This document summarizes the assessment of 35 measures to reduce greenhouse gas emissions from long-distance freight transport in the EU by 2020, 2035, and 2050. Key measures were evaluated based on their potential to lower emissions, fossil fuel dependency, congestion, and accidents. Measures fell into categories like road pricing, rail investments, clean vehicles, and supply chain optimization. The most promising "A" measures included internalizing external costs, logistics optimization, low-carbon fuels, batteries, and clean vehicle standards. "B" measures like liberalizing cabotage also showed potential to significantly lower emissions.

1. Helena Kyster-Hansen,
Seniorkonsult, transport & utveckling
Tetraplan A/S, Köpenhamn

2. FP7 Project for DG TREN
18 months (Sept. 2008-Feb. 2010)

3. road
rail
long-distance
Inland navigation
GHG/CO2
Fossil Fuel Share
FORESIGHT
2050 shaping
sustainability
Congestion
Accidents
Transport policy
Action plan 2020-2035-2050
Technology policy
Demonstration projects
Vision
Targets

5. Progress
Final
Conference
4. Forum
Step 4 Vision and Action Plan
3. Forum
Step 3 Measures‘ Assessment & Action Scenario
2. Forum
Step 2 BAU Forecasts & Preliminary Vision
1. Forum
Step 1 Policy Technology Mega Trends

6. Policy , Technology
& Mega-Trends
Propulsion Systems & Energy
Technology
Demonstration Projects
ITS Logistics Technologies
Policy European Policy
National Policies
Freight Transport Demand Logistics Trends
Mega-Trends
Energy Emissions

7. BAU Forecast
3 Business as usual forecasts:
• A trend forecast consisting of the most likely
development
• A low forecast, which combines positive
developments that result in easier mitigation
(lower limit)
• A high forecast that describes a future, which is
more difficult to mitigate than the other two
(upper limit)

8. Preliminary
Vision
What progress will be socially and
politically expected from long
distance freight transport until 2020,
2035 and 2050?
2020 2035 2050
Reduction of GHG emissions -20% -70% -80%
Fossil Fuel Share 80% 60% 40%
Reduction of accidents -40% -65% -80%
Reduction of congestion -17% -33% -50%

9. BAU Forecast &
Preliminary Vision (1)
GHG – emissions
Total CO2 equivalents (in tonnes) that are caused by LDFT by
road, rail and IWW within the EU27 (including upstream).
Input:
GHG emissions (Mt CO2 equ)
•Freight transport demand
350
•Modal split
300
•Average load
250
High Forecast
•Bio-fuels
200
Trend Forecast •Non-convent. foss. Fuels
Low Forecast
150
Preliminary Vision •Carbon capture and storage
100
•Electricity production
50
0
2005 2020 2035 2050

10. BAU Forecast &
Preliminary Vision (2)
Fossil Fuel Share
Fossil fuel energy input (primary energy) for LDFT by road, rail and IWW
within the EU27 divided by Total energy input (primary energy) for LDFT
by road, rail and IWW within the EU27.
Input (same as GHG):
Fossil fuel dependency (in %)
•Freight transport demand
100,00%
90,00%
•Modal split
80,00% •Average load
70,00%
High Forecast
•Biofuels
60,00%
50,00%
Trend Forecast •Non-convent. foss. Fuels
Low Forecast
40,00%
Preliminary Vision •Carbon capture and storage
30,00%
20,00%
•Electricity production
10,00%
0,00%
2005 2020 2035 2050

11. BAU Forecast &
Preliminary Vision (3)
Congestion
Delay time measured as the difference between travel time in a loaded
network and an unloaded network multiplied with the number of trucks
affected for an average day.
Input:
Congestion (in mio h)
•Transport demand
2,50
•Infrastructure
2,00 •Total cost/veh.km
1,50
Trend Forecast
Preliminary Vision
1,00
0,50
0,00
2005 2020 2035 2050

