MEASURING THE OIL VULNERABILITY OF CANADIAN CITIES
Ruby Socorro M. Arico M. Sc. in Industrial Engineering and Operations Research University of the Philippines, 1997
RESEARCH PROJECT SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF URBAN STUDIES
In the Urban Studies Program of Faculty of Arts and Social Sciences
O Ruby Socorro M. Arico 2007
SIMON FRASER UNIVERSITY
Spring 2007
All rights reserved. This work may not be reproduced in whole or in part, by photocopy or other means, without permission of the author. APPROVAL
Name: Ruby Socorro M. Arico Degree: Master of Urban Studies Title of Research Project: Measuring the Oil Vulnerability of Canadian Cities
Examining Committee: Chair: Dr. Karen Ferguson
Dr. Anthony Perl Professor and Director, Urban Studies Program Simon Fraser University Vancouver, British Columbia Senior Supervisor
Dr. Meg C. Holden Assistant Professor, Urban Studies Program and Department of Geography Simon Fraser University Vancouver, British Columbia Supervisor
Dr. Aprodicio Laquian, Member Professor Emeritus, Community and Regional Planning University of British Columbia Vancouver, British Columbia External Examiner
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Simon Fraser University Library Burnaby, BC, Canada ABSTRACT
Availability of cheap oil has allowed cities to maintain a certain standard of living and growing dependence on it makes cities vulnerable. Oil is a finite resource that will reach its peak production level then decline. The impacts of oil depletion on cities and its consequences to human existence are therefore inevitable. Adaptation of cities to a potential future when cheap oil is no longer the norm is an important urban policy and little is known about the vulnerability of urban areas.
This study attempted to measure the vulnerability to oil prices of 14 census metropolitan areas in Canada representing its large and mid-sized cities. The goals are to raise public awareness, stimulate more research, and to provide baseline information. A composite indicator of social vulnerability from a set of indicators was constructed which revealed that Calgary is the least vulnerable and Saint John's as most vulnerable to oil prices.
Keywords: composite indicator, social vulnerability, peak oil, vulnerability index DEDICATION
lothe loving memory of my mother, whose passing away 6rought me to the Ur6an Studies firgram ofSimon 'Fraser University,
lomy sisters and brotherfor their unconditionallbve andunderstanding of my desire for academic quest,
lomy nieces, Carh, Athens, andaze4 and to my nephews, Shannon and Christopher, that they too may appreciate that baning is a lifetime journey. I would like to express my deepest gratitude to my Senior Supervisor, Dr. Anthony Perl, for his understanding, patience and guidance to keep me focused on the things that matter to this research project. Special thanks to my Supervisor, Dr. Meg Holden, not only for her scholarly advice but also for the inspiration to continue working on indicators, and for her friendliness. It was a great pleasure working with her not only in this research project but also in other coursework. I am honoured to have Dr. Aprodicio Laquian, as my External Examiner and my appreciation to Dr. Karen Ferguson who served as Chair of the Examining Committee.
I am also grateful to Ms. Terri Evans, for her friendliness and unwavering assistance since I joined the Urban Studies Program. I would like to thank Ms. Jill Mandrake and Mr. Daniel Jans of Belzberg Library for their help and cooperation while I am doing all my coursework.
To my friends, Ms. Vivien Ramos, Ms. Concepcion Javier and her husband, Joey, and to Ms. Zenaida Abanto for their assistance, patience in answering my technical questions and for their emotional support that helped to see me through the graduate program.
Finally, to my sister, Maria Isabel, for her inspiration, understanding and support to make the completion of this research project easier for me. TABLE OF CONTENTS
.. Approval ...... 11 ... Abstract ...... III Dedication ...... iv Acknowledgements ...... v Table of Contents ...... vi ... List of Figures ...... VIII List of Tables ...... ix Chapter 1: Introduction ...... 1 1 . 1 Background of the Study ...... 5 1.1.1 Travel to Work ...... 5 1.1.2 A Look at Petroleum Products Supply and Demand ...... 6 1.2 Rationale of the Study ...... 7 1.3 Significance of the Study ...... 8 1.4 Research Questions ...... 10 Chapter 2: Understanding the Concepts of Vulnerability ...... 11 2.1 Defining Vulnerability ...... 11 2.2 The Role of Indicators and Indices ...... 14 2.3 Past Initiatives in Developing Vulnerability Indices ...... 16 2.3.1 Economic Vulnerability Index ...... 16 2.3.2 Environmental Vulnerability Index ...... 17 2.3.3 Social Vulnerability Index ...... 18 2.3.4 Oil Vulnerability Index ...... 19 Chapter 3: Research Design and Methodology ...... 25 3.1 Epistemology...... 25 3.2 Theoretical Paradigm ...... 25 3.3 Research Approach ...... 26 3.4 Research Methodology ...... 27 3.4.1 Structural Variables ...... 29 3.5 The Research Model ...... 30 3.5.1 Concept of Vulnerability ...... 30 3.5.2 Selection Criteria for Indicators ...... 32 3.5.3 Sampling ...... 37 3.5.4 Data Collection ...... 37 3.5.5 Normalization, Weighting and Aggregation ...... 38 3.5.6 Test for Robustness ...... 39 Chapter 4: Results and Analysis ...... 42 4.1 Ranking of Census Metropolitan Areas ...... 44 4.2 Aggregation of Indicators ...... 50 4.3 Test for Robustness of the Vulnerability Index ...... 55 4.4 Implications and Directions for Future Research ...... 59 4.5 Limitations of the Study ...... 60 Chapter 5: Conclusion and Recommendations ...... 61 5.1 What We Need to Know ...... 61 5.2 What Others are Doing ...... 63 5.3 What Needs to be Done ...... 65 5.3.1 "Business-as-Usual'' Scenario ...... 65 5.3.2 "No regrets" Strategies ...... 67 Bibliography ...... 70
vii LIST OF FIGURES
Figure 1 Elements of Research Process (adapted from Saunders et al 2000 cited in Gray 2004) ...... 28 Figure 2 Visual Model of Dependent and Independent Variables (adapted from Creswell 1994, p85) ...... 29 Figure 3 Vulnerability Egg Model ...... 31 Figure 4 Indicators of Vulnerability to Oil Prices, 2001 ...... 43 Figure 5 CMA Ranking for Vulnerable Age Group Population ...... 45 Figure 6 CMA Ranking for Mode of Transport to Work ...... 46 Figure 7 CMA Ranking for Average Household Expenditure on Transportation ...... 47 Figure 8 CMA Ranking for Incidence of Low Income ...... 48 Figure 9 Social Vulnerability Index to Oil Prices. 2001 ...... 51 Figure 10 Comparison of Social Vulnerability Index. 1996 and 2001 ...... 55
viii LIST OF TABLES
Table 1 Summary of Vulnerability Definitions ...... 13 Table 2 Frequencies of Articles with Selected Keywords in Newspapers. percent ...... 22 Table 3 Selection of Indicators using SMART ...... 33 Table 4 Percentage Distribution of Workers by Mode of Transportation. 2001 (all CMA workers) ...... 34 Table 5 Summary of Indicators and Assumptions ...... 36 Table 6 Ranking of CMAs by Indicator (least vulnerable to most vulnerable) ...... 49 Table 7 Final Ranking of CMAs ...... 50 Table 8 Comparison of Ranking. 2001 and 1996 ...... 54 Table 9 Comparison of CMA Rankings ...... 57 Table 10 2001 Average Retail Price of Regular Unleaded Gasoline at Self- Service Filling Stations. cents per litre ...... 58 CHAPTER 1: INTRODUCTION
The Master said, "If a man takes no thought about what is distant, he will find sorrow near at hand. " - Analects of Confucius, Book 15.
The rapid increase of international oil prices in 2004 triggered speculations about the security of oil supply and spurred great public interest on the underlying causes of the price increase. In an article on high oil prices on September 28, 2004, BBC News attributed the price increase to rising demand, low stocks, geopolitical issues, and to the strategy of the Organization of Petroleum Exporting Countries. In another article on world oil markets on April 28, 2005, the CBC News also linked the price increase to rising demand particularly from China and India. According to CBC News, China surpassed Japan in 2004 as the second largest consumer of oil while India consumed 2 million barrels (mmb) per day compared to Canada's 2.25 mmb per day. Bhushan Bahree cited the strained global oil supply system as the cause of price increases (Wall Street Journal Eastern Edition, July 14, 2004, pA2).
Is this the beginning of an era of energy constraints? Are we heading to a point when the global production rate of oil reaches a maximum level and declines thereafter, or simply, peak oil? Marion King Hubbert, an American geologist, made predictions of future world oil production in 1969. According to Hubbert, the annual oil production follows a bell-shaped curve (now known as "Hubbert's peak") such that an unconstrained production of a finite source starts from zero until it reaches a peak output then begins declining to zero (Campbell 1997, p87). Using this theory in 1956, Hubbert predicted that the U. S. oil production will peak in 1970 and it came true.
Based on Hubbert's method, Kenneth Deffeyes (2005, p45) estimated that global oil production will peak in 2005 or the first months of 2006. A former geologist of Amoco, Colin Campbell also estimated the future global oil production. At a conservative low case scenario of no increase in demand, Campbell predicted that the level of oil production remains flat until 2010 then starts declining at an annual rate of about 2 percent due to resource constraints (Campbell 1997, p104; Campbell and Laherrere 1998, p79; Aleklett and Campbell 2003). The Association for the Study of Peak Oil and Gas (ASPO)', a network of scientists interested in determining the date and impacts of the peak of global oil and gas production, supports Campbell's estimate (Aleklett et al 2002).
In 2003, Jean Laherrere, a petroleum consultant, conducted detailed analyses of reported reserves and production values since the 1900s using the available technical databases of the oil industry (Illum 2004, p64). Laherrere gave an estimate that by 2030 almost all of the ultimate reserves of about 2,000 Gb would have been produced.2 Both Campbell and Laherrere believe that the next oil crisis will not be so temporary because oil supply will not be able to meet the steadily increasing demand.
lnternational energy agencies put forward different estimates. The U. S. Energy Information Administration, in its lnternational Energy Outlook 2006 (p159), indicated that global liquids production in 2030 would be 101.9 mmb per day while the lnternational Energy Agency (IEA)~states that oil prices will remain roughly stable for another two decades. The World Energy Outlook 2005 of IEA estimated that the world oil production in the reference scenario would be 115.4 mmb per day by 2030 (p90). Hook (2006, p17) states that this pronouncement is being challenged by other experts like Matthew Simmons who claims in his book, Twilight in the Desert, that Saudi Arabia has already reached its maximum oil production level.
Based on estimates of oil experts, it looks like we are living in an era where supply of cheap oil is critical. According to Hirsch et al (2005), the prediction of the peak of global oil production is extremely difficult due to variations in pricing, demand elasticity, other measurement challenges including geo-political complexities and influences. Despite these challenges, the fact remains that global oil peak production will happen but the timing is uncertain. While the timing of when peak oil will actually happen is highly debated, the associated consequences to human existence are not and the impacts on cities are inevitable.
' ASP0 started in 2001 2 Ultimate reserves, as described by K. lllum is the "total production of conventional oil from the time when the recording of production began until production has declined to an insignificant level" (p63) and 1Gb is equivalent to 1 billion barrel of oil. 3 Established within the framework of the Organization for Economic Cooperation and Development (OECD) in November 1974, the lnternational Energy Agency is an autonomous body tasked to implement the energy programme among 26 OECD member countries. A Place Highly-Dependent on Cheap Oil
Cities have long been the sites for markets and the mixing of people, commodities, ideas and cultures. In its publication, World Resources 1996-97: The Urban Environmenf, the World Resources Institute concluded that cities grow because they provide greater social and economic benefits compared to rural areas. The World Bank in its World Development Report 2003 echoes this conclusion that "cities are sources of productivity and innovation" (p109).
The bedrock of cities' growth is the availability of cheap oil, which allowed large cities to participate in global economy (Newman 2006, p5). Oil as an energy source heats and cools homes and buildings, powers transportation to move goods and people, and is an essential component in production of goods such as farm machinery, pharmaceuticals, processed food, telecommunications equipment, clothing, vehicles, appliances, and virtually all that we use at present for existence. Thus, oil is an inextricable part of modern life and the economic wealth of societies is generally correlated to consumption of energy. In 2001, Japan consumed 4,091 kilogram oil equivalent (kgoe) per capita compared to India's consumption of 514 kgoe per capita. Undoubtedly, energy is crucial to effective city life. The 2006 World Urban Forum Ill of UN Habitat argues that, "when power supply fails, cities stop working" and "....when energy supply is uncertain, cities falter" (Our Future: Sustainable Cities-Turning Ideas Into Action, Background Paper p3).
According to Organization for Economic Cooperation and Development (OECD), Canada is one of the most urbanized nations and cited by OECD in Figures 2005 Edition as the third most energy-intensive society in 2003. More than half of Canada's population (or 64 percent) is concentrated in the existing 27 census metropolitan areas (CMAS)~and is increasing by 6.2 percent from 1996 to 2001 (Heisz and LaRochelle-Cote 2005).
Canadian cities are among the most highly automobile-dependent next to the United States and Australian cities (Kenworthy and Laube 1999). According to Transport Canada (TC), in 2004, transport sector in Canada represents 34 percent of the total energy consumption, a growth of 3.5 percent from 2003 or a total growth of more than 25
Census metropolitan area is defined by Statistics Canada as a place with one or more adjacent municipalities situated around a major urban core with a minimum population of 100,000. The adjacent municipality or municipalities must have high degree of economic and social integration with the urban core. percent since 1990. Its report Transportation in Canada 2005 indicates that of the total energy consumed by the transport sector, road transport accounts for 77 percent and on average, Canadians spent 14.8 percent of their total personal expenditures on transportation, generally, higher than expenditure on food.
Given the pivotal role of oil to urban life, are Canadian CMAs prepared in the event of peak oil? How will peak oil affect the CMAs? Which CMA will be most or least vulnerable to oil prices?
According to Newman (2006), there are no models that can be easily used to understand how cities will manage the age of reduced oil availability and Prugh et al (2005) conclude that "where oil once helped ensure human security, it now makes us more vulnerable."
With current trends in energy use, industrialized economies remain vulnerable to higher oil prices and transportation will likely be the sector most greatly affected. Vulnerability to fluctuations in oil prices vary from cities to cities depending on its socioeconomic conditions, and energy use and efficiency. Unfortunately, most of the existing vulnerability assessments are related to economic resilience, coping with climate change, and disaster preparedness. There is little known about the vulnerability of metropolitan areas within the context of oil price increases.
