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Many see natural gas as a bridge fuel to help transition Canada towards a low-carbon economy. Not only is natural gas abundant in Canada,4 but it is the cleanest burning fossil fuel and has various applications for end-users, including residential, commercial, industrial and power generation. Natural gas represents 35% of the Canadian primary energy consumption and 31% of the secondary energy consumption. More than half of the total demand comes from the industrial sector (Figure 1), followed by residential and commercial at 26.2% and 19.1%, respectively. Figure 1: Natural Gas Demand in Canada
Source: CERI, data source: Natural Resource Canada5 Although the share of natural gas is expected to continue increasing for electricity generation and industrial end use, achieving a lower carbon economy requires a deep transformation of energy systems. The transformation is challenging because “technology innovation, political and institutional, and behavioral systems are path dependent”6 (Aghion, et al). This is broader than economic policy shift, where people’s habits, trust in institutions and each other, could be challenged. Most of the current climate regulations are, however, based on the old framework or design: government subsidizes energy efficiency initiatives, renewable generation from the private sector and, on the other hand, it applies price on carbon emissions through a carbon tax or carbon trade to GHG emissions. Government and policy makers are often frustrated that some of their decisions do not deliver their full potential. They always need to find a trade-off between the cost of enforcing the policy and the associated benefits. While governments have been successful using carrot and stick regulations for the private sector, any successful energy
December 2017
CERI Natural Gas Report
Nudging Energy Policy? Alpha Sow Canada is a key player among nations engaged to transition towards a low-carbon economy. The nation takes part of an ambitious international commitment to reduce greenhouse gas emissions (GHG) by 30 percent below 2005 levels by 2030. The government of Canada, along with some provinces and territories, agreed to a four pillars general framework, the “PAN-Canadian Framework on Clean Growth and Climate” to achieve GHG reduction targets: pricing carbon pollution, complementary action to reduce emissions across the economy, adaptation measures and actions to accelerate innovation in clean technology and jobs creation in cleantech.1 With regards to the former, carbon pricing is recognized as an effective instrument for a transition to a low-carbon economy through its ability to provide a signal to the market, to reduce emissions and stimulate green technology innovation and stimulate growth. The federal framework consists of a minimum carbon price starting at $10 per tonne of CO2 eq in 2018, rising by $10 per year to $50 per tonne in 2022.2 The framework also comes with built-in flexibility. As such, provinces can opt for a cap and trade (Ontario and Quebec), a direct pricing system (British Columbia) or the latter combined with performance-based allocation (Alberta).3 The transition toward a lower carbon economy is a gradual process, where stranding assets is either avoided or limited and retiring assets are gradually replaced by cleaner ones through incentives or natural replacement through cleaner standards. During this process, the economy still needs a low emitting energy source.
CERI Commodity Report – Natural Gas Editorial Committee: Ganesh Doluweera, Paul Kralovic, Dinara Millington, Megan Murphy, Allan Fogwill About CERI The Canadian Energy Research Institute is an independent, not-for-profit research establishment created through a partnership of industry, academia, and government in 1975. Our mission is to provide relevant, independent, objective economic research in energy and related environmental issues. For more information about CERI, please visit our website at www.ceri.ca or contact us at [email protected].
