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D di P k Oil V l bilit St d dDunedin Peak Oil Vulnerability Study and Strategic Transition Plan

New Methods to Investigate Peak Oil Risks, Adaptation and Mitigation

Dr. Susan KrumdieckAssociate Professor

Department of Mechanical Engineering

University of Canterbury

Christchurch, New Zealand

IPENZ TG Conference 20 March 2012 Rotorua

Dunedin Peak Oil Vulnerability

July - Dec 2010 EAST Research Consultants LtdJuly Dec 2010 EAST Research Consultants Ltd.

Krumdieck, Rendall, Watcharasukarn, Page

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Peak Oil Issue

Even if you believed it was an issueEven if you believed it was an issue, what would you do about it?

Stand and Deliver

• Understand Oil Supply as a Planning and Management Issue

• Assess Risks to Essential Activities & Goods

• Quantify Adaptation over Planning Time-Frames

• Strategic Transition Analysis, Design, and Re-DevelopmentRe Development

Dantas, Krumdieck, PageDantas, Krumdieck, Page

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Peak Oil: Understanding the Issue

• Facts are Clear• Facts are Clear

• Probability and Time Frame

(Campbell, 2004)

Long Range Planning Issue

Meta Analysis of petroleum geology expertsy p g gy p 

25

30

35

40

Bar

rels

per

yea

r)

15%

3%

Supply probability Raleigh Distribution

Monte‐Carlo Simulation 

1960 1970 1980 1990 2000 2010 2020 2030 2040 20505

10

15

20

Year

Oil

Pro

duct

ion

(Bill

ion

97%

85%

50%

Historic Projected

50% Reduction by 2050

(Dantas et al., 2007, NZTA 311)(Krumdieck, et al. 2010, Trans Res A)

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Impact Depends on Adaptation

• How do activity systems currently depend on fuel?How do activity systems currently depend on fuel?• What is the Adaptive Capacity?

Current Energy UseFor Current Travel Demand

Change in Oil Supply

Future Energy UseFor Future Travel Demand

Population - Origins & Destinations

(StatsNZ Data)

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VKT Demand Audit

• Annual Vehicle Kilometers Traveled• Annual Vehicle Kilometers Traveled

6 000

8,000

10,000

12,000

14,000

16,000

18,000

20,000

es p

er H

ouse

hold

Veh

icle

Urban        Suburbs               Lifestyle                  Rural

0

2,000

4,000

6,000

Cent

ral D

uned

in

North

Dun

edin

Sout

h Dun

edin

Maori

Hill

Rosly

n

Opoho

North

Eas

t Vall

ey

Green

Islan

d

Rave

nsbo

urne

Mosgie

l

Port

Chalm

ers

Fairf

ield

Macan

drew

Bay

Broa

d Ba

y-Po

rtobe

llo

Brigh

ton

Compa

ny B

ay

Sawye

rs Ba

y

Wait

ati

Waik

ouait

i

Outra

m

Ave

rage

Ann

ual K

ilom

etre

(UC LATEE model using MOT WOF Data)

Affordability

•Car Ownership•Household Income•Drive to Work

VIPER (Dodson & Sipe, 2005) analysis using Census Data

High VulnerabilityLess VulnerableLow Vulnerability

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Travel Adaptive Capacity Survey

• MondayMonday

• Work

• Drive CRV

• Home to Uni

• If you couldn’t take your car, how many other ways do you have?• Walk• Bike• Bus

(Krumdieck, Page, Watcharasukarn, 2012, NZTA Research Report)

Adaptive Capacity Assessment

• TACA SurveyTACA Survey

 

Travel Adaptive Capacity

Price Elasticity

Behavior Trigger

Pressure for Change of Travel Behaviour (Price increase or other factor)

p p y

(Watcharasukarn et al., 2011,Trans Res A)

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Adaptability in Travel Demand

• Number of Trips

Travel Demand Pattern for Dunedin

15%

20%

25%

Walk

Bike

• Number of Trips

• Distance

• Mode

NormalAdapted

0%

5%

10%

0 - 1

1 - 2

2 - 3

3 - 4

4 - 6

6 - 8

8 - 1

0

10 -

15

15 -

20

> 20

Trip Distance [km]

Bus

Vehicle Passenger

Vehicle Driver

Travel Adaptive Capacity

• Dunedin could reduce fuel use by 40% and• Dunedin could reduce fuel use by 40% and not lose access to activities!

