases have not been fully standardized between countries, reducing our ability to apply consistent LCI data to assess e.g., a product being produced in one country but consumed in another. Significant work has been done in recent years to address this supported by the UNEP SETAC Life Cycle Initiative. The recently released ecoinvent 3.0 database includes far greater regional specificity, including, for example, energy grid data for many countries around the globe. A related challenge is the inherent trade-off between 41 accuracy and wider applicability. For example, events located in the City of Vancouver may choose to apply energy grid numbers from British Columbia (almost exclusively hydro-powered), whereas an event organizer in another part of Canada or the US might find it more appropriate for national level consistency to apply a Canadian (mostly hydro, coal, natural gas, and nuclear) or North American (higher % of coal) average mix even though this would potentially compromise the regional specificity of the results.  Another issue related to geographic specificity is the challenge of incorporating appropriate spatial variation when characterizing environmental impacts. While climate change and ozone depletion may be universally relevant, most impacts such as land use, water scarcity, or photochemical smog need to be adapted to regional scales, a fact that most LCA studies ignore (Reap et al., 2008b). New impact assessment methods such as IMPACT World+ incorporate greater spatial resolutions for impact assessment; however much work remains to be done in this area.  2.3 Sport Events and the Environment  2.3.1 Event Impacts, Leveraging and Legacy The IOC has adopted legacy planning as a guiding philosophy. In remarks to The Chicago Council on Global Affairs and The Economic Club of Chicago (2007), then President of the International Olympic Committee, Jacques Rogge, said “Legacy is our raison d’être. It ensures that the Olympic Games are more than metres and medals. The Games leave behind 42 a host of social, economic and environmental benefits. Legacy changes cities and countries. It builds a better world.”  Since the 1990’s, a growing body of literature has discussed impacts, leveraging, and legacies of mega events – predominantly sporting events (Chappelet, 2008; Gaffney, 2013; MacAloon, 2008; Masterman, 2004; VanWynsberghe, 2014). Much of this work relates to whether or how mega events can be leveraged to create positive long-term economic, societal, and environmental impacts.  The extent to which events can be used as a platform of positive sustainable change is a matter of debate (Chappelet, 2008; Preuss, 2007). On one hand, many impacts of events have not been demonstrably positive, and on the other hand, their ability to leverage wider change is as yet unproven. Mega events such as the 1992 Winter Olympic Games in Albertville, for example, have been portrayed as having significant negative impacts on the ecosystem from construction and transportation projects (Chappelet, 2008). Nevertheless, the argument is often put forward that these negative impacts can be offset by “nudging” stakeholders into wider action, leading to legacy benefits (Death, 2011). To determine whether an event has a net positive or negative impact, a number of researchers support the need for increased measurement of the sustainability of events (Getz, 2009; Hede, 2007; Preuss, 2004; Sherwood, 2007; Sherwood et al., 2005).  The emphasis on legacy and urban development may in part be a result of a series of mega-events that caused significant economic debts, environmental degradation, and misguided 43 infrastructure development1. On the other hand, Gold & Gold (2008) argue that cities such as London and Beijing used the Olympics not only to leave a positive social, economic, and environmental legacy but to become a regenerative force in the region, bringing needed roads, buildings, infrastructure, and environmental regulations: “The [London 2012 Games] bid (…) addressed the growing concern for sustainable legacy by using the mega-event as a vehicle for regenerating one of the largest areas of brownfield land in the London region” (p. 311).  Several reasons are often cited for why events may be amenable as vehicles for social or environmental change. Events: • are “symbols of power and ideology”, which may be harnessed to improve sustainability (Getz, 2009); • are “spatial-temporal phenomena” with each instance being unique, adding to the attraction of the event experience for participants (Getz, 2008); • bring people together and thereby engender a sense of community which can be leveraged for social change (Bladen, Wilde, Kennell, & Abson, 2012); • have an ability to inspire engagement and emotion through the creation of a liminoid space – a temporary state outside the norm of social structure (Chalip, 2006); • can have visibility and influence beyond the physical location of the event, i.e., through media and television (Mol, 2010).                                                  1 Oft-cited examples include: the Montreal 1976 Olympic Games had a debt of £692 million (Gratton, Dobson, & Shibli, 2000); the strong environmental critiques surrounding the Albertville 1992 Olympic Games (Lesjø, 2000); poorly used venues and infrastructure post the Athens 2004 Olympic Games (Gold & Gold, 2008). 44 Even with the renewed efforts to achieve positive legacies, some would argue that these lofty aims are not necessarily borne out. Chappelet (2008) suggests that mega events such as the Olympic Games suffer from “gigantism” – referring to the massive amounts of money spent on construction and transportation – and questions whether they would ever allow for the possibility of a sustainable event. Other studies have shown that the true impacts of large events are often underreported and that better measurement methodologies are needed to test and support their claims (Flyvbjerg, 2007; Getz, 2009). The literature is not limited to the Olympics. Death (2011) examined how effectively the 2010 FIFA South African World Cup mitigated its environmental footprint and “catalyzed a broader societal shift towards more sustainable pathways” (p. 101). He concludes that while the 2010 World Cup raised the profile of its sustainability actions through communication and performance measurement, it did not achieve substantial impact reductions. To do this more effectively in future, Death suggests they need to embed ES in the planning and design phase, involve key stakeholders, and formulate a clear and ambitious strategy.  2.3.2 Characteristics of Small and Medium Events Mega events such as the Olympic Games and the FIFA World Cup have the resources to hire internal and external sustainability experts. Most sport event organizers do not have the finances, expertise, or human resources to develop and implement comprehensive procedures. Without standardized, simplified and tailored management protocols and assessment methods, event organizers face a steep development and implementation curve. They not only risk wasting resources by reinventing the wheel, they also risk adopting ineffective policies and practices. If, however, it was possible for multiple small and medium 45 sized events to adopt proven standards and methods and easily assess priority areas such as energy consumption or transportation – and if this knowledge in turn could be channeled to positive change – the cumulative impact reduction could be significant. One issue in such an approach is how best to catalogue events and target ES issues, given high levels of variability across event types.  There have been a number of attempts to classify events by type. Bovy et al. (2003) apply geographic, temporal, and spatial characteristics including number of participants, location, duration, time of year, one-time/recurring, urban/rural, ticketed/non-ticketed, indoor/outdoor environment, permanent/temporary venue, mono-site/multi-site, and fixed location/moving location. Gratton, Dobson, & Shibli (2000) have attempted to classify events by economic importance; Getz (2008) utilizes audience type such as cultural, sporting, academic, etc., or tourism opportunities for the region depending on whether the event is local, regional, hallmark, or mega. The European Commission (2009) classifies enterprises by size based on number of employees or gross revenue. For example, organizations with less than 250 employees and a turnover under 50 million Euros are considered “medium” sized, whereas those with less than 50 employees and a turnover under 10 million Euros are “small”, and those with less than 10 employees and a budget under 2 million Euros are “micro.”  A key finding from these efforts is that small events make the up the vast majority of activities for a sport. For example, Figure 4 shows the “sport pyramid” of International Tennis Federation events for 2011 (ITF, n.d.) and their sanctioned professional events classified according to the European Commission small to medium enterprise definition. 46 “Micro” and “small” events are clearly the vast majority. Even for a highly professionalized and monetized sport like tennis, no events, including Wimbledon or the US Open, would fall in the “large” or “mega” category since no tennis event budget exceeds 50 million Euros. If we calculate total financial turnover based on the number of events using the upper budget cut-offs for each category and use a very conservative 10,000 Euros as an estimate for Amateur events, we can see that the overall financial impact of amateur or micro events is significantly larger than the small or medium category of events. 2,800 micro events might have an estimated total budget of 5,600 million Euros compared to only 200 million Euros for the four medium sized events. Similarly, mega-events like the World Cup or Olympic Games may well capture much of the public’s attention, however they make up only a small part of the overall sport event industry.   Figure 4: Number of International Tennis Federation events classified by the European Commission small-medium enterprise designation in 2011 and showing estimated turnover.  2.3.3 Environmental Sustainability Standards for Events In the business sector, several strategic management approaches focus on strategic planning to improve organizational performance such as the Kaplan and Norton’s Balanced Scorecard 1 sport4 tournaments20 tournaments2,800 tournamentsmillions—€200M€200M€5,600M€10,000MITFMediumeventsSmall eventsMicro eventsAmateur events47 or the Baldrige model (Kaplan & Norton, 1992; Pojasek, 2000). Robert Pojasek claims that these models are effective in embedding environmental performance factors within strategic management, however they do not provide prescriptive guidance on what specific actions should be taken regarding the environment (Pojasek, 2001). The ISO 14001 Environmental Management System (ISO, 2004) attempts to tackle this by providing a management standard focused on the environment. It was followed by another management standard, ISO 26000 Guidance on Social Responsibility (ISO, 2010), emphasizing social sustainability. The Global Reporting Initiative (GRI) takes another approach to standardization by creating a sustainability reporting guidance mechanism – seen as an extension of financial accounting reporting standards.  Increasingly, standards bodies have been extending their ES guidance further to incorporate  sustainability management and reporting guidelines specific to the event industry. Prominent examples include: BSI 8901 (BSI, 2007), CSA Z2010 (CSA, 2010), GRI – Event Sector Supplement (GRI, 2012), and ISO 20121 Sustainability in Event Management (ISO, 2012). There has also been a growing effort by large events such as the Olympic Games and the FIFA World Cup to embed sustainability management and reporting in their organizational structure. All Olympic and Paralympic Games Organizing Committees since Lillehammer in 1994 have explicitly included an environmental component in their planning and reporting. Public sustainability commitments have been published by the Organizing Committees of Olympic and Paralympic Games for Torino 2006 (TOROC, 2006), Vancouver 2010 (VANOC, 2010), and London 2012 (LOCOG, 2012). Each makes progressively more 48 ambitious public commitments suggesting they are driving economic, environmental, and social sustainability agendas to new heights (Hayes & Horne, 2011).  As I discuss in Section 1.3, there is growing critique in the literature about exaggerated rhetoric by sport event organizers that they are being environmentally sustainable. This often involves either promises made during the bidding or planning phase about achieving positive legacies which are not born out, or discrepancies that surface between public claims of sustainability and the reality witnessed on the ground. Gaffney (2013), for example, cites the Golf course built for the 2016 Olympic Games in Rio de Janeiro as an example of a project where organizers claimed to incorporate sustainability considerations but in reality, the project led to degradation of a sensitive natural environment. Gaffney also critiques mega events for having such short planning cycles that there is little time for stakeholders to critique or hold organizers to account. It is important to note that most ES guidelines for events are meant to assist organizers with embedding sustainability planning and evaluation but most will caution that statements of conformance should not be conflated with statements of absolute achievements of ES. This disconnect can lead to an issue of authenticity where the reality does not live up to the stated goals. Without objective and commonly agreed-to measures, it is difficult to assess if an event is being environmentally sustainable, whether in terms of its own merit or in relation to other events.  No standard exists at present for how to carry out environmental impact assessments of events. As a result, the methodologies, scope and performance indicators employed by sport events vary greatly (Hiller, 1998; Preuss, 2007; Sherwood et al., 2005). For example, the 49 2006 and 2010 Olympic and Paralympic Winter Games Organizing Committees both claimed to be “carbon neutral,” but their scope and parameters were self-defined and differed on factors such as time-line, stakeholder impacts, and offsetting requirements. Major events and sporting governing bodies such as the NHL (National Hockey League, 2014), FIFA World Cup (see for e.g., FIFA, 2013), and the Olympic Games (see for e.g., VANOC, 2010), have started to publish sustainability reports which include environmental impact assessment metrics. The quantitative analysis of environmental impacts is largely limited to carbon footprinting and the explanations of methodology and results vary significantly in their detail. Few include third party verification of the approach or of the results as an LCA study conducted in conformance with ISO 14044 standard would need. A notable exception is the carbon footprint study carried out by the London 2012 Organizing Committee which was developed and verified with third party groups. The London 2012 Carbon footprint study: Methodology and reference footprint (LOCOG, 2010) publication is a significant step forward in terms of transparency and robustness for an event-based approach to environmental impact assessment, and will surely inform future development of standardized approaches for events.   50 2.3.4 “What Gets Measured Gets Done” (…) the attainment of a sustainable and responsible events sector will require the institutionalization of a new paradigm, one that employs a triple-bottom-line (TBL) approach both to the determination of the worth of events and to evaluation of their impacts (Getz, 2009, p. 62).  This section explores the literature on event management, organizational management, and environmental assessment with regards to sustainability planning and assessment. The management axiom “what gets measured gets done” is, according to Behn (2003), one of the most widely used phrases tied to performance measurement. However, Behn cautions that measurement for its own sake may not be effective and that the area of measurement should also be linked to the implementation of the overall strategy and objectives of the organization. For example, managers may measure the wrong things and/or oversimplify them (Behn, 2003). Otley (2003) suggests that the measure itself may become the focus of attention rather than the organizational factors and considerations underlying it. Similarly, over-measurement may lead to “paralysis by analysis” (Otley, 2003, p. 319). Kaplan and Norton (1992), originators of the widely adopted Balanced Scorecard strategic planning and management system, also argue that measurements tied to objectives are more effective in achieving managerial action than measurements isolated from objectives.  Drawing on the management literature, Plaut et al. (2012) categorize environmentally “green” tools as either product- or process-based: product-based approaches measure the performance of the end result of the object or activity in question; process-based approaches 51 enable decision-making and human interaction – what Cole (2011) also refers to as “guiding design.” The organizational management literature suggests that the consideration of both product-based measurement and process-based approaches is more effective in improving organizational performance than one approach in isolation (see for e.g., Kolk & Mauser, 2002). Within the event management literature, Bladen et al. (2012) argue that evaluating an event’s impacts through quantitative or qualitative data sources is a product-based approach and should be tied to an “ongoing process,” or strategy, since it is a critical part of event management. Similarly, Chalip (2006) says that the measurement of event “impacts” is product-oriented, and should be differentiated from measures of process. This suggests that unless product- and process-based approaches are linked when it comes to ES in events, evaluating impacts on its own will not lead to effective change.  Pojasek (2012) cautions that virtually all existing sustainability guidance systems and standards employ “lagging” indicators rather than “leading” indicators and that both should be combined to support effective performance. In Pojasek’s terms, leading indicators are “process-based forward-strategy” approaches and lagging indicators are “backward-looking outcome-based” measures. Examples of leading indicators in an event management context include the incorporation of ES as a guiding principle for event planning, a commitment to public reporting, or the inclusion of ES in the title of a senior staff position in the organization. Lagging indicators are usually quantifiable measures that already occurred such as GHG emissions, financial accounting, or number of sustainability commitments achieved. Similarly, Kolk & Mauser (2002) suggest using leading and lagging indicators to incorporate both process- and outcome-based approaches in performance planning and stress the 52 difference in purpose. They note that lagging indicators are more often used because they are easier to assess and summarize since they employ concrete, post-hoc measures. Leading indicators, by comparison, are often less exact, but may actually lead to more embedded change since they are focused on internal practices and efforts that are intended to improve future performance.   It must also be acknowledged that the distinctions between leading and lagging and process and outcome are not entirely clear-cut, and depend on how measurement systems are used. LCA, for example, is generally considered a tool for an outcome or product-based system of analysis, but it is often used in a process-based manner to inform management strategy regarding the chain of activities and associated costs in production, consumption, maintenance and disposal or reuse, spanning geographical and causal cradle to grave (or cradle to cradle) relationships. Indeed according to the International Standards Organization (2006b): “the information developed in an LCA or LCI study can be used as part of a much more comprehensive decision process” (p. vi). Assessment tools like LCA can be used to investigate environmental issues during active decision-making (aka “under the hood”) to improve timely data collection and assessment, stakeholder buy-in, and alignment of management goals and efforts with organizational objectives. An LCA also has potential outward facing promotional benefits for the organization by helping to inform clients and stakeholders about the environmental pedigree of a product or service. The greater value, however, is arguably in giving the planners insights into how each step of the process can be improved.  53 2.3.5 Use of LCA in Sports Events Few events have adopted LCA to evaluate their events. Measuring the impact of sports events is a relatively new endeavour and therefore it is not surprising that early adopters have used qualitative criteria or simpler carbon or ecological footprinting based on input-output approaches (Jones, 2008). There are some exceptions. For example, the City of Lausanne, Switzerland embedded the use of a multiple impact category LCA into the planning process of the 2011 World Gymnaestrada; an event with 20,000 athletes (“World Gymnaestrada Lausanne 2011,” n.d.). Mega events such as the London 2012 Olympic Games have also begun to use LCA, particularly for their venues. For LCA to be widely adopted by events, the LCA community needs to increase coherence and reduce confusion surrounding current approaches commonly used including carbon footprints, ecological footprints, and multiple impact category LCAs. They will also need to devise ways to disseminate their results in ways that speak clearly and authentically to the public.  More research is also needed to understand the considerations and requirements for applying LCA in a sport event context. Few if any events have applied LCA methods to give deeper insights into up and downstream environmental impacts, choosing most often to report on impacts based on cost and ownership boundaries as suggested, for example, in the GHG Protocol Guidelines (WBCSD & WRI, 2004). Pandey et al. (2011) have suggested that standardization is a critical issue for events because the absence of a framework for applying consistent scopes and boundaries regarding emissions may lead to inconsistencies in reporting. For example, one event may include spectator travel and another may not.  54 Even though monitoring environmental impacts might be beneficial for small to medium sized sport events, in practical terms only events with significant budgets and internal expertise are likely to be willing to invest in more rigorous environmental impact assessments such as LCA-based methods unless the costs can be brought down. In a case study conducted by Mallen et al. (2010), organizers of a major international multi-sport event identified a lack of resource allocation to environmental performance as a major structural barrier to advancing their sustainability agenda. New governance requirements and heightened awareness by the events sector of the need to incorporate sustainability assessment may increase demand and willingness to invest in more robust impact assessment methods. There are recent examples of this in jurisdictions such as British Columbia where a Carbon Tax has sought to strengthen the business case for measuring and reducing GHG emissions (Province of British Columbia, 2008).  The research in this dissertation takes an LCA approach to measure the environmental impacts of sport events for four main reasons. Firstly, an LCA provides a holistic approach where the scope of analysis can incorporate the upstream and downstream impacts of event-related goods and services as well as facilities and transportation. Secondly, this approach is useful for assessing multiple environmental impact categories. Thirdly, there now exist large databases of life cycle inventory (LCI) data, allowing for practical estimates of impacts when primary data are not available. Finally, the fact that LCA is becoming an industry standard for products means that there will be strong scientific and industrial support for this approach.  55 Chapter 3: Research Questions  3.1 Thesis Goal Statement The goal of this research is to analyze the explanatory power and use-value of LCA in examining the environmental impacts of small to medium events and explore how it might be adapted to better assist event organizers to plan more sustainable events.  3.2 Research Questions • How might LCA methods inform and provide use-value to organizers of small to medium events in measuring their environmental impacts? • What are the significant environmental impacts and opportunities for impact reduction of small to medium sized university varsity sport league events?  • What are the significant environmental impacts and opportunities for impact reduction of small to medium sized multi-sport events? • How might LCA contribute to more sustainable sport events?  3.3 Research Objectives • Develop an LCA approach to assess the environmental impacts of small to medium events in key organizational areas. • Identify critical considerations, assumptions, and data sources to inform how LCA’s can be conducted on events and used by event organizers. • Undertake case studies on two small to medium events in order to identify opportunities to improve the environmental impacts of sporting events.  56  3.4 Assumptions This research makes several assumptions: • Events can be planned in a more sustainable manner if managers have access to appropriate tools to assess environmental impacts. • While LCA is analyzed as one type of approach that holds promise for events, this research does not seek to make direct comparisons of the use-value of this method against other potential approaches. • While the patterns of environmental impacts of small to medium sized events are discussed in the context of large events, this research does not specifically assess the relative impacts of such events based on size. Similarly, because there is significant variation in the individual characteristics of events, it is understood that the results of this research will not necessarily be generalizable to other events whether of a similar size, sport or purpose. • While many social and economic impacts are important when assessing the sustainability of events, this research is focused primarily on environmental factors. 57 Chapter 4: Methods  The research for this dissertation applied an embedded multiple-case study design (Yin, 2009) focusing on two case studies of sports events at the University of British Columbia. The first case study is the UBC Athletics & Recreation (UBC Athletics) varsity 2011–2012 athletic season. The second is the Special Olympics Canada 2014 Summer Games (hereafter referred to as SOC 2014) hosted in Vancouver primarily on the UBC campus on July 8–12, 2014. Within each case, this research employs multiple units of analysis, namely environmental impacts are grouped into organizational areas: transportation, food & beverage, accommodation, venue construction and operation, communication, and waste.  4.1 Research Design: Case Study Yin classifies case study research design as either single or multiple case studies and as either holistic or embedded case studies. Single case studies examine one context while multiple case studies look at more than one context. The term holistic distinguishes case studies that examine a context as a single unit of analysis, while embedded approaches examine multiple units of analysis within a given context. In each case, I have considered the event as an individual context and identified a number of embedded units of analysis within each context, therefore taking an embedded multiple-case study design approach.  The case study approach was selected because it allows an in-depth look at the patterns of individual cases and uses a variety of evidence sources to draw conclusions. Case study research has been defined by VanWynsberghe & Khan (2008) as “a transparadigmatic and 58 transdisciplinary heuristic that involves the careful delineation of the phenomena for which evidence is being collected (event, concept, program, process, etc.)” (p. 80). Events by their nature are highly transitory and often exhibit non-uniform characteristics, making study of their characteristics challenging compared to other phenomena that can be accommodated in an experimental design with control groups. An interdisciplinary case study approach to events has promise in that it allows for a rich understanding of the event as a single case. Additionally, according to Yin (2009),  case study inquiry:  • copes with the technically distinctive situation in which there will be many more variables of interest than data points, and as one result • relies on multiple sources of evidence, with data needing to converge in a triangulating fashion, and as another result • benefits from the prior development of theoretical propositions to guide data collection and analysis (p. 18).  The case studies for this research each used a predominantly descriptive research design to address the research questions. To help ensure the validity of this approach, I applied a number of quality controls outlined by Yin (2009). First, I used multiple sources of evidence in order to assess the research questions under investigation. Primarily these consisted of: quantitative modeling based on archival and collected data, documentation, and direct observation. Secondly, the two case studies themselves were intended to broaden the scope and relevance of the results, even while recognizing that each study had differing units of 59 analysis that would limit statistical comparisons and restrict the generalizability of the findings. Accordingly, each case study was approached separately, with the understanding that there might still emerge common patterns in the results that could reflect back on the robustness and validity of the theoretical and methodological approach operationalized in the research. Thirdly, to improve the reliability of the study, a clear set of investigative procedures was developed, largely drawing on LCA protocols.  4.2 Overview of Case Studies  4.2.1 Case 1: UBC Thunderbirds Teams, Events, and Venues The first case study was carried out from September – December, 2011 under the auspices of a research internship that partnered Quantis Intl. with the UBC Athletics & Recreation (Athletics) department and was supported by MITACS. Quantis Intl. is an environmental impact assessment company specializing in LCA. The four-month internship was funded by a Canadian MITACS Accelerate grant and had matching financial support from Quantis Intl. and UBC Athletics.  This case study modeled impacts of UBC Athletics’ 500 sports events, 10 sports facilities, and 24 varsity sports teams over one varsity season. The aim was to design an environmental impact assessment framework based on LCA methods appropriate for small to medium events held at the UBC campus. Venues included an ice hockey arena, an aquatic centre, outdoor stadiums, a rowing centre, a tennis centre, and indoor gymnasiums. UBC Athletics has a comprehensive men’s and women’s sports program that encompasses: baseball, 60 basketball, cross-country, field hockey, football, golf, ice hockey, rowing, rugby, skiing, soccer, softball, swimming, track, and volleyball. Spectator attendance at individual events ranged between 100 – 3,000 people. Total annual spectator attendance was estimated at approximately 40,000 person-visits determined through UBC Athletics data for athletes and staff and through event ticketing and survey samples for spectators.  4.2.2 Case 2: Special Olympics Canada 2014 Summer Games The second case study assessed the environmental impacts of the Special Olympics Canada 2014 Summer Games, which took place in Vancouver, BC from July 8–12, 2014. The event saw approximately 1,800 athletes, coaches, and officials from across Canada participating in 11 sports taking place at nine sporting venues. All competition and accommodation venues were located at UBC except golf, which took place at the University Golf Club in Vancouver, and bowling, which took place at the Zone Bowling Centre in the City of Richmond. This five-day event had an operating budget of approximately $2,250,000 (Somerville & Taylor, 2014). Total spectator attendance was estimated at 7,600 person-visits based on event registration for staff and participants and surveys samples for spectators. The event was organized by the 2014 Special Olympics Canada Summer Games Society, a not-for-profit entity created solely for the purpose of implementing this event.  4.3 Geographic Context and Site of Research The Province of British Columbia, the City of Vancouver, and the University of British Columbia (UBC) offer a supportive context for ES events organized within their respective jurisdictions because sustainability and climate change policies are already in place. The 61 Province has taken a strong leadership position in North America with respect to climate change policy. It passed Bill-44 (2007), a binding legal commitment to reduce Greenhouse Gases by 33% below 2007 levels by 2020; and in 2010 a mandate on carbon neutrality and emissions reporting for its public institutions – including provincial ministries and agencies, schools, colleges, universities, health authorities and crown corporations. This was followed in 2008 by Bill-37 (2008), implementing a revenue-neutral tax on GHG emissions from fuels burned in the Province.  The City of Vancouver has a stated aim of becoming the Greenest City in the World by 2020 with an action plan encompassing a green economy, carbon, buildings, transportation, waste, access to nature, ecological footprint, water, air, and food (City of Vancouver, 2012). They have set a GHG emission reduction target of 5% from 1990 levels.  UBC is subject to the provincial requirements to pay tax on fuel use and offset its GHG emissions. Beyond this, in 2010 it set some of the most aggressive climate change targets among top 40 ranked universities in the world, aiming to reduce greenhouse gas (GHG) emissions 33% below the 2007 benchmark level by 2015, 67% by 2020 and 100% by 2050 (UBC, 2010). UBC has also embedded sustainability as one of its nine strategic commitments and signed a number of influential environmental sustainability commitments for higher education institutions including the Talloires Declaration in 1990, the Halifax Declaration in 1991, and the 1998 Climate Change Statement of Action for Canada.  62 In the context of events taking place in British Columbia, direct fuel consumption attributed to building operations and event organizer vehicle travel is covered under the GHG mandates. Other impacts arising from out-of-province air travel, livestock production, or material production, for example, do not fall under these mandates and generally go unmeasured. It is worth noting that neither the Province, the City, nor UBC have specific requirements or impact assessment methods tailored to events.  4.4 Research Method: Life Cycle Assessment This research applied an LCA method that followed the procedures laid out in the ISO 14044 Environmental management – Life cycle assessment – Requirements and guidelines (ISO, 2006b) to quantitatively assess the major environmental impacts of the events in each case study. The assessment framework encompassed multiple environmental impact categories including: global warming, resource use, human health, and ecosystems quality using the IMPACT 2002+ method (Jolliet et al., 2003). For each case study, these impact categories were applied to the event-specific organizational areas of: transportation, food & beverage, accommodation, venue construction and operation, communication, and waste. The choice of organizational areas largely drew on the categorization used in event sustainability management standards (BSI, 2007; CSA, 2010).  The remainder of this chapter lays out the ISO 14044 standard procedures on which each case study draws for its methodological approach.  63 4.4.1 Goals of the study According to ISO 14044, the goals of an LCA study need to be clearly stated and encompass the intended application of the method, the reasons the study is being conducted, the intended audience for the results, and whether public assertions comparing the performance between two or more products or services will be made.  A principal aim of the first case study was to find an economical and rigorous way to identify major impacts resulting from the activities of UBC Athletics’ operations, stakeholders, and supply chain. The specific purposes for undertaking this study were 1) to test the suitability of LCA to quantify the environmental contributions of the 2011/2012 UBC varsity athletics events; and 2) to create event organizational area-based indicators (e.g. accommodation and transportation) using available event activity data, for potential use by future events.  The aim of the second case study was similar, notably to find an economical and rigorous way to identify major impacts resulting from the activities of SOC 2014 Games operations, stakeholders, and supply chain. The specific purposes for undertaking this study were to 1) quantify the environmental contributions of a small to medium sized multi-sport event with an LCA approach; and 2) seek opportunities for event impact reduction.  4.4.2 Functional Unit The functional unit translates the inputs and outputs of the product system into a measurable reference point as a basis for comparison (e.g. 1 year, 1 kg, $1, 1 m2). The functional unit for each case study was, respectively: 64 • The provision of an entertainment / athletic experience to participants of the UBC Athletics Thunderbird sports events for the period of 2011/12 season. • The provision of an entertainment / athletic experience to participants of the Special Olympics Canada 2014 Summer Games for the period of July 8 – 12, 2014.  This unit divides activity data into seven indicators based on relevant organizational areas for event planners that are common to most events:  • travel • venues • waste • accommodation • food • communication • office & management  The office and management organizational area was not included in the SOC 2014 case as these impacts were all captured within the venues organizational area.  4.4.3 Product System Boundary The system boundary of a product or service under study “separates the system to be studied from the rest of the technosphere and the environment” (Klöpffer, 2014). The choices of which unit processes are included, and which approaches – whether attributional or consequential – are taken in the LCA, need to be consistent with the goals of the study. This 65 system boundary is often depicted using a process flow diagram that shows the functions which are included and excluded as well as their inter-relationships. Typically, it includes the sources of raw materials or intermediate products, the transformations and operations that occur, and the end of life of the process.  