Executive Summary
Reducing
global transport greenhouse gas (GHG) emissions will be challenging since the
continuing growth in passenger and freight activity could outweigh all
mitigation measures unless transport emissions can be strongly decoupled from
GDP growth (high confidence).
The transport sector produced 7.0
GtCO2eq of direct GHG emissions (including non-CO2
gases) in 2010 and hence was responsible for approximately 23 % of total
energy-related CO2 emissions (6.7 GtCO2)
[8.1]. Growth in GHG emissions has continued since the Fourth Assessment Report
(AR4) in spite of more efficient vehicles (road, rail, water craft, and
aircraft) and policies being adopted. (robust
evidence, high agreement) [Section 8.1, 8.3]
Without aggressive and sustained
mitigation policies being implemented, transport emissions could increase at a
faster rate than emissions from the other energy end-use sectors and reach
around 12 Gt CO2eq / yr by 2050. Transport demand per capita in
developing and emerging economies is far lower than in Organisation for
Economic Co-operation and Development (OECD) countries but is expected to
increase at a much faster rate in the next decades due to rising incomes and
development of infrastructure. Analyses
of both sectoral and integrated model scenarios suggest a higher emission
reduction potential in the transport sector than the levels found possible in
AR4 and at lower costs. Since many integrated models do not contain a detailed
representation of infrastructural and behavioural changes, their results for
transport can possibly be interpreted as conservative. If pricing and other
stringent policy options are implemented in all regions, substantial decoupling
of transport GHG emissions from gross domestic product (GDP) growth seems
possible. A strong slowing of light-duty vehicle (LDV) travel growth per capita
has already been observed in several OECD cities suggesting possible
saturation. (medium evidence, medium
agreement) [8.6, 8.9, 8.10]
Avoided
journeys and modal shifts due to behavioural change, uptake of improved vehicle
and engine performance technologies, low-carbon fuels, investments in related
infrastructure, and changes in the built environment, together offer high
mitigation potential (high confidence).
Direct (tank-to-wheel) GHG
emissions from passenger and freight transport can be reduced by:
• avoiding journeys where possible — by,
for example, densifying urban landscapes, sourcing localized products, internet
shopping, restructuring freight logistics systems, and utilizing advanced
information and communication technologies (ICT);
• modal shift to lower-carbon transport
systems — encouraged by increasing
investment in public transport, walking and cycling infrastructure, and
modifying roads, airports, ports, and railways to become more attractive for users
and minimize travel time and distance;
• lowering energy intensity (MJ /
passenger km or MJ / tonne km) — by enhancing vehicle and engine performance,
using lightweight materials, increasing freight load factors and passenger
occupancy rates, deploying new technologies such as electric 3-wheelers;
• reducing carbon intensity of fuels (CO2eq
/ MJ) — by substituting oilbased products with natural gas, bio-methane, or
biofuels, electricity or hydrogen produced from low GHG sources.
In addition, indirect GHG emissions arise during the
construction of infrastructure, manufacture of vehicles, and provision of fuels
(well-totank). (robust evidence, high
agreement) [8.3, 8.4, 8.6 and
Chapters 10, 11, 12]
Both
short- and long-term transport mitigation strategies are essential if deep GHG
reduction ambitions are to be achieved (high
confidence).
Short-term mitigation measures could overcome barriers to
low-carbon transport options and help avoid future lock-in effects resulting,
for example, from the slow turnover of vehicle stock and infrastructure and
expanding urban sprawl. Changing behaviour of consumers and businesses will
likely play an important role but is challenging and the possible outcomes,
including modal shift, are difficult to quantify. Business initiatives to
decarbonize freight transport have begun, but need support from policies that
encourage shifting to low-carbon modes such as rail or waterborne options where
feasible, and improving logistics. The impact of projected growth in world
trade on freight transport emissions may be partly offset in the near term by
more efficient vehicles, operational changes, ‘slow steaming’ of ships,
eco-driving and fuel switching. Other short-term mitigation strategies include
reducing aviation contrails and emissions of particulate matter (including
black carbon), tropospheric ozone and aerosol precursors (including NOx)
that can have human health and mitigation co-benefits in the short term. (medium evidence, medium agreement) [8.2, 8.3, 8.6, 8.10]
Methane-based fuels are already increasing their share for
road vehicles and waterborne craft. Electricity produced from low-carbon
sources has near-term potential for electric rail and short- to medium-term
potential as electric buses, light-duty and 2-wheel road vehicles are deployed.
Hydrogen fuels from low-carbon sources constitute longer-term options. Gaseous
and liquid-biofuels can provide co-benefits. Their mitigation potential depends
on technology advances (particularly advanced ‘drop-in’ fuels for aircraft and
other vehicles) and sustainable feedstocks. (medium evidence, medium agreement) [8.2, 8.3]
The technical potential exists to substantially reduce the
current CO2eq emissions per passenger or tonne kilometre
for all modes by 2030 and beyond. Energy efficiency and vehicle performance
improvements range from 30 – 50 % relative to 2010 depending on mode and
vehicle type. Realizing this efficiency potential will depend on large
investments by vehicle manufacturers, which may require strong incentives and
regulatory policies in order to achieve GHG emissions reduction goals. (medium evidence, medium agreement) [8.3, 8.6, 8.10]
Over the medium-term (up to 2030) to long-term (to 2050 and
beyond), urban (re)development and investments in new infrastructure, linked
with integrated urban planning, transit-oriented development and more compact
urban form that supports cycling and walking can all lead to modal shifts. Such
mitigation measures could evolve to possibly reduce GHG intensity by 20 – 50 %
below 2010 baseline by 2050. Although high potential improvements for aircraft
efficiency are projected, improvement rates are expected to be slow due to long
aircraft life, and fuel switching options being limited, apart from biofuels.
Widespread construction of high-speed rail systems could partially reduce
short-to-medium-haul air travel demand. For the transport sector, a reduction
in total CO2eq emissions of 15 – 40 % could be plausible
compared to baseline activity growth in 2050. (medium evidence, medium agreement) [8.3, 8.4, 8.6, 8.9, 12.3, 12.5]
Barriers
to decarbonizing transport for all modes differ across regions, but can be
overcome in part by reducing the marginal mitigation costs (medium evidence, medium agreement).
Financial, institutional, cultural, and legal barriers
constrain low-carbon technology uptake and behavioural change. All of these
barriers include the high investment costs needed to build low-emissions
transport systems, the slow turnover of stock and infrastructure, and the
limited impact of a carbon price on petroleum fuels already heavily taxed.
Other barriers can be overcome by communities, cities, and national governments
which can implement a mix of behavioural measures, technological advances, and
infrastructural changes. Infrastructure investments (USD / tCO2
avoided) may appear expensive at the margin, but sustainable urban planning and
related policies can gain support when co-benefits, such as improved health and
accessibility, can be shown to offset some or all of the mitigation costs. (medium evidence, medium agreement) [8.4, 8.7, 8.8]
Oil price
trends, price instruments on emissions, and other measures such as road pricing
and airport charges can provide strong economic incentives for consumers to
adopt mitigation measures. Regional differences, however, will likely occur due
to cost and policy constraints. Some near term mitigation measures are
available at low marginal costs but several longer-term options may prove more
expensive. Full societal mitigation costs (USD / tCO2eq)
of deep reductions by 2030 remain uncertain but range from very low or negative
(such as efficiency improvements for LDVs, long-haul heavy-duty vehicles (HDVs)
and ships) to more than 100 USD / tCO2eq for some electric
vehicles, aircraft, and possibly high-speed rail. Such costs may be
significantly reduced in the future but the magnitude of mitigation cost
reductions is uncertain. (limited
evidence, low agreement) [8.6,
8.9]
There are regional differences in transport mitigation pathways with
major opportunities to shape transport systems and infrastructure around
low-carbon options, particularly in developing and emerging countries where
most future urban growth will occur (robust
evidence, high agreement).
Transport can be an agent of
sustained urban development that prioritizes goals for equity and emphasizes
accessibility, traffic safety, and time-savings for the poor while reducing
emissions, with minimal detriment to the environment and human health.
Transformative trajectories vary with region and country due to differences in
the dynamics of motorization, age and type of vehicle fleets, existing
infrastructure, and urban development processes. Prioritizing access to
pedestrians and integrating non-motorized and public transit services can
result in higher levels of economic and social prosperity in all regions. Good
opportunities exist for both structural and technological change around
low-carbon transport systems in most countries but particularly in fast growing
emerging economies where investments in mass transit and other low-carbon transport
infrastructure can help avoid future lockin to carbon intensive modes.
Mechanisms to accelerate the transfer and adoption of improved vehicle
efficiency and low-carbon fuels to all economies, and reducing the carbon
intensity of freight particularly in emerging markets, could offset much of the
growth in non-OECD emissions by 2030. It appears possible for LDV travel per
capita in OECD countries to peak around 2035, whereas in non-OECD countries it
will likely continue to increase dramatically from a very low average today.
However, growth will eventually need to be slowed in all countries. (limited evidence, medium agreement)
[8.7, 8.9]
A range of strong and mutually-supportive policies will be needed for
the transport sector to decarbonize and for the cobenefits to be exploited (robust evidence, high agreement).
Decarbonizing the transport
sector is likely to be more challenging than for other sectors, given the
continuing growth in global demand, the rapid increase in demand for faster
transport modes in developing and emerging economies, and the lack of progress
to date in slowing growth of global transport emissions in many OECD countries.
Transport strategies associated with broader non-climate policies at all
government levels can usually target several objectives simultaneously to give
lower travel costs, improved mobility, better health, greater energy security,
improved safety, and time savings. Realizing the co-benefits depends on the
regional context in terms of economic, social, and political feasibility as
well as having access to appropriate and cost-effective advanced technologies.
(medium evidence, high agreement)
[8.4, 8.7]
In rapidly growing developing
economies, good opportunities exist for both structural and technological
change around low-carbon transport. Established infrastructure may limit the
options for modal shift and lead to a greater reliance on advanced vehicle technologies.
Policy changes can maximize the mitigation potential by overcoming the barriers
to achieving deep carbon reductions and optimizing the synergies. Pricing
strategies, when supported by education
policies to help create social acceptance, can help reduce travel demand and
increase the demand for more efficient vehicles (for example, where fuel
economy standards exist) and induce a shift to low-carbon modes (where good
modal choice is available). For freight, a range of fiscal, regulatory, and advisory
policies can be used to incentivize businesses to reduce the carbon intensity
of their logistical systems. Since rebound effects can reduce the CO2
benefits of efficiency improvements and undermine a particular policy, a
balanced package of policies, including pricing initiatives, could help to
achieve stable price signals, avoid unintended outcomes, and improve access,
mobility, productivity, safety, and health. (medium evidence, medium agreement) [8.7, 8.9, 8.10]
Knowledge
gaps in the transport sector
There is a lack of comprehensive
and consistent assessments of the worldwide potential for GHG emission
reduction and especially costs of mitigation from the transport sector. Within
this context, the potential reduction is much less certain for freight than for
passenger modes. For LDVs, the long-term costs and high energy density
potential for on-board energy storage is not well understood. Also requiring
evaluation is how best to manage the tradeoffs for electric vehicles between
performance, driving range and recharging time, and how to create successful
business models.
Another area that requires additional research is in the
behavioural economic analysis of the implications of norms, biases, and social
learning in decision making, and of the relationship between transport and
lifestyle. For example, how and when people will choose to use new types of
low-carbon transport and avoid making unnecessary journeys is unknown.
Consequently, the outcomes of both positive and negative climate change impacts
on transport services and scheduled timetables have not been determined, nor
have the cost-effectiveness of carbon-reducing measures in the freight sector
and their possible rebound effects. Changes in the transport of materials as a
result of the decarbonization of other sectors and adaptation of the built
environment are unknown. [8.11]
8.1 Freight and passenger transport (land, air, sea and water)
Greenhouse gas (GHG) emissions
from the transport sector have more than doubled since 1970, and have increased
at a faster rate than any other energy end-use sector to reach 7.0 Gt CO2eq
in 2010[1]
(IEA, 2012a; JRC / PBL, 2013; see Annex II.8). Around 80 % of this increase has
come from road vehicles (see Figure 8.1). The final energy consumption for
transport reached 28 % of total end-use energy in 2010 (IEA, 2012b), of which
around 40 % was used in urban transport (IEA, 2013). The global transport
industry (including the manufacturers of vehicles, providers of transport
services, and constructors of infrastructure) undertakes research and
development (R&D) activities to become more carbon and energy efficient.
Reducing transport emissions will be a daunting task given the inevitable
increases in demand and the slow turnover and sunk costs of stock (particularly
aircraft, trains, and large ships) and infrastructure. In spite of a lack of
progress to date, the transition required to reduce GHG emissions could arise
from new technologies, implementation of stringent policies, and behavioural
change.
Key developments in the transport sector since the
Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4)
(IPCC, 2007) include:
•
continued increase in annual average passenger
km per capita, but signs that LDV[2]
ownership and use may have peaked in some OECD countries (8.2);
•
deployment of technologies to reduce particulate
matter and black carbon, particularly in OECD countries (8.2);
•
renewed interest in natural gas as a fuel,
compressed for road vehicles and liquefied for ships (8.3);
•
increased number of electric vehicles (including
2-wheelers) and bus rapid transit systems, but from a low base (8.3);
•
increased use of sustainably produced biofuels
including for aviation (8.3, 8.10);
•
greater access to mobility services in
developing countries (8.3,
8.9);
•
reduced carbon intensity of operations by
freight logistics companies, the slow-steaming of ships, and the maritime
industry imposing GHG emission mandates (8.3, 8.10);
•
improved comprehension that urban planning and
developing infrastructure for pedestrians, bicycles, buses and light-rail can
impact on modal choice while also addressing broader sustainability concerns
such as health, accessibility and safety (8.4, 8.7);
•
better analysis of comparative passenger and
freight transport costs between modes (8.6);
•
emerging policies that slow the rapid growth of
LDVs especially in Asia, including investing in non-motorized transport systems
(8.10);
•
more fuel economy standards (MJ / km) and GHG
emission vehicle performance standards implemented for light and heavy duty
vehicles (LDVs and HDVs) (8.10); and
• widely
implemented local transport management policies to reduce air pollution and
traffic congestion (8.10).
|
Figure 81 | Direct GHG emissions of the
transport sector (shown here by transport mode) rose 250 % from 2.8 Gt CO2eq
worldwide in 1970 to 7.0 Gt CO2eq in 2010
(IEA, 2012a; JRC / PBL, 2013; see Annex II.8).
Note:
Indirect emissions from production of fuels, vehicle manufacturing,
infrastructure construction etc. are not included.
|
For each mode of transport, direct GHG
emissions can be decomposed[3]
into:
•
activity
— total passenger-km / yr or freight tonne-km / yr having a positive feedback
loop to the state of the economy but, in part, influenced by behavioural issues
such as journey avoidance and restructuring freight logistics systems;
•
system
infrastructure and modal choice (NRC,
2009);
•
energy
intensity — directly related to vehicle and engine design efficiency,
driver behaviour during operation (Davies,
2012), and usage patterns; and
• fuel carbon intensity — varies for
different transport fuels including electricity and hydrogen.
Each of these components has good potential for mitigation
through technological developments, behavioural change, or interactions between
them, such as the deployment of
electric vehicles impacting on average journey distance and urban
infrastructure (see Figure 8.2).
Deep long-term emission reductions also require pricing
signals and interactions between the emission factors. Regional differences
exist such as the limited modal choice available in some developing countries
and the varying densities and scales of cities (Banister, 2011a). Indirect GHG
emissions that arise during the construction of transport infrastructure,
manufacture of vehicles, and provision of fuels, are covered in Chapters 12,
10, and 7 respectively.
811 The context for transport of passengers
and freight
Around 10 % of the global
population account for 80 % of total motorized passenger-kilometres (p-km) with
much of the world’s population hardly travelling at all. OECD countries
dominate GHG transport emissions (see Figure 8.3) although most recent growth has
taken place in Asia, including passenger kilometres travelled by low GHG
emitting 2- to 3-wheelers that have more than doubled since 2000 (see Figure
8.4). The link between GDP and transport has been a major reason for increased
GHG emissions (Schafer and Victor, 2000) though the first signs that decoupling
may be happening are now apparent (Newman and Kenworthy, 2011a; Schipper,
2011). Slower rates of growth, or even reductions in the use of LDVs, have been
observed in some OECD cities (Metz, 2010, 2013; Meyer et al., 2012; Goodwin and
van Dender, 2013; Headicar, 2013) along with a simultaneous increase in the use
of mass transit systems (Kenworthy, 2013). The multiple factors causing this
decoupling, and how it can be facilitated more widely, are not well understood
(ITF, 2011; Goodwin and Van Dender, 2013). However, ‘peak’ travel trends are
not expected to occur in most developing countries in the foreseeable future,
although transport activity levels may eventually plateau at lower GDP levels
than for OECD countries due to higher urban densities and greater
infrastructure constraints (ADB, 2010; Figueroa and Ribeiro, 2013).
As shown in
Figure 8.3, the share of transport emissions tended to increase due to
structural changes as GDP per capita increased, i. e., countries became richer.
The variance between North America and other OECD countries (Western Europe and
Pacific OECD) shows that the development path of infrastructure and settlements
taken by developing countries and economies in transition (EITs) will have a
significant impact on the future share of transport related emissions and,
consequently, total GHG emissions (see Section 12.4).
Figure 82 | Direct transport GHG emission
reductions for each mode and fuel type option decomposed into activity
(passenger or freight movements); energy intensity (specific energy inputs
linked with occupancy rate); fuel carbon intensity (including non-CO2 GHG emissions);
and system infrastructure and modal choice. These can be summated for each
modal option into total direct GHG emissions. Notes: p-km = passenger-km; t-km
= tonne-km; CNG = compressed natural gas; LPG = liquid petroleum gas (Creutzig
et al., 2011; Bongardt et al., 2013).
 |
Figure 83 | GHG
emissions from transport sub-sectors by regions in 1970, 1990 and 2010 with
international shipping and aviation shown separately (IEA, 2012a; JRC / PBL,
2013; see Annex II.8). Inset shows the relative share of total GHG emissions
for transport relative to GDP per capita from 1970 to 2010 for each region and
the world. Adapted from Schäfer et al. (2009), Bongardt et al. (2013) using
data from IEA (2012a) and JRC / PBL (2013); see Annex II.8.
812 Energy demands and direct / indirect
emissions
Over 53 % of
global primary oil consumption in 2010 was used to meet 94 % of the total
transport energy demand, with biofuels supplying approximately 2 %, electricity
1 %, and natural gas and other fuels 3 % (IEA, 2012b). LDVs consumed around
half of total transport energy (IEA, 2012c). Aviation accounted for 51 % of all
international passenger arrivals in 2011 (UNWTO, 2012) and 17 % of all tourist
travel in 2005 (ICAO, 2007a; UNWTO and UNEP, 2008). This gave 43 % of all
tourism transport CO2eq emissions, a share forecast to increase to
over 50 % by 2035 (Pratt et al., 2011). Buses and trains carried about 34 % of
world tourists, private cars around 48 %, and waterborne craft only a very
small portion (Peeters and Dubois, 2010).
Freight transport consumed
almost 45 % of total transport energy in 2009 with HDVs using over half of that
(Figure 8.5). Ships carried around 80 % (8.7 Gt) of internationally traded
goods in 2011 (UNCTAD, 2013) and produced about 2.7 % of global CO2
emissions (Buhaug and et. al, 2009).
Direct vehicle CO2
emissions per kilometre vary widely for each mode (see Figure 8.6). The
particularly wide range of boat types and sizes gives higher variance for
waterborne than for other modes of transport (Walsh and Bows, 2012). Typical
variations for freight movement range from ~2 gCO2 / t-km for
bulk shipping to ~1,700 gCO2 / t-km for short-haul aircraft, whereas
passenger transport typically ranges from ~20 – 300 gCO2
/ p-km. GHG emissions arising from the use of liquid and gaseous fuels produced
from unconventional reserves, such as
Figure
84 | Total passenger distance travelled by mode and region in
2000 and 2010 (IEA, 2012c)
Note: Non-motorized modal shares are not included, but
can be relatively high in Asia and Africa. For RC5 region definitions see Annex
II.2.
from oil sands and shale deposits,
vary with the feedstock source and refining process. Although some uncertainty
remains, GHG emissions from unconventional reserves are generally higher per
vehicle kilometre compared with using conventional petroleum products (Brandt,
2009, 2011, 2012; Charpentier et al., 2009; ETSAP, 2010; IEA, 2010a; Howarth et
al., 2011, 2012; Cathles et al., 2012).
‘Sustainable transport’, arising from the concept of
sustainable development, aims to provide accessibility for all to help meet the
basic daily mobility needs consistent with human and ecosystem health, but to
constrain GHG emissions by, for example, decoupling mobility from oil
dependence and LDV use. Annual transport emissions per capita correlate
strongly with annual income, both within and between countries (Chapter 5) but
can differ widely even for regions with similar income per capita. For example,
the United States has around 2.8 times the transport emissions per capita than
those of Japan (IEA, 2012a). In least developed countries (LDCs), increased
motorized mobility will produce large increases in GHG emissions but give
significant social benefits such as better access to markets and opportunities
to improve education and health (Africa Union, 2009; Pendakur, 2011;
Sietchiping et al., 2012). Systemic goals for mobility, climate, and energy
security can help develop the more general sustainable transport principles.
Affordable, safe, equitable, and efficient travel services can be provided with
fairness of mobility access across and within generations (CST, 2002; ECMT,
2004; Bongardt et al., 2011; E C Environment, 2011; Zegras, 2011; Figueroa and
Kahn Ribeiro, 2013).
The
following sections of this chapter outline how changes to the transport sector
could reduce direct GHG emissions over the next decades to help offset the
significant global increase in demand projected for movement of both passengers
and freight.
average
conversion efficiency of fuel to kinetic energy of around 32 %. Note: Width of
lines depicts total energy flows. (IEA, 2012d).
 |
Direct* CO2 Emissions per Distance [gCO2/km] Direct*
CO2 Emissions per Distance [gCO2/km]
*The ranges only give an indication of direct vehicle fuel
emissions. They exclude indirect emissions arising from vehicle manufacture,
infrastructure, etc. included in life-cycle analyses except from electricity
used for rail.
Figure 86 | Typical ranges of direct CO2 emissions
per passenger kilometre and per tonne-kilometre for freight, for the main
transport modes when fuelled by fossil fuels including thermal electricity
generation for rail. (ADEME, 2007; US DoT, 2010; Der Boer et al., 2011; NTM,
2012; WBCSD, 2012).
8.2 New developments in emission trends and drivers
Assessments of transport GHG emissions require a
comprehensive and differential understanding of trends and drivers that impact
on the movement of goods and people. Transport’s share of total national GHG
emissions range from up to 30 % in high income economies to less than 3 % in
LDCs, mirroring the status of their industry and service sectors (Schäfer et
al., 2009; Bongardt et al., 2011) (IEA, 2012a; JRC / PBL, 2013; see Annex II.8)
(see inset Figure 8.3). Travel patterns vary with regional locations and the
modes available, and guide the development of specific emission reduction pathways.
Indicators such as travel activity, vehicle occupancy
rates, and fuel consumption per capita can be used to assess trends towards
reducing emissions and reaching sustainability goals (WBCSD, 2004; Dalkmann and
Brannigan, 2007; Joumard and Gudmundsson, 2010; Kane, 2010; Litman, 2007;
Ramani et al., 2011). For example, petroleum product consumption to meet all
transport demands in 2009 ranged from 52 GJ / capita in North America to less
than 4 GJ / capita in Africa and India where mobility for many people is
limited to walking and cycling. Likewise, residents and businesses of several
cities in the United States consume over 100 GJ / capita each year on transport
whereas those in many Indian and Chinese cities use less than 2 GJ / capita
(Newman and Kenworthy, 2011a). For freight, companies are starting to adopt
green initiatives as a means of cost savings and sustainability initiatives
(Fürst and Oberhofer, 2012). Such programmes are also likely to reduce GHG
emissions, although the long-term impact is difficult to assess.