This study is an attempt to measure the social vulnerability to oil prices of selected CMAs in Canada. This involved the construction of an oil vulnerability index from a set of available indicators, identification of processes that give rise to vulnerability, and selecting a way to aggregate that will allow for comparison of CMAs. As an exploratory research, the goal is to determine and compare which among the CMAs is the least and most vulnerable to higher oil prices as reflected by indicators that best capture the existing condition.
Aside from this introduction, this report is organized further into four chapters. Chapter 2 introduces the concepts of vulnerability, the results of reviewing past initiatives on vulnerability indices, and the roles of indicators and indices as tool for decision- making. Chapter 3 discusses the research design, methodology, and the research model adopted in this study. Chapter 4 presents the data analysis, results of study, and implications for future research. Chapter 5 discusses the findings in relation to research questions and hypotheses, and concludes the report with a summary of assessment, and recommendations.
1.1 Background of the Study
This section provides a brief description of work travel patterns as key component of social vulnerability to oil prices and a look at the supply and demand for petroleum products in Canada. The existing situation in these areas underscores the potential to oil vulnerability. Thus far, there are no alternative liquid fuels that compete economically with oil in the transport sector.
1.I .I Travel to Work
Canada's vast geography, climate, and population make driving an essential component of daily living. More than half of Canada's 33 million people live in CMAs. In 2005, the Canadian Vehicle Survey of Statistics Canada recorded about 18.6 million vehicles in Canada (or one vehicle for every two Canadians) that travelled a total distance of 315 billion kilometres. This represents an increase of 1.6 percent from 2004.
This volume of travelling consumed 38.5 billion litres of gasoline and 16.2 billion litres of diesel fuel. Despite higher prices of petroleum products, The Daily of Statistics Canada indicates that consumers purchased 144,394 new vehicles in August 2006 up by 3,882 vehicles (or 2.8 percent change) compared to July 2006.~
Heisz and LaRochelle-Cote (2005) examined the spatial location of employment and commuting patterns in Canada's largest metropolitan regions over the period 1996 to 2001. Their study showed that while the city centres continue to dominate as job location, its relative importance has declined in recent years due to faster job creation away from the city centres. They noted that this job growth in suburban locations thus, compels workers to drive instead of using public transit since most of the public transit systems are city centre-oriented.
Their findings also indicated that in almost all CMAs, more than half of all workers commuted more than 5 km and many up to more than 25 km. They cited that generally,
5 The Daily is Statistics Canada's official release bulletin that provides news on current social and economic conditions, http://www.statcan.ca/Daily/English/0605Ol/d060501a.htm. (accessed August 22, 2006). young people (ages 20-34 years old), lower income, women (representing 19.3 percent), and recent immigrants relied on public transit as mode of transport to work.
1.I .2 A Look at Petroleum Products Supply and Demand
Canada is fortunate to have abundant energy resources. Aside from its hydropower capacity, crude oil was produced from its seven provinces at 136.4 million cubic meters in 2005 (Rowat 2006, p3). If the 175 billion barrels of oil sands from Alberta will be accounted for, Canada will be second (179 billion barrels) to Saudi Arabia (264 billion barrels) in global oil resources (Maynard 2006, p6).
The report, Overview of the Canadian Downstream Petroleum Industry (July2005) by Natural Resources Canada (NRCan) indicates that even with these energy resources, more than half (or 55 percent) of its domestic refinery demands in 2005 are supplied by imported crude oil that makes Canada's oil economy unique working on a "dual market." In Ontario for example, 40 percent of the crude oil processed in its refineries was imported while 60 percent was supplied by Western Canada. On average, the utilization of Canadian refining capacity has been over 90 percent to meet domestic fuel demands (Rowat 2006, p10). Canadians consumed 41 billion litres of gasoline in 2005 of which 94 percent was used by the road sector. Given this trend, of all the 26 member countries of OECD, Canada is 5'h among most oil-consuming countries in 2005 at 2.2 mmb per day (British Petroleum, Statistical Review of World Energy 2006, pl1 ).
Canada is also the largest exporter of crude oil to the U. S. and in 2005 supplied about 10 percent of the U. S. requirements (Rowat 2006, p3). Under the North America Free Trade Agreement (NAFTA) Canada cannot reduce its energy resource exported to the U. S. below the average for the most recent 36-month period (Part Two,Chapter Six, Article 605). Barlow (2001, pl0) explains that this NAFTA provision has given the U. S. a "security blanket." Barlow further notes that with the dismantling of the 25-year surplus of natural gas as "vital-supply safeguard" of Canadians coupled with the National Energy Board "stripped of its power," there is no longer a government agency or law that will protect Canada's future energy security and to guarantee an adequate energy supply.
Since the world market decides oil prices, Canada will not be immune to the adverse consequences of a limited cheap oil supply. According to Gilbert and Perl (2005), the transport sector provides a significant contribution in sustaining Canada's high standard of living. With its geography and dispersed population, Canada will be faced with mixed challenges in adapting to an energy-constrained situation.
Hook (2006) also cautions politicians to prepare themselves for days of expensive oil, cheaper vehicles, few motor vehicle manufacturing jobs, and tight competition for limited road space. Higher energy prices will happen and it is better to examine the issues further and prepare (Beaumont and Keys 1982, p162). Undoubtedly, increasing oil prices will have adverse impacts for Canadian cities that are highly dependent on automobiles.
1.2 Rationale of the Study
It will not be difficult to identify the sectors that will be potentially affected by peak oil. As oil prices soared, a remarkable percentage change in the retail prices of road diesel and regular unleaded gasoline were recorded by Transport Canada (2005). For road diesel, from 8.6 percent in 200212003, it increased to 9.8 percent in 200312004 and 22.2 percent by 200412005. For regular unleaded gasoline, from 6.3 percent in 200212003, it went up to II .Ipercent in 200312004 and 13.5 percent in 200412005. The May 2006 issue of The Daily indicates that the prices for manufactured goods at the factory gate increased in March due to higher prices of gasoline and fuel oils.
Oil is an important feedstock and any price increase resulting from sudden supply disruptions is translated into higher costs for the production of goods and services. The low-income population will most acutely feel this economic impact. According to Statistics Canada, the incidence of low income among individuals in 2004 is 11.7 percent.
Al-Husseini (2004, p14) believes that with the complexity of discovering and developing new oil production capacity, there is little hope for a return to an era of inexpensive oil prices. The authors of the book, The Coming Economic Collapse, Stephen Leeb and Glen Strathy (2006) also believe that the impacts of cheap oil supply disruptions will be more severe compared to any previous energy crisis because the next oil crisis is perceived to be permanent. Therefore, the problem should not be ignored and steps be taken to cushion the impacts of transition or experience a mass future shock. An important action to prepare for these challenges is to understand the issue. Understanding the issue will avoid what Lansberg (1974) refers to as "an animated search for the villain" (p248). The public may not be willing to understand that cheap oil supply is running out and to accept the inevitable consequences to their way of life. Landsberg states that convenient targets of blame are the federal government, the energy industry, and the environmentalists. It is important to take the necessary steps to make the public understand that oil price increases are imminent in order to minimize misplaced aggression that may result to panic. Understanding and accepting reality will make it easier for the public to "swallow the bitter pill."
Given the magnitude of potential impacts, it is crucial to prepare and contemplate strategies to be able to adapt to a future scenario of limited cheap oil supply. The associated challenges and uncertainties need to be better understood by the public particularly in Canadian cities.
Developing a vulnerability index, proposed in this study, is an initial cost-effective strategy by providing a single-value measure of vulnerability based on indicators selected through a meaningful criteria. The public and policy-makers can easily understand a vulnerability index in dealing with transport issues as it helps identify vulnerable groups.
This study aims to measure the relative oil vulnerability of Canadian cities by constructing an index that is useful for ranking the CMAs, to raise public awareness of the need to take action, encourage more urban research, and to present a complex issue in a form that can be easily understood.
1.3 Significance of the Study
There are limited studies that deal directly with preparations for a potential future of limited cheap oil supply. What is being done in Canada to prepare for the challenges associated with peak oil? Google Trends showed that Vancouver ranked seventh among the cities with the most searches on 'peak oil' while Portland, Oregon tops the list.6 Calgary is gthwhile the rest among the top ten list are cities from the U. S. There
Google Trends analyzes a portion of Google web searches to compute how many searches have been done for the terms entered relative to the total number of searches done on Google over time. When the Cities tab is selected, Google Trends first looks at a sample of all Google searches to determine the cities from which we received the most searches for the first term. Then, for those top cities, Google Trends calculates the ratio of searches for the term coming from each city divided by total Google searches coming from the same city. http:l/www.google.comltrends. (accessed September 18, 2006). seems to be a much greater interest in peak oil and its potential impact to cities in the U. S. than among Canadian cities.
At the city level, the Transportation Committee of the City of Burnaby circulated to the City Council the report, Global Peak in Oil Production: The Municipal Context on January 16, 2006. This report was circulated for information purposes only and thus far, is the first peak oil report to be publicly received by any government in Canada and was sent to 185 governments in British Columbia (Ramsey 2006).
Another initiative to prepare for future energy challenges is the Auto 21-funded research project, Automotive Policy Options in an Era of Energy ran sit ion.^ In April 2006, the project conducted a survey to better understand how the people who contribute to transport-policy making view future energy issues. Based on their survey, 87 percent and 63 percent of the respondents think that the government and the automotive industry, respectively, are not doing enough to prepare for future energy challenges.
On May 23-25, 2006, lpsos Reid, on behalf of the Canadian Centre for Energy Information (CCEI), conducted a telephone-based survey of adult Canadians on their perceptions of gasoline prices (CCEI News Release June 2006, pl). One of their findings shows that there is limited public awareness on important facts about gasoline such as fuel taxation and that Canada's position, as major producer of oil and gasoline, is not well understood by the public.
The peak oil debate also attracted the media. On September 23, 2006, the Vancouver Sun featured a seven-day series entitled "Energy Tough Choices Ahead: Staking a Future on Fossil Fuels."
Thus, within the purview of attracting public interest and stimulating more detailed research, this research study is relevant and timely by providing a comparison of social vulnerability to oil prices among the CMAs.
Dr. Anthony Perl, Professor and Director of Urban Studies, Simon Fraser University is the Principal Investigator and Dr. Richard Gilbert as Co-Investigator. 1.4 Research Questions
According to Peattie (1994), questions that should arise from urban research would be those of who gains and who loses and value questions. With this consideration, the study will seek to answer the questions: Why are certain CMAs vulnerable to oil price increases? Which CMA will be most and least vulnerable to oil price increases? Are small CMAs more vulnerable than big CMAs? To what extent can a CMA move towards resiliency? How best to construct an index to measure the relative vulnerability of CMAs? CHAPTER 2: UNDERSTANDING THE CONCEPTS OF VULNERABILITY
"Not everything that counts can be counted and not everything that can be counted counts. " - Albert Einstein
The following section briefly describes the concepts of vulnerability, the role of indicators and indices as tool for decision making, and the results of reviewing past initiatives in developing vulnerability indices.
2.1 Defining Vulnerability
Merriam-Webster's College Dictionary (2003) indicates that the etymology of the word, vulnerability, is in 1605 from the Late Latin word, vulnerabilis, or from Latin word, vulnerare, which means to wound, or open to attack or damage. Compared to sustainable development, there is no internationally accepted definition of vulnerability. According to Brooks (2003), social scientists and climate change scientists have diverging views of vulnerability while Vincent (2004) considers vulnerability as a "contested term." Other social scientists think of vulnerability as another way to describe poverty aspects that may not be reflected in monetary terms (Alwang et al 2001).
Even in disaster management, a consensus on defining vulnerability is also lacking. According to Heijmans (2004), disaster agencies do not share a common understanding or definition of vulnerability. However, they recognize that vulnerability is a major concern for the poor and that most vulnerable sectors in society require special attention.
Blaikie et al (1994) gave a simple hazard-related working definition of vulnerability as,
"the characteristics of a person or group in terms of their capacity to anticipate, cope with, resist, and recover from the impact of a natural hazard. It involves a combination of factors that determine the degree to which someone's life and livelihood is put at risk by a discrete or identifiable event in nature or in society (p.9)." Specifically to rank countries based on their economic vulnerability, Briguglio (1995) defines vulnerability as "proneness to harm or damage originating from external factors." In relation to climate change, the Third Assessment Report (TAR): Climate Change 2001 of the Intergovernmental Panel for Climate Change (IPCC) defines vulnerability as,
"The degree to which a system is susceptible to, or unable to cope with, adverse effects of climate change, including climate variability and extremes. Vulnerability is a function of the character, magnitude, and rate of climate variation to which a system is exposed, its sensitivity, and its adaptive capacity." (IPCC 2001, p.995).
This IPCC definition aims to ensure a common understanding of vulnerability among climate change researchers and practitioners.
Adger et al (2004) give another view of vulnerability. They consider vulnerability as a state, "something that exists within systems independently of external hazards" (p. 29). Applied to most human systems, they refer to it as social vulnerability (Adger 1999; Brooks 2003; Adger and Kelly 1999). Specifically, social vulnerability is the "capacity of individuals and social groups to respond to, that is, to cope with, recover from and adapt to any external stress placed on their livelihoods and well-being" (Kelly and Adger 2000, p. 328 cited in Eriksen and Kelly 2006). Pelling (2003) has a similar view and referred to it as the vulnerability experienced by people and their social, economic and political systems.
Another dimension of vulnerability that can be associated with social vulnerability is defensible space. Newman (1972) refers to defensible space as a territorial concept, which involves a range of mechanisms that residents use to control their own spaces. While Newman proposed the defensible space theory within the context of physical environment and crime, it can be one of the key factors affecting social vulnerability in the event of "long-term energy crisis" resulting from peak oil. This aspect will be a major challenge in urban areas as culturally-diverse as Canadian cities. During the 1974 and 1979 oil crises in the U. S., citizens tired of waiting in long gas lines and service stations vented their anger on each other resulting in a number of people actually killed in the gas lines (Money 1984). In the book, The Long Emergency, James Howard Kunstler also mentioned that in a post-peak oil era, people may tend to take the law into their own hands and suggested a possibility of conflicts over energy. In a review of literature from different disciplines, Alwang et al (2001) concluded that there is a tendency to have varying views of vulnerability each focusing on different results and concerned with several forms of risk. Despite varying and diverging definitions of vulnerability, there is a consensus or a common thread which means the "susceptibility to harm in a system relative to a stimulus1'(Ford and Smit 2004). Heijmans (2004) argues that the definition of vulnerability depends on the user and its function on the society or system involved. Table 1 gives a summary of vulnerability definitions.