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policy should be based on the end user’s long-term behavior changes. Energy use is shaped by behavior. As an example, households with the same characteristics can have a consumption difference near 2.5-fold.7 This type of inconsistency that cannot be explained in a classic optimization model, has been investigated by behavioral economists. It also represents a challenge for energy demand projections and modeling. The first attempt to incorporate behavior insight for the National Energy Model (NEMS) was envisioned by the US Energy Information Administration (US EIA). A report by Leidos Engineering, LLC prepared for the US EIA in October 2014 finds that “the extraction of potentially viable aggregate demand specifications within the existing literature has not revealed a “silver bullet” framework that holistically defines an alternative specification for aggregate demand that is fully reflective of behavioral variables”.8 Behavioral Economics Behavioral economics attempt to incorporate insights from other social sciences, mainly psychology, in order to enrich the standard economic model [Thaler, 20169]. The existence of psychological bias is not new. It has been acknowledged since the beginning of economics discipline. Adam Smith (1776), Pareto (1906), Pigou (120), Fisher (1930), Keynes (1936) and many others have expressed doubt that a human being is a rational economic agent. Behavioral economics show that human kind is not rational. Individuals treat losses and gains in a different manner, they are loss-averse. Individual preference is bound by the way choices are framed, environment, and temporality, and is also subject to pro-social behavior because of its self-image. Individuals also process a limited amount of information and recourse to short cuts, opt for default choices and are satisfied more often by status-quo than change. Individuals can also, however, improve the quality of their decision by learning, seeking positive information and feedback. It is important to note that behavioral economics does not contradict the mainstream economics assumption of “optimal behavior”, it augments it “with additional descriptive theories that are derived from data rather than axioms”10 and overall, increase the accuracy of the model predictions. The Royal Swedish Academy of Sciences awarded Richard Thaler, a University of Chicago professor, the 2017 Nobel Memorial Prize in Economic Science for his work on
behavioral economics, fifteen years after the first prize was awarded to Daniel Kahneman (2002 Nobel Memorial Prize in Economics Science) for his work on “prospect theory.” These ideas are entering mainstream thought. While private companies, military and investors have been leveraging on this work to improve their operations and gained economic benefits, more recently, behavioral economics is certainly impacting governments and policy-makers, primarily through the “nudge units”.11 “Nudge” is defined as “any aspect of the choice architecture that alters people’s behavior in a predictable way without forbidding any options or significantly changing their economic incentives” (Thaler and Sunstein 2008).12 Figure 2 illustrates “nudge units” around the world. The first institution dedicated to behavioral sciences was set up by the British government in 2010 – the Behavioral Insights Team (BIT). Other countries followed, such as Germany, Norway and the US. Like its British counterpart, the US started the Social and Behavioral Sciences Team (SBST)13 under the Obama administration, which works to address various social issues including college enrollment by low-income students, boosting health insurance take up, and encouraging federal workers to save for retirement. Figure 2: Nudge Units around the World
Source: Behavioral Economics in Action at Rotman (BEAR), Rotman School of Management, University of Toronto
In Canada, there are some organizations or teams affiliated with bigger government branches or agencies tasked with incorporating behavioral economic insights in government policy: the Innovation Hub, the Canada Revenue Agency, Employment and Social Development Canada or the Ontario Insight Unit.
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None of those units, however, have done publicly-available work on energy or climate related issues. Energy Policy, Climate Change and Behavioral Economics Energy policy plays a pivotal role in helping Canada transition to a low-carbon economy. It implies changing energy flows, promoting investment in the new type of generation as well as end user’s behavior changes. From an economic perspective, those transitions have been primarily modeled by classical means, without consideration for behavior. For the last few decades, many behavioral field experiments have been performed with energy end users, working towards a broader policy approach. Household and Mobility Energy Efficiency Programs Many of the behavioral developments in energy policy are targeting energy efficiency programs, whether they are residential, commercial, industrial or transportation. Household energy efficiency programs include experiments in electricity rate structure, where time of use (TOU) rates and critical peak pricing induced a decrease in electricity demand by 3-6% and 13-20%, respectively;14 billing and payment methods; non-pecuniary incentives to conserve energy15 (most of the studies about non-pecuniary incentives to conserve energy are not conclusive, because they were performed using a smaller sample, so in the short term, energy consumption is reduced, but it is unclear if energy conservation habits will persist long term); information provisions;16 energy efficiency investment in household appliances; and public appeals to conserve energy. In recent years, three emerging trends have been active in disrupting energy demand in the transportation sector and illustrate behavioral economics in practice. These are the emergence of transport services such as Uber, a continuous decline of passenger kilometers driven coupled with young adults delaying driving across OECD countries, and the emergence of electric vehicles. The US National Renewable Energy Laboratory (NREL) experiment led by Andrew Duvall demonstrates that people’s mobility can be nudged in order to optimize energy consumption through applications by giving real time feedback on departure time, routes, modes and estimated energy impact.17 The app messages are framed through micro surveys, non-monetary incentives and gamification.
