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UNIVERSITY OF CALGARY
The Power of the Individual: Saving Energy through Conscious Consumption
by
Lidia Sorial
A RESEARCH PROJECT
SUBMITTED TO THE FACULTY OF GRADUATE STUDIES
IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE
DEGREE OF MASTER OF SCIENCE
GRADUATE PROGRAM IN SUSTAINABLE ENERGY DEVELOPMENT
CALGARY, ALBERTA
AUGUST, 2016
© Lidia Sorial 2016
i
CERTIFICATE OF COMPLETION OF PROJECT
Approval Page
FOR THE UNIVERSITY OF CALGARY
MASTER OF SCIENCE DEGREE IN SUSTAINABLE ENERGY DEVELOPMENT
The undersigned certifies that she has read, and recommends to the Sustainable Energy
Development Program (SEDV) for acceptance, the Project Report entitled “The Power of the
Individual: Saving Energy through Conscious Consumption,” submitted by Lidia Sorial, in partial
fulfilment of the requirements for the degree of Master of Science in Sustainable Energy
Development.
______________________________________ ______________________________
Supervisor: Dr. Irene Herremans Date:
ii
Abstract
The purpose of this study is to capitalize on an opportunity to become more sustainable.
The points in question are: How much energy savings can be achieved through conscious
consumption alone? What changes are people willing to make at their own discretion? Are there
any correlations between certain demographics and energy use? Experimental results from 10
households showed that the minimum savings achieved over one month are equal to a potential
annual savings of 250,000 GJ of natural gas, 43 million kWh of electricity, and 5 million m3 of
water across Calgary. Water-related changes were the most commonly applied by participants.
Successful households had more members, more kids, slightly higher education levels, more
awareness in reality, and less awareness by perception compared to their less successful peers
and the applicable statistics. Overall, energy-saving tips were deemed an effective mechanism by
which to notably reduce energy consumption in an urban setting.
iii
Acknowledgements
I would like to give a special thanks to Dr. Irene Herremans, my supervisor, who provided me
with continuous support and guidance throughout this project and the completion of this report.
I would also like to thank my sister, Nermine Sorial, who not only acted as a participant in my
study but also offered me invaluable advice and encouragement since the very birth of the idea.
I am especially indebted to my friends and coworkers who were willing to act as participants in
my study and without whom this research would not be possible. Namely Aleks Johnston,
Andrey Gornik, Darren Schurman, Faheem Ahmed, Hans Verwijs, Keyvan Tabrizi, Maximiliano
Bustamante, Mustafa Hassan, and Oleksiy Golovchenko.
Finally, I would like to thank the Graduate Program in Sustainable Energy Development at the
University of Calgary for the opportunity to pursue this subject. Special thanks to Anil Mehrotra,
Program Director, for being a backbone to the program and for his dedicated support to students.
iv
Table of Contents
Approval Page ...................................................................................................................... i
Abstract ............................................................................................................................... ii
Acknowledgements ............................................................................................................ iii
Table of Contents ............................................................................................................... iv
List of Tables .................................................................................................................... vii
List of Figures and Illustrations ......................................................................................... ix
List of Symbols, Abbreviations and Nomenclature .............................................................x
Epigraph ............................................................................................................................. xi
CHAPTER ONE: INTRODUCTION ..................................................................................1
1.1 Energy Production .....................................................................................................4
1.2 Energy Demand .........................................................................................................4
1.2.1 Natural Gas ........................................................................................................7
1.2.2 Electricity ..........................................................................................................7
1.2.3 Water .................................................................................................................9
CHAPTER TWO: LITERATURE REVIEW ....................................................................11
2.1 Jevons Paradox ........................................................................................................11
2.2 Consumer Behaviour ...............................................................................................14
2.3 Human Nature ..........................................................................................................17
CHAPTER THREE: METHODS ......................................................................................20
3.1 Criteria .....................................................................................................................20
3.1.1 Target Demographic ........................................................................................21
3.1.2 Guidelines ........................................................................................................21
3.1.3 Surveys ............................................................................................................22
3.2 Baseline ....................................................................................................................22
3.2.1 Assumptions ....................................................................................................23
3.2.2 Approximations ...............................................................................................27
v
CHAPTER FOUR: RESULTS ..........................................................................................28
4.1 Analysis and Findings ..............................................................................................28
4.1.1 Energy Savings ................................................................................................28
4.1.2 General Survey ................................................................................................33
4.1.3 Guidelines Survey ...........................................................................................35
4.2 Interpretation and Discussion ..................................................................................40
4.2.1 Participant Success Rate ..................................................................................40
4.2.2 Equivalency of Minimum Savings ..................................................................41
4.2.3 Per Capita Consumption ..................................................................................45
4.2.4 Summary ..........................................................................................................49
4.2.5 Correlations .....................................................................................................51
CHAPTER FIVE: CONCLUSIONS .................................................................................56
5.1 Conclusions ..............................................................................................................56
5.2 Recommendations ....................................................................................................58
5.2.1 Energy Efficiency ............................................................................................58
5.2.2 Sectoral Application ........................................................................................59
5.2.3 Next Steps ........................................................................................................61
5.3 Limitations ...............................................................................................................63
5.3.1 Approximation .................................................................................................63
5.3.2 Baseline ...........................................................................................................63
5.3.3 Human Error ....................................................................................................64
5.3.4 Response Bias ..................................................................................................64
5.3.5 Sample Size .....................................................................................................65
5.4 Future Research .......................................................................................................65
5.4.1 Historical Trends .............................................................................................65
5.4.2 Guideline Application .....................................................................................65
5.4.3 Education .........................................................................................................66
5.4.4 Biomimicry ......................................................................................................66
REFERENCES ..................................................................................................................68
vi
APPENDIX A GUIDELINES ........................................................................................76
Natural Gas ....................................................................................................................76
Electricity .......................................................................................................................77
Water ..............................................................................................................................79
APPENDIX B SURVEYS .............................................................................................81
General Survey ..............................................................................................................81
Demographics ...........................................................................................................81
Home Characteristics ................................................................................................84
Changes ....................................................................................................................84
Awareness .................................................................................................................86
Final Thoughts ..........................................................................................................86
Guidelines Survey ..........................................................................................................87
vii
List of Tables
Table 3-1: Adjustments Based on Frequency of Presence at Home ............................................. 25
Table 3-2: Case-by-Case Adjustment Allocations ........................................................................ 25
Table 3-3: Water Adjustments Based on Rainfall Patterns .......................................................... 27
Table 4-1: Natural Gas Consumption (GJ) ................................................................................... 29
Table 4-2: Electricity Consumption (kWh) .................................................................................. 30
Table 4-3: Water Consumption (m3)............................................................................................. 31
Table 4-4: General Survey Results Summary – Demographics ................................................... 33
Table 4-5: General Survey Results Summary – Home Characteristics ........................................ 34
Table 4-6: General Survey Results Summary – Awareness ......................................................... 34
Table 4-7: Guidelines Survey Results Summary – Natural Gas (NG) ......................................... 35
Table 4-8: Guidelines Survey Results Summary – Electricity (E) ............................................... 36
Table 4-9: Guidelines Survey Results Summary – Water (W) ..................................................... 36
Table 4-10: Participant Success Rate ............................................................................................ 40
Table 4-11: Actual Energy Savings – By Single Household – Per Month ................................... 42
Table 4-12: Potential Energy Savings – For Calgary Population – Per Month ............................ 42
Table 4-13: Potential Energy Savings – For Calgary Population – Per Year ............................... 42
Table 4-14: Number of Homes' Use for One Year – Monthly Savings Payoff – Energy ............ 43
Table 4-15: Carbon Dioxide Equivalent – Monthly Savings Payoff – Environment ................... 43
Table 4-16: Cost Equivalent – Monthly Savings Payoff – Economy ........................................... 44
Table 4-17: Natural Gas – Average Per Capita Consumption ...................................................... 46
Table 4-18: Electricity – Average Per Capita Consumption ........................................................ 47
Table 4-19: Water – Average Per Capita Consumption ............................................................... 48
Table 4-20: Results Summary by Analysis Method ..................................................................... 50
Table 4-21: Household Initial Consumption (May 2014 / May 2015) ......................................... 53
viii
Table 4-22: Number of Guidelines Applied vs. Initial Consumption (May 2014 / May 2015) ... 54
Table 4-23: Number of Guidelines Applied vs. Savings .............................................................. 54
Table 4-24: Income vs. Average Consumption ............................................................................ 55
ix
List of Figures and Illustrations
Figure 1-1: The Consumption-Production Gap .............................................................................. 1
Figure 1-2: Energy Demand in Calgary by Sector, 2011 ................................................................ 5
Figure 1-3: Water Demand in Calgary by Sector, 2003 ................................................................. 6
Figure 1-4: Natural Gas Consumption, 2013 or Most Recent Year (m3) ....................................... 7
Figure 1-5: Household Electricity Consumption, 2010 (kWh) ....................................................... 8
Figure 1-6: Residential Electricity Consumption Per Capita, 2010 (kWh) .................................... 8
Figure 1-7: Water Consumption Per Capita, 2009 or Most Recent Year (m3) ............................... 9
Figure 3-1: Typical Home Water Use in Calgary ......................................................................... 26
Figure 4-1: Natural Gas Consumption (GJ) .................................................................................. 29
Figure 4-2: Electricity Consumption (kWh) ................................................................................. 30
Figure 4-3: Water Consumption (m3) ........................................................................................... 31
Figure 4-4: Guidelines Survey Results Summary ......................................................................... 39
Figure 4-5: Participant Success Rate ............................................................................................ 41
Figure 4-6: Natural Gas – Average Per Capita Consumption....................................................... 46
Figure 4-7: Electricity – Average Per Capita Consumption ......................................................... 47
Figure 4-8: Water – Average Per Capita Consumption ................................................................ 48
x
List of Symbols, Abbreviations and Nomenclature
NG Natural Gas
E Electricity
W Water
xi
Epigraph
“It is in the power of every individual to do that which the community as a whole is powerless to
effect.”
–William Thomas Stead
1
Chapter One: Introduction
How much energy savings can be achieved through conscious consumption alone? In
other words, what is the effect of energy management at the individual or household level? This
is important because the rise in energy consumption is constantly driving the demand for energy
production, which is ultimately limited by the scale of natural capital and the earth’s absorptive
capacity. Increased energy production, and the consequent exploitation of resources, is
ineffectual if constantly paralleled by consumption. Even the improvement of technological
efficiencies and the expansion of renewable energies can quickly be offset by unmoderated
consumption. Additionally, the moderation of per capita consumption is of increasing
importance with the global rise in population. It is crucial that while energy production is
facilitated, consumption is moderated, in order to merge the gap between these two parameters
and justify the perseverant efforts toward production. The idea is that instead of only targeting
efforts toward improving production, why not target equal efforts toward moderating
consumption, and thereby meet in the middle? Figure 1-1 illustrates this concept.
Figure 1-1: The Consumption-Production Gap
(Sorial, 2016)
2
Peter Tertzakian, Calgary-based energy economist and author of the book The End of
Energy Obesity: Breaking Today’s Energy Addiction for a Prosperous and Secure Tomorrow,
summarizes this phenomenon as follows:
The sheer scale of our seven billion-person global village means that we can no longer easily
meet our world’s craving for cheap, clean, and secure energy just by following old paradigm
approaches such as tapping new supplies, legislating partial policies, or instituting slow advances
in conventional and alternative energy technologies. Hard science and engineering can and will
help us figure out how to rebalance our needs in the face of our next break point, but the root
cause of our energy problems must be addressed by considering the social dynamics of
consumption as well … The good news is that we can solve all of our energy-related problems by
focusing on the one fundamental challenge that is often overlooked: reducing the quantity of
energy we actually consume. If we focus on reducing energy appetite rather than putting so much
emphasis on searching for oil in extreme parts of the world, relying on incomplete energy
policies, making dubious trade-offs between food and fuel, or curbing, trading, and burying
carbon emissions, we won’t continue fooling ourselves (like the dieter who swears off cake and
cookies and binges on ice cream as a reward for good behaviour). (Tertzakian & Hollihan, 2009,
pp. xii, xiv)
Of particular interest is the per capita energy consumption in developed nations, such as
Canada. Energy consumption around the globe is vastly disproportionate, and this can be
partially attributed to the standard of living in developed nations. My research question attempts
to identify how much of the energy consumption in a typical Calgary household is due to
affluence and negligence, and thus determine whether changing consumer behaviour through
3
information and awareness can render significant energy savings. The specific information and
awareness technique examined in this study is the provision of energy-saving tips. The
motivation is that this proportion of energy consumption can be combatted at low cost – that is,
through conscious consumption or “mindful use” – a concept that can be exercised by the simple
means of education and collaboration.
