Overview of the potential for modal shift, insights on costs/benefits, details on modal shift policies and possible sources of funding
Lew Fulton
Institute of Transportation Studies
University of California, Davis
IEA 2015 Energy efficiency
training week
10 June, 2015
Key themes
• Planning (compact cities, transport integration in land
use planning - e.g. transit oriented development),
• Taxation and charges (fuel taxation, CO2 taxation,
cordon pricing, congestion charging, parking fees, road
pricing for freight),
• Regulations (access restrictions - eventually time
related, e.g. for freight deliveries, reserved/dedicated
lanes),
• investments (public transport infrastructure, subsidies
to public transport operations).
What is modal shift? Why do we care?
• Modal shift is the changing of travel patterns by
mode – not necessarily more or less travel, just
different
• Different modes have different characteristics
– Cost
– Energy efficiency, CO2 rates
– Space efficiency
– Speed, comfort, door-to-door convenience
– Safety, security
– Availability
Why do cars often dominate urban travel?
• In most countries, those who can afford to buy a
motorbike or a car do, and then travel by car for a
large share of their trips
• Seen as fast, convenient, comfortable, low
(marginal) cost, high status
• Public transport seen as slow, uncomfortable, high
marginal cost, low status
• Changing this picture requires shifting all these
variables for both modes.
Seite 5 Source: City of MünsterMu
Traditional focus was given to road design: More infrastructure for cars, more space for motorized vehicles, unsustainable focus: Question is, how to use limited road space best
Tackling the Problem
Seite 6
Equivalency road width: In order to carry 20,000 automobile commuters PHPD, a highway must be at least 18 lanes wide.
(assumption 1.2 passengers per automobile)
19000 1500-
2000
Mixed
Traffic
40000 –
60000
Heavy Rail/
Metro
60000 –
90000
Suburban
Rail (e.g. Mumbai)
14000
Cyclists
9000
BRT
single lane Pedestrians
5000
Regular
Bus
??
BRT
double lane
Light Rail
18000 –
20000
(people per hour on 3.5 m wide lane in the city – PPHPD [PAX/hour/direction])
Source: Botma & Papendrecht, TU Delft 1991 and own figures
PPHPD
Range ()
2000 8000 14000 17000,
Curitiba
19000 20000 43000,
Bogota
80000,
HKK >100000,
Mumbai
Maximum
PPHPD
achieved&
where ()
Why public transport priority? Corridor Capacity
Characteristics of modes
A way of imaging changes in mode shares
Modal shares by trip distance
Source: IEA (2009), transport, energy and CO2. Moving towards sustainability
Mode shares by income group vary considerably
Shares vary even for the highest income groups,
depending on country
BRT impacts on modal shift and CO2
Table 1 : BRT Length and Costs
BRT Country BRT (KM) Financed Cost Million USD
Ahmedabad India 59.0 Indian Government 106
Cebu Philippines 16.0 Co-funded by Climate Technology Fund
152
Guangzhou China 23.0 Chinese Government 146
Pimpri India 19.2 Co-funded by Global Environment Facility
147
Sudhir Gota, 2014, Changing Do-nothing Baselines for Transport
Investments, paper written as Lee Schipper Scholar (2013)
Gota analysis – BRT impacts on CO2
Figure 1 : BRT Daily Ridership/kilometer
Gota analysis – BRT impacts on CO2
Table 2 : BRT Modeshift, Trip length and Occupancy details at Starting Year
BRT Starting Year
Ahmedabad Cebu Pimpri Guangzhou
Mo
de
Shif
t
Trip
Len
gth
Occ
up
ancy
Mo
de
Shif
t
Trip
Len
gth
Occ
up
ancy
Mo
de
Shif
t
Trip
Len
gth
Occ
up
ancy
Mo
de
Shif
t
Trip
Len
gth
Occ
up
ancy
Cars 2% 11 1.1 14% 6 2 2% 6.4 1.42 20% 20 2
2-Wheeler 12% 5.6 1 18% 6 1 12% 6.4 1.09
3-Wheeler 38% 5.3 3 38% 6.4 1.9
Taxi 5% 2 7% 10 3
Normal bus 47% 12 28 47% 6.4 35 72% 12 45
Minibus 63% 6 16
Cycling 1% 1% 6.4 2% 7
BRT 8 45 6 40 6.4 45 12 54
Gota analysis – BRT impacts on CO2
Figure 2: BRT Vehicle Kilometer Travel and CO2 Emissions Savings
Gota analysis – BRT impacts on Infrastructure
Figure4: BRTS and Avoided Infrastructure Costs
Global High Shift Scenario Project
• During 2013-2014, ITDP and UCD developed an
Urban Model and created a “High Shift” scenario,
toward much greater use of public and active
transport, for global cities
• Report published in November 2014, presented at
COP in Lima
2
Analysis Approach
• Global travel projected to 2050 using an urban
model adapted from the International Energy
Agency’s Mobility Model
• World modeled at level of 33 countries/regions
• Detailed reporting for 13 groupings with major
economies like the U.S., China and India broken
out.