Matt Biggar studied the San Francisco Bay area and found that “considering how community-level conditions meet practical and psychological needs may offer ways to more effectively support individual-level sustainable transportation choices.”18 Public Policy Instruments and Environmental Morals Carbon taxes, quotas (100 Mt cap on oil sands producers) or cap and trade tools are viewed in classical economic analysis as negative externalities regulation, their differences remain purely in terms of economic and administrative efficiency. Psychologist Frey (1999) argues that both tradable permits and carbon taxes will have opposite effects on consumers. An increase in price of activity will discourage behavior, but reduce intrinsic environmental morals. Frey also claims that environmental morals will be reduced by tradable permits more than taxes. He extends his analysis on the level of taxation, both low and high environmental taxes are more effective than medium ones because of its crowding-out effect on intrinsic motivation and failure to set a higher extrinsic motivation. Climate Change and Climate Policy The Columbia Center for Research for Environmental Decisions (CRED) published a guide19 on how to better communicate climate issues – the guide is largely based on behavioral economics and psychological research. The report reveals how psychologic elements such as confirmation bias and misconception alter our perception of facts related to climate change. It also suggests ways in which to improve framing information, present scientific facts, or leverage our analytic and intuitive ideas without falling to emotional plea. The foundational transition of behavioral economic theories in policy making were sourced from Thaler and Sunstein 2003 (Libertarian Paternalism), followed by Camerer et al. 2003 (Asymmetric Paternalism),20 both advocating for policy making with tradeoffs between welfare and freedom. For Bhargava, et al. (2015), the role of behavior economics in public policy should be limited to “medium sized gain with Nano-size interventions-Kahneman” but achieve the three following goals:21
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1. Address market failure, limited information and correct negative externalities. It also sought to move from environment choice simplification to product and incentives that underlie those choices.
2. Policy makers should aggressively protect consumers from firm behavior manipulation.
3. Improve policy design and implementation. The author concluded that “psychological factors, such as motivated disbelief, the ostrich effect, confirmation bias, present-bias, adaptation, and intangibility” are the main components climate policy failure. Canadian Application Due to the complexity and scope of transitioning to a lower carbon economy and the concomitant results of behavior economic field experiments “achieving medium results with Nano investment”, a nudge unit could certainly be part of the tool set for Canada. The country must run its own field experiments and cannot directly leverage on foreign field tests because results are socially connoted. Even within the same country, such as Canada, regional differences mean that solutions in central or eastern parts of the country could not be the same in the western or northern parts of the country. Shifting energy flow has a high risk on economic growth and it also has a path dependence, where institutions or individuals could resist change and retract on progressive policy decisions seen as invasive, or providing limited economic opportunity. A perfectly framed energy policy would also help Canada move away from the bias, disbelief, and intangibility of climate change with a lower cost for its implementation. Failing to do so will exacerbate gaps in the current energy policy debate fueled by bias and loss aversion. In the meantime, Canada remains a key player to transition towards a low-carbon economy. However, in the short- to mid-term, if Canada wants to meet its ambitious climate change goals, it must continue to reduce emissions. In a recent OECD report, the organization provided several suggestions to help Canada meet its climate change goals. Among the recommendations, including expanding renewable energy production and increasing the number of zero-emission vehicles in urban areas, was the idea of expanding the use of natural gas in transportation.22