A system boundary diagram is challenging to prepare for an event as it represents the aggregation of many sub-unit processes such as food ingredients, energy sources, and venue materials. The system boundary for each unit process is already defined in the EcoInvent dataset that was used in the two case studies, however some additional broad system boundary implications for study are described below.  Both case studies include major direct and indirect environmental impacts for all life cycle stages (cradle to grave) for each organizational area of the event. Both cases applied a 99% cut-off criterion. Through initial estimates and regular sensitivity checks, all inputs and outputs estimated to contribute an impact of greater than 1% to the total impact were included.  Specific areas under review for the UBC Athletics & Recreation Thunderbirds case study occurring September 2011 – August 2012 included: • All Thunderbirds events and activities organized by UBC Athletics. • All UBC Athletics owned and managed sports venues used for varsity activities. 66 • For home games occurring at UBC, spectator, staff, and team (both UBC and their opponents) travel, accommodation, food, waste, communication, and office activities were counted. • For away games, only the UBC team travel and accommodation was included. • Spectators included sponsors, media, and guests.  Specific areas under review for the Special Olympics Canada 2014 Summer Games occurring July 8 – 12, 2014 included: • All events and event-related activities organized by the Games Organizing Committee. • Use of sports venues for the period of the Games. • Team member, spectators, and staff on-site travel, accommodation, food, waste, communication, and office activities were counted. • Spectators included friends and family members, sponsors, media, and guests.  4.4.4 Primary Functions of the Product System The function of the system for both case studies was two-fold: (a) to provide an entertainment experience to spectators and (b) a competitive athletic experience to team members. In order to do this, the event organizers had to ensure a minimum level of comfort and safety, suitable accommodation and transportation options, and provide an excellent event experience to all attendees.  67 4.4.5 LCA Assessment Methods Section 2.2.1 introduced Attributional LCA, which deals with the impact of goods and services that can be attributed to an event, and Consequential LCA, which would include the effects that the event has on the configuration of the larger system. The present studies followed procedures for an Attributional LCA in order to describe the actual environmental components of the system. No consequential impacts were considered since the events were small in scope and unlikely to affect broader environmental impacts on the overall Canadian economy nor the markets for specific products and services which is the usual test for a Consequential approach.  4.4.6 LCA Inventory Data Sources Environmental impact/emission factors apply activity data using primarily unit process data (individual material impacts). Where this information is not readily available, however, input-output data (impacts by economic sector) can be substituted or added to supplement available material impacts data (Finnveden et al., 2009). Environmental impact/emission factors for the study were derived from a number of sources including: • EcoInvent Data Life Cycle Inventory – provides LCI data across Europe with over 4,000 datasets in areas including transport, energy supply, materials, and agriculture. • Country specific databases including Environment Canada, the US EPA (Environmental Protection Agency), DEFRA (UK Department for Environment Food and Rural Affairs), and FOEN (Swiss Federal Office for the Environment). • Region specific databases including BC Ministry of Environment, the City of Vancouver, and UBC. 68 • Carnegie Mellon Economic Input-Output Life Cycle Assessment Estimator – provides GHG emissions for economic sectors in Canada, the US, and some European Countries. • Scientific literature and LCA studies.  4.4.7 Data Collection and Impact Assessments by Event Organizational Area Appendix A  and Appendix B  outline the data collection and impact assessment methods by organizational area applied for the UBC Athletics case study and the SOC 2014 case study respectively. While units of analysis and data collection procedures are as similar as possible, the characteristics of each event necessitate some adjustments; they are detailed where this is the case.  4.4.8 Sensitivity Analysis A sensitivity analysis illustrates how assumptions and parameters can influence the results and qualifies the robustness of recommendations. A sensitivity analysis was applied to test alternate assumptions on a number of key parameters. In Case Study one, these were: electricity grids applied (BC vs. CAN vs. NA); passenger travel occupancy rates; and venue allocation % to teams. In the SOC 2014 case study, these were: an examination of variable occupancy rates and associated emission factors; grouping travel distances in regions of city, regional district, province, and extra-provincial. For sensitivity analyses concerning environmental impact assumptions, the climate change damage category was used as it has the least uncertainty within the IMPACT 2002+ impact assessment method.  69 4.5 Limitations The chief purpose of each study was to assess the impacts of major event-related organizational activities and functions in each case. The results should not be taken outside of these contexts. A key limitation to the application of the study findings, therefore, is that the environmental damage categories in the two studies were selected according to their relevance to the case, and do not reflect categories that may be more relevant in other contexts – land use change for instance. Additionally, many of the environmental factors were taken from an LCA database for a European context. Where possible, efforts were made to represent a BC / Canadian context, however in some instances this was not possible due to data unavailability.  IMPACT 2002+ characterizes results as potential impacts rather than actual impacts in order for us to better understand how the environment may be damaged by our activities (i.e., the climate change category looks at a 100-year time horizon for the environmental impacts of GHG emissions). The IMPACT 2002+ results in particular should be interpreted and communicated cautiously therefore.  In addition, the study data are necessarily based on samples, averages, or assumptions using available data points. For the most significant impacts (travel and venues), increased effort was made to get detailed and specific data. The representativeness of impact assessment data is also a concern since there is limited applicable, current, and useful impact assessment data. Determining local food impacts is a common challenge, for example. A related limitation is data reliability. To deal with this, each unit process was assigned a quotient between one and 70 four to create a pedigree matrix to represent the quality of the data and assumptions (see Table 2). The matrix and choice of data quality indicators are adapted from an approach put forward by Weidema and Wesnaes (1996).  Data quality Reliability Representativeness 1 – High quality Specific validated or calculated data Good geographical and technological representativeness 2 – Acceptable quality Validated or calculated data from other source Geographical or technological lack of representativeness 3 – Low quality Qualified estimate Geographical and technological lack of representativeness 4 – Very low quality Rough estimation Proxy  Table 2: Pedigree matrix for inventory data  Given the broad scope of the two studies, delimitation was necessary and therefore some relevant factors may have been missed or over/under represented. As well, in some areas no data or only rough proxies were available. For example, the construction material impacts of venues were based on typical concrete, steel, or wood buildings. Sports venues likely have significant structural differences.  One of the imposed limitations of this research was the necessity of balancing accuracy of results with feasibility of data collection and assessment. As discussed above, small to medium sized events need to be able to efficiently obtain higher order results for a few key areas without overwhelming their limited staff and financial resources. Development of the assessment framework took account of this imperative and where possible utilized existing impact assessment databases. It also made use of results from other LCA studies or 71 environmental input-output approaches to ensure completeness when the unit process approach was either not feasible or had limited or insufficient data.  4.6 Self-reflection “However far [people] may extend [themselves] with [their] knowledge, however objective [they] may appear to [themselves] ultimately [they] reap nothing but [their] own biography” (Nietzsche, 1878/1984, p. 513).  As Nietzsche’s quote illustrates, my personal and professional experience in relation to this research undoubtedly coloured my approach, analysis, and conclusions. I have worked for over 10 years in the sport management industry with a focus on event management and environmental sustainability. In particular, I have been involved in the development of sustainability guidelines for sport. In 2007, while working at the AISTS (International Academy of Sports Science and Technology), I led the development of the “SportEco Management System” in partnership with the Swiss company EcoIntesys. SportEco was a management framework for sport organizations to measure the effectiveness of their environmental planning initiatives. In 2008, I co-authored the Sustainable Sport and Event Toolkit (SSET) in a partnership between the AISTS and the Vancouver Organizing Committee for the 2010 Olympic and Paralympic Winter Games and supported by the International Olympic Committee. The purpose of SSET was to provide guidance to sport governing bodies and events to operationalize sustainability. SSET also served as the seed document for a new Canadian Standard for organizers of sustainable events, for which I am a member of the technical committee. 72 Since coming to UBC in 2010 to begin my doctoral studies, I have been working for the UBC Centre for Sport and Sustainability on a variety of research and educational projects, largely related to the issues of environmental impact assessment of events. Most recently, I worked part-time as the Director of Special Olympics Initiatives for UBC to facilitate our hosting of the Special Olympics Canada 2014 Summer Games. My responsibility included overseeing implementation of sustainability aspects for the Games.  A personal observation that has shaped my research interests is the lack of environmental guidance for the sport industry based on empirical environmental assessment. When reflected upon, my experience as a practitioner and observer were useful in informing my research approach and providing access to data for analysis.  73 Chapter 5: UBC Athletics  5.1 Introduction A principal aim of this case study was to examine how Life Cycle Assessment methods might enable organizers of small to medium events to efficiently and cost effectively evaluate their environmental impacts and identify opportunities for reduction.  The first unit of analysis was the 2011/2012 season of varsity events and facilities that were managed by the UBC Athletics & Recreation department (UBC Athletics). The case study examined seven organizational areas typical of most events: food, office, waste, communication, travel, accommodation, and venues. The study used the IMPACT 2002+ LCA method to determine cradle to grave impacts across four damage categories and also normalized into a single score as the number of average Canadians per year contributing the same amount of environmental impact. The environmental impacts of UBC Athletics in this period were: • 8,300 tonnes CO2e for climate change. • 4.2 DALY (Disability Adjusted Life Years) for human health. • 2,100,000 PDF×m2×year (Potentially Disappeared Fraction) for ecosystems quality. • 140,000,000 MJ prim (primary non-renewable energy consumption and mineral extraction) for natural resources. • 790 points (Canadians contributing equivalent emissions per year)  74 Venues and travel contributed the dominant impact across all damage categories while the organizational areas of food, office, waste, communication, and accommodation combined were less than 5% of total across all damage categories.  This chapter begins with a section providing an overview of the methods, results, and implications related to the UBC Athletics venues organizational area because this was the dominant contributor in terms of annualized impacts for all four damage categories. Following that, the majority of the chapter consists of the full text of a published journal article by Dolf & Teehan (2015) which discusses the climate change impacts of participant travel. Participant travel was chosen for emphasis in this paper because it is area that events often try to assess, robust data were collected for this organizational area, and because it was considered a promising area to propose reduction solutions. Appendix A  incudes a summary of assumptions, data sources, results, and impacts for each of the seven organizational areas.  5.2 UBC Athletics Venues Venues were the dominant contributor to the overall environmental impact of the 2011/2012 season of varsity events and facilities that were managed by the UBC Athletics across all IMPACT 2002+ categories and normalized to the number of average Canadians per year contributing these impacts. Venues contributed: 72% for climate change, 74% for human health, 83% for ecosystems quality, and 75% for natural resources (see Figure 5).  75  Figure 5: Total annual environmental impacts for the UBC Thunderbirds 2011/2012 season normalized to the number of average Canadians per year contributing the same amount of environmental impact.  The UBC Thunderbirds varsity teams compete in 13 different venues at UBC that are wholly owned and operated by UBC Athletics: Aquatics Centre & Empire Pool (Swimming); Baseball diamond (Baseball); Doug Mitchell Thunderbird Arena (Ice Hockey); John M.S. Lecky Boathouse (Rowing); Rashpal Dhillon Oval (Track & Field); Student Recreation Centre (Multi-use); Thunderbird Stadium (American football); UBC Tennis Centre (Tennis); Varsity Soccer Field (Soccer); War Memorial Gym (Basketball & Volleyball); Warren Soccer Field (Soccer); Wolfson Fields and Rugby Pavilion (Rugby); Wright Field (Field Hockey). The Cross-Country Running, Skiing, Golf, and Softball teams do not have any events hosted at UBC and make use of external venues. These latter four venues were 0100200300400Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasAccommodationCommunicationFoodOfficeWasteTravelVenues76 considered out of scope because they are not owned or managed by UBC Athletics and because the few hours of use were estimated to be negligible contributors to the overall impact.  The annual operating impacts of each venue were calculated based on the usage of the preceding year: September 1, 2010 - September 1, 2011. The following data were collected for each venue from UBC Athletics and other relevant UBC departments: building area, building lifespan, predominant construction materials (e.g., wood, cement, or steel), energy use (electricity, fuel use), water use, and wastewater. Impacts include resource extraction, production, transportation, operation, and end-of-life impacts for construction, electricity, fuels, tap water, and wastewater for all venues. LCI data were primarily taken from the Swiss ecoinvent Life Cycle Inventory database v2.2 adapted for North America (“ecoinvent Centre,” n.d.). Appendix A.7 provides a summary of data collection methods and sources per venue.  Figure 6 shows the total climate change impacts for all UBC Athletics venues for the UBC Thunderbirds 2011/2012 season. The Aquatic Centre, Doug Mitchell Arena, and War Memorial Gym were the top three contributors for climate change, largely due to energy used for heating, cooling, lighting, and plug loads. Building facilities had significantly higher impacts than field venues across all impact categories, largely due to their higher energy needs and construction material impacts.  77  Figure 6: Total annual climate change impacts for all UBC Athletics venues for the UBC Thunderbirds 2011/2012 season.  Overall, energy consumption through electricity and fuel use was the largest source of environmental impacts for most venues and across most impact categories. The dominant venues in terms of environmental footprint were also multipurpose indoor venues which Rashpal Dhillon OvalWright Hockey FieldRugby Pavilion and FieldsWarren Soccer FieldVarsity Soccer FieldBaseball DiamondJohn Lecky BoathouseUBC Tennis CentreThunderbird StadiumStudent Recreation CentreWar Memorial GymDoug Mitchell ArenaAquatic Centre0 1,000 2,000 3,000tonnes CO2eAreasChemicalsWastewaterWasteWaterConstructionElectricityFuels78 housed competition areas, offices, and fitness facilities. At approximately 3,100 t CO2e, the Aquatic Centre had three times the impact of the next highest contributor in terms of climate change, and just slightly over the total impact of the other 12 venues put together. Outdoor sport field venues, while contributing a much smaller impact overall, showed construction as the largest contributor because they consumed relatively little energy. Chemicals used in the indoor pool contributed 6% of the total impact in terms of climate change. For all venues, the areas of water, wastewater, waste, and fertilizer use each contributed under 5% of the total.   Each venue varied significantly in terms of their pattern of impacts. Further details for the three venues with the highest climate change impact contribution and one artificial field are described below and shown in Figure 7 in order to illustrate this variability: • UBC Aquatic Centre is a concrete building built in 1978 housing an indoor and an outdoor pool with seating for 2,500 spectators and a surface area of 9,000 m2. Energy use for electricity and heating contribute the most for climate change and resource use categories. Construction materials contribute significantly to the human health and ecosystem quality impact categories. • UBC Doug Mitchell Arena is a wood and concrete building built in 2008 housing three indoor ice hockey rinks and office spaces. It has seating for 5,000 spectators and a surface area of 36,000 m2. Energy use for electricity and heating contribute the most across all environmental impact categories. • UBC War Memorial Gym is a concrete building built in 1950 housing an indoor basketball court and office spaces. It has seating for 2,800 spectators and a surface area of 13,000 m2. Energy use for electricity and heating contribute the most impact 79 to climate change and resource use categories. Construction materials contribute the most to the human health and ecosystem quality impact categories. • UBC Baseball Diamond is an artificial turf field built in 2008 with seating for 100 spectators and a surface area of 10,000 m2. Electricity is used for lighting and the artificial turf requires regular watering to stay moist. Construction materials dominate the contribution across all environmental impact categories.    Figure 7: Total environmental impacts for UBC Thunderbirds for the 2011/2012 season normalized to the average Canadian person’s impact per year for a) UBC Aquatic Centre, b) UBC Doug Mitchell Arena, c) UBC War Memorial Gym, d) UBC Baseball Diamond.  050100150Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasWaterWastewaterWasteChemicals−poolConstructionElectricity and heatinga) UBC Aquatic Centre010203040Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasWaterWastewaterWasteConstructionElectricity and heatingc) UBC War Memorial Gym01234Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasWater−irrigationFuel−fieldChemicals−fertilizerConstructionElectricityd) UBC Baseball Diamond010203040Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasWaterWastewaterWasteConstructionElectricity and heatingb) UBC Doug Mitchell Arena80 5.2.1 Methodological Considerations for Venue Impact Assessment Because UBC Athletics is the owner and operator of these venues, these results are based on one full year of operation, encompassing multiple events, training sessions, and use for other purposes over that time. Therefore 100% of venue impacts are allocated to UBC Athletics. However, if we allocate the impacts to a single varsity team or a single event they compete in, a portion of venue use could be allocated based on a number of factors. For example, if venues are used by multiple teams, if venues are rented out to external users for periods of time, or if some of the venue space is used for other purposes such as offices or classrooms.  A second consideration is the potential inaccuracy arising from estimating construction impacts based on three building archetypes within ecoinvent 2.2: wood, steel, and concrete buildings. These archetypes were used for venues with buildings both because material take-off data were not readily available and would have been time-consuming to calculate for all venues, and because initial estimates did not indicate that construction would be a major impact within venues. Sporting venues may vary significantly in their building material composition to these proxies, however, as they exhibit different construction characteristics from office buildings. For example, arenas and pools are built to accommodate large open viewing spaces and tightly stacked seating areas. More research is needed to find out how much variation there is among different types of sports facilities to determine whether better archetypes need to be developed. For synthetic fields, however, UBC Athletics provided construction estimates of the base layer and surface materials so these are likely to be more accurate.  81 To illustrate the sensitivity of allocation choices, Figure 8 shows the men’s ice hockey team results using an allocation of 5% of the annual Doug Mitchell Arena venue impacts and Figure 9 shows the women’s soccer team results using an allocation of 10% of Warren Field. Each chart shows the allocation alongside a mix of other allocation scenarios. The Ice Hockey Team is assigned a maximum of 50% of the venue because it shares the arena with the Women’s team.    Figure 8: Climate change contribution of Doug Mitchell Arena to men’s ice hockey team based on different allocation scenarios.  Allocation used−15%+15%+59%+134%02004006008000% 5% 10% 25% 50%Venue allocation %tonnes CO 2eAreasVenueWasteCommunicationFoodAccommodationOfficeTravel82  Figure 9: Climate change contribution of Warren Field to Women’s soccer team based on different allocation scenarios.  The results show that the type of venue and the venue allocation decisions can affect results significantly – in the case of the men’s ice hockey team, either decreasing the overall team impact by up to 15% or increasing it by up to 134%. For the women’s soccer team, the overall impacts could decrease by up to 4% or increase by up to 33%.  Overall, further study is needed to develop and test robust guidelines to assess venue impacts and support allocation choices. These results indicate that these allocation choices such as time or space allotted to a single event, series of league events, or to the organizing entity overall in the case of UBC Athletics, can change the overall event footprint substantially.  Allocation used−4% −2%+15%+33%03060901200% 5% 10% 50% 100%Venue allocation %tonnes CO 2eAreasVenueWasteCommunicationFoodAccommodationOfficeTravel83 5.3 Reducing the Carbon Footprint of Spectator and Team Travel at the University of British Columbia’s Varsity Sports Events The remainder of this Chapter incorporates the full text of a published journal article: Dolf, M., & Teehan, P. (2015). Reducing the carbon footprint of spectator and team travel at the University of British Columbia’s varsity sports events. Sport Management Review, 18(2), 244–255.  The carbon footprint of spectator and team impacts was analyzed at small-scale varsity sports events held at the University of British Columbia. Sport management literature suggests a need for quantitative environmental impact studies of events, in particular to seek out transport footprint reduction opportunities. This study applies a Life Cycle Assessment (LCA)-based approach to increase methodological rigour and transparency. We analyze event impact patterns of spectators and teams, with a particular emphasis on travel, and put forward several scenarios for impact reduction. Results show that UBC spectators had a smaller footprint than teams on a per person basis but a larger overall carbon footprint. Although only 4% of the spectators travelled by air, this constituted 52% of total spectator impact. We find the biggest opportunities for footprint reductions by spectators and teams alike are strategies that (a) reduce long-distance air travel, (b) increase vehicle occupancy rates, and (c) encourage low-emission travel mode choices.  5.3.1 Introduction  Climate change due to human activities is a pressing concern that could lead to extreme levels of social, ecological and economic disruption over the next century. The United 84 Nations Intergovernmental Panel on Climate Change (IPCC) said in its 2013 Climate Change Assessment Report Summary for Policy Makers:  Warming of the climate system is unequivocal, and since the 1950s, many of the observed changes are unprecedented over decades to millennia. The atmosphere and ocean have warmed, the amounts of snow and ice have diminished, sea level has risen, and the concentrations of greenhouse gases have increased (2013, p. 3).   The 2013 report further cautions: “Continued emissions of greenhouse gases will cause further warming and changes in all components of the climate system. Limiting climate change will require substantial and sustained reductions of greenhouse gas emissions” (p.13).  Along with other sectors of society, sport organizations need to address existing environmental issues and mitigate environmental harm. Sport can be both a contributor to environmental degradation and be directly impacted by its effects. Winter sports are a good example, where resorts suffer from shorted snow seasons due to climate change and yet contribute to the problem by using energy to make artificial snow (Scott et al., 2003). Air pollution levels are another oft-cited problem as evidenced by the concerns for athlete health surrounding the Beijing 2008 Olympic Games due to the high levels of particulate matter (Streets et al., 2007). A side effect of the globalisation of sport has been a growing contribution to environmental impacts, due in large part to the resulting increase in participant travel to events (Thibault, 2009).  85 Beyond addressing the environmental impacts caused by events themselves, a number of researchers have suggested that events are also worth investigating as an opportunity to leverage wider change because they are highly visible platforms that have the ability to galvanize action (Death, 2011; Getz, 2009). Sport managers and university athletics’ departments are taking a growing responsibility for climate change issues as they aim to improve the environmental sustainability of events and incorporate this messaging into stakeholder outreach (Mallen et al., 2010). Prominent recent examples include the low-carbon commitments of the London 2012 Olympic and Paralympic Summer Games (Hayes & Horne, 2011), the emergence of organizations such as the Green Sports Alliance for professional sports teams and college athletics departments, and the development and adoption of event sustainability management and reporting guidelines such as the International Standards Organization’s document, ISO 20121:2012 Event Sustainability Management Systems – Requirements with Guidance for Use (2012) and the Global Reporting Initiative’s Sustainability Reporting Guidelines & Event Organizers Sector Supplement (2012).  These guidelines refer to the broader concept of sustainability – most commonly understood as including three distinct but related spheres: society, economy, and environment. There exist many approaches to measuring sustainability, with most models designed to assess subsets rather than sustainability as a whole. A carbon footprint is typically understood as an approach to measure one type environmental impact: climate change, caused by the effect of greenhouse gas (GHG) emissions. Since climate change is one of our most pressing societal issues, carbon footprinting is an important arrow in the sport manager’s quiver and should be 86 considered alongside other important sustainability issues such as equity, water scarcity, affordability, or biodiversity.  The University of British Columbia sits in a regulatory context conducive to environmental sustainability and, in particular, to reducing greenhouse gas emissions. The Province of British Columbia has taken a strong leadership position in North America with respect to climate change policy. In 2007 it passed a binding legal commitment to reduce Greenhouse Gases to 33% below 2007 levels by 2020 as well as a mandate for its public institutions – including provincial ministries and agencies, schools, colleges, universities, health authorities and crown corporations – to become carbon neutral and report emissions. A 2008 bill added a revenue-neutral tax on GHG emissions from fuels burned in the Province.  UBC has embedded sustainability as one of its nine strategic commitments and signed environmental sustainability commitments for higher education institutions including the Talloires declaration in 1990, the Halifax Declaration in 1991, and the 1998 Climate Change Statement of Action for Canada. In 2010 it set some of the most aggressive climate change targets among top 40 ranked universities in the world, aiming to reduce greenhouse gas (GHG) emissions 33% below the 2007 benchmark level by 2015, 67% by 2020 and 100% by 2050 (UBC Sustainability Initiative, 2012).  One of the most direct implications for the UBC Athletics Department is the fact that direct fuel consumption from building operations falls within the provincial and public institution requirements to pay tax and offset fees on carbon emissions. Additional activities within 87 Athletics operations such as travel do not fall under this scope since the department is managed ancillary to the University. Further impacts such as those arising from out-of-province air travel, agricultural production of food, or material and equipment production, for example, also do not fall under current Provincial mandates and go unmeasured. UBC Athletics does not currently conduct in-house carbon footprinting on their activities.  At UBC – as with most North American universities – athletics form a major part of campus activities and operations, with over 20 sport venues including fields, stadiums, an aquatic centre, a tennis centre, indoor gymnasiums, fitness facilities, and ice hockey arenas. The UBC Athletics and Recreation department manages 23 varsity “Thunderbird” teams that travel across North America to participate in the Canadian Interuniversity Sport (CIS) league and the National Association of Intercollegiate Athletics (NAIA). The Thunderbirds teams compete in approximately 500 events per year, with one third typically hosted at UBC. Total annual attendance at all UBC home events in 2011–2012 season was approximately 40,000 spectators (Dolf, 2012). However, despite the campus-wide emissions reduction mandate, Athletics’ events have not yet been considered as a major source of emissions-reduction opportunities.  We focus on the methodology and implications of the carbon footprint of participant travel at small-scale varsity events held at UBC, where typical events have 50–1000 spectators. Few peer-reviewed studies have conducted in-depth quantitative analysis of the environmental impacts of event travel, particularly on small to medium sized events. The events that do report their carbon footprints typically show significant GHG emissions associated with 88 travel but more rigour is needed to examine the underlying travel patterns and opportunities for impact reduction. Investigating the travel impacts of different types of events is of practical importance, particularly since sport events vary widely in terms of characteristics such as size, importance (e.g., playoffs versus regular season), geographic location, or participant demographics. Understanding the travel patterns and the opportunities for maximum influence would support sustainability programme decisions at UBC and provide a template for analysis for other university athletics departments.  We examine the following research questions: (1) How can carbon footprint methodology be adapted for event managers to estimate the climate change impact of travel in a rigorous yet rapid manner? (2) What are the spectator and team travel mode choices and travel distances for UBC varsity events and which of these have the largest environmental impact? (3) What opportunities exist for travel footprint reduction of UBC events and how might they be generalizable to other small-medium sized events?  We examine current literature around carbon footprinting of events as well as the broader need for rigorous quantitative approaches. The methods section lays out our data collection, statistical methods, and carbon footprinting approach. The results section provides a breakdown of travel patterns by spectators and athletes and the resulting environmental impacts. Finally, we discuss implications for events both in terms of methodology and opportunities to minimize the carbon footprint of participant travel.  89 5.3.2 Carbon Footprinting and Sports Events In order to quantify the environmental performance of their events, sport organizations need to track metrics such as energy consumption, water use, and waste recycling. To go a step further and compare the environmental impacts of these metrics, they need to be characterized with common damage categories such as Global Warming Potential (GWP) – commonly termed a carbon footprint. Carbon footprinting is a widely adopted method for converting various Greenhouse Gases (GHG) into a single carbon dioxide equivalent (CO2e) unit (BSI, Carbon Trust, & DEFRA, 2008; WBCSD & WRI, 2011). However, even as events calculate GHG emissions of their activities, they are not applying a consistent methodology. Indeed, Pandey, Agrawal, and Pandey (2011) have noted that “The concept of carbon footprinting has permeated and is being commercialized in all the areas of life and economy, but there is little coherence in definitions and calculations of carbon footprints among the studies” (p. 135). Pandey et al. specify that carbon footprints are becoming an important part of event management, noting that events such as London 2012 have taken a relatively broad responsibility for emissions not directly under their control by including associated activities such as spectators, media, and sponsors.  Some carbon footprinting issues in debate include whether to include direct or embodied emissions, which GHGs to include, determining responsibility bounds, applying geographic specificity, and calculating uncertainty (Pandey et al., 2011). Weidema et al. (2008) suggest that the use of carbon footprinting has not been driven by research so much as practice, and that academics are playing catch-up to develop standard definitions and methodology. The GHG Protocol (WBCSD & WRI, 2004), PAS 2050 (BSI et al., 2008), and ISO 14067 (ISO, 90 2013) provide useful tools and guidance for the intricate calculation of carbon footprints of products and systems for industry but these have not yet been adapted to an event setting. The sport events literature has emphatically called for more research to address the lack of appropriate quantitative environmental impacts assessment methods (Collins et al., 2009; Getz, 2009; Hiller, 1998; Jones, 2008).  With regards to the environmental implications of event travel patterns, the literature is relatively thin. Some researchers in the sport and tourism literature have drawn a link between climate change and travel to events, suggesting this has implications for how participants travel. According to Higham and Hall (2005) “at a broad scale of analysis climate change will likely mean not that people will stop travelling but that they will change their travel preferences in both space and time” (p. 15). Most published studies and reports focus on large events and provide only high-level summaries of travel impacts. Result do, however, indicate that travel is consistently a dominant contributor in terms of GHG emissions. A study by Econ Pöyry (2009) of the 2010 World Cup in South Africa showed an impact of 2.8 million tonnes CO2e attributed to travel, representing 86% of the total event’s reported footprint, with the majority from international air travel by spectators. The Vancouver 2010 Olympic and Paralympic Winter Games also reported travel as their largest carbon footprint contributor at 70% of the 268,000 tonnes CO2e of direct and indirect impacts (VANOC, 2010). Collins et al. (2009) performed a study of an international one-day football match in Wales using another method – Wackernagel and Rees’ (1996) Ecological Footprint – and showed travel contributing 55% of the total spectator impact, although the event’s overall impact was not measured. On a smaller scale, a recent study by one of the 91 authors of this paper of the annual impact of the UBC Athletics department’s operations revealed that travel contributed approximately 2,000 tonnes CO2e per year, 24% of the total, compared to 72% for venues and 4% for accommodation, food, office, communication, and waste put together (Dolf, 2012).  