From these schools of thought, vulnerability, as it will be used in this study, refers to the condition or state that makes a community or a system susceptible to harm or damage arising from external factors. This condition is an inherent characteristic or attribute of the CMA that is independent of oil prices. This falls within the category of "starting-point" approach referred to by Eriksen and Kelly (2006) in their study to develop credible vulnerability indicators for climate change adaptation.
The focus of this study is social vulnerability, defined as the capacity of people in CMAs to cope with and adapt to future oil price increases resulting from peak oil. This definition generally adopts the social vulnerability concept of Adger and Kelly (1999), Brooks (2003), and Adger et al (2004). As pointed out by Eriksen and Kelly (2006), a "starting-point" vulnerability assessment asks, "what can be done to strengthen people's own capacity to respond and adapt" to external factors such as peak oil or disruptions in cheap oil supply. This study constructed a social vulnerability index to determine which CMAs are least or most vulnerable to oil prices, what makes them vulnerable based on their existing conditions, and examined how vulnerability to oil prices can be reduced.
Table 1 Summary of Vulnerability Definitions
Vulnerability Definition Application Briguglio 1995 "Proneness to harm or damage originating from Economic vulnerability external forces" of small island developing states > Economic condition Blaikie et al "The characteristics of a person or group in terms of I Natural hazards and 1994 their capacity to anticipate, cope with, resist, and disaster management recover from the impact of natural hazard. It ~~~~~~i~, involves a combination of factors that determine the environmental, and degree to which someone's life and livelihood is put Vulnerability Definition Application at risk by discrete or identifiable event in nature or in social conditions society" (p.9). IPCC-TAR "The degree to which a system is susceptible to, or Climate change 2001 unable to cope with, adverse effects of climate 9 Economic, social, change, including climate variability and extremes. environmental, and Vulnerability is a function of the character, political conditions magnitude, and rate of climate variation to which a system is exposed, its sensitivity, and adaptive capacity" (p. 995) Alwang et al Another way to describe poverty aspects that may Research on 2001 not be reflected in monetary terms. vulnerability from different disciplines P Social and economic conditions Adger et al "Something that exists within systems independently Climate change 2004; Brooks of external hazards" research 2003; Adger k Social, economic and Kelly 1999 and environmental conditions Kelly and Social vulnerability is the "capacity of individuals and Climate change Adger 2000 (in social groups to respond to, that is, to cope with, research Eriksen and recover from and adapt to any external stress i; Social condition Kelly 2006) placed on their livelihoods and well-being" Pelling 2003 "Social vulnerability is the vulnerability experienced Natural disasters and by people and their social, economic, and political social resilience systems." research - - -- "Susceptibility to harm in a system relative to Climate change stimulus." research > Environmental and social conditions Heijmans 2004 Depends on the user and its function on the society Natural hazards and or system involved disaster management > Environmental, social and economic K conditions 2.2 The Role of Indicators and Indices
An indicator is a specific, measurable or observable sign that facilitates transition from a current condition to a future direction. lndicators are usually quantitative because they easily translate into a measurable guide to show progress and facilitate understanding of a complex issue.
Indicators are also useful as an educational tool to effect change and signal to attract attention. For example, people became aware of air pollution through air quality indices. As another example, energy use per $1,000 purchasing power parity is one of the indicators of the Millennium Development Goals by the United Nations. However, indicators are only snapshots that give an incomplete reflection of reality. Thus, it is necessary to use a wide range of indicators to describe the diverse aspects of a situation (Maclaren 1996). To do this, indicators can be aggregated to form indices (or composite indicator) that could lead to a more comprehensive model of reality.
lndices can be "used to represent complex phenomena in a format which permits easy comparison over time, or across subjects" (Briguglio 1995). An example is the Human Development lndex (HDI) that measures human progress and introduced by the United Nations Development Programme (UNDP) in its Human Development Report in 1990. HDI is a composite of three basic dimensions of human development: longevity, knowledge, and standard of living. Another example is the Canadian lndex of Well- being, which once completed, captures progress in seven areas: health, family, work, environment, education, community, and civic engagement through a full range of indicators that determine current wellbeing and sustainable wellbeing (Atkinson Foundation, http:llwww.atkinsonfoundation.calciw).
While indicators and indices are useful in providing information on conditions or problems, they also share a number of weaknesses. Indices do not reflect the structure and causes of vulnerability (Adger et al 2004). At the same time, aggregating indicators into an index is associated with subjectivity in the choice of variables, problems of measurement, availability of data at various scales, difficulty of validating or testing the indicators, and weighting (Luers et a1 2003; Vincent 2004; Briguglio 2003).
The process of averaging in a composite indicator reduces the importance of a single vulnerability factor indicating that it is not vulnerable when in fact it is on a single critical factor (Rygel et al 2006). According to Briguglio (1995), some of the associated problems in aggregating indicators may never be resolved and Vincent (2004) argues that it is critical to have new, valid and reliable indicators and indices in a theoretically- diverse field such as vulnerability for a continuous development of a policy-relevant science.
2.3 Past Initiatives in Developing Vulnerability Indices
Given the importance of oil to urban life, it is unfortunate that there are limited studies measuring the vulnerability of cities to oil prices and impacts of disruptions in supply. Most vulnerability assessments deal with food security, climate change, and natural disasters. Several attempts were made to rank countries (and recently cities) according to relative social, economic and environmental vulnerability.
Luers et al (2003) argue that in order to apply the concept of vulnerability in policy-driven assessment, there is a need to measure it. They cited that the major challenges in measuring vulnerability are due to the absence of a precise meaning for the term, the complexity of systems analyzed, and that vulnerability is not a directly observable phenomenon. They further note that despite these challenges, quantitative and semi-quantitative approaches have been proposed and applied, the most common of which is by using a set of indicators to create an index (for different approaches in developing indices, refer to Saisana and Tarantola 2002; Nardo et al 2005).
2.3.1 Economic Vulnerability lndex8
Briguglio did one of the earliest attempts to develop vulnerability indices in mid- 80s focusing on economic vulnerability of countries (Briguglio 1995; Briguglio 2003). Briguglio selected principal indicators that reflect the inherent conditions of the small island developing states exposing them to external factors. These indicators include economic openness, dependence on a narrow range of exports, peripherality (proxied by transport costs), and dependence on a narrow range of exports, and dependence on strategic imports. The offshoot of Briguglio's work is the proposal of Malta to the UN Conference on Trade and Development in 1990 to construct a vulnerability index for Island Developing countries (Benson 2004, p209).
Vulnerability index took center stage again during the Barbados Global Conference on Sustainable Development of Small Island Developing States in 1994. This led to the development of a vulnerability index by a group of experts under the
The review relied heavily on Briguglio (2003). auspices of the UN Department of Economic and Social Affairs (ECOSOC). The UN Committee for Development Policy (CDP) considered their output in 1998 as one of the criteria for identifying the less developed countries (UN ECOSOC 1999).
The UN-CDP economic vulnerability is a composite index of five equally-weighted indicators representing shocks (measured by instability of agricultural production and instability of exports of goods and services) and exposure to shocks (measured by population size, share of manufacturing and modern services in GDP, and merchandise export concentration) (UN-CDP, Reporf on the VII Session 2005, p27).
Recognizing the importance of vulnerability indices, the U. K. Commonwealth Secretariat developed a composite vulnerability index (CVI) to rank 111 countries representing 37 small and 74 large states (Atkins et al 2001, p53). Consistent with the vulnerability definition in their 1997 report, A Future for Small States: Overcoming Vulnerability, the CVI reflects the three broad areas of economic exposure, remoteness and insularity, and susceptibility to environmental events and hazards. The components of CVI are not so different from the economic vulnerability index of UN-CDP in 1998. By and large, the results of CVI showed that small states are more vulnerable to external economic factors and environmental hazards than large states (Atkins et al 2001, p63). The U. K. Commonwealth Secretariat now refers to the index as Commonwealth Vulnerability lndex for developing countries and is being used to determine if small states should be given differential treatment by the international community.
The Caribbean Development Bank also developed their economic vulnerability index using indicators divided into six groups: peripherality and accessibility, export concentration, convergence of export destination, dependence on energy imports, reliance on external finance, and proneness to natural disasters (Crowards 1999).
Briguglio (2003) notes that common to economic vulnerability indices proposed by various authors (Briguglio 1995, Crowards 1999, Atkins et al 1999, UN-CDP 2000) were its simplicity and ease of comprehension, and the very few components all of whose data were taken from available published statistics like the International Monetary Fund's lnternational Financial Statistics.
2.3.2 Environmental Vulnerability lndex
The indicators-based approach in developing environmental vulnerability index (EVI) at the national level began in 1998. The South Pacific Applied Geoscience Commission (SOPAC) presented the first output in 1999 in their report, Environmental Vulnerability lndex to summarise national environmental vulnerability profiles. The development of EVI was a response to the call made during the 1994 Barbados Programme of Action for Sustainable Development of Small Island States (SIDS) to prepare a composite vulnerability index incorporating both economical and ecological concerns (SOPAC Report on the Environmental Vulnerability lndex 2004).
SOPAC developed the EVI focusing on the risk of damage to the natural environment, which they considered as the life support of all human systems (Kaly et al 2004). EVI is a component of hazard, resistance, and damage. EVI uses a scale of 1 to 7 to categorize countries into five vulnerability groups: extremely vulnerable, highly vulnerable, vulnerable, at risk, and resilient. Similar to the economic vulnerability index, aggregation of EVI uses simple averaging for simplicity. A preliminary EVI, based on 50 indicators for 235 countries, was launched in 2004 during the 12'~UN Commission on Sustainable Development in New York (SOPAC, http://www.vulnerabilityindex.net/ EVI-Background. htm).
EVI (also known as Global EVI) is evolving and future works involved the provision of environmental vulnerability data from at least 15 representative countries as basis for mathematical and statistical testing and refinement of the EVI. This testing period will use different weighting methods and if needed, to establish a suitable way of weighting the indicators (SOPAC, Future Directions for the EVI Project, nda).
2.3.3 Social Vulnerability lndex
The Economic Commission for Latin America and the Caribbean (ECLAC) of the United Nations took the main initiative in this area. The ECLAC project started in 2000 and was designed to produce a social statistical database and development of a methodological approach for a social vulnerability index. The ECLAC initiative was driven by the need articulated by policy makers at the national and international levels to have better quality social statistical data and indicators to measure the vulnerability of small states in the region (Reporf of the Seminar on the Results of the Social Vulnerability lndex 2004). The social vulnerability index of ECLAC is built on the work of St. Bernard (2004) and is based on 10 indicators in areas of education, health, security, social order and governance, resources allocation, and communications architecture. Other researchers developed social vulnerability indices in the areas of climate change and natural disasters. At the national level, Vincent (2004) developed social vulnerability index to climate change and ranked the 49 states of Africa. The social vulnerability index for Africa is a component of five sub-indices: economic well-being and stability (20 percent), demographic structure (20 percent), institutional stability and strength of public infrastructure (40 percent), global interconnectivity (10 percent) and dependence on natural resources (10 percent). The author notes that if the results are used acknowledging its limitations, it "marks the first robust and systematic assessment of relative levels of social vulnerability in Africa."
Cutter et al (2003) developed a county-level social vulnerability index to environmental hazards for 3,141 counties in the U. S. based on socioeconomic and demographic data for 1990. They used factor analysis to identify I1 factors out of 42 independent variables. The 11 factors were transformed into an additive model to compute a summary score for the index. They noted that in the results, factors that contribute to the total score of the index are different for each county such that some factors increase the vulnerability while some moderate the effects.
2.3.4 Oil Vulnerability Index
So far, there have been very limited initiatives employing indices to measure oil vulnerability. The Energy Sector Management Assistance Program (ESMAP) of the World Bank measured the vulnerability of African countries to oil price shocks focusing on oil importing countries (Bacon and Mattar 2005). The purpose of their study is to highlight the vulnerability of national economy of oil-importing countries to oil prices , as measured by the gross domestic product (GDP). ESMAP defined oil vulnerability as a function of the value of net oil imports, current GDP, and the price of Brent crude oil for the year. They calculated the impact of oil price shock as a vulnerability index multiplied by the corresponding percentage increase in oil prices. Thus, the vulnerability of an oil importing country is measured by the ratio of the value of net oil imports to GDP expressed in the equation below;
Oil vulnerability = price of oil x [(volume of net oil importsltotal oil use) x (total oil useltotal energy use) x (total energy uselGDP)]
According to ESMAP, the higher the vulnerability, the larger the fall in GDP needed to make up for higher oil prices. Their results showed that the impact of increasing oil prices is highest for countries of lowest income but the level of GDP is not related to differences in oil intensity (measured as the ratio of oil use to GDP) suggesting that other factors determine oil vulnerability.
The oil vulnerability of ESMAP used linear additive aggregation and incorporated the price of crude oil in computing the index. Decision-makers can easily understand their simple approach, however, it focuses on the impacts of higher oil prices to national economy that cannot be scaled down to the city level. The indicators selected for their index such as oil consumption, volume of imports and production are generally available only at the national level.
At the city level, SustainLane ranks US cities' preparedness for an oil crisis based on an index created from six variables using varying weights: city commute-to-work data (greatest weighting), regional public transportation ridership (standard weighting), sprawl (standard weighting), city freewaylsurface street congestion (reduced weighting), local food as measured by farmers markets and community gardens per capita (reduced weighting), and wireless network availability (least ~eighting).~Based on this index, New York tops the list of most ready for an oil crisis and Oklahoma City is the most vulnerable. These rankings used data from 2002-2006 collected by the US Bureau of Census, US Department of Agriculture, Smart Growth America, Intel Corporation, Texas Mobility Study1 Texas A & M, and through primary research with US cities. When released, the SustainLane rankings received online media coverage from Reuters Foundation, WSJ.com, Utne Reader, and CNNMoney.com as indicated in SustainLane in the Media (http://www.sustainlane.us/sl-media.jsp).