Natural gas is certainly viewed by many as a bridge fuel, helping Canada transition to a low-carbon economy. Endnotes 1 Government of Canada, Pan-Canadian Framework on Clean Growth and Climate Change, https://www.canada.ca/en/services/environment/weather/climatechange/pan-canadian-framework.html 2 Government of Canada, Pricing carbon pollution in Canada: how it will work, https://www.canada.ca/en/environment-climate-change/news/2017/05/pricing_carbon_pollutionincanadahowitwillwork.html 3 ibid 4 Canada was the 5th largest natural gas producer in 2016 with 5,368 billion cubic feet (bcf) (BP Statistical Review, 2017) and reserves estimated to be 1,225 trillion cubic feet (NEB, 2017). 5 NRCan website, Natural Gas Facts, https://www.nrcan.gc.ca/energy/facts/natural-gas/20067 6 Aghion. P and al. Path dependence, innovation, and economics of climate change, 2014, Grantham Research Institute 7 https://www.eia.gov/analysis/studies/demand/economicbehavior/pdf/behavioraleconomics.pdf 8 ibid. 9 https://www.uchicago.edu/features/richard_thaler_delivers_nobel_prize_lecture/ 10 ibid. 11 Cabinet’s Office, The Behavioral Insights Team, http://www.behaviouralinsights.co.uk/about-us/ 12 https://www.uchicago.edu/features/richard_thaler_delivers_nobel_prize_lecture/ 13 Social and Behavioral Sciences Team, About SBST, https://sbst.gov/ 14 Ahmad Faruqui and Sanem Sergici, Household Response to Dynamic Pricing of Electricity—A Survey of The Experimental Evidence, January 10, 2009, pp. 2. 15 Nolan, Jessica M., P. Wesley Schultz, Robert B. Cialdini, Noah J. Goldstein, and Vlada Griskevicius, “Normative Social Influence in Underdetected,” Personality and Social Psychology Bulletin, 34 (2008), pp. 913 – 924. 16 Richard Thaler and Cass Sunstein, Nudge: Improving Decisions About Health, Wealth, and Happiness, 2008. 17 US National Renewable Energy Laboratory, Personalized Infrastructure: Leveraging Behavioral Strategies for Future Mobility, https://www.nrel.gov/docs/fy18osti/70309.pdf 18 Matt Biggar and Nicole Ardoin, Community context, human needs, and transportation choices: A view across San Francisco Bay Area communities, https://trid.trb.org/view/1465271 19 http://guide.cred.columbia.edu/pdfs/CREDguide_full-res.pdf 20https://www.cmu.edu/dietrich/sds/docs/loewenstein/BEPP1https://www.cmu.edu/dietrich/sds/docs/loewenstein/BEPP102.pdf02.pdf 21 ibid. 22 http://www.cbc.ca/news/politics/oecd-canada-climate-report-card-1.4455379
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SOU
RC
E: N
EB.
SOU
RC
E: N
EB.
SOU
RC
E: N
EB, E
IA.
SOU
RC
E: N
EB.
02468
10
12
Oct-
16
Dec-1
6F
eb
-17
Ap
r-17
Ju
n-1
7A
ug
-17
Oct-
17
We
st
Mid
wes
tE
as
t
US
Im
po
rts o
f C
an
ad
ian
Ga
sB
y U
S R
eg
ion
(B
cfp
d)
02468
Oc
t-1
6D
ec-1
6F
eb
-17
Ap
r-1
7J
un
-17
Au
g-1
7O
ct-
17
We
st
Mid
wes
tE
as
t
Ave
ra
ge
Ca
na
dia
n E
xp
ort P
ric
eB
y U
S R
eg
ion (
C$
/GJ
)
02468
10
12 Sep
-16
No
v-1
6Jan
-17
Mar-
17
May-1
7Ju
l-17
Sep
-17
Ca
na
da
Me
xic
o
To
ta
l U
S P
ipe
lin
e G
as I
mp
orts (
Bc
fpd
)
01234
Oct-
16
Dec-1
6F
eb
-17
Ap
r-17
Ju
n-1
7A
ug
-17
Oct-
17
Co
urt
rig
ht
Sa
rnia
St.
Cla
irO
the
r
Ca
na
dia
n G
as I
mp
orts
By I
mp
ort P
oin
t (
Bc
fpd
)
Relevant • Independent • Objective
Page 13
SOU
RC
E: U
S. D
OE.
SOU
RC
E: U
S D
OE.
SOU
RC
E: U
S D
OE.
No
te:
Ther
e w
ere
no
LN
G im
po
rts
for
the
mo
nth
of
No
vem
ber
20
14
.
SOU
RC
E: U
S D
OE.
