COMMISSION STAFF WORKING DOCUMENT - IMPACT ASSESSMENT - ANNEXES Accompanying the document Proposal for a Regulation of the European Parliament and of the Council setting emission performance standards for new passenger cars and for new light commercial vehicles as part of the Union's integrated approach to reduce CO2 emissions from light-duty vehicles and amending Regulation (EC) No 715/2007 (recast)

1.

Kerngegevens

Document date 14-11-2017
Publication date 15-11-2017
Reference 14217/17 ADD 3
From Secretary-General of the European Commission, signed by Mr Jordi AYET PUIGARNAU, Director
External link original article
Original document in PDF

2.

Text

Council of the European Union

Brussels, 14 November 2017 (OR. en)

14217/17

Interinstitutional File: ADD 3

2017/0293 (COD) i

CLIMA 302 ENV 918 TRANS 466 MI 807 CODEC 1787 IA 178

COVER NOTE

From: Secretary-General of the European Commission, signed by Mr Jordi AYET PUIGARNAU, Director

date of receipt: 9 November 2017

To: Mr Jeppe TRANHOLM-MIKKELSEN, Secretary-General of the Council of the European Union

No. Cion doc.: SWD(2017) 650 final - Part 2/2

Subject: COMMISSION STAFF WORKING DOCUMENT - IMPACT ASSESSMENT - ANNEXES Accompanying the document Proposal for a Regulation of the European Parliament and of the Council setting emission performance

standards for new passenger cars and for new light commercial vehicles as part of the Union's integrated approach to reduce CO2 emissions from light-duty vehicles and amending Regulation (EC) No 715/2007 i (recast)

Delegations will find attached document SWD(2017) 650 final - Part 2/2.

Encl.: SWD(2017) 650 final - Part 2/2

EUROPEAN COMMISSION

Brussels, 8.11.2017 SWD(2017) 650 final

PART 2/2

COMMISSION STAFF WORKING DOCUMENT

IMPACT ASSESSMENT

ANNEXES

Accompanying the document

Proposal for a Regulation of the European Parliament and of the Council setting emission performance standards for new passenger cars and for new light commercial vehicles as part of the Union's integrated approach to reduce CO2 emissions from lightduty

vehicles and amending Regulation (EC) No 715/2007 i (recast)

{COM(2017) 676 final i} - {SWD(2017) 651 final} Table of contents

1 ANNEX 1: PROCEDURAL INFORMATION CONCERNING THE PROCESS TO PREPARE THE IMPACT ASSESSMENT REPORT AND THE RELATED INITIATIVE ................................................................................................................ 3

1.1 Organisation and timing .................................................................................... 3

1.2 Consultation of the Regulatory Scrutiny Board (RSB) ..................................... 3

1.3 Evidence ............................................................................................................ 6

1.4 External expertise .............................................................................................. 7

2 ANNEX 2: STAKEHOLDER CONSULTATION ..................................................... 8

2.1 Introduction ....................................................................................................... 8

2.2 Public consultation ............................................................................................ 9

2.2.1 Process and quantitative results ........................................................... 9

2.2.2 The need and objectives for setting CO 2 emission targets for cars and vans in the EU after 2020 ........................................................... 10

2.2.3 Technology specific requirements ..................................................... 13

2.2.4 Distribution of efforts between different actors ................................ 13

2.2.5 Incentivising low- and zero-emission vehicles ................................. 13

2.2.6 Modalities (eco-innovations and derogations) .................................. 14

2.3 Dedicated stakeholder event on jobs and skills ............................................... 15

2.4 Use of the stakeholder input for the impact assessment .................................. 15

3 ANNEX 3: WHO IS AFFECTED BY THE INITIATIVE AND HOW ................... 17

4 ANNEX 4: ANALYTICAL MODELS USED IN PREPARING THE IMPACT ASSESSMENT ......................................................................................................... 20

4.1 PRIMES-TREMOVE transport model ............................................................ 20

4.2 DIONE model (JRC) ....................................................................................... 22

4.3 Macroeconomic models (E3ME and GEM-E3) .............................................. 25

4.3.1 E3ME................................................................................................. 26

4.3.2 GEM-E3 ............................................................................................ 27

4.4 Baseline scenario ............................................................................................. 28

4.4.1 Scenario design, consultation process and quality assurance ............ 28

4.4.2 Main assumptions of the Baseline scenario ...................................... 29

4.4.3 Summary of main results of the Baseline scenario ........................... 31

4.5 Consistency with previous analytical work ..................................................... 38

4.6 Determination of conversion factors from NEDC to WLTP emission values 40

5 ANNEX 5: FROM NEDC TO WLTP – TRANSITION TO THE NEW TYPE APPROVAL EMISSIONS TEST UNDER THE CURRENT CARS AND VANS REGULATIONS ....................................................................................................... 43

6 ANNEX 6: REAL WORLD EMISSION MONITORING ....................................... 45

7 ANNEX 7: EMPLOYMENT AND QUALIFICATION ......................................... 48 8 ANNEX 8: ADDITIONAL INFORMATION CONCERNING THE

ASSESSMENT OF THE ECONOMIC, ENVIRONMENTAL AND SOCIAL IMPACTS OF THE DIFFERENT POLICY OPTIONS ........................................... 54

8.1 Emission targets: metric .................................................................................. 54

8.1.1 Methodological considerations concerning Well-to-Wheel (WTW) and life-cycle analysis (LCA) approaches ......................................... 54

8.1.2 Considerations regarding well-to-wheel emissions ........................... 55

8.1.3 Considerations regarding embedded emissions ................................ 64

8.2 Target levels for cars (TLC) and vans (TLV) ................................................. 68

8.2.1 Economic impacts ............................................................................. 68

8.2.2 Social Impacts ................................................................................... 82

8.3 Distribution of effort (DOE): additional information regarding impacts on competition between manufacturers ................................................................ 86

8.4 ZEV/ LEV incentives ...................................................................................... 88

8.4.1 Passenger cars: assessment of options with additional incentives for low-emission vehicles: economic and social impacts ................. 88

8.4.2 Vans: assessment of options with additional incentives for lowemission vehicles: economic and social impacts ............................ 107

1 A NNEX 1: P ROCEDURAL INFORMATION CONCERNING THE PROCESS TO PREPARE THE

IMPACT ASSESSMENT REPORT AND THE RELATED INITIATIVE

1.1 Organisation and timing

The Directorate-General for Climate Action is the lead service for the preparation of the initiative (2015/CLIMA/019) and the work on the impact assessment.

An inter-service steering group (ISG), chaired by the Secretariat-General, was set up in December 2015 with the participation of the following Commission Directorates-General: Legal Service; Economic and Financial Affairs; Internal Market, Industry, Entrepreneurship and SMEs; Environment; Mobility and Transport; Joint Research Centre; Taxation and Customs Union; Justice and Consumers, Employment, Social Affairs and Inclusion, Research and Innovation, Competition, Energy, Communications Networks, Content & Technology.

The ISG met six times between December 2015 and the end of September 2017, discussing the inception impact assessment, the questionnaire for and results of the public consultation, the outcome of the stakeholder workshops and the draft impact assessment.

1.2 Consultation of the Regulatory Scrutiny Board (RSB)

The Regulatory Scrutiny Board received the draft version of the present impact assessment report on 25 September 2017 and following the Board meeting on 11 October 2017 issued a positive opinion with reservations on 13 October 2017.

The Board made the following recommendations, which were addressed in the revised impact assessment report as indicated below.

Main RSB considerations Response

The report does not describe the key The policy context and links with other EU EU policy initiatives that initiatives, including the upcoming initiative on complement this initiative. It leaves heavy duty vehicles have been further elaborated in out what these other EU initiatives Section 1.1 of the report. The contribution of the need to achieve for this initiative to initiative to the Effort Sharing Regulation succeed. objectives is described in Sections 6.2 and

6.3.2.4.3.

The EU Action Plan for Alternative Fuel Infrastructure and other flanking measures, such as the Revision of the Clean Vehicles Directive which will be part of the second 2017 Mobility Package, will ensure that infrastructure and demand-side action is aligned with supply-side measures. Additional enabling measures can be put in place by Member States or local authorities, as acknowledged in Sections 2 and 7 of the report.

The report does not explain the The main elements hampering the uptake of more bottlenecks to a higher consumer efficient vehicles are the fact that consumers value uptake of electric vehicles. The upfront costs over lifetime costs and/or have other report is also unclear on whether the consumer preferences, and in the particular case of competitiveness challenge is zero-emission vehicles, the 'range anxiety' and technological leadership or concerns over the resale value of the vehicle. This protecting EU employment. is further elaborated in Section 2.2 (drivers 1 and

2), with reference to several studies.

The competitiveness challenge for EU industry has been expanded in Section 2.1.3, highlighting the risk of losing technological leadership, esp. in view of the expected growing global demand of lowemission vehicles, and the increased costcompetitiveness of batteries, and recent regulatory developments in particular in China. Creating an EU market for low-emission vehicles is an important enabler for enhancing economies of scale, cost reduction and technological leadership, which in turn can help EU manufacturers retain market shares in the global automotive market. The link with employment and skills requirements is further elaborated in Section 6.3.2.2.3.3.

The impact analysis does not show The legislation setting CO 2 standards is a how technical CO 2 standards regulatory measure acting on the supply side, increase consumer uptake of lowrequiring vehicle manufacturers to develop, market emission vehicles and make the and promote more efficient vehicles, including European car industry more zero- and low- emission vehicles, in order to competitive. It does not indicate the comply with the standards. Better and more models cost of the flanking policies offered to consumers will result in a higher market underlying the positive outcome. uptake which will in turn drive additional

investments in the needed refuelling and recharging infrastructure, for instance at home and in offices.

In addition, the Alternative Fuel Infrastructure Plan aims to support the deployment of charging infrastructure along the core TEN-T network by 2025, thereby reducing range anxiety among potential customers.

Furthermore, CO 2 standards complemented by well-designed incentives for zero- and lowemission vehicles provide a clear and long-lasting market signal for the entire automotive value chain, and create certainty for manufacturers. This will create economies of scale lowering the costs of low-emission vehicles, thus further contributing to their market uptake. Lower costs of batteries enable larger capacity batteries to be built into cars, thereby increasing the range and reducing range anxiety among potential customers. This is described in Section 5.3.1 of the report.

In terms of the costs of flanking measures, the investments needed for the deployment of the fuelling/charging infrastructure are the most significant ones. The macro-economic analysis presented in Section 6.5.4 of the report takes into account the need for investments to support the roll-out of the necessary infrastructure.

The report does not identify which Section 7 of the report indicates the preferred key trade-offs are genuinely open for option for most of the elements considered.

political decision. In the case of the CO

2 target levels and the ZEV/LEV incentives, the report describes the trade-offs, points to the most cost-effective options and provides the necessary analysis for a political decision to be taken.

The report does not assess the Overall, most of the policy options considered are regulatory burden and the potential not expected to significantly alter the administrative for simplification costs compared to the current Regulations.

The ZEV/LEV incentives mechanisms considered would not create additional administrative burden. The deletion of the derogation for niche manufacturers will reduce administrative burden.

No changes in the compliance regime and in the level of fines are foreseen. The impacts of the options related to governance will depend on the concrete implementing measures.

Information on the expected impacts in terms of administrative burden has been added in different parts of Section 6.

Further RSB considerations and Response adjustment requirements

The narrative on the links between this The links between this initiative and initiative and competitiveness of the competitiveness of EU automotive value chain are EU automotive industry should be described in Sections 2.1 and 4. developed substantially. The report

should expand on how the initiative to This initiative is part of the second 2017 Mobility accelerate change in car technologies Package which includes different flanking relates to support for public transport to measures, in particular the EU Action Plan reduce emissions. It should indicate regarding Alternative Fuel Infrastructure, the

how important policy initiatives like the revision of the Clean Vehicle Directive and a dedicated initiative on batteries. The combination

Alternative Fuels Infrastructure

Directive and the EU battery alliance of regulatory (CO 2 standards, Clean Vehicles are for the effectiveness of standard Directive), financing (infrastructure) and industrial

setting. (batteries) measures provides a mutually reinforcing approach on the demand and supply

side to address the identified problems. This is described in Section 1.1 of the report.

The report should detail what elements As explained above, consumer uptake will be would help promote consumer uptake. stimulated as a result of an appropriate combination It should also clarify what elements of CO 2 standards, LEV/ZEV incentives and would trigger greater demand for lowdemand-side measures, leading to economies of emission vehicles, leading to scale scale, a better market offer and the removal of economies in production. The report currently existing market barriers.

should make clear which assumptions Further information on the modelling approach and

are responsible for the respective

modelling outcomes. assumptions has been added in Annex 4, where reference is made to more detailed descriptions

which can be found in public literature.

The impact assessment should make The Commission will review the effectiveness of clear what has to complement the the legislation, including in terms of the setting of emission standards to turn competitiveness impacts. A mid-term review is technological leadership into job and foreseen, which will allow taking into account i.a. export opportunities for Europe, and the uptake of zero- and low-emissions vehicles, the what this would cost. It should also evolution of technology costs and the progress consider the risks that these made in establishing the necessary recharging complementary measures are not infrastructure. realised, and how the Commission will take this into account.

The report should clearly present the Section 6 of the report shows the detailed impacts trade-offs between CO 2 targets of the options considered in terms of CO 2 emission (environmental benefits), impacts on reduction, the costs for manufacturers, and the consumers, public finances and impacts savings from a societal perspective and for first and on the competitiveness of the EU car second end-users.

producers. As regards public finances, the macro-economic

assessment assumes revenue neutrality. Additional information on the impact on public finance has been added in Section 6.

1.3 Evidence

The Impact Assessment draws on evidence from the evaluation of Regulations 443/2009 i and 510/2011 on CO 2 emissions from light-duty vehicles 1 . The evaluation study provided a comprehensive assessment and concluded that the Regulations were overall effective, efficient and still relevant.

For the quantitative assessment of the economic, social and environmental impacts, the Impact Assessment report builds on a range of scenarios developed for the PRIMES-

TREMOVE model by ICCS-E3MLab. This analysis was complemented by applying other modelling tools, such as GEM-E3 and E3ME (for the macro-economic impacts) and the JRC DIONE model developed for assessing impacts at manufacturer (category) level (see Annex 4 for more details on the models used and other methodological considerations).

1 http://ec.europa.eu/clima/policies/transport/vehicles/docs/evaluation_ldv_co2_regs_en.pdf

Monitoring data on greenhouse gas emissions and other characteristics of the new light-duty vehicle fleet was sourced from the annual monitoring data as reported by Member States and collected by the European Environment Agency (EEA) under Regulations 443/2009 i and 510/2011 on CO 2 emissions from light-duty vehicles 2 .

1.4 External expertise

Further information was gathered through several support studies commissioned from external contractors, in particular addressing the following issues:

• the available technologies that can be deployed in the relevant time period to reduce new LDV CO 2 emissions, as well as their effectiveness and cost;

• elements potentially impacting industrial competitiveness and employment;

• growing gap between test and real driving emissions and the factors contributing to this;

• the impact of different regulatory approaches, regulatory metrics and possible design elements (modalities);

• impacts on GHG and pollutant emissions.

These studies were mainly run between 2014 and 2017 and the main ones are listed below:

• Data gathering and analysis to assess the impact of mileage on the cost effectiveness of the LDV CO 2 Regulations

• Improvements to the definition of lifetime mileage of light duty vehicles

• Improving understanding of technology and costs for CO 2 reductions from cars and LCVs in the period to 2030 and development of cost curves [to be published]

• Review of in-use factors affecting the fuel consumption and CO 2 emissions of passenger cars

• Supporting analysis on real-world light duty vehicle CO 2 emissions

• Data gathering and analysis to improve the understanding of 2nd hand car and LDV markets and implications for the cost effectiveness and social equity of LDV CO 2 regulations

• Assessment of the Modalities for Light Duty Vehicle CO 2 Regulations Beyond 2020 [to be published]

• Assessing the impacts of selected options for regulating CO 2 emissions from new passenger cars and vans after 2020 [to be published]

2 https://www.eea.europa.eu/data-and-maps/data/co2-cars-emission-12/#parentfieldname-title for cars and https://www.eea.europa.eu/data-and-maps/data/vans-8/#parent-fieldname-title for vans

2 A NNEX 2: S TAKEHOLDER CONSULTATION

2.1 Introduction

Stakeholders' views have been an important element of input to the revision of Regulation (EC) No 443/2009 i 3 and Regulation (EU) No 510/2011 i 4 . The main purpose of the consultation was to verify the accuracy of the information available to the Commission and to enhance its understanding of the views of stakeholders with regard to different aspects of the possible revision of the Regulations.

A mapping of stakeholders at the initial stages of the impact assessment allowed identifying the following relevant stakeholder groups:

• Member States (national, regional authorities)

• Vehicle manufacturers

• Component and materials suppliers

• Energy suppliers

• Vehicle purchasers (private, businesses, fleet management companies)

• Drivers associations

• Environmental, transport and consumer NGOs

• Social partners

The Commission sought feedback from stakeholders through the following elements:

• a public on-line consultation (20 July 2016 until 28 October 2016)

• a stakeholder workshop (24 March 2017) to present the results of the public consultation;

• a stakeholder workshop dedicated to jobs and skills (26 June 2017);

• meetings with relevant industry associations representing car manufacturers, components and materials suppliers, fuel suppliers.

• bilateral meetings with Member State authorities, vehicle manufacturers, suppliers, social partners and NGOs;

• position papers submitted by stakeholders or Member States.

A detailed summary and the results of the public consultation and the stakeholder workshop on jobs and skills are presented below.

3 Regulation (EC) No 443/2009 i of the European Parliament and of the Council of 23 April 2009 setting emission performance standards for new passenger cars as part of the Community's integrated approach to reduce CO 2 emissions from light-duty vehicles, OJ L 140, 5.6.2009, p. 1

4 Regulation (EU) No 510/2011 i of the European Parliament and of the Council of 11 May 2011 setting emission performance standards for new light commercial vehicles as part of the Union's integrated approach to reduce CO 2 emissions from light-duty vehicles, OJ L 145, 31.5.2011, p. 1

2.2 Public consultation

2.2.1 Process and quantitative results

An on-line public consultation was carried out between 20 July 2016 and 28 October 2016 on the EU Survey website 5 . The consultation was divided into two sections, the first of which asked questions of a general nature, including the need and objectives for EU action, while the second was of a more technical nature asking questions related to policy design and intended for a well-informed audience. Respondents were invited to choose whether to complete only the first or both sections. The key issues addressed reflect the key elements of the impact assessment as follows:

• The need and objectives for setting CO 2 emission targets for cars and vans after 2020

• Technology specific requirements

• Distribution of efforts between different actors

• Incentivising low- and zero-emission vehicles

• Modalities (eco-innovations and derogations)

The results of the public consultation are presented below for each key element. The replies are differentiated across stakeholder groups and summarised as factually as possible. The summary considers diverging views between or within stakeholder groups.

The consultation received 205 replies in total. The greatest number of responses (82 or 40%) were received from individuals. Civil society organisations, professional organisations and private enterprises all responded in fairly similar numbers, with 33 (16%), 31 (15%) and 28 (14%) responses respectively. Civil society organisations mainly included environmental and/or transport NGOs as well as consumer organisations. Professional organisations comprised mainly national and EU level associations representing the automotive sector and the fuels sector. Similarly, private enterprises included car manufacturers, suppliers in the automotive sector and fuels companies. Eleven public authorities from seven different Member States submitted replies, most of which operating at regional or local level. Table 1 summarises the distribution of respondents by category.

Table 1: Distribution of respondents by category

Category Number of Percentage of total number

respondents of respondents

Academic / Research institution 6 3%

Civil society organisation 33 16%

Individual / private person 82 40%

International organisation 4 2%

Private enterprise 28 14%

Professional organisation 31 15%

Public authority 11 5%

Other 10 5%

5 https://ec.europa.eu/clima/consultations/articles/0030_en .

Total 205 100%

Most responses were submitted from stakeholders based in Belgium (34), followed by Germany (26), the Netherlands and Denmark (17 each), France (15) and Hungary (13). Responses were received from all Member States, except for Croatia, Cyprus, Estonia, Malta and Slovakia. Six responses were received from stakeholders that were based outside the EU: Japan (4), Norway (1), and 'global' (1).

A stakeholder event was organised on 24 March 2017 in Brussels to inform stakeholders on the results of the on-line public consultation and to allow them to provide further feedback. The feedback received at the workshop was generally in line with stakeholders' views as submitted in the public consultation.

2.2.2 The need and objectives for setting CO 2 emission targets for cars and vans in the EU after 2020

When asked to assess the importance of setting CO 2 emission targets for new cars and light commercial vehicles to reduce emissions and contribute to meeting the EU's overall climate goals, most respondents across all stakeholder groups thought CO 2 emission targets for new cars and light commercial vehicles were 'important' or 'very important'. However, while all environmental and transport NGOs, consumer organisations, component suppliers, energy suppliers and public authorities (except for one regional authority) considered it 'very important', most car manufacturers considered it 'important'. Two car manufacturers and one petroleum company considered it 'somewhat important'.

There were mixed views on whether, without EU action, Member States would individually implement legislation. Most stakeholders representing the automotive sector 6 considered it likely that Member States would do so, whereas most environmental NGOs and consumer organisations considered it unlikely. Most respondents considered it likely (or were neutral) that this would lead to market fragmentation and higher costs. Only six individuals and one environmental NGO and one private enterprise considered this unlikely.

Policy objectives

Concerning the main policy objectives for future LDV CO 2 legislation, the following objectives were considered most important by the respondents:

• Continuing to reduce CO 2 emissions from LDVs cost-effectively and in line with EU climate and energy goals;

• Promoting the market update of LEV/ ZEV;

• Contributing to reducing air pollution.

The more detailed analysis shows that continuing to reduce CO 2 emissions from LDVs cost-effectively and in line with EU climate and energy goals was considered important by all but four respondents.

Ensuring technology neutrality was considered important by most respondents from the automotive sector (except for two car manufacturers who considered this objective unimportant). All public authorities that responded to the question considered this objective

6 Car manufacturers or associations representing the car manufacturing industry.

important. While one environmental NGO considered this important, most environmental and transport NGOs and consumer organisations considered technology neutrality unimportant.

Ensuring competitive neutrality between manufacturers was considered important (or neutral) by all but three respondents.

Preserving the competitiveness of EU automotive manufacturing was considered important by most professional associations and consumer organisations as well respondents from the EU automotive sector. One non-EU car manufacturer and some environmental and transport NGOs judged this objective as unimportant. Other environmental NGOs and non

European car manufacturers had a neutral position.

Ensuring that the legislation's impacts are socially equitable was considered important by all consumer organisations as well as most private enterprises.. Most environmental and transport NGOs and some professional organisations as well as public authorities were neutral on this objective.

The objective to promote the uptake of low-emission and zero-emission vehicles was considered important by most respondents while only three oil companies and one national car industry organisation considered it unimportant. Some car manufacturers and one car industry association, component suppliers as well as one public authority expressed a neutral position.

Contributing to reducing air pollution was considered important by almost all respondents.

Action to be taken

The respondents were asked about the form that action should take and the majority favoured LDV CO 2 emissions targets at the EU level. Among the stakeholder groups this action was the most preferred option by nearly all civil society organisations as well as by most public authorities that responded to this question. "Other" was the second most chosen option as preference which in many cases was also supporting a target at EU level but with some specific preference on timing or target level.

Target levels

The majority of respondents thought that targets should be set at a higher rate of reduction than under current regulations, only few stakeholders were in favour of a lower rate. Most environmental and transport NGOs and the majority of individual respondents were in favour of a higher rate of reduction than that required under the current Regulations. However, consumer organisations were mostly in favour of a similar rate of reduction as required under the current Regulations. Most public authorities were in favour of higher or similar reduction rates; none was in favour of lower reduction rates. A reduction rate lower than that required under the current Regulations was supported by the European car manufacturers association and individual car manufacturers, the European trade union representing workers in the manufacturing sector as well as some component suppliers.

Innovation and competitiveness

When asked about innovation and competitiveness, the majority of respondents thought that EU legislation to regulate CO 2 emissions would increase the competitiveness of EU industry on the global market or were neutral on that point. One national car industry association and stakeholders from the petroleum sector disagreed that it would enhance competitiveness. When asked whether EU legislation to regulate CO 2 emission for LDVs will increase the likelihood of the EU automotive industry developing further CO 2 reducing technology for conventional engines only four national associations representing different stakeholder groups disagreed. When asked whether future EU CO 2 legislation for LDVs would increase the likelihood of the EU industry developing technology for alternative powertrains, all stakeholders agreed or were neutral.

Social impacts

When considering social impacts, all consumer organisations, most environmental NGOs as well as several public authorities were of the opinion that LDV CO 2 legislation is likely to lead to benefits for lower income social groups and countries. Trade unions and stakeholders representing the petroleum industry largely disagreed with this statement. Most representatives of the automotive sector were neutral on this point. Most respondents were in favour of considering second hand LDV purchasers and cross-border trade in second hand vehicles when assessing the social impacts of the legislation, very few were opposed.

Regulatory aspects

Regarding the scope of the future CO 2 legislation nearly all car manufacturers were opposed (or neutral) to extending the scope to heavier vehicles (N2) or to include small light commercial vehicles. Most consumer organisations, stakeholders from the petroleum industry and public authorities were in favour of extending the scope.

