Planning and Regulation
Route Planning
New Lines
Programme
Comparing environmental impact of
conventional and high speed rail
Comparing the Environmental Impact of Conventional and High-Speed Rail
Executive Summary
Introduction
The New Lines Programme is to test the hypothesis that in 2020, the existing rail lines from London to
the North and West will be operating at full capacity and the conventional and the next generation
tools for increasing capacity will be exhausted. There will be the need for additional intervention.
The programme aims to develop and evaluate the options for building new lines; including in this is the
need to evaluate the environmental impacts of such an intervention in terms of expected energy
consumption of new rolling stock, understand any step change in energy consumption between new
versus existing rolling stock including diesel versus electric and to assess localised environmental
impact during and after construction.
As a result there is a need to better understand the environmental impact of building one or more new
lines in terms of:
1) Performance (energy consumption) of rolling stock, both current high-speed (electric),
conventional (diesel) rolling stock and future electric rolling stock;
2) Seating occupancy levels in high-speed versus conventional services;
3) Estimated direct and indirect greenhouse gas emissions from diesel and electric rolling stock (both
in current and likely future electric mix);
4) Estimated emissions resulting from the construction, maintenance and decommissioning of rolling
stock;
5) The potential energy consumption/emissions resulting from construction of new infrastructure in
terms of materials used in the construction of infrastructure (and the energy consumption
/emissions per kg of these materials) as well as the energy use/emissions resulting from
infrastructure construction activities;
6) The role of energy consumption/emissions savings resulting from modal shift and factoring in
demand generation in the overall comparison.
This environmental study was carried out to assess the relative environmental performance of
conventional and high speed electric rail services. The purpose of this work is to provide an objective
comparison between the different options and the key assumptions that affect the outcome of the
comparison. In doing this, the work also needs to take into account the long timeframes associated
with planning and constructing large railway infrastructure projects including wholly new rail lines (e.g.
around 20 years for both the Channel Tunnel Rail Link and Crossrail). Hence comparisons will need to
be made on the anticipated performance of future high-speed and conventional rail rolling stock likely
to be put into service in the 2025-2030 timeframe.
For the purposes of this study, high-speed rail (HSR) services are defined as services faster than
typical UK intercity limit of 200 km/hour, typically over 250 km/hour and up to 350+ km/hour.
Comparisons in this report are made for similar types of electric rail services for HSR vs conventional
rail – i.e. with conventional intercity service rolling stock (up to 200 km/hour), rather than rolling stock
used in slower stop-start commuter services. The focus for the work for this project has been on
energy consumption and greenhouse gas emissions. Other environmental impacts will be considered
in more detail at a later phase and are not within the scope of this project.
In order to obtain as up to date and accurate information as possible the project team consulted widely
with experts in industry and academia, as well as with the Department for Transport (DfT). This was
carried out via a letter of introduction and accompanying questionnaire and follow-up by email and
telephone interviews.
ii
Comparing the Environmental Impact of Conventional and High-Speed Rail
Summary of Analysis Results and Conclusions
The results of the comparative analysis of conventional versus high-speed rail have been presented
split between three source areas:
1. GHG emissions resulting from to direct energy consumption by the trains;
2. GHG emissions resulting from the construction, maintenance, use and disposal of new electric rail
infrastructure;
3. GHG emissions resulting from the production, disposal and maintenance of electric trains.
These results have demonstrated the following points:
•
Per seat-km conventional rail uses less energy and produces fewer GHG emissions than highspeed rail. High-speed rail would be expected to result in around 9.3% more GHG emissions on
average (at 12.8 gCO2eq/seat-km) than equivalent conventional rail (at 11.7 gCO2eq/seat-km) in
2025, according to calculations using central scenario values. This difference drops to 4.4% more
over the 30-year lifetime of the trains, with HSR at 7.8 gCO2eq/seat-km and conventional rail at
7.5 gCO2eq/seat-km. This is because the importance of emissions from direct energy consumption
decreases due to decarbonisation of electricity generation;
•
Per passenger-km (pkm) HSR is anticipated to produce significantly lower GHG emissions than
conventional rail. This is the case both when assuming typical differences in European occupancy
levels between conventional and HSR and for the modelled differences in occupancy levels from
the NLP Strategic Business Case. On average HSR (at 30.3 gCO2eq/pkm) is expected to result in
around 15% less GHG emissions on average than conventional rail (at 35.7 gCO2eq/pkm) in
2025, according to the calculations using central values. This GHG emissions for HSR reduce
further to 18.8% less (at 18.5 gCO2eq/pkm) than conventional rail (at 22.7 gCO2eq/pkm) when
considering them over the 30-year lifetime of the trains. The differential increases further when
modal shift and demand creation are factored in – to 17.4% less (26.4 gCO2eq /pkm and 32.0
gCO2eq/pkm respectively for HSR and conventional rail) in 2025, and 23.5% less (15.1
gCO2eq/pkm and 19.7 gCO2eq/pkm respectively) over the 30-year train lifetime;
•
Impact of electricity decarbonisation: When assuming current grid electricity emission factors
and electric train models the GHG emissions due to direct energy use of the train accounted for
over 80% of the total emissions (with 18% due to rail infrastructure and <1% due to indirect
emissions due to trains). However, the direct train component drops to around 28% when
assuming the use of new trains over 30 years from 2025 and the CCC’s proposed rapid
decarbonisation of UK electricity generation. In this case the emissions resulting from new rail
infrastructure dominate, accounting for around 70% of the total. The majority of the emissions
from construction of new rail infrastructure result from the use of concrete and steel. Significant
gains might therefore be achieved by focussing on reducing the emissions footprint of these
materials.
•
Comparison of conventional and high-speed rail under central assumptions: Conventional
and high-speed rail were compared for the different reference routes for services proposed under
the NLP Strategic Business Case. Under the central assumptions the total average GHG
emissions over the 30 year lifetime of the trains were calculated to be 18.5 gCO2eq/pkm for highspeed rail and 22.7 gCO2eq/pkm for conventional rail. When modal shift and demand creation
effects are also included the average figures drop to 15.1 and 19.7 gCO2eq/pkm respectively for
HSR and conventional rail. The benefits of modal switching therefore outweigh the counter-action
of factoring in demand creation. Due to significantly lower modelled average occupancy levels, the
equivalent modelled services direct from Birmingham to Glasgow and Edinburgh have average
emission factors around double these figures.
•
Sensitivity analysis on occupancy levels and passenger numbers: The ±20% sensitivities on
occupancy levels and passenger numbers show that as the average percentage occupancy levels
of conventional and high-speed rail become closer together, the advantage high-speed rail has in
terms of direct emissions per passenger-km is eroded. Parity is reached in their relative
emissions when load factors for conventional rail are around 4% lower than those for high-speed
rail. However, it is the total passenger numbers that are critical in the analysis, as this affects the
allocation of emissions resulting from the rail infrastructure. Therefore a higher number of
services with lower occupancy but high overall passenger numbers is strongly favoured over
significantly less-frequent but high-occupancy services that potentially move fewer passengers.
iii
Comparing the Environmental Impact of Conventional and High-Speed Rail
•
Sensitivity analysis on the carbon intensity of electricity generation: The sensitivity on the
electricity decarbonisation rate shows that varying the assumption on future decarbonisation of
electricity generation has a 30-40% impact on the total greenhouse gas emissions and over 60%
on the component due to direct energy consumption by trains. Under central (rapid
decarbonisation) assumptions the range for the GHG emissions between 2025 and 2055
respectively was from 30.3 to 15.0 gCO2eq/pkm for respectively HSR and 35.7 to 19.0
gCO2eq/pkm for conventional rail (excluding the effects of modal shift and demand creation).
•
Sensitivity analysis on embedded greenhouse gas emissions: The percentage of recycling of
materials at the end of the life of infrastructure (and to much a lesser degree trains) has a very
significant impact on the final results. Because of the dominating effect of embedded
infrastructure emissions in the overall assessment this puts a high level of importance to designing
recyclability into the design of new infrastructure as far as possible. The sensitivities on % tunnels
on new line infrastructure and on the type of track also underline the importance of these elements
in the overall analysis. Using ballastless track results in significantly higher GHG emissions in its
construction compared to conventional track, but no detailed information was available on GHG
savings due to reduced maintenance. More detailed evaluation of the GHG savings potential
through avoided maintenance would be beneficial to inform the comparison should this option
become preferred over conventional track in the future. The sensitivity on the % tunnels on new
lines suggests that the alternatives to tunnelling should be investigated where possible.
•
Sensitivity analysis on modal shift and demand creation: The analysis using information from
the NLP Business Case showed that the benefits of modal shift from car and air tranpsort
outweighed the counteracting demand creation element in the overall analysis. They also showed
that the net benefits due to modal shift and demand creation for high-speed rail services are
notably larger than those for conventional rail, further improving high-speed rail’s relative
performance. Because of the complexity in changes to rail services and passenger numbers on
existing lines it was not possible to quantitavily factor in the impact if abstraction from existing rail.
Overall Conclusions and Recommendations for Future Work
Overall, this work has provided a comprehensive review and evaluation of the elements that contribute
to the overall energy consumption and net greenhouse gas emissions from electric rail. Through
detailed analysis and sensitivities this study has also explored the impacts of key assumptions on
these elements on the overall comparison of the relative performance of future conventional and highspeed rail on proposed new lines. The work has clearly demonstrated the significant net benefit of
high-speed rail services over equivalent conventional services in terms of energy consumption and
GHG emissions per passenger-km in the context of proposed new line development. Factoring in the
net effects of modal shift and journey creation adds to this advantage. Also highlighted is the
overriding significance of the GHG emissions due to new rail infrastructure in the anticipated future
where the electricity system is highly decarbonised. This in turn puts significant emphasis on the
importance of minimising emissions from the construction of any new rail infrastructure, focussing on
sourcing lower carbon materials and on the recyclability of end of life components. On the basis of the
analysis for this study, the development of new lines to provide high-speed rail services appears to be
highly desirable in reducing GHG emissions in the long-term. However, there will be very significant up
front GHG emissions from the construction of new infrastructure in the short-term.
The results of the work also suggest a number of areas for further research to help better understand
and minimise the environmental impact of rail.
iv
•
More detailed analysis of specific proposals including other environmental impacts: This work
has provided a preliminary scoping level assessment of the potential impacts of the
development a high-speed rail service in terms of greenhouse gas emissions. However, a
more detailed assessment would be beneficial once the preliminary proposals have been
firmed up. At this stage an assessment of the other environmental impacts would be
appropriate, such as emissions of air quality pollutants, noise and land-take.
•
Research into ways to minimise the environmental impact of new rail infrastructure: The
results on the relative importance of infrastructure emissions suggests a more detailed piece
of research focussing on this element would be worthwhile to include other impacts such
embedded emissions of air quality pollutants. Whilst a preliminary assessment of the impacts
have been carried out here, a more in depth life cycle assessment is desirable. Research into
the potential for minimisation of the GHG emissions footprint of new rail infrastructure through
sourcing of less carbon intensively produced materials would also seem worthwhile.
Comparing the Environmental Impact of Conventional and High-Speed Rail
Table of Contents
Executive Summary
Glossary and Energy Unit Equivalencies
1
2
3
ii
viii
Introduction
1
1.1
Scope of work
1
1.2
Information collection
2
1.3
Report structure
2
Factors Affecting Comparisons of Energy Consumption and GHG
Emissions
3
2.1
Direct energy consumption and emissions from trains
4
2.2
Indirect energy consumption and emissions from trains
15
2.3
Energy consumption and emissions resulting from rail infrastructure
20
2.4
Other factors affecting comparisons
24
Results of Comparative Analysis
32
3.1
Definition of scenarios
32
3.2
Breakdown of relative impacts
35
3.3
Sensitivity analysis on key parameters
40
4
Summary and Conclusions
45
5
References
50
Appendices
Appendix 1:
Consultation Questionnaire
55
v
Comparing the Environmental Impact of Conventional and High-Speed Rail
List of Figures
Figure 2.1:
Figure 2.2:
Figure 2.3:
Typical composition of energy demand for high-speed and conventional rail services
Energy flow diagrams for passenger trains with and without regenerative braking
Energy conversion losses for a German ICE electric multiple unit
Figure 2.4:
Figure 2.5:
Figure 2.6:
Figure 2.7:
Figure 2.8:
Figure 2.9:
Figure 2.10:
Comfort function demands for a train in UK winter (0°C)
7
Typical breakdown of components in electric multiple unit trains by weight
10
Typical breakdown of components contribution to drag in electric trains
10
Energy consumption of current and future rolling stock (kWh per seat-km)
13
Trend between energy use (kWh/seat-km) and speed (km/h) for European trains
13
Low and High Scenarios for Future Carbon Intensity of UK Grid Electricity
15
Proportional breakdown of materials used in electric rail rolling stock and corresponding
net emissions of greenhouse gases for production and disposal at different recycling
rates
18
Breakdown by electric rail infrastructure element of the net embedded greenhouse gas
emissions for (at a 50% recycling rate), annualised over the infrastructure lifetime
21
Proportional breakdown of materials used in electric rail infrastructure and
corresponding net emissions of greenhouse gases for production and disposal (at a
50% recycling rate)
23
The core New Line only options from London considered in the New Lines Programme
Strategic Business Case (NEW LINES PROGRAMME, 2009)
26
Speed Assumptions for the New Lines Programme Strategic Business Case (NEW
LINES PROGRAMME, 2009)
26
Detail on the full option (MB1.4.1) considered in the New Lines Programme Strategic
Business Case (NEW LINES PROGRAMME, 2009)
27
Train Service Specification for Full Option (MB1.4.1) considered in the New Lines
Programme Strategic Business Case (NEW LINES PROGRAMME, 2009)
27
Modal share of high-speed rail services and flights by journey time
30
Assumptions on the projected improvement in the greenhouse gas emissions from cars
and domestic air transport
31
Breakdown of the total GHG emissions from conventional and high-speed rail per seatkm for different routes (assumes current trains and carbon intensity of electricity)
35
Breakdown of the total GHG emissions from conventional and high-speed rail per seatkm for different routes (assumes future trains and carbon intensity of electricity)
36
Breakdown of the total GHG emissions from conventional and high-speed rail per
passenger-km for different routes (assumes future trains and carbon intensity of
electricity)
37
Breakdown of the total GHG emissions from conventional and high-speed rail per
passenger-km by impact area
38
Summary comparison of the relative performance of conventional and high-speed rail at
different timeframe assumptions (NLP-SBC Total)
39
Sensitivity analysis breakdown on the impact of varying occupancy levels and
passenger numbers on the comparison of total GHG emissions from conventional and
high-speed rail
40
Sensitivity analysis on the impact of the assumptions on the future decarbonisation
electricity generation to the comparison of conventional and high-speed rail
41
Sensitivity analysis on the impact of the assumptions on the % recycling of end of life
infrastructure and trains to the comparison of conventional and high-speed rail
43
Sensitivity analysis on the impact of the infrastructure assumptions on the % tunnels
and type of rail track to the comparison of conventional and high-speed rail
43
Figure 2.11:
Figure 2.12:
Figure 2.13:
Figure 2.14:
Figure 2.15:
Figure 2.16:
Figure 2.17:
Figure 2.18:
Figure 3.1:
Figure 3.2:
Figure 3.3:
Figure 3.4:
Figure 3.5:
Figure 3.6:
Figure 3.7:
Figure 3.8:
Figure 3.9:
vi
4
5
7
Comparing the Environmental Impact of Conventional and High-Speed Rail
Figure 3.10:
Sensitivity analysis on the impact of the assumptions on modal shift and demand
creation to the comparison of conventional and high-speed rail
44
List of Tables
Table 2.1:
Table 2.2
Table 2.3
Table 2.4:
Table 2.5:
Table 2.6:
Table 2.7:
Table 2.8:
Table 2.9:
Table 2.10:
Table 2.11:
Table 2.12:
Table 2.13:
Table 2.14:
Table 3.1:
Table 3.2:
Table 3.3:
Table 3.4:
Table 3.5:
Table 3.6:
Principal contributors and example values for the three Davis formula coefficients
6
Elasticities for efficiency measures on total energy consumption for current electric
trains
8
Modelled impacts of efficiency measures on energy consumption for Japanese
Shinkansen HSR
8
Summary of measures to reduce energy consumption from trains
9
Characteristics of current and future rolling stock used for conventional and high-speed
rail
12
Total greenhouse gas emissions (in kgCO2eq per tonne material) resulting from
different stages of the material lifecycle (production, recycling, other disposal)
16
Material breakdown for typical electric rail rolling stock and corresponding net emissions
of greenhouse gases for production and disposal at different recycling rates
18
Characteristics of current and future rolling stock used for conventional and high-speed
rail and the net greenhouse gas emissions under the central recycling scenario
19
Estimated energy and water consumption per train-drive km for train maintenance and
refitting
19
Estimated embedded emissions for electric rail infrastructure based on ballasted or
ballastless track, breakdown by element
22
Estimated annual in-use activity elements for electric rail infrastructure and equivalent
2007 emissions factors
23
Typical load factors for European high-speed rail services
25
Modelled average load factors for conventional and high-speed services from the New
Lines Programme Strategic Business Case (NEW LINES PROGRAMME, 2009)
28
Modelled average modal switch and journey creation for conventional and high-speed
services from the New Lines Programme Strategic Business Case (NEW LINES
PROGRAMME, 2009)
30
Summary definition of the Central, Low and High scenario assumptions used in the
analysis
32
Assumtions for scenarios on the projected greenhouse gas emission factors for
electricity, passenger cars and domestic flights
32
Detailed definition of the Central, Low and High scenario assumptions for passenger
numbers, occupancy and the proportion of tunnels on new lines for different services 33
Comparison of services in the New Lines Programme Strategic Business Case with
typical European high-speed rail services
34
Definition of the Central, Low and High scenario assumptions for modal shift and
demand creation on new lines for different services
34
Sensitivity analysis on the impact of the assumptions on modal shift and demand
creation to the comparison of conventional and high-speed rail (NLP-SBC Total)
44
vii
Comparing the Environmental Impact of Conventional and High-Speed Rail
Glossary
Term/Abbreviation Definition/Explanation
Carbon footprint
A measure of the impact human activities have on the environment in terms of
the amount of greenhouse gases produced
Catenary
The system of overhead wires suspended above the track that deliver power
to electric trains.
CH4
Methane
CO2
Carbon dioxide
eq CO2 or CO2eq
Carbon dioxide equivalent: a quantity that describes, for a given mixture and
amount of greenhouse gas, the amount of CO2 that would have the same
global warming potential (GWP), when measured over a specified timescale
(usually 100 years).
EMUs
Electric Multiple Units – a type of electric train that has powered vehicles
across the train formation, rather than a single power vehicle/locomotive at
either end with unpowered carriages.
GHG
Greenhouse gas
GWP
Global Warming Potential
IPCC
Intergovernmental Panel on Climate Change
LCA
Life cycle assessment
Load Factor
The fractional or percentage occupancy of a train
N2O
Nitrous oxide
Pantograph
A pantograph is a device fitted to the roof of the train that collects current from
the overhead wires.
passenger-km or pkm Passenger kilometre = Unit of measure representing the transport of one
passenger over one kilometre.