02468
10
12
14
16
Oct-
15
Jan
-16
Ap
r-16
Ju
l-16
Oct-
16
Jan
-17
Ap
r-17
Ju
l-17
Oct-
17
Co
ve
Po
int
Elb
a Isla
nd
Eve
rett
NE
Gate
wa
yN
ep
tun
e
Ea
ste
rn
US
LN
G I
mp
orts B
y F
ac
ilit
y (
Bc
f)
02468
Oct-
15
Jan
-16
Ap
r-16
Ju
l-16
Oct-
16
Jan
-17
Ap
r-17
Ju
l-17
Oct-
17
Fre
ep
ort
Lak
e C
harl
es
Sab
ine P
as
sC
am
ero
nG
old
en
Pass
Gu
lf L
NG
US
Go
M L
NG
Im
po
rts B
y F
ac
ilit
y (
Bc
f)
05
10
15
20
Oct-
15
Jan
-16
Ap
r-16
Ju
l-16
Oct-
16
Jan
-17
Ap
r-17
Ju
l-17
Oct-
17
Nig
eri
aT
rin
idad
No
rwa
yY
em
en
US
LN
G I
mp
orts B
y O
rig
in (
Bc
f)
02468
10
12
JF
MA
MJ
JA
SO
ND
201
5201
6201
7
Volu
me-W
eig
hted A
verage L
NG
Pric
e (
US
$/M
MB
tu)
CERI Natural Gas Report
Page 14
SOU
RC
E: U
S D
OE,
NEB
.
SOU
RC
E: E
IA, U
S D
OE.
SO
UR
CE:
US
DO
E.
01234567
Oct-
15
Jan
-16
Ap
r-1
6J
ul-
16
Oc
t-1
6J
an
-17
Ap
r-1
7J
ul-
17
Oc
t-1
7
Tu
rkey
Bra
zil
Eg
yp
tIn
dia
Arg
en
tin
a
US
LN
G R
e-E
xp
orts
By D
estin
atio
n (B
cf)
0
10
20
30
40
50
60
70
80
90
Oct-
15
Ja
n-1
6A
pr-
16
Ju
l-1
6O
ct-
16
Ja
n-1
7A
pr-
17
Ju
l-1
7O
ct-
17
Chart
Title
Lit
hu
an
ia
Un
ited
Kin
gd
om
Po
lan
d
Th
aila
nd
Neth
erl
an
ds
Pak
ista
n
Ma
lta
Eg
yp
t
So
uth
Ko
rea
Ita
ly
Tu
rkey
Me
xic
o
Do
min
ican
Re
p.
Ch
ina
Jo
rdan
Sp
ain
Ch
ile
Ku
wa
it
Arg
en
tin
a
Po
rtu
gal
UA
E
Ind
ia
Bra
zil
Ta
iwan
Ja
pan
US
LN
G E
xp
orts b
y D
estin
atio
n (
Bc
f)
Relevant • Independent • Objective
Page 15
SOU
RC
E: C
ERI,
CA
OD
C, B
aker
Hu
ghes
. SO
UR
CE:
CER
I, C
AO
DC
.
SOU
RC
E: C
ERI,
CA
OD
C.
0
50
0
1,0
00
1,5
00
2,0
00
2,5
00
3,0
00 Jan
-06
Ju
l-07
Jan
-09
Ju
l-10
Jan
-12
Ju
l-13
Jan
-15
Ju
l-16
US
WC
SB
No
rth
Am
eric
an
Ac
tiv
e R
igs
0
100
20
0
300
400
500
60
0
70
0
800
900
1,0
00 Ja
n-0
6J
ul-
07
Ja
n-0
9J
ul-
10
Ja
n-1
2J
ul-
13
Ja
n-1
5J
ul-
16
Acti
ve R
igs
To
tal R
ig D
rillin
g F
leet
Ca
na
dia
n R
ig F
lee
t U
tiliz
atio
nW
ee
kly
Ave
ra
ge
Ac
tiv
e R
igs
-
100
200
300
400
500
600
700
15
913
17
21
25
29
33
37
41
45
49
5-Y
ear
Avg
.2016
2017
We
ste
rn
Ca
na
da
Ac
tiv
e R
igs
We
ek
ly A
ve
ra
ge
Week N
um
ber
SOU
RC
E: C
ERI,
CA
OD
C.