821
Trends
As economies have shifted from
agriculture to industry to service, the absolute GHG emissions from transport
(Figure 8.1) and the share of total
GHG emissions by the transport sector (Chapter 5.2.1) have risen considerably.
Total LDV ownership is expected to double in the next few decades (IEA, 2009)
from the current level of around 1 billion vehicles (Sousanis, 2011). Two-thirds
of this growth is expected in non-OECD countries where increased demand for
mobility is also being met by motorized two-wheelers and expansion of bus and
rail public transport systems. However, passenger kilometres travelled and per
capita ownership of LDVs will likely remain much lower than in OECD countries
(Cuenot et al., 2012; Figueroa et al., 2013).
Air transport demand is projected
to continue to increase in most OECD countries (see Section 8.9). Investments
in high-speed rail systems could moderate growth rates over short- to
medium-haul distances in Europe, Japan, China, and elsewhere (Park and Ha,
2006; Gilbert and Perl, 2010; Åkerman, 2011; Salter et al., 2011).
There is limited evidence that reductions to date in carbon
intensity, energy intensity, and activity, as demonstrated in China, Japan, and
Europe, have adequately constrained transport GHG emissions growth in the
context of mitigation targets. Recent trends suggest that economic, lifestyle,
and cultural changes will be insufficient to mitigate global increases in
transport emissions without stringent policy instruments, incentives, or other
interventions being needed (see Section 8.10).
8211
Non-CO2 greenhouse gas emissions, black carbon,
and aerosols
The transport sector emits non-CO2
pollutants that are also climate forcers. These include methane, volatile
organic compounds (VOCs), nitrogen oxides (NOx), sulphur dioxide
(SO2), carbon monoxide (CO), F-gases, black carbon, and
non-absorbing aerosols (Ubbels et al., 2002; Sections 5.2.2 and 6.6.2.1).
Methane emissions are largely associated with leakage from the production of
natural gas and the filling of compressed natural gas vehicles; VOCs, NOx
and CO are emitted by internal combustion engines; and F-gas emissions
generally from air conditioners (including those in vehicles) and
refrigerators. Contrails from aircraft and emissions from ships also impact on
the troposphere and the marine boundary layer, respectively (Fuglestvedt et
al., 2009; Lee et al., 2010). Aviation emissions can also impact on cloud
formation and therefore have an indirect effect on climate forcing (Burkhardt
and Kärcher, 2011).
Black carbon and non-absorbing aerosols, emitted mainly
during diesel engine operation, have short lifetimes in the atmosphere of only
days to weeks, but can have significant direct and indirect radiative forcing
effects and large regional impacts (Boucher et al., 2013). In North and South
America and Europe, over half the black carbon emissions result from combusting
diesel and other heavy distillate fuels (including marine oil), in vehicle
engines (Bond et al., 2013). Black carbon emissions are also significant in
parts of Asia, Africa, and elsewhere from biomass and coal combustion, but the
relative contribution from transport is expected to grow in the future. There
is strong evidence that reducing black carbon emissions from HDVs, off-road
vehicles, and ships could provide an important short term strategy to mitigate
atmospheric concentrations of positive radiative forcing pollutants (USEPA,
2012; Shindell et al., 2013; Chapter 6.6; WG I Chapter 7).
Conversely, transport is also a significant emitter of
primary aerosols that scatter light and gases that undergo chemical reactions
to produce secondary aerosols. Primary and secondary organic aerosols,
secondary sulphate aerosols formed from sulphur dioxide emissions, and
secondary nitrate aerosols from nitrogen oxide emissions from ships, aircraft,
and road vehicles, can have strong, local, and regional cooling impacts
(Boucher et al., 2013).
The relative contributions of different short-term
pollutants to radiative forcing in 2020 have been equated by Unger et al.
(2010) to having continuous constant GHG emissions since 2000. Although this
study did not provide a projection for future emissions scenarios, it did offer
a qualitative comparison of short- and long-term impacts of different
pollutants. Relative to CO2, major short-term impacts stem from
black carbon, indirect effects of aerosols and ozone from land vehicles, and
aerosols and methane emissions associated with ships and aircraft. Their
relative impacts due to the longer atmospheric lifetime of CO2
will be greatly reduced when integrated from the present time to 2100.
Although emissions of non-CO2 GHGs and
aerosols can be mitigated by reducing carbon intensity, improving energy
intensity, changing to lower-carbon modes, and reducing transport activity,
they can also be significantly reduced by technologies that prevent their
formation or lead to their destruction using after-treatments. Emission control
devices such as diesel particulate filters and selective catalytic reduction
have fuel efficiency penalties that can lead to an increase in transport CO2
emissions.
Non-CO2
emissions from road transport and aviation and shipping activities in ports
have historically been constrained by local air quality regulations that are
directed at near-surface pollution and seek to protect human health and welfare
by reducing ozone, particulate matter, sulphur dioxide, and toxic components or
aerosols, including vanadium, nickel, and polycyclic aromatic hydrocarbons
(Verma et al. 2011). The importance of regional climate change in the context
of mitigation has prompted a growing awareness of the climate impact of these
emissions. Policies are already in place for reducing emissions of F-gases,
which are expected to continue to decrease with time (Prinn et al., 2000). More
efforts are being directed at potential programmes to accelerate control
measures to reduce emissions of black carbon, ozone precursors, aerosols, and
aerosol precursors (Lin and Lin, 2006). Emissions from road vehicles continue
to decrease per unit of travel in many regions due to efforts made to protect
human health from air pollution. The implementation of these controls could
potentially be accelerated as a driver to mitigate climate change (Oxley et
al., 2012). Short-term mitigation strategies that focus on black carbon and
contrails from aircraft, together with national and international programmes to
reduce aerosol and sulphate emissions from shipping, are being implemented
(Buhaug and et. al, 2009; Lack, 2012). However, the human health benefits from
GHG emissions reductions and the cobenefits of climate change mitigation
through black carbon reductions need to be better assessed (Woodcock et al.,
2009).
822
Drivers
The major drivers that affect transport trends are travel
time budgets, costs and prices, increased personal income, and social and
cultural factors (Schäfer, 2011). For a detailed discussion of effects of urban
form and structure on elasticities of vehicle kilometres travelled see Section
12.4.2.
Travel time budget
Transport helps determine the economy of a city or region based on the time
taken to move people and goods around. Travel time budgets are usually fixed
and tied to both travel costs and time costs (Noland, 2001; Cervero, 2001;
Noland and Lem, 2002). Because cities vary in the proportion of people using
different transport modes, urban planners tend to try to adapt land use
planning to fit these modes in order to enable speeds of around 5 km / hr for
walking, 20 – 30 km / hr for mass transit, and 40 – 50 km / hr for LDVs, though
subject to great variability. Infrastructure and urban areas are usually
planned for walking, mass transit, or LDVs so that destinations can be reached
in half an hour on average (Newman and Kenworthy, 1999).
Urban travel time budgets for a typical commute between work
and home average around 1.1 – 1.3 hours per traveller per day in both developed
and developing economies (Zahavi and Talvitie, 1980; van Wee et al., 2006). Higher
residential density can save fuel for LDVs, but leads to more congested
commutes (Small and Verhoef, 2007; Downs, 2004). While new road construction
can reduce LDV travel time in the short run, it also encourages increased LDV
demand, which typically leads to increases in travel time to a similar level as
before (Maat and Arentze, 2012). Moreover, land uses quickly adapt to any new
road transport infrastructure so that a similar travel time eventually resumes
(Mokhtarian and Chen, 2004).
Regional
freight movements do not have the same fixed time demands, but rather are based
more on the need to remain competitive by limiting transport costs to a small
proportion of the total costs of the goods (Schiller et al. 2010). See also
Section 12.4.2.4 on accessibility aspects of urban form.
Costs and prices The relative decline of transport costs as a share
of increasing personal expenditure has been the major driver of increased
transport demand in OECD countries throughout the last century and more
recently in non-OECD countries (Mulalic et al., 2013). The price of fuel,
together with the development of mass transit systems and nonmotorized
transport infrastructure, are major factors in determining the level of LDV use
versus choosing public transport, cycling, or walking (Hughes et al., 2006).
Transport fuel prices, heavily influenced by taxes, also impact on the
competition between road and rail freight. The costs of operating HDVs,
aircraft, and boats increase dramatically when fuel costs go up given that fuel
costs are a relatively high share of total costs (Dinwoodie, 2006). This has
promulgated the designs of more fuel efficient engines and vehicle designs
(Section 8.3) (IEA, 2009). Although the average life of aircraft and marine
engines is two to three decades and fleet turnover is slower than for road
vehicles and small boats, improving their fuel efficiency still makes good
economic sense (IEA, 2009).
The high cost of developing new
infrastructure requires significant capital investment that, together with
urban planning, can be managed and used as a tool to reduce transport demand
and also encourage modal shift (Waddell et al., 2007). Changing urban form
through planning and development can therefore play a significant role in the
mitigation of transport GHG emissions (see Section 8.4) (Kennedy et al., 2009).
See also Section 12.5.2 on urban policy instruments.
Social and cultural factors. Population
growth and changes in demographics are major drivers for increased transport
demand. Economic structural change,
particularly in non-OECD countries, can lead to increased specialization of
jobs and a more gender-diversified workforce, which can result in more and
longer commutes (McQuaid and Chen, 2012). At the household level, once a
motorized vehicle becomes affordable, even in relatively poor households, then
it becomes a major item of expenditure; however, ownership has still proven to
be increasingly popular with each new generation (Giuliano and Dargay, 2006;
Lescaroux, 2010; Zhu et al., 2012). Thus, there is a high growth rate in
ownership of motorized two-wheel vehicles and LDVs evident in developing
countries, resulting in increasing safety risks for pedestrians and
non-motorized modes (Nantulya and Reich 2002; Pendakur, 2011). The development
of large shopping centres and malls usually located outside the city centre
allows many products to be purchased by a consumer following a single journey
but the travel distance to these large shopping complexes has tended to
increase (Weltevreden, 2007). For freight transport, economic globalization has
increased the volume and distance of movement of goods and materials (Henstra
et al., 2007).
Modal choice can be driven by social
factors that are above and beyond the usual time, cost, and price drivers. For
example, some urban dwellers avoid using mass transit or walking due to safety
and security issues. However, there is evidence that over the past decade
younger people in some OECD cities are choosing walking, cycling, and mass
transit over LDVs (Parkany et al., 2004; Newman and Kenworthy, 2011b; Delbosc
and Currie, 2013; Kuhnimhof et al., 2013) although this trend could change as
people age (Goodwin and van Dender, 2013).
Another example is that in some
societies, owning and driving a LDV can provide a symbolic function of status
and a basis for sociability and networking through various sign-values such as
speed, safety, success, career achievement, freedom, masculinity, and
emancipation of women (Mokhtarian and Salomon, 2001; Steg, 2005; Bamberg et
al., 2011; Carrabine and Longhurst, 2002; Miller, 2001; Sheller, 2004; Urry,
2007). In such cases, the feeling of power and superiority associated with
owning and using a LDV may influence driver behaviour, for example, speeding
without a concern for safety, or without a concern about fuel consumption,
noise, or emissions (Brozović and Ando, 2009; Tiwari and Jain, 2012). The
possible effects on travel patterns from declining incomes are unclear.
Lifestyle and behavioural factors are important for any assessment
of potential change to low-carbon transport options and additional research is
needed to assess the willingness of people to change (Ashton-Graham, 2008;
Ashton-Graham and Newman, 2013). Disruptive technologies such as driverless
cars and consumer-based manufacturing (e. g. 3-D printing) could impact on
future transport demands but these are difficult to predict. Likewise, the
impact of new information technology (IT) applications and telecommuting could
potentially change travel patterns, reduce trips, or facilitate interactions
with the mode of choice (ITF, 2011). Conversely, increased demand for tourism
is expected to continue to be a driver for all transport modes (Sections 8.1
and 10.4; Gössling et al., 2009).
8.3 Mitigation technology options, practices and behavioural aspects
Technological improvements and new technology-related
practices can make substantial contributions to climate change mitigation in
the transport sector. This section focuses on energy intensity reduction
technology options for LDVs, HDVs, ships, trains and aircraft and fuel carbon
intensity reduction options related to the use of natural gas, electricity,
hydrogen and biofuels. It also addresses some technologyrelated behavioural
aspects concerning the uptake and use of new technologies, behaviour of firms,
and rebound effects. Urban form and modal shift options are discussed in
Section 8.4.
831 Energy intensity reduction —
incremental vehicle technologies
Recent advances in LDVs in response to strong regulatory
efforts in Japan, Europe, and the United States have demonstrated that there is
substantial potential for improving internal combustion engines (ICEs) with
both conventional and hybrid drive-trains. Recent estimates suggest substantial
additional, unrealized potentials exist compared to similar-sized, typical 2007
– 2010 vehicles, with up to 50 % improvements in vehicle fuel economy (in MJ /
km or litres / 100km units, or equal to 100 % when measured as km / MJ, km / l,
or miles per gallon) (Bandivadekar et al., 2008; Greene and Plotkin, 2011).
Similar or slightly lower potentials exist for HDVs, waterborne craft, and
aircraft.
8311
Light duty vehicles
As of 2011, leading-edge LDVs had drive-trains with direct
injection gasoline or diesel engines (many with turbochargers), coupled with
automated manual or automatic transmissions with six or more gears (SAE
International, 2011). Drive-train redesigns of average vehicles to bring them
up to similar levels could yield reductions in fuel consumption and GHG
emissions of 25 % or more (NRC, 2013). In European Union 27 (EU27), the average
tested emissions of 2011 model LDVs was 136 gCO2 / km, with
some models achieving below 100 gCO2 / km (EEA, 2012). In
developing countries, vehicle technology levels are typically lower, although
average fuel economy can be similar since vehicle size, weight, and power
levels are also typically lower (IEA, 2012d).
Hybrid drive-trains (ICE plus electric motor with battery
storage) can provide reductions up to 35 % compared to similar non-hybridized
vehicles (IEA, 2012e) and have become mainstream in many countries, but with
only a small share of annual sales over the last decade except in Japan, where
over two million had been sold by 2012 (IEA, 2012e). There is substantial
potential for further advances in drive-train design and operation, and for
incremental technologies (NRC, 2013). There is often a time lag between when
new technologies first appear in OECD countries and when they reach developing
countries, which import mostly second-hand vehicles (IEA, 2009).
Lower fuel consumption can be
achieved by reducing the loads that the engine must overcome, such as
aerodynamic forces, auxiliary components (including lighting and air
conditioners), and rolling resistance. Changes that reduce energy loads include
improved aerodynamics, more efficient auxiliaries, lower rolling-resistance
tyres, and weight reduction. With vehicle performance held constant, reducing
vehicle weight by 10 % gives a fuel economy improvement of about 7 % (EEA,
2006). Together, these non-drive-train changes offer potential fuel consumption
reductions of around 25 % (ICCT, 2012a; NRC, 2013). Combined with improved
engines and drive-train systems, overall LDV fuel consumption for new
ICE-powered vehicles could be reduced by at least half by 2035 compared to 2005
(Bandivadekar et al., 2008; NRC, 2013). This predicted reduction is consistent
with the Global Fuel Economy Initiative target
for new LDVs of a 50 % reduction in average fuel use per kilometre in 2030
compared to 2005 (Eads, 2010).
8312
Heavy-duty vehicles
Most modern medium and HDVs already have efficient diesel
engines (up to 45 % thermal efficiency), and long-haul trucks often have
streamlined spoilers on their cabs to reduce drag, particularly in OECD
countries. Aerodynamic drag can also be reduced using other modifications
offering up to 10 % reduction in fuel consumption (TIAX, 2009; NRC, 2010; AEA, 2011).
In non-OECD countries, many older trucks with relatively inefficient (and
highly polluting) engines are common. Truck modernization, along with better
engine, tyre, and vehicle maintenance, can significantly improve fuel economy
in many cases.
Medium and HDVs in the United States can achieve a reduction
in energy intensity of 30 – 50 % by 2020 by using a range of technology and
operational improvements (NRC, 2010a). Few similar estimates are available in
non-OECD countries, but most technologies eventually will be applicable for
HDVs around the world.
Expanding the carrying capacity of HDVs in terms of both
volume and weight can yield significant net reductions in the energy intensity
of trucks so long as the additional capacity is well utilized. A comparison of
the performance of 18 longer and heavier HDVs in nine countries (ITF / OECD,
2010) concluded that higher capacity vehicles can significantly reduce CO2
emissions per t-km. The use of long combination vehicles rather than single
trailer vehicles has been shown to cut direct GHG emissions by up to 32 %
(Woodrooffe and Ash, 2001).
Trucks and buses that operate
largely in urban areas with a lot of stop-and-go travel can achieve substantial
benefits from using electric hybrid or hydraulic hybrid drive-trains. Typically
a 20 – 30 % reduction in fuel consumption can be achieved via hybridization
(Chandler et al., 2006; AEA, 2011).
8313
Rail, waterborne craft, and
aircraft
Rail is generally energy efficient, but improvements can be
gained from multiple drive-trains and load-reduction measures. For example, the
highspeed ‘Shinkansen’ train in Japan gained a 40 % reduction of energy
consumption by optimizing the length and shape of the lead nose, reducing
weight, and by using efficient power electronics (UIC, 2011); Amtrack in the
United States employed regenerative braking systems to reduce energy
consumption by 8 % (UIC, 2011); and in China, electrification and other
measures from 1975 to 2007 contributed to a 87 % reduction in CO2
emission intensity of the rail system (He et al., 2010).
Shipping is a comparatively efficient mode of freight and
passenger transport, although size and load factor are important determinants
for specific motorized craft, large and small. Efficiency of new-built vessels
can be improved by 5 – 30 % through changes in engine and transmission
technologies, waste heat recovery, auxiliary power systems, propeller and rotor
systems, aerodynamics and hydrodynamics of the hull structure, air lubrication
systems, electronically controlled engine systems to give fuel efficient
speeds, and weight reduction (IMO, 2009; Notteboom and Vernimmen, 2009; AEA,
2007; IEA, 2009; IMO, 2009; ICCT, 2011). Retrofit and maintenance measures can
provide additional efficiency gains of 4 – 20 % (Buhaug and et. al, 2009) and
operational changes, such as anti-fouling coatings to cut water resistance,
along with operation at optimal speeds, can provide 5 – 30 % improvement
(Pianoforte, 2008; Corbett et al., 2009; WSC, 2011).
Several methods for improving
waterborne craft efficiency are already in use. For example, wind propulsion
systems such as kites and parafoils can provide lift and propulsion to reduce
fuel consumption by up to 30 %, though average savings may be much less
(Kleiner, 2007). Photovoltaics and small wind turbines can provide on-board
electricity and be part of ‘cold ironing’ electric systems in ports. For
international shipping, combined technical and operational measures have been
estimated to potentially reduce energy use and CO2 emissions by
up to 43 % per t-km between 2007 and 2020 and by up to 60 % by 2050 (Crist,
2009; IMO, 2009).
Aircraft designs have received substantial, on-going
technology efficiency improvements over past decades (ITF, 2009) typically
offering a 20 – 30 % reduction in energy intensity compared to older aircraft
models (IEA, 2009). Further fuel efficiency gains of 40 – 50 % in the 2030 –
2050 timeframe (compared to 2005) could come from weight reduction, aerodynamic
and engine performance improvements, and aircraft systems design (IEA, 2009).
However, the rate of introduction of major aircraft design concepts could be
slow without significant policy incentives, regulations at the regional or
global level, or further increases in fuel prices (Lee, 2010). Retrofit
opportunities, such as engine replacement and adding ‘winglets’, can also
provide significant reductions (Gohardani et al., 2011; Marks, 2009). Improving
air traffic management can reduce CO2 emissions through
more direct routings and flying at optimum altitudes and speeds (Dell’Olmo and
Lulli, 2003; Pyrialakou et al., 2012). Efficiency improvements of ground
service equipment and electric auxiliary power units can provide some
additional GHG reductions (Pyrialakou et al., 2012).
832 Energy intensity reduction — advanced
propulsion systems
At present, most vehicles and equipment across all transport
modes are powered by ICEs, with gasoline and diesel as the main fuels for LDVs;
gasoline for 2- and 3-wheelers and small water craft; diesel for HDVs; diesel
or heavy fuel oil for ships and trains (other than those using grid
electricity); and kerosene for aircraft turbine engines. New propulsion systems
include electric motors powered by batteries or fuel cells, turbines
(particularly for rail), and various hybridized concepts. All offer significant
potential reductions in GHG, but will require considerable time to penetrate
the vehicle fleet due to slow stock turnover rates.
8321
Road vehicles — battery and
fuel cell electricdrives
Battery electric vehicles (BEVs) emit no tailpipe emissions
and have potentially very low fuel-production emissions (when using low-carbon
electricity generation) (Kromer and Heywood, 2007). BEVs operate at a
drive-train efficiency of around 80 % compared with about 20 – 35 % for
conventional ICE LDVs. At present, commercially available BEVs typically have a
limited driving range of about 100 – 160km, long recharge times of four hours
or more (except with fast-charging or battery switching systems), and high
battery costs that lead to relatively high vehicle retail prices (Greene and
Plotkin, 2011). Lithium ion (Li-ion) batteries will likely improve but new
battery technologies (e. g., Li-air, Li-metal, Li-sulphur) and ultra-capacitors
may be required to achieve much higher energy and power densities (IEA, 2009;
NRC, 2013). Compressed air as an energy storage medium for LDVs is
thermo-dynamically inefficient and would require high storage volume (Creutzig
et al., 2009).
Plug-in hybrid electric vehicles
(PHEVs) capable of grid recharging typically can operate on battery electricity
for 20 to 50 km, but emit CO2 when their ICE is operating. The
electric range of PHEVs is heavily dependent on the size of battery, design
architectures, and control strategies for the operation of each mode (Plotkin
et al., 2001).
For HDVs, the use of BEVs is most
applicable to light-medium duty urban vehicles such as delivery vans or garbage
collection trucks whose drive cycles involve frequent stops and starts and do
not need a long range (TIAX, 2009; AEA, 2011). Transit buses are also good
candidates for electrification either with batteries or more commonly using
overhead wire systems (IEA, 2009). Electric 2-wheelers with lower requirements
for battery and motor capacities are a mature technology with widespread
acceptance, especially in developing countries (Weinert, 2008). For example,
there were over 120 million electric 2-wheelers in China by the end of 2010 (Wu
et al., 2011).
Fuel cell vehicles (FCVs) can be
configured with conventional, hybrid, or plug-in hybrid drive-trains. The fuel
cells generate electricity from hydrogen that may be generated on-board (by
reforming natural gas, methanol, ammonia, or other hydrogen-containing fuel),
or produced externally and stored on-board after refuelling. FCVs produce no
tailpipe emissions except water and can offer a driving range similar to
today’s gasoline / diesel LDVs, but with a high cost increment. Fuel cells
typically operate with a conversion efficiency of 54 – 61 % (significantly
better than ICEs can achieve), giving an overall fuel-cycle efficiency of about
35 – 49 % for an LDV (JHFC, 2011).
Although a number of FCV LDVs, HDVs, and buses have been
demonstrated and some are expected to become commercially available within five
years, overall it could take 10 years or longer for FCVs to achieve commercial
success based on current oil and vehicle purchase prices (IEA, 2012e).