RE
Renewable energy
seat-km or skm
Seat kilometre = Unit of measure representing the movement over one
kilometre of one seat available in a train (or other mode of transport)
Tare mass
The technical term for the total unlaiden mass of a train
TOC
Train Operating Company
Energy Unit Equivalencies
From
/To - multiply by
Gigajoule, GJ
Kilowatthour, kWh
Tonne oil equivalent, toe
viii
GJ
1
0.00360
41.868
kWh
277.78
1
11630
Toe
0.023885
8.5985E-05
1
Comparing the Environmental Impact of Conventional and High-Speed Rail
1
Introduction
The New Lines Programme is to test the hypothesis that in 2020, the existing rail lines from London to
the North and West will be operating at full capacity and the conventional and the next generation
tools for increasing capacity will be exhausted. There will be the need for additional intervention.
The programme aims to develop and evaluate the options for building new lines; including in this is the
need to evaluate the environmental impacts of such an intervention in terms of expected energy
consumption of new rolling stock, understand any step change in energy consumption between new
versus existing rolling stock including diesel versus electric and to assess localised environmental
impact during and after construction.
As a result there is a need to better understand the environmental impact of building one or more new
lines in terms of:
•
Performance (energy consumption) of rolling stock, both current high-speed (electric),
conventional (diesel) rolling stock and future electric rolling stock;
•
Seating occupancy levels in high-speed versus conventional services;
•
Estimated direct and indirect greenhouse gas emissions from diesel and electric rolling stock (both
in current and likely future electric mix);
•
Estimated emissions resulting from the construction, maintenance and decommissioning of rolling
stock;
•
The potential energy consumption/emissions resulting from construction of new infrastructure in
terms of materials used in the construction of infrastructure (and the energy
consumption/emissions per kg of these materials) as well as the energy use/emissions resulting
from infrastructure construction activities;
•
The role of energy consumption/emissions savings resulting from modal shift and factoring in
demand generation in the overall comparison.
This environmental study was carried out to assess the relative environmental performance of
conventional and high speed electric rail services. The purpose of this work is to provide an objective
comparison between the different options and the key assumptions that affect the outcome of the
comparison. In doing this, the work also needs to take into account the long timeframes associated
with planning and constructing large railway infrastructure projects including wholly new rail lines (e.g.
around 20 years for both the Channel Tunnel Rail Link and Crossrail). Hence comparisons will need to
be made on the anticipated performance of future high-speed and conventional rail rolling stock likely
to be put into service in the 2025-2030 timeframe.
1.1
Scope of work
1.1.1
Definition of High-Speed Rail and Evaluation of Environmental Impacts
For the purposes of this study, high-speed rail (HSR) services are defined as services faster than
typical UK intercity limit of 200 km/hour, typically over 250 km/hour and up to 350+ km/hour.
Comparisons in this report are made for similar types of electric rail services for HSR and conventional
rail – i.e. with conventional intercity service rolling stock (up to 200 km/hour), rather than rolling stock
used in slower stop-start commuter services.
Although there are a wide range of environmental impacts resulting from rail, the focus for the work at
this stage is primarily on energy consumption/ greenhouse gas emissions. Other environmental
impacts (e.g. air quality, noise and land-take) will be considered in more detail at a later phase and are
not within the scope of this project.
1
Comparing the Environmental Impact of Conventional and High-Speed Rail
1.2
Information collection
In order to obtain as up to date and accurate information as possible the project team needed to
consult widely with experts in industry and academia. This was to enable the collection of more
detailed information and develop of a more nuanced understanding of the issues than could be
achieved from a simple review of the available literature. As part of this consultation an introductory
letter was sent out in March 2009 requesting cooperation. A questionnaire (provided in Appendix 1)
was also provided alongside this request to help identify key information for the analysis. The letter
and questionnaire was subsequently followed up in email and telephone conversations and interviews.
Advice and information was gratefully received by the project team from the following organisations
and individuals which has informed the work:
•
•
•
•
•
•
•
•
Alstom;
Association of Train Operating Companies
(ATOC);
DeltaRail;
Department for Transport (DfT);
Forum for the Future (FFF);
Greengauge 21;
Hitachi;
Professor Roger Kemp (University of Lancaster);
1.3
•
•
•
•
•
•
•
Rail Industry Association (RIA);
Rail Industry Forum;
Rail Research UK (RRUK);
Rail Safety and Standards Board (RSSB);
Siemens;
Steer Davies Gleave;
International Union of Railways (UIC).
Report structure
The aim of this report is to provide a preliminary assessement of the relative environmental impact of
conventional and high-speed rail to help inform the wider business case being developed for the New
Lines Programme. The report provides a summary of the results from this project, including the review
of literature and consultation with stakeholders, results from comparative analyses, sensitivities and
conclusions. This report is structured as follows:
2
•
The theoretical background to train energy consumption, measures available to reduce this
and, discussion of the different elements affecting the comparison of high-speed and
conventional rail are provided in Section 2.
•
A summary and discussion of the comparative analysis is presented in Section 3;
•
The summary and conclusions for the work are presented in Section 4, together with
recommendations for future work;
•
References for source material are provided in Section 5.
Comparing the Environmental Impact of Conventional and High-Speed Rail
2
Factors Affecting Comparisons of Energy
Consumption and GHG Emissions
This chapter provides a discussion of the major elements that influence the overall energy
consumption comparison of conventional and high-speed rail. For the purposes of this work, the
comparison is restricted to energy use and greenhouse gas emissions. To properly consider the
relative impacts a range of factors need to be evaluated. These can be loosely grouped into the
following major categories:
1) Direct performance (energy consumption) of the rail rolling stock: In making comparisons it
is important to understand both the current situation and the anticipated performance of trains that
would be supplied to service new lines (i.e. most likely not going into service before 2025).
Comparisons between different trains are most usefully made in terms of the average energy used
per seat-kilometre (i.e. total energy used per kilometre for the whole train divided by the total
number of seats).
2) Seating occupancy levels and service frequency for high-speed versus conventional rail:
Seating occupancy levels (also known as the load factor) directly influence the net energy use /
emissions per passenger. There are significant differences between different types of services,
with high-speed services typically having higher occupancy levels. Together, average seating
occupancy and service frequency provide a measure of the intensity of the use of the rail
infrastructure. This is important to enable the embedded emissions from infrastructure to be
allocated on a per passenger-km basis.
3) Direct and indirect greenhouse gas emissions from electricity production (current and
likely future electricity mix): Assumptions on the projected carbon intensity of electricity in the
future will significantly impact on the relative importance of the components of direct energy
consumption by rail vehicles versus other elements such as the indirect/embedded energy
consumption/emissions from rolling stock and infrastructure production and disposal;
4) Indirect emissions resulting from the construction, maintenance and decommissioning of
rolling stock: A complete assessment of the impact or rail rolling stock needs to factor in the
energy consumption and emissions resulting from the production, disposal and maintenance
phases, as well as the direct energy consumption considered in earlier sections. There may be
differences between the types or volumes of different materials used for conventional and HSR
rolling stock that will affect their relative impacts;
5) Energy consumption/emissions resulting from construction and use of new rail
infrastructure: These can be very significant in size and could potentially significantly alter the
picture if there are significant differences between conventional rail and HSR in the total
passengers carried on rail new infrastructure. Elements include:
a) Materials used in the construction of infrastructure (and the energy consumption /emissions
per tonne of these materials);
b) Energy use/emissions resulting from infrastructure construction activities;
c) Annual variable energy use/emissions from infrastructure use and maintenance.
6) Energy consumption/emissions savings resulting from modal shift and factoring in
demand generation: Modal shift (e.g. from car and air transport to rail) and journey creation have
effectively opposing impacts on the overall evaluation. Whilst modal shift from other modes of
transport will provide additional benefits, demand creation effectively reduces the benefits of the
higher occupancy rates (and total passenger numbers) typically achieved by high-speed rail. It is
therefore important to provide a quantitative estimate of their respective impacts in the overall
evaluation. Abstraction from existing rail services is much more complex to quantify due to
changes in the type and frequency of service provision affecting the total energy consumption and
passenger-km.
The primary focus of the project work was initially on the first three categories. However, it was
important to consider the other areas where they may influence the relative comparison between HSR
and conventional rail. The analysis presented in Section 3 has shown the importance of including the
3
Comparing the Environmental Impact of Conventional and High-Speed Rail
other elements in the comparison, particularly the embedded emissions from construction of new rail
infrastructure.
The following sub-sections provide a more detailed discussion of the different elements and a
summary of the default and sensitivity data used for the analysis in Section 3.
2.1
Direct energy consumption and emissions from trains
2.1.1
Theoretical background to energy consumption
The direct energy consumption of electric train systems from electric substation to wheel-rail interface
can be broken down into four main areas:
•
•
•
•
Energy required to overcome the train’s resistance to movement;
Energy lost due to inefficiencies in the traction system between pantograph and wheel;
Energy used for on-board passenger comfort functions; and
Losses in the electrical supply system between the substation and pantograph.
Figure 2.1 shows the breakdown of energy demand for power taken from the catenary for high-speed
and conventional electric trains; it can be seen that the majority of demand for energy is to provide
motive power to overcome running and inertial \ grade resistance. Figure 2.2 shows the energy flow
for trains with and without regenerative braking (which feeds power back into the catenary that would
otherwise be dissipated as heat in friction brakes).
Figure 2.1:
Typical composition of energy demand for high-speed and conventional rail services
Regional (with
regeneration)
Regional (without
regeneration)
Intercity (with
regeneration)
High Speed (with
regeneration)
4
22%
69%
9%
20%
63%
17%
20%
Inertia and grade resistance
Notes:
20%
61%
19%
0%
22%
68%
10%
High Speed (without
regeneration)
20%
27%
53%
Intercity (without
regeneration)
28%
37%
35%
40%
60%
Running resistance
Reproduced from UIC EVENT (2003) Project report p27
80%
100%
Comfort functions
Comparing the Environmental Impact of Conventional and High-Speed Rail
Figure 2.2:
Energy flow diagrams for passenger trains with and without regenerative braking
a) Energy flow diagram for a passenger train without regenerative braking
Energy fed in at electric substation
Net energy intake
Train
Mechanical energy at the wheels (train motion)
Catenary
losses
Comfort
functions
Inertia and grade
resistance
Losses in
traction
system
Air resistance and
friction
Eventually dissipated in
brakes
b) Energy flow diagram for a passenger train with regenerative braking
Energy fed in at electric substation
Net energy intake
Train
Mechanical energy at the wheels (train motion)
Energy returned to
catenary
Comfort
functions
Inertia and grade
resistance
Losses in
traction
system
Air resistance and
friction
Regenerative
braking
Dissipated in
brakes
Losses in traction
system
Notes:
Catenary
losses
Reproduced from UIC EVENT (2003) Project report, Figures 2 and 3.
5
Comparing the Environmental Impact of Conventional and High-Speed Rail
2.1.1.1
Energy required to move the train
The energy required by the traction system accounts for around three-quarters of a train’s direct
energy use in service (UIC EVENT 2003), as indicated earlier in Figure 2.1. Traction energy demand
falls into two main categories: energy required to overcome inertial (ie accelerating the train) and
grade resistance, and energy needed to overcome running resistance (friction and drag).
The energy needed to overcome inertial and grade resistance is caused by and hence directly
proportional to train mass. Energy used is not dissipated but stored as kinetic and gravitational
potential energy respectively, and thus is theoretically fully recoverable. Regenerative braking aims to
recover as much of this energy as possible, but inefficiencies and operational restrictions mean that
inevitably a proportion is lost. The acceleration profile of the train (eg number of stop/start cycles,
driving style) affects the amount of energy needed to overcome inertia; topography of the line affects
the energy input needed due to grade resistance.
All energy needed to overcome running resistance is due to friction and is disspiated, mostly as heat.
An empirical expression for train resistance R on a straight level track is given by the Davis formula
(UIC EVENT 2003, RSSB 2007a) as:
R = A + Bv + Cv 2
Where A, B and C are constants for a given train-track system:
• A is the rolling resistance component independent of train speed v;
• B is the train resistance component dependant on train speed v;
• C is a coefficient dependent on train aerodynamic properties, proportional to the square of
train speed.
Table 2.1:
Principal contributors and example values for the three Davis formula coefficients
Principal contributors
Journal resistance; rolling rotational resistance; track resistance
Flange friction; flange impact; wave action of rail; wheel to rail
rolling resistance
Head end wind pressure; skin air friction on train sides; rear air
drag; air turbulence between vehicles; yaw angle of constant wind
A
B
C
Example values1
2240
43.53
4.41
Sources: Based on information from RSSB (2007a) and UIC EVENT (2003)
Notes:
1
Figures for the Swedish X2 high-speed train in a 6-car configuration running at 200km/h (v = 55.56m/s) calculated
from p20 of the EVENT final report.
It can be seen from the example values given in Table 2.1 that for a train travelling at 200 km/h (55.56
m/s) the aerodynamic term (Cv2) is around an order of magnitude greater than the other two terms,
which are similar to each other in magnitude. From this it can be concluded that:
• For modern high-speed rail travel, aerodynamic resistance dominates, and;
• For a given train, the resistance to motion increases approximately with the square of train
speed.
2.1.1.2
Losses in traction systems
Inefficiencies in various electrical and mechanical components in the train traction system lead to
energy being dissipated as heat, which in turn leads to a demand for ancillary energy for cooling.
Modern electric trains draw power from overhead lines, transform to DC (if necessary) before using a
traction inverter to provide 3-phase AC power to synchronous motors. State-of-the-art 16.7Hz 15kV
AC systems are around 85% power efficient at full load, with 50Hz AC or DC systems reporting higher
efficiencies (UIC EVENT, 2003). However it should be noted that overall power efficiency is lower at
lower loads, meaning that energy efficiency over a typical load cycle will be much lower than at peak
load. The inverse power train (used in regenerative braking) has approximately the same efficiency as
the forward power train (Kemp 2009, Hitachi 2009).
6
Comparing the Environmental Impact of Conventional and High-Speed Rail
In some cases (e.g. transformers), the most efficient components are also the heaviest, and so there
is a trade-off between reducing weight and reducing traction system losses when optimising traction
components.
Figure 2.3:
Energy conversion losses for a German ICE electric multiple unit
6%
12%
Gear
Motor
Traction inverter
26%
40%
DC link
Rectifier
Transformer
10%
5%
1%
Auxiliaries
Sources: Based on information from UIC EVENT (2003) Project report, p36
2.1.1.3
Comfort functions
Comfort functions include lighting, heating and ventilating coaches for passenger comfort. Whilst this
is mainly required during operation there is demand during stabled hours for cleaning and
maintenance and to ensure a comfortable temperature when the train begins operation. Comfort
function energy demand depends strongly on ambient temperature. The UIC EVENT (2003) study
estimated that comfort functions account for around 20% of the energy consumption of a train on
average. Since comfort function energy use is independent of train speed, a train that travels at higher
speeds or spends less time idling between stations will have a lower comfort function energy use per
seat-km than the same train taking more time to cover a given distance.
Figure 2.4:
Comfort function demands for a train in UK winter (0°C)
Passenger area
climate control
10%
8%
Heating of secondary
spaces
56%
Coach ventilation
26%
Lighting etc
Sources: Based on information from UIC EVENT (2003) Project report, p43
2.1.1.4
Losses in supply system
Losses occur in the electrical supply system due to resistance in catenary lines and inefficiencies at
substations. However, such losses will be constant for an electrical system supplying power at a given
voltage, regardless of the characteristics of the trains in the system. For this reason supply system
losses are not discussed further in this section.
7
Comparing the Environmental Impact of Conventional and High-Speed Rail
2.1.2
Principal measures to reduce energy consumption in electric rail
Measures to reduce energy consumption in electric rail can be grouped into two categories: technical
measures where hardware is modified to reduce its consumption in given operating conditions, and
operational measures where the operating conditions are modified to reduce the energy consumption
of hardware. These measures are summarised in Table 2.4, and the most significant are discussed in
more detail below.
None of the studies reviewed or interviews conducted as part of this research pointed to any
measures, technical or operational, which only applied to one of high-speed or conventional rail
services. The rolling stock manufacturers interviewed affirmed that the main technical measures
planned to reduce energy consumption in new rolling stock are common to both high-speed and
conventional rail, and the magnitude of benefit achieved by each measure was broadly similar.
Table 2.2 shows the elasticities1 for three key efficiency measures on overall train energy
consumption: improving the efficiency of the traction system, reducing train mass and reducing train
running resistance (friction and drag). The effect of regenerative braking on the elasticities is also
shown. It can be seen that the elasticities are very similar for high speed and intercity trains; the likely
differences for elasticities with regard to train mass and running resistance are discussed in 2.1.2.1
and 2.1.2.2 respectively. Similar levels of significance for the different types of measure can also be
seen in the simulated impacts for the Japanese high-speed Shinkansen trains in Table 2.3 (WCHSR,
2008). It is important to note that considering elasticities alone can be deceptive. In considering how
to target effort, the relative ease (and cost) of making improvements and the total remaining potential
for improvements also needs to be taken into account. For example, it may be that it is easier or more
cost effective to make significant reductions in train mass than to improve traction efficiency.
Furthermore, it is important to also take account of potentially counter-balancing effects of different
options. For example, high-efficiency transformers tend to be heavier, offsetting electrical efficiencies
gained.
The consensus amongst the rolling stock manufacturers interviewed was that high-speed trains will
always consume more energy per seat-km than conventional trains with the same technological
refinements, and that the current proportional difference in direct energy consumption is unlikely to
change significantly in the next 20-30 years.
Table 2.2
Elasticities for efficiency measures on total energy consumption for current electric trains
Train type
High speed without regenerative braking
High speed with regenerative braking
Intercity without regenerative braking
Intercity with regenerative traking
Notes:
Elasticities with regard to:
Traction
Train
Running
Efficiency
Mass
Resistance
1.00
0.17
0.63
1.11
0.12
0.66
1.00
0.19
0.61
1.12
0.14
0.65
Reproduced from UIC EVENT Project report, Table 2.
Table 2.3
Modelled impacts of efficiency measures on energy consumption for Japanese Shinkansen
HSR
Measures
Level of measure
Reducing vehicle weight
Reducing air friction
Efficiency of main electrical circuit
1 ton/car decrease
10% decrease
1% increase
Notes:
Impact on energy Impact for
consumption
1% change
-1%
-0.4%
-6%
-0.6%
-4.0%
-4.0%
Based on figures on effects estimated by simulation for Shinkansen vehicles with regenerating brake, 515 km from
Tokyo to Osaka (WCHSR, 2008)
1
Elasticity is defined as the level of influence an energy efficiency measure has on total energy consumption; for example, if for a certain train the
elasticity with regard to reducing train mass is 0.17, reducing the train mass by 10% will reduce overall energy consumption by 0.1 x 0.17 = 1.7%.
8
Comparing the Environmental Impact of Conventional and High-Speed Rail
Table 2.4:
Type of
measure
Techical
Summary of measures to reduce energy consumption from trains
Measure
Typical effect on energy
Typical Applicability for HSR vs CR
consumption
Elasticity
Broadly similar effects to both
Mass
See elasticities in Table 2.2;
types of train; slightly more
reduction
WCHSR (2008) report a 1 ton/car
0.12 benefit to services with more
decrease in weight on Shinkansen
0.14
frequent stops.
reduces energy consumption/CO2
emissions by 1% (Table 2.3).
