Integrated approach to reducing CO2
emissions of passenger cars
Measures associated with the use of the vehicles
Final report
Report for ACEA
Avenue des Nerviens 85
1040 Brussels
Belgium
Date: 30 July 2015
Author: Tim Breemersch
Transport & Mobility Leuven
Diestsesteenweg 57
3010 Leuven
Belgium
http://www.tmleuven.be
2
Executive summary
The European tr ansport sector is an important contributor to the European economy. It gets
people to their place of work, gives them access to leisure activities, and brings them the goods they
need or want. It creates employment in production, in research activities and in transport services.
Transport comes at a cost though. Vehicles need to be bought and maintained, fuel is for a large
part imported from outside the EU, and emissions of transport create externalities for humans,
animals and the environment. One of the most important externalities is the contribution of the
transport sector to climate change through CO2 emissions. The second largest contributor to EU
carbon emissions, transport is also the largest of those sectors for which emission levels are still
higher than the Kyoto protocol’s baseline value (of year 1990). Road transport is specifically subject
to this, as it relies for the bulk of its fuel needs on fossil fuels that generate carbon emissions.
European and national policies have been targeting road transport for several years, with vehicle
fuel efficiency standards as one of the most noteworthy measures. Current targets go up to 2021,
and further goals are being studied. These targets are expected to be met mainly by technical
changes to the vehicles’ propulsion systems. For the period beyond 2021, increasing marginal costs
of improving fuel efficiency could lead to price increases.
The aim of this project was to list and assess options to reduce CO2 emissions of passenger cars
that were not directly based on vehicle technology, and that could spread the burden of carbon
intensity reduction over all parties contributing to carbon emissions. It was estimated that passenger
cars as a subsector should reduce its CO2 emissions by around 170 million tonnes in 2030,
equivalent to 30% of the 2005 level.
The following options were considered:
 Ecodriving (training and ADAS)
 Road traffic management through ITS
 Road infrastructure
 Energy/Carbon content of fuels – renewable fuels
 Road transport in EU ETS
 Autonomous fleet renewal
 CO2 based vehicle taxation
 Vehicle labelling
 Tyres
Ecodriving can be promoted using two pathways: either by driver training, or by ADAS (advanced
driver assistance systems). Both have the same objective: making the driver operate the vehicle in
the most fuel efficient manner, either by a change in intrinsic behaviour (training), or by providing
instantaneous in-vehicle feedback and guidance (ADAS). While both can have an impact, their
combined effect is limited to around 15% reduction. The benefits can mainly be reaped in urban
environments and at lower speeds, where accelerations and decelerations occur more frequently.
On motorways, some benefits can come from free coasting as well.
ITS based Road traffic management systems can reduce vehicle fuel consumption by making
traffic smoother and vehicles running closer to peak efficiency. The systems can work at a local
level (intersections and highway corridors), the network level (spatial and temporal dispersion of
traffic, e.g. through dynamic routing) or the demand level (modal choice). In a way, the local level
3
effects extend the ecodriving measures at vehicle level to inter-vehicle communication, thus
reinforcing the benefits made there. At the higher aggregation levels, current research (which is still
fairly limited) indicates that a 1.3% additional decrease in CO2 emissions should be possible. Higher
gains are possible, e.g. with large scale implementation of local scale measures, but further research
is needed to quantify the potential.
Improving fuel efficiency of passenger cars by taking on road infrastructure is another possibility.
While multiple methods exist, the biggest effect can probably be generated by keeping roads well
maintained, thereby keeping parameters such as macrotexture and roughness close to the optimal
level. Improvement potential is around 1-2%. Road pavement material (usually a choice between
concrete and asphalt) is not a critical factor on its own. Limiting road gradients is generally not
considered a cost-effective manner of reducing vehicle fuel consumption, especially ex-post.
Nonetheless, it should be taken on board as a factor contributing to emissions when building new
roads. At a higher level of aggregation, building bypass roads around urban areas can have a
positive impact on fuel efficiency in the right circumstances, but the opposite can happen when
conditions are not right.
The use of biofuels in transport could possibly bring the single greatest improvement in CO2
intensity of the sector. However, the short to medium term outlook calls for tempered
expectations. EC policy, in the form of the RED and FQD, calls for limited contributions, and
research shows that even those are probably beyond reach (a JEC study estimates only 4.4% of 6%
FQD target will be achieved). The directives are being reviewed at this moment, but in their current
form they do not account for ILUC. The outcome of discussions on this topic could be decisive for
the future of biofuels. As for the improvement they could generate under the assumptions that
current policy will continue in a similar form, a reduction of GHG emissions of road transport
around 8% is estimated for 2030. As the potential for diesel vehicles is somewhat lower than for
gasoline vehicles, and these diesel powered HDV represent a significant part of total road transport
emissions, passenger car reductions could be higher still.
Literature suggests that moving from fuel efficiency standards to ETS as the practice for
management road transport carbon emissions would – at current permit prices – generate a 3%
reduction; much less than what recent proposals for CO2 targets beyond 2020 aim to achieve
(Note: this study covered road transport as part of the EU ETS only conceptually as it is not a
measure per se, but a system with a broader scope).
While the scope of this study explicitly omits new fuel standards, an assessment of the effect of
autonomous fleet renewal was made, under the assumption that the current 2021 target would
remain in place until at least 2030. In all three considered scenarios (differing real world new vehicle
emission levels for 2021), fleet renewal suffices for passenger car transport to meet a 30% reduction
by 2030 – with a baseline value of 37% reduction. The wave effect caused by fuel efficiency
standards lasts about a decade, and without further reduction measures, CO2 emissions will start
increasing again before 2035.
CO2 based vehicle taxation is becoming a common practice throughout Europe, but the absolute
and relative tax levels vary greatly between countries. Research suggests that it has a measurable
effect on fleet evolution. In the Netherlands and the UK, about 1/8 of recent reductions in average
new vehicle fuel consumption are due to CO2 based taxes – equivalent to 2-4%.
The effects of vehicle labelling as a measure to reduce fuel consumption by improving buyers’
knowledge have been insufficiently documented. A review of applicable legislation is ongoing.
4
Tyres for passenger cars have been subject to EC legislation since 2012, and effects on fuel
consumption are still building up throughout the fleet. However, they are expected to reach their
full potential around 2020, and are thus not expected to contribute much in the 2020’s.
The table below summarises the findings of this study.
Table A: Potential of non-vehicle tech CO2 reduction options for passenger cars, 2030 horizon
Measure
Potential
Comment
Ecodriving
15%
Combined effects of driver training and ADAS
ITS (network level)
1.3%
Network measures – local effects can be higher
Road infrastructure
1-2%
Improved maintenance, material choice less important
Biofuels
8%+
Not including ILUC
ETS
N/A
Much lower effect than fuel efficiency standards as CO2 is saved in other sectors
Autonomous fleet renewal
37%
Lingering effect of 2021 targets, fades out after 2030
CO2 based vehicle taxation
2-4%
Depends on the level of the tax
Vehicle labelling
N/A
Insufficient literature available for assessment
Tyres
0%
Most vehicles already equipped with fuel efficient tyres
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Contents
Executive summary ............................................................................................................................................3
Contents ...............................................................................................................................................................7
1
2
3
4
Introduction ...............................................................................................................................................9
1.1
Preamble......................................................................................................................................9
1.2
What are the 2030 targets? .......................................................................................................9
Longlist of available CO2 reduction options ..................................................................................... 11
2.1
Ecodriving................................................................................................................................ 11
2.2
Road traffic management systems (ITS based) .................................................................. 12
2.3
Road infrastructure ................................................................................................................. 15
2.4
Energy/Carbon content of fuels – Renewable fuels ........................................................ 17
2.5
Emission trading system ........................................................................................................ 18
2.6
Autonomous fleet renewal .................................................................................................... 19
2.7
CO2 based vehicle taxation ................................................................................................... 21
2.8
Vehicle labelling ...................................................................................................................... 25
2.9
Tyres ......................................................................................................................................... 26
2.10
Conclusion ............................................................................................................................... 27
Additional reviews of selected measures ............................................................................................ 29
3.1
Ecodriving................................................................................................................................ 29
3.2
Fuel Quality Directive/Renewable Energy Directive ....................................................... 33
3.3
Road transport in EU ETS ................................................................................................... 37
3.4
Autonomous fleet renewal .................................................................................................... 42
Conclusions ............................................................................................................................................. 45
References ......................................................................................................................................................... 47
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1
Introduction
1.1
Preamble
The European Union has adopted policies to reduce its CO2 emissions significantly in the future, as
part of the effort to limit global warming to no more than 2 degrees Celsius. As one of the most
important carbon emitting sectors, transport has been targeted by these policies both directly and
indirectly.
Through the adoption of fuel standards for passenger cars, the automobile industry is contributing
to the CO2 reduction efforts. Targets have been set for 2015 and 2021, and the EC is looking at the
possibilities for new regulation beyond that. The industry is committed to comply with current
regulation, but has always taken the position that the same burden share is applied for all sectors.
Therefore, ACEA commissioned Transport & Mobility Leuven (TML) to look into the potential
contribution to the CO2 reduction efforts of measures that go beyond the typical targets of EC
regulation, which focus primarily on the specific emissions of new vehicles (expressed in g/km).
This study provides an overview and brief assessment of the most interesting non- vehicle
technology measures that can help reduce passenger car transport’s CO2 emissions.
1.2
What are the 2030 targets?
Before starting the review of options to reach the EC’s CO2 targets, it is interesting to first consider
what the target actually is.
The general target for the EU as a whole is a reduction of Greenhouse Gas emissions of 40% of
1990 levels by the year 2030, double the 20% target that was set for 2020.1 At this point in time
however, it appears that there is no target for the (road) transport sector specifically. The only
general target is that non-ETS sector should reduce emissions by 30% compared to 2005 levels.
According to the EEA (indicator CSI010)2, road transport CO2 emissions evolved as follows (1 Gg
= 1000 tonnes; 1000 Gg = 1 Mt):
As defined in the EC’s 2030 framework for climate and energy policies,
http://ec.europa.eu/clima/policies/2030/index_en.htm
2 http://www.eea.europa.eu/data-and-maps/indicators/greenhouse-gas-emission-trends-5
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EU28 Road Transport CO2 emissions (Gg)
950,000
900,000
850,000
800,000
750,000
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
700,000
Figure 1: Evolution of EU28 road transport CO2 emissions
The values for the key years are:
Table 1: Historic Road Transport CO2 emissions
Year
1990
2005
2008
2012
Emissions
710,160.75 Gg
899,232.04 Gg
908,385.95 Gg
833,274.84 Gg
Comment
Kyoto protocol base year
EC policy framework base year
Transport White paper 2011 base year
Most recent reported data
To get an estimate of the absolute CO2 reduction from passenger cars, we can use TREMOVE 3.5c
as a starting point. Assuming the 30% reduction target will apply to all non-ETS sectors equally,
road transport as a whole should save just under 270 million tonnes of CO2 in the year 2030. If
within road transport all submodes (car, van, bus, two wheelers) are assumed to split the effort
according to their 2005 share in emissions, just under 30% would be the responsibility of freight
vehicles, and the remaining 70% comes from passenger transport. Within passenger transport,
passenger cars represent just under 90% of emissions. That would imply that passenger car CO2
emissions would have to be reduced by around 170 million tonnes in 2030.
The latest reported data (2012) suggest that about 1/3 of that total has already been realised. Based
on that dataset, it cannot be determined how much of that reduction can be attributed to passenger
transport and how much to freight transport. An approximation of the effect of the economic crisis
can be made based on Eurostat transport volumes, which show that freight vkm have decreased by
9% between 2005 and 2012 (24 countries), while passenger km of cars have increased by 4.4% over
that same period (6 countries: Spain, France, Czech Republic, Poland, Finland and the UK).
However, this does not provide an indication for the split of the reduction already achieved.
It should be noted that these emissions only cover tailpipe emissions (tank-to-wheel or TTW), and
not the emissions from fuel production (well-to-tank or WTT).
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2
Longlist of available CO2 reduction
options
In this section, a longlist of options will be compiled that can reduce CO2 emissions of passenger
cars in the post-2020 era. Measures related to vehicle and specifically engine technology are out of
scope, as they are sufficiently covered in other research.