8322
Rail, waterborne craft, and
aircraft
Diesel-hybrid locomotives
demonstrated in the UK and advanced types of hybrid drive-trains under
development in the United States and Japan, could save 10 – 20 % of diesel fuel
plus around a 60 % reduction of NOx and particulate matter compared to
conventional locomotives (JR East, 2011). A shift to full electrification may
enable many rail systems to reach very low CO2 emissions per
kilometre where electricity generation has been deeply decarbonized. Fuel cell
systems for rail may be attractive in areas lacking existing electricity
infrastructure (IEA, 2012e).
Most ocean-going ships will probably continue to use marine
diesel engines for the foreseeable future, given their high reliability and low
cost. However, new propulsion systems are in development. Full electrification
appears unlikely given the energy storage requirements for long-range
operations, although on-board solar power generation systems could be used to
provide auxiliary power and is already used for small craft (Crist, 2009). Fuel
cell systems (commonly solid-oxide) with electric motors could be used for
propulsion, either with hydrogen fuel directly loaded and stored on board or
with on-board reforming. However, the cost of such systems appears relatively
high, as are nuclear power systems as used in some navy vessels.
For large commercial aircraft,
no serious alternative to jet engines for propulsion has been identified,
though fuel-switching options are possible, including ‘drop-in’ biofuels (that
are fungible with petroleum products, can be blended from 0 to 100 %, and are
compatible with all existing engines) or hydrogen. Hydrogen aircraft are
considered only a very long run option due to hydrogen’s low energy density and
the difficulty of storing it on board, which requires completely new aircraft
designs and likely significant compromises in performance (Cryoplane, 2003).
For small, light aircraft, advanced battery electric / motor systems could be
deployed but would have limited range (Luongo et al., 2009).
833
Fuel carbon intensity reduction
In principle, low-carbon fuels from natural gas,
electricity, hydrogen, and biofuels (including biomethane) could all enable
transport systems to be operated with low direct fuel-cycle CO2eq
emissions, but this would depend heavily on their feedstocks and conversion
processes.
Natural gas
(primarily methane) can be compressed (CNG) to replace gasoline in Otto-cycle
(spark ignition) vehicle engines after minor modifications to fuel and control
systems. CNG can also be used to replace diesel in compression ignition engines
but significant modifications are needed. Denser storage can be achieved by
liquefaction of natural gas (LNG), which is successfully being used for
long-haul HDVs and ships (Buhaug and et. al, 2009; Arteconi et al., 2010). The
energy efficiency of driving on CNG is typically similar to that for gasoline
or diesel but with a reduction of up to 25 % in tailpipe emissions (CO2
/ km) because of differences in fuel carbon intensity. Lifecycle GHG analysis
suggests lower net reductions, in the range of 10 – 15 % for natural gas fuel
systems. They may also provide a bridge to lower carbon biomethane systems from
biogas (IEA, 2009).
Electricity can be supplied to BEVs and PHEVS via home or
public rechargers. The varying GHG emissions intensity of power grids directly
affects lifecycle CO2eq emissions (IEA, 2012e). Since the GHG
intensity of a typical coal-based power plant is about 1000 gCO2eq
/ kWh at the outlet (Wang, 2012a), for a BEV with efficiency of 200 Wh / km,
this would equate to about 200 gCO2eq / km, which is higher than for an
efficient ICE or hybrid LDV. Using electricity generated from nuclear or
renewable energy power plants, or from fossil fuel plants with carbon dioxide
capture and storage (CCS), near-zero fuel-cycle emissions could result for
BEVs. The numbers of EVs in any country are unlikely to reach levels that
significantly affect national electricity demand for at least one to two
decades, during which time electricity systems could be at least partially
decarbonized and modified to accommodate many EVs (IEA, 2012e).
Hydrogen used in FCVs, or directly in modified ICEs, can be
produced by the reforming of biomass, coal or natural gas (steam methane
reforming is well-established in commercial plants); via commercial but
relatively expensive electrolysis using electricity from a range of sources
including renewable; or from biological processes (IEA, 2009). The mix of
feedstocks largely determines the well-to-wheel GHG emissions of FCVs.
Advanced, high-temperature and photo-electrochemical technologies at the
R&D stage could eventually become viable pathways (Arvizu et al., 2011).
Deployment of FCVs (8.3.2.1) needs to be accompanied by large, geographically
focused, investments into hydrogen production and distribution and vehicle
refuelling infrastructure. Costs can be reduced by strategic placement of
stations (Ogden and Nicholas, 2011) starting with specific locations
(‘lighthouse cities’) and a high degree of coordination between fuel suppliers,
vehicle manufacturers and policy makers is needed to overcome ‘chicken-or-egg’
vehicle / fuel supply problems (ITS-UC Davis, 2011).
A variety of liquid and gaseous biofuels can be produced
from various biomass feedstocks using a range of conversion pathways (Chapter
11.A.3). The ability to produce and integrate large volumes of biofuels
cost-effectively and sustainably are primary concerns of which policy makers
should be aware (Sims et al., 2011). In contrast to electricity and hydrogen,
liquid biofuels are relatively energy-dense and are, at least in certain forms
and blend quantities, compatible with the existing petroleum fuel
infrastructure and with all types of ICEs installed in LDVs, HDVs, waterborne
craft, and aircraft. Ethanol and biodiesel (fatty-acid-methyl-ester, FAME) can
be blended at low levels (10 – 15 %) with petroleum fuels for use in unmodified
ICEs. New ICEs can be cheaply modified during manufacture to accommodate much
higher blends as exemplified by ‘flex-fuel’ gasoline engines where ethanol can
reach 85 % of the fuel blend (ANFAVEA, 2012). However, ethanol has about a 35 %
lower energy density than gasoline, which reduces vehicle range — particularly
at high blend levels — that can be a problem especially for aircraft. Synthetic
‘drop-in’ biofuels have similar properties to diesel and kerosene fuels. They
can be derived from a number of possible feedstocks and conversion processes,
such as the hydro-treatment of vegetable oils or the Fischer-Tropsch conversion
of biomass (Shah, 2013). Bio-jet fuels suitable for aircraft have been
demonstrated to meet the very strict fuel specifications required (Takeshita
and Yamaji, 2008; Caldecott and Tooze, 2009). Technologies to produce
ligno-cellulosic, Fisher-Tropsch, algae-based, and other advanced biofuels are
in development, but may need another decade or more to achieve widespread
commercial use (IEA, 2011a). Bio-methane from suitably purified biogas or
landfill gas can also be used in natural gas vehicles (REN21, 2012).
Biofuels have direct, fuel-cycle GHG emissions that
are typically 30 – 90 % lower per kilometre travelled than those for gasoline
or diesel fuels. However, since for some biofuels, indirect emissions —
including from land use change — can lead to greater total emissions than when
using petroleum products, policy support needs to be considered on a case by
case basis (see Chapter 11.13 and, for example, Lapola et al., 2010; Plevin et
al., 2010; Wang et al., 2011; Creutzig et al., 2012a).
834
Comparative analysis
The vehicle and power-train
technologies described above for reducing fuel consumption and related CO2
emissions span a wide range and are not necessarily additive. When combined,
and including different propulsion and fuel systems, their overall mitigation
potential can be evaluated as an integrated fuel / vehicle system (see Section
8.6). However, to produce an overall mitigation evaluation of the optimal
design of a transport system, non-CO2 emissions, passenger
or freight occupancy factors, and indirect GHG emissions from vehicle
manufacture and infrastructure should also be integrated to gain a full
comparison of the relative GHG emissions across modes (see Section 8.4; Hawkins
et al., 2012; Borken-Kleefeld et al., 2013).
Taking LDVs as an example, a comparative assessment of
current and future fuel consumption reduction potentials per kilometre has been
made (Figure 8.7), starting from a 2010 baseline gasoline vehicle at about 8
lge[4] / 100km and 195 g / km CO2.
Using a range of technologies, average new LDV fuel economy can be doubled (in
units of distance per energy, i. e., energy intensity cut by 50 %). Further
improvements can be expected for hybrids, PHEVs, BEVs, and FCVs, but several
hurdles must be overcome to achieve wide market penetration (see Section 8.8).
Vehicle cost increases due to new technologies could affect customers’
willingness to pay, and thus affect market penetration, although cost increases
would be at least partly offset by fuel cost savings (see Section 8.6).
835
Behavioural aspects
The successful uptake of more
efficient vehicles, advanced technologies, new fuels, and the use of these
fuels and vehicles in ‘real life’ conditions, involves behavioural aspects.
Change in Energy Use per Vehicle km [%]
Figure
87 | Indicative fuel consumption reduction potential ranges for a
number of LDV technology drive-train and fuel options in 2010 and 2030,
compared with a baseline gasoline internal combustion engine (ICE) vehicle
consuming 8 l / 100km in 2010. (Based on Kobayashi et al., 2009; Plotkin et
al., 2009; IEA, 2012b; NRC, 2013).
• Purchase behaviour: Few consumers
attempt to minimize the lifecycle costs of vehicle ownership (Greene, 2010a),
which leads to a considerable imbalance of individual costs versus society-wide
benefits. There is often a lack of interest in purchasing more fuel efficient
vehicles (Wozny and Allcott, 2010) due to imperfect information, information
overload in decision making, and consumer uncertainty about future fuel prices
and vehicle life (Anderson et al., 2011; Small, 2012). This suggests that in
order to promote the most efficient vehicles, strong policies such as fuel
economy standards, sliding-scale vehicle tax systems, or ‘feebate’ systems with
a variable tax based on fuel economy or CO2 emissions may be
needed (Section 8.10) (Gallagher and Muehlegger, 2011). Vehicle characteristics
are largely determined by the desires of new-car buyers in wealthier countries,
so there may be a five-year or longer lag before new technologies reach
second-hand vehicle markets in large quantities, particularly through imports
to many developing countries (though this situation will likely change in the
coming decades as new car sales rise across non-OECD countries) (IEA, 2009).
•
New
technologies / fuels: Consumers’ unwillingness to purchase new types of
vehicles with significantly different attributes (such as smaller size, shorter
range, longer refuelling or recharging time, higher cost) is a potential
barrier to introducing innovative propulsion systems and fuels (Brozović and Ando,
2009). This may relate simply to the perceived quality of various attributes or
to risk aversion from uncertainty (such as driving range anxiety for
BEVs[5])
(Wenzel and Ross, 2005). The extent to which policies must compensate by
providing incentives varies but may be substantial (Gallagher and Muehlegger,
2011).
• On-road fuel economy: The fuel economy
of a vehicle as quoted from independent testing can be up to 30 % better than
that actually achieved by an average driver on the road (IEA, 2009; TMO, 2010;
ICCT, 2012). This gap reflects a combination of factors including inadequacies
in the test procedure, real-world driving conditions (e. g., road surface
quality, weather conditions), driver behaviour, and vehicle age and
maintenance. Also congested traffic conditions in OECD cities differ from
mixed-mode conditions in some developing countries (Tiwari et al., 2008; Gowri
et al., 2009). Some countries have attempted to adjust for these differences in
their public vehicle fuel economy information. A significant reduction in the
gap may be achievable by an ‘integrated approach’ that includes better traffic
management, intelligent transport systems, and improved vehicle and road
maintenance (IEA, 2012e).
• Eco-Driving: A 5 – 10 % improvement in
on-road fuel economy can be achieved for LDVs through efforts to promote
‘eco-driving’ (An et al., 2011; IEA, 2012d). Fuel efficiency improvements from
ecodriving for HDVs are in the 5 – 20 % range (AEA, 2011).
• Driving behaviour with new types of
vehicles: Taking electric vehicles (EVs) as an example, day / night
recharging patterns and the location of public recharging systems could affect
how much these vehicles are driven, when and where they are driven, and
potentially their GHG emissions impacts (Axsen and Kurani, 2012).
• Driving rebound effects: Reactions to
lowering the cost of travel (through fuel economy measures or using budget
airline operators) can encourage more travel, commonly known as the (direct)
rebound effect (Greene et al., 1999; for a general discussion of the rebound
effect see Section 5.6.1). In North America, fuel cost elasticity is in the
range of a – 0.05 to – 0.30 (e. g., a 50 % cut in the fuel cost would result in
a 2.5 % to 15 % increase in driving). Several studies show it is declining
(Hughes et al., 2006; Small and van Dender, 2007; EPA, 2012). The rebound
effect is larger when the marginal cost of driving (mostly gasoline) is a high
share of household income. The implication for non-OECD countries is that the price
elasticity of demand for vehicle travel will be a function of household income.
The rebound effect may be higher in countries with more modal choice options or
where price sensitivity is higher, but research is poor for most countries and
regions outside the OECD. Minimizing the rebound can be addressed by fuel taxes
or road pricing that offset the lower travel costs created by efficiency
improvements or reduced oil prices (see Section 8.10) (Hochman et al., 2010;
Rajagopal et al., 2011; Chen and Khanna, 2012).
• Vehicle choice-related rebounds: Other
types of rebound effect are apparent, such as shifts to purchasing larger cars
concurrent with cheaper fuel or shifts from gasoline to diesel vehicles that
give lower driving costs (Schipper and Fulton, 2012). Shifts to larger HDVs and
otherwise less expensive systems can divert freight from lower carbon modes,
mainly rail, and can also induce additional freight movements (Umweltbundesamt,
2007; TML, 2008; Leduc, 2009; Gillingham et al., 2013).
•
Company behaviour:
Behavioural change also has a business dimension. Company decision making can
exert a strong influence on the level of transport emissions, particularly in
the freight sector (Rao and Holt, 2005). Freight business operators have a
strong incentive to reduce energy intensity, since fuel typically accounts for
around one third of operating costs in the road freight sector, 40 % in
shipping, and 55 % in aviation (Bretzke, 2011). The resulting reductions in
transport costs can cause a rebound effect and generate some additional freight
movement (Matos and Silva, 2011). For company managers to switch freight
transport modes often requires a tradeoff of higher logistics costs for lower
carbon emissions (Winebrake et al., 2008). Many large logistics service
providers have set targets for reducing the carbon intensity of their
operations by between 20 % and 45 % over the period from 2005 / 2007 to 2020,
(McKinnon and Piecyk, 2012) whereas many smaller freight operators have yet to
act (Oberhofer and Fürst, 2012).
8.4 Infrastructure and systemic perspectives
Transport
modes, their infrastructures, and their associated urban fabric form a system
that has evolved into the cities and regions with which we are most familiar.
‘Walking cities’ existed for 8000 years; some are being reclaimed around their
walkability (Gehl, 2011). ‘Transit cities’ were built and developed around
trams, trolley buses, and Table
81 | High-speed rail transport infrastructure GHG emissions based
on LCA data. train systems since the mid 19th century (Cervero, 1998;
Newman and Kenworthy, 1999). ‘Automobile cities’ evolved from the advent of
cheap LDVs (Brueckner, 2000) and have become the dominant paradigm since the
1950s, leading to automobile dependence and automobility (Urry, 2007). A region
can be defined and understood in terms of the transport links to ports and
airports regardless of the number and types of cities located there. In all
cases, the inter-linkages between transport infrastructure and the built
environment establish path dependencies, which inform long-term
transport-related mitigation options. For a general discussion of urban form
and infrastructure see Chapter 12.4.
841 Path dependencies of infrastructure and
GHG emission impacts
Systemic change tends to be slow
and needs to address path dependencies embedded in sunk costs, high investment
levels, and cultural patterns. Technological and behavioural change can either
adapt to existing infrastructures, or develop from newly constructed
infrastructures, which could provide an initial template for low carbon
technologies and behaviour. Developments designed to improve infrastructure in
rapidly urbanizing developing countries will decisively determine the future
energy intensity of transport and concomitant emissions (Lefèvre, 2009), and
will require policies and actions to avoid lock-in.
The construction, operation, maintenance, and eventual
disposal of transport infrastructure (such as rail tracks, highways, ports, and
airports), all result in GHG emissions. These infrastructure-related emissions
are usually accounted for in the industry and building sectors. However, full
accounting of life cycle assessment (LCA) emissions from a
transport-perspective requires these infrastructure-related emissions to be
included along with those from vehicles and fuels (see Section 8.3.5). GHG
emissions per passenger-kilometre (p-km) or per tonne-kilometre (t-km) depend, inter alia, on the intensity of use of
the infrastructure and the share of tunnels, bridges, runways, etc. (Åkerman, 2011;
Chang and Kendall, 2011; UIC, 2012). In the United
Note: Since LCA assumptions vary,
the data can only be taken as indicative and not compared directly.
|
States, GHG emissions from infrastructure built for LDVs,
buses, and
air transport amount to 17 – 45
gCO2eq / p-km, 3 – 17 gCO2eq / p-km, and 5 – 9
gCO2eq / p-km respectively (Chester and Horvath, 2009) with
rail typically between 3 – 11 gCO2eq / p-km (see Table 8.1). Other than
for rail, relevant regional infrastructure-related GHG emissions research on
this topic is very preliminary.
Opportunities exist to
substantially reduce these infrastructure related emissions, for instance by up
to 40 % in rail (Milford and Allwood, 2010), by the increased deployment of
low-carbon materials and recycling of rail track materials at their end-of-life
(Network Rail, 2009; Du and Karoumi, 2012). When rail systems achieve modal
shift from road vehicles, emissions from the rail infrastructure may be
partially offset by reduced emissions from road infrastructures (Åkerman,
2011). To be policy-relevant, LCA calculations that include infrastructure need
to be contextualized with systemic effects such as modal shifts (see Sections
8.4.2.3 and 8.4.2.4).
Existing vehicle stock, road
infrastructure, and fuel-supply infrastructure prescribe future use and can
lock-in emission paths for decades while inducing similar investment because of
economies of scale (Shalizi and Lecocq, 2009). The life span of these
infrastructures ranges from 50 to more than 100 years. This range makes the
current development of infrastructure critical to the mode shift opportunities
of the future. For example, the successful development of the United States
interstate highway system resulted in a lack of development of an extensive
passenger rail system, and this determined a demand-side lock-in produced by
the complementarity between infrastructure and vehicle stock (Chapter 12.3.2).
The construction of the highway system accelerated the growth of road vehicle
kilometres travelled (VKT) around 1970, and ex-urban development away from city
centres created a second peak in road transport infrastructure investment post
1990 (Shalizi and Lecocq, 2009). Conversely, the current rapid development of
high-speed rail infrastructure in China (Amos et al., 2010) may provide low
emission alternatives to both road transport and aviation. Substantial
additional rail traffic has been generated by constructing new lines (Chapter
12.4.2.5), although a net reduction of emissions will only occur after
achieving a minimum of between 10 and 22 million passengers annually (Westin
and Kågeson, 2012).
Aviation and shipping require less fixed infrastructures
and hence tend to have a relative low infrastructure share of total lifecycle
emissions. Rising income and partially declining airfares have led to increased
air travel (Schäfer et al., 2009), and this correlates not only with new
construction and expansion of airports, but also with shifting norms in travel
behaviour (Randles and Mander, 2009).
842 Path dependencies of urban form and
mobility
Transport demand and land use are
closely inter-linked. In low-density developments with extensive road
infrastructure, LDVs will likely dominate modal choice for most types of trips.
Walking and cycling can be made easier and safer where high accessibility to a
variety of activities are located within relative short distances (Ewing and
Cervero, 2010) and when safe cycle infrastructure and pedestrian pathways are
provided (Tiwari and Jain, 2012; Schepers et al., 2013). Conversely the stress
and physical efforts of cycling and walking can be greater in cities that
consistently prioritize suburban housing developments, which leads to distances
that accommodate the high-speed movement and volume of LDVs (Naess, 2006). In
developing countries, existing high-density urban patterns are conducive to
walking and cycling, both with substantial shares. However, safe infrastructure
for these modes is often lacking (Thynell et al., 2010; Gwilliam, 2013).
Sustainable urban planning offers tremendous opportunities (reduced transport
demand, improved public health from non-motorized transport (NMT), less air
pollution, and less land use externalities) (Banister, 2008; Santos et al.,
2010; Bongardt et al., 2013; Creutzig et al., 2012a). As an example, an
additional 1.1 billion people will live in Asian cities in the next 20 years
(ADB, 2012a) and the majority of this growth will take place in small-medium
sized cities that are at an early stage of infrastructure development. This
growth provides an opportunity to achieve the longterm benefits outlined above
(Grubler et al., 2012) (see also 8.7 and Chapter 12.4.1).
Urban population density inversely correlates with GHG
emissions from land transport (Kennedy et al., 2009; Rickwood et al., 2011) and
enables non-motorized modes to be more viable (Newman and Kenworthy, 2006).
Disaggregated studies that analyze individual transport use confirm the
relationship between land use and travel (Echenique et al., 2012). Land use,
employment density, street design and connectivity, and high transit
accessibility also contribute to reducing car dependence and use (Handy et al.,
2002; Ewing, 2008; Cervero and Murakami, 2009; Olaru et al., 2011). The built
environment has a major impact on travel behaviour (Naess, 2006; Ewing and
Cervero, 2010), but residential choice also plays a substantial role that is
not easy to quantify (Cao et al., 2009; Ewing and Cervero, 2010). There exists
a non-linear relationship between urban density and modal choice (Chapter
12.4.2.1). For example, suburban residents drive more and walk less than
residents living in inner city neighbourhoods (Cao et al., 2009), but that is
often true because public transit is more difficult to deploy successfully in
suburbs with low densities (Frank and Pivo, 1994). Transport options that can
be used in low density areas include para-transit[6]
and car-sharing, both of which can complement individualized motorized
transport more efficiently and with greater customer satisfaction than can
public transit (Baumgartner and Schofer, 2011). Demand-responsive, flexible
transit, and car sharing services can have lower GHG emissions per passenger
kilometre with higher quality service than regional public transport (Diana et
al., 2007; Mulley and Nelson, 2009; Velaga et al., 2012; Loose, 2010).
The number of road
intersections along the route of an urban journey, the number of destinations
within walking distance, and land use diversity issues have been identified as
key variables for determining the modal choice of walking (Ewing and Cervero,
2010). Public transport use in the United States is related to the variables of
street network design and proximity to transit. Land use diversity is a
secondary factor.
8421 Modal
shift opportunities for passengers
Small but significant modal shifts from LDVs to bus rapid
transit (BRT) have been observed where BRT systems have been implemented.
Approximately 150 cities worldwide have implemented BRT systems, serving around
25 million passengers daily (Deng and Nelson, 2011; BRT Centre of Excellence,
EMBARQ, IEA and SIBRT, 2012). BRT systems can offer similar benefits and
capacities as light rail and metro systems at much lower capital costs (Deng
and Nelson, 2011), but usually with higher GHG emissions (depending on the
local electricity grid GHG emission factor) (Table 8.2). High occupancy rates
are an important requirement for the economic and environmental viability of
public transport.
Public transit, walking, and cycling are closely related. A
shift from non-motorized transport (NMT) to LDV transport occurred during the
20th century, initially in OECD countries and then globally. However, a
reversion to cycling and walking now appears to be happening in many cities —
mostly in OECD countries — though accurate data is scarce (Bassett et al., 2008;
Pucher et al., 2011). Around 90 % of all public transit journeys in the United
States are accompanied with a walk to reach the final destination and 70 % in
Germany (Pucher and Buehler, 2010). In Germany, the Netherlands, Denmark, and
elsewhere, the cycling modal share of total trips has increased since the 1970s
and are now between 10 – 25 % (Pucher and Buehler, 2008). Some carbon emission
reduction has resulted from cycle infrastructure deployment in some European
cities (COP, 2010; Rojas-Rueda et al., 2011; Creutzig et al., 2012a) and in
some cities in South and North America (USCMAQ, 2008; Schipper et al., 2009;
Massink et al., 2011; USFHA, 2012). Walking and cycling trips vary
substantially between countries, accounting for over 50 % of daily trips in the
Netherlands and in many Asian and African cities (mostly walking); 25 – 35 % in
most European countries; and approximately 5 – 10 % in the United States and
Australia (Pucher and Buehler, 2010; Leather et al., 2011; Pendakur, 2011; Mees
and Groenhart, 2012).