We also know that travel uses a substantial amount of energy globally and therefore contributes significant GHG emissions. According to the World GHG Emission Flow Chart (Herzog, 2005), the global transportation sector is responsible for 14.3% of the planet’s total emissions, broken down by transport mode into 10.5% for road, 1.7% for air, and 2.5% for rail, ship, and “other”. In Canada, the transport sector contributes 195 million tonnes of CO2e, 28% of the total national footprint (Environment Canada, 2012).  Travel mode choice and travel distance have been studied in the context of university commuters but not for varsity events. A recent study applied carbon footprinting to investigate travel patterns of commuters to McGill University and compiled several scenarios to reduce impacts (Mathez, Manaugh, Chakour, El-Geneidy, & Hatzopoulou, 2013). Mathez et al. found that mode choice and travel distances were key determinants of the average impact per commuter type; in this case the higher use of public transportation and shorter travel distances led students to have a lower per person impact than employees. It is not clear how variables of mode choice and travel distance influence the carbon footprint signature for events, particularly since varsity events often include a significant percentage of long-distance team travel.   92 We suspect that the smaller size of the varsity events under study may exhibit different travel patterns compared to large events due to a high percentage of local spectators. Improving our understanding of smaller event patterns is important because while they may have minor individual carbon footprints, they happen in much larger numbers; resulting in large impacts overall. In addition, many events recur or form part of sports leagues, so there is an opportunity to propagate savings over time or throughout similar events.  5.3.2.1 Life Cycle Assessment – Measure to Manage Life Cycle Assessment (LCA) can be considered both a theory and methodology. LCA measures the environmental impacts of products and services “cradle to grave,” covering resource extraction, manufacture, distribution, use, and end-of-life. The LCA method is rapidly becoming the most internationally accepted way of holistically assessing environmental impacts (Finnveden et al., 2009). It is well suited to comparing products and services on a functional basis across several impact categories such as climate change, land use, water, smog, eutrophication, or acidification, among others.  As a holistic approach to environmental impact assessment, the term life cycle draws on cradle to cradle thinking, with much of the theoretical groundwork laid by Walter Stahel in the 1980s and by McDonough and Braungart (2002). They argued that industry should change manufacturing processes from considering products as simple linear throughputs of materials in and wastes out to a circular model where waste becomes a new resource in an interconnected system. An LCA is an empirical method used to measure impacts across these life cycle stages (whether cradle to grave or cradle to cradle), providing insights up and down 93 the supply chain beyond areas of ownership or control. This approach is strongly tied to Systems Theory, which suggests that we need to better understand the whole system rather than its individual parts in order to identify points of maximum leverage (D. Meadows, 2008).  Life cycle thinking extends beyond just environmental impacts. While an LCA typically examines the environmental impact of a product or services, the broader practice of embedding life cycle thinking in an organizational setting has increasingly been termed Life Cycle Management – with may include a range of approaches. Two such approaches that have developed significantly in recent years are Life Cycle Costing and Social Life Cycle Assessment. A tenet of Life Cycle Management is continuous improvement by identifying the major impacts – or hot spots – through quantitative assessment. While there still exist large uncertainties in getting accurate numbers of environmental impacts, this uncertainty can be reduced by comparing two or more options – even if the absolute number is not accurate, it may be accurate enough to allow us to choose one option relative to the other.  Baitz et al. (2013) have put forward three criteria that LCA application should meet when in practice:  94 (1) It must be reliable in order to ensure the credibility of information and results generated, (2) it must fit into existing information routines and practices in business to ensure applicability, and (3) it must provide quantitative and relevant information to inform decision makers (p. 5).  A recent study evaluated the environmental sustainability practices of American NCAA athletics departments and found that while efforts were underway, they lacked embedded measurement in management (Casper, Pfahl, & McSherry, 2012). The study also found that the majority of NCAA athletics departments did not measure their GHG emissions at all. Our study methodology, based on a travel survey, captures key event travel variables with the aim of enabling a more robust and rigorous understanding of participant emissions than current approaches. We measure participant travel choices, variables that influence those choices, and emissions-reductions opportunities with the best return on investment. Tracking this data should significantly improve the accuracy of carbon footprinting results and improve decision-making as a result.  This does not mean the effort of measurement will translate into direct environmental sustainability improvement. The commonly stated axiom “what gets measured gets done” has been widely taken up in business practice as an argument for more measurement (Kaplan & Norton, 1992). Some academics caution that this notion is overly simplistic and that in order to be translated into action, measurement should include “mobilization” and be tied to core organizational objectives (for further discussion see Catasús, Ersson, Gröjer, & Wallentin, 2007). The theory of Management by Objectives introduced by Drucker (1993) holds that 95 managers will improve organizational effectiveness by creating objectives that are tied to performance expectations of employees. In order to be effective, these objectives should also be SMART: Specific, Measurable, Attainable, Relevant, and Time-bound (Doran, 1981).  It follows then that event managers seeking to address environmental sustainability require high-quality information as long as the measurement is feasible in terms of cost, time, and expertise. This article primarily addresses the question of measurement, leaving aside the investigation of managers using this type of information for reasons of scope.  5.3.3 Methods 5.3.3.1 Carbon Footprint We applied a LCA unit-process method to assess the carbon footprint of spectator and team travel at UBC varsity events and to compare impact reduction scenarios (BSI et al., 2008). The methodology is guided by the International Standards Organization’s (ISO) 14044 requirements and guidelines, which is the most widely agreed upon standard for carrying out LCA studies (ISO, 2006b).  This study exclusively applied the impact category of Global Warming Potential, commonly called a carbon footprint, to assess travel impacts of event participants (WBCSD & WRI, 2011). The functional unit used is “impacts per spectator/team member travel to a UBC Varsity sports event.” The system boundary included return travel between the spectators’ place of residence or temporary accommodation and the event venue. We included spectators and teams travelling to UBC home games, and UBC team members (athletes plus staff) 96 travelling to away games. Neither spectators travelling to away games nor visiting teams travelling to UBC events were included as it was not feasible to collect data and because we considered that these impacts should be allocated to the other respective universities.  Carbon footprint emission factors (EFs) shown in Table 3 applied the Intergovernmental Panel on Climate Change’s 100- Year GWP characterization factors to determine carbon dioxide equivalents (kg CO2e) on a per person km basis for each mode of travel (IPCC, 2007). It should be noted that the IPCC has recently updated some characterization factors, notably for Methane, however we were not able to use these since they are not yet incorporated in life cycle inventories. In our case the six modes were: walk, bike, car, city bus (for transit), coach bus (for private use), and plane. We used the Swiss ecoinvent Life Cycle Inventory database v2.2 adapted for North America to derive the EFs including the full life cycle phases of vehicle manufacturing, maintenance, fuel use, end-of-life, and share of road/rail/air infrastructure (“ecoinvent Centre,” n.d.). Vehicle technologies are based on fleet averages. Walking was assumed to have no carbon footprint.  Mode NA EF  per vkm NA Average VO NA EF  per pkm UC spectator VO UC EF  per pkm [Unit] [kg CO₂e] [p/v] [kg CO₂e] [p/v] [kg CO₂e] Walk 0.000 1 0.000 – – Bike 0.013 1 0.013 – – Car 0.368 1.6 0.230 2.7 0.136 Transit 1.824 14 0.114 32 0.057 Coach bus 1.218 21 0.058 – – Plane 35.862 256 0.129 – –  Table 3: Carbon footprint emission factors (EF) and vehicle occupancy (VO) rates for North America (NA) and the UBC spectator context.  97 The equation used to model travel impacts for one person traveling by mode m is:  Where: I = the impact in kg carbon dioxide equivalents (CO₂e); d = the distance in km; EFvkm,m = the emission factor expressed in CO₂e per vehicle km for the corresponding travel mode; and VOm = the average vehicle occupancy rate in passengers per vehicle.  Equivalently, the ratio of EF per vkm of a given mode over the VO of that mode can be expressed as an emissions factor per person-km, EFpkm,m, such that one person's impacts is modeled by I = d * EFpkm,m. Emissions factors in terms of person-km are smaller, to account for multiple people sharing the ride. For example, the carbon footprint of one spectator traveling 10 km by car . The car travelled 10 km during that trip but carried (on average) 2.7 people, and thus accounted for 27 person-km.  5.3.3.2 Spectator Travel Survey After receiving approval from the UBC Behavioural Research Ethics Board, we obtained spectator travel data from surveys conducted at 16 separate UBC Athletics events over two varsity seasons and representing 10 sports teams over the period of 2011–2012. The sample size for spectators was n = 1413 out of an estimated total population of 40,000 annual spectators at UBC varsity events. The survey obtained the following information: mode of travel; number of people in the vehicle if they came by car; first 3 digits of their postal code (to determine which Canadian postal “Forward Sortation Area” they belonged to); whether they travelled to UBC primarily for the game (if not they were excluded); and participant I = d * EFvkm,mVOm!"#$%&=10 km*(0.368 kg CO2e vkm÷ 2.7 p v) =1.36 kg CO2e98 type (spectator, staff, team). The 16 events were chosen to cover a range of potential variables that might affect travel patterns including: sport, venue location, time of day, indoor/outdoor, weekday/weekend, and game importance (e.g., playoff game). Spectators were grouped by area of origin: campus, city, regional district, province, and extra-provincial. This sample did not, however, cover the full range of variables that might affect travel patterns, notably Summer vs. Winter or the difference between regular and playoff game attendance.  5.3.3.3 Occupancy Rates Occupancy rate assumptions supplied by ecoinvent are based on sector-wide average data and therefore may be inadequate for an event context. We anticipated that the UBC spectator occupancy rates for the travel modes of car and transit by city bus would differ significantly from these averages and therefore updated values to reflect the UBC context (see Table 3). The distribution for the car passenger occupancy rate at UBC Athletics events is shown in Figure 10. A total of 577 spectators in our sample travelled to the event by car, with a mean of 2.7 passengers per vehicle. This occupancy rate is significantly higher than the Canadian average of 1.6 (Transport Canada, 2009) or the UBC commuting average of 1.2 (UBC Transportation Planning, 2011).  99  Figure 10: Frequency distribution of the passenger occupancy rate for spectators traveling to UBC varsity events by car.  To derive the average occupancy rate of spectator buses, we performed a weighted mean of the peak average passengers per bus trip for the 14 buses that travel to UBC (Translink, 2011). Since the transit authority tracks only peak average load, we adjusted this down by 20% to estimate the average passenger load at any given time based on expert judgment (P. Klitz, personal communication, April 11, 2013). The resulting occupancy rate of 32 passengers per vehicle is twice the industry average, but appropriate given very high ridership patterns evident at UBC. Public transit systems can be utilized at much higher capacity during special events, particularly large ones, likely necessitating an adjustment to the occupancy rate in order to produce an accurate emissions estimate. An example of this is the almost exclusive use of public transport at Olympic Games by spectators due to significant road closures and the removal of parking at venues. Vancouver 2010 and London 2012 also provided all ticket-holders with free transit passes during the event.  01002003004001 2 3 4 5 6Car occupancy (persons)Frequency100 5.3.3.4 Team Travel Using the 2011–2012 competitive calendar and data provided by UBC Athletics, we determined the total number of varsity team members travelling to events held off campus. Teams travelled exclusively by coach bus or plane. We calculated travel distances by road using Google Maps and by air using the myclimate.ch flight calculator (myclimate.org, n.d.). Frequently, multiple games were played on the same trip, in which case the total travel per trip was evenly allocated between the number of events.  5.3.4 Results 5.3.4.1 Spectators Spectator travel over a UBC Thunderbirds athletic season generated 960 tonnes CO2e, which is the equivalent of approximately 1300 flights between New York and Paris. Events throughout the season collectively hosted about 40,000 spectators, typical for University athletics programmes in Canada but much smaller than many American programmes which could easily exceed this total in a single event. Survey data are shown in Figure 11, with all data points plotted in the upper graph, and the lower graph showing a zoomed-in view of the shaded area with boxplots. Distributions of travel distance are comparable across the sixteen games at which surveys were conducted. The average travel distance was 186 km per person, which was several times higher than the median of 44 km due to a small number of spectators travelling very long distances by plane. 101  Figure 11: Distance in km travelled by spectators to sampled UBC events showing all data points (upper graph) and a close-up view of box plots (lower graph).  Spectator travel patterns by travel mode are shown in Figure 12, pointing to the disproportionate effects of air travel on the carbon footprint: while only 4% of the spectators travelled by air, these spectators travelled an average of 2,500 km per person to attend UBC events, leading to a personal footprint of 330 kg CO2e per person and an overall carbon footprint representing 52% of spectator travel emissions. Travel by car has a much smaller average footprint of 17 kg CO2e per person, with a mean travel distance of 123 km and a median of 60 km, again showing that long distance travel leads to a skewed distribution. The ● ●●● ● ● ●● ●●●● ●● ●●●●● ●● ● ● ●●●●●● ●● ● ●●●●● ●●● ●●●●●●● ●●● ●● ● ●●●●●●●●● ●●●●● ● ●●●●● ●●● ●●● ●●●●●●●● ● ●● ●●●●●● ●●● ●●●●●●●●●●● ●●●●●●●●● ●●●●●●● ●●● ● ●●●● ●●●●●● ●●●●●●●●●●●● ●●●● ●●●● ●●● ●●● ●● ● ●● ●●●●●● ●●●● ●●●●● ●● ●●●●●● ●●● ●● ●●●● ●● ●●●● ●● ● ●●●● ●● ●● ●●● ●●● ●● ●● ●●● ●●● ●● ●●●● ●● ●●●● ● ●●● ●●● ●●●●● ● ●●●● ● ●●●050001000015000A B C D E F G H I J K L M N O PTravel distance (km) All survey responses●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●0100200300400500A B C D E F G H I J K L M N O PGamesTravel distance (km)Shaded region102 large number of people travelling by car, accounting for two-thirds of spectators, led to a large impact representing 47% of spectator travel emissions. The remaining modes of walking, biking, coach, and transit only contribute a combined total of 2% to the carbon footprint. The average travel carbon footprint per spectator per event was 24 kg CO2e.   Figure 12: Car travel was the most frequently used mode by spectators at 66% while plane and car travel dominated the spectator carbon footprint both on an average per person basis and for the overall total.  Figure 13 shows the number of spectators by the following areas of origin: UBC campus, City of Vancouver, Regional District of Vancouver, Province of British Columbia, and extra-0204060Travel modes (%)0100200300400kg CO2e per spectator0200400600WalkBikeCity BusCoach Bus CarPlanetonnes CO2e, overall103 provincial travel from outside British Columbia. We found that 82% of attendees travelled from within the Vancouver area, with the majority coming from the regional district. In terms of the spectator travel impact, however, 83% derives from travel originating beyond the regional district.   Figure 13: Spectators largely originated from within the Vancouver Regional District but the predominant GHG emissions were due to travel coming from outside the region.  5.3.4.2 Teams There were a total of 502 games played in the 2011–2012 season by 23 varsity teams (e.g., men’s soccer, women’s basketball, men’s football). Of these games, 159 were home games held at UBC and 343 were away games hosted in various cities across Canada and the US. Figure 14 shows the total carbon footprint for all UBC varsity teams split into event type and mode type. Exhibition games comprised 12% of the total events with 20% of the carbon 010203040Travel origin (%)0200400600Campus CityRegional DistrictProvinceExtraprovincetonnes CO2e, overall104 footprint; regular season games were 71% of the total games with 58% of the footprint; and playoff games made up 17% of the total with 22% of the impact. We note a discrepancy between the relatively higher footprint of air travel compared to coach bus travel for regular events as opposed to exhibition and playoff games. Based on the data, we suggest two reasons for this: firstly exhibition and playoff games are more frequently away games, and secondly they tend to be held at a farther distance away from UBC than regular season games. The difference in impact is also reflected in the increased relative percentage of plane travel for exhibition and playoff events, which has more than double the per km impact compared to travel by coach bus. For the 2011–2012 season, the total UBC team carbon footprint was 630 tonnes CO2e and the average carbon footprint per team member per event was 59 kg CO2e.   Figure 14: Carbon footprint of the UBC team by event type and subdivided by mode.  5.3.5 Discussion 5.3.5.1 Methodological Implications As has been suggested by (Saunders et al., 2013), some of the major obstacles to carrying out an LCA are the time and financial resources required to collect travel data, the complexity of 0100200300400Exhibition Regular Playofftonnes CO2e Modeplanecoach105 interpreting results, and the lack of understanding of LCA applications among non-experts. An LCA takes on the ambitious task of consolidating large systems of material and energy flows into a finite set of impacts useful for decision-makers. Organizations running small to medium sized events are unlikely to possess either the financial resources or the requisite level of chemistry, engineering, and statistical expertise on- hand for a full-blown LCA. In addition, the staff and public may be familiar with impact categories such as climate change or acid rain, but others such as eutrophication, acidification, photochemical smog, ecosystem quality, and so forth, are not as well understood. Our approach applied a LCA using climate change as the sole impact category for two reasons: first, because we argue that this category is the most accepted by sport managers; second, because limiting the complexity of the study to a single category enabled a clearer focus on possible methodological fine-tuning relevant to an event context.  Recent developments in LCA tools, databases, and publicly available emission factors for transport have greatly reduced the resources required for event organizers to track their carbon footprint. The collection of travel data is feasible, even for small to medium sized events. For this study, each event survey represented approximately 2–5 person-hours to conduct and in many cases volunteers and staff were already in place to do this work. Most team travel data were also readily available since the athletics department directly manages their varsity team travel plans.  We conclude that sport managers would benefit from applying the level of methodological rigour this paper takes. Our approach increases the accuracy and detail compared to 106 commonly used carbon footprinting tools by adapting the parameters of occupancy rates, vehicle technologies, travel distances by participant type, and localized mode splits. Each event will vary in terms of location, access to transit, and travel distances for spectators, requiring these parameters to be modified if they are to be accurate. For example, one event might be accessible directly by bike or transit, while another might only be reached by car. The occupancy rate, in particular, is often omitted in footprint studies even though this variable can easily change the emission factor applied by a factor of two or three.  There are a number of limitations of the LCA approach applied in this study. A key area for further development is going beyond carbon footprinting to include additional environmental impact categories such as photochemical smog, ecotoxicity, or ecosystems quality. This is important to determine potential trade-offs between impacts and to better understand site- specific issues such as air quality. Further, necessary simplifications were made regarding vehicle technologies and occupancy rates for modes such as car and plane travel. LCA databases now offer emission factors specific to the individual car model; however such specificity needs to be weighed against the added complexity and the relative effect on the results. Another limitation of this study’s methods is the use of a single geographic location for a series of events. Geographic location is likely an important variable in terms of types of vehicle technologies available, popular mode choices, and average travel distances. The results of this research are therefore not necessarily generalizable to the geographic locations or event types. Further research on patterns of event impacts are needed to increase our confidence in identifying the major areas of carbon footprint impacts and reduction across the events industry. 107 5.3.5.2 Patterns and Impacts Our results show the majority of both the UBC spectators and the UBC team carbon footprint coming from long-distance air travel. In the case of spectators, this result was perhaps surprising given that only 4% of people used this mode of travel. The majority of spectators used car travel, also contributing substantially to the overall carbon footprint.  Overall, the spectators had the larger footprint with a total of 960 tonnes of CO2e over the 2011–2012 season compared to 630 for the UBC team travel. However on a per person basis, the impact of one spectator was approximately one third that of a team member. Therefore, for events where the ratio of spectators to athletes is high, the dominant impact contribution would come from spectators. Even a mid-sized event with 25,000 spectators would likely see the spectator footprint predominate. Finally, we note that only 10% of spectators used transit, much lower than the UBC transit commuter average of 49% (UBC Transportation Planning, 2011). We suspect this drop was due largely to the reduced convenience of transit to sports venues, the longer travel distances on average, and to the minority of spectators being UBC students (all students have transit passes). The very small impact of travel from within the campus and city regions shows that emission reduction efforts should target those travelling long distances, i.e., greater than 100 km.  Nationally averaged vehicle EFs used in GHG emissions calculations include implicit occupancy rates which may be appropriate in certain contexts but which could lead to overestimates of emissions if applied to sporting event spectators. With an average car occupancy rate of 2.7, the impact per person was less than half of a typical UBC car 108 commuter – indicating that sporting event spectators may be significantly more likely to carpool than commuters (UBC Transportation Planning, 2011). A similar difference was also found for the UBC transit occupancy rate of 32 people per bus on average, double the industry average rate the ecoinvent emission factors are based on. This discrepancy is likely due to the higher transit use of the UBC commuters in general rather than the event itself. The low percentage of spectators who reported taking the transit was unlikely to have significantly affected this rate.  5.3.5.3 Opportunities for Carbon Footprint Reduction We examine a number of spectator- and team-based scenarios that may lead to a reduction in the carbon footprint. These scenarios are a combination of behaviour change initiatives targeting participants, technology choices, and planning decisions by organizing bodies. We primarily focus on long-distance car, plane, and coach bus travel because our results show that this is where the predominant footprint originates. A bike incentive is included as well since this is a common “greening initiative” found at events. Clearly, athletics departments have varying levels of say over implementing the scenarios presented. For example, the university league authorities fix the number of regular season games in most sports, whereas UBC Athletics will determine the number and location of exhibition games. The purpose of this paper is not to examine the feasibility of each option but rather to highlight the potential for impact reduction assuming equal ease of implementation.  For spectators, we examine three strategies to reduce their overall carbon footprint, in each case showing the net result of a 10% change in behaviour to highlight relative differences. 109 The first scenario for spectators assumes solutions that reduce flights. Asking fans to simply stay home may not be palatable unless other opportunities to get involved with games are offered. One way of achieving the latter is live streaming games so fans can watch from home. Another way might be to create “live sites.” Live sites are becoming more common in large events such as FIFA World Cup or NHL Stanley Cup Playoffs, where big screens are set up in off-site locations for fans. They have the dual benefit of decreasing long distance spectator travel while allowing more people to participate in a fan experience than can fit into stadium seats. Secondly, we assume an increase in the occupancy rate of cars – something that might be achieved through an incentive programme to car pool. The third scenario suggests a bike-to-the-game incentive to reduce car use. Here we assumed that only cars within a range of 22 km would be displaced (the maximum distance reported by respondents who biked).  As can be seen in Table 4, the most promising behaviour change scenario to reduce the spectator carbon footprint appears to be a reduction in overall flights at 5.1%, followed by increased occupancy rates at 4.7%, and – far less effective – a bike incentive programme leading to a 0.8% reduction. Scenario Action t CO2e reduction (%) Flights 10% decrease in people flying 50  (5.1%) Car pool 10% increase in car occupancy rate 44  (4.7%) Biking 10% mode switch from cars to bikes 7.5 (0.8%)  Table 4: Spectator behaviour change scenarios and resulting change in overall spectator carbon footprint.  110 For teams, we further examine three scenarios to reduce the travel impact of teams, again by applying a 10% change estimate (see Table 5). Our first scenario involves reducing travel for UBC teams to away games. This might be accomplished by modifying the schedule to prioritize universities located in closer proximity to UBC or increasing the number of events played per trip (currently UBC teams average 1.8 events per road trip). In the second scenario, UBC teams could choose to reduce the travel to compete in exhibition games. Reductions could be achieved by reducing the distances travelled to these events (many events are held in Southern USA), reducing the number of people travelling, or the number of events played. In the final scenario, teams might prioritize coach buses over planes for certain long-distance trips since the coach bus has less than half the impact of a plane on a per person km basis. We assume that any trip below 1,600 km from UBC would be feasible for mode switching.  Scenario Action t CO2e reduction (%) Away game travel 10% increase in games per trip or in proximity for away games 63 (10%) Exhibition events 10% decrease in travel to exhibition events 16 (2.5%) Coach bus 10% mode switch from plane to coach bus 14 (2.2%)  Table 5: Team behaviour change scenarios and resulting change in overall team carbon footprint.  For teams, the most promising scenario to lower their carbon emissions is a reduction in the amount of travel to away games at 10%, followed by a decrease in exhibition event impacts at 2.5%, and finally, prioritizing coach bus mode choice over plane for short-medium distance trips at 2.2%. One implication of these team-based results is that leagues could significantly reduce their carbon footprint by optimizing their schedules. Solutions might 111 include having a higher percentage of games among neighbouring teams, locating playoff games centrally to reduce flight distances, bringing multiple teams to a single location for multiple games per trip, or reducing the overall number of long-distance games. To highlight the event clustering solution further, four teams could travel to the same location and playing three matches each over a weekend rather than have each pair of teams travel to play one match over multiple weekends. This would cut in half the amount of travel required. A number of sports in the CIS league already do this to a certain extent, but there may be room for this to be increased.  Overall, we suggest that while all scenarios would likely lead to CO2e reductions, the most effective strategy is to decrease long-distance travel, regardless of the mode choice. This holds true for both spectators and teams. In the context of UBC varsity events, travel from spectators within the City of Vancouver only contributed 2% of the total spectator carbon footprint. Emphasizing a decrease in long-distance travel may seem counterintuitive since most spectators originate from nearby the event. While it may therefore seem attractive to target behaviour change messaging to local audiences (i.e., shifting from car to public transit or bike), these results show that the effect would be limited since local travelers are minor contributors to the overall carbon footprint. That said, however, there may still be longer-term benefits to educating even local spectators to prioritize low-impact travel since this might be taken up for longer distance travel decisions beyond the event as well.  112 5.3.5.4 Theoretical Implications As discussed earlier, life cycle thinking holds that understanding the larger pattern of impacts – beyond the scopes of responsibility for an event owner – would allow us to identify the leverage points with the most potential for environmental impact reduction. In addition, quantitative measurement allows for the comparison of solutions so managers can select the most effective course of action. In this case, a perhaps non-intuitive finding was that the carbon footprint created by a few spectators travelling a long distance was larger than the much greater number of people travelling locally. While an event cannot necessarily dictate how people must travel to the event, it could be seen as a leverage point that could nudge people towards choosing more sustainable behaviours.  This paper did not weigh in on the discussion about assigning responsibility for greenhouse gas emissions as would be required by an organization reporting their carbon footprint under the GHG Protocol (WBCSD & WRI, 2004). A challenge for events applying these guidelines is that most, if not all, of these participant travel emissions would fall under the category of Scope 3 “optional” emissions and therefore assessors might choose to ignore them. As the results of this paper show, these emissions can be substantial and event organizers may wish to take an inclusive approach to holistically assess major impacts and design solutions that influence maximum impact reduction.  5.3.6 Conclusion Carbon footprinting is promising as a method for quantifying environmental impacts and using the information to inform planning decisions. There is increasing understanding of this 113 metric in the public and, as a single impact category approach, it is relatively straightforward to calculate and interpret the results. The sport management community can build on the efforts being undertaken by the scientific, government, and private sectors to come to agreement on methods, databases, and reporting frameworks. Current LCA tools have greatly improved the ability of researchers and event managers to rapidly, accurately and relatively inexpensively calculate carbon footprint impacts as long as sufficient travel data are collected.  More research is needed, however, to refine the methodology and its application to events, particularly since they exhibit starkly contrasting characteristics in terms of size, location, ownership, facilities, length of time, and so forth. Consequently, a set of assumptions developed based on one event may not be valid for another, particularly where participant travel patterns vary. In addition, future environmental impact assessments of events should include other damage categories such as eutrophication, acidification, photochemical smog, human health impacts, and water impacts in order to determine tradeoffs missed by taking a purely carbon footprinting approach. Issues such as climate change are not tied to a single cause, nor can they be solved with a single solution. LCA as a method attempts to more holistically assess impacts cradle to grave (or cradle to cradle) and to provide a more complete picture of environmental impacts for decision makers. While a single indicator approach increases our understanding of environmental impacts, additional indicators may increase complexity of the study but will allow for a fuller understanding of the system. For example, travelling a shorter distance to compete at an event in a city with high air pollution may lower the carbon footprint but could increase the human health risks to competitors. 114 By tracking the mode choice, travel distances, occupancy rates, and travel patterns of both event spectators and teams, this study provides insights for event organizers to optimize their travel footprint. We demonstrated that the carbon footprint of car and flight travel dominated for both UBC spectators and teams participating in the 2011–2012 UBC Thunderbird varsity events. This is largely the result of the majority of spectators coming from outside the city of Vancouver to attend the events and the fact that UBC teams disproportionately travel to approximately two thirds of their scheduled events.  Our study offers insights into the impacts of small-scale events in a university varsity sport setting and contributes to the call for more research in this area by sport academics and managers alike. Our findings indicate that out-of-town travel, even when involving only a small percentage of participants, is the most effective area to target in order to mitigate the footprint of UBC Athletics & Recreation varsity events in terms of greenhouse gas emissions. We further found that although the majority of spectators travelled from nearby regions, strategies targeting these spectators would lead to only marginal emissions reductions since the distances are so small. While the travel patterns of small events likely depend on characteristics such as location, importance, or sport type, these results support previous studies of large events that have found long-distance travel to be a major contributor to the carbon footprint. 115 Chapter 6: Special Olympics Canada 2014 Summer Games  6.1 Introduction There has been a call, in literature and practice, for robust methods that can help event organizers efficiently and cost-effectively quantify the relative environmental impacts of events in order to better understand and more effectively address ES. The case study reported in this chapter applied a Life Cycle Assessment (LCA)-based approach to analyze the environmental impacts of the Special Olympics Canada 2014 Summer Games (SOC 2014) held in Vancouver, BC from July 8-12, 2014. The study investigated the relative importance of travel, accommodation, food, venues, communication, and waste impacts of the approximately 5,140 individuals participating in SOC 2014.  The research was intended to build on the previous UBC Athletics case study to focus further attention on the assumptions, methods, results, analysis, and implications of assessing the environmental impacts of participant travel. The findings of the UBC Athletics study showed that travel distance grouped by regions, occupancy rate, and travel modes were sufficient variables for a robust first order estimation of environmental impacts. Results pointed to long-distance travel, by air and road, as the chief contributor of environmental impacts for events of this type. Event organizers would therefore most effectively reduce the overall environmental footprint by reducing the number of people who travel long distance. Increased vehicle occupancy rates and lower emission travel modes would also reduce the overall footprint, but to a lesser degree.  116 The SOC 2014 event exhibited a different set of characteristics from the UBC Athletics case study and was therefore chosen to investigate how similar LCA methods would inform and provide use-value to decision makers – in particular to examine which variables might simplify the analysis of event impacts. By investigating the pattern of impacts, I hope to point the way forward to further refinement of methods and application of results in the industry.  