In this context, affluence refers to the tendency to consume liberally because the resource
is abundantly accessible to the home and the user has (or is willing to find) the means to cover
the cost; neither supply nor cost act as limiting factors. In other words, you use more than you
need because you can. Negligence refers to the tendency to consume liberally because of
carelessness, or lack of interest in exercising mindfulness toward the environment. In other
words, you use more than you need because you do not care to use less. Both affluence and
negligence represent a lack of conscious consumption, or a lack of consumption that is
purposeful and justified. Both concepts are overlapping and perpetuating in nature; affluence can
lead to negligence and vice versa. For example, a consumer may care about the environment, but
still consume liberally simply because they have the means (affluence), thereby exhibiting the
same behaviour as a consumer who is inherently negligent. To measure the energy consumption
due to affluence and negligence, a set of general guidelines reflecting the contrary case of
conscious consumption is provided to the test groups.
My research also uses consumer surveys to answer the following secondary questions:
What changes are people willing to make at their own discretion? Are there any correlations
between certain demographics and energy use?
4
1.1 Energy Production
Canada’s energy resources are among the largest in the world (NEB, 2016). Canadian
rivers discharge nearly 7% of the world’s renewable water supply, which in turn provides
extensive hydroelectric generating capability (NEB, 2016). Among global producers, Canada
ranks second in hydroelectricity production and fifth in natural gas production (NEB, 2016). This
substantial natural resource base has enabled Canada to sustain a developed economy.
Meanwhile, Canada has a relatively small population, with only 0.5% of the world share
(Worldometers, 2016). Given such prospects, and in line with the concept of equity, Canada –
and its fellow developed nations – have an inherent obligation to use energy resources
responsibly. We must think globally and act locally.
1.2 Energy Demand
On a per capita basis, Canada’s energy intensity is among the highest in the world (NEB,
2016). In 2012, Canadian total final energy consumption was 2.3% of the global total (NEB,
2016). Alberta, Ontario, and Quebec continue to account for most of the energy consumed in
Canada, with a combined share of 75.5% of total energy consumption in 2014 (Statistics Canada,
2016A). This can be attributed to the country’s northern climate, vast territory, industrial base,
and high standard of living (Natural Resources Canada, 2016). However, often overlooked, this
can also be attributed to consumption patterns as influenced by consumer behaviour.
Comparing per capita GDP to per capita energy consumption for different countries,
standard of living correlates with energy availability almost one-to-one (Gosselin, 2011). “No
country that consumes lots of energy is living in poverty, and no country that consumes little
energy is living in prosperity” (Gosselin, 2011, p. 1). In fact, global energy consumption has
increased in line with the increase in standard of living since the beginning of the industrial
5
revolution (OSQAR, 2010). As such, increased energy use has been a driving force for wealth
and prosperity. This study is based on the hypothesis that the reverse is also true: wealth and
prosperity (affluence) is a driving force for increased energy use, or at least, a sustaining agent.
The idea is that the more is available, the more is perceived to be required, and the more is
consumed. Meanwhile, Canada’s population has been on a constant historical rise, from 3.5
million in 1867 to 36 million today (Worldometers, 2016). Instead of reducing per capita energy
consumption, this has the effect of increasing energy demand and further driving energy
production. For this reason, it is important to identify the phenomena that influence per capita
consumption, and capitalize on the power of the individual.
Within the Calgary scope, energy demand is influenced by the needs of the residential,
commercial, and industrial sectors. Figure 1-2 shows the associated distribution. This study
focuses on the residential sector, where individuals have the most influence.
Figure 1-2: Energy Demand in Calgary by Sector, 2011
(AEEA, 2014)
6
Calgary’s commercial sector comprises about 13% of total energy demand, while the
residential sector comprises about 31% (AEEA, 2014). While electricity demand for the
commercial sector is slightly higher than for the residential sector, the natural gas demand for the
residential sector is significantly higher than for the commercial sector. This can be attributed to
the use of natural gas for water and space heating (AEEA, 2014). Meanwhile, global natural gas
demand is expected to increase 46% by 2040 (CAPP, 2015). Given Canada’s northern climate
and consequent heating requirements, energy-saving modifications related to natural gas in the
residential sector offer a high potential for savings. This also translates to notable monetary
savings. In 2014, the average Canadian residential customer spent just over $1,000 on natural gas
(CAPP, 2015).
Water demand is influenced by the needs of the residential, municipal, non-revenue,
rural, and industrial, commercial, or institutional (ICI) sectors. Figure 1-3 shows the associated
distribution.
Figure 1-3: Water Demand in Calgary by Sector, 2003
(The City of Calgary Water Services, 2010)
7
Calgary’s residential sector comprises just over half of the total water demand, while the
ICI sector is next in line (The City of Calgary Water Services, 2010). Therefore, like natural gas,
energy-saving modifications related to water in the residential sector offer a high potential for
savings.
1.2.1 Natural Gas
Canada is among the top ten total consumers of natural gas (Index Mundi, 2014). Figure
1-4 shows how Canada compares to other countries.
Figure 1-4: Natural Gas Consumption, 2013 or Most Recent Year (m3)
(Index Mundi, 2014)
1.2.2 Electricity
Canada has the highest electricity consumption, both per household and per capita
(Wilson, 2016A). Figure 1-5 and Figure 1-6 show how Canada compares to other countries.
8
Figure 1-5: Household Electricity Consumption, 2010 (kWh)
(Wilson, 2016A)
Figure 1-6: Residential Electricity Consumption Per Capita, 2010 (kWh)
(Wilson, 2016A)
9
1.2.3 Water
Canada has the second highest water consumption per capita (The Conference Board of
Canada, 2016). Figure 1-7 shows how Canada compares to other countries.
Figure 1-7: Water Consumption Per Capita, 2009 or Most Recent Year (m3)
(The Conference Board of Canada, 2016)
Canada’s water withdrawals are nearly double its peer average and over nine times that of
Denmark, the best performer (The Conference Board of Canada, 2016). The excessive water
withdrawals in the country can be attributed to the lack of widespread conservation practices and
pricing that does not promote efficiency (The Conference Board of Canada, 2016). According to
The Conference Board of Canada (2016, p. 1), “Canadians subject to water metering use less
water than their rural counterparts who have no means of accounting for their water usage.”
Municipalities with a volume-based pricing approach have a lower average daily consumption
rate than those with a flat-rate pricing approach (The Conference Board of Canada, 2016). For
example, in 2009, un-metered households used a daily average of 376 L per person while
metered households used 229 L – approximately 40% less (The Conference Board of Canada,
10
2016). Furthermore, in Europe, water withdrawals simultaneously decreased as water prices
increased (The Conference Board of Canada, 2016).
Calgary’s drinking water quality is among the best in the world (The City of Calgary,
2007). Unfortunately, this high-quality water is used for other purposes, predominantly toilets,
laundry, faucets, showers, and leaks (The City of Calgary, 2007). For example, 60% of all indoor
residential water use occurs in the bathroom, more than half of which is flushed down the toilet
(The City of Calgary, 2007). Experts suggest that water used for food preparation and drinking
purposes represents less than 3% of the water treated at municipal water treatment plants (The
City of Calgary, 2007). However, The City of Calgary Water Services (2010, p. 4) states that
“Although Canadians have the unfortunate distinction of generally being among the highest
water consumers per capita in the world, there are many opportunities in Calgary to find better
efficiencies through behaviours and technology.”
This is supported by the findings of this study, as water was found to be the most
overused commodity among the three elements, but also the most saved. Through the adoption of
energy-saving behaviours, the minimum potential water savings by Calgary as a whole were
equivalent to about 5,000 homes’ use for one year, or about $52 in annual expenses. In contrast,
natural gas and electricity savings equated to about 200 and 400 homes’ use for one year, or
about $1 and $5 in annual expenses respectively. Overall, this demonstrates a potential for
improvement that can be materialized through various techniques, of which changing consumer
behaviour is only one.
11
Chapter Two: Literature Review
2.1 Jevons Paradox
The idea that energy savings can be offset by such a phenomenon as “affluence” dates
back to the year 1865, when an Englishman named William Stanley Jevons published a book
called The Coal Question: An Inquiry Concerning the Progress of the Nation, and the Probable
Exhaustion of Our Coal-Mines. In this book, he argued that Britain’s affluence depended on its
endowment of coal, and the depletion of this resource could not be delayed through increased
“economy” in the use of coal – what we now call energy efficiency (Owen, 2010). He concluded,
“It is wholly a confusion of ideas to suppose that the economical use of fuel is equivalent to a
diminished consumption. The very contrary is the truth” (Owen, 2010, p. 1). This idea has come
to be known as the Jevons paradox, or the rebound effect.
Jevons illustrated this with an example of the British iron industry. If some technological
advance made it possible for a blast furnace to produce iron with less coal, then profits would
rise, new investment in iron production would be attracted, and the price of iron would fall –
which would inevitably stimulate additional demand (Owen, 2010). He concluded that “the
greater number of furnaces will more than make up for the diminished consumption of each”
(Owen, 2010, p. 1). In general, more freed up coal would promote the adoption of even more
steam engines, factories, and heated homes, ultimately perpetuating a “greater coal appetite”
(Tertzakian & Hollihan, 2009). At the end of his book, Jevons concluded that Britain faced a
choice between “brief greatness and longer continued mediocrity” (Owen, 2010). He chose
mediocrity, which resembles the concept we now call “sustainability” (Owen, 2010).
English economist Len Brookes then came to the same realization, only to discover that
Jevons had preceded him by more than a century (Owen, 2010). The concept was later
12
recognized by an American researcher, Harry D. Saunders, in a 1992 paper: “With fixed real
energy price, energy efficiency gains will increase energy consumption above where it would be
without these gains” (Owen, 2010, p. 1). In 2000, a journal titled Energy Policy devoted an entire
issue to the rebound effect; however, editor Lee Schipper concluded that “rebounds are
significant but do not threaten to rob society of most of the benefits of energy efficiency
improvements” (Owen, 2010, p. 1). The Jevons paradox is controversial because its effect cannot
be easily evidenced; it would require control experiments to determine whether energy use is
higher or lower than without efficiency improvements (Herring & York, 2006). Even then,
correlation does not imply causation. “The endlessly ramifying network of interconnections is
too complex to yield readily to empirical, mathematics-based analysis” (Owen, 2010, p. 1).
Furthermore, “the rebound effect has differing impacts at all levels of the economy, from the
micro-economic (the consumer) to the macro-economic (the national economy), and its
magnitude at all levels of the economy has not yet been determined” (Herring & York, 2006, p.
1) – which forms part of the motivation for this study.
James McWilliams, author of the book Just Food, recognized the application of the
Jevons paradox at the consumer level in terms of food waste (Owen, 2010). He stated,
“Refrigeration and packaging convey to the consumer a sense that what we buy will last longer
than it does. Thus, we buy enough stuff to fill our capacious Sub-Zeros and, before we know it, a
third of it is past its due date and we toss it” (Owen, 2010, p. 1). Stan Cook, author of the book
Losing Our Cool, also recognized this effect. In the US, between 1993 and 2005, “the energy
efficiency of residential air-conditioning equipment improved twenty-eight per cent, but energy
consumption for A.C. by the average air-conditioned household rose thirty-seven per cent” –
equivalent to the amount of electricity used for all purposes in 1955 (Owen, 2010, p. 1). Steven
13
Chu, Nobel Prize winner in Physics in 1997, took it one step further when he explained that
“drivers who buy more efficient cars can expect to save thousands of dollars in fuel costs; but,
unless those drivers shred the money and add it to a compost heap, the environment is unlikely to
come out ahead, as those dollars will inevitably be spent on goods or activities that involve fuel
consumption – say, on increased access to the Internet, which is one of the fastest-growing
energy drains in the world” (Owen, 2010, p. 1). In other words, he considered that energy
savings translate to monetary savings that are expended on energy-consuming activities; what is
now considered the indirect effect of energy efficiency, or the indirect rebound effect. A recent
study published in 2015 titled Energy Efficiency Policies and the Jevons Paradox realizes this
phenomenon, stating that “avoiding the monetary savings in households prevents the increase in
consumption patterns due to improved efficiency” (Freire-González & Puig-Ventosa, 2015, p.
76).
The inability to make such inferences and extrapolations that provide evidence for this
effect, as Jevons and many after him have recognized, leaves a gap in our understanding of
consumer behaviour. If, in fact, the full savings of improved energy efficiency never materialize
because they are effectively offset by consumer behaviour, then effecting consumer behaviour
itself is of utmost importance (Tertzakian & Hollihan, 2009). “If our machines use less energy,
will we just use them more?” (Owen, 2010, p. 1). Then, as noted above, where will we spend the
money we save from efficiency improvements? (Tertzakian & Hollihan, 2009). The answer to
these questions is not clearly known, because the society we live in is complex and consumer
choices are emotive. However, books have been written and studies have been conducted around
the factors that affect consumer behaviour, and these are discussed below.
14
2.2 Consumer Behaviour
Consumer behaviour today is characterized by the notion of “economic man,” or homo
economicus (Ehrenfeld & Hoffman, 2013). In this model of thinking, the human being is one
who measures value in purely economic terms, sees relationships as primarily transactional, and
extols utility (wealth) maximization as the ultimate goal in life (Ehrenfeld & Hoffman, 2013).