Dodson and Sipe (2005) constructed a composite indicator at the neighbourhood level or Collection District (CD), known as vulnerability index for petrol expense rises (VIPER), for Brisbane, Sydney, and el bourne.'^ Using data from 2001 Census of the Australian Bureau of Statistics (ABS), Dodson and Sipe used three variables for VIPER: socioeconomic index for areas (SEIFA), household motor vehicle ownership, and car- dependence for work journeys. They employed varying weights of variables for VIPER:
9 SustainLane is the first U. S. on-line community and media company dedicated to identifying, educating, and connecting cities, residents, and businesses striving to create a healthy, more sustainable life. http://www.sustainlane.com/page/59/. (accessed July 17, 2006).
'O Collection districts are smaller than suburbs and typically contain approx. 200 households. 50 percent for SElFA and 50 percent shared by vehicle ownership and journey to work. VIPER is the first oil vulnerability index developed in Australia.
VIPER results indicate that households in socio-economically disadvantaged outer-suburban locations will be most vulnerable to current and future oil price increases. Households located in central and inner areas will be less disadvantaged as the high- wage employment sectors are concentrated in the central business districts of most Australian cities. The study maps the spatial distribution of oil vulnerability that can be used to compare localities within the cities but do not allow for inter-city comparison since the data used are at CD level for a specific city. Collection districts are not homogeneous and aggregation of data for inter-city comparison will be inaccurate.
The vulnerability assessment for mortgage, petrol and inflation risks and expenditure (VAMPIRE) is another version of a neighbourhood-level index for Perth, Gold Coast, Brisbane, Sydney, and Melbourne (Dodson and Sipe 2006). VAMPIRE used car dependence, income level, and mortgage also based on the ABS 2001 census. VAMPIRE results show that the low level socioeconomic and mortgage vulnerability are concentrated in the inner and inner-middle suburban regions of Australian cities.
In Canada, there are several completed and ongoing indicators-based initiatives at the national, provincial and municipal levels but there is no record of oil vulnerability index being developed. These initiatives can be an opportunity to incorporate oil vulnerability measurement as there is no need to reinvent the wheel. Despite the value of measuring oil vulnerability of cities, there appears to be lack of interest in Canada to embark on this initiative. A number of possible reasons are given below:
Lack of information available to the public on the impacts of peak oil to cities
As discussed in Sect. 1.3, survey results of IPSOS-Reid and CCEl in May 2006 revealed that the public has limited awareness on important facts about gasoline and on Canada's situation as producer of crude oil and gasoline.
Media coverage on peak oil is also limited. In the Proof Committee Hansard of the Australian Senate's Rural and Regional Affairs and Transport References Committee (2006), Samsam Bakhtiari, as one of the witnesses, mentioned that the media is not interested on the issue because "there is no sponsorship for peak oil" (RRA&T9). A preliminary electronic search of National Post and the Globe and Mail was conducted using the engine and database, ProQuest and Canadian Newsstand, respectively, to determine the general topics in the public agenda. Document text and citation of articles from these two newspapers for the last four years were searched for related keywords such as peak oil and oil crisis. Results show that peak oil and/or oil crisis is covered in National Post only on the average of 4 percent per year and 4.3 percent in the Globe and Mail. Table 2 shows the summary of the frequencies.
Table 2 Frequencies of Articles with Selected Keywords in Newspapers, percent
11 Year I Peak Oil I Oil Crisis 11 11 National Post I Globe and Mail I National Post I Globe and Mail 11
A similar approach of searching for keywords in newspapers was conducted by The Danish Institute for Studies in Research and Research Policy in its quest for perceptions and attitudes towards biotechnology in Denmark (Siune and Mejlgaard 2001,
An individual unfamiliar with the issue of peak oil and its impacts to urban life will not understand or value its importance. The Centre for the Study of Environmental Change (CSES) at Lancaster University contends that, "receptivity to official information is strongly influenced by the degree to which the individual feels they can meaningfully act upon it" (Banks 1996). Thus, with lack of adequate information, there is no push either from top-down or bottom-up to measure oil vulnerability of cities.
Preparing for future energy challenges is not among the top priorities
As mentioned in Sect. 1.3, the Auto 21-funded research project, Automotive Policy Options in an Era of Energy Transition, conducted a survey in April 2006 to middle- and senior-level management respondents from the government and automotive industry. The results of their survey showed that 87 percent and 63 percent of their respondents believe that the government and the automotive industry, respectively, are not doing enough to prepare for future energy challenges. There is no national strategy to guide cities or local governments in preparing for a potential future of energy constraints or a clear national vision on future energy security. The reports of NRCan, Petroleum Product Market Outlook (September 2005) and Overview of the Canadian Downstream Petroleum lndustry (July 2005), recognized that oil supply disruptions will cause adverse impacts in the Canadian oil markets. The Petroleum Product Market Outlook (September 2005) mentioned that more than half of all homes in Atlantic Canada depend on oil for heating (over 85 percent of all households in Prince Edward Island use fuel oil for heating) (p5). In the event of short-term price spikes in the gasoline market, Western Canada and Ontario will be vulnerable as large price increases will be needed to transport the products from other regions in Canada to avoid product outages (p8). The report also recognized that with over 90 percent utilization of Canadian refining capacity to meet domestic fuel demand, occurrence of unplanned refinery shutdowns will exacerbate the situation. In 2005, Canada's crude petroleum industry has already experienced its first decline in production in the last six years (2.3 percent lower than 2004) (Rowat 2006, p3).
Given this current scenario, the Overview of the Canadian Downstream Petroleum lndustry (July 2005) indicated that one of the underlying causes of high prices of crude oil and gasoline in the last 10 years is geopolitics in oil-producing countries. The report identified that the "overriding factor" in these price increases is the local market working on price wars and restoration (i.e., lowering of price to attract more customers) (p19). Despite fluctuating high oil prices and the experience of a first decline in Canada's crude oil production in 2005, there has been no association from NRCan reports that these oil price increases could be early warnings of a declining global production of cheap oil. Given the uncertainties of peak oil predictions from experts, it appears that relevant government agencies are sceptical that peak oil may be imminent.
Lack of adequate data available to measure oil vulnerability
One of the major constraints in selecting indicators for this study is the availability of adequate data that will allow for comparison of CMAs. Transport-related data such as fuel consumption, vehicle registration, vehicle-kilometre-travelled or passenger- kilometre-travelled from Canadian Vehicle Survey of Transport Canada and Statistics Canada are available only at the provincial level.
However, the unavailability of data needed does not necessarily mean lack of interest of government agencies collecting statistics. The data from agencies like Statistics Canada, Transport Canada, Natural Resources Canada, and National Energy Board are collected for various administrative purposes that do not cover specific areas of interest like oil dependence of cities. For example, the major use of data collected by Statistics Canada from the Family Expenditure Survey in 1996 (now Spending Patterns in Canada) is for the computation of Consumer Price Index needed to adjust pensions, wage settlements and support projections for inflation. Thus, this limitation does not imply that government agencies believe the data are not important but rather there is compelling need or demand to collect such kind of data. In a survey conducted by UNDP in June 2005 of 135 composite indicators from 1991-2005, they concluded tha the driving factors in the growth of indices are due to increasing availability of information, emerging global issues, and the growing demand for transparency (Bandura 2005).
In Australia, the availability of socioeconomic data such as SElFA and household car ownership from ABS made it possible for the construction of VIPER and VAMPIRE at the neighbourhood level. SElFA is a composite indicator consisting of four sub-indices that allows for ranking of a wide range of geographic areas and comparison of Australian communities based on the level of social and economic well-being (ABS 2001). Despite this data availability, VIPER and VAMPIRE did not include the spatial distribution of household transport stress since data on income, transport costs and urban location at the household level are not available. However, this limitation did not discourage the authors of VIPER and VAMPIRE to raise the issue of rising fuel prices and the potential distribution of its adverse socioeconomic impacts to Australia's Senate Rural and Regional Affairs and Transport Committee by presenting their results on July 11, 2006 (Commonwealth of Australia, Proof Committee Hansard 2006).
Experience in Australia, therefore, proved that lack of adequate data available does not affect the overall reliability and credibility of oil vulnerability indices. The impetus is the recognition that the impacts of peak oil to cities are important for urban research and government action. This key element is lacking in Canada.
Based on past initiatives in developing vulnerability indices, the simplicity of the approach taken by researchers and agencies like the UN in their choice of components allowed for comparison of countries, cities, and neighbourhoods. The use of official statistical data in their indices provided factual evidence and gave a clear message to policy-makers highlighting areas for future action. CHAPTER 3: RESEARCH DESIGN AND METHODOLOGY
"If we could first know where we are, and whither we are tending, we could betterjudge what to do and how to do it. " - Abraham Lincoln
According to Gray (2004), in conducting research, it is important to define the epistemological stance and theoretical paradigm adopted by the researcher, as these will influence the methodology of the study. The following section briefly describes the analytical framework for the study.
3.1 Epistemology
Epistemology tries to understand what it means to know and provides a philosophical background for deciding what kinds of knowledge are legitimate and adequate (Gray 2004). From a standpoint of objectivist epistemology, reason is the only way to know. Episteme or scientific knowledge can be achieved with the aid of analytical rationality (Flyvbjerg 2001). Thus, while we know that oil prices affect how society operates, we can truly know that it is so by an objective inquiry into the social vulnerability of census metropolitan areas.
3.2 Theoretical Paradigm
The term, paradigm, was introduced initially by Thomas Kuhn in his book, The Sfrucfure of Scientific Revolutions (1962). Kuhn describes paradigm as the application of theories in solving important problems along with new experimental or mathematical techniques employed in those applications. According to Guba (1990), paradigm is a basic set of beliefs that guides action. These beliefs direct in a certain way what the inquiry is (i.e., epistemology) and how it should be done (i.e., methodology). This study begins with the knowledge that oil fuels the global economy and sustains modern life at a certain level of standard of living. Recent fluctuations in oil prices sent mixed and alarming signals that make society vulnerable.
What makes metropolitan areas vulnerable to oil prices? According to Cardona (2004), vulnerability encompasses the physical, economic, political or social susceptibility of a community from an event of natural or anthropogenic origin. This study described and measured the relative social vulnerability to oil prices of selected CMAs by constructing an index based on assumed theoretical relationship of indicators to vulnerability.
This approach lies within the paradigm of post-positivism. Under the lens of a post-positivist, there exists a reality "out there" to be discovered objectively based on careful observation and measurement (Creswell 2003). According to Cook and Campbell (1979, p.29 in Guba 1990), it is impossible for humans to truly understand the real world with their "imperfect sensory and intellective mechanisms." Given that objectivity is not achievable in any absolute sense and recognizing the limitations of human sensory and intellective mechanisms, post positivism strives to be as neutral as possible and emphasizes the use of multiple methods, data, and theories in which to base the findings of an inquiry (Guba 1990, p21). Post-positivist researchers continue to generate research ideas from observable facts (Lincoln and Guba 2000) and each researcher's participation generates a critical mass of theory that can be used to improve and broaden the quality of human endeavour in the world of practice (Greene 1990, p.233). In the absence of initiatives to measure the oil vulnerability of Canadian cities, this study provides a baseline comparison of social vulnerability to oil prices among selected CMAs.
3.3 Research Approach
According to Greene (1990, p.231) theory in post positivism is more like a "small theory" and the knowledge claims are more modest. Creswell (2003) describes it as reductionist with the intent of breaking down the ideas into a small and discrete set of ideas to test and analyze separately.
Vulnerability is not a straightforward concept (Adger et al 2004); a "human state or condition that cannot be measured directly in any objective fashion" (Eriksen and Kelly 2006). Using deductive approach, the study built on the theory that cities will be vulnerable to oil prices and came up with four hypotheses. A deductive approach selects the best possible indicators based on theoretical viewpoint and data availability (Niemeijer 2002). However, vulnerability is complex and only four "best available" theoretically-driven indicators are selected to measure the existing oil vulnerability of 14 CMAs. The indicators selected are vulnerable age group population (ages 15 years and over); use of car, van or truck as driver or as passenger for transport to work; average household expenditure on transportation, and incidence of low income living in private households. The vulnerable age group and incidence of low income reflect the "elements at risk" in the event of steadily increasing oil prices while the mode of transport to work by car shows the extent of auto-dependence. Mode of transport to work by car and the average household expenditure on transportation reflect a kind of "exposure" that could make the CMA population vulnerable to oil prices.
3.4 Research Methodology
According to Yin (1984, p23), case study research method is an empirical inquiry that investigates a contemporary phenomenon within its real-life context; when the boundaries between phenomenon and context are not clearly evident; and in which multiple sources of evidence are used. Flyvbjerg (2001) points out that it is important to select a critical case to achieve information that will allow for logical deductions of the type "if this is (not) valid for this case, then it applies to all (no) cases."
The CMAs are selected as an exploratory case study in determining urban vulnerability to oil prices. The index is a relative measure that does not reflect the spatial distribution of vulnerability for each CMA. To summarize the research design, Figure 1 shows the elements of the research process for this study. General Principle I Oil fuels economy and sustains modem life. I
I Why are cities vulnerable to oil prices? I
Research Four lndlmtors are selected based on their theoretical Approach -elationship to vulnerability to oil prices such that:
H,: (Indicator f, Xf)- Vulnerab!e age group population Deductive The higher the population of vulnerable age group. the greater the vulnerability.
H2:(lndicator 2, Xz)- Mode of Transport to Work The higher the working population using car, van or truck as driver or as passenger, the greater the vulnerability.
Hj (Indicator 3, XI- Average Household Expenditure on Transportation The higher the average househdd expenditure on transportation, the greater the vulnerability.
H+- (Indicator 4, X4)- Incidence of Low Income The higher the incidence of low income, the greater the vulnerabllfty.
Methodology I I I Selected 14 census metropolitan areas in Canada I
Data Collectiol. ,1996 and 200'1 Community Profiles from Statistics Canada; 1% Family Expenditure in Canada; 2001 Spending Patterns in Canada, Trends and Conditions in the Census Metropolitan Areas by Statistics Canada I Document Review ~overnment-pubkhed
Data Analysis
Construct ifidex from seiected i~~dicators
Figure 1 Elements of Research Process (adapted from Saunders et a12000 cited in Gray 2004) 3.4.1 Structural Variables
This exploratory research examined the assumed effect of independent variables (XI, X2, X3,and X4in Figure 1) to the dependent variable, social vulnerability to oil prices. In measuring the social vulnerability of CMAs to oil prices, four hypotheses (i.e., HI, H2, H3.H4) are identified (refer to Figure 1).