2.1
Ecodriving
The concept of ecodriving can take many forms, but based on the general principles, two main
groups can be distinguished: driver training and driver assistance systems.
The assessment of the former is quite straightforward. Ecodriving training, which can be started as
early as during first driver training, focusses on methods and techniques to reduce fuel
consumption. It is based on the following principles:
 Avoiding unnecessary accelerating and braking through an anticipatory driving style;
 Avoiding the use of the air conditioning system unless absolutely necessary, and certainly at
lower speeds (when it’s better to open a window for cooling);
 Efficient engine use by selecting the correct gears;
 Slower driving in general;
 Switching off the engine when stopping for a longer period.
 Removing unnecessary equipment from the outside (aerodynamics) and inside (weight
reduction) of the vehicle.
Ecodriving training is most effective immediately after the course, with savings around 15%. After
a few years, the saving is reduced to 5-10%.3 Regular refresher courses are thus very useful. This
could be a cheap and effective manner to reduce emissions, but it requires effort from vehicle users.
Driver assistance systems are another potential contributor to a more efficient driving style. In
essence, these systems built into the vehicle can either give the driver information on what actions
to take to optimise fuel efficiency, or can automate certain of those actions themselves. Examples
include:
 Navigation systems;
 Speed regulation systems;
 Adaptive/Predictive Cruise Control.
To some extent, ecodriving training and driver assistance systems are mutually exclusive, as the
methods of driver training are based on the same underlying processes as driver assistance systems.
However, the practically inevitable drop-off in driver training effectiveness is ample justification for
the continued development of driver assistance systems.
Ecodriving in its different forms will be part of the stage 2 review of this study.
ECODRIVEN project: “Campaign Catalogue for European Ecodriving & Traffic Safety Campaigns”, 2008,
http://ec.europa.eu/energy/intelligent/projects/sites/ieeprojects/files/projects/documents/ecodriven_catalogue_campaign_en.pdf
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Table 2: Summary table longlist: driver behaviour
2.2
What?
Improving driver behaviour
How?
Either by training or by assistance systems built into the vehicle
Effect?
Around 15% total
Road traffic management systems (ITS based)
Looking at the impact of ITS, centred around road traffic management there are a number of
measures that help reduce the amount and impact of CO2 emissions. It is however practically not
viable to make general conclusions about certain of those impacts on the longer term, let alone
estimate their costs. Our approach therefore is to go by examples, and to base ourselves in part on
the EU ECOSTAND FP7 project4, in which we distinguish different categories for ITS
applications5. These are:
(1) improving driving behaviour,
(2) energy-efficient traffic control for intersections and highway corridors,
(3) energy-efficient traffic management on a network scale,
(4) travel demand management, and
(5) fleet management.
For our purposes, the most relevant ones are (2) for the local scale and (3) and (4) for a more global
point of view (Note that (1) is already covered in the previous paragraph; (5) is at a higher level of
aggregation than the individual vehicle and thus out of scope). All of them group the current stateof-the-art in the scene of advanced traffic management systems (ATMs).
Cat. 2: Energy-efficient traffic control for intersections and highway corridors aims to
increase bottleneck capacity by means of dynamic performance adaptation of road & traffic
control facilities, such as traffic signals, lane markings, variable message signs, guide lights,
toll gates, etc. This should reduce the average number of stops, giving advice on approach
to a stop line for cooperative vehicles (speed and lane choice), special handling of heavy
goods vehicles, energy-saving mode in the case of over-saturation, and soft platoon
formation for green waves. ITS supports this by cooperative communication such as V2I
and I2V.
Cat. 3: In addition, energy-efficient traffic management on a network scale strives to
mitigate traffic congestion and to increase the average travel speed in a network context.
Typical measures are to disperse traffic spatially and temporally via traffic information
provision, such as a dynamic route guidance system. Others are to regulate traffic flows for
the optimisation of total traffic performance, such as ramp metering. The measures which
work for an incident scene or parking scene are also included in this category.
http://www.ecostand-project.eu/
Guidelines for Assessing the Effects of ITS on CO2 Emissions: International Joint Report, ECOSTAND Deliverable,
2013
4
5
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Cat. 4: Finally, travel demand management influences travel behaviour and modal choice,
aiming to reduce the volume of vehicle traffic demand. Typical measures are to encourage
public transportation use. The pricing scheme for road use is included in this category as
well.
An interesting example is the eCoMove project6; its core concept is that there is a theoretical
minimum energy consumption achievable with the ‘perfect eco-driver’ travelling through the
‘perfectly eco-managed’ road network. To that end, the project employs V2X communication,
thereby bridging it from “just eco-driving” to cat. 3 traffic management on a network scale and cat.
4 travel demand management. As road operators balance traffic flows in the most energy efficient
way, the underlying idea is to reduce fuel consumption and therefore CO2 emissions up to 20%.
This is done by providing drivers with recommendations on how to improve efficiency depending
on the driving context (as already discussed in the section on ecodriving), by facilitating a more
economical and fuel efficient driving style and by encouraging the use of the most efficient routes
(this is the ITS ATMS network aspect). This helps to achieve applications such as eco-friendly
navigation, ramp metering, speed and headway management, and parking guidance. eCoMove thus
puts the emphasis on three major inefficiencies: inefficient route choice, inefficient driving
performance, and inefficient traffic management and control. The first links to the V2X
communication paradigm, whereas the third clears the path for more optimal traffic light
synchronisation. The consortium claims that around 22% of all wasted fuel is caused by inefficient
deceleration and/or a lack of anticipation, congestion is responsible for another 15%, whereas
excessive speed, inefficient traffic light control, and construction sites and/or traffic accidents each
account for another 11%. Communication via signalised intersections promises overall fuel savings
estimated at 16% (this includes HDVs as well). Sending information about signal status to drivers
was found to reduce both CO2 and NOx emissions by 5%, and increase PM10 emissions by 2.6%.
Additionally, as an example for cat. 4, we highlight the earlier “Spitsvrij” project in The
Netherlands. Its goal was to let people avoid the rush hour. It increased the reachability of the
region, as well as improved traffic flows by better usage of the existing infrastructure. This was
achieved by enticing a portion of some 60,000 motorists to change their travel behaviour in the
peak period. Results seemed to indicate that this worked, as for almost 90% of the subjects this was
the first time they saw alternatives for driving their car during peak periods. The project removed
around 1.5% to 2% of all cars out of the peak period.
Furthermore, we refer to the COSMO project7 which demonstrated the impact of the new
generation of ITS systems quantifying their advantages by looking at energy savings, traffic
efficiency, and the reduction of CO2 emissions. The project adopts a range of cooperative ITS
applications in several pilot sites that include urban and motorway scenarios and involve public
transport as well as private cars.
In similar spirit, the FREILOT project8 (2009 – 2012) used applications such as acceleration and
adaptive speed limiters, delivery space booking, eco driving support, and energy efficient
intersection control, evaluated in a number of cities. Experiments within the project reached fuel
and CO2 reductions of 6.6% in the 0 – 100 km/h speed range and 15.3% in the 0 – 50 km/h speed
range (in urban/suburban use). In long haul use, the maximum fuel reduction achieved was 6.3% in
http://www.ecomove-project.eu/
http://www.cosmo-project.eu/
8 http://ec.europa.eu/information_society/apps/projects/factsheet/index.cfm?project_ref=238930
6
7
13
the 0 – 100 km/h speed range and 11.6% in the 0 – 50 km/h speed range. Another interesting
result was that, since the fuel consumption is directly linked to GHG emissions, the energy efficient
intersection control in Dutch and French field trials reduces the CO2 and NOx emissions by 13%;
these high scores were mainly achieved due to the drastic reduction in the number of stops that
vehicles had to be made.
When talking about the impact of ITS measures on CO2 emissions it is noteworthy to mention the
EU OPTIMISM FP7 project9. Even though its main objective was the creation and development of
different sets of strategies and methodologies for optimising passenger transport systems based on
co-modality ICT solutions, the project nevertheless assessed the impact of these strategies on
emissions. To that end, future global trends and challenges were identified after which the
decarbonisation potential and co-benefits of best practice(s)/solutions were calculated by analysing
ICT and co-modality options. Underneath the hood, the methodology was based on the wellknown TRANS-TOOLS and TREMOVE models. One of the main conclusions was that according
to a reference scenario for 2030, transport emissions will keep increasing and road passenger
transport will be responsible for 65% of the total CO2 transport emissions and 54% of the total
NOx transport emissions. Given certain defined strategies, the results indicated that it is very
difficult to shift this trend. With the best policy scenario including strategies to support co-modality
and integration, the models predicted that only slight differences could be achieved in the transport
emissions for passenger cars. The modal shift from passenger cars to public road and rail transport
may still result in positive environmental impacts. Combination of OPTIMISM co-modality and
internalisation measures represented in a policy scenario may reduce the CO2, NOx and PM10
transport emissions in 2030 by 1.3%, 0.1%, and 0.4% respectively. Note that whereas the former
examples were typically on a smaller scale, i.e. more localised be it an intersection or a city,
OPTIMISM’s scenarios hold for the whole of Europe. The lower numbers are mainly attributed to
the fact that on the one hand only the passenger transport sector is considered, and that on the
other hand it proved to be quite the challenge to translate the concept of “co-modality on an EUscale” into the models. This was approached by using safe, conservative estimates for some of the
parameters, consequently leading to weaker impacts.
Finally let us remark that estimating the impact of ITS measures on traffic and by extension CO2
emissions is a topic of ongoing research. A testimony to that is the currently rolled-out EU Melodic
project (which wants to develop a methodology to assess CO2 emissions, taking ‘mobility as a
whole’ into account), which in light of the 2015 ITS World Congress in Bordeaux, France, is
running an extensive survey to inventory the state-of-the-art of current practices for the integration
of the CO2 aspects in daily transportation areas in terms of evaluation or supervision, and to
identify needs and converse with major actors.
Table 3 below summarises the info from the various projects.
9
OPTIMISM, Final publishable summary report, EC 2013.
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Table 3: impact of ITS measures on passenger car emissions
Estimated impact
Project
Measure
eCoMove
Inter-signal communication
Signal information to drivers
Spitsvrij
Road user charging
FREILOT
Combination of driving-related
measures
Energy-efficient intersection control
OPTIMISM
2.3
Encouraging co-modality
C2 (EE Traffic Control
on Intersections &
Motorways)
C3 (EE Traffic
Management at
Network Scale)
C4 (Travel Demand
Management)
-16% CO2
-5% CO2
-5% NOx
+2.6% PM10
-1.5-2% cars
-6.3% to -15.3% CO2
-13% CO2 and NOx
-1.3% CO2
-0.1% NOx
-0.4% PM10
Road infrastructure
This section discusses the effects of modifying road infrastructure to reduce fuel consumption. In
general, expanding existing infrastructure (e.g. extra lanes on congested roads) is not considered a
sustainable manner to reduce congestion and contribute to emission reductions, though the
construction of bypass roads could in some cases have a positive contribution. Other types of
measures controlled by infrastructure managers exist that can have a positive effect on fuel
efficiency of road vehicles. These relate to the power requirements of the vehicle to overcome the
forces on the wheel-road interface. Two of the main contributing factors are the road pavement
and the road slope.
As for road pavement, two main types exist in Europe: asphalt and concrete (composites of the two
are also applied). While each material has its specificities with associated advantages and
disadvantages, our focus will be on the main infrastructure related factor impacting fuel
consumption, which is the rolling resistance coefficient (RRC). Other factors also play a role in the
choice for one material or the other (like traffic density, temperature resistance, acoustics, cost), but
these should be considered in a full cost-benefit analysis. The RRC is a function of a number of
underlying parameters, including macrotexture (Mean Profile Depth, MPD), roughness
(International Roughness index, IRI) and road gradient as the most important ones.
 Of the three, road gradient is the one most difficult and most costly to manipulate.