Unfortunately, utility has been reduced to money or material goods, because these are
conveniently tangible and easy to measure (Ehrenfeld & Hoffman, 2013). Ehrenfeld & Hoffman
(2013) suggest that while this model has been the central driving force in the evolution of the
modern era, it lies at the root of unsustainability, because it leads to an image of insatiability
where consumers are manipulated to convert inner emptiness into unending consumption. The
Jevons paradox is only exacerbated by this model of consumer behaviour, as “the benefits of
more efficient means are more than offset by the deleterious impact on the human beings
involved” (Ehrenfeld & Hoffman, 2013, p. 121).
How does the economic man perceive his own impact? One study was conducted on
public perceptions of energy consumption and savings (Attari, DeKay, Davidson, & de Bruin,
2010). The study examines perceptions of energy consumption and savings for a variety of
household, transportation, and recycling activities in a national online survey of 505 participants
(Attari, DeKay, Davidson, & de Bruin, 2010). Results indicate that participants underestimated
energy use and savings, and the study concludes that “well-designed efforts to improve the
public’s understanding of energy use and savings could pay large dividends” (Attari, DeKay,
Davidson, & de Bruin, 2010, p. 16054).
Freire-González & Puig-Vento (2015, p. 72) support this idea, suggesting that it would be
beneficial to “provide further information on energy consumption in households, and on its cost
15
and variations when taking certain energy saving actions, so it could encourage households to
reduce the use of energy even when rebound effect exists.” Literature on metering shows “how
smart metres can influence behaviour and reduce energy consumption, offering consumers the
possibility to voluntarily avoid direct rebound effect” and “how a better feedback on energy bills,
that is, a better understanding of energy consumption and costs of actions taken at households,
can produce up to 10% savings in electricity consumption for heating in cold climates” (Freire-
González & Puig-Ventosa, 2015, p. 72). Likewise, the Organisation for Economic Co-operation
and Development (2016, p. 1) states that consumers’ motivation to modify their behaviour to
support environmental goals depends on “how much consumers know about environmental
issues, the environmental impact of their consumption and lifestyle decisions, and the practical
actions that they can take to support sustainability goals.”
Another study used the Theory of Planned Behaviour to examine consumption and
consumer behaviour. The study indicates that attitude, norms, and control are three major
variables that influence the intention that ultimately leads to behaviour (Herremans & Lu, 2012).
In parity with the above studies, this study also acknowledges the effect of consumer
understanding on consumer behaviour: “Awareness and knowledge will influence attitudes about
behaviour and change them from negative to positive or vice versa” (Herremans & Lu, 2012, p.
9). For example, some studies found that households with pro-environmental attitudes are more
environmentally responsible, as demonstrated by their fuel consumption habits and ownership of
energy-efficient vehicles (Herremans & Lu, 2012). In other words, their attitude is reflected in
their actions. The study provides recommendations for the success of environmental programs on
this basis.
16
In their study, Freire-González & Puig-Vento (2015) question the assumption that
policies based on energy efficiency targets will reduce energy consumption (Freire-González &
Puig-Ventosa, 2015). The paper analyzes the main available policies to minimize the rebound
effect in households (Freire-González & Puig-Ventosa, 2015). It is interesting to note that “The
case of energy policies related to insulation of households, from the Department of Energy and
Climate Change (DECC) by the UK Government, is the only known example of the
consideration of direct rebound effect in the expected effects of a law. In this case, the United
Kingdom government includes a 15% reduction in the expected energy savings from insulation
measures in households in order to account for the direct rebound effect. Additionally, DECC
produced a guideline and a spreadsheet to account for the rebound effect on policies to reduce
energy consumption” (Freire-González & Puig-Ventosa, 2015, p. 71). The study identifies three
main categories of action to minimize the rebound effect: measures designed to change consumer
behaviour through information and awareness, regulatory instruments, and economic and energy
taxation instruments (Freire-González & Puig-Ventosa, 2015). My research explores the
potential for “measures designed to change consumer behaviour through information and
awareness,” which is important because there is a lack of literature on specific measures to
minimize the rebound effect such as these. In practice, however, “an appropriate policy mix
combining different sorts of instruments may be the most effective option” (Freire-González &
Puig-Ventosa, 2015, p. 72).
A similar study was conducted by Medina (2011) on the qualitative effect of consumer
behaviour on energy consumption. The study examined the consumer behaviour behind the
Healthy Homes Calgary Program, now replaced by the Green Homes & Communities program,
which is an urban environmental charity supporting Calgarians in living a more sustainable life
17
by helping them take effective environmental actions (Green Calgary, 2015A). “A survey
conducted in 40 homes concluded that the healthy-home actions recommended by the Healthy
Homes Calgary Program in regards to energy and water conservation, waste reduction, indoor air
quality, and sustainable food choices and mindful purchasing are certainly implemented. The
overall conclusion is that the Program is creating a positive and lasting change in regards to
energy consumption at home” (Medina, 2011, p. iii). This leaves room for a quantitative analysis
on energy consumption at home. The study notes that “consumer behaviour related to energy can
be measured by the amount of electricity, natural gas, and water used at home” (Medina, 2011, p.
1), which is exactly what my research aims to address.
“This is an area in which we can all have a profound impact … collectively we are the
ones who make billion-dollar decisions about energy in the way we heat our homes, light our
cities, and how far we drive our cars … We must develop, then, a healthier and more
conscientious awareness of the energy we consume” (Tertzakian & Hollihan, 2009, p. xiv).
2.3 Human Nature
What can be said about human nature and its role in consumer behaviour? In their book
Flourishing: A Frank Conversation about Sustainability, co-authors John Ehrenfeld and Andrew
Hoffman discuss the way in which culture shapes human nature. “There are households with
iPads that are sitting in a bottom drawer simply because someone wants to show off the latest
one sitting on the countertop. Some people dismiss this behaviour glibly as just ‘human nature,’
so there is nothing much we can do about it … But this behaviour is so embedded in our culture
of materialism that it appears to be human nature, and, therefore, unassailable” (Ehrenfeld &
Hoffman, 2013, p. 74). This behaviour, they argue, is not our human nature. Instead, it is a
cultural attribute. “We need to recognize that the way we consume does not derive from a
18
fundamental human characteristic. It is a cultural phenomenon. Once we realize that, then we can
begin to change it” (Ehrenfeld & Hoffman, 2013, p. 74). In other words, changing consumer
behaviour requires an understanding of the immensity of cultural influences and a rejection of
the idea that we are predisposed to behave a certain way. It demands a realization that our
individual, supposedly autonomous decisions are inadvertently skewed by the cultural
framework of the system in which they are made. For example, “our present culture tells us
every day in many different ways that we are and need to be consumers; what we own are our
status symbols” (Ehrenfeld & Hoffman, 2013, p. 73). Furthermore, our productive capacity
makes it essential to market ever more consumer goods (Ehrenfeld & Hoffman, 2013). The
promise of these consumer goods, whether implicit or explicit in marketing schemes, entices us
to consume even more (Ehrenfeld & Hoffman, 2013). The problem lies on the producer side as
well; even the efforts of high-scoring firms to reduce the impact of the goods and services that
flood the market cannot keep up with the drive to sell ever more of these goods and services
(Ehrenfeld & Hoffman, 2013). We need “a realistic, scalable menu and a trimmed down,
healthier appetite” (Tertzakian & Hollihan, 2009, p. 135).
The solution, then, must be a cultural shift. “Externally imposed behaviour change is
going to help, but what needs to happen is much more cultural. It takes a long time for the beliefs
driving the new habits to work down into the cultural structure. Only then do the new ways
become the accepted routines” (Ehrenfeld & Hoffman, 2013, p. 73).
However, the cultural structure does not operate alone. Ehrenfeld & Hoffman (2013)
recall the words of British sociologist Anthony Giddens, who speaks of “structuration.” He states
that the structure of a culture creates routine behaviour, and in return, behaviour embeds the
structure of culture more deeply (Ehrenfeld & Hoffman, 2013). As such, “cultures are constituted
19
by a sort of circular process that makes it meaningless to identify either the chicken or the egg as
the driver” (Ehrenfeld & Hoffman, 2013, p. 78). Therefore, any cultural shift must attend to both
the individual and the system (Ehrenfeld & Hoffman, 2013). After all, it is the individuals who
constitute the system. “[The sustainable future] can only be created through well-informed,
purposeful actions by the entire socioeconomic system: consumers, producers, citizens, and
politicians” (Ehrenfeld & Hoffman, 2013, p. 51). The question is, can we lower our energy
demand in conjunction with our efforts to meet it?
20
Chapter Three: Methods
3.1 Criteria
This research encompasses energy, the environment, and the economy. The amount of
energy savings from conscious consumption reflects the reduced environmental burdens and
quantifies the reduced economic costs. For example, the amount of energy savings can be traced
back to the source used to provide that energy, the depletion of which impacts the environment.
In Alberta, 83% of the installed electricity generation capacity is from non-renewable sources,
namely coal and natural gas (Alberta Energy, 2016A). The exploitation of these resources
ultimately contributes to the array of large-scale phenomena that threaten our environment today,
such as climate change and habitat loss. Thus, energy saved is environmental damage evaded.
Secondly, energy savings yield economic savings, both on the micro scale (household income)
and on the macro scale (energy costs). On the micro scale, individuals can save money through
various techniques, both behavioural (energy-saving habits) and technological (energy-saving
devices). On the macro scale, governments can save money through a number of undertakings,
such as city-wide improvements, land-use plans, and energy diversification. In addition, social
factors are at play, especially consumer behaviour. Since energy facilitates human quality of life,
at the core of energy matters are humans themselves. In a sense, we control energy and the
environment controls us, while the economy either reaps the benefits or suffers the
consequences.
The data for this study is collected from the natural gas, electricity, and water bills from a
sample of 10 households who are asked to exercise conscious consumption according to a set of
general guidelines over one month: May 2016. This is considered the case of conscious
consumption or “mindful use.” The base case is represented by the same month in previous
21
years: May 2014 and May 2015. These constitute the cases of normal consumption or “liberal
use.” Calgary averages are also used as a baseline. The participants are then required to complete
two surveys that serve to provide supporting information about demographics and consumer
choices. The results provide an idea of how much energy savings can be expected to be achieved
through conscious consumption alone. This research seeks only to examine the energy savings
from mindfulness at the discretion of the individual; future research may examine the energy
savings with more strict or more precise (quantified) guidelines for consumption.
3.1.1 Target Demographic
Specifically, the snowball sampling method is used to select participants, which means
they are either directly recruited or recommended. In order for the sample to be representative of
Calgary, the target demographic is census family households, which constitute 84% of living
arrangements in the city according to the 2011 Census of Canada and National Household
Survey (The City of Calgary Community & Neighbourhood Services, 2013). These include
couple families with children at home, couple families without children at home, and lone-parent
families (The City of Calgary Community & Neighbourhood Services, 2013). The sample
includes participants from among family, friends, and coworkers, all of which fit the stated
demographic. The sustainability attitude of the participants varies and is determined through the
surveys in order to capture perception vs. reality.
3.1.2 Guidelines
The general guidelines provided to the participants are listed in Appendix A. The most
important feature of these guidelines is that they are completely discretionary, which means it is
completely up to the participants which guidelines to follow and to what extent. As such, the
22
results reflect the savings that can be achieved without compulsion. Hence the question: In what
ways are people willing to modify their energy use?
3.1.3 Surveys
The two surveys administered to the participants are shown in Appendix B. These are the
General Survey and the Guidelines Survey. The purpose of the General Survey is to explore
connections between demographics and energy use and account for any household changes over
the three years in question. These include changes in member size, temporary absences, guest
visits, efficiency upgrades or improvements, and changes in employment status. These changes
are accounted for in order to make the three years comparable and the baseline valid. The
purpose of the Guidelines Survey is to identify which guidelines were followed before vs. during
the experiment, i.e. which guidelines were actually applied. This provides insight on the
willingness of participants to make particular changes, which can then be harnessed.
3.2 Baseline
As mentioned, the participants’ energy use in May 2014 and May 2015 is considered the
baseline for this study. The main reason for examining only two years in the past is to have
similar weather and situational conditions as today. That is, to avoid any significant life changes.
In addition, most utility providers only keep the last two to three years of their customers’ energy
bills on file. Finally, many participants have only been living in their current house for the last
few years, or have changed utility providers for at least one of the three elements within the last
few years. Importantly, participants are only considered to have made a savings if their energy
use this year is less than their lowest between May 2014 and May 2015. In other words, if they
surpassed their own personal record.
23
A secondary baseline for this study is the average use of natural gas, electricity, and
water in Calgary. For comparison:
Energy: In 2009, the per capita natural gas use in Calgary was about 80 GJ/year (The
City of Calgary Environmental & Safety Management, 2010), or 119 GJ/year according
to more recent sources (Direct Energy Regulated Services, 2013). As this differs from
month to month, the average use for the month of May is 6 GJ (Direct Energy Regulated
Services, 2013).
Electricity: In 2009, the per capita electricity use in Calgary was about 8500 kWh/year
(The City of Calgary Environmental & Safety Management, 2010). As this differs from
month to month, the average monthly use for an Alberta residence is 600 kWh/month
(Alberta Energy, 2016B).
Water: The per capita water use in Calgary is about 7 m3/month (The City of Calgary,
2016A). This amount includes water for irrigation and usually remains about the same
throughout the year (The City of Calgary, 2016A).
