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Indicator Assessment

Use of cleaner and alternative fuels - outlook from WBCSD

Indicator Assessment
Prod-ID: IND-89-en
Published 08 Jun 2009 Last modified 11 May 2021
10 min read
This page was archived on 09 Feb 2021 with reason: Other (Discontinued indicator)
Required information is not filled in: Information about the starting date of the publishing schedule is missing.

Projections of overall ethanol blend share into gasoline

Note: N/A

Projections of vehicle sales shares by vehicle type, for cars

Note: N/A

Projections of overall biodiesel blend share into diesel

Note: N/A

Supporting information

Indicator definition

Definition: Cleaner and alternative fuels are measured in absolute and relative forms: i) as a percentage (relative) and ii) amount (absolute)  of biofuels, gaseous fuels (CNG/LPG, hydrogen) and biodiesel in the total combined final energy consumption of gasoline, diesel and biofuels for transport.

The indicator is available for the following transport modes and vehicle technologies:

 

Sector/Mode

Vehicle Technology/Fuels

* Medium trucks
* Heavy-duty (long-haul trucks
*Rail freight
* National waterborne
(Inland plus coastal)
* Int'l shipping
Internal combustion engine:
* Gasoline
* Diesel
* LPG-CNG
* Ethanol
* Biodiesel
Hybrid- Electric ICE (same fuels)
Fuel-cell vehicle
* Hydrogen
With feedstock differentiation for biofuels and hydrogen)


Model used: IEA/SMP

Ownership:  World Business Council for Sustainable Development 

Temporal coverage: 1990 - 2050

Geographical coverage: OECD Europe: Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, Turkey, the United Kingdom; OECD North America: USA, Canada, Mexico; Former Soviet Union: Armenia, Azerbaijan, Belarus, Estonia, Georgia, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Republic of Moldova, Russian Federation, Tajikistan, Turkmenistan, Ukraine, Uzbekistan; Eastern Europe: Albania, Bosnia and Herzegovina, Bulgaria, Croatia, the Former Yugoslav Republic of Macedonia, Poland, Romania, Slovakia, Slovenia, Serbia and Montenegro; India; China

Units

The indicator is measured in bil litres gasoline equivalence, as well as exajoules are used for the indication.


 

Policy context and targets

Context description

Pan-European policy context

The large number of non binding policy instruments have been developed under fora such as Environment for Europe process, the European Council of Ministers of Transport (ECMT) and the UNECE/WTO Transport, Health and Environment Pan-European Programme (The PEP). The PEP was set up to address the key challenges to achieve more sustainable transport patterns and a closer integration of environmental and health concerns into transport policies.

EU policy context

The White Paper on the Common Transport Policy (CTP) "European Transport Policy for 2010: Time to Decide" is a headlight policy which covers EU objections relatively to use of alternative and cleaner fuels.

The main tasks provided in EU legislative documents provide more important role of biofuels as well as gaseous and alternative fuels.

Reducing greenhouse gas emissions and, therefore, to increase role of biofuels in the transport sector is one of the priority actions of the "The European Six Environmental action programme".

EECCA policy context

EECCA Environmental Strategy recognizes the need to incorporate environmental concerns into transport policies and sets this action as one of the Strategy objectives.

Targets

EU level

  • By 2005: the EU's fuel consumption should have a 2 % share of biofuels (EC Energy Security Communication, 2000).
  • By 2010: 2% of transport fuels from natural gas; 5.75% biofuels (EC Energy Security Communication, 2000).
  • By 2015: 5% natural gas; and 2% hydrogen for transport fuel (EC Energy Security Communication, 2000).
  • By 2020: 20% alternative fuels in road transport; 10% natural gas, 5% hydrogen(EC Energy Security Communication, 2000).
  • Promote the use of alternative fuels in the transport sector (Sixth Environment Action Prog.)