Generally speaking, whenever the road gradient is above 2%, uphill and downhill variations
are not balanced. For higher gradients, the impact is negative (surplus energy needed for
climbing is greater than saved energy in descent), as is confirmed by Wyatt (2014)10, among
others. This highlights the importance of considering the instantaneous rather than the
average road gradient when assessing vehicle emissions, and can serve as a guideline to
infrastructure managers when the decision on road gradient comes up in the process of
(re)building roads. However, given that gradient usually depends on the given terrain
Wyatt, D. et al.: “The impact of road grade on carbon dioxide (CO 2) emission of a passenger vehicle in real-world
driving” (2014), http://www.sciencedirect.com/science/article/pii/S136192091400100X?np=y
10
15


conditions, and that building detours to avoid high gradients could also increase travel
distance such that the positive effects of a lower gradient are offset completely.
MPD and IRI determine the amount of friction generated between the tyre and the road
surface, as they can cause local deformations in the tyres that have to be absorbed. While
different materials do not necessarily differ much on these parameters, road deterioration
has a strong impact on both, which calls for good road maintenance programs across
Europe.
Pavement stiffness, which is arguably the main varying parameter between concrete and
asphalt, has a much smaller impact on vehicle fuel consumption.
As rolling resistance is also a function of vehicle weight, it should be noted that the road pavement
material will mostly affect emissions from heavy vehicles rather than passenger cars. As a general
rule, for every 10% reduction in rolling resistance, there is a 1-2% reduction in fuel consumption
for passenger cars (3% for HDV).11 Several contributions of the MIRIAM project12 suggest that a
10% improvement in RRC can be achieved, citing country examples like Denmark and Sweden.
This implies that a 1-2% decrease of fuel consumption is a realistic value for the 2030 horizon.
Other evidence exists to suggest that an implicit difference does exist between the chosen materials.
A Swedish study13 estimates the difference in fuel consumption of passenger cars between asphalt
and concrete pavements to be 1.1%. The study does mention differences in underlying parameters
as potential causes for the difference.
A third aspect that can be considered, though at a somewhat higher level of aggregation, is whether
specific infrastructure can be built to alleviate the pressure on urban roads and draw it to a new city
bypass to be built. The argumentation is that congested traffic on its way through the city centre
will cause a surplus of emissions that can be avoided by guiding them around the city in free
flowing traffic. Evidence in favour of this argumentation exists, e.g. from reports of the ECPRD
study14 citing savings in energy use of 7% for a local situation (in this case, the M25 in Ireland
Waterford to Glenmore), or from SINTEF15, which quotes savings between 11% and 38% for
different cases in Norway. There are however also studies supporting the opposite reasoning (see
for example Carlson et al.16, which estimates an increase in total energy use from a bypass in
southern Sweden of 60%). These studies attribute the increased energy mainly to the extra distance
covered and higher speeds driven by vehicles using the bypass. All in all, it appears that the effects
of building bypass roads are very dependent on the specific situation. Among factors to consider
are the current level of urban congestion; the ratio of local vs. through traffic; the actual driving
profiles (speed, acceleration) on both trajectories; the demand generation by the new bypass road.
G. Mellios, S. Hausberger, M. Keller, C. Samaras, L. Ntziachristos: “Parameterisation of fuel consumption and CO2
emissions of passenger cars and light commercial vehicles for modelling purposes”, 2011
(http://publications.jrc.ec.europa.eu/repository/bitstream/111111111/22474/1/co2_report_jrc_format_final2.pdf)
12 http://miriam-co2.net/
13 Hultqvist, B., VTI: “Measurement of fuel consumption on asphalt and concrete pavements north of Uppsala.
Measurements with light and heavy goods vehicle.”, 2013, http://www.vti.se/en/publications/pdf/measurement-of-fuelconsumption-on-asphalt-and-concrete-pavements-north-of-uppsala--measurements-with-light-and-heavy-goodsvehicle.pdf
14 ECPRD, “Energy conservation in road pavement design, maintenance and utilisation”, 2010,
http://ec.europa.eu/energy/intelligent/projects/en/printpdf/projects/ecrpd
15 SINTEF: “Environmental benefits of better roads”, 2007,
http://www.irfnet.eu/images/Environmental_consequences_of_better_roads_English_Summary.pdf
16 Carlson, A., Mellin, A., VTI: “Life cycle assessment of a road investment – estimating the effect on energy use when
building a bypass road”, 2013, http://vti.diva-portal.org/smash/get/diva2:780431/FULLTEXT01.pdf
11
16
Particularly in heavily congested regions with a lot of latent demand, the latter effect is very
important to consider (yet often insufficiently accounted for in practice)17. The SINTEF study for
example does not cover this effect. In any case, it is practically impossible to make general
statements about the effects of bypass roads on CO2 emission levels, but in the right circumstances,
there certainly is potential.
It can be concluded that infrastructure managers can have a measurable impact on CO2 emissions
from transport. The factor most subject to policy choice is that of road surface, where a good
maintenance program can decrease CO2 emissions from passenger cars by 1-2%. Controlling road
gradients is a more complex process for which general statements cannot be made. Building bypass
roads as a means to reduce CO2 emissions should be considered on a case-to-case basis. The risk of
so called “induced demand” should be considered in any such decisions.
Table 4: Summary table longlist: infrastructure
2.4
What?
Building and maintaining roads that minimise fuel consumption of vehicles
How?
By maintaining an optimal road surface profile (texture and roughness). Material is not necessarily
the deciding factor. Limiting road gradients is useful, but can be expensive. The effect of bypass
roads is too dependent on local circumstances to allow a general statement on reduction potential.
Effect?
1-2%
Energy/Carbon content of fuels – Renewable fuels
The governing directives are coded 1998/70/EC, better known as the Fuel Quality Directive
(FQD), and 2009/28/EC, the Renewable Energy Directive (RED). These directives were part of
the package that was put in place to cement the EU’s 20-20-20 targets:
 A 20% reduction in EU greenhouse gas emissions from 1990 levels;
 Raising the share of EU energy consumption produced from renewable resources to 20%;
 A 20% improvement in the EU's energy efficiency;
to be realised by the year 2020.
The impact on the transport sector of these directives will be felt through the evolution of the fuel
mix. There is a wide variety in transport fuels, with fossil fuels that can be either liquid or gaseous,
and their renewable equivalents, that can be produced through different processes each with
different emissions associated with that process (well-to-tank/WTT emissions).
The RED sets a target of a 10% share of renewable energy sources in total transport fuel
consumption. The FQD (in its latest amendment through Directive 2009/30/EC) also adds a
target for life cycle GHG emission reduction per unit of energy of 10%, 6% of which should come
directly from WTW emissions (FQD article 7a)18. For transport biofuels specifically, GHG
emission savings should be at least 50% for them to contribute to the 10% goal from 2018 onwards
(60% for biofuels produced in installations that started operation in 2018 or later), along with other
See Litman, T., VTPI: “Generated Traffic and Induced Travel. Implications for Transport Planning”, 2012,
http://www.vtpi.org/gentraf.pdf
18 Of the other 4%, 2% should come from technologies like carbon capture or from reductions for non-road mobile
machinery, and 2% can come from credits purchased in the Kyoto protocol’s Clean Development Mechanism.
17
17
sustainability criteria mainly linked to land use. Reports from the JEC19 already suggest that this
2020 target will not be met.
In the directives, the EC included “default” values that can serve as a measure for the WTT
emissions of different fuel types, that can be used when more accurate calculations cannot be made
(among other conditions, these values are only applicable for imported fuels). It should be noted
that these default value explicitly exclude any effects of indirect land use changes (ILUC) – arguably
the most (politically and environmentally) sensitive part of any assessment of biofuel’s CO2 impact.
These directives have set targets for 2020, but no binding legislation is foreseen for the period
beyond that, which could become problematic for the stability of the sector – although article 23
(9) of the RED states that the EC should present a Renewable Energy Roadmap for the post-2020
period by 2018.
The 6% reduction in life cycle GHG emissions by 2020 is the reference for further action in the
field in the period beyond that. In the detailed assessment of phase two of this project, we base our
review on studies using a scenario based approach for the period up to 2030 for biofuel legislation,
including assumptions on projected fuel mix. Studies to be used during the stage 2 review include:
 “A harmonised Auto-Fuel biofuel roadmap for the EU to 2030”, E4Tech, 2013
 “The Role of Biofuels beyond 2020”, Element Energy, 2013
 “Technology Roadmap: Biofuels for Transport”, IEA, 2011
 “The contribution of biofuels in transport sustainability post-2020”, Emisia, 2014
Table 5: Summary table longlist: biofuels
2.5
What?
Effects of (successors of) the RED and FQD
How?
Substituting fossil fuels with fuel produced from renewable and sustainable sources
Effect?
FQD target is 6% reduction for 2020 (for all alternative fuels covered by the directive), but this
may not be met. Long term targets are not known yet.
Emission trading system
The inclusion of road transport in the EU ETS is a contentious subject among stakeholders and
policy makers. There are many arguments to consider in favour or against this policy measure.
Some of the most important ones are:
 At which point should the ETS be imposed? Three options are on the table: upstream (fuel
production), midstream (vehicle manufacturers) or downstream (fuel buyers).
 Should the ETS be open (i.e. included in the current ETS) or closed (a separate ETS for
road transport)?
 Is coverage of CO2 emissions the only factor that should be taken into account? Fuel
import dependency, job creation and reducing consumer costs are often cited as other
aspects to be taken into account by policy makers
JEC: “EU renewable energy targets in 2020: Revised analysis of scenarios for transport fuels”, 2014,
http://iet.jrc.ec.europa.eu/about-jec/sites/iet.jrc.ec.europa.eu.aboutjec/files/documents/JEC_Biofuels_2013_report_FINAL.PDF
19
18


How will permits be distributed? Free allocation can be done via e.g. benchmarking or
grandfathering, while auctioning permits can provide a so called ‘double dividend’ (lower
emissions + budget available for further measures). Combinations are possible as well.
The EU ETS in its current format is not considered to be a well-functioning system in the
sense that it does not sufficiently promote CO2 reduction efforts. This is due to an
oversupply of permits and insufficient protection from carbon leakage, among other issues.
These aspects need to be dealt with if road transport is to become part of the system.
Given the ongoing debate on the matter, this measure will be part of the detailed assessment of the
second part of this study. Some of the materials that will be used as the basis for that are:
(1) “The Impact of Including the Road Transport Sector in the EU ETS”, Cambridge
Econometrics (2014)
(2) “An analysis of the obstacles to inclusion of road transport emissions in the European
Union’s Emissions Trading Scheme”, IEEP (2009)
(3) “CO2 Emissions, Energy, and Economic Impacts of CO2 Mandates for New Cars in
Europe”, Paltsev et al. (2015)
(4) “Regulation of CO2 emissions from passenger cars within the European Union after
2020”, TU Braunschweig ea. (2014)
Study (4) also covers to a large extent the possible interaction of an ETS with variations of the
current regulation, i.e. an emission target per vehicle. It will not be possible to consider these
interactions in the present study, as they would present a conflict of interest with another TML
study for the European Commission dealing explicitly with these other types of options. Some of
the other studies also cover this topic, and the same reasoning applies.
Table 6: Summary table longlist: ETS
2.6
What?
Including road transport in the EU ETS
How?
Different options exist for the trading of emission allowances from road transport
(upstream/midstream/downstream, open/closed,…).
Effect?
Depends on the cap level, but highly likely that in the first phase emission reductions will be
achieved in other sectors than transport.
Autonomous fleet renewal
The concept of autonomous fleet renewal is based on the currently agreed emission standards for
passenger cars, namely the 2021 target for 95g CO2/vkm as the average of all new passenger cars.
This target is set to reduce CO2 emissions by a significant margin, yet in itself it does not reflect
how many tonnes of CO2 emissions are to be saved each year. It is (or should be) based on
assumptions on vehicle fleet evolution (that are themselves based on projected evolutions in vehicle
purchase price, fuel price, and consumer behaviour) in order to achieve the CO2 reduction targets.
However, given that the emission standard only applies to new vehicles, it will have effects on the
average fuel consumption of the fleet for years to follow, as the average vehicle replacement rate is
once every 10-15 years (depending on size, fuel type,…). Hence, effects of the 95 g/km limit in
2021 will only have spread throughout most of the European vehicle fleet in the first half of the
2030’s.
19
We propose to address this using a model based approach, using MOVEET (MObility, Vehicle
fleet, Energy use and Emissions forecast Tool )20. This model projects vehicle fleet evolution based
on transport demand, which is itself generated by the model based on evolutions of GDP,
population, and other factors, and is calibrated to a recent EU baseline. It also estimates CO2
emissions at a disaggregated level. The baseline fleet was calibrated to replicate the results of the
TRACCS study21 for 2005-2010.