3.2.1 Assumptions
Assumptions are made for any adjustments required to streamline the data. These
assumptions relate to the energy use impact of certain life changes and the water use impact of
varying rainfall patterns in different years.
Specifically, in order to make the three years comparable, certain adjustments are made.
These adjustments are increases or decreases to the energy use in a given year to account for the
additional presence or absence of a member at home. For example, if one member was employed
full-time in May 2014 and May 2015 and then went on maternity leave in May 2016, the energy
use in May 2016 is reduced by a certain amount to account for this year’s additional usage. An
24
online Electricity Calculator is used to help approximate these adjustments for a typical
household (State Government of Victoria, 2014). For the purposes of this study, the percent
adjustments to electricity use for one person are considered similar for natural gas and water. The
following information is used as representative and comparable input data:
Computers: In 2012, the average number of personal computers per household in
Canada was 2.85 ≈ 3 (TekCarta, 2016A).
TVs: In 2012, the average number of TV sets per TV household in Canada was 2.67 ≈ 3
(TekCarta, 2016B). Assume LCD TVs.
Refrigerators: Assume 1 refrigerator per household.
Dishwashers: Assume 2 dishwasher loads per household per week.
Dryers: Assume 2 dryer loads per household per week.
Assume no electric hot water system, swimming pool, electric cook top, electric oven,
electric under floor heating, air conditioning, or electric central heating.
The adjustments are approximated using the average yearly electricity use as determined
by the Electricity Calculator, depending on how often someone is home during a typical week
day, as shown in Table 3-1. These adjustments are applied on a case-by-case basis according to
the unique circumstances of participants as determined by the General Survey results, and
summarized in Table 3-2.
25
Table 3-1: Adjustments Based on Frequency of Presence at Home
None of the Time 1/4 of the Time Half of the Time 3/4 of the Time All of the Time Average Adjustment
Average Yearly (kWh) 5113.9 5468.3 5691.1 5913.8 6136.5 -
Average Monthly (kWh) 426 456 474 493 511 -
Quarter Adjustment - 7% 4% 4% 4% 5%
Half Adjustment - - 11% - 8% 10%
Full Adjustment - - - - 20% 20%
(State Government of Victoria, 2014)
Table 3-2: Case-by-Case Adjustment Allocations
Change From To Adjustment Type Adjustment
Unemployed to Employed Part-time All of the Time 3/4 of the Time Quarter 5%
Employed Full-time to Employed Part-time Half of the Time 3/4 of the Time Quarter 5%
Employed Full-time to Student Half of the Time Most of the Time (1) Quarter / Half 7.5%
Employed Full-time to Unemployed Half of the Time All of the Time Half 10%
Employed Full-time to Maternity Leave Half of the Time All of the Time Half 10%
New Child None of the Time Half of the Time (2) Half 10%
Unemployed to Vacation All of the Time None of the Time Full 20%
(Sorial, 2016)
(1) Since the student schedule is intermittent (i.e. a few hours of class time per week), the person is estimated to be
home most of the time (more than 3/4 of the time but less than all of the time).
(2) Since newborns consume less energy than adults and sleep for most of the daytime, the new child’s presence at
home all of the time is reduced to half of the time.
In addition to this, adjustments are made for water use. Figure 3-1 shows the typical
home water use for common household fixtures and appliances. Although this varies depending
on personal habits and fixture efficiencies, watering the lawn is the highest consumer in a typical
home (The City of Calgary, 2016A). While indoor water use remains relatively constant
throughout the year, outdoor water use peaks in spring and summer when it is used to irrigate
lawns and gardens, which presents a significant seasonal variation (The City of Calgary, 2007).
Adjustments are necessary to account for differences in rainfall quantities, and therefore lawn-
watering requirements, from year to year as these do not reflect consumer behaviour in the home.
26
Figure 3-1: Typical Home Water Use in Calgary
(The City of Calgary, 2016A)
The total precipitation in May 2014, May 2015, and May 2016 were 44.3 mm, 33.9 mm,
and 18.4 mm respectively (Environment and Climate Change Canada, 2016). The average
rainfall in the city for the month of May is 60 mm (Holiday Weather, 2016). This means that the
amount of rainfall has consistently decreased over the last few years, and remains below average.
Therefore, it is assumed that the lawn-watering requirements have increased accordingly over the
last few years. Using the average rainfall to represent the amount of rainfall generally required
for a healthy lawn, adjustments are calculated for each year, depending on the amount of rainfall
in that particular year. For example, since May 2016 had the lowest rainfall, it likely also had the
highest lawn-watering requirements, so this year’s water use is decreased accordingly. This
information is summarized in Table 3-3.
27
Table 3-3: Water Adjustments Based on Rainfall Patterns
May 2014 May 2015 May 2016 Average
Rainfall (mm) 44.30 33.90 18.40 60.00
Percent of Average 74% 57% 31% -
Adjustment -26% -44% -69% -
(Environment and Climate Change Canada, 2016)
After accounting for certain life changes and varying rainfall patterns in different years,
the data can be analyzed. Then, with all other variables constant, the differences due to conscious
consumption are identified.
3.2.2 Approximations
Approximations are made to align metering cycle dates with experimental dates.
Metering cycles differ both from household to household and from element to element, while the
experiment runs from May 1 to May 31. To match the available energy bill data with the dates of
the experiment, the energy use exclusive to the month of May is proportionated from the April-
May and May-June metering cycles. This essentially means averaging the April-May and May-
June energy use over the applicable metering cycle duration, and then applying that daily
average to the May duration only. For example, if two subsequent metering cycles are from April
18 to May 17 and then May 18 to June 16, the May energy use is approximated as the average
daily use between April 18 and May 17 applied to the first 17 days of May plus the average daily
use between May 18 and June 16 applied to the remaining 14 days of May. A Date-to-Date
Calculator is used to determine the exact metering cycle durations (Time and Date, 2016). While
this may reduce the accuracy of the findings, it is required in order to extract the relevant data.
That is, unless each household conducts the experiment on the specific metering cycle dates for
each element. In this case, the dates would not be consistent across all participants, and the
rainfall adjustments would have to be approximated.
28
Chapter Four: Results
4.1 Analysis and Findings
4.1.1 Energy Savings
The direct results of the study are the natural gas, electricity, and water savings achieved
by each of the 10 households in May 2016 as measured against their lowest between May 2014
and May 2015 (or May 2015 only in the two cases where May 2014 is unavailable). The savings
are then calculated both as a unit measure and as a percentage. The unit measures are gigajoules
(GJ) of natural gas, kilowatt-hours (kWh) of electricity, and cubic metres (m3) of water. Table
4-1 and Figure 4-1 show the natural gas consumption results, Table 4-2 and Figure 4-2 show the
electricity consumption results, and Table 4-3 and Figure 4-3 show the water consumption
results.
29
Table 4-1: Natural Gas Consumption (GJ)
House May 2014 May 2015 May 2016 Savings
House 1 11.3 9.0 7.6 1.4 16%
House 2 2.9 2.0 2.9 N/A N/A
House 3 - 4.6 4.5 0.1 2%
House 4 5.5 3.8 3.9 N/A N/A
House 5 4.9 5.8 6.4 N/A N/A
House 6 7.0 5.6 4.8 0.8 14%
House 7 - 5.8 6.8 N/A N/A
House 8 3.8 2.9 1.7 1.2 40%
House 9 6.7 3.8 3.6 0.3 7%
House 10 4.8 5.0 4.7 0.2 3%
Figure 4-1: Natural Gas Consumption (GJ)
0
2
4
6
8
10
12
House 1 House 2 House 3 House 4 House 5 House 6 House 7 House 8 House 9 House 10
Nat
ura
l Gas
(G
J)
Natural Gas Consumption
May 2014 May 2015 May 2016 Average
30
Table 4-2: Electricity Consumption (kWh)
Household May 2014 May 2015 May 2016 Savings
House 1 595 518 692 N/A N/A
House 2 453 462 441 12 3%
House 3 - 293 368 N/A N/A
House 4 506 525 470 36 7%
House 5 886 527 702 N/A N/A
House 6 418 380 417 N/A N/A
House 7 - 503 457 46 9%
House 8 330 354 338 N/A N/A
House 9 388 378 354 24 6%
House 10 537 581 474 63 12%
Figure 4-2: Electricity Consumption (kWh)
0
100
200
300
400
500
600
700
800
900
1000
House 1 House 2 House 3 House 4 House 5 House 6 House 7 House 8 House 9 House 10
Elec
tric
ity
(kW
h)
Electricity Consumption
May 2014 May 2015 May 2016 Average
31
Table 4-3: Water Consumption (m3)
Household May 2014 May 2015 May 2016 Savings
House 1 11.1 10.0 11.7 N/A N/A
House 2 21.4 10.2 7.1 3.1 31%
House 3 - 7.2 4.4 2.9 39%
House 4 14.6 10.6 6.1 4.4 42%
House 5 9.0 8.0 8.6 N/A N/A
House 6 7.0 14.0 7.6 N/A N/A
House 7 - 8.5 7.1 1.4 17%
House 8 11.1 10.2 4.4 5.8 57%
House 9 11.1 9.6 4.3 5.4 56%
House 10 15.5 13.0 5.4 7.6 58%
Figure 4-3: Water Consumption (m3)
0
5
10
15
20
25
House 1 House 2 House 3 House 4 House 5 House 6 House 7 House 8 House 9 House 10
Wat
er (
m3)
Water Consumption
May 2014 May 2015 May 2016 Average
32
In terms of the actual quantity of savings, House 8 made the most savings in natural gas
(40%), and House 10 made the most savings in electricity (12%) and water (58%). The black
dashed line in these figures represents the Calgary average for the month of May. Half of the
participants had below average consumption for natural gas, most had below average
consumption for electricity, and none had below average consumption for water. The household
water consumption from the experiment excludes water for irrigation, as it is factored out, while
the Calgary average is all-inclusive. This means that even without water for irrigation, all
participants were above average water users. From this, it can be inferred that water is the most
overused commodity among the three elements. Meanwhile, from the “Savings” percentage
column in these tables, it can be seen that water is also the most saved commodity among the
three elements.
33
4.1.2 General Survey
The results of the General Survey are summarized in Table 4-4, Table 4-5, and Table 4-6. These are divided into
demographics, home characteristics, and awareness.
Table 4-4: General Survey Results Summary – Demographics
House Members Age 1 Age 2 Kids Education 1 Education 2 Employment 1 Employment 2 Income Culture 1 Culture 2
House 1 3 30-39 30-39 2 Bachelor Bachelor Full-time Maternity Leave $200k+ Canadian Hungarian
House 2 3 40-49 40-49 4 Bachelor Associate Part-time Part-time $200k+ Canadian Canadian
House 3 4 20-29 20-29 5, 7 Bachelor Bachelor Full-time Full-time $175-200k Canadian Canadian
House 4 7 40-49 40-49 3, 9, 13 Graduate Graduate Part-time Unemployed $125-150k Asian Asian
House 5 2 50-59 60-69 N/A Graduate High School Full-time Retired $200k+ Canadian Canadian
House 6 2 50-59 50-59 N/A Bachelor Bachelor Full-time Self-employed $125-150k Persian Persian
House 7 6 40-49 40-49 12, 12, 18, 22 Associate College Unemployed Unemployed $125-150k Hispanic Hispanic
House 8 5 40-49 40-49 8, 10, 13 Graduate Graduate Self-employed Unemployed $50-75k Iraqi Iraqi
House 9 4 40-49 40-49 7, 10 Graduate Bachelor Unemployed Full-time $200k+ Egyptian Egyptian
House 10 5 30-39 30-39 1 Graduate Graduate Full-time Full-time $200k+ Russian, Ukrainian Ukrainian
34
Table 4-5: General Survey Results Summary – Home Characteristics
House Community House Type House Size AC?
House 1 Christie Park Single-family 2400 N
House 2 New Brighton Single-family 2400 N
House 3 Richmond Duplex 1800 N
House 4 Pineridge Single-family 1535 N
House 5 Westmount Single-family 2080 Y
House 6 Varsity Single-family 1200 N
House 7 Beddington Heights Single-family 2300 N
House 8 Aspen Woods Single-family 2300 N
House 9 Royal Oak Single-family 2400 N
House 10 Airdrie Single-family 2000 Y
Table 4-6: General Survey Results Summary – Awareness
House Course? Consciousness
House 1 N 7
House 2 Y 7
House 3 Y 5
House 4 N 7
House 5 N 7
House 6 N 7
House 7 N 5
House 8 N 6
House 9 Y 7
House 10 Y 6
35
4.1.3 Guidelines Survey
The results of the Guidelines Survey are summarized in Table 4-7, Table 4-8, and Table 4-9. These are divided into natural
gas, electricity, and water. The reference numbers (i.e. NG 1, E 1, W 1) correspond to the list of guidelines in Appendix A. The table
values represent the number of “jumps” in frequency for each guideline. The frequency scale consists of never, seldom, sometimes,
often, or always. For example, if a guideline was followed “sometimes” before the experiment and “often” during the experiment, that
is considered one jump in frequency. The minimum jump is zero (not applied at all) and the maximum jump is four (never applied to
always applied). As such, this evaluation does not display the frequency with which the guidelines are followed, but rather the change
in frequency between the months of normal consumption and the month of conscious consumption.