0
100
200
300
400
500
600
700 Ja
n-0
9J
an
-10
Jan
-11
Jan
-12
Ja
n-1
3J
an
-14
Ja
n-1
5J
an
-16
Jan
-17
Chart
Title
SK
AB
BC
WC
SB
Ac
tiv
e R
igs b
y P
ro
vin
ce
Wee
kly
Ave
ra
ge
CERI Natural Gas Report
Page 16
SOU
RC
E: C
ERI,
Bak
er H
ugh
es.
SO
UR
CE:
CER
I, B
aker
Hu
ghe
s.
SOU
RC
E: C
ERI,
Bak
er H
ugh
es.
0%
10%
20%
30%
40
%
50
%
60%
70%
80%
90
%
10
0%
0
200
400
600
800
1,0
00
1,2
00
1,4
00
1,6
00
1,8
00
2,0
00
2,2
00
2,4
00 Jan
-06
Ju
l-07
Jan
-09
Ju
l-10
Jan
-12
Ju
l-13
Jan
-15
Ju
l-16
Oil-d
irecte
dG
as-d
irecte
dG
as-d
irecte
d %
US
To
ta
l O
il-
an
d G
as-d
ire
cte
d A
ctiv
e R
igs
0
500
1,0
00
1,5
00
2,0
00
2,5
00 Ja
n-0
6J
ul-
07
Ja
n-0
9J
ul-
10
Ja
n-1
2J
ul-
13
Ja
n-1
5J
ul-
16
To
tal O
il-d
irecte
dG
oM
Gas-d
irecte
dO
nsh
ore
Gas-d
irecte
d
US
To
ta
l A
ctiv
e R
igs
0
20
40
60
80
100
120 J
an
-06
Ju
l-07
Jan
-09
Ju
l-10
Jan
-12
Ju
l-13
Jan
-15
Ju
l-16
Oil-d
irecte
dG
as-d
irecte
d
US
Gu
lf o
f M
ex
ico
Ac
tiv
e R
igs
Relevant • Independent • Objective
Page 17
SOU
RC
E: C
ERI,
Pla
tts
Gas
Dai
ly, S
tati
stics
Can
ada
CA
NSI
M T
able
12
9-0
00
5
SOU
RC
E: C
ERI,
Sta
tisti
cs C
anad
a C
AN
SIM
Tab
le 1
29
-00
05
.
SOU
RC
E: C
ERI,
EIA
. SO
UR
CE:
CER
I, E
IA.
-10
0
100
300
500
70
0
90
0
1,1
00
JF
MA
MJ
JA
SO
ND
5-Y
ear
Ran
ge
2017
Ca
na
dia
n W
ork
ing
Ga
s S
to
ra
ge
(Bc
f, M
on
th
-en
d)
0
100
20
0
30
0
40
0
500
600
700
800
900
1000
Oct-
16
Dec-1
6F
eb
-17
Ap
r-17
Ju
n-1
7A
ug
-17
Oct-
17
West
East
Ca
na
dia
n S
to
ra
ge
by R
eg
ion
(B
cf,
Mo
nth
-en
d)
0
500
1,0
00
1,5
00
2,0
00
2,5
00
3,0
00
3,5
00
4,0
00
4,5
00
5,0
00
JF
MA
MJ
JA
SO
ND
5-Y
ear
Avg
.2016
2017
US
Lo
we
r-4
8 W
ork
ing
Ga
s S
to
ra
ge
(B
cf,
Mo
nth
-en
d)
0
500
1,0
00
1,5
00
2,0
00
2,5
00
3,0
00
3,5
00
4,0
00
4,5
00
No
v-1
6Jan
-17
Mar-
17
Ma
y-1
7J
ul-
17
Se
p-1
7N
ov-1
7
East
Mid
west
Mo
un
tain
Pacif
icS
ou
th C
en
tral
US
Sto
ra
ge
by R
eg
ion
(B
cf,
Mo
nth
-en
d)
•Im
po
rtan
t N
ote
: So
urc
e o
f C
anad
ian
sto
rage
dat
a is
in
tra
nsi
tio
n,
fro
m P
latt
's G
as D
aily
to
Sta
tisti
cs
Can
ada
CA
NSI
M T
able
12
9-0
00
5 -
Can
adia
n m
on
thly
nat
ura
l gas
sto
rage
, C
anad
a an
d p
rovi
nce
s. 2
01
6
dat
a an
d o
nw
ard
s is
no
w c
olle
cted
fro
m t
he
latt
er w
hile
dat
a p
rio
r to
20
16
is f
rom
th
e fo
rmer
.