As to whether cars and light commercial vehicles should be covered by the same Regulation a majority of respondents was in favour, but there was no clear trend among stakeholder groups except for car manufacturers and many consumer organisations which were against such an approach. Most stakeholders, including all car manufacturers, did not agree that manufacturers should be replaced by manufacturer groups as the regulated entity.

When asked whether the current Tank to Wheel (TTW) metric should be replaced by a Well to Wheel (WTW) metric, all but one of the stakeholders representing the fuels industry as well as some component suppliers supported such a change. By contrast, consumer organisations, car manufacturers and stakeholders from the power sector were mostly in favour of keeping the current TTW metric. Public authorities had mixed views.

The majority of all stakeholder groups was against (or neutral) changing the current approach based on CO 2 emissions to be replaced by an approach based on energy use.

In response to the question whether emissions occurring during manufacturing and at the time of disposal should be included, most car manufacturers were against this approach, whereas other stakeholder groups had diverging views.

Across all stakeholder groups there was very strong support for the Commission to explore which potential exists to further reduce the divergence between the test cycles and real world emissions. Only representatives of car manufacturers and one component supplier were against.

Similarly, all stakeholder groups supported additional driving tests to give values closer to real emissions except for car manufacturers and one component supplier who opposed this idea. More specifically, many environmental and transport NGOs, car drivers associations and public authorities from one Member State called for the extension of real-driving emission (RDE) tests to include CO 2 emissions, often in combination with a not-to-exceed limit.

The use of mass monitoring of fuel consumption in vehicles for monitoring purposes was opposed by car manufacturers and a national car drivers association and some local authorities, whereas environmental and transport NGOs were largely in favour of this. Consumer organisations, the automotive supply industry as well as the majority of public authorities were neutral on this issue.

2.2.3 Technology specific requirements

When asked whether manufacturers should be given the freedom to choose the mix of technologies and emission levels for their vehicles provided they meet the overall target set for them, the majority of all stakeholder groups and citizens were in favour of providing manufacturers with that freedom. Among the respondents all research institutions, consumer organisations, car manufacturers and public authorities supported such an approach. A comparatively small number of respondents were against.

There were rather mixed views across stakeholder groups on whether specific CO 2 targets for different fuel types or technologies should be set. While all car manufacturers and the majority of all stakeholder groups were not in favour of such specific targets, some environmental NGOs, some component suppliers, one oil company, and two public authorities supported specific targets. Consumer organisations were neutral on that point.

The majority in all stakeholder groups were in favour of continuing setting manufacturer's targets based on their sales weighted average registrations. All car manufacturers and consumer organisations were in favour, whereas car drivers associations were neutral on that issue. Some environmental NGOs and all respondents representing specifically the biogas sector were against continuing with the current target-setting approach.

Stakeholder views were very mixed on the question whether average mileage by fuel and vehicle segment should be taken into account when establishing targets A number of environmental and transport NGOs, some research institutions, and all respondents from the petroleum sector were in favour of that option. By contrast, one NGO and the majority of car manufacturers were against this option. Most consumer organisations were neutral on that issue, whereas public authorities were equally split on this issue.

2.2.4 Distribution of efforts between different actors

Most car manufacturers and consumer organisations were in favour of using a utility parameter to distribute the effort between different vehicle manufacturers (as in the current legislation). Most of the other respondents across different stakeholder groups were neutral on this question. A relatively small number of respondents from different stakeholder groups were against the use of a utility parameter.

When asked which utility parameter should be used, the majority of respondents did therefore not provide answer. Among those that provided an answer, all consumer organisations, some environmental and transport NGOs as well as stakeholders from the petroleum sector supported footprint as utility parameter. Most car manufacturers supported mass as utility parameter. One car manufacturer commented that any utility parameter should not discriminate against light-weighting efforts. Two stakeholders (a professional organisation and a national public authority) suggested that the loading capacity could be used for light commercial vehicles as utility parameter.

2.2.5 Incentivising low- and zero-emission vehicles

A majority of stakeholders across all stakeholder groups thought there should be a mechanism to encourage the deployment of low and zero emission vehicles (LEVs/ZEVs) except for consumer organisations which were mostly neutral on whether and how LEVs/ZEVs should be incentivised. Only one trade union, the works council of a German car manufacturer, two oil companies and one public authority were against such a mechanism.

A mandate to produce and sell a minimum proportion of LEVs/ZEVs was opposed by car manufacturers but supported by most environmental and transport NGOs. When asked what kind of incentive should be introduced for LEVs/ZEVs, most environmental and transport NGOs were in favour of a flexible mandate that differentiates between LEVs and ZEVs and allows trading among manufacturers. Some car manufacturers were in favour of super credits, one manufacturer referred to the need for public support for charging infrastructure. Public authorities were split on this issue.

Concerning the definition of LEVs/ZEVs, the majority of respondents across stakeholder groups supported the use of CO 2 emission performance as criterion but this was opposed by two environmental NGOs and two stakeholders representing natural gas based transport modes. Zero emission range (km) as criterion to define LEVs/ZEVs was opposed by a majority across stakeholder groups, while individuals were more in favour of this criterion. Some respondents, mostly environmental and transport NGOs, proposed a specific criterion on how to define LEVs with thresholds ranging from 15g/km to 50g/km (in 2030). However, one research institution argued that 50g/km was likely too high as it would overly incentivise plug-in hybrid vehicles with a very low electric driving range and therefore proposed 30g/km. The European car manufacturers association argued that the 50g/km (NEDC) threshold as currently used for super-credits should be used to define LEVs.

2.2.6 Modalities (eco-innovations and derogations)

A majority of stakeholders across all stakeholder groups was in favour of taking account of CO 2 emission reduction arising from the deployment of technology which reduces emissions in normal driving but whose benefit is not shown in the normal test cycle . A few environmental NGOs and public authorities were however against such an approach. When asked more specifically on how eco-innovations should be considered in the future legislation, only few respondents provided an answer. Environmental and transport NGOs were in favour of continuing the current eco-innovation scheme but some of them argued for measuring eco-innovation savings during real-driving emission tests for CO 2 . Some stakeholders, mainly representing the steel industry, argued that the eco-innovation scheme should be complemented with an LCA credit option. The European car manufacturers association argued for the revision of some of the thresholds currently set in the legislation and supported the introduction of a pre-defined list of off-cycle CO 2 reduction technologies as well as the inclusion of technologies that are affected by the driver's behaviour.

Concerning the current derogation regime, car manufacturers were broadly in support of its continuation. Most other stakeholders also supported the current derogation regime for small volume car manufacturers (less than 10 000 registrations per year), although some environmental NGOs and public authorities were opposed. By contrast, a majority of environmental and transport NGOs as well as all consumer organisations were against the continuation of the current derogation regime for niche manufacturers (10 000 to 300 000 car registrations per year). Most consumer organisations but also a trade union and a works council as well as some public authorities supported to base the derogation regime on worldwide sales instead of EU sales. There was no strong support to grant derogations for certain types of vehicles rather than for manufacturers.

2.3 Dedicated stakeholder event on jobs and skills

A stakeholder meeting dedicated on jobs and skills was organised on 26 June 2017. The objective of the meeting was to seek experts' and stakeholders' views to ensure that all aspects are well covered in the impact assessment. The meeting was structured in two panels followed by an open discussion to allow all participants to present their views. In the first panel authors of relevant studies presented the methodology and key conclusions of their analysis, whereas the second panel was composed of representatives of the main stakeholder groups (vehicle manufacturers, component and materials suppliers, trade union, environmental and transport NGO) allowing them to present their perspective.

The key messages of the meeting can be summarised as follows:

• Broad agreement that alternative powertrains will play an important role in the future. There is a need for new qualifications (upskilling) and also higher participation rates in light of the demographic changes.

• Taking a macroeconomic perspective, the uptake of alternative powertrains will help

consumers to save money (around EUR 500 p.a.) which they will spend in other

sectors which will in turn create employment due low employment intensity of the

refinery industry (around 500,000 net employment effect for EU).

• The creation of a large EU EV market with the help of ambitious policies will ensure that alternative powertrains will be manufactured in the EU with net job increase in the EU instead of importing alternative powertrains from other world regions with lead

markets already in place that attract the production of alternative powertrains.

• manufacturers are faced with several transformative challenges including digitalisation and alternative powertrains which all require major investments in the coming years

and new skills.

• SMEs provide a significant part of the employment and are faced with particular challenges to adjust to the new market.

• Labour intensity of ICE compared to BEV (7:1) coupled with lower maintenance requirements for BEVs (1 million BEVs reduce number of employees in maintenance by 1000).

• It is important to allow the workforce to adapt to the new qualification needs and to

make the transition socially fair, e.g. organise social dialogues and provide for

necessary supporting instruments.

• Impacts may be very different for different regions in the EU, e.g. regional clusters focussing on ICE.

The meeting was attended by more than 70 stakeholders representing all relevant stakeholder groups.

2.4 Use of the stakeholder input for the impact assessment

Stakeholder input received during the stakeholder consultation was an important tool during the impact assessment. The results from the analysis of the stakeholder input have been used to develop and assess the policy options. Statements or positions brought forward by certain stakeholders have been clearly highlighted as such.

3 A NNEX 3: W HO IS AFFECTED BY THE INITIATIVE AND HOW

The following key target groups of this initiative have been identified.

• Vehicle Manufacturers

• Suppliers of components and materials from which vehicles are constructed

• Users of vehicles, both individuals and businesses

• Suppliers of fuels and energy suppliers

• Vehicle repair and maintenance businesses

• Workforce

• Other users of fuel and oil-related products (e.g. chemical industry, heating)

• Society at large

The below table summarises how these target groups are affected by this policy initiative. In some cases the analysis showed overlaps between identified target groups (e.g. vehicle manufacturers and suppliers of components and materials) as a result of which certain effects may be repeated. Section 6 of the Impact Assessment provides a more detailed analysis on cost and benefits for the different target groups.

Type of Practical implications stakeholder

Vehicle Investment needs / manufacturing costs

Manufacturers CO

2 standards require vehicle manufacturers to reduce CO 2 emissions as a result of which they will have to introduce technical CO 2 reduction measures. In the short-term, this is likely to result in increased production costs and could affect the structure of their product portfolios. As a consequence, they will have increased investment costs for production capacity and new technologies.

Benefits

Demand for low- and zero-emission CO 2 vehicles is expected to increase throughout the world as climate change and air quality policies develop and other jurisdictions introduce similar or even more ambitious standards. European automotive manufacturers have an opportunity to gain first mover advantage and the potential to sell advanced low CO 2 vehicles in other markets, i.e. the new regulatory framework will help them to retain or even increase their global market in particular in markets for ZEV/LEV with very dynamic growth rates.

Cost / benefits

Manufacturers and suppliers are expected to largely benefit from increased revenues from the increase sales of low- and zero-emission vehicles, with revenues being distributed among businesses involved in the manufacturing, marketing and sales of vehicles (including vehicle dealers). Benefits will largely outweigh cost.

Suppliers of Investment costs / new technologies components and

Suppliers of components and materials from which vehicles are materials from

which vehicles are constructed will be affected by changing demands on them. Component

constructed suppliers have a key role in researching and developing technologies and marketing them to vehicle manufacturers. Investment costs will not

be evenly spread across the supply chain. In particular suppliers for conventional vehicle technologies will have to adapt. Manufacturers and suppliers will have to invest into higher production capacities and technology development. These suppliers will also have to invest in skilling their workforce.

Benefits

Requirements leading to the uptake of additional technologies or materials (e.g. aluminium, advanced construction materials) may create extra business activity for suppliers in these sectors. In particular suppliers for non-conventional vehicle technologies will largely benefit.

Users of vehicles, Transport costs/prices both individuals

and businesses The use of technology to reduce in-use GHG emissions has a cost which is expected to be passed on to the vehicle purchaser. The

purchase cost for new more fuel-efficient vehicles, in particular

zero/low emission vehicles, is expected to be higher compared to less

fuel-efficient vehicles.

Benefits

Reducing the vehicle's CO 2 emissions will reduce the energy required and in turn increase fuel cost savings for vehicle users. Over the vehicles' lifetime, operational cost savings, including lower O&M costs for battery electric vehicles, will compensate the higher procurement costs.

Suppliers of fuels Adjustment costs and energy

suppliers Suppliers of fuels are affected by reduced energy demand leading to less utilisation of existing infrastructure. If demand shifts to vehicles

supplied with alternative energy sources, this may potentially increase the need for other types of infrastructure and create new business opportunities and challenges for electricity supply companies and network operators.

Investment needs

Energy suppliers/grid operators will have to invest into grid expansion and innovative technologies (e.g. smart metering) to cope with increased demand from recharging of vehicles.

Benefits

There will be new business opportunities for (alternative) fuel suppliers and energy suppliers as a result of the increase in electricity demand from electric vehicles.

Vehicle repair With the uptake of battery electric vehicles there will be lower demand and maintenance for maintenance requirements which will negatively affect vehicle businesses repair and maintenance businesses. On the other hand, the uptake of

plug-in hybrid electric vehicles will increase the complexity of the vehicle technology and require at least the same vehicle repair and maintenance as conventional powertrains. Moreover, the repair and maintenance of plug-in hybrid electric vehicles will require additional skills to deal with the electric and electronic components.

Workforce The production and maintenance of vehicles with an electrified powertrain will pose important challenges to the workforce in the automotive sector including manufacturers and component suppliers as well as repair and maintenance businesses. The workforce will need additional and/or different skills ("upskilling" and "reskilling") to deal with new components and manufacturing processes.

Other users of Benefits from reduced oil prices

fuel and oil Other users of fuel and oil-related products (e.g. chemical industry,

related products heating) are expected to benefit from lower prices if demand from the

(e.g. chemical

industry, heating) transport sector decreases. Sectors other than transport that emit GHGs will avoid demands to further reduce emissions to compensate for

increased transport emissions. In so far as these sectors are exposed to competition, this will be important for their competitiveness.

Society at large Citizens, especially those living in urban areas with high concentrations of pollutants, will benefit from better air quality and less associated health problems due to reduced air pollutant emissions, in particular when the uptake of zero-emission vehicles increases.

4 A NNEX 4: A NALYTICAL MODELS USED IN PREPARING THE IMPACT ASSESSMENT

The analytical work underpinning this Impact Assessment uses a series of models: PRIMES- TREMOVE, E3ME, GEM-E3, JRC DIONE. They have a successful record of use in the Commission's transport, energy and climate policy impact assessments – including for the 2020 climate and energy package, the 2030 climate and energy policy framework, the ESR and EED proposals, and for the analytical work in the SWD of the Low Emission Mobility Strategy.

A brief description of each model is provided below.

4.1 PRIMES-TREMOVE transport model

PRIMES-TREMOVE is a private model that has been developed and is maintained by E3MLab/ICCS of National Technical University of Athens 7 , based on, but extending features of the open source TREMOVE model developed by the TREMOVE 8 modelling community. Part of the model (e.g. the utility nested tree) was built following the TREMOVE model 9 . Other parts, like the component on fuel consumption and emissions, follow the COPERT model. When used as a module which contributes to a broader PRIMES scenario, it can show how policies and trends in the field of transport contribute to economy wide trends in energy use and emissions. As module of the PRIMES energy system model, PRIMES-TREMOVE 10 has been successfully peer reviewed 11 , most recently in 2011 12 . PRIMES-TREMOVE has been used for the 2011 White Paper on Transport, Low Carbon Economy and Energy 2050 Roadmaps, the 2030 policy framework for climate and energy and more recently for the Effort Sharing Regulation, the review of the Energy Efficiency Directive, the recast of the Renewables Energy Directive and for the European strategy on low-emission mobility.

7 Source: http://www.e3mlab.National Technical University of Athens.gr/e3mlab/

8 Source: http://www.tmleuven.be/methode/tremove/home.htm

9 Several model enhancements were made compared to the standard TREMOVE model, as for example: for the number of vintages (allowing representation of the choice of second-hand cars); for the technology categories which include vehicle types using electricity from the grid and fuel cells. The model also incorporates additional fuel types, such as biofuels (when they differ from standard fossil fuel technologies), LPG and LNG. In addition, representation of infrastructure for refuelling and recharging are among the model refinements, influencing fuel choices. A major model enhancement concerns the inclusion of heterogeneity in the distance of stylised trips; the model considers that the trip distances follow a distribution function with different distances and frequencies. The inclusion of heterogeneity was found to be of significant influence in the choice of vehicle-fuels especially for vehicles-fuels with range limitations.

10 The model can be run either as a stand-alone tool (e.g. for the 2011 White Paper on Transport and for the 2016 Strategy on low-emission mobility) or fully integrated in the rest of the PRIMES energy systems model (e.g. for the Low Carbon Economy and Energy 2050 Roadmaps, for the 2030 policy framework for climate and energy, for the Effort Sharing Regulation, for the review of the Energy Efficiency Directive and for the recast of the Renewables Energy Directive). When coupled with PRIMES, interaction with the energy sector is taken into account in an iterative way.

11 Source: http://ec.europa.eu/clima/policies/strategies/analysis/models/docs/primes_model_2013-2014_en.pdf .

12 https://ec.europa.eu/energy/sites/ener/files/documents/sec_2011_1569_2.pdf

The PRIMES-TREMOVE transport model projects the evolution of demand for passengers and freight transport by transport mode and transport mean. It is a dynamic system of multiagent choices under several constraints, which are not necessarily binding simultaneously.

PRIMES-TREMOVE is suitable for modelling soft measures (e.g. eco-driving, deployment of Intelligent Transport Systems, labelling), economic measures (e.g. subsidies and taxes on fuels, vehicles, emissions, pricing of congestion and other externalities such as air pollution, accidents and noise; measures supporting R&D), infrastructure policies for alternative fuels (e.g. deployment of refuelling/recharging infrastructure for electricity, hydrogen, LNG, CNG) and regulatory measures.

Regulatory measures include EU Regulations No 443/2009 i and No 510/2011 setting CO 2 emission performance standards for new passenger cars and new light commercial vehicles.

PRIMES-TREMOVE 13 simulates the equilibrium of the transport market. It has a modular structure, featuring a module projecting demand for transportation services for passenger and freight mobility and a supply module deriving ways of meeting the demand.

The supply module projects the optimum technology and fuel mix to produce transportation services which meet demand. It includes a vehicle stock sub-module which considers stock of transport means inherited from previous time periods and determines the necessary changes to meet demand.

PRIMES-TREMOVE tracks car vintages and formulates the dynamics of vehicle stock turnover by combining scrapping and new registrations.

The supply module of PRIMES-TREMOVE interacts with the demand module through the so-called generalised prices of transportation (measured in Euro per passenger km). Different generalised prices are calculated for the various alternative trip possibilities included in the decision tree of the demand module (e.g. area, time, distance) by transport mode. When the generalised prices differ from the baseline scenario, the model determines the new demand (for each of the various possible trips) based on the price differential relative to the baseline scenario and the elasticities of substitution (different among the various options) by respecting the overall budget (microeconomic foundation).

Regarding the purchasing of new vehicles, a menu of technology options is considered; for private cars, the available technology portfolio includes different car sizes and different powertrain technologies and fuel types. The choice of car type follows the approach of discrete choice modelling. A Weibull functional form is used to determine the frequency of choice of a certain car type. The cost indices entering the Weibull function include several elements in two main categories: (1) internal costs, (2) perceived costs, i.e. market acceptance for each technology, range anxiety, density of the refueling/recharging infrastructure.

Internal costs (true payable costs) include all cost elements over the lifetime of the candidate transport means: purchasing cost, annual fixed costs for maintenance, insurance and ownership/circulation taxation, variable costs for fuel consumption depending on trip type and operation conditions, other variable costs including congestion fees, parking fees and tolled roads.

Market acceptance factors are used to simulate circumstances where consumers have risk avert behaviours regarding new technologies when they are still in early stages of market

13 Pelopidas Siskos, Pantelis Capros, Alessia DeVita (2015) CO 2 and energy efficiency car standards in the EU in the context of a decarbonisation strategy: A model-based policy assessment", Energy Policy, 84 (2015) 22–34.

deployment. Perception of risk usually concerns technical performance, maintenance costs and operation convenience. When market penetration exceeds a certain threshold, consumers imitating each other change behaviour and increasingly accept the innovative technologies giving rise to rapid market diffusion. Therefore, the model simulates reluctance to adopt new technologies in early stages of diffusion and more rapid market penetration in later stages. The decision-making is also influenced by the availability of infrastructure and the range provided by each vehicle technology. For the analysis in this impact assessment, the availability of infrastructure is assumed: no specific restriction of infrastructure availability allows to determine for each policy scenario the requirements in terms of infrastructure needed to support the projected market penetration of vehicles. In order to represent in a more refined manner the true effects of the range limitations of some vehicle technologies, the trip categories represented into the model are assumed to follow a frequency distribution of trip distances. The model assumes that decision makers compare the range possibilities of each vehicle technology for all classes of trip types and trip distances and applies cost penalties in case of mismatches between range limitations. Because of range anxiety issues, based on the frequency distribution of trips existing in the model, certain consumer categories observe high penalties when selecting vehicles with range limitations. For such trip profiles, electric vehicles are not a viable option.

When a CO 2 target for new cars and vans is set, a representative seller is assumed to offer to the market a variety of vehicle types which on average have to respect the target. The average performance against the standard is endogenously calculated depending on consumer choice of vehicle types. The average performance of the new fleet has to be below the value of the CO 2 standard. Otherwise, the representative seller increases the prices of non-complying vehicle types (in the form of a penalty). This penalty factor is estimated endogenously and depends on the difference between the value of the standard and the performance of the particular vehicle type. This procedure is repeated until average performance of the new fleet is below the value of the standard.

The PRIMES-TREMOVE model has been updated to handle a mandate on LEV shares, meaning that all manufacturers need to achieve a specific share of their total vehicle sales via sales of LEVs. The mandate is formulated similarly to the already existing implementation of the regulations regarding the emissions standards for new vehicle sales.

In a similar way, energy efficiency performance standards for all road transport modes are integrated in the model, setting an efficiency constraint on new vehicle registrations.

The current EURO standards on road transport vehicles are explicitly implemented and are important for projecting the future volume of air pollutants in the transport sector and determining the structure of the fleet.

The PRIMES-TREMOVE projections, used for the analysis presented in Section 6 of the Impact Assessment, include details for a large number of transport means, technologies and fuels (both conventional and alternative types), and their penetration in various transport market segments. They include details about greenhouse gas and air pollution emissions (e.g. NO x , PM, SO x , CO), final energy demand.

4.2 DIONE model (JRC)

The DIONE model suite is developed, maintained and run by the JRC. It has been used for the assessment of capital and operating costs presented in Chapter 6 of the Impact Assessment.

The suite consists of different modules, some of which developed specifically for the analysis in this Impact Assessment, such as:

• DIONE Fleet Impact Model

• DIONE Cost Curve Model

• DIONE Cross-Optimization Module

• DIONE Fuel and Energy Cost Module

• DIONE TCO and Payback Module

The technology costs and CO 2 saving potentials developed during the project "Supporting Analysis on Improving Understanding of Technology and Costs for CO 2 Reductions from Cars and LCVs in the Period to 2030 and Development of Cost Curves" 14 were used as an input to the DIONE Cost Curve Model. Hundreds of cost curves were developed and used for the Impact Assessment, covering ten powertrains (SI, CI, SI HEV, CI HEV, SI PHEV, SI REEV, CI PHEV, CI REEV, BEV, FCEV), 7 vehicle segments (small, lower medium, upper medium and large car; small medium and large LCV), and 4 cost scenarios (high, medium, low and very low for batteries).

On the basis of the defined cost curves, the DIONE Cross-Optimization Module determines the optimal (i.e. cost minimizing) CO 2 and energy consumption reduction for each manufacturer category, powertrain and segment, given the relevant targets, fleet compositions and cost curves. As the cost curves have positive first and second derivatives, this is a mathematical problem with a unique solution that can be solved by a standard optimization algorithm. Outputs from the Cross-Optimization Module are optimal CO 2 (for conventional vehicles and PHEV, REEV) or energy consumption (for BEV, FCEV) reduction (xopt) per manufacturer category, segment and powertrain and the corresponding manufacturing costs (copt), which represent the capital costs shown in Chapter 6 of the Impact Assessment.

The DIONE Energy Cost Module is used to calculate Fuel and Energy costs. For each manufacturer category, powertrain and segment, the WLTP energy consumption (MJ/km) is derived from the CO 2 emission reduction (to comply with the targets) using specific energy conversion factors. The WLTP energy consumption figures are converted to real world energy consumption by multiplying for the real world over WLTP uplift factors for each powertrain and segment, in 2025 and 2030.

The fuel and energy cost per powertrain and segment is calculated taking into account the specific energy consumption, the vehicles mileage, the fuel costs. Vehicle mileages per segment and powertrain as well as mileage profiles over vehicle lifetime are based on PRIMES-TREMOVE. Costs of conventional fuels, and electricity and hydrogen (EUR/MJ) are aligned with PRIMES-TREMOVE. They are discounted and weighted by powertrain / segment activity over vehicle age, such that they can be used as multiplicators within the calculation.

In the DIONE TCO (total cost of ownership) and Payback Module, technology costs and operating costs are aggregated, discounted and weighted where appropriate, to calculate total costs of ownership from an end-user and societal perspective.