The broad aim of this chapter is to analyze participant travel as well as the overall impacts of SOC 2014 in order to refine approaches for evaluating the major environmental impacts of an event. More specifically, this Chapter will: • Evaluate and compare the relative importance of travel versus the other event organizational areas of food, venues, accommodation, communication, and waste. • Provide a detailed analysis of the main contributor to climate change for this event, participant travel, in terms of travel distance, mode of transport, and occupancy rates. • Provide guidelines for assessing the main travel impacts of a national event. • Identify some efficient ways for event planners to reduce impacts.  6.2 About the Games Special Olympics is the world’s largest sports organization for people with intellectual disabilities (Special Olympics, n.d.). 4.5 million athletes with an intellectual disability from 170 countries participate. International, national, and provincial Special Olympics chapters use sport to provide education, health and participation opportunities to individuals. Events 117 are a large part of the Special Olympics mandate; they estimate that 70,000 competitions are organized every year across the globe.  The Special Olympics Canada Summer Games is a multi-sport event for Canadian athletes with an intellectual disability. There are Summer and Winter Games that take place every four years – alternating every two years – each time in a different Canadian city. The national Games are overseen by the sport governing body of Special Olympics Canada (SOC). This edition was organized by the 2014 Special Olympics Canada Summer Games Society, a temporary not-for-profit entity set up for this sole purpose. These national Games were also a qualifying event for athletes to represent Canada at the 2015 Special Olympics World Summer Games in Los Angeles.  6.2.1 Event Overview The 2014 Summer Games were the largest national Special Olympics Games in Canadian history, with approximately 1,800 athletes, coaches, and officials from 12 of the 13 Canadian Provinces and Territories competing; only Nunavut was not represented. The Games featured the following 11 sports: 5-pin bowling, 10-pin bowling, athletics, basketball, bocce, golf, powerlifting, rhythmic gymnastics, soccer, softball, and swimming.  The Special Olympics format emphasizes competition but also participation by grouping athletes in categories (divisions) by skill level through a rigorous evaluation and qualification process. Within each division, an athlete is eligible to win Gold, Silver, or Bronze medals. 2,045 medals were presented at SOC 2014. 118 The GOC budget was approximately $2 Million (Somerville & Taylor, 2014). The majority of the revenue came from Special Olympics Canada, the Province of British Columbia, participant registrations, and the 16 Games sponsors. As detailed in Appendix C  the largest expenditures were $970,000 for Games operations (including accommodations, food and beverage, and transportation), $170,000 for sport operations, $170,000 for finance and administration, and $140,000 for ceremonies.  6.2.2 Games Venues The Games took place from July 8-12, 2014 in Metro Vancouver, with UBC as the primary host venue. UBC hosted the Athletes Village, the Opening and Closing Ceremonies, eight of the 11 sporting events, and provided a portion of the accommodation for spectators. The sporting events were held at 11 competition venues – seven at UBC and three off campus. There were also 15 identified non-competition venues, primarily used for accommodation, meals, and office space – 12 at UBC and three off campus. The Games map is included in Appendix D  .  6.2.3 Games Participants SOC 2014 had a total of approximately 5,140 unique participants. Of these, on average 4,240 participants were in attendance for each of the five event days (Special Olympics Canada Summer Games Society, 2014). A full breakdown of Games participants by province of origin is provided in Appendix E  . As shown in Table 12, the unique participants consisted of 1,736 team members (includes athletes, coaches, and mission staff), 1,500 staff (includes pre-Games organizing committee members and Games-time volunteers), and 1,900 119 spectators (the large majority were registered as friends and family of the athletes). The majority of spectators and of staff participants came from British Columbia. In terms of teams, all provinces contributed members, with British Columbia having the second highest contingent at 368 and Ontario with the most at 455 out of 1,736 total team members (see Table 13). Ten spectators and no staff or team members reported coming from out of country. The Games Organizing Committee was volunteer-run except for two part-time staff employed over a two-year period.  6.3 Methods  6.3.1 Environmental Impact Assessment An LCA unit-process method was used to assess environmental impacts of SOC 2014 participants for each of the IMPACT 2002+ damage categories: climate change, human health, ecosystem quality, and resource use. The LCA methodology is guided by the International Standards Organization’s (ISO) 14044 requirements and guidelines, which is the most widely agreed upon standard for carrying out LCA studies (ISO, 2006b). The functional unit used is “one five-day sport event.” Each of the following organizational areas were examined: travel, venues, waste, accommodation, food, and communication. I will first discuss the data collection methods for travel which was a point of emphasis for the study (see Sections 6.3.1.1 to 6.3.1.3 below) and then the methods used in the five remaining organizational areas (Section 6.3.2). This is followed by a results section (Section 6.4) and a discussion of the findings (Section 6.5). 120 6.3.1.1 The Climate Change Impacts of Travel I primarily apply the impact category of climate change to analyze the environmental impacts of travel impacts of event participants. Climate change emission factors (EFs) shown in Table 6 applied the Intergovernmental Panel on Climate Change’s 100- Year GWP characterization factors to determine carbon dioxide equivalents (kg CO2e) on a per person km or per vehicle km basis for each mode of travel (IPCC, 2007). The modes used were: walk, bike, car, city bus (for transit), coach bus, and plane. I used the Swiss ecoinvent Life Cycle Inventory database v2.2 adapted for North America to derive the EFs including the full life cycle phases of vehicle manufacturing, maintenance, fuel use, end-of-life, and share of road/rail/air infrastructure (“ecoinvent Centre,” n.d.). Vehicle technologies are based on fleet averages. Walking is assigned no carbon footprint since initial estimates under the defined system boundary and 99% cut-off criteria indicate insignificant associated emissions and infrastructure needs compared with other modes.  Mode NA EF  per vkm NA Average VO NA EF  per pkm SOC 2014 VO SOC 2014 EF  per pkm [Unit] [kg CO₂e] [p/v] [kg CO₂e] [p/v] [kg CO₂e] Walk 0.000 1 0.000 – – Bike 0.013 1 0.013 – – Car 0.368 1.6 0.230 2.7 0.136 Transit 1.824 14 0.114 32 0.057 Coach bus 1.218 21 0.058 – – Plane 35.862 256 0.129 – –  Table 6: Carbon footprint emission factors (EF) and vehicle occupancy (VO) rates for North America (NA) and SOC 2014 context.   121 As was used in the previous case study’s methodology, the equation used to model travel impacts for one person traveling by mode m is:  Where: I = the impact in kg carbon dioxide equivalents (CO₂e); d = the distance in km; EFvkm,m = the emission factor expressed in CO₂e per vehicle km for the corresponding travel mode; and VOm = the average vehicle occupancy rate in passengers per vehicle. Equivalently, the ratio of EF per vkm of a given mode over the VO of that mode can be expressed as an emissions factor per person-km, EFpkm,m, such that one person's impacts is modeled by I = d * EFpkm,m.  6.3.1.2 Data Collection Methods for Participant Travel to the Games Data were collected from team, staff, and volunteer registration information provided by the GOC (Special Olympics Canada Summer Games Society, 2014). The following information was captured: • mode of travel • number of people in the vehicle (if they came by car) • city of origin • whether they travelled primarily for the event (if not they were excluded) • participant type (spectator, staff, team)  For spectators, a sample of n = 1,488 out of an estimated total population of 1,900 unique individuals attending the event registered their travel information with the Games Organizing I = d * EFvkm,mVOm!"#$%&122 Committee. The total population estimate was determined based on on-site attendance and observation. The sample size for staff for whom data were collected was n = 159 out of an estimated total population of 1,500 people working at the event. All staff were volunteers other than two people who worked 1.5 full-time equivalent hours over two years.  The system boundary for travel included return travel between the participants’ city of origin to the event. All team members as well as some spectators and staff made only one trip to the event venue as their accommodation was on-site during the event. The remaining spectators and staff travelled to the event each of the five days if their accommodation was off-site.  Travel to the Games refers to return travel for staff, spectator, and team participants from their city of origin to the event. Participants whose accommodation was on-site only had one return trip counted. Participants who did not live on-site (primarily staff), had daily return trips counted. Impacts were determined by applying the average distance travelled from the city of origin to the event per mode and the % of the total number of people who reported using each mode.  Participants were grouped by four areas of origin: city, regional district, province, and extra-provincial. Travel impacts were determined by applying the average distances travelled for each mode of transport and the % of each transport mode. In the case of cars and transit within Vancouver to SOC 2014, a vehicle occupancy rate for the UBC context was used (refer to Table 6). For all other modes of transport, an industry average is used, e.g., for planes and coach. 123 6.3.1.3 Travel for Participants at the Games Travel at the Games refers to the travel of all event participants within and between event sites. Three travel options were primarily used by participants: walking, shuttle buses and a staff vehicle fleet. Walking and the use of shuttle buses were the exclusive travel modes used by 1,800 team participants during the Games. Shuttle buses were also occasionally used by spectators and staff. Table 7 shows the break-down of shuttle bus trip destinations, frequency and distances from the UBC campus. The largest portion of vehicle kilometers (vkm) – almost half of the total – came from shuttling team participants to and from the airport to the event. Bowling was the only sporting event held at a venue far enough away from UBC to require shuttle transport. This accounted for approximately a quarter of vehicle km. The other major contributor was the UBC shuttle that ran for the duration of the event transporting people between the various venues on the campus in a 6 km loop.  Shuttle destination Vehicles Total trips km / trip  Total vkm Airport 8 64 40 2,560 Bowling 1 25 50 1,250 Golf 2 10 3 30 UBC (loop) 1 250 6 1,500 Ceremonies 7 28 3 84 Total 19 377 – 5,424  Table 7: Shuttle vehicle travel at the event.    124 The GOC staff made use of a fleet of 50 vehicles consisting of bikes, cars, vans and trucks of various sizes for Games operations. Table 8 itemizes the fleet vehicle types and total vkm’s. The fleet units and fuel consumption data were obtained from GOC vehicle rental records and were used to approximate kilometers driven per vehicle.   Mode Units km / vehicle Total vkm Bikes 10 50 500 Cars 11 300 3,300 Minivans 16 300 4,800 Pick-up trucks 5 300 1,500 14-foot moving vans 8 300 2,400 Total 50 – 12,500  Table 8: Vehicle fleet travel at the event.  6.3.2 Data Collection Methods for Other Organizational Areas of the Games The following is a general overview of data collection methods and sources for organizational areas other than travel. Most of the data were obtained from operational documents provided by the SOC 2014 organizing committee. Appendix B  provides detailed data collection and impact assessment methods, data assumptions and sources, and environmental impact results for each of the areas of: accommodation, communication, food, waste, travel (both to and at the SOC 2014 event), and venues. The emission factors applied are outlined in Appendix B.7.  Detailed records were obtained from event organizers for accommodation nights, communication-related material purchases, food and beverages sold, and venue occupancy. In some cases – such as for the amount of signage used – mass estimates were made based on 125 the organizing committee purchase orders and signage inventories. While the number of meals consumed was tracked, the specific food and beverages ingredients were not tracked. Consumption patterns for a typical meal were therefore based on LCA studies of two other events, a food festival in Lausanne, Switzerland (Quantis SA, 2010) and a large conference in Paris, France (PRAXIS 21 STEP, 2008). For Games waste, a team of sustainability volunteers performed regular waste audits to determine estimates of total waste generated and the end of life treatment breakdown. In the case of utility use for sporting venues, food venues, and UBC accommodation venues, building owners and operators were contacted and they supplied utility numbers for electricity, heating fuels, and water usage over the period of the Games. For utility use in accommodation venues off campus, literature-based estimates were made based on a typical hotel night.  6.4 Results The overall environmental impact for the SOC 2014 event was 242 points using the IMPACT 2002+ environmental damage categories: 122 climate change points, 23 human health points, 12 ecosystem quality points, and 85 resource use points (see Figure 15). Points refer to the impact of a typical Canadian person’s emissions per year for each damage category (Lautier et al., 2010). Therefore 242 points is the equivalent of the impact of 242 Canadians per year. Since the average Canadian is responsible for emitting approximately 20.6 tonnes of CO2e per year (Environment and Climate Change Canada, 2016), 122 climate change points is equivalent to a carbon footprint for the event of approximately 2,500 tonnes of CO2e.   126  Figure 15: Total environmental impacts for the SOC 2014 event normalized to the number of average Canadians per year contributing the same amount of environmental impact.  Normalizing them this way allows the total impact to be totaled or compared across damage categories. Climate change was the largest contributors to overall impact, with 122 of the 242 points. Resources closely followed climate change in terms of overall impact and exhibited similar impact patterns with the contributions of each organizational area – largely because emissions from transportation fuel and energy use are closely linked with climate change and fossil fuel depletion. Human health and ecosystem were significantly lower overall impact contributors than climate change. These two damage categories also showed a different pattern of impact contributions from the organizational areas, with food contributing a significantly larger percentage. 0255075100125Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasAccommodationCommunicationFoodWasteTravel−atTravel−toVenues127 The percentage contributions of the organizational areas within each environmental impact category are provided in Table 9. Travel and food showed the most variability across impact categories. Travel to the event was a dominant contributor to all impact categories but relatively higher for climate change (87.4%) and resource use (87.3%), and relatively lower for human health (44.4%) and ecosystem quality (34%). Food was the dominant contributor in both the human health and ecosystem quality categories at 51.1% and 52.8% respectively but a minor contributor to the climate change and resource use categories at 4.5% for each. The remaining organizational areas were similar in their pattern of contributions to each environmental impact category and none contributed more than 10% of the total impact.  Organizational areas Climate Change Human Health Ecosystem Quality Resources Accommodation 6.0% 2.9% 8.6% 6.1% Communication 0.5% 0.5% 0.8% 0.7% Food 4.5% 51.1% 52.8% 4.5% Waste 0.2% 0.1% 0.0% 0.0% Travel at Games 0.3% 0.4% 0.5% 0.4% Travel to Games 87.4% 44.4% 34.0% 87.3% Venues 1.0% 0.6% 3.3% 1.0%  Table 9: Percentage contribution of SOC 2014 organizational areas for each IMPACT 2002+ environmental damage category.  In terms of food impacts, Figure 16 shows that food ingredient production contributed most, with meat and cheese combined making up 90% or more of the food ingredient impact in all damage categories. The high human health impact contribution from both meat and cheese is due primarily to fine particulate matter, ammonia, nitrogen oxides, and sulfur dioxide emissions to air. As is detailed in Appendix B.3, it is important to note that the ingredients 128 modeled represent a “typical meal” based on an LCA of an event in Switzerland (Quantis SA, 2010), and not the actual ingredient breakdown for all meals at SOC 2014. While uncertainty of food impacts is fairly high, the high impacts due to meat and cheese are supported by the literature which has consistently shown that raising livestock for food is a significant source of environmental impacts due to a range of production activities including land use change and deforestation, emissions of nitrous oxide from fertilizer use, ammonia emissions from manure, and methane from enteric fermentation (de Vries & de Boer, 2010).    Figure 16: a) the normalized environmental contributions for the organizational area of food and b) the percentage contribution for each food ingredient.  The remainder of the results in this case study will focus on participant travel since this organizational area was the dominant source of environmental impacts for the event at 195 points, or 80% of the total impact. Results will be provided primarily in terms of climate change since this category was the highest contributor among the damage categories. Climate change is also the category most commonly used by events to assess and report on their environmental impacts.   0.00000.00010.00020.0003Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasPreparation and storageTransport to eventBeverage ingredientsFood ingredients0.000.250.500.751.00Climate Change Human Health Ecosystem Quality ResourcespercentageIngredientsAppleCheeseMeatPotatoRice129 Figure 17 shows the climate change category breakdown for the 2,500 tonnes of CO2e created by this event. Participant travel to the Games contributed 87.4% of the impact, accommodation 6.0%, food 4.5%, venues 1.0%, communication 0.5%, travel at the Games 0.3%, and waste 0.2%. The significantly higher impact of travel to the event versus at the event is almost entirely due to the difference in total person kilometers of distance travelled.   Figure 17: SOC 2014 had a total carbon footprint of 2,500 tonnes of CO2e with travel to the event contributing the most among the organizational areas.  6.4.1 Travel Distance and Region of Origin Table 10 shows the average distances travelled by participants to/from SOC 2014 by region of origin. Because travel at the Games made up less than 1% of the total carbon footprint, the 0500100015002000Travel−to Accommodation Food Venue Communications Travel−at Wastetonnes CO 2e130 following sections concentrate on participant travel to the Games. Although 32% of participants came from within the City of Vancouver, they contributed only 2% of the total person kilometers. The 50.8% of participants from outside the Province of British Columbia contributed 97.8% of the total person kilometers.  Region Ave km / person (return) People % People Total pkm % pkm City 20 1,553 32% 31,060 0.2% Regional District 86 391 8.1% 33,750 0.2% Province 582 442 9.1% 257,339 1.8% Extra-province 5,846 2,452 50.8% 14,391,660 97.8% Total – 4,848 100.0% 14,138,810 100.0%  Table 10: Participant travel distances to SOC 2014 by region of origin.  The chart in Figure 18 shows on a log scale the participant travel distance to the Games by mode and faceted by region of origin. The regions of origin are grouped into: city (approximately 20 km return from the event); regional district (approximately 20-400 km return from the event); (approximately 400-800 km return from the event); extra-provincial (usually greater than 800 km return from the event). Results indicate that there is a greater difference in terms of distance by region of origin than by the mode traveled. This suggests that grouping participants by region of origin would be useful in making first order assumptions about contribution to impacts. For people originating from each area of regional district, province, and extra-province, there is significant deviation in distances by mode used. There is a trend, however, showing that people travel from farthest by plane, then coach, then car, and finally transit.  131   Figure 18: Travel distance on a log scale by event participants to the Games by mode and faceted by region of origin showing all data points (upper graph) and box plots (lower graph).  city regional−district province extraprovince100100010000Walk Bike Transit Car CoachPlane Walk Bike Transit Car CoachPlane Walk Bike Transit Car CoachPlane Walk Bike Transit Car CoachPlaneModeDistance (km) walkbiketransitcarcoachplanecity regional−district province extraprovince100100010000Walk Bike Transit Car Coach Plane Walk Bike Transit Car Coach Plane Walk Bike Transit Car Coach Plane Walk Bike Transit Car Coach PlaneModeDistance (km)132 6.4.2 Mode Choice and Participant Type Mode choices of participants of Vancouver SOC 2014 were grouped into six types: bicycle, car, coach, plane, transit, and walking. Figure 19 shows both the total trip count and total travel distance for staff, teams, and spectators – showing the mode split for each. Figure 20 shows the resulting carbon footprint for staff, teams, and spectators and mode split for each. The patterns among participant types vary significantly. In terms of modal split, staff made 56.3% of the trips, the majority of which was by car and transit. The 24.1% of spectator trips also travelled predominantly by car and transit, however with a greater share of relative car travel. Teams made 19.5% of the trips and of these, 81% were by planes with the remainder by coach.   Figure 19: Total (a) trip count and (b) distance in km by mode and participant type travelling  to SOC 2014.  01,0002,0003,0004,0005,000Team Spectators StaffCountModeWalkBikeTransitCarCoach−busPlane02,000,0004,000,0006,000,0008,000,000Team Spectators StaffDistance (km)ModeWalkBikeTransitCarCoach−busPlane133   Figure 20: Total carbon footprint by mode and participant type travelling to SOC 2014.  The differences in mode choice between spectator types can be largely attributed to two things. Firstly, the make-up of where people are coming from varies significantly. 94% of staff, 21% of spectators and 7.7% of team members came from the Vancouver region. Secondly, team members were required to travel together and therefore all teams originating from outside British Columbia flew. Spectators coming from out of province generally came by plane, car, or coach bus. Of those originating outside BC, 21.7% drove a car or took a coach bus, in some cases driving from as far as the east coast of Canada.  Even with fewer overall trips, teams and spectators dominate both in terms of travel distance and carbon footprint. Plane travel dominates for all participant categories both in terms of distance and carbon footprint because the further the trip, the more likely that it was by plane. There is no significant difference in patterns between travel distance and carbon footprint however, largely because the emission factors per person km for planes and high occupancy cars are quite similar.  0300600900Team Spectators Stafftonnes CO 2eModeWalkBikeTransitCarCoach−busPlane134 Planes were the mode with the largest contribution to the carbon footprint for team, spectator, and staff participants travelling to the event. The similarity in the pattern of carbon footprint and travel distance suggests that travel distance may be a useful primary indicator of estimating impacts, in part because it determines the mode (i.e., the greater the distance, the more likely people will choose air travel over car, or car over transit and cycling, etc.).  During the event, patterns also varied for each type of participant. Teams mainly lived and competed on the UBC campus and were therefore able to primarily walk. Spectators used a mix of on-campus and off-campus accommodations and used a mix of car, shuttle bus, and walking. Staff also primarily stayed on-campus and either walked or made use of the fleet of bikes and vehicles available to them.  6.4.3 Occupancy Rates and Sensitivity Occupancy rates vary significantly by mode of travel as is shown in Figure 21. Typically, LCA databases rely on population-wide averaged data sets to determine occupancy rates. Results from the UBC Athletics study showed that occupancy rates applied for a UBC event context were higher for car and transit than population-wide averages for the modes where data was captured (refer back to Table 3). The occupancy rates specific to SOC 2014 were not fully recorded because car and transit modes were mostly used by volunteer staff and this information was not captured on their registration. Preliminary results in the opt-in survey taken by volunteers indicated a similarity to UBC Athletics event car occupancy of approximately 2.7 people per vehicle, increasing my confidence in using this assumption. In 135 the case of transit rates to UBC, they were assumed to remain largely unchanged for this event.   Figure 21: Influence of occupancy rate on in emission factors (kg CO2e per passenger km) by mode. Red markers show occupancy rate used by SOC 2014.  To test whether the overall results are sensitive to the variable of occupancy, a higher and a lower occupancy rate scenario from the assumptions used was tested. Occupancy rates of cars, transportation, and coaches were each adjusted up and down by 25%, and for planes by 10%. Figure 22 shows that occupancy rates would significantly affect the overall carbon footprint impact of travel at SOC 2014. The higher occupancy scenario decreases carbon emissions by 10% overall and the lower occupancy scenario increases carbon emissions by 12% – in both cases leading to a significant change.  136  Figure 22: Total carbon footprint for each participant type travelling to SOC 2014 by mode for higher occupancy rate scenario, actual occupancy rates used, and lower occupancy rate scenario.  6.5 Discussion This event case study suggests some future directions for event organizers wishing to assess the main environmental impacts of a small to medium sized multi-sport event held for participants travelling from across the nation.  Results showed that participant travel, primarily to the event as opposed to at the event, was the dominant environmental impact area overall, particularly in terms of climate change and resource use. Among the variables of travel distance, transportation mode, and occupancy rate, travel distance was the most significant in terms of carbon footprint. Within travel distance, the clear majority of the impact came from participants originating outside the Metro Vancouver Regional District, a distance greater than 100 km return. This suggests that organizers of events who expect to see many participants travelling from outside of the region should prioritize distance for assessment rigour and impact reduction strategies.  137 Results further suggest that rough assumptions of local travel patterns are likely enough information to make planning decisions. For example, based on these results, organizers could use a proxy for travel distance for all participants from within each region as an estimate without needing detailed travel distance information at the individual address level for each person (i.e., 20 km return for Vancouver or 80 km for the regional district for SOC 2014). Using the average travel distances by region for each mode as the method for calculating impact would have led to a 5% difference in overall travel distance or carbon footprint as compared to the method of using the actual city to city distance travelled by each person. In an event where the vast majority of participants are from the local region, e.g., a local marathon with a large number of mostly local participants, this recommendation may not hold true because local travel could have more of an impact relative to long distance travel. A simplified tool for estimating the climate change footprint of participant travel to events is pictured in Appendix F  and is available on the www.css.ubc.ca website.  Organizers should therefore focus their efforts on gathering high quality data from long distance travel. Gathering data that capture city or airport of origin would provide a more accurate picture than just knowing whether participants came from within or outside the region. In this case study, city distances within Canada to Vancouver averaged 5,800 km but ranged between 400 and 10,000 km return – pointing to the high level of uncertainty if city distances are not captured.  Knowing which variables to prioritize would also help event organizers to make decisions to reduce overall impacts more effectively. One option to reduce long distance travel would be 138 to host SOC 2014 more frequently in provinces where most athletes are located, i.e., Vancouver, Toronto, and Montreal. Another opportunity would be to reduce the number of spectators needing to travel long distances by investing in online technologies such as live streaming so they can watch at home. Smaller, but still significant, reductions could be achieved by reducing the number of flights in the planning phase by organizing committee members for meetings. While some on-site meetings are likely necessary, video conferencing is a viable option in many cases. Encouraging lower emission travel options such as trains biking, and transit for short to medium distance travel would also reduce the impact. This is especially true when the event is hosted near large population centres like Toronto, Montreal, or Vancouver with good transit options. Finally, ensuring the highest occupancy rates possible for coach bus travel, car travel, or transit travel would reduce the overall impact. UBC already has exceptionally high transit occupancy rates, so for other locations this may make a more significant difference.  Travel impacts by participants at the event were particularly low compared with travel to the event because the organizing committee chose to hold the event in a location where many of the venues and accommodation options were within a 3 km radius. This allowed the vast majority of participants to walk, bike, or take short shuttle rides. For an event where venues and accommodation options are more spread out, the environmental impact of travel during the event could increase substantially.  In the environmental damage categories of human health and ecosystem quality, food was a main contributor as well – largely due to impacts related to meat and dairy consumption. 139 Event organizers therefore have an opportunity to reduce both human and ecological impacts by increasing the percentage of fruits and vegetable ingredients relative to meat and dairy. This is relatively straightforward to put in place for organizers and may even lead to cost savings. Life cycle inventories of food ingredients are still underdeveloped in terms of consistency of methods, the number of LCA studies performed, and the availability of tools and data sets. For example, Stylianou et al. (2016) have pointed out that nutritional effects on human health are usually missing from food LCA’s and have offered new work in this direction. This study did not conduct a detailed analysis of individual food ingredients at the event but the rapid progress being made in the development of LCA methodologies and inventories for food presents a significant opportunity for further research.   In conclusion, travel to the event was shown to be the dominant overall environmental impact for SOC 2014. To optimize decisions to reduce the environmental impact of the event, organizers should estimate participant travel impacts by capturing the following data: mode share, occupancy rate modes where feasible, city of origin for long distance travel, and region of origin for short distance travel. Opportunities to reduce impacts lie primarily in reducing the number of long distance travelers, the total distance travelled, and to a lesser extent, encouraging higher occupancy rates and more environmentally friendly mode choices. 140 Chapter 7: Discussion  This dissertation consisted of two case studies that applied LCA methodology to small to medium sized sport events located in Vancouver, British Columbia. The purpose of the research was twofold: i) to identify significant environmental impacts and opportunities for impact reduction and also ii) to identify opportunities for simplifying LCA methods for small events. The first case study examined a series of varsity league events organized by the UBC Athletics department over a one-year period. The second study examined the organization of a single multi-sport event which took place over five days.  This chapter begins by comparing the characteristics of each of the two events under investigation with a view to better understanding event attributes that may lead to similarities and differences in environmental impact patterns. The next section discusses environmental impact patterns for each case across the organizational areas of participant travel, venues, food, office, waste, communication, and accommodation. The third section discusses opportunities for events to support broader efforts to leverage environmental sustainability. The chapter concludes with reflections on how LCA can potentially help with planning more sustainable events and inform efforts to organize them in a more environmentally conscious manner.  7.1 Comparison of Event Characteristics Sections 2.3.2 and 2.3.3 in the literature review chapter highlight the need to better understand the impact patterns of small to medium sized events and to provide a framework 141 and evidence to inform the growing number of sustainability guidance documents for events. A comparison of the similarities and differences between event types can inform our ability to draw comparisons and inform future study. Table 11 compares the event characteristics for the season of UBC Athletics events and SOC 2014 according to the event classification approach developed by Bovy et al. (2003).  Event characteristics UBC Athletics SOC 2014 Number of participants 40,000 7,500 Duration (short / medium / long) Short (5 days) Long (1 year) Frequency (weekly / monthly / annually / supra-annually) Annually Supra-annually (every 4 years) Temporal (one-time / recurring) Recurring Recurring Temporal (time of year) All year Summer Temporal (day / night) Day Day Size (small / medium / large) Small Small Ticketed (yes / no) Yes No Capacity (predetermined / undetermined) Undetermined Undetermined Site (mono / multi) Multi-site Multi-site Site (same / changing) Same  Changing Venue (fixed / moving) Fixed Fixed Venue (permanent / temporary) Permanent Permanent Spatial (indoor / outdoor) Indoor & outdoor Indoor & outdoor Spatial (big city / small city) Big city Big city Spatial (urban / rural) Urban Urban  Table 11: A comparison of UBC Athletics and SOC 2014 event characteristics.  The two cases share the following characteristics: both were small sized events, occurred at multiple site locations, used fixed and permanent venues, and occurred primarily during the day and largely in the same geographic location in a big city. The events were also both located in the City of Vancouver and shared a number of the same sports and venues.  142 There are also differences in their characteristics that help explain the disparities in their environmental impacts. Primarily, UBC Athletics had 40,000 spectators compared to only 7,500 for SOC 2014 and therefore had many more people travelling, eating, and staying at hotels. Second, SOC 2014 had a relatively higher rate of participants and spectators who came from out of town and used accommodation and food services over multiple days. Third, the UBC Athletics varsity season takes place over a one year period compared to just five days for SOC 2014. Finally, the UBC Athletics department was both the event organizer and owner/operator of the venues, while the SOC 2014 organizers do not own/operate any venues but instead rent them for just the event time period. While the two cases used some of the same indoor and outdoor venues, some venues were different. In addition, in some instances the same venue was used but for different purposes. For example, Doug Mitchell Thunderbird Arena was primarily used for ice hockey games for UBC Athletics, whereas for SOC 2014 the same venue was used for the opening and closing ceremonies, powerlifting, and rhythmic gymnastics.  7.2 Comparison of Impact Patterns Across Events The environmental impact patterns between the two case studies differed significantly. Most notably, venues were the dominant contributor across all environmental damage categories for UBC Athletics, while travel was the dominant contributor for all categories for SOC 2014. This section will discuss some of the results for each organizational area, using primarily the climate change environmental damage category for comparison.  143 Long distance participant travel was a major contributor to the overall environmental footprint for each case study but characteristics and travel patterns within differed significantly. In the UBC Athletics case, travel contributed 24% of the total climate change impact and most participants were spectators who originated from within the Metro Vancouver Regional District. In the SOC 2014 study, travel contributed 88% of the total climate change impact. The majority of participants were team members and spectators originating from outside the Province of British Columbia. In both cases participants travelling long distance, primarily by air, was the dominant contributor to the travel footprint. This suggests that the people travelling from outside the regional area of an event are likely the most significant contributors to the overall impact of an event.  