Project Presentation to Land Transport New Zealand

1. Energy risks to activity
systems as a function of
urban form
Dr. André Dantas, Civil Engineering Department
Dr. Susan Krumdieck, Mechanical Engineering Department
Mr Shannon Page, Mechanical Engineering Department
Advanced Energy and Material Systems LabAdvanced Energy and Material Systems Lab

2. Presentation outline
• Discussion
•RECATS demonstration
•Case study findings
•RECATS model
•Context
•Energy supply analysis
•Risk analysis

3. Once upon the time, there was
an urban area ….
…. And the urban
area was changing
and growing…
t=1
t=2
t=n
And
growing
….

4. …and the more it was growing, the
more people had complex needs
Complex
commuting
patterns all
over the
city.
=1
t=2
t=n
Central
displacements
on foot;
Travel Demand
Long-
motorized
travel from
suburbs to
CBD;

5. …and the more people had
complex travel needs, ...
ENERGY crisis/shortage risks
???

6. Which urban
form
development
option minimizes
energy risks?

7. ?

8. Petroleum availability?
Alternative energy sources?
Transport technology?

9. Facts about Oil Resources
1930 1940 1950 1960 1970 1980 1990 2000 2010 2020 2030
60
50
40
30
20
10
BillionsofBarrelspery
Projected Discoveries
Discovery
Production
Energy supply analysis

10. World Oil Supply Situation
Sept 2005 Saudi’s Oil
Minister pledges (again) to
increase production
Oil production capacity remains
limited, leaving the market
vulnerable to shocks…
www.fin.gc.ca
High Price can cause oil shortages
in import-dependent economies
Philippines, Eritrea, Zimbabwe,
Nigeria, China, South Africa
Panic Buying can cause oil shortages
UK, USA, India, China
Energy supply analysis

11. Facts about NZ Oil Demand
Values in Gross Peta
Joules for the year
ending September 2005
Product Imports
Crude oil imports
(incl. condensate,
naptha and feed
stocks) International transport,
Industry & agriculture,
and other uses
50.0
Indigenous
production
33.0
Export
85.8
9
Losses, own use,
stock change and
exports
Domestic
Transport
Diesel 75.7
Motor
Gasoline 109.1
Av. Fuel &
others 21.6
231.30
Diesel 32.6
Gasoline 35.5
NZRC
Total refined
Products
311.0
Energy supply analysis

12. There is a Possibility
• Fuel Shortage
• High Price
Published January 14, 2003
2005 Minneapolis Star Tribune
Encarta.msn.com
That there will be a problem
Energy supply analysis

13. Peak Oil is a problem because…
It’s not accounted for in the original
design and operation
It is an issue we don’t have a plan to
deal with
Therefore it poses a RISK
Energy supply analysis

14. Peak Oil  Probability40
30
35
25
20
15
10
5
0
1900 1925 1950 1975 2000 2025 2050 21002075 2125
BillionsofBarrelsperyear
2005 2010 2015 2020 2025 2030
0
10
20
30
40
50
60
70
80
90
100
Probabilty(%)
Peak Oil
5% Reduction
7.5% Reduction
10% Reduction
15% Reduction
20% Reduction
Fuel Shortage
( ) ( )
( ) ( )
( )∑=
−
−





−−
−−+
=
Y
Y
yr
ry
yr
XCP
2005
2005
1
!1!2005
!20051
ρρ
Energy supply analysis

15. Probability of Fuel Shortfall
Shortage
10% Below 2005
2005 0%
2010 0%
2015 30%
2020 78%
2025 96%
2030 99.5%
Post Peak Oil Supply Decline neglecting cost or panic induced shortages
2005 2010 2015 2020 2025 2030
0
10
20
30
40
50
60
70
80
90
100
Probabilty(%)
Peak Oil
5% Reduction
7.5% Reduction
10% Reduction
15% Reduction
20% Reduction
Fuel Shortage
Energy supply analysis

16. Petroleum availability?
Alternative energy sources?
Transport technology?

17. Technology Substitutes or Alternatives?
 Alternative Vehicles
 Alternative Fuels
Alternatives don’t change the fact
that an oil shortage represents a
change in the amount of oil
currently being used.
Energy supply analysis

18. Petroleum availability?
Alternative energy sources?
Transport technology?

19. ?
PEAK OIL
AND THE SUBSEQUENT SUPPLY DECLINE

20. Risk to Transportation Activities?
Impacts on wellbeing?
Urban form and adaptability?
Essentiality?

21. Essentiality Metric
For Wellbeing
 Optional
 Necessary
 Essential
Risk Analysis

22. NumberofTrips
0
100
200
300
400
500
600
Essentiality
LevelsOptional Necessary Essential
Car
Bus
Walk
Bike
Trip Modes
Short
Distance Bins
Medium Long
Travel Demand
Risk Analysis

23. Opt Nec Ess Opt Nec Ess Opt Nec Ess
0
100
200
300
400
500
600
Short Distance Medium Distance Long Distance
TripsperDay(1000s)
Car
Bus
Walk
Bike
Opt Nec Ess Opt Nec Ess Opt Nec Ess
0
100
200
300
400
500
600
Short Distance Medium Distance Long Distance
TripsperDay(1000s)
Car
Bus
Walk
Bike
High Density
Low Density
Risk Analysis

24. Adaptation to Reduced Fuel Use
 Optional
 Necessary
 Essential
People will act to preserve wellbeing
Eliminate First
Eliminate Last
Eliminate Trips
Risk Analysis

25. Mode Shifting
 Walk
 Bike
 Bus (Public Transport)
 Car (Private Transport)
People will act to preserve
participation in activities
Function of Urban Form
Risk Analysis