14 https://ec.europa.eu/clima/sites/clima/files/transport/vehicles/docs/technology_results_web.xlsx

https://ec.europa.eu/clima/sites/clima/files/transport/vehicles/docs/technology_sources_web.xlsx

Table 2 shows the main assumptions made for the costs assessment by DIONE.

Table 2: Main assumptions made for the costs assessment by DIONE

Element Sub-category Assumption Notes

Discount Rate, Societal 4% This social discount rate is recommended % for Impact Assessments in the

Commission’s Better Regulation guidelines 15 .

End user (cars) 11% Consistent with the Reference Scenario 2016 16

End-user 9.5% Consistent with the Reference Scenario (LCVs) 2016

Period/age, Lifetime 15

years First end-user 0-5

Second end 6-10 user

Capital costs % sales Average marginal vehicle manufacturing weighted costs (including manufacturer cateogory

average from profit margins) calculated by DIONE for DIONE a given scenario.

Depreciation Based on CE Delft et al. (2017) 17

Mileage profile Total, and by The overall mileage is distributed over the age profile assumed lifetime of the vehicle in the

analysis, according to an age-dependant mileage profile estimated based on PRIMES-TREMOVE

Mark-up Cars 1.40 Used to convert total manufacturing costs factor to prices, including dealer margins,

logistics and marketing costs and relevant

LCVs 1.11 taxes. Consistent with values used in

previous IA analysis according to (TNO et al., 2011) 18 , (AEA/TNO et al., 2009) 19 .

15 See: http://ec.europa.eu/smart-regulation/guidelines/tool_54_en.htm

16 http://ec.europa.eu/energy/en/data-analysis/energy-modelling

17 CE Delft and TNO (2017) Assessment of the Modalities for LDV CO

2 Regulations beyond 2020 (report for the European Commission, DG CLIMA)

18 TNO, AEA, CE Delft, Ökopol, TML, Ricardo and IHS Global Insight (2011) Support for the revision of Regulation (EC) No 443/2009 i on CO 2 emissions from cars (report for the European Commission, DG CLIMA) - https://ec.europa.eu/clima/sites/clima/files/transport/vehicles/cars/docs/study_car_2011_en.pdf

19 AEA, TNO, CE Delft, Öko-Institut (2009) Assessment with respect to long term CO

2 emission targets for passenger cars and vans (report for the European Commission, DG CLIMA) - https://ec.europa.eu/clima/sites/clima/files/transport/vehicles/docs/2009_co2_car_vans_en.pdf

The mark-up for LCVs excludes VAT, as the vast majority of new purchases of LCVs are by businesses, where VAT is not applicable.

O&M costs By LDV % sales The calculation of the O&M costs is based segment, weighted on the assumptions made in powertrain type. average of PrimesTremove, which were used already

updated O&M for the Low Emission Mobility Strategy. costs. These are based on the TRACCS project database and have been revised in light of new evidence with respect to the costs for electrified powertrain types. The O&M costs are subdivided into three main

components: (1) annual insurance costs, (2) annual maintenance costs, (3) other ownership costs, mainly including fixed annual taxes. The maintenance and insurance costs comprise the largest shares of the overall total O&M costs. The O&M costs assumptions used are based on recent estimates for maintenance and insurance costs 20 . No assumption is made on the evolution of the O&M costs over time for a new vehicle of 2025 or 2030, due to lack of available quantitative data.

VAT % rate 20% Used to convert O&M costs including tax, to values excluding tax for social

perspective.

4.3 Macroeconomic models (E3ME and GEM-E3)

Two macroeconomic models have been used, representing two main different schools of economic thought. E3ME is a macro-econometric model, based on a post-Keynesian demanddriven non-optimisation non-equilibrium framework; GEM-E3 is a general equilibrium model that draws strongly on supply-driven neoclassical economic theory and optimising behaviour of rational economic agents who ensure that markets always clear 21 . GEM-E3 assumes that capital resources are optimally allocated in the economy (given existing tax "distortions"), and a policy intervention to increase investments in a particular sector (e.g. energy efficiency) is likely to take place at the expense of limiting capital availability, as a factor of production, for

20 Sources: Aviva. (2017). Your car insurance price explained. Retrieved from Aviva: http://www.aviva.co.uk/car-insurance/your-car-price-explained/ ; FleetNews. (2015). Electric vehicles offer big SMR cost savings. Retrieved from FleetNews: http://www.fleetnews.co.uk/fleet href="http://www.fleetnews.co.uk/fleet-management/environment/electric-vehicles-offer-big-smr-cost-savings">management/environment/electric-vehicles-offer-big-smr-cost-savings ; UBS. (2017). Q-Series: UBS Evidence Lab Electric Car Teardown – Disruption Ahead? UBS Global Research. Retrieved from https://neo.ubs.com/shared/d1BwmpNZLi/

21 Market clearance in GEM-E3 is achieved through the full adjustment of prices which allow supply to equal demand and thus a ‘general’ equilibrium is reached and maintained throughout the system.

other profitable sectors ("crowding out" effect). In other words, in GEM-E3, the total effect on the economy depends on the net effect of core offsetting factors, particularly between positive improved energy efficiency and economic expansion effects (Keynesian multiplier), on one hand, and negative economic effects stemming from crowding out, pressures on primary factor markets and competitiveness losses, on the other hand. A very detailed financial model has been added to GEM-E3 to represent the banking system, the bonds, the borrowing and lending mechanisms, projecting into the future interest rates of equilibrium both for public sector finance and for the private sector. This changes the dynamics of crowding out effects as opposed to standard CGE models without a banking sector. E3ME does not adhere to the ‘general’ equilibrium rule; instead demand and supply only partly adjust due to persistent market imperfections and resulting imbalances may remain a long-run feature of the economy. It also allows for the possibility of non-optimal allocation of capital, accounting for the existing spare capacity in the economy 22 . Therefore, the level of output, which is a function of the level of demand, may continue to be less than potential supply or a scenario in which demand increases can also see an increase in output.

While the macro-economic modelling takes into account the wider economic and employment effects for the different policy options for the CO 2 vans/cars regulation, it does not analyse trade balance effects (export/import of cars) as a result of changed competitiveness of individual manufacturers. This would require detailed knowledge on (1) the expertise, R&D capabilities and competitiveness of individual car manufacturers; (2) expected regulatory changes in third countries in a 2030 perspective 23 .

4.3.1 E3ME

E3ME is a computer-based model of Europe’s economies, linked to their energy systems and the environment. The model was originally developed through the European Commission’s research framework programmes in the 1990s and is now widely used in collaboration with a range of European institutions for policy assessment, for forecasting and for research purposes.

The model is run by Cambridge Econometrics, and its detailed description is available at https://www.camecon.com/wp-content/uploads/2016/09/E3ME-Manual.pdf.

The economic structure of E3ME is based on the system of national accounts, as defined by ESA95 (European Commission, 1996). In total there are 33 sets of econometrically estimated equations, also including the components of GDP (consumption, investment and international trade), prices, energy demand and materials demand. Each equation set is disaggregated by country and by sector.

The labour market is also covered in detail, with estimated sets of equations for labour demand, supply, wages and working hours. For the assessment of employment impacts across the different sectors, labour intensities (number of persons per unit of output) are based on Eurostat Structural Business Statistics (sbs_na_ind_r2). As a starting point, the labour intensity of battery manufacture (which is included in the electrical equipment manufacturing sector) at the EU28 level is around 3 jobs per €1 million output, compared to a labour

22 The degree of adjustment between supply and demand and the resulting imbalances are derived from econometric evidence of historical non-optimal behaviour based on the extensive databases and time-series underpinning the E3ME macro-econometric model.

23 In the analysis done with both the E3ME and with GEM-E3 models, there is no assumption made in terms of policy changes outside of Europe

intensity of around 5 jobs per €1 million output in the wider electrical equipment manufacturing sector. The labour intensity of the automotive sector (excluding the battery manufacturing) is about 3.5 jobs per €1 million output, reflecting a high labour intensity for manufacture of vehicle parts and engines (5 jobs per €1 million output) but lower labour intensity for the assembly of the vehicle itself (less than 2 jobs per €1 million output). The model also accounts for labour productivity improvements (i.e. the ratio of sectoral employment to gross output over the projection period), based on PRIMES projections for output by sector and CEDEFOP projections for employment by sector.

4.3.2 GEM-E3

The GEM-E3 model has been developed and is maintained by E3MLab/ICCS of National Technical University of Athens 24 , JRC-IPTS 25 and others. It is documented in detail but the specific versions are private. A full description of the model is available at https://ec.europa.eu/jrc/en/gem-e3/model

The model has been used by E3MLab/ICCS to provide the macro assumptions for the Reference scenario and for the policy scenarios. It has also been used by JRC-IPTS to assess macroeconomic impacts of target setting based on GDP per capita.

The GEM-E3 model is a multi-regional, multi-sectoral, recursive dynamic computable general equilibrium (CGE) model which provides details on the macro-economy and its interaction with the environment and the energy system. It is an empirical, large scale model, written entirely in structural form. GEM-E3 allows for a consistent comparative analysis of policy scenarios since it ensures that in all scenarios, the economic system remains in general equilibrium. In addition it incorporates micro-economic mechanisms and institutional features within a consistent macro-economic framework and avoids the representation of behaviour in reduced form. The model is built on rigorous microeconomic foundations and is able to provide in a transparent way insights on the distributional aspects of long-term structural adjustments. The GEM-E3 model is extensively used as a tool of policy analysis and impact assessment. It is updated regularly using the latest revisions of the GTAP database and Eurostat statistics for the EU Member States.

The version of the GEM-E3 model used for this Impact assessment features a significantly enhanced representation of the transport sector. The enhanced model version is referred to as GEM-E3T. The model is detailed regarding the transport sectors, representing explicitly transport by mode, separating private from business transport services, and representing in detail fuel production and distribution including biofuels linked to production by agricultural sectors.

GEM-E3 formulates separately the supply or demand behaviour of the economic agents who are considered to optimise individually their objective while market derived prices guarantee global equilibrium, allowing the consistent evaluation of distributional effects of policies. It also considers explicitly the market clearing mechanism and the related price formation in the energy, environment and economy markets: prices are computed by the model as a result of supply and demand interactions in the markets and different market clearing mechanisms, in addition to perfect competition, are allowed.

24 http://www.e3mlab.National Technical University of Athens.gr/e3mlab/

25 https://ec.europa.eu/jrc/en/institutes/ipts

GEM-E3 has a detailed representation of the labour markets being able to project effects on employment. Labour intensities for 2015 were calculated by dividing the full time jobs by the value of production of each sector. The economic and employment data are from the Eurostat database. For 2015, the direct labour intensity for conventional vehicle is 3.6 person per million output (excluding the number of persons required to produce all the intermediate inputs, which are accounted for in the respective sectors), while for electric vehicles it is 2.8 person per million output (excluding the number of persons required to produce all the intermediate inputs, which are accounted for in the respective sectors). Labour intensity projections are based on the results of the GEM-E3 that includes sectoral production and employment by 5-year period until 2050.

4.4 Baseline scenario

4.4.1 Scenario design, consultation process and quality assurance

The Baseline scenario used in this impact assessment builds on the EU Reference scenario 2016 but additionally includes few policy measures adopted after its cut-off date (end of 2014) and some updates in the technology costs assumptions.

Building an EU Reference scenario is a regular exercise by the Commission. It is coordinated by DGs ENER, CLIMA and MOVE in association with the JRC, and the involvement of other services via a specific inter-service group.

For the EU Reference scenario 2016, Member States were consulted throughout the development process through a specific Reference scenario expert group which met three times during its development. Member States provided information about adopted national policies via a specific questionnaire, key assumptions have been discussed and in each modelling step, draft Member State specific results were sent for consultation. Comments of Member States were addressed to the extent possible, keeping in mind the need for overall comparability and consistency of the results.

Quality of modelling results was assured by using state of the art modelling tools, detailed checks of assumptions and results by the coordinating Commission services as well as by the country specific comments by Member States.

The EU Reference scenario 2016 projects EU and Member States energy, transport and GHG emission-related developments up to 2050, given current global and EU market trends and adopted EU and Member States' energy, transport, climate and related relevant policies. "Adopted policies" refer to those that have been cast in legislation in the EU or in MS (with a cut-off date end of 2014 26 ). Therefore, the binding 2020 targets are assumed to be reached in the projection. This concerns greenhouse gas emission reduction targets as well as renewables targets, including renewables energy in transport. The EU Reference scenario 2016 provides projections, not forecasts. Unlike forecasts, projections do not make predictions about what the future will be. They rather indicate what would happen if the assumptions which underpin the projection actually occur. Still, the scenario allows for a consistent approach in the assessment of energy and climate trends across the EU and its Member States.

26 In addition, amendments to two Directives only adopted in the beginning of 2015 were also considered. This concerns notably the ILUC amendment to the Renewables Directive and the Market Stability Reserve Decision amending the ETS Directive.

The report "EU Reference Scenario 2016: Energy, transport and GHG emissions - Trends to 2050" 27 describes the inputs and results in detail. In addition, its main messages are summarised in the impact assessments accompanying the Effort Sharing Regulation 28 and the revision of the Energy Efficiency Directive 29 , and the analytical work accompanying the European strategy on low-emission mobility 30 .

PRIMES-TREMOVE is one of the core models of the modelling framework used for developing the EU Reference scenario 2016 and has also been used for developing the Baseline scenario of this impact assessment. The model was calibrated on transport and energy data up to year 2013 from Eurostat and other sources.

4.4.2 Main assumptions of the Baseline scenario

The projections are based on a set of assumptions, including on population growth, macroeconomic and oil price developments, technology improvements, and policies.

Macroeconomic assumptions

The Baseline scenario uses the same macroeconomic assumptions as the EU Reference scenario 2016. The population projections draw on the European Population Projections (EUROPOP 2013) by Eurostat. The key drivers for demographic change are: higher life expectancy, convergence in the fertility rates across Member States in the long term, and inward migration. The EU28 population is expected to grow by 0.2% per year during 2010- 2030 (0.1% for 2010-2050), to 516 million in 2030 (522 million by 2050). Elderly people, aged 65 or more, would account for 24% of the total population by 2030 (28% by 2050) as opposed to 18% today.

GDP projections mirror the joint work of DG ECFIN and the Economic Policy Committee, presented in the 2015 Ageing Report 31 . The average EU GDP growth rate is projected to remain relatively low at 1.2% per year for 2010-2020, down from 1.9% per year during 1995- 2010. In the medium to long term, higher expected growth rates (1.4% per year for 2020-2030 and 1.5% per year for 2030-2050) are taking account of the catching up potential of countries with relatively low GDP per capita, assuming convergence to a total factor productivity growth rate of 1% in the long run.

Fossil fuel price assumptions

Oil prices used in the Baseline scenario are the same with those of the EU Reference scenario 2016. Following a gradual adjustment process with reduced investments in upstream productive capacities by non-OPEC 32 countries, the quota discipline is assumed to gradually improve among OPEC members and thus the oil price is projected to reach 87 $/barrel in 2020 (in year 2013-prices). Beyond 2020, as a result of persistent demand growth in non

27 ICCS-E3MLab et al. (2016), EU Reference Scenario 2016: Energy, transport and GHG emissions - Trends to 2050

28 SWD(2016) 247

29 SWD(2016) 405

30 SWD(2016) 244

31 European Commission/DG ECFIN (2014), The 2015 Ageing Report: Underlying Assumptions and Projection Methodologies, European Economy 8/2014.

32 OPEC stands for Organization of Petroleum Exporting Countries.

OECD countries driven by economic growth and the increasing number of passenger cars, oil price would rise to 113 $/barrel by 2030 and 130 $/barrel by 2050.

No specific sensitivities were prepared with respect to oil price developments. Still, it can be recalled that lower oil price assumptions tend to increase energy consumption and CO 2 emissions not covered by the ETS. The magnitude of the change would depend on the price elasticities and on the share of taxation, like excise duties, in consumer prices. For transport, the high share of excise duties in the consumer prices act as a limiting factor for the increase in energy consumption and CO 2 emissions.

Techno-economic assumptions

For all transport means, except for light duty vehicles (i.e. passenger cars and light commercial vehicles), the Baseline scenario uses the same technology costs assumptions as the EU Reference scenario 2016.

For light duty vehicles, the data for technology costs and emissions savings has been updated based on a recent study commissioned by DG CLIMA 33 . Battery costs for electric vehicles are assumed to go down to 205 euro/kWh by 2030 and 160 euro/kWh by 2050; further reductions in the cost of both spark ignition gasoline and compression ignition diesel are assumed to take place. Technology cost assumptions are based on extensive literature review, modelling and simulation, consultation with relevant stakeholders, and further assessment by the Joint Research Centre (JRC) of the European Commission.

Specific policy assumptions

The key policies included in the Baseline scenario, similarly to the EU Reference scenario 2016, are 34 :

• CO 2 standards for cars and vans regulations (Regulation (EC) No 443/2009 i, amended by Regulation (EU) No 333/2014 i and Regulation (EU) No 510/2011 i, amended by Regulation (EU) No 253/2014 i); CO 2 standards for cars are assumed to be 95 gCO 2 /km as of 2021 and for vans 147 gCO 2 /km as of 2020, based on the NEDC test cycle, in line with current legislation. No policy action to strengthen the stringency of the target is assumed after 2020/2021.

• The Renewable Energy Directive (Directive 2009/28/EC i) and Fuel Quality Directive (Directive 2009/30/EC i) including ILUC amendment (Directive 2015/1513 i/EU): achievement of the legally binding RES target for 2020 (10% RES in transport target) for each Member State, taking into account the use of flexibility mechanisms when relevant as well as of the cap on the amount of food or feed based biofuels (7%). Member States' specific renewable energy policies for the heating and cooling sector are also reflected where relevant.

• Directive on the deployment of alternative fuels infrastructure (Directive 2014/94 i/EU).

• Directive on the charging of heavy goods vehicles for the use of certain infrastructures (Directive 2011/76 i/EU amending Directive 1999/62/EC i).

33 Ricardo Energy and Environment (2016) Improving understanding of technology and costs for CO

2

reductions from cars and LCVs in the period to 2030 and development of cost curves (report for the European Commission, DG CLIMA)

34 For a comprehensive discussion see the Reference scenario report: “EU Reference Scenario 2016: Energy, transport and GHG emissions - Trends to 2050”

• Relevant national policies, for instance on the promotion of renewable energy, on fuel and vehicle taxation, are taken into account.

In addition, a few policy measures adopted after the cut-off date of the EU Reference scenario 2016 at both EU and Member State level, have been included in the Baseline scenario:

• Directive on weights & dimensions (Directive 2015/719 i/EU);

• Directive as regards the opening of the market for domestic passenger transport services by rail and the governance of the railway infrastructure (Directive 2016/2370 i/EU);

• Directive on technical requirements for inland waterway vessels (Directive 2016/1629 i/EU), part of the Naiades II package;

• Regulation establishing a framework on market access to port services and financial transparency of ports 35 ;

• The replacement of the New European Driving Cycle (NEDC) test cycle by the new Worldwide harmonized Light-vehicles Test Procedure (WLTP) has been implemented in the Baseline scenario, drawing on work by JRC. Estimates by JRC show a WLTP to NEDC CO 2 emissions ratio of approximately 1.21 for cars when comparing the salesweighted fleet-wide average CO 2 emissions. WLTP to NEDC conversion factors are considered by individual vehicle segments, representing different vehicle and technology categories 36 .

• For Germany, an extension of the toll network by roughly 40,000 kilometres of federal trunk road from 2018 onwards for all heavy goods vehicles over 7.5t. 37

• For Austria, the incorporation of exhaust emissions and noise pollution in the distance based charges. All federal highways and motorways, totalling around 2,200 km, are subject to distance based charges.

• For Belgium, a distance based system replaced the former Eurovignette for heavy goods vehicles over 3.5t from April 2016. The system applies to all inter-urban motorways, main (national) roads 38 and all urban roads in Brussels.

• For Latvia, the introduction of a vignette system applied for goods vehicles below 3.5t on the motorways, starting with 1 January 2017. In addition, for all heavy goods vehicles over 3.5t the vignette rates applied on motorways for the EURO 0, EURO I, EURO II are increased by 10% starting with 1 January 2017.

4.4.3 Summary of main results of the Baseline scenario

EU transport activity is expected to continue growing under current trends and adopted policies beyond 2015, albeit at a slower pace than in the past. Freight transport activity for inland modes is projected to increase by 36% between 2010 and 2030 (1.5% per year) and 60% for 2010-2050 (1.2% per year). Passenger traffic growth would be slightly lower than for freight at 23% by 2030 (1% per year) and 42% by 2050 (0.9% per year for 2010-2050). The

35 Regulation (EU) 2017/352

36 See Annex 4.6

37 Currently, 15,000 kilometres of federal trunk road and motorways are subject to tolls.

38 E.g. http://www.viapass.be/fileadmin/viapass/documents/download/VlaanderenE.JPG

annual growth rates by mode, for passenger and freight transport, are provided in Error! Reference source not found. 39 .

Road transport would maintain its dominant role within the EU. The share of road transport in inland freight is expected to slightly decrease at 70% by 2030 and 69% by 2050. The activity of heavy goods vehicles expressed in tonnes kilometres is projected to grow by 35% between 2010 and 2030 (56% for 2010-2050) in the Baseline scenario, while light goods vehicles activity would go up by 27% during 2010-2030 (50% for 2010-2050). For passenger transport, road modal share is projected to decrease by 4 percentage points by 2030 and by additional 3 percentage points by 2050. Passenger cars and vans would still contribute 70% of passenger traffic by 2030 and about two thirds by 2050, despite growing at lower pace (17% for 2010-2030 and 31% during 2010-2050) relative to other modes, due to slowdown in car ownership increase which is close to saturation levels in many EU15 Member States and shifts towards rail.

Figure 1: Passenger and freight transport projections (average growth rate per year)

Passenger transport Freight transport

3.0% 3.0%

2.5% 2.5%

2.0% 2.0%

1.5% 1.5%

1.0% 1.0%

0.5% 0.5%

0.0% 0.0%

Road Rail Aviation Inland Road Rail Inland navigation

-0.5% navigation -0.5%

-1.0% -1.0%

'95-'10 '10-'30 '30-'50 '95-'10 '10-'30 '30-'50

Source: Baseline scenario, PRIMES-TREMOVE transport model (ICCS-E3MLab)

Note: For aviation, domestic and international intra-EU activity is reported, to maintain the comparability with reported statistics.

Rail transport activity is projected to grow significantly faster than for road, driven in particular by the opening of the market for domestic passenger rail transport services and the effective implementation of the TEN-T guidelines, supported by the CEF funding, leading to the completion of the TEN-T core network by 2030 and of the comprehensive network by 2050. Passenger rail activity goes up by 44% between 2010 and 2030 (84% for 2010-2050), increasing its modal share by 1 percentage point by 2030 and an additional percentage point by 2050. Rail freight activity grows by 51% by 2030 and 90% during 2010-2050, resulting in 2 percentage points increase in modal share by 2030 and an additional percentage point by 2050.

Domestic and international intra-EU air transport would grow significantly (by 59% by 2030 and 118% by 2050) and increase its share in overall transport demand (by 3 percentage points

39 Projections for international maritime and international extra-EU aviation are presented separately and not included in the total passenger and freight transport activity to preserve comparability with statistics for the historical period.

by 2030 and by additional 2 percentage points by 2050). Overall, aviation activity including international extra-EU flights is projected to go up by 60% by 2030 and 124% by 2050, saturating European skies and airports.

Transport activity of freight inland navigation 40 also benefits from the completion of the TEN-T core and comprehensive network, the promotion of inland waterway transport and the recovery in the economic activity and would grow by 26% by 2030 (1.2% per year) and by 46% during 2010-2050 (0.9% per year).

International maritime transport activity is projected to continue growing strongly with rising demand for oil, coal, steel and other primary resources – which would be more distantly sourced – increasing by 37% by 2030 and by 71% during 2010-2050.

Transport accounts today for about one third of final energy consumption. In the context of growing activity, energy use in transport is projected to decrease by 5% between 2010 and 2030 and to stabilise post-2030 (see Figure 2). These developments are mainly driven by the implementation of the Regulations setting emission performance standards for new light duty vehicles. Light duty vehicles are currently responsible for around 60% of total energy demand in transport but this share is projected to significantly decline over time, to 53% by 2030 and 49% by 2050. Energy use in passenger cars and passenger vans is projected to go down by 19% during 2010-2030 (-24% for 2010-2050). Heavy goods vehicles are projected to increase their share in final energy demand from 2010 onwards, continuing the historic trend from 1995. Energy demand by heavy goods vehicles would grow by 14% between 2010 and 2030 (23% for 2010-2050).

Bunker fuels for air and maritime transport are projected to increase significantly: by 17% by 2030 (33% for 2010-2050) and 24% by 2030 (42% for 2010-2050), respectively.