Venue impacts differed significantly as well. Venues at UBC Athletics made up 72% of the total climate change impact compared to only 1% for SOC 2014. It is important to note that many of the venues used for both UBC Athletics and SOC 2014 events were the same and therefore impacts would be similar for an equivalent period of use. This highlights the different “environmental overhead” incurred in being the full-time owner operator of venues versus an organization that rents a few hours of venues to run an event. In the case of UBC Athletics, a full year of venue operations was allocated to the 23 UBC Athletics varsity teams which compete in approximately 500 events – of which about one third were hosted at UBC. This choice was made because the venues were principally built for and were operated to host events. However, some venues also have a portion of the space used for other purposes, e.g., for academic offices or drop-in facility rental time for the public. An allocation percentage was therefore assigned per venue based on an estimation of average hours of 144 usage per day and the physical space usage. For SOC 2014, only the hours of time rented by the event were counted, i.e., 4.5 days for sport event venues, and seven days for accommodation venues and the Doug Mitchell Arena which hosted both sporting events and the opening and closing ceremonies. This choice was made because none of the venues were principally built or operated for this event and would have been used for other purposes if the SOC 2014 event had not been held there. Both cases were similar, however, in that the larger indoor facilities they used, which require energy for heating and cooling, had much larger impacts than outdoor field venues. The results of these case studies suggest that the proportion of an event’s impacts related to venues will likely be higher for organizations that own, build, or operate significant building infrastructure if this is the primary purpose of the venue. Events that rent existing facilities should only have the time used allocated since the facilities would most likely be used for other purposes the rest of the time.  As to accommodations, SOC 2014 figures were 6% of the total carbon footprint against only 1% for UBC Athletics. The UBC Athletics impacts were higher on a per person night basis, however, as accommodation was located 10 km away from the event venue while SOC 2014 participants stayed on-site and therefore had no associated travel footprint. SOC 2014 rooms were also smaller and used less energy since most participants were housed in modern university dorms and apartments. The reason SOC 2014 accommodation had a larger contribution relative to the other areas is because they have a larger percentage of people originating from out of town and spending multiple nights to spectate and participate in the events. Small to medium event organizers should therefore anticipate that impacts from this 145 area may be significant if accommodation is located far enough away to require vehicle travel and if a large number of participants choose to stay in hotels.  Environmental impacts from food and beverages were also higher for SOC 2014 at 4% as compared to under 1% for UBC Athletics for the climate change category. As regards ecosystem quality, however, they contributed 21% for SOC 2014 and remained under 1% for UBC Athletics. The difference is likely explained by the fact that SOC 2014 served three full meals per day to all team participants, whereas the varsity games mainly had snacks and beverages on offer for spectators. The dominant impact for food across all impact categories at SOC 2014 came from the ingredients themselves; consequently, ecosystems impacts were relatively higher contributors because of land use and fertilizer use impacts. This pattern is supported by the Collins et al. (2007) study using ecological footprint methodology which found food to be one of the highest contributors to the environmental impact of a soccer event. Events with substantial food provision should therefore consider both climate change and ecosystem impacts as much as possible.   Communications impacts contributed approximately 1% of the climate change impacts to UBC Athletics and 0.3% to SOC 2014. Paper use, media, and promotional material were minimal for both events.  Office impacts were only included for UBC Athletics as they had 100 full time employees working in office spaces organizing A&R events. This area contributed approximately 1% of the impact overall, taking into account staff commuting and office space. SOC 2014 only had 146 two part-time employees. The office impacts for SOC 2014 were therefore negligible. Only small to medium sized events with professional staff and dedicated office space are likely to see a contribution to the overall event impact.  Waste contributed 1% of the climate change impacts for UBC Athletics and 0.3% to SOC 2014. The majority of impacts in this category were attributed to landfill. SOC 2014 had a higher waste diversion from landfill rate of 68% versus 43% for UBC Athletics. Even with lower diversion rates, waste impacts at small to medium sized events appear unlikely to contribute a significant level of impact compared to other organizational areas.  7.3 Opportunities for Events to Contribute to Environmental Sustainability The disruptive nature of events as concentrations of resources and activity bound closely in time and space could easily unbalance normal patterns. However, researchers are investigating whether events might also be able to harness this disruption to leverage or nudge positive change to enhance regions, whether environmentally, economically, or socially (Grix, 2014; VanWynsberghe, 2014). Much of this literature suggests that while some events make claims about social, economic, or ecological benefit, they are largely unsubstantiated and difficult to support with evidence (Chappelet, 2008; Preuss, 2007). In contrast, Regenerative Design Theory offers a promising new approach to inform how human activities should strive to achieve net positive ES outcomes, ultimately restoring a better balance in our ecosystem.  147 This study supports the literature on sports events that regularly organizing or attending events involving long distance travel or high levels of energy use in venues will lead to substantial increases of the impacts of average citizens (see for e.g., Collins et al., 2007). Further, climate change impacts correlate strongly with consumption expenditures (Hertwich & Peters, 2009). Per capita greenhouse gas emissions per year range from under one tonne in African countries to over 20 tonnes in North America. The net climate change contribution per Canadian per year is 20.6 tonnes CO2e, or 56 kg CO2e per day (Environment and Climate Change Canada, 2016). Since a typical long-distance passenger flight from e.g., Vancouver to Toronto return represents roughly one tonne of CO2e emissions, it is easy to see how each long-haul flight to an event already represents a substantial increase in the individual’s climate change footprint. The SOC 2014 event was equivalent to the annual impact of 121 Canadians, or 118 kg CO2e per person per event day – more than double that of a typical Canadian’s activities. The UBC Athletics case study had the equivalent climate change annual impact of 408 Canadians but cannot be translated very well into a daily impact since the 500 events that made up the season varied significantly in length, most consisting of just a few hours.  As discussed in the literature review, a number of researchers including Getz (2009) and Hede (2007) have called for increased measurement of event impacts to substantiate how “sustainable” events really are. The results of this dissertation do not indicate that the events under study achieved anything resembling net positive. Rather, they suggest that events involving long distance travel or significant energy use are unlikely to be “environmentally sustainable” unless they drastically alter the way they are organized. This underscores the 148 need for events to use rigorous impact assessment methods such as LCA conducted by third parties to avoid misrepresenting the event’s ES as a result of widely practiced, but mainly token efforts to reduce impacts. Recycling efforts at an event, for example, are laudable and increasingly common but do not alter the overall impact of the event in any significant way.  This is not to say that we should not try to make events “more sustainable.” Even if it appears difficult for events to achieve net positive levels of sustainability with today’s technology, event organizers still bear a responsibility to minimize their impacts. Reducing the number of people who fly and our use of environmentally sensitive venues can make a meaningful difference. For example, if SOC 2014 Games had approximately 300 fewer spectators flying from Toronto to Vancouver – representing about 20% of out-of-region spectators – this impact reduction would equal the climate change contribution of all other organizational areas put together. This level of change is achievable. Events could be hosted in locations where most participants originate from, such as Ontario or Quebec. Another solution would be offering TV broadcasts or live streaming video of the events, which might convince some spectators to watch the event from home rather than travel.  In future, events should aim to eliminate the environmental impacts associated with travel and event organization. Investing in renewable energy solutions is already possible in many regions for electricity consumption and could substantially reduce impacts related to venue operation, accommodation, and food provision. Transportation options making use of renewable energy is already a reality for regional travel using cars and transit but not yet available for long distance travel. In the meantime, events could consider measures such as 149 encouraging only local people to travel while finding ways for people living further away to participate virtually or in parallel events. Another significant opportunity for travel reduction would be to have a greater percentage of people to compete regionally instead of travelling to national or international competitions. Varsity events could also be scheduled differently so more events are played on one road trip to minimize the number of separate trips.  Finally, it is important to note that it may be easier for events to aim for more aspirational levels of social sustainability in the short term and continue working on environmental sustainability over the longer term. Drawing on participant survey feedback from the SOC 2014 Games, the results indicate the event was viewed very positively with 83% of participants reporting that the Games met or exceeded their expectations (UBC Centre for Sport and Sustainability, 2014). The Healthy Athletes program itself, which provided free health care across a range of services such as hearing and vision services, was extremely well received. Numerous themes emerged from individual comments which suggested an increase in people’s sense of camaraderie, sense of accomplishment in both participation and sporting outcomes, and sense of accomplishment and happiness due to volunteering for the event. This appears to be a promising area for further study. Other research has suggested that while there may be some short-term gains in terms of health or wellbeing outcomes resulting from events, demonstrating permanent or long-lasting outcomes is much less certain (Thompson et al., 2014). With regards to smaller events specifically, recent work has suggested local communities may benefit economically and socially from them even more than mega events because their smaller size and limited resources make them more nimble, collaborative, and more connected to community needs (Taks, Chalip, & Green, 2015). 150 7.4 Reflections on Using LCA to Measure Environmental Impacts of Events This section discusses the use value of LCA in an event planning context. One of the strengths of LCA is that it provides organizers with better quantitative information to inform decisions (Baitz et al., 2013). Having quantitative environmental impact information of multiple options – such as a choice of venue or the distances of potential accommodation sites from the event site – would help organizers better optimize decisions in consideration of ES.  Hendrickson et al. (2006) have raised the concern around the time needed for data collection for LCA’s. To be useful, LCA tools should be used in pre-, during, and post-event planning to achieve more environmentally sustainable performance. Unfortunately, most events, especially single-occurring events, tend to have short planning cycles, making it difficult to capture data, inform planning, and further modify approaches based on feedback. Recurring events, on the other hand, have the benefit of being able to trial innovative solutions and build incrementally.  Methodological choices made in conducting an LCA can strongly influence the results of a study (Reap et al., 2008a). This is perhaps most clearly illustrated by the relative difference in how much the venues contributed to overall impacts for each study. In the case of UBC Athletics, the decision to include all impacts related to one full year of ownership (see Section 4.4.3), meant venues contributed 72% of the total. In the case of SOC 2014, only the event time period was allocated to the venues, with an overall contribution of only 1%. The choice of how much of the impact of the construction and operation of a building to allocate 151 to events is significant. If the venue was built primarily to host the event, they likely should include impacts beyond the time frame of the event itself. If organizers rent an existing venue built for other purposes, it arguably makes sense to include only the time of use. However, even then, the LCA investigator may need to determine what portion of the venue is being used and whether additional operational time should be added to capture, for example, preparation and upgrades for the event. A second area where allocation decisions can profoundly influence the results is participant travel since organizers do not typically have financial ownership or control of the spectator travel choices. If we only measure what is controlled or owned by the event, spectator travel could arguably be determined to be out of scope. If we choose to include areas that events have influence over, then spectators should likely be included to inform the most impactful sustainability interventions.  Allocation choices are not always transparent, and therefore clear guidance would improve the consistency with which events can measure and report on impacts. Environmental Product Declarations (EPD’s) is one promising option. An EPD could be developed for an event – or for subcomponents of events such as sports facilities – as one way to increase consistency, third-party verifiability, and public disclosure. Current event sustainability management and reporting guidelines could also be updated to include critical methodological choices.  As I discuss in section 2.2.2.1, there are many sources of uncertainty when conducting an LCA. While these may be reduced as databases, methods, and sector-specific guidelines are developed, they will likely remain significant for the foreseeable future. Event organizers are 152 therefore encouraged to use LCA primarily as a planning tool to guide decisions rather than to make absolute claims of environmental impact or sustainability. When communicating quantitative outcomes, such as the overall carbon footprint of the event, it is important to include disclaimers about the uncertainty of the results and provide transparency about the methods used to arrive at these results. Even without high levels of accuracy, an LCA used for planning purposes can help organizers identify the major areas of impact or determine which of two solutions would be optimal.  There also remains significant uncertainty around impacts in a few of the event organizational areas used in this dissertation’s methodology. Food ingredient choices, for example, yield significant variability in the impacts according to the menu and ingredients. The LCA literature suggests that meat typically has a much higher impact than vegetables but the actual environmental footprint will vary significantly depending on factors such as yield, soil and climate type, fertilizer use, and distribution distance – a level of data that is challenging for event managers to obtain (see for e.g., Dudley, Liska, Watson, & Erickson, 2014; Röös, Sundberg, & Hansson, 2010). Another source of uncertainty is quality of environmental impact assessment data in LCA databases (Bo Pedersen Weidema & Wesnaes, 1996). While these databases are rapidly becoming more comprehensive to e.g., capture electricity grid impacts at regional levels or more types of building construction impacts, in many cases rough assumptions need to be made to estimate impacts related to data collected for events – particularly outside Europe or the US, where the most comprehensive datasets exist. As LCA databases and information progress, we should be able to achieve greater levels of certainty. 153 The dissertation findings also raise the question of whether and how we can make direct comparisons of performance between events. One event might show a higher climate change impact due to high rates of travel while another might be lower in the climate change category but high in terms of ecosystems impacts due to construction in sensitive natural environments. Another event may also have a higher footprint overall but a lower one on a per person basis. Accuracy and confidence in reporting environmental performance of events would be increased if more standardized methodology is developed and used by sport event organizers. The sustainable sport event management and reporting guidance documents created by the Global Reporting Initiative (2012) and the International Standards Organization (2012) should articulate impact assessment considerations to a greater degree.  While the dissertation research did not seek to determine whether conducting an LCA would directly influence the organization and environmental strategy of these events, on personal reflection, I would argue that it did have some influence on decisions made by organizers for both UBC Athletics and SOC 2014. In addition, sustainability was referred to as a guiding principle by the event organizers in both case studies, likely influencing the degree to which knowledge about quantitative impacts shifted planning decisions.  Conducting the impact assessment study increased the awareness among event organizers of relative impacts and there were regular discussions around seeking out more environmentally friendly solutions. For example, on seeing the high level of impact associated with venues, UBC Athletics commissioned projects to review energy consumption in their hockey arenas, aquatics centre, and field lighting. Tracking water consumption data also highlighted an 154 abnormally high rate of consumption in one UBC Athletics venue, leading to the discovery of a leak in the water mains that had gone unnoticed. For SOC 2014, the organizing committee used the impact assessment estimates to target a sustainability behaviour change campaign for participants, among other things encouraging people to walk and bike, reduce energy consumption in venues, and promote tap water over bottled water. SOC 2014 also adjusted food provision of the Games to virtually eliminate packaging from boxed lunches, source a high percentage of non-meat options, and make 100% of associated food-waste compostable. Overall, the act of tracking data relevant to impact assessment, such as fuel use consumed by vehicles and materials purchased, appeared to lead planners to ask themselves regularly whether there were ways to reduce the amounts required.  It is not possible to say whether the decisions taken would have been any different without the impact assessment or overall sustainability commitments. Further study is required before these claims could be supported empirically but they do appear to support the management axiom that what gets measured gets managed as long as it is linked to objectives (Behn, 2003). 155 Chapter 8: Conclusion  8.1 LCA for Events This dissertation set out to address the call for more research to quantify the environmental impact assessment methods for the sports sector (see for e.g., Jones, 2008). The results from the two cases studies suggest that LCA can be a useful tool to assess the relative environmental impacts of small to medium size event operations. An understanding of which areas do and do not contribute significantly will assist organizers in making more effective decisions in consideration of environmental sustainability. While implementing an LCA can be resource intensive, particularly for smaller events, even a first order hot spot analysis can alert organizers to potential areas of focus.   The increase in unit process LCI databases for areas like food, transportation, and energy grids, makes it more feasible to do these first order assessments rapidly and rigorously, but more method development is needed. EIO LCA methods, for example, use financial inputs and outputs to estimate environmental impacts and may provide value for estimating impacts in some cases. While EIO LCA’s are a less resource intensive method for initial estimates, they are much less technologically explicit and don’t capture localized activities. Looking at the financial budgets events alone may also not adequately capture event activities. For example, many events are largely volunteer run and receive goods in kind and at a discount through partnerships and sponsorships. Activities influenced by events but not captured in the budget, such as spectator travel, may also not be captured. Further research is needed to 156 compare the usefulness of unit process and EIO LCA’s as well as other types of environmental impact assessment methods.  This dissertation shows that the patterns of impacts within each case varied significantly in some areas, even though the events both took place in the same city and used many of the same venues. Venue impacts were the largest contributor across all impact categories for the UBC Athletics study but were an insignificant contributor across all impact categories for the SOC 2014 event. Participant travel was a major impact contributor across all environmental impact categories in both cases. Within participant travel, the contribution from long-distance trips originating from outside the region was far greater than local trips, regardless of mode, for each case. Waste impacts also contributed a minor impact across all environmental impact categories in both case studies. This suggests that event organizers of other events are likely to achieve greater environmental gains by addressing long-distance travel rather than waste recycling, but these assumptions should be tested as there was significant variability across the two events in all organizational areas.  8.2 Opportunities for Environmental Impact Reduction Drawing on findings in the literature around the environmental impacts of events related to e.g., travel, competition venues, and food – and drawing on the results of this dissertation – there appear to be significant opportunities to reduce environmental impacts of small to medium sized events. For event organizers owning, operating, or renting venues, one area of focus should be reducing the consumption of electricity, fuels, and water. This can be addressed through utility monitoring, encouraging behaviour change programs to reduce 157 heating/air conditioning levels and turning off lights when not needed, and running the event in such a way as to minimize the need for utilities. An example of the latter would be a willingness to hold competitions on a grass field where water consumption has been reduced and the field as a result is not necessarily lush and green.  Participant travel shows up consistently as an area with some of the greatest potential for impact reduction – albeit the pattern of impacts can vary substantially depending on the number of attendees who are local or from out of town. The dissertation findings suggest that the greatest gains can achieved by a) reducing the number of people travelling, b) reducing the average distance participants travel, c) increasing occupancy rates of vehicles, and d) using modes with lower emissions such as walking, cycling, or transit. Reducing the number of people travelling long distances to events is challenging but certainly doable. Broadcasting matches on large screens with a fan zone experience in multiple cities has been done with success for mega events life the FIFA World Cup and professional sports leagues like the NHL. The proliferation of live streaming makes it much more affordable for smaller events to broadcast events to smaller audiences. This option does not provide an in-person event experience, but nevertheless it does provide a “live” experience of the event that potentially can be shared with other spectators and may help reduce the number of people who feel compelled to travel, particularly if it saves time and financial cost. Live streaming was trialled at the SOC 2014 Games for the first time on selected sporting events and was watched by approximately 5,000 people for 2,200 hours of time. If communicated in advance of an event, this option could prove a promising future opportunity for spectators to choose to stay home and watch. 158 For events with significant food consumption such as SOC 2014, ingredient choice is another area where event organizers can reduce environmental impacts – particularly in the damage categories of human health and resource use. Increasing the amount of plant-based ingredients while decreasing the percentage of meat and dairy is a fairly straightforward way to improve ES substantially.  Another opportunity is to use LCA for long-term planning in the hopes that ongoing evaluation will allow event organizers to trial solutions and enhance ES performance over time. This is a challenge for events since they are typically short-term, periodic concentrations of effort and time. Recurring events are well placed, however, to optimize their performance through evaluation and feedback. Transfer of knowledge for single occurring events could be enhanced if all events regularly published their ES approaches and performance. Events could also try to leverage other longer-term opportunities such as new infrastructure or a behaviour change program to increase active transportation modes of walking, biking, or transit. A study by Grabow et al. (2012), for example, found that a shift from short distance car trips to 50% of people cycling in midwestern United States would lead to reduced air pollution, increased physical activity, a decline in mortality, and savings of $US 8 billion per year. The event leveraging literature has shown examples where partnering with the region or other event stakeholders can be a way to create new policies or incentives. The “2010 Legacies Now” organization, for example, leveraged the Vancouver 2010 Games to bring tangible benefits in the community through new programs and partnerships (MacAloon, 2008). It has not been demonstrated yet, however, whether events can leverage net positive levels of environmental change. 159 For event organizers, the results from these two cases demonstrate that an effective strategy for identifying major opportunities to reduce impacts is to follow the energy footprint. Within venues and accommodation, electricity and fuel use are major contributors to overall impact. Within travel, fuel use dominates against the other life cycle stages of, say, vehicle construction. Within food and beverage consumption, the energy to heat or cool meals is also a significant contributor. Material things, such as paper or merchandise or waste, make up a tiny fraction of the overall impact. A focus on measuring the areas of highest impact aligns with the recommendations made in the management literature by Bladen (2012), among others, that better information and constant feedback will achieve closer alignment between system and function which should lead to more effective outcomes.  Based on the results of these two case studies, the areas of waste and communication appear to offer the fewest important opportunities for direct impact reduction. While events should certainly aim to minimize material use and waste production, these efforts would appear to only marginally lower the environmental impact of small to medium events relative to other organizational areas. There may still be a sustainability optics benefit in order to demonstrate environmentally conscious behaviours in line with the expectations of participants. Future research could explore whether events could more easily encourage behaviour change in other areas such as travel where they have less direct control, if they encourage behaviour change in areas that are within their control such as incentivizing recycling behaviours. 160 8.3 Revisiting Sustainability: The Opportunity for Small to Medium Events  As LOCOG put it, the intention is to use the ‘power of the Games to influence change to encourage vast numbers of people to be aware about their carbon footprint and do something about it’ (London Assembly Environment Committee, 2008 as cited in Hayes & Horne, 2011).  The current climate change crisis suggests that dominant societal practices and decision-making constraints are inhibiting our ability to achieve more sustainable levels of GHG emissions. A challenge for small to medium events that wish to promote a more aspirational approach to sustainability is their reliance on existing infrastructure and stakeholders. They have less influence compared to large events on how venues are built, where energy is purchased from, how they can move large numbers of people, and how they might leverage supply chains.  In this dissertation, I discussed regenerative design theory (RD) and ecological modernization theory (EM) as two theoretical frames for interpreting sustainability. A stark contrast exists between them. RD puts forward a more aspirational aim which favours a shift in our societal model to one that places humans and nature on equal footing and provides principles for place-based design. EM considers ecological rationality within a neoliberal reliance on economic growth and technological efficiency gains – a more short-term and human-centred approach.  161 There are some limitations with applying an RD frame. A major constraint of RD for events is that it is a conceptual framework with theoretical guidelines but it does not provide procedural guidance. Its principles are yet to be tested as a useful framework for practical implementation. Future work could marry this theoretical framework with a process of implementation, behaviour change, and assessment of vital areas.  The two case studies did show some opportunities for taking an RD approach. First, both events were organized in contexts where stakeholders aspired to take a more ambitious, regenerative approach. The vision and operational planning language for the Games Organizing Committee for the SOC 2014 event included a strategic objective to “leverage the Games to contribute positively to social and ecological well-being” (2014 Special Olympics Canada Summer Games Society, 2014). UBC Athletics also operates under a university-wide mandate with a 20 Year Sustainability Strategy that includes in its vision “(…) simultaneous improvements in human and environmental wellbeing, not just reductions in damage or harm. By 2035, such regenerative sustainability is embedded across the University throughout teaching, learning, research, partnerships, operations and infrastructure, and the UBC community” (UBC, 2014). These statements most closely align with an RD approach which aims to balance both human and ecological wellbeing in aspiring to net positive change.  I suggest that while it may be technically feasible to aim for aspirational ES change in certain areas, there are reasons why events struggle to achieve this. The primary one is that events are constrained by tight budgets that above all, need to ensure they deliver a high-quality 162 sporting and spectator experience. Another major constraint is the fact that people want to travel to see events and have limited options for long-distance travel. Third, an RD approach requires changing the fundamental consumption and production modes of buildings and travel modes. This may be difficult, but it is not out of reach of small to medium sized events with a collaborative approach.  The results of this dissertation confirm that transport and energy consumption, primarily in venues, make far and away the greatest impact. Small to medium events should therefore include at least initial estimates of the environmental impacts in these areas to inform planning decisions. There are a few potential opportunities for events to be more aspirational with their sustainability efforts: • Sponsorship could support higher cost sustainability decisions such as purchasing or creating onsite renewable energy. • Host cities or sanctioning bodies can incentivise or set certain standards and guidelines which must be met by events, such as selecting events with the most sustainability commitments. • Longer planning cycles and a transfer of knowledge program between events could incorporate learning from one event into planning for future events. • Events could engage suppliers and stakeholders who share the values and business practices in alignment with the sustainability ambitions of the event. • Travel could be reduced by encouraging spectators to stay home and watch events on television or the internet. 163 • Events could prioritize using venues which meet strong ES criteria, such as those put forward by the Living Building Challenge standard (International Living Future Institute, 2016). • Events could align impact assessments with standardized and third party-created benchmarks for what constitutes “green” or “sustainable” performance, and clearly delineate what is meant by a goal to be “net positive” in terms of ES impacts.  Without quantitative evaluation of ES, we cannot know whether publicly stated intentions of being “green” are authentic or whether they are just symbolic or minor harm reduction efforts (Flyvbjerg, 2007; Getz, 2009). To avoid this, Death suggests that event organizers need to embed ES in the planning and design phase, involve key stakeholders, and formulate a clear and ambitious strategy (2011). LCA may serve as one of the planning tools that can provide evidence-based solutions and create rigorous and standard evaluation approaches to both restructuring event planning and assessing whether they are contributing substantively to environmental sustainability.  8.4 Contributions This dissertation has contributed knowledge by bridging the fields of sport management and life cycle assessment to apply and evaluate measurement techniques in a new setting: sport events. Secondly, the results provide new knowledge on event impacts which can better inform organizers and event sustainability management guidelines. Thirdly, by focusing on small to medium events this dissertation builds on the recent scholarly work that has 164 primarily focused on mega events. Finally, the results should engender academic and public debate around the considerable impact of sports events.  This work has built on the handful of studies done on environmental impacts of events to date. Detailed assessments of individual events are generally costly and time-consuming. By carrying out an LCA on two separate types of events, the results of this approach shed light on how future event organizers might incorporate environmental assessment more effectively. Understanding the patterns of impacts from two separate case studies furthers our understanding of which impacts are most important and have the most change potential.  If we are to achieve meaningful change on important environmental concerns such as climate change, society must become much more ambitious in addressing environmental sustainability. Sport events therefore need to be organized in a much more environmentally sustainable manner while evaluating and sharing their environmental performance consistently and publicly. Sport events may also hold further promise as a catalyst to capture people’s imaginations and change their behaviours. In the same way that for many people sport events embody the promotion of human health, fair play, and a celebration of performance, we should recognize that a flourishing environment not only deserves the same consideration, but is a fundamental requirement to maintaining optimal human wellbeing now and in the future. 165 Bibliography  2014 Special Olympics Canada Summer Games Society. (2014). Special Olympics Canada 2014 Summer Games - Final Report. Vancouver, BC. Annan, K. (2010, April). 