26. Distance Shifting
 Neighbourhood
 Area
 Region
Function of Urban Form
People will act to preserve
participation in activities
Risk Analysis

27. Efficiency Shifting
 Share Rides
 Combine Trips or Modes
 Use or Purchase more
Efficient Vehicle
Function of Urban Form
People will act to preserve
participation in activities
Risk Analysis

28. Impact Assessment
 Loss of Essential Trip
 Loss of Necessary Trip
 Loss of Optional Trip
 Change of Mode
 Change of Destination
Risk Analysis

29. •Identify Risks
•Evaluate Impacts
•Mitigation Measures
•Implementation
Risk Analysis

30. Exploring Energy Constraint Impacts
 Impose a Fuel Shortage
 Choose an Urban Form
 Model Travel Demand
 Calculate Energy Demand
 Until Energy Demand = Supply
 Model Travel Behaviour Change
Opt Nec Ess Opt Nec Ess Opt Nec Ess
0
100
200
300
400
500
600
Short Distance Medium Distance Long Distance
TripsperDay(1000s)
Car
Bus
Walk
Bike
∑∑=
m d
ddmdm
DBECTDE ,,
*
Risk Analysis

31. Energy Constrained Activity Model
Travel Activity
RECATS Model
Implemented in MATLAB®
Energy Constraint
Calculate Energy
Consumption
E2< E1? Modify
Travel Activity
Constrained Travel Activity
Calculate Risk
Yes
NoE1
E2
Risk Analysis

32. Risk Assessment










−=
∑∑∑
∑∑∑
1
*
*
*
,,
,,
m d s
ssdm
m d s
ssdm
ee
IW
IWT
PR
Ψ
Risk = Probability * Impact
Probabilityofpeakhavingoccurred
2005 2010 2015 2020 2025 2030
0
0.02
0.04
0.06
0.08
0.1
0.12
ProbabilityofoilPeakinagivenyear
2005 2010 2015 2020 2025 2030
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Year Yeara) b)
Travel Activity
Energy Constraint
Calculate Energy
Consumption
E2< E1? Modify
Travel Activity
Constrained Travel Activity
Calculate Risk
Yes
NoE1
E2
1930 1940 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050
0
5
10
15
20
25
30
Risk Analysis

33. RECATS
Risk Analysis

34. Case Study, Christchurch 2041
What are the risks?
Scenario:
Probability Reduction event=20%

35. Case Study, Christchurch 2041
URBAN DEVELOPMENT OPTIONS AND MITIGATION MEASURES
Business As Usual Car Trips Lost
High
Risk=117
Opt Pur Ess Opt Pur Ess Opt Pur Ess
0
100
200
300
400
500
Short Distance Medium Distance Long Distance
TripsperDay(1000s)
Car
Bus
Walk
Bike
• Optional Trips must be reduced by 84%
• Necessary trips must be reduced by 1%
• 17% reduction in car travel

36. Option A – Centralized
development
Car Trips Lost
Low
Risk=105
Case Study, Christchurch 2041
Opt Pur Ess Opt Pur Ess Opt Pur Ess
0
100
200
300
400
500
Short Distance Medium Distance Long Distance
TripsperDay(1000s)
Car
Bus
Walk
Bike
URBAN DEVELOPMENT OPTIONS AND MITIGATION MEASURES
• Optional Trips must be reduced by 74%
• Necessary trips must be reduced by 2%
• 15% reduction in car travel

37. Option B – Hybrid-Corridor
based development Car Trips Lost
Moderate
Risk=110
Case Study, Christchurch 2041
Opt Pur Ess Opt Pur Ess Opt Pur Ess
0
100
200
300
400
500
Short Distance Medium Distance Long Distance
TripsperDay(1000s)
Car
Bus
Walk
Bike
URBAN DEVELOPMENT OPTIONS AND MITIGATION MEASURES
• Optional Trips must be reduced by 72%
• Necessary trips must be reduced by 2%
• 16% reduction in car travel

38. URBAN DEVELOPMENT OPTIONS AND MITIGATION MEASURES
Option C – Urban sprawl
Car based development Car Trips Lost
Very High
Risk=126
Case Study, Christchurch 2041
Opt Pur Ess Opt Pur Ess Opt Pur Ess
0
100
200
300
400
500
Short Distance Medium Distance Long Distance
TripsperDay(1000s)
Car
Bus
Walk
Bike
• Optional Trips must be reduced by 84%
• Necessary trips must be reduced by 1%
• 17% reduction in car travel

39. Impact of Shortages
0
20
40
60
80
100
120
140
1 2 3 4
Scenario
Risklevel(Re)
Option BAU Option A Option B Option C
7% 10% 15% 20%
Case Study, Christchurch 2041

40. Conclusions
•RECATS: a planning tool to assess future scenarios of urban
development forms.
•Transport energy: a critical sustainability issue.
•Energy supply analysis: probabilities of future disruption scenarios.
•Greater Christchurch 2041: urban development options subject
to different energy risk levels.
•Limitations and further studies: limited data on travel behavior
in energy constrained situations.

41. Acknowledgements
End-user organisations:
 Christchurch City Council
 Environment Canterbury
 Urban Development Strategy Forum
 Combined Owner Driver Association
 MWH Global
This research project was funded by

42. Dr. Susan Krumdieck
Susan.Krumdieck@Canterbury.Ac.Nz
Advanced Energy and
Material Systems Lab
Interdisciplinary research effort to develop the theory,
models, information, ideas, technology and planning
tools for New Zealand to begin the journey toward a
Sustainable Civilization.
Dr. André Dantas
Andre.Dantas@Canterbury.Ac.Nz