Figure 2: Evolution of total final energy consumption and GHG emissions for 1995-2050

Final energy demand (Mtoe) Total GHG emissions (Mt of CO2-eq)

1,200 5,400

1,000 4,500

800 3,600

600 2,700

400 1,800

200 900

0 0

95 00 05 10 15 20 25 30 35 40 45 50

19 20 20 20 20 20 20 20 20 20 20 20 95 00 05 10 15 20 25 30 35 40 45 50 19 20 20 20 20 20 20 20 20 20 20 20

Energy industries Industry

Industry Residential Tertiary Transport Residential & tertiary Transport

Non-CO2 emissions

Source: Baseline scenario, PRIMES model (ICCS-E3MLab)

Electricity use in transport is expected to increase steadily as a result of further rail electrification and the uptake of alternative powertrains in road transport. Battery electric and plug-in hybrid electric vehicles are expected to see faster growth beyond 2020, in particular in the segment of light duty vehicles, driven by EU and national policies offering various incentives and the decrease in battery costs. The share of battery electric and plug-in hybrid

40 Inland navigation covers inland waterways and national maritime.

electric vehicles in the total light duty vehicle stock would reach about 6% by 2030 and 15% by 2050 (with the shares of battery electric being 2% in 2030 and 6% in 2050). The uptake of hydrogen would be facilitated by the increased availability of refuelling infrastructure, but its use would remain limited in lack of additional policies beyond those assumed in the Baseline scenario. Fuel cells would represent about 3% of the light duty vehicle stock by 2050.

LNG becomes a candidate energy carrier for road freight and waterborne transport, especially in the medium to long term, driven by the implementation of the Directive on the deployment of alternative fuels infrastructure and the revised TEN-T guidelines which represent important drivers for the higher penetration of alternative fuels in the transport mix. In the Baseline scenario, the share of LNG is projected to go up to 3% by 2030 (8% by 2050) for road freight and 4% by 2030 (7% by 2050) for inland navigation. LNG would provide about 4% of maritime bunker fuels by 2030 and 10% by 2050 – especially in the segment of short sea shipping.

Biofuels uptake is driven by the legally binding target of 10% renewable energy in transport (Renewables Directive), as amended by the ILUC Directive, and by the requirement for fuel suppliers to reduce the GHG intensity of road transport fuel by 6% (Fuel Quality Directive). Beyond 2020, biofuel levels would remain relatively stable at around 6% in the Baseline scenario. The Baseline scenario does not take into account the recent proposal by the Commission for a recast of the Renewables Energy Directive.

In the Baseline scenario, oil products would still represent about 90% of the EU transport sector needs in 2030 and 85% in 2050, despite the renewables policies and the deployment of alternative fuels infrastructure which support some substitution effects towards biofuels, electricity, hydrogen and natural gas (see Figure 3.

Figure 3: Evolution of final energy use in transport by type of fuel

400 Electricity & hydrogen

350 Gas & biomethane

300 Biofuels

LPG

250 Fuel oil

e

to 200 Jet fuel

M Diesel

150 Gasoline

100

50

0 2010 2015 2020 2025 2030 2035 2040 2045 2050

Source: Baseline scenario, PRIMES-TREMOVE transport model (ICCS-E3MLab)

The declining trend in transport emissions is expected to continue, leading to 13% lower emissions by 2030 compared to 2005, and 15% by 2050. 41 However, relative to 1990 levels, emissions would still be 13% higher by 2030 and 10% by 2050, owing to the fast rise in the transport emissions during the 1990s. The share of transport in total GHG emissions would

41 Including international aviation but excluding international maritime and other transportation.

continue increasing, going up from 23% currently (excluding international maritime) to 25% in 2030 and 31% in 2050, following a relatively lower decline of emissions from transport compared to power generation and other sectors (see Figure 2). Aviation would contribute an increasing share of transport emissions over time, increasing from 14% today to about 18% in 2030 and 21% in 2050. Maritime bunker fuel emissions are also projected to grow strongly, increasing by 22% during 2010-2030 (38% for 2010-2050).

CO 2 emissions from road freight transport (heavy goods and light goods vehicles) are projected to increase by 6% between 2010 and 2030 (11% for 2010-2050) in the Baseline scenario. For heavy goods vehicles, the increase would be somewhat higher (10% for 2010- 2030 and 17% for 2010-2050), in lack of specific measures in place. At the same time, emissions from passenger cars and passenger vans are projected to decrease by 22% between 2010 and 2030 (32% for 2010-2050) thanks to the CO 2 standards in place and the uptake of electromobility. CO 2 emissions from buses and coaches are projected to remain relatively unchanged by 2030 compared to their 2010 levels, and to slightly increase post-2030 (3% increase for 2010-2050).

The overall trend in transport emissions is determined by three broad components: transport activity levels (expressed in passenger or tonne-kilometres), the energy intensity of transport (defined as energy consumption per passenger or tonne-kilometre) and the carbon intensity of the energy used (given by the CO 2 emissions divided by energy consumption). Following this approach, it has been evaluated how much the projected transport emissions will increase/decrease (in percentage terms or Mt of CO 2 ) between 2010 and 2030 due to transport activity growth, improvements in energy intensity and carbon intensity. 42,43

Overall, CO 2 emissions from passenger transport decrease by 14% (109 Mt of CO 2 ) between 2010 and 2030 in the Baseline scenario. The 14% decrease in CO 2 emissions from passenger transport is due to transport activity growth (+21%, equivalent to 165 Mt of CO 2 ), improvements in energy intensity (-31%, equivalent to 246 Mt of CO 2 ) and in carbon intensity (-4%, equivalent to 28 Mt of CO 2 ). The trend for the three components and their contribution to emissions is different by transport mode. Efficiency gains play a decisive role in reducing emissions in road transport, while in aviation they would not offset the activity growth leading to higher fuel use and emissions. The use of less CO 2 intensive fuels contributes to a reduction of emissions for road and rail passenger transport with no effect on aviation by 2030.

For freight transport, the 5% (13 Mt of CO 2 ) increase in CO 2 emissions between 2010 and 2030 is the result of transport activity growth (+30%, equivalent to 75 Mt of CO 2 ), improvements in energy intensity (-20%, equivalent to 49 Mt of CO 2 ) and in carbon intensity (-5%, equivalent to 13 Mt of CO 2 ). The efficiency gains and the uptake of alternative fuels for road freight transport are not sufficient to offset the effects of activity growth, and thus CO 2 emissions go up between 2010 and 2030. The electrification in rail has positive effects on emissions, despite the growth in traffic volumes. For inland navigation, efficiency gains and to some lower extent the uptake of LNG has also positive effects on emissions reduction.

42 The proposed method is the Montgomery decomposition. For a recent application of the method see: De Boer, P.M.C. (2008) Additive Structural Decomposition Analysis and Index Number Theory: An Empirical Application of the Montgomery Decomposition, Economic Systems Research, 20(1), pp. 97-109.

43 The decomposition analysis only takes into account the tank to wheel emissions, under the assumption that biofuels are carbon neutral.

NOx emissions would drop by about 56% by 2030 (64% by 2050) with respect to 2010 levels. The decline in particulate matter (PM2.5) would be less pronounced by 2030 at 51% (65% by 2050). By 2030, over 75% of heavy goods vehicle stock is projected to be Euro VI in the Baseline scenario and more than 80% of the passenger cars stock is projected to be Euro 6. Overall, external costs related to air pollutants would decrease by about 56% by 2030 (65% by 2050). 44

Noise related external costs of transport would continue to increase, by about 17% during 2010-2030 (24% for 2010-2050), driven by the rise in traffic. Thanks to policies in place, external costs of accidents are projected to go down by about 46% by 2030 (-42% for 2010- 2050) – but still remain high at over €100 billion in 2050. Overall, external costs 45 are projected to decrease by about 10% by 2030 and to increase post-2030; by 2050 they stabilise around levels observed in 2010.

Figure 4: Decomposition of CO 2 emissions in the Baseline scenario (2010-2030)

Passenger transport

TOTAL COMPONENTS

150

100 14% 51%

50 17% 31%

2

O 0% 0

f C Change in CO2 emissions Activity Energy intensity CO2 intensity

t o

M -50 -18% -4% -42%

-29% -34% -100

-150 -21%

-200 -31%

-250

Road Rail Aviation

44 External costs are expressed in 2013 prices. They cover NOx, PM2.5 and SOx emissions.

45 External costs cover here air pollution, congestion, noise and accidents.

Freight transport

80 31%

TOTAL COMPONENTS

60

40

2

O 20 6%

f C 39% 23% t o

M 0 Change in CO2 emissions Activity Energy intensity Carbon intensity

-20 -3% -15% -17% -4% -32% -9% -8%

-40

-20% -60

Road Rail Inland navigation

Source: EC elaboration based on the Baseline scenario, PRIMES-TREMOVE transport model (ICCS-E3MLab)

Note: The figures report the changes in CO 2 emissions due to the three broad components (transport activity levels, energy intensity of transport and carbon intensity of the energy used) in two ways: in levels and in relative terms compared to 2010. The size of each column bar, read on the left axis, represents the change in terms of CO 2 emissions compared to 2010, expressed in Mt of CO 2 . The percentage changes reported above the column bars represent relative changes in these emissions compared to their respective 2010 levels. Provided that CO 2 levels for 2010 corresponding to each transport mode are not comparable in size, the percentage changes reported in the figures are not directly comparable. The figures above include only tank to wheel emissions.

4.5 Consistency with previous analytical work

A consistency check was performed between the policy scenarios used for this impact assessment and the "EUCO30" scenario 46 , which is underlying several Commission climate, energy and transport policy proposals adopted in 2016. This scenario corresponds in particular with the achievement of the EU-wide 2030 targets regarding greenhouse gas emissions in the ESR sectors and regarding final energy demand.

In addition to the LDV related policies, a number of broader, transport and fuel related policies 47 were accounted for in order to allow a direct comparison of the results.

The tables below show a comparison between the EUCO30 scenario, and a scenario where the fleet wide targets for cars and vans are set at the levels of TLC30 and TLV25 (referred to as TL30c/25v). 48

As the TL30c/25v scenario used for this impact assessment focuses on the LDV related policies, of the aforementioned broader, transport and fuel related policies 47 had to be accounted for in order to allow a direct comparison of the PRIMES-TREMOVE outputs with those of EUCO30. This is what is referred to below as the " TL30c/25v+" scenario.

Table 3 provides a comparison of emissions from the sectors covered by the ESR for those scenarios, under the assumption that changes in emissions only occur in the transport sector (emission levels remaining the same in all other ESR sectors).

Table 3: Comparison of ESR emissions (Mt CO 2 ) across scenarios

2005 2030

EUCO30 TL30c/25v TL30c/25v+

ESR emissions [Mt CO 2 ] 2,848 1,985 2,014 1,999

% change from 2005 -30.3% -29.3% -29.8%

In EUCO30, ESR emissions fall by 30.3% in 2030 compared to 2005 levels, which is in line with the 30% target. In the new TL30c/25v scenario, this reduction becomes 29.3% and, after including all EUCO30 transport related policies and taking account of the Renewable Energy Directive revision (TL30c/25v+), reductions are 29.8%.

46 The EUCO30 scenario is a key input to several Commission documents adopted in 2016: Impact Assessment underpinning the Proposal for the Effort Sharing Regulation, Staff Working Document accompanying the Communication on the low-emission mobility strategy, Impact Assessment accompanying the proposal for recast of the Directive on the promotion of energy from renewable sources, Impact Assessment accompanying the proposal for a revised Energy Efficiency Directive. ( https://ec.europa.eu/energy/sites/ener/files/documents/20170125_- _technical_report_on_euco_scenarios_primes_corrected.pdf )

47 These concern eco-driving, Cooperative Intelligent Transport Systems (C-ITS), internalisation of transport externalities, road infrastructure charges for Heavy Goods Vehicles. Concerning fuel policies, the TLC30c/25v and the EUCO30 scenario assume that the 27% target for renewable energy in 2030 is met; scenario TLC30c/25v+ assumes in addition that the specific shares for renewable energy sources used in transport set in Article 7 of the Renewable Energy Directive Proposal for post 2020 are also met ..

48 For the comparison with the EUCO30 scenario, the scenario was chosen for which the CO 2 targets for the new fleet are consistent with those applied for EUCO30.

As shown in Table 4, the difference between EUCO30 and the new policy scenarios is solely due to road transport, where CO 2 emissions in 2030 are 29 Mt higher under the TL30c/25v and 14 Mt under the TL30c/25v+ scenario.

Table 4: Comparison of transport emissions between EUCO30 and new TL30c/25v scenarios in 2030 (Mt CO 2 )

2030 emissions Difference between

EUCO30 TL30c/25v TL30c/25v+ TL30c/25v TL30c/25v+ and and

EUCO30 EUCO30

Transport total 871 900 885 29 14

Road transport 674 703 687 29 13

Cars 346 375 368 29 22

Vans 91 88 86 -3 -5

Other road transport 237 240 233 3 -4

Another consistency check with EUCO30 concerns the Energy Efficiency target (30%) 49 for 2030. The difference in final energy demand in transport between the TL30c/25v, TL30c/25v+ and EUCO30 in 2030 is 8 ktoe and 5 ktoe, respectively (Table 5). As these differences are very small compared to the “Gross Inland Consumption (GIC) of energy (minus non-energy uses)”, it can be concluded that the energy efficiency target is also respected under the new policy scenarios.

Table 5: Final energy demand in EU-28 (ktoe)

2007 2030

baseline EUCO30 TL30c/25v TL30c/25v+

Final energy demand in transport [ktoe] 322 329 326

Difference with EUCO30 - 8 5

GIC for energy 1,887 1,321 1,329 1,326

(-30.0%) (-29.6%) (-29.7%)

Table 6 shows a comparison for road transport based on the changes of emission reduction and final energy savings with respect to EUCO30.

Table 6: Greenhouse gas savings from 30% reduction in CO 2 standards for cars

Scenario Emissions savings Lower emission Higher final 2005-2030 savings in 2030 energy demand

EUCO30 24.7%

49 30% primary energy consumption reduction (i.e. achieving 1321 Mtoe in 2030) compared to the 2007 baseline (1887 Mtoe in 2030). This means a reduction of primary energy consumption of 23% compared to 2005 (1713 Mtoe in 2005).

TL30c/25v 21.3% -3.4% +3.2%

TL30c/25v+ 23.0% -1.7% +2.1%

4.6 Determination of conversion factors from NEDC to WLTP emission values

JRC Science for Policy Report "From NEDC to WLTP: effect on the type-approval CO 2 emissions of light-duty vehicles" (Tsiakmakis, S. Fontaras, G., Cubito, C., Anagnostopoulos, K., J. Pavlovic, Ciuffo, B. (2017), publication pending)

EXECUTIVE SUMMARY

This study aimed at analysing the impact on the European light duty vehicle fleet CO 2 emissions of the introduction of the Worldwide Light duty vehicle Test Procedure (WLTP) in the European vehicle type-approval process. The calculations made for conventional vehicles rely mainly on the use of the PyCSIS (Passenger Car fleet emissions SImulator) model, which was developed on the basis of CO 2 MPAS (CO 2 Model for PAssenger and commercial vehicles Simulation), the model used in the phasing-in of the WLTP for the adaptation of the CO 2 targets for light duty vehicles to the new test procedure 50 . However, while CO 2 MPAS depends on the test results of individual vehicles, PyCSIS makes use of limited information, referring mainly to already available data sources and using empirical models and information collected from measurements at the Joint Research Centre of the European Commission.

The methodology was applied to assess the impact of the introduction of the new CO 2 certification procedure in Europe on the vehicle fleet CO 2 emissions.

Table 7 summarises the main results of this calculation for passenger cars and light commercial vehicles. For conventional, internal combustion engine (ICEV) passenger cars, the PyCSIS model has been applied to all new registrations of year 2015. For battery electric, plug-in hybrid electric and hybrid electric vehicles, a different approach has been used due to the limited number of such vehicles sold in the European market in 2015. For this reason, in the table below only the WLTP to NEDC ratio is shown or these vehicle segments and not the NEDC values.

Considering the certification values for CO 2 emissions, results for ICEV passenger cars show an average WLTP to NEDC CO 2 emissions ratio of 1.21 (sales weighted average across the fleet). The ratio is higher for cars with lower NEDC emission values, while at very high emission levels (about 250 CO 2 g/km) WLTP and NEDC lead to comparable results between the two procedures. Similar trends are found for light commercial vehicles, with a slightly higher average ratio for ICEVs (~1.3).

Results for hybrid electric vehicles (HEVs) show an average WLTP to NEDC CO 2 emissions ratio significantly higher than for ICEVs (approximately 1.33 for passenger cars and 1.4 for light commercial vehicles). Like in the case of ICEVs, the ratio is higher for vehicles with lower CO 2 emissions.

Results for battery electric (BEV) and fuel cell vehicles (FCEV) show an expected average WLTP to NEDC electric energy ratio of approximately 1.28 and a pure electric range ratio of approximately 0.9 (approximately 0.8 for BEV and 0.95 for FCEV). Differently from the case

50 European Commission Regulations 1152/2017 and 1153/2017

of the ICEVs, the ratio for EVs remains approximately constant for vehicles of different size. In addition, the energy ratio is slightly higher for bigger vehicles than for smaller vehicles.

Table 7: Overview of the ratio between WLTP and NEDC emission levels for different types of passenger cars and vans

Passenger Cars NEDC Type Approval Emissions Ratio (g/km) (official 2015 data) WLTP/NEDC

All ICEV 123 1.21

All 125 1.22

< 1.4 l 115 1.24 Gasoline

1.4-2.0 l 148 1.15

> 2.0 l 225 1.07

All 121 1.20

< 1.4 l 93 1.26 Diesel

1.4-2.0 l 114 1.21

> 2.0 l 159 1.14

LPG 116 1.16

Gas 104 1.36

< 1.4 l 1.37

HEV Gasolinel 1.4-2.0 l 1.32

> 2.0 l 1.23

< 1.4 l 1.38

HEV Diesel 1.4-2.0 l 1.34

> 2.0 l 1.30

PHEV 1.00

Small 1.258

BEV/FCEV* Medium 1.283

Large 1.299

Light Commercial Vehicles Ratio WLTP/NEDC

All ICEV 1.30

Gasoline 1.22

Diesel 1.31

LPG 1.16

Gas 1.36

HEV Gasoline 1.38 HEV Diesel 1.45

PHEV 1.00

BEV/FCEV* 1.21

*The WLTP to NEDC ratios for BEV and FCEV refer to the electric energy consumption

Finally, results for plug-in hybrid electric vehicles (PHEVs) show a peculiar trend. Due to the differences between the two test procedures (especially in the way they combine results from the charge depleting and charge sustaining tests), the WLTP to NEDC CO 2 emissions ratio strongly depends on the capacity of the electric battery. The ratio quickly decreases as the battery capacity increases. For this reason, also considering the evolution in the battery capacity, an average ratio of 1 has been estimated for PHEV.

5 A NNEX 5: F ROM NEDC TO WLTP TRANSITION TO THE NEW TYPE APPROVAL EMISSIONS TEST UNDER THE CURRENT C ARS AND V ANS R EGULATIONS

The CO 2 emission targets for cars and vans have until now been set on the basis of the emissions resulting from the New European Driving Cycle (NEDC) type approval test. Since 1 September 2017, the NEDC has been replaced by the new Worldwide Harmonised Light Vehicle Test Procedure (WLTP). The WLTP has been designed to better reflect real driving conditions and will therefore provide more realistic fuel consumption and CO 2 emissions values. The WLTP type approval test will be fully applicable to all new cars and vans from 1 September 2019. WLTP-based manufacturer CO 2 targets will apply from 2021 onwards.

The WLTP test is likely to result in increased type approval CO 2 emission values for most vehicles, but the increase will not be evenly distributed between different manufacturers. Due to this non-linear relationship between the CO 2 emission test results from the NEDC and WLTP test-procedures, it is impossible to determine one single factor to correlate NEDC into WLTP CO 2 emission values. A correlation procedure together with a methodology for translating individual manufacturer CO 2 targets have therefore been put in place 51 which will ensure that the CO 2 reduction requirements of the current Regulations under WLTP conditions are of a stringency comparable to those that have been defined under the NEDC conditions.

More precisely, during the period 2017 to 2020, NEDC-based CO 2 targets will continue to apply for cars and vans. All vehicles placed on the market in this period will progressively be certified with both NEDC and WLTP values. The Commission will monitor those values until 2020, which is the first full calendar year in which both NEDC and WLTP values will be available for all new vehicles registered. Based on the 2020 monitoring data (available in 2021), each individual manufacturer's performance on both test procedures will be compared with a view to determining its WLTP-based reference target. That reference target will correspond to the manufacturer's average WLTP-based CO 2 emissions in 2020 adjusted either upwards or downwards depending on how close the manufacturer will be in complying with its NEDC based CO 2 target in 2020. The reference WLTP targets will be used to calculate the manufacturers' annual specific emission targets starting from 2021 using the approach set out in Commission Delegated Regulations (EU) 2017/1499 and 2017/1502. The 2021 targets will be published by the Commission in October 2022 52 .

This process allows the cars and vans CO 2 emission targets set for 2020 and 2021 onwards to be maintained after the transition to the WLTP test is completed and to use those targets as the starting point for the new legislation..

51 Commission Implementing Regulations (EU) 2017/1152 and 2017/1153 and Commission Delegated Regulations (EU) 2017/1499 and 2017/1502.

52 The monitoring timetable means that the data, on the basis of which the annual targets are calculated, is submitted by Member States in the year following that for which the targets apply, e.g. the 2021 monitoring data needed for calculating the 2021 targets, will be submitted by Member States end February 2022. Following a verification of the correctness of the data, the Commission will confirm and publish the 2021 targets by 31 October 2022.

6 A NNEX 6: R EAL WORLD EMISSION MONITORING

JRC Science for Policy Report "Characterization of real-world CO2 variability and implications for future policy instruments " (Pavlovic, J., Clairotte, M., Anagnostopoulos, K., Arcidiacono, V., Fontaras, G., Ciuffo, B. (2017), publication pending)

EXECUTIVE SUMMARY

As part of its policy for reducing the greenhouse gas emissions from transport and improving its energy efficiency, Europe has set a target for the average CO 2 emissions of new passenger cars at 95 gCO 2 /km, applying from 2021 on. Over the past years, improvements in fuel efficiency have been claimed, on the basis of emission tests, which are part of the type approval of the vehicles. Nevertheless there is increasing evidence that fuel consumption improvements are only partly visible in real-world operating conditions, since they originate, at least in part, from test-oriented vehicle optimizations and test-related practices. As a result, the offset between officially reported values and real-world vehicle CO 2 emissions has increased year by year, and is estimated to be around 40% for 2015/2016.

There are three main reasons why a high and increasing difference between officially reported and actual CO 2 emissions of vehicles constitutes a problem: a) it undermines the collective effort to reduce greenhouse gas emissions in Europe, b) it creates an unfair playing field for different competitors, and c) it affects the credibility of vehicle manufacturers amongst vehicle buyers. Different stakeholders have been suggesting approaches for dealing with the gap both to provide consumers with more reliable information and to ensure that progresses to meet fuel-economy/CO 2 emission standards are also visible in real life. Among the different options, the following ones have been more frequently advanced: i) the development of an RDE test for CO 2 and fuel consumption, ii) the development of a fleet-monitoring system based on a fuel consumption meter introduced in all new vehicles, iii) the use of statistical and/or model-based approaches to correct the type-approval figures in order to be closer to the real-life conditions 53 . However, a fundamental question remains unsolved: does a single reallife fuel consumption figure make sense or alternative approaches (distributions, ranges, customized figures, etc.) need to be developed? Furthermore, the development of a new approach will require time to have it fully developed and validated.

In this light, the present study aims at characterizing the uncertainty (variability) in the vehicle fuel consumption. This should help to develop an appropriate and effective approach to deal with the gap between type-approval and real-world vehicle fuel consumption, in the context of the CO 2 target setting and compliance monitoring as well as for informing consumers on the CO 2 emissions and fuel consumption (car labelling).

Two types of data sources are used in the analysis, namely (i) data collected during a period of ~6 months from the same vehicle driven by different drivers and in different conditions, and (ii) data collected from different vehicles tested by a few drivers on a limited number of routes. Combining these two sets of data allowed to merge a wider coverage of testing conditions (first data set) with a wider coverage of vehicle technologies (second data set).

As shown in Figure 5, the variability of the vehicle fuel consumption over different operating conditions is high (ranging from 5 to 13 l/100km in 95% of the cases), both for the same

53 Scientific Advice Mechanism (SAM) (2016): Closing the gap between light-duty vehicle real-world CO2 emissions and laboratory testing, High Level Group of Scientific Advisors, Scientific Opinion 01, Brussels, 11 November 2016

driver and for different drivers. The average fuel consumption measured for all trips is 8 l/100km and the median fuel consumption is 7.4 l/100km. As the type-approval value for the vehicle is 5.5l/100km ("TA NEDC FC"), the mean and median value imply a gap of 45%, and 35%, respectively, which is overall in line with the evidence reported in the existing literature.

Figure 5: Overview of results: fuel consumption of individual drivers and all drivers combined

These findings put into question the meaningfulness of solutions, which try to characterize the fuel consumption of a vehicle with a single central figure measured ex-ante.

From the perspective of monitoring the real-world fuel efficiency improvements under a regulatory target, one may wonder how to ensure that a single figure corresponds to the average of the fuel consumption experienced by all drivers using the same vehicle. Similarly, from the perspective of providing reliable information to the users, one may also question the value of a median figure when the variability for different drivers over different trips can be so high.