CERI Natural Gas Report
Page 18
SOU
RC
E: C
ERI,
Pla
tts
Gas
Dai
ly, S
tati
stics
Can
ada
CA
NSI
M T
able
12
9-0
00
5.
SOU
RC
E: C
ERI,
Pla
tt’s
Gas
Dai
ly, S
tati
stics
Can
ada
CA
NSI
M T
able
12
9-0
00
5.
SOU
RC
E: C
ERI,
Pla
tt’s
Gas
Dai
ly, S
tati
stics
Can
ada
CA
NSI
M T
able
12
9-0
00
5.
-60
-20
20
60
JF
MA
MJ
JA
SO
ND
WC
_IJ
_W
D
5-Y
ear
Avg
.2016
2017
We
ste
rn
Ca
na
dia
n S
to
ra
ge
In
jec
tio
ns/W
ith
dra
wa
ls(B
cf,
Mo
nth
-en
d)
-80
-60
-40
-200
20
40
60
JF
MA
MJ
JA
SO
ND
5-Y
ear
Avg
.2016
2017
Ea
ste
rn
Ca
na
dia
n S
to
ra
ge
In
jec
tio
ns/W
ith
dra
wa
ls
(Bc
f, M
on
th
-end)
-150
-100
-500
50
100
JF
MA
MJ
JA
SO
ND
5-Y
ear
Avg
.2016
2017
Ca
na
dia
n S
to
ra
ge
In
jec
tio
ns/W
ith
dra
wa
ls
(Bc
f, M
on
th
-en
d)
Relevant • Independent • Objective
Page 19
SOU
RC
E: C
ERI,
EIA
. SO
UR
CE:
CER
I, E
IA.
SOU
RC
E: C
ERI,
EIA
.
-250
-200
-150
-100
-500
50
10
0
150
200
JF
MA
MJ
JA
SO
ND
5-Y
ear
Avg
.2016
2017
US
Ea
st S
to
ra
ge
In
jec
tio
ns/W
ith
dra
wa
ls(B
cf,
Mo
nth
-end)
-300
-200
-1000
100
200
300
JF
MA
MJ
JA
SO
ND
5-Y
ear
Avg
.2016
2017
US
Mid
we
st R
eg
ion
Sto
ra
ge
Inje
ctio
ns/W
ith
dra
wa
ls
-60
-50
-40
-30
-20
-100
10
20
30
JF
MA
MJ
JA
SO
ND
5-Y
ear
Avg
.2016
2017
US
Mo
un
ta
in R
eg
ion
Sto
ra
ge
Inje
ctio
ns/W
ith
dra
wa
ls
(Bc
f, M
on
th
-end)
-80
-60
-40
-200
20
40
60
JF
MA
MJ
JA
SO
ND
5-Y
ear
Avg
.2016
2017
US
Pa
cif
ic R
eg
ion
Sto
ra
ge
In
jec
tio
ns/W
ith
dra
wa
ls(B
cf,
Mo
nth
-en
d)
SOU
RC
E: C
ERI,
EIA
.
CERI Natural Gas Report
Page 20
SOU
RC
E: C
ERI,
EIA
. SO
UR
CE:
CER
I, E
IA.
-300
-200
-1000
100
200
30
0
JF
MA
MJ
JA
SO
ND
5-Y
ear
Avg
.2016
2017
US
So
uth
Ce
ntra
l R
eg
ion
Sto
ra
ge
Inje
ctio
ns/W
ith
dra
wa
ls
(Bc
f, M
on
th
-en
d)
-1000
-800
-600
-400
-2000
200
400
600
800
JF
MA
MJ
JA
SO
ND
5-Y
ear
Avg
.2016
2017
US
Sto
ra
ge
In
jec
tio
ns/W
ith
dra
wa
ls
(Bc
f, M
on
th
-en
d)