More significant at higher
Aerodynamics See elasticities in Table 2.2;
speeds as proportion of
and friction
WCHSR (2008) report a 10%
0.65 energy demand due to
reduction in air drag on Shinkansen
0.66
aerodynamic drag is greater.
reduces energy consumption/CO2
emissions by 6% (Table 2.3).
The potential for reducing
Reducing
See elasticities in Table 2.2; 1%
energy consumption is the
traction
reduction in energy use of a traction
same for both train types.
system losses component reduces overall energy
1.11 use by 1%, more if regenerative
1.12
braking is employed as efficiency of
both traction and regenerative
braking systems are improved.
A prerequesite on any
Regenerative Kemp (2009) has estimated 5-7%
modern electric train. More
braking
energy savings on intercity services;
benefit to services with more
UIC EVENT (2003) implies trains
N/A
frequent stops.
that employ regenerative braking
use 8-9% less energy than trains
that do not.
Improved
TGV duplex achieves almost 30%
Equally applicable to both
space
reduction in energy per seat-km over
types of train; some
utilisation
single-storey TGV.
N/A
strategies (double-deck, wide
body) incompatible with UK
infrastructure.
Improved
Reducing passenger climate control
Trains that travel more km
comfort
energy consumption by 10% would
per day will have
function
reduce overall train energy use by
0.1
proportionally lower comfort
efficiency
around 1%2.
function energy demand per
seat-km.
Operational Increase load UIC EVENT (2003) states increasing
Equally applicable to both
factor
the load factor has the biggest
types of train; high-speed
1
potential of any measure to reduce
trains typically have higher
energy on a passenger-km basis.
load factors than intercity
services.
Efficient
RSSB (2007a) estimate a potential
Equally applicable to both
N/A
driving
for up to 7.5% of overall traction
types of train. Not an issue
strategies
energy use.
for consideration in this study.
Notes:
(a) Typical elasticities assume trains are fitted with regenerative braking systems. Estimates are derived from UIC EVENT
(2003).
2.1.2.1
Mass reduction
All of the rolling stock manufacturers interviewed cited mass reduction as the most significant measure
to reduce energy consumption of future models. Reducing train mass will reduce train energy use in
several ways. Primarily it reduces the energy needed to overcome inertial and grade resistance;
though theoretically recoverable by regenerative braking, inefficiencies in the traction system mean
that in reality only a proportion can be returned to the catenery in this way. The total regenerative
braking cycle, where energy is drawn from the catenary, put into train motion through the motors and
then converted back through the inverse drive train, has a typical maximum efficiency of (0.85 x 0.85 =
0.72) (UIC EVENT 2003, Kemp 2009). In some cases (and more likely for heavier trains or trains
travelling at higher speed) the braking force needed is greater than that available using regenerative
2
Calculation based on UIC EVENT 2003 figures
9
Comparing the Environmental Impact of Conventional and High-Speed Rail
braking, meaning additional dissipative braking is used, further reducing the cycle efficiency. Reducing
the train mass reduces the use of the comparitively inefficient regenerative braking cycle. Additionally,
mass reduction will reduce frictional running resistance.
Mass reduction is typically achieved through reducing the weight of specific components (e.g.
carbodies, bodies, bogies etc.) or through a system-based approach to lightweighting (e.g. the
articulated train design favoured by Alstom, which reduced the number of bogies by around 20% by
placing them between cars). Mass reduction will benefit services with less homogenous velocity
profiles (more accellerating and decelerating) most (i.e. those that accelerate and decelerate more
often).
Figure 2.5:
Typical breakdown of components in electric multiple unit trains by weight
Carbodies
15%
21%
Powered bogies,
motors and drives
Trailer bogies
17%
Propulsion equipment
22%
Interior
10%
Miscellaneous
(heating, batteries etc)
15%
Sources: Based on information from UIC EVENT (2003)
2.1.2.2
Aerodynamics and friction
As previously mentioned, at speeds above 200km/h aerodynamic drag dominates resistance to train
motion. Figure 2.6 shows a breakdown of a train’s drag by component; it shows that for a long train
(as high-speed and intercity train sets typically are), surface friction and drag around the bogies
dominate aerodynamic drag. The main strategies to reduce drag are streamlining the nose and tail
profile of the train, reducing flow separation around the bogies, pantograph and train body by
streamlining, and reducing the skin friction on the train roof and sides. More effort has gone into
reducing the drag of high-speed trains as at higher speeds aerodynamic drag is more significant, but
the same principles apply to conventional trains. Interviewees suggested that improvements to
medium and high speed train aerodynamics are incremental and that developments in the next 20-30
years are unlikely to radically alter the contribution of drag to energy demand, particularly in the UK
where regulation prevents some radical aerodynamic train shapes (Hitachi 2009, Kemp 2009).
Figure 2.6:
Typical breakdown of components contribution to drag in electric trains
3.5%
4.5%
Front
Tail
27.0%
Bogies and wheels
Pantographs
45.5%
7.5%
4.0%
8.0%
Ventilation etc
Underfloor equipment
Surface friction on side
and roof
Sources: Based on information from UIC EVENT (2003)
10
Comparing the Environmental Impact of Conventional and High-Speed Rail
2.1.2.3
Reducing traction system losses
New model specifications from the major rolling stock manufacturers report improved efficiency in the
traction system, both by improvements in the major components (for example permanent magnet
motors, medium frequency transformers) and improvements in the energy management control
software for the system as a whole. The fundamental technologies are the same for both high-speed
and conventional rail rolling stock and consequently forecast percentage energy savings are also
similar.
2.1.2.4
Reducing energy consumption for comfort functions
The principal component of comfort function energy use is air heating and cooling (UIC EVENT 2003).
Energy demand in air temperature control can be reduced either by reducing heat transmission
through improved coach insulation, or reducing fresh air intake through CO2 monitoring (fresh air
intake dependant on number of passengers rather than number of seats). In addition, energy can be
supplied from waste heat rejected from traction equipment (particularly in electric multiple units,
EMUs) if the requirement is for heat. It is thought that there is significant scope for energy savings in
this area (Kemp, 2009), but there is no anticipated difference in reduction of comfort function energy
use between high-speed and conventional trains.
2.1.3
Energy consumption of current and future rolling stock
In making comparisons between conventional and high-speed rail the previous sections have
discussed the theoretical background to energy consumption and the potential impacts of different
energy saving measures that might be applied. However, it is important not only to factor in these
considerations, but also the more practical market limitations on what new train types will actually be
available to be put into service at the 2025 timeframe. Compared to the road transport sector, the rail
industry is relatively small and trains have much longer service lives. As such, there are relatively few
train manufacturing companies and train model platforms available. Also as a result of this there are
relatively much longer development cycles for new platforms and much lower frequencies of platform
replacement. This makes it easier to foresee with greater certainty the likely characteristics and
performance of different types of electric trains in the timeframe we are interested in. The train
manufacturers consulted as part of this work have confirmed that the conventional and high-speed rail
platforms they are currently marketing will essentially be the ones that would be supplied for the 2025
timeframe. Although it is likely there will be some smaller incremental improvements in the efficiency
of the currently available platforms, major improvements are unlikely.
The following Table 2.5 provides a summary of the characteristics of different conventional and highspeed rail rolling stock, based on information from ATOC (2009) and DfT (2009a). The data on
energy consumption presented in this table and in Figure 2.7 are approximate figures based on a
combination of in-service measurements and modelled data. In real applications the actual achieved
energy consumption will vary significantly depending on the particular characteristics of a given
service. Factors that can significantly affect the actual performance will include elements such as:
• Service distance and number of intermediate stops;
• Line gradients;
• Service speeds;
• Variations in service speed along the route (e.g. due to major curves, junctions, etc.),
It can be seen from the table and figure that similar levels of improvements (15-20% reduction in
kWh/seat-km) have been achieved for conventional and high-speed rail rolling stock between the 1990
timeframe and the most recent models (excluding the Japanese Shinkansen). In addition, in Figure
2.8 shows a much less pronounced increase in energy consumption than has previously been
suggested. For the purposes of comparisons in this study we have taken the proposed Hitachi Super
Express (HSE) for the UK Intercity Express Programme (IEP) and Alstom AGV as representative of
the likely performance of rolling stock in the 2025 timeframe for conventional and high-speed rail
respectively. In this case, the relative increase in the energy consumption per seat-km of the AGV
and the HSE compared to equivalent current designs is around 18%, which is also consistent with the
trend line in Figure 2.8.
11
Comparing the Environmental Impact of Conventional and High-Speed Rail
The AGV is a train prototype rolling stock design from Alstom intended as the successor to France’s
current TGV high-speed trains, with a commercial service speed up to 360 km/h (220 mph). The AGV
will have distributed traction with motors under the floors of the passenger carriages, instead of the
current TGV configuration with separate power cars at either end of the train. This arrangement is
used on many regular-speed multiple-unit trains and also high-speed trains such as the Siemens
Velaro and Japan's Shinkansen trains (Wikipedia, 2009) built by Hitachi. Not having separate,
dedicated power cars creates additional space that enables the AGV to provide higher seating density
compared to current models. This design feature is also employed in the Hitachi Super Express (HSE)
trains. Alstom offer the AGV in configurations from seven to fourteen carriages, with a total of 250-650
seats (depending on internal layout and number of carriages). The AGV weighs less than its rivals
which reduces its power consumption, and it consumes significantly less energy than previous TGV
designs. Other design elements implemented to reduce the energy consumption of the AGV include
articulation and permanent magnet motors. Both of these elements contributed to a reduction in the
number of bogies, leading to further weight and aerodynamic benefits. It can be seen from Table 2.5
that both the HSE and the AGV have similar seating capacities at similar train lengths. However, the
AGV has shorter vehicles and therefore a larger number in each train unit for a similar capacity.
Table 2.5:
Train
Characteristics of current and future rolling stock used for conventional and high-speed rail
Conventional Rail
High Speed Rail
Class
Class
AVE Shinkan
Hitachi
Class 390
TGV
TGV
Alstom
91
373
S103 -sen 700
Super
Pendolino
Reseau Duplex
AGV
IC225
Velaro Series
Express Eurostar
1989
2003
1993
1992-6 1995-7 2004
1998
Future
Future
Year
Max Speed,
200
km/h
Service
200
Speed,km/h *
Seating Capacity 536
Length (m)
247
Vehicles per unit
11
Tare mass
498
(tonnes)
Mass per vehicle
45.3
(tonnes)
Mass per train
2.02
metre (tonnes)
Mass per seat
0.93
(tonnes)
Energy
0.035
consumption *
(kWh/seat-km)
225
200
300
300
300
350
300
360
200
200
300
300
300
300
270
300
439
215
9
649
260
10
750
394
20
377
200
10
545
200
10
404
200
8
1323
400
16
650
250
14
460
412
723
386
384
425
634
510
51.1
41.2
36.2
38.6
38.4
53.1
39.6
36.4
2.14
1.58
1.84
1.93
1.92
2.13
1.59
2.04
1.05
0.63
0.96
1.02
0.70
1.05
0.48
0.78
0.033
0.028
0.041
0.039
0.037
0.039
0.029
0.033
Sources: Figures for the Class 91 IC225 and Hitachi Super Express were supplied by DfT (2009a) based on public information
on the IEP. All other figures are based on figures from ATOC (2009), produced for Greengauge 21.
Notes:
12
* The energy consumption figures are based on the service speed. Here the service speed represents the typical
maximum speed of the train in service, usually dictated by the limits of the line infrastructure.
Comparing the Environmental Impact of Conventional and High-Speed Rail
Figure 2.7:
Energy consumption of current and future rolling stock (kWh per seat-km)
Energy Consumption, kWh/seat-km
Conventional
0.00
0.01
0.01
0.02
0.02
0.03
0.03
0.04
0.04
0.05
Class 91 IC225 (1989)
Class 390 Pendolino (2003)
Hitachi Super Express (Future)
Class 373 Eurostar (1993)
High Speed
TGV Reseau (1992-6)
TGV Duplex (1995-7)
AVE S103 Velaro (2004)
Shinkansen 700 Series (1998)
AGV (Future)
Figure 2.8:
Trend between energy use (kWh/seat-km) and speed (km/h) for European trains
0.065
Energy use, kWh/seat-km
0.060
0.055
0.050
0.045
0.040
0.035
0.030
0.025
150
200
250
300
350
Speed km/h
Notes:
This plot the trend-line of speed versus energy consumption has been updated from the original presented in the
RSSB (2007) traction energy metrics report using data from the more recent ATOC (2009) work and information from
the IEP (DfT, 2009a).
Although the anticipated AGV performance is taken as representative for future UK HSR, the highspeed Japanese Shinkansen 700 trains already achieve lower energy consumption than the AGV, as
shown in Table 2.5. In fact the newest model, the N700, has reportedly even lower energy
consumption per seat-km – an improvement of up to 19% over the 700 series (WCHSR, 2008).
However, there are a number of important barriers to trains with the energy performance of such trains
being used in the UK. The main barriers3 are linked to standards and interoperability: the wide body of
the Shinkansen (which allows for 3+2 seats across the carriage as opposed to 2+2 in the EU) and
3
Cited by both Hitach and by ATOC in discussions as part of the consulation for this project, and in the RSSB (2007) report.
13
Comparing the Environmental Impact of Conventional and High-Speed Rail
long nose section are incompatible with UK infrastructure. Furthermore, crashworthiness regulations
in the EU mean that European trains are heavier and cannot utilise certain parts of the train for
passenger seating when compared to their Japanese counterparts.
Other measures used to improve the performance per seat-km of rail in Europe include the doubledeck configuration used by the TGV Duplex. However, as for the wide-body configuration, the need
for future cross-compatibility of future rolling stock with the wider UK electricited network is a
significant limiting factor. Long-distance direct services are favoured for a number of reasons in the
UK (including minimising cost and maximising stock utilisation). It is therefore likely that any highspeed rolling stock procured for new high-speed lines would also need to be compatible to run on
conventional speed electrified infrastructure. This would preclude new rollingstock utilising either the
wide-body or double-deck designs to reduce energy consumption per seat.
2.1.4
Emissions from electricity generation
In establishing the lifetime emissions impacts resulting from direct rail energy consumption of different
options it is important to factor in the likely change in the carbon intensity of the future electricity
generation mix over time. Taking into account that services on any new lines would not be in place
before 2025 at the earliest, and the typical 30 year lifetime of rail rolling stock this means developing
suitable electricity carbon intensity scenarios to at least 2055.
Two legislative proposals will drive the decarbonisation of the UK electricity generation mix in the short
and long term:
1. The EU’s commitment to a 20% reduction in GHGs by 2020 (rising to 30% if an international
agreement can be reached beyond 2012) together with the EU Renewable Energy Directive target
of 20% of EU energy consumption to come from renewable sources by 2020. As a result of effortsharing between Member States, the UK-specific target is 15% reduction by 2020;
2. The UK’s domestic Climate Change Act target of an 80% reduction in GHGs by 2050 on a 1990
baseline.
In the short term the UK renewables share for electricity generation will need to be increased from
around 5% currently to between 30-37% by 2020. This is because it is assumed the bulk of the 15%
UK renewables target will need to come from electricity rather than other energy carriers (e.g. oil
based transport fuels).
In the long term the UK’s statutory target to reduce greenhouse gas emissions by 80% by 2050 is
taken as given, giving an approximate upper bound to the likely generation mix in this timeframe.
However, detailed energy system modelling and analysis has shown that decarbonising electricity
generation is one of the most cost-effective ways of making significant reductions in national carbon
emissions. The Committee on Climate Change’s (CCC) analysis has shown the greater potential and
cost-effectiveness of carbon emissions reductions in electricity generation in the short to medium term.
CCC has therefore recommended much faster decarbonisation of the electricity sector and a more
significant net contribution in the long term as essential to achieve the 2050 80% reduction goal (CCC
2008, ATOC 2009). This accelerated decarbonisation would require substantial measures to stimulate
renewables, nuclear and carbon capture and storage in the short-medium term.
For the analysis carried out in this study we have therefore constructed two scenarios for the future
carbon intensity of electricity, similar to those suggested by ATOC (2009) in their analysis for
Greengauge 21, presented in Figure 2.9. In the high scenario a 4% year-on-year reduction in carbon
intensity is assumed from 2010. The low scenario is more aggressive than the high scenario in terms
of the rate at which the carbon intensity of electricity generation decreases and follows the rapid
decarbonisation pathway proposed by CCC (2008)4. In both cases we have assumed the downward
trend continues after 2050, with essentially complete decarbonisation of electricity generation by 2070.
In addition to the direct emissions of CO2 from electricity generation there are also smaller direct
emissions of other greenhouse gasses - methane (CH4) and nitrous oxide (N2O). These account for
around 0.7% of the total direct emissions of greenhouse gases resulting from electricity production.
There are also further indirect emissions of CO2 and other greenhouse gasses resulting from the
4
For 2010-2020: DECC Energy Model, CCC abatement scenario, (extended ambition, central fuel prices); for 2025-2050: MARKAL modelling for
the CCC (80% trajectory), adjusted to take account of losses in transmission and distribution.
14
Comparing the Environmental Impact of Conventional and High-Speed Rail
extraction, transport and distribution of the primary fuels used in electricity generation. These indirect
emissions have been estimated to add a further 12% (Carbon Tust, 2008) to the total (and are
primarily due to the fossil fuel based component of generation). For completeness, we have included
both the direct and indirect emissions of all the greenhouse gases in the analysis for this study.
Figure 2.9:
Low and High Scenarios for Future Carbon Intensity of UK Grid Electricity
Projection of Carbon Intensity of UK Grid Electricity
0.60
Low Scenario
0.50
kgCO2 per kWh
High Scenario
0.40
0.30
0.20
0.10
0.00
2005
2010
2020
2030
2040
2050
2060
2070
Notes: The above figure only includes the direct emissions of CO2 from electricity generation. Resistive losses from
transmission and distribution systems are included in the figures presented.
2.2
Indirect energy consumption and emissions from
trains
A complete assessment of the impact or rail rolling stock needs to factor in the energy consumption
and emissions resulting from the production, disposal and maintenance phases, as well as the direct
energy consumption considered in earlier sections. Whilst no quantitative information has been
identified on the energy and emissions resulting purely from the rolling-stock manufacturing process,
information is available on the breakdown (in tonnes) of material used in the construction of a typical
electric vehicle unit. It is expected there would be some differences between different models of
rolling stock in terms of the relative breakdown of materials, but no model-specific information has
been identified. However, discussions with rolling stock manufacturers as part of this study have at
least indicated that there are no fundamental differences expected between conventional and highspeed trains. The assumption made for this study is therefore that the relative material breakdown by
weight of different rolling stock is similar.
A number of data sources were consulted to obtain information on the emissions due to the
manufacturing, recycling and disposal of the materials in question. Where data for specific materials
was not available, proxy data have been used when possible based on the closest equivalents. The
results for the group of materials included are summarised in the following Table 2.6, together with the
primary source basis of the data. This dataset includes the materials utilised in analysis of embedded
emissions from rail infrastructure in later Section 2.3.