Alternatives to Individual Car Trips in Dunas reported in TACA Survey August 2010

Trips/weekCar - No Alternative

Car - Share a Ride

B

Car Walk

0% 20% 40% 60% 80% 100%

Litres/week

km/weekBus

Bike

Walk

Work from home

Bus

Percentage of trips normally made by car

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Active Mode Accessibility

(Rendall et al., 2012, Trans Res Record)

Active Mode Accessibility

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Development Scenarios

• Urban Form Developments• Urban Form Developments

• Technology Developments

• Behaviour Developments

Alternatives

• Biofuels: 50% of petrol replaced• Biofuels: 50% of petrol replaced

• Electric Cars: 50% of vehicles replaced

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Current Urban Form: No Change

Current Urban FormCar= 95% Bus= 3 5% Walk= 0 9% Bike= 0 5%Car= 95%, Bus= 3.5%, Walk= 0.9%, Bike= 0.5%

Dense Urban Form

Car= 85%, Bus= 5%, Walk= 6%,  Bike= 4%

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Development Scenario

• Integrated Urban Form - Urban Villagesg gCar= 75%, Bus= 12%, Walk= 5%, Bike= 8%

Development Scenario: Active Mode

• 100 km Bike Ways• 100 km Bike WaysAll children under 12 can get to their school by walking or by bike without being at risk from cars or trucks. 

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Development Scenarios: Public Transport

• 50 km of Electric Trolleybus• 50 km of Electric Trolleybus

Village Centres, CBD, Schools connected.

Development Scenarios: Vehicle Turnover and Reduction

• High Efficiency Vehicles Fl t Effi i 5 l/100k• High Efficiency Vehicles

2 litres/100km

4.5 litres/100km

Fleet Efficiency = 5 l/100k

1 car +1 scooter per household

11 litres/100km

17 litres/100km

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Development Scenarios: Behaviour Adaptation

• “Low-Carbon Lifestyle”• Low-Carbon Lifestyle

Vehicle = 25% Bus =  35% Walk= 30% Bike = 10%

Bill Campbell ODT

High Efficiency Vehicles and Scooters

Risk to Essential Transport Activities

RECATS Method

Travel Activity

Energy Constraint

Calculate Energy Consumption

E2< E1?Modify

Travel ActivityNoE1

E2

15%

20%

25%

Walk

Bike

 

1960 1970 1980 1990 2000 2010 2020 2030 2040 20505

10

15

20

25

30

35

40

Year

Oil

Pro

duct

ion

(Bill

ion

Bar

rels

per

yea

r)

97%

85%

50%

15%

3%

Historic Projected

Supply probability

(Dantas et al, 2008, JEAST; NZTA Report)

Constrained Travel ActivityCalculate Risk

Yes

0%

5%

10%

5%

0 - 1

1 - 2

2 - 3

3 - 4

4 - 6

6 - 8

8 - 1

0

10 -

15

15 -

20

> 20

Trip Distance [km]

Bike

Bus

Vehicle Passenger

Vehicle Driver

Re Pe

T m, d, s

s

IW s

d

m

T m, d , s

s

IW s

d

m

Nms Nds Ntc Dm, d, s

s

IW s

d

m

1

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Strategic Analysis to 2050

Urban Form AdaptationsUrban Form

viour Adaptations

Active Infrastructure 100km Bikeways

Dense City Centre

Integrated Urban Villages

Current Urban Form

3 L/100kmFleet Efficiency

50% Biofuels Synfuels

Possible

No No No No

UnlikelyPossible Possible

AlternativesNot availableHigh costNot feasible

Changes+EfficiencyImprovements

High Riskof DoingNothing

Fuel, Vehicle, B

eha

50% Electric Vehicles

Low Carbon Lifestyle 

50 km of Electric Trolleys

NoUnlikely 

golf carts onlyNo No 

Unlikely

Yes Yes Yes

Possible Possible

Possible

Possible

Urban FormChanges+ Behaviour Changes

Nothing

Strategic Analysis Opportunities

Conclusion: There are no solutions, only choices

Automobilese of

Tra

nspo

rt

50%

100%

75%

Automobiles

Transportation System 1930 - 2050

Biofuel & Electric

Walk & Bike

Sha

re

25%

1930 1940 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050

Public Transport

Scooters

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Thank you for your attentionThank you for your attentionThank you for your attentionThank you for your attention

Engineering Research to Investigate and Mitigate Peak Oil RisksDr. Susan Krumdieck

Presentation to Walloon Parliament 26 April 2011 Namur, Belgium

Dense Urban Centre

• 50% Reduction in Commuting over 10 km50% Reduction in Commuting over 10 km• Loft Apartments• Pedestrian Zones• Amenity Apartments• Culture, Arts

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Integrated Urban Villages

• Village Centres: Shopping Medical• Village Centres: Shopping, Medical

• Activity Areas

• Weekend Markets

• 30% local business growth