Table 4-7: Guidelines Survey Results Summary – Natural Gas (NG)
House NG 1 NG 2 NG 3 NG 4 NG 5 NG 6 Total
House 1 0 0 0 1 0 0 1
House 2 0 0 0 0 0 0 0
House 3 0 0 1 0 2 1 3
House 4 0 0 0 0 2 2 2
House 5 0 0 1 0 0 0 1
House 6 0 0 0 2 0 1 2
House 7 4 0 0 4 0 1 3
House 8 1 3 1 2 2 1 6
House 9 0 0 0 0 2 0 1
House 10 1 0 0 1 2 1 4
Total 3 1 3 5 5 6
36
Table 4-8: Guidelines Survey Results Summary – Electricity (E)
House E 1 E 2 E 3 E 4 E 5 E 6 E 7 E 8 E 9 E 10 E 11 E 12 E 13 E 14 E 15 E 16 E 17 E 18 E 19 E 20 E 21 E 22 E 23 Total
House 1 0 0 0 1 0 1 1 1 0 0 1 1 0 1 0 0 0 0 0 1 0 1 0 9
House 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
House 3 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 3
House 4 0 0 0 0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 3
House 5 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2
House 6 1 0 1 1 1 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 1 0 0 8
House 7 0 0 0 0 0 0 2 0 2 0 4 0 0 0 0 0 0 0 0 0 0 1 1 5
House 8 1 1 0 2 1 1 1 1 0 0 0 3 3 3 0 0 0 1 1 1 1 1 1 16
House 9 2 2 0 2 0 2 2 3 0 0 4 2 2 2 0 0 0 2 2 2 0 0 2 14
House 10 1 1 1 2 1 1 1 1 0 0 0 0 0 0 1 0 1 2 2 1 0 1 1 15
Total 6 3 2 5 3 4 5 4 2 2 3 4 4 4 1 0 1 5 3 4 2 4 4
Table 4-9: Guidelines Survey Results Summary – Water (W)
House W 1 W 2 W 3 W 4 W 5 W 6 W 7 W 8 W 9 Total
House 1 0 1 0 0 0 0 0 0 1 2
House 2 0 0 0 0 0 0 0 0 0 0
House 3 0 0 0 0 0 0 0 0 0 0
House 4 0 0 1 1 1 0 0 0 0 3
House 5 0 1 0 0 0 0 0 0 0 1
House 6 1 1 1 1 0 0 0 0 0 4
House 7 1 0 0 1 0 0 0 0 0 2
House 8 2 2 1 1 0 1 0 1 1 7
House 9 0 0 0 2 2 2 0 0 0 3
House 10 1 1 0 1 1 1 0 0 0 5
Total 4 5 3 6 3 3 0 1 2
37
Table 4-7 shows that NG 6 was the most commonly applied natural gas guideline,
followed by a tie between NG 4 and NG 5. Table 4-8 shows that E 1 was the most commonly
applied electricity guideline, followed by a tie between E 4, E 7, and E 18. Table 4-9 shows that
W 4 was the most commonly applied water guideline, followed by W 2. All three tables show
that House 8 applied the most guidelines in each area. The “winning” or most commonly applied
guidelines were as follows:
Natural Gas
1. NG 6: Water Temperature. If possible, try to take cooler showers to minimize water
heating. For example, try reducing the temperature a little bit each time until you
accustom to a lukewarm temperature.
2. NG 4: Water Temperature. Lower your water heater thermostat to anywhere from 55 to
60°C to minimize water heating and also avoid scalding your hands.
2. NG 5: Water Temperature. Switch from hot to cold water for laundry loads to minimize
water heating. “Unless you’re doing a load of clothes that is caked in dirt, it’s not
necessary to use hot water to wash them; in fact, hot water wears your clothes out much
faster.”
Electricity
1. E 1: Lighting. Turn off any unnecessary lights.
2. E 4: Electronics. Conserve battery life of electronics. For example, do not leave unused
laptop on such that the battery drains. Instead, set to hibernate or sleep mode or turn off
completely.
2. E 7: Electronics. Unplug battery chargers when unused or when batteries are fully
charged, as many chargers draw power continuously.
38
2. E 18: Electronics. Unplug unused electronics such as coffee makers, kettles, toasters, hair
dryers, etc. to minimize standby power. Consider also unplugging major appliances such
as computers, TV’s, and sound systems when unused for more pronounced savings.
Water
1. W 4: Duration. Take shorter showers. For example, try to reduce idle time in the shower
or take more efficient showers. Try to think / ponder / daydream less, as this tends to
slow you down and make you spend a longer time in the shower.
2. W 2: Volume. Do not let the water run while brushing teeth, lathering face, etc. or any
tasks that do not actually require the water.
In summary, the most popular guidelines were related to water temperature for natural
gas, lighting and electronics for electricity, and duration and volume for water. For natural gas,
the other guidelines were related to house temperature and air circulation. These may be less
applicable in the summer as compared to winter in Calgary because of the minimal requirements
for space heating. Thus, it makes sense that water temperature was the easiest variable to
manipulate. For electricity, the other guidelines were related to laundry, dishwashing,
refrigeration, cooking, cleaning, and leisure. It makes sense that lighting and electronics were the
easiest variables to manipulate, as these are used on a daily basis, and lighting and entertainment
are the main sources of electricity consumption in the home next to air conditioning (Wilson,
2016B). That is, assuming a traditional electric-powered air conditioner, if applicable. According
to the General Survey results, only two out of all ten participants have air conditioning in their
home. For water, the other guidelines were related to pressure, laundry, and dishwashing. It
makes sense that duration and volume were the easiest variables to manipulate, as these are also
used on a daily basis and are in the direct control of the user at low sacrifice.
39
Interestingly, the top guideline for both natural gas and water was shower-related. People
were willing to take cooler showers (to reduce water heating) and shorter showers (to reduce
water quantity). This is noteworthy because these are perhaps the guidelines that most directly
interfere with people’s comfort. This seems promising for energy-saving initiatives that target an
education and awareness approach. Meanwhile, the top guideline for electricity was to turn off
unnecessary lights, which is perhaps the least cumbersome guideline. However, the fact that so
many people applied it means that they did not necessarily do so before the experiment, or that
there was room for improvement. This suggests that “easy” guidelines, because they are easy,
can always be applied more often.
Figure 4-4 shows the total number of guidelines applied by each household.
Figure 4-4: Guidelines Survey Results Summary
0
5
10
15
20
25
30
35
House 1 House 2 House 3 House 4 House 5 House 6 House 7 House 8 House 9 House 10
Nu
mb
er o
f G
uid
elin
es A
pp
lied
Guidelines Survey Results Summary
40
From this, House 8, House 10, and House 9 applied the most guidelines, respectively.
House 2, House 5, and House 3 applied the least guidelines, respectively. The minimum number
of guidelines applied was zero, and the maximum number of guidelines applied was 29 out of all
38 (approximately 76%). The household that applied zero guidelines claimed that they had
already been following most of the guidelines before the experiment, but paid closer attention to
them during the experiment. Therefore, although no notable jumps in frequency were
documented, it is considered that they participated in the experiment to some level.
4.2 Interpretation and Discussion
4.2.1 Participant Success Rate
One way to analyze the results is to determine which participants successfully lowered
their energy use in all three elements, irrespective of the actual quantity of savings. As such, the
participants are grouped into Tier 1, Tier 2, Tier 3, and Tier 4. Tier 1 includes those who
improved in all three elements, Tier 2 includes those who improved in two of the three elements,
Tier 3 includes those who improved in one of the three elements, and Tier 4 includes those who
did not improve in any of the three elements. These results are shown in Table 4-10 and Figure
4-5.
Table 4-10: Participant Success Rate
Tier 1 (3/3) Tier 2 (2/3) Tier 3 (1/3) Tier 4 (0/3)
Number of Households 2 5 2 1
Percentage of Households 20% 50% 20% 10%
41
Figure 4-5: Participant Success Rate
From these results, it can be seen that half of the participants fell in Tier 2, which means
they managed to improve two of the three elements. There was an even split between participants
in Tier 1 and Tier 3, which can be considered the best and worst performers, respectively. One
participant landed in Tier 4, which means that in all three elements, their energy use actually
increased compared to at least one of the last two years. Overall, however, 80% of all
participants showed at least one improvement. This proclaims that the majority of participants
were successful in making an energy savings by following the guidelines.
4.2.2 Equivalency of Minimum Savings
Another way to analyze the results is to determine the large-scale effect of the actual
quantity of savings achieved by a single household. Specifically, the minimum savings achieved
by a single household are used to calculate the savings across the Calgary population, because
0
1
2
3
4
5
6
Tier 1 (3/3) Tier 2 (2/3) Tier 3 (1/3) Tier 4 (0/3)
Nu
mb
er o
f P
arti
cip
ants
Level of Improvement
Participant Success Rate
42
these are a conservative representation of consumer behaviour. In 2011, the total number of
census family households in Calgary was 296,430 (The City of Calgary Community &
Neighbourhood Services, 2013). The minimum savings achieved by a single household
multiplied by the total number of census family households in Calgary gives the potential energy
savings that can be achieved if all consumers in Calgary behaved like the least conscious
participant in the sample. Table 4-11 shows the actual energy savings achieved in one month,
and Table 4-12 and Table 4-13 show the potential energy savings that can be achieved across the
Calgary population in one month and one year, respectively.
Table 4-11: Actual Energy Savings – By Single Household – Per Month
Natural Gas (GJ) Electricity (kWh) Water (m3)
Maximum 1.4 63 7.6
Average 0.30 15 3.0
Minimum 0.07 12 1.4
Table 4-12: Potential Energy Savings – For Calgary Population – Per Month
Natural Gas (GJ) Electricity (kWh) Water (m3)
Maximum 415,002 18,675,090 2,252,868
Average 88,929 4,446,450 889,290
Minimum 20,750 3,557,160 415,002
Table 4-13: Potential Energy Savings – For Calgary Population – Per Year
Natural Gas (GJ) Electricity (kWh) Water (m3)
Maximum 4,980,024 224,101,080 27,034,416
Average 1,067,148 53,357,400 10,671,480
Minimum 249,001 42,685,920 4,980,024
These results show that the minimum savings achieved by a single household over the
month of the experiment are 0.07 GJ of natural gas, 12 kWh of electricity, and 1.4 m3 of water.
43
Over the population, these translate to about 21,000 GJ of natural gas, 3.5 million kWh of
electricity, and 400,000 m3 of water. Over the course of a year, these become 250,000 GJ of
natural gas, 43 million kWh of electricity, and 5 million m3 of water.
To give these values more meaning, energy equivalency is used, in terms of energy
(consumption savings), environment (impact savings), and economy (cost savings). Namely, the
equivalent number of homes’ use for one year, the carbon dioxide equivalent (CO2eq) in the
atmosphere, and the equivalent cost savings based on current utility prices. Considering that the
average annual consumption in Calgary is 119 GJ of natural gas (Direct Energy Regulated
Services, 2013), 8500 kWh of electricity (The City of Calgary Environmental & Safety
Management, 2010), and 84 m3 of water (The City of Calgary, 2016A), the equivalent number of
homes’ use for one year is shown in Table 4-14. Then, using a Greenhouse Gas Equivalencies
Calculator, the CO2eq values are shown in Table 4-15 (EPA, 2015). Finally, considering that the
current average costs in Calgary are $1.63/GJ for natural gas (Direct Energy Regulated Services,
2013), $0.03/kWh for electricity (ENMAX Corporation, 2016A), and $3.10/m3 of water (The
City of Calgary, 2016B), the equivalent cost savings are shown in Table 4-16.
Table 4-14: Number of Homes' Use for One Year – Monthly Savings Payoff – Energy
Natural Gas Electricity Water
Maximum 3,487 2,197 26,820
Average 747 523 10,587
Minimum 174 418 4,941
Table 4-15: Carbon Dioxide Equivalent – Monthly Savings Payoff – Environment
Natural Gas Electricity Water
Maximum 17,989 13,124 N/A
Average 2,998 3,125 N/A
Minimum 2,398 2,500 N/A
44
Table 4-16: Cost Equivalent – Monthly Savings Payoff – Economy
Natural Gas ($/GJ) Electricity ($/kWh) Water ($/m3)
Maximum 2.28 2.08 23.53
Average 0.49 0.50 9.29
Minimum 0.11 0.40 4.33
These equivalency calculations show that the minimum savings achieved by a single
household over the month of the experiment are equivalent to at least 174 homes’ use of all three
elements for one year, about 5,000 tons of CO2eq out of the atmosphere, and about $60 a year in
cost savings. This is significant considering the potential savings that can be achieved by
developed nations collectively. If this sample is considered representative of any country that
enjoys the benefits of energy accessibility, the energy savings can be extrapolated to the
population of developed countries, which stands at more than 1.2 billion today (PRB, 2013). In
perspective, if only 84% of these are census family persons (The City of Calgary Community &
Neighbourhood Services, 2013) and the average number of persons in a household is 2.6
(Statistics Canada, 2013A) as is the case in Calgary, the city’s savings would be multiplied by
over 1300 times. This reflects the power in numbers at no cost and little sacrifice.