15
Comparing the Environmental Impact of Conventional and High-Speed Rail
Table 2.6:
Total greenhouse gas emissions (in kgCO2eq per tonne material) resulting from different
stages of the material lifecycle (production, recycling, other disposal)
Production
Recycling
Other
Disposal
Material
Aggregates
Aluminium
Bricks
Concrete
Copper
Glass
Lubricating oil
Plastic
Plywood
Silt/soil
Steel
Synthetic rubber
Wood
Aggregates
Aluminium
Bricks
Concrete
Copper
Glass
Lubricating oil
Plastic
Plywood
Silt/soil
Steel
Synthetic rubber
Wood
Aggregates
Aluminium
Bricks
Concrete
Copper
Glass
Lubricating oil
Plastic
Plywood
Silt/soil
Steel
Synthetic rubber
Wood
Total Greenhouse gas (GHG)
emissions, kg/tonne material
8
11,000
192
1,090
1,700.9
840
1,004.8
3,100
887.1
4
3,100
2,774.1
84.3
-4
-9,000
10
-4
1,723.8
-315
0
-1,500
250
16
-1,300
40
250
10
10
10
10
10
10
3,938.6
40
10
10
10
40
10
Primary Data Source
GHG CF (2009)
GHG CF (2009)
GHG CF (2009)
DfT (2007)
SimaPro, 2007
SimaPro
SimaPro
GHG CF (2009)
SimaPro
GHG CF (2009)
GHG CF (2009)
SimaPro
SimaPro, 2007
GHG CF (2009)
GHG CF (2009)
GHG CF (2009)
GHG CF (2009)
SimaPro, 2007
SimaPro
N/A
GHG CF (2009)
SimaPro
GHG CF (2009)
GHG CF (2009)
SimaPro
SimaPro, 2007
GHG CF (2009)
GHG CF (2009)
GHG CF (2009)
GHG CF (2009)
GHG CF (2009)
GHG CF (2009)
GHG CF (2009)
GHG CF (2009)
GHG CF (2009)
GHG CF (2009)
GHG CF (2009)
GHG CF (2009)
GHG CF (2009)
Sources: GHG CF = Defra/DECC GHG Conversion Factors, 2009 update (forthcoming), Annex 9; SimaPro = Data from the
SimaPro EcoInvent database (extracted 2007).
Notes:
It is assumed that the alternative to recycling a material is disposal is to landfill = other disposal.
For each of the materials, the relevant factor from the Defra/DECC GHG Conversion Factors was
used (2009 update - Annex 9, forthcoming). In the absence of factors from this source, the SimaPro
lifecycle analysis software tool was used to calculate emissions associated with production and
recycling (where applicable) of most of the other material elements. The database values generally
represent average European production conditions, which is appropriate for the materials in question.
For the rest of the materials listed above, alternative sources of data were used to obtain the energy
usage to produce or recycle the material. These alternate sources are described below.
Glass: Because data on the energy used to produce or recycle toughened or laminated glass were not
available, data for regular glass from the Defra/DECC GHG Conversion Factors have been used as a
16
Comparing the Environmental Impact of Conventional and High-Speed Rail
proxy. According to Berryman,5 a glass recycling company, laminated and toughened glass can be
recycled, though separating the laminate from the glass does add an extra step (and cost) to the
process. After the glass is recovered, it is crushed and sold to the glass making industry. The glass
would be used for making bottles and glasses as opposed to being used for flat glass again. At this
point the process of recycling is the same as that for non-laminated flat glass; thus, emissions for
recycling flat glass have been used as a proxy.
Lubricating Oil: No specific information on the emissions from recycling lubricating oil has been
identified. Much of the waste oil collected for recovery in the UK is processed (by removing excess
water and filtering out particulates) and used as a fuel burnt in heavy industry and power stations. For
this study, unrecycled lubricating oil is therefore assumed to be burned and the appropriate emission
factor from the forthcoming 2009 update to the Defra/DECC GHG Conversion Factors has been used.
The preferred option for lubricating oils is re-refining for reuse as a base lubricant, although this
doesn't currently occur on a large scale in the UK.6 In comparison to the cost of burning waste oil, the
cost of recycling oil is relatively high, making it difficult for regenerated or laundered oil to compete with
virgin. In addition, it is not easy to market recycled lubricant, which is more poorly perceived to be of
poor quality compared to its virgin alternative7.
Concrete: DfT (2007) quotes a figure from the Carbon Trust for the production of concrete of 1.09
tonnes of CO2 per tonne of concrete. In the absence of other data, figures for the recycling or disposal
of concrete are assumed to be similar to comparable figures for aggregates from the forthcoming 2009
update to the Defra/DECC GHG Conversion Factors. [Relevant to the assessment rail infrastruce
covered in Section 2.3, but presented here for completeness].
Bricks: The emissions resulting from the production of bricks were taken from IJLCA (2003). In the
absence of other data, figures for the recycling or disposal of concrete are assumed to be similar to
comparable figures for aggregates from the forthcoming 2009 update to the Defra/DECC GHG
Conversion Factors. [Relevant to the assessement rail infrastruce covered in Section 2.3, but
presented here for completeness].
The net greenhouse gas emissions or a given train will vary significantly depending on the level of
recycling of the component materials at the end of its life. Three scenarios have been set up to
illustrate the sensitivity of this assumption
(a) No recycling (low scenario);
(b) 50% recycling (central scenario); and
(c) 90% recycling (high scenario).
The following Table 2.7 provides a summary of the material composition of a typical electric rail vehicle
and the corresponding production and disposal emissions for the different recycling scenarios. Figure
2.10 illustrates the percentage breakdown due to different materials in terms of the vehicle tonnage
and in terms of the net greenhouse gas emissions for different recycling scenarios.
5
Berryman (www.berryman-uk.co.uk).
http://www.wasteonline.org.uk/resources/InformationSheets/vehicle.htm
7
DTI (2001), “Waste Oil Recycling.” Available at http://www.nnfcc.co.uk/nnfcclibrary/productreport/download.cfm?id=69
6
17
Comparing the Environmental Impact of Conventional and High-Speed Rail
Table 2.7:
Material breakdown for typical electric rail rolling stock and corresponding net emissions of
greenhouse gases for production and disposal at different recycling rates
Component
Material
Steel
Aluminium
Copper
Glass
Lubricating oil
Wood
Plastic (and rubber)
Total
Tonnes
% Total
27.05
12.60
1.20
0.82
0.63
1.45
3.43
47.18
57%
27%
3%
2%
1%
3%
7%
100%
Net GHG
Tonnes CO2eq
Tonnes GHG
/tonne train
Central
Low
High
Central
Low
High
66.41
81.96
3.08
0.56
1.87
1.47
3.95
159.31
84.13
138.73
2.05
0.70
3.11
1.30
6.08
236.09
52.23
36.55
3.90
0.46
0.88
1.61
2.25
97.89
1.41
1.74
0.07
0.01
0.04
0.03
0.08
3.38
1.78
2.94
0.04
0.01
0.07
0.03
0.13
5.00
1.11
0.77
0.08
0.01
0.02
0.03
0.05
2.08
Sources: Breakdown of materials used in typical electric rolling stock vehicle was sourced from DeltaRail (2007). GHG emission
factors per tonne of material are based upon the data in Table 2.6.
Notes:
Information is presented for the following recycling scenarios: Low = No recycling, Central = 50% recycling, High =
90% recycling of materials used in the production of the train at the end of its lifetime. The remainder (any materials
not recycled) are assumed to go to landfill.
Figure 2.10: Proportional breakdown of materials used in electric rail rolling stock and corresponding net
emissions of greenhouse gases for production and disposal at different recycling rates
Material breakdown of a typical electric train
Net GHG (no recycling)
Steel
Steel
Aluminium
Aluminium
Copper
Copper
Glass
Glass
Lubricating
oil
Lubricating
oil
Wood
Wood
Plastic
Plastic
Material Breakdown
Net GHG Emissions – Low (No Recycling)
Net GHG (50% recycling)
Net GHG (90% recycling)
Steel
Steel
Aluminium
Aluminium
Copper
Copper
Glass
Glass
Lubricating
oil
Lubricating
oil
Wood
Wood
Plastic
Plastic
Net GHG Emissions –Central (50% Recycling)
Net GHG Emissions – High (90% Recycling)
Sources: Breakdown of materials used in typical electric rolling stock vehicle was sourced from DeltaRail (2007). GHG emission
factors per tonne of material are based upon the data in Table 2.6.
18
Comparing the Environmental Impact of Conventional and High-Speed Rail
The final element in the evaluation of the relative lifecycle impacts of conventional and high-speed rail
is to take account of their respective levels of activity in terms of total lifetime vehicle km. The
following Table 2.8 provides a summary of the estimated net emissions for the different trains
identified earlier in Section 2.1.3. Under the assumption that high-speed rail vehicles travel roughly
20% further in their lifetime compared to conventional equivalents the HSE and AGV trains taken as
representative for the 2025 timeframe appear to perform similarly per seat-km travelled.
Table 2.8:
Characteristics of current and future rolling stock used for conventional and high-speed rail
and the net greenhouse gas emissions under the central recycling scenario
Train
Seating Capacity
Vehicles per unit
Tare mass
(tonnes)
Mass per vehicle
(tonnes)
Emissions from
production and
disposal, tonnes
CO2eq
Typical lifetime
train-km (million)
Emissions over
lifetime,
kgCO2eq/train-km
Emissions over
lifetime,
gCO2eq/seat-km
Notes:
Conventional Rail
High Speed Rail
Class
Class
AVE Shinkan
Hitachi
Class 390
TGV
TGV
Alstom
91
373
S103 -sen 700
Super
Pendolino
Reseau Duplex
AGV
IC225
Velaro Series
Express Eurostar
536
439
750
377
545
404
1323
649
650
11
9
20
10
10
8
16
10
14
498
460
412
723
386
384
425
634
510
45.3
51.1
41.2
36.2
38.6
38.4
53.1
39.6
36.4
1,682
1,553
1,391
2,442
1,304
1,297
1,435
2,141
1,722
12
12
12
15
15
15
15
15
15
0.140
0.129
0.116
0.163
0.087
0.086
0.096
0.143
0.115
0.26
0.29
0.179
0.22
0.23
0.16
0.24
0.11
0.177
Typical lifetime train-km for high-speed rail is based on a 30 year lifetime and information from Siemens on typical
annual travel of 500,000 km, with the typical annual travel by conventional rail taken to be 400,000 km.
In addition to the embedded emissions resulting from the production and disposal of materials for rail
rolling stock, there will also be emissions resulting from the in-service maintenance of rail rolling stock.
Information was available from IJLCA (2003) on the average electricity, heating and drinking water
used, presented in Table 2.9. According to our research and consultation with industry experts for this
study, there is no reason to suggest that there should be any significant differences between figures
for conventional and high-speed rail. Therefore the figures from Table 2.9 are taken to be applicable
to both types of service.
Table 2.9:
Estimated energy and water consumption per train-drive km for train maintenance and
refitting
Element
Train maintenance
and refitting
Area
Operation
Item
Electricity
Heating
Drinking water
Value
0.191
0.811
3.881
Units
kWh/tdkm
kWh/tdkm
kg/tdkm
2007 Net GHG,
kgCO2eq /tdkm
0.117
0.149
0.000004
Sources: Activity data was sourced from IJLCA (2003), with corresponding net GHG per tdkm calculated for 2007 using
emission factors for electricity, gas and water use (supply and treatment) from the forthcoming 2009 update to the
Defra/DECC GHG Conversion Factors.
Notes:
tdkm = train-drive km, the number of km travelled by the train
19
Comparing the Environmental Impact of Conventional and High-Speed Rail
2.3
Energy consumption and emissions resulting from
rail infrastructure
In this section is discussed both the embedded energy consumption and emissions from rail
infrastructure and the emissions resulting from its ongoing operation and maintenance.
The embedded emissions resulting from the construction and eventual decommissioning of rail
infrastructure are expected to be very significant primarily due to the very large quantities of steel and
concrete used, which are both highly energy intensive in their production. Therefore in the evaluation
of the relative significance of such emissions it is necessary to understand both:
A. If there might be differences between the infrastructure required for conventional and high-speed
rail, and how significant these might be overall in terms of materials and construction emissions.
B. If there are significant differences in the intensity of use of this infrastructure, and how that could
affect the comparison per seat-km or passenger-km over the lifetime of the infrastructure.
Both of these elements have been explored in detail as part of this study, through research and
consultation with rail industry experts. In terms of the potential differences between the infrastructure
requirements, the following provides a summary for different elements:
•
Stations: It is assumed that the requirements of stations for high-speed and conventional rail
services would be the broadly similar, with few differences in total embedded energy from
construction and maintenance work on stations.
•
Track: The types of track that can be used for conventional of high-speed services are essentially
the same. Both conventional ballasted track (with gravel driveway) and ballanstless track can be
equally be used for conventional and high-speed services. The main difference for conventional
ballasted track used for high speed services is that greater quantities of ballast are required with
larger stone sizes. Ballastless track has significantly higher embedded emissions due to the
higher volume of concrete (4-6 times more than ballasted track). However, some studies have
suggested that over its lifetime this may be offset to a significant degree by decreased
maintenance.
•
Tunnelling: The construction energy use is expected to be broadly similar for both high speed
and conventional rail requirements.
•
Distance and Curves: Conventional rail would not require banked curves due to the tilting
technology (e.g. as already used by Pendolino rolling stock in the UK). However, depending on
the required curvature, in some cases high speed lines may still require banked curves or
superelevation, potentially adding to the embedded emissions.
•
Catenaries and other infrastructure: Both conventional rail and high speed require similar
catenaries infrastructure for electrification. Signalling equipment needs to be of higher
performance for high-speed rail services, but this is unlikely to affect the volume of component
materials and the corresponding greenhouse gas footprint.
•
Land area: Due to the pressure caused when two trains pass each other at high speeds (250-350
kph), the width of the transport corridor for high-speed lines needs to allow for a greater distance
between tracks (1-2 metres) when compared with conventional rail. Whilst this might be
significant in terms of land-take, it is unlikely to have a significant impact in terms of energy
consumption and greenhouse gas emissions compared to the materials used in infrastructure
construction.
These findings seem to indicate that broadly there are no anticipated differences between the
infrastructure requirements for conventional versus high-speed rail that might lead to significant
differences in embedded or in-use (e.g. maintenance) energy consumption or net greenhouse gas
emissions. However, the importance of differences in the intensity of use of the infrastructure for
conventional versus high-speed rail can only be established with an estimate for the embedded and
in-use emissions.
Estimates for the embedded emissions from new rail infrastructure have therefore been developed
based on materials use, materials transport (construction materials and excavated soil) and energy
used for boring tunnels. The results of these calculations on embedded emissions are presented in
20
Comparing the Environmental Impact of Conventional and High-Speed Rail
Table 2.10. This table provides figures for central, low and high recycling scenarios and a split of
figures for open track sections, tunnel track sections and an average for (a typical) 10% tunnels as
proportion of the total line km. Separate totals are also presented for track using standard gravel
ballast and for ballastless track to give low and high estimates respectively on the total potential
embedded infrastructure emissions. Illustrative breakdowns of the materials use and greenhouse net
gas emissions are also provided in Figure 2.11 and Figure 2.12, under assumptions of central (50%)
recycling and 10% tunnelling.
The table and figures illustrate several points: First, the importance of the assumptions made on
tunnelling (and bridges), which contribute significantly to the overall totals. Second, the type of track
laid has a significant impact on the total embedded emissions - in the order of 30-40 tonnes CO2eq per
rail track km. Third there is an overiding impact resulting from the use of concrete and steel in the
total GHG emissions, which can account for over 75% of the total embedded greenhouse gas
emissions (from less than 50% of the raw materials used in the construction).
Whilst the embedded emissions look very large, they will be much reduced when distributed per
passenger carried over the track, which can be as high as 9-10 million per year for major city-to-city
services alone (e.g. Eurostar) and higher still if services to multiple destinations are operated. This will
be explored in detail in the discussion of the main results (Section 3).
Figure 2.11: Breakdown by electric rail infrastructure element of the net embedded greenhouse gas
emissions for (at a 50% recycling rate), annualised over the infrastructure lifetime
Ballastless Track
Gravel Bed
0
50
100
150
200
250
300
Tonnes CO2 eq per rail track km per year
Notes:
Rails
Rail driveway
OHLE Structures and Wires
Tunnels
Bridges (road / railway)
Construction of buildings
Material transport
Tunnelling (10%)
Figures are based on annualised emissions based on the anticipated lifetime of individual elements and with tunnels
estimated at 10% of the total km
21
Comparing the Environmental Impact of Conventional and High-Speed Rail
Table 2.10:
Estimated embedded emissions for electric rail infrastructure based on ballasted or ballastless track, breakdown by element
Element
Railway track
Railway passenger
stations
Other
TOTAL (Low)
Area
Rails
Rail driveway (gravel bed)
(ballast, sleepers, etc)
Item
Steel
Steel
Concrete
Gravel
OHLE Structures and Wires Steel
Aluminium
Copper
Tunnels (10%)
Soil
Concrete
Steel
Bridges (road / railway) (1%) Concrete
Steel
Construction of buildings
Concrete
Bricks
Material transport (t/rtkm)
Transport
Tunnelling (10%), MWh/rtkm Electricity
Average (Tunnels 10%)
Open sections
Tunnel sections
Railway Track
Rail driveway (ballastless)
Other
TOTAL (High)
Material transport (t/rtkm)
Average (Tunnels 10%)
Open sections
Tunnel sections
Concrete
Steel
Transport
Tonnes
per rtkm
282
39
990
7,950
500
70
138
27,000
4,400
210
890
49
0.65
1.30
42,521
1,213
4,500
132
33,542
Life
(years
of use)
30
30
30
15
30
30
30
100
100
100
50
50
100
100
100
60
60
Net GHG emissions, kgCO2eq per Tonnes CO2eq per rtkm
tonne
per year
Other
Production Recycling Disposal Central Low
High
3,100
-1,300
10
23.1
29.2
18.2
3,100
-1,300
10
3.2
4.0
2.5
1,090
-4
10
36.1
36.3
35.9
8
-4
10
5.8
9.5
2.9
3,100
-1,300
10
40.9
51.8
32.2
11000
-9,000
10
15.3
25.9
6.8
1701
1,724
10
11.8
7.9
15.0
4
16
10
4.6
3.8
5.2
1,090
-4
10
48.1
48.4
47.8
3,100
-1,300
10
5.2
6.5
4.1
1,090
-4
10
19.5
19.6
19.4
3,100
-1,300
10
2.4
3.0
1.9
1,090
-4
10
0.007
0.007 0.007
192
10
10
0.003
0.003 0.003
8.405
8.405
8.405
15.7
15.7
15.7
0.411
5.0
5.0
5.0
236.5
266.7 212.4
162.1
191.3 138.7
906.7
944.7 876.3
1,090
3,100
8.405
-4
-1,300
8.405
10
10
8.405
82.0
5.4
7.5
270.6
200.8
945.4
82.5
6.8
7.5
298.0
227.2
980.6
81.6
4.2
7.5
248.8
179.6
917.3
Sources: Material data was sourced mainly from IJLCA (2003), EIR (2007) and DfT (2007) with corresponding net GHG per tdkm calculated using emission factors for different materials from Table 2.6.
An estimated 12,125 MWh/tunnel km electricity use is based on the energy used by Tunnel Boring Machines at 90% of max operation x 48.5 TJ/km(line) from Eurotrib (2008).
Notes:
22
rtkm = rail-track km. OHLE = overhead line equipment. Emissions from material transport have been estimated based on a 50:50 split of 100km round-trips by articulated HGVs and diesel rail
freight according to current UK average emission factors (GHG CF, 2009). Electricity emissions have been estimated based on average for the anticipated construction period (2010-2025)
from the projected emission factors summarised in Section 2.1.4.