The above figure also shows the fuel consumption measured in the Vehicle Emission LAboratory (VELA) of the Joint Research Centre from the same vehicle running a NEDC test ("Measured NEDC FC"). As already reported in the literature (please refer to Table 1 in the report), the NEDC TA value is systematically lower than the results of measurements carried out in an independent lab. Introducing a more robust test procedure, such as WLTP, will therefore significantly increase the representativeness of the lab-based test. Since, as of September 1 st 2017, the WLTP has replaced the NEDC as test procedure to be used in the emission type-approval of light-duty vehicles, it is expected that the vehicles that will be introduced in the market in the near future will show a more realistic single value of fuel consumption and CO 2 emissions.

The results achieved in the present study suggest however that there is further potential to enhance the existing type-approval system by coupling it with additional instruments, such as a fleet-wide fuel consumption monitoring system (to monitor the evolution of the gap between real-world and type-approval figures) and/or tools able to provide users with customized fuel consumption information derived on the basis of driver-specific conditions of vehicle use. Concerning this latter point, the Green Driving tool 54 developed by the JRC is a first attempt in this direction.

54 http://green-driving.jrc.ec.europa.eu

7 A NNEX 7: E MPLOYMENT AND QUALIFICATION

Building on a stakeholder meeting 55 dedicated to the social impacts of the transition to electrified powertrains, this Annex summarises, based on different scenarios, how different levels of uptake of electrified powertrains may affect employment and skills. It also lists possible measures on how to address social impacts.

Employment

The automotive value chain until 2025 and beyond

A recent analysis by Deloitte underlines the multitude of drivers the automotive value chain is faced with until 2025 and beyond 56 . Key challenges include digitalisation, new business models such as car sharing, and the uptake of alternative powertrains. The study develops four different scenarios for a globally operating manufacturer looking inter alia at the impact on employment and skills. Under two scenarios the uptake of alternative powertrains will reach between 33% and 36% of annual global sales of the manufacturer in 2025 and nearly 100% in 2030, whereas the other two scenarios assume an uptake of between 18% and 21% in 2025 and around 55% in 2030. Hence, in all scenarios the global share of alternative powertrains is at least 18% in 2025 and 55% in 2030.

The scenarios show that the effect on employment and skills is affected by more factors than the speed in the uptake of alternative powertrains. Whereas an alternative powertrain share of 33% combined with a slowdown in vehicle sales of 24% due to car sharing would for that manufacturer result in the loss of around 15 000 employees in production, an additional 13 000 IT related jobs would be created in the digital business contributing then 20% of the manufacturer's revenues. Under the 36%-scenario the manufacturer is also faced with 24% decrease in car sales, loses the digital business to IT giants and becomes a mere hardware platform provider using manufacturing 4.0 at large scale. As a consequence, the manufacturer would lose 24% of its workforce. By contrast under the 21%-scenario the manufacturer's workforce would be reduced by 50% in a scenario of consumers' reduced willingness to pay due to lost trust in the car industry. Under the 18%-scenario the manufacturer's workforce would increase by 5% due to a large remaining share of combustion engines and no major change in the manufacturer's business model due to a limited impact of digitalisation.

The impact of electrification of powertrains trains on direct employment and skills

The study "Electric Mobility and Employment" 57 (ELAB) analysed how the electrification of the powertrain effects personnel structures. It quantified these effects on employment for an "ideal" production of main systems for conventional and electric vehicles for a fix production capacity of 1 million powertrains. In addition, the study assessed how changes in tasks affect

55 Stakeholder meeting "Revision of the Regulations on CO 2 emissions from light-duty vehicles (post-2020) –

Impact on jobs and skills in the automotive sector", Brussels, 26 June 2017.

56 Deloitte: The Future of the Automotive Value Chain – 2025 and beyond, https://www2.deloitte.com/de/de/pages/consumer-industrial-products/articles/automotiv-value-chain-2025.html

57 Fraunhofer IAO (2012): Elektromobilität und Beschäftigung – Wirkungen der Elektrifizierung des

Antriebsstrangs auf Beschäftigung und Standortumgebung (ELAB), http://www.muse.iao.fraunhofer.de/content/dam/iao/muse/de/documents/AbgeschlosseneProjekte/elababschlussbericht.pdf . The study does not consider how much the workforce is affected along the value chain, e.g. component suppliers, not does it look at labour structures. These issues are assessed in a follow-up study "ELAB2". Results were not available yet.

skill requirements. For the analysis the study assumed different scenarios for the uptake of alternative powertrains.

In the reference scenario BEVs would reach a share of 10% and plug-in hybrids (including range-extender) of 30%. Under an ICE-scenario conventional powertrains would remain dominant in 2030 with a market share of more than two thirds, while BEVs would not enter the market. Under a BEV-scenario BEVs would constitute 40% and fuel cells 10% of new vehicles in 2030, while conventional powertrains would be out of the market in 2030. Under an FCV-scenario fuel cells would reach a market share of 40%, plug-in hybrids around 30% and BEVs and conventional powertrains around 10%.

When assessing how employment in production changes under each scenario, the impacts change over time. Under all scenarios – except for the very conservative ICE-scenario with no uptake of BEVs – an immediate increase in employment is expected (see Figure X). Under the BEV-scenario peak in employment will be reached after 10 years and will then decrease. In all scenarios employment will be higher in 2030 compared to the starting point. However, the FCV scenario is the most labour-intensive scenario, whereas the BEV-scenario is the least labour intensive scenario in the long run. During the transition phase the role of hybrid vehicles has an important effect on employment as a result of more components required in these vehicles.

Figure 6: Employment impacts of different ELAB scenarios

Socio-economic impacts to the wider economy

A series of studies 58 assessed the socioeconomic impact of the uptake of low- and zeroemission vehicles in Europe. Building on techno-economic modelling, four different scenarios are tested. In the reference scenario it is assumed current technology and vehicle efficiency does not progress further. A second scenario assumes that the 2021 CO 2 standards are met without further action beyond that date. Another scenario assumes a strong penetration of advanced powertrains which would account for 90% of sales by 2050 and hybrid-electric vehicles for the remaining 10%. Finally in technology specific scenarios different penetration rates for alternative powertrains are assumed.

The main conclusion of the macroeconomic assessment is that an increase in vehicle efficiency has a positive impact on the wider economy in Europe including employment. GDP will benefit from lower oil imports as a result of an improved trade balance and consumers as

58 https://www.camecon.com/how/our-work/fuelling-europes-future/

well as businesses are better off due to lower fuel spending. In the technology specific scenarios three trends emerge from the modelling. First, the reduction in total cost of ownership allows consumers to spend their incomes on other goods and services which is typically spent on leisure activities or consumer services that are inherently labour intensive. Secondly, the additional spending on extra technology in the automotive sector increases employment throughout the associated manufacturing supply chain. Finally, the expenditure on supporting infrastructure results in additional employment in the construction sector.

In the technology specific scenarios most additional employment is created in the manufacturing sector with an increase of between 350,000 and 550,000 jobs. Net employment increases most in the scenario with the highest uptake of alternative powertrains. Assuming that electric vehicles will have a share of 9.5% in 2020 and 80% in 2030, with the remaining 20% being hybrid-electric vehicles, direct and indirect jobs in the automotive value chain increase by 591,200 and economy-wide 508,800 jobs are created due to avoided oil use. This takes account of jobs lost in the transition such as in the refining industry.

The impact of Electrically Chargeable Vehicles on the EU economy – A literature review and assessment

A literature review 59 of recent studies on employment impacts of a higher share of electrified powertrains, carried out for ACEA, confirms that the majority of studies conclude with positive impacts on employment as is summarised in the following table:

Table 8: Summary of literature review (from FTI Consulting, 2017)

59 FTI Consulting (2017): The impact of Electrically Chargeable Vehicles on the EU economy, A literature review and assessment. Study prepared for ACEA: http://www.fticonsulting.com/~/media/Files/emea-- files/insights/reports/impact-electrically-chargeable-vehicles-eu-economy.pdf

However, the study points out that the positive impact on employment rely on some critical assumptions including on labour intensity and value-added of the technologies as well as the EU's continued technological leadership.

EU Skills Panorama

The EU Skills Panorama on the automotive sector and clean vehicles 60 concluded that the continued development of cleaner vehicles will impact considerably on the occupational and skills profile of the sector. It estimated that by 2025 the automotive industry will have to fill 888.000 jobs mainly due to the aging of the workforce and the forecasted growth of production in the sector. Over half of the total job openings to 2025 are forecast to require high-level qualifications (461,000 jobs). This includes 213,000 new jobs requiring high-level qualifications, which partially compensates a decline in the number of jobs requiring low- and medium-level qualifications.

At the national level, the EU Skills Panorama forecasts the largest expansion in automotive employment for Romania (an additional 48,040 jobs, representing a 38% increase in sector employment by 2025) and the United Kingdom (an additional 33,050 jobs, representing a 25.8% increase). Other Member States anticipated to have an above-average employment growth include Finland, Spain and Hungary. The small Latvian automotive sector is also expected to grow considerably. Germany is expected to continue dominating automotive employment in the EU with 850,650 automotive workers in 2013 representing 37.9% of the

60 European Commission (2014): EU Skills Panorama 2014: Automotive sector and clean vehicles, http://skillspanorama.cedefop.europa.eu/sites/default/files/EUSP_AH_Automotive_0.pdf

total automotive industry in the EU with a small net increase in jobs by 2025. In other countries, such as Poland, France and Italy, employment in the sector is expected to decline.

Impact on regional automotive clusters

The transition to electrified powertrains may affect employment more significantly in regions with a strong automotive industry. The regions with the highest number of persons directly employed in automotive manufacturing are located in South Germany (Baden Württemberg/Stuttgart and Bayern) followed by Île de France.

A recent study 61 analysed how employment in the automotive sector may change in the region of Baden-Württemberg in Germany with the highest number of people directly employed in automotive manufacturing, if in 2030 nearly 50% of all new vehicles will have an electric powertrain, 25% ICE with and 25% with a conventional powertrain. The study concluded that Baden-Württemberg could benefit from 18 000 additional jobs compared to the reference scenario 2013, of which 5 600 additional jobs for conventional technologies, 6 900 additional jobs related to efficiency technologies and 5 600 related to electrification. If more of the value chain for electric vehicles, mainly production of battery cells, will be located in the region additional 5 800 jobs could be created.

Qualification

In terms of skills requirements for future automotive sector, the ELAB-study 62 points to the increasing importance of electrics/electronics compared to mechanics. New skills are needed to deal with high voltage systems, hazardous materials (e.g. lithium), and new assembly tasks (electric motors). New technical competencies (e.g. electrochemical coating in the case of fuel cell systems) and specific knowledge related to hydrogen storage (e.g. high pressure).

However, independently from the uptake of alternative powertrains, the automotive industry – as all other sectors – will be faced with fundamental changes in labour markets. Demographic changes will significantly reduce the labour force potential until 2030 and beyond. In combination with a trend towards more academic qualification, the automotive sector may be faced with a shortage in employees for powertrain production. 63

As part of the GEAR 2030 process a "Human Capital" Project Team 64 was established to

“Identify the impact on employment in the EU, prepare approaches for mitigating possible

61 e-mobil BW GmbH – Landesagentur für Elektromobilität und Brennstoffzellentechnologie, Fraunhofer

Institut für Arbeitswirtschaft und Organisation IAO, Ministerium für Finanzen und Wirtschaft Baden

Württemberg (2013): STRUKTURSTUDIE BWe mobil 2015 Elektromobilität in Baden-Württemberg.

62 Fraunhofer IAO (2012): Elektromobilität und Beschäftigung – Wirkungen der Elektrifizierung des

Antriebsstrangs auf Beschäftigung und Standortumgebung (ELAB), http://www.muse.iao.fraunhofer.de/content/dam/iao/muse/de/documents/AbgeschlosseneProjekte/elababschlussbericht.pdf . The study does not consider how much the workforce is affected along the value chain, e.g. component suppliers, not does it look at labour structures. These issues are assessed in a follow-up study "ELAB2". Results were not available yet at the time of writing.

63 Fraunhofer IAO (2012): Elektromobilität und Beschäftigung – Wirkungen der Elektrifizierung des

Antriebsstrangs auf Beschäftigung und Standortumgebung (ELAB), http://www.muse.iao.fraunhofer.de/content/dam/iao/muse/de/documents/AbgeschlosseneProjekte/elababschlussbericht.pdf . The study does not consider how much the workforce is affected along the value chain, e.g. component suppliers, not does it look at labour structures. These issues are assessed in a follow-up study "ELAB2". Results were not available yet.

64 http://ec.europa.eu/growth/tools-databases/newsroom/cf/itemdetail.cfm?item_id=8640

negative consequences and develop a strategy for ensuring that the necessary skills will be available in 2030” for the EU automotive industry. The work assessed the landscape of existing initiatives across the EU, looked at what trends will impact the sector up to 2030. Moreover, it investigated the skills and human capital needs as we experience the digitalisation of the automobile industry. The GEAR2030 Project Team "Human Capital" concludes that SMEs are at the nexus of addressing skills challenges in the automotive value chain. It also argues that EU and Member State actions should focus on developing digital skills and that upskilling and reskilling will become the priority issues in corporate HR strategies to meet future job requirements.

Possible measures to address social implications

Regions with a strong automotive sector and clusters of rather closely integrated manufacturers and suppliers of components of conventional powertrains may face particular challenges by the transition to alternative powertrains if this happens at high pace.

Stakeholders have identified several actions to address these challenges. Actions include industrial collaboration, building new value chains, creating social dialogue, supporting the employability and retraining of workers / lifelong learning, stimulating entrepreneurship and creating new job opportunities in circular economy. Financial support by existing and newly developed instruments (e.g. European Structural and Investment Funds, Innovation Fund, Global Adjustment Fund) could be used to support regions to successfully cope with the transition. Regional regeneration strategies could be developed with the help of regional task forces composed of all relevant stakeholders to develop smart specialisation/transition strategies including re-training and re-employment as well as the promotion of entrepreneurship and start-ups.

To address the challenges of upskilling and reskilling GEAR2030 made the following recommendations:

Facilitating the vertical and horizontal transferability of skills and skilled labour

force: make it easier for workers to have their skills and knowledge recognised and

transferred throughout the value chain (vertical) and everywhere in the EU

(horizontal).

Creating a framework of standard job roles, working with, using and building upon the ESCO classifications (to ensure horizontal/pan-European

comparability): To provide improved knowledge of specific roles, standard job framework descriptions and potential career tracks enabling coordination and promotion of professional development courses/training on the job.

Individual Skills Passport to document more non-formal learning, increasing vertical employability throughout the supply chain: validation of informal

competences (identification of acquired skills, documentation, assessment and certification), e.g. via individual Skills Passports.

8 A NNEX 8: A DDITIONAL INFORMATION CONCERNING THE ASSESSMENT OF THE ECONOMIC , ENVIRONMENTAL AND SOCIAL IMPACTS OF THE DIFFERENT POLICY

OPTIONS

8.1 Emission targets: metric

8.1.1 Methodological considerations concerning Well-to-Wheel (WTW) and life-cycle analysis (LCA) approaches

When considering WTW or LCA approaches, discussion exists over which method provides a better balance between limited complexity and data availability while capturing the most relevant elements as regards GHG emissions related to vehicles (see Moro and Helmers, 2017 65 for more information).

The main advantage of the WTW approach as a framework for analysis is that it allows comparing results across different contexts and allows comparing over time as opposed to , a full LCA approach. A WTW analysis also has the advantage of clearly defined boundaries which facilitates data collection and reporting. WTW can be regarded as a simplified LCA, focusing on the energy consumption and GHG emissions of the preparation of road transport fuels and their operation, while ignoring other elements such as the impacts of manufacturing and decommissioning of the equipment.

A schematic overview on the different boundaries of a WTW and LCA approach is visualised in Figure 7.

Figure 7: Schematic representation of WTW boundaries, completed by possible additional elements of an LCA system describing a vehicle

65 Moro, A., Helmers, E.: A new hybrid method for reducing the gap between WTW and LCA in the carbon footprint assessment of electric vehicles. Int J Life Cycle Assess (2017) 22: 4–14. DOI 10.1007/s11367-015- 0954-z

Source: Moro A. and Helmers E. (2017)

8.1.2 Considerations regarding well-to-wheel emissions

This sub-section looks into the GHG emissions that occur in the fuel production and use of different types of vehicles – the 'well-to-wheel' approach - based on selected existing studies.

The scope of the well-to-wheel (WTW) analysis considers energy and GHG emissions balances related to the fuel production (Well-to-Tank – WTT) and related to the vehicle use (Tank-to-Wheel – TTW). The WTW emissions are assessed for a wide range of automotive fuels and powertrain options in the EU by the "J.E.C." research collaboration 66 between the European Commission's Joint Research Centre (JRC), the European Council for Automotive R&D (EUCAR) and the research division of the European Petroleum Refiners Association (CONCAWE). The assessment is updated periodically; the currently latest available version 4.a dates from the year 2014 (JEC, 2014) 67,68,69 ; the WTT emissions of electricity have been updated more recently by JRC (Moro and Lonza, 2017) 70 .

8.1.2.1 Well-to-Tank (WTT) analysis

Fossil fuel: Diesel and gasoline

The WTT ('upstream') energy and GHG emissions related to fossil fuels that are addressed in the JEC (2014) analysis cover the chain from extraction, transportation and refining as shown in Figure 8 below. The analysis aims at quantifying marginal emissions in order to correctly assess the impact of substituting fossil fuels through alternative options.

Figure 8: Conventional fossil fuels pathways

Source: JEC (2014), WTT report version 4.a

The key elements can be summarised as follows:

• Emissions from crude oil production and conditioning at source originate mainly in the energy chain required to extract and pre-treat the oil, and the flaring and venting and fugitive losses of associated volatile hydrocarbons, which vary across regions and fields. These are analysed for the different regions that supply the European market to obtain representative values for GHG emissions and energy use related to crude production and conditioning at source. For the WTT calculations the energy and GHG associated with the marginal crude available to Europe are calculated. This marginal crude is likely to

66 http://iet.jrc.ec.europa.eu/about-jec/welcome-jec-website

67 JEC - JRC-EUCAR-CONCAWE collaboration (JEC 2014): Well-to-Tank Report - Version 4.a

68 JEC - JRC -EUCAR-CONCAWE collaboration (JEC 2014): Well-to-Wheels Report - Version 4.a

69 JEC - JRC -EUCAR-CONCAWE collaboration (JEC 2014): Tank-to-Wheels Report - Version 4.a

70 Moro, A., Lonza, L. (2017): Electricity carbon intensity in European Member States: Impacts on GHG emissions of electric vehicles. Transportation Research Part D, http://dx.doi.org/10.1016/j.trd.2017.07.012

originate from the Middle East where the amount of energy needed for production tends to be at the low end of the range.

• The GHG emissions stemming from the transportation of crude to Europe are calculated.

• Refining of crude oil is the most energy-intensive process in the fossil fuel supply chain. In order to best estimate the savings from substituting conventional fuels, the study assessed how the EU refineries would have to adapt to a marginal reduction in demand, differentiating between gasoline and diesel.

• Finally, emissions related to the distribution of gasoline and diesel are considered.

Figure 9: WTT GHG emissions of conventional diesel and gasoline

Source: JEC (2014), WTT report version 4.a

Overall, the WTT GHG emissions for gasoline and diesel fuel amount to 13.8 and 15.4 g CO 2 eq per MJ of final fuel, respectively. Refining is the most energy- and emission-intensive step, followed by the crude production (Figure 9).

Regarding the changes in the WTT emissions of conventional diesel and gasoline in Europe over the next decades, according to JEC (2014), the use of unconventional oils in the European fuel supply is likely to remain limited until 2020.

Council Directive 652/2015 lays down rules on calculation methods and reporting requirements regarding the greenhouse gas intensity of fuels, in accordance with the Fuel Quality Directive 98/70/EC i 71 .

Electricity

The WTT emissions of electricity as a fuel for vehicles are based on Moro and Lonza (2017), who updated and expanded the JEC (2014) analysis. Moro and Lonza provide the GHG intensity of the electricity consumed in the year 2013 at the EU-28 level, and by Member

71 http://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32015L0652&from=EN

State. While noting there are important differences in the carbon-intensity across countries, this section focuses on average EU28 figures only, as shown in Table 9.

The WTT GHG emissions (considering CO 2 , CH 4 and N 2 O) include upstream emissions caused by the extraction, refining and transportation of fuels, as well as, the emissions related to the generation of electricity (i.e. combustion emissions), while assigning GHG emission credits for heat produced by CHP plants. In addition, losses due to own-consumption in power plants, pump storage and transmission losses occurring at the high, medium and low-voltage levels are taken into account, considering that charging of electric vehicles may to a large extent take place at the low-voltage level.

Table 9: GHG emission intensity of electricity in the year 2013, EU-28 average

gross electricity production - combustion only 340 g CO 2eq /kWh

gross electricity production - combustion plus upstream 387 g CO 2eq /kWh

net electricity production - including upstream 407 g CO 2eq /kWh

electricity supplied- including upstream 417 g CO 2eq /kWh

electricity consumed at high voltage level - including upstream 428 g CO 2eq /kWh

electricity consumed at medium voltage level - including upstream 432 g CO 2eq /kWh

electricity consumed at low voltage level - including upstream 447 g CO 2eq /kWh

Source: Moro and Lonza, 2017

In order to provide an indication of the possible evolution of the WTT emissions of electricity as road transport fuel for 2020, 2025 and 2030 in line with the EU's energy and climate targets, the following calculations were performed.

The trajectory of the carbon intensity of the European electricity and steam production over the period 2010-2030, as projected by the PRIMES model in the EUCO30 scenario 72 , was applied on the WTT electricity emissions provided by Moro and Lonza (2017). To this end, in a first step the WTT GHG emission intensity for the year 2013 was back-calculated for the year 2010, taking into account the observed reduction in the CO 2 intensity of electricity and steam generation. On these 2010 WTT emissions, the relative reductions in the carbon intensity of electricity and steam production between the years 2010, 2020, 2025 and 2030 - as modelled by PRIMES – were applied.

On that basis, the EU-28 average WTT GHG emissions at the low-voltage network would be 101 gCO 2 eq/MJ (364 gCO 2 eq/kWh) in 2020, 90 gCO 2 eq/MJ (322 gCO 2 eq/kWh) in 2025, and 70 gCO 2 eq/MJ (252 gCO 2 eq/kWh) in 2030, as shown in Figure 10.

Obviously, these figures need to be interpreted as rough estimations only as the simplified approach does not account for any (rather probable) changes in the losses assumed and in the upstream emissions; moreover, it is implicitly assumed that emissions of non-CO 2 GHG decrease proportionally to that of CO 2 .

72 https://ec.europa.eu/energy/sites/ener/files/documents/20170125_- _technical_report_on_euco_scenarios_primes_corrected.pdf

Figure 10: WTT GHG emissions of the EU electricity consumed at the high, medium and low voltage level in 2013, 2020 and 2030

Source: 2013 data from Moro and Lonza (2017); 2020/2030 estimates derived by applying trends of the direct CO 2 emission intensity from PRIMES EUCO30 scenario on the WTT emissions reported in Moro and Lonza

8.1.2.2 Tank-to-wheel analysis

The Tank-to-wheel analysis in this sub-section is based on 'real world' energy consumption figures as used elsewhere in the Impact Assessment. As an illustrative example, the energy consumption of a representative vehicle of the 'lower-medium' category has been considered.

The specific energy consumption of various vehicle types for the years 2025 and 2030 is displayed in Figure 11 for three different policy options regarding the EU-wide fleet CO 2 target level (TLC20, TLC30, TLC40).

On the basis of the specific fuel consumption, the TTW (exhaust) CO 2eq -emissions are calculated through the fuel specific CO 2 emission factors used in the Impact Assessment. CH 4 and N 2 O emissions are taken from the JEC (2014) assessment that considers the EURO6 limits for 2020+ vehicle configurations; they are left unchanged between 2020 and 2030.

Figure 11: Specific energy consumption of different passenger car configurations (lowermedium segment) in 2025 and 2030 under different EU-wide CO 2 target options as defined in this Impact Assessment

8.1.2.3 Well-to-Wheel analysis

This section brings the information from the previous sections together for a selected number of vehicle types, providing the GHG emission balances that occur from a Well-toWheel (WTW) perspective.

Figure 12 summarises the WTW GHG emissions for 2025 and 2030 passenger car configurations for three CO 2 target level options (TLC20, TLC30 and TLC40). The WTW emissions are disaggregated into those that relate to the use of the vehicle (TTW) and those that stem from the fuel production (WTT), the latter being split into fossil fuel production and electricity generation and distribution. Note that for electric vehicles, charging at the low voltage level was assumed.

The figure illustrates the difference between ICEV and EV in terms of WTW emissions, but also clearly shows the importance of the evolution of the electricity generation mix, which increases with higher degrees of electrification up to the extreme of the battery-electric vehicles.

Figure 12: WTW GHG emissions from different passenger car configurations (lowermedium size segment) in 2025 and 2030 under different EU-wide CO 2 target options as defined in this Impact Assessment

8.1.3 Considerations regarding embedded emissions

This sub-section provides some insight into existing LCA-studies. It should be noted however that these studies may not be directly comparable among them. Moreover, they are not necessarily consistent with the WTW analysis shown in the previous section

The interest in LCAs for objects as complex as automotive products has existed for many years but has only become more rigorous and robust in recent years. Manufacturers have been routinely producing LCAs of their products or key subassemblies for the past five years or so. More and more published material is available, but in spite of standardisation efforts e.g. under the ISO 14040 standard, there is still broad variability in the methodologies, assumptions and results available, mainly due to a scarcity in (verifiable) supply chain data and this often makes comparison impossible.