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Only a very small percentage of spectators reported being from out of town and among those, few reported staying at a hotel. As they represented significantly less than 1% of accommodation nights, they were excluded.Data CollectionAccommodation person nights were based on team travel information provided by UBC Athletics. The average number of hotel nights per person for UBC teams when travelling was applied to the total number of visiting team individuals.Impact AssessmentImpacts include all upstream processes related to building construction, electricity, fuel, water, wastewater use, and waste related to accommodation. Travel impacts from accommodation to event venues are not included since this is captured under ‘travel’. Only waste to landfill are assumed for simplification (deductions for recycling are not assumed to be significant). LCI data were primarily taken from the ecoinvent 2.2 database.Due to the large number of different hotels used by travelling teams, an average North American hotel was modeled. The NA energy grid was applied rather than the BC one since most hotels are located outside BC.OutcomesElectricity was the most significant impact in terms of climate change and resources and therefore these assumptions should be updated in future to reflect the trend of hotels becoming more energy efficient.Key FiguresAverage number of UBC team nights per event when on the road: 1Total number of UBC team person nights when on the road: 6,700*Total number of opponent team person nights at UBC events: 2,400**UBC competes in 343 away games compared to 159 home games, hence the higher number of UBC team hotel nights.IMPACTS PER TYPICAL NORTH AMERICAN HOTEL PERSON NIGHTClimate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)11 7.0E-06 3.5 1800e+002e−044e−04Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasWaterWastewaterWasteConstructionTravelFuelsElectricityData Assumptions and Sources (per North American hotel person night)FLOW DATA UNIT ASSUMPTIONS DATA SOURCESBuilding construction materials0.002 m3 20 m2 per person * 3 m ceiling for a standard multi-story building with 80 yr lifespanQuantis-Gymnaestrada & TourBench Layman ReportElectricity 10 kWh 0.474 kWh/m2/yr * 20 m2 per person: 10 kWh per person per night US EPA (2005) CHP in the Hotel and Casino SectorsFuels 29 MJ 1.44 kWh/m2/yr * 20 m2 per person: 29 MJ per person per night US EPA (2005) CHP in the Hotel and Casino SectorsWater 300 L 300 L water per person per night Quantis-Gymnaestrada 2010 studyWastewater 0.3 m3 100% of tap water to wastewaterWaste 1 kg 1 kg per person per night (100% landfilled) Quantis-Gymnaestrada 2010 studyTravel 20 km 10 km travel return from hotel to venue UBC Athletics178 A.2 Communication - UBC Athletics & Recreation  Communication impacts were included for all participants at UBC hosted events. Very little communication material is distributed or sold on-site other than some paper event brochures and textile merchandise. TV, radio, newspaper, and advertising impacts were not included since there were none reported.Data CollectionAssumptions for communication data were based on rough estimations by UBC Athletics staff that four pieces of office paper (5 g per sheet) and one t-shirt were consumed on average per spectator. The material and waste transport assumptions were based on industry averages and other studies undertaken by Quantis Intl. The Internet time per person was estimated at 2 minutes of internet time per event participant as this appeared to be only a minor contributor to overall impacts.Impact AssessmentImpacts include all upstream processes related to production and transport of merchandise and paper consumed at the event. End of life impacts for paper and merchandise were included in the waste section in order to avoid double counting. LCI data were primarily taken from the ecoinvent 2.2 database.OutcomesThe main impacts for the event across all impact categories was the production of the textiles sold at the event as merchandise. Transportation of materials to the event, use of energy for communication, and paper use combined for 17% of the total climate change impact.Key FiguresTotal paper consumed in a season: 970 kgTotal merchandise sold in a season: 485 kgData Assumptions and SourcesFLOW DATA UNIT ASSUMPTIONS DATA SOURCESRecycled paper 0.02 kg One 4-page recycled event program (5 g per page) per participant (with de-inking)UBC Athletics Event CoordinatorTextiles 0.01 kg 1 item (t-shirt/hat/scarf ) sold for every 20 participants. Reference unit 1 t-shirt (200 g)UBC Athletics Event CoordinatorTransport 21.6 kgkm Estimate 720 km travel from regional storage to UBC Quantis guidelines for average transport in NA marketElectricity from internet use0.0033 kWh Each participant visits the UBC Athletics website for 2 minutes per event (0.0033 kWh per 2 min.)Internet time is estimated.  Quantis guidelines for internet energy use.IMPACTS PER PARTICIPANT ATTENDING AN AVERAGE UBC EVENTClimate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)0.33 3.30E-07 0.35 3.80.0e+005.0e−061.0e−051.5e−05Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasTransportInternetRecycled paperTextiles179 A.3 Food - UBC Athletics & Recreation  This organizational area included all food and beverages consumed at UBC events.Data CollectionBased on the estimates from UBC Athletics food contractors, an assumption of 1/5 of an average meal was applied for each UBC event participant.Alcoholic and non-alcoholic beverages were separated since their relative impacts differ significantly – alcoholic drinks have a carbon footprint approximately 3.5 times higher than non-alcoholic drinks. Although total volume of beverages sold was provided by UBC Athletics, the breakdown of drink types are also based on the Comptoir Gruyeren event study (Quantis, 2010). Tap water consumption was not included as this is already covered under stadium usage and would result in double counting. Impact AssessmentSince detailed information on the impacts of food ingredients and sources was not available, an estimation based on an LCA study by Quantis International in 2010 of an average three course meal at the Comptoir Gruyeren event in Switzerland was used. End of life impacts of food were covered in the waste section.OutcomesThe main impacts for the event across all impact categories was the production and preparation of food consumed at the event. Beverages were relatively minor contributors to overall impact.Key FiguresTotal meal equivalents served at UBC events: 9,700Liters of alcohol consumed at UBC events: 1,200Liters of non-alcoholic beverages at UBC events: 4,850IMPACTS PER PARTICIPANT ATTENDING AN AVERAGE UBC EVENTClimate Change  (kg CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)0.47 5.90E-08 0.059 5.9Data Assumptions and Sources (per typical three course meal)FLOW DATA UNIT ASSUMPTIONS DATA SOURCESFood 0.2 meal 0.2 meals per person, includes transport UBC Athletics Food contractorAlcoholic beverages 0.05 L 50 ml per person, 50% beer in glass bottle, 50% wine, includes transport UBC Athletics Food contractorNon-alcoholic beverages 0.1 L 100 ml per person, 75% coca-cola, 25% water, includes transport UBC Athletics Food contractor0.0e+005.0e−061.0e−051.5e−052.0e−05Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasNon−alcoholic beveragesAlcoholic beveragesFoodData Assumptions and SourcesFLOW DATA UNIT ASSUMPTIONS DATA SOURCESBuilding construction materials0.75 m3 20 m2 per person * 3 m ceiling for a standard multi-story building with 80 yr lifespanGSA report for average workspaceElectricity 2600 kWh 130 kWh/m2/yr * 20 m2 per person National Resources Canada - BC office energyFuels 11800 MJ 590 MJ/m2/yr * 20 m2 per person National Resources Canada - BC office energy averageWater 3750 L 15 L per person day x 250 days Quantis-Gymnaestrada 2010 studyWastewater 3.75 m3 100% of tap water to wastewaterWaste 80 kg 4 kg waste/m2/yr to landfill * 20 m2 per person UBC Sustainability OfficeStaff commuting 1 unit 49% car 20 km (1.2 p/v), 49% transit 20 km, 1% walk 2 km, 1% bike 10 km UBC TREK Transport Survey - travel distance is an estimate from Main St. to UBC (return)180 A.4 Office & Management - UBC Athletics & Recreation  This area covers communication and office space impacts related to UBC Athletics staff that organize UBC athletics events.Data CollectionUBC Athletics reports having approximately 100 administration, facilities, and coaching staff working full-time throughout the year to manage the venues, teams, communication, budgets, administration, etc. Most teams have a full-time coach. Some, such as Football, have additional coaching staff while others, such as tennis, are fully student run.Most UBC Athletics offices are located in the War Memorial Gym, Thunderbird Stadium, and Doug Mitchell Arena venues. For offices in these venues, all impacts except staff commuting were excluded from the overall impact since this would have resulted in double counting.Impact AssessmentSpecific office dimensions and data for energy, water, waste, etc. were not available and therefore an estimation was applied based on average British Columbia office building energy use and North American office sizes.Impacts include resource extraction, production, transportation, operation, and end-of-life impacts for transportation and for venue construction, electricity, fuels, tap water, and wastewater for office spaces. LCI data are taken from the ecoinvent 2.2 database.OutcomesFor employees working outside varsity venues, electricity and fuel energy use for office heating and cooling as well as staff commuting were the biggest contributors across all impact categories except water use.For employees working inside varsity venues (the vast majority), impacts from staff commuting were the only aspect included and therefore contributed 100% of the impacts.Key FiguresUBC Athletics staff: 100Data Assumptions and SourcesFLOW DATA UNIT ASSUMPTIONS DATA SOURCESBuilding construction materials0.75 m3 20 m2 per person * 3 m ceiling for a standard multi-story building with 80 yr lifespanGSA report for average workspaceElectricity 2600 kWh 130 kWh/m2/yr * 20 m2 per person National Resources Canada - BC office energyFuels 11800 MJ 590 MJ/m2/yr * 20 m2 per person National Resources Canada - BC office energy averageWater 3750 L 15 L per person day x 250 days Quantis-Gymnaestrada 2010 studyWastewater 3.75 m3 100% of tap water to wastewaterWaste 80 kg 4 kg waste/m2/yr to landfill * 20 m2 per person UBC Sustainability OfficeStaff commuting 1 unit 49% car 20 km (1.2 p/v), 49% transit 20 km, 1% walk 2 km, 1% bike 10 km UBC TREK Transport Survey - travel distance is an estimate from Main St. to UBC (return)IMPACTS PER FULL-TIME EMPLOYEE PER YEAR WHERE BUILDING IMPACTS WERE INCLUDEDClimate Change  (kg CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)2,400 1.30E-03 570 38,0000.000.030.060.090.12Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasWaterWastewaterMunicipal wasteConstructionElectricityFuelsStaff commute181 A.5 Waste - UBC Athletics & Recreation  Waste included all on-site garbage at the designated events venues. Off-site waste impacts (i.e., for affiliated hotels and offices) were embedded in estimations for those sections. Impacts include transport to end-of-life as well as end-of-life treatment.Data CollectionData were collected by providing all major suppliers with data sourcing sheets to itemize travel distances, modes, and shipment volumes for food and materials supplied to the event. Procurement and sales budgets were used to estimate food and materials impacts where unit process data were not available. Where detailed information was available or supplied – assumptions of average consumption were made. Currently, UBC does not track the amount of waste generated at their events or event venues. It was therefore considered sufficient to create estimates based on a few on site waste audits to create assumptions. In a previous audit of a UBC Athletics Basketball Game, we found that waste contributed less than 1% of the overall carbon footprint (Dolf, Teehan, Vigneault, Zhang, & Storey, 2011). Waste audits comprised emptying out garbage bins at various event venues to separate and weigh contents. The key metrics tracked used were total mass in kg of waste, % recycled and % composted.Impact AssessmentImpacts include transport to end-of-life as well as end-of-life treatment. LCI data were taken from the ecoinvent 2.2 database. For recycling, a cut-off, no benefits approach is applied to avoid giving credits to both the organization recycling the waste and the organization using the recycled material. This helped avoid the issue of whether 100% of waste sent to recycling was actually recycled.OutcomesWaste to landfill dominated the impact across all categories.Key FiguresTotal waste generated by event participants: 2,400 kgUBC recycling rate: 35%UBC composting rate: 8%Data Assumptions and SourcesFLOW DATA UNIT ASSUMPTIONS DATA SOURCESMunicipal waste 0.029 kg 0.05 kg of waste per person per event * 57% of waste to landfill Basketball pilot study (Dolf et al. 2011) & UBC Sustainability Office for recycling %Waste to recycling 0.018 kg No recycling credits UBC Sustainability OfficeWaste to compost 0.002 kg .08 kg / 2.33 mass conversion. 2.33 kg fresh organics to produce 1 kg compost Amount: UBC Sustainability Office. Compost conversion: Boldrin et al., 2010Transport to landfill 0.860 kgkm Delta landfill is 30 km (one way) from UBC Google MapsTransport to recycling 0.350 kgkm Assume 20 km trip (one way) to recycling plant EstimateTransport to compost 0.004 kgkm Assume 1 km trip (one-way) to compost plant (at UBC) UBC Sustainability OfficeIMPACTS PER PARTICIPANT ATTENDING AN AVERAGE UBC EVENTClimate Change  (kg CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)0.017 1.10E-09 3.50E-04 0.0140e+002e−074e−076e−078e−07Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasRecyclingCompostLandfill182 A.6 Travel - UBC Athletics & Recreation    Participant travel was anticipated to be a major contributor to environmental impacts and therefore detailed results were collected for spectators, staff, UBC team, and opponent team at UBC home events as well as for UBC team at away events.Data CollectionTo determine spectator and staff travel patterns, surveys were carried out at 16 separate events over two varsity seasons and representing 10 sports teams over the period of 2011-2012. The sample size for spectators was n = 1,413 out of an estimated total population of 46,000 annual spectators at UBC Athletics events. For staff, the sample size was n = 82 out of a total population of 100 at two events. The survey obtained the following information: mode of travel; number of people in the vehicle if they came by car; first 3 digits of their postal code (to determine which Canadian postal ‘Forward Sortation Area’ they belonged to); whether they traveled to UBC primarily for the game (if not they were excluded); and participant type (spectator, staff, team). The 16 events were chosen to cover a range of potential variables that might affect travel patterns including: sport, venue location, time of day, indoor/outdoor, weekday/weekend, and game importance (e.g., playoff game). Spectators were grouped by area of origin: Campus, City, Regional District, Province, and Extra-provincial. This sample did not, however, cover the full range of variables that might affect travel patterns, notably summer versus winter or the difference between regular and playoff game attendance.Occupancy rate assumptions supplied by ecoinvent are based on sector-wide average data. It was anticipated that the UBC spectator occupancy rates for the travel modes of car and transit (primarily by city bus) would differ significantly from these averages and therefore values were updated to reflect the UBC context. To derive the average occupancy rate of buses used by spectators, a weighted mean of the peak average passengers per bus trip for the 14 buses that travel to UBC was performed. Since only peak average load is tracked by the transit authority, this was adjusted down by 20% to estimate the average passenger load at any given time based on expert judgement (P. Klitz, personal communication, April 11, 2013). The resulting occupancy rate of 32 passengers per vehicle is twice the industry average, but appropriate given very high ridership patterns evident at UBC. Public transit systems are often utilized at much higher capacity during special events, necessitating an adjustment to the occupancy rate in order to produce an accurate emissions estimate. An example of this was the almost exclusive use of public transport in Vancouver during the 2010 Games due to road closures and the removal of parking at venues.Team travel information was obtained using the 2011-2012 competitive calendar and data provided by UBC Athletics to determine the total number of varsity team members traveling to events held off campus. Teams traveled exclusively by coach bus or plane. Travel distances by road were calculated by using Google Maps and by air using the myclimate.org flight calculator (“myclimate.org,” n.d.). Frequently, multiple games were played on the same trip, in which case the total travel per trip was evenly allocated between the number of events.Staff travel patterns were only based on results from two events and those results varied significantly. Nevertheless, results indicated that the travel distances are shorter than for spectators. This may be due to many event staff members being students and living close to campus.No specific travel data were gathered for UBC teams traveling to home games and practices. It was assumed that for home games, the UBC team travel patterns would be similar those of event staff since both are predominantly made up of students.Plane Transit Coach Car Bike WalkSplit CO2e Split CO2e Split CO2e Split CO2e Split CO2e Split CO2e0%20%40%60%Figure 1: Carbon Footprint by Travel ModeFigure 2: Spectator Mode Share and Carbon FootprintCar 1 personPlane−businessPlane−economyScooterCar 2.7 peopleTransitBus−coachTrainBicycle0.0 0.1 0.2 0.3kg CO2e / passenger kmUBC Athletics Spectator AverageData Assumptions and SourcesFLOW DATA UNIT ASSUMPTIONS DATA SOURCESMunicipal waste 0.029 kg 0.05 kg of waste per person per event * 57% of waste to landfill Basketball pilot study (Dolf et al. 2011) & UBC Sustainability Office for recycling %Waste to recycling 0.018 kg No recycling credits UBC Sustainability OfficeWaste to compost 0.002 kg .08 kg / 2.33 mass conversion. 2.33 kg fresh organics to produce 1 kg compost Amount: UBC Sustainability Office. Compost conversion: Boldrin et al., 2010Transport to landfill 0.860 kgkm Delta landfill is 30 km (one way) from UBC Google MapsTransport to recycling 0.350 kgkm Assume 20 km trip (one way) to recycling plant EstimateTransport to compost 0.004 kgkm Assume 1 km trip (one-way) to compost plant (at UBC) UBC Sustainability OfficeIMPACTS PER PARTICIPANT ATTENDING AN AVERAGE UBC EVENTClimate Change  (kg CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)0.017 1.10E-09 3.50E-04 0.014183 Travel – UBC Athletics & Recreation (continued)    Impact AssessmentTravel impacts for all participants were determined by applying the average distances travelled for each mode of transport, the mode split % of each transport mode, and the occupancy rate. Figure 1 shows the emission factors applied for the modes of travel: bike, transit (by city bus), coach bus, car, scooter/motorcycle, plane, train, and walk. Impacts are based on the manufacture, operation, and end-of-life each mode, as well as a share of infrastructure used (e.g., road or airport). LCI data are taken from the ecoinvent 2.2 database.OutcomesAs shown in Figure 2, the 4% of spectators who flew by plane to attend events flights dominate the overall carbon footprint contribution for participant travel.Air and car travel contributed the most across all environmental impact categories for spectators at UBC home events. Bus and car travel dominated for Staff and UBC team members travelling to home events where there was no air travel option.Air travel dominated over coach bus travel in most environmental impact categories for both UBC team members travelling to away events and opponent team members travelling to compete at UBC events.Key Figures40,000 annual spectators3,200 annual staff participants4,000 annual UBC team participants at home events8,000 annual UBC team participants at away events4,000 annual opponent team participants at UBC home events37,000,000 passenger km travelled total0.0000.0050.0100.0150.020Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasBus−coachPlaneIMPACT PER SPECTATOR ATTENDING AN AVERAGE HOME EVENTClimate Change  (kg CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)27 1.20E-05 4 4200.00000.00050.0010Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasBicycleTransitBus−coachCarPlaneIMPACT PER OPPONENT TEAM MEMBER (AT HOME) ATTENDING AN AVERAGE UBC EVENTClimate Change  (kg CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)370 1.60E-04 43 5,5000.0000.0050.0100.015Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasBus−coachPlaneIMPACT PER UBC TEAM MEMBER ATTENDING AN AVERAGE AWAY EVENTClimate Change  (kg CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)440 2.00E-04 54 6,6000.000000.000040.000080.00012Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasBicycleCarTransitIMPACT PER STAFF AND UBC TEAM MEMBER ATTENDING AN AVERAGE HOME EVENTClimate Change  (kg CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)2.6 2.60E-06 0.75 41184 Travel – UBC Athletics & Recreation (continued)  Data Assumptions and Sources for Participant Types (Per Participant)SPECTATOR TRAVEL AT HOME GAMESFLOW DATA UNIT ASSUMPTIONS DATA SOURCESWalk  0.2 pkm Modal split of 12% and average return distance of 2 km Travel surveysBike  0.1 pkm Modal split of 2% and average return distance of 5 km Travel surveysCar  12 pkm Modal split of 67% and average return distance of 123 km / vehicle occupancy rate of 2.7 Travel surveysTransit 3 pkm Modal split of 10% and average return distance of 30 km Travel surveysCoach bus  5 pkm Modal split of 6% and average return distance of 90 km Travel surveysPlane  100 pkm Modal split of 4% and average return distance of 2500 km Travel surveysSTAFF TRAVEL AT HOME GAMESFLOW DATA UNIT ASSUMPTIONS DATA SOURCESWalk  0.6 pkm Modal split of 20% and average return distance of 3 km Travel surveysBike  0.5 pkm Modal split of 10% and average return distance of 5 km Travel surveysCar  6 pkm Modal split of 40% and average return distance of 50 km / vehicle occupancy rate of 3.1 Travel surveysTransit  9 pkm Modal split of 30% and average return distance of 30 km Travel surveysCoach bus  0 pkm Modal split of 0% and average return distance of 0 km Travel surveysPlane  0 pkm Modal split of 0% and average return distance of 0 km Travel surveysUBC TEAM TRAVEL AT HOME GAMESFLOW DATA UNIT ASSUMPTIONS DATA SOURCESWalk  0.6 pkm Modal split of 20% and average return distance of 3 km Estimate based on staff travelBike  0.5 pkm Modal split of 10% and average return distance of 5 km Estimate based on staff travelCar  6 pkm Modal split of 40% and average return distance of 50 km / vehicle occupancy rate of 3.1 Estimate based on staff travelTransit  9 pkm Modal split of 30% and average return distance of 30 km Estimate based on staff travelCoach bus  0 pkm Modal split of 0% and average return distance of 0 km Estimate based on staff travelPlane  0 pkm Modal split of 0% and average return distance of 0 km Estimate based on staff travelUBC TEAM TRAVEL AT AWAY GAMESFLOW DATA UNIT ASSUMPTIONS DATA SOURCESCoach bus  450 pkm Modal split of 100% and average return distance of 450 km UBC AthleticsPlane  3,300 pkm Modal split of 100% and average return distance of 3300 km UBC AthleticsOPPONENT TEAM TRAVEL AT UBC HOME GAMESFLOW DATA UNIT ASSUMPTIONS DATA SOURCESCoach bus  450 pkm Modal split of 100% and average return distance of 450 km UBC AthleticsPlane 3,300 pkm Modal split of 100% and average return distance of 3,300 km UBC AthleticsIMPACT PER OPPONENT TEAM MEMBER (AT HOME) ATTENDING AN AVERAGE UBC EVENTClimate Change  (kg CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)370 1.60E-04 43 5,5000.0000.0050.0100.015Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasBus−coachPlane0.000000.000040.000080.00012Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasBicycleCarTransitIMPACT PER STAFF AND UBC TEAM MEMBER ATTENDING AN AVERAGE HOME EVENTClimate Change  (kg CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)2.6 2.60E-06 0.75 41185 A.7 Venues - UBC Athletics & Recreation    TOTAL IMPACT FOR GAMES VENUESClimate Change  (t CO2e)Human Health (DALY) Ecosystem Quality (PDF•m2•yr) Resources (MJ Prim)5,979,359 3.128 1,738,364 102,164,991UBC Thunderbirds compete in 13 different venues at UBC that are wholly owned and operated by UBC Athletics:• Aquatics Centre & Empire Pool [Swimming]• Baseball diamond [Baseball]• Doug Mitchell Thunderbird Arena [Ice Hockey]• John M.S. Lecky Boathouse [Rowing]• Rashpal Dhillon Oval [Track & Field]• Student Recreation Centre [Multi-use]• Thunderbird Stadium [American football]• UBC Tennis Centre [Tennis]• Varsity Soccer Field [Soccer]• War Memorial Gym [Basketball & Volleyball]• Warren Soccer Field [Soccer]• Wolfson Fields and Rugby Pavilion [Rugby]• Wright Field [Field Hockey]The Cross Country Running, Skiing, Golf, and Softball teams do not have any events hosted at UBC and make use of external venues. Impacts of these venues are considered out of scope both because they are not owned and managed by UBC Athletics and because the few hours of use are considered negligible.Data CollectionThe following data were collected for each venue from the relevant UBC departments: building area, building lifespan, predominant construction materials (e.g., wood, cement, steel), energy use (electricity, steam, fuels), water use, and wastewater. UBC Athletics has installed smart energy meters in most of their venues and therefore usage data are generally considered accurate. Where detailed data were not available, facility managers provided annual energy and water usage based on readings of on site meters or utility bills. Data on construction impacts were estimated on a building area basis using secondary data assumptions from the ecoinvent database.Impact AssessmentWhile the venues were designed primarily for varsity team competitions, a significant portion of the use is for other purposes including community programs, recreational events, and office lease space. Allocation of the total facility impacts to the event was based on the amount of time used and, where only part of a facility is used by UBC Athletics, a % estimate of space. The annual operating impacts of each venues are calculated based on the usage of the preceding year: September 1, 2010 - September 1, 2011.Venue construction impacts are based on three building archetypes within ecoinvent 2.2: wood, steel, and concrete buildings. Impacts include resource extraction, production, transportation, operation, and end-of-life impacts for venue construction, electricity, fuels, tap water, and wastewater. LCI data are taken from the ecoinvent 2.2 database.OutcomesEach venue varied significantly in terms of their pattern of impacts. The Aquatic Centre, Doug Mitchell Arena, and War Memorial Gym were the top three contributors for all environmental impact categories, largely due to energy used for heating, cooling, lighting, and plug loads. Building facilities had significantly higher impacts than field venues across all impact categories, largely due to their higher energy needs and construction material impacts.The results represent combined impacts from the Aquatic Centre, consisting of an indoor facility housing a 50 meter pool, and the 50 meter outdoor Empire Pool. Hydro electricity and steam for heating are major contributors in all impact categories at 88% for climate change, 52% for human health, 33% for ecosystem quality, and 90% for resources. Much of the steam use goes to pool heating, particularly for the year-round heating of the uncovered outdoor pool. UBCs planned conversion of steam to a hot water heating system should lead to a reduction in overall energy use. Construction materials contribute less than 5% each for climate change and resources but more significantly to human health and ecosystem quality at 26% and 33% respectively. The assumptions are based on average construction materials per m2 of a typical building, which is not necessarily representative of a swimming pool.A relatively large amount of pool chemicals are used per year; this translates into contributions of 15% for human health and 14% for ecosystem quality.Waste impacts are negligible at under 1% for all categories.Wastewater impacts in the human health (6%) and ecosystem quality (16%) categories are a result of treatment of wastewater contents and the associated infrastructure materials, transports, and land use burdens. This scenario assumes that 75% of water becomes wastewater, with 25% lost to evaporation and leakage.The pool uses approximately 48 million liters of municipal tap water and this contributes 4% or less for all categories.Venues - UBC Athletics & RecreationRashpal Dhillon OvalWright Hockey FieldRugby Pavilion and FieldsWarren Soccer FieldVarsity Soccer FieldBaseball DiamondJohn Lecky BoathouseUBC Tennis CentreThunderbird StadiumStudent Recreation CentreWar Memorial GymDoug Mitchell ArenaAquatic Centre0 100 200 300person·year / unitemissionAreasClimate ChangeHuman HealthEcosystem QualityResourcesKey FiguresTotal energy consumed by venues: 16 GWh•  8 GWh electricity• 7.8 GWh steam• 365 MWh natural gasTotal water consumed by venues: 190,000,000 LitresGross venue area (13 venues) 140,000 m2050100150Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasWaterWastewaterWasteChemicals−poolConstructionElectricity and heatinga) UBC Aquatic Centre186 Venues – UBC Athletics & Recreation (continued)    TOTAL IMPACT FOR GAMES VENUESClimate Change  (t CO2e)Human Health (DALY) Ecosystem Quality (PDF•m2•yr) Resources (MJ Prim)5,979,359 3.128 1,738,364 102,164,991The results represent combined impacts from the Aquatic Centre, consisting of an indoor facility housing a 50 meter pool, and the 50 meter outdoor Empire Pool. Hydro electricity and steam for heating are major contributors in all impact categories at 88% for climate change, 52% for human health, 33% for ecosystem quality, and 90% for resources. Much of the steam use goes to pool heating, particularly for the year-round heating of the uncovered outdoor pool. UBCs planned conversion of steam to a hot water heating system should lead to a reduction in overall energy use. Construction materials contribute less than 5% each for climate change and resources but more significantly to human health and ecosystem quality at 26% and 33% respectively. The assumptions are based on average construction materials per m2 of a typical building, which is not necessarily representative of a swimming pool.A relatively large amount of pool chemicals are used per year; this translates into contributions of 15% for human health and 14% for ecosystem quality.Waste impacts are negligible at under 1% for all categories.Wastewater impacts in the human health (6%) and ecosystem quality (16%) categories are a result of treatment of wastewater contents and the associated infrastructure materials, transports, and land use burdens. This scenario assumes that 75% of water becomes wastewater, with 25% lost to evaporation and leakage.The pool uses approximately 48 million liters of municipal tap water and this contributes 4% or less for all categories.FACTS & FIGURES(Based on annual consumption Sept. 2010 - Sept. 2011)• Varsity sports teams: Men’s & Women’s Swimming• Year built: 1978 1• Anticipated life span: 40 years 2• Spectator seating capacity: 2,500 1• Venue area: 7,688 m2 (AC) & 1,314 m2 (Empire) 3• Venue volume: 26,429 m3 (AC) 3• Floors: 3 3• Primary construction materials: Concrete 3• Grid electricity: 1,546,800 kWh (AC) 4• Steam: 3,361,318 kWh (AC) & 2,546,594 kWh (Empire) 4• Water: 48,903,000 L 4• Overlay materials: negligible• Waste: 105,716 kg 5• Maintenance (pool chemicals): • Sodium hypochlorite: 105,000 kg 6• Calcium chloride: 14,000 kg 6• Diatomaceous earth: 35,000 kg 6• Sodium bicarbonate: 28,000 kg 6• Sodium thio sulfate: 100 kg 6• Calcium hypochlorite: 300 kg 6• Soda ash: 50 kg 6• Muriatic acid: 37,440 kg 6• Cyanuric acid: 100 kg 61 Source: www.athletics.ubc.ca2 Source: UBC Athletics Facilities Manager3 Source: UBC Campus & Community Planning & UBC LiDar4 Source: UBC Utilities5 Estimate based on UBC average of 4 kg waste per m2 per year (source: UBC Sustainability Office)6 Source: UBC Aquatics facilities managerVenues - UBC Athletics & RecreationIMPACTS FOR 2014 GAMES —JULY 8-12, 2014Climate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)3,100 0.840 430,000 55,000,000050100150Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasWaterWastewaterWasteChemicals−poolConstructionElectricity and heatinga) UBC Aquatic CentreAquatic Centre + Empire Pool [Swimming]© 2011 UBC Athletics & Recreation, by permission187 Venues – UBC Athletics & Recreation (continued)    The Baseball Diamond consists of a synthetic grass field and has no permanent facilities attached.Electricity contributes 6% or less of the impact to all damage categories. These impacts come mainly from the use of hydro electricity for field lighting. Construction materials are the primary impact across all categories contributing 94% for climate change, 85% for human health, 89% for ecosystem quality, and 97% for resources. Within the materials used to construct the synthetic field, rubber contributes over 80% of the impact in all categories. Although the turf manufacturer reported using recycled rubber, the LCA process used is based on virgin rubber and therefore these results likely represent a higher impact. Also, information from the turf manufacturer was only provided for one average field type; the material composition of individual fields may vary.The impacts from water irrigation and chemical fertilizer use are minor as they are only applied to the real grass on the field periphery.Fuel use by tractors for field maintenance contribute 9% to human health and 1-2% to the remaining categories.Waste impacts are negligible at under 0.1% for all categories.The Doug Mitchell Arena houses three ice hockey rinks, office space, a fitness area, and multi-purpose rooms. The addition of a 6,000 seat arena built to LEED (Leadership in Energy and Design) Silver specifications was added in 2008 to the two existing ice hockey arenas.Electricity and heating are the largest contributors for all impact categories with 74% for climate change, 69% for human health, 52% for ecosystem quality , and 77% for resources. This is primarily due to hydro electricity for lighting and plug loads as well as some natural gas use for heating.Construction materials contribute approximately 19% to climate change. The assumptions are based on average construction materials per square meter of a typical building, which is not necessarily representative of an ice hockey arena. The LEED Silver design specifications suggest that it likely has a lower construction–related impact than typical ice hockey arenas.Wastewater impacts in the human health (8%) and ecosystem quality (24%) categories are a result of treatment of wastewater contents and the associated infrastructure materials, transports, and land use burdens. This scenario assumes that 100% of water becomes wastewater.Waste impacts, although likely overestimated, contribute less than 5% of the impacts in all categories.Direct water use from tap water contributes 1% or less for all categories.FACTS & FIGURES(Based on annual consumption Sept. 2010 - Sept. 2011)• Varsity sports teams: Men’s Baseball• Year built: 2008• Anticipated life span: 10 years 1• Spectator seating capacity: None• Venue area: 10,426 m2 1• Field type: Synthetic grass• Grid electricity (field lighting): 11,400 kWh 2• Water (for irrigation): 600,000 L 2• Overlay materials: Negligible• Waste: Negligible• Construction materials:• Grass (polyethylene): 1.288 kg per m2 3• Primary backing (polypropylene): 0.271 kg per m2 3• Secondary coating .61 kg per m2 3• Sand 22 kg per m2 3• Rubber 16.65 kg per m2 3• Field maintenance:• Diesel: 1,800 L 4• Fertilizer 23-3-23: 400 kg 41 Source: UBC Athletics facilities manager2 Source: UBC Utilities3 Estimate based on information from turf manufacturer4 Source: UBC Athletics maintenanceVenues - UBC Athletics & Recreation Venues - UBC Athletics & RecreationIMPACTS FOR 2014 GAMES —JULY 8-12, 2014Climate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)60 3.70E-02 10,100 1,900,00001234Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasWater−irrigationFuel−fieldChemicals−fertilizerConstructionElectricityd) UBC Baseball Diamond010203040Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasWaterWastewaterWasteConstructionElectricity and heatingb) UBC Doug Mitchell ArenaBaseball Diamond [Baseball] Doug Mitchell Arena [Ice Hockey]© 2011 UBC Athletics & Recreation, by permission188 Venues – UBC Athletics & Recreation (continued)    The Doug Mitchell Arena houses three ice hockey rinks, office space, a fitness area, and multi-purpose rooms. The addition of a 6,000 seat arena built to LEED (Leadership in Energy and Design) Silver specifications was added in 2008 to the two existing ice hockey arenas.Electricity and heating are the largest contributors for all impact categories with 74% for climate change, 69% for human health, 52% for ecosystem quality , and 77% for resources. This is primarily due to hydro electricity for lighting and plug loads as well as some natural gas use for heating.Construction materials contribute approximately 19% to climate change. The assumptions are based on average construction materials per square meter of a typical building, which is not necessarily representative of an ice hockey arena. The LEED Silver design specifications suggest that it likely has a lower construction–related impact than typical ice hockey arenas.Wastewater impacts in the human health (8%) and ecosystem quality (24%) categories are a result of treatment of wastewater contents and the associated infrastructure materials, transports, and land use burdens. This scenario assumes that 100% of water becomes wastewater.Waste impacts, although likely overestimated, contribute less than 5% of the impacts in all categories.Direct water use from tap water contributes 1% or less for all categories.FACTS & FIGURES(Based on annual consumption Sept. 2010 - Sept. 2011)• Varsity sports teams: Men’s & Women’s Ice Hockey• Year built: 2008 1• Anticipated life span: 60 years 2• Spectator capacity: 5,000 1• Venue area: 36,410 m2 3• Venue volume: not available• Floors: 3 3• Primary construction materials: Concrete 3• Grid electricity: 4,361,241 kWh 4• Natural gas: 133,042 kWh 4• Water: 19,070,000 L 4• Overlay materials: negligible• Waste: 145,640 kg 51 Source: www.athletics.ubc.ca2 Source: UBC Athletics facilities manager3 Source: UBC Campus & Community Planning4 Source: UBC Utilities5 Estimate based on UBC average of 4 kg waste per m2 per year (source: UBC Sustainability Office)*Note: Cooling systems is ammonia basedVenues - UBC Athletics & RecreationIMPACTS FOR 2014 GAMES —JULY 8-12, 2014Climate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)950 9.10E-01 450,000 14,000,000010203040Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasWaterWastewaterWasteConstructionElectricity and heatingb) UBC Doug Mitchell ArenaDoug Mitchell Arena [Ice Hockey]© 2011 UBC Athletics & Recreation, by permission189 Venues – UBC Athletics & Recreation (continued)    The John M. S. Lecky Boathouse is located outside of the UBC Campus, approximately 15 