The projection up to 2030 for the passenger car vehicle fleet is presented in Table 7. Between 2010
and 2030, the total fleet is expected to grow by 24%.
Table 7: MOVEET passenger car fleet evolution up to 2030, baseline
Stock
Country
Year
Austria
2005
4,156,736
2010
4,656,932
2015
4,851,767
2020
4,961,621
2025
5,100,853
2030
5,223,101
Belgium
4,876,684
5,338,648
5,456,353
5,619,406
5,891,391
6,181,526
Bulgaria
2,538,091
2,599,377
3,291,443
3,861,197
4,108,316
4,000,314
Croatia
1,394,612
1,492,191
1,534,874
1,755,504
2,027,530
2,310,910
Cyprus
416,758
534,836
322,303
397,930
668,541
814,161
2,012,216
2,246,675
2,311,270
2,431,587
2,565,342
2,685,184
Denmark
354,697
422,131
491,774
580,701
662,601
713,672
20,250,377
22,143,872
22,677,810
24,454,158
26,558,402
28,554,391
Finland
2,414,001
2,856,002
2,483,719
2,631,247
2,779,122
2,898,109
France
30,142,016
31,389,057
33,090,372
34,176,808
35,499,907
36,763,771
UK
27,498,864
28,333,370
30,278,241
32,214,873
34,096,750
35,775,228
Greece
4,303,129
5,216,880
4,624,518
5,324,662
5,984,089
6,500,685
Hungary
2,880,954
2,983,983
3,393,849
3,939,222
4,403,317
4,595,386
Ireland
1,684,375
1,899,898
1,919,712
2,020,217
2,155,863
2,296,658
34,665,860
37,418,595
38,263,630
40,012,485
42,018,173
43,903,749
423,800
506,881
551,419
635,307
720,680
797,200
1,455,276
1,725,525
1,966,989
2,226,467
2,492,183
2,706,945
Luxemburg
307,000
337,000
365,002
381,614
401,600
418,523
Malta
212,720
240,960
241,603
257,514
265,230
259,053
7,087,084
7,679,922
8,005,007
8,439,619
8,898,892
9,301,564
11,720,001
16,866,021
17,302,425
19,135,665
19,740,157
19,684,787
4,192,836
4,684,006
4,914,263
5,218,888
5,460,256
5,654,359
Estonia
Spain
Italy
Latvia
Lithuania
Netherlands
Poland
Portugal
3,951,999
4,491,004
5,079,261
5,809,309
6,452,968
6,770,967
Germany
45,449,755
41,660,290
44,908,709
47,375,798
49,870,109
51,875,887
Romania
3,284,355
5,264,040
5,384,429
6,609,551
7,485,928
8,029,223
Slovakia
1,303,699
1,669,102
1,663,736
1,887,273
2,116,082
2,297,896
Slovenia
936,258
1,081,990
1,084,308
1,196,916
1,286,299
1,311,861
Sweden
4,052,754
4,131,029
4,359,734
4,583,804
4,808,594
4,971,580
223,966,908
239,870,218
250,818,519
268,139,341
284,519,176
297,296,692
Czech Republic
Grand Total
20http://www.tmleuven.be/methode/moveet/home.htm
21
http://traccs.emisia.com/
20
The associated CO2 emissions for the passenger car fleet in baseline are shown in Table 8. A
baseline reduction of nearly 220 Mt is projected by 2030, which is equivalent to 37% of 2005
baseline emissions.
Table 8: Passenger car CO2 emissions in baseline, in Mt
CO2 emissions: total
Country
EU28
Year
2005
584.8
2010
513.9
2015
445.5
2020
404.5
2025
374.9
2030
366.2
This is of course caused by ever more vehicles meeting the 2021 target emission value of 95g/km.
In fact, the baseline projects fleet average CO2 emissions per km to decrease from 190g/km in 2010
to 107g/km in 2030 – which includes a real world correction factor of just over 10%.
Table 9: Passenger car specific CO2 emissions per vehicle in baseline, total fleet average, in gCO2/vkm
CO2 emissions per vkm
Country
EU28
Year
2005
230
2010
190
2015
154
2020
130
2025
114
2030
107
To gain additional insight, the review of part 2 will include simulations of scenarios for real world
new vehicle emission levels for the 2021 horizon, namely 95g/km, 105g/km and 115g/km. The
baseline scenario already matches de facto with the 105g/km scenario, leaving 2 to be simulated.
Table 10: Summary table longlist: Autonomous fleet renewal
2.7
What?
Autonomous fleet renewal
How?
As the fleet renews itself gradually, older vehicles are replaced by newer ones with lower fuel
consumption. After 10-15 years, 80-90% of the fleet is renewed. The average and total emission
levels of the fleet will decrease each year, even without stricter CO 2 targets.
Effect?
Likely sufficient to meet a proportional share of the assumed 2030 reduction target of the road
transport sector, in the range of 200Mt by 2030 – equivalent to 37% of the 2005 emission level.
CO2 based vehicle taxation
Vehicle taxation is a very suitable measure to promote or discourage the purchase of certain types
of vehicles as a form of demand management. Most European countries currently include a car’s
CO2 emissions as part of their environmental regulation, albeit with mixed setups – and results.
ACEA’s own tax guide (2014) presents an overview of current CO2 based vehicle registration and
ownership taxes.
21
Table 11: CO2 based vehicle taxation in the EU28
Country
Austria
Belgium
Bulgaria
Croatia
Cyprus
CO2 based vehicle taxation
A fuel consumption tax (Normverbrauchsabgabe or NoVA) is levied upon the first registration of a
passenger car. It is calculated as follows: (CO2 emissions in g/km minus 90 divided by 5) minus
NoVA deduction/plus NoVA malus. The deduction amounts to €350 for diesel vehicles, €450 for
petrol vehicles and €600 for hybrid and other alternative fuel vehicles. Electric vehicles are exempt.
The malus amounts to €20 for each g/km emitted in excess of 250 g/km.
1. The company car tax is based on CO2 emissions.
2. The deductibility under corporate tax of expenses related to the use company cars (50 to 120%)
is linked to CO2 emissions.
3. The Walloon Region operates a malus system whereby cars emitting more than 145 g/km pay a
penalty (maximum €2,500 for cars emitting more than 255 g/km).
4. The registration tax in Flanders is based on CO2 emissions as well as exhaust emissions
standards, fuel and age.
None
The registration tax is based on CO2 emissions, price and the type of fuel used. The CO2
component varies from 1.5% (up to 100 g/km) to 31% (above 300 g/km) for diesel cars and from
1% (up to 100 g/km) to 29% (above 300 g/km) for cars using petrol, CNG or LPG as well as
diesel cars meeting Euro 6 standards.
1. The registration tax is based on CO2 emissions.
2. The annual circulation tax is based on CO2 emissions.
Czech Republic
None
Denmark
1. The annual circulation tax is based on fuel consumption.
- Petrol cars: rates vary from 580 Danish Kroner (DKK) for cars driving at least 20 km per litre of
fuel to DKK 20,160 for cars driving less than 4.5 km per litre of fuel.
- Diesel cars: rates vary from DKK 240 for cars driving at least 32.1 km per litre of fuel to DKK
30,360 for cars driving less than 5.1 km per litre of fuel.
2. Registration tax (based on price): An allowance of DKK 4,000 is granted for cars for every
kilometre in excess of 16 km (petrol) respectively 17 km (diesel) they can run on one litre of fuel. A
supplement of DKK 1,000 is payable for cars for every kilometre less than 16 km (petrol)
respectively 18 km (diesel) they can run on one litre of fuel.
Estonia
None
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Latvia
1. The registration tax is based on CO2 emissions. Rates vary from 5 to 50%.
2. The annual circulation tax is based on CO2 emissions for cars registered since 1 January 2001
(total mass up to 2,500 kg) or 1 January 2002 (total mass above 2,500 kg) respectively and for vans
registered since 1 January 2008.
1. Under a bonus‐malus system, a premium is granted for the purchase of a new car when its CO2
emissions are 90 g/km or less. The maximum premium is €6,300 (20 g/km or less). An additional
bonus of €200 is granted when a car of at least 15 years old is scrapped and the new car purchased
emits maximum 90 g/km. A malus is payable for the purchase of a car when its CO2 emissions
exceed 130 g/km. The maximum tax amounts to €8,000 (above 250 g/km).
2. Cars emitting more than 190 g/km pay a yearly tax of €160. 3. The company car tax is based on
CO2 emissions. Tax rates vary from €2 for each gram emitted between 50 and 100 g/km to €27 for
each gram emitted above 250g/km.
The annual circulation tax for cars registered as from 1 July 2009 is based on CO2 emissions. It
consists of a base tax and a CO2 tax. The base tax is €2 per 100 cc (petrol) and €9.50 per 100 cc
(diesel) respectively. The CO2 tax is linear at €2 per g/km emitted above 95g/km. Cars with CO2
emissions below 95 g/km are exempt from the CO2 tax component.
The annual circulation tax for cars registered since 1 January 2011 is based on CO2 emissions. Rates
vary from €0.90 per gram of CO2 emitted (101 – 120 g/km) to €3.40 per gram (above 250 g/km).
Cars with emissions up to 100g/Km are exempt.
None
1. The registration tax is based on CO2 emissions. Rates vary from 14% for cars with CO2
emissions of up to 80 g/km to 36% for cars with CO2 emissions above 225 g/km.
2. The annual circulation tax for cars registered since 1 July 2008 is based on CO2 emissions. Rates
vary from €120 (0 g/km) to €2,350 (above 255 g/km).
Grants are available for the purchase of alternative fuel vehicles (electric, hybrid, natural gas, biogas,
LPG, biofuels, hydrogen) emitting maximum 120 g/km. Most grants are available only for
companies and conditioned by the scrapping of a vehicle that is at least ten years old. The only
exception is the purchase of vehicles with emissions of maximum 95 g/km, for which private
individuals can also obtain a grant without having to scrap another vehicle. The grants amount to
maximum €5,000 (up to 50 g/km), €4,000 (51 ‐ 95 g/km) and €2,000 (96 – 120 g/km) respectively.
The registration tax is based on CO2 emissions. Rates vary from €0.2 per g/km for cars emitting
22
120 g/km or less to €3.5 per g/km for cars emitting more than 350 g/km.
Lithuania
Luxemburg
Malta
Netherlands
Poland
Portugal
Romania
Slovak Republic
Slovenia
Spain
Sweden
United Kingdom
None
1. The annual circulation tax for cars registered since 1 January 2001 is based on CO2 emissions.
Tax rates are calculated by multiplying the CO2 emissions in g/km with 0.9 for diesel cars and 0.6
for cars using other fuels respectively and with an exponential factor (0.5 below 90 g/km and
increased by 0.1 for each additional 10 g of CO2 /km).
2. Purchasers of new electric and plug‐in hybrid vehicles emitting maximum 60 g/km receive an
incentive of €5,000.
1. The registration tax is calculated through a formula that takes into account CO2 emissions, the
registration value and the length of the vehicle.
2. The annual circulation tax is based on CO2 emissions and the age of the vehicle. During the first
five years, the tax only depends on CO2 emissions and varies from €100 for a car emitting up to
100 g/km to €180 for a car emitting between 150 and 180 g/km.
1. The registration tax is based on price and CO2 emissions. Cars emitting maximum 85 g/km
(diesel) and 88 g/km (other fuels) respectively are exempt from the registration tax.
2. Cars emitting maximum 50 g/km are exempt from the annual circulation tax.
None
1. The registration tax is based on engine capacity and CO2 emissions. The CO2 component is
calculated as follows: - Petrol cars emitting up to 115 g pay [(€4.03 x g/km) – 378.98]. Diesel cars
emitting up to 95 g pay [(€19.39 x g/km) – 1,540.30] - The highest rates are for petrol cars emitting
more than 195g (€143.39 x g/km) – 23,321.94] and for diesel cars emitting more than 160g
[(€187.97 x g/km) – 23,434.67].
2. The annual circulation tax for cars registered since 1 July 2007 is based on cylinder capacity, CO2
emissions and age.