In parallel several academic studies (and reviews) have been published also comparing LCAs of conventional vs. alternative vehicles. These are described in more detail below.

While the purpose of most LCA/lifecycle impact assessment (LCIA) 73 studies is to enable comparison of alternative vehicle options across a range of different impact categories, we focus on climate impacts captured as normalised greenhouse gas (GHG) emissions. Note, however, that the conclusions may change when looking into other impact categories (e.g. acidification potential).

8.1.3.1 Relevance of embedded GHG emissions

Nordelöf et al. (2014) 74 analysed 79 papers on different types of LCA studies of electrified vehicles with the aim of identifying some robust conclusions on the environmental impacts of these vehicles. Despite the divergence in the analyses, some robust trends could be identified, noting that the predominant focus is on the current situation and not the future perspective. All studies agree that the WTW-related part currently dominates the total emissions of GHG both for ICEVs and for EVs. However, in relative terms, embedded emissions are of larger importance for electric vehicles both because of the drastic reductions in WTW emissions when using low-carbon electricity, and the need for components like the battery whose production is generally associated with elevated emissions. 75

This is confirmed by a study supported by the German Federal Ministry of Transport and Digital Infrastructure 76 , which bases the energy consumption values of EVs on the measured actual consumption of 735 vehicles that were operated in Germany with a total mileage of 5.2

73 Lifecycle impact assessment, the step of the LCA where environmental impacts are calculated.

74 Nordelöf, A., Messagie, M., Tillman, A.-M., Ljunggren Söderman, M., Van Mierlo, J.: Environmental impacts of hybrid, plug-in hybrid, and battery electric vehicles—what can we learn from life cycle assessment? Int J Life Cycle Assess (2014) 19:1866–1890; see also Erratum Int J Life Cycle Assess (2016) 21:134–135

75 Obviously, the contribution of the embedded emissions to the overall life cycle GHG emissions per km largely depends on the lifetime mileages (decreasing importance with increasing lifetime mileage).

76 BMVI (2016), publ. (German Federal Ministry of Transport and Digital Infrastructure): Bewertung der Praxistauglichkeit und Umweltwirkungen von Elektrofahrzeugen ("Final report: Assessment of the feasibility and environmental impacts of electric vehicles").

million km until 2015, primarily in fleets but also by private owners 77 . Figure 13, which is taken from this report, confirms that the equipment-related emissions become relatively more important in the case of EVs, in particular in the case of reduced WTW emissions due to a green electricity mix.

Figure 13: Life-cycle GHG emissions of different vehicles (compact class; Germany)

Source: adapted from BMVI, 2016; lifetime mileage assumed is 150,000 km

The largest source of equipment related emissions of BEV is the glider (Moro and Helmers, 2017, quoting Habermacher, 2011 78 ), followed by the battery and the drivetrain. Considering that the glider is – to a large extent – common to the different vehicle type options, the manufacturing of the battery including the related production of the materials is the single most important source of GHG emissions, even though different studies vary concerning its share in the total emissions.

8.1.3.2 Battery related GHG emissions

IVL recently performed an extensive literature review concerning the energy consumption and GHG emissions of vehicle battery production 79 . They found that the results among studies differ significantly, as shown in Figure 14.

77 The measured average fuel consumption in the mini class was 4.73l/100km for gasoline, 3.72 l/100km for diesel and 13.9 kWh/100km for battery electric vehicles. In the compact class, the average consumption was 5.73l/100km gasoline, 4.3l/100km diesel and 14.9kWh/100 km BEV.

78 Habermacher F (2011) Modeling material inventories and environmental impacts of electric passenger cars, MS-thesis, available at: http://www.empa.ch/plugin/template/empa/*/109104/—/l=1

79 Romare, M., Dahllöf, L. (2017): The Life Cycle Energy Consumption and Greenhouse Gas Emissions from Lithium-Ion Batteries – A Study with Focus on Current Technology and Batteries for Light-duty Vehicles. IVL Swedish Environmental Research Institute.

Figure 14: Calculated greenhouse gas emissions for different LCA studies of lithium-ion batteries for light vehicles for the chemistries NMC, NMC/LMO, LFP and LMO

Notes: T-D=Top-down approach for manufacturing and B-U is Bottom-Up approach.

Source: IVL, 2017

Ellingsen et al. (2017) also carried out a review to assess the key assumptions and differences between 16 studies examining the lifecycle GHG emissions of batteries. They report up to a tenfold difference in the arising overall GHG emissions, as illustrated below regarding production emissions (cradle to gate):

Figure 15. Greenhouse gas emissions of battery production for different chemistries

Source: Ellingsen et al. (2017)

Both studies find that such differences can be explained by the different methodologies followed in the various papers, for example

• top down versus bottom-up 80 approaches,

• the scope (e.g. cooling system included)

• assumptions on production process steps and the energy sources used

• assumptions on cell materials and battery components

• the availability of primary versus secondary data.

Very few studies assessed the ulterior lifecycle steps, i.e. use phase and end-of-life, for GHG impacts; however, these are estimated to make a minor contribution to overall impacts. Overall, it is concluded (in line with Nordelöf et al., 2014) 81 that "most articles are nontransparent and there are usually information gaps in the goal and scope reporting" (IVL, 2017, p. 19).

Battery-production related GHG emissions seem to stem primarily from the battery (including cell) manufacturing, and only little from the mining and refining of the materials. In particular the production of the cathode requires large amounts of energy and is therefore highly GHG emitting, followed by anode and electrolyte production. Since the largest part of the energy used in the battery production is in the form of electricity, its carbon intensity largely influences the battery-related GHG emissions. A successful implementation of the EU's energy and climate objectives would therefore not only reduce the TTW-emissions of electric vehicles during their operation, but could further reduce the embedded emissions of the battery manufacturing process, assuming battery manufacturing takes place in the EU.

80 The top-down studies start with manufacturing data from e.g. a plant, and allocate energy use to the processes based on information about the process. Bottom-up approaches on the other hand, collect data for each single activity in a facility. It is likely that the top-down data is more complete and includes energy use from auxiliary processes.

81 Anders Nordelöf, Maarten Messagie, Anne-Marie Tillman, Maria Ljunggren Söderman, Joeri Van Mierlo: Environmental impacts of hybrid, plug-in hybrid, and battery electric vehicles—what can we learn from life cycle assessment? Int J Life Cycle Assess (2014) 19:1866–1890; see also Erratum Int J Life Cycle Assess (2016) 21:134–135

8.2 Target levels for cars (TLC) and vans (TLV)

8.2.1 Economic impacts

As explained in Section 6.1 of the Impact Assessment, the economic impacts for the "average" new vehicle were calculated using the cost output data of the PRIMES-TREMOVE model by averaging the contributions of the different size segments and powertrains, weighed according to their market penetration.

For this analysis, the following indicators have been used:

• Net economic savings from a societal perspective

This parameter reflects the change in costs over the lifetime (15 years) of an "average" new vehicle without considering taxes and using a discount rate of 4%.

• Net savings from an end-user perspective, using two different indicators:

o Total Cost of Ownership (TCO) over the vehicle lifetime

This parameter reflects the change in costs over the lifetime (15 years) of an "average" new vehicle. In this case, given the end-user perspective, taxes are included and a discount rate of 11% (cars) or 9.5% (vans) 82 is used.

o TCO for the first user, i.e. net savings during the first five years after

registration:

This parameter reflects the change in costs, during the first five years of use (i.e. the average time the first buyer is using the vehicle). Again, taxes are included and a discount rate of 11% (cars) or 9.5% (vans) is used. The calculation also takes account of the residual value of the vehicle (and the technology added) with depreciation.

8.2.1.1 Passenger cars (TLC)

This Section of the Annex provides an overview of the details of the calculations of the net savings and their components. The main results and the assessment are to be found in Section 6.3.2.2 of the Impact Assessment.

8.2.1.1.1 Net economic savings over the vehicle lifetime from a societal perspective

Table 10 shows the net savings (EUR per vehicle, expressed as the difference with the baseline) over the vehicle lifetime from a societal perspective for an average new passenger car registered in 2025 and in 2030 under the different TLC options.

The net savings observed are the result of differences in capital costs– which in this case are equal to manufacturing costs -, fuel cost savings and O&M costs.

Table 10: Net economic savings over the vehicle lifetime from a societal perspective in

2025 and 2030 (EUR/car)

2025 (EUR/car) TLC20 TLC25 TLC30 TLC40 TLC_EP40 TLC_EP50

Capital cost [1] 115 229 380 747 1,411 1,193

82 Refer to Ref2016

O&M cost [2] 139 139 130 96 25 22

Fuel cost savings [3] 354 514 661 922 1,394 1,198

Net savings 100 147 152 78 -42 -17

[3]-[1]-[2]

2030 (EUR/car) TLC20 TLC25 TLC30 TLC40 TLC_EP40 TLC_EP50

Capital cost [1] 419 679 1,020 1,812 1,861 2,752

O&M cost [2] -62 -62 -96 -157 -168 -192

Fuel cost savings [3] 1,159 1,520 1,802 2,220 2,214 2,558

Net savings 802 902 878 565 521 -2

[3]-[1]-[2]

8.2.1.1.2 TCO-15 years (vehicle lifetime)

Table 11 shows the TCO over 15 years (EUR per car) of an average new passenger car registered in 2025 and in 2030 under the different TLC options (expressed as the difference with the baseline), with "medium" costs assumption.

Table 11: TCO-15 years in 2025 and 2030 (EUR/car)

TLC20 TLC25 TLC30 TLC40 TLC_EP40 TLC_EP50

2025 329 413 436 391 253 309

2030 1,227 1,374 1,359 1,012 1,012 389

8.2.1.1.3 TCO-first user (5 years)

Table 12 shows the net savings (EUR per car) from a first end-user perspective for an average new passenger car registered in 2025 and in 2030 under the different TLC options (expressed as the difference with the baseline).

The net savings observed are the result of differences in capital costs, fuel cost savings and O&M costs.

Table 12: TCO-first user (5 years) in 2025 and 2030 (EUR/car) for different TLC options

2025 (EUR/car) TLC20 TLC25 TLC30 TLC40 TLC_EP40 TLC_EP50

Capital cost [1] 90 179 297 585 1,104 934

O&M cost [2] 58 58 54 40 10 9

Fuel cost savings [3] 348 482 614 866 1,286 1,138

Net savings 200 245 263 241 171 195

[3]-[1]-[2]

2030 (EUR/car) TLC20 TLC25 TLC30 TLC40 TLC_EP40 TLC_EP50

Capital cost [1] 328 532 799 1,419 1,456 2,154

O&M cost [2] -26 -26 -40 -66 -71 -82

Fuel cost savings [3] 1,025 1,323 1,576 1,992 2,012 2,354

Net savings 723 817 818 639 627 282

[3]-[1]-[2]

8.2.1.1.4 Sensitivity – economic impacts under varying cost assumptions

As explained in Section 6.1 of the Impact Assessment, for the purpose of analysing the sensitivity of cost assumptions apart from the "medium" costs, a number of cost-curves were developed illustrating the impact of low and high technology cost estimates. These different cost estimates were calculated using a methodological approach developed and refined in consultation with stakeholders and a statistical model to assess the uncertainty in the future cost projections. The "medium" cost case represents the most likely scenario resulting from significant future technology deployment to meet post-2020 CO 2 targets.

The tables below summarise the net economic savings for a range of TLC options, with technology costs varying as follows:

• "High": High costs for EV and ICEV

• "High ICE": Medium costs for EV, High Costs for ICEV

• "Medium": 'default' case with medium cost assumptions for all technologies, as applied in Section 8.2.1.1;

• "LxEV": Low costs for EV, Medium Costs for ICEV;

• "Low": Low costs for EV and ICEV

The tables document to what extent the capital costs, O&M costs and fuel savings, as well as the resulting net savings vary with differing technology cost assumptions.

Results are presented for the savings over a vehicle lifetime from a societal perspective, for a TOC-15-years end-user perspective (only showing the net savings in this case) and from a TCO-first user (5 years) perspective.

Net savings increase as technology costs are getting lower due to a combination of lower capital costs and higher fuel savings (as the share of alternative powertrains, incl. EV, increases).

Across the different cost assumptions assessed, the highest net savings are usually found when using "Low" costs.

Table 13: Sensitivity - Net economic savings from a societal perspective in 2025 and 2030 under different cost assumptions for a range of TLC options (EUR/car) (N/A: data are not available)

TLC20 - 2025 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 593 380 115 N/A N/A

O&M cost [2] 158 147 139 N/A N/A

Fuel cost savings [3] 412 321 354 N/A N/A

Net savings [3]-[1]-[2] -338 -205 100 N/A N/A

TLC20 - 2030 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 1,000 689 419 N/A N/A

O&M cost [2] -31 -45 -62 N/A N/A

Fuel cost savings [3] 1,260 1,127 1,159 N/A N/A

Net savings [3]-[1]-[2] 290 483 802 N/A N/A

TLC25 - 2025 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 769 538 229 91 -110

O&M cost [2] 158 147 139 116 106

Fuel cost savings [3] 587 495 514 396 407

Net savings [3]-[1]-[2] -340 -190 147 189 412

TLC25 - 2030 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 1,416 1,034 679 366 166

O&M cost [2] -31 -45 -62 -100 -117

Fuel cost savings [3] 1,621 1,486 1,520 1,323 1,347

Net savings [3]-[1]-[2] 236 498 902 1,057 1,297

TLC30 - 2025 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 989 716 380 215 -19

O&M cost [2] 131 133 130 116 106

Fuel cost savings [3] 691 627 661 578 592

Net savings [3]-[1]-[2] -429 -222 152 247 505

TLC30 - 2030 (EUR/car) High High ICE Medium LxEV Low Capital cost [1] 1,863 1,415 1,020 654 386

O&M cost [2] -86 -80 -96 -100 -117

Fuel cost savings [3] 1,829 1,747 1,802 1,687 1,717

Net savings [3]-[1]-[2] 51 412 878 1,133 1,448

TLC40 - 2025 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 1,863 1,415 1,020 654 386

O&M cost [2] -86 -80 -96 -100 -117

Fuel cost savings [3] 1,829 1,747 1,802 1,687 1,717

Net savings [3]-[1]-[2] 51 412 878 1,133 1,448

TLC40 - 2030 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 2,807 2,241 1,812 1,310 988

O&M cost [2] -133 -133 -157 -153 -185

Fuel cost savings [3] 2,168 2,156 2,220 2,151 2,213

Net savings [3]-[1]-[2] -506 48 565 994 1,410

Table 14: Sensitivity - TCO-lifetime (15 years) in 2025 and 2030 under different cost assumptions (net savings in EUR/car) for a range of TLC options

TLC20 High High ICE Medium LxEV Low

2025 -303 -84 329 N/A N/A

2030 479 798 1,227 N/A N/A

TLC25 High High ICE Medium LxEV Low

2025 -297 -53 413 507 815

2030 411 829 1,374 1,660 1,987

TLC30 High High ICE Medium LxEV Low

2025 -393 -75 439 599 952

2030 195 738 1,359 1,770 2,187

TLC40 High High ICE Medium LxEV Low

2025 -674 -173 391 652 1,084 2030 -441 342 1,012 1,663 2,221

Table 15 Sensitivity - TCO-first end user (5 years) in 2025 and 2030 under different cost assumptions (net savings in EUR/car)

TLC20 - 2025 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 464 297 90 N/A N/A

O&M cost [2] 67 63 58 N/A N/A

Fuel cost savings [3] 379 326 348 N/A N/A

Net savings [3]-[1]-[2] -152 -34 200 N/A N/A

TLC20 - 2030 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 783 539 328 N/A N/A

O&M cost [2] -13 -19 -26 N/A N/A

Fuel cost savings [3] 1,083 1,006 1,025 N/A N/A

Net savings [3]-[1]-[2] 314 486 723 N/A N/A

TLC25 - 2025 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 602 560 179 71 -86

O&M cost [2] 67 57 58 50 45

Fuel cost savings [3] 525 594 482 417 424

Net savings [3]-[1]-[2] -144 -22 245 297 466

TLC25 - 2030 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 1,108 809 532 287 130

O&M cost [2] -13 -19 -26 -43 -50

Fuel cost savings [3] 1,381 1,302 1,323 1,213 1,229

Net savings [3]-[1]-[2] 285 513 817 969 1,148

TLC30 - 2025 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 774 872 297 168 -15

O&M cost [2] 56 41 54 50 45

Fuel cost savings [3] 631 837 614 569 579 Net savings [3]-[1]-[2] -199 -75 263 352 549

TLC30 - 2030 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 1,458 1,107 799 512 302

O&M cost [2] -36 -34 -40 -43 -50

Fuel cost savings [3] 1,589 1,542 1,576 1,513 1,534

Net savings [3]-[1]-[2] 167 469 818 1,044 1,282

TLC40 - 2025 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 1,150 560 585 411 190

O&M cost [2] 41 57 40 39 39

Fuel cost savings [3] 835 594 866 836 855

Net savings [3]-[1]-[2] -355 -22 241 386 627

TLC40 - 2030 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 2,197 1,754 1,419 1,025 773

O&M cost [2] -57 -57 -66 -65 -79

Fuel cost savings [3] 1,957 1,951 1,992 1,959 1,999

Net savings [3]-[1]-[2] -184 254 639 998 1,304

8.2.1.1.5 Sensitivity – economic impacts with varying international oil price

Section 6.3.2.2 of the Impact Assessment shows the net economic savings (from different perspectives) from new CO 2 target levels, resulting from an higher increase of the fuel savings with respect to the capital costs in case the fleet is composed by more efficient vehicles. The international fuel price projections used for the calculation of the fuel savings are those used in the Reference Scenario 2016 83 , both for the baseline and for the policy options.

As a sensitivity analysis, it is relevant to assess the changes to the net economic savings in case of different international fuel price projections. Therefore a scenario is considered assuming a different evolution of the fuel prices in 2030. The new projected fuel price used for this sensitivity is about 25% lower than in the assumptions used for the Reference Scenario 2016.

The economic analysis is repeated with the lower international fuel prices, both in the baseline and for selected options for the target levels: TLC20, TLC25, TLC30, TLC40.

Table 16 and Table 17 show the results for the net economic savings for passengers cars from a societal perspective and for the TCO-15 years, respectively. Even with the lower oil prices,

83 https://ec.europa.eu/energy/sites/ener/files/documents/20160713%20draft_publication_REF2016_v13.pdf

CO 2 targets continue to have a positive economic effect, with fuel savings continuing to overweight increased capital expenditures for more efficient vehicles.

Table 16: Net economic savings over the vehicle lifetime from a societal perspective in 2025 and 2030 (EUR/car) under different TLC options in case of a lower international fuel price

TLC20 TLC25 TLC30 TLC40

2025 13 31 4 -135

2030 570 612 525 96

Table 17: TCO-lifetime (15 years) in 2025 and 2030 under different cost assumptions (net savings in EUR/car) for a range of TLC options in case of a lower international fuel price

TLC20 TLC25 TLC30 TLC40

2025 253 304 301 195

2030 1,010 1,106 1,035 590

8.2.1.2 Light commercial vehicles (TLV)

8.2.1.2.1 Net economic savings over the vehicle lifetime from a societal perspective

This Section of the Annex provides an overview of the details of the calculations of the net savings and their components. The main results and the assessment are to be found in Section 6.3.2.2 of the Impact Assessment.

Table 18 shows the net savings over the vehicle lifetime from a societal perspective for an average new van registered in 2025 and in 2030 under the different TLV options (expressed as the difference with the baseline).

The net savings observed are the result of differences in capital costs– which in this case are equal to manufacturing costs -, fuel cost savings and O&M costs.

Table 18: Net economic savings over the vehicle lifetime from a societal perspective in 2025 and 2030 (EUR/van)

2025 TLV20 TLV25 TLV30 TLV40 TLV_EP TLV_EP

40 50

Capital cost [1] 232 355 393 877 1,251 1,469

O&M cost [2] -40 -52 -58 -106 -91 -119

Fuel cost savings [3] 1,002 1,265 1,685 2,061 2,529 2,316

Net savings [3-1-2] 810 962 1,350 1,290 1,369 967

2030 TLV20 TLV25 TLV30 TLV40 TLV_EP TLV_EP

40 50

Capital cost [1] 426 620 891 1,582 1,415 2,439

O&M cost [2] -50 -55 -75 -142 -141 -239

Fuel cost savings [3] 2,063 2,600 3,064 3,827 3,341 4,261

Net savings [3-1-2] 1,687 2,036 2,247 2,386 2,067 2,060

8.2.1.2.2 TCO-15 years (vehicle lifetime)

Table 19 shows the TCO over 15 years (EUR per car) of an average new passenger car registered in 2025 and in 2030 under the different TLC options (expressed as the difference with the baseline).

Table 19: TCO-15 years in 2025 and 2030 (EUR/van)

TLV20 TLV25 TLV30 TLV40 TLV_EP40 TLV_EP50

2025 1,382 1,680 2,255 2,466 2,520 2,390

2030 2,764 3,377 3,825 4,390 3,211 4,403

8.2.1.2.3 TCO-first user (5 years)

Table 20 shows the net savings from a first end-user perspective for an average new van registered in 2025 and in 2030 under the different TLV options (expressed as the difference with the baseline).

Table 20: TCO-first user (5 years) in 2025 and 2030 (EUR/van)

2025 (EUR/van) TLV20 TLV25 TLV30 TLV40 TLV_EP40 TLV_EP50

Capital cost [1] 144 221 244 545 778 913

O&M cost [2] -17 -23 -25 -46 -40 -52

Fuel cost savings [3] 1,016 1,281 1,662 2,115 2,614 2,485

Net savings 889 1,083 1,443 1,616 1,876 1,624

[3]-[1]-[2]

2030 (EUR/van) TLV20 TLV25 TLV30 TLV40 TLV_EP40 TLV_EP50

Capital cost [1] 265 386 554 984 879 1,516

O&M cost [2] -22 -24 -33 -62 -61 -104

Fuel cost savings [3] 2,026 2,546 3,013 3,833 3,382 4,412

Net savings 1,783 2,184 2,492 2,912 2,564 3,000

[3]-[1]-[2]

8.2.1.2.4 Sensitivity – economic impacts under varying cost assumptions

As explained in Section 6.1 of the Impact Assessment, for the purpose of analysing the sensitivity of cost assumptions apart from the "medium" costs, a number of cost-curves were developed illustrating the impact of low and high technology cost estimates. These different cost estimates were calculated using a methodological approach developed and refined in consultation with stakeholders and a statistical model to assess the uncertainty in the future cost projections. The "medium" cost case represents the most likely scenario resulting from significant future technology deployment to meet post-2020 CO 2 targets.

The tables below summarise the net economic savings for a range of TLV options, with technology costs varying as follows:

• "High": High costs for EV and ICEV

• "High ICE": Medium costs for EV, High Costs for ICEV

• "Medium": 'default' case with medium cost assumptions for all technologies, as applied in Section 8.2.1.1;

• "LxEV": Low costs for EV, Medium Costs for ICEV;

• "Low": Low costs for EV and ICEV

The tables document to what extent the capital costs, O&M costs and fuel savings, as well as the resulting net savings vary with differing technology cost assumptions.

Results are presented for the savings over a vehicle lifetime from a societal perspective, for a TOC-15-years end-user perspective (only showing the net savings in this case) and from a TCO-first user (5 years) perspective.

Net savings increase as technology costs are getting lower due to a combination of lower capital costs and higher fuel savings (as the share of alternative powertrains, incl. EV, increases).

Across the different cost assumptions assessed, the highest net savings are usually found when using "Low" costs.