In terms of number of homes’ use for one year, these results show that water has a payoff
of more than 10 times that of natural gas and electricity. That is, the amount of water savings is
enough to supply significantly more homes than the amount of natural gas and electricity
savings. This may be because water use is more sporadic and volatile; it only takes one minute
for a faucet to dispense 7.5 L (The City of Calgary, 2010). In other words, a small amount of
time spent running water equates to a notable volume, while natural gas and electricity are more
slow and incremental. Water use is also perhaps more tangible to the consumer, and thus creates
a perceivable consumer feedback system.
45
It is important to note that these results are also likely conservative due to the
demographic characteristics of the sample. Eight of the ten participants are engineers who work
in the oil and gas extraction industry, nine of the ten households have high education levels (at
least one member with a bachelor level education) and high incomes (annual combined income
of $125,000 or more), and all ten participants rated themselves high on the environmentally
conscious scale (5/10 score or more). This demographic is likely to apply more energy-saving
practices than a less educated group, but is also likely to have less room for application than a
less educated group since they are already relatively conscious. From personal interaction, this
demographic tended to be highly receptive to and interested in energy-saving practices, and were
actually concerned that their contribution to the experiment would be minimal (i.e. they would
not be able to render much more savings than they believe they are already achieving). In
addition to this, Calgary is said to have the highest family income in the country (CBC News,
2014). This can mean that Calgarians have the least incentive to make energy-saving (and
therefore cost-saving) changes compared to lower-income city residents.
4.2.3 Per Capita Consumption
Finally, a way to validate the data is to determine the average per capita consumption,
and verify that this decreases as the average number of members increases. Considering the
average number of members and the average gross consumption for each household over the
three months in question, the average per capita consumption for each of the three elements are
determined. Table 4-17 and Figure 4-6 show the natural gas average per capita consumption,
Table 4-18 and Figure 4-7 show the electricity average per capita consumption, and Table 4-19
and Figure 4-8 show the water average per capita consumption.
46
Table 4-17: Natural Gas – Average Per Capita Consumption
House Average Number of Members Natural Gas (GJ)
House 1 3 2.8
House 2 3 0.9
House 3 4 1.1
House 4 7 0.6
House 5 2 2.8
House 6 2 2.9
House 7 6 1.1
House 8 5 0.6
House 9 4 1.2
House 10 5 1.0
Figure 4-6: Natural Gas – Average Per Capita Consumption
This figure shows that as the average number of members increases, the average natural
gas consumption per capita decreases.
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
0 1 2 3 4 5 6 7 8
Nat
ura
l Gas
(G
J)
Average Number of Members
Natural Gas - Average Per Capita Consumption
47
Table 4-18: Electricity – Average Per Capita Consumption
House Average Number of Members Electricity (kWh)
House 1 3 201
House 2 3 151
House 3 4 83
House 4 7 71
House 5 2 352
House 6 2 203
House 7 6 80
House 8 5 68
House 9 4 93
House 10 5 106
Figure 4-7: Electricity – Average Per Capita Consumption
This figure shows that as the average number of members increases, the average
electricity consumption per capita decreases.
0.0
50.0
100.0
150.0
200.0
250.0
300.0
350.0
400.0
0 1 2 3 4 5 6 7 8
Elec
tric
ity
(kW
h)
Average Number of Members
Electricity - Average Per Capita Consumption
48
Table 4-19: Water – Average Per Capita Consumption
House Average Number of Members Water (m3)
House 1 3 3.6
House 2 3 4.3
House 3 4 1.5
House 4 7 1.5
House 5 2 4.3
House 6 2 4.8
House 7 6 1.3
House 8 5 1.7
House 9 4 2.1
House 10 5 2.3
Figure 4-8: Water – Average Per Capita Consumption
This figure shows that as the average number of members increases, the average water
consumption per capita decreases.
0.0
1.0
2.0
3.0
4.0
5.0
6.0
0 1 2 3 4 5 6 7 8
Wat
er (
m3)
Average Number of Members
Water - Average Per Capita Consumption
49
These figures affirm the expected trend that as the average number of members in a
household increases, the average per capita consumption decreases. It is also important to note
that house size plays a role. “As square footage increases, the burden on heating and cooling
equipment rises, lighting requirements increase, and the likelihood that the household uses more
than one refrigerator increases” (EIA, 2012, p. 1). According to a report on Households and the
Environment: Energy Use issued by Statistics Canada (2007, p. 12), “Overall, smaller
households use less energy than larger households … Though energy use increased with
household size, on a per person basis, small households consumed more energy.” This is
consistent with the results of this study.
4.2.4 Summary
Each method of analysis yielded similar results. The first is the energy savings method,
which refers to the actual quantity of energy saved by each household. In this case, the best
performers are those who made the most energy savings and the worst performers are those who
did not make any savings at all (their energy use actually increased compared to at least one of
the last two years). The second is the guidelines method, which refers to the number of
guidelines applied by each household (out of all 38). In this case, the best performers are those
who applied the most number of guidelines and the worst performers are those who applied the
least number of guidelines. The third is the participant success rate method, which refers to the
number of elements improved by each household (out of natural gas, electricity, and water). In
this case, the best performers are those who landed in Tier 1 and the worst performers are those
landed in Tier 3 or Tier 4. The fourth is the per capita consumption method, which refers to the
average per capita consumption over the three months in question by each household. In this
case, the best performers are those who have the lowest per capita consumption and the worst
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performers are those who have the highest per capita consumption, in at least two of the three
elements. These results are summarized in Table 4-20.
Table 4-20: Results Summary by Analysis Method
Analysis Method Best Performers Worst Performers
Energy Savings House 8 (Natural Gas) House 10 (Electricity) House 10 (Water)
N/A
Guidelines House 8 (29/38) House 10 (24/38) House 9 (18/38)
House 2 (0/38) House 5 (4/38) House 3 (6/38)
Participant Success Rate House 9 (Tier 1) House 10 (Tier 1)
House 1 (Tier 3) House 6 (Tier 3) House 5 (Tier 4)
Per Capita Consumption House 4 (3/3) House 7 (2/3) House 8 (2/3)
House 5 (3/3) House 6 (2/3) House 1 (2/3)
From this, in terms of the actual quantity of savings, House 8 and House 10 were the
most successful. In terms of the number of guidelines applied, House 8, House 9, and House 10
were the most successful. In terms of the number of elements improved, House 9 and House 10
were the most successful. Finally, in terms of the actual quantity of energy consumed per person,
House 4, House 7, and House 8 were the most successful. Therefore, overall, House 8, House 9,
and House 10 achieved the best results. This supports the fact that these three households applied
the most guidelines. In other words, as expected, those who applied the most guidelines showed
the most success. This upholds that the guidelines made a difference in consumer behaviour and
energy consumption. House 1, House 5, and House 6 were consistently unsuccessful, and House
5 in particular was unsuccessful in all the applicable analysis methods.
51
4.2.5 Correlations
The observed correlations are relative to fellow participants as well as to general
statistics. These are as follows:
Fellow Participants
Members: The average number of persons in a household in the sample is 4.1.
Age: The median age of the sample is 40-49.
Kids: The average number of children at home per family in the sample is 1.8.
Education: 50% of the sample has at least one member with a bachelor level education
and 50% has at least one member with a graduate level education.
Employment: 90% of the sample has at least one source of income.
Income: The median total income per census family in the sample is $166,750.
Culture: The most common ethnic origin in the sample is Canadian (40%), followed by
Asian, Persian, Hispanic, Iraqi, Egyptian, and Ukrainian (10% each).
House Type: 90% of the sample lives in a single-detached house.
House Size: The average home size in the sample is about 2000 square feet.
General Statistics
Members: In 2011, the average number of persons in a household in Calgary was 2.6
(Statistics Canada, 2013A).
Age: In 2011, the median age in Calgary was 36.4 (Statistics Canada, 2016B).
Kids: In 2011, the average number of children at home per family in Calgary was 1.0
(Statistics Canada, 2013B).
52
Education: In 2011, 67.4% of the population in Calgary aged 25 years and over had
completed some level of post-secondary education (The City of Calgary Community &
Neighbourhood Services, 2013).
Employment: In June 2016, 91% of the labour force was employed (Statistics Canada,
2016C).
Income: In 2014, the median total income per census family in Calgary was $104,530
(Statistics Canada, 2016C).
Culture: In 2011, the most common ethnic origin in Calgary was British (23.3%),
followed by Canadian (19.4%) and Scottish (17.9%) (The City of Calgary Community &
Neighbourhood Services, 2013).
House Type: In 2011, 60.6% of the population in Calgary lived in a single-detached
house (Statistics Canada, 2016B).
House Size: According to an industry survey by the Canadian Home Builders
Association, the average home size in Canada is about 1900 square feet (Hopper, 2012).
According to the General Survey results, the most successful households (House 8,
House 9, and House 10) all have large member sizes (four to five members), are relatively young
in age (30 to 49 years old), have a high number of kids living at home (one to three), have high
education levels (at least one member with a graduate level education), are non-Canadian
(identify with another culture in addition to the Canadian culture), live in large single-family
houses (2000 square feet or more), and rated themselves high on an environmentally conscious
scale (6/10 to 7/10 score). Specifically, two of these three participants are students in the
University of Calgary Graduate Program in Sustainable Energy Development (SEDV). The least
successful households (House 1, House 5, and House 6) all have small member sizes (two to
53
three members), have a small number of kids living at home (zero to one), have average
education levels (at least one member with a bachelor level education), are actively working (at
least one member employed full-time), have high incomes (annual combined income of
$125,000 or more), have never taken a course related to sustainability (environmental and social
issues), and also rated themselves relatively high on an environmentally conscious scale (7/10
score). This may suggest that the least successful households were actually better performers to
start with, however, this is not the case. In fact, they were actually some of the highest
consumers of natural gas and electricity, as shown in Table 4-21.
Table 4-21: Household Initial Consumption (May 2014 / May 2015)
These results are consistent with reports that “Households that used a greater number of
selected energy-saving practices were also likely to live in single-detached homes, have larger
household sizes, heat larger areas, and have higher incomes and more education” (Statistics
Canada, 2007, p. 15). However, the results do not agree with reports that “These households
were also more likely to use more energy overall,” as this was not the case (Statistics Canada,
2007, p. 15). In this experiment, the level of improvement did not seem to be a direct function of
room for improvement, as shown in Table 4-22.
House Natural Gas (GJ) Electricity (kWh) Water (m3)
House 1 10.1 557 10.6
House 2 2.4 458 15.8
House 3 4.6 293 7.2
House 4 4.6 515 12.6
House 5 5.4 707 8.5
House 6 6.3 399 10.5
House 7 5.8 503 8.5
House 8 3.3 342 10.6
House 9 5.3 383 10.3
House 10 4.9 559 14.3
54
Table 4-22: Number of Guidelines Applied vs. Initial Consumption (May 2014 / May 2015)
As expected, the level of improvement did seem to be a function of the number of
guidelines applied, as shown in Table 4-23.
Table 4-23: Number of Guidelines Applied vs. Savings
This study also tests the hypothesis that wealth and prosperity (affluence) is a driving
force for increased energy use. Table 4-24 shows the annual household income compared to the
average consumption over the three months in question for each household. The data
demonstrates that this is somewhat the case, however, no clear or pronounced pattern is
discerned to support this theory.
Number of Guidelines Applied Natural Gas (GJ) Electricity (kWh) Water (m3)
0 2.4 458 15.8
4 5.4 707 8.5
6 4.6 293 7.2
8 4.6 515 12.6
10 5.8 503 8.5
12 10.1 557 10.6
14 6.3 399 10.5
18 5.3 383 10.3
24 4.9 559 14.3
29 3.3 342 10.6
Number of Guidelines Applied Natural Gas (GJ) Electricity (kWh) Water (m3)
0 N/A N/A 2.9
4 N/A N/A N/A
6 0.1 36 4.4
8 N/A N/A N/A
10 N/A N/A 5.8
12 1.4 12 3.1
14 0.8 46 1.4
18 0.3 63 7.6
24 0.2 63 7.6
29 1.2 24 5.4
55
Table 4-24: Income vs. Average Consumption
In summary, though correlation does not imply causation, some of the interesting
commonalities were that the most successful households tended to have more members, more
kids, slightly higher education levels (graduate vs. bachelor), more awareness in reality
(sustainability course), and less awareness by perception (environmentally conscious score).
Overall, they seemed to be more “active,” since they had more people in their household (which
requires teamwork) and pursued higher educations (which requires drive). In terms of perception
vs. reality, the most successful participants were SEDV students but rated themselves slightly
lower in awareness, while the least successful participants had never taken a course related to
sustainability but rated themselves slightly higher in awareness. This establishes that consumer
awareness is subjective, and aligns with the findings of previous studies that participants
underestimated energy use and savings (Attari, DeKay, Davidson, & de Bruin, 2010). This
suggests that consumer feedback systems can be effective because they address the discrepancy
between perception and reality.