The special pollution tax (registration tax) is based on CO2 emissions, cylinder capacity, exhaust
emission standards and age.
None
The registration tax is based on price and CO2 emissions. Rates vary from 0.5% (petrol) and 1 %
(diesel) respectively for cars emitting up to 110 g/km to 28% (petrol) and 31% (diesel) respectively
for cars emitting more than 250 g/km.
The registration tax is based on CO2 emissions. Rates vary from 4.75% (121 – 159 g/km) to
14.75% (200 g/km and more).
1. The annual circulation tax for cars meeting at least Euro 4 exhaust emission standards is based
on CO2 emissions. The tax consists of a basic rate (360 Swedish Kroner) plus SEK 20 for each
gram of CO2 emitted above 117 g/km. This sum is multiplied by 2.33 for diesel cars. Diesel cars
registered for the first time in 2008 or later pay an additional SEK 250 and those registered earlier
an additional SEK 500. For alternative fuel vehicles, the tax is SEK 10 for every gram emitted
above 117 g/km.
2. A five‐year exemption from annual circulation tax applies for “green” cars (definition partly
based on CO2 emissions).
1. The annual circulation tax for cars registered after March 2001 is based on CO2 emissions. Rates
range from £0 (up to 100 g/km) to £490 (for cars over 255 g/km) (alternative fuels receive a £10
discount where a rate is paid). A first year rate of registration applies since 1 April 2010. Rates vary
from £ 0 (up to 130 g/km) to £1,055 (more than 255 g/km).
2. The individual’s company car tax liability is based on CO2 emissions.
A 2014 T&E study22 attempted to find correlations between the extent of CO2 based taxation and
the emissions of newly sold passenger cars in a country. They ranked the tax systems based on the
included emission reduction incentives and compared those to both the average CO2 emission level
of new cars (2013) and the decrease from the year before. Their concluding table was:
Transport & Environment: “CO2 emissions from new cars in Europe: Country ranking”, (2014),
http://www.transportenvironment.org/sites/te/files/publications/2014%20TE%20cars%20CO2%20MS%20report_FI
NAL_compressed%20cover_0.pdf
22
23
The correlation appears to be real: the highest rated systems consistently deliver the lowest average
emissions (apart from Greece, which can be considered an outlier given the current economic
crisis). The study also concludes that taxes payable upon vehicle purchase (registration tax) give a
much stronger price signal than periodic taxes (ownership).
In terms of steering customers toward low CO2 emission vehicles, working via the vehicle tax
system – often under the flag of a so called “feebate system” - can be considered an effective
measure. However, it remains to be seen how efficient this system is. As a very rough example, we
can compare the purchase in the Netherlands of two identical cars, except for their CO2 emissions:
one has 110g/km, the other 160g. For customers to “accept” buying the 110g/km car instead of
the 160g/km, society “loses” 5,600€ in direct tax revenue. In terms of lifetime CO2 emissions, the
110g car would have around 15 tonnes less than the 160g car23, which implies that for a decrease of
external cost of 75€ (15 tonnes multiplied by the currently permit price of around 5€), users get a
5,600€ fiscal benefit.
Apart from taxation at the moment of purchase or each year the vehicle remains in use, several EU
countries applied so called “scrappage schemes” in the past 5-10 years, in order to promote the
purchase of new vehicles by providing a scrappage premium to put old vehicles out of commission
and replacing them with new ones. These schemes were highly popular, in many cases burning
through the originally budgeted amount much faster than expected, and effectively stimulating the
economy. However, the effect on long term fleet CO2 emissions is limited – the increase in new
vehicle sales is usually compensated by a decrease a few years later, at the moment the old vehicles
would normally have been replaced - and the cost efficiency is lower still than feebate schemes.
Assuming 225,000 km lifetime mileage and a 31% difference between TA and real world emissions, not accounting for
other cost aspects. This is a simplified calculation of CO2 abatement cost not accounting for marginal cost of public
funds.
23
24
And IHS Global Insight study24 states an average CO2 abatement cost of €1,100/tonne – though it
also mentions that the scrappage schemes’ objective was not only to reduce carbon emissions, and
thus that cost is an overestimate.
Measuring the effects of a CO2 based tax requires a thorough statistical analysis. In a 2013 study25,
Cambridge Econometrics estimated the contribution of CO2 based taxes to the reduction of
average emissions of new vehicles at 6.3g/km for the Netherlands, and 3.6g/km for the UK, over
the period 2005-2012. In both cases, this represented about 1/8 of the total CO2 reduction and 24% of the average CO2 emission level, which was around 168g/km at the start of the research
period in 2005. In a similar but more short-run oriented study, Klier and Linn estimated the effects
of CO2 taxation between 2007 and 2009 in France (7.95g/km reduction), Germany (1.67g/km) and
Sweden (0.57g/km). In each case, the CO2 tax was found to be the biggest contributor to the
observed reduction in CO2 emissions of new vehicles.
Given the interaction of vehicle taxation with many other aspects of the tax system, the setup of the
present study does not allow for a further investigation of the contribution of vehicle taxes to CO2
reduction post-2020. Nonetheless, it should still be considered a supporting measure to manage
demand.
Table 12: Summary table longlist: Car taxation
2.8
What?
CO2 based vehicle taxation
How?
By basing tax levels (registration, ownership) on CO2 emission levels, governments can give price
signal to guide buyers towards more fuel efficient vehicles. The opportunity cost of these types of
measures can however be significant.
Effect?
Depends on the level of the tax, could be up to 4%.
Vehicle labelling
Vehicle labelling is a means to standardise the information regarding vehicles’ properties as it is
made available to the customer at the moment of purchase. Ideally, this improved knowledge will
help the consumer make a better and more sustainable choice. The information should allow
prospective buyers to assess the additional costs of operating the vehicle, the largest part of which
is formed by fuel costs. As mentioned before, price signals are strongest at the moment of purchase
– costs that arise at a later date, like ownership taxes and fuel costs, are generally discounted by
consumers (a phenomenon known as consumer myopia). If the consumer is explicitly aware of
these costs at the moment of purchase, his decision could be affected. As such, a label is another
method to manage demand for vehicles. It is regulated by directive 1999/94/EC, last amended in
2008. There is an ongoing discussion about the need to update the directive to include a more
standardised approach to the format and contents of the label.
IHS Global Insight: “Assessment of the Effectiveness of Scrapping Schemes for Vehicles”, 2010,
http://ec.europa.eu/enterprise/sectors/automotive/files/projects/report_scrapping_schemes_en.pdf
25 Cambridge Econometrics: “The effectiveness of CO2-based ‘feebate’ systems in the European passenger vehicle
market context”, 2013,
http://www.theicct.org/sites/default/files/publications/CambridgeEconometrics_ICCT_feebate_rpt_Nov2013.pdf
24
25
Assessing the impact of vehicle labelling on average CO2 emissions of new vehicles is difficult due
to the amount of interactions with other policy measures. In an ex-ante assessment performed in
1999 by the Austrian Energy Agency26, it was expected that mandatory vehicle labelling would push
emissions down by 4-5% over a 10 year period, i.e. by 0.5% per year (it is likely that the effects top
out at some point though). No ex-post assessments of the effect of vehicle labelling have been
found. This “soft” measure should best be considered a complement to other demand management
measures.
Table 13: Summary table longlist: labelling
2.9
What?
Vehicle labels, showing emission factors
How?
By better informing buyers of fuel consumption, they can make a more correct assessment of the
lifetime cost of the vehicle. This should steer demand towards more fuel efficient vehicles.
Effect?
No ex-post research that has isolated the effect of labelling was found.
Tyres
As the only contact points between a vehicle and the road, tyres can contribute a great deal – 20 to
30% according to the EC27 - to a vehicle’s fuel efficiency. The applicable EU legislation is
Regulation (EC) No 1222/2009, which mandates the labelling of tyres according to their rolling
resistance coefficient (among other aspects) – which is directly correlated to the energy efficiency of
the tyre. The difference between the worst and best tyre is equivalent to a decrease of fuel
consumption by 6-9% (depending on average speed). It entered into force in 2012, which means
that the full effects of the regulations are still building up throughout the fleet.
However, by 2020, all vehicle owners will have had the chance to upgrade to the most efficient
tyres, and the projected efficiency gains should have been realised by then. Available literature does
not seem to contain much information about the long term fuel efficiency improvement potential
of further reducing rolling resistance. In an earlier TML study for ACEA on the integrated
approach to reducing HDV emissions, it was concluded that 75-80% of total reduction potential
for low rolling resistance tyres would be realised by 2020, which can serve as a reference for the
case of cars as well. In any case, tyre rolling resistance improvement can be an important
contributor to achieving real world fuel consumption reductions, also in the post-2020 period.
Decreasing rolling resistance by changing the material composition of the tyre is one side of the
issue. Another important aspect is optimal tyre inflation. A tyre that is underinflated by 25%,
increases rolling resistance by 10% and fuel consumption by 1-2%. Tyre Pressure Monitoring
Systems (TPMS) have automated the process of checking tyre pressure, which shifts responsibility
for proper inflation fully onto drivers. They have been made mandatory in all passenger cars since
November 2014, which implies that by 2030, close to 100% of the European car fleet should be
equipped with TPMS. As such, there is no immediate need for new policies, as long as the facilities
EVA: “Energy Efficiency of Passenger Cars: Labelling and its Impacts on Fuel Efficiency and CO2-Reduction”, 1999,
http://www.eceee.org/library/conference_proceedings/eceee_Summer_Studies/1999/Panel_5/p5_5/paper
27 “A Consumer’s Guide to Energy Efficient Tyres”,
https://ec.europa.eu/energy/sites/ener/files/documents/FIN%20User%20guide%20-%20tyres.pdf
26
26
to inflate tyres to the proper pressure level are common, freely accessible and easy to operate in the
entire EU.
Table 14: Summary table longlist: tyres
2.10
What?
Tyres
How?
Tyres with low rolling resistance can be applied at any tyre change. Tyre Pressure Monitoring
Systems indicate when inflation is at a suboptimal level.
Effect?
Through several directives, the EC has internalised much of the potential improvement for tyres
in the near future. Little is known about further potential improvements.
Conclusion
EU policy with regard to CO2 reduction in the transport sector has up to now mainly been based
on vehicle fuel standards, mandating vehicle manufacturers to comply with ever more stringent
emission limits. Ex-ante impact assessments suggest that the current targets up to 2021 come with
negative CO2 abatement costs, making them cost-effective by definition. However, as technology
costs increase more than linearly with lower target emission levels, this does not necessarily hold for
targets beyond the current ones – this is subject of ongoing EC studies.
We have listed 9 types of potential measures that can help reduce CO2 emissions of passenger cars
post-2020 that are not directly based on vehicle technology improvement. Of these 9, 4 will be part
of a more thorough review in the next part of this study, namely:
 Eco-driving
 Fuel Quality/Renewable energy
 ETS
 Autonomous fleet renewal
For the others, it could be that expected impact is straightforward and/or only of secondary
concern with regard to CO2 reduction, not requiring additional review in the present study (tyres,
road infrastructure), already part of a specific ACEA study (ITS) or beyond the scope of the
present study (CO2 based taxation, vehicle labelling).
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3
Additional reviews of selected measures
In this section, the measures selected from the longlist will be studied in more detail, to gain
additional insights in the driving forces behind each of them.
3.1
Ecodriving
The practice of ecodriving can have two initiators: the driver or the vehicle – or a combination of
both.
3.1.1
Driver training
In the first case, specific driver training is the underlying instrument that leads to lower fuel
consumption. We say “specific”, because driver training can serve several purposes.
 Basic driving training aims to teach young drivers with very little or no driving experience
the basic principles of driving on the public road network, and how to do so in a safe and
fluent manner, in accordance with road traffic regulation. While some part of the initial
driver training may cover ecodriving, this is likely to be more theoretical than practical, as
the evaluation test (to obtain a driver’s licence) does not directly include an assessment of
fuel efficient driving; though fluent driving implies at least to some extent that e.g.
excessive braking and acceleration behaviour is not tolerated.
 Mandatory driver training can be part of the rehabilitation program imposed by judges on
traffic offenders. While the focus could depend on the nature of the offence, it is likely to
be more on road safety than on fuel efficiency.