km to the Southeast. Electricity and heating are the largest contributors for the impact potential categories of climate change at 91% and resources at 93%. This is largely due to grid electricity for lighting and plug loads, and natural gas for heating.Construction materials contribute approximately 4% for climate change, 11% for human health, 8% for ecosystem quality, and 4% for resources respectively. The assumptions are based on average construction materials per square meter of a typical building, which is not necessarily representative of this boathouse. Due to the use of primarily wood materials and the relatively low amount of materials per m2, the construction impacts are likely overestimated.Wastewater impacts in the human health (38%) and ecosystem quality (67%) categories are a result of treatment of wastewater contents and the associated infrastructure materials, transports, and land use burdens. This scenario assumes that 100% of water becomes wastewater.Wastewater impacts in the human health and ecosystem quality categories are a result of treatment of wastewater contents and the associated infrastructure materials, transports, and land use burdens.Direct water use from tap water contributes 4% or less for all categories.Waste contributes a negligible impact.FACTS & FIGURES(Based on annual consumption Sept. 2010 - Sept. 2011)• Varsity sports teams: Men’s & Women’s Rowing• Year built: 2006 1• Anticipated life span: 40 years 2• Spectator capacity: 192 1• Venue area: 540 m2 3• Venue volume: not available• Floors: 2 3• Primary construction materials: Wood 3• Grid electricity: 100,010 kWh 3• Natural gas: 231,056 kWh 3• Water: 3,855,000 L 4• Overlay materials: negligible• Waste: 2,160 kg 51 Source: www.athletics.ubc.ca2 Source: UBC Athletics facilities manager3 Source: Boathouse facilities manager4 Source: UBC Utilities5 Estimate based on UBC average of 4 kg waste per m2 per year (source: UBC Sustainability Office)Venues - UBC Athletics & RecreationIMPACTS FOR 2014 GAMES —JULY 8-12, 2014Climate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)82 4.10E-02 33,000 1,400,000IMPACTS FOR 2014 GAMES —JULY 8-12, 2014Climate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)7.3 1.20E+05 2,600 120,00001234Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasWasteWaterWastewaterConstructionElectricity and heating0.00.10.20.3Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasConstructionWater−irrigationFuel−fieldElectricityChemicals−fertilizerJohn M. S. Lecky Boathouse  [Rowing]© 2011 UBC Athletics & Recreation, by permission190 Venues – UBC Athletics & Recreation (continued)    The Rashpal Dhillon Oval consists of a synthetic track surrounding a grass field in the centre. No permanent buildings are attached.The impacts from chemical – fertilizer use for the grass field are 25% for climate change, 13% for human health, 15% for ecosystem quality, and 20% for resources.Electricity contributes 24% for climate change, 20% for human health, 23% for ecosystem quality, and 23% for resources. These impacts can be attributed to the use of hydro electricity for field lighting.Fuel use by tractors for field maintenance contribute 19% for climate change, 49% for human health, 9% for ecosystem quality, and 17% for resources.Tap water for irrigation contributes 16% for climate change, 9% for human health, 45% for ecosystem quality, and 18% for resources.Construction materials contribute 16% for climate change, 9% for human health, 8% for ecosystem quality, and 23% for resources. The material break-down of the track was not available and therefore an estimate is made for sand and rubber based on the composition of the other synthetic field types. No construction materials are attributed to the natural grass field portion of this venue.Waste impacts are negligible at under 0.1% for all categories.FACTS & FIGURES(Based on annual consumption Sept. 2010 - Sept. 2011)• Varsity sports teams: Men’s & Women’s Rowing• Year built: 2006 1• Anticipated life span: 40 years 2• Spectator capacity: 192 1• Venue area: 540 m2 3• Venue volume: not available• Floors: 2 3• Primary construction materials: Wood 3• Grid electricity: 100,010 kWh 3• Natural gas: 231,056 kWh 3• Water: 3,855,000 L 4• Overlay materials: negligible• Waste: 2,160 kg 51 Source: www.athletics.ubc.ca2 Source: UBC Athletics facilities manager3 Source: Boathouse facilities manager4 Source: UBC Utilities5 Estimate based on UBC average of 4 kg waste per m2 per year (source: UBC Sustainability Office)FACTS & FIGURES(Based on annual consumption Sept. 2010 - Sept. 2011)• Varsity sports teams: Men’s & Women’s Track• Year built: 2009• Anticipated life span: 10 years 1• Spectator capacity: None• Venue area: 10,426 m2 1• Field type: Rubber track & grass field• Grid electricity (field lighting): 11,400 kWh 2• Water (for irrigation): 3,681,000 L 2• Overlay materials: Negligible• Waste: Negligible• Construction materials (for track)• Sand: 22 kg per m2 3• Rubber: 16.65 kg per m2 3• Field maintenance:• Diesel: 400 L 4• Fertilizer 23-3-23: 1,000 kg 4• Fertilizer 18-18-18: 250 kg 4• Lime: 1,680 kg 41 Source: UBC Athletics facilities manager2 Source: UBC Utilities3 Estimate based on information from turf manufacturer4 Source: UBC Athletics maintenanceVenues - UBC Athletics & RecreationIMPACTS FOR 2014 GAMES —JULY 8-12, 2014Climate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)7.3 1.20E+05 2,600 120,0000.00.10.20.3Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasConstructionWater−irrigationFuel−fieldElectricityChemicals−fertilizerRashpal Dhillon Oval  [Track & Field]© 2011 UBC Athletics & Recreation, by permission191 Venues – UBC Athletics & Recreation (continued)    The Student Recreation Centre is a multi-purpose building, housing fitness gyms, basketball courts, martial arts studies, office space, and fitness rooms. It does not host a specific Thunderbirds team but it is used by them for training and fitness purposes.Electricity and heating contribute 69% for climate change, 38% for human health, 22% for ecosystem quality, and 75% for resources. This is primarily due to hydro electricity for lighting and plug loads as well as steam for heating.Construction materials contribute approximately 28% for climate change, 53% for human health, 56% for ecosystem quality, and 24% for resources. The assumptions are based on average construction materials per square meter of a typical building, which is not necessarily representative of this building.Wastewater impacts in the human health (9%) and ecosystem quality (20%) categories and less than 1% in the other categories. This scenario assumes that 100% of water becomes wastewater.Tap water and waste impacts are minimal, contributing less than 2% for all impact categories.FACTS & FIGURES(Based on annual consumption Sept. 2010 - Sept. 2011)• Varsity sports teams: None• Year built: 1995 1• Anticipated life span: 60 years 2• Spectator capacity: none• Venue area: 6,790 m2 3• Venue volume: 37,040 m3 4• Floors: 3 3• Primary construction materials: Concrete 3• Grid electricity: 907,200 kWh 5• Heating from steam: 444,770 kWh 5• Water: 8,431,000 L 5• Overlay materials: negligible• Waste: 27,160 kg 61 Source: www.athletics.ubc.ca2 Source: UBC Athletics facilities manager3 Source: UBC Campus & Community Planning4 Source: UBC LiDar5 Source: UBC Utilities6 Estimate based on UBC average of 4 kg waste per m2 per year (source: UBC Sustainability Office)Venues - UBC Athletics & RecreationIMPACTS FOR 2014 GAMES —JULY 8-12, 2014Climate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)470 3.90E-01 240,000 7,400,00005101520Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasWaterWastewaterWasteConstructionElectricity and heatingStudent Recreation Centre  [Fitness, Multi-use]© 2011 UBC Athletics & Recreation, by permission192 Venues – UBC Athletics & Recreation (continued)    The Thunderbird Stadium venue comprises cement stands with integrated office spaces and a synthetic football field.Electricity and heating contributed 31% for climate change, 25% for human health, 16% for ecosystem quality, and 26% for resources. These impacts can be attributed to the use of hydro electricity for lights, plug loads, and heating.Construction for the building contribute 39% for climate change, 53% for human health, 58% for ecosystem quality, and 29% for resources.Construction materials for the field contribute 25% for climate change, 12% for human health, 5% for ecosystem quality, and 43% for resources. The main impact for the synthetic field is due to rubber. Although the turf manufacturer reported using recycled rubber, the LCA process used is based on virgin rubber and therefore these results likely represent a higher impact. Also, information from the turf manufacturer was only provided for one average field type; the material composition of individual fields may vary.The impacts from chemical–fertilizers are minor contributors as they are primarily used for the real grass on the field periphery.Water, waste, fertilizer use and fuel use all contribute less than 3% of the impacts in all categories. Wastewater impacts contributed 8% for human health and 18% for ecosystem quality. This scenario assumes that 40% of water is used by the stadium and becomes wastewater, whereas the 60% used for the field does not become wastewater.FACTS & FIGURES(Based on annual consumption Sept. 2010 - Sept. 2011)• Varsity sports teams: None• Year built: 1995 1• Anticipated life span: 60 years 2• Spectator capacity: none• Venue area: 6,790 m2 3• Venue volume: 37,040 m3 4• Floors: 3 3• Primary construction materials: Concrete 3• Grid electricity: 907,200 kWh 5• Heating from steam: 444,770 kWh 5• Water: 8,431,000 L 5• Overlay materials: negligible• Waste: 27,160 kg 61 Source: www.athletics.ubc.ca2 Source: UBC Athletics facilities manager3 Source: UBC Campus & Community Planning4 Source: UBC LiDar5 Source: UBC Utilities6 Estimate based on UBC average of 4 kg waste per m2 per year (source: UBC Sustainability Office)FACTS & FIGURES(Based on annual consumption Sept. 2010 - Sept. 2011)• Varsity sports teams: Men’s Football• Year built: 1967• Anticipated life span: 60 years 1• Spectator capacity: 3,500 1• Venue area: 3,156 m2 (building) & 11,250 m2 (field) 1• Venue volume: 26,608 m3 2• Primary construction materials: Concrete• Field type: Synthetic grass• Grid electricity: 490,000 kWh 3• Water: 12,969,000 L 3• Overlay materials: Negligible• Waste: 12,600 kg• Construction materials (for field)• Grass (polyethylene): 1.288 kg per m2 4• Primary backing (polypropylene): 0.271 kg per m2 4• Secondary coating .61 kg per m2 4• Sand 22 kg per m2 4• Rubber 16.65 kg per m2 4• Field maintenance:• Diesel: 200 L 5• Fertilizer 23-3-23: 475 kg 5• Fertilizer 18-18-18: 125 kg 51 Source: UBC Athletics facilities manager2 Source: UBC LiDar3 Source: UBC Utilities4 Source: UBC Athletics5 Source: UBC Athletics maintenanceVenues - UBC Athletics & RecreationIMPACTS FOR 2014 GAMES —JULY 8-12, 2014Climate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)240 2.70E-01 170,000 4,400,000036912Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasFuel−fieldChemicals−fertilizerWastewaterWater−buildingWasteConstruction−fieldConstruction−buildingElectricity and heatingThunderbird Stadium [Football]© 2011 UBC Athletics & Recreation, by permission © 2011 UBC Athletics & Recreation, by permission193 Venues – UBC Athletics & Recreation (continued)    The UBC Tennis Centre was built in September, 2011 and consists of six indoor tennis courts, offices, and a viewing area.Electricity and heating contribute 46% for climate change, 47% for human health, 37% for ecosystem quality, and 54% for resources. This is primarily due to hydro electricity for lighting and plug loads as well as natural gas for heating.Construction materials contribute approximately 42% for climate change, 47% for human health, 46% for ecosystem quality, and 45% for resources. The assumptions are based on average construction materials per square meter of a typical building, which is not necessarily representative of this building since it is an open structure with few walls. It is recommended that a future investigation be carried out to improve the accuracy of these estimations.Waste impacts, although likely overestimated, contribute 11% to climate change and less than 1% of the impacts in the other categories.Wastewater impacts in the human health (5%) and ecosystem quality (15%) categories are a result of treatment of wastewater contents and the associated infrastructure materials, transports, and land use burdens. This scenario assumes that 100% of water becomes wastewater.Tap water makes up 1% or less of the contribution for all impact categories. A full year’s worth of water metering was not yet available and therefore an estimate was made based on the first four months of usage.The Varsity Soccer Field consists of a synthetic grass field and has no permanent facilities attached.Construction materials are the primary impact for all categories at 95% for climate change, 90% for human health, 89% for ecosystem quality, and 97% for resources. Within the materials used to construct the synthetic field, rubber contributes over 80% of the impact in all categories. Although the turf manufacturer reported using recycled rubber, the LCA process used is based on virgin rubber and therefore these results likely represent a higher impact. Information from the turf manufacturer was only provided for one average field type. The material composition of individual fields may vary however.Electricity and heating contribute 10% or less of impacts to all damage categories. These impacts can be attributed to the use of hydro electricity for field lighting.Fuel use by tractors for field maintenance contribute 3% to the human health impact and less than 1% to the remaining categories.The impacts from water irrigation and chemical fertilizer use are minor as they are only applied to the real grass on the field periphery.Waste impacts are negligible at under 0.1% for all categories.FACTS & FIGURES(Based on annual consumption Sept. 2010 - Sept. 2011)• Varsity sports teams: Men’s & Women’s Tennis• Year built: 2011 1• Anticipated life span: 60 years 2• Spectator capacity: none 1• Venue area: 7,178 m2 3• Venue volume: not available• Floors: 1 3• Primary construction materials: Steel 3• Grid electricity: 264,600 kWh 4• Heating from natural gas: 540 kWh 4• Water: 1,000,000 L 5• Overlay materials: Negligible• Waste: 29,000 kg 61 Source: www.athletics.ubc.ca2 Source: UBC Athletics facilities manager3 Source: UBC Campus & Community Planning4 Source: UBC Utilities5 Estimate based on average use of other UBC Athletics buildings (water meter information not yet available)6 Estimate based on UBC average of 4 kg waste per m2 per year (source: UBC Sustainability Office)Venues - UBC Athletics & Recreation Venues - UBC Athletics & RecreationIMPACTS FOR 2014 GAMES —JULY 8-12, 2014Climate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)89 1,200,000 8.00E-02 38,000IMPACTS FOR 2014 GAMES —JULY 8-12, 2014Climate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)38 1,200,000 2.20E-02 6,20001234Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasWaterWastewaterWasteConstructionElectricity and heating012Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasChemicals−fertilizerFuel−fieldElectricityConstructionUBC Tennis Centre [Tennis] Varsity Field [Soccer]© 2011 UBC Athletics & Recreation, by permission194 Venues – UBC Athletics & Recreation (continued)    The Varsity Soccer Field consists of a synthetic grass field and has no permanent facilities attached.Construction materials are the primary impact for all categories at 95% for climate change, 90% for human health, 89% for ecosystem quality, and 97% for resources. Within the materials used to construct the synthetic field, rubber contributes over 80% of the impact in all categories. Although the turf manufacturer reported using recycled rubber, the LCA process used is based on virgin rubber and therefore these results likely represent a higher impact. Information from the turf manufacturer was only provided for one average field type. The material composition of individual fields may vary however.Electricity and heating contribute 10% or less of impacts to all damage categories. These impacts can be attributed to the use of hydro electricity for field lighting.Fuel use by tractors for field maintenance contribute 3% to the human health impact and less than 1% to the remaining categories.The impacts from water irrigation and chemical fertilizer use are minor as they are only applied to the real grass on the field periphery.Waste impacts are negligible at under 0.1% for all categories.FACTS & FIGURES(Based on annual consumption Sept. 2010 - Sept. 2011)• Varsity sports teams: Men’s & Women’s Tennis• Year built: 2011 1• Anticipated life span: 60 years 2• Spectator capacity: none 1• Venue area: 7,178 m2 3• Venue volume: not available• Floors: 1 3• Primary construction materials: Steel 3• Grid electricity: 264,600 kWh 4• Heating from natural gas: 540 kWh 4• Water: 1,000,000 L 5• Overlay materials: Negligible• Waste: 29,000 kg 61 Source: www.athletics.ubc.ca2 Source: UBC Athletics facilities manager3 Source: UBC Campus & Community Planning4 Source: UBC Utilities5 Estimate based on average use of other UBC Athletics buildings (water meter information not yet available)6 Estimate based on UBC average of 4 kg waste per m2 per year (source: UBC Sustainability Office)FACTS & FIGURES(Based on annual consumption Sept. 2010 - Sept. 2011)• Varsity sports teams: Men’s Soccer• Year built: 2008• Anticipated life span: 10 years 1• Spectator capacity: 300 1• Venue area: 6,898 m2 1• Field type: Synthetic grass• Grid electricity (field lighting): 11,400 kWh 2• Water (for irrigation): 0 L 2• Overlay materials: Negligible• Waste: Negligible• Construction materials (for field)• Grass (polyethylene): 1.288 kg per m2 3• Primary backing (polypropylene): 0.271 kg per m2 3• Secondary coating .61 kg per m2 3• Sand 22 kg per m2 3• Rubber 16.65 kg per m2 3• Field maintenance:• Diesel: 30 L 4• Fertilizer 23-3-23: 75 kg 41 Source: UBC Athletics facilities manager2 Source: UBC Utilities3 Source: UBC Athletics4 Source: UBC Athletics maintenanceVenues - UBC Athletics & RecreationIMPACTS FOR 2014 GAMES —JULY 8-12, 2014Climate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)38 1,200,000 2.20E-02 6,200012Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasChemicals−fertilizerFuel−fieldElectricityConstructionVarsity Field [Soccer]© 2011 UBC Athletics & Recreation, by permission © 2011 UBC Athletics & Recreation, by permission195 Venues – UBC Athletics & Recreation (continued)    The War Memorial Gymnasium consists of an indoor basketball/volleyball gymnasium with spectator seats, offices, classrooms, and research laboratories.Electricity and heating contribute 75% for climate change, 21% for human health, 10% for ecosystem quality, and 81% for resources. This is primarily due to hydro electricity for lighting and plug loads as well as steam for heating.Construction materials contribute approximately 22% to climate change, 69% to human health, 68% to ecosystem quality, and 18% to resources respectively. The assumptions are based on average construction materials per m2 of a typical building, which is not necessarily representative of this building since it has a number of open spaces with few walls.Wastewater impacts in the human health (10%) and ecosystem quality (21%) categories are a result of treatment of wastewater contents and the associated infrastructure materials, transports, and land use burdens. This scenario assumes that 100% of water becomes wastewater.Waste and water contribute less than 2% of the impacts in all categories.Waste impacts are negligible at under 0.1% for all categories.FACTS & FIGURES(Based on annual consumption Sept. 2010 - Sept. 2011)• Varsity sports teams: Men’s & Women’s Basketball, Men’s & Women’s Volleyball• Year built: 1950 1• Anticipated life span: 65 years 2• Spectator capacity: 2,800 1• Venue area: 12, 674 m2 3• Venue volume: 61,082 m3 3• Floors: 5 3• Primary construction materials: Concrete 3• Grid electricity: 275,000 kWh 4• Heating from steam: 1,469,000 kWh 4• Water: 10,840,000 L 4• Overlay materials: Negligible• Waste: 51,000 kg 51 Source: www.athletics.ubc.ca2 Source: UBC Athletics facilities manager3 Source: UBC Campus & Community Planning4 Source: UBC Utilities5 Estimate based on UBC average of 4 kg waste per m2 per year (source: UBC Sustainability Office)Venues - UBC Athletics & RecreationIMPACTS FOR 2014 GAMES —JULY 8-12, 2014Climate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)880 4.50E-01 300,000 15,000,000010203040Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasWaterWastewaterWasteConstructionElectricity and heatingc) UBC War Memorial GymWar Memorial Gym [Basketball, Volleyball]© 2011 UBC Athletics & Recreation, by permission196 Venues – UBC Athletics & Recreation (continued)    The Warren Soccer Field consists of a synthetic grass field and has no permanent facilities attachedConstruction materials were the primary impact for all categories at 93%, 88%, 88%, and 97% for climate change, human health, ecosystem quality, and resources respectively. Within the materials used to construct the synthetic field, rubber contributes over 80% of the impact in all categories. Although the turf manufacturer reported using recycled rubber, the LCA process used is based on virgin rubber and therefore these results likely represent a higher impact. Information from the turf manufacturer was only provided for one average field type. The material composition of individual fields may vary however.Electricity and heating contribute 11% or less of impacts to all damage categories. These impacts can be attributed to the use of hydro electricity for field lighting.The impacts from water irrigation, chemical fertilizer use and fuel use are minor contributors at 2% or less for all categories since they are only applied to the real grass on the field periphery.Waste impacts are negligible at under 0.1% for all categories.FACTS & FIGURES(Based on annual consumption Sept. 2010 - Sept. 2011)• Varsity sports teams: Men’s & Women’s Basketball, Men’s & Women’s Volleyball• Year built: 1950 1• Anticipated life span: 65 years 2• Spectator capacity: 2,800 1• Venue area: 12, 674 m2 3• Venue volume: 61,082 m3 3• Floors: 5 3• Primary construction materials: Concrete 3• Grid electricity: 275,000 kWh 4• Heating from steam: 1,469,000 kWh 4• Water: 10,840,000 L 4• Overlay materials: Negligible• Waste: 51,000 kg 51 Source: www.athletics.ubc.ca2 Source: UBC Athletics facilities manager3 Source: UBC Campus & Community Planning4 Source: UBC Utilities5 Estimate based on UBC average of 4 kg waste per m2 per year (source: UBC Sustainability Office)FACTS & FIGURES(Based on annual consumption Sept. 2010 - Sept. 2011)• Varsity sports teams: Women’s Soccer• Year built: 2008• Anticipated life span: 10 years 1• Spectator capacity: 300 1• Venue area: 5,434 m2 1• Field type: Synthetic grass• Grid electricity (field lighting): 11,400 kWh 2• Water (for irrigation): 0 L 2• Overlay materials: Negligible• Waste: Negligible• Construction materials (for track)• Grass (polyethylene): 1.288 kg per m2 3• Primary backing (polypropylene): 0.271 kg per m2 3• Secondary coating .61 kg per m2 3• Sand 22 kg per m2 3• Rubber 16.65 kg per m2 3• Field maintenance:• Diesel: 31 L 4• Fertilizer 23-3-23: 75 kg 41 Source: UBC Athletics facilities manager2 Source: UBC Utilities3 Estimate based on information from turf manufacturer4 Source: UBC Athletics maintenanceVenues - UBC Athletics & RecreationIMPACTS FOR 2014 GAMES —JULY 8-12, 2014Climate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)31 970,000 1.80E-02 5,4000.00.51.01.52.0Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasFuel−fieldChemicals−fertilizerElectricityConstructionWarren Field [Soccer]© 2011 UBC Athletics & Recreation, by permission197 Venues – UBC Athletics & Recreation (continued)    The Rugby venue comprises two grass fields and a small wood frame pavilion with locker rooms and office space.Electricity and heating contribute 30% for climate change, 31% for resources and less than 10% in the other categories. This is primarily due to hydro electricity for lighting, plug loads, and heating.Water and wastewater impacts contribute 43% for climate change, 79% for human health, 94% for ecosystem quality, and 46% for resources. These impacts made up a larger percentage relative to other venues due to the high level of water consumption for the relatively small pavilion primarily due to a leak in the water pipes. Impacts include treatment of wastewater contents and the associated infrastructure materials, transports, and land use burdens. This scenario assumes that only the water used by the pavilion becomes wastewater; the water for irrigation is assumed to evaporate or drain naturally.Construction materials contribute 11% to climate change, 5% to human health, 2% to ecosystem quality, and 10% to resources respectively. The assumptions are based on average construction materials per square meter of a typical building, which is not necessarily representative of this venue. It is recommended that a future investigation be carried out to improve the accuracy of these estimations.The impacts from chemical fertilizer use for the grass field are 8% for climate change, 2% for human health, 1% for ecosystem quality, and 7% for resources.Waste impacts contribute less than 3% of the impacts in all categories.FACTS & FIGURES(Based on annual consumption Sept. 2010 - Sept. 2011)• Varsity sports teams: Men’s & Women’s Rugby• Year built: 1963• Anticipated life span: 50 years 1• Spectator capacity: 3,500 1• Venue area: 376 m2 2 (pavilion) & 13,796 m2 (fields) 1• Venue volume (pavilion): 1,309 m3 2• Floors: 1 2• Primary construction materials: Wood 2• Field type: Grass• Grid electricity (pavilion): 36,700 kWh 3• Water: 10,017,000 L (pavilion) & 7,525,000 L (fields) 3• Overlay materials: Negligible• Waste: 1,500 kg 5• Field maintenance:• Diesel: 600 L 6• Fertilizer 23-3-23: 1,500 kg 6• Fertilizer 18-18-18: 500 kg 6• Lime: 3,600 kg 61 Source: UBC Athletics facilities manager2 Source: UBC Campus and Community Planing & UBC LiDar3 Source: UBC Utilities (electricity figure missing, estimate for pavilion based on 100 kWh per m2 based on usage of other Athletics buildings)4 Source: UBC Athletics5 Estimate based on UBC average of 4 kg waste per m2 per year (source: UBC Sustainability Office)5 Source: UBC Athletics maintenanceVenues - UBC Athletics & RecreationIMPACTS FOR 2014 GAMES —JULY 8-12, 2014Climate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)19 5.50E-02 66,000 275,0000.00.30.60.9Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasWasteFuel−fieldsChemicals−fertilizerConstruction−pavillionWastewaterWaterElectricity and heatingWolfson Fields & Pavilion [Rugby]© 2011 UBC Athletics & Recreation, by permission198 Venues – UBC Athletics & Recreation (continued)    The Wright Field Hockey Field consists of a synthetic turf field and has no permanent facilities attached.Construction materials are the primary impact for most categories at 78% for climate change, 66% for human health, 39%, for ecosystem quality, and 89% for resources. Within the materials used to construct the synthetic field, nylon for the synthetic grass contribute the majority of impacts in all categories. Information from the turf manufacturer was only provided for one average field type. The material composition of individual fields may vary however.Electricity and heating contribute 11% to climate change, 22% to human health, 55% to ecosystem quality, and 9% to resources. These impacts can be attributed to the use of hydro electricity for field lighting.Water irrigation contributes 51% to climate change, 11% to human health, 7% to ecosystem quality, and 7% to resources.Fuel use by tractors for field maintenance contribute 11% to the human health impact and 5% or less for the remaining categories.The impacts chemical fertilizer use are 1% or less in all categories as they are only applied to the real grass on the field periphery.Waste impacts are negligible at under 0.1% for all categories.FACTS & FIGURES(Based on annual consumption Sept. 2010 - Sept. 2011)• Varsity sports teams: Men’s & Women’s Rugby• Year built: 1963• Anticipated life span: 50 years 1• Spectator capacity: 3,500 1• Venue area: 376 m2 2 (pavilion) & 13,796 m2 (fields) 1• Venue volume (pavilion): 1,309 m3 2• Floors: 1 2• Primary construction materials: Wood 2• Field type: Grass• Grid electricity (pavilion): 36,700 kWh 3• Water: 10,017,000 L (pavilion) & 7,525,000 L (fields) 3• Overlay materials: Negligible• Waste: 1,500 kg 5• Field maintenance:• Diesel: 600 L 6• Fertilizer 23-3-23: 1,500 kg 6• Fertilizer 18-18-18: 500 kg 6• Lime: 3,600 kg 61 Source: UBC Athletics facilities manager2 Source: UBC Campus and Community Planing & UBC LiDar3 Source: UBC Utilities (electricity figure missing, estimate for pavilion based on 100 kWh per m2 based on usage of other Athletics buildings)4 Source: UBC Athletics5 Estimate based on UBC average of 4 kg waste per m2 per year (source: UBC Sustainability Office)5 Source: UBC Athletics maintenanceFACTS & FIGURES(Based on annual consumption Sept. 2010 - Sept. 2011)• Varsity sports teams: Men’s Baseball• Year built: 2003• Anticipated life span: 8 years 1• Spectator capacity: none• Venue area: 5,973 m2 1• Field type: Synthetic turf• Grid electricity (field lighting): 11,400 kWh 2• Water (for irrigation): 3,500,000 L 2• Overlay materials: Negligible• Waste: Negligible• Construction materials (for track)• Grass (nylon): 2.046 kg per m2 3• Primary backing (polypropylene): 0.26 kg per m2 3• Secondary coating 0.186 kg per m2 3• Sand 22 kg per m2 3• Field maintenance:• Diesel: 40 L 4• Fertilizer 23-3-23: 100 kg 41 Source: UBC Athletics facilities manager2 Source: UBC Utilities3 Estimate based on information from turf manufacturer4 Source: UBC Athletics maintenanceVenues - UBC Athletics & RecreationIMPACTS FOR 2014 GAMES —JULY 8-12, 2014Climate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)17 300,000 7.80E-03 2,2000.00.20.40.60.8Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasFuel−fieldChemicals−fertilizerWater−irrigationElectricityConstructionWright Fields [Field Hockey]© 2011 UBC Athletics & Recreation, by permission © 2011 UBC Athletics & Recreation, by permission199 A.8 Emission Factors - UBC Athletics & Recreation    TRAVELFLOW UNIT CLIMATE CHANGEkg CO2eHUMAN HEALTHDALYECOSYSTEM QUALITYPDF-m2-yrRESOURCESMJ primSOURCEBike pkm 1.25E-02 1.12E-08 2.97E-03 1.90E-01 Ecoinvent 2.2: transport, bicycleCar pkm 2.30E-01 1.27E-07 4.19E-02 3.48E+00 Ecoinvent 2.2: transport, passenger carCoach bus vehicle vkm 1.22E+00 1.34E-06 4.28E-01 1.87E+01 Ecoinvent 2.2: transport, coachPlane pkm 1.29E-01 6.77E-08 1.38E-02 1.90E+00 Ecoinvent 2.2: transport, aircraft, passengerTransit pkm 1.14E-01 1.35E-07 3.41E-02 1.72E+00 Ecoinvent 2.2: transport, regular bus passengerWalk pkm 0 0 0 0 N/AFOODFLOW UNIT CLIMATE CHANGEkg CO2eHUMAN HEALTHDALYECOSYSTEM QUALITYPDF-m2-yrRESOURCESMJ primSOURCEAlcoholic beverage L 1.37E+00 2.44E+01 2.44E-07 2.44E-01 Quantis: based on Comptoir Gruyeren Study (2010)Non-alcoholic beverageL 3.74E-01 7.00E+00 7.00E-08 7.00E-02 Quantis: based on Comptoir Gruyeren Study (2010)Meal kg 1.82E+00 2.00E+01 2.00E-07 2.00E-01 Quantis: based on Comptoir Gruyeren Study (2010)ENERGYFLOW UNIT CLIMATE CHANGEkg CO2eHUMAN HEALTHDALYECOSYSTEM QUALITYPDF-m2-yrRESOURCESMJ primSOURCEElectricity kwh 1.54E-01 2.33E+00 1.43E-07 5.34E-02 Quantis: Electricity, medium voltage, at grid/BCNatural gas MJ 6.88E-02 1.25E+00 5.89E-09 1.62E-03 Ecoinvent 2.2: natural gas, burned in boiler modulating >100kW WATERFLOW UNIT CLIMATE CHANGEkg CO2eHUMAN HEALTHDALYECOSYSTEM QUALITYPDF-m2-yrRESOURCESMJ primSOURCEWater kg 3.20E-04 5.60E-03 2.08E-10 3.21E-04 Ecoinvent 2.2: tap water, at userBUILDING CONSTRUCTION & MATERIALSFLOW UNIT CLIMATE CHANGEkg CO2eHUMAN HEALTHDALYECOSYSTEM QUALITYPDF-m2-yrRESOURCESMJ primSOURCEBuilding multi-storey m3 2.11E+02 2.86E+03 3.30E-04 2.18E+02 Ecoinvent 2.2: building, multi-storyBuilding hall m2 3.13E+02 4.32E+03 3.15E-04 1.45E+02 Ecoinvent 2.2: building, hallSYNTHETIC FIELD CONSTRUCTIONFLOW UNIT CLIMATE CHANGEkg CO2eHUMAN HEALTHDALYECOSYSTEM QUALITYPDF-m2-yrRESOURCESMJ primSOURCESand for base kg 2.11E-02 3.29E-01 7.91E-09 5.05E-03 Ecoinvent 2.2: silica sand, at plantSynthetic grass kg 3.33E+00 1.05E+02 1.32E-06 2.79E-01 Ecoinvent 2.2: polyethylene, HDPE, granulate, at plant + injection moldingPrimary backing kg 2.02E+00 1.61E-06 2.59E-02 7.58E+01 Ecoinvent 2.2: polypropylene, granulate, at plantSecondary coating kg 4.53E+00 2.90E-06 1.91E-01 1.03E+02 Ecoinvent 2.2: polyurethane, rigid foam, at plantFERTILIZERFLOW UNIT CLIMATE CHANGEkg CO2eHUMAN HEALTHDALYECOSYSTEM QUALITYPDF-m2-yrRESOURCESMJ primSOURCEPotassium (K) kg 5.04E-01 9.05E+00 3.03E-07 1.09E-01 Ecoinvent 2.2: potassium chloride, as K2O, at regional storehousePhosphate (P) kg 1.61E+00 2.31E+01 3.27E-06 9.23E-01 Ecoinvent 2.2: monoammonium phosphate, as P2O5, at regional storehousePhosphate (for N) kg 2.84E+00 5.85E+01 2.69E-06 4.40E-01 Ecoinvent 2.2: monoammonium phosphate, as N, at regional storehouseAmmonium Nitrate (for N)kg 8.57E+00 5.98E+01 3.31E-06 6.28E-01 Ecoinvent 2.2: ammonium nitrate, as N, at regional storehouseUrea (for N) kg 3.33E+00 6.79E+01 2.03E-06 4.04E-01 Ecoinvent 2.2: urea, as N, at regional storehouse200 Emission Factors – UBC Athletics & Recreation (continued)  POOL CHEMICALSFLOW UNIT CLIMATE CHANGEkg CO2eHUMAN HEALTHDALYECOSYSTEM QUALITYPDF-m2-yrRESOURCESMJ primSOURCESodium hypochlorite kg 8.92E-01 1.66E+01 5.36E-07 2.06E-01 Ecoinvent 2.2: sodium hypochlorite, 15% in H2O, at plantCalcium chloride kg 9.05E-01 1.10E+01 7.77E-07 2.87E-01 Ecoinvent 2.2: calcium chloride, CaCl2, at regional storageSodium bicarbonate kg 1.06E+00 1.91E+01 5.25E-07 1.87E-01 Ecoinvent 2.2: sodium carbonate from ammonium chloride production, at plantSodium thio sulfate kg 4.66E-01 8.78E+00 2.86E-07 6.58E-02 Ecoinvent 2.2: sodium sulphate, powder, production mix, at plantCalcium hypochlorite kg 4.86E-01 1.04E+01 2.42E-07 7.42E-02 Ecoinvent 2.2: calcium chloride, from hypochlorination of allyl chloride, at plantSoda ash kg 4.45E-01 5.31E+00 3.81E-07 1.43E-01 Ecoinvent 2.2: soda, powder, at plantCyanuric acid kg 1.20E+00 4.67E+01 5.17E-07 1.88E-01 Ecoinvent 2.2: acetic acid from butane, at plantMuriatic acid kg 8.58E-01 1.67E+01 5.42E-07 2.14E-01 Ecoinvent 2.2: hydrochloric acid, 30% in H2O, at plant Diatomaceous earth kg 2.11E-02 3.28E-01 7.86E-09 4.62E-03 Ecoinvent 2.2: silica sand, at plantChemical transport tkm 9.86E-02 1.56E+00 1.06E-07 3.04E-02 Ecoinvent 2.2: transport, 53’ dry van (Class 8) - NACOMMUNICATIONS & MATERIALSFLOW UNIT CLIMATE CHANGEkg CO2eHUMAN HEALTHDALYECOSYSTEM QUALITYPDF-m2-yrRESOURCESMJ primSOURCEPaper kg 1.57E+00 2.62E+01 8.50E-07 7.28E-01 Ecoinvent 2.2: paper, recycling, with deinking, at plantPlastics kg 3.33E+00 1.05E+02 1.32E-06 2.79E-01 Ecoinvent 2.2 - polyethylene, HDPE at plant + injection mouldingTextiles kg 2.74E+01 2.89E+02 2.99E-05 3.34E+01 Ecoinvent 2.2 - textiles, woven cotton, at plantMetal kg 5.24E+00 8.68E+01 4.10E-06 1.88E+00 Ecoinvent 2.2 - Steel at plant + sheet rolling + cold impac t extrusion + manufacturingGlass kg 6.74E-01 1.17E+01 5.18E-07 1.34E-01 Ecoinvent 2.2 - packaging glass, green, at regional storageMaterial transport tkm 9.86E-02 1.56E+00 1.06E-07 3.04E-02 Quantis - transport, 53' dry van (Class 8) -NA WASTEFLOW UNIT CLIMATE CHANGEkg CO2eHUMAN HEALTHDALYECOSYSTEM QUALITYPDF-m2-yrRESOURCESMJ primSOURCELandfill kg 5.63E-01 4.07E-01 2.51E-08 9.12E-03 Ecoinvent 2.2: treatment of municipal solid waste, sanitary landfillCompost kg 3.62E-01 5.32E-01 1.46E-07 2.94E-02 Ecoinvent 2.2: compost, at plantRecycling kg 0 0 0 0 Cut-off, no benefits approachPaper kg 0 0 0 0 Cut-off, no benefits approachWastewater m3 3.57E-01 5.01E+00 4.01E-06 5.71E+00 Ecoinvent 2.2: treatment, sewage, to wastewater treatment, class 2Waste transport tkm 1.36E+00 1.36E-06 1.70E-01 1.96E+01 Ecoinvent 2.2: transport, municipal waste collection, lorry 21t201 Appendix B  Case 2: Data Collection & Impact Assessments by Event Organizational Area for SOC 2014 The following section provides an overview of data collection, assumptions, sources, and impact assessment methods for each organizational area of the 2014 Game case study.  