The causes for high modal share
of NMT differ markedly between regions depending on their cultures and
characteristics. For example, they tend to reflect low-carbon urban policies in
OECD countries such as the Netherlands, while reflecting a lack of motorization
in developing countries. Land use and transport policies can influence the
bicycle modal share considerably (Pucher and Buehler, 2006), most notably by
the provision of separate cycling facilities along heavily traveled roads and
at intersections, and traffic-calming of residential neighbourhoods (Andrade et
al., 2011; NRC, 2011b) Many Indian
and Chinese cities with traditionally high levels of walking are now reporting
dramatic decreases in this activity (Leather et al., 2011), with modal shifts
to personal transport including motorbikes and LDVs. Such shifts are to some
degree inevitable, and are in part desirable as they reflect economic growth.
However, the maintenance of a healthy walking and cycling modal share could be
a sign of a liveable and attractive city for residents and businesses (Bongardt
et al., 2011; Gehl, 2011).
Deliberate policies based around
urban design principles have increased modal shares of walking and cycling in
Copenhagen, Melbourne, and Bogota (Gehl, 2011). Public bicycle share systems
have created a new mode for cities (Shaheen et al., 2010), with many cities now
implementing extensive public cycling infrastructure, which results in
increased bicycle modal share (DeMaio, 2009). Revising electric bicycle
standards to enable higher performance could increase the feasible commuting
range and encourage this low emissions personal transport mode. Electric
bicycles offer many of the benefits of LDVs in terms of independence,
flexibility of routes, and scheduling freedom, but with much lower emissions
and improved health benefits.
|
Table 82 | Comparison of capital costs,
direct CO2 emissions, and capacities for BRT, light rail, and
metro urban mass transit options (IEA, 2012e).
|
With rising income and
urbanization, there will likely be a strong pull toward increasing LDV
ownership and use in many developing countries. However, public transit mode
shares have been preserved at fairly high levels in cities that have achieved
high population densities and that have invested heavily in high quality
transit systems (Cervero, 2004). Their efficiency is increased by diverse forms
of constraints on LDVs, such as reduced number of lanes, parking restrictions,
and limited access (La Branche, 2011). Investments in mass rapid transit, timed
with income increases and population size / density increases, have been
successful in some Asian megacities (Acharya and Morichi, 2007). As traffic
congestion grows and freeway infrastructure reaches physical, political, and
economic limits, the modal share of public transit has increased in some OECD
countries (Newman and Kenworthy, 2011b).
High-speed rail can substitute for short-distance passenger
air travel (normally up to around 800 km but also for the 1500 km in the case
of Beijing to Shanghai), as well as for most road travel over those distances,
and hence can mitigate GHG emissions (McCollum et al., 2010; IEA, 2008). With
optimized operating speeds and long distances between stops, and high passenger
load factors, energy use per passenger-km could be as much as 65 to 80 % less
than air travel (IEA, 2008). A notable example is China, which has shown a fast
development of its high-speed rail system. When combined with strong landuse
and urban planning, a high-speed rail system has the potential to restructure
urban development patterns, and may help to alleviate local air pollution, noise,
road, and air congestion (McCollum et al., 2010).
8422 Modal
shift opportunities for freight
Over the past few decades, air
and road have increased their global share of the freight market at the expense
of rail and waterborne transport (European Environment Agency, 2011; Eom et
al., 2012). This has been due to economic development and the related change in
the industry and commodity mix, often reinforced by differential rates of
infrastructure improvement and the deregulation of the freight sector, which
typically favours road transport. Inducing a substantial reversal of recent
freight modal split trends will be difficult, inter alia because of ‘structural inelasticity’ which confines
shorter distance freight movements to the road network because of its much
higher network density (Rich et al., 2011). If growth in global truck travel
between 2010 and 2050 could be cut by half from the projected 70 % and shifted
to expanded rail systems, about a 20 % reduction in fuel demand and CO2
could be achieved, with only about a fifth of this savings being offset by
increased rail energy use (IEA, 2009). The European Commission (EC) set an
ambitious target of having all freight movements using rail or waterborne modes
over distances greater than 300 km by 2030, leading to major changes in modal
shares (Figure 8.8) (Tavasszy and Meijeren, 2011; EC, 2013).
The capacity of the European rail
network would have to at least double to handle this increase in freight
traffic and the forecast growth in rail passenger volumes, even if trains get
longer and run empty less often (den Boer et al., 2011). Longer-term
transformations need to take account of the differential rates at which
low-carbon technologies could impact on the future carbon intensity of freight
modes. Applying current average energy intensity values (Section 8.3.1) may
result in over-estimates of the potential carbon benefits of the modal shift
option. Although rail freight generates far lower GHG emissions per
tonne-kilometre than road (Table 8.3), the rate of carbon-related technical
innovation, including energy efficiency improvements, has been faster in HDV
than rail freight and HDV replacement rate is typically much shorter, which
ensures a more rapid uptake of innovation.
The potential for shifting freight to greener modes is
difficult in urban areas. Improvements in intra-urban rail freight movements
are possible (Maes and Vanelslander, 2011), but city logistical systems are
almost totally reliant on road vehicles and are likely to remain so. The
greater the distance of land haul for freight, the more competitive the lower
carbon modes become. Within cities, the concept of modal split between
passenger and freight movement can be related to the interaction. Currently,
large amounts of freight on the so-called ‘last mile’ to a home or business are
carried by shoppers in LDVs and public transport vehicles. With the rapid
growth of on-line retailing, much private car-borne freight, which seldom
appears in freight transport statistics, will be transferred to commercial
delivery vans. Comparative analyses of conventional and on-line retailing
suggest that substituting a van delivery for a personal shopping trip by
private car can yield a significant carbon saving (Edwards et al., 2010).
At the international level,
opportunities for switching freight from air to shipping services are limited.
The two markets are relatively discrete and the products they handle have
widely differing monetary values and time-sensitivity. The deceleration of
deep-sea container vessels in recent years in accordance with the ‘slow
steaming’ policies of the shipping lines has further widened the transit time
gap between sea and air services. Future increases in the cost of fuel may,
however, encourage businesses to economize on their use of air-freight,
possibly switching to sea-air services in which products are air-freighted for
only part of the way. This merger of sea and air transport offers substantial
cost and CO2 savings for companies whose global supply
chains are less time-critical (Conway, 2007; Terry, 2007).
Figure 88 | Projected freight modal split in
the EU-25 in 2030 comparing 2011 shares with future business-as-usual shares
without target and with EU White Paper modal split target. Source: Based on
Tavasszy and Meijeren, 2011.
8.5 Climate
change feedback and interaction with adaptation
Transport is impacted by
climate change both positively and negatively. These impacts are dependent on
regional variations in the nature and degree of climate change and the nature
of local transport infrastructure and systems. Adapting transport systems to
the effects of climate in some cases complement mitigations efforts while in
others they have a counteracting effect. Little research has so far been
conducted on the inter-relationship between adaptation and mitigation
strategies in the transport sector.
851 Accessibility and feasibility of
transport routes
Decreases in the spatial and temporal extent of ice cover in
the Arctic and Great Lakes region of North America regions are opening new and
shorter shipping routes over longer periods of the year (Drobot et al., 2009;
Stephenson et al., 2011). The expanded use of these routes could reduce GHG
emissions due to a reduction in the distance travelled. For example, the
Northern Sea Route (NSR) between Shanghai and Rotterdam is approximately 4,600
km shorter (about 40 %) than the route via the Suez Canal. The NSR passage
takes 18 – 20 days compared to 28 – 30 days via the southern route (Verny and
Grigentin, 2009). Climate change will not only affect ice coverage, but may
also increase the frequency and severity of northern hemisphere blizzards and
arctic cyclones, deterring use of these shorter routes (Wassmann, 2011; Liu et
al., 2012). It is, nevertheless, estimated that the transport of oil and gas
through the NSR could increase from 5.5 Mt in 2010 to 12.8 Mt by 2020 (Ho,
2010). The passage may also become a viable option for other bulk carriers and
container shipping in the near future (Verny & Grigentin, 2009; Schøyen
& Bråthen, 2011). The economic viability of the NSR is still uncertain
without assessments of potentially profitable operation (Liu and Kronbak, 2010)
and other more pessimistic prospects for the trans-Arctic corridors (Econ,
2007). One possible negative impact would be that the increase in shipping
through these sensitive ecosystems could lead to an increase in local
environmental and climate change impacts unless additional emissions controls
are introduced along these shipping routes (Wassmann, 2011). Of specific
concern are the precursors of photochemical smog in this polar region that
could lead to additional local positive regional climate forcing (Corbett et
al., 2010) and emissions of black carbon (see Section 8.2.2.1). Measurement
methods of black carbon emissions from ships and additional work to evaluate
their impact on the Arctic are needed before possible control measures can be
investigated.
Changes in climate are also
likely to affect northern inland waterways (Millerd, 2011). In summer, these
effects are likely to adversely affect waterborne craft when reductions in
water levels impair navigability and cut capacity (Jonkeren et al., 2007;
Görgen et al. 2010; Nilson et al., 2012). On the other hand, reduced winter
freezing can benefit inland waterway services by extending the season. The net
annual effect of climate change on the potential for shifting freight to this
low-carbon mode has yet to be assessed.
852 Relocation of production and reconfiguration of global supply chains
Climate change will induce changes to patterns of
agricultural production and distribution (Ericksen et al., 2009; Hanjra and
Qureshi, 2010; Tirado et al., 2010; Nielsen and Vigh, 2012; Teixeira et al.,
2012). The effect of these changes on freight transport at different
geographical scales are uncertain (Vermeulen et al., 2012). In some scenarios,
food supply chains become longer, generating more freight movement (Nielsen and
Vigh, 2012; Teixeira et al., 2012). These and other long supply lines created by
globalization could become increasingly vulnerable to climate change. A desire
to reduce climate risk may be one of several factors promoting a return to more
localized sourcing in some sectors (World Economic Forum and Accentura, 2009),
a trend that would support mitigation. Biofuel production may also be adversely
affected by climate change inhibiting the switch to lower carbon fuels (de
Lucena et al., 2009).
853
Fuel combustion and technologies
Increased ambient temperatures
and humidity levels are likely to affect nitrogen oxide, carbon monoxide,
methane, black carbon, and other particulate emissions from internal combustion
engines and how these gases interact with the atmosphere (Stump et al., 1989;
Rakopoulos, 1991; Cooper and Ekstrom, 2005; Motallebi et al., 2008; Lin and
Jeng, 1996; McCormick et al., 1997; Pidolal, 2012). Higher temperatures also
lead to higher evaporative emissions of volatile organic compound emissions
(VOCs) (Roustan et al., 2011) and could lead to higher ozone levels (Bell et al.,
2007). The overall effects are uncertain and could be positive or negative
depending on regional conditions (Ramanathan & Carmichael, 2008).
As global average temperatures
increase, the demand for on-board cooling in both private vehicles and on
public transport will increase. The heating of vehicles could also grow as the
frequency and severity of cold spells increase. Both reduce average vehicle
fuel efficiencies. For example, in a passenger LDV, air-conditioning can
increase fuel consumption by around 3 – 10 % (Farrington and Rugh, 2000; IEA,
2009). Extremes in temperature (both high and low) negatively impact on the
driving range of electric vehicles due to greater use of on-board heating and
air conditioning, and thus will require more frequent recharging. In the
freight sector, energy consumption and emissions in the refrigeration of
freight flows will also increase as the extent and degree of
temperature-control increases across the supply chains of food and other
perishable products (James and James, 2010).
854
Transport infrastructure
Climate proofing and adaptation
will require substantial infrastructure investments (see Section 8.4 and the
Working Group II (WGII) Contribution to the IPCC Fifth Assessment Report (AR5),
Chapter 15). This will generate additional freight transport if implemented
outside of the normal infrastructure maintenance and upgrade cycle. Climate
proofing of transport infrastructure can take many forms (ADB, 2011a; Highways
Agency, 2011) varying in the amount of additional freight movement required.
Resurfacing a road with more durable materials to withstand greater temperature
extremes may require no additional freight movement, whereas re-routing a road
or rail link, or installing flood protection, are likely to generate additional
logistics demands, which have yet to be quantified.
Adaptation efforts are likely to
increase transport infrastructure costs (Hamin & Gurran, 2009), and
influence the selection of projects for investment. In addition to inflating
maintenance costs (Jollands et al., 2007; Larsen et al., 2008), climate
proofing would divert resources that could otherwise be invested in extending
networks and expanding capacity. This is likely to affect all transport modes
to varying degrees. If, for example, climate proofing were to constrain the
development of a rail network more than road infrastructure, it might inhibit a
modal shift to less carbon-intensive rail services.
The future choice of freight and
passenger traffic between modes may also become more responsive to their
relative sensitivity to extreme weather events (Koetse and Rietveld, 2009;
Taylor and Philp, 2010). The exposure of modes to climate risks include
aviation (Eurocontrol, 2008), shipping (Becker et al., 2012), and land
transport (Hunt and Watkiss, 2011). Little attempt has been made to conduct a
comparative analysis of their climate risk profiles, to assess the effects on
the modal choice behaviour of individual travellers and businesses, or to take
account of regional differences in the relative vulnerability of different
transport modes to climate change (Koetse and Rietveld, 2009).
Overall, the transport sector will be highly exposed to
climate change and will require extensive adaptation of infrastructure,
operations, and service provision. It will also be indirectly affected by the
adaptation and decarbonization of the other sectors that it serves. Within the
transport sector there will be a complex interaction between adaptation and
mitigation efforts. Some forms of adaptation, such as infrastructural climate
proofing, will be likely to generate more freight and personal movement, while
others, such as the NSR, could substantially cut transport distances and
related emissions.
8.6 Costs and potentials
For transport, the potential for
reducing GHG emissions, as well as the associated costs, varies widely across
countries and regions. Appropriate policies and measures that can accomplish
such reductions also vary (see Section 8.10) (Kahn Ribeiro et al., 2007; Li,
2011). Mitigation costs and potentials are a function of the stringency of
climate goals and their respective GHG concentration stabilization levels
(Fischedick et al., 2011; Rogelj et al., 2013). This section presents estimates
of mitigation potentials and associated costs from the application of new
vehicle and fuel technologies, performance efficiency gains, operational
measures, logistical improvements, electrification of modes, and low-carbon
fuels and activity reduction for different transport modes (aviation, rail,
road, waterborne and cross-modal). Potential CO2eq emissions
reductions from passenger-km (p-km) and tonne-km (t-km) vary widely by region,
technology, and mode according to how rapidly the measures and applications can
be developed, manufactured, and sold to buyers replacing existing ones in
vehicles an fuels or adding to the total fleet, and on the way they are used
given travel behaviour choices (Kok et al., 2011). In general, there is a
larger emission reduction potential in the transport sector, and at a lower cost,
compared to the findings in AR4 (Kahn Ribeiro et al., 2007).
The efforts undertaken to reduce activity, to influence
structure and modal shift, to lower energy intensity, and to increase the use
of low-carbon fuels, will influence future costs and potentials. Ranges of
mitigation potentials have an upper boundary based on what is currently
understood to be technically achievable, but will most likely require strong
policies to be achieved in the next few decades (see Section 8.10). Overall
reductions are sensitive to per-unit transport costs (that could drop with
improved vehicle efficiency); resulting rebound effects; and shifts in the
type, level, and modal mix of activity. For instance, the deployment of more
efficient, narrow-body jet aircraft could increase the number of
commerciallyattractive, direct city-to-city connections, which may result in an
overall increase in fleet fuel use compared to hub-based operations.
This assessment follows a bottom-up approach to maintain
consistency in assumptions. Table 8.3 outlines indicative direct mitigation
costs using reference conditions as baselines, and illustrative examples of
existing vehicles and situations for road, aviation, waterborne, and rail (as
well as for some cross-mode options) available in the literature. The data
presented on the cost-effectiveness of different carbon reduction measures is
less detailed than data on the potential CO2eq savings due to
literature gaps. The number of studies assessing potential future GHG reductions
from energy intensity gains and use of low-carbon fuels is larger than those
assessing mitigation potentials and cost from transport activity, structural
change and modal shift, since they are highly variable by location and
background conditions.
Key assumptions made in this analysis were:
•
cost estimates are based on societal costs and
benefits of technologies, fuels, and other measures, and take into account
initial costs as well as operating costs and fuel savings;
•
existing transport options are compared to
current base vehicles and activities, whereas future options are compared to
estimates of baseline future technologies and other conditions;
•
fuel price projections are based on the IEA
World Energy Outlook (IEA, 2012b) and exclude taxes and subsidies where
possible;
•
discount rates of 5 % are used to bring future
estimates back to present (2013) values, though the literature considered has
examined these issues mostly in the developed-world context; and
•
indirect responses that occur through complex
relationships within sectors in the larger socioeconomic system are not
included (Stepp et al., 2009).
Results in Table 8.3 indicate that, for LDVs, efficiency
improvement potentials of 50 % in 2030 are technically possible compared to
2010, with some estimates in the literature even higher (NRC, 2010). Virtually
all of these improvements appear to be available at very low, or even negative,
societal costs. Electric vehicles have a CO2eq reduction cost
highly correlated with the carbon intensity of electricity generation: using
relatively high-carbon intensity electricity systems (500 – 600 gCO2eq
/ kWh), EVs save little CO2eq compared to conventional LDVs and the
mitigation cost can be many hundreds of dollars per tonne; for very low-carbon
electricity (below 200 gCO2eq / kWh) the mitigation cost drops
below 200 USD2010 / tCO2eq. In the future,
with lower battery costs and low-carbon electricity, EVs could drop below 100
USD2010 / tCO2eq and even approach zero net cost.
For long-haul HDVs, up to a 50 % reduction in energy
intensity by 2030 appears possible at negative societal cost per tCO2eq
due to the very large volumes of fuel they use. HDVs used in urban areas where
their duty cycle does not require as much annual travel (and fuel use), have a
wider range of potentials and costs, reaching above 100 USD2010
/ t CO2eq. Similarly, inter-city buses use more fuel annually than
urban buses, and as a result appear to have more low-cost opportunities for CO2eq
reduction (IEA, 2009; NRC, 2010; TIAX, 2011).
Recent
designs of narrow and wide-body commercial aircraft are significantly more
efficient than the models they replace, and provide CO2eq
reductions at net negative societal cost when accounting for fuel savings over
10 – 15 years of operation at 5 % discount rate. An additional 30 – 40 % CO2eq
reduction potential is expected from future new aircraft in the 2020 – 2030
time frame, but the mitigation costs are uncertain and some promising
technologies, such as open rotor engines, appear expensive (IEA, 2009; TOSCA,
2011).
For virtually all types of
ocean-going ships including container vessels, bulk carriers, and oil tankers,
the potential reduction in CO2eq emissions is estimated to be over 50
% taking into account a wide range of technology and operational changes. Due
to the large volume of fuel used annually by these ships, the net cost of this
reduction is likely to be negative (Buhaug and et. al, 2009; Crist, 2009).
Key factors in the long term
decarbonization of rail transport will be the electrification of services and
the switch to low-carbon electricity generation, both of which will vary widely
by country. Potential improvements of 35 % energy efficiency for United States
rail freight, 46 % for European Union rail freight and 56 % for EU passenger
rail services have been forecast for 2050 (Anderson et al., 2011; Vyas et al.,
2013). The EU improvements will yield a 10 – 12 % reduction in operating costs,
though no information is available on the required capital investment in
infrastructure and equipment.
Regarding fuel substitution in
all modes, some biofuels have the potential for large CO2eq
reduction, although net GHG impact assessments are complex (see Sections 8.3
and 11.13). The cost per tonne of CO2eq avoided will be
highly dependent on the net CO2eq reduction and the relative cost of
the biofuel compared to the base fuel (e. g., gasoline or diesel), and any
technology changes required to the vehicles and fuel distribution network in
order to accommodate new fuels and blends. The mitigation cost is so sensitive
that, for example, while an energy unit of biofuel that cuts CO2eq
emissions by 80 % compared to gasoline and costs 20 % more has a mitigation
cost of about 80 USD / t CO2eq, if the biofuel’s cost drops to parity
with gasoline, the mitigation cost drops to 0 USD / t CO2eq
(IEA, 2009).
The mitigation potentials from
reductions in transport activity consider, for example, that “walking and cycle
track networks can provide 20 % (5 – 40 % in sensitivity analyses) induced walking and cycle journeys that
would not have taken place without the new networks, and around 15 % (0 – 35 %
in sensitivity analyses) of current journeys less than 5 km made by car or
public transport can be replaced by
walking or cycling” (Sælensminde, 2004). Urban journeys by car longer than
5 km can be replaced by combined use of
non-motorized and intermodal public transport services (Tirachini and Hensher,
2012).
 |
 |
 |
8.7 Co-benefits, risks and spillovers
Mitigation in the transport
sector has the potential to generate synergies and co-benefits with other
economic, social, and environmental objectives. In addition to mitigation costs
(see Section 8.6), the deployment of mitigation measures will depend on a
variety of other factors that relate to the broader objectives that drive
policy choices. The implementation of policies and measures can have positive
or negative effects on these other objectives — and vice versa. To the extent
these effects are positive, they can be deemed as ‘co-benefits’; if adverse and
uncertain, they imply risks. Potential co-benefits and adverse side effects of
alternative mitigation measures (Section 8.7.1), associated technical risks and
uncertainties (Section 8.7.2), and public perceptions (Section 8.7.3) can
significantly affect investment decisions and individual behaviour as well as
influence the priority-setting of policymakers. Table 8.4 provides an overview
of the potential co-benefits and adverse side-effects of the mitigation
measures that are assessed in this chapter. In accordance with the three
sustainable development pillars described in Sections 4.2 and 4.8, the table
presents effects on objectives that may be economic, social, environmental, and
health related. The extent to which co-benefits and adverse side effects will
materialize in practice, and their net effect on social welfare, differ greatly
across regions. Both are strongly dependent on local circumstances and
implementation practices as well as on the scale and pace of the deployment of
the different mitigation measures (see Section 6.6).
871
Socio-economic, environmental, and health effects
Transport relies almost entirely on oil with about 94 % of
transport fuels being petroleum products (IEA, 2011b). This makes it a key area
of energy security concern. Oil is also a major source of harmful emissions
that affect air quality in urban areas (see Section 8.2) (Sathaye et al.,
2011). In scenario studies of European cities, a combination of public transit
and cycling infrastructures, pricing, and land-use measures is projected to
lead to notable co-benefits. These include improved energy security, reduced
fuel spending, less congestion, fewer accidents, and increased public health
from more physical activity, less air pollution and less noise-related stress
(Costantini et al., 2007; Greene, 2010b; Rojas-Rueda et al., 2011; Rojas-Rueda
et al., 2012; Creutzig et al., 2012a). However, only a few studies have
assessed the associated welfare effects comprehensively and these are hampered
by data uncertainties. Even more fundamental is the epistemological uncertainty
attributed to different social costs. As a result, the range of plausible
social costs and benefits can be large. For example, the social costs of the
co-dimensions congestion, air pollution, accidents, and noise in Beijing were
assessed to equate to between 7.5 % to 15 % of GDP (Creutzig and He, 2009).
Improving energy security, mobility access, traffic congestion, public health,
and safety are all important policy objectives that can possibly be influenced
by mitigation actions (Jacobsen, 2003; Goodwin, 2004; Hultkrantz et al., 2006;
Rojas-Rueda et al., 2011).