12. BAU Forecast &
Preliminary Vision (4)
Accidents
The number of road fatalities within EU27 attributable to HGV.
Input:
Accidents (Number of Fatalities)
•Deployment of techn. Develop.
8000 •Veh.km
7000
6000
5000 High Forecast
Trend Forecast
4000
Low Forecast
3000 Preliminary Vision
2000
1000
0
2005 2020 2035 2050

13. Measures' Assessment
(1)
• After the 2nd Forum 35 measures have
been identified
• These 35 measures have been evaluated
(desk research) by the project partners

14. Measures' Assessment
(2)
Road transport related measures: Supply chain related measures
• Investment in ITS • Training for eco-driving
• Investment in TEN-road • Automated platooning
• Internalisation of external costs • Standardized Loading Units
• HGV weights and dimensions • E-freight
• Liberalisation of cabotage • Network optimisation – cargo owner
• Progressive distance pricing • Network optimisation –
• Different pricing type of freight logistics service provider
• Harmonised speed limits • CO2 labels
• Congestion charge • Intermodal transport
• Enforcement of regulations • Transport consolidation & cooperation
• Transport route planning & control
Rail transport related measures
• Investment in new railway lines Energy suppliers related measures
• Freight prioritisation • Taxation of fossil fuels
• Funding for ERTMS/ETCS • Hydrogen Infrastructure
• Electrification of rail corridors • Improved Batteries (energy storage)
• Longer trains • Vehicle Supplier related measures
• Heavier trains • Including CO2 standards into HGV
regulation
IWW & maritime transport related measures • Best available technology – BAT
• Investment in IWT infrastructure vehicle certification for HGVs
• Develop new technologies in IWW • Clean vehicle technologies
• Investment in maritime port infrastructure. Aerodynamics – Alt. engines/fuels

15. Measures' Assessment
(3) - Methodology

16. Measures Assessment
(4) – ABC Analysis
• GHG 'A's: Internalisation of external
costs, Network optimisation logistics
service providers, CO2 labels,
Intermodal transport, Taxation of
fossil fuels, Improved batteries, BAT
certification for HGV, Clean vehicle
technologies
• GHG 'B's: Liberalisation of cabotage,
congestion charge, ....
• GHG 'C's ...

17. Scenario (1)
• Goal: One realistic scenario where
the preliminary vision is reached
• It is impossible to estimate the
impact of a certain measure.
• What development of the models'
input parameters is necessary and
possible?
• Assumptions for transport demand
are unchanged)

18. Scenario (2)
• GHG & Fossil Fuel – Model Input
parameters
• Engine efficiency (42% → 60%)
• Vehicle energy demand (-50%)
• Low carbon electricity (-88%)
• Bio-fuels (2% → 33%, emissions -93%)
• Efficient usage of vehicle (-45%)
• Electric engines in road transport (25%)
• Modal shift (road 75% → 65%, rail 19% →
25%, IWW 6% → 10%)
• Vehicle split/Larger Trucks (10%)
• Electrification of rail (63% → 80%)

19. Scenario (3)

20. Scenario (4)
Ceteris Paribus Analysis
•Impact if one parameter fails
(and all other reach their goal)

21. Scenario (5)
• Congestion – Model Input Parameters
• transport costs (toll costs pass. veh. 15 ct,
30 ct HGV)
• logistics efficiency (+20%)
• infrastructure availability (20%)

22. Scenario (6)
•Until 2035
•Truck vehicle km TRANSTOOLS based
•Ratio of Fatality per vehicle km to 1/3

23. Scenario (7)
• These input parameters have been
discussed.
• The conclusion of the discussion was
• That some assumptions seem to be
very optimistic and have to be
looked in detail, but in general
• the preliminary vision seems to be
possible to achieve

24. Final Step
• Elaborate for each measure
• Market perspective
• Demand for RTD actions (demonstration
projects, Basic & Applied Research)
• Demand for Transport Policy actions
• Demand for actions in Related policy areas
• Milestones
Vision
• What progress should be achieved by 2020,
2035 and 2050?

25. Final Conference: 24th Feb. 2010,
Brussels
Thanks for your attention!
www.freightvision.eu
Helena Kyster-Hansen
hkh@tetraplan.dk