The independent variables here are specifically referred to as attribute independent variables (sometimes called status variables) because they are not manipulated to determine the change in the dependent variable. This study determined the outcome of the dependent variable as a function of the various conditions of the independent variables (Bohrnstedt and Knoke 1988, p9; Gliner and Morgan 2000, p49). These attribute independent variables determined why some CMAs are more vulnerable to oil prices than others. The social vulnerability to oil prices is constructed as an index (or composite indicator) consisting of these four indicators. In Figure 2, the "strength" of relationship of the independent variable to the dependent variable is indicated by a positive sign while the two-headed arrows connected by a curved line show unanalyzed correlations between independent variables (Creswell 1994, p85.)
ode of Transport to Wary Social Vulnerability lndex Average Household Expenditure I I on Transportation I I I + I I Incidence of Low Income I I I I I I I I I I Attribute lndependent Variable Theoretical Relationship Dependent Variable
Social Vulnerability lndex f (vulnerable age group population, mode of transport to work by car, average household expenditure on transportation, incidence oflow income)
Visual Model of Vulnerability to Oil Prices
Figure 2 Visual Model of Dependent and lndependent Variables (adapted from Creswell 1994, p85) As discussed in Sect. 2.3, the use of indicators is a common approach of measuring vulnerability as researchers are faced with the challenge that vulnerability is a phenomenon which cannot be directly measured or observed in an objective way.
The method of constructing the social vulnerability index in this study is similar to VIPER and VAMPIRE for selected Australian cities. However, VIPER and VAMPIRE are indices at the neighbourhood level that do not allow for intercity comparison while the vulnerability index in this study is at census metropolitan area that allows for comparison. Other methodological differences of this study compared to VIPER and VAMPIRE are the number of indicators, weighting, and test for robustness of the vulnerability index. The approach taken in this study is consistent with the aim of constructing a vulnerability index that can provide a simple and informative way of understanding oil vulnerability of cities and as baseline for further research. The research model is discussed in more details in the next section.
3.5 The Research Model
This section discusses the overall research model toward the goal of constructing a social vulnerability index to oil prices. The following steps are based on the Handbook on Constructing Composite Indicators: Methodology and User Guide of OECD (Nardo et al 2005).
3.5.1 Concept of Vulnerability
As discussed in Sect. 2.1, vulnerability is defined in this study as the condition that makes a CMA susceptible to the adverse impacts of oil prices. Figure 3 shows the model as vulnerability egg encompassing the social, political, and environmental dimensions that are closely-linked to each other. This study isolated four "best available" indicators to construct the social vulnerability index to oil prices for CMAs.
Social vulnerability definition adopted here refers to the capability of the CMA population to cope with or adapt to the impacts of high oil prices. With the social vulnerability index, this study determined who (or which CMA) are vulnerable and why In the past, indices have been constructed as a way to measure specific dimension of vulnerability to natural disasters or climate change like the Environmental Vulnerability lndex of SOPAC and the Social Vulnerability lndex of the ECLAC. Figure 3 Vulnerability Egg Model Why isolate the social aspect in constructing the vulnerability index? There is limited research in this area. According to Cutter et al (2003), "there have been few, if any, attempts to develop larger theoretical or conceptual understandings of comparative indicators of social vulnerability, despite the clear need to develop such a robust and replicable set" (p257).
The long-term environmental impacts of efficiency and reduced oil consumption due to high oil prices would be beneficial (e.g., less vehicular emissions, improved technology and design, fuel substitution and alternative renewable energy sources, sustainable consumption, etc.). ESMAP of the World Bank developed oil vulnerability index at the national level focusing on economic aspects. There are available models that can estimate the costs associated with a potential reduction in economic growth resulting from disruptions of cheap oil supply. The outcome of these models can be interpreted as proxy for vulnerability in terms of economic loss but are not used to compare geographical areas. For example, in fall of 2005, a contractor of the U. S. Department of Energy developed a model using a hypothetical oil disruption scenario similar to the Venezuelan strike in 2003 (i.e., maximum of 2.2 million barrels per day disruption for 6 months) and assuming an oil price of $55 per barrel (U. S. Government Accountability Office 2006). The model predicted that world crude oil prices would increase by about $1 1 per barrel in the 2" month of disruption (or $66 per barrel), the impact of which will be $23 billion reductions in the U. S. gross domestic product.
The social aspect of vulnerability to oil prices is complex and in some cases, involve individual choices such that despite high oil prices, people may still choose to drive to their workplace in the absence of other transport choices, geographical location, or extreme weather conditions. In the context of climate change, Adger and Kelly (1999, p. 254) argue that one of the main reasons for studying social vulnerability is to provide information about the problem to be able to assess the magnitude of the threat.
3.5.2 Selection Criteria for Indicators
The next step is to select indicators using suitable criteria. Broadly, the selection of indicators was guided by the conventional business wisdom, SMART (Moghan 2004, pl51) modified to fit the purpose of the study:
S - simple;
M - measurable;
A - available;
R - reliable; and,
T - timely.
Further to the definition in Section 3.5.1, social vulnerability to oil prices is a function of exposure and elements at risk. Exposure is the condition of being subject to some effect or influence. The choice of transport to work and average household expenditure on transportation are considered as a kind of exposure that could make one vulnerable to oil prices. The use of car, van, or truck for transport to work as driver or as passenger captures the extent of automobile dependence in a CMA.
Risk (or elements at risk) is the potential to be subjected to an adverse condition, damage or loss. According to the Emergency Management of Australia 1998 (cited in Buckle et al 2000), elements at risk is the "population, buildings and civil engineering works, economic activities, public services and infrastructure, etc. exposed to hazards." In this study, the population belonging to ages 15 years (i.e., working population) and over is considered elements at risk. This portion of the total population is considered to be most directly affected or harmed by oil price increases and referred to as the vulnerable age group. Another indicator that reflects elements at risk is the incidence of low income of population living in private households. Table 3 gives the summary of selecting indicators using SMART and the next section describes the four indicators.
Table 3 Selection of Indicators using SMART
Simple Measurable Available Reliable Timely d 4 4 age group (from Community (collected and (every census population (15 Profiles of reviewed by year) years and Statistics Canada) experts from over) Statistics Canada) Mode of 4 4 transport to (from Community (collected and (every census work by car, Profiles of reviewed by year) van or truck as Statistics Canada) experts from driver or as Statistics passenger Canada) Average 4 4 household (from Spending (collected and (every year) expenditure on Patterns in reviewed by transportation i Canada) experts from Statistics Canada) 4 d 4 low income of (from summary of (collected and (every census population table available for reviewed by year) living in private census experts from households metropolitan areas Statistics from Statistics Canada) Canada)
Vulnerable age group population (ages 15 years and over), X,
The basis for selecting this age group is the study of Heisz and LaRochelle-Cote (2005) of Statistics Canada, Work and Commuting in Census Metropolitan Areas, 1996- 2001. According to their study, the population ages 15 years and over commute to work more as the driver (e.g., 75.9 percent for age group 45-54 years) and less as a passenger (4.8 percent for age group 35-44 years, see Table 4). Given this trend, oil price increases will directly affect this age group population. Their study also indicates that public transit use of people aged 65 years and over decreases at 12.5 percent.
Rosenbloom (2001) also confirms the lower use of public transit in elderly. Using data from the US, Australia, Germany, New Zealand, Norway, and UK, Rosenbloom concluded that compared to a decade ago, older people around the world are more likely to have driver's licenses, less likely to use public transit, and take additional trips more often as the driver regardless of differences in culture or policy. An OECD report (1998) also cited that older people take as many or more non-work trips than younger people.
Table 4 Percentage Distribution of Workers by Mode of Transportation, 2001 (all CMA workers)
11 I I I I I I Age Group Public Driver Passenger Walk Bicycle Other Transit
15-19 22.9 35.4 25.1 12.7 2.6 1.3
Source: Statistics Canada, Trends and Conditions in CMAs, Work and Commuting in Census Metropolitan Areas, 1996-2001(Table 3.4, p.49)
On the other hand, a study conducted by Noland et a1 (2003) revealed that one of the main effects of disruption resulting from the British fuel crisis in September 2000 is the trips involving children bringing them to and from school. The adverse impacts involving children can be considered secondary compared to the impacts of work-related trips by the working age population in the event of oil price increases or oil supply disruptions.
Mode of transport to work, Xz
According to Statistics Canada, this indicator refers to the regular mode of transport from home to work of non-institutional residents that are 15 years of age and over who worked at some time since January 1,2000. The mode of transport to work by car, truck or van as driver or as passenger reflects the extent of automobile dependence in a CMA. As more workers opt to use automobiles in getting to work, the more vulnerable they will be to higher oil prices. The mode of transport to work in this study includes the working population using car, truck or van as driver or as passenger and also those indicated as other mode (i.e., taxi or any motorized vehicle). Public transit, cycling or walking are other ways of getting to work. The total of the percentages of using car, truck or van as driver or as passenger and use of public transit, cycling or walking equals 100 percent. Thus, if a CMA has a high use of car, truck or van as mode of transport to work then it implies that the use of public transit is low.
Average household expenditure on transportation, X3
Households that spend more on transportation are more vulnerable to oil price increase. Based on the spending patterns in Canada from I996 and 2001 census data of the 14 CMAs, households spend more on transportation than on food, clothing; water, fuel and electricity. On average, households spend 12.4 percent on transportation, 11.3 percent on food, 3.2 percent on water, fuel and electricity; and 4.3 percent on clothing. Transportation expense is steadily increasing and will likely increase with higher oil prices.
Incidence of low income of population living in private households, Xq
Statistics Canada defines incidence of low income as the "proportion or percentage of economic families or unattached individuals in a given classification below the low income cut-offs." This proportion covers only those living in private household and excludes those in the institutions or other collective dwellings. Low-income population is generally vulnerable because they have limited resources to spend for additional expense not only for the transport costs but for other goods as well whose prices are also affected by higher oil prices. Thus, the capacity to absorb the increasing oil prices from their existing income is a significant indicator of vulnerability. Table 5 presents the summary of indicators and assumptions. Table 5 Summary of Indicators and Assumptions
lndicator Description of Assumptions on Source of the lndicator the functional Data relationship between the indicator and vulnerability to oil prices Mode of Use of car, van The higher the Statistics transport to or truck as driver population using Canada, work or as passenger car, van or truck (as Community by residents 15 driver or as Profiles years of age and passenger), the 2001 and over as percent greater the 1996 of all total modes vulnerability to oil of transport to prices work Average Transportation The higher the Statistics household expenditure as average household Canada, expenditure on percent of total expenditure on Family transportation expenditure transportation, the Expenditure greater the Survey 1996 vulnerability to oil and prices. Spending Patterns in Canada 2001 Incidence of Population living The higher the Statistics low income in private incidence of low Canada, households income, the greater Community excluding those the vulnerability to Profiles in institutions or oil prices. 2001 and collective 1996 dwellings as percent of economic families or unattached individuals below the income cut- offs
Vulnerable age Ages 15 years The higher the Statistics group and over as vulnerable Zanada, population percent of total oopulation, the Zommunity population of the greater the 'rofiles CMA ulnerability to oil ZOO1 and orices. 1996
Modified presentation from Vincent 2004. 3.5.3 Sampling
The unit of analysis is the census metropolitan area (CMA) and as of 2001, Statistics Canada lists 27 CMAs. Within the sampling frame of 27 CMAs, convenience sampling was used to select 14 CMAs as sample. Convenience sampling is obtaining a group that has available data. This type of sampling is cost-effective for case studies as it overcomes the use of huge resources required to have the same data for a larger representative sample (Black 2002).
These 14 CMAs account for 52 percent of the total number of CMAs representing Canada's large and mid-sized cities. In addition, these CMAs cover 84 percent of the total urban population in Canada. The CMAs are St. John's in Newfoundland, Halifax in Nova Scotia, Saint John in New Brunswick, Quebec City and Montreal in Quebec, Ottawa-Hull and Toronto in Ontario, Winnipeg in Manitoba, Regina and Saskatoon in Saskatchewan, Calgary and Edmonton in Alberta, Vancouver and Victoria in British Columbia.
3.5.4 Data Collection
The apparent sources of data for most of the research purposes are the government-produced official statistics. Data for the selected indicators relied heavily on the 1996 and 2001 Community Profiles of the Statistics Canada, which are available online from its official website (http://www.statcan.ca/communityprofiles/). The Community Profiles provide census data of communities, counties (or their equivalents), and large and smaller metropolitan areas.
Other publications referred to are the 1996 Family Expenditure in Canada, Spending Patterns in Canada 2001, and the thematic Analytical Papers on Trends and Conditions in Census Metropolitan Areas also published by Statistics Canada. The Family Expenditure Survey is conducted about every two years since 1953 and coverage is restricted to CMAs and census agglomeration. In 1997, Survey of Household Spending replaced the Family Expenditure Survey. The Survey of Household Spending is carried out in private households covering the 10 provinces and 3 territories.
The use of government-produced official statistics offers several advantages to researchers such as availability at relatively no cost to the researcher and data are collected by experts systematically over time that allow for comparative analysis (Henn et al 2006). Other sources of data are published journals, survey results of selected research projects, and government publications.
3.5.5 Normalization, Weighting and Aggregation
It is necessary to normalize the data to allow for aggregation into an index. Normalization is translating the indicators into some sort of standard score to sum up the components of the index. Ranking is the simplest normalization method.
The CMAs were ranked for each indicator based on their theoretical relationship to vulnerability to oil prices (i.e., the higher the incidence of lower income population in the CMA, the greater is the vulnerability to oil prices). Ranking the CMAs converts the data into ordinal values. This approach is simple and independent of outliers but does not indicate the magnitude of differences between the measurements.
In weighting, the simplest and most common method is using equal weights of indicators (St. Bernard 2004; Briguglio 2003; Briguglio 1995; Crowards 1999; UN-CDP 2000; OECD 2003). Another method is varying weights based on literature and expert judgment (Vincent 2004; Dodson and Sipe 2005; SustainLane 2006; Dodson and Sipe 2006; Cutter et al 2003). In the absence of a defensible method for assigning weights and the relationship among indicators, this study used equal weights. Equal weights assume that each indicator has an equal contribution to the vulnerability of CMAs, thus, not making a priori assumptions about the importance of the indicator to the overall vulnerability index. According to Salzman (2003), given the complexity of social and economic phenomena, the use of Principal Component Analysis and Factor Analysis in determining the weights "do not always make sense to social indices" which strengthens the equal weights method. The limitation of not having an "objective" approach for determining weights and aggregation methods does not necessarily mean that the validity of the index should be rejected (Nardo et al 2005, p.23). Thus, it is important to keep the process transparent and the objectives of constructing the index clear.
