6/12/2018

1

Global Transport: Challenges & Opportunities

TU-Graz Lectures for the Course“Energy Systems Analysis”

June 2018

David McCollumResearch Scholar

IIASA Energy Program

Source: https://www.freepik.com/free-vector/transport-elements-collection_1170138.htm

Sonia Yeh, Sustainable Energy Futures, 2017

How people traveled in 2005 (Mode Shares)

PKM: passenger kilometer

Source: S. Yeh

6/12/2018

2

Source: Schäfer, Heywood, Jacoby, Waitz (2009)

Travel Time Budget: Stability (Zahavi, 1970s)

Travel Time Budget: Stability (Marchetti, 1994)

Time-use surveys, 1965/66 and early 2000sRome in the Middle Ages

Travel

Personal care & meals

Household & family care

Leisure & study

Sleep

Rome in the Middle-Ages and today

Sources: Schäfer

Work = ↓

Sleep, leisure/study, personal care, meals = ↑

Travel = ~~

2-3 km

10 km

C. Marchetti: City boundaries grow at rate proportional to avg. speed of fastest mode => 1 round-trip per day to city center in ~1.2 hr.

Travel Money Budget:Transport continues to become more affordable

Source: Schäfer, Heywood, Jacoby, Waitz (2009)

In 1882, average cost of rail travel in US was $0.20 (in 2000$). By 2020 only $0.05.Meanwhile, GDP/cap increased by 10x.

Air transport => biggest decline since 1950 (by 2/3rd)

Travel Money Budget => 5-10% of GDP spent on travel, increasing w/ GDP

6/12/2018

3

Growth in Global Mobility (1950‐2005)

Source: Schäfer, Heywood, Jacoby, Waitz (2009)

Shift from Slow to Fast (1950‐2005)

Source: Schäfer, Heywood, Jacoby, Waitz (2009)

Where are we heading?

Sources: https://uberexpansion.com/uber-provides-helicopter-flights/, https://skift.com/2017/08/19/private-jet-companies-and-airlines-know-how-to-profit-from-the-eclipse/

6/12/2018

4

Example Implication: “Peak Car” in the US

0

5000

10000

15000

20000

25000

1960 1970 1980 1990 2000 2010 2020 2030 2040 2050

Au

tom

ob

ile T

raffi

c V

olu

me

per

Ca

pita

, pk

m

Year

Source: Schäfer and Victor (2000)

Air Travel Demand

Source: Schäfer (2017)

•Benefits of mobility include…•Education•Employment•Connect markets (labor/manufacturing to consumers)

•Tourism•Recreation•…

Why do we travel?

6/12/2018

5

What problems does transport cause?

Source: J. Axsen

Congestion

Economic losses

Oil dependence

Air pollution

Climate change

Sonia Yeh, Sustainable Energy Futures, 2017

Global transport energy consumption – by mode

2W & 3W

Bus

Cars and light trucks

Heavy-duty trucks

Passenger rail

Air travel

Domestic shipping and rail

International shipping

Fu

el c

on

sum

ed

(E

J/yr

)

2010

Source: S. Yeh

Global transport energy consumption – by mode and fuel

Source: IPCC AR5 WG3, Figure 8.5

6/12/2018

6

Global transport GHG emissions – by mode

Source: IPCC AR5 WG3, Figure 8.1

Road transport(mostly passenger, but freight growing quickly)

Air transport

Water transport

Rail transport

Note: Indirect emissions from production of fuels, vehicle manufacturing, infrastructure construction etc. are not included.

Global transport GHG emissions – by region

Source: IPCC AR5 WG3, Figure 8.3

Why all these problems in transportation?