Comparing the Environmental Impact of Conventional and High-Speed Rail
Figure 2.12: Proportional breakdown of materials used in electric rail infrastructure and corresponding
net emissions of greenhouse gases for production and disposal (at a 50% recycling rate)
Breakdown of Embedded Rail Infrastructure
Tonnes/track-km by Material
Breakdown of Embedded Rail Infrastructure
Tonnes/track-km by Material
Steel
Concrete
Steel
Concrete
Gravel
Aluminium
Gravel
Aluminium
Copper
Soil
Copper
Soil
Bricks
Bricks
Materials (conventional ballasted track)
Materials (ballastless track)
Breakdown of Embedded Rail Infrastructure
Tonne GHG Emissions by Element
Breakdown of Embedded Rail Infrastructure
Tonne GHG Emissions by Element
Steel
Concrete
Steel
Concrete
Gravel
Aluminium
Gravel
Aluminium
Copper
Soil
Copper
Soil
Bricks
Transport
Bricks
Transport
Electricity
Electricity
GHG emissions (conventional ballasted track)
Notes:
GHG emissions (ballastless track)
Soil = soil excavated as part of construction activities for rail driveway and from tunnelling (estimated 10% of total km)
In addition to the embedded emissions resulting from the production and disposal of materials for new
rail infrastructure, there will also be emissions resulting from the in-service maintenance of
infrastructure and heating of track points to avoid de-icing in winter. Information was available from
IJLCA (2003) on energy for heating points, and consumption of energy and materials building
operation and maintenance. This data is presented in Table 2.11 and taken to be applicable to both
conventional and high-speed services. Based on illustrative energy and water carbon intensity figures
for 2007, the figures in Table 2.11 for in-use infrastructure emissions appear to be insignificant next to
the total embedded infrastructure emissions.
Unfortunately no information has been identified to enable an estimate of the embedded energy use
and greenhouse gas emissions from rail track maintenance. It has therefore not been possible to
ascertain to what degree savings in track maintenance activities might offset the greater materials
footprint of ballastless track over conventional track with gravel bed driveways.
Table 2.11:
Estimated annual in-use activity elements for electric rail infrastructure and equivalent 2007
emissions factors
Element
Area
Railway track Points
Maintenance
Operation
Railway
passenger
stations
Maintenance
of buildings
Item
Heating
No data
Electricity
Heating
Drinking water
Concrete
Bricks
Value
840
No data
9.72
35.3
196
70
160
Units
kWh/rtkm
No data
Wh/passenger
Wh/passenger
g/passenger
mg/passenger
mg/passenger
2007 GHG EF
514.2
No data
0.0059505
0.0064938
0.0000002
0.0000765
0.0000323
Units
kgCO2eq
/rtkm
kgCO2eq
/passenger
Sources: Activity data was sourced from IJLCA (2003), with corresponding net GHG per tdkm calculated for 2007 using
emission factors for electricity, gas and water use (supply and treatment) from the forthcoming 2009 update to the
Defra/DECC GHG Conversion Factors.
Notes:
rtkm = rail-track km.
23
Comparing the Environmental Impact of Conventional and High-Speed Rail
2.4
Other factors affecting comparisons
2.4.1
Service occupancy levels/ passenger load factors
When comparing similar types of train or service it is appropriate to consider energy consumption and
emissions per seat km as a basis for comparison of their relative performance. However, different
types of service can have markedly different levels of passenger occupancy. The level of occupancy
is principally influenced by the following factors:
• Intrinsic demand for a particular journey;
• Length of train/seating capacity available;
• Service frequency;
• Train configuration planning and punctuality of services;
• Type of service /number of railway station stops – load factors tend to fall as stops increase;
• Segregated lines for high speed, regional, commuter and freight traffic;
• In-cab signalling systems for traffic management;
• Time of day.
Train occupancy levels (load factors) are a highly sensitive variable in the evaluation of impacts and
have a significant impact on the net emissions per passenger km. A discussion of occupancy/load
factors for high speed and conventional lines is therefore important.
2.4.1.1
Average occupancy levels/load factors from the literature
The load factors of conventional rail services across UK TOCs range from 25% to 48%, with a median
of 31%, or positive skew (RSSB, 2007). However, these average statistics hide significant variations
between different service segments and times. For example, services such as Euston – Glasgow
achieve high average occupancies of 45% (DfT, 2009a), on which the first 100km is often standing
only but the final 100km is considerably less busy. Conventional intercity load factors are generally
significantly lower than those for high speed services due to lenient reservation systems and lower
marketability of the service. In the UK a typical load factor for conventional intercity services is around
40% (RSSB, 2007).
In comparison, the following Table 2.12 summarises typical load factors for European high-speed rail
services, which range from 42% to as high as 88%. The lower load factors of the German ICE
services are notable compared to the French TGV and Spannish AVE. The primary reason for this is
considered to be a degree of over-capacity provided by the ICE services (ATOC, 2009a) in order to
compete more effectively with services from new low-cost airlines. On ICE lines, services are run
closer to the capacity of the network than comparable TGV and Eurostar services. Load factors above
60% are achieved by TGV and Eurostar in most cases, which is achieved by running trains under the
capacity of the infrastructure and pulling passengers to the train times (Network Rail, 2009). It is also
notable that the medium-long distance high-speed rail services seem to achieve higher average load
factors than the shorter distance services. This is presumably due to the increased competition with
road at lower distances, where road transport can more effectively compete in terms of journey time.
24
Comparing the Environmental Impact of Conventional and High-Speed Rail
Table 2.12:
Typical load factors for European high-speed rail services
Route
Country
London to Paris (Eurostar)
Paris to Strasbourg (TGV First class)
Paris to Strasbourg (TGV Second class)
Paris to Marseille (TGV First Class)
Paris to Marseille (TGV Second Class)
Nurnberg to Ingolstadt (ICE)
Berlin to Hamburg (ICE)
ICE Average
Madrid to Sevilla (AVE)
Malaga to Cordoba (AVE)
AVE long distance average
AVE medium distance average
2.4.1.2
UK-France
France
France
France
France
Germany
Germany
Germany
Spain
Spain
Spain
Spain
Distance,
km
496
487
487
740
740
90
288
472
159
-
Load
Factor
64%
77%
88%
60%
76%
42%
49%
50%
85%
56%
70%
56%
Year
Source
2009
2007
2007
2003
2003
2006
2006
N/A
1997
2007
2007
2007
Telegraph, 2009
ESPA, 2007
ESPA, 2007
BNET, 2003
BNET, 2003
RG, 2006
RG, 2006
EEA, 2000
MEET, 1997
UIC, 2009.
UIC, 2009
UIC, 2009
Comparisons with Data from the New Lines Programme Strategic Business Case
The Strategic Business Case (NEW LINES PROGRAMME, 2009) considers a range of options in a
corridor running from London to the North West and Scotland, including connections with Heathrow.
Several core New Line only options were investigated outlined in Figure 2.13, although other options
integrated with the classic network have also been considered. The business case carried out
demand modelling across a range for speed scenarios from conventional intercity rail speeds (125
mph / 200 kph) up to the current top end of high-speed rail services (225 mph / 360 kph). The speed
profile of the primary high-speed scenario investigated is defined in Figure 2.14, with the full option
provided in more detail in Figure 2.15.
Additional information was produced on service frequencies, passenger miles and loadings relating to
the full option (MB1.4.1). These were broken down into the component station to station flows with allday loading factors assumed over a 16 hour day. Figure 2.16 below shows the train service
specification for a standard hour for the full option (MB1.4.1).
25
Comparing the Environmental Impact of Conventional and High-Speed Rail
Figure 2.13: The core New Line only options from London considered in the New Lines Programme
Strategic Business Case (NEW LINES PROGRAMME, 2009)
MB1.0
MB1.1
MB1.2.1
MB1.4.1
London to
Manchester,
Birmingham via a
diverging mainline
with a link allowing
services between
Birmingham and
Manchester
With new line to
Liverpool and
Warrington
With new line to
Preston and
Edinburgh and
Glasgow
Full option
Figure 2.14: Speed Assumptions for the New Lines Programme Strategic Business Case (NEW LINES
PROGRAMME, 2009)
Assumed maximum speeds on N ew Lines from London Central
200mph
90mph
0-10miles
125mph
10-25miles
London Central
Notes:
26
125mph
25-10miles
N ew Line
90mph
10-0miles
Destination
Line speed maximum on New Line: 200mph (320kph), Line speed on diverging routes at junctions: 125mph.
Comparing the Environmental Impact of Conventional and High-Speed Rail
Figure 2.15: Detail on the full option (MB1.4.1) considered in the New Lines Programme Strategic
Business Case (NEW LINES PROGRAMME, 2009)
Edinburgh
Glasgow
Caledonian Junc
Preston
GM North
Manchester
Liverpool
GM South
Warrington
Mersey Junction
WM North
WM South
Birmingham
WM West Junc.
London Central
Figure 2.16: Train Service Specification for Full Option (MB1.4.1) considered in the New Lines
Programme Strategic Business Case (NEW LINES PROGRAMME, 2009)
Option MB 1.4.1 (TPH)
Formation 10 10 10 10 10 10 10 10 10 10 10 10 10 10 5
5
5
5
Glasgow
Edinburgh
Preston
Liverpool
Warrington
Manchester
Birmingham
London
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Notes:
In this service diagram, each line represents an individual return service that operates hourly (there being 18 in total).
27
Comparing the Environmental Impact of Conventional and High-Speed Rail
Research for the New Lines Programme (NEW LINES PROGRAMME, 2009) has carried out demand
modelling resulting in the load factors shown in Figure 2.15. These are based on services running to
the maximum capacity of the proposed new line infrastructure indicated in Figure 2.15. In this
modelling a modest estimate for journey creation has been used to not distort current demand. This
means that load factors could increase depending on the amount of induced demand, and also into
the future.
Table 2.13:
Modelled average load factors for conventional and high-speed services from the New Lines
Programme Strategic Business Case (NEW LINES PROGRAMME, 2009)
Route
Overall for all services
London - Birmingham
London - Manchester
London - Warrington - Liverpool
London - Preston - Glasgow
London - Edinburgh
Birmingham -Manchester - Preston - Edinburgh
Birmingham - Preston - Edinburgh
Notes:
Modelled Load Factors
Conventional:
High-Speed:
125mph (200kph) 200mph (320kph)
33%
42%
27%
34%
33%
42%
36%
47%
36%
47%
42%
54%
26%
34%
11%
14%
Figures for high-speed services are averages for particular routes based on more detailed estimates by route subsection. The estimates for occupancy levels on conventional speed routes are based on the average difference in
modelled total passenger numbers for conventional and high-speed services.
There is a clear difference between the modelled load factors from Table 2.13 and those of currently
operating European services from Table 2.12. The mean average for the modelled services is 42%,
compared to load factors typically above 60% for currently operating European services. One of the
reasons for this difference is that the modelled figures represent the capacity of the proposed new line,
and therefore show the maximum number of services available with their correlating load factors. New
lines are likely to conform to a model similar to that of the ICE (i.e. providing services closer to the
capacity of the line infrastructure). Furthermore, the demand figures (passenger numbers and load
factors) from NEW LINES PROGRAMME (2009) are based on modelling up to 2026. Therefore these
figures can be considered to be a conservative estimate as demand would be expected to increase
further into the future.
It is anticipated that services on a new high-speed line would not be hop-on conventional style with
low loadings (i.e. lower speed commuter line or local services). Instead it is anticipated they would be
frequent enough to ensure a pick and drop train on the same route does not detract from demand,
even when including platform waiting times. This would allow more room for demand growth or journey
creation over time. Current intercity type services running along the same route as new lines would
most likely be reduced to pick and drop style, to avoid competition for the high speed line and also
improve access to local stations. This should also improve the load factor of services on the new lines.
Splitting or joining of trains at certain points in a given service can be an effective way of improving
load factors. The German ICE trains do successfully implement splitting and joining when given a
straight, long platform and appropriate service load factors (although it is not used to a great extent).
In the UK, this option is rarely used due to health and safety concerns, possibilities of a malfunction,
consequences for other services and a lack of appropriate platforms. However, splitting and joining
would not be ruled out for new lines in the first instance (Network Rail, 2009).
2.4.2
Service frequency/infrastructure utilisation
Earlier sections have already referred to the potential significance of service frequency /infrastructure
utilisation in evaluating the relative impacts of conventional and high speed rail. In other studies it has
been common not to factor in the embedded emissions of infrastructure into the overall analysis,
negating the need to consider overall utilisation of this infrastructure. However, the discussion and
estimated emissions of greenhouse gasses resulting from infrastructure presented in Section 2.3 have
highlighted the significant importance of this element.
28
Comparing the Environmental Impact of Conventional and High-Speed Rail
Load factors are very important in evaluating the relative performance in terms of energy consumption
and emissions resulting from the use of conventional and high-speed rolling stock. However, in the
context of embedded emissions from infrastructure load factors need to be combined with information
on service frequency or total passenger numbers in order to get an accurate representation of the
intensity of infrastructure utilisation. This information is needed to allocate embedded emissions from
infrastructure on a per passenger km basis.
For example, a service operating at 60% load factor and 2 services per hour will transport the same
number of people per day as a similar service (with the same number of train seats) running at 40%
load factor and 3 service per hour. In this example, whilst the energy use/emissions resulting from the
train will be lower per passenger km in the first case, the embedded energy consumption/emissions
component will be the same in both cases.
Part of the attraction of high-speed rail services from this perspective is that they generally attract
higher passenger numbers than similar conventional rail services. Therefore the environmental impact
of embedded emissions from the infrastructure would be lower per passenger km travelled compared
to conventional equivalents. However, this benefit may be partly offset by journey creation, discussed
in the following Section 2.4.3.
2.4.3
Modal shift and journey creation
To make a complete assessment, both modal shift and journey creation need to be factored into the
equation. Rail services have demonstrated a significant ability to achieve high market shares in midrange transport services, where journey times are competitive with those for other transport modes as
illustrated in Figure 2.17. Research from Spain provided by UIC (2009) has also concluded that:
wherever high speed rail coexists with the other modes of transport, it attracts passengers away from
flights, private cars, coaches and conventional trains (regardless of whether the latter continues to
exist or disappears). The research also concludes that introducing high-speed rail services also
introduces additional demand that was not there previously and that analysis cannot therefore be
limited to comparson with the conventional trains.
Factoring modal shift and journey creation into the overall evaluation have effectively opposing
impacts. It is clear that modal shift from other modes of transport to high-speed rail will provide
additional benefits to the overall result. However, factoring in demand creation effectively reduces the
benefits of the higher occupancy rates (/passenger numbers) typically achieved by high-speed rail.
This is demonstrated in Table 2.14, which presents modal shift and journey creation percentages
derived from the demand modelling for the New Lines Programme Strategic Business Case. The
table also includes illustrative comparisons of the impacts of these figures, using assumptions on the
projected performance of future cars and aircraft. These assumptions have also been summarised in
Figure 2.18, with the following basis for the car and air emission factors:
•
Cars: Assume by the year 2070 all cars are powered either by grid electricity or renewably
produced hydrogen, resulting in effectively zero net emissions. Emission factors are assumed to
decrease linearly from 2007 averages to 2070. Load factors are similar to current average of 1.6.
•
Domestic Flights: Assume by the year 2070, 60% technical and other efficiency improvements to
aircraft and systems, plus 50% sustainable biofuel at 80% net CO2 saving. Emission factors
decrease linearly from 2007 averages (GHG CF, 2009) and include direct and fuel cycle
emissions. The impacts of radiative forcing from other non-CO2 greenhouse gases (mainly NOX
and water vapour) are excluded as their impacts currently have significant uncertainty attached to
them. Load factors are similar to current averages.
In making the comparison, ideally one would also factor in the relative impacts of abstraction from rail
services on existing infrastructure. However, modelling under the NLP Strategic Business Case
assumes significant changes to the types and frequencies of the services operated on existing
infrastructure as a result of new line development. Such changes could have a +ve or –ve net impact
on the comparison of conventional and high-speed rail. It has not been possible to quantify the size of
this impact in the overall analysis.
29
Comparing the Environmental Impact of Conventional and High-Speed Rail
Table 2.14:
Modelled average modal switch and journey creation for conventional and high-speed
services from the New Lines Programme Strategic Business Case (NEW LINES
PROGRAMME, 2009)
Type
High-Speed Average
Conventional Average
Demand component (%)
GHG Emissions, gCO2eq/pkm
From From
New
From From
New
Net
Car
Air
Demand Car (1) Air (2) Demand (3) Change
8.3% 1.4%
24.3%
-5.99 -1.86
4.70
-3.15
7.9% 1.3%
19.6%
-5.67 -1.81
4.67
-2.81
Notes:
(1)
Illustrative figures based on 30-yr cumulative average performance of cars of average occupancy of 1.6
(2)
Illustrative figures based on 30-yr cumulative average performance of domestic flights
(3)
Illustrative figures based on 30-yr cumulative average electricity generation factors and central assumptions for all other
elements (i.e. % recycling, % occupancy factors, % tunnels, total passenger numbers, etc).
Figure 2.17: Modal share of high-speed rail services and flights by journey time
Source:
30
Presentation by Jim Steer (Director, Greengauge 21) at an International Rail Air Conference on ‘Integrating HighSpeed Rail with Heathrow’, (GG21, 2008a)
Comparing the Environmental Impact of Conventional and High-Speed Rail
Figure 2.18: Assumptions on the projected improvement in the greenhouse gas emissions from cars and
domestic air transport
Projection of Carbon Intensity of Cars and Short-haul Air
0.25
Cars
Air
kgCO2eq per pkm
0.20
0.15
0.10
0.05
0.00
2005
2010
2020
2030
2040
2050
2060
2070
31
Comparing the Environmental Impact of Conventional and High-Speed Rail
3
Results of Comparative Analysis
This section presents the results from the comparative analysis of high-speed rail versus conventional
rail services and sensitivities on the assumptions for the key parameters that influence the
comparison. The principal assumption made in the analysis is that the comparison is made for
equivalent services on new line infrastructure and therefore is not a comparison of high-speed rail with
existing rail services.
3.1
Definition of scenarios
In this section is a summary of the main assumptions used in the analysis for the general results and
the sensitivity analyses. As part of the analysis a number of variables were explored to understand
the significance of different elements to the total greenhouse gas emissions. The following Table 3.1
provides a summary of the scenarios that have been defined. Additional detail on the values used in
the analysis are provided in Table 3.2 (for electricity, cars and flights) and in Table 3.3 (for passenger
numbers, % tunnels and % occupancy by reference route). The figures provided in Table 3.2 are
based upon the scenarios discussed and defined in earlier report sections 2.1.4 (for electricity) and
2.4.3 (for cars and domestic flights).
Table 3.1:
Summary definition of the Central, Low and High scenario assumptions used in the analysis
Conventional Train Model
High-Speed Train Model
Occupancy % and
Passenger numbers (1)
Rail Driveway type
Recycling % at end of life of
infrastructure and trains
Tunnel % of total line km
Time Period for electricity,
car and air emission factors
Electricity Scenario
Modal Switch and Demand
Creation
Notes:
Central / Default
Low
Hitachi Super Express Hitachi Super Express
Alstom AGV
Alstom AGV
Central
-20%
Conventional Gravel
50%
Conventional Gravel
0%
Ballastless Track
90%
Central
30-yr Cumulative Av.
