how to valorise research on the effects of peak oil for urban planning? a method to investigate peak...
TRANSCRIPT
How to Valorise Research on the Effects of Peak Oil for Urban Planning?
A Method to Investigate Peak Oil Risks and Mitigation
Dr. Susan KrumdieckAssociate Professor
Department of Mechanical Engineering
University of Canterbury
Christchurch, New Zealand
Presentation to Walloon Parliament 26 April 2011 Namur, Belgium
Peak Oil Issue
Even if you believed it was an issue, what would you do about it?
Research Developments 2000-2011
• Peak Oil as a Planning Issue• Transition Engineering for Mitigation
Risk Assessment and Mitigation
• Risk Assessment: Probability and Impact• Adaptive Capacity• Resilience• Re-Development• Strategic Development Planning
New Zealand Herald
Peak Oil: Understanding the Issue
• Not really a question of if • Probability
(Campbell, 2004)
Peak Oil: Probability
Expert Assessments of Peak Oil Year
Num
ber
2005 2010 2015 2020 2030
Expert predictions of Supply Decline Rate
1.4%2.0%2.4%4.0%4.8%6.7%
Meta Analysis of Petroleum Geology and Supply Experts
P(y) Nr y 2006)!
(y 2006)!(r 1)!
r 1 y 2006
Peak Oil Issue: Probability
Meta Analysis of petroleum geology experts
1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 5
10
15
20
25
30
35
40
Year
Oil
Pro
du
ctio
n (
Bill
ion
Ba
rre
ls p
er
yea
r)
97%
85%
50%
15%
3%
Historic Projected
Supply probability
50% Reduction by 2050
Raleigh DistributionMonte-Carlo Simulation
(Krumdieck, Page, Dantas, 2010)
Long Range Fuel Supply Probability
World Oil Production (mbpd)* Probability Scenario 2020 2030 2040 2050
Unexpected Problems 54 38 27 19
No New Giant Oil Fields 60 45 38 26
Most Experts Agree 71 57 44 37
Discovery of Giant Fields 85 68 58 48
* For reference: 2008 average daily world oil production was 85 mbpd
Probability associated with scenarios of oil supply issues.
Peak Oil: Impact
• Behaviour and Access to Activities • Assets and Infrastructure Investments
Current Energy UseFor Current Travel Demand
Change in Oil Supply
Future Energy UseFor Future Travel Demand
Oil Supply Decline Impact
University of Canterbury, Christchurch
Students$13,500 pa
Staff$66,000 pa
Study of Adaptation
Local Adaptive Capacity
• Travel Adaptive Capacity Assessment Survey (TACA Survey)
Pressure for Change of Travel Behaviour (Price increase or other factor)
Tra
vel
Beh
avio
ur
Ad
ap
tati
on
(%
VK
T)
Tr avel Adaptive Capacity
0
100
200
300
400
500
600
700
800
0-1 1-2 2-3 3-4 4-6 6-8 8-10 10-15 15-20 > 20
Skateboard
Bicycle
Walking
Bus
Vehicle (passenger)
Vehicle (driver)
Travel Behaviour
Trips per week per 100 persons
Distance Traveled
Students5.6 litres/wk34.7 km/wk
Staff17.6 litres/wk60.7 km/wk
0
100
200
300
400
500
600
700
800
0-1 1-2 2-3 3-4 4-6 6-8 8-10 10-15 15-20 > 20
E TD m, d
d
m
ECm, d DBd
Transport Energy
Adaptation in Travel Demand
0
50
100
150
200
250
300
350
400
0 - 1
1 - 2
2 - 3
3 - 4
4 - 6
6 - 8
8 - 10
10 - 15
15 - 20
> 20
Trip Distance (km)
Trip
Fre
quen
cy
Other (e.g. taxi)
Electric bike
Rollerblades/skates
Bicycle
Walking
Bus or Park n ride (bus)
Vehicle (passenger)
Vehicle (driver)
NormalAlternatives
Do you have an alternative?
Car use reduction
Travel Behaviour Adaptive Capacity
Christchurch
Energy Reduction
Public Transport Adaptive Potential
Bus RoutesChristchurch
Bus Potential
Council Urban Plan 2041
Christchurch Densification Christchurch Sprawl
45% higher fuel demand than 2006
95% higher fuel demand than 2006
Risk to Essential Transport Activities
RECATS Method
(Dantas et al, 2008)
Travel Activity
Energy Constraint
Calculate Energy Consumption
E2< E1?Modify
Travel Activity
Constrained Travel ActivityCalculate Risk
Yes
NoE1
E2
0%
5%
10%
15%
20%
25%
0 - 1
1 - 2
2 - 3
3 - 4
4 - 6
6 - 8
8 - 1
0
10 -
15
15 -
20
> 20
Trip Distance [km]
Perc
en
tag
e o
f Tr
ips
Walk
Bike
Bus
Vehicle Passenger
Vehicle Driver
1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 5
10
15
20
25
30
35
40
Year
Oil
Pro
du
ctio
n (
Bill
ion
Ba
rre
ls p
er
yea
r)
97%
85%
50%
15%
3%
Historic Projected
Supply probability
Re Pe
T m, d, s
s
IW s
d
m
T m, d, s
s
IW s
d
m
Nms Nds N tc D m, d, s
s
IW s
d
m
1
Risk to Essential Activities
1990 2000 2010 2020 2030 2040 2050
100
200
300
400
500
600
Greater Christchurch Fuel consumptionUDS ConcentratedUDS Dispersal
95% Energy Increase
45% Increase
Canterbury Regional Fuel Use
Mitigation and Planning
• Urban Form Developments• Urban Villages and Free Markets• Public Transport• Densification• Bike Infrastructure
• Technologies• Vehicles and Fuels
• Behaviours• Residential Location• Mode Choice
Strategic Analysis: Opportunities
Automobiles
Transportation System 1930 - 2050
Biofuel & Electric
Walk & Bike
Sh
are
of
Tran
sp
ort
50%
100%
75%
25%
1930 1940 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050
Public Transport
Scooters
Strategic Analysis to 2050
Urban Form Adaptations
Fuel
, Veh
icle
, Beh
avio
ur A
dapt
atio
ns
Active Infrastructure 100km Bikeways
Dense City Centre
Integrated Urban Villages
Current Urban Form
3 L/100kmFleet Efficiency
50% Biofuels Synfuels
50% Electric Vehicles
Low Carbon Lifestyle
50 km of Electric Trolleys
Possible
No No No No
NoUnlikely
golf carts onlyNo No
Unlikely
Unlikely
Yes Yes Yes
Possible Possible
Possible Possible
Possible
Possible
Personal Travel in Dunedin
• Technical Feasibility
• Resource Availability
• Economic Viability
• Social
• Environment
• Asset Value
• Future Risk
Thank you for your attentionThank you for your attentionEngineering Research to Investigate and Mitigate Peak Oil Risks
Dr. Susan Krumdieck
Presentation to Walloon Parliament 26 April 2011 Namur, Belgium