Table 21: Sensitivity - Net economic savings from a societal perspective in 2025 and 2030 under different cost assumptions for a range of TLV options (EUR/van) (N/A: data are not available)

TLV20 - 2025 (EUR/van) High High ICE Medium LxEV Low

Capital cost [1] 565 393 232 N/A N/A

O&M cost [2] -32 -45 -40 N/A N/A

Fuel cost savings [3] 1,067 959 1,002 N/A N/A

Net savings [3]-[1]-[2] 534 611 810 N/A N/A

TLV20 - 2030 (EUR/van) High High ICE Medium LxEV Low

Capital cost [1] 873 596 426 N/A N/A

O&M cost [2] -34 -56 -50 N/A N/A

Fuel cost savings [3] 2,156 2,020 2,063 N/A N/A

Net savings [3]-[1]-[2] 1,316 1,480 1,687 N/A N/A

TLV25 - 2025 (EUR/van) High High ICE Medium LxEV Low

Capital cost [1] 765 545 355 240 121

O&M cost [2] -55 -60 -52 -63 -58

Fuel cost savings [3] 1,313 1,212 1,265 1,155 1,191

Net savings [3]-[1]-[2] 602 727 962 979 1,127

TLV25 - 2030 (EUR/van) High High ICE Medium LxEV Low

Capital cost [1] 1,194 843 620 358 235

O&M cost [2] -47 -67 -55 -83 -77

Fuel cost savings [3] 2,642 2,537 2,600 2,438 2,470

Net savings [3]-[1]-[2] 1,495 1,760 2,036 2,163 2,312

TLV40 - 2025 (EUR/van) High High ICE Medium LxEV Low

Capital cost [1] 1,561 1,132 877 669 370

O&M cost [2] -110 -110 -106 -112 -59

Fuel cost savings [3] 1,954 1,964 2,061 1,973 2,250

Net savings [3]-[1]-[2] 503 942 1,290 1,416 1,938

TLV40 - 2030 (EUR/van) High High ICE Medium LxEV Low

Capital cost [1] 2,553 1,863 1,582 1,091 814

O&M cost [2] -154 -154 -142 -161 -79

Fuel cost savings [3] 3,715 3,742 3,827 3,738 4,301

Net savings [3]-[1]-[2] 1,317 2,033 2,386 2,808 3,566

Table 22: Sensitivity - TCO-lifetime (15 years) in 2025 and 2030 under different cost assumptions (net savings in EUR/van) for a range of TLV options]

TLV20 High High ICE Medium LxEV Low

2025 1,079 1,165 1,382 N/A N/A

2030 2,361 2,529 2,764 N/A N/A

TLV25 High High ICE Medium LxEV Low 2025 1,280 1,418 1,680 1,706 1,867

2030 2,777 3,064 3,377 3,528 3,676

TLV40 High High ICE Medium LxEV Low

2025 1,586 2,074 2,466 2,627 3,209

2030 3,198 3,995 4,390 4,902 5,785

Table 23 Sensitivity - TCO-first end user (5 years) in 2025 and 2030 under different cost assumptions (net savings in EUR/van)

TLV20 - 2025 (EUR/van) High High ICE Medium LxEV Low

Capital cost [1] 351 244 144 N/A N/A

O&M cost [2] -14 -20 -17 N/A N/A

Fuel cost savings [3] 1,056 988 1,016 N/A N/A

Net savings [3]-[1]-[2] 719 763 889 N/A N/A

TLV20 - 2030 (EUR/van) High High ICE Medium LxEV Low

Capital cost [1] 543 370 265 N/A N/A

O&M cost [2] -15 -24 -22 N/A N/A

Fuel cost savings [3] 2,087 1,994 2,026 N/A N/A

Net savings [3]-[1]-[2] 1,559 1,648 1,783 N/A N/A

TLV25 - 2025 (EUR/van) High High ICE Medium LxEV Low

Capital cost [1] 476 339 221 149 75

O&M cost [2] -24 -26 -23 -28 -25

Fuel cost savings [3] 1,310 1,247 1,281 1,214 1,237

Net savings [3]-[1]-[2] 859 934 1,083 1,093 1,186

TLV25 - 2030 (EUR/van) High High ICE Medium LxEV Low

Capital cost [1] 742 524 386 223 146

O&M cost [2] -20 -29 -24 -36 -33

Fuel cost savings [3] 2,570 2,500 2,546 2,439 2,460

Net savings [3]-[1]-[2] 1,848 2,005 2,184 2,253 2,347 TLV40 - 2025 (EUR/van) High High ICE Medium LxEV Low

Capital cost [1] 970 704 545 416 230

O&M cost [2] -48 -48 -46 -49 -26

Fuel cost savings [3] 2,042 2,048 2,115 2,065 2,249

Net savings [3]-[1]-[2] 1,119 1,393 1,616 1,698 2,044

TLV40 - 2030 (EUR/van) High High ICE Medium LxEV Low

Capital cost [1] 1,587 1,158 984 678 506

O&M cost [2] -67 -67 -62 -70 -34

Fuel cost savings [3] 3,753 3,774 3,833 3,783 4,184

Net savings [3]-[1]-[2] 2,234 2,684 2,912 3,175 3,713

8.2.1.2.5 Sensitivity – economic impacts with varying international oil price

Similarly as for cars, as a sensitivity analysis, the changes to the net economic savings in case of different international fuel price projections were assessed, using a scenario assuming an reduction of the oil prices of around 25% in 2030 with respect to the price in 2030 of the Reference Scenario 2016. " (see Section 8.2.1.1.5).

The economic analysis is repeated with the lower international fuel prices, both in the baseline and for selected options for the target levels TLV20, TLV25, TLV40.

Table 16 and Table 17 show the results for the net economic savings for passengers cars from a societal perspective and for the TCO-15 years, respectively. Even with the lower oil prices, CO 2 targets continue to have a positive economic effect, with fuel savings continuing to overweight increased capital expenditures for more efficient vehicles.

Table 24: Net economic savings over the vehicle lifetime from a societal perspective in 2025 and 2030 (EUR/van) under different TLV options in case of a lower international fuel price

TLV20 TLV25 TLV40

2025 588 682 814

2030 1,281 1,527 1,546

Table 25: TCO-15 years (vehicle lifetime) in 2025 and 2030 under different cost assumptions (net savings in EUR/car) for a range of TLV options in case of a lower international fuel price

TLV20 TLV25 TLV40

2025 1,180 1,422 2,027

2030 2,368 2,881 3,601 8.2.2 Social Impacts

8.2.2.1 TCO for second user - passenger cars (TLC)

The detailed results of the analysis of the TCO for the second car user are summarised in Table 26.

Table 26: TCO-second user in 2025 and 2030 (EUR/car)

2025 (EUR/car) TLC20 TLC25 TLC30 TLC40 TLC_EP40 TLC_EP50

Capital cost [1] 43 86 143 282 532 450

O&M cost [2] 58 58 54 40 10 9

Fuel cost savings [3] 302 416 527 742 1,096 976

Net savings [3]-[1]-[2] 201 272 329 420 553 516

2030 (EUR/car) TLC20 TLC25 TLC30 TLC40 TLC_EP40 TLC_EP50

Capital cost [1] 158 256 385 684 702 1,039

O&M cost [2] -26 -26 -40 -66 -71 -82

Fuel cost savings [3] 841 1,083 1,292 1,640 1,659 1,953

Net savings [3]-[1]-[2] 708 853 947 1,022 1,028 996

8.2.2.2 Sensitivity - TCO for second user - passenger cars (TLC) with varying technology cost assumptions

Table 27 summarises the detailed results of the sensitivity analysis of the TCO for the second car user for various TLC options and with different technology cost assumptions.

Table 27: Sensitivity - TCO-second end user (years 6-10) for passenger cars in 2025 and 2030 under different cost assumptions (net savings in EUR/car)

TLC20 - 2025 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 224 143 43 N/A N/A

O&M cost [2] 67 63 58 N/A N/A

Fuel cost savings [3] 324 283 302 N/A N/A

Net savings [3]-[1]-[2] 33 77 201 N/A N/A

TLC20 - 2030 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 377 260 158 N/A N/A

O&M cost [2] -13 -19 -26 N/A N/A

Fuel cost savings [3] 882 823 841 N/A N/A

Net savings [3]-[1]-[2] 518 582 708 N/A N/A

TLC25 - 2025 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 290 203 86 34 -42

O&M cost [2] 67 63 58 50 45

Fuel cost savings [3] 445 404 416 366 373

Net savings [3]-[1]-[2] 88 139 272 282 370

TLC25 - 2030 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 534 390 256 138 63

O&M cost [2] -13 -19 -26 -43 -50

Fuel cost savings [3] 1,125 1,065 1,083 998 1,011

Net savings [3]-[1]-[2] 603 694 853 903 997

TLC30 - 2025 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 373 270 143 81 -7

O&M cost [2] 56 57 54 50 45

Fuel cost savings [3] 538 509 527 492 500

Net savings [3]-[1]-[2] 109 182 329 362 463

TLC30 - 2030 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 703 534 385 247 146

O&M cost [2] -36 -34 -40 -43 -50

Fuel cost savings [3] 1,300 1,264 1,292 1,243 1,258

Net savings [3]-[1]-[2] 634 764 947 1,039 1,162

TLC40 - 2025 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 555 420 282 198 91

O&M cost [2] 41 41 40 39 39

Fuel cost savings [3] 717 718 742 718 734

Net savings [3]-[1]-[2] 122 257 420 481 604

TLC40 - 2030 (EUR/car) High High ICE Medium LxEV Low

Capital cost [1] 1,059 846 684 494 373 O&M cost [2] -57 -57 -66 -65 -79

Fuel cost savings [3] 1,611 1,607 1,640 1,613 1,644

Net savings [3]-[1]-[2] 609 818 1,022 1,183 1,350

8.2.2.3 TCO for second user - vans (TLV)

The detailed results of the analysis of the TCO for the second van user are summarised in Table 28.

Table 28: Table: TCO-second user in 2025 and 2030 (EUR/van)

2025 (EUR/van) TLV20 TLV25 TLV30 TLV40 TLV_EP40 TLV_EP50

Capital cost [1] 69 106 118 263 375 440

O&M cost [2] -17 -23 -25 -46 -40 -52

Fuel cost savings [3] 707 893 1,155 1,475 1,824 1,739

Net savings [3]-[1]-[2] 655 809 1,063 1,258 1,489 1,351

2030 (EUR/van) TLV20 TLV25 TLV30 TLV40 TLV_EP40 TLV_EP50

Capital cost [1] 128 186 267 474 424 731

O&M cost [2] -22 -24 -33 -62 -61 -104

Fuel cost savings [3] 1,388 1,743 2,064 2,629 2,321 3,032

Net savings [3]-[1]-[2] 1,282 1,582 1,830 2,217 1,958 2,405

8.2.2.4 TCO for second user - vans (TLV) and sensitivity regarding technology cost assumptions

Table 29 summarises the detailed results of the sensitivity analysis of the TCO for the second user of vans for various TLV options and with different technology cost assumptions.

Table 29: Sensitivity - TCO-second end user (years 6-10) for vans in 2025 and 2030 under different cost assumptions (net savings in EUR/van)

TLV20 - 2025 (EUR/van) High High ICE Medium LxEV Low

Capital cost [1] 169 118 69 N/A N/A

O&M cost [2] -14 -20 -17 N/A N/A

Fuel cost savings [3] 734 689 707 N/A N/A

Net savings [3]-[1]-[2] 579 591 655 N/A N/A

TLV20 - 2030 (EUR/van) High High ICE Medium LxEV Low

Capital cost [1] 262 179 128 N/A N/A

O&M cost [2] -15 -24 -22 N/A N/A

Fuel cost savings [3] 1,428 1,366 1,388 N/A N/A

Net savings [3]-[1]-[2] 1,181 1,212 1,282 N/A N/A

TLV25 - 2025 (EUR/van) High High ICE Medium LxEV Low

Capital cost [1] 229 163 106 72 36

O&M cost [2] -24 -26 -23 -28 -25

Fuel cost savings [3] 912 869 893 848 863

Net savings [3]-[1]-[2] 706 732 809 804 852

TLV25 - 2030 (EUR/van) High High ICE Medium LxEV Low

Capital cost [1] 358 253 186 107 70

O&M cost [2] -20 -29 -24 -36 -33

Fuel cost savings [3] 1,759 1,713 1,743 1,673 1,687

Net savings [3]-[1]-[2] 1,422 1,489 1,582 1,602 1,650

TLV40 - 2025 (EUR/van) High High ICE Medium LxEV Low

Capital cost [1] 468 339 263 200 111

O&M cost [2] -48 -48 -46 -49 -26

Fuel cost savings [3] 1,425 1,430 1,475 1,442 1,565

Net savings [3]-[1]-[2] 1,006 1,139 1,258 1,290 1,479

TLV40 - 2030 (EUR/van) High High ICE Medium LxEV Low

Capital cost [1] 765 558 474 327 244

O&M cost [2] -67 -67 -62 -70 -34

Fuel cost savings [3] 2,575 2,589 2,629 2,596 2,865

Net savings [3]-[1]-[2] 1,877 2,098 2,217 2,339 2,655 8.3 Distribution of effort (DOE): additional information regarding impacts on

competition between manufacturers

The analysis presented in Section 6.4 of the Impact Assessment has looked at how manufacturing costs of different types of manufacturers may change across different policy options considered for distributing the efforts. It used both an absolute price indicator and a relative one (cost increase relative to the average price of the vehicles).

This Section presents additional modelling results, complementing those presented in the main text of the Impact Assessment.

Passenger cars

The two figures below show the main results of the analysis for passenger cars in case of an EU-wide fleet CO 2 target in 2025 and 2030 under option TLC25.

Figure 16 shows the cost increase per vehicle (EUR/car), while in Figure 17 these costs are related to the vehicle price (cost increase in % of car price).

Figure 16: Additional manufacturing costs (EUR/car) for categories of passenger car manufacturers under different options DOE and with the EU-wide fleet CO 2 target levels as in option TLC25

Figure 17: Additional manufacturing costs relative to vehicle price (% of car price) for categories of passenger car manufacturers under different options DOE and with the EU-wide fleet CO 2 target levels as in option TLC25

Vans

The two figures below show the main results for vans with EU-wide fleet CO 2 targets in 2025 and 2030 as under option TLV25. Figure 18 shows the absolute manufacturing cost increase (EUR/van), while in Figure 19 these costs are related to the vehicle price (cost increase in % of van price).

Figure 18: Additional manufacturing costs (EUR/van) for categories of van manufacturers under different options DOE and with the EU-wide fleet CO 2 target levels as in option TLV25

Figure 19: Additional manufacturing costs relative to vehicle price (% of van price) for categories of van manufacturers under different options DOE and with the EU-wide fleet CO 2 target levels as in option TLV25

8.4 ZEV/ LEV incentives

8.4.1 Passenger cars: assessment of options with additional incentives for low-emission vehicles: economic and social impacts

Table 30 provides a detailed overview of the net savings achieved under the different LEV incentives options using the different indicators used in the economic and social analysis.

Table 30: Detailed overview of the net savings in EUR/car under different LEV incentive options (LEV definitions, CO 2 targets and LEV mandate/benchmark levels) for 2025 and 2030 passenger cars using several economic (societal perspective, TCO-first user) and social (TCO-second user) impact indicators

TLC20 – 2025 (LEVD_ZEV)

LEVD_ZEV Net savings from a societal perspective (EUR/car)

TLC20 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 115 -241 -273

O&M cost [2] 1 136 176

Fuel cost savings [3] 354 143 -71

Net savings [3]-[1]-[2] 100 248 27

LEVD_ZEV TCO-first user (5 years) (EUR/car)

TLC20 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 90 -189 -214

O&M cost [2] 58 57 74

Fuel cost savings [3] 348 228 116

Net savings [3]-[1]-[2] 200 360 257

LEVD_ZEV TCO-second user (years 6-10) (EUR/car)

TLC20 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 43 -91 -103

O&M cost [2] 58 57 74

Fuel cost savings [3] 302 198 94

Net savings [3]-[1]-[2] 201 232 124

TLC20 – 2030 (LEVD_ZEV)

LEVD_ZEV Net savings from a societal perspective (EUR/car)

TLC20 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 419 -116 -139

O&M cost [2] -62 -129 -120

Fuel cost savings [3] 1,159 739 595

Net savings [3]-[1]-[2] 802 984 854

LEVD_ZEV TCO-first user (5 years) (EUR/car)

TLC20 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 328 -91 -109

O&M cost [2] -26 -54 -50

Fuel cost savings [3] 1,025 789 719

Net savings [3]-[1]-[2] 723 934 878

LEVD_ZEV TCO-second user (years 6-10) (EUR/car)

TLC20 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 158 -44 -53

O&M cost [2] -26 -54 -50

Fuel cost savings [3] 841 648 589

Net savings [3]-[1]-[2] 708 746 692

TLC25 – 2025 (LEVD_ZEV)

LEVD_ZEV Net savings from a societal perspective (EUR/car)

TLC25 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 229 -150 -194

O&M cost [2] 1 138 168

Fuel cost savings [3] 514 298 97

Net savings [3]-[1]-[2] 149 310 123

LEVD_ZEV TCO-first user (5 years) (EUR/car)

TLC25 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 179 -117 -152

O&M cost [2] 58 59 72

Fuel cost savings [3] 482 365 259

Net savings [3]-[1]-[2] 245 424 339

LEVD_ZEV TCO-second user (years 6-10) (EUR/car)

TLC25 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 86 -57 -73

O&M cost [2] 58 59 72

Fuel cost savings [3] 416 310 213

Net savings [3]-[1]-[2] 272 308 215

TLC25 – 2030 (LEVD_ZEV)

LEVD_ZEV Net savings from a societal perspective (EUR/car)

TLC25 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 682 37 -3

O&M cost [2] -60 -131 -126

Fuel cost savings [3] 1,521 1,094 952

Net savings [3]-[1]-[2] 899 1,188 1,080

LEVD_ZEV TCO-first user (5 years) (EUR/car)

TLC25 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 533 29 -2

O&M cost [2] -26 -56 -53

Fuel cost savings [3] 1,325 1,085 1,015

Net savings [3]-[1]-[2] 817 1,111 1,070 LEVD_ZEV TCO-second user (years 6-10) (EUR/car)

TLC25 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 257 14 -1

O&M cost [2] -26 -56 -53

Fuel cost savings [3] 1,084 889 830

Net savings [3]-[1]-[2] 853 931 884

TLC30 – 2025 (LEVD_ZEV)

LEVD_ZEV Net savings from a societal perspective (EUR/car)

TLC30 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 380 -43 -101

O&M cost [2] 1 144 166

Fuel cost savings [3] 661 462 274

Net savings [3]-[1]-[2] 152 361 209

LEVD_ZEV TCO-first user (5 years) (EUR/car)

TLC30 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 297 -34 -79

O&M cost [2] 54 60 70

Fuel cost savings [3] 614 510 408

Net savings [3]-[1]-[2] 263 483 417

LEVD_ZEV TCO-second user (years 6-10) (EUR/car)

TLC30 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 143 -16 -38

O&M cost [2] 54 60 70

Fuel cost savings [3] 527 429 338

Net savings [3]-[1]-[2] 329 385 306

TLC30 – 2030 (LEVD_ZEV)

LEVD_ZEV Net savings from a societal perspective (EUR/car)

TLC30 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 1,020 249 181

O&M cost [2] -96 -138 -136

Fuel cost savings [3] 1,802 1,466 1,314

Net savings [3]-[1]-[2] 878 1,355 1,269

LEVD_ZEV TCO-first user (5 years) (EUR/car)

TLC30 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 799 195 142

O&M cost [2] -40 -58 -57

Fuel cost savings [3] 1,576 1,393 1,315

Net savings [3]-[1]-[2] 818 1,256 1,230

LEVD_ZEV TCO-second user (years 6-10) (EUR/car)

TLC30 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 385 94 68

O&M cost [2] -40 -58 -57

Fuel cost savings [3] 1,292 1,138 1,074

Net savings [3]-[1]-[2] 947 1,101 1,062

TLC40 – 2025 (LEVD_ZEV)

LEVD_ZEV Net savings from a societal perspective (EUR/car)

TLC40 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 747 179 116

O&M cost [2] 1 107 122

Fuel cost savings [3] 922 799 701

Net savings [3]-[1]-[2] 78 513 462

LEVD_ZEV TCO-first user (5 years) (EUR/car)

TLC40 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 585 140 91

O&M cost [2] 40 45 51

Fuel cost savings [3] 866 808 756

Net savings [3]-[1]-[2] 241 623 615

LEVD_ZEV TCO-second user (years 6-10) (EUR/car)

TLC40 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 282 68 44

O&M cost [2] 40 45 51

Fuel cost savings [3] 742 677 630

Net savings [3]-[1]-[2] 420 565 535

TLC40 – 2030 (LEVD_ZEV)

LEVD_ZEV Net savings from a societal perspective (EUR/car)

TLC40 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 1,812 794 730

O&M cost [2] -157 -169 -187

Fuel cost savings [3] 2,220 2,045 1,999

Net savings [3]-[1]-[2] 565 1,420 1,456

LEVD_ZEV TCO-first user (5 years) (EUR/car)

TLC40 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 1,419 621 571

O&M cost [2] -66 -71 -78

Fuel cost savings [3] 1,992 1,906 1,887

Net savings [3]-[1]-[2] 639 1,356 1,395 LEVD_ZEV TCO-second user (years 6-10) (EUR/car)

TLC40 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 684 299 275

O&M cost [2] -66 -71 -78

Fuel cost savings [3] 1,640 1,557 1,539

Net savings [3]-[1]-[2] 1,022 1,329 1,342

TLC20 – 2025 (LEVD_25)

LEVD_25 Net savings from a societal perspective (EUR/car)

TLC20 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 115 -233 -229

O&M cost [2] 1 170 207

Fuel cost savings [3] 354 42 -153

Net savings [3]-[1]-[2] 100 106 -131

LEVD_25 TCO-first user (5 years) (EUR/car)

TLC20 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 90 -183 -179

O&M cost [2] 58 71 87

Fuel cost savings [3] 348 164 47

Net savings [3]-[1]-[2] 200 276 139

LEVD_25 TCO-second user (years 6-10) (EUR/car)

TLC20 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 43 -88 -87

O&M cost [2] 58 71 87

Fuel cost savings [3] 302 137 33

Net savings [3]-[1]-[2] 201 154 33

TLC20 – 2030 (LEVD_25)

LEVD_25 Net savings from a societal perspective (EUR/car)

TLC20 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 419 -114 -107

O&M cost [2] -62 -87 -4

Fuel cost savings [3] 1,159 608 297

Net savings [3]-[1]-[2] 802 810 407

LEVD_25 TCO-first user (5 years) (EUR/car)

TLC20 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 328 -89 -84

O&M cost [2] -26 -36 -2

Fuel cost savings [3] 1,025 710 515

Net savings [3]-[1]-[2] 723 836 600

LEVD_25 TCO-second user (years 6-10) (EUR/car)

TLC20 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 158 -43 -40

O&M cost [2] -26 -36 -2

Fuel cost savings [3] 841 583 429

Net savings [3]-[1]-[2] 708 662 471

TLC25 – 2025 (LEVD_25)

LEVD_25 Net savings from a societal perspective (EUR/car)

TLC25 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 229 -153 -157

O&M cost [2] 1 185 205

Fuel cost savings [3] 514 169 23

Net savings [3]-[1]-[2] 149 138 -25

LEVD_25 TCO-first user (5 years) (EUR/car)

TLC25 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 179 -120 -123

O&M cost [2] 58 79 87

Fuel cost savings [3] 482 282 195

Net savings [3]-[1]-[2] 245 323 230

LEVD_25 TCO-second user (years 6-10) (EUR/car)

TLC25 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 86 -58 -59

O&M cost [2] 58 79 87

Fuel cost savings [3] 416 232 156

Net savings [3]-[1]-[2] 272 212 128

TLC25 – 2030 (LEVD_25)

LEVD_25 Net savings from a societal perspective (EUR/car)

TLC25 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 682 22 3

O&M cost [2] -60 -95 -14

Fuel cost savings [3] 1,521 966 673

Net savings [3]-[1]-[2] 899 1,039 684

LEVD_25 TCO-first user (5 years) (EUR/car)

TLC25 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 533 17 2

O&M cost [2] -26 -40 -6

Fuel cost savings [3] 1,325 1,009 826

Net savings [3]-[1]-[2] 817 1,032 830

LEVD_25 TCO-second user (years 6-10) (EUR/car)

TLC25 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 257 8 1

O&M cost [2] -26 -40 -6

Fuel cost savings [3] 1,084 825 681

Net savings [3]-[1]-[2] 853 858 686

TLC30 – 2025 (LEVD_25)

LEVD_25 Net savings from a societal perspective (EUR/car)

TLC30 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 380 -64 -71

O&M cost [2] 1 205 210

Fuel cost savings [3] 661 305 209

Net savings [3]-[1]-[2] 152 163 70

LEVD_25 TCO-first user (5 years) (EUR/car)

TLC30 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 297 -50 -56

O&M cost [2] 54 86 88

Fuel cost savings [3] 614 407 351

Net savings [3]-[1]-[2] 263 371 319

LEVD_25 TCO-second user (years 6-10) (EUR/car)

TLC30 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 143 -24 -27

O&M cost [2] 54 86 88

Fuel cost savings [3] 527 334 286

Net savings [3]-[1]-[2] 329 272 225

TLC30 – 2030 (LEVD_25)

LEVD_25 Net savings from a societal perspective (EUR/car)

TLC30 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 1,020 203 147

O&M cost [2] -96 -106 -25

Fuel cost savings [3] 1,802 1,326 1,049

Net savings [3]-[1]-[2] 878 1,229 927

LEVD_25 TCO-first user (5 years) (EUR/car)

TLC30 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 799 159 115

O&M cost [2] -40 -44 -11

Fuel cost savings [3] 1,576 1,309 1,137

Net savings [3]-[1]-[2] 818 1,194 1,033

LEVD_25 TCO-second user (years 6-10) (EUR/car)

TLC30 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 385 77 55

O&M cost [2] -40 -44 -11

Fuel cost savings [3] 1,292 1,069 934

Net savings [3]-[1]-[2] 947 1,037 890

TLC40 – 2025 (LEVD_25)

LEVD_25 Net savings from a societal perspective (EUR/car)

TLC40 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 747 160 85

O&M cost [2] 1 129 173

Fuel cost savings [3] 922 748 570

Net savings [3]-[1]-[2] 78 460 312

LEVD_25 TCO-first user (5 years) (EUR/car)

TLC40 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 585 125 66

O&M cost [2] 40 54 73

Fuel cost savings [3] 866 773 670

Net savings [3]-[1]-[2] 241 595 531

LEVD_25 TCO-second user (years 6-10) (EUR/car)