(or 2025 (2))
Low
Central
-20%
2055
+20%
2025
(or 2007 (2))
High
+20%
Assumtions for scenarios on the projected greenhouse gas emission factors for electricity,
passenger cars and domestic flights
Relevant
time period:
2007
2025
2055
30-yr Cumulative Av.
32
Low
-20%
(1) For the purposes of the scenario analysis the occupancy levels/load factors and passenger numbers were
assumed to be intrinsically linked, i.e. 20% change in the load factor results in a 20% change in the total numbers of
passengers transported.
(2) In some cases different time periods have been used as the basis for certain scenario comparisons.
The 30-year cumulative average factor represents an average of the relevant emission factors over the 2025 – 2055
period for electricity (in kgCO2 per kWh), cars and domestic air (in kgCO2 per passenger km).
Table 3.2:
Notes:
High
Class 91 IC225
Class 373 Eurostar
+20%
Electricity Scenario
kgCO2eq/kWh
Low
High
0.612
0.612
0.218
0.306
0.023
0.083
0.066
0.177
Transport Scenario
kgCO2eq per pkm
Car
Air
0.151
0.202
0.108
0.166
0.036
0.106
0.072
0.136
The total GHG emission factors include both direct emissions (i.e. from electricity production, or from the car tailpipe
or aircraft engine) and indirect emissions (i.e. from the production and distribution of the electricity generation fuel or
transport fuel). Indirect emissions account for around 11% of the overall total for electricity and 15% for transport
fuels. The 30-year cumulative average factor represents an average of the relevant emission factors over the 2025 –
2055 period for electricity (in kgCO2 per kWh), cars and domestic air (in kgCO2 per passenger km).
Comparing the Environmental Impact of Conventional and High-Speed Rail
Table 3.3:
Detailed definition of the Central, Low and High scenario assumptions for passenger
numbers, occupancy and the proportion of tunnels on new lines for different services
Million passengers
per year
Reference Route
Typical European
NLP-SBC Total (2)
London - Birmingham
London - Manchester
London - Liverpool
London - Glasgow
London - Edinburgh
Birmingham - Glasgow
Birmingham - Edinburgh
Typical European
NLP-SBC Total (2)
London - Birmingham
London - Manchester
London - Liverpool
London - Glasgow
London - Edinburgh
Birmingham - Glasgow
Birmingham - Edinburgh
Notes:
Type (1) Central Low
HS
8.0
6.4
HS
20.4 16.3
HS
8.5
6.8
HS
10.6
8.5
HS
5.8
4.6
HS
5.8
4.7
HS
6.7
5.4
HS
2.1
1.7
HS
0.8
0.7
C
6.2
5.0
C
15.9 12.7
C
6.6
5.3
C
8.2
6.6
C
4.5
3.6
C
4.5
3.6
C
5.2
4.2
C
1.6
1.3
C
1.3
1.1
% Tunnels
% Occupancy
High
Central
Low
High
Central
Low
High
9.6
24.5
10.2
12.7
7.0
7.0
8.1
2.5
1.0
7.5
19.1
8.0
9.9
5.4
5.4
6.3
2.0
1.6
10.0%
11.6%
19.7%
21.8%
12.3%
10.2%
10.3%
10.7%
9.3%
10.0%
11.6%
19.7%
21.8%
12.3%
10.2%
10.3%
10.7%
10.3%
8.0%
9.3%
15.8%
17.4%
9.8%
8.2%
8.2%
8.6%
7.5%
8.0%
9.3%
15.8%
17.4%
9.8%
8.2%
8.2%
8.6%
8.2%
12.0%
13.9%
23.7%
26.2%
14.8%
12.3%
12.3%
12.9%
11.2%
12.0%
13.9%
23.7%
26.2%
14.8%
12.3%
12.3%
12.9%
12.3%
50%
42%
34%
42%
47%
47%
54%
34%
14%
39%
33%
27%
33%
36%
36%
42%
26%
11%
40%
34%
27%
34%
37%
37%
43%
27%
11%
31%
26%
21%
26%
29%
29%
34%
21%
8%
60%
51%
41%
51%
56%
56%
65%
41%
16%
47%
39%
32%
40%
43%
44%
50%
32%
13%
(1) HS = High-speed rail; C = Conventional rail.
(2) The figures for NLP-SBC Total takes into account the overlap of services using the same infrastructure and
represents the average figures per typical km over the entire length of the new lines.
The Central scenarios provided in Table 3.3 are based primarily on outputs from the New Lines
Programme Strategic Business Case (NEW LINES PROGRAMME, 2009). The corresponding High
and Low scenarios are based on a +20% and -20% sensitivity around the central assumptions
respectively. The data for the NLP-SBC Total Average reference route are weighted average figures
for each parameter over the entire proposed rail service network. The figures for the number of
passengers are higher than for the individual routes because they represent the average per km of
track taking into account different services share the some stretches of track. The track utilisation
intensity was also been factored into the calculations allocating embedded greenhouse gas emissions
from rail infrastructure for different services in the following sub-sections. The demand figures
(passenger numbers and load factors) from NEW LINES PROGRAMME (2009) are based on
modelling up to 2026. Therefore these figures can be considered to be a conservative estimate as
demand would be expected to increase further into the future.
As already discussed earlier in Section 2.4.1, there is a clear difference between the modelled load
factors from Table 3.3 and those of currently operating European services. A more detailed
comparison is provided in Table 3.4, which shows an average occupancy of 65% for the European
high-speed services reviewed. However, one of the reasons for this difference is that the modelled
figures represent the capacity of the proposed new line, meaning comparison with the German ICE
services is likely to be a closer match than the others. A central occupancy figure for typical European
services of 50% is therefore used for comparisons in the analysis.
The impact of demand creation was estimated by effectively removing these passengers from the
equation, thereby decreasing the overall percentage occupancy levels and increasing the GHG
emissions per passenger-km. The impact of modal switching was estimated by subtracting the
emissions that would have been generated by passengers travelling by car and air from the total8.
The assumptions on percentage modal shift and demand creation are presented in Table 3.5.
8
One passenger from an air service would not have any significant impact on the net emissions since the flight would still operate. However, for
the purposes of this analysis it is assumed that the modal switching of significant numbers of passengers beteen air and rail services (as
suggested by demand modelling) would result in the proportional reduction of the air passenger transport services.
33
Comparing the Environmental Impact of Conventional and High-Speed Rail
Table 3.4:
Comparison of services in the New Lines Programme Strategic Business Case with typical European high-speed rail services
Reference Route
NLP-SBC Total
London - Birmingham
London - Manchester
London - Liverpool
London - Glasgow
London - Edinburgh
Birmingham - Glasgow
Birmingham - Edinburgh
London - Paris
Madrid - Sevilla
Cordoba - Malaga
Berlin - Hamburg
Nuremberg - Munich
Paris - Marseille
Paris - Strasbourg
Average European
Notes:
Population
London
London
London
London
London
Birmingham
Birmingham
13,122,500
13,122,500
13,122,500
13,122,500
13,122,500
2,284,093
2,284,093
Birmingham
Manchester
Liverpool
Glasgow
Edinburgh
Glasgow
Edinburgh
2,284,093
2,240,230
1,103,089
2,300,000
450,000
2,300,000
450,000
London
Madrid
Cordoba
Berlin
Nordberg
Paris
Paris
13,122,500
7,061,748
325,453
5,000,000
500,132
12,672,000
12,672,000
Paris
Sevilla
Malaga
Hamburg
Munich
Marseille
Strasbourg
12,672,000
1,500,000
576,725
4,300,000
2,600,000
1,804,550
702,000
Distance
Journey
Load
(km)
Time (mins) Factor
764
179
42%
185
46
34%
290
66
42%
322
83
47%
612
131
47%
604
129
54%
467
120
34%
451
116
14%
496
472
155
288
171
740
487
401
135
165
77
100
60
180
140
121
64%
85%
56%
49%
42%
73%
86%
65%
Av. Speed,
km/h
256
241
263
233
280
281
233
233
220
172
198
173
171
247
209
198
Services
4
4
2
2
2
2
2
Class 373 (Eurostar)
AVE (RENFE)
AVE (RENFE)
ICE 3 (Deutsche Bahn)
ICE 3 (Deutsche Bahn)
TGV (SNCF)
TGV (SNCF)
Definition of the Central, Low and High scenario assumptions for modal shift and demand creation on new lines for different services
Service Type
High Speed Rail
Conventional Rail
34
Population Destination
Population figures are for the wider metropolitan area/ conurbation where data is available (only city figures were available for Edinburgh), rather than the city itself.
Table 3.5:
Notes:
Origin
Central
8.3%
7.9%
Car
Low
6.7%
6.3%
High
10.0%
9.5%
Central
1.4%
1.3%
Air
Low
1.10%
1.06%
High
1.64%
1.60%
New Demand
Central
Low
High
24.3%
19.4%
29.1%
19.6%
15.7%
23.6%
The central case is based on information from the NLP Strategic Business Case (NEW LINES PROGRAMME, 2009), with the Low and High scenarios being sensitivities of ±20%.
Comparing the Environmental Impact of Conventional and High-Speed Rail
3.2
Breakdown of relative impacts
This section provides a summary of the breakdown of emissions resulting from direct energy
consumption by the trains, indirect emissions resulting from trains (rolling stock embedded emissions
and from maintenance) and those from rail infrastructure (embedded and in-use emissions). In the
results provided in the following sub-sections, all variables (as defined in Section 3.1) are set to their
central values /defaults unless otherwise stated.
3.2.1
Relative impacts per seat-km
This section provides a comparison of the relative performance of conventional and high-speed rail
independently of passenger occupancy levels and total passenger numbers. As a frame of reference
it is useful to consider how the currently active conventional and high-speed rolling stock might
compare on the proposed new lines infrastructure and services. The following Figure 3.1 provides a
comparison of the estimated net greenhouse gas emissions per seat-km for the different reference
routes assuming:
•
•
•
2007 values for grid electricity emission factors;
Conventional Rail energy consumption = Class 91 IC225;
High-Speed Rail energy consumption = Class 373 Eurostar.
Figure 3.1:
Breakdown of the total GHG emissions from conventional and high-speed rail per seat-km
for different routes (assumes current trains and carbon intensity of electricity)
Conventional
High-Speed
Total GHG Emissions, gCO2eq per seat-km
0
5
10
15
20
25
30
35
Typical European
NLP-SBC Total
London - Birmingham
London - Manchester
London - Liverpool
London - Glasgow
London - Edinburgh
Birmingham - Glasgow
Birmingham - Edinburgh
Typical European
NLP-SBC Total
London - Birmingham
London - Manchester
London - Liverpool
London - Glasgow
London - Edinburgh
Birmingham - Glasgow
Birmingham - Edinburgh
Rail Infrastructure
Train Direct
Train Indirect
35
Comparing the Environmental Impact of Conventional and High-Speed Rail
Unsurprisingly Figure 3.1 shows that the higher energy consumption high-speed trains results in
greater net greenhouse gas emissions. Also the emissions directly resulting from the train’s energy
consumption account for on average over 80% of the total emissions. In contrast, the indirect
emissions from the train’s production, maintenance and disposal account for less than 1% of the total.
Emissions from production, maintenance, disposal and use of the electric rail infrastructure (and
stations) account for around 18% of the total.
Looking forwards and considering how the future rail rolling stock might perform on average over its
lifetime, Figure 3.2 shows a significantly different picture. In this example the following is assumed:
•
•
•
30-year cumulative average factor represents an average of the relevant emission factors over
the 2025 – 2055 period for electricity (in kgCO2 per kWh), grid electricity emission factors;
Conventional Rail energy consumption = Hitachi Super Express;
High-Speed Rail energy consumption = Alstom AGV.
As before it can be seen that on a per seat-km basis conventional rail has lower total emissions.
However, because of the significant decarbonisation of electricity generation over the 30 year period
the emissions resulting from the provision and use of the rail infrastructure now dominate. In this
scenario the infrastructure emissions account for around 70% of the total, with the direct emissions
from train use only accounting for 28% of the total. This is a very important result as it clearly
highlights the need to incorporate low carbon construction and materials procurement in any new line
development programme. As shown earlier in Figure 2.12 in Section 2.3, the majority of the emissions
from construction of new rail infrastructure result from the use of concrete and steel. Significant gains
might therefore be achieved by focussing on reducing the emissions footprint of such materials.
Figure 3.2:
Breakdown of the total GHG emissions from conventional and high-speed rail per seat-km
for different routes (assumes future trains and carbon intensity of electricity)
Conventional
High-Speed
Total GHG Emissions, gCO2eq per seat-km
0
2
4
6
8
10
12
Typical European
NLP-SBC Total
London - Birmingham
London - Manchester
London - Liverpool
London - Glasgow
London - Edinburgh
Birmingham - Glasgow
Birmingham - Edinburgh
Typical European
NLP-SBC Total
London - Birmingham
London - Manchester
London - Liverpool
London - Glasgow
London - Edinburgh
Birmingham - Glasgow
Birmingham - Edinburgh
Rail Infrastructure
36
Train Direct
Train Indirect
Comparing the Environmental Impact of Conventional and High-Speed Rail
3.2.2
Relative impacts per passenger-km
This section provides a comparison of the relative performance of conventional and high-speed rail
independently of passenger occupancy levels and total passenger numbers. As a frame of reference
it is useful to consider how the currently active conventional and high-speed rolling stock might
compare on the proposed new lines infrastructure and services. The following Figure 3.3 and Figure
3.3 provide a comparison of the estimated net greenhouse gas emissions per passenger-km for the
different reference routes with the central assumptions, i.e.:
•
•
•
•
30-year cumulative average factor represents an average of the relevant emission factors over
the 2025 – 2055 period for electricity (in kgCO2 per kWh), grid electricity emission factors;
Conventional Rail energy consumption = Hitachi Super Express;
High-Speed Rail energy consumption = Alstom AGV;
Modal shift and demand creation are factored into the results.
The figures demonstrate the importance of factoring rail service load factors and total passenger
numbers into the analysis. The higher modelled and typical load factors achieve by high-speed rail vs
equivalent conventional rail services result in significantly lower total greenhouse gas emissions per
passenger-km over all the routes for high-speed rail. The relatively low load factors on the services to
Glasgow and Edinburgh originating from Birmingham result in values much higher than the average.
Figure 3.3:
Breakdown of the total GHG emissions from conventional and high-speed rail per
passenger-km for different routes (assumes future trains and carbon intensity of electricity)
Total GHG Emissions, gCO2 eq per passenger-km
Conventional
High-Speed
0
10
15
20
25
30
35
40
45
Typical European
NLP-SBC Total
London - Birmingham
London - Manchester
London - Liverpool
London - Glasgow
London - Edinburgh
Birmingham - Glasgow
Birmingham - Edinburgh
Typical European
NLP-SBC Total
London - Birmingham
London - Manchester
London - Liverpool
London - Glasgow
London - Edinburgh
Birmingham - Glasgow
Birmingham - Edinburgh
Rail Infrastructure
Notes:
5
Train Direct
Train Indirect
The figures presented also take into account the net impacts of modal shift and demand creation on the totals.
37
Comparing the Environmental Impact of Conventional and High-Speed Rail
The higher occupancy levels by themselves contribute to reducing the direct and indirect train
emissions per passenger-km of high speed rail below (illustrated in Figure 3.4). As discussed in
earlier sections, greater total passenger numbers transported over the new lines also results in a
proportional reduction of the greenhouse gas emissions per passenger-km due to the infrastructure
and is by far the most important component. The enhanced modal switching achieved by high-speed
services also contributes to reducing their per passenger-km impact compared to conventional
equivalents. This is explored in more detail in the sensitivity analysis in Section 3.3.4.
Figure 3.4:
Breakdown of the total GHG emissions from conventional and high-speed rail per
passenger-km by impact area
Total:
NLP-SBC Total
Typical European
0
High-Speed
5
Conventional
10
15
20
25
Total gCO2eq per passenger-km
Infrastructure:
NLP-SBC Total
Typical European
High-Speed
0
2
4
6
8
10
12
Infrastructure gCO2eq per passenger-km
Conventional
14
16
Direct Train:
NLP-SBC Total
Typical European
High-Speed
0.0
1.0
Conventional
2.0
3.0
4.0
5.0
6.0
Train Direct gCO2eq per passenger-km
Indirect Train:
NLP-SBC Total
Typical European
High-Speed
Conventional
Notes:
38
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
Train Indirect gCO2eq per passenger-km
The figures presented also take into account the net impacts of modal shift and demand creation on the totals.
0.50
Comparing the Environmental Impact of Conventional and High-Speed Rail
The following Figure 3.5 provides an illustrative comparison of the relative performance of
conventional and high-speed rail per passenger-km at different time periods. The figure clearly shows
the shifting significance of the direct energy consumption of the trains over time. At the end of the new
trains’ lifecycle in 2055 the carbon intensity of electricity generation (and of car and air transport) has
decreased very significantly. The principal reason why emissions from infrastructure and indirect
emissions from trains are higher in 2055 is because the allocated credit for modal shift is lower in 2055
compared to 2025 as cars and flights have significantly decarbonised.
Figure 3.5:
Summary comparison of the relative performance of conventional and high-speed rail at
different timeframe assumptions (NLP-SBC Total)
Total:
Conventional
High-Speed
2007
2025
2055
0
10
20
30
40
50
60
70
80
90
14
16
18
Total gCO2eq per passenger-km
Infrastructure:
Conventional
High-Speed
2007
2025
2055
0
2
4
6
8
10
12
Infrastructure gCO2eq per passenger-km
Direct Train:
Conventional
High-Speed
2007
2025
2055
0
10
20
30
40
50
60
70
Train Direct gCO2eq per passenger-km
Indirect Train:
Conventional
High-Speed
2007
2025
2055
Notes:
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Train Indirect gCO2eq per passenger-km
Figures for 2007 assume train efficiencies for the Class 91 IC225 and Class 373 Eurostar for representative
conventional and high-speed rail. Figures for 2025 and 2055 assume train efficiencies for the Hitachi Super Express
and Alstom AGV for conventional and high-speed rail respectively. Modal shift, demand creation are also included.
39
Comparing the Environmental Impact of Conventional and High-Speed Rail
3.3
Sensitivity analysis on key parameters
The following sub-sections provide a number of sensitivity analyses on the major variables that
influence the overall calculation of greenhouse gas emissions from high-speed and conventional rail.
These include:
•
•
•
•
3.3.1
Service occupancy levels and total passenger numbers;
The carbon intensity of electricity generation;
Various infrastructure aspects, including the type of track used, the level of recycling of
materials at the end of the track’s lifetime and the proportion of tunnels along new lines;
The influences of modal shift and demand creation on the overall assessment.
Sensitivity on service occupancy / passenger numbers
This section provides a sensitivity analysis of the load factors and corresponding passenger numbers
for the central, low (-20%) and high (+20%) scenarios. The assumptions for the demand modelling for
the new lines business case is relatively conservative. There is potential for services on the proposed
new lines to reach the upper end of the range used in the sensitivity analysis as the services become
more established (Network Rail, 2009).