EngineersInefficient technology, lack of good alternatives

Economists: Market failuresEnvironmental externalities (GHG emissions, air pollution)

Common pool resources (too much congestion)

Consumers undervalue fuel savings

PsychologistsIdentity, attitudes, social norms, habit

Sociologists, geographersThe broader “system” (industry, policy, infrastructure), lock-in

Urban plannersLand-use problems, need for high-density

Source: J. Axsen

6/12/2018

7

The solutions?(focus on GHGs)

The ‘legs of the stool’ represent the different ‘levers’ available for reducing transport GHGs

Source: https://www.fhwa.dot.gov/environment/sustainability/energy/workshops_and_peer_exchanges/seattle_10_2008/gccseattle.cfm

3- (or 4-) legged stool

Transportation GHG policy cantarget specific “legs of the stool”

Transportation GHGs = (GHG/MJ) x (MJ/km) x (km/person) x (# of people)

1. Transform fuels (reduce GHG/MJ): reduce carbon intensity of fuel via fuel switching– Replace gas with lower carbon fuels (e.g., electricity, biofuels)

2. Transform vehicles (reduce MJ/km): improve vehicle fuel efficiency– E.g. smaller, down-weighted, more efficient, hybridized

3. Transform behaviour (reduce km/person): decrease demand for motorized mobility (i.e., VMT) – Change land-use management (more mixed and dense

land-use, ‘walkable’ and ‘bike-friendly’, transit-oriented)

– Encourage mode switching (e.g., transit use)

– Gas tax, tolls, ‘pay per km’ insurance, allow congestion…

Travel/Behaviour

Source: J. Axsen

6/12/2018

8

‘ASIF’ decomposition (Schipper et al., 2000)

Source: IPCC AR5 WG3, Figure 8.2

A I F S

Relevance: Greenhouse Gas Emissions

GGE = GGE

EE

PKTPKT

Advanced Technologies

6/12/2018

9

The future of transportation

What will it look like in 2030-50?

This?

Source: J. Axsen

Alternative Fuel Vehicle Pathways

Source: https://www.featurepics.com/online/Alternative-Fuel-Race-Hybrid-Hydrogen-Etc-1225502.aspx

Source: Hwang (2013)

Biomass Biofuels

Flex Fuel Vehicle

The future of transportation

What will it look like in 2030-50?

The “3 Revolutions”

Electric?

Autonomous?

Shared?

Source: J. Axsen

6/12/2018

10

#1: Electric VehiclesCountries with the most electric vehicles

Source: IEA Global EV Outlook 2018

Stock

Sales

53 kWh24 kWh

16 kWh

Types of plug-in electric vehicles (PEVs)

4 kWh

~100-150 km electric range

Nissan Leaf

~56 km ~500 km gasoline

+300km electric range

Tesla Roadster

Toyota Prius PHV

Chevy Volt (Opel Ampera)

20 km ~800 km gasoline

Plug-inHybrid(PHEV)

BatteryElectric(BEV)

Comparing Battery Sizes:Source: J. Axsen

EV benefits depend on upstream electricity supply

LifecycleGHGsg/km

Conventional

Hybrid

PEVs

PEV

Note: Alberta is only getting

cleaner over time

PEVs

Conventional

Hybrid

Source: J. AxsenHydropower

Coal,Natural gas

Renewables, Nuclear, Natural gas

6/12/2018

11

#2: Autonomous vehicles (AVs)

Fully Autonomous

Source: J. Axsen

Huge uncertainty about the ultimate impact of AVs

“Utopia”• Fewer accidents

• Platoons of self-driving trucks

• Need fewer parking spots

• No wasted commuting time

• Reduce congestion(?)

• More accessible for variety of “drivers”

“Dystopia”• Could increase # of vehicles

• Could increase total VMT (circle the block?)

• May not be electric

• Safety / computer malfunctions

• Truck and taxi drivers out of work

Source: J. Axsen

AVs can create “heaven or hell”:cut GHGs by 50%...or double them!

Save Energy

Extra Energy

Source: Wadud et al., 2016: https://doi.org/10.1016/j.tra.2015.12.001Source: J. Axsen

6/12/2018

12

#3: Shared mobility

Source: J. Axsen

Combine the “3 Revolutions”to save the world?