Income Natural Gas (GJ) Electricity (kWh) Water (m3)
$50-75k 2.8 341 8.6
$125-150k 4.4 500 10.4
$125-150k 5.8 405 9.5
$125-150k 6.3 480 7.8
$175-200k 4.5 331 5.8
$200k+ 9.3 602 10.9
$200k+ 2.6 452 12.9
$200k+ 5.7 705 8.5
$200k+ 4.7 373 8.3
$200k+ 4.8 531 11.3
56
Chapter Five: Conclusions
5.1 Conclusions
This study explores the potential for large-scale energy savings through small-scale
consumer actions. To quantify this potential, 10 different households were provided with a set of
energy-saving guidelines related to natural gas, electricity, and water. Participants were asked to
follow these guidelines at their own discretion for the month of May 2016, considered the month
of conscious consumption. Next, the participants were asked to provide their energy bills from
May 2014, May 2015, and May 2016. Their energy use from May 2016 was then compared
against that of May 2014 and May 2015, considered the months of normal consumption, in order
to quantify the expected energy savings. The participants were also asked to complete two
surveys: a General Survey to collect demographic characteristics and explore correlations with
energy use, and a Guidelines Survey to identify which guidelines were followed (most popular
changes) and how many (most dedicated households). Then, four different analysis methods
were used to evaluate the success of the energy-saving initiative: energy savings, guidelines,
participant success rate, and per capita consumption. These are summarized below.
How much energy savings can be achieved through conscious consumption alone? In
terms of energy savings, the minimum savings achieved by a single household over the month of
the experiment were 0.07 GJ of natural gas, 12 kWh of electricity, and 1.4 m3 of water. When
scaled over the Calgary population and over the course of a year, this translated to a meaningful
savings. Specifically, the monthly savings equated to a potential annual savings of 250,000 GJ of
natural gas, 43 million kWh of electricity, and 5 million m3 of water for the city. That is
equivalent to at least 174 homes’ use of all three elements for one year, about 5,000 tons of
CO2eq out of the atmosphere, and about $60 a year in cost savings.
57
What changes are people willing to make at their own discretion? In terms of guidelines,
the most popular guidelines were related to water temperature for natural gas, lighting and
electronics for electricity, and duration and volume for water. The most applied guideline for
both natural gas and water was shower-related: people were willing to take cooler and shorter
showers. This may explain why water was found to be the most overused resource, but also the
most saved. The number of guidelines applied ranged from none at all to 76% of those provided.
In terms of participant success rate, although the results of participants varied, nine of the
ten households were able to make one saving or another. Two improved in all three elements,
five improved in two of the three elements, two improved in only one element, and one did not
improve at all. Finally, in terms of per capita consumption, the trend was as expected: as the
average number of members in a household increased, the average per capita consumption
decreased. The results of this study support the pursuit of measures designed to change consumer
behaviour through information and awareness. The overall conclusion is that such an endeavour
is worthwhile.
Are there any correlations between certain demographics and energy use? From these
analysis methods, House 8, House 9, and House 10 were generally the most successful. These
households had more members, more kids, slightly higher education levels (graduate vs.
bachelor), more awareness in reality (sustainability course), and less awareness by perception
(environmentally conscious score) compared to their less successful counterparts and the
relevant statistics.
Overall, the study concludes that the power of the individual is a relatively untapped
source of energy-savings that can certainly be leveraged to combat the energy, environmental,
and economic issues we face today.
58
5.2 Recommendations
5.2.1 Energy Efficiency
The EnerGuide for Homes (EGH) rating is a measure of efficiency for residential
buildings that scores home performance on a scale of 0 to 100. As it stands, the most efficient
homes built in Calgary in recent years are below the Canadian benchmark of EGH 80, and
Calgary trails other mid-sized cities in terms of home retrofits (AEEA, 2014). Overall,
“residential energy demands in Calgary are relatively high when compared to other mid-sized
cities in Calgary and present a large opportunity for potential retrofits or other energy efficiency
programs” (AEEA, 2014, p. 12).
To advance energy efficiency, Calgary plans to emulate a common strategy used by other
jurisdictions called the market transformation approach (AEEA, 2014). This model suggests
commercialization for new energy efficient products, followed by information and incentives
targeted toward high performers and then regulations targeted toward minimum performers
(AEEA, 2014). This approach is expected to overcome the weaknesses of the individual
components, since regulations are difficult to enact before market capacity is built and incentives
are difficult to sustain on a long-term basis (AEEA, 2014).
Education and outreach is said to support all stages of market transformation (AEEA,
2014). As part of a renewal plan in Boston, the city planned to add energy outreach to all of its
existing constituent and neighborhood services, support outreach by neighborhood volunteers,
and support development of an independent website with innovative social media functionality
(The Renew Boston Facilitation Team, 2010). This mechanism for outreach and referral is a
viable option for Calgary. The city also planned to use city data, MIS systems, and IT expertise
to enable intake for energy efficiency programs and provide follow-up assistance for residents
59
(The Renew Boston Facilitation Team, 2010). Calgary can combine these resources and
strategies to promote information and awareness. The AEEA (2014, p. 20) concludes that
“government engagement through incentives and regulations will be key in setting the pace of
energy efficient technology and behaviour adoption.”
5.2.2 Sectoral Application
While all sectors exhibit a strong potential for energy conservation, each commodity is
used in certain sectors more than others. For example, natural gas and water are predominantly
used in the residential sector, while electricity is predominantly used in the commercial sector.
With this information, energy-saving efforts can be targeted toward broad-scale application in
the most promising sector.
Natural gas in the residential sector offers a high potential for savings, especially due to
Canada’s heating demands in the expansive winter months. In addition to consumer behaviour,
household improvements can be broadly applied or incentivized, such as programmable
thermostats, south-facing windows, electric ceiling fans, roof and window insulation, ENERGY
STAR® furnaces and water heaters, regular replacement or cleaning of furnace filters, caulking
of leaks, etc. (California Energy Commission, 2016). “Energy efficiency improvements such as
better insulation, airtight windows and heat exchangers combined with more efficient furnaces
could reduce energy use in a typical new house in Calgary by 25%” (AEEA, 2014, p. 12).
Similar savings can be achieved through home renovation programs that encourage energy
retrofits for existing houses (AEEA, 2014). Likewise, water reduction techniques can be
facilitated, such as low-flow toilets and shower heads, flow restrictors or aerators, rainwater
barrels, etc. (Royal Borough of Greenwich, 2016). This has an extensive payoff since water was
found to have a much higher savings value in terms of number of homes’ use for one year
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compared to natural gas and electricity. This also has an extensive payoff due to the water-
energy nexus; saving water in turn saves the energy required to heat or cool that water for the
home and the energy required to extract, convey, treat, distribute, consume, and collect that
water for the city (Achari, 2016). For example, energy is required to extract water from sources,
convey water into storage facilities, pump and treat water in water treatment plants, transport
water to consumers, heat or cool water for use, and pump and treat water in wastewater treatment
plants (Achari, 2016). In perspective, running a hot water faucet for five minutes requires the
same amount of energy as burning a 60 W bulb for 14 hours (Achari, 2016). In many places, the
indirect use of water for turning on lights and running electric appliances is actually equal to the
direct use of water for taking showers and watering lawns (Achari, 2016). As water requires
energy, energy also requires water. Specifically, 140 L of water are required to produce 1 kWh
of electricity from fossil fuels (Achari, 2016). For this reason, it would also be wise to integrate
water and energy policy.
Finally, similar applications can be made for electricity in the commercial sector, which
has the added advantage of enabling changes across the board as opposed to effecting individual
households. In addition to the energy and cost savings that could be realized, energy efficient
buildings are found to have various health benefits, such as improved productivity, retail sales,
and school test scores from good daylighting (AEEA, 2014). For comparison, the Manitoba
Hydro Place office building in Winnipeg (LEED Platinum certified) has an energy use intensity
(EUI) of 88 kWh/m2, while the average Canadian office building has an EUI of about 380
kWh/m2 (AEEA, 2014). Calgary does not stray far from the national average, with an average
EUI of about 350 kWh/m2 from a sample of 40 office buildings (AEEA, 2014). In all cases, with
any efficiency improvements, caution must be taken to avoid the rebound effect.
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5.2.3 Next Steps
Calgary has identified six opportunities related to information programs, incentives, and
regulations that have successfully achieved wide-scale energy savings in other jurisdictions
(AEEA, 2014). In the area of information programs, the options are consumer feedback systems
and energy labelling of houses at time of sale (AEEA, 2014). In the area of incentives, the sole
strategy is incentives for energy efficiency upgrades (AEEA, 2014). Finally, in the area of
regulations, the options are requirements for energy audits of large industrial facilities,
regulations for higher energy efficiency in buildings and industrial facilities, and requirements
for the southward orientation of new buildings (AEEA, 2014). Of these, the ones that directly
influence consumer behaviour are those related to information and incentives. Some of these
strategies, namely consumer feedback systems, can be implemented with the help of utility
providers. For example, on January 27, 2016, Enmax launched a new personalized tool called My
Energy IQ™, which enables customers to understand how they use energy compared to other
nearby homes, learn what they can do to save money over time, and create a personal energy
savings plan (ENMAX Corporation, 2016B). Given the predominance of natural gas in the
residential sector in Calgary, this would be a valuable application by the other natural gas utility
providers in the city, which are Direct Energy, Encor by EPCOR, and Just Energy Alberta
(Energy Rates, 2016).
To augment these strategies, other organizations can be leveraged, such as Green
Calgary. Organizations can undertake many of the outreach and referral activities, especially to
advertise their own services, such as in-home consultations that serve to inform and educate
consumers about the areas in which they can save. For example, Green Calgary offers a service
called Green Teas, wherein consumers are given $50 worth of green cleaning products, water
62
saving fixtures, and personalized home solutions for free (Green Calgary, 2015B). This is similar
to the Energy Savings Kit Program and Energy Conservation Assistance Program offered by the
city of Vancouver, who works in partnership with BC Hydro and FortisBC to provide free
energy-saving products, evaluations, and installations for qualified low income households (City
of Vancouver, 2016). This can be very powerful if it is widely known or even made mandatory;
here, innovative social media techniques can be harnessed to generate awareness and help instill
energy-saving norms over large peer domains. In turn, prudent consumer behaviour has the
power to steer corporate behaviour, which is a useful non-regulatory instrument that
governments can use to supplement regulatory initiatives (Muldoon, Lucas, Gibson, Pickfield, &
Williams, 2015).
Further to this, Calgary can consider implementing embedded energy solutions. For
example, Toronto has developed an area-based approach to energy planning that models energy
needs for both existing and future development, called Community Energy Planning (CEP) (City
of Toronto, 2016). Such an approach reduces system-scale infrastructure costs, reduces pressure
on existing infrastructure, and reduces inefficiencies (City of Toronto, 2016). For example, peak
demand reduction alleviates pressure on existing infrastructure and provides capacity for new
development (City of Toronto, 2016). This is also a valuable approach for Calgary in future
planning, as the city continues to expand and energy demands rise. As part of this initiative,
Calgary can conduct feasibility studies and develop implementation plans for a vast array of city-
wide retrofits to existing infrastructure, much like the current e2 Street Lighting Program which
is set to install energy efficient LED lighting in 80,000 streetlights between 2015 and 2018 (The
City of Calgary, 2016C).
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5.3 Limitations
5.3.1 Approximation
The first and most important limitation of this study is that the energy savings can only be
approximated, because some monthly fluctuations may be caused by external factors and not
necessarily attributed to conscious consumption. There is no foolproof method to isolate
improvements due to conscious consumption alone, since consumer behaviour is not the sole
actor that determines energy use. For example, if less energy is used this year, is it solely due to a
change in habits or did other factors come in to play? To combat this, there must be a way to
separate regular fluctuations from changes due to habits, both of which are irregular and
unpredictable. This study accounts for changes with the help of the information provided in the
survey responses and various assumptions that inform case-by-case adjustments.
5.3.2 Baseline
Accuracy is dependent on the last two years being a representative baseline, because the
lowest consumption between May 2014 and May 2015 is considered the reference point from
which to calculate the energy savings in May 2016. However, this is only one instance in time,
and thus may not be a true reference point from which to quantify potential. The examination of
longer historical trends requires that more changes be accounted for, which further diminishes
accuracy. For water in particular, the average rainfall in the city for the month of May is used as
a reference point from which to calculate the lawn-watering requirements, and thus the lawn-
watering amounts. There are two underlying assumptions here: that the average rainfall is equal
to that required for a healthy lawn, and that the average consumer waters the lawn according to
this requirement. In reality, the lawn-watering amounts are subject to both weather conditions
and consumer choices, and historical irrigation amounts for each household are not available
64
because they are amalgamated with other water uses. As such, the water savings are founded on
an approximation of irrigation amounts, not an exact measured volume. This may be alleviated
by conducting a similar study during the winter months, when irrigation is not required and
therefore not reflected on water bills.