The vulnerability index is calculated by the equation below:
where, n is the number of CMAs and rank of CMA for each indicator at time, t (Saisana and Tarantola 2002; Nardo et al 2005). External validity is ensured by choosing a critical case study (see sect. 3.3) of 14 CMAs in Canada. 3.5.6 Test for Robustness
Nardo et al (2005) argue that "no model (construction path of the composite indicator) is a priori better than another and because each model serves different interests." To strengthen the reliability, usefulness and credibility of the index, a test for robustness or sensitivity analysis was conducted.
A sensitivity analysis is normally done when there is uncertainty about the true value of the input. Potential sources of uncertainty are selection of indicators, normalization method, and weighting. To test the robustness of the social vulnerability index, linear scaling technique was used as alternative normalization method, inclusion of population density as another indicator, and varying the weight of mode of transport to work.
Linear Scaling Technique (or Rescaling)
The linear scaling technique (LST) was used by UNDP in their Human Development Index, in the lndex of Social Health by the Human Resources Development of Canada, and in the lndex of Economic Freedom by the Heritage lnstitute and Economic Freedom produced by Cato Institute (Salzman 2003, p13).
Rescaling follows the equation,
where XqCt= indicator for CMA, c at time, f
Minc(Xqct)and Maxc(Xqct)are the minimum and maximum values of xqCtacross all CMAs at time, t.
Aggregation of indicators (Nardo et al 2005, p75)
Composite Indicator, CI = I,=,,, Q (wq)(lqc)
where, tqZlto Q = 1 and 0 5 wq 5 1
Varying the Weights of the Indicators
Initial ranking of CMAs used equal weights. Mode of transport to work by car was assumed to have higher weight or contribution to the vulnerability index compared to the other three indicators as Canadian cities are among the most highly auto-dependent. Compared to other three indicators, mode of transport to work involves individual choices that can be influenced by policies intended to reduce oil vulnerability. It is unclear what interventions will fit for vulnerable age group population and incidence of low income to reduce oil vulnerability.
The varying weights are 50 percent for mode of transport to work, and 16.7 percent each to vulnerable age group population, incidence of low income, and average household expenditure on transportation (or 50 percent divided by the three indicators).
Inclusion of Another Indicator
Population density was chosen as another indicator. According to Newman (1999), transport energy use declines as population density increases while Sanghi (1976) asserts that low population density and higher income cause higher levels of automobile dependence. While these authors suggest that population density influences auto-dependence and transport energy consumption which ultimately will affect social vulnerability to oil prices, its inclusion, in this case, is not to test the relationship but only to show how another indicator affects the CMA ranking. Since the research model assumed equal weights, population density was not selected as one of the indicators in constructing the social vulnerability index because it is correlated with vulnerable age group population, mode of transport to work, and average household expenditure on transportation.
Link to Other Variables
The social vulnerability index can be linked or correlated to oil prices in the CMAs to determine the quality of the construct and to test the explanatory power of the index (Nardo et al 2005, p24). This approach is also known as external validation to distinguish between "good" and "bad" indices (Booysen 2002, p130). Cutter et al (2003) used this method to test their Social Vulnerability Index of the U. S. developed for 3,141 counties. They used number of presidential disaster declarations by county to test the reliability and usefulness of their social vulnerability index to environmental hazards. To test the correlation between the social vulnerability index and oil prices, Spearman's rank correlation coefficient, r, or p, was used. The Spearman's rank correlation coefficient uses ordinal data and is expressed by the equation,
where d is the difference in ranks for a pair of sample data (i.e., oil prices and vulnerability index) and N is the sample size (Triola et al 1999).
Researchers generally regard that correlation coefficients between 0.3 and 0.7 (positive or negative) demonstrate some reasonable correlation (0.3 reasonably weak, 0.7 reasonably strong) (Denscombe 1998; Lewin 2005, p230). High correlation value between the social vulnerability index and oil prices implies a high quality index. However, high correlation does not imply causation. Harnett and Murphy (1 993, p. 492) argue that belief in causation does not come from statistics but from the mind of the one who conceptualizes the research model. CHAPTER 4: RESULTS AND ANALYSIS
"The best way to have a good idea is to have a lot of ideas." - Linus Pauling
A social vulnerability index to oil prices was constructed from four "best available" indicators according on their theoretical relationship to vulnerability. Based on the social vulnerability index, the 14 CMAs were ranked from least to most vulnerable to oil prices. This chapter summarizes the analysis of the data collected and the interpretation of findings. The theoretical relationship of the indicators to vulnerability is given below:
HI: The higher the population of vulnerable age group in the CMA, the greater the vulnerability to oil prices (X,).
H2: The higher the population using car, truck or van as driver or as passenger as mode of transport to work, the greater the vulnerability (X2).
H3: The higher the household expenditure on transportation, the greater the vulnerability (X3).
H4: The higher the incidence of low income, the greater the vulnerability (X4).
Figure 3 shows the indicators used for the social vulnerability index. The aim is to construct the index based on the most recent available data, thus, the 2001 Community Profiles of Statistics Canada were used since the 2006 Census data are not yet available.
4.1 Ranking of Census Metropolitan Areas
The 14 CMAs were ranked for each indicator based on their theoretical relationship to vulnerability to oil prices. This approach was also used by Fagerberg (2001) to rank 19 countries using five indicators to determine the overall situation on information and communications technologies applications and development (cited in Nardo et al 2003, p18). Table 6 gives the summary of ranking for each indicator.
Vulnerable Age Group Population (ages 15 years and over), Xi
Saskatoon, SK has the lowest population of vulnerable age group (79.4 percent) among the 14 CMAs and Regina, SK ranked second lowest (80.1 percent). On the other hand, Victoria, BC has the highest population of vulnerable age group at 84.8 percent followed by Quebec, QC (83.9 percent). Following the theoretical relationship of this indicator to vulnerability, Victoria, BC and Quebec, QC will be most vulnerable to future increase in oil prices while Saskatoon, SK and Regina, SK will be the least vulnerable. Calgary, AB and Toronto, ON (both at 80.4 percent) tied in the fourth rank while Winnipeg, MB and Saint John, NB (both at 80.9 percent) tied in the 6'h rank. Figure 5 shows the CMA ranking for this indicator. -~~ulner~ble Age Group ~o~ulation,XI
Figure 5 CMA Ranking for Vulnerable Age Group Population
Mode of Transport to Work Using Car, Van or Truck as Driver or as Passenger, X2
On the mode of transport to work, St. John's, NFL and Regina, SK are the highest users of car, van or truck either as driver or as passenger (91.1 percent and 89 percent, respectively) while Montreal, QC (28.9 percent), Toronto, ON (27.8 percent) and Ottawa-Hull, ON (27.3 percent) are the top three highest users of public transit, cycling or walking. With this trend, the working population from Montreal, QC; Toronto, ON and Ottawa-Hull, ON can better adapt to potential oil constraints than St. John's, NFL whose working population is highly auto-dependent. Figure 6 shows the CMA ranking for X2.
Noland et al (2003) did a survey and analyzed the behavioural adaptation of individuals and households from the British fuel crisis of September 2000. Their findings showed that most activities and individuals do not expect major disruption in the everit of another fuel shortage. The authors associate this finding with the diversity of transport system in UK and its compact urban form. This finding is positive but they also found out that many respondents expect severe disruption to work-related trips. The authors suggest that this reflects auto-dependency and attempts to shift people to other modes of transport may be difficult.
E3 Mode of Transporl to Work by car, truck or van as driver or as passenger, X2 . -.
Figure 6 CMA Ranking for Mode of Transport to Work
Average Household Expenditure on Transportation, X3
In contrast to XI, vulnerable age group population, Victoria, BC has the lowest average household expenditure on transportation while Saint John, NB spends the highest on transportation as a percentage of total expenditure. While Victoria, BC is most vulnerable to oil prices due to its high vulnerable age group population (84.8 percent), it will be least vulnerable on transportation expenditure. Fifteen percent of its working population walk or use bicycle to get to their workplace.
In Quebec, QC, ranked next to Victoria, BC as most vulnerable to oil prices due to its vulnerable age group population (83.9 percent), only 8 percent of its working population walk or use bicycle as mode of transport to work. Ten percent of the working population in Victoria, BC and Quebec, QC use public transit. Therefore, all things being equal, these results suggest that an individual has the option whether to drive, use public transit, cycle or walk to their workplace in order to reduce their vulnerability to oil prices. Figure 7 shows the CMA ranking for XB.
Q) 1 Average Household Expendilure on Transportation, X3
Figure 7 CMA Ranking for Average Household Expenditure on Transportation
Incidence of Low Income Living in Private Households, Xq
Montreal, QC and Vancouver, BC have the highest incidence of low income living in private households (22.2 percent and 20.8 percent, respectively) while Calgary, AB and Victoria, BC have the lowest incidence of low income (14.1 percent and 14.4 percent, respectively). This suggests that Calgary, AB and Victoria, BC are in a better position to adapt economically in the event of high oil prices both on transport costs as well as on other costs influenced by oil prices such as food, water, fuel & electricity, or clothing. Similarly, households in Winnipeg, MB (ranked 12'~at 19.2 percent) will have difficulty absorbing the higher costs resulting from oil prices compared to households from Ottawa-Hull, ON (3rdat 15 percent), Halifax, NS (4'h at 15.5 percent), and Regina, SK (5that 15.5 percent). Toronto, ON is between the least and most vulnerable CMA (the biggest CMA is ranked 7'h at 16.7 percent) which could suggest that low-income households may have the capacity to absorb the impact of oil prices. A likely scenario that could make households adapt is the availability of transport choices other than car as a default, location of jobs within areas serviced by public transit, available amenities within walking distance, and reliability of public transit. Figure 8 shows the CMA ranking for X4.
11 lncidence of LOW Income, X4 I
Figure 8 CMA Ranking for Incidence of Low Income Table 6 Ranking of CMAs by Indicator (least vulnerable to most vulnerable)
CMA Vulnerable Mode of Average Incidence of Age Group Transport to Household Low Income Population Work (using Expenditure car, van or on truck as driver Transportation or as passenger)
St. John's, NFL 11 14 13 8
Halifax, NS 9 5 4 4.5
Saint John,.NB 7.5 12 14 9
Quebec, QC 13 9 7 11
Montreal, QC 10 1 2 14
Ottawa-Hull, ON 6 3 6 3
Toronto, ON 4.5 2 10 7
Winnipeg, MB 7.5 6 11 12
Regina, SK 2 13 9 4.5
Saskatoon, SK 1 11 12 10
Calgary, AB 4.5 7 3 1
Edmonton, AB 3 10 8 6
Vancouver, BC 12 8 5 13
Victoria, BC 14 4 1 2
From Table 6, Montreal, QC has the highest incidence of low income and the lowest user of automobiles as mode of transport to work. This trend suggests that low- income population uses public transit more compared to high-income population or could be that low-income commuters opt to use public transit as the only affordable choice.
According to the study of Heisz and LaRochelle-Cote (2005) of Statistics Canada, high-income commuters have a choice between using public transit or driving because they can afford both. Their study also revealed that high-income commuters prefer to drive than use public transit the closer they live and work to the city centre Ottawa-Hull, ON is third lowest in the incidence of low income and third among the highest users of public transit. This trend is also shown in Halifax, NS (4thamong lowest in incidence of low income and 5thhighest users of public transit) and Victoria, BC (next to Calgary, AB in the lowest incidence of low income and 4thamong highest users of public transit at 25.9 percent). The trends in Ottawa-Hull, ON, Halifax, NS; and Victoria, BC confirm that high-income population has the option between driving to work and taking the public transit. It is likely that in these CMAs, more high-income commuters may have chosen public transit to work instead of driving. In contrast, Regina, SK is fourth lowest in the incidence of low income but second highest user of car as mode of transport to work. A likely reason could be households in Regina, SK opted to drive because they can afford or could be that there are no other transport choices available for them in getting to work except to drive.
4.2 Aggregation of Indicators
Aggregation of indicators results to a highest index score of 56 (most vulnerable) and a lowest index score of 4 (least vulnerable). The ranking shows that St. John's, NFL, Saint John, NB, Quebec, QC, and Vancouver, BC are the four most vulnerable CMAs while Calgary, AB, Ottawa-Hull, ON, Victoria, BC and Halifax, NS are the four least vulnerable to oil price increase. The final ranking of CMAs is given in Table 7 and Figure 8.
Table 7 Final Ranking of CMAs
Vulnerability to Oil Prices CMA (least to most vulnerable)
Rank Index
Calgary, AB 1 15.5
Ottawa-Hull, ON 2 18
Victoria, BC 3 21
Halifax, NS 4 22.5
Toronto, ON 5 23.5
Edmonton, AB 6 2 7 Vulnerability to Oil Prices CMA (least to most vulnerable)
Rank Index
Montreal, QC 7 2 7
Regina, SK 8 28.5
Saskatoon, SK 9 34
Winnipeg, MB 10 36.5
Vancouver, BC 11 38
Quebec, QC 12 40 Saint John, NB I St. John's, NFL I
Least Vulnerable to Most Vulnerable
Calaarv.- - AB I Ottawa-Hull, ON E-d Victoria, BC ( 121
Halifax, NS I- 022.5
OSocial Vulnerability lndex to Oil 1 P, -1
Saint John, NB em425 St. John's, NFL - 146 Figure 9 Social Vulnerability lndex to Oil Prices, 2001 Following the assumed theoretical relationship between the four indicators and vulnerability, the social vulnerability index to oil prices, in general, indicates that St. John's, NFL is most vulnerable because its vulnerable age group population is high, it is highly-dependent on automobile as mode of transport to work, its average household expenditure on transportation is high, and its incidence of low income is high. Similarly, Calgary, AB, is least vulnerable to oil prices because its vulnerable age group population is low, its use of automobiles as mode of transport to work is low, its average household expenditure on transportation is low, and its incidence of low income living in private households is low compared to other CMAs
In a linear additive aggregation method, as used in this study, there is an expression of trade-off or compensation where a deficit in one indicator can be compensated by a surplus in another indicator (Nardo et al 2005, p22). In the case of Montreal, QC, its high incidence of low income was compensated by its high use of public transit and low average household expenditure on transportation. Similarly, the high vulnerable age group population in Victoria, BC was compensated by its high use of public transit, low incidence of low income, and low average household expenditure on transportation.