Source: J. Axsen

Source: J. Axsen

6/12/2018

13

Botma & Papendrecht, TU Delft 1991 & GIZ

22 000 80 0009 0002 000 14 000 17 000 19 000

BRT –Single Lane / Articulated Bus

Heavy Rail(e.g. Hong Kong)

Light Rail

Corridor Capacity(people per hour on 3.5 m wide lane in the city)

Source: Creutzig

Bus Rapid Transit (BRT)

Seto et al., IPCC Ch. 12 (2014)

Source: Creutzig

Policies

6/12/2018

14

What policies can support AFVs?

Purchase incentives Rebates, tax breaks, fee reductions

Non-monetary benefits Carpool lane access, free parking

Chargers Home: incentives, building codes, streamlined permittingWork: workplace incentivesPublic: deployment, incentives

Demand-focused policies

ZEV mandate Direct AFV deployment requirements

Efficiency standards Fuel economy credits for AFVs

Low-carbon fuel standard Carbon reduction credits for electricity sold

R&D support Funds for various research activities

Supply-focused policies

Adapted from: Melton et al. (2017), Energy PolicySource: J. Axsen

Multi-pronged efforts to promote advanced vehicle adoption are more effective than a single sectoral or economy-wide policy

Sectoral strategies and policies

Targets for cumulative vehicle sales, sales quotas, vehicle mandates

Vehicle efficiency or emission standards

Vehicle sales incentives (purchase subsidies, tax credits, fee‐bates, reduced registration fees)

Vehicle manufacturer support (RD&D, production subsidies)

High transport fuel taxes (also carbon taxes or pricing)

Government and company vehicle procurement policies, other demonstration & test fleets

Trialling in car clubs or car‐sharing networks

Recharging and refuelling public infrastructure investments

Workplace or home charging incentives

Preferential parking or roadway access; reduced congestion charges or tolls

Promotions, social marketing, outreach, information campaigns

Consumer preferences

Financial Upfront 

capital cost

+ ++ ++ +

Fuel cost + ++ + +

Non‐financial

Risk aversion

+ + + ++ ++ + ++

Model variety

++ + + + +

Refuelling availability

+ + ++ ++ ++ ++ +

Range anxiety

+ + + ++ ++ ++

Example countries where strategies and policies have been implemented

Norway, Netherlands, UK, USA (10 states with California mandates), China, France, Germany

Norway, Netherlands, UK, USA, Japan, China, France, Germany

Norway, Netherlands, UK, USA, Japan, China, France, Germany

Norway, Netherlands, UK, USA, Japan, China, France, Germany

Norway, Netherlands, UK, France, Germany

UK, USA, Japan, China, France

France, Germany, Netherlands, USA

Norway, Netherlands, UK, USA, Japan, China, France, Germany

USA, France

Norway, Netherlands, UK, USA, Japan, France, Germany

Norway, Netherlands, UK, USA, Japan, China, France, Germany

Notes: ++ indicates a strong or direct influence on consumer preference; + indicates a weak or indirect influence on consumer preference; based on authors’ assessment. The selection of countries here represented >90% of global electric vehicle sales in 2014.

Strong coordination needed across different levels of government (national, state/provincial, and local)

Are efficiency standards for passenger LDVs stringent enough? … perhaps so …

US 2025[2]: 1.3EU 2021: 1.2

China 2020[1]: 1.5

India 2021: 1.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

2000 2005 2010 2015 2020 2025

MJ

/km

(n

orm

ali

zed

to

CA

FE

Te

st

Cyc

le)

US EU Japan China India

Source: the ICCT: „Global Comparison: Light‐duty Fuel Economy and GHG“ (May 2014 update, http://transportpolicy.net/)

Solid lines: historical performanceDashed lines: enacted targets Dotted lines: proposed targets or targets under study

[1] China's target reflects gasoline vehicles only. The target may be higher after new energy vehicles are considered. [2] The U.S. standards are fuel economy standards set by NHTSA, which is slightly different from GHG stadards due to A/C credits.[3] Supporting data can be found at: http://www.theicct.org/info‐tools/global‐passenger‐vehicle‐standards.