5.3.3 Human Error
Accuracy is also contingent on the integrity of the survey responses, especially those
about household changes over the three years in question. There are no absolute means to ensure
that all information is true (honest) and precise (accurate), since human error is built-in. The
survey respondent may not remember certain information, provide incorrect data, or answer
vaguely. In addition to this, one participant represents the entire household in the survey
responses, which means that any misinformation between individuals within that household is
not captured. Furthermore, the Guidelines Survey depends on said participant’s perception of
how well the entire household applied the guidelines. Finally, eight of the ten participants have at
least one child living at home under the age of 13, which adds a complicating factor to the
diligent adherence of guidelines.
5.3.4 Response Bias
There is some response bias associated with the Guidelines Survey in particular, because
respondents may be inclined to provide answers that support the research goals. For example,
respondents may wish to showcase an environmentally conscious attitude through extensive
guideline application. In addition, all were willing participants in the study, which implies a
generally positive inclination that is reflected in the outcome. That is, since none were unwilling,
the results are optimistic; the selected sample may not be representative of the average consumer.
65
5.3.5 Sample Size
A sample size of 10 households is statistically small for a population size of 296,430
households. For example, for an 80% confidence level and a 5% margin of error, the
recommended sample size for this population size is 164 (SurveyMonkey, 2016). This number
rises to 384 for a 95% confidence level and 665 for a 99% confidence level (SurveyMonkey,
2016). Due to the time and resource constraints of this study, only 10 participants were selected.
Consequently, the results obtained and correlations observed in this study require validation on a
broader spectrum of people.
5.4 Future Research
5.4.1 Historical Trends
In addition to increasing the sample size, the results of this research can be improved by
examining the full record of participants’ energy bills over the three years in question. This
would provide a more in-depth, case-by-case report of each household’s energy use, which can
offer more insights, help detect patterns, or explain inconsistencies. The experiment itself can be
extended to a yearly duration, which would minimize generalizations such as the application of
May savings across the whole year, and overall provide more data points for comparison.
5.4.2 Guideline Application
To expand on this research, it would be interesting to administer a survey that seeks to
understand why certain guidelines are preferentially followed while others are not. There may be
various reasons as to why a participant may consider a guideline unfavourable. For example,
they may consider it an inconvenience, they may believe it to be ineffectual, they may find it
difficult to bring a family member or child on board, or they may simply dislike doing it
themselves. This experiment only captures to what extent each guideline was followed, so herein
66
lies an opportunity for future research to encompass the underlying reasons. This level of
understanding can help tailor energy-saving strategies to the consumer base and expedite the
social acceptance of new initiatives.
5.4.3 Education
To continue this research, it would also be interesting to educate the worst performers,
and then repeat the experiment to gauge the effect of education on energy use. This can help
determine what it takes to change individuals’ energy habits. What are the motivators and what
are the deterrents?
Problem-solving in the environmental field involves both pollution prevention and
pollution control (Hettiaratchi, 2016). Pollution prevention reflects a proactive approach while
pollution control, or end-of-pipe treatment, reflects a reactive approach (Hettiaratchi, 2016).
Educational strategies are in line with the pollution prevention step, which reflects a proactive
approach. This is much less damaging and costly than a reactive approach; it is better to
anticipate and prevent than to react and cure. In the Integrated Waste Management (IWM)
hierarchy, “reduce” is considered the one and only method for complete elimination, unlike the
subsequent alternatives of reuse, recycle, recover, and residual (Hettiaratchi, 2016). Indeed, the
only way to completely eliminate environmental damage is to prevent it from happening in the
first place. For this reason, it would be worthwhile to test the efficacy of educational strategies,
and adapt them to consumer motivations.
5.4.4 Biomimicry
“Biomimicry is an approach to innovation that seeks sustainable solutions to human
challenges by emulating nature’s time-tested patterns and strategies” (Biomimicry Institute,
2015, p. 1). The core idea is that animals, plants, and microbes have already solved many of the
67
problems we face today (Biomimicry Institute, 2015). These solutions can be adapted and
harnessed by humanity to tackle global challenges. One such example is the ability of a zebra to
reduce its surface temperature by more than eight degrees Celsius with microscopic air currents
produced by the different heat absorption rates of its black and white stripes (Lappe, 2013). By
this premise, the Daiwa House office building in Sendai, Japan uses alternating dark and light
surfaces to generate small air currents that lower its exterior temperature, resulting in a 20%
energy savings over the summer months (Lappe, 2013). With Calgary’s extensive water and
space heating requirements in the winter months, and in parallel with the emergence of energy
efficient buildings, this is a pertinent area of research and development for the city.
The state today is no more than the total cumulative effect of a multitude of little things,
and herein lies the power of the individual.
68
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Appendix A Guidelines
Natural Gas
1. House Temperature. If you do not have a programmable thermostat: When you are home
and awake, set your thermostat as low as is comfortable. When you are asleep or out of
the house, lower your thermostat to anywhere from 10 to 15°C.
2. House Temperature. Use south-facing windows for natural temperature control when
possible. For example, open curtains on your south-facing windows during the day to
allow sunlight to naturally heat your home, and close them at night to reduce the chill you
may feel from cold windows.
3. Air Circulation. Avoid blocking air vents with drapes and furniture.
4. Water Temperature. Lower your water heater thermostat to anywhere from 55 to 60°C to
minimize water heating and also avoid scalding your hands.
5. Water Temperature. Switch from hot to cold water for laundry loads to minimize water
heating. “Unless you’re doing a load of clothes that is caked in dirt, it’s not necessary to
use hot water to wash them; in fact, hot water wears your clothes out much faster.”
6. Water Temperature. If possible, try to take cooler showers to minimize water heating.
For example, try reducing the temperature a little bit each time until you accustom to a
lukewarm temperature.
77
Electricity
1. Lighting. Turn off any unnecessary lights.
2. Lighting. Use south-facing windows for natural lighting when possible.
3. Lighting. If you have lamps, place them in corners so they reflect light from two walls,
and possibly avoid turning on a new light.
4. Electronics. Conserve battery life of electronics. For example, do not leave unused laptop
on such that the battery drains. Instead, set to hibernate or sleep mode or turn off
completely.
5. Electronics. Use your laptop instead of your desktop when possible, as it uses less
energy.
6. Electronics. Turn off unused electronics. For example, turn off desktop when unused,
turn off TV when no one is watching, etc.
7. Electronics. Unplug battery chargers when unused or when batteries are fully charged, as
many chargers draw power continuously.
8. Electronics. Unplug unused electronics such as coffee makers, kettles, toasters, hair
dryers, etc. to minimize standby power. Consider also unplugging major appliances such
as computers, TV’s, and sound systems when unused for more pronounced savings.
9. Laundry. Air dry / hang dry your laundry to minimize use of the dryer if possible.
10. Laundry. Separate your wash loads into light and heavy fabrics to achieve the shortest
drying times. Option here to air dry / hang dry your lightest fabrics.
11. Laundry. Toss a dry towel with the dryer load, which can also significantly reduce drying
times.
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12. Laundry. Wash and dry several loads at once, so that your dryer is not completely cooled
down when it heats up for the next load.
13. Laundry. Avoid over-drying your clothes, as this wastes energy and also causes static
and wrinkling.
14. Dishwashing. Skip the heat-dry setting for your dishwasher. Turn off your dishwasher
after the wash cycle and air dry your dishes.
15. Refrigeration. If you have a second fridge with minimal items, consider unplugging it
and relocating the items to the main fridge.
16. Refrigeration. Keep your freezer full, as it uses less energy than an empty one. Consider
filling it with ice.
17. Cooking. Use microwaves or toaster ovens to cook or heat leftovers.
18. Cooking. Optimize your oven use. For example, do all your baking on the same day of
the week if possible (heat once and bake more than one thing).
19. Cooking. Keep the oven door closed while cooking. “The temperature can drop by as
many as 25 degrees [F] each time you open the oven door.”
20. Cooking. Turn off the oven or burners when food is almost ready and let the existing heat
finish the cooking for you.
21. Cooking. Use tight-fitting covers on pots and pans when cooking on the stove, which also
shortens your cooking time.
22. Cleaning. Sweep instead of vacuuming when possible. If you have carpet, you can sweep
up large crumbs and clots of dirt with a broom in between sessions.
23. Leisure. If possible, limit TV time to a few hours a week, and encourage family members
to pursue activities that do not require electricity.
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Water
1. Pressure. In general, do not use water at full pressure / open faucet or showerhead at full
power. For example, try to accustom to a lower flow rate for dishwashing, handwashing,
showering, etc. in the same amount of time. In other words, increase your water
efficiency (try to use less water to achieve the same task).
2. Volume. Do not let the water run while brushing teeth, lathering face, etc. or any tasks
that do not actually require the water.
3. Volume. Take showers instead of baths.
4. Duration. Take shorter showers. For example, try to reduce idle time in the shower or
take more efficient showers. Try to think / ponder / daydream less, as this tends to slow
you down and make you spend a longer time in the shower.
5. Laundry. Optimize your laundry load. For example, try to accumulate more laundry per
batch instead of washing small quantities at a time. Combine or coordinate with family
members when possible, such as everyone’s black outerwear together as opposed to one
person’s black outerwear at a time. Cut one load of wash per week if possible.
6. Dishwashing. Optimize your dishwasher load. For example, try to fit more dishes in the
same batch by organizing or loading them strategically. Try to reuse dishes and utensils
that are relatively clean as much as possible, even if they require a quick rinse. Think
twice before using a new dish or utensil for a minimal task. Cut one load of wash per
week if possible.
7. Dishwashing. Scrape solids (bones, peels, crumbs, uneaten tidbits) into the garbage as
thoroughly as possible before you place your dish in the sink.
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8. Dishwashing. Gather all the dishes as close to the sink as possible, to save time as the
water is running.
9. Dishwashing. Rinse only as necessary. You may need to do less pre-rinsing than you
think. Experiment to find out how little you can get away with.
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Appendix B Surveys
General Survey
Demographics
1. Name:
2. How many members are in your household?
3. What is your age?
4. What is your spouse’s age?
5. If you have children in your household, what are their ages?
6. What is your highest level of education?
Less than high school degree
High school degree or equivalent (e.g., GED)
Some college but no degree
Associate degree
Bachelor degree
Graduate degree
7. What is your spouse’s highest level of education?
Less than high school degree
High school degree or equivalent (e.g., GED)
Some college but no degree
Associate degree
Bachelor degree
Graduate degree
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8. Which of the following categories best describes your employment status?
Employed, working full-time
Employed, working part-time
Employed, working from home
Self-employed
Not employed, looking for work
Not employed, NOT looking for work
Retired
Disabled, not able to work
Other (please specify)
9. Which of the following categories best describes your spouse’s employment status?
Employed, working full-time
Employed, working part-time
Employed, working from home
Self-employed
Not employed, looking for work
Not employed, NOT looking for work
Retired
Disabled, not able to work
Other (please specify)
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10. What was the approximate combined income of all the members of your household last
year?
$0 to $9,999
$10,000 to $24,999
$25,000 to $49,999
$50,000 to $74,999
$75,000 to $99,999
$100,000 to $124,999
$125,000 to $149,999
$150,000 to $174,999
$175,000 to $199,999
$200,000 or over
Prefer not to say
11. Do you identify with any other culture(s) in addition to the Canadian culture? If yes,
please specify.
Yes
No
12. Does your spouse identify with any other culture(s) in addition to the Canadian culture?
If yes, please specify.
Yes
No
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Home Characteristics
13. In which residential community do you live? (e.g. Signal Hill)
14. In which type of housing do you live?
Apartment
Condominium
Townhouse
Duplex
Single-family house
Other (please specify)
15. What is the approximate size of your home in square feet?
16. Do you have air conditioning in your home?
Yes
No
Changes
17. Has the number of members in your household changed in May of the past few years or
of the current year? If yes, please specify changes and dates (e.g. had a child or child
moved out on May XX, 2015).
Yes
No
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18. Have you or any of the members in your household been away for more than one night in
May of the past few years or of the current year? If yes, please specify dates (e.g. family
vacation or spouse was away from May XX - June XX 2015).
Yes
No
19. Have you had any guests stay in your home for more than one night in May of the past
few years or of the current year? If yes, please specify number of guests and dates (e.g.
three guests from May XX - June XX, 2015).
Yes
No
20. Have you made any efficiency upgrades or improvements to any heat, electricity, or
water systems in your home in May of the past few years or of the current year? If yes,
please specify changes and dates (e.g. installed low-flow toilet in 1 of 3 bathrooms on
May XX, 2015).
Yes
No
21. Have you or any of the members of your household had a change in employment status in
May of the past few years or of the current year? If yes, please specify changes and dates
(e.g. went from unemployed to employed or part-time to full-time on May XX, 2015).
Yes
No
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Awareness
22. Have you ever taken a course related to sustainability (environmental and social issues)?
If yes, please elaborate on the type of course.
Yes
No
23. On a scale of 1 being least, 5 being average, and 10 being most, where would you place
your household on an environmentally conscious scale, compared to the average
Calgarian?
1 2 3 4 5 6 7 8 9 10
Final Thoughts
24. Is there anything else you would like to share that you believe may be relevant to your
energy use?
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Guidelines Survey
The following scale is used to determine the frequency of application of each guideline:
Never Seldom Sometimes Often Always
Before Experiment
During Experiment