• More detailed breakouts and analysis of urban
travel modes than MoMo
• Modal shift based on potential to boost capacity of
transit/NMT systems to allow fewer cars
5
Comparison of Two Scenarios
• “High Shift” Scenario:
• Projection of cities by size through 2050
• Increased rapid transit km per million population
• Encourage walking and cycling for short trips
• E-bikes expand in lieu of motor cycles and some cars
• Preserve total projected growth in personal mobility in
low and middle income (non-OECD) countries to 2050
• Cut car travel in cities by half by 2050 in High Shift
scenario compared to Baseline Scenario
• “Baseline” Scenario aligns with the IEA 4 degree scenario
• About 25% improvement in fuel economy to 2050
(slight additional improvements in High Shift scenario)
• No shift away from car growth trends
• Other modes static or slow growth
6
The efficiency of vehicles improves slowly in the
scenario
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
2010 2050 Base 2050 HS
Ener
gy E
ffic
ien
cy m
j/vk
m
LDV
2-3W
Urban bus
BRT
Minibus
Metro
Tram/LRT
Commuter rail
e-bike
Energy per pkm – big advantage for transit, but
declining over time
0.000
0.005
0.010
0.015
0.020
0.025
2010 2050 Base 2050 HS
OECD
Ener
gy E
ffic
ien
cy m
j/p
km
LDV
2-3W
Urban bus
BRT
Minibus
Metro
Tram/LRT
Commuter rail
e-bike
cycle
Combined length of transit systems to 2050
OECD non-OECD OECD non-OECD OECD non-OECD OECD non-OECD OECD non-OECD
Metro 6,336 4,883 6,970 6,103 7,604 7,324 9,078 18,922 11,820 32,962
BRT 574 1,910 862 3,820 1,149 5,729 4,740 35,781 8,905 69,652
Tram/LRT 10,221 7,983 11,243 9,979 12,266 11,975 13,516 15,896 16,810 23,809
Commuter rail 28,915 4,967 31,806 6,209 34,698 7,450 43,478 40,488 58,040 76,009
2010
4DS High Shift
2030 2050 2030 2050
0
20
40
60
80
100
120
140
160
OEC
D
no
n-O
ECD
OEC
D
no
n-O
ECD
OEC
D
no
n-O
ECD
OEC
D
no
n-O
ECD
OEC
D
no
n-O
ECD
2030 2050 2030 2050
2010 4DS Current Case
Tho
usa
nd
Km
s
Metro BRT Tram/LRT Commuter rail
High Shift
Rapid Transit per Resident (RTR) to 2050
OECD non-OECD OECD non-OECD OECD non-OECD OECD non-OECD OECD non-OECD
Metro 7.1 1.8 6.8 1.5 6.9 1.4 8.8 4.8 10.7 6.4
BRT 0.6 0.7 0.8 1.0 1.0 1.1 4.6 9.0 8.1 13.5
Tram/LRT 11.5 3.0 10.9 2.5 11.1 2.3 13.2 4.0 15.2 4.6
Commuter rail 32.5 1.9 31.0 1.6 31.5 1.4 42.3 10.2 52.6 14.8
2010
4DS High Shift
2030 2050 2030 2050
Kilometers of system per million residents
The Base and High Shift Scenario
Doubling of public transport and NMT urban travel and
about a halving of LDV travel in 2050 v. Baseline
8
0
5
10
15
20
25
30
35
40
45
2010 2050Base
2050HS
2010 2050Base
2050HS
OECD non-OECD
ann
ual
PK
m (
trill
ion
s)
Walk
Cycle
e-bike/scooter
Commuter rail
Tram/LRT
Metro
Minibus
BRT
BRT Feeder bus
Urban bus
ICE 2Ws
LDV
High Shift Scenario – travel per capita
Total travel in non-OECD preserved, travel reduced some in OECD
9
0.0
2.0
4.0
6.0
8.0
10.0
12.0
2010 2050Base
2050HS
2010 2050Base
2050HS
OECD non-OECD
Tho
usa
nd
PK
m p
er c
apit
a
Walk
Cycle
e-bike/scooter
Commuter rail
Tram/LRT
Metro
Minibus
BRT
BRT Feeder bus
Urban bus
ICE 2Ws
LDV
High Shift Scenario – Spotlight on Asia
Rapid growth in urban bus travel, big drop in ICE 2W travel
9
0
2
4
6
8
10
12
20
10
20
50
Bas
elin
e
20
50
HS
20
10
20
50
Bas
elin
e
20
50
HS
20
10
20
50
Bas
elin
e
20
50
HS
20
10
20
50
Bas
elin
e
20
50
HS
20
10
20
50
Bas
elin
e
20
50
HS
20
10
20
50
Bas
elin
e
20
50
HS
20
10
20
50
Bas
elin
e
20
50
HS
20
10
20
50
Bas
elin
e
20
50
HS
UnitedStates
Europe OECD Pacific OtherAmericas
China India Other Asia Africa/Middle East
Trill
ion
PK
m
walk
cycle
e-bike
Commuter rail
Tram/LRT
Metro
Minibus
BRT
Urban bus
Motor 2W
LDV