PASSENGER CARS ONLY

6/12/2018

15

• Governments across the world have set ambitious targets for EVs. (Collectively, by 2025, sales of ~7 million per year, or ~30 million cumulative stock … compared to >1000 million passenger vehicles globally at present)

• Automakers also have big plans. (e.g., VW Group has pledged that BEVs will comprise 20-25% of its annual sales by 2025; 2-3 million per year.)

• A consortium of companies, governments, and other organizations announced at the 2015 United Nations Climate Change Conference (COP 21) the “Paris Declaration on Electro-Mobility and Climate Change and Call to Action”.

Ambitious targets for electric-drive vehicles have been announced

Source: http://newsroom.unfccc.int/media/521376/paris-electro-mobility-declaration.pdf

Stated targets:• 100 million electric-drive LDVs by

2030 (~ 3 million at end-of-2017)• 400 million electric-drive 2/3-wheelers

by 2030 (~250 million today)

Transport mitigation measures in NDCs• 75% of NDCs explicitly identify

transport as a mitigation source (among 160 NDCs, 2016-Aug-01)

• 63% propose trans. mitig. measures

• 9% include transport emission reduction targets

• 12% include assessments of country-level transport mitigation potential

• Strong bias toward passenger transport: included in 91% of NDCs identifying specific transport modes, while freight is only in 29%.

• High-speed rail (2%), aviation (5%), and walking and cycling (14%) receive less attention.

• High-income countries => vehicle eff. standards and biofuels/elec/H2

• Low/middle-income countries => [eff./fuels] + public transport, vehicle import restrictions, ‘green’ freight

Source: http://www.ppmc-transport.org/overview_indcs/

Based on analyses by SLoCaT, Ricardo, GIZ, and German BMUB

Mixed urban development reduces travel demand

Seto et al., IPCC Ch. 12 (2014)

Source: Creutzig

6/12/2018

16

Land use policies to reduce urban emissions

Seto et al., IPCC Ch. 12 (2014)

Source: Creutzig

Push policies• Car traffic restrictions• City toll• Reduce available lanes• Parking fees• Speed limits

Pull policies• Better public transport• Safe space for cycling and

walking• Prioritisation of bicycles• Bicycle racks

Land use policies• Compact cities• Polycentric cities• Avoid urban sprawl• No greenfield development• Mixed use neighbourhoods

Source: Creutzig

Transport and the UN’s Sustainable Development Goals (SDGs)

Source: https://sustainabledevelopment.un.org/

Road traffic accidentsAir quality

Energy efficiency

Reliable/resilient infrastructure

Public transport

Transport (fossil) fuel subsidies

6/12/2018

17

Future scenarios

Transport mitigation requirements for 2°C target

Transport: A Roadblock to Climate Change Mitigation?F. Creutzig, P. Jochem, O. Edelenbosch, L. Mattauch, D. P. van Vuuren, D. McCollum, J. Minx (2015)Science, 350(6263), 911-912

Source: Creutzig

Working Group III contribution to the IPCC Fifth Assessment Report

Mitigation burden of transport sector impacts, and is impacted by, mitigation elsewhere in the system.

51

Source: IPCC AR5 WG3, Figure SPM.7

~2 ºC || including CCS

6/12/2018

18

Working Group III contribution to the IPCC Fifth Assessment Report

Transport mitigation burden could either be light or heavy before 2050.