202 B.1 Accommodation – SOC 2014  Data Assumptions and Sources (per person accommodation night)FLOWN.A.DATAUBCDATAUNIT ASSUMPTIONS DATA SOURCESConstruction 0.007 0.0041 m3 50 m2 per person * 3 m ceiling, 60 yr lifespan Deng & Burnett (2000); UBC Conferences & AccommodationsElectricity 23 5 kWh Building electricity usage / number of occupants US EPA (2005) CHP in the Hotel and Casino sectors; UBC UtilitiesFuels 72 24 MJ Building fuel usage / number of occupants US EPA (2005) CHP in the Hotel and Casino sectors; UBC UtilitiesWater 300 80 L Building water usage / number of occupants Quantis (2010) & Bohdanowicz and Martinac (2007); UBC UtilitiesWastewater 0.3 0.08 m3 100% of tap water to wastewater AssumptionWaste 1 0.50 kg 1 kg per person per night (100% landfilled) Assumption based on Quantis (2010) & UBC Waste DataAccommodation impacts are included for all participants (teams, staff, spectators) who spent nights away from their home for the event. Participants returning home each evening were not included because this did not represent a change in impacts due to the event. Data CollectionFor all participant types, data were captured in GOC registration information. Team data were also captured in GOC invoices since they fed and housed all team members. All participants provided their address of origin, postal code of their place of residence during the event, mode of travel used to the event, and the number of event-related accommodation nights. Participants were asked to only include accommodation nights primarily for attending the event in order to avoid including e.g., nights for an extended vacation in Vancouver.Impact AssessmentImpacts include all upstream processes related to building construction, electricity, fuel, water, wastewater use, and waste related to accommodation. Travel impacts from accommodation to event venues are not included since this is captured under ‘travel’. LCI data were primarily taken from the ecoinvent 2.2 database (NA-background).Two major accommodation types with significantly different characteristics were used by participants and therefore each is modeled: average North American hotel person night and average UBC accommodation person night. The majority of UBC accommodation consisted of dorm-style rooms and therefore the specific room dimensions, energy use, water use, and building type are considered. For off-campus guests, an average North American hotel room night is modeled. The BC energy grid is used for all accommodation options.OutcomesTotal person nights generated by the event was approximately 21,000 over an average of 6.7 nights for spectators, and 6.2 nights for team and staff. The breakdown of person nights was 11,000 for teams, 10,000 for spectators, and 100 for staff. The main contributors in terms of climate change impact for both accommodation types were building construction, electricity use, and fuel use.Although there were a similar number of team and spectator person nights, the climate change impact of spectators at 110 t CO2e was more than double that of team members at 41 t CO2e because spectators predominantly used average North American hotel rooms for accommodation. The relatively small number of staff contributed a significantly smaller impact of approximately 1 t CO2e.Key FiguresTotal person nights: 21,000 (11,000 team, 10,000 spectator, 100 staff )Average nights in Vancouver: 6.7 spectator, 6.2 team, 6.2 staffTOTAL IMPACT FOR GAMES ACCOMMODATIONClimate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)151.75 0.077 63,925 2,256,450030,00060,00090,000Team Staff SpectatorkgCO2eCLIMATE CHANGE IMPACT FOR ACCOMMODATION BY PARTICIPANT TYPEIMPACT PER TYPICAL UBC ACCOMMODATION PERSON NIGHTIMPACT PER TYPICAL NORTH AMERICAN HOTEL PERSON NIGHT0.00000.00020.0004Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasWasteWastewaterWaterFuelsElectricityConstruction0.000000.000050.000100.00015Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasWasteWastewaterWaterFuelsElectricityConstruction203 B.2 Communication – SOC 2014  This area includes materials and energy use related primarily to Games’ communications and operations for all participants at the event as well as for communication activities to external audiences such as the website, posters, and online video streaming.Data CollectionAssumptions for communication data are based on rough estimations by the GOC. Specific mass and $ value were supplied by the GOC based on purchase orders from major event suppliers. The transport assumptions are based on industry averages and other studies undertaken by Quantis Intl. IT use is based on GOC estimates. The Internet time per person is based on assumed web traffic statistics.Impact AssessmentOn-site communication material includes production, use, and end-of-life impacts for clothing, paper, textile merchandise, giveaways, and signage provided by the GOC. Note that athlete uniforms are provided by the Provincial chapters for ongoing use and are not provided by the event itself. TV, radio, newspaper, and advertising impacts were not included as they were considered negligible contributors based on initial estimates.Virtually all sport equipment (e.g., soccer balls) and overlay materials (e.g., seating or fencing) were rented or borrowed and were therefore excluded as the impacts were considered minimal for this event.OutcomesThe main impacts for the event across all impact categories was the production of the materials purchased by the event. Transportation of materials to the event, use at the event of energy for communication, and waste treatment combined for less than 15% of climate change.Key FiguresEvent materials: 3,600 shirts; 3,600 hats; 3,600 water bottles; 1500 umbrellas; 500 pins.Event paper: 200 kgEvent web streaming: 2,150 hrs Data Assumptions and SourcesFLOW DATA UNIT ASSUMPTIONS DATA SOURCESMaterial production 2158 kg Metal, plastic, glass, paper and textile materials Manufacturer websites for materials. GOC Invoices.Transport to event 1544 tkm Estimate 720 km travel of materials from regional storage to UBC Quantis guidelines for average transport in NA marketIT use 46012,000kWhh2150 hrs web streaming 2500 hrs internet use at 0.0017 kWh per min. at Games time; 2 computers pre-games & 40 computers games-timeInternet time is estimated. Web streaming data from GOC.Computer time estimated based on GOC invoices.End-of-life 2158 kg All materials to landfill, 20 km transport to landfill included AssumptionTOTAL IMPACT FOR GAMES COMMUNICATIONS & MATERIALSClimate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)13 0.013 6,129 246,5090.00.20.40.6Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasIT useTransport to eventEnd of lifeMaterial productionShirtUmbrellasHatWater BottlePaperSignageFlagsPins0 200 400 600Mass (kg)TOTAL MASS COMMUNICATION MATERIALThis area includes all food and beverages consumed at the event and during side-events (e.g., the Friends and Family BBQ). Data CollectionData for meals sold was primarily supplied by the food vendors and GOC invoices. The GOC provided breakfast, lunch, and dinner to all team members for the duration of the Games at the Athletes Village. Staff were served meals while they were on duty, usually either a lunch or dinner per person per day. Spectators purchased food during the event from both Games-provided and nearby vendors. A large barbeque was also organized by the GOC for Friends and Family on one evening for 1,000 people.Impact AssessmentSince detailed information on the meal ingredients and sources were not available, an estimation is made for a ‘typical meal’ of fruit, vegetables, starch, meat, and dairy based on an LCA study SEMGEST (2008) of an event in France. Alcoholic, non-alcoholic beverages and tap water are assessed separately since their relative impacts differ significantly – i.e., alcoholic drinks have a carbon footprint approximately 3.5 times higher than non-alcoholic drinks, and 3,500 times higher than tap water.OutcomesThe main impacts for the event across all impact categories was the meal ingredients themselves purchased for the event. In terms of climate change, this represented 82% of the total. The team participants consumed 80% of the meals and therefore contributed the highest environmental impact in all categories for this organizational area.Key FiguresTotal meals served: 40,000Total beverages served: 20,000 Liters204 B.3 Food – SOC 2014  0.00000.00010.00020.0003Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasPreparation and storageTransport to eventBeverage ingredientsFood ingredients010,00020,00030,000Team Staff SpectatorMealsTOTAL MASS COMMUNICATION MATERIAL TOTAL MEALS BY PARTICIPANT TYPEThis area includes all food and beverages consumed at the event and during side-events (e.g., the Friends and Family BBQ). Data CollectionData for meals sold was primarily supplied by the food vendors and GOC invoices. The GOC provided breakfast, lunch, and dinner to all team members for the duration of the Games at the Athletes Village. Staff were served meals while they were on duty, usually either a lunch or dinner per person per day. Spectators purchased food during the event from both Games-provided and nearby vendors. A large barbeque was also organized by the GOC for Friends and Family on one evening for 1,000 people.Impact AssessmentSince detailed information on the meal ingredients and sources were not available, an estimation is made for a ‘typical meal’ of fruit, vegetables, starch, meat, and dairy based on LCA studies of the Comptoir Gruyeren event in Lausanne, Switzerland (Quantis, 2010) and the SEMGEST event in Paris, France (PRAXIS 21 STEP, 2008). Alcoholic, non-alcoholic beverages and tap water are assessed separately since their relative impacts differ significantly – i.e., alcoholic drinks have a carbon footprint approximately 3.5 times higher than non-alcoholic drinks, and 3,500 times higher than tap water.OutcomesThe main impacts for the event across all impact categories was the meal ingredients themselves purchased for the event. In terms of climate change, this represented 82% of the total. The team participants consumed 80% of the meals and therefore contributed the highest environmental impact in all categories for this organizational area.Key FiguresTotal meals served: 40,000Total beverages served: 20,000 LitersTOTAL IMPACT FOR GAMES FOODClimate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)112.99 1.342 394,017 1,654,714Data Assumptions and Sources (per meal)FLOW DATA UNIT ASSUMPTIONS DATA SOURCESFood ingredients 0.400 kg 0.05 kg Apple; 0.05 kg Rice; 0.10 kg Red meat; 0.10 kg Potato; 0.10 kg CheeseBilan carbone de la SEMGEST (2008)Beverages ingredients 0.500 kg 0.03 kg Alcohol (50% beer in glass bottle, 50% wine); 0.18 kg Non-alcoholic; 0.30 kg Tap water Quantis Comptoir Gruyeren (2010) & Nestle Waters (2015)Transportation to event 0.432 tkm Transportation of 0.400 kg food and 0.210 kg beverage ingredients  * distance of 720 km from production to eventQuantis guidelines for average transport in NA marketPreparation & storage 1.06 kWh 0.800 kWh Cooking; 0.0700 kWh ingredient refrigeration; 0.1200 kW warming during service; 0.0700 kWh refrigeration during service.Bilan carbone de la SEMGEST (2008)Waste n/a kg Included under ‘Waste’ section N/A205 B.4 Waste – SOC 2014  Waste includes all on-site garbage sent to landfill, compost and recycling at the designated event venues (competition, food, and operations spaces). Off-site waste impacts (e.g., affiliated hotels) are embedded in estimations for those sections.Data CollectionUBC and the City of Richmond provided garbage, recycling and compost bins at all venues, ensuring that bins were both available and accessible. These bins were accompanied by signage with consistent colours throughout the event venues to encourage waste sorting. Sorting stations were set up at the sustainability booth with event-specific signage at all bins for participants and spectators. Data were collected by SOC 2014 sustainability volunteers. This consisted of recording waste bin fill % (by volume) for each of four bin types at the event venues: municipal, compost, recycling (plastics, glass, metal), and paper.Impact AssessmentImpacts include transport to end-of-life as well as end-of-life treatment. LCI data were taken from the ecoinvent 2.2 database (NA-background). For recycling, a cut-off, no benefits approach is applied to avoid giving credits to both the organization recycling the waste and the organization using the recycled material. This helps avoid the issue of whether 100% of waste sent to recycling actually gets recycled.OutcomesTotal waste generated by the event was approximately 4 tonnes per day over 5.5 days (the additional 0.5 day is a best estimate to capture pre- and post-event waste), totalling 22 tonnes for the event. The approximate waste composition breakdown by mass was 54% compost, 9% recycling, 5% paper and 32% waste, with a total waste diversion of 68%. The majority of waste came from food and food packaging, virtually all of which was compostable. It should be noted that the Games prioritized rental and reuse of equipment wherever possible, significantly reducing the amount of waste generated compared to many events. The GOC assumed that 80% of equipment for sport, overlay (e.g., tents, tables, seating), and office was rented or borrowed.Key FiguresTotal waste generated by SOC 2014: 22 tonnesWaste per person per day: 0.9 kgGames recycling rate (diversion from landfill): 68%— 54% compost, 9% recycling, 5% paperData Assumptions and Sources (per 1 kg waste)FLOW DATA UNIT ASSUMPTIONS DATA SOURCESWaste to landfill 0.032 kg 32% of event waste to landfill On-site data collectionWaste to compost 0.054 kg 18% of event waste to compost. 2.33 kg fresh organics to produce 1 kg compost On-site data collection.Waste to recycling 0.009 kg 9% of waste to recycling. No recycling credits On-site data collectionWaste to paper recycling 0.005 kg 9% of waste to paper recycling. No recycling credits On-site data collectionTransport to landfill 0.0095 tkm Delta landfill is 30 km (one way) from UBCUBC Operations for locations; Google Maps for distancesTransport to compost 0.0005 tkm Assume 1 km trip (one-way) to compost plant (at UBC)Transport to recycling 0.0028 tkm Assume 20 km trip (one way) to recycling plantTOTAL IMPACT FOR GAMES WASTEClimate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)6.3 0.0014 258 11,694TOTAL WASTE MASS GENERATED AND TRANSPORTED TO TREATMENTLandfill Compost Recycling Paperkg tkm kg tkm kg tkm kg tkm02,5005,0007,50010,0000.0000000.0000050.000010Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionAreasPaperRecyclingCompostLandfill206 B.5 Travel – SOC 2014    05001,0001,5002,000To Games At GamestonnesCO2eTRAVEL CARBON FOOTPRINT TO GAMES VERSUS AT GAMESTOTAL CARBON FOOTPRINT TO GAMES BY PARTICIPANT TYPE AND MODEParticipant travel includes team, staff, and spectator participants both to the Games and at the Games. Team participants includes 1,800 athletes, coaches, and mission staff. Staff participants includes 1,400 Games-time volunteers and 100 organizing committee volunteers as well as one paid staff person. The 1,900 spectator participants were almost exclusively made up of friends and family of the athletes.Data CollectionTravel data for teams, staff and volunteers came from registration information collected by the GOC and included city of origin, mode share to and at the Games, and occupancy rates in cars. Spectator and volunteer staff travel information was supplemented by an on-line survey conducted during the Games to test validity.Impact AssessmentEmission factors were applied for six modes of travel: bike, transit, coach bus, car, plane, and walk. Impacts are based on the manufacture, operation, and end-of-life each mode, as well as a share of infrastructure used (e.g., road or airport). Emission factors for car and transit modes were adjusted to reflect occupancy rates for the Vancouver 2010 context. For coach bus and plane modes, the industry average occupancy rates were used since it was not anticipated that the Games would affect them significantly.Travel “to” the Games refers to round trip travel for staff, spectators, and team from their city of origin to the event. Participants whose accommodation was on-site only had one round trip counted. Participants who did not live on-site (typically staff ), had daily round trips counted. Impacts were determined by applying the average distance travelled from the city of origin to the event per mode and the % of the total number of people who reported using each mode. Travel “at” the Games refers to the shuttle bus and vehicle fleet operated and managed by the GOC. Impacts are not broken down by participant type as this information was not captured as there was mixed use of these modes. The average travel distance per trip was multiplied by the total number of vehicle trips taken.OutcomesTeam and spectator travel dominate travel impacts across all environmental damage categories. Plane travel dominates as the mode with the highest contribution in terms of climate change for all three participant types with 98% for team, 80% for spectators, and 97% for staff of the respective totals. Overall, the carbon footprint to the Games was much higher at 2,184 tonnes CO2e than the footprint at the Games with 8 tonnes CO2e.Key FiguresTotal travel distance to Games by participants: 17,000,000 kmTotal travel distance at Games by participants: 18,000 vkmTOTAL IMPACT FOR GAMES TRAVEL TO AND AT THE GAMESClimate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)2,174 1.16 254,436 32,167,4060255075100Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasFleet vehicles at eventShuttles at eventVolunteer staff to GamesGOC staff to GamesSpectators to GamesTeam to Games0300600900Team Spectators StafftonnesCO2eModeWalkBikeTransitCarCoach−busPlane207 Travel – SOC 2014 (continued)  Data Assumptions and SourcesSPECTATOR TRAVEL TO GAMESFLOW DATA UNIT ASSUMPTIONS DATA SOURCESBike 1,250 pkm To Vancouver: modal split of 0% of 1,900 people and average return distance of 0 km Van. to Games: modal split of 1.7% of 1,500 people and average return distance of 10 km ppl for 5 daysGOC Spectator RegistrationCar 1,451,681 pkm To Vancouver: modal split of 46.7% of 1,900 and average return distance of 1,693 km Van. to Games: modal split of 1.7% of 1,500 people and average return distance of 25 km ppl for 5 daysGOC Spectator RegistrationCoach bus 52,950 pkm To Vancouver: modal split of 0.6% of 1,900 people and average return distance of 4,870 km Van. to Games: modal split of 28.3% of 1,500 people (included in Shuttle Bus travel)GOC Spectator RegistrationPlane 6,161,778 pkm To Vancouver: modal split of 56.2% of 1,900 people and average return distance of 5,776 km Van. to Games: modal split of 0% of 1,500 people and average return distance of 0 km ppl for 0 daysGOC Spectator RegistrationTransit 4,117 pkm To Vancouver: modal split of 0.7% of 1,900 people and average return distance of 119 km Van. to Games: modal split of 1.7% of 1,500 people and average return distance of 20 km ppl for 5 daysGOC Spectator RegistrationWalk 8,179 pkm To Vancouver: modal split of 0.1% of 1,900 people and average return distance of 20 km Van. to Games: modal split of 21.7% of 1,500 people and average return distance of 5 km ppl for 5 daysGOC Spectator RegistrationSTAFF TRAVEL TO GAMESFLOW DATA UNIT ASSUMPTIONS DATA SOURCESBike 4,650 pkm Modal split of 9% of 1,000 people and average return distance of 10 km GOC Registration and Games SurveyCar 58,625 pkm Modal split of 41% of 1,000 people and average return distance of 21 km GOC Registration and Games SurveyCoach bus 850 pkm Modal split of 2% of 1,000 people and average return distance of 35 km GOC Registration and Games SurveyPlane 660,000 pkm Modal split of 10% of 1,000 people and average return distance of 6,600 km GOC Registration and Games SurveyTransit 36,400 pkm Modal split of 36% of 1,000 people and average return distance of 20 km GOC Registration and Games SurveyWalk 675 pkm Modal split of 5% of 1,000 people and average return distance of 3 km GOC Registration and Games SurveyTEAM TRAVEL TO GAMESFLOW DATA UNIT ASSUMPTIONS DATA SOURCESBike 0 pkm Modal split of 0% and actual distance from home city to event GOC Team RegistrationCar 70,650 pkm Modal split of 0% and actual distance from home city to event GOC Team RegistrationCoach bus 122,410 pkm Modal split of 19% and actual distance from home city to event GOC Team RegistrationPlane 8,211,300 pkm Modal split of 81% and actual distance from home city to event GOC Team RegistrationTransit 0 pkm Modal split of 0% and actual distance from home city to event GOC Team RegistrationWalk 0 pkm Modal split of 0% and actual distance from home city to event GOC Team RegistrationSHUTTLE BUS AT GAMESFLOW DATA UNIT ASSUMPTIONS DATA SOURCESCoach Bus to Airport 2,560 vkm 64 vehicle trips * average distance of 40 km / trip Distances from Google maps. Trip numbers from GOCCoach Bus to Bowling 1,250 vkm 25 vehicle trips * average distance of 50 km / trip Distances from Google maps. Trip numbers from GOCTransit to Golf 30 vkm 10 vehicle trips * average distance of 3 km / trip Distances from Google maps. Trip numbers from GOCCoach Bus to UBC (loop) 1,500 vkm 250 vehicle trips * average distance of 6 km / trip Distances from Google maps. Trip numbers from GOCCoach Bus to Ceremonies 84 vkm 28 vehicle trips * average distance of 3 km / trip Distances from Google maps. Trip numbers from GOCVEHICLE FLEET AT GAMESFLOW DATA UNIT ASSUMPTIONS DATA SOURCESBike 500 vkm 10 vehicles * average distance of 50 km / event GOC Budget & Vehicle RecordsCar 9,600 vkm 32 vehicles * average distance of 300 km / event GOC Budget & Vehicle RecordsCoach bus 2,400 vkm 8 vehicles * average distance of 300 km / event GOC Budget & Vehicle RecordsPlane 0 vkm n/a n/aTransit 0 vkm n/a n/aWalk 0 vkm n/a n/a208 B.6 Venues – SOC 2014   TOTAL IMPACT FOR GAMES VENUESClimate Change  (t CO2e)Human Health (DALY)Ecosystem Quality (PDF•m2•yr)Resources (MJ Prim)25,284 0.016 24,649 379,758Venues includes the following competition venues rented for the period of the SOC 2014 Games:• UBC Aquatic Centre [Swimming]• Zone Bowling Alley [5- and 10-Pin Bowling]• UBC Doug Mitchell Thunderbird Sports Centre [Powerlifting, Rhythmic Gymnastics, Ceremonies]• University Golf Course & Clubhouse [Golf ]• Noble Park [Softball]• UBC Thunderbird Park [Soccer, Bocce, Softball, Track & Field]• UBC War Memorial Gym [Basketball]Food and accommodation venues are included in those respective areas. All venues were pre-existing and were rented out for Games-time.Data CollectionAll data were provided by the venue operators. Utilities data were either actual usage for the period of used by the Games or usage over a monthly or quarterly period of the same time period as the Games, in which case an average per day was estimated for period of the event.Impact AssessmentImpacts include resource extraction, production, transportation, operation, and end-of-life impacts for venue construction, electricity, fuels, tap water, and wastewater for all venues. Venue construction impacts are based on three building archetypes within ecoinvent 2.2: wood, steel, and concrete buildings. As construction was not a major contributor of environmental impacts, these proxies were considered sufficient; however it should be noted that sport venues may vary significantly in their building material composition to these proxies.LCI data are taken from the ecoinvent 2.2 database (NA-background). Travel to the venues and waste generated by event operation within venues is included under ‘travel’ and ‘waste’ organizational areas respectively.OutcomesThe Aquatic Centre and Doug Mitchell Arena contributed the most for the environmental impact categories of climate change, human health, and resources, largely due to energy used for heating, cooling, lighting, and plug loads. For ecosystem quality, the major contributors were the Aquatic Centre, Doug Mitchell Arena, University Golf Course, and Thunderbird Park.Each venue varied significantly in terms of their pattern of impacts. Two examples are illustrated right for UBC Doug Mitchell Thunderbird Arena and the UBC Aquatics Centre. In terms of climate change, Doug Mitchell Arena impacts largely came from electricity use for heating, cooling, and for the lighting and sound systems for events and ceremonies. This building uses electricity almost exclusively for its energy needs.The UBC Aquatic Centre also had energy consumption as its highest impact for climate contribution, although largely through fuel use rather than electricity use. This was largely due to pool heating. Key FiguresTotal electricity consumed by venues: 79,000 kW hTotal fuels consumed by venues: 45,502 MJTotal consumed by venues: 2,939,036 Litres0.000.250.500.751.001.25Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emissionVenuesNoble ParkWar Memorial GymBowling AlleyThunderbird ParkGolf CourseDoug MitchellAquatic Centre0.00.10.20.30.40.5Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasWastewaterWaterFuelsElectricityConstruction0.00.10.20.30.40.5Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasWastewaterWaterFuelsElectricityConstructionVENUE IMPACTS FOR UBC AQUATIC CENTREVENUE IMPACTS FOR UBC DOUG MITCHELL ARENAData Assumptions and SourcesAQUATIC CENTRE [SWIMMING]FLOW DATA UNIT ASSUMPTIONS DATA SOURCESConstruction 8.1 m3 26,429 m3 / 40 yr lifespan for 4.5 days using 100% of the venue UBC Athletics & RecreationElectricity 11,836 kWh Building electricity usage for 4.5 days using 100% of the venue UBC UtilitiesFuels 89,021 MJ Building fuel usage for 4.5 days using 100% of the venue UBC UtilitiesWater 501,805 L Building water usage for 4.5 days using 100% of the venue UBC UtilitiesWastewater 502 m3 100% of tap water to wastewater AssumptionBOWLING ALLEY [5- AND 10-PIN BOWLING]FLOW DATA UNIT ASSUMPTIONS DATA SOURCESConstruction 0.5 m2 3,293 m2 / 40 yr lifespan for 4.5 days using 50% of the venue Zone Bowling Centre ManagerElectricity 3,646 kWh Building electricity usage for 4.5 days using 50% of the venue Zone Bowling Centre ManagerFuels 189 MJ Building fuel usage for 4.5 days using 50% of the venue Zone Bowling Centre ManagerWater 72,581 L Building water usage for 4.5 days using 50% of the venue Zone Bowling Centre ManagerWastewater 73 m3 100% of tap water to wastewater AssumptionDOUG MITCHELL THUNDERBIRD SPORTS CENTRE [POWERLIFTING, RHYTHMIC GYMNASTICS & CEREMONIES]FLOW DATA UNIT ASSUMPTIONS DATA SOURCESConstruction 5.8 m2 36,410 m2 / 60 yr lifespan for 7 days using 50% of the venue UBC Athletics & RecreationElectricity 57,009 kWh Building electricity usage for 7 days using 50% of the venue UBC UtilitiesFuels 61 MJ Building fuel usage for 7 days using 50% of the venue UBC UtilitiesWater 530,165 L Building water usage for 7 days using 50% of the venue UBC UtilitiesWastewater 530 m3 100% of tap water to wastewater AssumptionUNIVERSITY GOLF COURSE & CLUB HOUSE [GOLF]FLOW DATA UNIT ASSUMPTIONS DATA SOURCESConstruction 0.23 m2 1,858 m2 / 50 yr lifespan for 4.5 days using 50% of the venue University Golf Club ManagerElectricity 5,371 kWh Building & course electricity usage for 4.5 days using 50% of the venue University Golf Club ManagerFuels 0 MJ Building & course fuel usage for 4.5 days using 50% of the venue University Golf Club ManagerWater 798,387 L Building & course water usage for 4.5 days using 50% of the venue University Golf Club ManagerWastewater 798 m3 100% of tap water to wastewater AssumptionNOBLE PARK [SOFTBALL]FLOW DATA UNIT ASSUMPTIONS DATA SOURCESConstruction 12.9 m2 10,426 m2 / 10 yr lifespan for 4.5 days using 50% of the venue GOCElectricity 0 kWh Field electricity usage for 4.5 days using 50% of the venue Estimate based on UBC Field UtilitiesFuels 0 MJ Field fuel usage for 4.5 days using 50% of the venue Estimate based on UBC Field UtilitiesWater 88,200 L Field water usage for 4.5 days using 50% of the venue Estimate based on UBC Field UtilitiesWastewater 88 m3 100% of tap water to wastewater AssumptionTHUNDERBIRD PARK [SOCCER, SOFTBALL, BOCCE, AND TRACK & FIELD]FLOW DATA UNIT ASSUMPTIONS DATA SOURCESConstruction 39.5 m2 32,000 m2 / 10 yr lifespan for 4.5 days using 50% of the venue UBC Athletics & RecreationElectricity 126 kWh Field electricity usage for 4.5 days using 50% of the venue UBC UtilitiesFuels 0 MJ Field fuel usage for 4.5 days using 50% of the venue UBC UtilitiesWater 907,050 L Field water usage for 4.5 days using 50% of the venue UBC UtilitiesWastewater 907 m3 100% of tap water to wastewater Assumption209 Venues – SOC 2014 (continued)   0.00.10.20.30.40.5Climate Change Human Health Ecosystem Quality Resourcesperson·year / unit emission AreasWastewaterWaterFuelsElectricityConstructionData Assumptions and SourcesAQUATIC CENTRE [SWIMMING]FLOW DATA UNIT ASSUMPTIONS DATA SOURCESConstruction 8.1 m3 26,429 m3 / 40 yr lifespan for 4.5 days using 100% of the venue UBC Athletics & RecreationElectricity 11,836 kWh Building electricity usage for 4.5 days using 100% of the venue UBC UtilitiesFuels 89,021 MJ Building fuel usage for 4.5 days using 100% of the venue UBC UtilitiesWater 501,805 L Building water usage for 4.5 days using 100% of the venue UBC UtilitiesWastewater 502 m3 100% of tap water to wastewater AssumptionBOWLING ALLEY [5- AND 10-PIN BOWLING]FLOW DATA UNIT ASSUMPTIONS DATA SOURCESConstruction 0.5 m2 3,293 m2 / 40 yr lifespan for 4.5 days using 50% of the venue Zone Bowling Centre ManagerElectricity 3,646 kWh Building electricity usage for 4.5 days using 50% of the venue Zone Bowling Centre ManagerFuels 189 MJ Building fuel usage for 4.5 days using 50% of the venue Zone Bowling Centre ManagerWater 72,581 L Building water usage for 4.5 days using 50% of the venue Zone Bowling Centre ManagerWastewater 73 m3 100% of tap water to wastewater AssumptionDOUG MITCHELL THUNDERBIRD SPORTS CENTRE [POWERLIFTING, RHYTHMIC GYMNASTICS & CEREMONIES]FLOW DATA UNIT ASSUMPTIONS DATA SOURCESConstruction 5.8 m2 36,410 m2 / 60 yr lifespan for 7 days using 50% of the venue UBC Athletics & RecreationElectricity 57,009 kWh Building electricity usage for 7 days using 50% of the venue UBC UtilitiesFuels 61 MJ Building fuel usage for 7 days using 50% of the venue UBC UtilitiesWater 530,165 L Building water usage for 7 days using 50% of the venue UBC UtilitiesWastewater 530 m3 100% of tap water to wastewater AssumptionUNIVERSITY GOLF COURSE & CLUB HOUSE [GOLF]FLOW DATA UNIT ASSUMPTIONS DATA SOURCESConstruction 0.23 m2 1,858 m2 / 50 yr lifespan for 4.5 days using 50% of the venue University Golf Club ManagerElectricity 5,371 kWh Building & course electricity usage for 4.5 days using 50% of the venue University Golf Club ManagerFuels 0 MJ Building & course fuel usage for 4.5 days using 50% of the venue University Golf Club ManagerWater 798,387 L Building & course water usage for 4.5 days using 50% of the venue University Golf Club ManagerWastewater 798 m3 100% of tap water to wastewater AssumptionNOBLE PARK [SOFTBALL]FLOW DATA UNIT ASSUMPTIONS DATA SOURCESConstruction 12.9 m2 10,426 m2 / 10 yr lifespan for 4.5 days using 50% of the venue GOCElectricity 0 kWh Field electricity usage for 4.5 days using 50% of the venue Estimate based on UBC Field UtilitiesFuels 0 MJ Field fuel usage for 4.5 days using 50% of the venue Estimate based on UBC Field UtilitiesWater 88,200 L Field water usage for 4.5 days using 50% of the venue Estimate based on UBC Field UtilitiesWastewater 88 m3 100% of tap water to wastewater AssumptionTHUNDERBIRD PARK [SOCCER, SOFTBALL, BOCCE, AND TRACK & FIELD]FLOW DATA UNIT ASSUMPTIONS DATA SOURCESConstruction 39.5 m2 32,000 m2 / 10 yr lifespan for 4.5 days using 50% of the venue UBC Athletics & RecreationElectricity 126 kWh Field electricity usage for 4.5 days using 50% of the venue UBC UtilitiesFuels 0 MJ Field fuel usage for 4.5 days using 50% of the venue UBC UtilitiesWater 907,050 L Field water usage for 4.5 days using 50% of the venue UBC UtilitiesWastewater 907 m3 100% of tap water to wastewater Assumption210 Venues – SOC 2014 (continued)  Data Assumptions and Sources (continued)WAR MEMORIAL GYMNASIUM [BASKETBALL]FLOW DATA UNIT ASSUMPTIONS DATA SOURCESConstruction 1.2 m2 12,674 m3 / 65 yr lifespan for 4.5 days using 50% of the venue UBC Athletics & RecreationElectricity 1,297 kWh Building electricity usage for 4.5 days using 50% of the venue UBC UtilitiesFuels 1,132 MJ Building fuel usage for 4.5 days using 50% of the venue UBC UtilitiesWater 40,848 L Building water usage for 4.5 days using 50% of the venue UBC UtilitiesWastewater 41 m3 100% of tap water to wastewater Assumption211 B.7 Emission factors – SOC 2014   TRAVELFLOW UNIT CLIMATE CHANGEkg CO2eHUMAN HEALTHDALYECOSYSTEM QUALITYPDF-m2-yrRESOURCESMJ primSOURCEBike pkm 1.25E-02 1.12E-08 2.97E-03 1.90E-01 Ecoinvent 2.2: transport, bicycleCar pkm 2.30E-01 1.27E-07 4.19E-02 3.48E+00 Ecoinvent 2.2: transport, passenger carCoach bus vehicle vkm 1.22E+00 1.34E-06 4.28E-01 1.87E+01 Ecoinvent 2.2: transport, coachPlane pkm 1.29E-01 6.77E-08 1.38E-02 1.90E+00 Ecoinvent 2.2: transport, aircraft, passengerTransit pkm 1.14E-01 1.35E-07 3.41E-02 1.72E+00 Ecoinvent 2.2: transport, regular bus passengerWalk pkm 0 0 0 0 N/AFOODFLOW UNIT CLIMATE CHANGEkg CO2eHUMAN HEALTHDALYECOSYSTEM QUALITYPDF-m2-yrRESOURCESMJ primSOURCEAlcoholic beverage L 1.37E+00 2.44E+01 2.44E-07 2.44E-01 Quantis: based on Comptoir Gruyeren Study (2010)Non-alcoholic beverageL 3.74E-01 7.00E+00 7.00E-08 7.00E-02 Quantis: based on Comptoir Gruyeren Study (2010)Apple kg 3.75E-01 5.81E-07 5.78E-01 4.95E+00 Ecoinvent 3.1: market for appleRice kg 1.42E+00 1.35E-06 6.52E-01 1.22E+01 Ecoinvent 3.1: market for riceRed meat kg 9.27E+00 1.24E-05 1.47E+01 5.41E+01 Ecoinvent 3.1: market for red meat, live weightPotato kg 3.14E-01 4.99E-07 8.84E-01 3.89E+00 Ecoinvent 3.1: market for potatoCheese kg 5.42E+00 6.91E-06 5.90E+00 4.45E+01 Ecoinvent 3.1: market for cheese, from cow milk, fresh, unripenedMilk kg 1.35E+00 1.75E-06 1.62E+00 9.21E+00 Ecoinvent 3.1: market for cow milkFood transport tkm 3.04E-01 3.39E-07 1.30E-01 4.75E+00 Ecoinvent 2.2: transport, lorry 3.5-20t, fleet averageENERGYFLOW UNIT CLIMATE CHANGEkg CO2eHUMAN HEALTHDALYECOSYSTEM QUALITYPDF-m2-yrRESOURCESMJ primSOURCEElectricity kwh 1.36E-01 6.59E-08 4.18E-02 1.94E+00 Ecoinvent 3.1: market for electricity, medium voltage (BC)Natural gas MJ 6.94E-02 8.23E-09 1.67E-03 1.26E+00 Ecoinvent 2.2: natural gas, burned in boiler modulating >100kW WATERFLOW UNIT CLIMATE CHANGEkg CO2eHUMAN HEALTHDALYECOSYSTEM QUALITYPDF-m2-yrRESOURCESMJ primSOURCEWater kg 4.39E-04 3.44E-10 3.19E-04 6.39E-03 Ecoinvent 2.2: tap water, at userBUILDING CONSTRUCTION & MATERIALSFLOW UNIT CLIMATE CHANGEkg CO2eHUMAN HEALTHDALYECOSYSTEM QUALITYPDF-m2-yrRESOURCESMJ primSOURCEBuilding multi-storey m3 2.67E+02 3.88E-04 2.27E+02 3.35E+03 Ecoinvent 2.2: building, multi-storyBuilding hall m2 3.60E+02 3.84E-04 1.64E+02 4.73E+03 Ecoinvent 2.2: building, hallSYNTHETIC FIELD CONSTRUCTIONFLOW UNIT CLIMATE CHANGEkg CO2eHUMAN HEALTHDALYECOSYSTEM QUALITYPDF-m2-yrRESOURCESMJ primSOURCESand for base kg 2.34E-02 9.71E-09 4.85E-03 3.43E-01 Ecoinvent 2.2: silica sand, at plantSynthetic grass kg 1.99E+00 1.50E-06 2.49E-02 7.79E+01 Ecoinvent 2.2: polyethylene, HDPE, granulate, at plantPrimary backing kg 2.02E+00 1.61E-06 2.59E-02 7.58E+01 Ecoinvent 2.2: polypropylene, granulate, at plantSecondary coating kg 4.53E+00 2.90E-06 1.91E-01 1.03E+02 Ecoinvent 2.2: polyurethane, rigid foam, at plantCOMMUNICATIONS & MATERIALSFLOW UNIT CLIMATE CHANGEkg CO2eHUMAN HEALTHDALYECOSYSTEM QUALITYPDF-m2-yrRESOURCESMJ primSOURCEComputer h 1.24E-02 9.46E-09 3.86E-03 1.65E-01 Ecoinvent 2.2: use, computer, laptop, office use Paper kg 1.84E+00 1.18E-06 6.29E-01 2.81E+01 Ecoinvent 2.2: paper, recycling, with deinking, at plantTextile (Cotton) kg 2.23E+01 1.95E-05 1.73E+01 3.27E+02 Ecoinvent 2.2: textile, woven cotton, at plantTextile (Fleece) kg 3.03E+00 2.00E-06 1.45E-01 9.57E+01 Ecoinvent 2.2: fleece, polyethylene, at plantPET kg 3.31E+00 5.27E-06 4.31E-01 8.49E+01 Ecoinvent 2.2: polyethylene terephthalate, granulate, bottle grade, at plantSignage (Coroplast) kg 2.02E+00 1.61E-06 2.59E-02 7.58E+01 Ecoinvent 2.2: polypropylene, granulate, at plantSteel kg 5.13E+00 1.05E-05 5.21E+00 7.96E+01 Ecoinvent 2.2: chromium steel 18/8, at plantMaterial transport tkm 3.04E-01 3.39E-07 1.30E-01 4.75E+00 Ecoinvent 2.2: transport, lorry 3.5-20t, fleet averageWASTEFLOW UNIT CLIMATE CHANGEkg CO2eHUMAN HEALTHDALYECOSYSTEM QUALITYPDF-m2-yrRESOURCESMJ primSOURCELandfill kg 5.71E-01 3.01E-08 8.45E-03 4.55E-01 Ecoinvent 2.2: treatment of municipal solid waste, sanitary landfillCompost kg 1.60E-01 6.46E-08 1.28E-02 2.55E-01 Ecoinvent 2.2: compost, at plantRecycling kg 0 0 0 0 Cut-off, no benefits approach.Paper kg 0 0 0 0 Cut-off, no benefits approach.Plastic waste kg 9.89E-02 1.89E-08 4.84E-03 3.43E-01 Ecoinvent 2.2: disposal, plastics, mixture, 15.3% water, to sanitary landfillWastewater m3 5.35E-01 9.69E-07 5.77E+00 6.07E+00 Ecoinvent 2.2: treatment, sewage, to wastewater treatment, class 2Waste transport tkm 1.36E+00 1.36E-06 1.70E-01 1.96E+01 Ecoinvent 2.2: transport, municipal waste collection, lorry 21t212 Emission Factors – SOC 2014 (continued)  COMMUNICATIONS & MATERIALSFLOW UNIT CLIMATE CHANGEkg CO2eHUMAN HEALTHDALYECOSYSTEM QUALITYPDF-m2-yrRESOURCESMJ primSOURCEComputer h 1.24E-02 9.46E-09 3.86E-03 1.65E-01 Ecoinvent 2.2: use, computer, laptop, office use Paper kg 1.84E+00 1.18E-06 6.29E-01 2.81E+01 Ecoinvent 2.2: paper, recycling, with deinking, at plantTextile (Cotton) kg 2.23E+01 1.95E-05 1.73E+01 3.27E+02 Ecoinvent 2.2: textile, woven cotton, at plantTextile (Fleece) kg 3.03E+00 2.00E-06 1.45E-01 9.57E+01 Ecoinvent 2.2: fleece, polyethylene, at plantPET kg 3.31E+00 5.27E-06 4.31E-01 8.49E+01 Ecoinvent 2.2: polyethylene terephthalate, granulate, bottle grade, at plantSignage (Coroplast) kg 2.02E+00 1.61E-06 2.59E-02 7.58E+01 Ecoinvent 2.2: polypropylene, granulate, at plantSteel kg 5.13E+00 1.05E-05 5.21E+00 7.96E+01 Ecoinvent 2.2: chromium steel 18/8, at plantMaterial transport tkm 3.04E-01 3.39E-07 1.30E-01 4.75E+00 Ecoinvent 2.2: transport, lorry 3.5-20t, fleet averageWASTEFLOW UNIT CLIMATE CHANGEkg CO2eHUMAN HEALTHDALYECOSYSTEM QUALITYPDF-m2-yrRESOURCESMJ primSOURCELandfill kg 5.71E-01 3.01E-08 8.45E-03 4.55E-01 Ecoinvent 2.2: treatment of municipal solid waste, sanitary landfillCompost kg 1.60E-01 6.46E-08 1.28E-02 2.55E-01 Ecoinvent 2.2: compost, at plantRecycling kg 0 0 0 0 Cut-off, no benefits approach.Paper kg 0 0 0 0 Cut-off, no benefits approach.Plastic waste kg 9.89E-02 1.89E-08 4.84E-03 3.43E-01 Ecoinvent 2.2: disposal, plastics, mixture, 15.3% water, to sanitary landfillWastewater m3 5.35E-01 9.69E-07 5.77E+00 6.07E+00 Ecoinvent 2.2: treatment, sewage, to wastewater treatment, class 2Waste transport tkm 1.36E+00 1.36E-06 1.70E-01 1.96E+01 Ecoinvent 2.2: transport, municipal waste collection, lorry 21t213 Appendix C  SOC 2014 Organizing Committee Expenditures Expense Amount Finance & Administration $168,951 Ceremonies $143,130 Marketing $56,841 Media $4,245 Volunteer Committee $62,920 Operations $971,317 Accommodations $400,951 Food & Beverage $363,075 Security $3,393 Transportation $66,650 Logistics $1,975 Overlay $46,028 Miscellaneous $89,245 Sport Operations $169,978 Medical Services $46,681 Technology $8,592 Clothing $60,244 Total Expenditures $1,632,655  Source: Somerville, T., & Taylor, B. (2014). Economic Impact of the 2014 Special Olympics Summer Games on the BC Economy. Vancouver, BC: Centre for Urban Economics and Real Estate.    214 Appendix D  SOC 2014 Map  215 Appendix E  SOC 2014 Participant Break-down Province / Territory Spectators Staff Team Total Alberta 213 0 161 374 British Columbia 650 1,400 368 2,418 Manitoba 173 0 123 296 New Brunswick 32 0 62 94 Newfoundland & Labrador 30 0 49 79 Northwest Territories 72 0 11 83 Nova Scotia 5 0 111 116 Nunavut 0 0 – 0 Ontario 491 100 455 1,046 Prince Edward Island 36 0 62 98 Quebec 70 0 192 262 Saskatchewan 68 0 100 168 Yukon 40 0 42 82 Outside Canada 20 0 – 20 Total 1,900 1,500 1,736 5,136  Table 12: Spectator, staff and team quotas for SOC 2014 by Province/Territory. These are unique registered participants, not total daily attendees.   Province / Territory Athletes Coaches Mission Staff Total Alberta 120 30 11 161 British Columbia 277 70 21 368 Manitoba 91 24 8 123 New Brunswick 43 13 6 62 Newfoundland & Labrador 33 12 4 49 Northwest Territories 7 2 2 11 Nova Scotia 79 21 11 111 Nunavut – – – – Ontario 353 86 16 455 Prince Edward Island 44 12 6 62 Quebec 142 38 12 192 Saskatchewan 74 19 7 100 Yukon 24 13 5 42 Total 1,287 340 109 1,736  Table 13: Team quotas for the SOC 2014 by Province/Territory. 216 Appendix F  Event Carbon Footprint Estimator  Figure 23: Screenshot of event travel carbon footprint tool. Users can enter number of people originating from each region to estimate total travel impacts.      Figure 24: Screenshot of assumptions table which feeds into estimator tool. The parameters can be adjusted to suit each event. 

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