EECCA level 

  • Promote cleaner fuels for transport

LInks to other policy:

EECCA Environmental strategy

Related policy documents

No related policy documents have been specified

 

Methodology

Methodology for indicator calculation

The projections of share of alternative and cleaner fuels in total transort fuel mix are taken from the IEA/WBCSD Sustainable Mobility Project (SMP) model. To cover pan-European region these data were extracted from the publicly available IEA/SMP model spreadsheet (version 1.6) for the following geographical areas: OECD Europe, Eastern Europe, and Former Soviet Union region.
Outlook for the modal split share for use biofuels and cleaner fuels (for all types of vehicles presented in the section definition) was extracted from the same model.

Overview of the SMP Spreadsheet Model


The IEA/SMP Transport Spreadsheet Model is designed to handle all transport modes and most vehicle types. It produces projections of vehicle stocks, travel, energy use and other indicators through 2050 for a reference case and for various policy cases and scenarios. It is designed to have some technology-oriented detail and to allow fairly detailed bottom-up modeling. The SMP spreadsheet model 1.60 is the most recent version and is available for a more detailed inspection (and use, though no user guide has been prepared and there are no plans, at this time, of providing on-going usersupport for the model. A very basic outline of how to use the model is provided in the first sheet of the model spreadsheet).

The model does not include any representation of economic relationships (e.g., elasticities) nor does it track costs. Rather, it is an "accounting" model, anchored by the "ASIF" identity:

  • Activity (passenger and freight travel)
  • Structure (travel shares by mode and vehicle type)
  • Intensity (fuel efficiency)
  • Fuel type = fuel use by fuel type (and CO2 emissions per unit fuel use).

Various indicators are tracked and characterized by coefficients per unit travel, per vehicle or per unit fuel use as appropriate.

The modes, technologies, fuels, regions and basic variables are included in the spreadsheet model. Not all technologies or variables are covered for all modes. Apart from energy use, the model tracks emissions of CO2, and CO2-equivalent GHG emissions (from vehicles as well as upstream), PM, NOx, HC, CO and Pb. Projections of safety (fatalities and injuries) are also incorporated.

The most detailed segment of the model covers light-duty vehicles. The flow chart  on the page 4 of the Model Documentation provides an overview of the key linkages in the light-duty vehicle section of the model. For other passenger modes (such as buses, 2-wheelers), the approach is similar, however there is no stock model. Stocks are projected directly; vehicle sales needed to achieve these stocks is not currently tracked.

Overview of the projections, regions and viraibales used by the IEA/SMP transport spreadsheet model is peresented in the table below:

Sectors / Modes Vehicle
Technologies/
Fuels
Regions Variables
Light-duty
vehicles (cars, minivans,
SUVs)
* Medium trucks
* Heavy-duty (long-haul)
trucks
* Mini-buses ("paratransit")
* Large buses
* 2-3 wheelers
* Aviation (Domestic +
Int'l)
* Rail freight
* Rail passenger
* National waterborne
(Inland plus coastal)
* Int'l shipping
* Internal combustion engine:
* Gasoline
* Diesel
* LPG-CNG
* Ethanol
* Biodiesel
* Hybrid-
Electric ICE (same fuels)
* Fuel-cell vehicle
* Hydrogen
(With feedstock
differentiation for biofuels
and hydrogen)
* OECD Europe
* OECD North
America
* OECD Pacific
(Japan, Korea,
Australia, NZ)
* Former Soviet
Union (FSU)
* Eastern Europe
* Middle East
* China
* India
* Other Asia
* Latin America
* Africa
Passenger kilometres
of travel
* Vehicle sales (LDVs
only)
* Vehicle stocks
* Average vehicle fuelefficiency
* Vehicle travel
* Fuel use
* CO2 emissions
* Pollutant emissions
(PM, NOx, HC, CO,
Pb)
* Safety (road fatalities
and injuries)

Key model assumptions for the reference case

The reference case projects one possible set of future conditions, based on recent trends in various important indicators and other variables. Adjustments are made for expected deviations from recent trends due to factors such as existing policies, population projections, income projections and expected availability of new technologies. Expectations for other future changes in trends, such as saturations in vehicle ownership, are also incorporated.