52

~2 ºC || no CCS

Source: IPCC AR5 WG3, Figure SPM.7

Urban policies to halve global transport emissions by 2050

• Halving of transport sector GHG emissions until 2050 possible but ambitious; requires high CO2 price, efficiency standards, and additionally: rapid electrification, and strong urban policies

• Multiple behavioral options for reducing GHG emissions in the transport sector to support urban solutions

• Especially endogenous preferences point to wider implications for economic theory

Creutzig et al., Science 2015Mattauch et al., TRD, 2015

Source: Creutzig

Different communities and their approach to climate change mitigation

Evolving Narratives of Low‐Carbon Futures in Transportation (2015) F. Creutzig, Transport Reviews

Source: Creutzig

6/12/2018

19

Comparing narratives of three transport communities

Evolving Narratives of Low-Carbon Futures in Transportation (2015) F. Creutzig, Transport Reviews

Methodological Focus, objectives, and solutions influence each other

Source: Creutzig

Which ‘levers’ hold the biggest potential, or could/should be pulled hardest? …not entirely clear…

• ‘Economics-based’ IAMs (GCAM and MESSAGE) favor low-carbon fuels. [endogenous]

• ‘Expert-based’ transport-only models (MoMo and Roadmap) favor vehicle efficiency improvements. [exogenous]

• Changes in activity / behavior (mode-shifting, demand avoidance) are more pronounced in MoMo and Roadmap.

• MoMo and Roadmap see the transport sector bearing a greater mitigation burden than GCAM and MESSAGE.

Results from the iTEM global transport-energy model comparison (Yeh et al., 2016)

2 integrated assessment

models (‘economics-

based’)

2 transport-only models

(‘expert-based’)

Future global transport CO2 emissions –comparing different kinds of models

Source: IPCC AR5 WG3, Figure 8.9

6/12/2018

20

• Technology adoption decisions (e.g., vehicle choices) are influenced by BOTH financial AND non-financial considerations.

• Financial attributes: upfront (capital) costs and expectations about future operating and fuel costs (affected by fuel efficiency)

– Pretty well understood and nearly always included in energy-economy / systems models.

• Non-financial attributes: available models and brands, perceived risks, comfort, vehicle range and refueling/recharging station availability

– Less well understood. Sometimes included in vehicle choice models (discrete choice or agent-based), but very rarely in energy-economy / systems models.

• Consumer preferences for these financial and non-financial attributes are very heterogeneous (within and across societies).

Vehicle choices depend on more than just techno-economic considerations

GEM‐E3 IMAGE MESSAGE TIAM‐UCL WITCHIMACLIM

EDVShareofTotalLDVPassenger‐Kilom

eters(2050)

Average across models = 24% (range: 15-34%)

Global, economy-wide carbon pricing is assumed as climate policy in both scenarios from 2020 onward (100 US$2010/tCO2 held constant over time).

Sectoral actions targeting consumers’ non-financial preferences are necessary for promoting EDVs; carbon pricing is insufficient

Model=>

Average across models = 1% (range: 0-3%)

McC

ollu

m, W

ilso

n e

t al

. (20

18).

Nat

ure

En

erg

y.

Learning OutcomesNow, you should be able to:1. Summarize the historical development of transportation

systems and main drivers of development

2. Explain the benefits and problems associated with transport.

3. Identify a few of the common technological and policy solutions to overcoming transport problems

4. Describe the “legs” of the transport GHG stool and the ASIF approach commonly used to decompose emissions drivers

5. Articulate the direction the global transport is heading and what that depends on, as well as how transport researchers make future projections

Source: J. Axsen

6/12/2018

21

Questions?Comments?

Contact: David McCollum (mccollum@iiasa.ac.at)

Back-up slides

Source: Magazine of the OeAMTC (Austrian Automobile Association), March 2017 issue

Flying cars courtesy of a Dutch manufacturer(reserve yours now)

Flying (drone) taxis in Dubai(coming July 2017)

“The automobile has been perfected. No further improvements are necessary.”

-- Allgemeine Automobil Zeitung of Berlin, 1921

6/12/2018

22

Limited evidence that shared mobility (alone) will greatly reduce GHG emissions

Source: J. Axsen