The results in Figure 3.6 demonstrate the significant impact assumptions on occupancy levels and
total passenger numbers have on the result. As the average percentage occupancy levels of
conventional and high-speed rail become closer together, the advantage high-speed rail has in terms
of direct emissions per passenger-km is eroded. For the current assumptions on the relative
efficiencies of conventional and high-speed rail trains, parity is reached when load factors for
conventional rail are around 4% lower than those for high-speed rail. However, it is the total
passenger numbers that are critical in the analysis, as this affects the allocation of emissions resulting
from the rail infrastructure. Therefore a higher number of services with lower occupancy but high
overall passenger numbers is strongly favoured over significantly less-frequent but high-occupancy
services that potentially move fewer passengers.
Figure 3.6:
Sensitivity analysis breakdown on the impact of varying occupancy levels and passenger
numbers on the comparison of total GHG emissions from conventional and high-speed rail
Total:
Conventional
High-Speed
High
Low
Central
0
5
10
15
20
25
30
Total gCO2eq per passenger-km
Infrastructure:
Conventional
High-Speed
High
Low
Central
Notes:
40
0
5
10
15
20
25
Infrastructure gCO2eq per passenger-km
High and Low scenarios are based on a +20% and -20% sensitivity around the central assumptions respectively.
The figures presented also take into account the net impacts of modal shift and demand creation on the totals.
Comparing the Environmental Impact of Conventional and High-Speed Rail
Figure 3.6:
Sensitivity analysis breakdown on the impact of varying occupancy levels and passenger
numbers on the comparison of total GHG emissions from conventional and high-speed rail
(continued)
Direct Train:
Conventional
High-Speed
High
Low
Central
0
1
2
3
4
5
6
7
0.6
0.7
Train Direct gCO2eq per passenger-km
Indirect Train:
Conventional
High-Speed
High
Low
Central
Notes:
3.3.2
0.0
0.1
0.2
0.3
0.4
0.5
Train Indirect gCO2eq per passenger-km
High and Low scenarios are based on a +20% and -20% sensitivity around the central assumptions respectively.
The figures presented also take into account the net impacts of modal shift and demand creation on the totals.
Sensitivities on the carbon intensity of electricity generation
The following Figure 3.7 provides the results of sensitivity analyses on the effect of different future
rates of electricity decarbonisation in comparison to the result using the most current UK average grid
electricity emission factor. The figure shows that varying the assumption on future decarbonisation of
electricity generation has a 30-40% impact on the total greenhouse gas emissions and over 60% on
the component due to direct energy consumption by trains. The impact on indirect emissions from
infrastructure and trains is much less significant.
Figure 3.7:
Sensitivity analysis on the impact of the assumptions on the future decarbonisation
electricity generation to the comparison of conventional and high-speed rail
Total:
Conventional
High-Speed
High
Low
2007
Notes:
0
10
20
30
40
50
60
70
80
Total gCO2eq per passenger-km
The figures presented also take into account the net impacts of modal shift and demand creation on the totals.
The High and Low decarbonisation scenarios assume the respective 30-year average electricity emission factors for
the period 2025-2055.
41
Comparing the Environmental Impact of Conventional and High-Speed Rail
Figure 3.7:
Sensitivity analysis on the impact of the assumptions on the future decarbonisation
electricity generation to the comparison of conventional and high-speed rail (continued)
Infrastructure:
Conventional
High-Speed
High
Low
2007
0
2
4
6
8
10
12
14
16
18
Infrastructure gCO2eq per passenger-km
Direct Train:
Conventional
High-Speed
High
Low
2007
0
10
20
30
40
50
60
0.5
0.6
Train Direct gCO2eq per passenger-km
Indirect Train:
Conventional
High-Speed
High
Low
2007
Notes:
0.0
0.1
0.2
0.3
0.4
Train Indirect gCO2eq per passenger-km
The figures presented also take into account the net impacts of modal shift and demand creation on the totals.
The High and Low decarbonisation scenarios assume the respective 30-year average electricity emission factors for
the period 2025-2055.
Sensitivities on the time period for electricity have already been presented earlier in Figure 3.5, which
illustrated the shifting significance of the direct energy consumption of the trains over time due to
significant decreases in the carbon intensity of electricity (and of car and air transport) by 2055.
3.3.3
Sensitivities on embedded greenhouse gas emissions
The sensitivity analysis on the level of recycling of materials from rail infrastructure and trains
presented in Figure 3.8 shows the high level of importance this consideration has in both areas.
Because of the dominating effect of embedded infrastructure emissions in the overall assessment this
puts a high level of importance to designing recyclability into the design of new infrastructure as far as
possible.
The sensitivities on % tunnels on new line infrastructure and on the type of track presented in Figure
3.9 also underline the importance of these elements in the overall analysis. Discussions with industry
experts as part of the consultation process for this work indicate that there is at the moment no
particular preference for either rail track type for either conventional or high speed rail. However,
should ballastless track become a more preferred option for other reasons in the future, more detailed
42
Comparing the Environmental Impact of Conventional and High-Speed Rail
evaluation of savings potential through avoided maintenance would be beneficial to inform the
comparison in terms of net greenhouse gas emissions. The sensitivity on the % tunnels indicates it
would be worthwhile to factor in the relative greenhouse gas emissions of tunnelling versus less direct
routing in any decision-making on pathways for future new line infrastructure.
Figure 3.8:
Sensitivity analysis on the impact of the assumptions on the % recycling of end of life
infrastructure and trains to the comparison of conventional and high-speed rail
Infrastructure:
Conventional
High-Speed
High
Low
Central
0
2
4
6
8
10
12
14
16
18
Infrastructure gCO2eq per passenger-km
Indirect Train:
Conventional
High-Speed
High
Low
Central
Notes:
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Train Indirect gCO2eq per passenger-km
The figures presented also take into account the net impacts of modal shift and demand creation on the totals.
Figure 3.9:
Sensitivity analysis on the impact of the infrastructure assumptions on the % tunnels and
type of rail track to the comparison of conventional and high-speed rail
Conventional
Gravel
Ballast:
Conventional
High-Speed
High
Low
Central
Ballastless
Track:
0
2
4
6
8
10
12
14
16
18
20
16
18
20
Infrastructure gCO2eq per passenger-km
Conventional
High-Speed
High
Low
Central
Notes:
0
2
4
6
8
10
12
14
Infrastructure gCO2eq per passenger-km
The figures presented also take into account the net impacts of modal shift and demand creation on the totals.
43
Comparing the Environmental Impact of Conventional and High-Speed Rail
3.3.4
Sensitivity on modal shift and demand creation
The following Figure 3.10 and Table 3.6 provides illustrative comparisons the potential importance of
modal shift for high-speed rail services in comparison to conventional equivalents on the basis of
demand modelling for the business case for new lines (NEW LINES PROGRAMME, 2009).
The figure and table show that the benefits of modal shift outweigh the counteracting demand creation
element in the overall analysis. They also show that the net benefits due to modal shift and demand
creation for high-speed rail services are notably larger than those for conventional rail, further
improving high-speed rail’s relative performance.
Figure 3.10: Sensitivity analysis on the impact of the assumptions on modal shift and demand creation
to the comparison of conventional and high-speed rail
Conventional
High-Speed
None
High
Low
Central
Notes:
0
5
10
20
25
Total gCO2eq per passenger-km
Central, Low and High scenarios are defined in Table 3.5 based on information from NEW LINES PROGRAMME
(2009). Low = Central - 20%, High = Central + 20%
Table 3.6:
Sensitivity analysis on the impact of the assumptions on modal shift and demand creation
to the comparison of conventional and high-speed rail (NLP-SBC Total)
Value
Total emission, gCO2eq per passenger-km
Net emission change due to modal shift and
demand creation, gCO2eq per passenger-km
44
15
Service Type
High-Speed
Conventional
High-Speed
Conventional
Central
15.1
19.7
-3.4
-3.0
Low
15.7
20.3
-2.7
-2.4
High
14.4
19.1
-4.1
-3.6
None
18.5
22.7
0
0
Comparing the Environmental Impact of Conventional and High-Speed Rail
4
Summary and Conclusions
Data Collection and Consultation
The purpose of this project is to provide an objective comparison of the relative energy consumption
and environmental impact of conventional versus high-speed rail. This is to help inform the wider
business case being developed as part of the New Lines Programme (NLP) into HS2. In doing this,
the work also needed to take into account the long timeframes associated with large infrastructure
projects. Hence comparisons needed to be made on the anticipated performance of future HSR and
conventional rail rolling stock in likely to be put into service in the 2025-2030 timeframe. In order to
obtain as up to date and accurate information as possible the project team consulted widely with
experts in industry and academia. This enabled the collection of more detailed information and
development of a more nuanced understanding of the issues than could be achieved from a simple
review of the available literature.
Factors Affecting Comparisons of Energy Consumption and GHG Emissions
For the purposes of this study, high-speed rail (HSR) services are defined as services faster than
typical UK intercity limit of 200 km/hour, typically over 250 km/hour and up to 350+ km/hour.
Comparisons in this report are made for similar types of electric rail services for HSR vs conventional
rail – i.e. with conventional intercity service rolling stock (up to 200 km/hour), rather than rolling stock
used in slower stop-start commuter services. The focus for the work for this project has been on
energy consumption and greenhouse gas emissions. Other environmental impacts will be considered
in more detail at a later phase and are not within the scope of this project.
To properly consider the relative impacts a range of factors needed to be evaluated, the following
provides a summary of the main factors and their impact on the assessment:
1) Direct performance (energy consumption) of the rail rolling stock: This is the principal (and
sometimes only) element considered in the assessment of different types of trains and services.
The principal measures available to reduce the energy consumption of electric trains include (in
order of significance according to the manufacturers consulted: (a) weight reduction, (b)
aerodynamic improvements (particularly significant for HSR) and (c) improvements in the overall
electrical efficiency (including the regenerative braking systems). According to industry experts
the relative performance of HSR and conventional rail is not anticipated to change significantly in
the future. Information obtained on the typical energy consumption of the forthcoming Alstom
AGV (0.033 kWh/seat-km) and the Hitachi Super Express (0.028 kWh/seat-km)9 were taken as
representative for HSR and conventional rail rolling stock going into service in the 2025-2030
timeframe. These trains also have similar seating capacities (650, 649) at similar lengths (250m,
260m). The relative impact of energy consumption to the overall picture is anticipated to decrease
significantly in the future with the decarbonisation of electricity generation.
2) Seating occupancy levels and service frequency for conventional versus high-speed rail:
Seating occupancy levels (also known as the load factor) directly influence the net energy use /
emissions per passenger-km from trains. There are significant differences between different types
of service. HSR services typically have higher occupancy levels which counter-balance the higher
energy use of the trains compared to conventional rail. Together, average seating occupancy and
service frequency provide a measure of the intensity of the use of the rail infrastructure in terms of
overall passenger numbers. The total number of passengers carried per km of track has a
significant impact on the allocation of the emissions resulting from provision and use of rail
infrastructure on a per passenger-km basis. Information was collected on typical European highspeed services, with different strategies adopted in terms of service provision in different cases.
Eurostar and TGV services tend to run at levels well under the network capacity and obtain very
high load factors. Conversely the German ICE services tend to operate much closer to network
capacity and achieve lower average occupancy levels. This is also the type of operation applied
in the detailed demand modelling carried out for the wider business case by NEW LINES
PROGRAMME (2009). Passenger numbers and occupancy levels were provided from the
9
As specified for the Department for Transport’s Intercity Express Programme (IEP)
45
Comparing the Environmental Impact of Conventional and High-Speed Rail
Strategic Business Case for the main new line/ service option and are used the analysis for this
project.
3) Direct and indirect greenhouse gas emissions from electricity production (current and
likely future electricity mix): Assumptions on the projected carbon intensity of electricity in the
future significantly impact on the relative importance of the components of direct energy
consumption by trains versus emissions due to other elements such as the production,
maintenance and disposal of infrastructure and trains. Significant decarbonisation of electricity
generation is expected in the timeframe new rolling stock would be utilised as part of meeting the
challenging statutory UK national target of 80% reduction of greenhouse gas emissions by 2050
(based on 1990 levels). This will significantly reduce the direct emissions from electric rail in the
future, so high and low electricity decarbonisation scenarios were developed. Indirect emissions
of GHGs from electricity generation (from production and distribution of primary fuels) are also
significant (around 11% of total) and should therefore be accounted for in the overall analysis;
4) Indirect emissions resulting from the construction, maintenance and decommissioning of
rolling stock: A complete assessment of the impact of proposed new trains also needs to factor
in the energy consumption and emissions resulting from their production, maintenance and
disposal phases. This study has identified no obvious differences between the types or
proportions of different materials used for conventional and high-speed trains that would
significantly affect their relative impacts. Data on the net life-cycle emissions resulting from the
production and disposal of different materials has been used to estimate a greenhouse gas
footprint in tonne CO2eq per tonne of vehicle for a typical electric train. Due to the very high
lifetime km travelled by rail vehicles the resulting net emissions per km are small compared to
emissions due to the direct energy consumption of trains currently (around 1%). However, their
significance will increase in the future as electricity generation decarbonises. The information
identified on energy and materials use for train maintenance suggested these were of even lower
significance (less than 0.1% of current direct in-use emissions) and are also considered unlikely to
be significantly different for conventional versus high-speed trains.
5) Energy consumption/emissions resulting from construction and use of new rail
infrastructure: At the start of the project this area was identified as potentially being very
important given the anticipated decarbonisation of the electricity system. The industry experts
consulted did not anticipate any differences in the infrastructure required by conventional versus
high-speed rail that were likely to significantly affect the embedded infrastructure emissions.
However, despite this any significant differences between conventional and HSR in the total
numbers of passengers carried on new rail infrastructure are expected to have a strong influence
on the overall comparison of their relative environmental performance. This is because the
embedded infrastructure emissions will be lower per passenger km where the emissions are
spread over a greater number of passengers for otherwise similar routes and services. Since
high-speed services typically attract higher load factors / passenger numbers this was anticipated
to favour high-speed rail in the overall comparison. Detailed information was identified in the
course of the project on the following elements that enabled the quantification of GHG emissions
for this area:
a) Volumes of materials used per km in the construction of new electric rail infrastructure (for
track with gravel ballast as well as ballastless track) - dominated by steel and concrete.
b) Information on the GHG emissions per tonne of material used in the track infrastructure;
c) Energy use/GHG emissions from major infrastructure construction activities (e.g. tunnelling);
d) Annual variable energy use/GHG emissions from infrastructure use (e.g. point heating).
Detailed information on modelled demand and passenger numbers for different reference routes
were sourced from the NLP Strategic Business Case in order to estimate the net greenhouse gas
emission per passenger-km component resulting from infrastructure.
Unfortunately, no information on the maintenance of infrastructure was identified that would
enable estimation of its impact.
6) Energy consumption/emissions savings resulting from modal shift and factoring in
demand generation: Modal shift and journey creation have effectively opposing impacts on the
overall evaluation of the environmental impacts of rail. Modal shift from other more carbon
intensive modes of transport will provide additional benefits. However, factoring in demand
creation effectively reduces the benefits of the higher occupancy levels (/ total passenger
numbers) typically achieved by high-speed rail. It was therefore identified as important to provide
a quantitative estimate of both of these impacts in the overall evaluation. Information on both
modal shift and demand creation was sourced from the NLP Strategic Business Case. This was
46
Comparing the Environmental Impact of Conventional and High-Speed Rail
used together with assumptions on the projected carbon intensity of passenger cars and domestic
air travel to estimate the net impact on the comparison of conventional rail and HSR.
Comparative Analysis Results
The results of the comparative analysis of conventional versus high-speed rail have been presented
split between three source areas:
4. GHG emissions resulting from to direct energy consumption by the trains;
5. GHG emissions resulting from the construction, maintenance, use and disposal of new electric rail
infrastructure;
6. GHG emissions resulting from the production, disposal and maintenance of electric trains.
These results have demonstrated the following points:
•
Per seat-km conventional rail uses less energy and produces fewer GHG emissions than highspeed rail. High-speed rail would be expected to result in around 9.3% more GHG emissions on
average (at 12.8 gCO2eq/seat-km) than equivalent conventional rail (at 11.7 gCO2eq/seat-km) in
2025, according to calculations using central scenario values. This difference drops to 4.4% more
over the 30-year lifetime of the trains, with HSR at 7.8 gCO2eq/seat-km and conventional rail at
7.5 gCO2eq/seat-km. This is because the importance of emissions from direct energy consumption
decreases due to decarbonisation of electricity generation;
•
Per passenger-km (pkm) HSR is anticipated to produce significantly lower GHG emissions than
conventional rail. This is the case both when assuming typical differences in European occupancy
levels between conventional and HSR and for the modelled differences in occupancy levels from
the NLP Strategic Business Case. On average HSR (at 30.3 gCO2eq/pkm) is expected to result in
around 15% less GHG emissions on average than conventional rail (at 35.7 gCO2eq/pkm) in
2025, according to the calculations using central values. This GHG emissions for HSR reduce
further to 18.8% less (at 18.5 gCO2eq/pkm) than conventional rail (at 22.7 gCO2eq/pkm) when
considering them over the 30-year lifetime of the trains. The differential increases further when
modal shift and demand creation are factored in – to 17.4% less (26.4 gCO2eq /pkm and 32.0
gCO2eq/pkm respectively for HSR and conventional rail) in 2025, and 23.5% less (15.1
gCO2eq/pkm and 19.7 gCO2eq/pkm respectively) over the 30-year lifetime of the trains;
•
Impact of electricity decarbonisation: When assuming current grid electricity emission factors
and electric train models the GHG emissions due to direct energy use of the train accounted for
over 80% of the total emissions (with 18% due to rail infrastructure and <1% due to indirect
emissions due to trains). However, the direct train component drops to around 28% when
assuming the use of new trains over 30 years from 2025 and the CCC’s proposed rapid
decarbonisation of UK electricity generation. In this case the emissions resulting from new rail
infrastructure dominate, accounting for around 70% of the total. The majority of the emissions
from construction of new rail infrastructure result from the use of concrete and steel. Significant
gains might therefore be achieved by focussing on reducing the emissions footprint of these
materials.
•
Comparison of conventional and high-speed rail under central assumptions: Conventional
and high-speed rail were compared for the different reference routes for services proposed under
the NLP Strategic Business Case. Under the central assumptions the total average GHG
emissions over the 30 year lifetime of the trains were calculated to be 18.5 gCO2eq/pkm for highspeed rail and 22.7 gCO2eq/pkm for conventional rail. When modal shift and demand creation
effects are also included the average figures drop to 15.1 and 19.7 gCO2eq/pkm respectively for
HSR and conventional rail. The benefits of modal switching therefore outweigh the counter-action
of factoring in demand creation. Due to significantly lower modelled average occupancy levels, the
equivalent modelled services direct from Birmingham to Glasgow and Edinburgh have average
emission factors around double these figures.
•
Sensitivity analysis on occupancy levels and passenger numbers: The ±20% sensitivities on
occupancy levels and passenger numbers show that as the average percentage occupancy levels
of conventional and high-speed rail become closer together, the advantage high-speed rail has in
terms of direct emissions per passenger-km is eroded. Parity is reached in their relative
emissions when load factors for conventional rail are around 4% lower than those for high-speed
rail. However, it is the total passenger numbers that are critical in the analysis, as this affects the
allocation of emissions resulting from the rail infrastructure. Therefore a higher number of
47
Comparing the Environmental Impact of Conventional and High-Speed Rail
services with lower occupancy but high overall passenger numbers is strongly favoured over
significantly less-frequent but high-occupancy services that potentially move fewer passengers.