TLC40 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 282 60 32

O&M cost [2] 40 54 73

Fuel cost savings [3] 742 645 551

Net savings [3]-[1]-[2] 420 531 446

TLC40 – 2030 (LEVD_25)

LEVD_25 Net savings from a societal perspective (EUR/car)

TLC40 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 1,812 768 649

O&M cost [2] -157 -172 -144

Fuel cost savings [3] 2,220 2,026 1,896

Net savings [3]-[1]-[2] 565 1,430 1,391

LEVD_25 TCO-first user (5 years) (EUR/car)

TLC40 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 1,419 601 507

O&M cost [2] -66 -72 -60

Fuel cost savings [3] 1,992 1,896 1,825

Net savings [3]-[1]-[2] 639 1,367 1,378 LEVD_25 TCO-second user (years 6-10) (EUR/car)

TLC40 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 684 290 245

O&M cost [2] -66 -72 -60

Fuel cost savings [3] 1,640 1,548 1,488

Net savings [3]-[1]-[2] 1,022 1,331 1,303

TLC20 – 2025 (LEVD_50)

LEVD_50 Net savings from a societal perspective (EUR/car)

TLC20 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 115 -230 -231

O&M cost [2] 1 178 255

Fuel cost savings [3] 354 -50 -334

Net savings [3]-[1]-[2] 100 3 -358

LEVD_50 TCO-first user (5 years) (EUR/car)

TLC20 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 90 -180 -181

O&M cost [2] 58 74 107

Fuel cost savings [3] 348 103 -70

Net savings [3]-[1]-[2] 200 209 5

LEVD_50 TCO-second user (years 6-10) (EUR/car)

TLC20 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 43 -87 -87

O&M cost [2] 58 74 107

Fuel cost savings [3] 302 94 -54

Net savings [3]-[1]-[2] 201 107 -73

TLC20 – 2030 (LEVD_50)

LEVD_50 Net savings from a societal perspective (EUR/car)

TLC20 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 419 -117 -120

O&M cost [2] -62 -66 40

Fuel cost savings [3] 1,159 463 115

Net savings [3]-[1]-[2] 802 645 195

LEVD_50 TCO-first user (5 years) (EUR/car)

TLC20 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 328 -92 -94

O&M cost [2] -26 -27 17

Fuel cost savings [3] 1,025 622 410

Net savings [3]-[1]-[2] 723 741 487

LEVD_50 TCO-second user (years 6-10) (EUR/car)

TLC20 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 158 -44 -45

O&M cost [2] -26 -27 17

Fuel cost savings [3] 841 518 348

Net savings [3]-[1]-[2] 708 589 377

TLC25 – 2025 (LEVD_50)

LEVD_50 Net savings from a societal perspective (EUR/car)

TLC25 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 229 -150 -168

O&M cost [2] 1 183 239

Fuel cost savings [3] 514 128 -156

Net savings [3]-[1]-[2] 149 96 -227

LEVD_50 TCO-first user (5 years) (EUR/car)

TLC25 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 179 -118 -131

O&M cost [2] 58 78 102

Fuel cost savings [3] 482 252 80

Net savings [3]-[1]-[2] 245 292 110

LEVD_50 TCO-second user (years 6-10) (EUR/car)

TLC25 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 86 -57 -63

O&M cost [2] 58 78 102

Fuel cost savings [3] 416 218 70

Net savings [3]-[1]-[2] 272 197 32

TLC25 – 2030 (LEVD_50)

LEVD_50 Net savings from a societal perspective (EUR/car)

TLC25 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 682 5 -26

O&M cost [2] -60 -87 15

Fuel cost savings [3] 1,521 832 484

Net savings [3]-[1]-[2] 899 914 494

LEVD_50 TCO-first user (5 years) (EUR/car)

TLC25 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 533 4 -20

O&M cost [2] -26 -37 6

Fuel cost savings [3] 1,325 927 715

Net savings [3]-[1]-[2] 817 959 728

LEVD_50 TCO-second user (years 6-10) (EUR/car)

TLC25 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 257 2 -10

O&M cost [2] -26 -37 6

Fuel cost savings [3] 1,084 765 596

Net savings [3]-[1]-[2] 853 800 600

TLC30 – 2025 (LEVD_50)

LEVD_50 Net savings from a societal perspective (EUR/car)

TLC30 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 380 -62 -91

O&M cost [2] 1 186 243

Fuel cost savings [3] 661 290 27

Net savings [3]-[1]-[2] 152 165 -125

LEVD_50 TCO-first user (5 years) (EUR/car)

TLC30 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 297 -49 -71

O&M cost [2] 54 78 102

Fuel cost savings [3] 614 392 234

Net savings [3]-[1]-[2] 263 363 204

LEVD_50 TCO-second user (years 6-10) (EUR/car)

TLC30 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 143 -24 -34

O&M cost [2] 54 78 102

Fuel cost savings [3] 527 333 199

Net savings [3]-[1]-[2] 329 278 132

TLC30 – 2030 (LEVD_50)

LEVD_50 Net savings from a societal perspective (EUR/car)

TLC30 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 1,020 171 106

O&M cost [2] -96 -88 16

Fuel cost savings [3] 1,802 1,197 863

Net savings [3]-[1]-[2] 878 1,115 741

LEVD_50 TCO-first user (5 years) (EUR/car)

TLC30 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 799 133 83

O&M cost [2] -40 -37 6

Fuel cost savings [3] 1,576 1,228 1,029

Net savings [3]-[1]-[2] 818 1,132 939

LEVD_50 TCO-second user (years 6-10) (EUR/car)

TLC30 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 385 64 40

O&M cost [2] -40 -37 6

Fuel cost savings [3] 1,292 1,011 853

Net savings [3]-[1]-[2] 947 984 806

TLC40 – 2025 (LEVD_50)

LEVD_50 Net savings from a societal perspective (EUR/car)

TLC40 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 747 157 73

O&M cost [2] 1 133 161

Fuel cost savings [3] 922 728 513

Net savings [3]-[1]-[2] 78 438 279

LEVD_50 TCO-first user (5 years) (EUR/car)

TLC40 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 585 122 57

O&M cost [2] 40 56 67

Fuel cost savings [3] 866 756 632

Net savings [3]-[1]-[2] 241 578 507

LEVD_50 TCO-second user (years 6-10) (EUR/car)

TLC40 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 282 59 27

O&M cost [2] 40 56 67

Fuel cost savings [3] 742 636 529

Net savings [3]-[1]-[2] 420 522 434

TLC40 – 2030 (LEVD_50)

LEVD_50 Net savings from a societal perspective (EUR/car)

TLC40 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 1,812 785 547

O&M cost [2] -157 -176 -117

Fuel cost savings [3] 2,220 2,040 1,748

Net savings [3]-[1]-[2] 565 1,432 1,318

LEVD_50 TCO-first user (5 years) (EUR/car)

TLC40 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 1,419 614 428

O&M cost [2] -66 -74 -49

Fuel cost savings [3] 1,992 1,904 1,739

Net savings [3]-[1]-[2] 639 1,363 1,360 LEVD_50 TCO-second user (years 6-10) (EUR/car)

TLC40 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 684 296 206

O&M cost [2] -66 -74 -49

Fuel cost savings [3] 1,640 1,555 1,420

Net savings [3]-[1]-[2] 1,022 1,333 1,263

Sensitivity – economic impacts under varying cost assumptions for the battery

As explained in Section 6.5.1 of the impact assessment report, to assess the impacts of the options setting a LEV mandate/benchmark, the following technology costs were used: battery pack costs of around 100 EUR/kWh in 2025 and 65 EUR/kWh in 2030.

For the purpose of analysing the sensitivity of the battery cost assumptions, a different evolution is considered, corresponding to battery pack costs of around 130 EUR/kWh in 2025 and 100 EUR/kWh in 2030, in line with the "Low" costs in Section 8.2.1.1.4 of the impact assessment report.

Table 31 documents how the net savings vary with the differing battery cost assumptions for the option LEV%_A.

Results are presented for the savings over a vehicle lifetime (TCO-15-years) from an end-user perspective.

Table 31: Detailed overview of the net savings (TCO-15 years) in EUR/car under different options for the EU-wide fleet CO 2 target (TLC) combined with a LEV incentive (LEV mandate/benchmark as in option LEV%_A and different LEV definitions LEVD) for 2025 and 2030 passenger cars with varying battery costs ("Low" and "Very Low")

LEVD_ZEV TCO-15 years (EUR/car)

2025 TLC20 TLC30 TLC40

Battery cost "Low" 383 583 703

Battery cost "Very Low" 620 820 1,055

LEVD_ZEV TCO-15 years (EUR/car)

2030 TLC20 TLC30 TLC40

Battery cost "Low" 1,349 1,760 1,670

Battery cost "Very Low" 1,623 2,155 2,303

LEVD_25 TCO-15 years (EUR/car)

2025 TLC20 TLC30 TLC40

Battery cost "Low" 279 382 646

Battery cost "Very Low" 462 608 1,002

LEVD_25 TCO-15 years (EUR/car)

2030 TLC20 TLC30 TLC40

Battery cost "Low" 866 1,478 1,685

Battery cost "Very Low" 1,449 2,048 2,325

LEVD_50 TCO-15 years (EUR/car)

2025 TLC20 TLC30 TLC40

Battery cost "Low" -4 283 493

Battery cost "Very Low" 352 607 978

LEVD_50 TCO-15 years (EUR/car)

2030 TLC20 TLC30 TLC40

Battery cost "Low" 597 1,297 1,707

Battery cost "Very Low" 1,289 1,947 2,317

Net savings are lower when battery costs are at the "Low" levels. However the impacts under different battery cost assumptions remain generally positive, with higher capital costs with respect to the baseline compensated by higher fuel savings.

8.4.2 Vans: assessment of options with additional incentives for low-emission vehicles: economic and social impacts

Table 32 provides a detailed overview of the net savings achieved under the different LEV incentives options using the different indicators used in the economic and social analysis.

Table 32: Detailed overview of the net savings in EUR/van under different LEV incentive options (LEV definitions, CO 2 targets and LEV mandate/benchmark levels) for 2025 and 2030 vans using several economic (societal perspective, TCO-first user) and social (TCO-second user) impact indicators

TLV20 – 2025 (LEVD_ZEV)

LEVD_ZEV Net savings from a societal perspective (EUR/van)

TLV20 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 232 39 173

O&M cost [2] 1 -134 -237

Fuel cost savings [3] 1,002 253 -340

Net savings [3]-[1]-[2] 810 349 -276

LEVD_ZEV TCO-first user (5 years) (EUR/van)

TLV20 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 144 24 107

O&M cost [2] -17 -58 -102

Fuel cost savings [3] 1,016 603 264

Net savings [3]-[1]-[2] 889 637 259

LEVD_ZEV TCO-second user (years 6-10) (EUR/van)

TLV20 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 69 12 52

O&M cost [2] -17 -58 -102

Fuel cost savings [3] 707 436 212

Net savings [3]-[1]-[2] 655 482 262

TLV20 – 2030 (LEVD_ZEV)

LEVD_ZEV Net savings from a societal perspective (EUR/van)

TLV20 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 426 90 140

O&M cost [2] -51 -236 -317

Fuel cost savings [3] 2,063 905 505

Net savings [3]-[1]-[2] 1,688 1,051 682

LEVD_ZEV TCO-first user (5 years) (EUR/van)

TLV20 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 265 56 87

O&M cost [2] -22 -101 -136

Fuel cost savings [3] 2,026 1,301 1,062

Net savings [3]-[1]-[2] 1,783 1,346 1,111

LEVD_ZEV TCO-second user (years 6-10) (EUR/van)

TLV20 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 128 27 42

O&M cost [2] -22 -101 -136

Fuel cost savings [3] 1,388 909 752

Net savings [3]-[1]-[2] 1,282 983 846

TLV25 – 2025 (LEVD_ZEV)

LEVD_ZEV Net savings from a societal perspective (EUR/van)

TLV25 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 355 115 226

O&M cost [2] 1 -136 -225

Fuel cost savings [3] 1,265 557 36

Net savings [3]-[1]-[2] 962 577 35

LEVD_ZEV TCO-first user (5 years) (EUR/van)

TLV25 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 221 71 141

O&M cost [2] -23 -58 -96

Fuel cost savings [3] 1,281 893 600

Net savings [3]-[1]-[2] 1,083 880 556

LEVD_ZEV TCO-second user (years 6-10) (EUR/van)

TLV25 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 106 34 68

O&M cost [2] -23 -58 -96

Fuel cost savings [3] 893 637 444

Net savings [3]-[1]-[2] 809 661 473

TLV25 – 2030 (LEVD_ZEV)

LEVD_ZEV Net savings from a societal perspective (EUR/van)

TLV25 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 620 210 266

O&M cost [2] -56 -239 -319

Fuel cost savings [3] 2,600 1,473 1,051

Net savings [3]-[1]-[2] 2,037 1,502 1,105

LEVD_ZEV TCO-first user (5 years) (EUR/van)

TLV25 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 386 130 165

O&M cost [2] -24 -102 -137

Fuel cost savings [3] 2,546 1,841 1,595

Net savings [3]-[1]-[2] 2,184 1,813 1,567

LEVD_ZEV TCO-second user (years 6-10) (EUR/van)

TLV25 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 186 63 80

O&M cost [2] -24 -102 -137

Fuel cost savings [3] 1,743 1,278 1,117

Net savings [3]-[1]-[2] 1,582 1,317 1,174 TLV40 – 2025 (LEVD_ZEV)

LEVD_ZEV Net savings from a societal perspective (EUR/van)

TLV40 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 877 406 459

O&M cost [2] 1 -154 -249

Fuel cost savings [3] 2,061 1,564 1,050

Net savings [3]-[1]-[2] 1,291 1,312 840

LEVD_ZEV TCO-first user (5 years) (EUR/van)

TLV40 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 545 252 285

O&M cost [2] -46 -66 -107

Fuel cost savings [3] 2,115 1,851 1,570

Net savings [3]-[1]-[2] 1,616 1,665 1,392

LEVD_ZEV TCO-second user (years 6-10) (EUR/van)

TLV40 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 263 122 138

O&M cost [2] -46 -66 -107

Fuel cost savings [3] 1,475 1,302 1,117

Net savings [3]-[1]-[2] 1,258 1,246 1,086

TLV40 – 2030 (LEVD_ZEV)

LEVD_ZEV Net savings from a societal perspective (EUR/van)

TLV40 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 1,582 696 718

O&M cost [2] -145 -278 -362

Fuel cost savings [3] 3,827 3,122 2,721

Net savings [3]-[1]-[2] 2,389 2,704 2,365 LEVD_ZEV TCO-first user (5 years) (EUR/van)

TLV40 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 984 433 446

O&M cost [2] -62 -119 -155

Fuel cost savings [3] 3,833 3,389 3,162

Net savings [3]-[1]-[2] 2,912 3,076 2,871

LEVD_ZEV TCO-second user (years 6-10) (EUR/van)

TLV40 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 474 209 215

O&M cost [2] -62 -119 -155

Fuel cost savings [3] 2,629 2,334 2,186

Net savings [3]-[1]-[2] 2,217 2,245 2,126

TLV20 – 2025 (LEVD_40)

LEVD_40 Net savings from a societal perspective (EUR/van)

TLV20 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 232 47 203

O&M cost [2] 1 -124 -221

Fuel cost savings [3] 1,002 498 27

Net savings [3]-[1]-[2] 810 575 45

LEVD_40 TCO-first user (5 years) (EUR/van)

TLV20 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 144 29 126

O&M cost [2] -17 -53 -95

Fuel cost savings [3] 1,016 715 435

Net savings [3]-[1]-[2] 889 739 404

LEVD_40 TCO-second user (years 6-10) (EUR/van)

TLV20 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 69 14 61

O&M cost [2] -17 -53 -95

Fuel cost savings [3] 707 508 322

Net savings [3]-[1]-[2] 655 547 356

TLV20 – 2030 (LEVD_40)

LEVD_40 Net savings from a societal perspective (EUR/van)

TLV20 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 426 57 209

O&M cost [2] -51 -186 -327

Fuel cost savings [3] 2,063 1,266 666

Net savings [3]-[1]-[2] 1,688 1,395 784

LEVD_40 TCO-first user (5 years) (EUR/van)

TLV20 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 265 35 130

O&M cost [2] -22 -80 -140

Fuel cost savings [3] 2,026 1,492 1,119

Net savings [3]-[1]-[2] 1,783 1,537 1,129

LEVD_40 TCO-second user (years 6-10) (EUR/van)

TLV20 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 128 17 63

O&M cost [2] -22 -80 -140

Fuel cost savings [3] 1,388 1,032 784

Net savings [3]-[1]-[2] 1,282 1,094 861

TLV25 – 2025 (LEVD_40)

LEVD_40 Net savings from a societal perspective (EUR/van)

TLV25 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 355 145 232

O&M cost [2] 1 -142 -206

Fuel cost savings [3] 1,265 729 420

Net savings [3]-[1]-[2] 962 726 394

LEVD_40 TCO-first user (5 years) (EUR/van)

TLV25 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 221 90 144

O&M cost [2] -23 -61 -88

Fuel cost savings [3] 1,281 961 778

Net savings [3]-[1]-[2] 1,083 931 722

LEVD_40 TCO-second user (years 6-10) (EUR/van)

TLV25 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 106 44 70

O&M cost [2] -23 -61 -88

Fuel cost savings [3] 893 679 558

Net savings [3]-[1]-[2] 809 696 577

TLV25 – 2030 (LEVD_40)

LEVD_40 Net savings from a societal perspective (EUR/van)

TLV25 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 620 170 270

O&M cost [2] -56 -176 -306

Fuel cost savings [3] 2,600 1,875 1,354

Net savings [3]-[1]-[2] 2,037 1,881 1,390 LEVD_40 TCO-first user (5 years) (EUR/van)

TLV25 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 386 105 168

O&M cost [2] -24 -75 -131

Fuel cost savings [3] 2,546 2,060 1,733

Net savings [3]-[1]-[2] 2,184 2,030 1,696

LEVD_40 TCO-second user (years 6-10) (EUR/van)

TLV25 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 186 51 81

O&M cost [2] -24 -75 -131

Fuel cost savings [3] 1,743 1,420 1,202

Net savings [3]-[1]-[2] 1,582 1,445 1,253

TLV40 – 2025 (LEVD_40)

LEVD_40 Net savings from a societal perspective (EUR/van)

TLV40 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 877 484 586

O&M cost [2] 1 -265 -347

Fuel cost savings [3] 2,061 1,135 725

Net savings [3]-[1]-[2] 1,291 916 485

LEVD_40 TCO-first user (5 years) (EUR/van)

TLV40 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 545 301 364

O&M cost [2] -46 -114 -149

Fuel cost savings [3] 2,115 1,589 1,343

Net savings [3]-[1]-[2] 1,616 1,401 1,127 LEVD_40 TCO-second user (years 6-10) (EUR/van)

TLV40 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 263 145 176

O&M cost [2] -46 -114 -149

Fuel cost savings [3] 1,475 1,126 963

Net savings [3]-[1]-[2] 1,258 1,095 936

TLV40 – 2030 (LEVD_40)

LEVD_40 Net savings from a societal perspective (EUR/van)

TLV40 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 1,582 717 778

O&M cost [2] -145 -359 -508

Fuel cost savings [3] 3,827 2,801 2,179

Net savings [3]-[1]-[2] 2,389 2,444 1,909

LEVD_40 TCO-first user (5 years) (EUR/van)

TLV40 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 984 446 483

O&M cost [2] -62 -154 -218

Fuel cost savings [3] 3,833 3,176 2,781

Net savings [3]-[1]-[2] 2,912 2,884 2,516

LEVD_40 TCO-second user (years 6-10) (EUR/van)

TLV40 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 474 215 233

O&M cost [2] -62 -154 -218

Fuel cost savings [3] 2,629 2,192 1,930

Net savings [3]-[1]-[2] 2,217 2,131 1,914 TLV20 – 2025 (LEVD_50)

LEVD_50 Net savings from a societal perspective (EUR/van)

TLV20 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 232 188 349

O&M cost [2] 1 -242 -333

Fuel cost savings [3] 1,002 -360 -931

Net savings [3]-[1]-[2] 810 -306 -947

LEVD_50 TCO-first user (5 years) (EUR/van)

TLV20 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 144 117 217

O&M cost [2] -17 -104 -143

Fuel cost savings [3] 1,016 253 -78

Net savings [3]-[1]-[2] 889 240 -153

LEVD_50 TCO-second user (years 6-10) (EUR/van)

TLV20 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 69 56 105

O&M cost [2] -17 -104 -143

Fuel cost savings [3] 707 204 -14

Net savings [3]-[1]-[2] 655 252 24

TLV20 – 2030 (LEVD_50)

LEVD_50 Net savings from a societal perspective (EUR/van)

TLV20 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 426 239 362

O&M cost [2] -51 -394 -497

Fuel cost savings [3] 2,063 95 -371

Net savings [3]-[1]-[2] 1,688 249 -236

LEVD_50 TCO-first user (5 years) (EUR/van)

TLV20 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 265 149 225

O&M cost [2] -22 -169 -213

Fuel cost savings [3] 2,026 811 542

Net savings [3]-[1]-[2] 1,783 831 530

LEVD_50 TCO-second user (years 6-10) (EUR/van)

TLV20 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 128 72 109

O&M cost [2] -22 -169 -213

Fuel cost savings [3] 1,388 587 410

Net savings [3]-[1]-[2] 1,282 684 515

TLV25 – 2025 (LEVD_50)

LEVD_50 Net savings from a societal perspective (EUR/van)

TLV25 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 355 251 411

O&M cost [2] 1 -241 -330

Fuel cost savings [3] 1,265 -43 -641

Net savings [3]-[1]-[2] 962 -53 -721

LEVD_50 TCO-first user (5 years) (EUR/van)

TLV25 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 221 156 255

O&M cost [2] -23 -103 -142

Fuel cost savings [3] 1,281 553 203

Net savings [3]-[1]-[2] 1,083 500 89

LEVD_50 TCO-second user (years 6-10) (EUR/van)

TLV25 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 106 75 123

O&M cost [2] -23 -103 -142

Fuel cost savings [3] 893 412 181

Net savings [3]-[1]-[2] 809 441 199

TLV25 – 2030 (LEVD_50)

LEVD_50 Net savings from a societal perspective (EUR/van)

TLV25 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 620 332 454

O&M cost [2] -56 -391 -500

Fuel cost savings [3] 2,600 693 102

Net savings [3]-[1]-[2] 2,037 752 148

LEVD_50 TCO-first user (5 years) (EUR/van)

TLV25 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 386 206 282

O&M cost [2] -24 -168 -214

Fuel cost savings [3] 2,546 1,371 1,007

Net savings [3]-[1]-[2] 2,184 1,332 939

LEVD_50 TCO-second user (years 6-10) (EUR/van)

TLV25 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 186 99 136

O&M cost [2] -24 -168 -214

Fuel cost savings [3] 1,743 969 729

Net savings [3]-[1]-[2] 1,582 1,037 807

TLV40 – 2025 (LEVD_50)

LEVD_50 Net savings from a societal perspective (EUR/van)

TLV40 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 877 464 555

O&M cost [2] 1 -238 -348

Fuel cost savings [3] 2,061 1,085 475

Net savings [3]-[1]-[2] 1,291 859 268

LEVD_50 TCO-first user (5 years) (EUR/van)

TLV40 – 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 545 288 345

O&M cost [2] -46 -102 -152

Fuel cost savings [3] 2,115 1,587 1,241

Net savings [3]-[1]-[2] 1,616 1,400 1,047

LEVD_50 TCO-second user (years 6-10) (EUR/van)

TLV40 - 2025 LEV0 LEV%_A LEV%_B

Capital cost [1] 263 139 166

O&M cost [2] -46 -102 -152

Fuel cost savings [3] 1,475 1,127 898

Net savings [3]-[1]-[2] 1,258 1,090 884

TLV40 – 2030 (LEVD_50)

LEVD_50 Net savings from a societal perspective (EUR/van)

TLV40 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 1,582 733 764

O&M cost [2] -145 -394 -491

Fuel cost savings [3] 3,827 2,541 2,024

Net savings [3]-[1]-[2] 2,389 2,203 1,751 LEVD_50 TCO-first user (5 years) (EUR/van)

TLV40 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 984 455 475

O&M cost [2] -62 -169 -214

Fuel cost savings [3] 3,833 3,051 2,740

Net savings [3]-[1]-[2] 2,912 2,764 2,479

LEVD_50 TCO-second user (years 6-10) (EUR/van)

TLV40 - 2030 LEV0 LEV%_A LEV%_B

Capital cost [1] 474 220 229

O&M cost [2] -62 -169 -214

Fuel cost savings [3] 2,629 2,113 1,908

Net savings [3]-[1]-[2] 2,217 2,062 1,894


3.

Referenced document

10 Nov
'17
Proposal for a REGULATION OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL setting emission performance standards for new passenger cars and for new light commercial vehicles as part of the Union's integrated approach to reduce CO2 emissions from light-duty vehicles and amending Regulation (EC) No 715/2007 (recast)
COVER NOTE
Secretary-General of the European Commission
14217/17
 
 
 

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5.

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