Given these four indicators, the most likely dimension to focus strategies of reducing oil vulnerability is on mode of transport to work (see Sect. 4.3). Depending on the incentives andlor disincentives available, individuals can choose whether to increase or reduce their vulnerability to higher oil prices in their transport choices.
The results of the 1992 Orange County Annual Survey in California showed that employed solo drivers are willing to stop driving solo if employers give them a cash bonus to stop solo driving (28 percent), or more carpools at work (35 percent), or if more public transit (33 percent) were available. Only few were likely to stop solo driving if charged with parking fee at work (20 percent), a smog fee (17 percent) or a congestion fee (16 percent) (Baldassare et al 1998). Consequently, the average household expenditure on transportation will be greatly influenced by preferences on mode of transport to work. It will be complex and difficult to even consider strategies focusing on vulnerable age group population or incidence of low income to reduce oil vulnerability. One of the advantages of the index is the easy interpretation of a complex issue since it provides the "big picture" of relative social vulnerability to oil prices that can serve as a starting point for further research and investigation. As a single value, the social vulnerability index facilitates understanding compared to various trends given by the four indicators and allows for easier comparison of CMAs. As a communication tool to attract public interest, ranking of CMAs is easier to remember.
Several underlying factors affect the social vulnerability of CMAs to oil prices. Some of these factors are fuel consumption in transportation per capita, vehicle ownership, and available incentives to discourage the use of automobile. These indicators vary from province to province and, hence, from CMA to CMA. Unfortunately, the data for these indicators at the CMA level are not available, no other research is available to compare the results of this study, and no available data set to measure vulnerability more comprehensively that could identify its spatial distribution.
Comparison of Vulnerability Indices, 1996 and 2001
The vulnerability index for 1996 Census data was also calculated to determine the change in the relative vulnerability between 1996 and 2001, if any. A highest score of 56 is most vulnerable and a lowest score of 4 is least vulnerable. The results show that in 1996, Ottawa-Hull, ON is the least vulnerable and St. John's, NFL the most vulnerable CMA. In terms of rank, Quebec, QC is consistently 3rdmost vulnerable while Montreal, QC remained in between the least and most vulnerable CMAs. The comparison of indices showed that half of the CMAs (or 50 percent) has reduced vulnerability to oil prices from 1996 to 2001. With the high oil prices occurring in late 2004 up to the present, it would be interesting to determine whether these prices influenced the mode of transport to work by car, average household expenditure on transportation, and the incidence of low income in the CMAs. Table 8 and Figure 10 give the comparison of ranking between 1996 and 2001. Table 8 Comparison of Ranking, 2001 and 1996
CMA 2001 1996 I Rank I lndex ( Rank I lndex St. John's, NFL 1 14 1 46 1 14 1 43 Halifax, NS 4 22.5 5 26
Saint John, NB 13 42.5 11 36
Quebec, QC 12 4 0 12 37
Montreal, QC 7 27 7 29
Ottawa-Hull, ON 2 18 1 15
Toronto, ON 5 23.5 4 25
Winnipeg, MB 10 36.5 10 34
Regina, SK 8 28.5 6 29
Saskatoon, SK 9 34 8 33
Calgary, AB 1 15.5 3 2 1
Edmonton, AB 6 27 9 34
Vancouver, BC I 11 I 3 8 1 13 1 38 Victoria, BC 3 21 2 20 Least Vulnerable to Most Vulnerable
Calgary, AB 21
Ottawa-Hull, ON
Victoria, BC 021 Halifax, NS
Toronto, ON
Montreal, QC 0 2001 Edmonton, AB 34
Saskatoon, SK
Winnipeg. MB
Vancouver, BC
Quebec, QC 40
Figure 10 Comparison of Social Vulnerability Index, 1996 and 2001
4.3 Test for Robustness of the Vulnerability Index
No model is above criticism and subjectivity can not be entirely avoided in selecting the indicators, choice of normalization methods, and assigning weights of importance to indicators (Briguglio 1995; Luers et al 2003; Vincent 2004; Briguglio 2003; OECD 2003). The reliability and usefulness of the index are determined by testing its robustness. The following section summarizes the results and Table 9 gives the comparison of CMA rankings after the test for robustness.
Linear Scaling Technique
The use of linear scaling technique (LST) did not result to significant changes in the ranking of the CMAs. Spearman's rank correlation coefficient between the ranks using LST and the original ranks is 0.977 (significant at a = 0.01). This high correlation value implies that ranking of the CMAs is stable and not affected by the choice of normalization method. Varying the Weights of Indicators
As indicated in Sect. 3.5.6, the new weights of the indicators are: 50 percent for the mode of transport to work using car, truck or van as driver or as passenger, and 50 percent shared equally by vulnerable age group population, incidence of low income, and average household expenditure on transportation (or 16.7 percent for each indicator). If increasing the importance of mode of transport to work will significantly affect the degree of vulnerability to oil prices (or ranking of the CMAs) then measures may be considered to shift the working population away from car use.
Results of varying weights show that St. John's, NFL remains the most vulnerable while Ottawa-Hull, ON, the least vulnerable (2"d least vulnerable from original ranking). Increasing the importance of mode of transport to work makes Calgary, AB vulnerable (1'' from original ranking to 5'h after varying weights). Regina, SK (8'h from original ranking to Ilth after varying weights) and Saskatoon, SK (gthfrom original ranking to 12'~after varying the weights) are affected in a similar way. About 80 percent of the working population in Calgary, AB are auto-dependent, 89 percent in Regina, SK and 88 percent in Saskatoon, SK. On the other hand, Montreal, QC (7thfrom original ranking to 3rdafter varying the weights) and Toronto, ON (5'h from original ranking to 2nd after varying the weights) will be less vulnerable as these CMAs are the highest users of public transit, bicycle and walking.
Inclusion of Another Indicator
The ranks of four CMAs were not affected with the inclusion of population density in the calculation of the index. Calgary, AB remains the least vulnerable and Saint John, NB (13'~from original ranking to 14Ihafter inclusion of population density) emerged the most vulnerable. Saint John, NB, and St. John's, NFL are consistently among the most vulnerable CMAs. Similarly, Calgary, AB, Ottawa-Hull, ON, and Victoria, BC are among the least vulnerable CMAs.
CMAs with low population densities like Halifax, NS (65 persons per sq. km) and Saskatoon, SK (44 persons per sq. km) became more vulnerable while Vancouver, BC (691 persons per sq. km), Montreal, QC (847 persons per sq. km), and Quebec, QC (217 persons per sq. km) became less vulnerable.
The changes from the original ranking to the new ranking (with population density) range from 2 to 3 positions. These results show the sensitivity of the index to an inclusion or exclusion of an indicator. The social vulnerability index is valid and reliable only for the set of indicators chosen (in this case, the four indicators). Therefore, it is essential to make sure that the choice of indicators is transparent, using a set of acceptable criteria, and in consultation with experts and non-experts if the vulnerability index is aimed as a tool to drive policy interventions.
Overall, as given by Spearman's rank correlation coefficient, the CMA ranking is not affected by the choice of normalization method.
Table 9 Comparison of CMA Rankings
CMA Original Linear Varying Inclusion of Ranking Scaling Weights Another Technique Indicator
St. John's NFL 14 14 14 13
Halifax, NS 4 5 6 6
Saint John, NB 13 13 13 14
Quebec, QC 12 12 10 10
Montreal, QC 7 6 3 5
Ottawa-Hull, ON 2 1 1 2
Toronto, ON 5 3 2 4
Winnipeg, MB 10 9 7 11
Regina, SK 8 8 11 8
Saskatoon, S 9 10 12 12
Calgary, AB 1 2 5 1
Edmonton, AB 6 7 8 7
Vancouver, BC 11 11 9 9
Victoria, BC 3 4 4 3
Link to other Variables
The 2001 average retail prices of regular unleaded gasoline at self-service filling stations from Statistics Canada were used to determine the correlation of the social vulnerability index to oil prices (see Table 10). The Spearman's rank correlation coefficient, r,, between the social vulnerability index and the 2001 average gasoline prices is 0.568 (significant at a=0.05). This correlation value indicates a medium strength relationship (Lewin 2005, p230).
The construction of the vulnerability index was based on 2001 census data when gasoline prices were considered normal. Despite this, an acceptable positive correlation was established. This correlation value implies that based on the four indicators used in constructing the index, social vulnerability of CMAs will increase as the price of oil increases. The strength of correlation may be increased with better choice of indicators with available data and in assigning of weights that can characterize the social vulnerability to oil prices more realistically and comprehensively.
Cutter et al (2003) constructed a social vulnerability index for 3,141 counties in the U. S. Using the same approach, they determined the relationship between the number of disaster declarations per county in 1990 and their social vulnerability index. Their objective is to test the reliability and usefulness of their social vulnerability index. Their results showed a weak but negative relationship (r = -0.099, s=0.000) suggesting no discernible trend between the frequency of disaster declarations per county and degree of social vulnerability. This led them to conclude that social vulnerability index is not a "perfect construct" and more fine tuning is required such as examining the change of social vulnerability over time and space or using economic data together with the frequency of hazard events to determine which factors contribute most in loss of dollar.
Table 10 2001 Average Retail Price of Regular Unleaded Gasoline at Self-service Filling Stations, cents per litre
CMA Price, cents per litre St. John's, NFL I 79.1 1 11 - - - Halifax, NS 72.83 Saint John, NB 70.02 Quebec, QC 73.95 Montreal, QC 73.75 Ottawa-Hull, ON 66 Toronto, ON 67.78 Winnipeg, MB 65.03 Regina, SK 72.24 Saskatoon, SK 72.23 Calgary, AB 64.51 CMA Price, cents per litre 11 Edmonton, AB I 61.33 11 11 Vancouver, BC 1 68.93 11 Victoria, BC 73.93 Source: CANSIM, Table 326-0009,2001.
4.4 Implications and Directions for Future Research
According to the World Development Report 2003 (p132) of the World Bank, in order to achieve sustainable urban development, cities need stronger and forward- looking institutions that could sense emerging problems, balance interests, commit to effective execution of agreed solutions, and to provide wide access to assets that ensure the provision of public goods. Local governments need to become organized and begin to understand the consequences of peak oil.
Why local governments? Article 28 of Agenda 21 recognizes the key role of local governments in educating, mobilizing, and responding to the public in promoting sustainability initiatives (Brugman 1996). Preparing the public for future energy challenges is an integral part of urban sustainability. There is paucity of data on urban planning and policy in a future scenario of energy constraints. The use of indices could be a powerful tool in educating the public on important issues that could affect their lives.
Future research should be able to determine the spatial distribution and other dimensions of vulnerability to oil prices. Social learning may be attained by involving the public and experts in selecting the indicators to measure vulnerability and in determining the appropriate weights and aggregation method for a more realistic and valid vulnerability index. Research to further understand public perceptions and views on oil vulnerability is crucial in achieving their support on strategies preparing for peak oil.
Most importantly, oil constraints should be central to short- and long-term research on sustainable urban planning and development. Alternatively, climate change policy research should be consistent with future availability of oil supply because climate change impacts are contingent on oil consumption.
Other future research should deal with what or when will be the "tipping point" beyond which a widespread policy or behavioural change becomes necessary for transportation choices. Kunstler (2005) presented some grim scenarios of a "next economy" with limited supply of cheap oil. According to Kunstler, the "long emergency" will bring about unprecedented social and economic dislocation, an economy that will dramatically shrink, local, and centered on farming. Should the government become ineffective and irrelevant during the long emergency; Kunstler believes that the "dominant culture of the American South1'may tend to promote people to take the law into their hands (p.287). This presents a different kind of vulnerability.
There should be vulnerability assessments to oil crisis that measure the values and attitudes of people in a community. King and MacGregor (2000) argue that a community's vulnerability can be measured by the attitudes and values of its residents. Values are "set of philosophical, ethical, moral, and emotional principles" that direct individual or society (Rapport et al 1998 in King and MacGregor 2000). The focus of future research should be on individual adaptation, adjusting the mindset, attitudes and values to accommodate the new circumstances of limited cheap oil -a critical paradigm shift because the party is definitely over.
4.5 Limitations of the Study
The choice of indicators was limited by availability of adequate data to measure social vulnerability. The desire to compare CMAs based on a common set of indicators at the same year constrained the choice to only four indicators. The results of this study show the relative vulnerability of CMAs based on the 2001 census data as measured by selected indicators. The positive correlation between the social vulnerability index and average gasoline prices are valid only for the set of indicators used in this study. These results do not capture the spatial distribution of vulnerability and most importantly, will not in any way be able to specifically predict the nature of future oil vulnerability. CHAPTER 5: CONCLUSION AND RECOMMENDATIONS
"It is not the strongest of the species that survive, or the most intelligent, but the one most responsive to change." - Charles Darwin
The preceding chapters dealt with the importance of facing the challenges of a potential end of cheap oil. There is no debate that the impacts of limited cheap oil supply to urban life are inevitable. An effective approach to cushion the adverse impacts is to prepare.
One of the strategies advanced by this study is to measure the social vulnerability to oil prices from a set of indicators to construct an index. The objective is to raise public awareness, to stimulate more detailed research, and to provide baseline comparison of Canadian cities. This section of the report provides a summary assessment and recommendations for future action.
5.1 What We Need to Know
Urban systems are complex and vulnerability is difficult to quantify. The indicator-approach of measuring oil vulnerability adopted in this study is designed to simplify - a reductionist stance to facilitate understanding of a complex issue. As pointed out by King and MacGregor (2000), vulnerability remains the most difficult to measure and is highly dependent on indicators with available data from the census. Buckle et al (2000) believe that even the social conditions that cause and maintain vulnerability are difficult to comprehend. Thus, a definitive conclusion based on the results of this study cannot be easily drawn. This study can only offer possibilities.