 Professional drivers are required to take periodic training sessions (Directive 2003/59/EC,
for HDV), both of driving theory (e.g. legislation) and driving practice, focusing on
different areas of their driving style. However, in practice this regulation only covers
drivers of HDV.
 Voluntary driver training sessions are aimed at different aspects of driving, including safety
and/or fuel efficiency. This form of driver training is the primary form of ecodriving
education covered by this paragraph.
 Furthermore, we can also distinguish between the training method: on road/in class/elearning.
In the previous chapter, the basic principles of eco-driving were presented. The rest of this section
will provide more supporting data for the concept and give additional details on fuel saving
potential under different circumstances.
Ecodriving training should cover both the pre-drive and in-drive phase.
 In the pre-drive phase, drivers should mark off a “checklist”:
o Are the tyres properly inflated and in good condition?
o Is the vehicle not carrying unneeded excess weight?
o Are there any objects attached to the outside of the vehicle that are not required
for the trip (e.g. ski or bike racks, roof boxes)?
o How are traffic conditions along the trajectory of the trip? In case of congestion,
can the trip be postponed?
 While driving, the guiding principles are:
29
o
o
Use a sensible acceleration strategy; shifting gears before the engine reaches higher
rpm (i.e. around 2000-2500 rpm)28
Speed should be maintained as much as possible, and ideally be around the
optimal level (70-80km/h), insofar as this does not create safety issues (like on
motorways).
Source: Ecodriven project
o
o
o
o
28
Using the vehicle’s momentum as much as possible by coasting when appropriate,
e.g. when driving down a hill.
Decelerating while remaining in gear (instead of switching to neutral).
Switching the engine off when the idling period lasts more than a few seconds – in
case the car is not equipped with a start/stop system.
Avoiding the use of systems like air conditioning when they are not needed.
Note that for diesel engines, driving at too low rpm will generate higher NOx volumes.
30
As indicated earlier, the average potential of ecodriving training is usually estimated around 10-15%,
with a drop-off as time goes on, to around 5%.
A study by the Sapienza University of Rome29 has made a theoretic assessment of ecodriving
potential based on real world driving patterns that are computer-optimised based on ecodriving
principles afterwards. It indicates that effectiveness of driver training is greatest for driving on
urban roads (about 30% maximum potential at very low speeds, with averages around 25% for
normal urban speeds up to 40km/h), as frequent start/stops and gear shifting are required here. As
speed exceeds 80-90km/h (motorway driving), the influence of driving style on fuel consumption is
much smaller (between 5% and 10%). This applies to gasoline vehicles. The differences in potential
savings between diesel and gasoline are generally small, with the maximum potential at low speeds
topping out at about 22%, but still remaining significant at higher speeds (10+%).
Figure 2: Obtainable CO2 average reduction for gasoline vehicles adopting the eco-driving driving style.
(Source: Alessandrini report)
Alessandrini, A. et al. : « Driving style influence on car CO2 emissions », 2012,
http://www.epa.gov/ttnchie1/conference/ei20/session8/acattivera.pdf
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31
Figure 3: Obtainable CO2 average reduction for diesel vehicles adopting the eco-driving driving style.
(source: Alessandrini report)
These results should be considered the maximum obtainable savings. As such, they are in line with
the general average projections. Other literature on the subject includes:
 Van Mierlo et al. (2004)30, which quotes savings between 5% and 25% (based on real
driving under controlled circumstances);
 Fonseca et al. (2010)31: savings of 14% in urban driving in Madrid;
 TNO (2006)32: savings of 7% for petrol cars, and of 8-10% for diesel cars in real world
urban and rural driving on Dutch roads.
 Fiat (2010)33: average real world savings of 6%, with the top 10% of drivers achieving
16%.
 Australian automobile drivers’ club RACQ (2012)34 states average real world savings from
ecodriving are 4.6%, with the top 15.9% reaching 15% or more.
Van Mierlo, J. et al.: " Driving style and traffic measures—influence on vehicle emissions and fuel consumption”,
(2004), http://pid.sagepub.com/content/218/1/43.short
31 Fonseca, N. et al.: “Influence of Driving Style on Fuel Consumption and Emissions in Diesel Powered Passenger Car”
(2010), http://oa.upm.es/13473/1/INVE_MEM_2010_78666.pdf
32 Vermeulen, R.J.: “The effects of a range of measures to reduce the tail pipe emissions and/or the fuel consumption of
modern passenger cars on petrol and diesel.” (2006),
http://www.cieca.eu/download.asp?file=Effects_of_a_range_of_ecodriving_measures_on_emissions_and_fuel_consumption_TNO_2006.pdf
33 FIAT company: “Ecodriving uncovered”, 2010, http://www.lowcvp.org.uk/assets/reports/Fiat_EcoDriving%20Uncovered.pdf
34 RACQ: “RACQ ecodrive research study”, 2012, http://www.racq.com.au/cars-and-driving/driving/greenermotoring/racq-ecodrive-research-study
30
32
The results all confirm that the potential savings of adopting an ecological driving style can reduce
CO2 emissions by up to 15%, without an absolute need for technological guidance through invehicle systems.
3.1.2
Driver assistance systems
Advanced driver assistance systems (ADAS) can typically be divided in two groups. One group
targets a safety improvement, the other aims to reduce fuel consumption. Some systems can do
both.
As already discussed in earlier sections, driver behaviour optimisation has a great CO2 reduction
potential, around 15%. Most of that improvement can be achieved by the driver paying close
attention to his driving style, but it is not realistic to assume drivers will always be at their best.
Advanced driver assistance systems, built into the vehicle or as an aftermarket solution, can help
advise and correct the driver’s choices, so as to come as close as possible to the 15% maximum
potential.
The contributions of different types of systems were studied in the euroFOT project35. In D6.5 and
6.6, the consortium studied the environmental effects of a number of systems:
 Navigation systems
 Adaptive Cruise Control (ACC)
 Speed regulation systems (SRS), either as a speed limiter (SL) or cruise control (CC)
The study finds that built-in navigation systems can reduce fuel consumption of passenger cars by
3% (all roads), ACC by 2.8% (motorways only), SL by 1.6% (motorways) to 5.2% (urban) and
cruise control by 1.1% (motorways) up to 36.1% (urban roads) – though one may question on how
many urban roads cruise control can be safely used.
Most other driver assistance systems rely for a large part of their functionality on vehicle-to-vehicle
or vehicle-to-infrastructure communication, and in that respect they should be considered as ITS
measures. Given that ACEA is planning a specific study on this topic, we will not elaborate further
on that matter here. We can nonetheless conclude that the total potential of measures supporting a
more fuel efficient driving style (training+ADAS) can reduce CO2 emissions by up to 15%.
3.2
Fuel Quality Directive/Renewable Energy Directive
In the shortlist description, it was established that key contributions are needed from the biofuel
sector to achieve the prospective 2030 CO2 abatement targets for the road transport sector. The
other potential contributor to the goals of the eventual successor of the RED, the further
electrification of Europe’s passenger car fleet, will likely be included in the considerations regarding
the vehicle technology objectives.
The share of renewable energy in European transport has been growing steadily, from 1% in 2004
to 5.4% in 201336 (note that this includes more than just biofuels or road transport).
http://www.eurofot-ip.eu/
Source: Eurostat, indicator code tsdcc340,
http://ec.europa.eu/eurostat/tgm/table.do?tab=table&init=1&language=en&pcode=tsdcc340&plugin=1
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3.2.1
Types of biofuels and their GHG reduction potential
The current market for biofuels mostly consists of first generation biofuels produced from food
crops like sugarcane, sugar beet or maize (bioethanol); or rape, soybean or palm oil (biodiesel).
These feedstocks typically come with a high risk of ILUC effects, which jeopardises their positive
GHG reduction potential.
Second generation or “advanced” biofuels are generally produced from non-food feedstocks such
as waste products, which limits their risk of ILUC. These products are still at an early stage of
commercialisation, and it is unclear when they will be available on a sufficient scale.
When referring to third generation biofuels, fuels produced from algae are intended. They give high
yields and as they are produced in water bodies, pose no risk of LUC. However, their main
disadvantage is the amount of fertilizer (nitrogen and phosphorus) they require to grow – and the
production of those fertilizers generates high amounts of GHG (not to mention the monetary cost
of producing these fertilisers). A large scale implementation of algae-based biofuel is unlikely to
happen in the short to medium term.
The GHG reduction potential of different biofuel pathways is described in Annex IV to the FQD,
yet this excludes both DLUC and ILUC effects. Article 7b of the Directive states that GHG
savings should be at least 35%, and increasing to 50% from 2017 on. For new production plants
starting operations from 2018 on, the savings of the produced biofuels should be at least 60%.
 For bioethanol, the default savings range from 16% (wheat based) to 71% (sugar cane
based);
 for biodiesel, the range of savings goes from 19% (palm oil) to 83% (waste vegetable or
animal oil);
 for biogas, 73% (municipal waste) to 82% (dry manure) of GHG emissions can be saved;
 Advanced fuels have higher average savings, from 70% (farmed wood ethanol) up to 95%
(waste wood Fischer-Tropsch diesel and waste wood DME).
These numbers are generally in line with those of other publications, like those of the JEC37.
When determining the potential impact of biofuels, one should also take account of so called
“blend walls” for fuels. For first generation biofuels, there is a limit to the amount of biofuel that
can be blended with fossil fuels, beyond which the engine’s proper operation can be at risk. For
biodiesel, the blend wall is around 7% (B7), while bioethanol, a blend up to 10% (E10 – this may
increase to E20 by the mid-to-late 2020’s) is technically feasible without major modifications to the
engine. Many advanced biofuels are simply synthetic versions of the equivalent fossil fuel, and can
generally be blended without such restrictions (drop-in fuels).
3.2.2
Current status of legislation
The EU framework of legislation concerning the renewable energy/biofuel topic has a time horizon
of just a few years, up to 2020, and the current lack of direction beyond that moment is cause of
great uncertainty in the sector, which in turn causes delays or even abandonment of investments.
Different European bodies (Commission, Energy Council and Parliament) have made propositions
EC Joint Research Centre, EUCAR, CONCAWE cooperation, publications available on
http://iet.jrc.ec.europa.eu/about-jec/
37
34
in the past months to amend the legislative framework for 2020, but no consensus has been
reached yet. The amended legislation is expected to cover 4 points:
 Increase the GHG reduction of biofuels produced in new installations to 60% (up from
35%);
 Include Indirect Land Use Change (ILUC) in the GHG balance of different fuels;
 Set a cap on the amount of biofuels from food crops;
 Set up a framework for financial support to second and third generation biofuels only.
The uncertainty makes the assessment of the contribution of renewable energy to long term road
transport CO2 reductions far from straightforward. Two main aspects are to be considered for that.
First, there is the projected share of biofuels in the total fuel mix of road transport. Biofuels are
generally still more expensive to produce than fossil fuels, meaning their market is mostly based on
the targets set by legislators, and depends on subsidies that are coupled with those targets. Fossil
fuel price has been very unpredictable, but nonetheless also impacts the market for biofuel and any
investments made therein. Second is the contribution to GHG reduction of different biofuels.
Biofuel production has different pathways with different life cycle CO2 emissions (see previous
section), which should include the amount of carbon taken from the atmosphere during the growth
of the feedstock, the amount of carbon emitted during fuel production, but also the effects of
Direct and Indirect Land Use Change (DLUC and ILUC). Especially those LUC effects are subject
to interpretation and greatly depend on very local circumstances. Along with the cap on food crops,
ILUC is the main subject of discussion for the current amendment of legislation.
As stated earlier in this report, the GHG reduction target currently set for transport fuels is part of
the Fuel Quality Directive (last amended by 2009/30/EC), at a level of 6% by 2020. The latest
publication on the topic by the JEC38 however, already puts this target beyond reach; it does the
same for any of the proposed changes. 4.4 % is about the maximal level that is achievable. The
RED target of 10% of energy supplied by biofuels would also be missed, with a similar margin (89% is achievable).
3.2.3
Potential beyond 2020
A few studies cover the potential contribution of biofuels for the period beyond 2020. We will only
highlight the data regarding the GHG reduction potential coming out of these studies, along with
the main framework conditions. For detailed information on the assumptions, we refer to the
original studies.