High Shift Scenario – travel per capita for Asia
Convergence toward 8000 kms per person per year
9
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.02
01
0
20
50
Bas
elin
e
20
50
HS
20
10
20
50
Bas
elin
e
20
50
HS
20
10
20
50
Bas
elin
e
20
50
HS
20
10
20
50
Bas
elin
e
20
50
HS
20
10
20
50
Bas
elin
e
20
50
HS
20
10
20
50
Bas
elin
e
20
50
HS
20
10
20
50
Bas
elin
e
20
50
HS
20
10
20
50
Bas
elin
e
20
50
HS
UnitedStates
Europe OECD Pacific OtherAmericas
China India Other Asia Africa/Middle East
Tho
usa
nd
Pkm
pe
r ca
pit
a
walk
cycle
e-bike
Commuter rail
Tram/LRT
Metro
Minibus
BRT
Urban bus
Motor 2W
LDV
High Shift Scenario: Bus, Rail, Bike, E-Bike, Walk Travel
Total Passenger Kilometers
Travel (PKT) for bus, rail,
walk, bike, and e-bike by
year and scenario
8
Public and Private Direct Costs
High Shift Scenario lowers total costs in all categories
3
• Vehicle purchase costs (all modes)
• System infrastructure costs (road, rail)
• Vehicle and system operating costs
• Fuel costs (liquid fuel, electricity)
$0
$50
$100
$150
$200
$250
$300
$350
OECD non-OECD OECD non-OECD OECD non-OECD OECD non-OECD
2010-2030 2010-2050 2010-2030 2010-2050
Base High Shift
Tri
llio
n U
S D
olla
rs
User costs by Scenario and region, summed across time periods
Vehicle purchase Fuel purchase O&M expenses Infrastructure construction
Distribution of Car Ownership by Income
Car ownership is lower for all income groups under High Shift,
but becomes slightly more equitably distributed than under BAU
3
0
100
200
300
400
500
600
Baseline High Shift Baseline High Shift
2010 2050 2010 2050
OECD Non-OECD
LDV
s p
er 1
00
0 r
esid
ents
Lowest 20% Second 20% Third 20% Fourth 20% Highest 20%
Impacts on Equity of Access to Mobility
3
Under High Shift Scenario vs. Business-As-Usual:
• Public transport mobility of poorest 20% triples
• Public transport mobility of 2nd
poorest 20% doubles
0
2
4
6
8
10
12
Low
est
20
%
Seco
nd
20%
Thir
d 2
0%
Fou
rth
20
%
Hig
hes
t 2
0%
Low
est
20
%
Seco
nd
20%
Thir
d 2
0%
Fou
rth
20
%
Hig
hes
t 2
0%
Low
est
20
%
Seco
nd
20%
Thir
d 2
0%
Fou
rth
20
%
Hig
hes
t 2
0%
Low
est
20
%
Seco
nd
20%
Thir
d 2
0%
Fou
rth
20
%
Hig
hes
t 2
0%
Low
est
20
%
Seco
nd
20%
Thir
d 2
0%
Fou
rth
20
%
Hig
hes
t 2
0%
Low
est
20
%
Seco
nd
20%
Thir
d 2
0%
Fou
rth
20
%
Hig
hes
t 2
0%
2010 2050 Baseline 2050 High Shift 2010 2050 Baseline 2050 High Shift
OECD Non-OECD
tho
usa
nd
kilo
me
tres
per
cap
ita
LDV Motorized 2W Bus/Rail Transit walk/cycle/e-bike
Impact on urban passenger transport CO2 emissions
Compared to baseline scenario for 2050, High Shift
scenario would also cut global warming pollution
• Cut annual CO2 emissions 1.7 GT (40%)
• Cut cumulative 2015-2040 CO2 emissions 25 GT (25%)
3
Impact on urban passenger transport CO2 emissions
3
Opportunities for CO2 reduction in both rich and poor
countries, benefits ramping up especially in 2030-2050
High Shift Scenario - In Summary
3
More investment in clean urban public transport, walking,
and cycling between now and 2050 could:
• Cut cumulative public and private urban transportation
costs by $114 trillion, with biggest savings in non-OECD
• Boost public transport mobility of poorest 20% by 300%
• Cut annual CO2 emissions from urban passenger
transport by 1.7 GT in 2050, a 40% drop
• Cut cumulative CO2 emissions from urban passenger
transport by 25 GT 2015-2050, a 25% drop
• Yield growing cost savings and CO2 savings over time
• Develop only if there is increased private sector and
government support & investment in public transport
How to make modal shift happen? Push and Pull
3
Pull Push
Invest heavily in high-quality bus and rail transit systems
Increase the cost of car use!