Energy security. Transport stands out in comparison to other energy
end-use sectors due to its almost complete dependence on petroleum products
(Sorrell and Speirs, 2009; Cherp et al., 2012). Thus, the sector suffers from
both low resilience of energy supply and, in many countries, low sufficiency of
domestic resources. (For a broader discussion on these types of concerns see
Section 6.6.2.2). The sector is likely to continue to be dominated by oil for
one or more decades (Costantini et al., 2007). For oil-importing countries, the
exposure to volatile and unpredictable oil prices affects the terms of trade
and their economic stability. Measuring oil independence is possible by
measuring the economic impact of energy imports (Greene, 2010b). Mitigation
strategies for transport (such as electrifying the sector and switching to
biofuels) would decrease the sector’s dependence on oil and diversify the
energy supply, thus increasing resilience (Leiby, 2007; Shakya and Shrestha,
2011; Jewell et al., 2013). However, a shift away from oil could have
implications for energy exporters (see Chapter 14). Additionally, mitigation
measures targeted at reducing the overall transport demand — such as more
compact urban form with improved transport infrastructure and journey distance
reduction and avoidance (see Sections 8.4 and 12.4.2.1) — may reduce exposure
to oil price volatility and shocks (Sovacool and Brown, 2010; Leung, 2011;
Cherp et al., 2012).
Access and mobility.
Mitigation strategies that foster multi-modality are likely to foster improved
access to transport services particularly for the poorest and most vulnerable
members of society. Improved mobility usually helps provide access to jobs,
markets, and facilities such as hospitals and schools (Banister, 2011b;
Boschmann, 2011; Sietchiping et al., 2012). More efficient transport and modal
choice not only increases access and mobility it also positively affects
transport costs for businesses and individuals (Banister, 2011b). Transport
systems that are affordable and accessible foster productivity and social
inclusion (Banister, 2008; Miranda and Rodrigues da Silva, 2012).
Employment impact. In
addition to improved access in developing countries, a substantial number of
people are employed in the formal and informal public transport sector
(UN-Habitat, 2013). A shift to public transport modes is likely to generate
additional employment opportunities in this sector (Santos et al., 2010).
However, the net effect on employment of a shift towards low-carbon transport
remains unclear (UNEP, 2011).
Traffic congestion.
Congestion is an important aspect for decision makers, in particular at the
local level, as it negatively affects journey times and creates substantial
economic cost (Goodwin, 2004; Duranton and Turner, 2011). For example, in the
United States in 2000, time lost in traffic amounted to around 0.7 % of GDP
(Federal Highway Administration, 2000) or approximately 85 billion USD2010.
This increased to 101 billion USD2010 in 2010, also being 0.7 % of GDP,
but with more accurate data covering the cost per kilometre travelled of each
major vehicle type for 500 urban centres (Schrank et al., 2011). Time lost was
valued at 1.2 % of GDP in the UK (Goodwin, 2004); 3.4 % in Dakar, Senegal; 4 %
in Manila, Philippines (Carisma and Lowder, 2007); 3.3 % to 5.3 % in Beijing,
China (Creutzig and He, 2009); 1 % to 6 % in Bangkok, Thailand (World Bank,
2002) and up to 10 % in Lima, Peru where people on average spend around four
hours in daily travel (JICA, 2005; Kunieda and Gauthier, 2007).
Modal shifts that reduce traffic
congestion can simultaneously reduce GHG emissions and short-lived climate
forcers. These include road congestion pricing, modal shifts from aviation to
rail, and shifts from LDVs to public transport, walking, and cycling (Cuenot et
al., 2012). However, some actions that seek to reduce congestion can induce
additional travel demand, for example, expansions of airport infrastructure or
construction of roads to increase capacity (Goodwin, 2004; ECMT, 2007; Small
and van Dender, 2007).
Health. Exposure to
vehicle exhaust emissions can cause cardiovascular, pulmonary, and respiratory
diseases and several other negative health impacts (McCubbin, D. R., Delucchi,
1999; Medley et al., 2002; Chapters 7.9.2, 8.2, and WG II Chapter 11.9). In
Beijing, for example, the social costs of air pollution were estimated to be as
high as those for time delays from congestion (Creutzig and He, 2009). Various
strategies to reduce fuel carbon intensity have varying implications for the
many different air pollutants. For example, many studies indicate lower carbon
monoxide and hydrocarbon emissions from the displacement of fossil-based
transport fuels with biofuels, but NOx emissions are often
higher. Advanced biofuels are expected to improve performance, such as the low
particulate matter emissions from ligno-cellulosic ethanol (see Hill et al.,
2009, Sathaye et al., 2011 and Section 11.13.5). Strategies that target local
air pollution, for example switching to electric vehicles, have the potential
to also reduce CO2 emissions (Yedla et al., 2005) and black carbon emissions
(UNEP and WMO, 2011) provided the electricity is sourced from low-carbon
sources. Strategies to improve energy efficiency in the LDV fleet though
fostering dieselpowered vehicles may affect air quality negatively
(Kirchstetter et al., 2008; Schipper and Fulton, 2012) if not accompanied by
regulatory measures to ensure emission standards remain stable. The structure
and design of these strategies ultimately decides if this potential can be
realized (see Section 8.2).
Transport also contributes to noise
and vibration issues, which affect human health negatively (WHO, 2009;
Oltean-Dumbrava et al., 2013; Velasco et al., 2013). Transport-related human
inactivity has also been linked to several chronic diseases (WHO, 2008). An
increase in walking and cycling activities could therefore lead to health
benefits but conversely may also lead to an increase in traffic accidents and a
larger lung intake of air pollutants (Kahn Ribeiro et al., 2012; Takeshita,
2012). Overall, the benefits of walking and cycling significantly outweigh the
risks due to pollution inhalation (Rojas-Rueda et al., 2011; Rabl and de
Nazelle, 2012).
Assessing the social cost of public health is a contested
area when presented as disability-adjusted life years (DALYs). A reduction in
CO2emissions through an increase in active travel and less use of ICE vehicles
gave associated health benefits in London (7,332 DALYs per million population
per year) and Delhi (12,516 (DALYs / million capita) / yr) — significantly more
than from the increased use of loweremission vehicles (160 (DALYs / million
capita) / yr) in London, and 1,696 in Delhi) (Woodcock et al., 2009). More
generally, it has been found consistently across studies and methods that
public health benefits (induced by modal shift from LDVs to non-motorized
transport) from physical activity outweighs those from improved air quality
(Woodcock et al., 2009; de Hartog et al., 2010; Rojas-Rueda et al., 2011;
Grabow et al., 2012; Maizlish et al., 2013). In a similar trend, reduced car
use in Australian cities has been shown to reduce health costs and improve
productivity due to an increase in walking (Trubka et al., 2010a).
Safety The
increase in motorized road traffic in most countries places an increasing
incidence of accidents with 1.27 million people killed globally each year, of
which 91 % occur in low and middle-income countries (WHO, 2011). A further 20
to 50 million people suffer serious injuries (WHO, 2011). By 2030, it is
estimated that road traffic injuries will constitute the fifth biggest reason
for premature deaths (WHO, 2008). Measures to increase the efficiency of the
vehicle fleet can also positively affect the crash-worthiness of vehicles if
more stringent safety standards are adopted along with improved efficiency
standards (Santos et al., 2010). Lack of access to safe walking, cycling, and
public transport infrastructure remains an important element affecting the
success of modal shift strategies, in particular in developing countries
(Sonkin et al., 2006; Tiwari and Jain, 2012).
Fossil fuel displacement. Economists have criticized the
assumption that each unit of energy replaces an energy-equivalent quantity of
fossil energy, leaving total fuel use unaffected (Drabik and de Gorter, 2011;
Rajagopal et al., 2011; Thompson et al., 2011). As with other energy sources,
increasing energy supply through the production of bioenergy affects energy
prices and demand for energy services, and these changes in consumption also
affect net global GHG emissions (Hochman et al., 2010; Rajagopal et al., 2011;
Chen and Khanna, 2012). The magnitude of the effect of increased biofuel
production on global fuel consumption is uncertain (Thompson et al., 2011) and
depends on how the world responds in the long term to reduced petroleum demand
in regions using increased quantities of biofuels. This in turn depends on the
Organization of Petroleum Exporting Countries’ (OPEC) supply response and with
China’s and India’s demand response to a given reduction in the demand for
petroleum in regions promoting biofuels, and the relative prices of biofuels
and fossil fuels including from hydraulic fracturing (fracking) (Gehlhar et
al., 2010; Hochman et al., 2010; Thompson et al., 2011). Notably, if the
percentage difference in GHG emissions between an alternative fuel and the
incumbent fossil fuel is less than the percentage rebound effect (the fraction
not displaced, in terms of GHG emissions), a net increase in GHG emissions will
result from promoting the alternative fuel, despite its nominally lower rating
(Drabik and de Gorter, 2011).
Table
84 | Overview of potential co-benefits (green
arrows) and adverse side effects (orange arrows) of the
main mitigation measures in the transport sector. Arrows pointing up / down
denote positive / negative effect on the respective objective / concern; a
question mark (?) denotes an
uncertain net effect. Co-benefits and adverse side-effects depend on local
circumstances as well as on the implementation practice, pace, and scale (see
Section 6.6). For an assessment of macroeconomic, cross-sectoral effects
associated with mitigation policies (e. g., energy prices, consumption, growth,
and trade), see Sections 3.9, 6.3.6, 13.2.2.3 and 14.4.2. For possible upstream
effects of low-carbon electricity and biomass supply, see Sections 7.9 as well
as 11.7 and 11.13.6. Numbers in brackets correspond to references below the table.
|
Mitigation
measures
|
|
Effect
on additional objectives / concerns
|
|
|||
|
|
Economic
|
|
Social
(including health)
|
|
Environmental
|
|
|
Reduction
of fuel carbon intensity: electricity,
hydrogen, CNG, biofuels, and other fuels
|
↑
↑
|
Energy
security (diversification, reduced oil dependence and exposure to oil price
volatility) (1 – 3,32 – 34,94)
Technological spillovers (e. g., battery technologies for
consumer electronics)
(17,18,44,55,90)
|
?
↓
↑
↓
↓
|
Health
impact via urban air pollution (59,69) by
CNG,
biofuels: net effect unclear
(13,14,19,20,36,50)
Electricity, hydrogen:
reducing most pollutants (13,20,21,36,58,63,92)
Shift to diesel: potentially increasing pollution
(11,23,25)
Health impact via reduced noise (electricity and fuel cell
LDVs) (10,61,64 – 66,82)
Road safety (silent
electric LDVs at low speed) (56)
|
↓
↑ ?
|
Ecosystem impact of electricity and hydrogen via:
Urban
air pollution (13,20,69,91 – 93)
Material use (unsustainable resource mining) (17,18)
Ecosystem impact of
biofuels (24,41,42,89)
|
|
Reduction
of energy intensity
|
↑
|
Energy security (reduced
oil dependence and exposure to oil price volatility) (1 – 3,32 – 34)
|
↓
↑
|
Health impact via reduced urban air pollution
(22,25,43,59,62,69,84)
Road safety
(crash-worthiness depending on the design of the standards) (38,39,52,60)
|
↓
|
Ecosystem and biodiversity
impact via reduced urban air pollution (20,22,69,95)
|
|
Compact
urban form and improved
transport
infrastructure Modal shift
|
↑
↑
?
|
Energy security (reduced oil dependence and exposure to oil
price volatility) (77 – 80,86)
Productivity (reduced urban
congestion and travel times, affordable and accessible transport) (6 –
8,26,35,45,46,48,49)
Employment opportunities in the public transport
sector vs. car manufacturing jobs (38,76,89)
|
↓
↑
↓
↑
↑
|
Health
impact for non-motorized modes via
Increased
physical activity
(7,12,27,28,29,51,64,70,73,74)
Potentially
higher exposure to air pollution
(19,27,59,69,70,74)
Noise
(modal shift and travel reduction)
(58,61,64
– 66,81 – 83)
Equitable mobility access to employment opportunities,
particularly in developing countries (4,5,8,9,26,43,47,49)
Road safety (via modal shift and / or infrastructure for
pedestrians and cyclists)
(12,27,37,39,40,87,88)
|
↓
↓
|
Ecosystem
impact via
Urban
air pollution (20,54,58,60,69)
Land-use competition (7,9,58,71,75)
|
|
Journey
distance reduction and avoidance
|
↑
↑
|
Energy security (reduced oil dependence and exposure to oil
price volatility) (31,77 – 80,86)
Productivity
(reduced urban congestion, travel times, walking) (6 – 8,26,45,46,49)
|
↓ Health
impact (for non-motorized transport modes) (7,12,22,27 – 30,67,68,72,75)
|
↓
↑
↓
|
Ecosystem
impact via
Urban
air pollution (20,53,54,60,69)
New
/ shorter shipping routes (15,16,57)
Land-use competition from transport infrastructure
(7,9,58,71,75)
|
|
References:
1: Greene (2010b), 2: Costantini et al. (2007), 3: Bradley and Lefevre (2006),
4: Boschmann (2011), 5: Sietchiping et al. (2012), 6: Cuenot et al. (2012), 7:
Creutzig et al. (2012a), 8: Banister (2008), 9: Geurs and Van Wee (2004),
Banister (2008), 10: Creutzig and He (2009), 11: Leinert et al. (2013), 12:
Rojas-Rueda et al. (2011), 13: Sathaye et al. (2011), 14: Hill et al. (2009),
15: Garneau et al. (2009), 16: Wassmann (2011), 17: Eliseeva and Bünzli (2011),
18: Massari and Ruberti (2013), 19: Takeshita (2012), 20: Kahn Ribeiro et al.
(2012), 21: IEA (2011a), 22: Woodcock et al. (2009), 23: Schipper and Fulton
(2012), 24: see Section 11.13.6, 25: Kirchstetter et al. (2008), 26: Banister
(2008), Miranda and Rodrigues da Silva (2012), 27: Rojas-Rueda et al. (2011),
Rabl and de Nazelle (2012), 28: Jacobsen (2003), 29: Hultkrantz et al. (2006),
30: Goodwin (2004), 31: Sorrell and Speirs (2009), 32: Jewell et al. (2013),
33: Shakya and Shrestha (2011), 34: Leiby (2007), 35: Duranton and Turner (2011),
36: Trubka et al. (2010a), 37: WHO (2011), 38: Santos et al. (2010), 39: Tiwari
and Jain (2012), 40: Sonkin et al. (2006), 41: Chum et al. (2011), 42: Larsen
et al. (2009), 43: Steg and Gifford (2005), 44: Christensen et al. (2012), 45:
Schrank et al. (2011), 46: Carisma and Lowder (2007), 47: World Bank (2002),
48: JICA (2005), 49: Kunieda and Gauthier (2007), 50: see Section 11.13.5, 51:
Maizlish et al. (2013), 52: WHO (2008), 53: ICCT (2012b), 54: Yedla et al.
(2005), 55: Lu et al. (2013), 56: Schoon and Huijskens (2011), 57: see Section
8.5, 58: see Section 12.8, 59: Medey et al. (2002), 60: Machado-Filho (2009),
61: Milner et al. (2012), 62: Kim Oanh et al. (2012), 63: Fulton et al. (2013),
64: de Nazelle et al. (2011), 65: Twardella and Ndrepepa (2011), 66: Kawada
(2011), 67: Grabow et al. (2012), 68: Pucher et al. (2010), 69: Section 7.9.2
and WGII Section 11.9, 70: de Hartog et al. (2010), 71: Heath et al. (2006),
72: Saelens et al. (2003), 73: Sallis et
al. (2009), 74: Hankey and Brauer (2012), 75: Cervero and Sullivan (2011), 76:
Mikler (2010), 77: Cherp et al. (2012), 78: Leung (2011), 79: Knox-Hayes et al.
(2013), 80: Sovacool and Brown (2010), 81: WHO (2009), 82: Oltean-Dumbrava et
al. (2013), 83: Velasco et al. (2013), 84: Smith et al. (2013), 86: see Section
8.4, 87: Schepers et al. (2013), 88: White (2004), 89: UNEP / GEF (2013), 90:
Rao and Wang (2011), 91: Notter et al. (2010), 92: Sioshansi and Denholm
(2009), 93: Zackrisson et al. (2010), 94: Michalek et al. (2011), 95: see
Section 8.2.2.1.
If biofuels displace high carbon-intensity oil from tar
sands or heavy oils, the displacement effect would provide higher GHG emission
savings. Estimates of the magnitude of the petroleum rebound effect cover a
wide range and depend on modelling assumptions. Two recent modelling studies
suggest that biofuels replace about 30 – 70 % of the energy equivalent quantity
of petroleum-based fuel (Drabik and de Gorter, 2011; Chen and Khanna, 2012),
while others find replacement can be as low as 12 – 15 % (Hochman et al.,
2010). Under other circumstances, the rebound can be negative. The rebound
effect is always subject to the policy context, and can be specifically avoided
by global cap and pricing instruments.
872
Technical risks and uncertainties
Different de-carbonization
strategies for transport have a number of technological risks and uncertainties
associated with them. Unsustainable mining of resources to supply low-carbon
transport technologies such as batteries and fuel cells may create adverse side
effects for the local environment (Massari and Ruberti, 2013; Eliseeva and
Bünzli, 2011). Mitigation options from lower energy-intensity technologies (e.
g., electric buses) and reduced fuel carbon intensity (e. g., biofuels) are
particularly uncertain regarding their technological viability, sources of
primary energy, and biomass and lifecycle emission reduction potential (see
Section 8.3). Biofuels indicators are being developed to ensure a degree of
sustainability in their production and use (UNEP / GEF, 2013; Sections 11.13.6
and 11.13.7). For shipping, there is potential for new and shorter routes such
as across the Arctic, but these may create risks to vulnerable ecosystems (see
Section 8.5).
A focus on improving vehicle fuel efficiency may reduce GHG
emissions and potentially improve air quality, but without an increase in modal
choice it may not result in improved access and mobility (Steg and Gifford,
2005). The shift toward more efficient vehicles, for example the increasing use
of diesel for the LDV fleet in Europe, has also created tradeoffs such as
negatively affecting air quality in cities (Kirchstetter et al., 2008). More
generally, mitigation options are also likely to be subject to rebound effects
to varying degrees (see Sections 8.3 and 8.10).
873
Technological spillovers
Advancements in technologies developed for the transport
sector may have technological spillovers to other sectors. For example
advancements in battery technology systems for consumer electronics could
facilitate the development of batteries for electric vehicles and viceversa
(Rao and Wang, 2011). The production of land-competitive biofuels can also have
direct and indirect effects on biodiversity, water, and food availability (see
Sections 11.13.6 and 11.13.7). Other areas where technological spillovers may
occur include control and navigation systems and other information technology
applications.
8.8 Barriers and opportunities
Barriers and opportunities are
processes that hinder or facilitate deployment of new transport technologies
and practices. Reducing transport GHG emissions is inherently complex as
increasing mobility with LDVs, HDVs, and aircraft has been associated with
increasing wealth for the past century of industrialization (Meyer et al.,
1965; Glaeser, 2011). The first signs of decoupling fossil fuel-based mobility
from wealth generation are appearing in OECD countries (Kenworthy, 2013). To
decouple and reduce GHG emissions, a range of technologies and practices have
been identified that are likely to be developed in the short- and longterms
(see Section 8.3), but barriers to their deployment exist as do opportunities
for those nations, cities, and regions willing to make lowcarbon transport a
priority. There are many barriers to implementing a significantly lower carbon
transport system, but these can be turned into opportunities if sufficient
consideration is given and best-practice examples are followed.
881 Barriers
and opportunities to reduce
GHGs by technologies and practices
The key transport-related technologies and practices
garnered from sections above are set out below in terms of their impact on fuel
carbon intensity, improved energy intensity of technologies, system
infrastructure efficiency, and transport demand reduction. Each has short- and
long-term potentials to reduce transport GHG emissions that are then assessed
in terms of their barriers and opportunities (Table 8.5). (Details of policies
follow in Section 8.10).
Psychological barriers can impede behavioural choices that
might otherwise facilitate mitigation as well as adaptation and environmental
sustainability. Many individuals are engaged in ameliorative actions to improve
their local environment, although many could do more. Gifford (2011) outlined barriers that included
“limited cognition about the problem, ideological worldviews that tend to
preclude pro-environmental attitudes and behaviour, comparisons with the
responses of other people, sunk costs and behavioural momentum, a dis-credence
toward experts and authorities, perceived risks as a result of making change
and positive but inadequate confidence to make behavioural change.”
The range of
barriers to the ready adoption of the above technologies and practices have
been described in previous sections, but are summarized in Table 8.5 along with
the opportunities available. The challenges involved in removing barriers in
each of the 16 elements listed depend on the politics of a region. In most
places, reducing fuel carbon and energy intensities are likely to be relatively
easy as they are technology-based, though they can meet capital investment
barriers in developing regions and may be insufficient in the longer-term. On
the other hand, system infrastructure efficiency and transport demand reduction
options would require human interventions and social change as well as public
investment. Although these may not require as much capital investment, they
would still require public acceptance of any transport policy option (see
Section 8.10). As implementation approaches, public acceptance fluctuates, so
political support may be required at critical times (Pridmore and Miola, 2011).
Table
85 | Transport technologies and practices with potential for both
short- and long-term GHG reduction and the related barriers and opportunities
in terms of the policy arenas of fuel carbon intensity, energy intensity,
infrastructure, and activity.
|
Transport technology or practice
|
Short-term possibilities
|
Long-term possibilities
|
Barriers
|
Opportunities
|
References
|
|
Fuel
carbon intensity: fuel s
|
witching BEV —
Battery electric vehicle; PHEV — Plug-in hybrid electric vehicle; FCV — Fuel
cell vehicles; CHP — combined heat and power;
|
||||
|
CNG — Compressed natu
|
ral gas; LNG — Liquefied natural gas; CBG — Compressed biogas; LBG —
Liquefied biogas)
|
||||
|
1. BEVs and PHEVs based on
renewable electricity.
|
Rapid increase in use likely over next decade from a
small base, so only a small impact likely in short-term.
|
Significant replacement of
ICE-powered LDVs.
|
EV and battery costs reducing but still high.
Lack of infrastructure, and recharging standards not
uniform.
Vehicle
range anxiety.
Lack of capital and electricity in some least
developed countries.
|
Universal standards adopted for EV rechargers.
Demonstration in green city areas with plug-in infrastructure.
Decarbonized electricity. Smart grids based on renewables.
EV subsidies.
New business models, such
as community car sharing.
|
EPRI
2008; Beck ,2009; IEA,
2011;
Salter et al., 2011;
Kley
et al., 2011; Leurent &
Windisch,
2011; GrahamRowe et al., 2012
|
|
2.
CNG, LNG, CBG and LBG
displacing
gasoline in
LDVs and diesel in HDVs.
|
Infrastructure available in some cities so can allow
a quick ramp – up of gas vehicles in these cities.
|
Significant replacement of HDV diesel use depends on
ease of engine conversion, fuel prices and extent of infrastructure.
|
Insufficient
government programmes, conversion subsidies and local gas infrastructure and
markets.
Leakage of gas.
|
Demonstration gas
conversion programmes that show cost and health co-benefits. Fixing gas
leakage in general.
|
IEA, 2007; Salter et al., 2011; Alvarez et al., 2012
|
|
3. Biofuels displacing gasoline,
diesel and aviation fuel.
|
Niche markets continue for first generation biofuels
(3 % of liquid fuel market, small biogas niche markets).
|
Advanced
and drop-in biofuels likely to be adopted around 2020 – 2030, mainly for
aviation.
|
Some biofuels can be relatively expensive,
environmentally poor and cause inequalities by inducing increases in food
prices.
|
Drop-in fuels attractive for all vehicles.