•
Sensitivity analysis on the carbon intensity of electricity generation: The sensitivity on the
electricity decarbonisation rate shows that varying the assumption on future decarbonisation of
electricity generation has a 30-40% impact on the total greenhouse gas emissions and over 60%
on the component due to direct energy consumption by trains. Under central (rapid
decarbonisation) assumptions the range for the GHG emissions between 2025 and 2055
respectively was from 30.3 to 15.0 gCO2eq/pkm for respectively HSR and 35.7 to 19.0
gCO2eq/pkm for conventional rail (excluding the effects of modal shift and demand creation).
•
Sensitivity analysis on embedded greenhouse gas emissions: The percentage of recycling of
materials at the end of the life of infrastructure (and to much a lesser degree trains) has a very
significant impact on the final results. Because of the dominating effect of embedded
infrastructure emissions in the overall assessment this puts a high level of importance to designing
recyclability into the design of new infrastructure as far as possible. The sensitivities on % tunnels
on new line infrastructure and on the type of track also underline the importance of these elements
in the overall analysis. Using ballastless track results in significantly higher GHG emissions in its
construction compared to conventional track, but no detailed information was available on GHG
savings due to reduced maintenance. More detailed evaluation of the GHG savings potential
through avoided maintenance would be beneficial to inform the comparison should this option
become preferred over conventional track in the future. The sensitivity on the % tunnels on new
lines suggests that the alternatives to tunnelling should be investigated where possible due to the
tunnelling’s relatively high GHG impact.
•
Sensitivity analysis on modal shift and demand creation: The analysis using information from
the NLP Strategic Business Case showed that the benefits of modal shift outweighed the
counteracting demand creation element in the overall analysis. They also showed that the net
benefits due to modal shift and demand creation for high-speed rail services are notably larger
than those for conventional rail, further improving high-speed rail’s relative performance. Because
of the complexity in changes to rail services and passenger numbers on existing lines it was not
possible to quantitavily factor in the impact if abstraction from existing rail.
Overall Conclusions
Overall, this work has provided a comprehensive review and evaluation of the elements that contribute
to the overall energy consumption and net greenhouse gas emissions from electric rail. Through
detailed analysis and sensitivities this study has also explored the impacts of key assumptions on
these elements on the overall comparison of the relative performance of future conventional and highspeed rail on proposed new lines. The work has clearly demonstrated the significant net benefit of
high-speed rail services over equivalent conventional services in terms of energy consumption and
GHG emissions per passenger-km in the context of proposed new line development. Factoring in the
net effects of modal shift and journey creation adds to this advantage. Also highlighted is the
overriding significance of the GHG emissions due to new rail infrastructure in the anticipated future
where the electricity system is highly decarbonised. This in turn puts significant emphasis on the
importance of minimising emissions from the construction of any new rail infrastructure, focussing on
sourcing lower carbon materials and on the recyclability of end of life components. On the basis of the
analysis for this study, the development of new lines to provide high-speed rail services appears to be
highly desirable in reducing GHG emissions in the long-term. However, there will be very significant up
front GHG emissions from the construction of new infrastructure in the short-term.
The results of the work also suggest a number of areas for further research to help better understand
and minimise the environmental impact of rail.
Recommendations for Future Work
•
48
More detailed analysis of specific proposals including other environmental impacts: This work
has provided a preliminary scoping level assessment of the potential impacts of the
development a high-speed rail service in terms of greenhouse gas emissions. However, a
more detailed assessment would be beneficial once the preliminary proposals have been
firmed up. At this stage an assessment of the other environmental impacts would be
appropriate, such as emissions of air quality pollutants, noise and land-take.
Comparing the Environmental Impact of Conventional and High-Speed Rail
•
Research into ways to minimise the environmental impact of new rail infrastructure: The
results on the relative importance of infrastructure emissions in the overall equation suggests
a more detailed piece of research focussing on this element would be worthwhile to include
other impacts such embedded emissions of air quality pollutants. Whilst a preliminary
assessment of the impacts have been carried out here, a more in depth life cycle assessment
might be desirable. Research into the potential for minimisation of the GHG emissions
footprint of new rail infrastructure through sourcing of less carbon intensively produced
materials would also seem worthwhile.
49
Comparing the Environmental Impact of Conventional and High-Speed Rail
5
References
Alstom, 2009. Information provided in email and telephone conversations by Alstom in response to the
project questionnaire, April 2009.
Alstom, 2009a. “AGV The Latest Revolution in Very High Speed Trains”, information brochure
downloaded from the Alstom website, May 2009. Available at:
http://www.transport.alstom.com/_eLibrary/brochure/upload_294430.pdf
Atkins, 2008. Capacity Constraints on Mainline Routes, by Michael Hayes, Atkins, 2008
ATOC, 2009. ATOC analysis for Greengauge 21 on the CO2 impacts of High Speed Rail, “Energy
consumption and CO2 impacts of High Speed Rail: ATOC analysis for Greengauge 21”. Available from
the Greengauge 21 website at: http://www.greengauge21.net/hsr-development-programme.html
ATOC, 2009a. Information provided by ATOC in response to the project consultation, May 2009.
ATOC, 2007. Baseline Energy Statement, ATOC, 2007.
BNET, 2003. TGV maintains its dominance over air. Article from the International Railway Journal by
David Briginshaw, August 2003. Available on BNET at:
http://findarticles.com/p/articles/mi_m0BQQ/is_8_43/ai_107756364/
CCC, 2008. Building a Low-Carbon Economy –The UK's Contribution to Tackling Climate Change,
launch presentation by CCC for their inaugural report, 1 December 2008. Available from CCC’s
website at: http://www.theccc.org.uk/reports
Carbon Trust, 2008. “Carbon Trust Carbon Footprinting and Product Labelling Scheme: Emission
Factor Data Sheet, Version 6.6” Carbon Trust, London, United Kingdom, 2 February 2008.
DfT,2009. Britain’s Transport Infrastructure, High Speed Two, DfT, January 2009.
DfT, 2009a. Information provided in email and telephone conversations with rail experts at the
Department for Transport, May 2009.
DfT, 2007. “Estimated Carbon Impact of a New North-South Line”, London, Booz Allen Hamilton Ltd
for the Department for Transport, 12 July 2007. Available from the DfT website at:
http://www.dft.gov.uk/pgr/rail/researchtech/research/newline/carbonimpact.pdf
EEA, 2000. Indicator 22-23: Vehicle utilisation, from Indicators on transport and environmental
integration in the EU: TERM 2000. Available from the EEA’s website at:
http://www.eea.europa.eu/publications/ENVISSUENo12/page029.html
EIR, 2007. "Bering Strait Tunnel, Alaska-Canada Rail. Infrastructure Corridors Will Transform
Economy", by Richard Freeman and Dr. Hal Cooper, EIR (Executive Intelligence Review) Economics,
21 September 2007. Available at: http://www.larouchepub.com/eiw/public/2007/2007_30-39/200738/pdf/26-31_737.pdf
ESPA, 2007. The Espa Express, Newsletter of The Empire State Passengers Association, September
- October 2007, Vol. 31, No. 5. Available at:
http://www.esparail.org/index.php/newsletters/more/september_october_2007_newsletter/
Eurostar, 2009. Update of Eurostar CO2 Emissions using Energy Logging Train Data, Report to
Eurostar, Independent research undertaken by: Paul Watkiss Associates, February 2009. Executive
summary is available from: http://www.eurostar.com/pdf/treadlightly/Executive_Summary.pdf
Eurotrib, 2008. Railways, energy, CO2 - Part 2. Online article from the European Tribune, Thu Jan
24th, 2008 at 08:40:09 AM EST, Available at: http://www.eurotrib.com/story/2008/1/24/84011/9363
50
Comparing the Environmental Impact of Conventional and High-Speed Rail
UIC EVENT, 2003. Evaluation of Energy Efficiency Technologies for Rolling Stock and Train
Operation of Railways (EVENT) Final Report (2003), International Union of Railways (UIC) \ Institute
for Future Studies & Technology Assessment (IZT)
GG21, 2008. Linking Heathrow to a national High-Speed Rail network, a presentation by Jim Steer
(Director, Greengauge 21) at the International Rail-Air Organisation’s (IRAO) converence ‘Integrating
High Speed Rail with Heathrow’, London Victoria Park Plaza Hotel, 23rd October 2008
GHG CF (2009). Defra/DECC Greenhouse Gas Conversion Factors – 2009 update (forthcoming),
produced by AEA for Defra and DECC, June 2009. The current versions (and those from previous
years) of the conversion factors are available from Defra’s website at:
http://www.defra.gov.uk/environment/business/reporting/conversion-factors.htm
Hitachi, 2009. Information provided in telephone interviews with Hitachi representatives in response to
the project questionnaire, May 2009.
IJLCA, 2003. “Ecology Profile of the German High-speed Rail Passenger Transport System, ICE”, by
Christian von Rozycki and Heinz Koeser (Martin-Luther-University, Germany) and Henning Schwarz
(Deutsche Bahn AG, Germany). An LCA Case Study published in the International Journal of LCA 8
(2) 83 - 91 (2003).
IMechE, 2007. A response to the Government White Paper “Delivering a Sustainable Railway, A LowCarbon Transport Vision for the Future” from the Institution of Mechanical Engineers (IMechE) to a
Call for Evidence from the House of Commons Transport Committee Inquiry into the Government’s
White Paper on Rail (Cm 7176). Response provided: 9 October 2007.
Kemp, 2009. Information provided in telephone interview with Professor Roger Kemp, Lancaster
University, March 2009.
Kumagai, 2008. Dr. Norimichi Kumagai (2008), Keystone of High Speed Rail: Safety & Environment,
Railway Technical Research Institute of Japan, presentation to the 6th World Congress on High
Speed Rail
MEET, 1997. Estimating Emissions from Railway Traffic. A report by Morten W. Jørgensen and
Spencer C. Sorenson for the Project MEET: Methodologies for Estimating Air Pollutant Emissions from
Transport. Project funded by the European Commission under the Transport RTD Programme of the
4th framework program. 1997.
Network Rail, 2009. Information provided in telephone conversations with Network Rail experts
concerning initial plans for HS2 / New Lines. May 2009.
NEW LINES PROGRAMME, 2009. “New Lines Programme Strategic Business Case”, Network Rail,
2009.
Siemens, 2009. Information provided by email to AEA by Siemens AG in response to the project
questionnaire, May 2009.
RG, 2006. Football fever fuels DB traffic boom. Article by Murray Hughes in Railway Gazzette
International, 1 September 2006.
RSSB, 2007. T618 - Traction Energy Metrics, a report for RSSB by Interfleet and Lancaster University,
December 2007. Available from RSSB’s website at:
http://www.rssb.co.uk/pdf/reports/research/T618_traction-energy-metrics_final.pdf
RSSB, 2007a. Rail Safety and Standards Board (RSSB) (2007), T618 – Improving The Efficiency Of
Traction Energy Use, a report for RSSB by Interfleet and Lancaster University, December 2007.
Available from RSSB’s website at: http://www.rssb.co.uk/pdf/reports/research/T618_tractionrpt_final.pdf
Telegraph, 2009. Eurostar feeding on hunger for travel, article by Andrew Cave, from the Telegraph
online, 12 April 2009. Available at:
51
Comparing the Environmental Impact of Conventional and High-Speed Rail
http://www.telegraph.co.uk/finance/newsbysector/transport/5145700/Eurostar-feeding-on-hunger-fortravel.html
UIC, 2009. “Energy consumption and emissions of High Speed trains” (published in Spanish in “La
importancia de la velocidad”, by Alberto Garcia Alvarez, researcher of the Spanish Foundation for the
Railways (“Fundación de los Ferrocarriles Españoles”), and Professor in the engineering University of
Comillas in Madrid, edited by: Romo, E. and Zamorano, C. (2008). Draft English translation supplied
by UIC, 2009
van Wee et al (2003). Environmental impacts of high-speed rail links in cost–benefit analyses: a case
study of the Dutch Zuider Zee line. Bert van Wee (Delft University of Technology), Robert van den
Brink and Hans Nijland (National Institute of Public Health and the Environment (RIVM)),
Transportation Research Part D 8 (2003) 299–314
WCHSR, 2008. “Keystone of High Speed Rail: Safety & Environment”, UIC 6th World Congress on
High Speed Rail, Amsterdam 2008. Presentation by Dr Norimichi Kumagai, Dr. Executive Director,
Railway Technical Research Institute, JAPAN. Available from UIC’s website at:
http://www.uic.org/apps/presentation/kumagai.pdf
Wikipedia, 2009. Summary information and images on Alstom’s AGV, downloaded May 2009.
http://en.wikipedia.org/wiki/Automotrice_à_grande_vitesse
52
Comparing the Environmental Impact of Conventional and High-Speed Rail
Appendices
Appendix 1:
Consultation Questionnaire
53
Comparing the Environmental Impact of Conventional and High-Speed Rail
54
Comparing the Environmental Impact of Conventional and High-Speed Rail
Appendix 1: Consultation Questionnaire
55
Comparing the Environmental Impact of Conventional and High-Speed Rail
STUDY ON HIGH-SPEED RAIL ENVIRONMENTAL PERFORMANCE
VERSUS CONVENTIONAL RAIL
Introduction
The purpose of this study is to access and examine information on the current and future
energy/greenhouse gas emissions performance of (electric) high-speed rail (HSR)10 and conventional
rail11. The essential information required to evaluate this performance can be loosely grouped into the
following major categories:
1) Performance (energy consumption) of the rail rolling stock:
a) Current high-speed (electric) and conventional (electric, diesel) rolling stock;
b) Future electric rolling stock (on up to a 20 year timeframe);
2) Seating occupancy levels in high-speed versus conventional rail services.
3) Estimated direct and indirect greenhouse gas emissions from diesel and electricity use (current
and likely future electricity mix);
4) Estimated emissions resulting from the construction, maintenance and decommissioning of rolling
stock;
5) Information relating to the potential energy consumption/emissions resulting from construction new
rail infrastructure:
a) Materials used in the construction of infrastructure (and the energy/emissions per kg of these
materials);
b) Energy use/emissions resulting from infrastructure construction activities.
The primary focus of the project work is on the first three categories; however it is important to
consider the other areas where they may influence the relative comparison between HSR and
conventional rail. A significant amount of data/information is has already been identified on
comparisons between existing rolling stock. However, given for the likely timeframe for the potential
development of new lines for HS2, i.e. potentially up to 15-20 years, there is a need to identify new
information on the likely performance of future rolling stock.
A number of significant claims have been made for forthcoming HSR technology by manufacturers
(e.g. 20%-30% reduction in energy consumption compared to current generation. There is a need to
investigate such claims in more detail and in comparison to potential related technological advances in
conventional rail.
Of equal importance is evidence on the potential differences in passenger loading factors for HSR
versus conventional rail services, as this will have a marked impact on their relative performance per
passenger km.
We are writing to you to request your assistance in filling in this short questionnaire about your
activity / knowledge of this area. We have identified you as the key contact in this area of work, but if
this is not the case could you please forward the email to the relevant contact and let us know.
The timescale of this work is necessarily tight: preliminary results are needed by the middle of April.
Consequently we would be grateful for swift responses.
10
Defined as services faster than typical UK intercity limit of 200km/hr, and up to 300+km/hr
Comparisons are for similar types of services for HSR vs conventional rail – i.e. conventional intercity service rolling stock (up to 200 km/hr),
rather than rolling stock used in slower stop-start commuter services
11
56
Comparing the Environmental Impact of Conventional and High-Speed Rail
STUDY ON HIGH-SPEED RAIL ENVIRONMENTAL PERFORMANCE
VERSUS CONVENTIONAL RAIL – QUESTIONNAIRE
NOTE: If there is any information you would like to provide anonymously (i.e. not directly attributed to
your organisation), or is commercially confidential (i.e. not to be directly disclosed in any study
documentation), please indicate/highlight this clearly in your response.
RETURN OF REPONSE
Please type responses into the boxes provided and email your completed document to:
To:
Nikolas.hill@aeat.co.uk (Tel. 0870 190 6490)
Cc:
Matthew.Morris@aeat.co.uk (Tel. 0870 190 2844)
Robert.Milnes@aeat.co.uk (Tel. 0870 190 2634)
Your name/role:
Organisation:
Contact details:
Email:
Telephone no.:
Address:
Please mark the area(s) in which you are able to provide information, and add further detail in the
corresponding section(s).
Section
Yes / No
(as appropriate)
A
Likely performance (energy consumption)
conventional electric rail rolling stock
of
future
HSR
and
B
Evidence on seating occupancy levels in high-speed versus conventional
rail services
C
Material on embedded energy/emissions resulting from construction,
maintenance and decommissioning of new electric rail rolling stock
D
Information relating to the potential energy consumption/emissions
resulting from construction of new rail infrastructure (e.g. materials,
energy from construction activity)
57
Comparing the Environmental Impact of Conventional and High-Speed Rail
A. Likely performance (energy consumption) of future HSR and
conventional electric rail rolling stock
Q1
Are you able to provide information on the anticipated future performance of high-speed and
conventional electric rail rolling stock (2020-2030 timeframe)?
[Ideally this would be in kWh per seat-km, plus (or if not available) % improvement over a
specific current model]
Response:
Q2
What are the key technological / other measures utilised in achieving reduction in energy
consumption in future models, and their approximate % contribution to improvements?
Response:
Q3
To what extent are the measures / improvements in efficiency planned for high-speed rail
rolling stock transferable to conventional rail?
Response:
Q4
Is there anything else you feel we should take into account in this area?
Response:
B. Evidence on seating occupancy levels in high-speed versus
conventional rail services
Q5
Can your provide, or point us to information / experience / evidence on the relative seating
occupancy of high-speed rail services, particularly in relation to equivalent conventional
lower speed intercity rail services?
Response:
Q6
Is there anything else you feel we should take into account in this area?
Response:
58
Comparing the Environmental Impact of Conventional and High-Speed Rail
C. Material on embedded energy/emissions resulting from construction,
maintenance and decommissioning of new electric rail rolling stock
Q7
Can you provide (or direct us to) any information on the embedded energy / emissions from
new electric rail rolling stock?
[For example, information on materials use per train/seat equivalent, energy from
construction activity, maintenance, recyclability for disposal, etc.]
Response:
Q8
Are there likely to be any significant differences between electric HSR or conventional rail
rolling stock?
[Specifically, changes that could affect embedded energy/emissions in their construction,
maintenance and decommissioning]12
Response:
Q9
Is there anything else you feel we should take into account in this area?
Response:
D. Information relating to the potential energy consumption/emissions
resulting from construction of new rail infrastructure (e.g. materials,
energy from construction activity)
Q10
Can you provide (or direct us to) any information on the embedded energy/emissions from
new electric rail infrastructure?
[For example, information on materials use per km of new line, energy from construction
activity, maintenance, etc.]
Response:
Q11
Are there likely to be any significant differences between the infrastructure necessary to
support electric HSR or conventional rail services?
[Specifically, changes that could affect embedded energy/emissions in their
construction/maintenance]
Response:
Q12
Is there anything else you feel we should take into account in this area?
Response:
12
For example, additional energy required for implementation of rail banking, use of continuous welded rail, etc.
59
Comparing the Environmental Impact of Conventional and High-Speed Rail
E. Other comments
Q13
Do you have any other comments, or is there anything else you feel we should take account
of in comparing high-speed and conventional rail?
Response:
60