A study of Element Energy for BP39 covering the UK only developed 3 scenarios (baseline,
medium and high) with varying degrees of biofuel blending, coupled with financial support for the
development of advanced biofuels, projected fleet evolutions and production capacity of biofuels.
It concluded that GHG savings from biofuel use could range from 9% (medium scenario) up to
27% (high scenario) by 2030. Given the vehicle fleet composition of the UK, the focus is mainly on
(advanced) bioethanol as a replacement for gasoline, which makes it difficult to generalise results
and compare them to countries with a higher diesel share, e.g. France and Belgium. The study is
furthermore rather optimistic about the development of advanced biofuels production
JEC: “EU renewable energy targets in 2020: Revised analysis of scenarios for transport fuels”, 2014,
https://www.concawe.eu//uploads/Modules/Publications/jec_biofuels_2013_report_final.PDF
39 Element Energy: “The Role of Biofuels beyond 2020”, 2013, http://www.element-energy.co.uk/wordpress/wpcontent/uploads/2013/09/20130916-Element-Energy_Role-of-biofuels_FINAL.pdf
38
35
capacity/costs, but nonetheless provides a useful indication for biofuel’s contribution to road
transport’s GHG reductions.
E4Tech performed a study40 for a consortium of Daimler, Honda, Neste, OMV, Shell and
Volkswagen in 2013 with a similar aim, but covering the entire EU28. In 4 scenarios, varying in the
supply of biofuel up to 2030 (volume, EU vs external production capacity, and costs), and
accounting for road fleet evolution (all road vehicles including HDV), the study assessed the GHG
reduction potential of biofuels, explicitly distinguishing the contribution of second generation
biofuels. For all scenarios, the GHG reduction potential is calculated to be around 8% in 2030.
Second generation diesel substitutes would be 9-21% of the total, while for gasoline, advanced fuels
contribute 16-21%. The assessed potential is just below lower edge of the range suggested by the
previous study.
Figure 4: assessment of CO2 reduction potential from biofuels in road transport from E4tech study
According to the IEA’s 2014 World Energy Outlook, the share of biofuels in road transport would
range from 11% to 31% in the EU by 2040 – up from around 9% by 2020 (based on JEC). Linear
interpolation puts the 2030 value between 10 and 20% based on energy, roughly equivalent to a 510% reduction in GHG emissions.
In a study by Emisia for the European Biodiesel Board41, the CO2 reduction of biofuels in road
transport in the most optimistic scenario (assuming specific GHG savings over 70% and
benevolent policy making) is around 7.2% in 2030, up from 6.4% in 2020 (note that the study
assumes that the current 2020 targets will be met, contrary to other literature discussed above).
E4Tech: “A harmonised Auto-Fuel biofuel roadmap for the EU to 2030”, 2013,
http://www.e4tech.com/pdf/eu_auto-fuel-report.pdf
41 Ntziachristos, L., et al., Emisia: “ The contribution of biofuels in transport sustainability post-2020”, 2014,
http://www.ebb-eu.org/studiesreports/EMISIA_Contribution_Biofuels_transport_sustainability.pdf
40
36
3.2.4
Conclusion
With varying assumptions, most of the studies dealing with the topic seem to agree that the GHG
reduction potential of biofuels in 2030 is around 8%. However, this figure accounts for all of road
transport (including HDV), which implies that diesel powered vehicles are overly represented. As
the potential for diesel substitution seems to be somewhat lower than for gasoline, the GHG
reduction for passenger cars could be a bit higher still. However, none of these studies account for
ILUC effects, one of the major topics of discussion for new policies regarding biofuels. Other
assumptions often include a non-negligible market share for advanced biofuels, which will also be
heavily dependent on the outcome of negotiations regarding the support mechanisms in the new
legislation.
3.3
Road transport in EU ETS
The European Emission Trading System has been in operation since 2005. Now in its third trading
period (2013-2020), the system incorporates 45% of GHG emissions (including CO2) from a range
of sectors including power generation, energy-intensive industry sectors and aviation. The system
sets an EU wide cap of emissions and allows trading of emission allowances between the parties
that are subject to it.
For several years, setting up an emission trading system for road transport - and possibly a direct
inclusion of road transport in the current system - has been a topic of debate, and several studies
have been conducted providing arguments in support of or against this measure, possibly in
combination with a continued fuel efficiency standard. As was noted before, this topic is partly
covered in an EC study being performed in parallel to the present one, and due to a conflict of
interest, a comparison of the options cannot be made. Instead, we will make an overview of the
potential design parameters of such a system and highlight positive and negative properties of each
option.
Issues that will be addressed include:
 Which party will be responsible for the purchase of allowances?
 Should the system be open or closed?
 How will allowances be allocated?
3.3.1
Responsible party
The responsible party is the actor in charge of obtaining and submitting allowances as needed. For
road transport, three options can be considered:
 Fuel suppliers (upstream);
 Vehicle manufacturers (midstream);
 Fuel consumers = vehicle owners (downstream).
An upstream system has two major advantages. The primary advantage is that it is a transparent
system in which a direct link can be set between the fuel suppliers’ activities and the amount of
allowances submitted. The amount of fuel sold by each party directly reflects the CO2 emissions
each party is responsible for. Another advantage is that fuel production is already part of EU ETS
as an energy-intensive sector and that additional compliance costs would be very limited. Another
aspect adding to that argument is the fact that the amount of responsible parties in such a system is
37
limited (just under 100 according to TU Braunschweig (2014)42). A disadvantage of the upstream
option is that the responsible parties do not have a major incentive to reduce emissions, as they will
be able to pass the additional cost of allowances on the consumer.
A downstream system has the same transparency as an upstream system, but it does not have the
advantage of low compliance costs, as each fuel buyer/vehicle owner will have to take action to
purchase and submit allowances, either upon fuel purchase or at regular intervals. However, a
downstream system does promote fuel efficient behaviour, both in driving style and vehicle
purchase decisions.
In a midstream system, car manufacturers would be responsible for the procurement of emission
allowances. The main advantage of that system is the incentive it provides to develop, produce and
sell fuel efficient vehicles. The main problem with a midstream system is the fuzziness about the
actual amount of emissions generated by every vehicle after the sale. As the OEMs only carry
responsibility for the vehicle up to the moment of sale, the use phase emissions would require
several assumptions to be calculated, including on real world emissions and lifetime mileage – both
of which can vary significantly between drivers and are beyond the control of OEMs.
Whereas the uncertainties brought about by a midstream system could be solved through
negotiations, and the lack of incentives in an upstream system can be overcome in practice, it is
probable that a downstream system is intrinsically impossible due to the compliance costs, which
may outweigh the costs of the allowances themselves.
3.3.2
Open or closed system
The primary goal of an emission trading system is to achieve a reduction of emissions at the lowest
possible cost to society. A regulatory system aiming to control emission levels may however also
have other targets: reducing the dependency on fuel imports; promoting innovation and job
creation within the own region; lowering fuel costs for end users; just to name a few. These
arguments play an important role not just in the decision whether or not to implement ETS, but
also in the format of the ETS that is chosen, namely whether the system should be open (allowing
trade of allowances between all participating sectors) or closed (only allowing trade within a sector).
In order to achieve emissions at the lowest possible cost, an open system has a clear advantage.
With more parties able to contribute, lower marginal abatement cost levels can be reached, and
assuming that the market for allowances is efficient, CO2 reduction will happen in those sectors and
companies where it is the cheapest. In the case of road transport, it is very likely that most of the
required permits would be purchased from other sectors, which is the main drawback of the
system, even though it may be a perception issue: both policy makers and the public could consider
this a way for road transport to buy out of its responsibility and defer to other sectors, which
impacts the acceptance level and perceived fairness of the policy, in spite of economic reality. Some
of that perception may be due to the aforementioned other aspects of emission control policies, like
job creation, fuel cost reduction and lowering import dependency. All of these parameters should
be considered when redesigning the system. An open system can be combined with all options for
the responsible parties, taking into account the caveats about the amount of responsible parties in a
downstream system and the compliance costs that would entail.
Institute of Automotive Management and Industrial Production, Technische Universität Braunschweig: “Regulation of
CO2 emissions from passenger cars within the European Union after 2020”, 2014
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While a closed system does not have the issue of perceived responsibility dodging, the efficiency of
such a system is limited. Restricting the scope of an ETS to just road transport is practically only
feasible for a midstream system, given that the ETS in which fuel suppliers currently participate is
an open one, and that a downstream system is likely not practically feasible in any form. A closed
midstream system would leave trading of allowances only between a small amount of market
players, which not only limits the efficiency of the system, it also increases the risk of market
failures, e.g. by strategic hoarding of allowances. Such a closed market would need to be very
strongly regulated and monitored to achieve its maximum efficiency. A closed system can be a
solution if aspects other than lowest marginal abatement cost are taken into account, but they need
to be properly valued and compared to the cost of not achieving maximal efficiency.
3.3.3
Allocation of permits
Allowances can be distributed using three systems: grandfathering, benchmarking or auctioning –
or a combination thereof.
Grandfathering is the free distribution of allowances based on historic emission levels. This method
was applied in the first years of the EU ETS, to ease the transition into the system. However, this
method presented two major problems. The first is that historic levels only partly impact future
emission levels. They do not reward parties that have already made efforts to reduce emissions in
the past; they in fact do the opposite. The second, and this is the case for all free allocation
methods, is that they create windfall profits. No matter how allowances are obtained, they have a
value on the market, and this value will be passed on to the customers as an additional cost.
Benchmarking as a way to distribute emissions has the advantage of rewarding parties that have
already made an effort to reduce emissions in the past. However, setting the benchmark can be a
complex process, and the problem of windfall profits remains, albeit to a lesser extent.
The preferred option is the auctioning of allowances. This system puts the mechanics of the market
to work from the start, and creates an income for the government that can be used for other
purposes (together with the reduction of emissions, it is referred to as a double dividend). The EU
ETS has been moving toward 100% auctioning.
For the inclusion of road transport in the EU ETS, the choice of allocation method will not affect
the market, only the bottom line of the trading parties.
3.3.4
Other aspects to be considered
Apart from general design parameters, other aspects need to be considered.
One of the main critiques of the current ETS is that there is an oversupply of allowances (due to
the economic crisis), which has led to very low prices for allowances. While the low price is not
necessarily a problem, an oversupply of allowances generates no incentives to invest in CO2
reduction technologies, which may cause problems when settings further emission reduction
targets.
Another problem is the concept of carbon leakage, where emission-generating activities are moved
outside the zone in which ETS is applied, but they remain active nonetheless. While the road
transport sector is not a sector where carbon leakage is expected to be a major problem (except at
the outside borders of the ETS zone, where people may fill up their tanks across the border), but
39
other sectors are. Inclusion of road transport in an open ETS exposes the sector to the same
carbon leakage problem.
Assuming an upstream system is set up, the cost of allowances would be added to that of fuel at the
pump, which is already heavily taxed. The additional cost of ETS would be lower than the periodic
variation in fuel prices, and the price signal would be negligible. Given that elasticity of transport
demand with regard to fuel price is low (long term values range around -0.743), emissions would not
be noticeably affected.
Abandoning the current fuel efficiency standards in favour of EU ETS for road transport may lead
to a more efficient manner of meeting the EU’s GHG emission targets. However, the current
system has a few other advantages that may not be covered as well by an ETS:
 Reduced energy demand
 Reduced fossil fuel imports
 Expansion of the vehicle supply chain (high quality job creation)
 Lower TCO due to lower fuel costs, with knock on effects on the rest of the economy
3.3.5
Potential impact of EU ETS on road transport emissions
The inclusion of road transport in an EU ETS would require a revision of the current cap
provisions and could lead to an increase of current allowance prices. While this means that any
target set is theoretically achievable, a scenario analysis is needed to assess the practical
consequences. A number of studies have performed simulations to estimate the effect on road
transport in EU ETS on emission levels of transport and of allowance prices. Cambridge
Econometrics performed a study for the European Climate Foundation (2014)44 in which they
simulated the effects of the inclusion with 2 allowance prices, a low price (€10/tonne) and a price in
line with EC simulations with PRIMES (€19.4/tonne). They also simulated a continuation of
current fuel efficiency policies, which resulted in a projected 33% decrease in road transport CO2
emissions (2030 vs 2015). Their final simulation intended to calculate allowance price if the same
reduction were to be achieved using ETS. As a reference, they used a PRIMES scenario in which
the 2020 fuel efficiency target of 95g/km is not met, which will reduce CO2 emissions by 12%
between 2015 and 2030. The conclude that an ETS with a normal price evolution (S1 and S2)
hardly reduce CO2 emissions of road transport more than in the reference, at -3% and -1%
respectively. In order to achieve a reduction similar to a continuation of fuel efficiency standards,
allowance prices would need to top €200/tonne.