Combining the vulnerable age group population, mode of transport by car, truck or van as driver or as passenger, average household expenditure on transportation, and incidence of low income into an index presents the "big picture" of the relative social vulnerability of CMAs to oil prices. The CMA ranking based on its oil vulnerability cannot give a concrete and specific policy direction but as a starting point for action, more detailed research, attract public attention of the issue, and consultation. Cutter (2003, p.7) states that "from the perspective of the policy community, there is a real need to develop a set of metrics to measure and compare the relative vulnerability of one place to another." The outcome of this study is an effort towards this direction by identifying that Calgary, AB, Ottawa-Hull, ON and Victoria, BC are the top three least vulnerable CMAs while St. John's, NFL, Saint John, NB and Quebec, QC are the top three most vulnerable CMAs to oil prices. Based on the social vulnerability index, the size of the CMA, expressed as population density, is not contingent to oil vulnerability. St. John's NFL (215 persons per sq. km) and Quebec, QC (217 persons per sq. km) are almost six times denser compared to Saint John, NB (37 persons per sq. km) but they are identified as among the most vulnerable CMAs. These results could lead to some broader questions and further investigation to examine the conditions at the local level.
Testing the reliability and usefulness of the results, Spearman's rank correlation coefficient between the social vulnerability index and average gasoline prices implies medium strength positive relationship such that higher oil prices may result to greater social vulnerability. The value of these indicators may change over time and space but the positive relationship to oil prices will remain. Given the fact that the data were based on 2001 census when gasoline prices were considered "normal," this positive relationship is likely to be stronger with the same set of indicators if based on 2006 census data. Test for robustness of the index suggests that increasing the weight of mode of transport favours CMAs with high use of public transit, bicycle or walking.
Therefore, consistent with this positive relationship and test for robustness, there is sufficient confidence that measures and strategies to shift the working population of the CMA away from the car will reduce vulnerability to increasing oil prices that could also bring about long-term beneficial impacts on oil consumption and GHG emissions.
It will be futile to expect that the outcome of this study alone will compel decision- makers to act. The primary objective of constructing the social vulnerability index is to raise public awareness of the CMA ranking and to encourage more vulnerability assessments of cities to peak oil. Ranking is one of the best ways to attract public attention (e.g., best and worst country to live using the Human Development Index of UNDP, ranking of 50 U. S. cities' preparedness for an oil crisis by SustainLane, etc). Compared to other countries like Australia and the U. S., there was no initiative in Canada to compare places based on oil vulnerability using indices. Key factors are lack of public awareness on peak oil and its consequences to urban life, limited national media coverage, and the lack of recognition from government agencies and urban researchers that the recent fluctuations in oil prices could imply a constrained global oil production. There is no debate that supply of cheap oil will end, the "tipping point" for action to prepare for this scenario is the recognition and acceptance that it is imminent. Similar to the U. S. and Australia, the outcome of this study is envisioned to attract media attention, the NGOs, and other urban researchers about the issue.
There is nothing new in the methodology of constructing index adopted in this study. While the method is simple, selection of indicators with available data to allow for comparison of CMAs proved to be challenging. The Australian experience in constructing their oil vulnerability index also recognized this data limitation. Given the importance of preparing for peak oil, the availability of adequate data should not be an obstacle to sustained research efforts or in raising the issue to the higher level of government, as in the case of Australia. According to Kasperson and Kasperson (2001), the existing conflict between the scale where data are available and the scale at which vulnerability needs to be measured may not be resolved.
There is enough information and analytical tools on how best to construct vulnerability indices but it is essential to involve a wide range of stakeholders in the process to ensure credibility, transparency, and ownership. Despite challenges associated with construction of indices, they will continue to be developed and will remain useful in making a point of action, as a communication tool and for analytical purposes (OECD 2003).
5.2 What Others are Doing
While not directly related to reducing vulnerability to oil prices, other places have embarked on efforts to improve public awareness and to prepare them for future energy challenges. Some of the initiatives at the local level are given below:
San Francisco, California
The PR Web Press Release on April 14, 2006 indicates that San Francisco is the first US city to pass a resolution on peak oil in April 2006. The resolution urges the city to take action by developing a comprehensive plan to respond to this global energy crisis. The San Francisco Oil Awareness, a citizen's group, was instrumental in advancing the resolution to the local officials.
Portland City, Oregon
On May 10, 2006, the City Council of Portland, Oregon passed a resolution creating a task force on peak oil to investigate its implications (Portland Peak Oil Policy Working Group, Press Release 2006). The passing of the resolution was largely due to the activism of Portland Peak Oil, a local grassroots group.
The initial success of these efforts is evidenced by public involvement at the early stage of the process. It is likely that there will be public ownership of the future actions generated from these initiatives.
Hamilton: The Electric City (Hamilton, Ontario)
This report was prepared for the City Council of Hamilton to provide guidance and recommendations on how to best prepare for a future scenario with limited supply of cheap oil (Gilbert 2006). The focus of the report is to produce and use electricity as the main fuel in an era of energy constraints. The goal is to revive Hamilton as 'The Electric City' and be the forefront of transition to electric transport and new electricity generation.
City of Burnaby, British Columbia
The Transportation Committee of the City of Burnaby circulated to the City Council the report, Global Peak in Oil Production: The Municipal Context on 16 January 2006. This report was circulated for information purposes only (Ramsey 2006).
City of North Vancouver, British Columbia
Mayor Darrell Mussatto of the City of North Vancouver together with David Hughes of Geological Survey of Canada hosted a free public forum on Peak Oil and the Future of Energy on November 26, 2006 (http://www.cnv.org//server.aspx?c=2&l=217). The special public presentation focused on local energy issues and global energy crisis.
The preliminary efforts being undertaken in these places contribute to providing public information about the importance of the issue. These opportunities could trigger initiatives to consider measuring oil vulnerability at the city level using indicators. There are numerous indices developed for various purposes and interests as they recognize its usefulness as a policy-making instrument and communication tool to drive action. UN- CDP and the U. K. Commonwealth Secretariat use vulnerability indices to guide their development interventions.
5.3 What Needs to be Done
The outcome of this study can offer a number of possible strategies and actionable ideas to reduce vulnerability to oil prices. The recommendations are broken down into "business-as-usual" scenario and "no regrets" strategies.
5.3.1 "Business-as-Usual" Scenario
Central to the "business-as-usual" scenario is to provide accurate and reliable information to the public about peak oil and its impacts to daily urban life. In the event of steadily high oil prices and disruptions of supply, the immediate reaction of the public could be panic and hoarding (e.g., during the boil water advisory in the Greater Vancouver Regional District in November 2006 due to inclement weather).
Information Drive
Money (1984) cites that during the oil crises in 1974 and 1979, a national opinion poll was conducted and showed that more than half of the U. S. population (or 77 percent) thought that there was no petroleum crisis and 40 percent did not know that U. S. imports oil. These opinion poll results in spite of all the publicity by the Carter Administration on the need for energy conservation.
A crucial step is to convince the public that an end to the era of cheap oil is imminent. Public support for intensive demand side management, and energy conservation and energy efficiency is important. According to Whitelegg and Haq (2003), people are ready to make behavioural changes if given enough information and discussion to shift away from the car. This is experienced in Perth, Australia with their 'individualized marketing' project that resulted to a reduction by 78,000 vehicles on the road per day (p. 279).
As mentioned in Sect. 1.3, a survey conducted by lpsos Reid in May 2006 on the perceptions to gasoline prices showed that Canadians have acted or started to consider behavioural changes due to gasoline prices. Behavioural changes considered include purchase of a more fuel-efficient vehicle (55 percent), less driving (57 percent), and changed vacation plans to stay closer to home (35 percent) (CCEI Information News Release 2006).
Similar perception surveys can be done at the city level to get public views and concerns about a future of oil constraints. The results will be valuable in understanding their needs and limitations. Public inputs on this critical issue will be useful to build on strategies and approaches fit to the local level to reduce vulnerability such as making car use less attractive. Developing vulnerability indices suitable to the city level can be a cost-effective way of providing public information and encourage participation. An approach is proposed by Beaumont and Keys (1982, p. 42) to consider the household as a decision-making unit because any change in oil prices will definitely impact income at the household level. Getting the public involved early in the process is important in achieving their cooperation as proven in San Francisco, CA and Portland, Oregon experience (see Sect. 5.2).
The experience by the Campaigns for Awareness using Media and Publicity to Assess Responses of Individuals in Europe Project (2000) of the European Commission showed that general awareness campaigns should be repeated at regular intervals to sustain the power to influence behaviour, and to target specific groups like neighbourhoods to have stronger and long-lasting effects.
Diverging views and endless debate about the underlying reasons for the rapid oil price increases confuse the public and threaten their trust in who is giving the accurate information. This situation undermines the public in making an informed decision on transportation choices or energy conservation. Regester and Larkin (2005, p. 20) mentions that Market & Opinion Research International (MORI) conducted a public opinion survey after the Brent spar1' incident in 1995 and revealed that public confidence in scientists working for environmental groups is 97 percent, for government is 77 percent and for industry is 64 percent. Therefore, the source of information is critical. While the Brent Spar experience indicates higher public confidence in scientists from environmental groups, a multipartite source representing the government,
" Brent Spar is a vertically floating oil storage terminal in Brent Field capable of holding 300,000 bbls of crude oil. It is 141 m-high fixed to the seabed and moored in the North Sea. In 1995, Shell UK decided to pursue deepwater disposal of Brent Spar onsite as the Best Practicable Environmental Option (BPEO). While deepwater disposal for Brent Spar was approved by UK government in 1995, it spurred great international outcry from environmental groups like Greenpeace. (Regester and Larkin 2005, pp85-95) neighbourhood associations, academic institutions, non-government organizations, and the private sector will be more effective, comprehensive and credible.
5.3.2 "No regrets" Strategies
The following strategise are considered "no regrets" measures as they will have long-term beneficial impacts even if peak oil may not come sooner than predicted by oil experts. Ultimately, these could be "win-win" solutions to the environment and sustainable city life. Decision-makers need to contemplate that implementing these measures in advance, as a precautionary principle, is better than during the "long- emergency" of post-peak oil.
Road Pricing
The outcome of this study showed that mode of transport to work by car contributes significantly to oil vulnerability. Therefore, interventions to reduce auto- dependence in getting to work will reduce vulnerability to oil prices. Road pricing can be seriously considered by Vancouver's Translink and Montreal's L'Agence metropolitaine de transport to reduce auto-dependence. These agencies have the powers to raise revenues through new charges on motorists (Lindsey 2003). Road pricing has been implemented in several countries with varying degrees of success and lessons to learn from. According to Irwin (2006), urban transit congestion costs Canadians about $2.3 billion to $3.7 billion per year in nine largest urban areas. The Canadian road pricing scheme may be enhanced if it is bundled with other incentives such as rebate in tax, a reduced price for public transit passes, or free bus rides in Downtown areas.
Lessons can be learned from Singapore, which introduced road pricing in 1975, and the London Congestion Charging Scheme (LCCS) implemented on February 17, 2003. According to Santos and Shaffer (2004), the net economic benefits of LCCS for the first year were US$78 million and net revenues of US$106 million. Net revenues were mainly being used to improve public transport.
A more recent congestion tax scheme was implemented by Stockholm from 3 January until 31 July 2006. Preliminary evaluation of the Stockholm Trial in June 2006 showed that traffic dropped by 22 percent from 6:30AM to 6:30PM in Spring 2006. Voters in Stockholm approved the implementation of the congestion tax in a referendum on September 17, 2006 (Stockholmsforsoket 2006). Experiences in other cities show that a congestion charging scheme is not easy to adopt with respect to public acceptance and costs. A summary of worldwide experiences on road charging is given in the official website of the Commission for Integrated Transport in U. K. (http://www.cfit.gov.uk). According to the website, a Singapore survey showed that 75 percent of respondents believed that charging vehicles on the congestion they caused was fair. In Oslo, Norway, public opposition was 70 percent in 1989 then slightly dropped to 64 percent in 1991. In London, 56 percent of the population believe that the congestion charging has been effective. Based on these experiences, it is very likely that providing information is a key element of their success.
Introduce Car-free Day or Provide Free Bus Rides in Downtown Core
Primary objectives of car-free day and free bus rides are reducing emissions and congestion in downtown cores. Toronto is the first city in North America to introduce a car-free day in 2001 and soon followed by Montreal and Ottawa (Car-free Day in Canada, http://www.carfreeday.ca).
The City of Seattle has provided free bus rides in its Downtown core from 6AM to 7PM everyday since the early 1970s. According to an article on 'ride free zone' to ease traffic flow, (Seatfle Post-lntelligencer, December 18, 2000), the free bus rides cost the City of Seattle a total of US$313,650 in its 1999-2000 budget. The City of Chicago has a free bus trolley system that runs all year round (but reduced service after summer) to provide service to most of the City's popular museums, shopping centres and visitor attractions (Chicago Department of Transportation official website). Another city that has introduced free public transit rides is the City of Perth in Australia. Free Transit Zones (FTZ) operate within the boundaries of the City of Perth for both bus and train specifically in its central business districts (City of Perth official website). Signposts for FTZ are displayed on the route limits.
While the objectives of these initiatives may not be due to peak oil, one of the positive impacts is reduced oil consumption. The IEA estimates that the implementation of an odd-even driving ban policy or a one-day-a-week ban tied to license plate numbers in the U. S. and Canada will save 1.467 million barrels per day or a 12.4 percent road transport fuel saved while a one-day-in-I 0 driving ban policy will save 110,000 barrels of fuel per day or 0.9 percent road transport fuel saved (IEAIOECD 2005, p97). In Canada, data from Statistics Canada on sales of fuel used for road motor vehicles from 2001 to 2005 showed that net sales for diesel fuel is steadily increasing (16.2 billion litres in 2005 from 13.3 billion litres in 2001). Net sales of gasoline showed a slight reduction in 2005 (38.5 billion litres) compared to 2004 (39 billion litres). Stronger support for car-free day and free bus rides may be achieved if the public and policy-makers had better understanding of the peak oil issue.
The list of measures that can be adopted at the city level to reduce oil vulnerability and lessons that can be learned from other places is endless. There is adequate information and experience from other areas that constitute best practices. The major block or "fork in the road" is the "unwillingness of politicians at all levels to make the policy shift" to reduce car-dependence (Whitelegg and Haq 2003, p281).
The ratification of the Kyoto Protocol by Canada aligns all its efforts to reduce vehicular emissions and fuel efficiency in the transport sector towards meeting the agreement. The recommendations listed in this section are consistent with the broad objectives of the Kyoto Protocol.
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