Hi quality Infrastructure for walking and cycling
Tax vehicle ownership
Land use macro: encourage growth in transit-oriented way,
better integrate, improve institutional framework
Fuel pricing
Land use micro: connectivity between transit and NMT, streetscapes, walkability
Road pricing, parking pricing and restrictions
Support for cultural change Restricted car use zones
How to pay for all the infrastructure?
3
Answer – cross subsidize
• Vehicle sales taxes or registration fees
o Can be based on CO2 emissions, and raise
revenues for sustainable transportation projects
o California is using it’s revenues from Cap and
Trade law in part to build high-speed rail
o Co2 related vehicle taxation
• Fuel taxes
• Road pricing – can be differentiated across modes
• There are a range of types of pricing schemes
• There are many other potential revenue sources…
Top priority – reduce fuel subsidies where they exist
3
Potential Revenue Sources
3
Source: Victoria Transport Policy Institute, 2015 (vtpi.org)
Comparison of road pricing systems
3
Name Description Objectives Road toll (fixed rates)
A fixed fee for driving on a particular road. To raise revenues.
Congestion pricing (time-variable)
A fee that is higher under congested conditions than uncongested conditions, intended to shift some vehicle traffic to other routes, times and modes.
To raise revenues and reduce traffic congestion.
Cordon fees Fees charged for driving in a particular area. To reduce congestion in major urban centers.
HOT lanes A high-occupant-vehicle lane that accommodates a limited number of lower-occupant vehicles for a fee.
To favor HOVs compared with a general-purpose lane, and to raise revenues compared with an HOV lane.
Distance-based fees
A vehicle use fee based on how many miles a vehicle is driven.
To raise revenues and reduce various traffic problems.
Pay-As-You-Drive insurance
Prorates premiums by mileage so vehicle insurance becomes a variable cost.
To reduce various traffic problems, particularly accidents.
Road space rationing
Revenue-neutral credits used to ration peak-period roadway capacity.
To reduce congestion on major roadways or urban centers.
Public-Private Partnerships (PPPs)
3
• PPPs involve private financing and ownership of publically
used infrastructure and systems, allowing private capital to
help fund public goods.
• PPP is constrained for transport. Barriers common in many
low and middle income countries include:
o Laws that prohibit foreign involvement in certain sectors or
private operation of government-owned assets,
o Deficient PPP contracts that may transfer excessive risk thus
deterring a wide pool of bidders or greatly increase the cost of
private capital, and a changeable policy environment.
o Institutional investors, who could potentially increase
investments in sustainable transport, have not always well
defined sustainability criteria for their investments.
Recommended Finance-related Actions
3
• Improve regulatory and investment frameworks, remove perceived
risks, and enhance government and private sector capacity.
• Enhance governments’ efforts to expand the pool of well prepared
sustainable transport projects.
• Aggregate sustainable transport investment options that in their
own right are too small to attract large scale financing.
• Use fiscal instruments and user charges to broaden and deepen
revenue sources while reducing demand for unsustainable
transport.
• Better align prevailing fiscal rules and developing sustainable
transport.
• Promote innovative regional financing mechanisms that achieve
scale by targeting benefits to multiple countries, rather than
focusing on financing directed to individual countries.
(from UN draft report to HAGST, 2015)