In general, no major new policies are assumed to be implemented beyond those already implemented in 2003. An exception to this is where there is clear evidence of what might be called "policy trajectories" - future policy actions that are either explicit or implicit in other trends. For example, a clear trend is emerging in the developing world to adopt vehicle emissions standards of a form similar to those already implemented in OECD countries. It is assumed that this "policy trajectory" will continue in the future. In contrast, no such policy trajectory is evident for reduced light-duty vehicle (LDV) fuel consumption; we therefore only incorporate existing fuel consumption programmes through the year they currently end; we assume a return after that date to historical (non-policy-driven) trends in fuel consumption.

In general, the model tried to avoid introducing significant changes in trends after 2030. We run the trends assumed to exist in 2030 out to 2050 in order to see the net effects  and directions in that latter year of actions and events that often occurred years earlier.

For more infomation click here.

Methodology for gap filling

No methodology for gap filling has been specified. Probably this info has been added together with indicator calculation.

Methodology references

No methodology references available.

 

Uncertainties

Methodology uncertainty

Uncertainties related to indicator calculation

All data should be based on movements on national territory, regardless of the nationality of the vehicle. It is unknown what the assumptions are regarding movement of the transport when the assigned regions.  

Uncertainties related to IEA/SMP transport model

The model does not include any representation of economic relationships (e.g.,
elasticities) nor does it track costs. The IEA has a cost-optimization model capable of this, the ETP model, but this model was not employed in the SMP's work due to its lack of transparency and its complexity.

Data sets uncertainty

The table below provides a simplified picture of what types of variables and the level of
detail modelled for each major transport mode in the IEA/SMP transport spreadsheet model. As can be seen in the next table, there is a range of coverage by mode, as well as variations in the quality of the data available (indicated by x or i). In general, there is better data available for light-duty vehicles than for other modes, though for non-OECD regions most data is quite poor, except for aggregate estimates of transport energy consumption. New vehicle characteristics are only tracked for light-duty vehicles; existing stock is used as the basic vehicle indicator for all other modes.

The reference case includes the modes and variables identified in the table below:

Modes and Variables Covered in the Reference Case Projection

 

 

Auto

Air

Truck

Frt
Rail

Pass
Rail

Buss

Mini-
bus

2-3
wheel

Water

OECD regions

 

 

 

 

 

 

 

 

 

Activity (passenger
or tonne km)

*

*

*

*

*

*

i

i

 

New vehicle
characteristics
(sales, fuel
consumption)

*

 

 

 

 

 

 

 

 

Stock-average
energy intensity

*

*

*

*

*

*

i

i

 

Calculation of
energy use and
vehicle CO2
emissions

*

*

*

*

*

i

i

i

 

Non-OECD regions

 

 

 

 

 

 

 

 

 

Activity (passenger
or tonne km)

i

*

i

*

*

i

i

i

 

New vehicle
characteristics
(sales, fuel
consumption)

i

 

 

 

 

 

 

 

 

Stock-average
energy intensity

i

i

i

i

i

i

i

i

 

Calculation of
energy use and
vehicle CO2
emissions

i

*

i

*

*

i

i

i

*

Note: * = have data of fair to good reliability; i = have data but incomplete or of poor reliability; blank = have nothing or have not attempted to project. Note that data of fair reliability is available for energy use across all road vehicles in non-OECD countries, but breaking this out into various road modes (cars, trucks, buses, 2- wheelers) is difficult and relatively unreliable.
For more information click here

Rationale uncertainty

No uncertainty has been specified

Data sources

  • No datasets have been specified.

Other info

DPSIR: Response
Typology: Performance indicator (Type B - Does it matter?)
Indicator codes
  • Outlook 016
EEA Contact Info info@eea.europa.eu

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