Biofuels and bio-electricity can be produced together,
e. g., sugarcane ethanol and CHP from bagasse.
New biofuel options need to be further tested,
particularly for aviation applications.
|
Ogden et
al., 2004; Fargione et al., 2010; IEA, 2010;
Plevin et al., 2010; Creutzig et al., 2011; Salter et al., 2011;
Pacca
and Moreira, 2011;
Flannery et al., 2012
|
|
Energy intensity: efficiency
|
of technologies FEV — fuel
efficient vehicles ICE — internal
combustion engine
|
||||
|
4. Improved vehicle ICE
technologies and on-board information and communication technologies (ICT) in
fuelefficient vehicles.
|
Continuing
fuel efficiency improvements across new vehicles of all types can show large,
low-cost, near-term reductions in fuel demand.
|
Likely to be a significant source of reduction.
Behavioural issues (e. g., rebound effect). Consumer choices can reduce
vehicle efficiency gains.
|
Insufficient regulatory support for vehicle emissions
standards.
On-road performance
deteriorates compared with laboratory tests.
|
Creative regulations that enable quick changes to
occur without excessive costs on emissions standards. China and most OECD
countries have implemented standards. Reduced registration tax can be
implemented for low CO2eq-based vehicles.
|
Schipper
et al., 2000; Ogden et al., 2004; Small and van Dender, 2007; Sperling and
Gordon,
2009; Timilsina and
Dulal,
2009; Fuglestvedt et al., 2009; Mikler, 2010; Salter et al., 2011
|
|
Structure: system infrastru
|
cture efficiency
|
||||
|
5. Modal shift by public
transport displacing private motor vehicle use.
|
Rapid short-term growth
already happening.
|
Significant displacement only where quality system
infrastructure and services are provided.
|
Availability of rail, bus, ferry, and other quality transit
options.
Density of people to allow more access to services.
Levels of services. Time barriers on roads without
right of way Public perceptions.
|
Investment in quality transit infrastructure, density
of adjacent land use, and high level of services using innovative financing
that builds in these features. Multiple co-benefits especially where
walkability health benefits are a focus.
|
Kenworthy,
2008; Millard-Ball & Schipper, 2011; Newman and Kenworthy, 2011; Salter
et al., 2011; Buehler and
Pucher,
2011; Newman and
Matan, 2013
|
⇒
|
Transport technology or practice
|
Short-term possibilities
|
Long-term possibilities
|
Barriers
|
Opportunities
|
References
|
|
6. Modal
shift by cycling displacing private motor vehicle use.
|
Rapid
short-term growth already happening in many cities.
|
Significant
displacement only where quality system infrastructure is provided.
|
Cultural
barriers and lack of safe cycling infrastructure and regulations. Harsh
climate.
|
Demonstrations
of quality cycling infrastructure including cultural programmes and
bike-sharing schemes.
|
Bassett et al., 2008;
Garrard et al., 2008; Salter et al.,
2011; Anon, 2012; Sugiyama et al., 2012
|
|
7. Modal
shift by walking displacing private motor vehicle use.
|
Some
growth but depends on urban planning and design policies being implemented.
|
Significant
displacement where large-scale adoption of polycentric city policies and
walkable urban designs are implemented.
|
Planning and design
policies can work against walkability of a city by too easily allowing cars
into walking city areas. Lack of density and integration with transit.
Culture of
walkability.
|
Large-scale adoption of
polycentric city policies and walkable urban designs creating walking city in
historic centres and new ones.
Cultural
programmes.
|
Gehl, 2011; Höjer et al., 2011; Leather et al.,
2011; Salter et al., 2011
|
|
8. Urban
planning by reducing the distances to travel within urban areas.
|
Immediate
impacts where dense transit-oriented development (TOD) centres are built.
|
Significant
reductions where widespread polycentric city policies are implemented.
|
Urban
development does not always favour dense TOD centres being built. TODs need
quality transit at their base. Integration of professional areas required.
|
Widespread
polycentric city policies implemented with green TODs, backed by quality
transit. Multiple co-benefits in sprawl costs avoided and health gains.
|
Anon, 2004; Anon, 2009;
Naess, 2006; Ewing et al.,
2008; Cervero and Murakami,
2009; Cervero and Murakami,
2010; Cervero and Sullivan,
2011; Salter et al., 2011;
Lefèvre;
2009
|
|
9. Urban
planning by reducing private motor vehicle use through parking and traffic
restraint.
|
Immediate
impacts on traffic density observed.
|
Significant
reductions only where quality transport alternatives are available.
|
Political
barriers due to perceived public opposition to increased costs, traffic and
parking restrictions. Parking codes too prescriptive for areas suited to
walking and transit.
|
Demonstrations of better transport outcomes from
combinations of traffic restraint, parking and new transit / walking
infrastructure investment.
|
Gwilliam, 2003; ADB, 2011;
Creutzig et al., 2011; Shoup,
2011; Newman
and Matan,
2013
|
|
10. Modal
shift by displacing aircraft and LDV trips through high-speed rail
alternatives.
|
Immediate
impacts after building rail infrastructure.
|
Continued
growth but only short-medium distance trips suitable.
|
High-speed
rail infrastructure expensive.
|
Demonstrations
of how to build quality fast-rail using innovative finance.
|
Park and Ha, 2006; Gilbert and Perl, 2010; Åkerman,
2011; Salter et al., 2011
|
|
11. Modal
shift of freight by displacing HDV demand with rail.
|
Suitable
immediately for medium- and long-distance freight and port traffic.
|
Substantial
displacement only if large rail infrastructure improvements made, the
external costs of freight transport are fully internalized, and the quality
of rail services are enhanced. EU target to have 30 % of freight tonne-km
moving more than 300 km to go by rail (or water) by 2030.
|
Inadequacies in rail infrastructure and service
quality. Much freight moved over
distances that are too short for rail to be competitive.
|
Upgrading of inter-modal
facilities. Electrification of rail freight
services. Worsening traffic congestion
on road networks and higher fuel cost will favour rail.
|
IEA, 2009;
Schiller et al., 2010; Salter et al., 2011
|
|
12. Modal
shift by displacing truck and car use through waterborne transport.
|
Niche options already available. EU “Motorways of the Sea” programme
demonstrates potential to expand short-sea shipping share of freight market.
|
Potential
to develop beyond current niches, though will require significant investment
in new vessels and port facilities.
|
Lack of
vision for water transport options and landlocked population centres. Long
transit times. Tightening controls on
dirty bunker fuel and SOx and NOx emissions
raising cost and reducing modal competitiveness.
|
Demonstrations
of quality waterborne transport that can be faster and with lower-carbon
emissions than alternatives.
|
Fuglestvedt
et al., 2009; Salter et al. 2011
|
|
13. System
optimization by improved road systems, freight logistics and efficiency at
airports and ports.
|
Continuing
improvements showing immediate impacts.
|
Insufficient in long term to significantly reduce
carbon emissions without changing mode, reducing mobility, or reducing fuel
carbon intensity.
|
Insufficient
regulatory support and key performance indicators (KPIs) covering logistics
and efficiency.
|
Creative
regulations and KPIs that enable change to occur rapidly without excessive
costs.
|
Pels and Verhoef, 2004;
A. Zhang and Y. Zhang,
2006; Fuglestvedt et al.,
2009;
Kaluza et al., 2010; McKinnon, 2010; Simaiakis and Balakrishnan, 2010;
Salter et
al., 2011
|
|
Activity:
demand reduction
|
|||||
|
14. Mobility service
substitution by reducing the need to travel through enhanced communications.
|
Niche
markets growing and ICT improving in quality and reliability.
|
Significant
reductions possible after faster broadband and quality images available,
though ICT may increase the need for some trips.
|
Technological
barriers due to insufficient broadband in some regions.
|
Demonstrations
of improved video-conferencing system quality.
|
Golob and Regan, 2001;
Choo et al., 2005; Wang and
Law, 2007; Yi and Thomas, 2007; Zhen et al., 2009;
Salter et al., 2011; Mokhtarian and Meenakshisundaram, 2002
|
⇒
|
Transport technology or practice
|
Short-term possibilities
|
Long-term possibilities
|
Barriers
|
Opportunities
|
References
|
|
15.
Behavioural change from reducing private motor vehicle use through pricing
policies, e.g, network charges and parking fees.
|
Immediate
impacts on traffic density observed.
|
Significant
reductions only where quality transport alternatives are available.
|
Political
barriers due to perceived public opposition to increased pricing costs. Lack
of administrative integration between transport, land-use and environment
departments in city municipalities.
|
Demonstrations of better
transport outcomes from combinations of pricing, traffic restraint, parking
and new infrastructure investment from the revenue. Removing subsidies to
fossil fuels important for many co-benefits.
|
Litman, 2005, 2006; Salter
et al., 2011; Creutzig et al.,
2012a
|
|
16. Behavioural change resulting from education to
encourage gaining benefits of less motor vehicle use.
|
Immediate impacts of 10 –
15 % reduction of LDV use are possible.
|
Significant
reductions only where quality transport alternatives are available.
|
Lack of
belief by politicians and professionals in the value of educational behaviour
change programmes.
|
Demonstrations of ‘travel
smart’ programmes linked to improvements in sustainable transport
infrastructure. Cost effective and multiple co-benefits.
|
Pandey, 2006; Goodwin and
Lyons, 2010; Taylor and Philp,
2010; Ashton-Graham et al.,
2011; Höjer et al., 2011;
Salter et
al., 2011
|
882
Financing low-carbon transport
Transport is a foundation for any economy as it enables
people to be linked, goods to be exchanged, and cities to be structured (Glaeser,
2011). Transport is critical for poverty reduction and growth in the plans of
most regions, nations, and cities. It therefore is a key area to receive
development funding. In past decades the amount of funding going to transport
through various low-carbon mechanisms had been relatively low, but has had a
recent increase. The projects registered in the United Nations Environmental
Programme (UNEP) pipeline database for the clean development mechanism (CDM)
shows only 42 projects out of 6707 were transport-related (Kopp, 2012). The
Global Environment Facility (GEF) has approved only 28 projects in 20 years,
and the World Bank’s Clean Technology Fund has funded transport projects for
less than 17 % of the total. If this international funding does not improve,
then transport could move from emitting 22 % of energy-related GHGs in 2009 to
reach 80 % by 2050 (ADB, 2012a). Conversely, national appropriate mitigation
measures (NAMAs) could attract low-carbon financing in the transport area for
the developing world. To support sustainable transport system development,
eight multi-lateral development banks have pledged to invest around 170 billion
USD2010 over the next ten years (Marton-Lefèvre, 2012).
A major part of funding
sustainable transport could arise from the redirection of funding from
unsustainable transport (Sakamoto et al., 2010; UNEP, 2011; ADB, 2012b). In
addition, land-based taxes or fees can capitalize on the value gains brought by
sustainable transport infrastructures (Chapter 12.5.2). For example, in
locations close to a new rail system, revenue can be generated from land-based
taxes and council rates levied on buildings that are seen to rise by 20 – 50 %
compared to areas not adjacent to such an accessible facility (Cervero 1994;
Haider and Miller, 2000; Rybeck, 2004). Local municipal financing by land value
capture and land taxes could be a primary source of financing for public
transit and non-motorized transport infrastructure, especially in rapidly
urbanizing Asia (Chapter 12.5.2; Bongardt et al., 2013). For example, a number
of value capture projects are underway as part of the rapid growth in urban
rail systems, including Indian cities (Newman et al., 2013). The ability to
fully outline the costs and benefits of lowcarbon transport projects will be
critical to accessing these new funding opportunities. R&D barriers and
opportunities exist for all of these agendas in transport.
883 Institutional, cultural, and legal
barriers and opportunities
Institutional barriers to
low-carbon transport include international standards required for new EV
infrastructure to enable recharging; low pricing of parking; lack of
educational programmes for modal shift; and polycentric planning policies that
require the necessary institutional structures (OECD, 2012; Salter et al.,
2011). Cultural barriers underlie every aspect of transport, for example,
automobile dependence being built into a culture and legal barriers that can
exist to prevent the building of dense, mixed-use community centres that reduce
car dependence. Overall, there are political barriers that combine most of the
above (Pridmore and Miola, 2011).
Opportunities also exist.
Low-carbon transport elements in green growth programmes (OECD, 2011; Hargroves
and Smith, 2008) are likely to be the basis of changing economies because they
shape cities and create wealth (Glaeser, 2011; Newman et al., 2009). Those
nations, cities, businesses, and communities that grasp the opportunities to
demonstrate these changes are likely to be the ones that benefit most in the
future (OECD, 2012). The process of decoupling economic growth from fossil fuel
dependence could become a major feature of the future economy (ADB, 2012a) with
sustainable transport being one of four key approaches. Overcoming the barriers
to each technology and practice (Table 8.5) could enable each to contribute to
a more sustainable transport system and realize the opportunities from
technological and social changes when moving towards a decarbonized economy of
the future.
8.9 Sectoral implications of transformation pathways and sustainable development
Scenarios that focus on possible
reductions of energy use and CO2 emissions from transport are sourced
from either integrated models that incorporate a cross-sector approach to
modelling global emissions reductions and other mitigation options, or sectoral
models that focus solely on transport and its specific potential for emissions
reductions. A comparison of scenarios from both integrated and sectoral models
with a focus on long-term concentration goals up until 2100 is conducted in
this section. This comparison is complemented by the results of the
transport-specific evaluation of cost and potentials in Section 8.6 and
supported by a broader integrated assessment in Chapter 6[7].
The integrated and sectoral model
transport literature presents a wide range of future CO2
emissions reduction scenarios and offers two distinct forms of assessment. Both
contemplate how changes in passenger and freight activity, structure, energy
intensity, and fuel carbon intensity could each contribute to emissions
reductions and assist the achievement of concentration goals.
The integrated model literature
focuses upon systemic assessments of the impacts of macro-economic policies
(such as limits on global / regional emissions or the implementation of a
carbon tax) and reviews the relative contributions of a range of sectors to
overall global mitigation efforts (Section 6.2.1). Within the WG III AR5
Scenario Database (Annex II.10), transport specific variables are not available
for all scenarios. Therefore, the present analysis is based on a sub-sample of
almost 600 scenarios[8].
Due to the macro-economic scale of their analysis, integrated models have a
limited ability to assess behaviour changes that may result from structural
developments impacting on modal shift or journey avoidance, behavioural factors
such as travel time and budget might contribute up to 50 % reduction of
activity globally in 2100 compared to the 2005 baseline (Girod et al., 2013). 
Sectoral scenarios, however,
are able to integrate results concerning emission reduction potentials from
sector specific interventions (such as vehicle taxation, parking fees, fuel
economy standards, promotion of modal shift, etc.). They can be instrumental in
evaluating how policies that target structural factors[9]
can impact on passenger and freight travel demand reductions (see Sections 8.4
and 8.10). Unlike integrated models, sectoral studies do not attempt to measure
transport emissions reductions with respect to the amounts that other sectors
could contribute in order to reach long-term concentration goals.
891 Long term stabilization goals —
integrated and sectoral perspectives
A diversity of transformation pathways highlights the
possible range of decarbonization options for transport (Section 6.8). Results
from both integrated and sectoral models up until 2050 closely match each
other. Projected GHG emissions vary greatly in the long term integrated
scenarios, reflecting a wide range in assumptions explored such as future
population, economic growth, policies, technology development, and acceptance
(Section 6.2.3). Without policy interventions, a continuation of current travel
demand trends could lead to a more than doubling of transport-related CO2
emissions by 2050 and more than a tripling by 2100 in the highest scenario
projections (Figure 8.9). The convergence of results between integrated and
sectoral model studies suggests that through substantial, sustained, and
directed policy interventions, transport emissions can be consistent with
limiting long-term concentrations to 430 – 530 ppm CO2eq.
The growth of global transport
demand could pose a significant challenge to the achievement of potential
emission reduction goals. The average transport demand growth from integrated
scenarios with
respect to 2010 levels suggests that total passenger and
freight travel will continue to grow in the coming decades up to 2050, with
most of this growth taking place within developing country regions where large
shares of future population and income growth are expected (Figure 8.10) (UN
Secretariat, 2007).
A positive income elasticity and the relative
price-inelastic nature of passenger travel partially explain the strength of
the relationship between travel and income (Dargay, 2007; Barla et al., 2009).
Both integrated and sectoral model projections for total travel demand show
that while demand in non-OECD countries grows rapidly, a lower starting point
results in a much lower per capita level of passenger travel in 2050 than in
OECD countries (Figure 8.10) (IEA, 2009; Fulton
Figure
89 | Direct global transport CO2 emissions.
All results for passenger and freight transport are indexed relative to 2010
values for each scenario from integrated models grouped by CO2eq
concentration levels by 2100, and sectoral studies grouped by baseline and
policy categories. Sources: Integrated models — WG III AR5 Scenario Database
(Annex II.10). Sectoral models: IEA (2008, 2011b, 2012b), WEC (2011a), EIA
(2011), IEEJ (2011). 
Note: All figures in Section 8.9 show the full range
of results for both integrated and sectoral studies. Where the data is sourced
from the WG III AR5 Scenario Database a line denotes the median scenario and a
box and bolder colours highlight the inter-quartile range. The specific
observations from sectoral studies are shown as black dots with light bars
(policy) or dark bars (baseline) to give the full ranges. “n” equals number of
scenarios assessed in each category.
Figure 810 | Global passenger (p-km / capita /
yr) and freight (t-km / capita / yr) regional demand projections out to 2050
based on integrated models for various CO2eq
concentration levels by 2100 — with normalized values highlighting growth and
controlling differences in base year values across models. Source: WG III AR5
Scenario Database (Annex II.10).
et al., 2013). Consistent with a recent decline in growth of
LDV use in some OECD countries (Goodwin and Van Dender, 2013), integrated and
sectoral model studies have suggested that decoupling of passenger transport
from GDP could take place after 2035 (IEA, 2012; Girod et al., 2012). However,
with both transport demand and GDP tied to population growth, decoupling may
not be fully completed. At higher incomes, substitution to faster travel modes,
such as fast-rail and air travel, explains why total passenger and freight
travel continues to rise faster than per capita LDV travel (Schäfer et al.,
2009).
Freight transport increases in all scenarios at a slower
pace than passenger transport, but still rises as much as threefold by 2050 in
comparison to 2010 levels. Freight demand has historically been closely coupled
to GDP, but there is potential for future decoupling. Over the long term,
changes in activity growth rates (with respect to 2010) for 430 – 530 ppm CO2eq
scenarios from integrated models suggest that decoupling freight transport
demand from GDP can take place earlier than for passenger travel. Modest
decreases in freight activity per dollar of GDP suggest that a degree of relative
decoupling between freight and income has been occurring across developed
countries including Finland (Tapio, 2005), the UK (McKinnon, 2007a) and Denmark
(Kveiborg and Fosgerau, 2007). Two notable exceptions are Spain and South
Korea, which are at relatively later stages of economic development (Eom et
al., 2012). Where decoupling has occurred, it is partly associated with the
migration of economic activity to other countries (Corbertt and Winebrake,
2008; Corbertt and Winebrake, 2011). See Sections 3.9.5 and 5.4.1 for a broader
discussion of leakage. Opportunities for decoupling could result from a range
of changes, including a return to more localized sourcing (McKinnon, 2007b); a
major shift in the pattern of consumption to services and products of higher
value; the digitization of media and entertainment; and an extensive
application of new transport-reducing manufacturing technologies such as 3-D
printing (Birtchnell et al., 2013).
Due to the increases in total transport demand, fuel
consumption also increases over time, but with GHG emissions at a lower level
if policies toward decarbonization of fuels and reduced energy intensity of
vehicles are successfully implemented. The integrated scenarios suggest that
energy intensity reductions for both passenger and freight transport could
continue to occur if the present level of fuel economy standards are sustained
over time, or could decrease further with more stringent concentration goals
(Figure 8.11).
Projected reductions in energy intensity for freight
transport scenarios (EJ / bn t-km) in the scenarios show a wider spread (large
ranges in Figure 8.11 between the 25th and 75th percentiles) than for
passengers, but still tend to materialize over time. Aviation and road
transport have higher energy intensities than rail and waterborne transport
(Figure 8.6). Therefore, they account for a larger share of emissions than
their share of meeting service demands (Girod et al., 2013). However, limited
data availability makes the assessment of changes in modal structure
challenging as not all integrated models provide information at a sufficiently
disaggregated level or fully represent structural and behavioural choices.
Sectoral studies suggest that achieving significant reductions in aviation
emissions will require reductions in the rate of growth of travel activity
through demand management alongside technological advances (Bows et al., 2009).
|
bon intensity based on scenarios
from integrated models grouped by CO2eq
concentration levels by 2100 (right panel). Source: WG III AR5 Scenario
Database (Annex II.10). Note “n” equals number of scenarios assessed in each
category.
 |
In addition to energy intensity reductions, fuel carbon
intensity can be reduced further in stringent mitigation scenarios and play an
important role in the medium term with the potential for continued improvement
throughout the century (Figure 8.11). Scenarios suggest that fuel switching
does not occur to a great extent until after 2020 – 2030 (Fig 8.12) after which
it occurs sooner in more stringent concentration scenarios. The mix of fuels
and technologies is difficult to foresee in the long term, especially for road
transport, but liquid petroleum fuels tend to dominate at least up until 2050
even in the most stringent mitigation scenario. Within some sectoral studies,
assumed breakthroughs in biofuels, fuel cell vehicles, and electrification of
road vehicles help achieve deep reductions in emissions by 2050 (Kahn Ribeiro
et al., 2012; Williams et al., 2012). Other studies are less confident about
fuel carbon intensity reductions, arguing that advanced biofuels, low-carbon
electricity, and hydrogen will all require time to make substantial
contributions to mitigation efforts. They therefore attribute greater potential
for emission reductions to structural and behavioural changes (Salter et al.,
2011).
Model assumptions for future technology cost, performance,
regulatory environment, consumer choice, and fuel prices result in different
shares of fuels that could replace fossil fuels (Table 8.3; Krey and Clarke,
2011). Availability of carbon dioxide capture and storage (CCS) is also likely
to have major impact on fuel choices (Luckow et al., 2010; Sathaye et al.,
2011). Uncertainty is evident by the wide ranges in all the pathways
considered, and are larger after 2050 (Bastani et al., 2012; Wang et al., 2012;
Pietzcker et al., 2013). In terms of direct emissions reductions, biofuels tend
to have a more important role in the period leading up to 2050. In general,
integrated models have been criticized as being optimistic on fuel substitution
possibilities, specifically with respect to lifecycle emission assumptions and
hence the utilization of biofuels (Sections 8.3 and 11.A.4; Creutzig et al.,
2012a; Pietzcker et al., 2013). However, scenarios from integrated models are
consistent with sectoral scenarios with respect to fuel shares in 2050 (Figure
8.12). Within the integrated model scenarios, deeper emissions reductions
associated with lower CO2eq concentrations in 2100 are consistent
with increasing market penetration of low-carbon electricity and hydrogen in
the latter part of the century. Uncertainties as to which fuel becomes
dominant, as well as on the role of energy efficiency improvements and fuel
savings, are relevant to the stringent mitigation scenarios (van der Zwaan et
al., 2013). Indeed, many scenarios show no dominant transport fuel source in 2100,
with the median values for electricity and hydrogen sitting between a 22 – 25 %
share of final energy, even for scenarios consistent with limiting
concentrations to 430 – 530 ppm CO2eq in 2100 (Figure 8.12).
Both the integrated and sectoral model literature present
energy efficiency measures as having the greatest promise and playing the
largest role for emission reductions in the short term (Skinner et al., 2010;
Harvey, 2012; IEA, 2009; McKinnon and Piecyk, 2009; Sorrell et al., 2012).