See Litman, T., VTPI: “Understanding Transport Demands and Elasticities”, 2013, http://www.vtpi.org/elasticities.pdf
Cambridge Econometrics: “The Impact of Including the Road Transport Sector in the EU ETS”, 2014,
http://www.camecon.com/Libraries/Downloadable_Files/Including_Road_Transport_in_the_EU_ETS__Final_Report.sflb.ashx
43
44
40
Table 15: Cambridge Econometrics EU ETS simulation results
These numbers are generally confirmed by a study done by Öko-Institut (2015)45, which estimates
the reduction from ETS between -0.5% (€5/tonne) to -2.3% (€25/tonne), based on an elasticity
approach.
In a draft publication, MIT (2015)46 compared the effects of fuel efficiency standards with those of
an ETS, focussing on total economic cost of the different options. The study finds that fuel
efficiency standards are significantly more costly than emission trading to achieve the same target
(2025 horizon); for a target of 68g/km, the difference amounts to 63 billion euro in 2025, mainly
due to higher capital and investment costs, and lower fuel tax revenue. However, the authors do
acknowledge that fuel imports are lower in a scenario with efficiency standards, and they do not
include the added value created by those standards in the form of employment and know-how
generation in their calculations.
3.3.6
Conclusion on road transport as part of EU ETS
As stated earlier, this study did not perform a full assessment of the potential inclusion of road
transport in EU ETS. However, some conclusions can still be made:
 A well designed ETS for road transport has the potential to achieve the European emission
targets at a lower direct cost than a continuation of the current policy;
 The difference in marginal abatement costs between road transport and other ETS sectors
essentially means that most of the CO2 reduction will occur in other sectors than road
transport; road transport may only reduce emissions by 3% when included in the EU ETS;
 Fuel efficiency standards have secondary effects beyond CO2 reduction that have not yet
been properly valued, but should also be considered when making a decision.
Kasten, P., et al., Öko Institut: “Policy mix in the transport sector: What role can the EU ETS play for road
transport?”, 2015, http://www.oeko.de/oekodoc/2221/2015-006-en.pdf
46 Paltsev, S. et al., MIT: “CO2 Emissions, Energy, and Economic Impacts of CO2 Mandates for New Cars in Europe”,
2015
45
41
3.4
Autonomous fleet renewal
The initial assessment of the potential of autonomous fleet renewal made in section 2.6 revealed
that this process could generate the projected CO2 reduction requirements for 2030 on its own.
That scenario assumed that the 95g/km test cycle target would translate into around 105g/km real
world emissions, a 10.5% correction.
Reaching this target by 2021 and maintaining it afterwards would lead to a reduction of fleet
emissions of nearly 220 Mt. Underlying assumptions are a growth of the fleet from 240 million
vehicles in 2010 to 297 million in 2030 (+24%), and an increase of demand from 2,703 billion vkm
in 2010 to 3,433 billion in 2030 (+27%). ICE vehicles are projected to still represent 97% of the
fleet by 2030, which makes this a conservative assessment.
To complete the picture, two additional simulations were performed. The first assumes that real
world emissions of new vehicles in 2021 will be lower than the baseline and equal to test cycle
emissions at 95 g/km. The second assumes that real world emissions will instead be higher, and
reach a 115g/km average. After 2021, no further improvements in fuel efficiency are assumed. The
scenarios only cover traditional vehicle types – emission factors for hybrids, electric, NG, etc.
vehicles are not changed. Given their very limited assumed share, this simplification does not have
a major impact.
The results of these simulations are shown in the graphs and tables below. If real world emissions
of 95g/km are achieved for new vehicles from 2021 onward, an additional 25 Mt CO2 can be
reduced – equivalent to the combined 2010 CO2 emissions of Belgium and the Netherlands. In case
real world emissions would be closer to 115 g/km, the total reduction would be limited to 193 Mt –
which is still more than the 30% target reduction. A connotation with this scenario is that emissions
start going up again slightly by 2030, due to the increasing demand.
550
500
450
95 g/km
400
105 g/km
115 g/km
350
300
250
2010
2015
2020
2025
2030
Figure 5: Passenger car CO2 emissions, total fleet value, in Mt
42
Table 16: Passenger car CO2 emissions, total fleet value, in Mt
Mt CO2
2010
2015
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
95 g/km
513.9
445.5
398.8
389.2
380.2
371.4
364.4
358.2
353.4
349.1
345.6
343.1
341.4
105 g/km
513.9
445.5
404.5
397.2
390.4
384.0
379.0
374.9
371.8
369.2
367.4
366.4
366.2
115 g/km
513.9
445.5
410.3
405.4
400.7
396.7
393.7
391.6
390.4
389.6
389.6
390.1
391.3
Another interesting parameter to consider is the average emissions of the vehicles in the fleet, as
this is a measure for the penetration of the higher fuel efficiency vehicles. In the baseline, the CO2
emission factor of the average vehicle is 107g/km, very close to the value for newly sold vehicles.
In the 95g/km scenario, the average is still at 99g/km, while in the 115g/km scenario, the average
is just below the target 115g/km. This is caused by the smaller gap between the vehicles being
replaced and the newly sold vehicles, and the (limited) contribution of non-traditional propulsion
type vehicles.
200
180
160
95 g/km
140
105 g/km
115 g/km
120
100
80
2010
2015
2020
2025
2030
Figure 6: average CO2 emission factor of the fleet, in g/km
Table 17: average CO2 emission factor of the fleet, in g/km
Fleet
average
emissions
2010
2015
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
95 g/km
189.8
154.1
128.2
123.4
119.1
115.3
112.0
109.1
106.5
104.3
102.3
100.6
99.1
105 g/km
189.8
154.1
130.3
126.2
122.7
119.5
116.9
114.5
112.4
110.7
109.1
107.8
106.7
115 g/km
189.8
154.1
132.4
129.1
126.3
123.9
121.8
120.0
118.5
117.2
116.0
115.1
114.3
Autonomous fleet renewal will likely be the greatest contributor to CO2 reduction of passenger car
transport until 2030. A strong effort for a certain period has an effect that lasts for about a decade until increased demand catches up with the efficiency improvement. Autonomous fleet renewal can
ride the impulse created by fuel efficiency standards, but repeated efforts are needed to continue
the improvement. In light of the stricter 2050 reduction targets set in the 2011 Transport White
Paper (-60% for transport), the positive effects of autonomous fleet renewal are as such not a
sufficient argument to abandon or even postpone new fuel efficiency standards.
43
2030
44
4
Conclusions
The aim of this project was to list and assess options to reduce CO2 emissions of passenger cars
that were not directly based on vehicle technology. These measures should help Europe meet its
anti-climate change targets. It was estimated that passenger cars as a subsector should reduce its
CO2 emissions by around 170 million tonnes, equivalent to 30% of the 2005 level. The following
options were considered:
 Ecodriving (training and ADAS)
 Road transport in EU ETS
 Road traffic management through
 Autonomous fleet renewal
ITS
 CO2 based vehicle taxation
 Road infrastructure
 Vehicle labelling
 Energy/Carbon content of fuels –
 Tyres
renewable fuels
Ecodriving can be promoted using two pathways: either by driver training, or by ADAS (advanced
driver assistance systems). Both have the same target: making the driver operate the vehicle in the
most fuel efficient manner, either by a change in intrinsic behaviour (training), or by providing
instantaneous in-vehicle feedback and guidance (ADAS). While both can have an impact, their
combined effect is limited to around 15% reduction. The benefits can mainly be reaped in urban
environments and at lower speeds, where accelerations and decelerations occur more frequently.
ITS based Road traffic management systems can reduce vehicle fuel consumption by making traffic
smoother and vehicles running closer to peak efficiency. The systems can work at a local level
(intersections and highway corridors), the network level (spatial and temporal dispersion of traffic,
e.g. through dynamic routing) or the demand level (modal choice). In a way, the local level effects
extend the ecodriving measures at vehicle level to inter-vehicle communication, thus reinforcing the
benefits made there. At the higher aggregation levels, current research (which is still fairly limited)
indicates that a 1.3% additional decrease in CO2 emissions should be possible. Higher gains are
possible, e.g. with large scale implementation of local scale measures, but further research is needed
to quantify the potential.
Improving fuel efficiency of passenger cars by taking on road infrastructure is another possibility.
While multiple methods exist, the biggest effect can probably be generated by keeping roads well
maintained, thereby keeping parameters such as macrotexture and roughness close to the optimal
level. Improvement potential is around 1-2%. Road pavement material (usually a choice between
concrete and asphalt) is not a critical factor on its own. Limiting road gradients is generally not
considered a cost-effective manner of reducing vehicle fuel consumption, especially ex-post.
Nonetheless, it should be taken on board as a factor contributing to emissions when building new
roads. At a higher level of aggregation, building bypass roads around urban areas can have a
positive impact on fuel efficiency in the right circumstances, but the opposite can happen when
conditions are not right.
The use of biofuels in transport could possibly bring the single greatest improvement in CO2
intensity of the sector. However, the short to medium term outlook calls for caution. EC policy, in
the form of the RED and FQD, calls for limited contributions, and research shows that even those
are probably beyond reach (JEC: only 4.4% of 6% FQD target will be achieved). The directives are
being reviewed at this moment, but in their current form they do not account for ILUC. The
45
outcome of discussions on this topic could be decisive for the future of biofuels. As for the
improvement they could generate under the assumptions that current policy will continue in a
similar form, a reduction of GHG emissions of road transport around 8% is estimated for 2030. As
the potential for diesel vehicles is somewhat lower than for gasoline vehicles, and these diesel
powered HDV represent a significant part of total road transport emissions, passenger car
reductions could be higher still.
Literature suggests that moving from fuel efficiency standards to ETS as the practice for
management road transport carbon emissions would – at current permit prices – generate a 3%
reduction; much less than what recent proposals for CO2 targets beyond 2020 aim to achieve
(Note: this study covered road transport as part of the EU ETS only conceptually as it is not a
measure per se, but a system with a broader scope).
While the scope of this study explicitly omits new fuel standards, an assessment of the effect of
autonomous fleet renewal was made, under the assumption that the current 2021 target would
remain in place until at least 2030. In all three considered scenarios, fleet renewal suffices for
passenger car transport to meet a 30% reduction by 2030. The wave effect caused by fuel efficiency
standards lasts about a decade, and without further reduction measures, CO2 emissions will start
increasing again before 2035.
CO2 based vehicle taxation is becoming a common practice throughout Europe, but the absolute
and relative tax levels vary greatly between countries. Research suggests that it has a measurable
effect on fleet evolution. In the Netherlands and the UK, about 1/8 of recent reductions in average
new vehicle fuel consumption are due to CO2 based taxes – equivalent to 2-4%.
The effects of vehicle labelling as a measure to reduce fuel consumption by improving buyers’
knowledge have been insufficiently documented. A review of applicable legislation is ongoing.
Tyres for passenger cars have been subject to EC legislation since 2012, and effects are still building
up throughout the fleet. However, they are expected to reach their full potential around 2020, and
are thus not expected to contribute much in the 2020’s.
Table 18: summary of effects
Measure
Potential
Comment
Ecodriving
15%
Combined effects of driver training and ADAS
ITS (network level)
1.3%
Network measures – local effects can be higher
Road infrastructure
1-2%
Improved maintenance, material choice less important
Biofuels
8%+
Not including ILUC
ETS
N/A
Much lower effect than fuel efficiency standards as CO2 is saved in other sectors
Autonomous fleet renewal
37%
Not a lasting effect
CO2 based vehicle taxation
2-4%
Depends on the level of the tax
Vehicle labelling
N/A
Insufficient literature available for assessment
Tyres
0%
Most vehicles already equipped with fuel efficient tyres
46
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