Since models typically assume limited cost reduction impacts, they include slow
transitions for new transport technologies to reach large cumulative market
shares. For example, a range of both sectoral and integrated studies note that
it will take over 15 – 20 years for either BEVs or FCVs to become competitive
with ICE vehicles (Baptista et al., 2010; Eppstein et al., 2011; IEA, 2011c;
Girod et al., 2012; Girod et al., 2013; Bosetti and Longden, 2013; van der
Zwaan et al., 2013). Since integrated models do not contain a detailed
representation of infrastructural changes, their results can be interpreted as
a conservative estimate of possible changes to vehicles, fuels, and modal
choices (Pietzcker et al., 2013).
|
III AR5 Scenario Database (Annex II.10). Sectoral
models — IEA, 2012; IEA, 2011b; IEA, 2008; WEC, 2011a; EIA, 2011 and IEEJ,
2011.
Note: Interpretation is similar
to that for Figs. 8.9 and 8.10, except that the boxes between the 75th and
25th percentiles for integrated model results have different colours to highlight
the fuel type instead of GHG concentration categories. The specific
observations from sectoral studies are shown as black dots
|
The sectoral
literature presents a more positive view of transformational opportunities than
do the integrated models (IEA, 2008, 2012b; DOE / EIA, 2010; Kahn Ribeiro et
al., 2012). Sectoral studies suggest that up to 20 % of travel demand could be
reduced by avoided journeys or shifts to low-carbon modes (McCollum and Yang,
2009; Harvey, 2012; IEA, 2012d; Kahn Ribeiro et al., 2012; Anable et al., 2012;
|
Box
81 | Transport and sustainable development in developing countries
Passenger and freight
mobility are projected to double in devel- GHG
emissions (IEA, 2012a). Failure to manage the growth of oping countries by
2050 (IEA, 2012e). This increase will improve motorized mobility in the near term will inevitably lead
to higher access to markets, jobs, education, healthcare and other services environmental cost and greater
difficulty to control emissions in by providing opportunities to reduce
poverty and increase equity the long
term (Schäfer et al., 2009; Pietzcker et al., 2013).
(Africa Union, 2009;
Vasconcellos, 2011; United Nations Human
Settlements Programme,
2012). Well-designed and well-managed A
high modal share of public transport use characterizes developtransport
infrastructure can also be vital for supporting trade and ing cities (Estache and GóMez-Lobo, 2005)
and this prevalence competitiveness (United Nations Human Settlements
Programme, is expected to
continue (Deng and Nelson, 2011; Cuenot et al., 2012). Driven by
urbanization, a rapid transition from slow non- 2012). However, deficient infrastructure and
inadequate services motorized transport modes to faster modes using 2- or 3-
wheel- leads to the
overloading of para-transit vans, minibuses, jeeps and ers, LDVs, buses, and
light rail is expected to continue (Schäfer shared
taxis and the use of informal transport services (Cervero et al., 2009;
Kumar, 2011). In rural areas of Africa and South Asia, and Golub, 2011). By combining technologies,
providing new the development of all-season, high-quality roads is becoming social arrangements, and incorporating
a long-term sustainability a high priority (Africa Union, 2009; Arndt et al.,
2012). In many and climate
perspective to investment decisions, these services megacities, slum area
development in peri-urban fringes confines can
be recast and maintained as mobility resources since they the urban poor to a
choice between low paying jobs near home service
the poor living in inaccessible areas at affordable prices or long commuting
times for marginally higher wages (Burdett (Figueroa
et al., 2013). A central strategy that can have multiple and Sudjic, 2010).
The poor have limited options to change living health, climate, environmental, and social benefits is to
invest in locations and can afford few motorized trips, so they predomi- the integration of infrastructure systems
that connect safe routes nantly walk, which disproportionally burdens women
and children for walking and
cycling with local public transport, thus giving it (Anand and Tiwari, 2006;
Pendakur, 2011). The urban poor in OECD priority
over infrastructure for LDVs that serve only a small share cities have
similar issues (Glaeser, 2011). Reducing vulnerability to of the population (Woodcock et
al., 2009; Tiwari and Jain, 2012). climate change requires integrating the
mobility needs of the poor Opportunities
for strategic sustainable urban transport develinto planning that can help
realize economic and social develop- opment
planning exist that can be critical to develop medium ment objectives
(Amekudzi et al., 2011; Bowen et al., 2012). sized
cities where population increases are expected to be large
(Wittneben
et al., 2009; ADB, 2012b; Grubler et al., 2012). Vision, Total transport
emissions from non-OECD countries will likely leadership, and a coherent programme for action, adaptation,
and surpass OECD emissions by 2050 due to motorization, increasing consolidation of key
institutions that can harness the energy and population and higher travel
demand (Figure 8.10). However, esti- engagement
of all stakeholders in a city will be needed to achieve mated average
personal travel per capita in non-OECD countries these goals (Dotson, 2011). Today, more than 150 cities worldwide
at will remain below the average in OECD countries. With coun- have implemented bus rapid transit (BRT)
systems. Innovative tries facing limits to transport infrastructure
investment (Arndt features
such as electric transit buses (Gong et al., 2012) and the et al., 2012), the
rapid mobility trends represents a major chal- ambitious high-speed rail expansion in China provide
evidence of lenge in terms of traffic congestion, energy demand, and related a fast process of planning and
policy implementation.
|
Huo and
Wang, 2012). They also estimate that urban form and infrastructure changes can
play decisive roles in mitigation, particularly in urban areas where 70 % of
the world’s population is projected to live in 2050 (Chapter 8.4 and 12.4),
although the estimated magnitude varies between 5 % and 30 % (Ewing, 2007; Creutzig
and He, 2009; Echenique et al., 2012). Altogether, for urban transport, 20 – 50
% reduction in GHG emissions is possible between 2010 and 2050 compared to
baseline urban development (Ewing, 2007; Eliasson, 2008; Creutzig and He, 2009;
Lefèvre, 2009; Woodcock et al., 2009; Ewing and Cervero, 2010; Marshall, 2011;
Echenique et al., 2012; Viguié and Hallegatte, 2012; Salon et al., 2012;
Creutzig et al., 2012a). Since the lead time for infrastructure development is
considerable (Short and Kopp, 2005), such changes can only be made on decadal
time scales.
Conversely, some developing
countries with fast growing economies have shown that rapid transformative
processes in spatial development and public transport infrastructure are
possible. Further advances may be gaining momentum with a number of significant
initiatives for reallocating public funding to sustainable and climate-friendly
transport (Bongardt et al., 2011; Wittneben et al., 2009; ADB, 2012; Newman and
Matan, 2013).
892
Sustainable development
Within all scenarios, the future contribution of emission
reductions from developing countries carries especially large uncertainties.
The accelerated pace with which both urbanization and motorization are
proceeding in many non-OECD countries emphasizes serious constraints and
potentially damaging developments. These include road and public transport
systems that are in dire condition; limited technical and financial resources;
the absence of infrastructure governance; poor legal frameworks; and rights to
innovate that are needed to act effectively and improve capacity competences
(Kamal-Chaoui and Plouin, 2012; Lefèvre, 2012). The outcome is a widening gap
between the growth of detrimental impacts of motorization and effective action
(Kane, 2010; Li, 2011; Vasconcellos, 2011). A highly complex and changing
context with limited data and information further compromise transport
sustainability and mitigation in non-OECD countries (Dimitriou, 2006; Kane,
2010; Figueroa et al., 2013). The relative marginal socio-economic costs and
benefits of various alternatives can be context sensitive with respect to
sustainable development (Amekudzi, 2011). Developing the analytical and data
capacity for multi-objective evaluation and priority setting is an important
part of the process of cultivating sustainability and mitigation thinking and
culture in the long-term.
Potentials for controlling
emissions while improving accessibility and achieving functional mobility
levels in the urban areas of rapidly growing developing countries can be
improved with attention to the manner in which the mobility of the masses
progresses in their transition from slower (walking / cycling) to faster
motorized modes (Kahn Ribeiro et al., 2012). A major shift towards the use of
mass public transport guided by sustainable transport principles, including the
maintenance of adequate services and safe infrastructure for non-motorized
transport, presents the greatest mitigation potential (Bongardt et al., 2011;
La Branche, 2011). Supporting non-motorized travel can often provide access and
also support development more effectively, more equitably, and with fewer
adverse side-effects, than if providing for motorized travel (Woodcock et al.,
2007). Transport can be an agent of sustained urban development that
prioritizes goals for equity and emphasizes accessibility, traffic safety, and
time savings for the poor with minimal detriment to the environment and human
health, all while reducing emissions (Amekudzi et al., 2011; Li, 2011; Kane,
2010). The choice among alternative mitigation measures in the transport sector
can be supported by growing evidence on a large number of co-benefits, while
some adverse side effects exist that need to be addressed or minimized (see
Section 8.7) (Figueroa and Kahn Ribeiro, 2013; Creutzig and He, 2009; Creutzig
et al., 2012a, b; Zusman et al., 2012).
8.10 Sectoral policies
Aggressive policy intervention is needed to significantly
reduce fuel carbon intensity and energy intensity of modes, encourage travel by
the most efficient modes, and cut activity growth where possible and reasonable
(see Sections 8.3 and 8.9). In this section, for each major transport mode,
policies and strategies are briefly discussed by policy type as regulatory or
market-based, or to a lesser extent as informational, voluntary, or
government-provided. A full evaluation of policies across all sectors is
presented in Chapters 14 and 15. Policies to support sustainable transport can
simultaneously provide co-benefits (Table 8.4) such as improving local
transport services and enhancing the quality of environment and urban living,
while boosting both climate change mitigation and energy security (ECMT, 2004;
WBCSD, 2004, 2007; World Bank, 2006; Banister, 2008; IEA, 2009; Bongardt et
al., 2011; Ramani et al., 2011; Kahn Ribeiro et al., 2012). The type of
policies, their timing, and chance of successful implementation are context
dependent (Santos et al., 2010). Diverse attempts have been made by transport
agencies in OECD countries to define and measure policy performance (OECD,
2000; CST, 2002; Banister, 2008; Ramani et al., 2011). The mobility needs in
non-OECD countries highlight the importance of placing their climate-related
transport policies in the context of goals for broader sustainable urban development
goals (see Section 8.9; Kahn Ribeiro et al., 2007; Bongardt et al., 2011).
Generally speaking,
market-based instruments, such as carbon cap and trade, are effective at
incentivizing all mitigation options simultaneously (Flachsland et al., 2011).
However, vehicle and fuel suppliers as well as end-users, tend to react weakly
to fuel price signals, such as fuel carbon taxes, especially for passenger
travel (Creutizig et al., 2011; Yeh and McCollum, 2011). Market policies are
economically more efficient at reducing emissions than fuel carbon intensity
standards (Holland et al., 2009; Sperling and Yeh, 2010; Chen and Khanna, 2012;
Holland, 2012). However, financial instruments, such as carbon taxes, must be
relatively large to achieve reductions equivalent to those possible with
regulatory instruments. As a result, to gain large emissions reductions a suite
of policy instruments will be needed (NRC, 2011c; Sperling and Nichols, 2012),
including voluntary schemes, which have been successful in some circumstances,
such as for the Japanese airline industry (Yamaguchi, 2010).
8101
Road transport
A wide array of policies and strategies has been employed in
different circumstances to restrain private LDV use, promote mass transit
modes, manage traffic congestion and promote new fuels in order to reduce
fossil fuel use, air pollution, and GHG emissions. These policies and
strategies overlap considerably, often synergistically.
The magnitude of urban growth and population redistribution
from rural to urban areas in emerging and developing countries is expected to
continue (see Sections 8.2 and 12.2). This implies a large increase in demand
for motorized transport especially in medium-size cities (Grubler et al.,
2012). In regions and countries presently with low levels of LDV ownership,
opportunities exist for local and national governments to manage future rising
road vehicle demand in ways that support economic growth, provide broad social
benefits (Wright and Fulton, 2005; IEA, 2009; Kato et al., 2005) and keep GHG
emissions in bounds. Local history and social culture can help shape the
specific problem, together with equity implications and policy aspirations that
ultimately determine what will become acceptable solutions (Vasconcellos, 2001;
Dimitriou, 2006; Kane, 2010; Li, 2011; Verma et al., 2011).
Even if non-OECD countries pursue strategies and policies
that encourage LDV use for a variety of economic, social, and environmental
motivations, per capita LDV travel in 2050 could remain far below OECD
countries. However, in many OECD countries, passenger LDV travel demand per
capita appears to have begun to flatten, partly driven by increasing levels of
saturation and polices to manage increased road transport demand (Section 8.2.1;
Millard-Ball and Schipper, 2011; Schipper, 2011; Goodwin, 2012; IEA, 2012c;
Meyer et al., 2012). Even if this OECD trend of slowing growth in LDV travel
continues or even eventually heads downwards, it is unlikely to offset
projected growth in non-OECD LDV travel or emissions because those populations
and economies are likely to continue to grow rapidly along with LDV ownership.
Only with very aggressive policies in both OECD and non-OECD countries would
total global LDV use stabilize in 2050. This is illustrated in a 2 °C LDV
transport scenario generated by Fulton et al. (2013), using mainly IEA (2012c)
data. In that policy scenario, LDV travel in OECD countries reaches a peak of
around 7500 vehicle km / capita in 2035 then drops by about 20 % by 2050. By
comparison, per capita LDV travel in non-OECD countries roughly quadruples from
an average of around 500 vehicle km / capita in 2012 to about 2000 vehicle km /
capita in 2050, remaining well below the OECD average.
Many countries have significant motor fuel taxes that,
typically, have changed little in recent years. This indicates that such a
market instrument is not a policy tool being used predominantly to reduce GHG
emissions. The typical approach increasingly being used is a suite of
regulatory and other complementary policies with separate instruments for
vehicles and for fuels. The challenge is to make them consistent and coherent.
For instance, the fuel efficiency and GHG emission standards for vehicles in
Europe and the United States give multiple credits to plug-in electric vehicles
(PEVs) and fuel cell vehicles (FCVs). Zero upstream emissions are assigned,
although this is technically incorrect but designed to be an implicit subsidy
(Lutsey and Sperling, 2012).
Fuel choice and
carbon intensity[10].
Flexible fuel standards that combine regulatory and market features include the
Californian lowcarbon fuel standard (LCFS) (Sperling and Nichols, 2012) and the
European Union fuel quality directive (FQD). Fuel carbon intensity reduction
targets for 2020 (10 % for California and 6 % for EU) are expected to be met by
increasing use of low-carbon biofuels, hydrogen, and electricity. They are the
first major policies in the world premised on the measurement of lifecycle GHG
intensities (Yeh and Sperling, 2010; Creutzig et al., 2011), although
implementation of lifecycle analyses can be challenging and sometimes
misleading since it is difficult to design implementable rules that fully
include upstream emissions (Lutsey and Sperling, 2012); emissions resulting from
induced market effects; and emissions associated with infrastructure, the
manufacturing of vehicles, and the processing and distribution of fuels (for
LCA see Annex II.6.3 Kendall and Price, 2012).
Biofuel policies have become increasingly controversial as
more scrutiny is applied to the environmental and social equity impacts
(Section 11.13). In 2007, the European Union and the United States adopted
aggressive biofuel policies (Yeh and Sperling, 2013). The effectiveness of
these policies remains uncertain, but follow-up policies such as California’s
LCFS and EU’s FQD provide broader, more durable policy frameworks that harness
market forces (allowing trading of credits), and provide flexibility to
industry in determining how best to reduce fuel carbon intensity. Other related
biofuel policies include subsidies (IEA, 2011d) and mandatory targets (REN21,
2012).
Vehicle energy intensity. The element of transport that
shows the greatest promise of being on a trajectory to achieve large reductions
in GHG emissions by 2050 is reducing the energy and fuel carbon intensities of
LDVs. Policies are being put in place to achieve dramatic improvements in
vehicle efficiency, stimulating automotive companies to make major investments.
Many countries have now adopted aggressive targets and standards (Figure 8.13),
with some standards criticized
emissions targets for LDVs in selected countries and
European Union, normalized by using the same New European Driving Cycle (NDEC)
that claims to represent real-world driving conditions. Source: ICCT (2007,
2013)
Notes: (1)
China’s target reflects gasoline LDVs only and may become higher if new energy
vehicles are considered. (2) Gasoline in Brazil contains 22 % ethanol but data
here are converted to 100 % gasoline equivalent.
for not representing real-world conditions (Mock et al.,
2012). Most are developed countries, but some emerging economies, including
China and India, are also adopting increasingly aggressive standards (Wang et
al., 2010).
Regulatory standards focused on fuel consumption and GHG
emissions vary in their design and stringency. Some strongly stimulate
reductions in vehicle size (as in Europe) and others provide strong incentives
to reduce vehicle weight (as in the United States) (CCC, 2011). All have
different reduction targets. As of April 2010, 17 European countries had
implemented taxes on LDVs wholly or partially related to CO2
emissions. Regulatory standards require strong market instruments and align
market signals with regulations as they become tighter over time. Examples are
fuel and vehicle purchase taxes and circulation taxes that can limit rebound
effects. Several European countries have established revenue-neutral feebate
schemes (a combination of rebates
awarded to purchasers of low carbon emission vehicles and fees charged to purchasers of less efficient vehicles) (Greene and
Plotkin, 2011). Annual registration fees
can have similar effects if linked directly with carbon emissions or with
related vehicle attributes such as engine displacement, engine power, or
vehicle weight (CARB, 2012). One concern with market-based policies is their
differential impact across population groups such as farmers needing robust
vehicles to traverse rugged terrain and poor quality roads. Equity adjustments
can be made so that farmers and large families are not penalized for having to
buy a large car or van (Greene and Plotkin, 2011).
Standards are likely to spur major changes in vehicle
technology, but in isolation are unlikely to motivate significant shifts away
from petroleum-fuelled ICE vehicles. In the United States, a strong tightening
of standards through to 2025 is estimated to trigger only a 1 % market share
for PEVs if only economics is considered (EPA, 2011).
A more explicit regulatory instrument to promote EVs and
other new, potentially very-low carbon propulsion technologies is a zero
emission vehicle mandate, as originally adopted by California in 1990 to
improve local air quality, and which now covers almost 30 % of the United
States market. This policy, now premised on reducing GHGs, requires about 15 %
of new vehicles in 2025 to be a mix of PEVs and FCVs (CARB, 2012).
There are large potential efficiency improvements possible
for medium and heavy-duty vehicles (HDVs) (see Section 8.3.1.2), but policies
to pursue these opportunities have lagged those for LDVs. Truck types, loads,
applications, and driving cycles are much more varied than for LDVs and engines
are matched with very different designs and loads, thereby complicating
policy-making. However, China implemented fuel consumption limits for HDVs in
July 2012 (MIIT, 2011); in 2005 Japan set modest fuel efficiency standards to
be met by 2015 (Atabani et al., 2011); California, in 2011, required compulsory
retrofits to reduce aerodynamic drag and rolling resistance (Atabani et al.,
2011); the United States adopted standards for new HDVs and buses manufactured
from 2014 to 2018 (Greene and Plotkin, 2011); and the EU intends to pursue
similar actions including performance standards and fuel efficiency labelling
by 2014 (Kojima and Ryan, 2010). Aggressive air pollution standards since the
1990s for NOx and particulate matter emissions from HDVs in
many OECD countries have resulted in a fuel consumption penalty in the past of
7 % to 10 % (IEA, 2009; Tourlonias and Koltsakis, 2011). However, emission
technology improvements and reductions in black carbon emissions, which
strongly impact climate change (see Section 8.2.2.1), will offset some of the
negative effect of this increased fuel consumption.
Activity reduction.
A vast and diverse mix of policies is used to restrain and reduce the use of
LDVs, primarily by focusing on land use patterns, public transport options, and
pricing. Other policy strategies to reduce activity include improving traffic
management (Barth and Boriboonsomsin, 2008), better truck routing systems
(Suzuki, 2011), and smart realtime information to reduce time searching for a
parking space. Greater support for innovative services using information and
communication technologies, such as dynamic ride sharing and demand-responsive
para-transit services (see Section 8.4), creates still further opportunities to
shift toward more energy efficient modes of travel.
Policies can be effective at reducing dependence on LDVs as
shown by comparing Shanghai with Beijing, which has three times as many LDVs
even though the two cities have similar levels of affluence, the same culture,
and are of a similar population (Hao et al., 2011). Shanghai limited the
ownership of LDVs by establishing an expensive license auction, built fewer new
roads, and invested more in public transport, whereas Beijing built an
extensive network of high capacity expressways and did little to restrain car
ownership or use until recently. The Beijing city administration has curtailed
vehicle use by forbidding cars to be used one day per week since 2008, and
sharply limited the number of new license plates issued each year since 2011
(Santos et al., 2010) Hao et al., 2011). The main aims to reduce air pollution,
traffic congestion, and costs of road infrastructure exemplify how policies to
reduce vehicle use are generally, but not always, premised on non-GHG
co-benefits. European cities have long pursued demand reduction strategies,
with extensive public transport supply, strict growth controls, and more recent
innovations such as bicycle sharing. California seeks to create more liveable
communities by adopting incentives, policies, and rules to reduce vehicle use,
land use sprawl, and GHG emissions from passenger travel. The California law
calls for 6 – 8 % reduction in GHG emissions from passenger travel per capita
(excluding changes in fuel carbon intensity and vehicle energy intensity) in
major cities by 2020, and 13 – 16 % per capita by 2035 (Sperling and Nichols,
2012).
The overall
effectiveness of initiatives to reduce or restrain road vehicle use varies
dramatically depending on local commitment and local circumstances, and the
ability to adopt synergistic policies and practices by combining pricing, land
use management, and public transport measures. A broad mix of policies
successfully used to reduce vehicle use in OECD countries, and to restrain
growth in emerging economies, includes pricing to internalize energy,
environmental, and health costs; strengthening land use management; and
providing more and better public transport.
Policies to reduce LDV activity can be national, but mostly
they are local, with the details varying from one local administration to
another.
Some policies are intrinsically more effective than others.
For instance, fuel taxes will reduce travel demand but drivers are known to be
relatively inelastic in their response (Hughes et al., 2006; Small and van
Dender, 2007). However, drivers are more elastic when price increases are
planned and certain (Sterner, 2007). Pricing instruments such as congestion
charges, vehicle registration fees, road tolls and parking management can
reduce LDV travel by inducing trip chaining, modal shifts, and reduced use of
cars (Litman, 2006). Policies and practices of cities in developing countries
can be influenced by lending practices of development banks, such as the Rio+20
commitment to spend approximately 170 billion USD2010 on more
sustainable transport projects, with a focus on Asia (ADB, 2012c).
System efficiency. Improvements have been far greater in
freight transport and aviation than for surface passenger transport (rail and
road). Freight transport has seen considerable innovation in containerization
and intermodal connections, as has aviation, though the effects on GHG
emissions are uncertain (and could be negative because of just-in-time
inventory management practices). For surface passenger travel, efforts to
improve system efficiency and inter-modality are hindered by conflicting and
overlapping jurisdictions of many public and private sector entities and
tensions between fiscal, safety, and equity goals. Greater investment in roads
than in public transport occurred in most cities of developed countries through
the second half of the 20th century (Owens, 1995; Goodwin, 1999). The 21st
century, though, has seen increasing government investment in bus rapid transit
and rail transit in OECD countries (Yan and Crookes, 2010; Tennøy, 2010) along
with increasing support for bicycle use.
Since the 1960s, many cities
have instigated supportive policies and infrastructure that have resulted in a
stable growth in cycling (Servaas, 2000; Hook, 2003; TFL, 2007; NYC, 2012).
Several European cities have had high cycle transport shares for many years,
but now even in London, UK, with efficient public transport systems, the 2 %
cycle share of travel modes is targeted to increase to 5 % of journeys in 2026
as a result of a range of new policies (TFL, 2010). However, in less developed
cities such as Surabaya, Indonesia, 10 % of total trips between 1 – 3 km are
already by cycling (including rickshaws) in spite of unsupportive
infrastructure and without policies since there are few affordable alternatives
(Hook, 2003). Where cycle lanes have been improved, as in Delhi, greater uptake
of cycling is evident (Tiwari and Jain, 2012).
8102
Rail transport
Rail transport serves 28 billion passengers globally,
carrying them around 2500 billion p-km / yr[11].
Rail also carries 11.4 billion tonne of freight (8845 billion t-km / yr)
(Johansson et al., 2012). Policies to further improve system efficiency may
improve competitiveness and opportunities for modal shift to rail (Johansson et
al., 2012). Specific energy and carbon intensities of rail transport are
relatively small compared to some other modes (see Section 8.3). System
efficiency can also be assisted through train driver education and training
policies (Camagni et al., 2002).
Fuel intensity. Roughly one third of all rail
transport is driven by diesel and two-thirds by electricity (Johansson et al.,
2012). Policies to reduce fuel carbon intensity are therefore linked to a large
extent to those for decarbonizing electricity production (Chapter 7; DLR,
2012). For example, Sweden and Switzerland are running their rail systems using
very low carbon electricity (Gössling, 2011).
Energy intensity. Driven largely by corporate
strategies, the energy intensity of
rail transport has been reduced by more than 60 % between 1980 and 2001 in the
United States (Sagevik, 2006). Overall reduction opportunities of 45 – 50 % are
possible for passenger transport in the EU and 40 – 50 % for freight (Andersson
et al., 2011). Recent national policies in the United Kingdom and Germany
appear to have resulted in 73 % rail freight growth over the period 1995 –
2007, partly shifted from road freight.
System efficiency. China,
Europe, Japan, Russia, United States and several Middle-eastern and Northern
African countries continue (or are planning) to invest in high-speed rail (HSR)
(CRC, 2008). It is envisaged that the worldwide track length of about 15,000 km
in 2012 will nearly triple by 2025 due to government supporting policies,
allowing HSR to better compete with medium haul aviation (UIC, 2012).
8103
Waterborne transport
Although
waterborne transport is comparatively efficient in terms of gCO2
/ t-km compared to other freight transport modes (see Section 8.6), the
International Maritime Organization (IMO) has adopted mandatory measures to
reduce GHG emissions from international shipping (IMO, 2011). This is the first
mandatory GHG reduction regime for an international industry sector and for the
standard to be adopted by all countries is a model for future international
climate change co-operation for other sectors (Yamaguchi, 2012). Public
policies on emissions from inland waterways are nationally or regionally based
and currently focus more on the reduction of NOx and
particulate matter than on CO2. However, policy measures are being
considered to reduce the carbon intensity of this mode including incentives to
promote ‘smart steaming’, upgrade to new, larger vessels, and switch to
alternative fuels, mainly LNG (Panteia, 2013). Few if any, policies support the
use of biofuels, natural gas or hydrogen for small waterborne craft around
coasts or inland waterways and little effort has been made to assess the
financial implications of market (and other) policies on developing countries
who tend to import and export low value-to-weight products, such as food and
extractible resources (Faber et al., 2012).
Energy intensity IMO’s Energy Efficiency Design Index (EEDI) is to
be phased in between 2013 and 2025. It aims to improve the energy efficiency of
certain categories of new ships and sets technical standards (IMO, 2011).
However, the EEDI may not meet the target if shipping demand increases faster
than fuel carbon and energy intensities improve. The voluntary Ship Energy
Efficiency Management Plan (SEEMP)
was implemented in 2013 (IMO, 2011). For different ship types and sizes it provides
a minimum energy efficiency level. As much as 70 % reduction of emissions from
new ships is anticipated with the aim to achieve approximately 25 – 30 %
reductions overall by 2030 compared with business-as-usual (IISD, 2011). It is
estimated that, in combination, EEDI requirements and SEEMP will cut CO2
emissions from shipping by 13 % by 2020 and 23 % by 2030 compared to a ‘no
policy’ baseline (Lloyds Register and DNV, 2011). 
8104
Aviation
After the Kyoto Protocol directed parties in Annex I to
pursue international aviation GHG emission limitation / reduction working
through the International Civil Aviation Organization (ICAO) (Petersen, 2008),
member states are working together with the industry towards voluntarily
improving technologies, increasing the efficient use of airport infrastructure
and aircraft, and adopting appropriate economic measures (ICAO, 2007b; ICAO,
2010a). In 2010, ICAO adopted global aspirational goals for the international
aviation sector to improve fuel efficiency by an average of 2 % per annum until
2050 and to keep its global net carbon emissions from 2020 at the same level
(ICAO, 2010b). These goals exceed the assumptions made in many scenarios (Mayor
and Tol, 2010).
Policy options in place or under consideration include
regulatory instruments (fuel efficiency and emission standards at aircraft or
system levels); market-based approaches (emission trading under caps, fuel
taxes, emission taxes, subsidies for fuel efficient technologies); and
voluntary measures including emission offsets (Daley and Preston, 2009).
Environmental capacity constraints on airports also exist and may change both
overall volumes of air transport and modal choice (Upham et al., 2004; Evans,
2010). National policies affect mainly domestic aviation, which covers about 30
– 35 % of total air transport (IATA, 2009; Lee et al., 2009; Wood et al.,
2010). A nationwide capand-trade policy could have the unintended consequence
of slowing aircraft fleet turnover and, through diverted revenue, of delaying technological
upgrades, which would slow GHG reductions, though to what degree is uncertain
(Winchester et al., 2013). In the UK, an industry group including airport
companies, aircraft manufacturers and airlines has developed a strategy for
reducing GHG emissions across the industry (Sustainable Aviation, 2012).
The EU is currently responsible for 35 % of global aviation
emissions. The inclusion of air transport in the EU emission trading scheme
(ETS) is the only binding policy to attempt to mitigate emissions in this
sector (Anger, 2010; Petersen, 2008; Preston et al., 2012). The applicability
of ETS policy to non-European routes (for flights to and from destinations
outside the EU) (Malina et al., 2012) has been delayed for one year, but the
directive continues to apply to flights between destinations in the EU
following a proposal by the European Commission in November 2012 in
anticipation of new ICAO initiatives towards a global market-based mechanism
for all aviation emissions (ICAO, 2012).
Taxing fuels, tickets, or emissions may reduce air transport
volume with elasticities varying between – 0.3 to – 1.1 at national and
international levels, but with strong regional differences (Europe has 40 %
stronger elasticities than most other world regions, possibly because of more
railway options). Airport congestion adds considerable emissions (Simaiakis and
Balakrishnan, 2010) and also tends to moderate air transport demand growth to
give a net reduction of emissions at network level (Evans and Schäfer, 2011).
Fuel carbon intensity.
Policies do not yet exist to introduce low-carbon biofuels. However, the
projected GHG emission reductions from the possible future use of biofuels, as
assumed by the aviation industry, vary between 19 % of its adopted total
emission reduction goal (Sustainable Aviation, 2008) to over 50 % (IATA,
2009),depending on the assumptions made for the other reduction options that
include energy efficiency, improved operation and trading emission permits.
Sustainable production issues also apply (see Section 8.3.3).
Energy intensity. The energy efficiency of aircraft has
improved historically without any policies in force, but with the rate of fuel
consumption reducing over time from an initial 3 – 6 % in the 1950s to between
1 % and 2 % per year at the beginning of the 21st century (Pulles et al., 2002;
Fulton and Eads, 2004; Bows et al., 2005; Peeters and Middel, 2007; Peeters et
al., 2009). This slower rate of fuel reduction is possibly due to increasing
lead-times required to develop, certify, and introduce new technology (Kivits
et al., 2010).
System efficiency. The interconnectedness of aviation services can be a complicating
factor in adopting policies, but also lends itself to global agreements. For
example, regional and national air traffic controllers have the ability to
influence operational efficiencies. The use of market policies to reduce GHG
emissions is compelling because it introduces a price signal that influences
mitigation actions across the entire system. But like other aspects of the
passenger transport system, a large price signal is needed with aviation fuels
to gain significant reductions in energy use and emissions (Tol, 2007; Peeters
and Dubois, 2010; OECD and UNEP, 2011). Complementary policies to induce system
efficiencies include measures to divert tourists to more efficient modes such
as high-speed rail. However, since short- and medium-haul aircraft now have
similar energy efficiencies per passenger km compared to LDVs (Figure 8.6),
encouraging people to take shorter journeys (hence by road instead of by air),
thereby reducing tourism total travel, has become more important (Peeters and
Dubois, 2010). No country has adopted a low-carbon tourism strategy (OECD and
UNEP, 2011).
8105
Infrastructure and urban planning
Urban form has a direct effect on transport activity (see
Section 12.4). As a consequence, infrastructure policies and urban planning can
provide major contributions to mitigation (see Section 12.5). A modal shift
from LDVs to other surface transport modes could be partly incentivized by
policy measures that impose physical restrictions as well as pricing regimes.
For example, LDV parking management is a simple form of cost effective, pricing
instrument (Barter et al., 2003; Litman, 2006). Dedicated bus lanes, possibly
in combination with a vehicle access charge for LDVs, can be strong instruments
to achieving rapid shifts to public transport (Creutzig and He, 2009).
Policies that support the
integration of moderate to high density urban property development with
transit-oriented development strategies that mix residential, employment, and
shopping facilities can encourage pedestrians and cyclists, thereby giving the
dual benefits of reducing car dependence and preventing urban sprawl (Newman
and Kenworthy, 1996; Cervero, 2004; Olaru et al., 2011). GHG emissions savings
(Trubka et al., 2010a; Trubka et al., 2010b) could result in cobenefits of
health, productivity, and social opportunity (Trubka et al., 2010c; Ewing and
Cervero, 2010; Höjer et al., 2011) if LDV trips could be reduced using
polycentric city design and comprehensive smartgrowth policies (Dierkers et
al., 2008). Policies to support the building of more roads, airports, and other
infrastructure can help relieve congestion in the short term, but can also
induce travel demand (Duranton and Turner, 2011) and create GHG emissions from
construction (Chester and Horvath, 2009).
8.11 Gaps in knowledge and data
The following gaps made assessing the mitigation potential
of the transport sector challenging.
Gaps in the basic statistics are still evident on the costs
and energy consumption of freight transport, especially in developing
countries.
•
Data and understanding relating to freight
logistical systems and their economic implications are poor, as are the future
effects on world trade of decarbonization and climate change impacts. Hence, it
is difficult to design new low-carbon freight policies.
•
Future technological developments and costs of
batteries, fuel cells, and vehicle designs are uncertain.
•
The infrastructure requirement for new
low-carbon transport fuels is poorly understood.
•
Cost of components for novel vehicle powertrains
cannot be determined robustly since rates of learning, cost decreases, and
associated impacts are unknown.
•
Assessments of mitigating transport GHG
emissions, the global potential, and costs involved are inconsistent.
•
Prices of crude oil products fluctuate widely as
do those for alternative transport fuels, leading to large variations in
scenario modelling assumptions. 
•
A better knowledge of consumer travel behaviour
is needed, particularly for aviation.
•
Limited understanding exists of how and when
people will choose to buy and use new types of low-carbon vehicles or mobility
services (such as demand responsive transit or car-share).
•
There are few insights of behavioural economics
to predict mobility systematically and whether producers will incorporate
low-carbon technologies that may not maximize profit.
•
How travellers will respond to combinations of
low-carbon strategies (mixes of land use, transit, vehicle options) is
especially important for fast-growing, developing countries where alternative
modes to the car-centric development path could be deployed, is unknown.
•
Understanding how low-carbon transport and
energy technologies will evolve (via experience curves and innovation
processes) is not well developed. Most vehicles rely on stored energy, so there
is a need to better understand the cost and energy density of nonhydrocarbon
energy storage mediums, such as batteries, supercapacitors and pressure
vessels.
•
Decoupling of transport GHG from economic growth
needs further elaboration, especially the policy frameworks that can enable
this decoupling to accelerate in both OECD and non-OECD nations.
•
The rate of social acceptance of innovative
concepts such as LDV road convoys, induction charging of electric vehicles, and
driverless cars (all currently being demonstrated) is difficult to predict, as
is the required level of related infrastructure investments. Recent rapid
developments in metro systems in several cities illustrate how quickly new
transport systems can be implemented when the demand, policies, and investments
all come together and public support is strong.
8.12 Frequently Asked Questions
FAQ 81 How much
does the transport sector contribute to GHG emissions and how is this changing?
The transport sector is a key enabler of economic activity
and social connectivity. It supports national and international trade and a
large global industry has evolved around it. Its greenhouse gas (GHG) emissions
are driven by the ever-increasing demand for mobility and movement of goods.
Together, the road, aviation, waterborne, and rail transport sub-sectors
currently produce almost one quarter of total global energy-related CO2
emissions [Section 8.1]. Emissions have more than doubled since 1970 to reach
7.0 Gt CO2eq by 2010 with about 80 % of this increase
coming from road vehicles. Black carbon and other aerosols, also emitted during
combustion of diesel and marine oil fuels, are relatively short-lived radiative
forcers compared with carbon dioxide and their reduction is emerging as a key
strategy for mitigation [8.2].
Demands for transport of people and goods are expected to
continue to increase over the next few decades [8.9]. This will be exacerbated
by strong growth of passenger air travel worldwide due to improved
affordability; by the projected demand for mobility access in non-OECD
countries that are starting from a very low base; and by projected increases in
freight movements. A steady increase of income per capita in developing and
emerging economies has already led to a recent rapid growth in ownership and use
of 2-wheelers, 3-wheelers and light duty vehicles (LDVs), together with the
development of new transport infrastructure including roads, rail, airports,
and ports.
Reducing transport emissions
will be a daunting task given the inevitable increases in demand. Based on continuing current rates of growth
for passengers and freight, and if no mitigation options are implemented to
overcome the barriers [8.8], the current transport sector’s GHG emissions could
increase by up to 50 % by 2035 at continued current rates of growth and almost
double by 2050 [8.9]. An increase of transport’s share of global energy-related
CO2
emissions would likely result. However, in spite of lack of progress in many
countries to date, new vehicle and fuel technologies, appropriate infrastructure
developments including for non-motorized transport in cities, transport
policies, and behavioural changes could begin the transition required [8.3,
8.4, 8.9].
FAQ 82 What are
the main mitigation options and potentials for reducing GHG emissions?
Decoupling transport from GDP growth is possible but will
require the development and deployment of appropriate measures, advanced
technologies, and improved infrastructure. The cost-effectiveness of these
opportunities may vary by region and over time [8.6]. Delivering mitigation
actions in the short-term will avoid future lock-in effects resulting from the
slow turnover of stock (particularly aircraft, trains, and ships) and the
long-life and sunk costs of infrastructure already in place [8.2, 8.4].
When developing low-carbon transport systems, behavioural
change and infrastructure investments are often as important as developing more
efficient vehicle technologies and using lower-carbon fuels [8.1, 8.3].
•
Avoidance:
Reducing transport activity can be achieved by avoiding unnecessary
journeys, (for example by tele-commuting and internet shopping), and by
shortening travel distances such as through the densification and mixed-zoning
of cities.
• Modal choice: Shifting transport
options to more efficient modes is possible, (such as from private cars to
public transport, walking, and cycling), and can be encouraged by urban
planning and the development of a safe and efficient infrastructure.
• Energy intensity: Improving the performance efficiency of aircraft, trains, boats,
road vehicles, and engines by manufacturers continues while optimizing
operations and logistics (especially for freight movements) can also result in
lower fuel demand.
• Fuel carbon intensity: Switching to lower carbon fuels and
energy carriers is technically feasible, such as by using sustainably produced
biofuels or electricity and hydrogen when produced using renewable energy or
other low-carbon technologies.
These four categories of transport mitigation options tend
to be interactive, and emission reductions are not always cumulative. For
example, an eco-driven, hybrid LDV, with four occupants, and fuelled by a
low-carbon biofuel would have relatively low emissions per passenger kilometre
compared with one driver travelling in a conventional gasoline LDV. But if the
LDV became redundant through modal shift to public and non-motorized transport,
the overall emission reductions could only be counted once.
Most mitigation options apply to both freight and passenger
transport, and many are available for wide deployment in the short term for
land, air, and waterborne transport modes, though not equally and at variable
costs [8.6]. Bus rapid transit, rail, and waterborne modes tend to be
relatively carbon efficient per passenger or tonne kilometre compared with LDV,
HDV, or aviation, but, as for all modes, this varies with the vehicle occupancy
rates and load factors involved. Modal shift of freight from short- and
medium-haul aircraft and road trucks to high-speed rail and coastal shipping often
offers large mitigation potential [Table 8.3]. In addition, opportunities exist
to reduce the indirect GHG emissions arising during the construction of
infrastructure; manufacture of vehicles; and extraction, processing, and
delivery of fuels.
The potentials for various
mitigation options vary from region to region, being influenced by the stage of
economic development, status and age of existing vehicle fleet and
infrastructure, and the fuels available in the region. In OECD countries,
transport demand reduction may involve changes in lifestyle and the use of new
information and communication technologies. In developing and emerging
economies, slowing the rate of growth of using conventional transport modes
with relatively high-carbon emissions for passenger and freight transport by
providing affordable, low-carbon options could play an important role in
achieving global mitigation targets. Potential GHG emissions reductions from
efficiency improvements on new vehicle designs in 2030 compared with today
range from 40 – 70 % for LDVs, 30 – 50 % for HDVs, up to 50 % for aircraft, and
for new ships when combining technology and operational measures, up to 60 %
[Table
8.3].
Policy options to encourage the
uptake of such mitigation options include implementing fiscal incentives such
as fuel and vehicle taxes, developing standards on vehicle efficiency and
emissions, integrating urban and transport planning, and supporting measures
for infrastructure investments to encourage modal shift to public transport,
walking, and cycling [8.10]. Pricing strategies can reduce travel demands by
individuals and businesses, although
successful transition of the sector may also require strong education policies
that help to create behavioural change and social acceptance. Fuel and vehicle
advances in the short to medium term will largely be driven through research
investment by the present energy and manufacturing industries that are endeavouring
to meet existing policies as well as to increase their market shares. However,
in order to improve upon this business-asusual scenario and significantly
reduce GHG emissions across the sector in spite of the rapidly growing demand,
more stringent policies will be needed. To achieve an overall transition of the
sector will require rapid deployment of new and advanced technology
developments, construction of new infrastructure, and the stimulation of
acceptable behavioural changes.
FAQ 83 Are
there any co-benefits associated with mitigation actions?
Climate change mitigation strategies in the transport sector
can result in many co-benefits [8.7]. However, realizing these benefits through
implementing those strategies depends on the regional context in terms of their
economic, social, and political feasibility as well as having access to
appropriate and cost-effective advanced technologies. In developing countries
where most future urban growth will occur, increasing the uptake, comfort, and
safety of mass transit and nonmotorized transport modes can help improve
mobility. In least developing countries, this may also improve access to
markets and therefore assist in fostering economic and social development. The opportunities to shape urban
infrastructure and transport systems to gain greater sustainability in the
short- to medium-terms are also likely to be higher in developing and emerging
economies than in OECD countries where transport systems are largely locked-in
[8.4]. 
A reduction in LDV travel and ownership has been observed in
several cities in OECD countries, but demand for motorized road transport,
including 2- and 3-wheelers, continues to grow in non-OECD nations where
increasing local air pollution often results. Well-designed policy packages can
help lever the opportunities for exploiting welfare, safety, and health
co-benefits [8.10]. Transport strategies associated with broader policies and
programmes can usually target several policy objectives simultaneously. The
resulting benefits can include lower travel costs, improved mobility, better
community health through reduced local air pollution and physical activities
resulting from nonmotorized transport, greater energy security, improved
safety, and time savings through reduction in traffic congestion.
A number of
studies suggest that the direct and indirect benefits of sustainable transport
measures often exceed the costs of their implementation [8.6, 8.9]. However,
the quantification of co-benefits and the associated welfare effects still need
accurate measurement. In all regions, many barriers to mitigation options exist
[8.8], but a wide range of opportunities are available to overcome them and
give deep carbon reductions at low marginal costs in the medium- to long-term
[8.3, 8.4, 8.6, 8.9]. Decarbonizing the transport sector will be challenging
for many countries, but by developing well-designed policies that incorporate a
mix of infrastructural design and modification, technological advances, and
behavioural measures, co-benefits can result and lead to a cost-effective
strategy.
[1] CO2eq
units are used throughout this chapter for direct emissions wherever feasible,
although this is not always the case in some literature that reports CO2
emissions only. For most transport modes, non-CO2 gases are
usually less than 5 % of total vehicle emissions.
[2] LDVs are motorized
vehicles (passenger cars and commercial vans) below approximately 2.5 – 3.0 t
net weight with HDVs (heavy duty vehicles or “trucks” or “lorries”) usually
heavier.
[3] Based on the
breakdown into A (total Activity), S (modal Structure), I (modal energy
Intensity), and F (carbon content of Fuels) using the ‘ASIF approach’. Details
of how this decomposition works and the science involved can be found in
Schipper et al. (2000); Kamakaté and Schipper (2009).
[4] “Litre per gasoline
equivalent” allows for a comparison between fuels with different energy
contents.
[5]
Should a BEV run out of stored energy, it is less easy to refuel than is an ICE
vehicle that runs out of gasoline. With typical ranges around 100 – 160 km, BEV
drivers can become anxious about failing to complete their journey.
[6] Para-transit, also
called “community-transit”, is where flexible passenger transport minibuses
(also termed matatus and marshrutkas), shared taxis, and jitneys operate in
areas with low population density without following fixed routes or schedules.
[7] Section 6.2.2 and
Annex II.10 provide details on the WG III AR5 Scenario Database, which is the
source of more than 1,200 integrated scenarios.
[8] This section builds
upon the scenarios which were collated by Chapter 6 in the WG III AR5 Scenario
Database and compares them to global scale transport studies. The scenarios
were grouped into baseline and mitigation scenarios. As described in more
detail in Chapter 6.3.2, the scenarios are further categorized into bins based
on 2100 concentrations: between 430 – 480 ppm CO2eq, 480 – 530
ppm CO2eq, 530 – 580 ppm CO2eq, 580 – 650 ppm CO2eq,
650 – 720 ppm CO2eq, and > 720 ppm CO2eq.
An assessment of geo-physical climate uncertainties, consistent with the
dynamics of Earth System Models assessed in WGI, found that the most stringent
of these scenarios, leading to 2100 concentrations between 430 and 480 ppm CO2eq,
would lead to an end-of-century median temperature change between 1.6 to 1.8 °C
compared to pre-industrial times, although uncertainties in understanding of
the climate system mean that the possible temperature range is much wider than
this. They were found to maintain temperature change below 2 °C over the course
of the century with a likely chance. Scenarios in the concentration category of
650 – 720 ppm CO2eq correspond to comparatively modest
mitigation efforts, and were found to lead to median temperature rise of
approximately 2.6 – 2.9 °C in 2100 (Chapter 6.3.2). The x-axis of Figures 8.9
to 8.12 show specific sample numbers for each category of scenario reviewed.
[9]
These include land use planning that favours high density or polycentric urban
forms; public transport oriented developments with mixed uses; and high quality
city environments.
[10] The following four
sub-sections group policies along the lines of the decomposition as outlined in
8.1 and Figure 8.2
[11]
By way of comparison, aviation moves 2.1 billion passengers globally (some 3900
billion p-km / yr).
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